NASA SP-2009-3405 

Human Health and Performance 

Risks of Space Exploration Missions 

Evidence reviewed by the NASA Human Research 

Program 

Edited by: 

Jancy C. McPhee, Ph.D., 

Associate Program Scientist 

 

John B. Charles, Ph.D., 

Program Scientist 

National Aeronautics and 

Space Administration 

Lyndon B. Johnson Space Center 

Houston, Texas 77058
Other Contributors 

We would like to acknowledge the following for their review of many versions of book chapters: Craig Kundrot, 

Lisa Stephenson, Ron White, Michelle Edwards, Wilma Anton, Maneesh Arya, Susan Steinberg-Wright, Edna 

Fiedler, Marcelo Vazquez, Mary Anne Frey, and Victor Schneider. We also appreciate the editing assistance that 

was provided by Jane Krauhs, Carrie Gilder, and Eileen Nicholas and the valuable peer review that was provided by 

the Institute of Medicine in spring 2008, which was under the direction of Daniel Masys and Kathy Livermore, as 

sponsored by Richard Williams, NASA Chief Health and Medical Officer. Lastly, we would like to thank Dennis 

Grounds, the Human Research Program Manager, for making the capture of the risk evidence a priority and for 

supporting the effort that was required by the authors to write (and rewrite) these challenging chapters. 
Introduction iii

Introduction 

The Human Research Program (HRP), which is within the NASA Exploration Systems Mission Directorate, 

is a directed and applied research program that addresses agency needs for human health and performance risk 

mitigation strategies in support of space exploration as described in the Vision for Space Exploration1

, the U.S. 

National Space Policy2, and the NASA Strategic Plan3. These exploration undertakings include missions to the 

moon and Mars. Although all of them will involve some of the same human health and performance challenges, 

each mission also will include specific challenges that depend on the nature of the exact undertaking and the development schedule. Accordingly, HRP research and technology development are focused on the highest-priority 

risks to crew health and safety, with the goal of ensuring mission success and maintaining long-term crew health. 

Three core documents describe the HRP. The first is the Program Requirements Document (PRD)4

, which defines, documents, and allocates high-level requirements to different organizational arms of the program; these 

requirements include responsibility for specific human system risks listed in the PRD. Previously, the Bioastronautics Roadmap5

 documented the health and performance risks and areas of concerns of a wide cross-section of the 

professional space life sciences community, but it did not have the level of detail that is necessary to prioritize risks 

across physiological disciplines or to compare strategies for how to manage a given risk across mission operational 

architectures. The HRP 2009 PRD risk list thus identifies a narrowed and more operationally-focused series of risks. 

The second HRP document is the Integrated Research Plan6

 (IRP), which describes what implementation activities are necessary to fill the knowledge and mitigation gaps that are associated with each risk that is listed in the PRD. 

It also details when those activities will be accomplished, where they will be accomplished (e.g., the International 

Space Station (ISS) or a ground analog), who will accomplish them (investigators within a specific project or organization within the HRP), and what is being produced (risk uncertainty reduction, candidate health or performance 

standard, countermeasure strategy, etc.). 

The third HRP document is the Evidence Book7

, which is a collection of evidence-based risk reports and journal 

articles for each individual risk that is contained within the HRP PRD and for which implementation activities are 

listed in the Integrated Research Plan. Thus, the collection provides the current state of knowledge for each of the 

defined human health and performance risks for future NASA exploration missions. All three of these documents, 

which are updated as evidence or events dictate, provide relevant information that can be used to manage the HRP. 

The initial 2008 Evidence Book was a collection of written evidence reports that was created from both published 

and unpublished information reviewed by the HRP in 2006. From April to August 2008, the 2008 Evidence Book 

was reviewed by members of the Committee on NASA’s Research on Human Health Risks, established by the Institute of Medicine (IOM), which is the arm of the U.S. National Academy of Sciences that is charged with examining 

public health policy. The resulting thorough Review of NASA’s Human Research Program Evidence Books: A Letter 

Report (2008) provides guidance for both a revision of the current risk reports and for the development of future 

versions. It is publicly available via the National Academies Press Website.8

 

1

See http://www.nasa.gov/missions/solarsystem/explore_main_old.html. 2

See http://www.ostp.gov/galleries/press_release_files/Unclassified%20National%20Space%20Policy%20--%20FINAL.pdf. 3

See http://nodis3.gsfc.nasa.gov/npg_img/N_PD_1001_000_/N_PD_1001_000_.pdf. 4

See http://humanresearch.jsc.nasa.gov/files/hrp-47052_revc_PRD.pdf. 5

See http://bioastroroadmap.nasa.gov/index.jsp. 6

See http://humanresearch.jsc.nasa.gov/files/hrp-47065_reva_IRP.pdf. 7

See http://humanresearch.jsc.nasa.gov/elements/smo/hrp_evidence_book.asp. 8

See http://books.nap.edu/openbook.php?record_id=12261. 
iv Introduction 

The IOM strongly recommended that the 2008 and future Evidence Book risk report information be made publicly 

available. For more than half of the HRP risk reports, therefore, single reports were revised to incorporate as much 

as possible the recommendations from the IOM Review and are presented as a collection in this NASA Special Publication, Human Health and Performance Risks of Space Exploration Missions; these reports are also available on 

the HRP Evidence Book Website. For the remaining risks, report information is currently being revised and reviewed 

as per the specifications of the specialized, subject-specific journals in which the authors have requested to publish 

the work. Citations for these journal publications, as they become available, will also be listed on the HRP Evidence 

Book Website. In the future, updated risk report information for all of the HRP risks will be maintained on the HRP 

Evidence Book Website in an electronic and rapidly updatable text format. 

To help characterize the kind of evidence that is provided in each of the risk reports in this book, the authors were 

encouraged to label the evidence that they provided according to the “NASA Categories of Evidence.” 

 Category I data are based on at least one randomized controlled trial. 

 Category II data are based on at least one controlled study without randomization, including cohort, casecontrolled or subject operating as own control. 

 Category III data are non-experimental observations or comparative, correlation and case, or case-series 

studies. 

 Category IV data are expert committee reports or opinions of respected authorities that are based on clinical 

experiences, bench research, or “first principles.” 

The NASA categories are comparable to more familiar versions of Levels of Evidence scales (e.g., Silagy C, 

Haines A. Evidence Based Practice in Primary Care, 2nd Ed., London: BMJ Books, 2001). The use of a coordinated data categorization system is new to many NASA life scientists, but authors were encouraged to use such a 

system to help clarify the type of evidence that was presented and thus provide additional information about the 

strength of interpretations that were derived from those data; however, scientists were not required to use the categorization system hierarchically if they determined that this system would obscure or otherwise interfere with the 

clarity of the evidence that they were presenting. 

The HRP, which recognizes the limitations of the distribution of the current risk report information, is evaluating 

even more thorough distribution possibilities for future editions of the risk evidence information. Through these 

initial actions, however, the HRP has made a good-faith attempt to fulfill the recommendation of the IOM and the 

requirement in the Space Act of 1958 (as amended) to disseminate to the widest possible audience the knowledge 

that is acquired during the course of NASA publicly funded activities. 

Jancy C. McPhee and John B. Charles 

May 2009 
Contents v

Contents 

 Introduction ................................................................................................................ iii

Behavioral Health and Performance 

Chapter 1 Risk of Behavioral and Psychiatric Conditions .......................................................... 3

Chapter 2 Risk of Performance Errors Due to Poor Team Cohesion and Performance, 

Inadequate Selection/Team Composition, Inadequate Training, and Poor 

Psychosocial Adaptation ............................................................................................ 45

Chapter 3 Risk of Performance Errors Due to Sleep Loss, Circadian Desynchronization, 

Fatigue, and Work Overload ...................................................................................... 85 

Space Radiation 

Chapter 4 Risk of Radiation Carcinogenesis .............................................................................. 119

Chapter 5 Risk of Acute Radiation Syndromes Due to Solar Particle Events ............................ 171

Chapter 6 Risk of Acute or Late Central Nervous System Effects from Radiation Exposure .... 191

Chapter 7 Risk of Degenerative Tissue or Other Health Effects from Radiation Exposure ....... 213

Exploration Medical Capabilities 

Chapter 8 Risk of Inability to Adequately Treat an Ill or Injured Crew Member ....................... 239 

Space Human Factors and Habitability 

Chapter 9 Risk of Error Due to Inadequate Information ............................................................. 253 

Chapter 10 Risk of Reduced Safety and Efficiency Due to Inadequately Designed Vehicle, 

Environment, Tools, or Equipment ............................................................................ 267 

Chapter 11 Risk of Error Due to Poor Task Design ...................................................................... 281 

Chapter 12 Risk Factor of Inadequate Food System ..................................................................... 295 

Chapter 13 Risk of Adverse Health Effects from Lunar Dust Exposure ...................................... 317 

Exercise and Extravehicular Activity

Chapter 14 Risk of Compromised EVA Performance and Crew Health Due to 

Inadequate EVA Suit Systems ................................................................................... 334

Chapter 15 Risk of Operational Impact of Prolonged Daily Required Exercise ........................... 359 
vi Introduction 

Appendices

 Authors and Affiliations ............................................................................................ 365

 Acronyms and Abbreviations .................................................................................... 367 

Index ................................................................................................................................................... 373 
Behavioral Health and 

Performance 

Risk of Behavioral and 

Psychiatric Conditions 

Risk of Performance Errors due 

to Poor Team Cohesion and 

Performance, Inadequate 

Selection/Team Composition, 

Inadequate Training, and Poor 

Psychosocial Adaptation 

Risk of Performance Errors due 

to Sleep Loss, Circadian 

Desynchronization, Fatigue, and 

Work Overload 

Risk of Performance Errors due 

to Poor Team Cohesion and 

Performance, Inadequate 

Selection/Team Composition, 

Inadequate Training, and Poor 

Psychosocial Adaptation

Risk of Behavioral and Psychiatric Conditions 3

Chapter 1: 

Risk of Behavioral and Psychiatric Conditions 

Kelley J. Slack 

Wyle Integrated Science and Engineering Group 

Camille Shea 

Universities Space Research Association 

Lauren B. Leveton

NASA Johnson Space Center 

Alexandra M. Whitmire

Wyle Integrated Science and Engineering Group 

Lacey L. Schmidt 

Wyle Integrated Science and Engineering Group 

Behavioral issues are inevitable among groups of people, no matter how well selected and trained. 

Spaceflight demands can heighten these issues. The Institute of Medicine [(IOM)] report, Safe Passage 

[Ball & Evans (eds.), 2001], notes that Earth analog studies show an incidence rate of behavioral problems 

ranging from 3-13 percent per person per year. The report transposes these figures to 6-7 person crews on 

a 3-year mission to determine that there is a significant likelihood of behavioral conditions and psychiatric 

disorders emerging. Impacts of behavioral issues are minimized if they are identified and addressed early. 

The HRP must provide the best measures and tools to monitor and assess mood and to predict risk for and 

management of behavioral and psychiatric conditions prior, during and following spaceflight. – Human Research 

Program Requirements Document, HRP-47052, Rev. C, dated Jan 2009. 

 

An iconic photograph of Russian cosmonaut 

Valery Poliakov, who has clearly demonstrated 

his capacity for long-duration space flights, having 

completed two tours of duty on the Russian space 

station Mir, including one that lasted 438 days, 

thus setting a record that remains unbroken to 

this day. Current International Space Station 

missions involve crew stays of up to 6 months, 

with provision of an effective set of psychosocial 

countermeasures to aid crew morale and team 

cohesion. 
4 Risk of Behavioral and Psychiatric Conditions 
Human Health and Performance Risks of Space Exploration Missions Chapter 1 

Risk of Behavioral and Psychiatric Conditions 5

 Executive Summary 

Space flight, whether of long or short duration, occurs in an extreme environment that has unique stressors. 

Even with excellent selection methods, behavioral problems among space flight crews remain a threat to mission success. Assessment of factors that are related to behavioral health can help minimize the chances of distress and, thus, reduce the likelihood of behavioral conditions and psychiatric disorders arising within a crew. 

Similarly, countermeasures that focus on prevention and treatment can mitigate the behavioral conditions 

and psychiatric disorders that, should they arise, would impact mission success. 

Risk, which within the context of this report is assessed with respect to behavioral health, is addressed in 

terms of occurrence in space flight and analog populations, and of predictors and other contributing factors. 

Based on space flight and analog evidence, the average incidence rate of an adverse behavioral health event 

occurring during a space mission is relatively low. While mood and anxiety disturbances have occurred, no 

behavioral emergencies have been reported to date in space flight. Anecdotal and empirical evidence indicates 

that the likelihood of a behavioral condition or psychiatric disorder occurring increases with the length of a mission. Further, while behavioral conditions or psychiatric disorders might not immediately and directly threaten 

mission success, such conditions can, and do, adversely impact individual and crew health, welfare, and 

performance, thus indirectly affecting mission success. 

Identification of predictors and other factors that can contribute to the risk of behavioral conditions and 

psychiatric disorders at all stages of a mission increases the efficacy of prevention and the treatment of those 

conditions. Many factors predict or otherwise play a role in the occurrence of a behavioral condition or psychiatric disorder. These include: sleep and circadian disruption, personality, negative emotions, physiological 

changes that occur when adapting to microgravity, lack of autonomy, daily personal irritants, physical conditions 

of life in space, workload, fatigue, monotony, cultural and organizational factors, family and interpersonal issues, 

and environmental factors. Positive or salutary aspects of space flight also contribute to behavioral health outcomes. Some factors have both detrimental and salutary aspects; teamwork, giving and receiving social support, 

and leadership responsibilities are a few examples of these. 

The current approaches to prevent behavioral conditions and psychiatric disorders begin during selection and 

continue post-flight. The goal of the behavioral health component of the astronaut selection system is to identify 

individuals who, at the time of application, have diagnoses that are incompatible with the demands of space flight, 

and also to identify those who are believed to be best suited psychologically to be astronauts. Countermeasures 

are a second line of defense to prevent behavioral conditions and psychiatric disorders from occurring pre-flight, 

during flight, and post-flight. For example, psychological support services are provided to crew members and 

their families before, during, and after missions. 

Approaches that prevent or mitigate behavioral conditions and psychiatric disorders often can be used to 

treat the occurrence of behavioral problems. Private psychological conferences, for example, can provide both 

prevention and treatment. While anecdotal evidence suggests that current practices may be sufficient, the efficacy of these practices has not yet been assessed systematically. 

In sum, evidence indicates that development of behavioral conditions and psychiatric disorders is a risk for 

human space flight, and that this risk increases as mission length increases. Multiple methods are employed to 

prevent and treat behavioral problems and appear to have some effect, although the extent to which prevention 

and treatment are effective has not been quantified. 
Chapter 1 Human Health and Performance Risks of Space Exploration Missions 

6 Risk of Behavioral and Psychiatric Conditions 

 Introduction 

The NASA commitment to long-duration space flight includes astronauts who will be returning to the moon 

as well as those who will take part in human missions to Mars. Successful exploration will require a better 

understanding of the effects that extended missions pose for the behavioral health of astronauts, not just during 

flight but also pre- and post-flight. As space flight missions lengthen, astronauts will spend longer periods away 

from families and friends. The absence of Earthly conveniences and daily routines will also intensify their feelings 

of isolation (Ball and Evans, 2001) (Category III9

) because the astronauts will be spending more time confined 

in the spacecraft and living in an environment that is fraught with potential danger. On their return to Earth, they 

will have to reintegrate into a world that has adapted and changed without them. Consequently, predicting the 

effect that extended periods of isolation will have on astronaut performance and psychological well-being becomes increasingly important (Kanas and Manzey, 2008). Further, the potential for psychiatric disorders developing in long-duration crews during or after missions requires that consideration be given to prevention 

and treatment (Kanas and Manzey, 2003; Palinkas, 1986) (Category IV). 

During astronaut selection, applicants who have been identified with a psychiatric disorder that would 

impede on-the-job success are removed from further consideration. However, important aspects of an individual’s mental health history – e.g., exposure to a traumatic event, family history of mental health struggles such 

as depression or schizophrenia – may not have been disclosed to NASA at the time of astronaut selection. Not 

only may potential astronauts be hesitant to share information that would prohibit selection, but some current 

astronauts have also demonstrated a reluctance to share information if they perceive such information could 

jeopardize their flight status. 

Disorders such as anxiety, post-traumatic stress, sleep loss/insomnia, adjustment, and depression can also 

develop unexpectedly in otherwise healthy individuals. A recent study by Tozzi et al. (2008) indicates that the 

average age of onset of depression for persons who have no family history of depression is 41 years (standard 

deviation (SD)=13.67); therefore, even astronauts who have never experienced depression are not immune from 

its development. The age of astronaut candidates when selected for the Astronaut Corps has ranged between 26 

and 46 years (NASA, 2008b). Between 1989 and 2003, the average age of the astronauts who were selected was 

36.5 years. It is important to note that depression could occur at any phase of an astronaut’s career. Furthermore, as reviewed by Collins (1985), behavioral problems that occur during space flight often do not terminate when the mission ends, but can linger with notable aftereffects (Category IV). 

Although the incidence of reported psychiatric disorders on shuttle missions has not been significant 

(Billica, 2000) (Category III), as the length of space missions increases the incidence of behavioral conditions and psychiatric disorders is also expected to increase (Ball and Evans, 2001; Otto, 2007; Stuster, 2008) 

(Category IV). Additionally, the ramifications of a disorder developing in flight are severe if that disorder is left 

unresolved. Anecdotal and empirical evidence from space flight and behavioral health incidence rates from 

 

9

To help characterize the kind of evidence that is provided in each of the risk reports in this book, the authors were encouraged to label 

the evidence that they provided according to the “NASA Categories of Evidence.” 

 Category I data are based on at least one randomized controlled trial. 

 Category II data are based on at least one controlled study without randomization, including cohort, case-controlled or subject

operating as own control. 

 Category III data are non-experimental observations or comparative, correlation and case, or case-series studies. 

 Category IV data are expert committee reports or opinions of respected authorities that are based on clinical experiences, bench 

research, or “first principles.” 
Human Health and Performance Risks of Space Exploration Missions Chapter 1 

Risk of Behavioral and Psychiatric Conditions 7

space analogs suggest that assessing, preventing, and treating behavioral health problems are essential to 

protecting the health of crew members and, consequently, the success of a mission. 

The NASA Human Research Program (HRP) is organized into topical areas called Elements; the Behavioral Health and Performance (BHP) Element is tasked with the responsibility of managing three risks: (1) risk 

of performance errors due to sleep loss, circadian desynchronization, fatigue, and work overload; (2) risk of 

performance errors due to poor team cohesion and performance, inadequate selection/team composition, inadequate training, and poor psychosocial adaptation; and (3) risk of behavioral and psychiatric conditions. While each 

of these risks is addressed in a separate chapter of this book, they should not be construed to exist independently 

of one another but, rather, should be evaluated in conjunction with one another. Furthermore, BHP risks overlap 

with risks in other HRP Elements and, as such, must also be considered in conjunction with one another. Refer 

to figure 1-1 for an example of these possible overlaps. 

Figure 1-1. Example of possible BHP risks overlapped with risks in other HRP Elements. 

The relationships of the BHP Element with other HRP Elements are further outlined in the HRP Integrated 

Research Plan (IRP)10. The nature of the IRP implies that the BHP Element is continually reviewing and updating 

integration points with other elements. While research is designed to address identified gaps, it will be necessary to 

update and revise each of the BHP evidence reports and the IRP as the element gaps are closed and new gaps 

emerge. 

 

10See http://humanresearch.jsc.nasa.gov/about.asp. 
Chapter 1 Human Health and Performance Risks of Space Exploration Missions 

8 Risk of Behavioral and Psychiatric Conditions 

 Evidence 

 Assessment of behavioral conditions and psychiatric disorders 

An assessment of behavioral conditions and psychiatric disorders improves our understanding of the factors 

that contribute to the development of these conditions, and the treatment options that are best to manage this 

risk. Assessments occur within a framework, or a theoretical approach, of assessing behavioral conditions and 

psychiatric disorders. This theoretical approach, which is taught by NASA BHP to astronauts and flight surgeons, 

is described below. Evidence of the occurrence of behavioral and psychiatric problems in space flight and space 

analogs is then presented. Predictors and other factors that contribute to the occurrence of a behavioral condition and psychiatric disorder are then discussed. Lastly, current countermeasures and treatments are described. 

The majority of the evidence that is cited is Category III. Please note that from this point on, only categories 

other than Category III are noted within the text. 

 Theoretical approach 

Behavioral and psychiatric problems can be classified in several ways. NASA relies heavily on the classification system that is used by the American Psychiatric Association (APA) in the Diagnostic and Statistical 

Manual Fourth Edition Text Revision (DSM-IV-TR) (APA, 2000). In a slight departure from the DSM-IV-TR 

classifications, behavioral medicine training that is taught by a NASA psychiatrist also incorporates the International Classification of Diseases-10 (ICD-10) (World Health Organization (WHO), 1996) standard diagnostic 

classification system. The ICD-10, which is used worldwide, is a more comprehensive system than the DSM-IVTR; it is used to classify physical and mental diseases as well as conditions for all general epidemiological 

and many health management purposes. Mental and Behavioural Disorders is only one chapter in this much 

broader tome. In contrast, the DSM-IV-TR, which focuses on mental and behavioral disorders, assigns the 

following classifications: 

 Axis I – clinical disorders 

 Axis II – personality disorders and mental retardation 

 Axis III – general medical conditions 

 Axis IV – psychosocial and environmental problems 

 Axis V – global assessment of functioning 

When using the DSM-IV-TR, general medical conditions, psychosocial and environmental problems, and global 

assessment of functioning are relevant only to the extent that they contribute to or exacerbate psychiatric diagnoses. 

Behavioral medicine training for the International Space Station (ISS) teaches NASA flight surgeons, crew 

medical officers (CMOs), and astronauts that there are three main types of significant mental disorders that 

might be encountered in a long-duration mission (NASA, 2008a): (1) delirium, which is a severe behavioral and 

cognitive response to physical injury or illness; (2) adjustment disorder, which is a severe and negative emotional 

response to a tragedy; and (3) asthenia, which is a progressive negative psychological response to the isolation 

and rigors of a long-duration mission. The Russian Space Agency, even more so than NASA, recognizes asthenia 

as a condition that occurs during long-duration missions (Kanas, 1991). NASA behavioral medical training also 

instructs astronauts to be vigilant for other possible psychiatric or behavioral conditions. These other conditions 

fall under the rubric of any other psychiatric disorders, which is the first indication of a preexisting or latent 

mental disorder that is, perhaps, worsened or triggered by the stress of long-duration space flight. 
Human Health and Performance Risks of Space Exploration Missions Chapter 1 

Risk of Behavioral and Psychiatric Conditions 9

 Occurrences of behavioral conditions and psychiatric disorders 

NASA differentiates between a behavioral condition and a psychiatric disorder in the following manner: a 

behavioral condition is any decrement in mood, cognition, morale, or interpersonal interaction that adversely 

affects operational readiness or performance; whereas a psychiatric disorder is one that meets the diagnoses 

criteria as outlined in the DSM-IV-TR. In other words, a behavioral condition is a sub-clinical, off-nominal set 

of behavioral and psychological circumstances or symptoms that, if left unchecked or unmitigated, may lead to 

the development of a psychiatric disorder that will, at that time, be considered an illness that requires a specific 

medical and psychiatric treatment plan. In the future, the title of the risk that is described in this chapter is 

expected to change to more clearly reflect these distinct definitions. 

 Space Flight 

The flight surgeon is usually the confidant if, and when, an astronaut reports behavioral signs and symptoms. Thirty-four behavioral signs and symptoms were reported among the 208 crew members who flew on 

89 shuttle missions between 1981 and 1989, spending a total of 4,442.8 person-days in space. This is an incidence rate of 0.11 for a 14-day mission; in other words, behavioral signs and symptoms, regardless of the type 

of sign or symptom, occurred at the rate of approximately one per every 2.86 person-year (Billica, 2000). The 

behavioral symptoms that were most commonly reported in these 89 missions were anxiety and annoyance 

(Billica, 2000). Between March 1995 and June 1998, seven astronauts flew on the Russian space station Mir; 

during this time, psychiatric events were reported twice for an incidence rate for astronauts of 0.77 per personyear (Marshburn, 2000). The actual incidence rate for both shuttle and Mir is likely to be understated, however, because of astronaut reluctance to report such symptoms (Ball and Evans, 2001; Shepanek, 2005). 

The actual reported behavioral events and recurrences can be reviewed in the U.S. Medical Events Tables 

found in the chapter appendix. 

Behavioral and psychiatric emergencies

NASA considers any behavioral condition or psychiatric disorder that causes serious behavioral or cognitive 

symptoms leading to incapacitation and severe mission impact as a behavioral emergency. Examples include 

the development of delirium due to a head injury, or a brief psychotic disorder following a tragic event such 

as the death of a family member or an international catastrophe. To date, no behavioral emergencies have 

occurred before or during any U.S. space flight. As previously mentioned, however, as the length of space 

missions increases, the probability of a behavioral and psychiatric emergency occurring also increases (Ball 

and Evans, 2001; Stuster, 2008) (Category IV). 

Not a lot of data are available from which to assess the many types of behavioral conditions and psychiatric 

disorders that could occur during a long-duration mission. This is due, in part, to the relatively few numbers 

of long-duration flyers, and to the fact that the consistent length of a mission for most of these flyers is approximately 6 months. Based on past NASA experience, one estimate of the possible rate of a behavioral or a 

psychiatric emergency occurring in flight as the result of depression or anxiety ranges from 0.000087 to 

0.000324 cases per person-year (NASA, 2007b). The likelihood of such an emergency occurring would 

further increase as mission length exceeds 1 year. Calculation of this estimate, which is based on NASA 

space flight data, is discussed more fully in the Mood and Mood Disorders section below. 

Some Russian space flight missions in the 1970s and 1980s were terminated early due to psychological 

factors (Cooper, 1976). In 1976, during the Soyuz- 21 mission to the Salyut-5 space station, the crew was 

brought home early after the cosmonauts complained of a pungent odor. No source for this odor was ever 

found, nor did other crews smell it. Since the crew had not been getting along, the odor may have been a 

hallucination. In 1985, the crew of the Soyuz T-14 mission to Salyut-7 was brought home after 65 days be-
Chapter 1 Human Health and Performance Risks of Space Exploration Missions 

10 Risk of Behavioral and Psychiatric Conditions 

cause cosmonaut Vladimir Vasyutin complained that he had a prostate infection (Clark, 2007). Doctors 

later believed that the problem was partly psychological. The Soyuz TM-2 mission in 1987 was similarly 

cut short because of some apparent psychosocial factors (Clark, 2007). The early termination of these 

missions may have prevented escalation of behavioral and psychiatric occurrences. 

The stress of space flight does not end at landing. In early 2007, an astronaut who had recently returned 

from a space mission allegedly engaged in actions that might be considered indicative of a behavioral and 

psychiatric emergency (c.f., Editorial, 2007). Space flight is not necessarily the sole or even the primary cause 

of post-flight behavioral conditions and psychiatric disorders. Other stressors in life, such as marital distress 

(Aldrin, 1973; Kanas, 1987) or the death of a family member (Clark, 2007), also may contribute to similar 

behavioral conditions and psychiatric disorders. Nevertheless, space flight and its associated factors – e.g., 

isolation, confinement, workload – can become significant triggers or sources of stress. These space flight 

stressors, when they are paired with traditional life stressors, will likely have an exponential impact on 

behavioral health for long-duration astronauts (Kanas and Manzey, 2008). 

Mood and mood disorders

Mood states can be dichotomized into positive and negative moods (Watson and Tellegen, 1985). Positive 

moods have been linked to increased helping behavior toward others (e.g., Fisher, 2002; George, 1991; Isen 

and Levin, 1972). A positive mood may result in better performance through interpersonal processes such as 

helping others (Tsai et al., 2007). Further, employees in positive moods may perform better through a motivational process such as higher self-efficacy and task persistence (Tsai et al., 2007). George and Brief (1996) 

found that people who were in positive moods were more likely to view their progress toward task goals 

positively and engage in increased task diligence. 

Like positive moods, negative moods can be functional. They can cause individuals to better identify 

problems by focusing on their current situation rather than on their underlying assumptions, attending to 

shortfalls in the status quo, identifying opportunities, and exerting high levels of effort to improve a situation 

(George and Zhou, 2002; George and Zhou, 2007; Kaufmann, 2003; Martin and Stoner, 1996; Schwarz, 2002; 

Schwarz and Skurnik, 2003). Additionally, negative moods promote creativity under certain conditions (e.g., 

Gasper, 2003; George and Zhou, 2002; Kaufmann, 2003; Kaufmann and Vosburg, 1997), which can 

facilitate problem-solving. 

The effects of positive mood are discussed in later sections of this chapter and address salutogenesis in 

space flight and analogs, respectively. Space-flight-related research, albeit quite limited, has focused on the 

displacement of negative mood from crew members to Mission Control personnel, and from Mission Control personnel to management (Kanas, 2005; Kanas et al., 2007). 

Mood disorders, which are categorized in the NASA integrated medical model (IMM) as depression and 

anxiety, have occurred during space flight. Data that were collected for 28.84 person-years of NASA space 

flight reveal that 24 cases of anxiety occurred in space flight for an incidence rate of .832 cases per personyear (NASA, 2007a). Over the same 28.84 person-years, four astronauts experienced signs and symptoms 

of depression during space flight for an incidence rate of .139 per person-year (NASA, 2007a). In other 

words, signs and symptoms of anxiety during space flight occurred once every 1.2 years, and signs and 

symptoms of depression occurred once every 7.2 years. 
Human Health and Performance Risks of Space Exploration Missions Chapter 1 

Risk of Behavioral and Psychiatric Conditions 11

According to a National Institute of Mental Health (NIMH) (1999) pamphlet (Category III), approximately 

one in 10 adults during a given year will suffer from some form of depression. Despite careful selection, a 

depression-free past does not guarantee a depression-free future. 

The data that were collected in the general population as well as in NASA are not definitive enough at 

this time to accurately predict the likelihood of an astronaut becoming depressed or suffering from a mood 

disorder while in flight. Rather, it emphasizes that the risk is real and should not be ignored. Therefore, 

NASA is continuing to gather the data that are needed to define and mitigate the risk of an astronaut 

developing an anxiety or a depressive disorder. 

Asthenia

Russian medical personnel view asthenia as one of the greatest problems affecting the emotional wellbeing of cosmonauts (Kanas, 1991). This syndrome, which is also called neurasthenia and asthenization, 

has been defined as “a nervous or mental weakness manifesting itself in tiredness...and quick loss of strength, 

low sensation threshold, extremely unstable moods, and sleep disturbance” (Kanas and Manzey, 2003, p. 115). 

It can be caused by excessive mental or physical strain, prolonged negative emotional experience or conflict, 

as well as somatic illness (Petrosvsky and Yaroshevsky, 1987). The diagnostic criteria for asthenia and 

neurasthenia are listed in the ICD-10 (WHO, 1996). However, this diagnosis is not recognized in the DSMIV-TR (APA, 2000). Other diagnoses with similar symptoms that are listed in DSM-IV-TR are adjustment 

disorder, dysthymia, major depressive disorder, and chronic fatigue syndrome. 

Examination of cosmonauts suggests that asthenia is particularly likely to occur when space flights last 

longer than 4 months (Myasnikov and Zamaletdinov, 1996). Symptoms and signs of asthenia have been 

reported anecdotally by U.S. astronauts who flew during Mir and Skylab (Burrough, 1998; Freeman, 2000; 

Harris, 1996). Kanas et al. (2001), however, failed to find empirical support for the occurrence of asthenia 

during Mir missions. This failure to find support could be due to the method that was used to operationalize 

asthenia. Only the psychological component of asthenia was examined; furthermore, the study used an instrument that was not specifically designed to measure asthenia. 

At present, the occurrence of asthenia in space flight crews does not require medications; this may be due in 

part to the current space flight parameters (e.g., length of flight, contact with the ground, Progress and shuttle 

flights, etc.). Furthermore, this is likely due in part to stringent selection methods that select out those with 

psychiatric problems, and to diligent monitoring and application of countermeasures when symptoms first 

appear (Myasnikov et al., 2000, as cited in Kanas et al., 2001). Longer-duration missions may demonstrate 

a need for asthenia medications. 

Psychosomatic reactions

Psychosomatic reactions occasionally have been reported during space flight. Psychosomatic is defined as 

“pertaining to a physical disorder that is caused by or notably influenced by emotional factors” (Dictionary, 

2008). These health struggles are not imaginary; in fact, more than half of all individuals who are seeking 

medical attention are suffering from psychosomatically induced or exacerbated illnesses (Goldensen, 1970; 

Birley, 1977; Fava and Sonino, 2000). For example, an otherwise healthy cosmonaut experienced a cardiac 

arrhythmia that required medication after being exposed to sustained stressors related to on-board equipment 

failure (Carpenter, 1997; Cowings et al., 2000; Kornilova et al., 1998, 2000). 
Chapter 1 Human Health and Performance Risks of Space Exploration Missions 

12 Risk of Behavioral and Psychiatric Conditions 

There are direct self-reports of somatizing by cosmonaut Valentin Lebedev during the record-breaking length 

of his Salyut 7 mission. Other psychosomatic reactions include complaints of toothaches after dreams of 

tooth infections (Chaikin, 1985) and fears of impotence due to perceived prostatitis (Harris, 1996). 

Salutogenesis

Not all of the effects of long-duration space flight are expected to be negative. Antonovsky, in 1979 

(Category IV), coined “salutogenesis” as the opposite of pathogenesis. Salutogenic experiences are those 

that promote a sense of health. The key factor of salutogenesis, according to Antonovsky (1979), is a person’s 

sense of coherence. He defined this sense of coherence as “a global orientation that expresses the extent to 

which one has a pervasive, enduring though dynamic feeling of confidence that one’s internal and external 

environments are predictable and that there is a high probability that things will work out as well as can reasonably be expected.” Kobasa et al. (1979) described individuals who stay healthy, even when they find themselves 

in challenging circumstances, as having the following characteristics: believing that they exert control over 

their environment; embracing life as meaningful; and experiencing changes in life as normal and beneficial. 

Factors contributing to salutogenesis are comprehensibility, manageability, meaningfulness, social support, 

spirituality, happiness, humor, and love (Kent, 2002; Smith, 2002). Smith (2002) commented that “an 

organism with a salutogenic brain would experience the world as manageable and coherent ... with a 

self-perpetuating cycle for enhancing self-confidence and well-being.” 

Suedfeld (2005) differentiates between positive environmental aspects and the positive personal and 

social aspects of space flight. Environmental aspects concern the external environment (e.g., mystery; beauty 

of space; views of Earth) and the capsule environment (e.g., safe haven; familiarity; free time). The positive 

personal and social aspects of space flight were likewise dichotomized into astronaut group dynamics (e.g., 

membership in an elite group; superordinate goals) and post-mission consequences (e.g., self-confidence; 

respect; new skills and values). 

Preliminary results suggest that a salutogenic response to space flight is common across astronauts and 

endures for some time post-flight. Astronauts and cosmonauts have reported experiencing transcendental, 

religious experiences or a sense of the unity of humankind while in space (Connors et al., 1985; Ihle et al., 

2006; Kanas, 1990). Analysis of the memoirs of four astronauts reveals that all four reported post-flight feelings of increased spirituality, defined as “meaning and inner harmony through transcendence” (Suedfeld and 

Weiszbeck, 2004, p. C7). Ihle et al. (2006) examined the positive psychological outcomes of space flight. All 

39 astronauts and cosmonauts who responded to the survey reported a positive reaction to being in space. The 

most frequently endorsed benefit of space flight related to the perception of the Earth; i.e., its beauty and fragility. Analysis of photographic images taken from ISS during Expeditions 4 through 11 indicates that most 

images taken by crew members were self-initiated (84.5% of 144,180 photographs) and that photography was 

considered a leisure activity (Robinson et al., in press). During missions to Mars, however, the Earth will not 

always be visible. The effects of not being able to see Earth could have a detrimental effect on the psychological well-being of crew members (Kanas and Manzey, 2003; 2008). 

Psychosocial adaptation and disorders

Anecdotal evidence from crew members illuminates the distress that some individuals encounter during longduration space flight missions. Psychosocial adjustment is, by definition, the psychological and social process 

of adapting or conforming to new conditions (Merriam-Webster, 2008). Unsuccessful psychosocial adaptation can lead to adjustment disorders that are characterized by decrements in performance (APA, 2000). 
Human Health and Performance Risks of Space Exploration Missions Chapter 1 

Risk of Behavioral and Psychiatric Conditions 13

In-flight diaries of cosmonauts and astronauts recount periods of psychological distress experienced during 

extended periods in space (Ball and Evans, 2001). Even crew members with otherwise cheerful dispositions 

may demonstrate changes in temperament when meeting the challenges of space flight adaptation. Lebedev 

wrote in his journal, “[M]y nerves were always on edge, I get jumpy at any minor irritation” (Lebedev, 1988, 

p. 291). One astronaut described his inability to fully prepare for long-duration space flight challenges, “I 

was astounded at how much I had underestimated the strain of living cut off from the world in an otherworldly environment” (Linenger, 2000, p. 151). 

Ineffective adjustment to life in space can take many forms. Withdrawal from fellow crew members or 

ground support crew is one form of ineffective adjustment. Discord or tense relations with fellow crew 

members is another form of ineffective adjustment. 

A third form of ineffective adjustment is deviant behavior. One expert of isolated and confined environments has identified two categories of deviant behavior in U.S. Antarctic winter-over crews: (1) individuals 

who fail to conform to group norms/expectations; and (2) individuals who act as the station class jester, whose 

behavior is outside of the mainstream yet not outrageously disruptive or threatening (Palinkas, 1989, 1992). 

Deviant types of behavior in space may fall into these same two categories. For example, Lebedev admitted 

that he disregarded safety procedures when he became frustrated. In his haste to access new letters from home, 

he did not wear safety goggles because “they fogged up, but if metal dust had entered my eye the flight would 

have ended” (Lebedev, 1988, p. 304). Illustrating the second category of deviant behavior is Linenger’s coping 

behavior: “I also made my own diversions ... Playing the space version of ‘sneaking up’ ... Flying silently 

down the length of a module, I would approach one of my crewmates and, still undetected by him, move 

very close. I would then hover patiently until he turned around. I knew that I had gotten him whenever he 

would gasp and flail his arms backward” (Linenger, 2000, p. 159). Anecdotal evidence from space flight 

suggests that astronauts and cosmonauts at times engage in disruptive coping behaviors that could presage larger behavioral issues. 

Crew size may be another factor contributing to different behavioral outcomes. In examining rates of 

deviance in seven polar and three space flight missions (Salyut 7; Apollo 11; and Apollo 13), Nolan and 

Dudley-Rowley (2005) determined that deviance rates were highest for crews of three. These researchers 

classified deviant behavior in three general categories: (1) bizarre or puzzling behavior, such as withdrawal; 

(2) acts of violence, either verbal or physical; and (3) acts of deliberation, such as hoarding resources. They 

found that when crew size increases to four, there is an apparent significant decrease in the amount of 

deviant behavior exhibited. 

Summary

Based on our past space flight experiences, various types of behavioral conditions and psychiatric disorders 

are expected to be a risk for future Exploration missions (Table 1-1). While current selection and countermeasure strategies have prevented the occurrence of any behavioral health emergencies during space flight 

that could have jeopardized mission success, the uniquely long durations and distances of future Exploration 

missions necessitate comparisons with analog environments that might indicate the other types of occurrences 

that could be expected. 

 Analog Populations 

Ground-based analogs, such as those in the Arctic and Antarctica or undersea habitats, are frequently used as a 

comparison to space flight because they are more accessible than space flight and provide an Earth environment in 

which to test and validate the feasibility of BHP countermeasures, tools, and procedures. Analogs, however, are 
Chapter 1 Human Health and Performance Risks of Space Exploration Missions 

14 Risk of Behavioral and Psychiatric Conditions 

also frequently criticized. It has been suggested that their fidelity, especially in laboratory simulation studies, is 

not always high. Natural analogs, such as those found in Antarctica and on submarines, frequently depart from 

actual space flight conditions. Most frequently, there are more individuals in analog settings than the two to six 

crew members that are common to current, and expected in future, long-duration space flight operations. Regardless of their limitations, however, some of the higher-fidelity mission analogs are the best, and often the only, 

method that is available for gathering the data that are necessary to successfully prepare for Exploration missions. Presenting data from his Antarctic mission, Astronaut Donald Pettit succinctly summed up the value 

of analogs when he stated that “analog physics might be wrong, but the mindset is right” (Pettit, 2007). 

Table 1-1. Behavioral Conditions and Psychiatric Disorders Occurring During Space Flight

Condition 

Occurred During Space Flight 

YES NO 

Behavioral/Psychiatric Emergency 

Mood and Mood Disorders 

Anxiety 

Depression – Signs and Symptoms 

Asthenia – Signs and Symptoms 

Psychosomatic Reactions 

Salutogenic Responses 

Poor Psychosocial Adaptation and Disorders 

Behavioral and psychiatric emergencies

Examining actual occurrences in Antarctica between 1994 and 1997, Palinkas et al. (2004) found that 

12.5% of the crew members at two Antarctic stations, McMurdo and South Pole, presented to the clinic with 

symptoms that met the DSM-IV-TR criteria for one or more disorders. This translates to an overall incidence 

rate of 5.2% over an 8.5-month austral winter. Age, gender, year, level of education, and prior winter experience were not statistically correlated to the DSM-IV-TR diagnoses. (It is important to note that an individual 

may have symptoms without qualifying for a diagnosis or a disorder in the DSM-IV-TR.) 

Another analog environment for space flight is submarines, with their typical mission lengths of 3 months. As 

with space missions, submarine missions occur in a physically confined, socially and physically isolated, 

and extreme environment. For submariners, the incidence of psychiatric disorders that were severe enough 

to result in either the loss of a workday or the need to be medically evacuated ranged between 0.44 and 2.8 

per person-year (Wilken, 1969; Tansey et al., 1979; Dlugos et al., 1995; Thomas et al., 2000). 

Mood and mood disorders

Palinkas et al. (2004) found that the most common category of disorders for individuals who were winteringover in Antarctica was mood disorders; these accounted for 30.2% of all diagnoses. Depressive symptoms 

were significantly related to gender (females were at greater risk), military occupation (rather than civilian), 

station (all diagnosed individuals were stationed at McMurdo; none were stationed at South Pole), year of 

expedition, and having a DSM-IV diagnosis. 

Otto (2007) based his research on 12 years of data from the South Pole Station. At the South Pole Station, 

between 1994 and 2005, the overall incidence rate for depression that required pharmacological intervention 

was 2.03%. This means that one case of depression can be expected every 1.1 winter seasons. The incidence 
Human Health and Performance Risks of Space Exploration Missions Chapter 1 

Risk of Behavioral and Psychiatric Conditions 15

rate for diagnoses of overall mental disorders, including depression, was 4.5% at the three Australian stations according to the Australian National Antarctic Research Expeditions (ANARE) and 6.4% at McMurdo 

Station (Otto, 2007). These incidence rates appear to be lower than those for the general public, which average 9.5% (Kessler, et al., 2005). Antarctic incidence rates could be artificially lower, however, due to a selection process that disqualifies individuals with existing diagnoses from wintering-over. Alternatively, the 

lower rate in Antarctica could be a result of self-selection, whereby individuals who apply to serve in winterover crews tend to have better behavioral health than the general population. 

Winter-over syndrome

Winter-over syndrome consists of a cluster of symptoms that includes interpersonal tension and conflict, 

cognitive impairment, sleep disturbance, and negative affect (Palinkas and Suedfeld, 2008; Strange and 

Youngman, 1971). This syndrome usually is not severe enough to warrant a DSM-IV diagnosis. Rather, it 

might more accurately be considered a subclinical condition (Judd et al., 2002). Some research has shown 

that symptoms peak shortly after the mid-point of an expedition (Palinkas and Suedfeld, 2008). This effect, which 

is called the third-quarter effect, is independent of the length of the expedition. It is believed to occur as a 

result of individuals realizing that their expedition is only half over. Evidence regarding this third-quarter 

effect is inconclusive, however, and researchers continue to debate its existence (e.g., Kanas and Manzey, 

2008; Stuster, 2008). 

Winter-over syndrome shares many similarities with asthenia (Palinkas and Suedfeld, 2008; Otto, 2007). 

Perhaps the most telling similarity is that they both reflect de-adaptation to a stressful situation (Myasnikov 

et al., 2000, as cited in Kanas and Manzey, 2008). 

Salutogenesis

Palinkas and Suedfeld (2008) (Category IV) dichotomize the salutary effects of polar expeditions as being: 

(1) the enjoyable characteristics inherent in the situation, and (2) the positive reactions that come from having 

successfully met and overcome the challenges of the environment. The former are positive effects that are 

felt during the mission. These effects can require coping and resilience. The latter are positive effects that 

are more long-term in nature, and they are met through post-return growth (Palinkas and Suedfeld, 2008) 

(Category IV). 

The isolated, confined, and extreme (ICE) environment, for some individuals, provides personally rewarding 

experiences (Palinkas et al., 1995). For example, the number of people requesting repeated winter-over assignments in Antarctica is evidence of the positive benefits that are associated with the ICE experience (Steel, 

2000; Wood et al., 2000). 

These kinds of effects are also seen in simulation studies. For example, three crew members were isolated 

in the Mir space station simulator for 135 days. They reported more expressiveness and self-discovery and 

less tension than during their pre-isolation training session (Kanas et al., 1996). 

Cognitive changes

Some evidence from Antarctic research suggests that clinical cognitive changes may occur in individuals 

who are exposed to ICE environments, such as space, for long periods of time. Investigators studying 

animal research have further speculated that behavioral changes in such environments may even be 

attributable to the effects of chronic stress on the hippocampus (Otto, 2007). 
Chapter 1 Human Health and Performance Risks of Space Exploration Missions 

16 Risk of Behavioral and Psychiatric Conditions 

Physical aspects of the environment can also produce cognitive changes. Exposure to high levels of radiation, for example, can damage the subcortical basal ganglia and hippocampus that are critical to cognitive 

functioning (Madsen et al., 2003; Vasquez et al., 2003, as cited in Lieberman et al., 2005). For specifics 

regarding the risks of space radiation, please refer to Chapters 4 through 7 in this book. 

Analog mission duration of 2 or more years

Available evidence from assignments in any analog lasting 2 or more years, as will occur for a Mars mission, 

is scant. In Biosphere 2, an eight-member team was isolated on a 3.15-acre artificial, closed ecological system 

in Arizona for 2 years (September 1991 to September 1993). Although they were in a relatively lush and diverse 

environment – with access to television and radio, and daily contact via an observation window – the inhabitants of Biosphere 2 nevertheless experienced psychological stress (MacCallum and Poynter, 1995). The team 

split into two factions within 6 months; stolen food was hoarded; and daily tasks were reported as monotonous. 

One month after the midpoint, some crew members reported experiencing depression that was severe enough 

to interfere with their ability to complete daily tasks (Poynter, 2006). The severity of these behavioral and 

psychiatric responses was most likely due, in part, to a need for more rigorous psychological evaluation when 

selecting those who were best suited for this study. Problems that were experienced with Biosphere 2, in comparison to those of space flight, include poor selection of participants and lack of adequate preparation and 

training. Extensive publicity also may have influenced the experiences of the Biosphere 2 team by sensationalizing them. Although the reader is cautioned about over-interpreting data as well as misapplication of the 

study to space flight, the Biosphere 2 experience is included in this report because it is one of the few 

examples of very long-duration isolation and confinement. 

Two-year assignments, which are common at the Russian Antarctic Station of Vostok, provide additional 

evidence that lengthier periods spent in isolation and confinement increase behavioral and psychiatric problems (Otto, 2007). Alcohol consumption contributed to the main power-generating building burning down 

as well as to the death of a station physician due to alcoholic liver failure. The depth of psychological stress 

that was experienced by some at the Vostok station is vividly illustrated by the example of a wintering-over 

Russian male who, after losing a game of chess, murdered his opponent with an axe (Anthony, 2006). 

These examples most likely do not generalize to astronauts and space travel due to the differences between 

analog and astronaut populations as well as the differences in mission characteristics. However, these examples are alarming and have been included to emphasize the increased risk of behavioral health and psychiatric problems that is associated with extended stays in highly isolated, confined, and extreme environments; 

such long durations are clearly at the outside boundary of our experience and evidence base. 

 Predictors and contributing factors 

Precursors of behavioral health distress serve as warning signals, and many factors contribute to an individual’s 

behavioral health. Monitoring the presence of predictors and contributing factors will allow for the development 

of better screening methods to prevent behavioral conditions and psychiatric disorders from emerging and the 

implementation of countermeasures more quickly and, thus, more effectively. 

As noted previously, numerous factors contribute to an individual’s behavioral health status. Certain factors such 

as crew member personality together with the quality and quantity of sleep predict the likelihood that behavioral 

and psychiatric distress will develop. These factors, which can be viewed as “stressors,” are discussed in the following section. Note that not all “stressors” are negative in terms of their impact on the behavioral health of an 

individual. 
Human Health and Performance Risks of Space Exploration Missions Chapter 1 

Risk of Behavioral and Psychiatric Conditions 17

The Space Studies Board of the U.S. National Academy of Sciences (NAS) differentiates between physical 

and psychosocial environmental stressors (National Research Council (NRC), 2000) as factors that contribute to 

changes in behavioral health. Physical environmental stressors include microgravity and the inherent hazards of 

space flight. Psychosocial environmental stressors include the isolation, confinement, and monotony of life in 

space. 

 Personality 

The results of personality tests have been used to predict job performance for many years. As mission 

length and distances from Earth increase, selecting astronauts and, latterly, composing entire crews/space 

flight teams based on personality traits becomes increasingly critical. 

Some personality evidence that is specific to astronauts exists. Generally speaking, the following types 

of personality comparisons are found. These are comparing: (1) astronauts or astronaut applicants to a 

normative group; (2) astronauts to another occupational group; and (3) astronauts to peer/supervisor performance ratings or selection decision. No research has been undertaken that examines the relationship between 

personality and objective job performance. This lack of objective job performance limits any true attempt to 

identify the “right stuff.” Further, no known research has examined astronaut personality with respect to 

successful reintegration post-flight. 

To date, the published research that is related to space flight has focused on two approaches of personality. 

One examines instrumentality and expressivity, while the other delineates personality in terms of the “Big Five” 

factors (i.e., openness, conscientiousness, agreeableness, extroversion, and neuroticism). The findings of each 

approach are discussed below. 

Instrumentality and expressivity

Personality can be examined in terms of the broad categories of instrumentality and expressivity. The first of 

these, instrumentality, describes the degree of goal-seeking and achievement orientation. Individuals who 

rate highly in instrumentality are highly goal-oriented and have an elevated need for achievement. Those 

who are low in instrumentality tend to be considered egotistical, dictatorial, and arrogant. Expressivity, which is 

the second of the broad categories, is defined as social competence or how an individual behaves in interpersonal relationships. High expressivity is reflected as kindness, emotionality, and warmth. Those who are 

low in expressivity demonstrate negative communion (e.g., submissiveness, servility, gullibility) and 

are verbally aggressive (Kanas and Manzey, 2008). 

Viewing personality in terms of instrumentality and expressivity has been found to be predictive in flight 

crews as well as in other aviation and space populations (Chidester and Foushee, 1991; Chidester et al., 1991; 

McFadden et al., 1994; Musson et al., 2004; Musson and Helmreich, 2005) and in the analog environments 

of submarines, hyperbaric chambers, polar expeditions, and the military (Sandal et al., 1996, 1998, 1999). 

Categorizing personality in terms of instrumentality and expressivity has led to three groups that have 

been informally termed the “right stuff,” the “wrong stuff,” and “no stuff” (Gregorich et al., 1989). The 

right stuff, which is characterized as high on instrumentality and on expressivity, is related to higher peer 

evaluations of job and interpersonal competence (McFadden et al., 1994). Having the right stuff in settings 

that involve complex group interaction is related to superior performance (Musson and Helmreich, 2005). 

In contrast, those who have the wrong stuff are high on instrumentality and low on expressivity. Individuals 

that are low on both instrumentality and expressivity are considered to have “no stuff.” 
Chapter 1 Human Health and Performance Risks of Space Exploration Missions 

18 Risk of Behavioral and Psychiatric Conditions 

Males and females who make it to the final round of astronaut selection are generally high on instrumentality compared to normative (student) scores; no differences are apparent on expressivity. Those who 

are astronauts demonstrate the same pattern as that of final-round astronaut applicants (Musson, 2003) suggesting that personality between the groups is homogenous enough to warrant the use of other attributes to 

further distinguish the best applicants for the job. 

The Big Five

As stated earlier, neuroticism, extroversion, openness to experience, agreeableness, and conscientiousness 

comprise the Big Five. Individuals who are highly neurotic are prone to psychological distress. Those who 

are highly extroverted direct a significant amount of energy toward others. Persons who are highly open to 

experience actively seek that which is new. Agreeable individuals prefer interactions that are compassionate 

rather than tough-minded. Those who are highly conscientious show a level of goal-directed behavior that is 

organized, motivated, controlled, and persistent (Costa and McCrae, 1992). While agreeableness is closely related to aspects of positive expressivity, the other four factors (i.e., neuroticism, extroversion, openness to experience, and conscientiousness) do not easily map onto the instrumentality/expressivity approach (Musson 

et al., 2004). 

A 1991 meta-analysis suggests that conscientiousness is positively related to job performance (defined as job 

proficiency, training proficiency, and personnel data) across occupations as varied as professionals, managers, 

sales, police, and skilled/semi-skilled (Mount and Barrick, 1991). Whether this holds true in Antarctica and 

possibly other ICE environments such as space flight is uncertain. Palinkas et al. (2000) found the opposite to 

be true in Antarctica, namely that better job performance was related to lower conscientiousness. These results 

could be artifacts of the sample or a function of how job performance was operationalized, however. 

Musson (2003), in his examination of human performance data that were collected by the Human Factors 

Research Project at the University of Texas, found that males who made it to the final round of astronaut 

selection were high on agreeableness and conscientiousness and low on neuroticism. As with males, female 

applicants were high on agreeableness and conscientiousness and low on neuroticism. Female applicants were 

also high on extroversion. 

Regarding astronauts rather than astronaut applicants, Musson (2003) found that male astronauts follow the 

same pattern as male astronaut applicants; i.e., they are high on agreeableness and conscientiousness and low 

on neuroticism. Female astronauts, on the other hand, appeared much different from their female applicant 

counterparts. This may be an artifact of the small sample size for female astronauts (N=10); interpretation of 

the apparent differences is not recommended. 

Tying personality to performance, Rose et al. (1994) found that agreeableness is positively related to 

four ratings of performance (i.e., peer-rated interpersonal, technical, and leadership competence as well as 

supervisor-rated job performance) for U.S. astronauts. Openness to experience was negatively related to peerrated technical and leadership competencies and to supervisor-rated job performance. No other significant correlations were found between these performance ratings and the Big Five. It is possible that a lack of significant 

correlations concerning conscientiousness could lend credence to the finding that conscientiousness is not a positive predictor of performance in ICE environments (Palinkas et al., 2000). Alternatively and perhaps more 

likely, the lack of additional significant relationships could be due to the fact that subjective rather 

than objective job performance ratings were used. 
Human Health and Performance Risks of Space Exploration Missions Chapter 1 

Risk of Behavioral and Psychiatric Conditions 19

Antarctica research suggests that ideal candidates for wintering-over in such an isolated and confined environment are relatively low in neuroticism but also relatively low in extroversion and conscientiousness 

(Palinkas et al., 2000). Rosnet et al. (2000) confirm that ideal individuals would be low on extroversion. In a 

third study, polar workers were found to place more highly than the normative group in all factors except neuroticism. Breaking these findings down by occupation reveals that scientists are lower than military personnel 

on extroversion and lower than technical/support staff on both agreeableness and conscientiousness. Differentiating by South vs. North Pole, Antarctic workers are higher than those in the Arctic in terms of extroversion, 

agreeableness, and conscientiousness (Steel et al., 1997). 

Personality as a predictor of adjustment

Individuals who are wintering-over in Antarctica tend to adapt better when they are low in extroversion 

and assertiveness (Rosnet et al., 2000). Gunderson (1966a) found that “achievement needs, needs for activity, 

needs for social relationships and affection, aesthetic needs, needs for dominance or leadership, a sense of 

usefulness in one’s job, and control of aggressive impulses [are] particularly important for adjustment in Antarctic small groups” (p. 4). Three individual characteristics that are related to adaptation in isolated and 

confined conditions in Antarctica are: high social compatibility, high emotional stability, and high task 

motivation (Gunderson, 1966; Stuster, 1996). 

 Emotional Reactions 

Emotional reactions, according to the NRC report by the Committee on Space Biology and Medicine 

(1998), have three primary response systems: language, behavioral acts, and the physiological response 

of alterations to the hypothalamic-pituitary-adrenal (HPA) axis. Language can be used to voice reactions 

to stress through reports of feelings and other communications. Behavioral reactions to emotions are more 

physical in nature, however, and include acts of avoidance or attack. Negative emotions are associated with 

decreased performance and motivation; disruptions to short-term memory, attention, and other cognitive processes; increased interpersonal conflict; isolation from others; and various psychosomatic and psychophysiological symptoms (NRC, 1998). HPA activation can be affected by or cause inadequately regulated emotions, thereby suppressing the immune system and leaving the individual at greater risk for disease (Charles 

and Mavandadi, 2004). HPA is a major component of the stress system that regulates the secretion of corticosteroids. Activation of HPA during depression is common, although whether HPA activation causes or results 

from a depressed mood is not known (NRC, 1998). Alterations of the HPA axis are known to be associated 

with negative emotion in ICE environments (Connors et al., 1986; Palinkas, 1991; Palinkas et al., 1989). 

Thus, during long-duration missions, it is possible that changes may take place in the HPA axis that might 

also affect mood and memory and the immune system (Baum et al., 1982; NRC, 1998; Otto, 2007). 

 Sleep and Circadian Rhythm 

While it is difficult to predict who will or will not develop depression, sleep disruption is one early 

warning sign. Sleep disturbances are common diagnostic criteria for many psychiatric disorders (Colton 

and Altevogt, 2006). Comorbidity of a sleep disorder with a psychiatric disorder is also common; e.g., 40% 

of individuals who are diagnosed with insomnia also have a psychiatric disorder. This comorbidity is higher 

for hypersomnia, where 46.5% of individuals also have a psychiatric disorder (Ford and Kamerow, 1989). 

Insomnia is both a risk factor for and a manifestation of major depression (Livingston et al., 1993; Ohayon 

and Roth, 2003; Cole and Dendukuri, 2003). Research indicates that 15% to 20% of individuals who are diagnosed with insomnia also suffer from major depression (Ford and Kamerow, 1989; Breslau et al., 1996). 

The circadian rhythm of the human body is linked to patterns of biological activities such as brain wave 

activity, hormone production, and cell regeneration. Circadian rhythms can be affected by environmental 
Chapter 1 Human Health and Performance Risks of Space Exploration Missions 

20 Risk of Behavioral and Psychiatric Conditions 

factors; e.g., the amount of ambient light (Czeisler et al., 1986) (Category I). Humans require 2,500 lux to 

entrain their circadian cycles; however, the illumination that is available on ISS at this time is limited to between 108 and 538 lux. Sleep is a large component of the daily circadian cycle and, as such, is affected by 

changes that influence the underlying circadian rhythm (NCR, 1998). Recent Category III unpublished data 

(Barger and Czeisler, 2008) from the ISS and shuttle confirm the findings of previous assessments of sleep 

quantity and quality on orbit; i.e., sleep in flight is indeed reduced in comparison to terrestrial sleep. Changes 

in work schedule also can adversely affect a crew member’s circadian rhythm. During the Russian Soyuz program, sleep schedules were occasionally set counter to the local time of the launch site. This change in sleep 

schedules was associated with decreased quantities of sleep and decrements in performance among the cosmonaut crews (NASA, 1991). Indeed, the Space Studies Board states that a lack of sleep leads to increased 

stress and decreased cognitive and psychomotor functioning (NRC, 1998). 

Current ISS operations often require slam shifting (i.e., sudden shifts in sleep/wake schedule), which can 

result in sleep loss and fatigue for the astronauts. Such schedule changes force critical mission operations to 

occur against the natural circadian rhythm of the body. The commander of Expedition 3, Frank L. Culbertson, 

Jr., did not consider slam shifting to be a problem for the flight crew as long as they had “adequate recovery 

time following the sleep shift and ensuing activities.” He advised that sleep/slam shifting did have some physiological effects on the crew with respect to insufficient rest time (Safety Review Panel, 2002). Slam shifting 

also impacts the ground teams that support the ISS during critical operations as well as the ground teams that 

work overnight against the homeostatic drive to sleep. For detailed information on the performance risk that 

is associated with sleep loss and circadian rhythm disturbances, please refer to Chapter 3 in this book. 

 Monotony and Boredom 

Monotony is a frequent complaint of individuals in ICE environments such as space flight (Kanas, 1998; 

Otto, 2007). In particular, it is the combination of monotonous work with requirements for high degrees 

of alertness and penalties for errors that is seen as especially stressful (Thackray, 1981). Even in the face of 

monotony, however, performance remains high enough for mission success, provided that the motivation is 

high (Kanas and Fedderson, 1971). The lack of variety in social interactions and the physical environment can 

lead to boredom, interpersonal conflict, and loss of energy and concentration (Otto, 2007; NRC, 1998). Members of Biosphere 2 reported that finding sources of stress relief was a major part of working in the Biosphere 

(MacCallum and Poyntner, 1995). Of major concern during long-duration missions is the possibility of too much 

monotonous free time. Boredom has long been known to be the worst enemy of polar explorers (Stuster, 1996). 

As missions become longer, the focus on the amount of work that humans can safely perform changes from 

how much to how little (Weiner, 1977). 

 Environment and Job Design 

In an environment in which an individual floats freely, distinctions between up and down are no longer meaningful. Environmental design, or habitability, is thus no longer confined to the Earthly distinctions among 

floors, walls, and ceilings; this is an asset when the size of the ship or the station is limited. How readily a 

crew member adapts to this truly three-dimensional world varies by individual (Connors et al., 1986). 

The lack of privacy, which has been associated with impaired individual well-being in analog studies, is a 

major psychosocial stressor in space flight (Connors et al., 1985). Individuals who are in confined spaces tend 

to withdraw from one another during leisure time. Further, the leisure time is characteristically spent in more 

passive activities (Seeman et al., 1971). Having private crew quarters in which a crew member can be alone 

thus becomes extremely important on long-duration missions (Santy, 1983; Kanas and Manzey, 2008). 
Human Health and Performance Risks of Space Exploration Missions Chapter 1 

Risk of Behavioral and Psychiatric Conditions 21

Anecdotal evidence suggests that interior décor can affect well-being (Stuster, 1996). Use of many different 

colors and the wide use of darker colors are contraindicated (Kanas and Manzey, 2008). Colors can also be 

used to orient crew members since gravitational cues, which are missing in space, no longer provide navigational aids (Raybeck, 1991). Windows promote well-being in ICE environments by decreasing the sense of 

confinement and monotony of the environment (Haines, 1991). Anecdotal evidence from the earliest space 

flights supports the importance of being able to look outside (Haines, 1991; Lebedev, 1988). Kelly and 

Kanas (1992) provide empirical evidence that “watching” activities became more important. 

In addition to designing the environment to promote well-being, jobs can be designed in such a way as 

to promote well-being and performance. To the extent possible, crew members should have autonomy in 

planning their work schedules, managing their workloads, and deciding when to perform nonessential tasks 

(Kanas and Manzey, 2008). Further, the appropriate amount of work that is to be performed daily must be determined. Overworking can result in performance errors as physical and mental exhaustion occur (Nechaev, 

2001). At the same time, a lack of sufficient meaningful work can adversely affect mental well-being. Quoting 

the first U.S. astronaut on Mir, Norman E. Thagard: “[T]he single most important psychological factor on a 

long-duration flight is to be meaningfully busy. And, if you are, a lot of the other things sort of take care of 

themselves” (Herring, 1997, p. 44). 

For greater detail, please refer to Chapter 10 in this book. 

 Daily Hassles and Major Life Events 

Although some stressors that are found in space are a result of the fact that space is an ICE environment, 

other stressors are unique to space itself. The number and extent of daily hassles of life, i.e., those “irritating, 

frustrating demands that occur during everyday transactions with the environment” (Holm and Holroyd, 

1992, p. 465), are significant predictors of health (DeLongis et al., 1982; Lazarus and DeLongis, 1983; 

Rowlison and Felner, 1988) since increased stress can lead to diminished health. Daily hassles that are associated with the physical environment that is unique to space include: a growing accumulation of garbage, 

limited facilities for sanitation, the need for constant vigilance, and a relative lack of privacy. The noise and 

vibration of ISS are acoustic stressors that can affect sleep quality and quantity, the low level of illumination 

on ISS is a photic stressor, and the physical space on ISS or in any space vehicle is limited. Social density is 

thus an added stressor (NCR, 1998). 

 Cultural and Organizational Factors 

Cultural and organizational factors can contribute to the stress of space flight. Both organizational and 

national cultural differences between the Russian Space Agency and NASA can influence crew dynamics 

(NRC, 1998). Perceived stress can be aggravated by cultural differences in interpersonal distance. An “us vs. 

them” attitude can develop between the crew and its off-site support, as well as feelings of animosity toward 

the same off-site support. This dynamic is sometimes termed “displacement” because the team is displacing 

the intra-group tension onto safer, more remote individuals (Kanas and Feddersen, 1971). Although displacement is not an uncommon occurrence between remote teams and their support centers, it nevertheless becomes 

more critical for space flight as the missions grow longer and the conditions of isolation expand. 

In 1974, friction between crew members and Mission Control during a Skylab mission resulted in a work 

stoppage in which crew members insisted on taking a scheduled day off after weeks of work without a day 

of rest. Russian crews have also experienced conflict with their ground support teams. The crew of one Salyut 

space station shut down communications with Mission Control for 24 hours. Lebedev (1988) and crew members 

failed to report a fire to the ground because “it would have just caused more panic” (p. 309). In addition, 
Chapter 1 Human Health and Performance Risks of Space Exploration Missions 

22 Risk of Behavioral and Psychiatric Conditions 

Antarctic winter-over crews report having avoided communicating with their administrative support or 

deliberately misleading their administrative support (Otto, 2007). 

 Family and Social Support 

According to the NASA Family Support Office, astronauts have reported feeling more relaxed and able to 

concentrate on tasks at hand when they believe that someone is taking care of their families (Category IV). 

Worrying about family and family events that might occur at home while the crew member is away can be 

extremely stressful. Psychiatric intervention was required post-flight for an Apollo 11 astronaut due to his 

marital distress and depression (Aldrin, 1973; Kanas, 1987). The death of his mother caused cosmonaut 

Vladimir Nikolaevich Dezhurov to withdraw for 1 week during his mission (Clark, 2007). 

Astronaut Daniel M. Tani experienced an unexpected personal loss during his ISS mission when his mother 

died in an accident in her hometown. A fuel gauge problem required that a shuttle mission be postponed for 

2 months. This resulted in Tani’s duties as a space station flight engineer being extended by 4 months. It was 

during this extension period that Tani’s mother died. At his return home ceremony, which was held in Houston 

on February 21, 2008, Tani commented on the importance of psychological support: “We so rightfully thank 

every technical trainer we have, but when you go and live on the station, there is a whole aspect of living that 

we have to think about and anticipate.” He expressed his gratitude for flight surgeons and psychologists as 

well as the implication for future missions: “That was invaluable to me. This is something we will have to 

learn how to really support and develop for long-duration flights to the moon and Mars” (Carreau, 2008). 

Such tragedies affect all crew members, including those who are on the ground crews, and they can be 

especially challenging for mission commanders who seek to lend support to a grieving crew member. 

 World Events 

In addition to family events, world events viewed from space, can be stressful. In 1991, the Mir space 

station crew launched as Soviet Union cosmonauts yet later returned to Earth as Russian Federation cosmonauts (Russian Spaceweb, 2008). On board ISS, Astronaut Frank L. Culbertson, Jr., used video and still cameras 

to document the aftermath of the Twin Towers attack on September 11, 2001. On being told of the attacks, he writes 

that he “zipped around the station” (Culbertson, 2001) until he found a window that would give him a view of 

New York City. Culbertson states, “It was pretty difficult to think about work after that, though we had some to 

do, but on the next orbit we crossed the U.S. farther south. All three of us were working one or two cameras to 

try to get views of New York or Washington” (Culbertson, 2001). Although far from home, astronauts and 

cosmonauts are not untouched by political turbulence. 

 Prevention and treatment countermeasures 

Psychological support is provided to prevent or mitigate the impact of potential stressors and to minimize 

the risk of occurrence of behavioral conditions and psychiatric disorders for all current long-duration space 

flight missions. If conditions do arise, a psychological support system allows for early detection of the condition 

and timely application of countermeasures. If necessary, more aggressive treatment methods can be applied. 

Countermeasures can be dichotomized into those that prevent the occurrence of a risk or mitigate the potential 

severity of the risk and those that monitor or treat the risk if it does occur (Strangman, 2008). 

 Prevention Countermeasures 

Seyle’s model of the General Adaptation Syndrome states that as a stressor appears and continues, an individual’s coping resources are first mobilized, deployed, and depleted if not resolved. Seyle (1978) termed these 
Human Health and Performance Risks of Space Exploration Missions Chapter 1 

Risk of Behavioral and Psychiatric Conditions 23

stages alarm, resistance, and exhaustion. One of the goals of prevention is to avoid distress by providing crew 

members with the wherewithal to minimize or negate a stressor. 

The lack of behavioral and psychiatric emergencies during flight is evidence of the efficacy of current countermeasures, given current mission lengths of approximately 6 months. The current practices and services that 

are offered by the BHP Operational Psychology Group at NASA include: pre-flight, in-flight, and post-flight 

preparation; training and support; resources from the Family Support Office; in-flight monitoring; clinical care 

for astronauts and their families; and expertise in the workload and work/rest scheduling of crews on ISS (Sipes 

and Vander Ark, 2005). These services are shaped in part by a crew member’s personal preferences, family 

requests, and specific events during the missions, as well as by programmatic requirements and other lessons 

learned. 

Pre-flight

Prevention begins with selection. Those individuals with the greatest likelihood of having a behavioral 

and psychiatric emergency in flight are eliminated during the selection process; i.e., they never become astronauts. This facet of the selection process is commonly called “select-out.” The NASA select-out system is 

thorough, but the predictive ability of all selection systems diminishes over time. Individuals and circumstances 

change as time passes so that a test that was administered during selection 10 years before an individual is 

assigned to a mission has a limited ability to predict in-flight and post-flight behavior. Not only are the individuals who are most likely to have a behavioral and psychiatric emergency selected-out, but the individuals who 

are best suited to being astronauts are identified. This aspect of selection is typically termed “select-in.” In the 

current NASA selection system rather than being “selected-in,” this aspect of selection is more accurately 

considered “suitability.” 

A suitability score, which is given to each interviewee, is a clinical judgment of the degree to which that 

interviewee would make a good astronaut. Factors that are considered when determining suitability include: 

personality, emotional stability, and family demands. Again, as with select-out tests, select-in suitability scores 

are less predictive over time. To counteract the deterioration of the selection data, annual psychological assessments were recommended in the “NASA astronaut health care system review committee: report to the 

administrator (February – June, 2007)” (Bachmann et al., 2007). Annual BHP assessment interviews, which are 

performed by an experienced flight surgeon who is also board-certified in psychiatry, started in October 2008. 

This assessment is comprised of a 30-minute interview in the NASA Johnson Space Center (JSC) Flight Medicine 

Clinic and covers broad areas of occupational relevance, including space flight experience, workload, fatigue, 

sleep, peer relationships, family, challenges, goals, and future plans. These annual assessments are not intended 

to be comprehensive psychological screenings for mental disorders or psychiatric illness, however. Such an 

assessment would be very time-consuming and produce an extremely low yield of any useful data. Of greater 

importance operationally are the ISS pre-flight assessments that begin 1 year prior to an astronaut being given a 

backup assignment. These interviews are longer (90 minutes) and far more intensive in terms of content. 

Despite the annual and pre-flight BHP assessments, there is a risk of unpredicted in-flight behavioral degradation due to unforeseen circumstances such as mishap, personal tragedy, interpersonal conflict, or the 

development of symptoms of a mental disorder that was latent before flight. In this regard, there remains a risk 

of mission-impacting mental distress and performance degradation that cannot be ignored, one that requires 

further review, improved assessment techniques, and autonomous intervention methods. 

The Operational Psychology (Op Psy) component of BHP provides psychological support to ISS crew 

members (Sipes and Vander Ark, 2005) (Category IV). While the majority of Op Psy support occurs in flight, 
Chapter 1 Human Health and Performance Risks of Space Exploration Missions 

24 Risk of Behavioral and Psychiatric Conditions 

preparations begin pre-flight as astronauts express their preferences for support options such as crew member 

Website content, movies, games, and food. These decisions allow crew members to take some of the familiarity 

and comfort of home with them. 

“Lessons learned” are shared both formally and informally among astronauts and family members. Formal 

Astronaut Office briefings are scheduled following each short- and long-duration mission as well as between 

the assigned crew members of adjacent missions. These lessons learned are documented and distributed among 

astronauts and their families. Formal briefings and training sessions are also scheduled with crew and family 

members before each mission. Informal briefings occur between experienced and inexperienced astronauts, as 

well as between their spouses or significant others. Other opportunities to share information are provided by the 

Astronaut Spouses Group (ASG) during social and educational events. General advice that is not targeted to a 

specific individual or family is available from a variety of resources such as the ASG newsletter, Astronaut 

Office documents, and Flight Medicine Clinic handouts. 

The JSC Family Support Office (FSO) acts for astronauts and their family members by liaising with the 

Astronaut Office, the ASG, BHP, JSC security, the Flight Medicine Clinic, the Military Liaison Office, 

the Public Affairs Office (PAO), and others. An organizational FSO is needed when employee tasks include 

lengthy deployments or hazardous duties that affect employee families. Personnel in the FSO assist with all 

issues or concerns in a confidential manner. They also connect and communicate with families so that these 

families are informed and ready in the event of an emergency. To support families in their readiness preparations, the FSO provides publications, newsletters, email notices, training and educational classes, and specialized seminars. The FSO was created to address the unique challenges that face astronauts and their families 

during astronaut training cycles and flight assignments (Sipes and Vander Ark, 2005). As several astronauts 

have noted, the FSO provides the support that enables them to more easily concentrate on their work in space 

because they believe that their family needs are being met by FSO personnel in their absence. 

One method for providing crew members with additional coping mechanisms is to teach them specific 

coping skills. BHP Op Psy provides classes to astronauts and, in some cases, their families. These classes are 

discussed below: 

In-flight Resource Plans 1 and 2 provide astronauts with an overview of the support that BHP provides to ISS astronauts. This course familiarizes astronauts with BHP and its functions, and provides 

them with a first look at some of the coping mechanisms that are available. 

Self-care/self-management refers to keeping oneself satisfied and productive under demanding circumstances and managing one’s own stress. This class teaches astronauts to apply strategies of selfcare/self-management as they encounter the stressors that are common to long-duration missions. 

Psychological Factors 1 exposes crew members to the psychological effects of long-duration space 

flight. The manifestations of various psychological factors are discussed, as well as the procedures 

that are used to manage any contingencies. 

Psychological Factors 2 continues the discussion of the support resources that are available during 

a mission for the crews and their families. It also identifies the principle environmental, interpersonal, and programmatic factors that can impair psychological health and performance during extended 

confinement. 
Human Health and Performance Risks of Space Exploration Missions Chapter 1 

Risk of Behavioral and Psychiatric Conditions 25

Psychological Support Planning 1, Psychological Support Planning 2, and ISS Crew/Family 

Psychological Support Familiarization classes brief crew members on the psychological support 

program that is established to assist crew members and their families during the pre-flight, in-flight, 

and post-flight phases of the mission. Each crew member begins to identify his or her desired inflight support resources, based on the options that are currently available. At the crew member’s 

discretion, family and/or primary support individuals will be invited to the meeting. 

Practical Planning for Long-duration Missions encourages crews and family members to consider 

important personal arrangements before long-duration missions. This class stresses critical actions 

(e.g., wills, emergency contact information), reviews “lessons learned,” and provides tools and checklists to help simplify the personal preparation process. The FSO offers this class in conjunction with 

BHP and the Astronaut Office. Spouses, significant others, and other key family members may 

attend this event at crew member discretion. 

Conflict Management is a discussion-oriented lesson that introduces a three-point cycle that drives, 

escalates, and de-escalates conflict. The course reviews methods for breaking the cycle at each of the 

three points so that conflicts are resolved in ways that preserve relationships with colleagues, friends, 

and family. Techniques include “rules” for fair fighting, checking the accuracy of interpreted meanings, 

and recognizing and managing emotions that can perpetuate conflict. This training was based on materials that were developed in a National Space Biomedical Research Institute (NSBRI)-supported 

study (Carter et al., 2005). 

Cross-cultural Training exposes U.S. astronauts to special circumstances that can arise from working with crew members and ground control personnel from the International Partners of NASA. The 

course addresses cultural factors, communication and negotiation styles, and work and social factors. 

Potential positive and negative effects of cultural differences are identified. Methods, strategies, and 

resources that can be used to handle cross-cultural challenges are described and practiced within the 

context of case-situations that occurred previously. This course was devised in answer to the interview 

requests of astronauts who flew on ISS and Mir for more and better cross-cultural training (Cartreine, 

2009). 

ISS Behavioral Medicine Training is provided to CMOs and flight surgeons. This training provides 

an overview of the psychiatric symptoms and disorders that might be seen during a mission. Discussion 

includes the therapeutic clinical response and resources that are available on ISS should a crew member 

exhibit seriously disordered behavior. The focus of this training is on serious psychiatric symptoms or illness as opposed to behaviors that fall within the norm for persons who are living in stressful circumstances. 

Behavioral medicine psychiatric interviews begin 12 months before launch and at 30 days post-return. 

These interviews are the mainstay of pre-flight detection and prevention of in-flight psychological or psychiatric problems (NASA, 2008). Interviews focus on mission training issues, crew-crew interaction, family 

issues, sleep and fatigue, workload, crew-ground communication, mood, cognition, ground re-adaptation, and 

family reintegration. 

Another behavioral medicine requirement on the ISS is the WinSCAT (space flight cognitive assessment 

tool for Windows), which is an 11- to 15-minute computer-based cognitive screening test. Baseline testing 

begins 6 months before launch, and the astronaut is requested to take it once a month while in orbit. WinSCAT 

is an operational medical requirement that will be used after an astronaut has suffered any unexpected medical 
Chapter 1 Human Health and Performance Risks of Space Exploration Missions 

26 Risk of Behavioral and Psychiatric Conditions 

event (e.g., head trauma, decompression sickness (DCS), exposure to toxic gases, medication side effects); it 

will serve as a data point for crew surgeon medical assessment/disposition (Kane et al., 2005). Off-nominal 

WinSCAT scores are evaluated in context before adjusting the work-rest schedule or taking another course 

of action. 

These extensive ISS pre-flight behavioral medicine interviews and assessments, along with the BHP training 

classes and other support that are provided, help to prepare crews for long-duration space flight and act as 

another behavioral health-screening aid. 

In-flight

Currently, provision of psychological support is at its most intensive when the astronauts are in flight as 

opposed to during the pre- or post-flight periods. This support system, which is provided by BHP Op Psy, 

includes crew care packages, contact with family and friends, communication technologies, and leisure/recreation activities. Crew care packages are either sent with the crew to be opened later or via resupply to ISS. They 

consist of items that are selected by crew members and their families and friends, such as favorite foods. In a 

Mir simulator study, researchers found that after a resupply event, crew anxiety, total mood disturbance, and 

overall crew tension significantly lessened (Stuster, 1996) (Category II). 

Providing crew members with the opportunity to keep up regular contact with their families is important 

for maintaining crew member behavioral health. Private family conferences are conducted via video between 

crew member and family from within the privacy and comfort of the family home. The internet protocol (IP) 

telephone is an additional link between a crew member and that crew member’s family. The crew member can 

call home when Ku-band coverage is available. The NASA tracking and data relay satellite uses Ku-band to 

communicate with both the shuttle and the ISS. 

Other social contact with the ground that is not necessarily family-specific helps to broaden the social support networks of crew members and acts to lessen crew member feelings of being objectified and separated. 

According to BHP Op Psy, Expedition crew members received approximately 20 greetings during one 

Christmas season. A greeting is a short message, usually in the form of a video that is recorded by family, 

friends, or coworkers, that is sent to a crew member. 

The crew Webpage, the IP telephone, and email can help crew members feel more connected to events on 

Earth. The crew Webpage, which is updated twice weekly for each crew member, is specifically tailored to a 

crew member and, thus, provides that crew member with a gateway to personal news selections, videos, MP3s, 

and photographs. 

Providing choices of leisure activities for crew members is another tool that can prevent behavioral health 

distress. Before flight, crew members request movies, music, and electronic books that will be uploaded to 

them. Even equipment can be requested; for example, in response to the request of various ISS crew members, 

several musical instruments are now on board the station. Astronauts have stated that they use movies and music 

to accompany their required daily exercise regimes. In addition to its physical benefits, exercise also is an 

effective countermeasure for maintaining positive mood. 

Regular private psychological conferences begin once an astronaut is in flight and continue throughout 

the duration of the mission. Private psychological conferences, which are held between a psychologist or 

a psychiatrist and a crew member, are normally conducted every 2 weeks for at least 15 minutes. These con-
Human Health and Performance Risks of Space Exploration Missions Chapter 1 

Risk of Behavioral and Psychiatric Conditions 27

ferences enable the psychologist or psychiatrist to assess the behavioral health of the astronaut and provide that 

astronaut a venue for venting and voicing concerns. 

The WinSCAT, which, as mentioned earlier, assesses cognitive functioning, is scheduled to be taken once a 

month by crew members while they are in orbit. The WinSCAT scores that are recorded after an astronaut has 

sustained any unexpected medical event are compared to that astronaut’s baseline and other pre-insult scores. 

The WinSCAT, along with other data, allows the crew surgeon to make an evaluation regarding the severity 

of an event (Kane et al., 2005). 

Post-flight

Prevention and treatment of post-flight behavioral conditions and psychiatric disorders rely primarily on 

behavioral medicine interviews after a crew member returns to Earth. These post-flight interviews may not be 

of sufficient length to be of benefit, since time is required to allow astronauts to feel comfortable and open up. 

Before astronauts will speak candidly, they must also trust the individual who is conducting the interview and 

believe that the contents of the interview will not adversely affect their future flight status. 

Other post-flight prevention and treatment methods could be incorporated. For instance, the annual 

psychological exams for current astronauts that are recommended in the Bachmann report (2007) would 

provide post-flight support for flown astronauts. A similar psychological exam could be implemented for 

retired astronauts. As all of the effects of flight and return might not be present immediately, continuing the 

behavioral medicine interviews for a longer period of time would provide astronauts with opportunities to 

discuss issues that might arise post-flight. If necessary, pharmacological aids can be prescribed. 

In addition to providing the best measures and tools to monitor and assess mood and predict risk for and 

management of behavioral conditions and psychiatric disorders before and during space flight, the HRP BHP 

Element is required to continue this provision after an astronaut’s return from space flight (NASA, 2007). 

When astronauts return to Earth, reintegration back into the family is not easy. It takes time and will require adjustment from all family members. A class for astronauts and their families that specifically targets the challenges of reintegration could be developed or an existing class could be modified. Education of astronauts and 

their families regarding reintegration is especially important for those who have no deployment experience. 

 Treatment 

Pre-flight

Astronauts and their families have pre-flight access to counseling. There might be some hesitancy to 

use these services, however, given the NASA culture and astronaut concern that flight status might be 

negatively impacted (Shepanek, 2005). 

In-flight

Medical kits that are aboard space shuttle and ISS missions contain supplies to help crew members 

cope with a variety of possible medical emergencies. These kits include medications that can be used in 

the treatment of space motion sickness, sleep problems, illnesses, injuries, and behavioral health problems. 

For example, space shuttle medical kits have included medications that can help to counter anxiety, pain, 

insomnia, fatigue (Caldwell et al., 2003), depression, psychosis, and space motion sickness (Graybiel and 

Lackner, 1987; Savin et al., 1997; Bagian and Ward, 1994; Davis et al., 1993; Harm et al., 1999; Hughes 

and Forney, 1964; Parrott and Wesnes, 1987; Cowings et al., 2000; Rice and Synder, 1993; Wood et al., 

1985, 1992). Putcha et al. (1999) evaluated the in-flight use of medications from astronaut debriefings 
Chapter 1 Human Health and Performance Risks of Space Exploration Missions 

28 Risk of Behavioral and Psychiatric Conditions 

that were conducted after 79 U.S. shuttle missions. The results show that 94% of the records indicated 

that medication was used during flight. 

Space motion sickness accounted for 47% of the medications that were used, while sleep disturbances 

accounted for 45%. The remainder of the medications was reportedly taken for headache, backache, and 

sinus congestion. These findings are an increase from the findings of Santy (1990), who reported that 78% 

of crew members took medications in space, primarily for space motion sickness (30%), headache (20%), 

insomnia (15%), and back pain (10%). Currently, the ISS medicine kit contains two anxiolytics, two antidepressants, and two antipsychotics. While the use of these medicines would be unexpected and unlikely, 

their inclusion is necessary in the event of an actual emergency, just as flying a defibrillator is a medical 

requirement, although no cardiac arrests have occurred to date. In extreme situations, a physical restraint 

system is available. Sedatives are also included in the medical kit if a crew member requires sedation to 

ensure the crew member’s or fellow crew members’ safety. 

As described above, several non-pharmacological tools are available to monitor behavioral issues on 

U.S. spacecraft. The first, and perhaps most important, is the private psychological conference that is held 

between a psychologist or a psychiatrist and a crew member. Private psychological conferences are useful both 

as a monitoring tool and in cases in which an intervention is required. They also can be used to counsel or 

treat astronauts. Initial statistical data that were compiled by BHP experts representing European, Russian, 

and U.S. space agencies indicate that private psychological conferences are accepted by crew members 

(Manzey et al., 2007). During private psychological conference debriefings, astronauts have praised the preflight briefings as well as the psychological services that are provided by operational psychology during 

flight (e.g., private family conferences, crew discretionary events, crew care packages, recreational items) 

and the behavioral medicine support (pre-flight briefings and private psychological conferences). Astronauts have told BHP in debriefings that they did not realize how important “that psych stuff” was until 

after they were on the ISS. 

The flight surgeon is also an important line of defense for reducing the likelihood of a behavioral condition or psychiatric disorder occurring or developing. The role of the flight surgeon is to monitor the physical 

health and well-being of the astronaut. To ensure this, the flight surgeon conducts a 15-minute private medical 

conference once a week with the astronaut. As with the psychologist or psychiatrist, the flight surgeon may 

be able to recognize early signs of behavioral health distress in an on-orbit crew member. Lebedev describes 

his crew doctor intervening during his Salyut 7 flight: “I kept myself under control but I was irritated. Our 

crew doctor, Eugeny Kobzeb, sensed it, and during the evening period of communication said, ‘Wait a minute.’ 

Suddenly I heard a very familiar Ukrainian melody. I couldn’t understand where it came from. Finally it 

dawned on me: it was my son playing the piano. It was so wonderful and unexpected that tears ran from 

my eyes” (Lebedev, 1988, p. 77). 

Post-flight

Several of the methods that are used to prevent the occurrence of post-flight behavioral conditions and 

psychiatric disorders can also be used to treat these conditions if they occur post-flight. Annual psychological 

exams for current and retired astronauts can be used as a springboard for targeting treatment options; e.g., 

continued counseling or pharmacological aids. As not all effects of space flight and reintegration are immediately present at the time at which an astronaut returns, post-flight behavioral medicine interviews could 

be continued at additional intervals beyond those intervals that currently occur post-flight. To the extent 

that a family is experiencing difficulty with an astronaut reintegrating, family counseling is another treatment option that is available post-flight. 
Human Health and Performance Risks of Space Exploration Missions Chapter 1 

Risk of Behavioral and Psychiatric Conditions 29

 Summary 

The operational set of activities that was described in the previous sections consists of specific medical 

requirements that are determined to be necessary by an international group of behavioral health specialists. 

If flight surgeons as well as astronauts had seen no value in these activities, they would have been waived or 

removed. Instead, astronauts have communicated their appreciation of and desire for these services. According 

to the lead NASA psychiatrist (personal communication), every ISS astronaut has stated that these training 

measures and countermeasures of behavioral medicine and operational psychology support are both valued and 

beneficial. Areas of enhancements that were cited by these astronauts include: crew morale, mood, motivation, 

crew cohesion, and family ties during the mission. 

Astronaut use of many BHP operational services is voluntary. They are presented to the crew member and 

family from the first meeting as a “buffet” from which they can choose all, some, or none, and they have an 

opportunity to request their own services. The fact that crew members and their families consistently have 

requested more operational psychology support as the program has developed and continue to request specific 

services that are already offered are indicators that these services are needed and should be continued. The internationally publicized death of a crew member’s family member during Expedition 16 tested the value and 

benefit of the services that are currently offered by BHP. 

This type of tragedy is addressed in pre-flight behavioral medicine training with all crews. As humans continue 

to explore space, it will surely not be the last time that this type of event occurs. The response to such a tragedy 

requires the implementation of all facets of operational psychology and behavioral medicine countermeasures. 

Lastly, the high number of Silver Snoopy awards11 that have been awarded by the astronauts to the BHP Op Psy 

Behavioral Specialists who have directly supported these services demonstrates astronaut appreciation of BHP 

training, treatment, and prevention services. 

 Risk in Context of Exploration Mission Operational Scenarios 

Depression is becoming more common in the general population. The WHO (2001), in its annual report, 

predicts that depression will become the second-largest cause of disability worldwide by the year 2020. It is 

already the leading cause of disability in the U.S. according to the NIMH (2000). In a given year, approximately 

20.9 million U.S. adults, or about 9.5% of the population who are age 18 or older, will develop a mood disorder 

(Kessler et al, 2005; NIMH, 1999). 

To assess and quantify the risk of behavioral conditions and psychiatric disorders in the context of future Exploration missions, it is important to consider the crew member’s nationality and age. Annual rates of depression differ 

from one region to another. In the U.S., depression is the third-most-frequent psychiatric diagnosis (NIMH, 2000). 

In other countries, however, the rate of depression is considerably lower. The likelihood of a mood disorder developing also varies by age group. Close to one-half of the psychiatric disorders that led to U.S. Naval aviation personnel waivers were for persons who were older than age 30 (Bailey et al., 1995). Major depression along with manic 

depressive disorder and obsessive compulsive disorder are highly likely to develop for the first time in North 

American and Western European astronauts’ age groups (Burke et al., 1990; Flynn, 2005). 

 

11The Silver Snoopy is the most prestigious award given by the members of the NASA Astronaut Corps. The award consists of a 

sterling-silver Snoopy lapel pin that has flown on a space shuttle mission, plus a certificate of appreciation and commendation letter. 
Chapter 1 Human Health and Performance Risks of Space Exploration Missions 

30 Risk of Behavioral and Psychiatric Conditions 

The total incidence rate for the general adult population is a summation of the incidence rates for each subgroup 

based on age and gender. The incidence rates for the subgroups are therefore lower than the total adult population 

incidence rate. More specifically, tailoring the incidence of depression in the general population to the age range 

of the astronaut population will yield a considerably lower rate than the 9.5% that is estimated for the general U.S. 

population. The NASA IMM uses an incidence rate of depression and anxiety (for males 0.00029 cases per personyear and females 0.0036 cases per person-year) that is extrapolated from the Longitudinal Study for Astronaut Health, 

whose incidence rate is limited to the average age range of the astronauts (i.e., 40 to 49 years). Behavioral emergencies 

in the general population occur in 3% to 9% of depression cases (Murphy et al., 1988; Ramadan, 2007). Extrapolating from these rates, the overall incidence rate of behavioral emergencies due to depression for astronauts can be 

estimated as 0.000087 to 0.000324 cases per person-year (NASA, 2007b). However, it is important to note that the 

rates that were used in these calculations were based on reported symptoms only and were not derived from a confirmed diagnosis. Therefore, the incidence of depression and anxiety may or may not be higher in crew members 

in space flight than in the age-adjusted general population due to the high workload and stressors that are associated with some aspects of space flight missions (NASA, 2007a). 

Rather than basing his estimate on the incidence rate of depression in the general population, Stuster (2008) predicted that the incidence rate of behavioral problems that could be expected on long-duration Exploration missions 

is based on known incidence rates in analog environments. Reporting physicians defined behavioral problems as 

symptoms that normally would warrant hospitalization. Stuster’s analyses show that as the length of a mission increases, so will the incidences of psychiatric disorders (see Table 1-2). Stuster’s (2008) assumptions are as follows: 

Table 1-2. Calculation of Expedition Risk of a Behavioral Problem Occurring Based on Incidence and Probabilities 

in Analog Environments

Long-stay Option 

Incidence Per 

365 Days 

Outbound Surface Return Total Longstay Risk 

Expected in a 

Crew of Six 

180 days 545 days 180 days 905 days 

Behavioral 

Problem 0.060 0.030 0.090 0.030 0.149 0.893 

Differential 0.020 0.030 0.030 0.030 0.089 0.534 

Short-stay Option 

Incidence Per 

365 Days 

Outbound Surface Return Total Shortstay Risk 

Expected in a 

Crew of Six 

313 days 40 days 308 days 661 days 

Behavioral 

Problem 0.060 0.051 0.007 0.051 0.109 0.652 

Differential 0.020 0.051 0.002 0.051 0.104 0.626 

Prepared by Jack Stuster, Ph.D., CPE 

Anacapa Sciences, Inc. 

The figures in the row labeled Behavioral Problem assume a 6% per year incidence rate of serious 

behavioral problems throughout the durations of the two mission options considered (i.e., Mars 

Long Stay, 905 days total; and Mars Short Stay, 661 days total). This predicted incidence rate is 

based on incidence rates of behavioral problems reported from Antarctic experience (i.e., Matusov, 

1968; Gunderson, 1968; Lugg, 1977; Rivolier and Bachelard, 1988; ANARE; Otto, 2007). The row 

labeled Differential assumes a 6% incidence rate per person-year during the interplanetary transit phases 

and a 2% rate per person-year while on the surface of Mars, when confinement would probably be less 

of a factor and other stressors might be offset by the novelty of task performance. The expected oc-
Human Health and Performance Risks of Space Exploration Missions Chapter 1 

Risk of Behavioral and Psychiatric Conditions 31

currence of a behavioral problem serious enough to require hospitalization on Earth in a crew of six 

is estimated to be .534 for the long-stay option and .626 for the short-stay option. Using the differential 

values, these translate to a 53.4% probability that a serious behavioral problem will occur during the 

long-stay option and a 62.6% probability during the short-stay option. Stuster asserts the probability 

of a serious problem occurring to be greater for the short-stay option [on Mars], due to the substantially 

longer time that must be spent by the crew confined to the space craft than in the long-stay option. 

However, the long-stay option will always generate a higher probability if the incidence rate were to 

remain constant throughout the mission. A uniform 6% incidence rate per person-year would increase 

the estimated probability of a serious behavioral problem to 65.2% for the short-stay option and 

89.3% for the long-stay option. 

The two approaches (IMM and Stuster’s analog-based) to estimating the incidence rate of behavioral conditions 

and psychiatric disorders yield very different predictions. Further investigation of the discrepancies between the 

two estimates is warranted. What is noteworthy in both approaches is the predicted occurrence of a behavioral 

problem during a long-duration mission. 

 Conclusion 

Evidence that was gathered from long-duration stays in ground analogs demonstrates that, despite the focus 

on screening and selection for suitability, behavioral conditions and psychiatric disorders such as depression 

develop. Of greater relevance, anecdotal reports from the earlier long-duration space missions (i.e., Mir and 

Skylab) and evidence from current long-duration missions on the ISS reveal that the signs and symptoms of 

depression and other behavioral disorders also have occurred in flight. The relevance of the risk of behavioral 

conditions and psychiatric disorders is supported further by the implementation by NASA of the Family Support 

Office as well as by the psychiatric support that is made available to the ISS crews and their families. 

Exploration missions will require crews to live in ICE environments for as many as 3 years. This is a significant leap from the 6-month duration of lower Earth orbit missions. To date, only five individuals have lived 

and worked in space for longer than 1 year.12 The incidence of behavioral and psychiatric disorders is expected 

to increase as the length of the mission increases (Ball and Evans, 2001; Otto, 2007; Stuster, 2008) (Category IV). 

The additional, unique stressors of radiation exposure, remote distances, and unknown dangers that will be experienced during long-term Exploration missions to the moon and Mars also may contribute to an increased 

likelihood of this risk. 

If a behavioral condition or psychiatric disorder should develop on an Exploration mission, the consequences 

could jeopardize mission objectives. Therefore, future research addressing the prevention of behavioral problems, 

as well as the early detection and treatment of problems that do occur, is recommended. 

The current rigorous astronaut selection system prevents some behavioral problems from manifesting 

themselves. Refining and updating the system could prevent the onset of additional problems. Recommended 

improvements to the selection system include: validation of the current system and implementation of a true 

select-in system (i.e., one that identifies the interviewees who are most likely to succeed as astronauts). Periodic 

psychological reassessment also could possibly detect early signs of a behavioral condition or psychiatric disorder. 

Further, if those who assign astronauts to crews and missions were to employ psychological selection methodology, 

 

12To date, three Russian cosmonauts (Sergei Krikalev, Sergei Avdeyev, and Alexander Kaleri) and two U.S. astronauts (C. Michael 

Foale and E. Michael Finke) have spent more than 1 year in space. 
Chapter 1 Human Health and Performance Risks of Space Exploration Missions 

32 Risk of Behavioral and Psychiatric Conditions 

they might increase the likelihood that those astronauts who are selected for a crew would be unlikely to experience an in-flight behavioral medicine emergency. 

Early detection is important in deterring and treating behavioral and psychiatric problems. Research that investigates the best assessment measures to detect behavioral and psychiatric disorders is warranted. Thus, one example 

of a possible future research topic is which personality measures best predict astronaut psychosocial adjustment 

to space flight. 

NASA has many countermeasures in place and will need to develop additional countermeasures that are tailored 

to long-term lunar and Mars missions. The efficacy of the current countermeasures for future Exploration mission 

scenarios needs to be formally assessed. The astronauts who will be venturing out on long-duration space flight 

missions beyond low-Earth orbit (LEO) will face unique challenges, including the need to manage behavioral 

health problems autonomously. Research is needed to address appropriate countermeasures that are specific 

to the Exploration mission environment. A better understanding of factors affecting positive emotional reactions 

also will be important when developing countermeasures for use during long-duration Exploration missions. 

Early, quick, and effective treatment of any behavioral problems that do occur is essential. Future research 

should include investigation of other treatment options and an assessment of the efficacy of those treatment 

options. 

This review of the evidence to date reveals that much work has been done to identify, prevent, and treat the 

behavioral conditions and psychiatric disorders that might affect astronauts and their performance during all 

phases of a mission. Given the relative lack of behavioral conditions and psychiatric disorders that have occurred 

within the astronaut population, the lack of behavioral and psychiatric emergencies in flight, and the number of 

long-duration mission successes, the current system for mitigating the risk of behavioral conditions and psychiatric 

disorders appears to be effective. As missions return to the moon and then look toward Mars, changes to behavioral 

medicine will be required. Our view of the “right stuff” will need to be adjusted. Factors such as personality might 

play a greater role, while other factors, such as pilot experience, might play a lesser role than they do at present. 

The selection system will therefore need to reflect those changes. Countermeasures will need to evolve. Some 

current countermeasures will not be relevant for longer flights, while other, new ones will need to be developed 

(e.g., alternative to seeing Earth). Effective countermeasures will help to protect and ensure astronaut behavioral 

health and performance, and, in turn, help NASA achieve mission success on the most challenging Exploration 

missions that humankind has dared to undertake to date. 

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Human Health and Performance Risks of Space Exploration Missions Chapter 1 

Risk of Behavioral and Psychiatric Conditions 43

 Acknowledgments 

We acknowledge the important and thoughtful contributions that were made by our BHP community, including 

flight surgeons and medical operations, researchers from the NSBRI, our external investigators, and many others 

as noted below. These efforts, while time-consuming, are critical for understanding and communicating what 

is known and unknown regarding the risks that are associated with human space flight, particularly as we embark on Exploration missions to the moon and Mars. Such knowledge will enable us to meet these future 

challenges and succeed. 

 Contributors and reviewers 

Pamela Baskin, B.S.; Research Scientist, BHP, Space Medicine Division; NASA Johnson Space Center; Wyle 

Integrated Science and Engineering Group; Houston. 

Gary Beven, M.D.; U.S. Air Force Flight Surgeon, Board-certified general and forensic psychiatrist, Chief, 

BHP, Space Medicine Division, NASA Johnson Space Center; Houston. 

Frank E. Carpenter, M.D.; U.S. Air Force Senior Flight Surgeon, board-certified general psychiatrist; (Formerly) 

Chief, BHP, Space Medicine Division, NASA Johnson Space Center; Houston. 

James (Carter) Cartreine, Ph.D., Research and Clinical Psychologist; Beth Israel Deaconess Medical Center; 

Instructor in Medicine and Psychiatry, Harvard Medical School; Boston, Mass. 

Jonathan B. Clark, M.D.; Space Medicine Liaison, NSBRI, Baylor College of Medicine; Houston. 

Edna R. Fiedler, Ph.D.; Liaison for Health and Science, NSBRI, Baylor College of Medicine; Houston. 

Kathy A. Johnson-Throop, Ph.D.; Information Systems, Decision Support Systems, Knowledge Management, 

and Healthcare Systems; Chief, Medical Informatics and Healthcare Systems Branch, Space Medicine Division, 

NASA Johnson Space Center; Houston. 

Kathryn Keeton, Ph.D.; BHP, Industrial Organizational Psychology, Research Scientist, Wyle Integrated 

Science and Engineering Group; Houston. 

Christian A. Otto, M.D.; Remote Operational Medicine Scientist, Division of Emergency Medicine, University 

of Ottawa; Canada. 

Lawrence A. Palinkas, Ph.D.; Professor, School of Social Work, University of Southern California; Los 

Angeles, Calif. 

Walter E. Sipes, Ph.D.; Lead, Operational Psychology, BHP, Space Medicine Division, NASA Johnson Space 

Center; Houston. 

Jack W. Stuster, Ph.D.; CPE, Human Performance in Extreme Environments; Habitability, Equipment, and 

Procedural Design. Vice President and Principal Scientist, Anacapa Sciences, Inc.; Santa Barbara, Calif. 

Steve Vander Ark, M.S.; BHP, Operational Psychology; Section Manager for Space Medicine, Wyle Integrated 

Science and Engineering Group; Houston. 
Chapter 1 Human Health and Performance Risks of Space Exploration Missions 

44 Risk of Behavioral and Psychiatric Conditions 

 Appendix: Incidence of Physical and Behavioral Medical 

 Events during Space Flight 

In-flight medical events for U.S. astronauts during the Space Shuttle Program (STS-1 through STS-89, 

Apr 1981 to Jan 1998) 

Medical Event or System 

by ICD-9a Category 

Number of 

Events Percent Incidence/ 14 days 

Incidence/ 

year 

Space adaptation syndrome 788 42.2 2.48 64.66 

Nervous system and sense organs 318 17.0 1.00 26.07 

Digestive system 163 8.7 0.52 13.56 

Skin and subcutaneous tissue 151 8.1 0.48 12.51 

Injuries or trauma 141 7.6 0.44 11.47 

Musculoskeletal system and connective tissue 132 7.1 0.42 10.95 

Respiratory system 83 4.4 0.26 6.78 

Behavioral signs and symptoms 34 1.8 0.11 2.87 

Infectious disease 26 1.4 0.08 2.09 

Genitourinary system 23 1.2 0.07 1.83 

Circulatory system 6 0.3 0.02 0.52 

Endocrine, nutritional, metabolic, and immunity 

disorders 

2 0.1 0.01 0.26 

a

International Statistical Classification of Diseases and Related Health Problems, 9th Ed. 

Source: Billica (2000) 

Medical events among seven NASA astronauts on Mir, Mar 14, 1995 through Jun 12, 1998 

Event Number of Events Incidence/100 days Incidence/year 

Musculoskeletal 7 0.74 2.70 

Skin 6 0.63 2.30 

Nasal congestion, irritation 4 0.42 1.53 

Bruise 2 0.21 0.77 

Eyes 2 0.21 0.77 

Gastrointestinal (GI) 2 0.21 0.77 

Psychiatric 2 0.21 0.77 

Hemorrhoids 1 0.11 0.40 

Headaches 1 0.11 0.40 

Sleep disorders 1 0.11 0.40 

Note: Data from the Russian Space Agency report that there were 304 in-flight medical events on board the Mir from 

Feb 7, 1987 through Feb 28, 1998. The numbers of astronauts at risk or the incidence per 100 days was not reported. 

Source: Marshburn (2000) 
Risk of Performance Errors Due to Poor Team Cohesion and Performance, Inadequate Selection/Team 

Composition, Inadequate Training, and Poor Psychosocial Adaptation 45

Chapter 2: 

Risk of Performance Errors due to Poor 

Team Cohesion and Performance, Inadequate 

Selection/Team Composition, Inadequate 

Training, and Poor Psychosocial Adaptation 

Lacey L. Schmidt 

Wyle Integrated Science and Engineering Group 

Kathryn Keeton 

Wyle Integrated Science and Engineering Group 

Kelly J. Slack

Wyle Integrated Science and Engineering Group 

Lauren B. Leveton

NASA Johnson Space Center 

Camille Shea 

Universities Space Research Association 

Human performance errors may occur due to problems associated with working in the space environment 

and incidents of failure of crews to cooperate and work effectively with each other or with flight controllers 

have been observed. Interpersonal conflict, misunderstanding and impaired communication will impact 

performance and mission success. The history of spaceflight crews regarding team cohesion, training and 

performance has not been systematically documented. Tools, training and support methods should be 

provided to reduce the likelihood of this risk and improve crew performance. – Human Research Program 

Requirements Document, HRP-47052, Rev. C, dated Jan 2009. 

Shared diversions on the International Space Station, including 

musical performances and movie 

nights, provide rest and relaxation 

while promoting team cohesion.
46 Risk of Performance Errors Due to Poor Team Cohesion and Performance, Inadequate 

 Selection/Team Composition, Inadequate Training, and Poor Psychosocial Adaptation 
Human Health and Performance Risks of Space Exploration Missions Chapter 2 

Risk of Performance Errors Due to Poor Team Cohesion and Performance, Inadequate Selection/Team 

Composition, Inadequate Training, and Poor Psychosocial Adaptation 47

 Executive Summary 

Evidence from space flight and ground-based studies supports the idea that performance and health are 

both influenced by several interpersonal factors that are related to teamwork, including: team cohesion, team 

selection and composition, team training, and psychosocial adaptation. Space flight evidence regarding performance and the effect of these psychosocial factors is more limited than evidence that is available from groundbased research. However, numerous NASA-funded and -supported reviews and reports (regarding space flight 

and space analogs) emphasize the need to consider the team as well as the psychosocial factors affecting the team 

(Ball and Evans, 2001; Hackman, 1996; Helmreich, 1985; NASA, 1987; Paletz and Kaiser, 2007; Vinograd, 1974). 

To date, no systematic attempt has been undertaken to measure the performance effects of team cohesion, team 

composition, team training, or psychosocial adaptation during space flight. As a result, evidence does not help 

us to identify specifically what team composition, level of training, amount of cohesion, or quality of psychosocial 

adaptation is necessary to reduce the risk of performance errors in space. Ground-based evidence demonstrates, 

however, that decrements in individual and team performance are related to the psychosocial characteristics of 

teamwork, and there are reasons to believe that ground support personnel and crew members experience many 

of the same basic issues regarding teamwork and performance (Hackman, 1996; Lautman and Gallimore, 1987; 

Vinograd, 1974). 

Although evidence does not identify specific factors or how these factors are important, evidence that was 

reviewed in this report demonstrates that addressing the psychosocial characteristics of teamwork will promote 

crew health and performance. Before this knowledge can be effectively applied to long-duration missions, however, 

more research must be done to determine what practices (e.g., selection, training, coaching, psychological support) 

best address the psychosocial characteristics of teamwork in space flight. The BHP Element has identified the 

gaps in the knowledge that is related to these issues, and a review of these gaps is included in this report. 

 Introduction 

Evidence that links crew selection/composition, training, cohesion, or psychosocial adaptation to performance 

errors is uncertain. This is mainly due to the fact that the research on performance errors is itself ambiguous. The 

study of performance errors implies that human actions may be simplified into a dichotomy of “correct” or “incorrect” responses, where incorrect responses or errors are always undesirable. Some researchers have argued 

that this dichotomy is a harmful oversimplification, and that it would be more productive to focus on the variability of human performance and how organizations can manage that variability (Hollnagel et al., 2006) 

(Category III13). 

Two particular problems occur when focusing on performance errors: (1) the errors are infrequent and, therefore, are difficult to observe and record; and (2) the errors do not directly correspond to failure. Research reveals 

that humans are fairly adept at correcting or compensating for performance errors before such errors result in 

 

13To help characterize the kind of evidence that is provided in each of the risk reports in this book, the authors were encouraged to 

label the evidence that they provided according to the “NASA Categories of Evidence.” 

 Category I data are based on at least one randomized controlled trial. 

 Category II data are based on at least one controlled study without randomization, including cohort, case-controlled or subject

operating as own control. 

 Category III data are non-experimental observations or comparative, correlation and case, or case-series studies. 

 Category IV data are expert committee reports or opinions of respected authorities that are based on clinical experiences, bench 

research, or “first principles.” 
Chapter 2 Human Health and Performance Risks of Space Exploration Missions 

48 Risk of Performance Errors Due to Poor Team Cohesion and Performance, Inadequate 

 Selection/Team Composition, Inadequate Training, and Poor Psychosocial Adaptation 

recognizable or recordable failures (Hollnagel et al., 2006) (Category III). Most failures are recorded only when 

multiple errors occur and humans are unable to recognize and correct or compensate for these errors in time to 

prevent a failure (Dismukes et al., 2007) (Category III). 

More commonly, observers record variability in levels of performance. Some teams commit no observable 

errors but fail to achieve performance objectives or perform only adequately, while other teams commit some 

errors but still manage to perform spectacularly. Successful performance, therefore, cannot be viewed as simply 

the absence of errors or the avoidance of failure (JSC Joint Leadership Team, 2008). While failure is commonly 

attributed to making a fatal error, focusing solely on the elimination of error(s) does not significantly reduce the 

risk of failure. Failure may also occur when performance is simply insufficient or an effort is incapable of adjusting 

sufficiently to a contextual change. The surest way to reduce the risk of failure is to achieve optimal performance. 

If NASA is to spend the same amount of money launching one of two crews and both crews have an equal risk 

of committing performance errors but one crew is more likely to perform more of the mission objectives (or 

otherwise perform better), it follows that the most desirable crew remains the highest-performing crew. From 

this point of view, the more critical question is: how can we optimize human performance during long-duration 

missions? 

Fortunately, the evidence that links crew selection/composition, training, cohesion, or psychosocial adaptation to 

performance differences is more conclusive and more relevant to future human space exploration operations than 

is the evidence regarding performance errors. The list of what is known from existing research (ground-based, space 

analog, and space flight) is considerable. In light of the positive influences of team performance, we know that 

 We can select individuals who are more capable of performing well in a team (Barrick et al., 1998) 

(Category III). 

 Different team compositions better facilitate different types of performance (Mannix and Neale, 2005) 

(Category III). 

 Training individual team skills and training teams together encourages better individual and team 

performance (Hirschfeld et al., 2006; Paris et al., 2000; Salas et al. Bowers, 2000) (Category II and 

Category III). 

 Teams that are more cohesive demonstrate better performance than less cohesive teams (Grice and 

Katz, 2005) (Category II). 

 Better teamwork increases the likelihood of recovery and survival in the event of a malfunction or 

error (Baker et al., 2006; Shapiro et al., 2004) (Category III). 

 Members of more cohesive teams demonstrate better individual performance and report more physical 

and psychological resilience under duress (Kidwell et al., 1997; Palinkas, 1991; Podsakoff et al., 1997; 

Vallacher et al., 1974) (Category II and Category III). 

 Individuals and teams perform better and maintain high performance and good health longer when 

they adapt more quickly and effectively to the stressors that are inherent in a psychosocial environment 

(Burke et al., 2006; Gunderson, 1966a; Lugg, 1977; Riggio et al., 1993) (Category III). 

 Psychosocial factors that influence teamwork and performance in traditional work environments 

appear in the space exploration work environment (Kanas et al., 2000) (Category III). 

Negative influences of team performance have also been researched. From the perspective of these, we know that 

 Negative consequences (e.g., incomplete objectives; lost time) that are related to interpersonal 

stressors such as isolation, confinement, danger, monotony, inappropriate workload, lack of control, 
Human Health and Performance Risks of Space Exploration Missions Chapter 2 

Risk of Performance Errors Due to Poor Team Cohesion and Performance, Inadequate Selection/Team 

Composition, Inadequate Training, and Poor Psychosocial Adaptation 49

group composition-related tensions, personality conflicts, and leadership issues have been observed on 

previous long-duration missions (Kanas and Manzey, 2003) (Category III). 

 Interpersonal stressors, which are cumulative over time, pose a greater threat to performance and team 

success as work duration increases (Cropanzano, 2003; Halbesleben and Bowler, 2007; Rasmussen and 

Jeppesen, 2006; Staal, 2004; You et al., 1998) (Category II and Category III). 

Selection, training, cohesion, and psychosocial adaptation influence performance and, as such, are relevant 

factors to consider as we prepare for costly, long-duration missions in which the performance objectives will 

be demanding, endurance will be tested, and success will be critical. During the selection of crew members, 

throughout their training, and during their psychosocial adaptation to the mission environment, we will have 

several opportunities to encourage optimal performance and, in turn, minimize the risk of failure. Researchers, 

who are faced with the very real prospect of needing to promote successful human explorations of the moon and 

Mars within the next 15 to 20 years, should not spend limited time and resources in attempts to quantify risks of 

failure or performance errors due to inadequate selection, training, cohesion, or psychosocial adaptation. Instead, 

these researchers should focus on how they can most efficiently optimize and support performance through selection, training, team building, and psychosocial adaptation. Human performance professionals currently possess 

the knowledge to be able to make this kind of research productive and operationally relevant within the projected 

time until launch. The evidence that is detailed in the following sections supports this argument. 

The NASA HRP BHP Element is responsible for managing three risks: (1) risk of performance errors due to 

sleep loss, circadian desynchronization, fatigue, and work overload; (2) risk of performance errors due to poor 

team cohesion and performance, inadequate selection/team composition, inadequate training, and poor psychosocial 

adaptation; and (3) risk of behavioral and psychiatric conditions. While each of these is addressed in a separate 

chapter in this report, they should not be construed to exist independent of one another; they instead should be 

evaluated in conjunction with one another. Moreover, as the BHP Risks overlap with the Risks in other HRP 

Elements, they must also be considered in conjunction with these Elements as well. Refer to figure 2-1 for 

an example of possible overlaps. 

Figure 2-1. Example of possible BHP Risks overlapped with Risks in other HRP Elements. 
Chapter 2 Human Health and Performance Risks of Space Exploration Missions 

50 Risk of Performance Errors Due to Poor Team Cohesion and Performance, Inadequate 

 Selection/Team Composition, Inadequate Training, and Poor Psychosocial Adaptation 

The BHP relationships with other Elements are further outlined in the HRP IRP (2008). The nature of the IRP 

implies that BHP is continually reviewing and updating integration points with other Elements. While research 

is designed to address identified gaps, it will be necessary to update and revise each of the BHP Evidence 

Reports that constitute this document and the IRP as the element gaps are closed and new gaps emerge. 

 Evidence 

 Individual selection and crew composition 

 Selecting Individuals to Perform in a Team 

A team is defined as: “two or more individuals who interact socially and adaptively, have shared or common 

goals, and hold meaningful task interdependences; it is hierarchically structured and has a limited life span; in 

it expertise and roles are distributed; and it is embedded within an organization/environmental context that influences and is influenced by ongoing processes and performance outcomes” (Salas et al., 2007a, p. 189). From 

the NASA perspective, a team is commonly understood to be a collection of individuals that is assigned to support and achieve a particular mission. Thus, depending on context, this definition can encompass both the crew 

and the individuals who are assigned to support that crew during a mission. Regardless of the extent to which 

the term is used, the selection of a team can be both complex and difficult when considering individual differences that may influence the functioning of a team. 

One way of selecting for teams is to identify those individuals who are best suited to work in teams, ensuring 

that each individual team member possesses the qualities and skills that lend themselves to optimal teamwork. 

For example, many organizations use competency frameworks to select individuals (e.g., IBM, GE, Verizon, 

Waste Management, Hanover, Shell, 3M, the United States Office of Personnel Management) (Rodriguez et 

al., 2002). Within these frameworks, a “team-working” competency may be found that measures how an individual supports other team members, shares knowledge with them, etc. Both space flight (Category III) and 

ground-based (Category I and Category II) evidence suggests that “teamwork” competencies help predict 

individual performance in teams. 

Several efforts have been made, within space flight operations, to identify factors that are important for selecting individual crew members for long-duration space flight (Caldwell, 2005; Galarza and Holland, 1999; 

Hackman, 1996; Holland, 2000; NASA, 1987; Nicholas and Fouchee, 1990; Vinograd, 1974) (Category III 

and Category IV). Galarza and Holland (1999) conducted a preliminary job analysis to identify the skills that 

would be necessary for long- vs. short-duration missions to inform the initial astronaut candidate selection 

process (Category III). 

Twenty experts (including astronauts) rated 47 relevant skills on criticality and rated an additional 42 environmental and work demands on their probability of occurrence. The environmental and work demands for 

long-duration space missions included group dynamics within a heterogeneous crew and with external groups 

such as ground control. The experts’ ratings resulted in 10 broad factors that were deemed important for longduration missions, including performance under stressful conditions, mental/emotional stability, judgment/decisionmaking, teamwork skills, conscientiousness, family issues, group living skills, motivation, communication 

skills, and leadership capabilities. These 10 factors overlap somewhat with those that were identified in 

previous peer-rating studies, which suggests both a job competence and an interpersonal dimension for 

astronaut performance (McFadden et al., 1994; Santy, 1994) (Category III). 
Human Health and Performance Risks of Space Exploration Missions Chapter 2 

Risk of Performance Errors Due to Poor Team Cohesion and Performance, Inadequate Selection/Team 

Composition, Inadequate Training, and Poor Psychosocial Adaptation 51

In 1990, a European astronaut working group reevaluated selection criteria for the selection of European astronauts. Although astronauts had not been historically screened for interpersonal skills, this group 

included social capabilities as criteria for selection (Sandal, 1999) (Category III). Selection research within 

space flight is severely limited by a lack of job performance data that are available to researchers. This lack of 

performance data is due, in part, to the fact that such a limited number of astronauts is actually selected (around 

340 U.S. astronauts over the life of the program), and that there is so much evolution in job duties and selection 

practices (from Project Mercury to the International Space Station Program). This issue is also related to the 

difficulty in identifying different levels of performance. Quantifying different levels of performance (i.e., 

optimal vs. adequate vs. inadequate) in relation to optimal selection methods or predictors is unrealistic with 

such small sample sizes. In such cases, it is unlikely that there are enough observable variances in performance to accurately quantify levels, and the levels thus quantified cannot be validated. 

These issues are also relevant for other international space agencies, which also suffer from a lack of performance data and small sample sizes. For example, Russian researchers have long collected personality 

data on cosmonauts (Kanas and Manzey, 2008), but the empirical linking of personality factors to specific 

performance levels that are necessary to provide cut-scores or norms for selection still eludes these researchers, 

perhaps because of small samples or inadequate performance data. Typically, space agencies have not provided 

objective performance data on enough astronauts to create a reasonably sized sample on which to perform an 

analysis. This lack of data also obfuscates the ability to identify optimal selection criteria and methods for teams. 

Thus, we do not have a good idea of the specific individual skills and characteristics that would best predict 

successful astronaut teamwork. Future researchers who are evaluating crew selection for space flight will thus 

have to resort to more creative tactics when quantifying performance and validating predictors. For example, 

space agencies should, at a minimum, conduct studies that generalize and validate predictors among samples 

of teams whose work approximates some portion of the work that will be performed by astronauts. 

In the meantime, 50 years of ground-based research on individual selection for work that is performed 

in teams, including small group research that is conducted in analog and/or extreme environments, informs 

astronaut selection for teamwork. Ground-based studies have identified many individual teamwork-related 

skills and characteristics. For new teams, picking individuals who are skilled at training and articulating their 

roles to others, compromising, and helping other team members take on their tasks as well as those who also 

understand effective team processes resulted in better-performing teams than when these individual skills were 

ignored at selection (Jones et al., 2000) (Category III). Individual values also make a difference, as teams that 

consist of members who value being on a team perform better than teams that consist of members who do not 

value being on a team (Bell, 2007; Salas et al., 2005) (Category II and Category III). Members who do not 

value being on the team are less likely to be motivated to learn team skills (Salas et al., 2005) (Category III). 

Evidence suggests that individual characteristics (in addition to individual skills and values) influence performance in a teamwork setting. Researchers who conducted a recent meta-analysis found that, in lab-based team 

studies, team performance was significantly positively related to average team general mental ability and 

average team task-relevant expertise (Bell, 2007) (Category I). 

In the field studies that were considered, the Big Five personality factors (i.e., openness, conscientiousness, 

extroversion, agreeableness, and neuroticism) were also all significantly correlated with team performance 

(Bell, 2007). In a traditional work environment, Barrick et al. (1998) found that a team member who had a 

very low score on conscientiousness (as measured by the NEO PI-R14) impacted team performance by acting 

 

14Refers to revised the NEO (neuroticism, extroversion, and openness to experience) personality inventory. 
Chapter 2 Human Health and Performance Risks of Space Exploration Missions 

52 Risk of Performance Errors Due to Poor Team Cohesion and Performance, Inadequate 

 Selection/Team Composition, Inadequate Training, and Poor Psychosocial Adaptation 

as the “weakest link,” thus constraining team performance (Category II). In assembly and maintenance work 

teams, team averages on three personality factors (i.e., emotional stability, conscientiousness, and agreeableness) 

and general mental ability were positively correlated with supervisor ratings of team effectiveness. Team average general mental ability and two personality factors (i.e., extroversion, emotional stability) were also positively 

related to supervisor ratings of the ability of the team to maintain itself over time (Barrick et al., 1998). Another 

review suggests that in team environments, agreeableness and emotional stability are the personality characteristics that are most strongly associated with job performance (Stewart and Barrick, 2000) (Category III). A 

meta-analysis that was conducted across a range of occupations found that interpersonal facilitation was significantly predicted by three personality factors: conscientiousness, emotional stability, and agreeableness (Hurtz 

and Donovan, 2000) (Category II). All of these studies provide evidence that individual factors, such as personality and general mental ability, help predict the quality of performance in a teamwork setting. (Note that 

although the authors of this chapter reviewed the Russian personality literature, findings from these studies 

were not included in this report due to sample size issues and the fact that the conceptualization of variables 

(e.g., certain personality factors) were not similar, and were thus not comparable.) 

Research on pilots offers further evidence that individual personality factors are relevant to selecting an 

individual who is capable of teamwork. In regards to interpersonal characteristics, a “right stuff” cluster 

that is based on the Personality Characteristics Inventory (PCI) is composed of high levels of expressivity 

(i.e., warmth, sensitivity), and low levels of negative instrumentality (i.e., arrogance/hostility) and verbal 

aggressiveness (i.e., complaining, nagging, passive-aggressive) (Chidester et al., 1991; Gregorich and 

Helmreich, 1990; Musson and Helmreich, 2005). A “wrong stuff” cluster, in regards to interpersonal characteristics, includes high levels of verbal aggressiveness and a low level of positive expressivity; whereas, a 

“no stuff” cluster includes low scores on expressiveness, instrumentality, mastery, etc. The “right stuff” cluster 

pilots were considered more effective by observers in a 1.5-day simulated trip with a crew than were the “low 

stuff” and “no stuff” pilots (Chidester et al., 1990). The results of U.S. Navy research in Antarctica suggest that 

while technical competence is necessary, it is also important to select individuals who exhibit “social compatibility or likeability, emotional control, patience, tolerance of others, self-confidence without egotism, the capacity 

to subordinate routinely one’s own interests to work harmoniously as a member of a team, a sense of humor, 

and the ability to be easily entertained” as well as those who are practical and hard working (Stuster, 1996, 

p. 268) (Category III). 

In summary, evidence suggests that individual factors should be considered when selecting astronauts for 

long-duration missions, but more research within the space flight context must be done to determine those 

factors that are most likely to support optimal performance and minimize errors that are related to astronaut 

teamwork (refer to Table 2-1 for a summary of presented evidence). More research must also be conducted in 

the analog context using arduous environments or simulation chambers that may resemble situations that are 

closer to those that are experienced by astronauts. By using both analog and space flight contexts to conduct 

this research, we may collect sufficient objective performance data so that the selection methods that are 

used may be examined within a team. 

 
Human Health and Performance Risks of Space Exploration Missions Chapter 2 

Risk of Performance Errors Due to Poor Team Cohesion and Performance, Inadequate Selection/Team 

Composition, Inadequate Training, and Poor Psychosocial Adaptation 53

Table 2-1. Summary of Findings Presented for Selection

Source Predictor Outcome Context Evidence 

Type 

Sandal, 1999 Teamwork competencies Improved individual 

performance in teams 

Space 

flight 

Category III 

McFadden et 

al., 1994 

Teamwork competencies Improved individual 

performance in teams 

Groundbased Category III 

Jones et al., 

2000 

Factors: Skilled at training and articulating their 

roles to others, at compromising, and at helping 

other team members as well as at understanding 

effective team processes 

Higher team 

performance 

Groundbased Category III 

Bell, 2007 Average team general mental ability Higher team 

performance 

Groundbased Category I 

Bell, 2007 Big Five personality factors Higher team 

performance 

Groundbased Category I 

Barrick et al., 

1998 

Team average general mental ability, and 

extroversion and emotional stability 

Higher team 

effectiveness 

Groundbased Category II 

Chidester et 

al., 1991 

“Right stuff” personality cluster Increased teamwork 

ability 

Groundbased Category II 

Stuster, 1996 Personality characteristics (e.g., social 

compatibility, emotional control, patience, etc.) 

Increased teamwork 

ability 

Analog Category III 

 Composing Teams to Perform 

The selection process by which individuals are chosen for their good “teamwork” or interpersonal skills 

does not take into account several additional factors that meaningfully impact team performance. For 

example, many researchers suggest that the composition of a team has a major impact on how successful 

that team is likely to be. Kanas et al. (2001), who based their findings on the shuttle/Mir missions, contend 

that composing an interpersonally compatible crew is an important countermeasure for potential psychosocial 

problems. Although selecting a crew for interpersonal compatibleness is preferred, operational constraints 

have severely limited space flight research opportunities. Furthermore, there is no empirical evidence from 

either U.S. space flights or international space flights that indicates how best to compose crews that have 

both the right technical competencies and the right interpersonal mix to achieve optimal performance. 

While literature on selecting individuals for team work abounds, there is little research literature on the 

composition of entire teams (Paletz, 2006). Most ground-based studies deal with teams that are already 

assembled and compare team-level features that are associated with high or low levels of team performance. 

For example, the teams that did not have any members who were particularly low in agreeableness or extroversion (personality factors) were found to be high-performing teams (Allen and West, 2005) (Category II). 

Likewise, high-performing teams had more moderate proportions of members who were more extroverted 

(Barry and Stewart, 1997) (Category II). 

Although little empirical evidence exists that would inform the composition of teams, evidence suggests that 

team composition is a key differentiating factor between high- and low-success teams. One measure of team 

composition is the heterogeneity or diversity of team members. In one study, Harrison et al. (1998) studied 

two types of diversity in teams – surface-level (i.e., gender, age, ethnicity, tenure) and deep-level (attitudes, 

values, beliefs, cultural norms) diversity – and the effects of these two types of diversity on team cohesion. 

Their findings suggest that the effects of surface-level diversity weakens as group members spend more time 

together while the effects of deep-level diversity strengthens. Surface-level diversity includes heterogeneity 

in age, sex, race, and, to a lesser extent, how long the individual has been a part of an organization (i.e., tenure). 
Chapter 2 Human Health and Performance Risks of Space Exploration Missions 

54 Risk of Performance Errors Due to Poor Team Cohesion and Performance, Inadequate 

 Selection/Team Composition, Inadequate Training, and Poor Psychosocial Adaptation 

Heterogeneity, at a deep level, includes differences among members’ attitudes, values, beliefs, and cultural 

norms. Information concerning deep-level factors is communicated through both verbal and nonverbal behavior patterns and is only learned through extended, individualized interaction (Harrison et al., 1998). Attitudinal 

similarity may facilitate communication as well as reduce role conflict as communication on the job increases 

and team members realize that they share similar conceptualizations of their organizations and jobs (Tsui et 

al., 1992). Although we do not know to what extent future Exploration missions will be based on international 

partnerships, it is important to remember that deep-level diversity is associated with differing cultural norms. 

Several studies have reported that deep-level similarity is one of the most important predictors of team 

cohesion (Byrne, 1971; McGrath, 1984) and long-term performance (Edwards et al., 2006; Hirschfeld et al., 

2006). In contrast, studies generally do not find support that surface-level diversity affects long-term performance; rather surface-level diversity affects short-term performance until team members have enough time to get 

to know each other, and the focus shifts away from surface-level differences. For example, Schmidt et al. (2004) 

found that perceptions of leadership effectiveness were significantly related to the general satisfaction of team 

members with their work, performance, and each other; but the authors of the study did not find any evidence 

that diversity in demographic composition variables (i.e., age, gender, tenure) was related to the satisfaction of 

team members (Category III). While some studies indicate that surface-level diversity affects performance 

and decision-making, these studies focus on short-term performance and decisions that require greater creativity 

(e.g. advertising decisions) (Bell, 2007; Harrison et al., 2003). The effects of surface-level diversity dissipate over 

time and are not likely to enhance the ability of a team to avoid “group think” or to continue creative problem 

solving; whereas the effects of deep-level diversity have little impact on short-term performance but become 

more salient the longer that a team exists (Harrison et al., 1998). 

Research in identifying the right “mix” of team members indicates that different kinds of diversity 

have different consequences on team conflict and, in turn, on team performance (Pelled and Xin, 2000). 

An important distinction in team conflict literature is the distinction between interpersonal and task conflict (De 

Dreu and Weingart, 2003). Interpersonal conflict is generally found to be destructive of team performance, 

while task conflict, in moderate amounts, is generally found to promote task performance because team 

members may correct each other’s misperceptions or argue out better alternatives (Pelled et al., 1999; Porter 

and Lilly, 1996). In a review of the literature, Mannix and Neale (2005) conclude that surface-level differences 

(e.g., demographics) negatively impact the short-term performance of teams as these teams initially experience 

more interpersonal conflict, but these differences have less impact on performance the longer that the teams 

are together. Deep-level diversity negatively impacts long-term performance only when teams are not provided 

with the training and incentives to manage interpersonal conflicts. When training and incentives for managing 

diversity are provided, deep-level diversity helps teams to maintain moderate amounts of the positive task conflict that supports team performance. Mannix and Neale (2005) suggest that giving teams ample time in which 

to train together and instructions on how to take advantage of multiple perspectives reduces the odds of interpersonal conflict stemming from either surface or deep-level diversity and increases the ability of teams to 

leverage the task conflict (Category III). Realistically, if future Exploration missions involve international 

partnerships, it may be difficult to schedule sufficient time for crew members to train together and learn to 

leverage their differing cultural norms. Future research should help to determine whether there are other viable 

means of training team members together (e.g., virtual training connections) that might also enable teams to 

take advantage of multiple perspectives and, at the same time, minimize interpersonal conflicts. 

In summary, the relationship between deep-level diversity, conflict, leadership, and team performance 

is of more interest for long-duration missions than for surface-level diversity (refer to Table 2-2 for a summary 

of the evidence). However, the lack of extensive empirical research in these areas demonstrates the little that 
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Risk of Performance Errors Due to Poor Team Cohesion and Performance, Inadequate Selection/Team 

Composition, Inadequate Training, and Poor Psychosocial Adaptation 55

is known about team composition and how the makeup of a crew may impact crew performance. Furthermore, the lack of empirical research conducted in a space flight or similar analog setting also brings into 

question the suitability of applying these findings of team composition to space flight. Thus, a further 

examination of crew composition, as it relates to optimal team performance, must be conducted (when in a 

space or similar analog setting) to help determine what deep-level diversity actually exists among crews, what 

deep-level characteristics impact astronaut performance, and what kinds of operational interventions (e.g., 

composition considering interpersonal compatibility, time spent training together, etc.) and leadership 

behaviors will promote optimal team performance. 

Table 2-2. Summary of Findings Presented for Crew Composition

Source Predictor Outcome Context Evidence 

Type 

Allen and West, 

2005 

Lack of members low in 

agreeableness or extroversion 

Higher-performing teams Groundbased Category II 

Barry and Stewart, 

1997 

High proportion of members 

who were extroverted 

Higher-performing teams Groundbased Category II 

Harrison et al., 1998; 

McGrath, 1984 

Deep-level similarity Increased team cohesion Groundbased Category II 

Edwards et al., 2006 Deep-level similarity Higher long-term performance Groundbased Category II 

Schmidt et al., 2004 Perceptions of leadership 

effectiveness 

Improved general satisfaction of 

team with work, performance, 

and each other 

Groundbased Category III 

 Team skills training for the individual and the collective team 

Long-duration space flights (i.e., flights that are in excess of 3 months), such as ISS missions, are so physically, 

mentally, and emotionally demanding that simply selecting individual crew members who have the “right stuff” is 

insufficient (Flynn, 2005). Training and supporting optimal performance, as well as selecting high performers, is a 

more effective and efficient approach than simply selecting high performers (Holland et al., 2007). Training involves 

imparting knowledge and/or teaching skills to a group of individuals. However, training team skills and supporting 

optimal performance entails more than educating astronauts about the technical aspects of the job. It also requires 

equipping those astronauts with the resources that are needed to maintain their psychological and physical health 

in an ICE environment over an extended period of time. 

Performance levels are also a consideration in relation to training team skills. When considering optimal performance, any training design should be accompanied by an evaluation to determine the standards of optimal, 

adequate, or inadequate performance, and what skills help differentiate expert from novice teams. In this way, 

training can be validated by checking student progression and the performance of teams before and after training. 

It is therefore recommended that team performance standards and levels be documented in the space flight context 

before effective training is designed. To date, this type of information is unavailable to researchers, and acquiring 

such performance data requires a better partnership between research and operations. 

Developing the right kind of training for team skills that will support astronaut performance is further complicated 

by other operational issues. To begin with, it is difficult to get an accurate picture of what knowledge and skills are 

required for successful performance. Not all tasks, or even types of tasks, can be anticipated. On an Exploration 

mission, new tasks may arise suddenly, so team training needs to be broad and flexible enough to support unexpected 

performance requirements. Another operational issue is that space exploration is a relatively new job, and not many 
Chapter 2 Human Health and Performance Risks of Space Exploration Missions 

56 Risk of Performance Errors Due to Poor Team Cohesion and Performance, Inadequate 

 Selection/Team Composition, Inadequate Training, and Poor Psychosocial Adaptation 

individuals have performed it, particularly for long-duration missions (only four individuals have lived and worked 

in space for 1 year). While all experienced astronauts are polled for this information on a regular basis, only a 

limited number of experienced astronauts can describe what kind of training they found useful on the job and 

what kind of training has not been critical to their performance. This situation makes describing successful performance reliably more difficult and evaluating the relationship between training and performance improvement more challenging, especially when considering the team context. 

Astronauts are also required to live and work together. Performance expectations include maintaining a healthy 

psychological and social environment in addition to achieving technical objectives. Astronaut performance is 

largely team dependent. While some tasks are performed independently, many more tasks (e.g. robotics, extravehicular activities (EVAs)) require the simultaneous involvement of both crew members and ground support 

members. Subject matter experts within the various space agencies argue that teamwork skills are critical to accomplishing overall mission objectives safely. The Human Behavior and Performance (HBP) Training Working Group 

at NASA JSC recently articulated the training requirements that are necessary to promote ISS astronaut performance, and teamwork was one of eight primary categories of training requirements. The group recommended that 

ISS crew members complete at least one technical training event as a team (Human Behavior and Performance 

Training Working Group, 2007). Additionally, the NASA Mission Operations Directorate provides teamwork 

training as one of nine primary space flight resource management skills sets that are provided to flight controllers, directors, and crews during mission operations (Mission Operations Directorate, 2007). 

As astronauts perform complex technical tasks that are at the forefront of modern science and human limitations, they currently complete a rigorous technical training curriculum that can span from 2 to 5 years. Adding 

requirements that allow them to practice or perfect skills is a critical concern for schedulers. If, as research suggests, teaching team members to exchange mental models and perceptions concerning performance can reduce 

the amount of time that is required to master a skill (Cannon-Bowers and Salas, 1998b; Edwards et al., 2006) 

(Category II), training team skills results in technical training efficiencies. Accordingly, a meta-analysis of 97 

studies, involving 11 different types of interventions, that was conducted by Guzzo et al. (1985) found that 

training and goal-setting are the most effective organizational interventions that are aimed at increasing 

motivation and individual performance (Category II). 

These findings support the idea that training is one of the best interventions for addressing the psychosocial 

characteristics of teamwork, and, as such, training offers NASA a great chance to promote crew health and 

optimal performance pre-flight, in-flight, and post-flight for long-duration missions. Evidence indicates that two 

facets of training are relevant to team performance: (1) individual training on teamwork and interpersonal skills, 

and (2) time training as a team. 

 Teamwork and Interpersonal Skills for the Individual 

Space flight evidence regarding teamwork and interpersonal skills training is more limited than ground-based 

evidence. Prior to starting joint operations on the Russian space station Mir, NASA mission specialists provided a 

discussion and resource guide that defined effective teamwork and highlighted several individual strategies for 

ensuring team performance for the U.S. astronauts who were preparing for those long-duration operations 

(Galarza et al., 1999), thus implying that training teamwork skills was at least operationally relevant to 

long-duration missions. 

Many training efforts in industry and in the military focus on developing the interpersonal skills of 

group members to enhance team performance. Arthur et al. (2003) classify studies in terms of three learning 

objectives: cognitive, interpersonal, and psychomotor skills. Four different training criteria were also identified: 
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Risk of Performance Errors Due to Poor Team Cohesion and Performance, Inadequate Selection/Team 

Composition, Inadequate Training, and Poor Psychosocial Adaptation 57

reaction (self-report), learning (test performance, usually pencil and paper), behavior (on-the-job 

performance, supervisor ratings, or objective measures), and results (company-category productivity, profits, 

or return-on-investment). These researchers concluded that cognitive and interpersonal skills training have 

the largest positive effects on behavioral criteria. This indicates that interpersonal skills training specifically 

benefits job performance (Category II). Bradley et al. (2003) conclude that interpersonal skills training also 

contributes to good supervisor ratings of team performance in ongoing teams for both short- and longduration tasks, and for short-term teams that are engaged in long-duration tasks (Category II). The 

interpersonal skills that contributed to performance include: role clarification, goal setting, identifying work priorities, group problem solving, team coordination, interpersonal relations and understanding, consensus building, 

and conflict management. Dependent measures that showed improvements included: cohesion, personal 

growth, motivation, team performance, work efficiency, and job satisfaction. It may therefore be suggested that 

interpersonal skills training relates positively to team performance. 

Baker et al. (2006) investigated the impact of training teamwork skills on surgical team performance and 

errors; they found that the training significantly improved patient mortality rates and reduced the amount of 

surgical errors (Category II). Powell and Hill (2006) noted reductions in adverse patient outcomes, medical 

errors, nursing attrition, and conflicts after crew resource management (a form of teamwork and psychosocial 

skills training) was implemented in health care arenas (Category III). In a review of the factors that determine 

the ability of a team to adapt its performance to successfully handle changing conditions, Burke et al. (2006) 

found that training teamwork skills and cross-training team members resulted in the most adaptive teams 

(Category III). 

In a laboratory simulation, researchers found that training that is designed to improve individual communication and interaction skills improves team performance under novel work conditions (Marks et al., 

2000) (Category I). In a similar study that was done with 60 graduate students in assigned teams, SmithJentsch et al. (1996) found that training students how to be appropriately assertive and to speak up about 

team performance issues significantly improved the ability of a team to adjust its performance. Leedom and 

Simon (1995) found that providing United States Air Force (USAF) aviators with standardized, behaviorbased training on teamwork increased team coordination and improved team task performance. 

Other studies suggest that teams that are composed of team members who have more knowledge concerning teamwork perform better than teams that are composed of team members who have less knowledge 

concerning teamwork (Morgeson and DeRue, 2006; Hirschfeld et al., 2006). In a manufacturing organization, 

Morgeson and DeRue (2006) observed that individual knowledge concerning teamwork helped to predict 

team performance. In a field study of 92 teams (1,158 team members) in a USAF officer development 

program, Hirschfield et al. (2006) found that team member mastery of teamwork knowledge predicted better 

team task proficiency and higher observer ratings of effective teamwork. 

Outside of the field and laboratory setting, however, we find little empirical evidence that relates interpersonal skills to the individual in a space flight or an analog setting. Nevertheless, the overall conclusion 

of the evidence that has been presented suggests that teamwork and interpersonal skills training promote team 

performance. Research must still help to determine the best kinds of interpersonal and teamwork skills training 

as well as the best implementation means for supporting optimal team (i.e., the whole mission team, including 

flight crew and ground control) performance prior to, during, and after long-duration missions. 

Furthermore, research must be conducted in analog and/or extreme environments and space flight contexts to 

examine interpersonal and teamwork skills training so that these findings may be extended to space flight. 
Chapter 2 Human Health and Performance Risks of Space Exploration Missions 

58 Risk of Performance Errors Due to Poor Team Cohesion and Performance, Inadequate 

 Selection/Team Composition, Inadequate Training, and Poor Psychosocial Adaptation 

 Training Team Skills to the Collective Team 

Space flight evidence regarding the effectiveness of team training in promoting team performance consists largely of professional opinion and anecdotal stories advocating the importance of team building for 

astronauts and ground support (Category III and Category IV). Nicholas (1989) argues that some problems 

that are encountered by crews can only be settled by training the crew as a whole in interpersonal, emotionalsupport, and group-interaction skills (Category IV). The authors of a 1998 National Academy of Science report 

on behavioral issues advise that crews and ground support personnel be trained together on interactive techniques prior to flight (National Research Council, 1998) (Category IV). Over the last 3 years, several space 

shuttle crews have specifically opted to complete ISS Expedition interpersonal training as a team to enhance 

their “cohesion and performance” (in personal communication, Shultz, 2007) (Category III). 

Ground-based research supports the idea that employees who are interacting in stressful environments, 

with high workloads, or in environments that require coordination at a distance (similar to the manner in 

which ground support and flight crews operate together) need team training (Harrison et al., 2003; Ilgen et al., 

2005) (Category III). In a study of 27 manufacturing teams (263 individuals) who had worked together for an 

average of 1.9 years, Austin (2003) found that team performance depended on how well individual team members 

could describe what knowledge resources the team possessed, and how those knowledge resources could be 

applied to new situations. 

This finding supports the notion that giving team members an opportunity to learn about each other’s taskrelated knowledge and skills supports team performance. Research indicates that more experience working 

together bolsters the performance of a team in a variety of ways, and that team training is one means of ensuring that team members gain some experience working together (Paris et al., 2000). For example, in a study 

of submarine attack crews, Espevik et al. (2006) found that knowledge concerning team members adds to the 

number of hits on target, over and above the contribution from operational skills (Category II). 

In addition, Espevik et al. (2006) found that the more experience crews had working together, the less 

physiological arousal the crew experienced during attack simulations. In a study comparing 83 work dyads, 

Edwards et al. (2006) found that more time spent working and training with their team members made junior 

and minority team members more likely to contribute to the team, and that teams in which individuals contributed more information performed better than teams in which one individual provided larger portions 

of information (Category III). 

More conflicts are generally associated with more stress, increases in errors, and decreases in productivity 

(Alper et al., 2000). In a review of 55 studies, Rasmussen and Jeppesen (2006) noted that every study found 

that the more time team members spent training together, the fewer conflicts and conflict-related performance 

deficiencies the team members experienced (Category III). This seems highly relevant when considering that 

current plans for astronaut teams include reducing the time that is spent training together. Reductions in team 

training will likely increase conflict and related performance decrements as the teams will be less able to create 

interpersonal ties and share mental models. Indeed, in a review of applied findings from the team performance 

training that took place in military settings, Cannon-Bowers and Salas (1998a) conclude that it is important 

for teams to practice complex or off-nominal situations together (Category III). Also, in a review of simulationbased training practices, Salas et al. (2007b) observe that more benefits can be accrued from team performance 

if teams are encouraged to practice complex and emergency simulations together than if team members are 

trained in simulations in random groups. 
Human Health and Performance Risks of Space Exploration Missions Chapter 2 

Risk of Performance Errors Due to Poor Team Cohesion and Performance, Inadequate Selection/Team 

Composition, Inadequate Training, and Poor Psychosocial Adaptation 59

A meta-analysis of 37 work teams found that teams that have densely configured interpersonal ties are more 

committed to staying together and attain more performance goals (Balkundi and Harrison, 2006). The authors 

note that team training is one mechanism whereby team familiarity and the density of interpersonal ties can 

be increased; however, it is important to note that non-work-oriented team training may not be sufficient or 

worthwhile by itself. Studies with geographically distributed teams that compare task-based team training 

with more socially oriented time together indicate that team members who are familiar with one another 

socially, but have little to no experience working together as a team, do not realize the same performance 

benefits as teams that consists of members who are experienced in working together (Espinosa et al., 2007; 

Kirkman et al., 2006) (Category II). 

In so far as team training requires that team members complete a task or objective as a team, it encourages better team performance (see Table 2-3 for a summary of the evidence that is cited). Interpersonal skills 

training that is intended to improve team member interactions and other teamwork skills training also encourages 

better individual and team performance. Although analog and space flight studies are not numerous, the other 

evidence, as reviewed above, indicates that training may be designed to promote flight crew and ground support 

team health and optimal performance. However, research is necessary to determine the most appropriate designs 

for preparing for, enduring, and recovering from long-duration missions. We thus suggest that team training 

is an essential component of achieving optimal performance, and recommend that steps be taken to examine 

team training, both at the individual and the group level, within the space flight context. 

 Cohesion 

Festinger (1950) originally defined group cohesiveness as the strength of members’ motivations to stay in the 

group and cited three primary characteristics: interpersonal attraction, task commitment, and group pride. As 

research accumulated, many attempts have since been made to operationalize and measure cohesion. Studies 

to determine the strength or willingness of individuals to stick together and act as a unit have most consistently 

assessed the level of conflict, degree of interpersonal tensions, facility and quality of communications, collective perceptions of team health and performance of the group, and the extent to which team members share 

perceptions or understandings concerning their operational contexts. 

As researchers at the U.S. Army Research Institute (ARI) note in their recent review of cohesion as a construct, the definition of cohesion is ambiguous; therefore, the means of measuring cohesion is complex. The 

ARI authors conclude that “cohesion can best be conceptualized as a multidimensional construct consisting of 

numerous factors representing interpersonal and task dynamics” (note that this is the definition of cohesion that 

will be referred to in this report) (Grice and Katz, 2005). Despite the inexact, less-than-rigorous understanding 

of cohesion as a construct, the ARI researchers do note that anyone who has worked with or played on a team 

knows what a cohesive team looks like, and most believe that teams that are more cohesive usually perform 

better than less-cohesive teams. 

Research also provides some understanding of what a cohesive team may look like. Members of cohesive teams 

sit closer together, focus more attention on one another, show signs of mutual affection, and display coordinated 

patterns of behavior. Members of cohesive teams who have established a close relationship are more likely to give 

due credit to their partners. In contrast, those who do not have a close relationship within a team are more likely 

to take credit for successes and blame others for failure (Thompson, 1967). It is also important to note that team 

cohesion is distinct from individual morale. Although an individual’s low morale may influence team cohesion 

(and possibly vice versa), it is possible for a team to remain cohesive with low-morale members. 
Chapter 2 Human Health and Performance Risks of Space Exploration Missions 

60 Risk of Performance Errors Due to Poor Team Cohesion and Performance, Inadequate 

 Selection/Team Composition, Inadequate Training, and Poor Psychosocial Adaptation 

Table 2-3. Summary of Findings Presented for Team Skills Training

Source Predictor Outcome Context Evidence 

Type 

Guzzo et al., 

1985 

Training Increasing motivation and individual 

performance 

Groundbased Category II 

Guzzo et al., 

1985 

Goal-setting Increasing motivation and individual 

performance 

Groundbased Category II 

Arthur et al., 

2003 

Cognitive skills 

training 

Improved job performance Groundbased Category II 

Arthur et al., 

2003 

Interpersonal skills 

training 

Improved job performance Groundbased Category II 

Bradley et al., 

2003 

Interpersonal skills 

training (includes goal 

setting, group problem 

solving, team coordination, etc.) 

Good supervisor ratings of team performance Groundbased Category II 

Baker et al., 

2006 

Teamwork skills 

training 

Improved surgical team performance and 

reduced errors 

Groundbased Category II 

Powell and Hill, 

2006 

Teamwork and psychosocial skills training Reductions in adverse patient outcomes, 

errors, etc. 

Groundbased Category III 

Burke et al., 

2006 

Teamwork skills 

training 

More adaptive teams Groundbased Category III 

Marks et al., 

2000 

Communication and 

interaction skills 

training 

Improved team performance Lab 

study 

Category I 

Smith-Jentsch et 

al., 1996 

Team skills training Improved team performance Lab 

study 

Category I 

Morgeson and 

DeRue, 2006 

Knowledge about 

teamwork 

Improved team performance Groundbased Category II 

Espevik et al., 

2006 

Knowledge about team 

members 

Improved team performance Groundbased Category II 

Edwards et al., 

2006 

Time spent working 

and training as a team 

Increased team contribution Groundbased Category III 

Rasmussen and 

Jeppesen, 2006 

Time spent training 

together as a team 

Few conflicts and conflict-related performance deficiencies Groundbased Category III 

Balkundi and 

Harrison, 2006 

Teams with densely 

configured interpersonal ties 

More committed to achieving performance 

goals 

Groundbased Category II 

Espinosa et al., 

2006 

Teams with experience 

working together 

Higher performance Groundbased Category II 

Psychosocial experts within the space flight research community have articulated their concern that interpersonal conflicts and lack of cohesion will impede the abilities of crews to perform tasks accurately, efficiently, or in 

a coordinated manner during long-duration missions (Hackman, 1996; NASA, 1987; Vinograd, 1974) (Category 

IV). Indeed, although prescreening precludes individuals with personality or mood disorders from being selected, 

the likelihood that certain disorders may develop (i.e., poor psychosocial adaptation) due to poor cohesion and/or 

support is a concern that could ultimately decrease performance in space flight crews. 

Space flight evidence regarding cohesion and performance is limited by a paucity of objective team performance data. However, case studies, interviews, and surveys that have been done within the space flight realm 

provide evidence that issues pertaining to cohesion exist and are perceived as threats to effective operations. For 

example, breakdowns in team coordination, resource and informational exchanges, and role conflicts (i.e., common 
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indicators of poor cohesion) were mentioned as contributors to both the Challenger and the Columbia space shuttle 

accidents (Columbia Accident Investigation Board Report, 2003; Launius, 2004) (Category IV). Likewise, interviews and surveys that were conducted with flight controllers reveal that mission teams are commonly concerned with team member coordination and communications, and that interpersonal conflicts and tensions 

exist (Caldwell, 2005; Parke et al., 2005) (Category III). 

We must again turn to other sources of empirical evidence to inform us of this relationship because space 

flight research is lacking in this regard. The bulk of evidence (Category I, Category II, and Category III) that is 

surrounding cohesion and performance comes from non-space domains such as aviation, medicine, the military, 

and space analogs. Some reports have estimated that “crew error” in aviation contributes to 65% to 70% of all 

serious accidents (Lautman, 1987; Sumwalt and Watson, 2001) (Category III). Accident investigations and mishap reports note poor teamwork, communication, coordination, and tactical decision-making as significant causal 

factors in mishap samples (NTSB [National Transportation Safety Board], 1994) (Category III). Team breakdowns 

are repeatedly implicated in accidents (Merket and Bergondy, 2000; Nagel, 1988) (Category III). In medicine, 

research indicates that interpersonal conflicts, miscommunications, failures to communicate, and poor teamwork skills contribute significantly to the rate of medical errors (Baker et al., 2006; McKeon et al., 2006; 

Powell and Hill, 2006) (Category III). 

Four meta-analyses (Category I) that were conducted across industries as well as types of performance teams 

(work, military, sport, educational, project, etc.) provide further ground-based evidence that cohesion is related 

to performance. The authors of the first of these meta-analyses (Evans and Dion, 1991) found a positive correlation between cohesion and individual performance, but their study did not include group performance criterion 

measures. Mullen and Copper (1994), in addressing these limitations in a subsequent meta-analysis, found that 

cohesion positively affects performance. They also found that this relationship was stronger in real (vs. ad hoc) 

teams, in small (vs. large) teams, and in field studies. Mullen and Copper (1994) noted that successful performance also promotes cohesion. Oliver et al. (2000) analyzed 40 years of military research, and noted positive relationships among cohesion and numerous performance outcomes, including individual and group performance, 

behavioral health, job satisfaction, readiness to perform, and absence of discipline problems. In the latest of the 

meta-analyses, Beal et al. (2003) re-analyzed the studies that were included in Mullen and Copper plus additional 

studies and found that, as the work required more collaboration, the cohesion-performance relationship became 

stronger and highly cohesive teams became more likely to perform better than less-cohesive teams. This conclusion coincides with Thompson’s (1967) cumulated field study finding that cohesion facilitates team processes and team coordination among work teams in various industrial settings (Category III). 

In a meta-analysis of 67 ground-based experimental studies, Gully et al. (2002) (Category I) note a significant positive relationship between performance and the generalized beliefs of team members concerning 

the capabilities of their team across different situations. While most of the research on team cohesion and 

performance deals with the positive aspects of team attitudes, several studies investigated level of conflict 

and negative attitudes concerning the team as indicators of cohesion. De Dreu and Weingart (2003) note an 

important distinction is between interpersonal conflict and task conflict; i.e., that defined, interpersonal conflicts 

are about relationship issues, whereas task conflicts are about how to handle tasks. 

Interpersonal conflict is generally found to be destructive to cohesion and, in turn, team performance; whereas 

task conflict can improve task performance. Team members may correct each other’s misperceptions, offer 

alternatives, and argue about how to solve a problem (Jehn and Mennix, 2001) (Category III). Interpersonal 

conflict is thus generally detrimental, as it appears to affect team cohesion. Some level of task-related conflict 

may be desirable, regardless of its affect on cohesion, because conflict can promote optimal performance. In 
Chapter 2 Human Health and Performance Risks of Space Exploration Missions 

62 Risk of Performance Errors Due to Poor Team Cohesion and Performance, Inadequate 

 Selection/Team Composition, Inadequate Training, and Poor Psychosocial Adaptation 

contrast, both aspects of cohesion (i.e., interpersonal and task-related) are generally found to influence performance positively. In a study that was conducted with Canadian military groups, path analysis showed that taskrelated cohesion was positively related to individual job satisfaction, interpersonal cohesion was negatively 

related to reports of psychological distress, and both types of cohesion were positively related to job performance (Ahronson and Cameron, 2007). 

Research that was conducted within Antarctic space analogs also investigated conflict, cohesion, and performance. In one survey of Expeditionary crews conflict that was measured as inter-member hostility was related to 

the poor ratings of member effectiveness that were meted out by supervisors (Vallacher et al., 1974). In one 

Antarctic expedition, scientists reported that team members’ perceptions of status contributed to conflicts and 

reduced perceptions of cohesion (Dutta Roy and Deb, 1999) (Category III). Wood et al. (2005) also collected data 

on human performance in Antarctica over a 10-year period, modeling individual and group effects on adaptation 

to life in this extreme environment using multilevel analyses (Category III). Positive team climate and cohesion 

helped to reduce interpersonal tensions, which, in turn, contributed to work satisfaction (Wood et al., 2005). 

Cohesion studies that were conducted by the military and in the aviation industries have focused more on 

task cohesion and the role of shared mental models (SMMs). SMMs, which refer to implicit agreements in 

team member expectations concerning how things work and what behaviors will result in various conditions, 

are proposed to characterize cohesive work teams (Baker et al., 2006; Edwards et al., 2006; Hirschfeld et al., 

2006). Studies that compare performance during simulated operations and training note that members of highperforming teams coordinate with one another frequently to establish, maintain, and adapt SMMs as the situation 

evolves (Edwards et al., 2006; Espevik et al., 2006; Wech, 2002) (Category II). Teams that have little to no training on developing or coordinating SMMs demonstrate more errors and are less productive as compared to teams 

that have received training on building SMMs (Edwards et al., 2006; Espevik et al., 2006; Hirschfeld et al., 

2006) (Category II and Category III). 

The authors of the studies that manipulate the stressors that flight simulation crews face have found that 

cohesive teams enhance their performance under stress by shifting from using more time-consuming, explicit 

coordination strategies to more streamlined, implicit coordination strategies to share mental models and information (Bowers et al., 2002; Driskell et al., 1999; Entin and Serfaty, 1999; Serfaty et al., 1998) (Category I and 

Category II). Effective teams share more task-critical information than less-effective teams, especially concerning the problem that is at hand, task goals, and team strategies (Bowers et al., 1998; Helmreich and Sexton, 2004; 

Orasanu and Fischer, 1992) (Category II and Category III). Moreover, members of effective teams tended to 

anticipate each other’s needs and to volunteer information and assistance more frequently (Orasanu and 

Fischer, 1992; Serfaty et al., 1993) (Category III). 

Leadership may also play a role in team cohesion. Although a vast amount of research exists concerning 

leadership characteristics and leadership and member interaction, as well as how leadership may relate to performance, many of the findings in this area of research are conflicting. Furthermore, many of the studies are 

conducted at the individual level, and the context in which much of this research has been conducted may not 

generalize to a space flight setting. 

In general, leadership is defined as the ability to influence others toward achieving group goals (Avolio et al., 

2003). Although studies have found evidence that supports a relationship between different types of leadership 

styles and individual performance and morale (Den Hartog et al., 2002; Howell and Avolio, 1993), research that 

examines leadership influence at the team level is more complex and findings are often mixed. However, the findings of one group of researchers who examined team leadership suggest that leaders who are within teams focus 
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on leadership in two primary domains: the task at hand (i.e., helping the team achieve a task-related goal), and 

the development of team members (the interpersonal aspect of team interaction) (Kozlowski et al., 1996). Their 

findings provide compelling evidence that leaders impact team cognition, motivation/affect, and team behavior 

within the team setting. This evidence makes the argument for the importance of team leadership research compelling. We therefore recommend further examination of team leadership in the context of a space flight or an 

analog setting to examine the effects of leadership behavior and team cohesion in relation to the effects on 

team performance. 

In summary, space flight evidence indicates that cohesion is a relevant concern for long-duration missions 

(see Table 2-4 for a summary of the evidence presented). For example, the delays in communicating with 

ground team members that are inherent in long-duration flight are likely to impact two key factors of team 

cohesiveness: the quality of communication and the quality of leader support. However, we must turn to research outside of space flight to provide insight as to the connection between cohesion and performance. 

Table 2-4. Summary of Findings Presented for Cohesion

Source Predictor Outcome Context Evidence Type 

Thompson, 2002 Cohesive team Give due credit to 

members of team 

Groundbased Category II 

Hackman, 1996 Lack of cohesion Poor performance Groundbased Category IV 

Merket and 

Bergondy, 2000 

Lack of cohesion (team breakdowns) Increased accident 

frequency 

Groundbased Category III 

Baker et al., 2006 Lack of cohesion (interpersonal 

conflict, miscommunication, etc.) 

Increased medical error Groundbased Category III 

Mullen and Cooper, 

1994 

High cohesion (stronger for real 

teams) 

Increased performance Groundbased Category I 

Oliver et al., 2000 High cohesion High individual and group 

performance, behavioral 

health, and job satisfaction 

Groundbased Category I 

Thompson, 2002 High cohesion Increased team 

coordination 

Groundbased Category III 

Ahronson and 

Cameron, 2007 

High interpersonal cohesion Decreased psychological 

distress 

Groundbased Category II 

Edwards et al., 2006 SMMs Increased productivity Groundbased Category II and 

Category III 

Bowers et al., 2002; 

Driskell et al., 1999 

Implicit coordination strategies More effective teams 

(more cohesive) 

Groundbased Category I and 

Category II 

A large body of ground-based evidence shows that cohesion influences levels of performance, but this evidence is primarily correlational rather than causal. Cohesive teams are more productive than are less cohesive 

teams, and this situation could be because (1) more productive teams become more cohesive, or (2) more cohesive teams become more productive. Teams preserve their cohesion when they succeed rather than when they 

fail. Therefore, applied scientists advise that it is important to promote three essential conditions for team performance: ability (i.e., knowledge and skills), motivation, and coordination strategy. Team members need to have sufficient levels of interpersonal and technical skills to perform their jobs at the same time at which they are attaining 

team objectives. Team members must also be motivated to use their knowledge and skills to achieve shared goals. 

Team context, which consists of organizational context, team design, and team culture, must create conditions 
Chapter 2 Human Health and Performance Risks of Space Exploration Missions 

64 Risk of Performance Errors Due to Poor Team Cohesion and Performance, Inadequate 

 Selection/Team Composition, Inadequate Training, and Poor Psychosocial Adaptation 

to avoid problems such as social loafing, free riding, or diffusion of responsibility. These kinds of problems 

undermine team performance and can have detrimental effects on team cohesion (Thompson, 2002). 

From the evidence, it cannot be said that a lack of team cohesion is statistically likely to result in numerous 

performance errors or an observable failure, but it does seem likely that ignoring the relationship between cohesion and performance will result in suboptimal performance (Grice and Katz, 2005). Although we know that 

many factors contribute to how cohesion is built and encouraged within a team and that cohesion is positively 

related to better performance, research cannot effectively determine, in a reasonable amount of time, what minimum level of cohesion is required to avoid catastrophic failure. Instead of investing research and time in such 

an endeavor, funding would be better used to test and identify effective means of building cohesion and promoting optimal performance in a long-duration mission context. This kind of research would generate enough 

immediate intellectual and operational benefits to justify the investment of funding. 

 Psychosocial adaptation 

Long-duration space flight is a unique environment with unique conditions. On one hand, research suggests 

that it may offer salutogenic conditions, a termed that was coined by Antonovsky (1987) to convey the idea that, 

under certain conditions, stress could actually be beneficial and health promoting (Palinkas, 2003) (Category III). 

Indeed, space flight offers the thrill of doing what few people have done before and the challenges of discovery; 

these conditions foster the personal growth of individuals (Suedfeld and Steel, 2002) (Category III). Yet stressful 

conditions are also inherent to long-duration missions. Working in space involves danger, isolation, and confinement; therefore, space is understood to be an extreme work environment. Survival in space requires the provision 

of constant shelter or the wearing of protective gear, and it is also subject to equipment malfunctions. Crew members must adapt to a certain level of danger or threat to survive. They must also adapt to certain levels of isolation as contact with others (i.e., outside of the immediate crew) may be very limited and inconsistent at times, 

and isolation from family and friends may create social rifts and isolation that persist post-flight. Finally, space 

flight crew members must adapt to being confined to a limited living and working space. Ground-based research 

involving similar conditions (e.g., submarines, offshore oil rigs, polar stations) has found that such conditions 

are generally detrimental to psychological health and social well-being over prolonged periods (Braun and Sells, 

1962; Britt and Bliese, 2003; Krueger, 2001; NASA, 1987). The exact mechanics are not well understood, but 

ground-based evidence suggests that social isolation is detrimental to individual health. Epidemiologists have 

noted higher mortality rates among socially isolated patients (House, 2001) (Category III), and physicians have 

described more issues with depression and somatic illnesses in conjunction with longer periods of relative social 

isolation among Antarctic expeditioners (Lugg, 1977; Lugg, 2005) (Category III). 

Finally, long-duration missions may require crews and ground operations to operate more or less autonomously over the course of a mission as the degree of crew isolation oscillates in accordance with the distance 

that the spacecraft travels from the Earth. Crews are likely to have some periods of great control as well as some 

periods of very little control over what tasks are done, how the tasks are done, and when they are done. Ground 

operations are likely to necessitate total control at certain points in the mission, and have no opportunity to exercise any control during other parts of the mission. Shifts in operational autonomy are expected to impact 

psychosocial adaptation to space flight demands (Kanas and Manzey, 2008). 

Researchers often conceptualize autonomy in relation to the job controls and demands that are found within 

a work environment (Theorell and Karasek, 1996). Ground-based evidence suggests that when job demands or 

personal risks are high and individual perceptions of control are low, health and performance suffer (MacDonald 

et al., 2001) (Category II). Furthermore, ground-based evidence suggests that under high-demand and low-control 

conditions, clarity in team member roles reduces the likelihood of individual strain and helps to ensure team co-
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ordination and performance (Bliese and Castro, 2000; Schaubroeck and Fink, 1998). Other contextual factors 

also play an influential role. Specifically, ground-based research has demonstrated that high social support and 

strong communication among team members may decrease the impact of individual strain, thereby once again 

buffering any negative effects on team effectiveness and performance (Guzzo and Dickson, 1996; Theorell 

and Karasek, 1996). 

Given all of the conditions and factors just described, the definitive point for research is that psychosocial 

adaptation is a multilevel construct that includes team and individual adaptation to the psychological and social 

demands that are inherent in an extreme environment and in teamwork. It is therefore important to understand 

how these factors (i.e., isolation, physical space, individual and group autonomy, etc.) influence psychosocial 

adaptation among crew members, as these factors ultimately will impact crew performance (Langfred, 2000). 

Suedfeld and Steele (2000) conclude that the objective characteristics of an extreme environment are less 

important than are the subjective perceptions of the environment in regards to performance. In general, individuals who believe that they are well adjusted perceive fewer physical pains and less mental anguish, and, in turn, 

learn more and are more productive than individuals who believe that they are not well adjusted (Joshi et al., 1998; 

LePine et al., 2004; Mocellin, 1995; Staal, 2004; Williams et al., 1996) (Category III). Likewise, individuals who 

have formed interpersonal networks at work have more access to critical information and resources, and, in turn, 

are able to accomplish more than less socially adapted individuals who have smaller interpersonal networks 

(Balkundi and Harrison, 2006; Burke et al., 2006; Johnson et al., 2003; Schaninger, 2002). The process of psychological and social adjustment to environmental conditions and demands is known as psychosocial adaptation. 

It is important to note, however, that the relationships among psychosocial adaptation, health, learning, productivity, and performance are somewhat reciprocal at both the individual and the team levels (e.g., good health 

improves psychosocial adaptation and learning, satisfaction with learning and team performance improves 

psychosocial adaptation, etc.) (Burke et al., 2006; Buunk et al., 1993; House et al., 2003; Israel et al., 1989; 

Kramer, 1993; Vogt et al., 2008) (Category II and Category III). 

The successful completion of technical objectives is not enough to consider an overall long-duration mission 

successful. The crew must also return home safely with psychological health intact; we are thus concerned with 

helping individuals and teams adapt quickly and effectively to long-duration space flight. Observations indicate 

that (1) individual factors help predict who is more likely to adapt effectively to the psychosocial requirements 

of long-duration missions (Gunderson and Nelson, 1963a; Kanas and Manzey, 2003; Lugg, 1977) (Category III), 

and (2) contextual factors help to predict how well individuals and teams may be able to adapt and recover under various conditions (Boyd, 2001; Lugg, 1977; Palinkas, 2003; Palinkas, 1991) (Category III). Focusing on 

these individual and contextual factors will help to identify ways in which to support pre-, in-, and post-flight 

performance and ensure mission success. 

 Predicting Individual Ability to Adapt 

A significant challenge of collecting data in flight is that the data are collected from a small or limited 

number of subjects, and many measures of psychosocial adaptation require a comparatively large amount 

of a subject’s time (e.g., extensive questionnaires on a repeated basis, repeated collection and storage of 

physiological stress data, etc.). The bulk of evidence that is available regarding adaptation to long-duration 

missions thus comes from space analogs, mainly from Antarctic expeditions. Findings from these Antarctic 

studies note that adapting is an individual process. Not all individuals successfully adapt to the psychosocial 

conditions of an isolated, a confined, and an extreme environment such as that in Antarctica; for these individuals, performance and health usually suffer. In an early correlational study comparing expeditionary 

groups, Gunderson and Nelson (1963b) found that a group rated as less effective also reported being more 
Chapter 2 Human Health and Performance Risks of Space Exploration Missions 

66 Risk of Performance Errors Due to Poor Team Cohesion and Performance, Inadequate 

 Selection/Team Composition, Inadequate Training, and Poor Psychosocial Adaptation 

bored, less compatible, less motivated, and less socially balanced than did a higher-performing group (Category 

III). To the extent that these perceptions can be viewed as indicators of adaptation, a better-adapted group 

appears to be a more effective group. 

Regarding individual performance, Palinkas (1987) found no significant differences between group members who wintered-over and members of a control group in terms of long-term performance (Category II). 

Although wintering over (vs. completing a long-duration expedition without winter) does not appear to have 

a lasting effect on performance, poor individual adaptation to work requirements in Antarctica was associated 

with an exaggeration of perceived injustices (Lugg, 1974) (Category III), and a failure to perform well appears 

to affect continued adaptation. As one low performer became a social isolate as the result of his poor performance (Lugg, 1974), this suggests that the adaptation-performance relationship is reciprocal for at least some 

individuals (Category III). 

Crocq et al. (1974) found that age was not correlated with adaptation among Antarctic expeditioners; 

however, some anecdotal evidence suggests that the youngest personnel sometimes have more difficulty 

adapting than the older personnel. Previous medical history and cognitive ability also predict adaptation 

among Antarctic expeditioners (Lugg, 1974). Crocq et al. (1974) also found that high cognitive ability has a 

positive relationship with adjustment. Low cognitive ability, however, does not necessarily indicate a correspondingly poor ability to adapt. The various personality characteristics of individual Antarctic station members and attitudes that they hold were found to predict adaptation. Individuals who were low in extroversion 

and assertiveness adapt better to life in Antarctica (Rosnet et al., 2000). As noted previously, however, groundbased evidence indicates that teams with more moderately extroverted members generally perform better 

(Allen and West, 2005; Barry and Stewart, 1997). Research must still determine how to balance individual 

extroversion at levels that are encouraging to both psychosocial adaptation and team performance. In fact, 

many characteristics influence adaptation, and several are likely to call for balancing within teams that are 

performing in extreme environments. As Gunderson (1966b) noted: “achievement needs, needs for activity, 

needs for social relationships and affection, aesthetic needs, needs for dominance or leadership, a sense of 

usefulness in one’s job, and control of aggressive impulses to be particularly important for adjustment 

in small Antarctic groups (those groups with less than 5 persons)” (p. 4). 

Generalizing the results that were found in Antarctica to those from space flight require caution. Firstly, 

any generalizations of Antarctic findings to space require the differences between the two environments to 

be taken into account. Group size, for example, is larger in Antarctica than it is on space flights. Given that 

group size has been seen to affect aspects of life in Antarctica, the degree to which Antarctic findings involving groups can be generalized to space might be limited. Secondly, any conclusions that are made regarding 

factors affecting performance in Antarctica are based on relatively few articles. 

Ground-studies that were conducted in traditional work environments regarding psychosocial adaptation 

and performance offer a broader base of evidence and some insight into the general principles of psychosocial 

adaptation to work; however, the utility of these findings are limited by the critical fact that most employees, 

unlike long-duration mission participants, do not live exactly where they work. Ground-based studies support 

the conclusion that some individual factors predict an individual’s ability to adapt. Gender may even play a 

role; the Vogt et al. (2008) study of stress reactions and hardiness among U.S. Marine recruits reveals that 

social support significantly bolsters the hardiness of women recruits after stress, but not that of male recruits. 

Caldwell et al. (2005) found that a small group of pilots and a control group of non-pilots who exhibited more 

cortical activity were less vulnerable to cognitive performance decrements and emotional distress related to 

36-hour sleep decrements. Additionally, LePine et al. (2004) found that selecting adult learners who had a 
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positive attitude toward a complex training program reduced resulting reports of fatigue and exhaustion 

(Category II). Independent of any particular stressor or stressful environments, Greenberg et al. (1992) 

observed that individuals who have more self-esteem generally experience less anxiety under the same 

or similar conditions as individuals who have less self-esteem (Category II). 

The existing evidence provides a starting point, but more focused research is needed to address the gaps 

in our knowledge. Achieving a better understanding of the individual factors influencing an individual’s 

ability to adapt to long-duration space missions would generate at least two operational benefits: (1) individual factors that predict adaptability could be used to aid selection or assignment decisions, and (2) these 

individual factors could be used to customize psychosocial support and resources to fit individual and team 

needs pre-flight, in-flight, and post-flight for long-duration missions. 

 Contextual Factors Influencing Adaptation 

Factors outside of the individual (e.g., duration of stressful conditions, coping resources available) can also 

help to predict individual adaptation. For example, a slow voyage to Antarctica and living and working in a 

larger station once in Antarctica predicts adjustment (Lugg, 1974) (Category III). Composition of the group 

and job skills of group members also predict adapting to the new environment (Lugg, 1974). Contextual 

factors influence adaptation by contributing to an individual’s stress perceptions. 

Stress is the disruption of homeostasis through physical or psychological stimuli that are known as stresssors. 

According to the Merriam-Webster Dictionary® (2007), stress is defined as “a physical, chemical, or emotional 

factor that causes bodily or mental tension and may be a factor in disease causation.” Some stress is unavoidable, 

such as the stress of competition during a game, and some stress is good, as the inverted-U of the performanceanxiety relationship demonstrates (Abramis, 1994). However, some stressors are so acute that even small 

amounts cause serious performance decrements (Abramis, 1994) (Category II), and chronic (long-term) stress 

or many acute stressors lead to strain or burnout (Barnett et al., 2007; Freedy and Hobfoll, 1994; Hobfoll et al., 

2001; van Gelderen et al., 2007) (Category II and Category III). Adler and Dolan (2006), for example, found 

that longer peacekeeping mission deployments for 3,339 military personnel were associated with increased 

reports of depression and post-traumatic stress syndrome (Category III). This indicates that there may be a 

limit to how long an individual can adapt to a particular environment or related stressors. From a space flight 

perspective, the Russian space station Mir operations indicate that astronauts and cosmonauts are capable of 

adapting to 6 months in orbit, but reports also indicate that many Mir participants who took part in longerduration flights (in excess of 6 months) developed symptoms of fatigue, irritability, and minor disorders 

of attention and memory (Boyd, 2001; Kanas et al., 2001) (Category III). 

There are individual differences in perceptions of and adaptations to particular stressors, and many 

different potential stressors are inherent in a long-duration mission. Two typical stressors (isolation and 

confinement) have already been discussed. More research is needed, however, particularly research involving 

ISS astronauts, to determine what stressors are most salient to crews and ground support during long-duration 

missions and how these stressors persistently affect team members post-flight. Research is also needed to 

determine what coping mechanisms and contextual factors best support psychosocial adaptation within the 

operational constraints of long-duration missions and when (i.e., pre-flight, in-flight, post-flight) they are 

likely to be most effective. 

It is known, from extensive ground-based evidence, that social support improves adaptation to, resilience 

to, and recovery from various stressors in traditional and military work environments; and that the more 

social support provided before, during, and after work from more sources (e.g., family, friends, supervisors), 
Chapter 2 Human Health and Performance Risks of Space Exploration Missions 

68 Risk of Performance Errors Due to Poor Team Cohesion and Performance, Inadequate 

 Selection/Team Composition, Inadequate Training, and Poor Psychosocial Adaptation 

the better individuals cope in general (Anderson, 2003; Riggio et al., 1993; Seers et al., 1983) (Category II). 

Social support has traditionally been operationalized as any assistance that individuals receive from others 

through interpersonal interactions, including information, emotional care, or instrumental resources (Buunk et 

al., 1993b; Riggio et al. 1993). Individuals who receive less social support are more likely to commit suicide, 

have accidents, incur injuries, or develop illnesses over their life span than individuals who have more social 

support available to them (Buunk et al., 1993a; House et al., 2003; Israel et al., 1989; LaRocco et al., 1980; 

Nowack, 1991) (Category II and Category III). Ground-based research also indicates that social support plays a 

positive role in team functioning and performance, individual achievement, and employee safety (Bhanthumnavin, 

2003; Buunk et al., 1993a; Buunk et al., 1993b; Heaney et al., 1995; Hearns and Deeny, 2007; Nowack, 1991; 

Schaubroeck and Fink, 1998; Seers et al., 1983; Settoon and Mossholder, 2002) (Category II, Category III, and 

Category IV). There is thus ample reason to consider social support as an important contextual factor promoting 

psychosocial adaptation for long-duration missions. Communication lags on longer-duration missions may stress 

the social support system more than previous experiences in space would lead us to expect. Flight operations 

would benefit from pre-identifying practical ways in which to provide and sustain social support systems in a 

long-duration mission context. 

Based on the literature, long-duration missions in extreme environments (Antarctica or space) require mission 

participants to adapt or cope with several inherent emotional stressors (e.g., isolation from family and friends, 

limited communication opportunities, limited stimulation, shifting work demands and control, etc.) (Kanas and 

Manzey, 2003; Mocellin and Suedfeld, 1991; Natani and Shurley, 1947; Nelson, 1962; Palinkas, 1991; Vinograd, 

1974) (Category III and Category IV). The evidence indicates that (1) optimal performance depends on coping 

with these stressors, (2) there is considerable individual variance in how, and how well, people cope, and 

(3) many contextual factors influence how well individuals and teams are able to cope and adapt (see Table 2-5 

for a summary of these findings). On the other hand, there is not much evidence on how contextual factors 

influence an individual’s ability to recover from work in similar environments. The critical point for longduration space flight is to determine the viability and utility of these factors for supporting the psychosocial 

adaptation to training, flight, and recovery of a crew – by doing so, research will identify ways in which to 

reduce the negative health impacts that are related to perceived stress and help to optimize performance 

on long-duration missions. 

 Risk in Context of Exploration Mission Operational Scenarios 

Given that we know selection/composition, training, cohesion, and psychosocial adaptation influence performance, many operationally relevant questions remain for research to address. These include: What mix of crew 

members is likely to perform best? What kind of team skills training and team training will be most useful for 

teams that are living and working together on a long-duration mission? What kinds of resources and support 

will facilitate psychosocial adaptation to a long-duration environment when outside intervention and facilitation 

is severely limited by communication lags? 

 
Human Health and Performance Risks of Space Exploration Missions Chapter 2 

Risk of Performance Errors Due to Poor Team Cohesion and Performance, Inadequate Selection/Team 

Composition, Inadequate Training, and Poor Psychosocial Adaptation 69

Table 2-5. Summary of Findings Presented for Psychosocial Adaptation

Source Predictor Outcome Context Evidence Type 

Braun and Sells, 1962; NASA, 1987 Confinement and 

isolation 

Decreased psychological 

health and social wellbeing 

Groundbased Category III 

House, 2001 Social isolation Increased mortality rates Groundbased Category III 

MacDonald et al., 2001 High job 

demands and low 

personal control 

Decreased performance Groundbased Category II 

Joshi et al., 1988; LePine et al., 2004 Adjustment Performance Groundbased Category III 

Crocq et al., 1974 High cognitive 

ability 

Lower adjustment Groundbased Category III 

Rosnet et al., 2000 Low in extroversion and 

assertiveness 

Higher adjustment/ 

adaptability 

Groundbased Category III 

LePine et al., 2004 Positive affect Increased ability to adapt 

(less fatigue) 

Groundbased Category II 

Greenberg et al., 1992 Self-esteem Less anxiety Groundbased Category II 

Lugg, 1974 Voyage duration Ability to adapt Groundbased Category III 

Lugg, 1974 Composition of 

group and job 

skills of group 

Ability to adapt Groundbased Category III 

Barnet et al., 2007; Hobfoll et al., 2007 Stress Decreased performance Groundbased Category II and 

Category III 

Anderson, 2004; Riggio et al., 1993 Social support Reduces stress Groundbased Category II 

Bhanthumnavin, 2003; Buunk et al., 

1993; Heaney et al., 1995 

Social Support Team functioning, team 

performance, individual 

achievement, and 

employee safety 

Groundbased Category II, 

Category III, 

and Category IV 

As previously detailed in this chapter, ground-based evidence demonstrates that long-duration team composition would be hampered by poor selection, ineffective team composition, inadequate training, and poor 

psychosocial adaptation. A possible qualitative likelihood scale for performance errors during certain mission 

operational scenarios is as follows: 

 Level 1 – will most likely not occur 

 Level 2 – could occur 

 Level 3 – will most likely occur 
Chapter 2 Human Health and Performance Risks of Space Exploration Missions 

70 Risk of Performance Errors Due to Poor Team Cohesion and Performance, Inadequate 

 Selection/Team Composition, Inadequate Training, and Poor Psychosocial Adaptation 

Using this scale, the likelihood of performance errors for each type of mission is displayed in Table 2-6 below. 

Table 2-6. Risk of Context of Exploration Mission Operational Scenarios 

Levels of Risk ISS Six-Person Lunar Sortie Lunar Long Mars 

Level 1 

Level 2 X X 

Level 3 X X 

While crew members often engage in Expeditionary training activities (e.g., National Outdoor Leadership 

School [NOLS]) to promote team cohesion, there is no scientific evidence regarding what type and method 

of training offers the best means of promoting team performance for long-duration missions. As the number 

of crew members that are involved in long-duration missions increases (from three ISS crew members to potentially seven Mars mission crew members), the complexity of crew communications and the likelihood of intercrew conflict increases exponentially. Anecdotal reports indicate that extensive training requirements and scheduling limitations make it difficult to set aside adequate time for crew members to train as a team. Increasing 

crew size and new operating systems (associated with the Constellation project) no doubt will create additional 

difficulties in training crew members as a team. 

Poor cohesion, poor composition, inadequate training, and difficulties adapting will have more pronounced 

consequences during long-term lunar and Mars missions, where there will be fewer resources for mitigating the 

effect of these factors on performance. Prolonged or pronounced exposure to stressors, such as interpersonal conflict, may produce strain among crew members; and strain is associated with negative physiological and mental 

health consequences. These health risks may become compounded by the fact that lunar and Mars missions 

introduce additional restrictions and stressors compared to the mission experiences of astronauts to date. 

Currently, the Spaceflight Human System Standards (Standard 5.2.3) states that training shall be provided 

on the psychosocial phenomena that will be experienced by crews and that additional training regarding crew 

integration and team dynamics may be included. The current standards are also found in the Human Integration 

Design Handbook (HIDH). However, these standards do not define such training or ensure that it will be available to crews prior to taking part in long-duration missions. Given the noted relationship between team composition, team training, cohesion, psychosocial adaptation, and performance, future space flight endeavors would 

benefit from specifying a “Fitness for Duty Standard” as well as “best practices” of psychosocial training and 

support for all crews prior to, during, and after flight. 

 Conclusion 

BHP research provides the knowledge, tools, and technologies that support crew health to prevent or 

mitigate the risk of human performance errors due to poor cohesion and performance, selection/team 

composition, training, and psychosocial adaptation (Team Risk). These efforts are operationally driven, 

consistent with human health and performance standards as outlined in the HIDH, and aligned with major 

Constellation milestones. From this, BHP made a prioritized list of gaps and related activities and deliverables. 

Priorities were determined by considering the operational relevance of each deliverable as well as its role in risk 

reduction and the advancement of countermeasure development in light of crew needs during Exploration 

missions. 
Human Health and Performance Risks of Space Exploration Missions Chapter 2 

Risk of Performance Errors Due to Poor Team Cohesion and Performance, Inadequate Selection/Team 

Composition, Inadequate Training, and Poor Psychosocial Adaptation 71

Veteran astronauts and ground control personnel have expressed the need for training requirements that 

will improve crew cohesion to reduce the likelihood of performance errors that are caused by inconsistent and 

suboptimal team dynamics. Some missions may have been jeopardized and, possibly, terminated as a result of 

interpersonal frictions in the past; therefore, the first priority of BHP insofar as team risk is concerned involves 

reducing the risk of team conflict and developing appropriate countermeasures. To this end, BHP is collaborating 

with the JSC Astronaut Office and flight surgeons to systematically collect information directly from the longduration crew members. BHP is also evaluating conflict management and communication tools for use by crews 

during space flight, and will provide recommendations that are based on the outcome from these research tasks. 

BHP is also collaborating with the HBP International Working Group on an HBP competency model that will ensure adequate team training of astronauts by NASA and international space agencies. These efforts will address 

specific gaps including the following: What are the most likely and serious threats to team cohesion, performance, and crew-ground interaction? What are the most optimal ways in which to compose crews? What are 

the most optimal ways in which to train crews? 

Long-duration missions to remote environments will increase astronaut exposure to extreme isolation and confinement, resulting in higher stress levels and an increased risk of crew morale deterioration. As the methods 

that are used to deal with crew stress could be critical to the success of the mission, the second priority of BHP 

insofar as Team Risk is concerned involves providing unobtrusive monitoring technologies for deteriorated crew 

cohesion, a situation that will ultimately decrease crew performance. The BHP gaps that address this issue are: 

What additional approaches and countermeasures exist to counter these threats? How can we monitor and 

measure these threats? 

Evidence supports the important role of environmental context in influencing team performance. Research 

demonstrates that specific factors can influence both team cohesion and team performance; it is therefore important to examine and implement practices that will ensure optimal performance while considering these issues. 

Therefore, the third priority of BHP insofar as Team Risk is concerned addresses the examination of autonomy 

and communication. The BHP gaps that cover these issues are: How does increased autonomy impact crew 

cohesion, crew performance, and crew-ground interaction? What aspects of communication impact crew 

cohesion, crew performance, and crew-ground interaction? 

In summation, the selection of crew members, team training and building, and the psychosocial adaptation of 

the crew to the mission environment present several opportunities to encourage optimal performance; but more 

research must be done, in the appropriate contexts, to inform mission designers of how to take advantage of 

these opportunities. 

The BHP Element has identified gaps in knowledge and mitigation strategies that are related to these issues. 

To close these gaps, the BHP Element needs to pursue more rigorous, longitudinal research designs and a multimethod research program. Space flight history and data are required to identify the performance objectives that 

are most likely to be influenced by psychosocial team factors, to assess which factors are most salient on the job, 

to develop relevant measures of cohesion and psychosocial adaptation, and to determine the baselines of individual and team performance. Laboratory-based and space analog studies are needed to pilot countermeasures and 

monitoring technologies, and to help identify the safest and most efficient means of manipulating factors to 

optimize performance. 

Finally, high-fidelity space analogs or current space flight studies are needed to test the utility of the tools and 

countermeasures that will be designed to promote optimal performance and support the psychosocial health of 

astronauts who are on long-duration missions. The funding and support of this research is justified by the poten-
Chapter 2 Human Health and Performance Risks of Space Exploration Missions 

72 Risk of Performance Errors Due to Poor Team Cohesion and Performance, Inadequate 

 Selection/Team Composition, Inadequate Training, and Poor Psychosocial Adaptation 

tial benefits of knowing how to promote optimal performance. In essence, the surest way to reduce the risk of 

failure when we are unable to isolate and eliminate potential error sources is to achieve optimal performance. 

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 Acknowledgments 

It is important to acknowledge the contributions that have been made by our BHP community, including 

those of flight surgeons and medical operations, researchers from the NSBRI, our external investigators, and 

many others as noted below. These efforts are critical for understanding and communicating what is known and 

unknown regarding the risks for human space flight, particularly as we embark on Exploration missions to the 

moon and Mars. Such knowledge will enable us to meet these future challenges and succeed. 

 Contributors and reviewers 

Pamela Baskin, B.S.; BHP, Space Medicine Division; NASA Johnson Space Center; Wyle Integrated Science 

and Engineering Group; Houston. 

Joseph Brady, Ph.D.; NSBRI and John Hopkins University, School of Medicine; Baltimore, Md. 

Frank E. Carpenter, M.D.; (Formerly) BHP, Space Medicine Division, NASA Johnson Space Center; Houston. 

David F. Dinges, Ph.D.; NSBRI and University of Pennsylvania School of Medicine, and School of Biomedical 

Engineering, Science and Health Systems, Drexel University, Philadelphia, Pa. 

Edna R. Fiedler, Ph.D.; NSBRI and Baylor College of Medicine, Houston. 
Human Health and Performance Risks of Space Exploration Missions Chapter 2 

Risk of Performance Errors Due to Poor Team Cohesion and Performance, Inadequate Selection/Team 

Composition, Inadequate Training, and Poor Psychosocial Adaptation 83

Albert Holland, Ph.D.; BHP, Space Medicine Division, NASA Johnson Space Center; Houston. 

Judith Orasanu, Ph.D.; NASA Ames Research Center; Moffett Field, Calif. 

Walter Sipes, Ph.D.; BHP, Space Medicine Division, NASA Johnson Space Center; Houston. 

Annette Spychalski, Ph.D.; (Formerly) BHP, Space Medicine Division; NASA Johnson Space Center; Houston. 

Alexandra Whitmire, M.S.; BHP, Space Medicine Division; NASA Johnson Space Center; Houston. 

Barbara Woolford, Ph.D.; Space Human Factors and Habitability (SHFH); HRP, NASA Johnson Space Center; 

Houston. 

 Glossary 

Term Definition 

Cohesion The strength or willingness of individuals to stick together and act as a unit. 

Composition The arrangement or mix of individuals into a group, team, or crew. 

Crew A group of astronauts who are assigned to a mission. 

Diffusion of 

Responsibility 

Phenomenon in which, because of the size of a group, individual responsibility is not assigned 

explicitly. For example, because of the size of the group, individuals allow something to occur that 

they would not allow if they were alone. 

Cut-score Cut-scores are selected points on the score scale of a test. The points are used to determine whether 

a particular test score is sufficient for a specific purpose. 

Free Riding Phenomenon in which an individual who is a part of a group allows others in the group to share his 

or her responsibilities rather than assume those responsibilities as his or her own. 

Group A collection of individuals into one place at one period in time. 

Interpersonal 

Interaction 

A communication exchange (verbal and nonverbal) between two or more individuals. 

Performance The execution of an action. 

Performance Error An act that deviates from an established code or a standard of performance. 

Performance 

Standard 

Specific requirements concerning how an action should be executed. 

Personality A person’s unique set of behavioral or cognitive patterns (usually described using “Big Five” broad 

factors: openness, conscientiousness, extroversion, agreeableness, and neuroticism). 

Psychosocial 

Adaptation 

An individual’s social, mental, and emotional adjustment to the stressors that are inherent in a 

particular environment or state of existence; quality of life as determined by an individual’s 

subjective perception of his/ her situation. 

Selection The choice of one individual for a particular purpose or role. 

Shared Mental 

Model [SMM] 

Shared beliefs among team members concerning how things work and what actions will result in 

various conditions; An organized set of expectations for performance and common understanding 

of the resources that are available among team members. 

Social Loafing Phenomenon in which individuals make less effort to achieve a goal when they work in a group 

than when they work alone. 

Strain A state of injury that is induced by prolonged or pronounced exposure to tension or stress. 

Stress Tension resulting from factors that alter a current or expected state of equilibrium. 

Stressor A stimulus that causes stress. 

Team A collection of individuals who are working cooperatively toward a common goal or common set 

of goals; the collection of individuals who are assigned to support and achieve a particular mission. 
Chapter 2 Human Health and Performance Risks of Space Exploration Missions 

84 Risk of Performance Errors Due to Poor Team Cohesion and Performance, Inadequate 

 Selection/Team Composition, Inadequate Training, and Poor Psychosocial Adaptation 

Term Definition 

Team Skills 

Training 

Educating or teaching an individual concerning the skills and knowledge that are associated with 

effective team performance. 

Team Training Educating or teaching skills to a team as a whole, rather than educating individual team members 

separately. 

Training The act of educating or teaching skills or knowledge; The skills, knowledge, or experience that is 

obtained through instruction or education. 
Risk of Performance Errors Due to Sleep Loss, Circadian Desynchronization, 

Fatigue, and Work Overload 85

Chapter 3: 

Risk of Performance Errors due to Sleep Loss, 

Circadian Desynchronization, Fatigue, 

and Work Overload 

Alexandra M. Whitmire 

Wyle Integrated Science and Engineering Group 

Lauren B. Leveton 

NASA Johnson Space Center 

Laura Barger

Harvard Medical School and Brigham and Women’s Hospital 

George Brainard

Jefferson Medical College, Thomas Jefferson University 

David F. Dinges 

University of Pennsylvania School of Medicine and Drexel University 

Elizabeth Klerman

Brigham and Women’s Hospital 

Camille Shea

Universities Space Research Association 

Fatigue occurs during spaceflight and will jeopardize health and performance. This risk may be influenced by 

artificial and transmitted light exposure, individual vulnerability to sleep loss and circadian dynamics, and 

work/sleep schedules. Efforts are needed to improve sleep hygiene, and to identify and improve conditions that 

interfere with sleep quality. Research areas may include: development of a self-assessment tool for cognitive 

function and fatigue, light therapy for phase shifting, alertness and mood disorders, and other means to improve 

sleep quality and reduce fatigue. – Human Research Program Requirements Document, HRP-47052, Rev. C, 

dated Jan 2009. 

Sleep accommodations on short-duration space 

shuttle flights were Spartan (as shown here), but 

sleep stations on board the International Space Station 

strive to provide a stable, comfortable, dark, and quiet 

environment to encourage the quality and quantity of 

sleep essential to optimize crew performance and 

health. 
86 Risk of Performance Errors Due to Sleep Loss, Circadian Desynchronization, 

Fatigue, and Work Overload 
Human Health and Performance Risks of Space Exploration Missions Chapter 3 

Risk of Performance Errors Due to Sleep Loss, Circadian Desynchronization, 

Fatigue, and Work Overload 87

 Executive Summary 

Data that have been collected during space flight missions consistently indicate that sleep loss, circadian 

desynchronization, fatigue, and work overload occur, to varying degrees, for some individuals. Few studies 

of performance have been conducted in flight, however, and the findings that have been generated remain unclear as to how a crew member’s performance during space flight is directly impacted by sleep loss. Extensive 

ground-based scientific literature, including controlled laboratory studies and data that have been gathered from 

industries, demonstrates that the degree of sleep and circadian disturbances that are often experienced by astronauts result in performance errors and may also impact long-term health. 

Space flight evidence regarding sleep loss primarily includes data that were collected through controlled 

studies (Category II15) as well as through self-report (Category III). These evaluations, which have focused on 

short-duration (fewer than 30-day) missions, have provided data from astronauts’ daily sleep logs, polysomnography, and actigraphy. These data have characterized sleep in space, overall, as shorter, less restful, and more interrupted than sleep on Earth. Circadian rhythms may also be misaligned due to scheduling constraints, with the 

result that fatigue (physical and mental) from work overload has been reported (Scheuring et al., 2007). 

Questions, however, remain regarding the nature of sleep and circadian rhythms on long-duration space flight 

missions. Despite the fact that ISS construction has been under way for 9 years, systematic data collection to 

address this issue has only been undertaken recently. In light of ground-based evidence on sleep-loss-related 

performance effects, it is critical to understand the various factors that exist in the space flight and long-duration 

mission environment, and to identify ways in which sleep and circadian rhythms can be protected for crews who 

are flying on ISS and shuttle missions. NASA ground support personnel, as well as space flight crews, experience 

sleep loss, fatigue, circadian misalignment, and work overload. Ground teams that support robotic missions to 

Mars, as evidenced during the Mars Pathfinder, Spirit, Opportunity, and Phoenix missions, similarly face 

issues of sleep loss and circadian desynchronization. 

As human space flight transitions from LEO (e.g., shuttle, ISS) to Exploration missions to the moon 

and Mars, and as NASA continues to support robotic missions to Mars and beyond, it becomes more important 

to characterize human risk factors accurately and adequately and to identify the ways in which to mitigate this performance risk safely and effectively. The first short-duration lunar missions, which will be similar to the shuttle 

missions, will seem to be fast-paced sprints as compared to the marathon-like races of later, longer lunar outpost 

missions (and ISS increments). Docking will require shifting of schedules for those in flight and for their support 

teams on the ground; the hurried schedule will likely include heavy workloads. Longer lunar missions will pose 

additional challenges to crews, including perpetual non-terrestrial day-night cues, environmental constraints, 

and extended periods of high-intensity workload. As the evidence reveals, crews on short- and long-duration 

lunar missions will need to be well-equipped and prepared for the potential performance and long-term 

health effects of sleep loss and circadian shifting. 

 

15To help characterize the kind of evidence that is provided in each of the risk reports in this book, the authors were encouraged to 

label the evidence that they provided according to the “NASA Categories of Evidence.” 

 Category I data are based on at least one randomized controlled trial. 

 Category II data are based on at least one controlled study without randomization, including cohort, case-controlled or subject

operating as own control. 

 Category III data are non-experimental observations or comparative, correlation and case, or case-series studies. 

 Category IV data are expert committee reports or opinions of respected authorities that are based on clinical experiences, bench 

research, or “first principles.” 
Chapter 3 Human Health and Performance Risks of Space Exploration Missions 

88 Risk of Performance Errors Due to Sleep Loss, Circadian Desynchronization, 

Fatigue, and Work Overload 

 Introduction

Sleep disorders plague a staggering number of individuals. The authors of the 2007 Institute of Medicine (IOM) 

report Sleep Disorders and Sleep Deprivation: An Unmet Public Health Problem state that as many as “60 to 70 

million individuals chronically suffer from a disorder of sleep and wakefulness, hindering daily functioning and 

adversely affecting health and longevity... a wide range of deleterious long-term health consequences are associated with chronic, or cumulative, sleep loss. These consequences include: hypertension, diabetes, obesity, heart 

attack, stroke, and psychiatric disorders such as depression or severe anxiety.” 

In addition to the negative health outcomes that are cited above, another risk that can result from sleep loss is 

an increase in performance errors. Evidence shows that 24 hours without sleep, or less severe but more chronic 

sleep loss, can lead to daytime feelings of fatigue and increase performance errors on a variety of tasks that require attention, memory, cognitive and psychomotor speed, and executive functioning (Harrison and Horne, 1998; 

Durmer and Dinges, 2006; Banks and Dinges, 2007). Research indicates that astronauts, on average, sleep fewer 

than 6 hours per day (Dijk et al., 2001; Barger and Czeisler, 2008). Several authors of Earth-based sleep-doseresponse studies reveal that sleeping 6 hours or fewer per day results in cumulative cognitive performance deficits (Belenky et al., 2003; Van Dongen et al., 2003; Dinges et al., 2005; Mollicone et al., 2008). Moreover, there 

is a disconnect between subjective and objective measures of sleep loss under these conditions; e.g., individuals 

who are suffering from sleep deprivation or fatigue may not be able to accurately gauge their degree of impairment, and, therefore, will not take appropriate countermeasures to mitigate the impacts that can arise from these 

conditions. 

Crews who are on orbit and the ground teams who support them face not only the likelihood of recurrent sleep 

loss but also the risk of circadian desynchronization. Circadian rhythms regulate subjective alertness, cognitive 

functions, and sleep propensity as well as core body temperature, hormone secretion (including melatonin), and 

the nocturnal secretion of growth hormone. A misalignment of circadian rhythms results in disturbed sleep and 

impaired performance and alertness (Ball and Evans, 2001, p.144; Van Dongen and Dinges, 2005). On Earth, shift 

workers often experience circadian misalignment, especially when they are working over night or rotating shifts; 

shift work schedules are associated with increased risk of accidents and injuries (Dinges, 1995; Czeisler et al., 

2005; Barger et al., 2006). Recent evidence suggests that shift work, which includes exposure to light at night, 

suppresses the normal nocturnal production of melatonin by the pineal gland; this suppression over time may 

increase the risk of developing cancer among individuals who are working shifts (Blask et al., 2002; Glickman 

et al., 2002, Blask et al., 2005; Stevens et al., 2007). 

Work overload also poses a risk to the behavioral health of space flight crews. NASA management currently 

sets limits, which are known as “Fitness for Duty Standards,” for the planned number of hours in which astronauts are to complete tasks and events. The planned nominal number of work hours for space crews is 6.5 hours 

per day; it is recommended that crew members not exceed a 48-hour total work week. NASA researchers have 

found that maintaining nominal work hours and workload is especially important during critical operations. The 

NASA definition of a critical overload workload for a space flight crew is 10-hour work days that are undertaken 

for more than 3 days per week, or more than 60 hours per week (NASA STD-3001, Vol. 1). Not only is the duration of the workday important, but so, too, is the intensity of the workloads for space flight crews. Astronauts 

who have taken part in high-tempo missions, from the historic Apollo to the current space shuttle missions, have 

accomplished complex tasks in the most dangerous surroundings while enduring hours of intense concentration. 

Anecdotal reports from veteran astronauts (Scheuring et al., 2007) indicate that at times of high intensity, workload can result in mental and physical fatigue. Field studies from the medical and aviation industries show that 

increased and intense workloads, particularly in conjunction with disturbed sleep and fatigue, can lead to 
Human Health and Performance Risks of Space Exploration Missions Chapter 3 

Risk of Performance Errors Due to Sleep Loss, Circadian Desynchronization, 

Fatigue, and Work Overload 89

significant health issues and performance errors, which, in turn, can cause increased incidents of injuries, 

accidents, or death (Barger et al., 2006; Goode, 2003). 

In light of the negative health and performance consequences that are associated with sleep, fatigue, circadian, 

and workload issues, the duration and quality of sleep among astronauts and ground crews is of concern to the 

designers of current NASA operations and the NASA Constellation Program. The consequences of human system risks for Constellation missions include loss of mission objectives as well as increased health risk during 

the mission or post-flight. Research addressing sleep quality and the circadian system endeavors to minimize 

these risks. 

The NASA HRP BHP Element (http://humanresearch.jsc.nasa.gov/about.asp) aims to further characterize 

the risk of performance errors due to sleep loss, fatigue, circadian desynchronization, and work overload in 

preparation for Exploration missions to the moon and Mars. Operationally relevant monitoring technologies that 

detect sleep quantity and quality, and individualized countermeasures that prevent or mitigate the risk in longduration isolated environments, will equip crews for optimal behavioral health and performance. Focused 

laboratory and ground analog studies as well as space flight studies will provide valuable insights into 

developing these technologies and countermeasures. 

The NASA HRP BHP Element is tasked with managing three risks. These are the risk of: (1) performance 

errors due to sleep loss, circadian desynchronization, fatigue, and work overload; (2) performance errors due 

to poor team cohesion and performance, inadequate selection/team composition, inadequate training, and poor 

psychosocial adaptation; and (3) behavioral and psychiatric conditions. As each of these risks is addressed in a 

separate evidence report chapter, they should not be construed to exist independently of one another but, rather, 

should be evaluated in conjunction with the other. Furthermore, the BHP risks overlap with the risks in other 

HRP Elements and, as such, must also be considered in conjunction with these other risks (see figure 3-1 for 

an example of these possible overlaps). 

The relationships of BHP with the other Elements are further outlined in the HRP IRP, which can be found at 

http://humanresearch.jsc.nasa.gov/about.asp. The nature of the IRP implies that BHP is continually reviewing 

and updating integration points with other Elements. Current research efforts are under way through collaborative efforts with the Exploration Medical Capabilities (ExMC) Element, Human Health and Countermeasures 

(HHC) Element, as well as the SHFH Element. While current research is designed to address identified gaps, it 

will be necessary to update and revise each of the BHP Evidence Reports as the Element gaps are closed and 

new gaps emerge. Such information will also inform the human system risk mitigation and assessment strategy 

of the NASA JSC Space Life Sciences Directorate. 
Chapter 3 Human Health and Performance Risks of Space Exploration Missions 

90 Risk of Performance Errors Due to Sleep Loss, Circadian Desynchronization, 

Fatigue, and Work Overload 

 Figure 3-1. Sample integration within the BHP Element, and with other HRP Elements.

 Evidence

 Ground-based evidence 

Studies, which include laboratory investigations (Category I) and field evaluations (Category II and Category 

III) of population groups that are analogous to astronauts (e.g., medical and aviation personnel), provide compelling evidence that working long shifts for extended periods of time contributes to sleep deprivation and can cause 

performance decrements, health problems, and other detrimental consequences, including accidents, that affect 

both the worker and others. 

 Performance Errors Relative to Sleep Loss and Extended Wakefulness 

A meta-analysis (Category I) that was conducted by Pilcher and Huffcutt (1996) examined data that were 

drawn from 19 research studies to characterize the effects of sleep deprivation on specific types of human 

performance. Motor skills, cognitive skills, and mood were assessed in terms of: partial sleep deprivation 

(also known as sleep restriction), which is defined as fewer than 5 hours of sleep in a 24-hour period for 1 or 

more days; short-term total sleep deprivation (no sleep attained for fewer than 45 hours); and long-term sleep 

deprivation (no sleep attained for a period in excess of 45 hours). These researchers found that sleep-deprived 

subjects performed considerably worse on motor tasks, cognitive tasks, and measures of mood than did nonsleep-deprived subjects. The greatest impact on cognitive performance was seen from multiple days of partial 

sleep deprivation, although short- and long-term sleep deprivation also showed an effect. Meta-analyses of 

sleep deprivation effects in medical residents found deficits in both laboratory tasks and clinical tasks 

(Philibert, 2005). 

The magnitude of the chronic partial sleep loss that has been experienced by astronauts in flight (Barger and 

Czeisler, 2008; Monk et al., 1998; Dijk et al., 2001; Kelly et al., 2005; Gundel et al., 1997; Santy et al., 1988; 

Frost et al., 1976) has been reported to negatively impact cognitive performance in multiple Category I, Category II, and Category III laboratory and field studies (Dinges et al., 1997; Lockley et al., 2004; Landrigan et 
Human Health and Performance Risks of Space Exploration Missions Chapter 3 

Risk of Performance Errors Due to Sleep Loss, Circadian Desynchronization, 

Fatigue, and Work Overload 91

al., 2004; Ayas et al., 2006; Barger et al., 2006). Performance can be affected whether sleep loss is in the form 

of a night of substantially reduced sleep, a night of total sleep deprivation, or a series of less drastic, but more 

chronic, restricted sleep hours. A 1997 study by Dinges et al. revealed that when sleep is restricted to the level 

that is commonly experienced by astronauts (i.e., 4 to 6 hours per day), a “sleep debt” accrues and, in less 

than 1 week, performance deficits during waking hours reach levels of serious impairment. 

Chronic reduction of sleep can impact performance in a manner that is similar to that of total sleep deprivation. A study by Van Dongen et al. (2003), which used 48 subjects, evaluated the specific performance effects 

of chronic sleep restriction in comparison to the effects of 3 nights of total sleep deprivation. Sleep restriction 

conditions included 14 consecutive nights of 8, 6, or 4 hours of sleep opportunity, with actual sleep quantity 

validated by polysomnography recordings. Subjects who were subjected to sleep restriction conditions underwent neurobehavioral assessments every 2 hours during their scheduled wakefulness, while subjects who were 

subjected to the sleep deprivation condition were tested every 2 hours throughout their total 88 hours of sleep 

deprivation. 

The neurobehavioral assessment battery that was used in the Van Dongen et al. (2003) study included the 

psychomotor vigilance task (PVT). The PVT – which determines alertness and the effects of fatigue on cognitive performance (as determined by lapses in response time and accuracy of responses) by measuring the 

speed with which subjects respond to a visual or an auditory stimulus (by pressing a response button) – has 

become a standard laboratory tool for the assessment of sustained performance in a variety of experimental 

conditions (Dorrian et al., 2005). The PVT detects changes in basic neurobehavioral performance that involve 

vigilant attention, response speed, and impulsivity; and it has been extensively validated in ground-based laboratory studies to detect cognitive deficits that are caused by a variety of factors (e.g., restricted sleep, sleep/ 

wake shifts, motion sickness, residual sedation from sleep medications) (Dinges and Powell (1985), Van 

Dongen et al. (2003), Drummond et al. (2005)). The PVT is an optimal tool for repeated use, in contrast to 

some other cognitive measures, as studies have shown no minimal learning effects and aptitude differences 

when using the PVT (Van Dongen et al., 2003; Balkin et al., 2004; Dorian et al., 2003). 

Results from these laboratory studies indicate that multiple consecutive sleep episodes of 4 or 6 hours 

significantly erode performance on the PVT and on measures of working memory, and that performance 

under these two conditions (i.e., 4 or 6 hours) was comparable to the performance that is found under conditions of 1 to 2 days of total sleep deprivation. Surprisingly, by the end of the 14 days of sleep restriction, subjects in the 4- and 6-hour sleep period conditions reported feeling only slightly sleepy. As these reports were 

taken when performance was at its lowest level, this indicates that the subjects may no longer have been aware 

of their performance deficits because of inadequate recovery sleep (Van Dongen et al., 2003) (figure 3-2). 

Subjects who spent 4 hours in bed reached levels of impairment at 6 days and of severe impairment at 

11 days. Subjects who spent 6 hours in bed reached levels of impairment at 7 days. Interestingly, it appears 

that subjects who spent 8 hours in bed approached levels of impairment. Figure 3-3, which is from Belenky et 

al. (2003), however, demonstrates that subjects who spent 9 hours in bed did not approach these levels of 

impairment, indicating that 9 hours in bed may be needed to alleviate the risk of performance errors. 

Similar performance effects resulting from chronically restricted sleep can also be seen in the Category I 

study by Belenky et al. (2003) and in figure 3-3. This study involved 66 subjects who were observed in four 

conditions (i.e., 3, 5, 7, and 9 hours in bed) for 7 days. PVT testing showed severe impairments in reaction 

time under the 3-hour condition, with lapses in responses increasing steadily across the 7 days of sleep re-
Chapter 3 Human Health and Performance Risks of Space Exploration Missions 

92 Risk of Performance Errors Due to Sleep Loss, Circadian Desynchronization, 

Fatigue, and Work Overload 

striction. Subjects who spent 3 hours in bed reached levels of severe impairment at 5 days, while subjects 

who spent 5 hours in bed reached levels of impairment at 4 days. 

 Figure 3-2. Performance lapses for time in bed (TIB) over 14 days of sleep restriction 

 (Van Dongen et al., 2003).

These Category I laboratory studies by Van Dongen et al. (2003) and Belenky et al. (2003) clearly show that 

subjects suffered performance impairments resulting from total sleep deprivation and/or chronic sleep restriction. 

 Figure 3-3. PVT performance lapses for TIB over 7 days sleep restriction (Belenky et al, 2002).
Human Health and Performance Risks of Space Exploration Missions Chapter 3 

Risk of Performance Errors Due to Sleep Loss, Circadian Desynchronization, 

Fatigue, and Work Overload 93

Cognitive impairments are present even after an individual has been awake for approximately 17 hours; in 

fact, recent studies have shown that these decrements are similar to those that result from an elevated blood 

alcohol level. A compelling Category I laboratory study from Williamson and Feyer (2000) used a cross-over 

randomized control design to observe cognitive and motor performance after minor sleep deprivation to performance after alcohol consumption. All subjects participated in both alcohol consumption and sleep deprivation, and the order of testing was counterbalanced so that half of the subjects participated in the alcohol 

consumption part first while the other half participated in the sleep deprivation part first. To avoid carry-over 

effects from one condition to the next, subjects were provided with a night of rest in a motel between each 

condition. 

Results indicate that, on average, performance with a blood alcohol level of 0.05% remained equivalent to 

performance after being awake for 16.9 to 18.6 hours. Performance with a blood alcohol level of 0.1% was 

equivalent to performance after being awake for 17.7 to 19.7 hours, or to restricted sleep of 4 to 5 hours per 

night for 1 week (Czeisler, 2006). Similar studies that compare performance after a time of sleep deprivation 

to performance with elevated blood alcohol levels have confirmed these results (Dawson and Reid, 1997; Arnedt 

et al., 2001). These findings are compelling as the duration of wakefulness (17 hours), which results in decrements that are similar to those that are induced by a 0.05% blood alcohol level, is considered by many to be 

within the range of a “normal” waking “day”; many individuals can recall an incident in which they had to 

waken early in the morning and work all day and into the night. Astronauts, who sleep an average of 6 hours 

per night (Santy et al., 1988; Gundel et al., 1997; Monk et al., 1998; Kelly et al., 2005), may be performing 

critical tasks 17 hours or more after wakening. 

 Performance Errors Relative to Sleep Desynchronization and Work Overload 

Research suggests that circadian desynchronization and work overload may also impair performance. 

Specifically, a controlled laboratory study by Wright et al. (2002) evaluated the relationship between 

circadian rhythms and performance by assessing body temperature, which is regulated by the circadian 

mechanisms of the body. Body temperature is at its highest near the circadian peak and lowest near the 

circadian minimum (this is when the body is driven to sleep). It has long been recognized that a positive 

relationship exists between daily rhythms of body temperature and neurobehavioral performance and 

alertness in humans (Wright et al., 2002). 

The study protocol (Wright et al., 2002) forced circadian desynchronization for 12 consecutive 28-hour 

days; participants were allowed 9.3 hours of scheduled time in bed and 18.7 hours of scheduled wakefulness. 

Performance on validated measures was evaluated every 2 hours, beginning 2 hours after the scheduled wake 

time. The protocol, therefore, assessed performance when the body is normally driven to sleep (which is related 

to the point at which body temperature at its lowest) relative to performance during normal waking hours, and 

allowed for assessment of the effects of body temperature independent of (and associated with) sleep hours and 

time of day. During the circadian peak (when body temperature is high), performance and alertness are high; 

conversely, near the circadian phase of low body temperature, performance and alertness are low. These 

results have been replicated in other forced desynchrony and extended wakefulness laboratory protocols 

(Wyatt et al., 1999). 

Results from these laboratory protocols can be extrapolated to field conditions. Studies in the medical industry, where highly educated and trained individuals (e.g., physicians) are subject to circadian shifting and 

extended work shifts in addition to sleep loss, further demonstrate serious performance errors with populations that are analogous to astronauts. In a two-session, within-subject, Category II experiment that was conducted by Arnedt et al. (2005), the performance of 34 medical interns was observed under four conditions: 
Chapter 3 Human Health and Performance Risks of Space Exploration Missions 

94 Risk of Performance Errors Due to Sleep Loss, Circadian Desynchronization, 

Fatigue, and Work Overload 

after 4 weeks of a light rotation (averaging 44 hours of rotations/week); after 4 weeks of a heavy rotation 

(averaging 80 hours of rotations/week); after 4 weeks of a heavy rotation with a 0.05% blood alcohol level; 

and after 4 weeks of a light rotation with a 0.05% blood alcohol level. 

Performance measures included the PVT and a simulated driving task. Findings of the Arnedt et al. (2005) 

experiment indicate that performance impairment after a heavy-call rotation is comparable to the impairment 

that is associated with a combined 0.04% to 0.05% blood alcohol level and a light-call rotation. Results of 

this experiment demonstrate that decrements that are created by extended work shifts are similar to the 

decrements that are created by elevated blood alcohol levels. 

Work hours and sleep loss were shown to impact performance in a Category III evaluation by Rogers et al. 

(2004). A total of 393 registered nurses logged scheduled hours worked, actual hours worked, time of day 

worked, overtime, days off, and sleep/wake patterns. Questions concerning errors and near-errors were also 

included. Analysis showed that work duration, overtime, and number of hours worked per week significantly 

affected the number of errors. The likelihood of making an error increased with longer work hours, and was 

three times higher when the nurses worked shifts lasting 12.5 hours or more. Working overtime increased the 

odds of making at least one error, regardless of the originally scheduled length of the shift. Working more 

than 40 and more than 50 hours per week significantly increased the risk of making an error. 

Similar findings were attained in a subsequent Category III evaluation of 2,737 medical interns (Barger et al., 

2006). A Web-based survey was conducted across the U.S. in which interns completed 17,003 confidential 

monthly reports. These 60-item reports contained information concerning work hours, sleep, and activities 

during the month, number of days off, and the number of extended-duration work shifts (defined as at least 

24 hours of continuous work). These interns were also asked to report whether they had made significant fatiguerelated or non-fatigue-related medical errors. Other questions assessed how often they had nodded off or 

fallen asleep during patient care or educational activities. 

Analysis revealed a significant relationship between the number of extended-duration work shifts and the 

reported rates of fatigue-related noteworthy medical errors. Specifically, the number of reported fatiguerelated medical errors increased as the number of extended-duration shifts per month increased. At least one 

fatigue-related significant medical error was reported in 3.8% of months with no extended-duration work shifts; 

and at least one fatigue-related significant medical error was reported in 9.8% of months that had between one 

and four extended-duration work shifts and in 16% of months that had five or more extended-duration work 

shifts (Barger et al., 2006). Furthermore, the frequency of attentional failures was strongly associated with the 

frequency of extended-duration work shifts. Evidence from this study further corroborates the negative impact that extended-duration work shifts may have on performance, as well as increased accidents and injuries 

(Barger et al., 2006; Ayas et al., 2006). 

Working extended hours or overnight shifts also poses the added difficulty of requiring performance from an 

individual at a time when the body is driven to sleep by the circadian system. Sleep, alertness, and cognitive 

functioning are determined by the interaction of two processes: the endogenous circadian pacemaker and the 

homeostatic drive for sleep (Czeisler et al., 2001). The endogenous circadian pacemaker generates the 24-hour 

circadian rhythm that regulates subjective alertness and sleep propensity as well as core body temperature, cognitive functions, and melatonin secretion, as described above (Czeisler, 2006). It is also highly sensitive to light, 

which is its primary synchronizer. Misalignment of the circadian rhythm results in disturbed sleep, impaired 

performance alertness, waking-hour melatonin secretion, and reduced levels of nocturnal secretion of growth 
Human Health and Performance Risks of Space Exploration Missions Chapter 3 

Risk of Performance Errors Due to Sleep Loss, Circadian Desynchronization, 

Fatigue, and Work Overload 95

hormone (Ball and Evans, 2001). The outcome, therefore, can range from performance errors to long-term 

health decrements. 

Individuals who work at night and attempt to sleep during the day suffer because the timing of their 

sleep/wake schedule remains out of phase with the timing of the environmental light. Night workers are 

particularly prone to vehicle accidents, and their decreased alertness, performance, and vigilance are likely 

to blame for a higher rate of industrial accidents and quality control errors on the job, injuries, and a general 

decline in work productivity rate (Czeisler et al., 2001). Recent information also suggests that as the body 

normally releases melatonin when it is dark, working under artificial light at night suppresses the release of 

melatonin, which may increase the risk of developing cancer (Blask et al., 2002; Glickman et al., 2002, Blask 

et al., 2005; Stevens et al., 2007). 

In summation, ground-based evidence demonstrates that sleep loss, circadian desynchronization, and extended work shifts lead to increased performance errors and accidents. The extent to which these risk factors 

are also present in the space flight environment is therefore an important consideration. 

 Space flight evidence 

 Occurrence of Sleep Loss and Fatigue in Space Flight 

Space flight research indicates that, overall, sleep quantity and quality in astronauts are markedly reduced in 

comparison to terrestrial sleep quantity. Seven Category II and Category III studies, which used polysomnographic measurements, actigraphy, or other measures, have consistently shown that astronauts sleep, on average, 

fewer than 6 hours per day (Table 3-1). This amount of sleep is between 1.5 to 2 hours fewer than the 8 hours 

that are recommended for astronauts per NASA-STD-3001, Vol. 1. 

Table 3-1. Space Flight Sleep Studies Summary and Category of Evidence

Source 

Average 

Hours of 

Sleep 

Missions Subjects 

(N) Measurement Tool Category of Evidence 

Barger and 

Czeisler, preliminary unpublished 

data 

5.9 

STS-104, -109, 

-111, -112, -113, 

-114, -115, -116, 

-118, -120, -121, 

-122, -123, -124 

23 analyzed 

to date Actigraphy II 

Dijk et al., 2001 6.5 STS-90, -95 5 Polysomnogram, 

actigraphy II 

Kelly et al., 2005 6.0 STS-89 4 Sleep logs III 

Monk et al., 1998 6.1 STS-78 4 Sleep physiology II 

Gundel et al., 1997 6.1 Mir 4 Sleep physiology II 

Santy et al., 1988 6.0 Space shuttle 58 Post-flight debriefing III 

Frost et al., 1976 5.8 Skylab 3 Physiology II 

A post-flight debriefing survey that was conducted in 1988 (Category III) found that 58 crew members from 

nine space shuttle missions (ranging in duration from 4 to 9 days) reported sleeping on average 6 hours per 

day while in space compared to 7.9 hours terrestrially (Santy et al., 1988). Sleep was most reduced during the 
Chapter 3 Human Health and Performance Risks of Space Exploration Missions 

96 Risk of Performance Errors Due to Sleep Loss, Circadian Desynchronization, 

Fatigue, and Work Overload 

first and last days of a mission (total 5.6 and 5.7 hours, respectively). Many crew members reported fewer than 

5 hours sleep on some nights, and some crew members slept 2 hours or less (Santy et al., 1988, p. 1096). While 

NASA flight surgeons recommend 8 hours of sleep per day in space, studies on 101 astronauts have found 

that, in space, they sleep an average of approximately 6 hours per day. 

Note that, in the table, the categories of evidence are limited to Category II and Category III. This limitation 

is due to the nature of space flight, which requires that researchers evaluate a small number of subjects, rendering it practically impossible to truly replicate a Category I when astronauts are on orbit. 

Actigraphy and self-reporting are currently measuring to what degree space flight results in disruption of 

sleep during both short-duration (shuttle) and long-duration (ISS) missions (Barger and Czeisler, 2008). This 

study will be the largest and most rigorous of its type. To date, 36 subjects on shuttle missions and six subjects 

on ISS missions have completed the protocol; a total of 20 subjects from ISS missions are planned to take part 

in the study, and shuttle data collection will continue until the ISS goal is achieved and/or the shuttle is retired. 

Data are collected at 90 days before launch for 2 weeks (to establish a baseline), from 11 days before launch 

until launch, in flight (as soon as possible on orbit until the last flight day), and, after landing, for 7 more days. 

Preliminary analysis, using 23 subjects over nine shuttle missions, estimated that the average total nightly 

sleep duration (estimated with actigraphy) was 5.9 hours in flight and 6.9 ± 1.0 hours in the first week after 

flight. Of the 279 nights in flight that were recorded with actigraphy, 52 (18.6%) included fewer than 6 hours 

of sleep. These findings confirm previous studies that show an incidence of reduced sleep quantity in space. 

Further preliminary analysis shows that sleep quantity may be reduced even more prior to undergoing critical mission operations. Evaluations of nine crew members who were performing between one and three EVAs 

each, across five missions, estimate that the average total amount of sleep that the crew members had the night 

before the EVAs was 5.6 ± 1.1 hours. As previously discussed, ground-based studies have consistently 

reported performance impairments under conditions of acute or chronic reduced sleep. 

Objective feedback on sleep quantity is important information to provide to flight surgeons and astronauts 

who are preparing to engage in critical mission activities; this will be particularly true for the more autonomous 

Exploration missions. Currently, actigraphy data for some missions are being shared among the researcher, 

the flight surgeon, and the crew member; the flight surgeons and astronauts, who have commented on the 

benefit of having this information available, support transitioning the Actiwatch (figure 3-4) protocol to an 

operational tool (flight surgeons G Beven and S Johnston, personal communication, 2008). 

A compelling testimony of sleep disturbances in flight is the degree to which sleep medications are used. 

A 1999 Category III study reviewed records from 79 space shuttle missions: of the 219 records that were obtained (each record representing one person on one flight), 94% indicated medication use during flight; and of 

the records that indicated medication use, 45% of them indicated that the medications were taken for sleep 

disturbances and that these were taken consistently for 9 flight days (Putcha et al., 1999). Two examples of 

astronaut sleep facilities on the ISS are provided in figure 3-5 and 3-6. 

 
Human Health and Performance Risks of Space Exploration Missions Chapter 3 

Risk of Performance Errors Due to Sleep Loss, Circadian Desynchronization, 

Fatigue, and Work Overload 97

Recent unpublished data from shuttle missions (Barger and Czeisler, 2008) also show a trend of regular use 

of medication to promote sleep. Of the first 32 crew members studied during 11 missions, 26 (81%) reported 

taking a sleep-promoting medication in flight. Crew members who used sleep medications reported taking them 

on approximately half the nights that data were collected aboard the space shuttle; two doses of sleep medication were taken on 7% of the nights when medication was used. The frequent use of sleep medication in flight 

serves as a strong indication that sleep is disturbed for some crew members. 

Sleep structure (i.e., sleep quality) may also be altered in space. A 1997 study (Gundel et al.), which used 

polysomnography (Category II) to evaluate sleep content, found that latency to the first rapid eye movement 

(REM) episode was shorter, and slow wave sleep (SWS) was redistributed from the first to the second sleep 

cycle. Dijk et al. (2001), who also used polysomnography, found a reduction of SWS during the final third of 

in-flight sleep episodes and post-flight (evaluated at 2, 4, and 5 days post-landing), with an increase in sleep 

duration and the amount of restorative sleep. 

Figure 3-6. Cosmonaut Vladimir Dezhurov of 

Rosaviakosmos, Expedition 3 flight engineer, works 

on a laptop computer in the temporary sleep station in 

the U.S. Laboratory. 

Figure 3-5. With most of his body tucked away in a 

sleeping bag, astronaut Daniel Tani, Expedition 16 

flight engineer, poses for a photograph near two

extravehicular mobility unit spacesuits in the 

Quest Airlock of the ISS. 

Figure 3-4. Image of an Actiwatch activity monitor 

that is shown next to a ruler to demonstrate the size 

of the Actiwatch. 
Chapter 3 Human Health and Performance Risks of Space Exploration Missions 

98 Risk of Performance Errors Due to Sleep Loss, Circadian Desynchronization, 

Fatigue, and Work Overload 

Subjective sleep quality diminished in flight in both the Gundel et al. (1997) and Dijk et al. (2001) studies. 

Studies by Gundel et al. (1997) and Monk et al. (1998) also revealed decreases in SWS and electroencephalogram (EEG) slow wave activity (SWA), reflecting the decrements in the putative restorative component of 

sleep that are known as Process S (Borbély and Achermann, 1999). In contrast, ground-based studies of sleep 

restriction have revealed a rapid increase in EEG SWS and SWA (Brunner et al., 1990). This discrepancy suggests that not only is sleep quantity reduced during space flight, but also that the restorative component of 

sleep may be disrupted in space, which may further increase the likelihood that waking neurobehavioral 

performance deficits will occur (Bonnet et al., 2005). 

 Individual, Physiological, and Environmental Factors that Contribute to 

 Sleep Loss and Fatigue During Space Flight 

Various factors influence the extent to which individuals experience sleep loss and fatigue in space. Differences exist among subjects when experiencing the deleterious effects resulting from inadequate sleep. 

Some may need less sleep and/or be more resistant to the effects of sleep loss on brain functions. Laboratory 

and field studies have found this to be the case for 10% to 30% of individuals when sleep loss is mild to moderate (Van Dongen et al., 2004, 2005b; Caldwell et al., 2005). For the majority of astronauts, however, sleep 

loss and fatigue remain a relevant issue, and self-report of alertness has been shown to be inaccurate under 

conditions of sleep loss (see above), even in motivated and trained individuals. 

The space flight environment affects this risk as well. For instance, recent data indicate that noise levels on 

the ISS, even during sleep periods, can average more than 70 dB, and that the recordings have “maxed out” at 

over 90 dB during scheduled sleep episodes (Goodman, 2003). For comparison, a circular saw creates noise 

levels from 91 to 99 dB. The degree to which noise and environmental disturbances impact sleep during 

space flight missions remains to be determined. 

Recent Category III unpublished data (Barger and Czeisler, 2008) confirm the findings of previous assessments of sleep quantity and quality on orbit. In particular, these findings suggest that the amount and quality 

of in-flight sleep is reduced in comparison to terrestrial sleep behavior for multiple reasons. Data from 23 astronauts who completed 274 sleep logs on nine shuttle flights indicate that in 163 (59%) of these logs, sleep was 

recorded as having been disturbed on the previous night. The most frequent causes of sleep disturbance were 

voids; noise; physical discomfort; other crew member disturbances; and temperature. These physiological and 

environmental factors may interfere with achieving good sleep quality on either the shuttle or the ISS, thereby 

depriving crews of the full restoration afforded by sleep. An evidence-gathering effort is under way by BHP 

researchers to evaluate the impact of these individual, physiological, and environmental factors on sleep and 

fatigue, and to address several BHP gaps concerning the effects of work-rest schedules, environmental 

conditions, and flight rules and requirements on sleep, fatigue, and performance. 

 Occurrence of Circadian Desynchronization in Space Flight 

A recent summary of findings from several short-duration evaluations shows that circadian desynchronization 

can and does affect at least some crew members in space, largely as a result of lighting conditions, scheduling 

constraints, or other aspects of the space flight environment (Mallis and DeRoshia, 2005). 

Limited research is available on circadian rhythms in space. From the studies that have been conducted, there 

are inconsistencies as to the degree of circadian desynchronization experienced in flight (Mallis and DeRoshia, 

2005). As an example, Gundel et al. (1997) assessed the circadian rhythms (using body temperature) of four 

astronauts over a period of 6 to 8 days during their stay on the Russian space station Mir. In comparison to baseline measures, these astronauts displayed a phase delay of more than 2 hours. The phase delay was attributed 
Human Health and Performance Risks of Space Exploration Missions Chapter 3 

Risk of Performance Errors Due to Sleep Loss, Circadian Desynchronization, 

Fatigue, and Work Overload 99

to the alterations of external cues (i.e., reduced light/dark modulation) and possibly delayed bedtimes, as well 

as the fact that the intrinsic period of the circadian pacemaker is longer than 24 hours (Gundel et al., 1997). 

Monk et al. (1998), however, analyzed the circadian rhythms of four astronauts (using body temperature) 

prior to, during, and following a 17-day shuttle mission. From this study, the authors determined that circadian rhythms in orbit appear to be very similar in phase and amplitude to those on the ground. 

Far fewer analyses have been conducted on circadian rhythms over long-duration missions. A case study 

involving an astronaut on a mission to Mir (Monk et al., 2001), revealed that a 24-hour circadian rhythm was 

maintained for about the first 3 months, with disruptions in sleep and a reduced circadian amplitude occurring 

during the last 12 days (Mallis et al., 2004). 

Another case study that was conducted over a 438-day Mir mission revealed delays in circadian rhythms 

(Mallis and DeRoshia, 2005). This and other circadian delays are attributed to a variety of factors including: 

the alterations of external cues, i.e., reduced light/dark modulation (Mallis and DeRoshia, 1995); possibly delayed bedtimes; as well as the fact that the intrinsic period of the circadian pacemaker is longer than 24 hours 

(Gundel et al., 1997. These inconsistencies in circadian desynchronization may also be due to individual differences, as some individuals (as previously mentioned) are more susceptible to sleep loss or the debilitating 

effects of shifted work-rest cycles (Dinges, 2004; Mallis and DeRoshia, 2005). 

 Factors that Contribute to Circadian Desynchronization During Space Flight 

Lighting remains the most significant external cue for altering the phase of the circadian rhythm. Lighting is 

so effective, in fact, that numerous Category I and Category II ground-based laboratory studies have shown 

that timed exposure to specific types of bright light and blue-enriched (short-wavelength) light serves as an 

effective countermeasure for circadian phase-shift and performance deficits due to sleep deprivation (Czeisler 

et al., 1986; Brainard et al., 1988; Czeisler et al., 1989; Brainard et al., 2001; Czeisler et al., 1995; Lockley et 

al., 2003; Brainard and Hanifin, 2005; Cajochen et al., 2005; Gronfier et al., 2007; Lockley, 2007). 

Any natural lighting to which crews are exposed on a spacecraft may impact their circadian adaptation. Note 

that the ISS and docked shuttle orbit the Earth every 1.5 hours, resulting in 16 sunrises and sunsets every 24 

hours, causing the natural lighting cues surrounding the ISS to vary greatly from the terrestrial 24-hour day 

and night cycle. Indeed, astronauts on shuttle and ISS are no longer exposed to the natural 24-hour day and 

night cycle of the Earth but, rather, rely on cues from artificial lighting in addition to those from any of the 

sunrises/sunsets. Thus, the astronauts’ circadian rhythms may be altered by these changes in light exposure. 

Less-than-optimal artificial lighting conditions have been reported on the ISS (Category IV). Station lighting 

is provided by both incandescent and fluorescent light sources. Over time, this lighting has degraded due to 

lamp burnout and the difficulty in supplying replacement lamps on orbit. Over the 9 years of ISS construction, lamps were resupplied piecemeal, with one or two lamps being shipped up by the Soyuz. The resultant 

decline in on-board lighting eventually was addressed by the first major resupply by STS-114 in July 2005. 

As soon as the lamps were delivered to the ISS, however, the re-lamping duty was officially given a relatively 

low priority. Crew members raised this priority significantly, however, because of their desire to improve the 

illumination on board the station (see Appendix 1 for additional details). This was not only to avoid eyestrain 

but because, as artificial lighting can impact circadian rhythms and acute alertness, inadequate lighting contributes to circadian desynchronization and fatigue. 

Slam shifting, which is an acute shift in the sleep/wake schedule to accommodate a docking or critical task in 

flight (Leveton et al., 2006), is another risk factor for circadian desynchronization in the current space flight 
Chapter 3 Human Health and Performance Risks of Space Exploration Missions 

100 Risk of Performance Errors Due to Sleep Loss, Circadian Desynchronization, 

Fatigue, and Work Overload 

environment. Slam shifting can result in sleep loss and fatigue for astronauts (Category III). Recent data from 

the JSC Missions Operations Directorate (MOD) (Korth et al., 2006) reveal that critical operations often require 

slam shifting. In 2,043 days of ISS operations (2000–2006), slam shifts occurred on 13% of these days, typically before and during critical operations (e.g., dockings/undockings, taxi spacecraft relocations, EVAs). 

Such schedule changes force critical mission operations to occur against the body’s natural circadian rhythm 

and after sleep deprivation. 

Slam shifting also affects the ground teams that are supporting the ISS during critical operations when these 

NASA teams often are working overnight. As described previously, people whose employment requires that 

they work overnight shifts must try to remain awake and alert to function well at times when their circadian 

rhythm and homeostatic drive are promoting sleep. Category IV evidence that is derived from flight surgeons 

indicates that crew members have said that “the shifting (circadian) was tougher on them than they thought it 

was going to be” (flight surgeon S Johnston, personal communication, 2007). 

 Occurrence of Work Overload During Space Flight 

Category III evidence reveals work overload occurring during some space flight missions, including those 

of the Skylab and Apollo Programs. The workload during the second Skylab mission steadily increased over 

8 weeks, while crew members of the third Skylab mission reported that they quickly ran into difficulty due to 

work overload. The fast-paced schedule and workload of the mission had initially caused these crew members 

to consistently “feel” behind on tasks as well as demoralized. At the start of the 45th day of their 59-day mission, 

the crew members of Skylab 3 elected to have a sit-down, during which they refused to perform scheduled tasks. 

Mission Control personnel later acknowledged that the schedule had been such that it had not given the crew 

members adequate time in which to adjust to their environment (Cooper Jr., 1996). Category III evidence from 

the Apollo Program also reveals that some of the Apollo crews reported serious mental fatigue while they were 

performing lunar EVAs (Scheuring et al., 2007). Current shuttle missions to ISS are recognized for their 

high-tempo nature as crews perform complex, critical tasks. Of the 22 EVAs that were conducted during 

2007, nine of these dangerous, and critical, endeavors lasted 7 or more hours. 

 Space Flight Performance Errors Due to Sleep Loss, Fatigue, 

 Circadian Desynchronization, and Work Overload 

While evidence indicates that sleep loss, fatigue, circadian desynchronization, and work overload have 

occurred during space flight, it remains unclear whether these factors directly affect the performance of a 

crew in space flight. A limited number of space flight studies have evaluated performance for sleep and 

fatigue effects, and, of those studies, many of them have very few subjects. In the limited studies in which 

performance was shown to be affected, questions remain regarding whether sleep loss and fatigue were the 

root cause. It is also difficult to ascertain causality and relevance to future long-duration missions, when the 

data from these studies are largely derived from short-duration space flight studies (Table 3-2). 

One of the first studies to evaluate cognitive in-flight performance was conducted by Benke et al. in 1993. This 

Category II evaluation assessed the performance of one cosmonaut in several cognitive tasks at three intervals 

during a 6-day mission on Mir. These tasks evaluated response time and accuracy. In-flight performance on 

the tasks was compared with pre- and post-flight performance. No significant decrements resulting from a 

short stay in space were found in this case study. 
Human Health and Performance Risks of Space Exploration Missions Chapter 3 

Risk of Performance Errors Due to Sleep Loss, Circadian Desynchronization, 

Fatigue, and Work Overload 101

Table 3-2. Space Flight Cognitive Performance Studies

Study Year Mission No. Measurement type Effect Type of Effect Mission 

Days 

Manzey and 

Lorenz 1998 Mir 1 

Accuracy and response 

time: four tasks from 

AGARD-STRES 

(GRT, MST, UTT); 

mood and workload 

assessments 

Yes 

Pre-launch decrements 

associated with lowered 

mood scores; decrements 

in tracking performance 

varied in flight, associated 

w/adaptation (i.e., to 

space, and back to Earth) 

438 

Manzey 

et al. 1998 Mir 1 

Accuracy and response 

time: four tasks from 

AGARD-STRES 

(GRT, MS, UTT, DT) 

Yes 

Fine manual control 

decrements (UTT) due to 

adaptation; potential 

decrement in tracking/ 

memory-search during 

DT 

8 

Newman 

and Lathan 1999 STS-42 4 Memory recall task No 4 

Schiflett 

et al. 1996 STS-65, 

STS-78 7 

PAWS (battery of 

performance tests); 

subjective assessments 

of cumulative fatigue 

Yes 

Decrements in memorysearch performance, 

correlated with selfassessment fatigue 

14 

(STS-65)

15 

(STS-78) 

Dijk et al. 2001 STS-90, 

STS-95 

5 

(STS-90) 

1 

(STS-95) 

PVT (calculation, 

recall memory, VAS, 

KSS) 

PVTnot sig. 

Most lapses in flight; 

least lapses post-flight 

16 

(STS-90) 

10 

(STS-95) 

Dijk et al. 2001 STS-90, 

STS-95 

5 

(STS-90) 

1 

(STS-95) 

Self-assessment of 

fatigue Yes Fatigue levels worst in 

flight; best post-flight 

16 

(STS-90) 

10 

(STS-95) 

Note: AGARD=Advisory Group for Aerospace Research and Development (NATO). STRES=simulated training requirements effectiveness 

report. GRT=grammatical reasoning task. MST=Memory Search Task. UTT=Unstable Tracking Task. PAWS=Performance Assessment 

Workstation. VAS=Visual Analog Scale. KSS=Karolinska Sleepiness Scale. DT=dual task. 

Manzey et al. (1998) conducted a similar study over an 8-day mission to Mir; this again was a short-duration 

evaluation using one subject. The study involved administering six pre-flight and six post-flight assessments 

to one subject, with 13 in-flight assessments occurring during the Soyuz approach to Mir (high stress) and also 

during the stay on board Mir. Four tasks were administered: grammatical reasoning, MST, UTT, and a DT that 

consisted of unstable tracking with concurrent memory search. These tasks probe information-processing functions that are known to react sensitively to the adverse effects of environmental stressors or that might become 

impaired by the direct effects of microgravity on sensory motor processes (Kanas and Manzey, 2000). The 

speed and accuracy of short-term memory retrieval and logical reasoning were found to be unimpaired under 

space flight conditions. Decrements, however, were found in fine manual control movements during the UTT. 

DT interference effects on the tracking task and the memory search were also reflected, increasing from the 

beginning to the end of the mission. 

During the experiment, researchers administered questionnaires to evaluate the crew members’ mood, fatigue 

levels, and assessment of workload. Correlations between reported fatigue and decrements that were observed 
Chapter 3 Human Health and Performance Risks of Space Exploration Missions 

102 Risk of Performance Errors Due to Sleep Loss, Circadian Desynchronization, 

Fatigue, and Work Overload 

during the tasks were revealed. As a result, the investigators proposed that the decrements may have been 

caused in part by the effects of accumulated fatigue. 

Newman and Lathan (1999) conducted a Category II experiment on cosmonauts during space flight and did 

not find impairments in a memory-search performance task, although tracking disruptions were apparent. A 

performance monitoring study by Schiflett et al. (1996) included daily assessments of the different mental 

functions of three astronauts during a 13-day shuttle mission. Impairments and decrements were found in 

tracking performance, time-sharing efficiency, and memory-search performance in space. The researchers 

hypothesized that the impairment in memory-search performance in two of the three astronauts was not 

related to microgravity but, rather, was a side effect of decreased alertness and fatigue. 

To further investigate the relationship between sleep and performance on orbit, Dijk et al. (2001) conducted 

an evaluation of the sleep, circadian rhythms, neurobehavioral performance, and light-dark cycles of five astronauts during two space shuttle flights, STS-90 (Neurolab) and STS-95. The researchers assessed neurobehavioral function and performance by administering several different tests, including the 10-minute PVT; a 4-minute, 

two-digit addition task; and a memory task. Subjective assessments of performance and effort were also recorded. 

Analysis of variance revealed that across performance and mood variables, there was a consistent trend toward 

worse performance in flight than was noted before or after flight (Dijk et al. 2001). A detailed analysis of the 

time course of changes involving neurobehavioral measures, which was based on two measures that were derived from the PVT and the probed recall memory test, suggested that most of the study subjects exhibited a 

decline in performance during the last week before launch, a further decline in flight, and a slow recovery postflight. While the effect for the number of lapses in attention on the PVT and for the median reaction time was 

not significant, this lack of effect could be due to the small sample size. 

Although findings were not significant, this continuously declining performance appearing in short-duration 

flight, and the trend of improvement in subjects post-flight correlated with the amount of REM sleep. On return 

to Earth, subjects experienced a marked increase in REM sleep, and their subjective sleep quality and neurobehavioral performance recovered. 

In summation, performance data from space flight thus far reveal some effects on accuracy, response time, 

and recall tasks; however, the quality of the evidence for performance decrements occurring as a result of 

fatigue and sleep loss during space flight remains uncertain. To date, no systematic attempt has been made to 

measure the performance effects of fatigue, sleep loss, circadian desynchronization, and work overload during 

space flight, and it is unknown whether the effect of these factors on performance significantly impacts the completion of mission objectives. More evaluation is therefore needed to accurately characterize this risk in space, 

and to understand how sleep loss, fatigue, circadian desynchronization, and work overload in flight translate 

into performance decrements. Other questions of interest include: Even if performance decrements exist on 

cognitive assessments, do these indeed translate into potential operational errors? And are decrements, when 

they exist, related to sleep, fatigue, circadian, and workload issues, or are they instead related to other aspects 

of the space flight environment? Undoubtedly, thorough evaluation is needed to accurately characterize this 

risk in space. Testing with the 3-minute PVT, which will be conducted on ISS starting in 2009, will include 

a larger number of subjects and test sessions to evaluate cognitive performance over the course of longduration missions. 

As noted previously, ground evidence strongly indicates that sleep loss, fatigue, circadian desynchronization, 

and work overload lead to performance decrements for some individuals. Evidence from space flight clearly 
Human Health and Performance Risks of Space Exploration Missions Chapter 3 

Risk of Performance Errors Due to Sleep Loss, Circadian Desynchronization, 

Fatigue, and Work Overload 103

demonstrates the occurrence of sleep loss, fatigue, and circadian desynchronization on orbit. One could 

therefore conclude that, based on the ground evidence, astronauts do indeed face a realistic risk of performance errors. 

It is essential, however, to accurately characterize the performance effects arising from sleep loss, fatigue, 

circadian desynchronization, and work overload more fully in the space flight environment so that individualized countermeasures can be implemented to prevent or reduce the risk. BHP research activities aim to 

determine the best measures and tools to assess cognitive performance in space and to characterize the effects 

of sleep loss, fatigue, extended work shifts, circadian desynchronization, and work overload on cognitive performance in this environment. 

 Computer-based Simulation Information

As detailed above, astronauts and ground personnel are exposed to many factors that may force their schedules away from the normal 24-hour routine: shift work, extended work hours, timeline changes, slam shifting, 

prolonged light of a lunar day, a Mars sol on Earth, a Mars sol on Mars, and abnormal environmental cues (e.g., 

inadequate or inappropriate light exposure). In addition, their quantity of sleep, particularly during critical mission operations, tends to be reduced due to a variety of operational, environmental, and individual factors. Extensive ground-based evidence demonstrates that reduced sleep increases the risk of performance errors, injuries, and 

accidents. As a result, a validated biomathematical model that instantiates the biological dynamics of sleep need 

and circadian timing could predict astronaut performance relative to fatigue and circadian desynchronization (Dinges, 

2004). Such models could also provide a means by which to optimally schedule targeted countermeasures for 

maintaining astronaut performance. Various biomathematical models that seek to achieve these goals are under 

development (Mallis et al., 2004; Dean et al., 2007; Kronauer et al., 2007). 

Two biomathematical models are discussed here: the Astronaut Scheduling Assistant, and the Circadian, 

Neurobehavioral Performance, and Subjective Alertness Model. Both of these models are based on extensive 

evidence that shows that the temporal dynamics and level of cognitive performance during wakefulness are the 

result of the interaction of sleep homeostatic drive and circadian timing (e.g., Borbély and Achermann, 1999). 

Both models incorporate predictions that are based on countermeasures. These predictions allow for the evaluation of the risk and safety of sleep/wake and work schedules during both the planning and the execution of space 

missions. Prospective studies on the accuracy of these model predictions remain to be done on Earth in conditions that simulate many of the sleep loss and circadian provocations that occur in space flight. Such studies 

are essential and may indicate the need for additional model parameters and changes in model structure. 

The Astronaut Scheduling Assistant software tool, which was developed in 2007 by David Dinges and 

Hans Van Dongen, is based on a validated biomathematical model that relates cognitive performance to the 

neurobiology of sleep and wakefulness and to the biological clock. As previously discussed, studies in recent 

years have documented that the detrimental effects on cognitive performance of chronic sleep loss accumulate 

linearly across consecutive days of sleep restriction below 7 hours per day (Belenky et al., 2003; Van Dongen et 

al., 2003; Molicone et al., 2007; Mollicone et al., 2008). This model therefore takes into account cumulative sleep 

loss and more accurately predicts performance than traditional models (Avinash et al., 2005). For more information, refer to Appendix 2 of this report.

Differential vulnerability to the effects of sleep loss (Van Dongen et al., 2004) and night work (Czeisler et al., 

2005) on performance must also be addressed by biomathematical models of astronaut performance because 
Chapter 3 Human Health and Performance Risks of Space Exploration Missions 

104 Risk of Performance Errors Due to Sleep Loss, Circadian Desynchronization, 

Fatigue, and Work Overload 

recent studies have documented large stable (trait-like) differences among individuals in the degree of cognitive 

deficits that are experienced during sleep loss (Van Dongen et al., 2004; Klerman and Dijk, 2005). Preliminary 

validation of these techniques indicates that as the number of past data points increases, the model increases the 

accuracy with which the trait parameters are estimated, resulting in significant improvements in performance 

prediction accuracy over population average models (figure 3-7) (Van Dongen et al., 2007). 

The second model that was mentioned previously – the Circadian, Neurobehavioral Performance, and 

Subjective Alertness Model – predicts the effects of different light/dark and sleep/wake patterns on the circadian 

biological clock, performance, and alertness. Astronaut performance or alertness for an entire schedule or for a 

mission-critical time can thus be predicted. The model has been validated with data from shifted sleep-wake 

(e.g., jetlag or night work), low-light conditions, intermittent bright-light exposure data, and non-24-hour 

schedules (e.g., Mars), all of which apply to NASA operations. This model has also been used successfully to 

design a pre-flight light exposure regimen that is associated with the early-morning launch times that are often 

necessary for shuttle flights. 

These methods can be used to design a variety of schedules that are relevant to NASA operations, including 

shifting sleep/wake (slam shifting) and non-24-hour schedules. Critically, these methods will be able to satisfy 

the variety of schedules that will be encountered during a Mars mission, where a day is 24 hours and 39 minutes. 

Current work includes quantifying individual differences in response to circadian and sleep/wake factors, and 

incorporating non-light stimuli (e.g., posture and social cues) and information concerning the various wavelengths of light into the model, since the circadian system is responsive to specific wavelengths of light and the 

wavelength distribution that is found in space differs from that found on Earth (both indoors or outdoors). 

This work allows for mathematical simulations that assess the impact of circadian alignment and sleep 

disruption on performance and alertness. 

Figure 3-7. Future performance of three individuals, measured with the 10-minute PVT, during total sleep 

deprivation condition is predicted starting from t = 44h of wakefulness, with mean (thick black line) and 95% 

confidence interval (vertical bars). Individual predictions are based on traits that are identified from prior 

performance measurements up to t = 44h (block dots). The individualized predictions more accurately 

forecast the actual future performance of each individual (gray dots) than does the population average 

prediction (red line).
Human Health and Performance Risks of Space Exploration Missions Chapter 3 

Risk of Performance Errors Due to Sleep Loss, Circadian Desynchronization, 

Fatigue, and Work Overload 105

 Risk in Context of Exploration Mission Operational Scenarios

As previously detailed in this report, space flight evidence shows that astronauts lose sleep during flight, and 

ground-based evidence shows that sleep loss, fatigue, extended work shifts, circadian desynchronization, and 

work overload lead to performance errors, injuries, and accidents. 

A possible qualitative likelihood scale for performance errors during certain mission operational scenarios is 

 Level 1 – will most likely not occur 

 Level 2 – could occur 

 Level 3 – will most likely occur 

Using this scale, the risk of performance errors due to sleep loss, fatigue, circadian desynchronization, 

and work overload is considered a Level 2 risk for ISS, lunar sortie, lunar long, and Mars missions. As 

this section addresses risk in the context of Exploration mission operational scenarios, the Level 2 risk for ISS 

will not be addressed. 

 Lunar sortie 

Early, short-duration lunar missions will be fast-paced “sprints” that are similar in nature to current shuttle 

missions. Representatives from MOD anticipate that crew rotations and schedule shifting will still be required 

during lunar sortie missions, particularly at the beginning and end of a mission when rendezvous between vehicles (the crew exploration vehicle and the lunar lander) will need to occur (S Curtis, personal communication). 

While shifting should not be prevalent for the duration of the lunar sortie stay, crews will be required to shift 

while they are conducting critical mission tasks (S Gibson, personal communication, 2008). 

In addition, the day-night cues on the surface of the moon will be different than the day-night cues on Earth. 

The elevated portions on the rim of Shackleton crater, which is a proposed landing site that is near the South 

Pole of the moon, may be exposed to light as much as 90% of the time (flight surgeon R Scheuring, personal 

communication, 2007). Anecdotal reports of individuals conducting 2- to 3-week exploration missions in the 

Arctic, where light exposure is, as it is on the moon, close to continuous, indicates that exposure to constant 

light may result in an individual being unable to detect a need for sleep and/or rest (flight surgeon R Scheuring, 

personal communication, 2007). If daily EVAs are conducted on the lunar surface, this level of sunlight exposure may stimulate the same physiological response as are experienced during Arctic expeditions. The hightempo operations of multiple EVAs on the lunar surface could lead to work overload, extended wake 

durations, cumulative sleep loss, and excessive fatigue. 

If the landing site is not at the lunar poles, however, but is at more equatorial locations, the day-night cycle 

on the moon involves 2 weeks of light exposure and 2 weeks of darkness. Either way, the natural lighting 

conditions will not be the same as those experienced on Earth due to the 24-hour clock. This means that 

astronauts will not be able to depend on natural lighting cues to help with their circadian rhythms.

Additional factors that are associated with sleep and circadian issues in the current space flight environment – 

e.g., high-tempo workloads and adaptation to the space flight environment – will remain risk factors on lunar 

sortie missions. Subsequently, performance errors remain a plausible risk during the short-duration missions to 

the moon and could occur during the lunar sortie mission scenario. 
Chapter 3 Human Health and Performance Risks of Space Exploration Missions 

106 Risk of Performance Errors Due to Sleep Loss, Circadian Desynchronization, 

Fatigue, and Work Overload 

 Lunar long 

Long-duration lunar missions will be marathon-like events that are similar in nature to the current ISS 

increments. During these missions, both ground and flight crews will experience high-tempo operations and 

shift work. As was noted above, unfamiliar day-night cues could affect the circadian system and the subjective 

need to sleep. As a result, for long-duration lunar missions, it is estimated that human performance errors due to 

sleep loss, fatigue, extended work shifts, circadian desynchronization, and work overload could occur. 

 Mars 

For a Mars mission, this risk remains relevant and important, although certain aspects of the risk may vary 

for the different mission phases. The initial transit to Mars is anticipated to be similar to the ISS long-duration 

experience with regard to sleep loss, extended work durations, and workload. It is anticipated that this transit 

will exclude the slam shifting and high-tempo schedules that are similar to the dockings and critical mission 

activities that were experienced during the building of the ISS. 

On the surface of Mars, work activities may consume a large part of crew time; the slam shifting that can lead to 

circadian desynchronization should be absent from a Mars scenario as the crews will, of necessity, manage their own 

timelines. It is suspected, however, that daylight is not bright on the surface Mars; the sunlight on Mars is about 

one-half of the brightness of that seen on Earth, and the martian sky does not appear blue but pink due to suspended dust, which means that the surface of Mars is, in fact, darker than what is experienced on Earth (Murphy, 

1997). The spectrum of light wavelengths is also different on Mars than on Earth. This difference in light exposure may complicate the entrainment of circadian rhythms, since the circadian system is most sensitive to blue 

wavelengths (Brainard et al., 2001), which are less prevalent on Mars than on Earth (Murphy, 1997). 

Additionally, Mars has a day-night cycle (lasting 24 hours 39 minutes) that differs from that on Earth, which, 

as evidenced by recent ground studies, may pose challenges to performance. Sleep disruption and subjective 

decrements in alertness and performance were reported to be very burdensome to the scientists and engineers at 

the NASA Jet Propulsion Laboratory who lived on a Mars sol schedule while working on the Mars exploration 

rovers (MERs) (Bass et al., 2004; Czeisler et al., 2001). A study by DeRoshia et al. (2007) on self-report findings 

from MER operations personnel showed increased fatigue levels among 82% of the participants, as well as increased levels of sleepiness and irritability. Reduced levels of concentration and energy were also reported by 

most of the participants. The degree to which the physiological challenge of living on the Mars sol can 

threaten the success of a mission is described further in the appendix of the DeRoshia et al. report. 

Subjects who were living on a laboratory-simulated Mars sol schedule experienced sleep disruption and decrements in alertness and performance (Wright et al., 2006; 2001). Most humans cannot adapt to this non-24-hour 

day without adequate countermeasures (Gronfier et al., 2007). Performance and circadian entrainment data have 

just been collected from the Mars Phoenix scout lander (MPSL) mission (May 25 – Sep 1, 2008) ground crew who 

were living on a Mars sol (L Barger, unpublished results, 2008). From these previous studies and a preliminary 

review of the MPSL data, it is expected that future crews who are traveling to Mars and the ground crews who 

will support the Mars missions will experience similar decrements in sleep, circadian alignment, performance, 

and alertness. As a result, for Mars missions, it is estimated that human performance errors that are due to sleep 

loss, fatigue, extended work shifts, circadian desynchronization, and work overload could occur. 
Human Health and Performance Risks of Space Exploration Missions Chapter 3 

Risk of Performance Errors Due to Sleep Loss, Circadian Desynchronization, 

Fatigue, and Work Overload 107

 Implications for future space flight 

The behavioral consequences of performance errors due to sleep loss, circadian desynchronization, extended 

work shifts, fatigue, and work overload on ISS are currently being evaluated. Cognitive decrements that are 

caused by fatigue, inadequate light exposure, circadian dynamics, and work-sleep schedules, will more profoundly affect crews who are on a long-term lunar or Mars mission, where fewer resources will be available to 

mitigate these factors. The risk factors may become compounded by the fact that lunar and Mars missions bring 

additional restrictions. For example, returning to Earth from a lunar mission is not a readily available option, 

and returning to Earth during a Mars mission is not an option at all. 

Currently, NASA STD-3001, Vol. 1 provides standards regarding a normal, uninterrupted sleep period; 

standards for circadian shifting caused by schedule demands; and limits for the amount of work that can be 

performed within 1 day and 1 week. The current standards, however, do not provide specific limits for performance thresholds. BHP anticipates developing normative databases for space flight using tools and measures 

that have been initially tested and verified in laboratories and high-fidelity analogs such as NEEMO [NASA Extreme Environment Mission Operations] and, subsequently, space flight. In mission analogs, astronauts can 

establish individual and group baselines as well as normative data for an environment that can be compared 

with space flight. 

Flight designers and flight surgeons are concerned that crew members, and especially ground control personnel, may not be obtaining the minimum recommended rest periods: actual work-sleep time is not the same as 

the time that is planned. Evidence shows that, overall, sleep is shorter and interrupted in flight. During critical 

mission phases, schedule shifting and workload demands are strenuous for both ground and flight teams. It is 

important to ensure that the current NASA STD-3001, Vol. 1 standards are enforced to protect work-rest 

schedules for both ground and flight crews, particularly during high-tempo operations. If crews are shifted or 

have to perform during this allotted sleep time, recovery time needs to be allowed and individualized 

countermeasures need to be readily available. 

 Conclusion

Ground evidence clearly demonstrates the risk of performance errors due to sleep loss, fatigue, circadian 

desynchronization, and work overload. Reviews in the aviation and medical industry have consistently attributed accidents, injuries, and even death to performance errors arising from sleep and circadian issues. Furthermore, long-term health consequences serve as another potential outcome. The WHO International Agency for 

Research on Cancer Monograph Working Group recently concluded that, on the basis of published evidence, 

“shift work that involves circadian rhythm disruption is probably carcinogenic to humans” (Straif et al., 2007). 

Space flight evidence shows that astronauts are regularly subject to shifting their sleep/wake schedules, long 

work hours, complex tasks, and sleep loss. The ground teams that support flight crews and robotic missions 

endure similar issues. As NASA transitions from LEO to lunar and Mars missions, flight and ground crews will 

certainly continue to face the challenges that are associated with acquiring adequate sleep, circadian desynchronization, fatigue, extended work shifts, and workload demands. 

As space flight performance data are limited, BHP research aims to further characterize performance in the 

space flight environment using validated tools that detect cognitive deficits that are related to fatigue. Evaluations of gross motor performance in space flight are also anticipated. BHP research efforts will further describe 

the nature of sleep in space over long-duration missions, and tasks are under way to determine which factors en-
Chapter 3 Human Health and Performance Risks of Space Exploration Missions 

108 Risk of Performance Errors Due to Sleep Loss, Circadian Desynchronization, 

Fatigue, and Work Overload 

hance or infringe on sleep and disrupt circadian rhythms in space. The space flight environment is reported to be 

noisy, poorly lit, and, for some, uncomfortable. Shifting schedules and heavy workloads, particularly for the shuttle 

astronauts, can pose additional challenges. Adequately assessing the environment and making recommendations 

to improve on it, as well as understanding individual vulnerabilities to sleep loss, is an essential part of preparing 

for future missions to the moon and Mars. 

Astronauts have proven to be resourceful in mitigating sleep loss, circadian desynchronization, fatigue, extended work shifts, and work overload. Lighting, medication, good sleep hygiene, and improved scheduling 

serve as effective countermeasures for space flight crews. Much remains unknown concerning the best ways in 

which to implement these countermeasures, however, particularly over time. Some medications, for instance, are 

suspected to work differently in space than they do on Earth. Non-sleep medications may be required in flight, 

and the potential interactions between these and the sleep medications that are prescribed in space flight have 

yet to be determined. Similarly, additional research will aid in the use of artificial lighting as a countermeasure 

for increasing acute alertness as well as facilitating the alignment of circadian rhythms. The long-term safety 

and efficacy of light as a non-pharmaceutical aid for alertness, circadian shifting, and sleep will inform requirements for the lunar and Mars crew habitats as well as recommendations to the crews, flight controllers, and 

flight medical operations. 

Continued research efforts are necessary to address the psychological and physiological health of individuals 

during and following space flight missions. The sleep and circadian systems affect immunology, hormone production, GI function, and cardiovascular health; sleep disruption can also serve as a contributing factor for the 

risk of behavioral conditions (Chapter 1) as well as for the risk that is related to poor team cohesion and psychosocial adaptation (Chapter 2). Similarly, countermeasures that are developed to aid the sleep and circadian system 

can also serve to enhance other aspects of health; as an example, research indicates that bright light can serve as an 

effective treatment for Seasonal Affective Disorder (Glickman et al., 1998). Addressing the sleep and circadian 

system thus further addresses other risks within BHP as well as enhances other discipline research areas that are 

related to the human system and health outcomes from living and working in the space flight environment. 

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 Acknowledgments

It is important to acknowledge the contributions that were made by our BHP community, including flight 

surgeons and medical operations, researchers from the NSBRI, our external investigators, and many others 

as noted below. Their time and work in this risk area are critical for understanding and communicating what is 

known and unknown regarding the risks of, and their mitigation for, human space flight, particularly as NASA 

plans exploration missions to the moon and Mars. Such knowledge will enable the space agency to meet these 

future challenges and succeed. 

 Contributors and reviewers 

Kelley J. Slack, Ph.D., Industrial and Organizational (I/O) Psychology; I/O Psychologist, BHP, Space 

Medicine Division; Wyle Integrated Science and Engineering Group, NASA Johnson Space Center, 

Houston. 

Pam Baskin, B.S., Biological Sciences; Research Scientist, BHP Element, HRP; Wyle Integrated 

Science and Engineering Group, NASA Johnson Space Center, Houston. 

Kathryn Keeton, Ph.D., I/O Psychology; Research Scientist, BHP Element, HRP; EASI/Wyle 

Integrated Science and Engineering Group, NASA Johnson Space Center, Houston. 

Walter Sipes, Ph.D., Clinical Psychology; Chief of Operational Psychology, BHP, Space Medicine 

Division; NASA Johnson Space Center, Houston. 

Joseph V. Brady, Ph.D., Behavioral Biology and Neuroscience; John Hopkins University, School of Medicine; 

Baltimore. Associate Team Leader, Neurobehavioral and Psychosocial Factors Team, NSBRI. 
Human Health and Performance Risks of Space Exploration Missions Chapter 3 

Risk of Performance Errors Due to Sleep Loss, Circadian Desynchronization, 

Fatigue, and Work Overload 115

 Appendix 1: International Space Station Lighting

The following information was provided by James Maida, Habitability and Human Factors Branch, NASA 

Johnson Space Center, and Charles Bowen, Ph.D., Human Factors Design Engineering Specialist from the Lockheed Martin Human Factors Design Team. This information illustrates the dim lighting that crew members 

experience on board the ISS. 

The best-case average illumination on board Node 1 of the ISS with eight out of eight fluorescent lamps burning is 13.82 foot-candles (fc). In contrast, on Mar 31, 2005, Node 1 was down to only one lamp burning, with 

an illuminance of 0.55 fc. Since color vision fails at approximately 0.30 fc, that lighting level is unacceptable for 

most tasks. The dim illumination in Node 1 presented a safety issue that was addressed, initially, by moving lamps 

from another area. The problem was ultimately solved by a resupply of the ISS by STS-114, which flew in Jul 

2005. 

In other examples, when the U.S. Laboratory on ISS has all 12 lamps burning, the illumination is 57.79 fc. 

When only four of the 12 lamps are burning, illumination is reduced to 16.48 fc. Finally, in an airlock that has all 

four of its fluorescent lamps working, the illuminance is 17.55 fc. When the airlock is down to one lamp, the illuminance can be as low as 2.62 fc. 

The above illuminances were determined by the radiance illuminance model of the Lawrence Berkeley National 

Laboratory, Berkeley, Calif., with modifications for space flight applications. 

Required illuminances for various tasks include: maintenance, 25 fc; transcribing, 50 fc; repair, 30 fc; reading, 

50 fc; and night lighting, 2 fc. 

Foot-candles can be converted to the international unit of lux by multiplying by 10. Thus, 10 fc = 100 lux. 

 Appendix 2: Mathematical Models of Human Circadian 

 Rhythms and Performance

NASA currently uses two different mathematical models of human circadian rhythms and performance: the 

Astronaut Scheduling Assistant, and the Circadian, Neurobehavioral Performance, and Subjective Alertness 

Model. 

At the heart of the Astronaut Scheduling Assistant is a comprehensive set of mathematical equations, numerical 

strategies, and computer program routines that enables the prediction of changes in astronauts’ neurobehavioral 

performance capability over time. The model core makes predictions of neurobehavioral performance capability 

that are based on sleep and sleep loss (acute and chronic), naps, circadian rhythms, and light exposure, which means 

that the model also incorporates predictions that are based on countermeasures. These predictions allow for the 

evaluation of risk and safety of sleep/wake/work schedules during both the planning and the execution of space 

missions. Prospective studies on the accuracy of these model predictions that simulate the conditions of many of 

the sleep loss and circadian provocations that occur in space flight remain to be done on Earth. Such studies are 

essential, and may indicate the need for additional model parameters and changes in model structure. 

Future work involves modifying the Astronaut Scheduling Assistant by integrating adaptive Bayesian performance prediction methods that use the results of an individual’s past performance to identify individual 
Chapter 3 Human Health and Performance Risks of Space Exploration Missions 

116 Risk of Performance Errors Due to Sleep Loss, Circadian Desynchronization, 

Fatigue, and Work Overload 

specific trait parameters (e.g., rate of homeostatic decay, magnitude of circadian fluctuation in performance, 

etc.) prior to predicting future performance with an individual-specific model. 

The Circadian, Neurobehavioral Performance, and Subjective Alertness Model approach has been directed 

towards increasing the accuracy of predictions and adding operationally relevant features. For example, melatonin is now incorporated as a circadian marker rhythm to accurately predict the phase and amplitude of the 

circadian pacemaker. Incorporation of wavelength-specific inputs is in progress. This model has recently been 

amended to allow the determination of an optimal light countermeasure regime for a given shift in sleep/wake 

or work schedule to improve performance at a desired time; this includes a schedule/countermeasure design 

prototype program that allows a user to interactively design a schedule and automatically design a countermeasure regime. 

A current BHP in-flight effort is collecting sleep-wake data through use of actigraphy. These data, 

which are accumulated from actual astronauts in flight, will be integrated into the Circadian, Neurobehavioral Performance, and Subjective Alertness Model. 
Space Radiation 

Risk of Radiation Carcinogenesis 

Risk of Acute Radiation 

Syndromes Due to Solar 

Particle Events 

Risk of Acute or Late 

Central Nervous System Effects 

from Radiation Exposure 

Risk of Degenerative Tissue 

or Other Health Effects 

from Radiation Exposure 

Risk of Radiation Carcinogenesis 119

Chapter 4: 

Risk of Radiation Carcinogenesis 

Francis A. Cucinotta 

NASA Johnson Space Center 

Marco Durante 

GSI Germany 

Occupational radiation exposure from the space environment may increase cancer morbidity or mortality risk 

in astronauts. This risk may be influenced by other space flight factors including microgravity and environmental contaminants. A Mars mission will not be feasible unless improved shielding is developed or transit 

time is decreased. – Human Research Program Requirements Document, HRP-47052, Rev. C, dated Jan 

2009. 

 Pictured is the Crab Nebula, a 6-light-year-wide 

expanding remnant of the supernova explosion of a 

star; the colors indicate the different expelled 

elements. Astronauts in space are exposed to 

protons and high-energy and charge ions that are 

released by events such as supernovae, along with 

secondary radiation, including neutrons and recoil 

nuclei that are produced by nuclear reactions in 

spacecraft and tissue. Ground studies and system 

biology models of cancer risk reduce uncertainties 

in risk projection models and pave the way for

biological countermeasure development to protect 

astronauts on future Exploration missions.
120 Risk of Radiation Carcinogenesis 
Human Health and Performance Risks of Space Exploration Missions Chapter 4 

Risk of Radiation Carcinogenesis 121

 Executive Summary 

Astronauts who are on missions to the ISS, the moon, or Mars are exposed to ionizing radiation with effective 

doses in the range from 50 to 2,000 mSv (milli-Sievert) as projected for possible mission scenarios (Cucinotta 

and Durante, 2006; Cucinotta et al., 2008). The evidence of cancer risk from ionizing radiation is extensive 

for radiation doses that are above about 50 mSv. Human epidemiology studies that provide evidence for cancer 

risks for low-linear energy transfer (LET) radiation such as X rays or gamma rays at doses from 50 to 2,000 mSv 

include: the survivors of the atomic-bomb explosions in Hiroshima and Nagasaki, nuclear reactor workers 

(Cardis et al., 1995; 2007) in the United States, Canada, Europe, and Russia, and patients who were treated therapeutically with radiation. Ongoing studies are providing new evidence of radiation cancer risks in populations 

that were accidentally exposed to radiation (i.e., from the Chernobyl accident and from Russian nuclear weapons 

production sites), and continue to analyze results from the Japanese atomic-bomb survivors from Hiroshima and 

Nagasaki. These studies provide strong evidence for cancer morbidity and mortality risks at more than 12 

tissue sites, with the largest cancer risks for adults found for leukemia and tumors of the lung, breast, stomach, 

colon, bladder, and liver. There is also strong evidence for inter-gender variations due to differences in the natural incidence of cancer as well as additional cancer risks for the breast and the ovaries and a higher risk from 

radiation for lung cancer in females (National Council on Radiation Protection and Measurements (NCRP), 

2000). Human studies also provide evidence for a declining risk with increasing age at exposure, although the 

magnitude of this reduction above age 30 years is uncertain (NCRP, 2000; Biological Effects of Ionizing 

Radiation (BEIR), 2006). Genetic and environmental factors that contribute to radiation carcinogenesis are 

also being explored to support the identification of individuals with higher or reduced risk. 

In space, astronauts are exposed to protons and high-Z high-energy (HZE) ions together with secondary 

radiation, including neutrons and recoil nuclei, which are produced by nuclear reactions in spacecraft or tissue. 

Whole body doses of 1 to 2 mSv/day accumulate in interplanetary space, and approximately half of this value 

accumulates on planetary surfaces(Cucinotta et al., 2006; NCRP, 2006). Radiation shielding is an effective 

countermeasure for solar particle events (SPEs), which are chiefly made up of protons with energies that are 

largely below a few hundred MeV. The intermediate dose-rates (<500 mSv/hour) and scarcity of data on the 

biological effectiveness of protons as compared to low-LET radiation make optimization of SPE shielding uncertain at this time, however. The energy spectrum of galactic cosmic rays (GCRs) peaks near 1,000 MeV/ 

nucleon; consequently, these particles are so penetrating that shielding can only partially reduce the doses that 

are absorbed by the crew (Cucinotta et al., 2006). Thick shielding poses obvious mass problems to spacecraft 

launch systems, and would only reduce the GCR effective dose by no more than 25% using aluminum, or about 

35% using more efficient polyethylene. Therefore, with the exception of solar proton events, which are effectively absorbed by shielding, current shielding approaches cannot be considered a solution for the space radiation 

problem (Cucinotta et al., 2006; Wilson et al., 1995). In traveling to Mars, every cell nucleus within an astronaut 

would be traversed by a proton or secondary electron every few days, and by an HZE ion every few months

(Cucinotta et al., 1998b). The large ionization power of HZE ions makes them the major contributor to the 

risk, in spite of their lower cell nucleus hit frequency compared to protons. 

Epidemiological data, which are largely derived from the atomic-bomb survivors in Japan(Preston et al., 2003), 

provide a basis for risk estimation for low-LET radiation. However, because no human data exist for protons 

and HZE ions, space risk estimates must rely entirely on experimental model systems and biophysical considerations. Projections to predict cancer risks in astronauts are currently made using the double detriment life-table 

for an average population such as is found in the U.S., which is made up of age- and gender-dependent rates of 

death from cancer and all causes of death combined with a model of radiation cancer mortality rate (NCRP, 

2000). The model that is used for the radiation cancer mortality rate is based on epidemiological studies of 

atomic-bomb survivors, which are assumed to be scalable to other populations, dose-rates, and radiation types. 
Chapter 4 Human Health and Performance Risks of Space Exploration Missions 

122 Risk of Radiation Carcinogenesis 

The two scaling parameters with large uncertainties are the radiation quality factor, which estimates the increased 

effectiveness of HZE nuclei as compared to gamma rays for the same dose, and the dose- and dose-rate effectiveness factor (DDREF). The DDREF estimates the reduction of a risk at low doses (<200 mGy) or dose-rates 

(<0.05 Gy/hour) compared to an acute exposure. Maximum acceptable levels of risk for astronauts are typically 

set at a 3% fatal risk (Cucinotta and Durante, 2006; NCRP, 1997b; 2000), but the large uncertainties in projections and the likelihood of other fatal or morbidity risks for degenerative diseases precludes a go/no-go decision 

at this time for Mars exploration. The scaling of mortality rates for space radiation risks to astronauts to the 

atomic-bomb survivors introduces many uncertaintiesinto risk estimates (Cucinotta et al., 2001; Cucinotta 

and Durante, 2006), and there are also important questions with regard to the correctness of any scaling 

approach because of qualitative differences in the biological effects of HZE ions and gamma rays. 

Acceptable levels of risk must be guided by societal or ethical norms. Debate continues on what level is 

acceptable for space radiation cancer risks for the exploration of the moon or Mars. Although a historical 

perspective is summarized herein, we note that the strong possibility of non-cancer mortality and morbidity 

risks must also be considered for a Mars mission. Improvements in safety in other areas of space flight should 

place pressure on radiation protection to improve and lower the risks to astronauts from space radiation. 

Ground-based experimentation (Durante and Cucinotta, 2008) is key to solving the problem of space radiation 

cancer risk estimation because flight experiments are difficult, expensive, and poorly reproducible; the dose-rate 

is too low to get useful data in reasonable time; and, in the past, experiments have yielded no major findings(Kiefer 

and Pross, 1999; Schimmerling et al., 2003; Durante and Kronenberg, 2005). As part of its Space Radiation Program, NASA has invested in the NASA Space Radiation Laboratory (NSRL) at Brookhaven National Laboratory (Upton, N.Y.) to simulate the high-energy protons and heavy ions that are found in space. NSRL, which 

opened for research in October 2003, has produced experimental data in the past few years that are of great 

relevance for reducing uncertainty on risk assessment. 

Although studies with animals are an important component of space radiation research, they are timeconsuming and expensive in light of the large number of radiation types, doses, and dose-rates that are of 

concern to NASA. Systems biology models of cancer risk that can be used to extrapolate radiation quality over 

the broad range of nuclear types and energies and fluence rates in space suggest that effective mitigation measures 

are a promising new approach to these problems. Mechanistic research performed at NSRL with two-dimensional 

(2D) human cell culture and three-dimensional (3D) human coculture models (Barcellos-Hoff et al., 2005) as 

well as animal studies in murine models is being pursued to establish level of risk, reduce uncertainties in risk 

projection models, guide the extrapolation from experiment to astronauts, and pave the way for biological 

countermeasure development (Cucinotta and Durante, 2006). 

 Introduction 

As noted by Durante and Cucinotta (2008), cancer risk that is caused by exposure to space radiation is now 

generally considered the main hindrance to interplanetary travel for the following reasons: large uncertainties 

are associated with the projected cancer risk estimates; no simple and effective countermeasures are available, 

and significant uncertainties prevent scientists from determining the effectiveness of countermeasures. Optimizing operational parameters such as the length of space missions, crew selection for age and gender, or applying 

mitigation measures such as radiation shielding or use of biological countermeasures can be used to reduce risk, 

but these procedures are clouded by uncertainties. 
Human Health and Performance Risks of Space Exploration Missions Chapter 4 

Risk of Radiation Carcinogenesis 123

Space radiation is comprised of high-energy protons and high-charge (Z) and -energy (E) nuclei (HZE) whose 

ionization patterns in molecules, cells, and tissues, and the resulting initial biological insults, are distinct from 

typical terrestrial radiation, which consists largely of X rays and gamma rays that are characterized as low-LET 

radiation. GCRs, which originate outside of our galaxy (probably from supernovas), are comprised mostly of 

highly energetic protons with a small component of HZE. Prominent HZE nuclei include: helium (He), carbon 

(C), oxygen (O), neon (Ne), magnesium (Mg), silicon (Si), and iron (Fe). GCR energy spectra peaks, which 

have median energies of about 1,000 MeV/amu, and nuclei with energies as high as 10,000 MeV/amu, make 

important contributions to the dose-equivalent.

Ionizing radiation is a well-known carcinogen on Earth (BEIR, 2006). The risks of cancer from X rays and 

gamma rays have been established at doses above 50 mSv (5 rem), although there are important uncertainties 

and ongoing scientific debate concerning cancer risk at lower doses and at low dose-rates (<50 mSv/hour). The 

relationship between the early biological effects of HZE nuclei and the probability of cancer in humans is poorly 

understood, and it is this missing knowledge that leads to significant uncertainties in projecting cancer risks 

during space exploration (Cucinotta and Durante, 2006; Durante and Cucinotta, 2008). 

 Uncertainties in cancer projections 

For space radiation risk assessments, the major uncertainties in cancer prediction are 

 Radiation quality effects on biological damage related to the qualitative and quantitative differences 

between space radiation compared to X rays 

 Dependence of risk on dose-rates in space related to the biology of deoxyribonucleic acid (DNA) 

repair, cell regulation, and tissue or organism responses 

 Predicting SPEs, including temporal, energy spectra, and size predictions 

 Extrapolation from experimental data to humans and between human populations 

 Individual radiation-sensitivity factors, including genetic, epigenetic, dietary, or “healthy worker” 

effects 

The minor uncertainties in cancer risk prediction are 

 Data on GCR environments 

 Physics of shielding assessments related to transmission properties of radiation through materials and 

tissue 

 Microgravity effects on biological responses to radiation 

 Errors in human data (statistical, dosimetry, or recording inaccuracies) 

Quantitative methods have been developed to propagate uncertainties for the several factors that contribute to 

cancer risk estimates (NCRP, 1997a; Cucinotta et al., 2001; 2006). A description of uncertainty analysis using 

Monte Carlo techniques is provided below. Current estimates of levels of uncertainty, which are represented as 

fold changes of the upper 95% confidence interval (C.I.) over the median risk projection, are illustrated in figure 

4-1, and a comparison of the risks for adults for both terrestrial and space exposures is shown in figure 4-2. The 

contribution of microgravity effects on space radiation risk has not yet been estimated but it is expected to be 

small (Kiefer and Pross, 1999). Changes in oxygen levels or in immune dysfunction (Smyth et al., 2006) are 

of concern during space flight. Their effects on radiation cancer risks are largely unknown. 
Chapter 4 Human Health and Performance Risks of Space Exploration Missions 

124 Risk of Radiation Carcinogenesis 

Figure 4-1. Estimates of fold uncertainties from several factors that contribute to cancer risk estimates 

from space radiation exposures. The uncertainties are larger for astronauts who are in space as compared 

to typical exposures on Earth, as illustrated.

Figure 4-2. Uncertainties in risk projection for terrestrial and space exposures. The uncertainties are larger 

for astronauts who are in space as compared to typical exposures on Earth, as illustrated here. This figure 

shows the current estimates of cancer risks (diamonds) and 95% confidence bands for adults of age 40 

years, which is the typical age of astronauts on space missions, for several terrestrial exposures and 

missions on the ISS as well as projections for a lunar colony and a Mars mission.
Human Health and Performance Risks of Space Exploration Missions Chapter 4 

Risk of Radiation Carcinogenesis 125

Radiation affects cells and tissues either through direct damage to the cellular components or through the production of highly reactive free radicals from water (Goodhead, 1994). Both of these mechanisms can generate 

sufficient damage to cause cellular death, DNA mutation, or abnormal cellular function. The extent of damage 

is generally believed to be dependent on the dose and type of particle with a linear dose-response curve (Goodhead, 

1994). This is true for high and moderate radiation exposure, but it is extremely difficult to measure for lower 

doses where it is not easy to discern the effects of radiation exposure from those that are triggered by the normal 

oxidative stress with which cells and tissues deal constantly. The HZE nuclei are unique components of space 

radiation that produce densely ionizing tracks as they pass through matter; when they traverse a biological system, they leave streaks or tracks of damage at the biomolecular level that fundamentally differ from the damage 

that is left by low-LET radiation sources such as gamma rays and X rays. In the nucleus of a cell, where the genetic material is stored, the traversal of a heavy ion can produce tracks of clustered DNA damage (Cucinotta 

and Durante, 2006), as illustrated in figure 4-3. 

Figure 4-3. Comparison of particle tracks in nuclear emulsions and human cells (Cucinotta and Durante, 2006). The 

right panel shows tracks of different ions, from protons to Fe, in nuclear emulsions, clearly showing the increasing 

ionization density (LET=ΔE/ Δ x) along the track by increasing the charge Z. The left panel shows three nuclei of 

human fibroblasts exposed to gamma rays or to Si- or Fe-ions, and immunostained for detection of -H2AXP. Each 

green focus corresponds to a DNA double strand break (DSB). While in the cell that is exposed to sparsely ionizing 

gamma rays foci of the histone variant, H2AX, are uniformly distributed in the nucleus, the cells that are exposed to 

HZE particles present DNA damage along tracks (one Si- and three Fe-particles, respectively), and the spacing 

between DNA DSB is reduced at a very high LET.

HZE nuclei impart damage via the primary energetic particle as well as from fragmentation events that produce a spectrum of other energetic nuclei, including protons, neutrons, and heavy fragments (Wilson et al., 1995; 

Cucinotta et al., 1998a; 2006); a large penumbra of energy deposition extends outward from the primary particle 
Chapter 4 Human Health and Performance Risks of Space Exploration Missions 

126 Risk of Radiation Carcinogenesis 

track (Cucinotta et al., 2000a). Secondary radiation that is produced in shielding materials can be controlled 

through the use of materials that have light atomic constituents (e.g., hydrogen and carbon). However, a large 

percentage of secondary radiation is produced within tissue and is, therefore, not practically avoidable. Due to 

the large amount of energy that is deposited as these particles traverse biological structures, the HZE nuclei are 

capable of producing the greatest amount of cellular damage, which means that they are of great concern for 

astronaut safety. The lack of epidemiological data and sparse radiobiological data on the effects for these radiation types leads to a high level of uncertainty when formulating risk estimates of long-term health effects 

following exposure to GCRs and SPEs. 

 Types of cancer caused by radiation exposure 

A broad spectrum of tissue types contributes to the overall cancer risk that is observed with low-LET radiation 

(Table 4-2), including lung, colorectal, breast, stomach, liver, and bladder cancers as well as several types of 

leukemia, including acute myeloid leukemia and acute lymphatic lymphoma (NCRP, 2000; Preston et al., 2003; 

BEIR, 2006). It is not known whether the same spectrum of tumors will occur for high-LET radiation as with 

low-LET radiation, and some differences should be expected. Relative biological effectiveness (RBE) factors 

describe the ratio of a dose of high-LET radiation to that of the X rays or gamma rays that produce the identical 

biological effect. RBEs that are observed in mice with neutrons vary with the tissue type and strain of the animal 

(NCRP, 1990; Fry and Storer, 1987), which provides evidence that the spectrum of tumors in humans who are 

exposed to space radiation will be distinct from that in humans who are exposed to low-LET radiation. These 

likely differences are not described by the models that are used currently at NASA to project space radiation 

risks. 

 Age, latency, gender, and individual sensitivity issues 

As cancer is a genetic disease with important epigenetic factors, individual susceptibility issues are an important consideration for space radiation protection. Females have a higher cancer risk from radiation than males, 

largely due to the additional risks to the breast and ovary; but studies show that there is also a much higher risk 

of lung cancer after radiation exposure in females than in males (NCRP, 2000). Risk at a sufficiently high age 

would be expected to decrease with age at exposure because the distribution of latency for tumor development 

would extend beyond the expected life span at older exposure ages. There may also be a reduction in the number 

of cells that are at risk at older age due to senescence or other biological factors (Campisi, 2003; 2007). However, 

the possibility that radiation acts more as a tumor promoter than as an initiator, and the fact that the animal data 

for high-LET radiation show tumors developing at earlier times than with low-LET radiation, suggests that the 

age dependence of space cancer risk is inadequately understood at this time. 

Genetic factors and environmental factors also impact the risk of cancer from radiation. Studying the mechanisms of genetic sensitivity provides important insights into the understanding of radiation risks to astronauts 

(Durante and Cucinotta, 2008). Studies of historical data sets, such as the atomic-bomb survivors, show that subsets of the exposed cohorts could have a higher-than-average radiation risk (Ponder, 2001). A well-known example 

is ataxia telangiectasia (AT) patients, who dramatically demonstrate the importance of genetic susceptibility to 

radiation damage in cancer treatment. Other examples that are related to DNA repair genes include BRCA1&2 

(Ponder, 2001, p. 53), NBS (Pluth et al., 2008), and Artemis (Wang et al., 2005), as well as the many other socalled high-penetrance genes that are involved in cancer susceptibility (Ponder, 2001). 

Ataxia telangiectasia mutated (ATM) homozygotes only represent a small fraction of the radiosensitive 

patients, although these patients appear to be the most sensitive. ATM heterozygotes, who are also cancerprone, are suspected to represent a large fraction of the extreme radiosensitive patients (Thompson et al., 2005). 
Human Health and Performance Risks of Space Exploration Missions Chapter 4 

Risk of Radiation Carcinogenesis 127

It has been shown that cells that are heterozygous for ATM mutations are slightly more sensitive to radiationinduced neoplastic transformation than are the wild-type cells(Sminelov et al., 2001). An increased sensitivity 

of ATM heterozygotes has been also proved in vivo, measuring the induction of cataracts in ATM homozygotes, heterozygotes, and wild-type mice exposed to 0.5- to 4-Gy X rays(Worgul et al., 2002). 

An important issue to address is how low-penetrance genes impact sensitivity to radiation-induced cancer. A 

recent study on subjects who were exposed to high radiation doses to treat ringworm of the scalp (tinea capitis) 

in Israel revealed a strong familial risk of radiation-induced meningioma (Flint-Ritcher and Sadetzki, 2007), suggesting that radiation carcinogenesis might be an issue for a genetically predisposed subgroup of the general 

population rather than a random event (Hall, 2007). 

It is not known whether individuals who display hypersensitivity to low-LET radiation will also be equivalently 

hypersensitive to HZE nuclei, or whether findings at high dose and dose-rates will hold at low dose-rates and 

doses. Mice that are heterozygous for the ATM gene are more sensitive to cataractogenesis than are wild-types, 

not only after exposure to X rays but also after localized irradiation with high-energy Fe-ions(Hall et al., 2006). 

However, other studies show that high-LET irradiation has a reduced dependence on genetic background compared to low-LET irradiation (George et al., 2009). 

A predictive assay that is able to identify radiation hypersensitive or cancer-prone subjects could be useful in 

crew selection for long-term space flights. Alternatively, identifying resistant individuals could substantially 

lower mission costs. Although this assay is neither scientifically achievable nor within society norms in most 

countries at the present time, ultimately, for a high-risk and high-cost endeavor such as a mission to Mars, screening astronauts for increased resistance to space radiation may be sought to reduce the costs of the missions. 

 Current NASA permissible exposure limits 

Permissible exposure limits (PELs) for short-term and career astronaut exposures to space radiation have been 

approved by the NASA Chief Health and Medical Officer, and requirements and standards for mission design 

and crew selection have been set. This section describes the cancer risk section of the PELs. 

 Career Cancer Risk Limits 

The astronaut career exposure to radiation is limited to not exceed 3% of the risk of exposure-induced death 

(REID) from fatal cancer. NASA policy is to assure that this risk limit is not exceeded at a 95% confidence 

level (CL) by using a statistical assessment of the uncertainties in the risk projection calculations to limit the cumulative effective dose (in units of Sievert) that is received by an astronaut throughout his or her career. These 

limits are applicable to missions of any duration in LEO and to lunar missions of less than 180 days duration. 

For longer missions that are outside LEO, further considerations of non-cancer mortality risks and approaches 

to reduce uncertainty in cancer risk projection models must occur before these missions can be safely assured. 

 Cancer Risk to Dose Relationship 

The relationship between radiation exposure and risk is both age- and gender-specific due to latency effects 

and differences in tissue types, sensitivities, and life spans between genders. These relationships are estimated 

using the methods that are recommended by the NCRP (NCRP, 2000) and more recent radiation epidemiology 

information (Preston et al., 2003; Cucinotta et al., 2006). Table 4-1 lists examples of career effective dose (E) 

limits for an REID=3% for missions that are of 1-year duration or less. Limits for other career or mission lengths 

will vary and should be calculated using the appropriate life-table formalism. Tissue contributions to effective 

doses are defined below, as are dose limits for other career or mission lengths. Estimates of average life-loss 
Chapter 4 Human Health and Performance Risks of Space Exploration Missions 

128 Risk of Radiation Carcinogenesis 

that are based on low-LET radiation are also listed in Table 4-1; however, higher values should be expected 

for high-LET exposures such as GCRs. 

Table 4-1. Example Career Effective Dose Limits in Units of milli-Sievert (mSv) for 

1-year Missions and Average Life-loss for an Exposure-induced Death for Radiation 

Carcinogensis (1 mSv = 0.1 rem) 

E(mSv) for 3% REID (Ave. Life Loss per Death, yr) 

Age, yr Males Females 

25 520 (15.7) 370 (15.9) 

30 620 (15.4) 470 (15.7) 

35 720 (15.0) 550 (15.3) 

40 800 (14.2) 620 (14.7) 

45 950 (13.5) 750 (14.0) 

50 1,150 (12.5) 920 (13.2) 

55 1,470 (11.5) 1,120 (12.2) 

 The Principle of As Low As Reasonably Achievable 

The as low as reasonably achievable (ALARA) principle is a legal requirement intended to ensure astronaut 

safety. An important function of ALARA is to ensure that astronauts do not approach radiation limits and that 

such limits are not considered as “tolerance values.” ALARA is especially important for space missions in view 

of the large uncertainties in cancer and other risk projection models. Mission programs and terrestrial occupational procedures resulting in radiation exposures to astronauts are required to find cost-effective 

approaches to implement ALARA. 

 Method of evaluating career limits 

 Radiation Doses and Risk Limits 

Cancer risk is not measured directly but is calculated using radiation dosimetry and physics methods. The 

absorbed dose D (in units of Gray) is calculated using measurements of radiation levels that are provided by 

dosimeters (e.g., film badges, thermoluminescent dosimeters (TLDs), spectrometers such as the tissue-equivalent 

proportional counter (TEPC), area radiation monitors, biodosimetry, or biological markers) and corrections 

for instrument limitations. The limiting risk is calculated using the effective dose, E (in units of mSv), and 

risk conversion life-table methodologies. 

For the purpose of determining radiation exposure limits at NASA, the probability of fatal cancer is 

calculated as shown on the following page. 

 
Human Health and Performance Risks of Space Exploration Missions Chapter 4 

Risk of Radiation Carcinogenesis 129

1.The body is divided into a set of sensitive 

tissues, and each tissue, T, is assigned a weight, 

wT, according to its estimated contribution to 

cancer risk, as shown in Table 4-2. 

2.The absorbed dose, DT, that is delivered to each 

tissue is determined from measured dosimetry. 

Different types of radiation have different biological effectiveness, depending on the ionization density that is left behind locally (e.g., in a 

cell or a cell nucleus) by the passage of radiation 

through matter. For the purpose of estimating 

radiation risk to an organ, the quantity characterizing this ionization density is the LET (in 

units of keV/μm). 

3. For a given interval of LET, between L 

and ∆L, the dose-equivalent risk (in units 

of Sievert, where 1 Sv = 100 rem) to a tissue, 

T, HT (L) is calculated as 

( ) ( ) ( ), HT T L QLD L  (1) 

where the quality factor, Q(L), is obtained according to the International Commission on Radiation 

Protection (ICRP) prescription that is shown in Table 

4-3. This way of calculating HT(L) differs from the 

method that is used by the ICRP, in which a tabulated 

set of weighting factors is given instead of the quality 

factor. The method that is used here is considered to 

yield a better approximation by using the quality 

factor as the weight that is most representative of 

cancer risk; the ICRP method, by contrast, may 

overestimate the risk, especially for high-energy protons. Neutron contributions are evaluated by their 

contribution to DT(L).

4.The average risk to a tissue T, due to all types of radiation contributing to the dose, is given by 

()() , HT T  D L Q L dL  (2) 

or, since DT (L)  LFT (L), where FT(L) is the fluence of particles with LET=L, traversing the organ, 

() (). HT T  dLQ L F L L  (3) 

Table 4-3. Quality Factor – Linear Energy Transfer

Relationship

Unrestricted LET, 

keV/μm in Water Q(LET) 

<10 1 

10 to 100 0.32 LET – 2.2 

>100 300/ Sqrt(LET) 

Table 4-2. Tissue Weighting Factors 

Tissue or Organ Tissue Weighting 

Factor, wT

Gonads 0.20 

Bone Marrow (red) 0.12 

Colon 0.12 

Lung 0.12 

Stomach 0.12 

Bladder 0.05 

Breast 0.05 

Liver 0.05 

Esophagus 0.05 

Thyroid 0.05 

Skin 0.01 

Bone Surface 0.01 

Remainder* 0.05 

*For purpose of calculation, the remainder is composed of the 

following additional tissues and organs: adrenals, brain, upper 

intestine, small intestine, kidney, muscle, pancreas, spleen, 

thymus, and uterus. 
Chapter 4 Human Health and Performance Risks of Space Exploration Missions 

130 Risk of Radiation Carcinogenesis 

5.The effective dose is used as a summation over radiation type and tissue using the tissue weighting factors, 

wT, 

. T T

T

E  w H (4) 

6. For a mission of duration t, the effective dose will be a function of time, E(t), and the effective dose for 

mission i will be 

() . i E  E t dt  (5) 

7.The effective dose is used to scale the mortality rate for radiation-induced death from the Japanese survivor data, applying the average of the multiplicative and additive transfer models for solid cancers and the 

additive transfer model for leukemia by applying life-table methodologies that are based on U.S. population 

data for background cancer and all causes of death mortality rates. A DDREF of 2 is assumed. 

 Evaluation of Cumulative Radiation Risks 

The cumulative cancer fatality risk (%REID) to an astronaut for occupational radiation exposures, N, is 

found by applying life-table methodologies that can be approximated at small values of %REID by summing 

over the tissue-weighted effective dose, Ei, as 

0

1

( , ),

N

i i

i

Risk E R age gender



  (6) 

where R0 are the age- and gender-specific radiation mortality rates per unit dose. The effective dose limits 

that are given in the Table 4-1 illustrate the effective dose that corresponds to a 3% REID for missions with a 

duration of as long as 1 year. Values for multiple missions or other occupational exposure are estimated using 

Eq(6) or directly from life-table calculations. For organ dose calculations, NASA uses the model of Billings 

et al. (1973) to represent the self-shielding of the human body in a water-equivalent mass approximation. 

Consideration of the orientation of the human body relative to vehicle shielding should be made if it is 

known, especially for SPEs (Wilson et al., 1995). 

Confidence levels for career cancer risks are evaluated using methods that are specified by the NCRP in 

Report No. 126 (NCRP, 1997a), which was modified to account for the uncertainty in quality factors and 

space dosimetry (Cucinotta et al., 2001; 2006). The uncertainties that were considered in evaluating the 95% 

CLs are the uncertainties in 

1. Human epidemiology data, including uncertainties in 

a. statistics limitations of epidemiology data, 

b. dosimetry of exposed cohorts, 

c. bias, including misclassification of cancer deaths, and 

d. the transfer of risk across populations. 

2.The DDREF factor that is used to scale acute radiation exposure data to low-dose and dose-rate radiation 

exposures. 
Human Health and Performance Risks of Space Exploration Missions Chapter 4 

Risk of Radiation Carcinogenesis 131

3.The radiation quality factor (Q) as a function of LET. 

4. Space dosimetry. 

The so-called “unknown uncertainties” from the NCRP Report No. 126 (1997a) are ignored by NASA. 

The statistical distribution for the estimated probability of fatal cancer is evaluated to project the most likely 

values and the lower and upper 95% C.I.’s that are reported within brackets. For example, for the average 

adult who is exposed to 100 mSv (10 rem) of gamma rays, the estimated cancer risk is 0.4 % and the 95%. 

C.I.’s are estimated as [0.11%, 0.82%] where 0.11% is the lower 95% level and 0.82% is the upper 95% CL. 

To assure that the career risk limit is not exceeded with a safety margin corresponding to a 95% CL, the upper 

CL (i.e., the worse case) is considered in developing mission constraints and for crew selection. Approximate 

fold-uncertainties for several NASA missions are shown in Table 4-4. 

Table 4-4. Approximate Fold-uncertainty Defined as a Ratio of Upper 95% 

Confidence Level to Point Risk Projection

Type of Exposure Fold-uncertainty at Upper 95% C.I. 

Medical Diagnostic 2.0 

ISS Environment 3.1 

SPE 2.5 

Deep Space or Lunar Surface GCR 4.0 

 Evidence 

The evidence and updates to projection models for cancer risk from low-LET radiation are reviewed 

periodically by several prestigious bodies, which include the following organizations: 

 The NAS Committee on the Biological Effects of Ionizing Radiation 

 The United Nations Scientific Committee on the Effects of Atomic Radiation (UNSCEAR) 

 The ICRP 

 The NCRP 

These committees release new reports about every 10 years on cancer risks that are applicable to low-LET 

radiation exposures. Overall, the estimates of cancer risks among the different reports of these panels will 

agree to within a factor of two or less. There is continued controversy for doses that are below 50 mSv, however, 

and for low dose-rate radiation because of debate over the linear no-threshold hypothesis that is often used in 

statistical analyses of these data. The BEIR VII report (BEIR, 2006), which is the most recent of the major reports, is used in the following summary. Evidence for low-LET cancer effects must be augmented by information on protons, neutrons, and HZE nuclei that is only available in experimental models. Such data have been 

reviewed by NASA several times in the past and by the NCRP (1989; 2000; 2006). 
Chapter 4 Human Health and Performance Risks of Space Exploration Missions 

132 Risk of Radiation Carcinogenesis 

 Epidemiology data for low-linear energy transfer radiation 

 Life Span Studies of Atomic Bomb Survivors 

The life span study (LSS) of the survivors of the atomic bombs in Hiroshima and Nagasaki, Japan, includes 

approximately 130,000 persons who were registered in 1950. Among these were 93,000 persons in Hiroshima 

and Nagasaki in 1945, and 37,000 persons who were living in these same cities in 1950. There is a gap in knowledge of the earliest cancer that developed in the first few years after the war, which impacts the assessment 

of leukemia to an important extent and for solid cancers to a minor extent. Some of the persons in the total 

data set were censured, leading to about 86,000 persons who have been followed in the study. Table 4-5 

shows summary statistics of the number of persons and deaths for different dose groups. These comparisons 

show that the doses that were received by the LSS population overlap strongly with the doses that are of 

concern to NASA Exploration mission (i.e., 50 to 2,000 mSv). 

Figure 4-4 shows the dose response for the excess relative risk (ERR) for all solid cancers from Preston et 

al. (2003). Tables 4-6 and 4-7 show several summary parameters for tissue-specific cancer mortality risks for 

females and males, respectively, including estimates of ERR, excess absolute risk (EAR), and percentage attributable risks. Cancer incidence risks from low-LET radiation are about 60% higher than cancer mortality 

risks (Preston et al., 2007). 

Table 4-5. Number of Persons, Cancer Deaths, and Non-cancer Deaths for Different Dose Groups in the 

Life Span Study (BEIR, 2006) 

DS86 Weighted Colon Dose, mSv 

Total 0-50 50–100 100–200 200–500 500–

1,000 

1,000–

2,000 

>2,000 

No. 

Subjects 

86,572 37,458 31,650 5,732 6,332 3,299 1,613 488 

Cancer 

Deaths 

9,335 3,833 3,277 668 763 438 274 82 

Noncancer 

Deaths 

31,881 13,832 11,633 2,163 2,423 1,161 506 163 

Figure 4-4. From Preston et al. (2003): 

Solid cancer dose-response function 

average over sex for attained age 70 after 

exposure at age 30. The solid straight-line is 

the linear slope estimate; the points are 

dose-category-specific ERR estimates; the 

dashed curve is a smoothed estimate that is 

derived from the points; and the dotted 

curves indicate upper and lower one-standerror bounds on the smoothed estimate. 
Human Health and Performance Risks of Space Exploration Missions Chapter 4 

Risk of Radiation Carcinogenesis 133

Table 4-6. From Preston et al. (2003): Tissue-specific Cancer Mortality Risk Summary Statistics (i.e., ERR, EAR, and 

Attributable Risks) for Females and Males, Respectively 

LSS Female Site-specific Summary Mortality Rate Estimates: Solid Cancers 1950–1997 

Site/system Deaths 

(>0.005 Sv) 

ERR/Sva

(90% CI) 

EAR/104PYb-Svc

(90% CI) 

Attributable 

risk (%)d

(90% CI) 

All solid cancer 

Oral cavity 

4,884 (2,948) 

42 (25) 

0.63 (0.49; 0.79) 

–0.20 (<–0.3; 0.75) 

13.5 (7.4; 16.3) 

–0.04 (<–0.3; 0.14) 

9.2 (7.4; 11.0) 

–4.1 (<–6; 14) 

Digestive system

 Esophagus 

 Stomach 

 Colon 

 Rectum 

 Liver 

 Gallbladder 

 Pancreas 

67(44) 

1,312 (786) 

272 (150) 

198 (127) 

514 (291) 

236 (149) 

244 (135) 

1.7 (0.46; 3.8) 

0.65 (0.40; 0.95) 

0.49 (0.11; 1.1) 

0.75 (0.16; 1.6) 

0.35 (0.07; 0.72) 

0.16 (–0.17; 0.67) 

–0.01 (–0.28; 0.45) 

0.51 (0.15; 0.92) 

3.3 (2.1; 4.7) 

0.68 (0.76; 1.3) 

0.69 (0.16; 1.3) 

0.85 (0.18; 1.6) 

0.18 (–0.21; 0.71) 

–0.01 (–0.35; 0.52) 

22 (6.6; 42) 

8.8 (5.5; 12) 

9.0 (3.4; 17) 

11.3 (2.6; 22) 

6.2 (1.3; 12) 

2.6 (–2.9; 10) 

–0.2 (–5.0; 7.6) 

Respiratory system

 Lung 

 Female breast 

 Uterus 

 Ovary 

548 (348) 

272 (173) 

518 (323) 

136 (85) 

1.1 (0.678; 1.6) 

0.79 (0.29; 1.5) 

0.17 (–0.10; 0.52) 

0.94 (0.07; 2.0) 

2.5 (1.6; 3.5 

1.6 (1.2; 2.2) 

0.44 (–0.27; 1.3) 

0.63 (0.23; 1.2) 

16 (10; 22) 

24 (18; 32) 

2.7 (–1.6; 7.9) 

15 (5.3; 28) 

Urinary system

 Bladder 

 Kidney 

67 (43) 

31 (21) 

1.2 (0.10; 3.1) 

0.97 (<–0.3; 3.8) 

0.33 (0.02; 0.74) 

0.14 (<–0.1; 0.42) 

16 (0.9; 36) 

14 (<–3; 42) 

Brain/CNSd 17 (10) 0.51 (<–0.3; 3.9) 0.04 (<–0.02; 0.2) 11 (<0.05; 57) 

a

ERR/SV for age at exposure 30 in an age-constant linear ERR model; bExcess absolute risk per 10,000 persons per year; cAverage EAR 

computed from ERR model; d

Attributable risk among survivors whose estimated dose is at least 0.005 Sv; CNS – central nervous system. 

Table 4-7. From Preston et al. (2003): Tissue-specific Cancer Mortality Risk Summary Statistics (i.e., ERR, EAR, and 

Attributable Risks) for Male 

LSS Male Site-specific Summary Mortality Rate Estimates: Solid Cancers 1950–1997 

Site/system Deaths 

(>0.005 Sv) 

ERR/Sva

(90% CI) 

EAR/104PYb-Svc

(90% CI) 

Attributable 

risk (%)d

(90% CI) 

All solid cancer 

Oral cavity 

4,451 (2,554) 

68 (37) 

0.37 (0.26; 0.49) 

–0.20 (<–0.3; 0.45) 

12.6 (9.4; 16.2) 

–0.12 (<–0.3; 0.25) 

6.6 (4.9; 8.4) 

–5.2 (<–6; 11) 

Digestive system

 Esophagus 

 Stomach 

 Colon 

 Rectum 

 Liver 

 Gallbladder 

 Pancreas 

224 (130 

1,555 (899) 

206 (122) 

172 (96) 

722 (408) 

92 (52) 

163 (103) 

0.61 (0.15; 1.2) 

0.20 (0.04; 0.39) 

0.54 (0.13; 1.2) 

–0.25 (<–0.3; 0.15) 

0.59 (0.11; 0.68) 

0.89 (0.22; 1.9) 

–0.11 (<–0.3; 0.44) 

1.1 (0.28; 2.0) 

2.1 (0.43; 4.0) 

1.1 (0.64; 1.9) 

–0.41 (<–0.4; 0.22) 

2.4 (1.2; 4.0) 

0.63 (0.17; 1.2) 

–0.15 (<–0.4; 0.58) 

11.1 (2.8; 21) 

3.2 (0.07; 6.2) 

12 (6.9; 21) 

–5.4 (<–6, 3.1) 

8.4 (4.2; 14) 

17 (4.5; 33) 

–1.9 (<–6; 7.5) 

Respiratory system

 Lung 

 Prostate 

716 (406) 

104(53) 

0.48 (0.23; 0.78) 

0.21 (<–0.3; 0.96) 

2.7 (1.4; 4.1) 

0.18 (<–0.2; 0.75) 

9.7 (4.9; 15) 

4.9 (<–5; 20) 

Urinary system

 Bladder 

 Kidney 

82 (56) 

36 (18) 

1.1 (0.2; 2.5) 

–0.02 (<–0.3; 1.1) 

0.7 (0.1; 1.4) 

–0.01 (–0.1; 0.28) 

17 (3.3; 34) 

–0.4 (<–5; 22) 

Brain/CNS 14 (9) 5.3 (1.4; 16) 0.35 (0.13; 0.59) 62 (23; 100) 

a

ERR/SV for age at exposure 30 in an age-constant linear ERR model; bExcess absolute risk per 10,000 persons per year; cAverage EAR 

computed from ERR model; d

Attributable risk among survivors whose estimated dose is at least 0.005 Sv. 
Chapter 4 Human Health and Performance Risks of Space Exploration Missions 

134 Risk of Radiation Carcinogenesis 

 Other Human Studies 

The BEIR VII report (BEIR, 2006) contains an extensive review of data sets from human populations, including nuclear reactor workers and patients who were treated with radiation. The recent report from Cardis 

et al. (2007) describes a meta-analysis for reactor workers from several countries. A meta-analysis at specific 

cancer sites, including breast, lung, and leukemia, has also been performed (BEIR, 2006). These studies require 

adjustments for photon energy, dose-rate, and country of origin as well as adjustments made in single population studies. Table 4-8 shows the results that are derived from Preston et al. (2002) for a meta-analysis of breast 

cancer risks in eight populations, including the atomic-bomb survivors. Median ERR varies by slightly more 

than a factor of two, but confidence levels significantly overlap. Adjustments for photon energy or dose-rate 

and fractionation have not been made. These types of analysis lend confidence to risk assessments as well as 

show the limitations of such data sets. 

Of special interest to NASA is the age at exposure dependence of low-LET cancer risk projections. The 

BEIR VII report (BEIR, 2006) prefers models that show less than a 25% reduction in risk over the range from 

35 to 55 years, while NCRP Report No. 132 (NCRP, 2000) shows about a two-fold reduction over this range. 

Table 4-8. Results from Meta-analysis of Breast Cancer Risk from Eight Population Groups, Including the Life Span Study 

of Atomic-bomb Survivors and Several Medical Patient Groups Exposed to X Rays, as described in Preston et al., 2002

Summary of Parameter Estimates for the Final Pooled ERR Model 

Cohort Reference age for 

the ERR/Gy estimate ERR/Gya

Percentage change 

per decade increase 

in age at exposure 

Exponent of 

attained age 

Background 

SIRb 

LSS attained age 50 2.10 

(1.6; 2.8) 

Not includedb –2.0 

(–2.8; –1.1) 

1.01 

(0.9; 1.1) 

TBO attained age 50 0.74 

(0.4; 1.2) 

Not included –2.0 

(–2.8; –1.1) 

0.96 

(0.7; 1.2) 

TBX attained age 50 0.74 

(0.4; 1.2) 

Not included –2.0 

(–2.8; –1.1) 

0.73 

(0.6; 0.9) 

THY attained age 50 0.74 

(0.4; 1.2) 

Not included –2.0 

(–2.8; –1.1) 

1.05 

(0.7; 1.5) 

BBD age at exposure 25 1.9 

(1.3; 2.8) 

–60% 

(–71%; –44%) 

Not includedc 0.98 

(0.8; 1.2) 

APM all ages 0.56 

(0.3; 0.9) 

Not included Not included 1.45 

(1.1; 1.8) 

HMG all ages 0.34 

(0.1; 0.7) 

Not included Not included 1.07 

(0.8; 1.3) 

HMS all ages 0.34 

(0.1; 0.7) 

Not included Not included 1.05 

(0.9; 1.2) 

a

95% C.I.’s within parentheses; bSIR = standardized incidence ratio; c”Not included” means that the risk is assumed not to vary with age at 

exposure (attained age). 

 Review of space flight issues 

In considering radiation risks for astronauts, it is useful to consider the historical recommendations that 

NASA has received from external advisory committees. These have formed the basis for the dose limits and risk 

projection models (Cucinotta et al., 2002). Early radiation effects usually are related to a significant fraction of 

cell loss that exceeds the threshold for impairment of function in a tissue. These “deterministic” effects are so 

called because the statistical fluctuations in the number of affected cells are very small compared to the number 
Human Health and Performance Risks of Space Exploration Missions Chapter 4 

Risk of Radiation Carcinogenesis 135

of cells that are required to reach the threshold (ICRP, 1991). Maintaining dose limits can ensure that no early effects occur; these are expected to be accurately understood. As late effects can result from changes in a very small 

number of cells, statistical fluctuations can be large and some level of risk is incurred even at low doses. Referring to them as “stochastic” effects recognizes the predominance of statistical effects in their manifestation. 

In recommendations by the NAS in 1967 (NRC, 1967), it was noted that radiation protection in human 

space flight is philosophically distinct from the protection practices of terrestrial workers because of the highrisk nature of space missions. This report by the NAS from 1967 did not recommend “permissible doses” for 

space operations, noting the possibility that such limits may jeopardize the mission, but instead estimated what 

the likely effects would be for a given dose of radiation. 

In 1970, the NAS Space Science Board (NRC, 1970) recommended guidelines for career doses to be used by 

NASA for long-term mission design and human operations. At that time, NASA employed only male astronauts 

and the typical age of astronauts was 30 to 40 years. A “primary reference risk” was proposed that was equal to 

the natural probability of cancer over a period of 20 years following the radiation exposure (using the period from 

35 to 55 years of age); this was essentially a doubling dose. The estimated doubling dose of 382 rem (3.82 Sv), 

which ignored a dose-rate reduction factor, was rounded to 400 rem (4 Sv). The NAS panel noted that its recommendations were not risk limits but, rather, a reference risk, and that a higher risk could be considered for planetary missions or a lower level of risk for a possible space station mission (NRC, 1970). Ancillary reference 

risks were described to consider monthly, annual, and career exposure patterns. However, the NAS recommendations were implemented by NASA as dose limits that were used operationally for all missions until 1989. 

At the time of the 1970 NAS report, the major risk from radiation was believed to be leukemia. Since that 

time, the maturation of the data from the Japanese atomic-bomb survivors has led to estimates of higher levels 

of cancer risk for a given dose of radiation, including the observation that the risk of solid tumors following 

radiation exposure occurs with a higher probability than that of leukemias, although with a longer latency period 

before expression. Figure 4-5 illustrates the changing estimates of cancer risks for an average adult worker since 

1970. Together with the maturation of the atomic-bomb data, reevaluation of the dosimetry of the atomic-bomb 

survivors, scientific assessments of the dose response models, and dose-rate dependencies have contributed to 

the large increase in risk estimate over this time period (1970–1997). The possibility of future changes in risk 

estimates can, of course, not be safely predicted today; it is possible that such changes could potentially impact 

NASA mission operations. Thus, protection against uncertainties is an ancillary condition to the ALARA 

principle, suggesting that conservatism be exercised as workers approach dose limits. 

By the early 1980s, several major changes had occurred that led to the need for a new approach in defining 

dose limits for astronauts. At that time, NASA requested that the NCRP reevaluate the dose limits that were 

to be used for LEO operations. Considerations included the increases in estimates of radiation-induced cancer 

risks, the criteria for risk limits, and the role of the evolving makeup of the astronaut population from male test 

pilots to a larger, diverse population of astronauts (~100), including mission specialists, female astronauts, and 

career astronauts of higher ages who often participate in several missions. In 1989, NCRP Report No. 98 (NCRP, 

1998) recommended age- and gender-dependent career dose limits using a 3% increase in cancer mortality as a 

common risk limit. This limiting level of 3% excess cancer fatality risk was based on several criteria, including 

a comparison to dose limits for ground radiation workers and to rates of occupational death in less-safe industries. 

It was noted that astronauts face many other risks, and that an overly large radiation risk was not justified. It 

also should be noted that the average years of life loss from radiation-induced cancer death, which is about 15 

years for workers over age 40 years and 20 years for workers between age 20 and 40 years, is less than that of 

other occupational injuries. A comparison of radiation-induced cancer deaths to cancer fatalities in the U.S. 
Chapter 4 Human Health and Performance Risks of Space Exploration Missions 

136 Risk of Radiation Carcinogenesis 

population is also complex because of the smaller years of life loss in the general population, where most 

cancer deaths occur above age 70 years.

In the 1990s, the additional follow-up and evaluation of atomic-bomb survivor data led to further increases in 

the estimated cancer risk for a given dose of radiation. Recommendations from the NCRP (NCRP, 2000), while 

keeping the basic philosophy of risk limitation that had been in the earlier report, advocate significantly lower 

limits than those that were recommended in 1989 (NCRP, 1989). Table 4-9 provides examples of career radiation limits for a career duration of 10 years, with the doses assumed to be spread evenly over the career. The 

values from the previous report are also listed for comparison. Both of these reports specify that these limits 

do not apply to Exploration missions because of the large uncertainties in predicting the risks of late effects 

from heavy ions. 

Table 4-9. Career Dose Limits (in Sv) Corresponding to a 3% Excess Cancer Mortality for 10-year Careers 

as a Function of Age and Sex, as Recommended by the NCRP (NCRP, 1989; 2000)

Age, year NCRP Report No. 98 NCRP Report No. 132 

Male (Sv) Female (Sv) Male (Sv) Female (Sv) 

25 1.5 1.00 0.7 0.4 

35 2.5 1.75 1.0 0.6 

45 3.2 2.50 1.5 0.9 

55 4.0 3.00 3.0 1.7 

The NCRP Report No. 132 (NCRP, 2000) notes that the use of comparisons to fatalities in the less-safe industries that were advocated by the NCRP in 1989 were no longer viable because of the large improvements 

that had been made in ground-based occupational safety. Table 4-10, which shows an update to such a comparison, demonstrates that, indeed, the decreased rate of fatalities in the so-called less safe industries (e.g., mining, 

agriculture) would suggest a limit below the 3% fatality level today as compared to that in 1989. The most recent reviews of the acceptable levels of radiation risk for LEO, including that provided during a 1996 NCPR 

symposium (NCRP, 1997b) and the recent NCRP Report No. 132 on the LEO dose limits (NCRP, 2000), instead advocate that comparisons to career dose limits for ground-based workers be used. It is also widely 

Year

1965 1970 1975 1980 1985 1990 1995 2000

Estimate of % Excess 

Fatal Cancer per Sv

0

1

2

3

4

5

Average Adult Worker

Figure 4-5. Estimates of the risk per 

Sv delivered at low dose-rates for the 

average adult worker from 1970 to 1997. 
Human Health and Performance Risks of Space Exploration Missions Chapter 4 

Risk of Radiation Carcinogenesis 137

held that the social and scientific benefits of space flight continue to provide justification for the 3% risk 

level for astronauts who are participating in LEO missions. 

In comparison to the limits that have been set by NASA, the U.S. nuclear industry uses age-specific limits that 

are gender-averaged, which is of sufficient accuracy for the low doses received by nuclear workers. Here career 

limits are set at a total dose-equivalent that is equal to the individual’s age  0.01 Sv. It is estimated by the NCRP 

that ground workers who reach their dose limits would have a lifetime risk of about 3%, but note the difference 

in dose values corresponding to the limit is due to differences in how the radiation doses are accumulated over 

the worker’s career. The short-term (30-day and 1-year) dose limits set by NASA are several times higher than 

those of terrestrial workers because they are intended to prevent acute risks, while the annual dose limits of 50 

mSv (5 rem), which are followed by U.S. terrestrial radiation workers, control the accumulation of career doses. 

Table 4-10. Occupational Death Rates (National Safety Council) and Lifetime Risks for 40-year Careers for the 

Less-safe and Safe Industries

Occupation 

Deaths per 10,000 Workers 

per year 

Lifetime Risk (%) of 

Occupational Death 

1977 1987 2002 1977 1987 2002 

Agriculture 5.4 4.9 2.1 2.2 2.0 0.8 

Mining 6.3 3.8 2.9 2.5 1.5 1.2 

Construction 5.7 3.5 1.3 2.3 1.4 0.6 

Transportation 3.1 2.8 1.0 1.2 1.1 0.5 

Manufacturing 0.9 0.6 0.28 0.4 0.2 0.1 

Government 1.1 0.8 0.26 0.4 0.3 0.1 

All 1.4 1.0 0.36 0.6 0.4 0.2 

The exposures that are received by radiation workers in reactors, accelerators, hospitals, etc. rarely approach 

dose limits with the average annual exposure of 1 to 2 mSv, which is a factor of 25 below the annual exposure 

limit and significantly less than the average dose for a 6-month ISS mission (100 mSv). Similarly, transcontinental pilots, although they are not characterized as radiation workers in the U.S., receive an annual exposure 

of about 1 to 5 mSv, and enjoy long careers without approaching the exposure limits that are recommended for 

terrestrial workers in the U.S. Under these conditions, ground-based radiation workers are estimated to be well 

below the career limits, even if a 95% CL is applied. As space missions have been of relatively short duration in 

the past, thereby requiring minimal mitigation, the impact of dose limits when space programs actually approach 

such boundaries, including the application of the ALARA principle, has been unexplored. 

 Summary of Approaches for Setting Acceptable Levels of Risk 

The various approaches to setting acceptable levels of radiation risk are summarized below. 

1. Unlimited Radiation Risk: NASA management, the families or loved ones of astronauts, and taxpayers 

would find this approach unacceptable. 

2.Comparison to Occupational Fatalities in Less-safe Industries: The life-loss from attributable radiation 

cancer death is less than that from most other occupational deaths. At this time, this comparison would also 

be very restrictive on ISS operations because of continued improvements in ground-based occupational 

safety over the last 20 years.
Chapter 4 Human Health and Performance Risks of Space Exploration Missions 

138 Risk of Radiation Carcinogenesis 

3.Comparison to Cancer Rates in General Population: The number of years of life-loss from radiationinduced cancer deaths can be significantly larger than from cancer deaths in the general population, which 

often occur late in life (>age 70 years) and with significantly less numbers of years of life-loss.

4. Doubling Dose for 20 Years Following Exposure: Provides a roughly equivalent comparison based on 

life-loss from other occupational risks or background cancer fatalities during a worker’s career; however, 

this approach negates the role of mortality effects later in life.

5. Use of Ground-based Worker Limits: Provides a reference point equivalent to the standard that is set on 

Earth, and recognizes that astronauts face other risks. However, ground workers remain well below dose 

limits, and are largely exposed to low-LET radiation where the uncertainties of biological effects are much 

smaller than for space radiation. 

A more recent review of cancer and other radiation risks is provided by the NCRP Report No.153 (NCRP, 

2006). The stated purpose of this report is to identify and describe the information that is needed to make 

radiation protection recommendations for space missions beyond LEO. The report contains a comprehensive 

summary of the current body of evidence for radiation-induced health risks, and makes recommendations on 

areas requiring future experimentation. 

 Past space missions 

The radiation doses on past space missions have been well characterized using physical and biological 

dosimetry and radiation transport models (Cucinotta et al., 2001; 2003a; 2008). Phantom torso experiments 

have been performed on ISS and space shuttle (Badhwar et al., 2000; Yasuda et al., 2000; Cucinotta et al., 2008). 

Phantom torsos offer good evidence of the accuracy of the NASA radiation transport code, HZETRN (Wilson et 

al., 1995), nuclear interaction cross sections (Cucinotta et al., 2006). Organ dose and dose-equivalent predictions 

are shown to agree with measurements to within ±15% in most cases, as shown in Table 4-11(a) and (b) 

(Cucinotta et al., 2008). 

Biodosimetry, which has been performed on all ISS missions as well as for four astronauts on Mir missions, 

offers an alternative evaluation of organ dose-equivalents. Figure 4-6 shows results for the pre- and post-flight 

frequency of translocations, which are complex aberrations involving more than two chromosomes, and total 

exchanges. Total exchanges are increased post-flight over pre-flight values in all cases, and translocations increase in all ISS astronauts, but they did not increase for two astronauts: one who was returning from the Mir

space station, and one who was on a Hubble repair mission. To test whether the overall frequency of complex 

aberrations was increased by space radiation, Cucinotta et al. (2008) pooled results into two groups: all ISS 

data, and all ISS data plus results from other NASA missions. The relative frequencies for complex aberrations and translocations were shown to be highly significant (P<10-4) (Cucinotta et al., 2008). 

Figure 4-7 shows a summary of the crew doses for all NASA missions through the year 2007. The level of 

accuracy in effective dose determination and in the GCR environments suggests a high level of accuracy in 

predicting organ dose and dose-equivalencies for both lunar and Mars missions. The cancer projection model 

of NCRP Report No. 132 (NCRP, 2000), which can be applied to these effective doses, indicates REID values 

approaching 1% for many astronauts who have flown on ISS or the Russian space station Mir (Cucinotta et al., 

2001). 
Human Health and Performance Risks of Space Exploration Missions Chapter 4 

Risk of Radiation Carcinogenesis 139

Table 4-11(a). From Cucinotta et al. (2008): Comparison of Measured Organ Dose-equivalent for the STS-91 Mission by 

Yasuda et al. (2000) Using the Combined CR-39/TLD Method to HZETRN/QMSFRG Space Transport Model 

Tissue 

Organ Dose-equivalent, mSv 

Measured HZETRN/QMSFRG Difference (%) 

Skin 4.5 ± 0.05 4.7 4.4 

Thyroid 4.0 ± 0.21 4.0 0 

Bone surface 5.2 ± 0.22 4.0 –23.1 

Esophagus 3.4 ± 0.49 3.7 8.8 

Lung 4.4 ± 0.76 3.8 –13.6 

Stomach 4.3 ± 0.94 3.6 –16.3 

Liver 4.0 ± 0.51 3.7 –7.5 

Bone marrow 3.4 ± 0.40 3.9 14.7 

Colon 3.6 ± 0.42 3.9 8.3 

Bladder 3.6 ± 0.24 3.5 –2.8 

Gonad 4.7 ± 0.71 3.9 –17.0 

Chest 4.5 ± 0.11 4.5 0 

Remainder 4.0 ± 0.57 4.0 0 

Effective dose 4.1 ± 0.22 3.9 –4.9 

Table 4-11(b). From Cucinotta et al. (2008): Comparison of Small Active Dosimetry Data from the ISS Expedition-2 

Phantom Torso (July–August 2001) for Absolute Predictions for the HZETRN/QMSFRG Model. [Details on the 

measurement procedures are given in Badhwar et al. (2000)] 

Organ 

Dose from Trapped 

Radiation, mGy/d 

Dose from GCR, 

mGy/d 

Total Dose, 

mGy/d 

Difference 

(%) 

Expt. Model Expt. Model Expt. Model 

Brain 0.051 0.066 0.076 0.077 0.127 0.143 13.3 

Thyroid 0.062 0.072 0.074 0.077 0.136 0.148 9.4 

Heart 0.054 0.061 0.075 0.076 0.129 0.137 6.7 

Stomach 0.050 0.057 0.076 0.077 0.126 0.133 5.5 

Colon 0.055 0.056 0.073 0.076 0.128 0.131 2.5 

 
Chapter 4 Human Health and Performance Risks of Space Exploration Missions 

140 Risk of Radiation Carcinogenesis 

Figure 4-6. From Cucinotta et al. (2008): The frequency of translocations, complex aberrations, or total chromosome 

exchanges that is measured in each astronaut’s blood lymphocytes before and after their respective space missions 

on ISS, Mir, or the space shuttle. An increase in total exchanges was observed for all astronauts. Translocations (22 

of 24) and complex aberrations (17 of 24) increased in the majority of astronauts.

 

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Translocations

0.000

0.005

0.010

0.015

0.020

0.025

0.030

Pre-Flight

Post-Flight

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Complex Aberrations

0.000

0.002

0.004

0.006

Pre-Flight

Post-Flight

Astronaut

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Total Exchanges

0.000

0.005

0.010

0.015

0.020

0.025

0.030

0.035

Pre-Flight

Post-Flight
Human Health and Performance Risks of Space Exploration Missions Chapter 4 

Risk of Radiation Carcinogenesis 141

Figure 4-7. Summary of mission personnel dosimetry from all past NASA crews (Cucinotta et 

al., 2008). Effective dose and population average biological dose-equivalent for astronauts on 

all NASA space missions, including Mercury, Gemini, Apollo, Skylab, Apollo-Soyuz, space 

shuttle, shuttle-Mir, and ISS missions. 

 Radiobiology evidence for protons and HZE nuclei 

Studies with protons and HZE nuclei of RBEs for molecular, cellular, and tissue endpoints, including tumor 

induction, document the higher risk for space radiation components (NAS, 1996; NCRP, 2006; Cucinotta and 

Durante, 2006). This evidence must be extrapolated to the chronic conditions that are found in space and from 

the mono-energetic beams that are used at the NSRL and other accelerators to the complex mixed radiation types 

that are in space. Sufficient proof that experimental models represent cancer processes in humans, including estimating the effectiveness of shielding and biological countermeasures, must be obtained for high-risk missions 

where acceptable levels of cancer risks are approached or, perhaps, exceeded. Evidence and progress in these 

areas is described next. 

 Cancer Induction by Space Radiation 

A necessary step for improving space radiation cancer risk assessment is to perform studies on the molecular 

pathways that are causative of cancer initiation and progression, and to extend these studies to learn how such 

pathways can be disrupted by HZE ions, including both genetic and epigenetic modifications that are noted as 

the hallmarks of cancer (figure 4-8). The goal of this research is to establish a more mechanistic approach to 

estimating risk and to answer questions, including whether HZE effects can be scaled from those of gamma 

rays, whether risk is linear with low dose-rate, and how individual radiation sensitivity impacts the risks for 

astronauts, a population that is selected for many factors related to excellence in health. 

Astronaut, i

0 100 200 300 400 500 600 700 800

Mission Dose

0.1

1

10

100

1000

Badge Dose, mGy

Effective Dose, mSv

Biodosimetry, mGy-Eq Skylab, Mir and ISS

Mercury

Apollo and Shuttle

Gemini

Hubble Missions
Chapter 4 Human Health and Performance Risks of Space Exploration Missions 

142 Risk of Radiation Carcinogenesis 

Figure 4-8. The hallmarks of cancer (Hanahan and Weinberg, 2000) and possible mechanisms of 

radiation damage that lead to these changes observed in all human tumors. 

 The Initial Biological Events 

Energy deposition by HZE ions is highly heterogeneous with a localized contribution along the trajectory 

of each particle and lateral diffusion of energetic electrons (delta rays) that are many microns from the ions 

path (Goodhead, 1994; Cucinotta et al., 2000b). These particles are, therefore, characterized by a high LET; 

however, they contain a low-LET component due to the high-energy electrons that are ejected by ions as they 

traverse tissue. Biophysical models have shown that the energy deposition events by high-LET radiation 

produce differential DNA lesions, including complex DNA breaks, and that there are qualitative differences 

between high- and low-LET radiation, in both the induction and the repair of DNA damage (Prise et al., 1998; 

Sutherland et al., 2000; Rydberg et al., 2005). The number of DNA single-strand breaks (SSBs) and DSBs that 

are produced by radiation varies little with radiation type; however, for high-LET radiation, a higher fraction 

of DNA damages are complex; i.e., clusters containing mixtures of two or more of the various types of damages (SSB, DSB, etc.) within a localized region of DNA. Complex damage is uncommon for endogenous 

damage or low-LET radiation, and has been associated with the increased RBE of densely ionizing radiation. 

The repair of DSB is known to occur through direct end-joining and homologous recombination processes. 

Indications are that (1) for high-LET radiation, where complex DSBs occur with high frequency, little repair 

occurs, leading to cell death; or (2) the mis-rejoining of unrepairable ends with other radiation-induced DSB 

leads to large DNA deletions and chromosome aberrations. While the high effectiveness in cell killing provides the rationale for heavy-ion cancer therapy (hadrontherapy), residual damage in surviving cells is of 

concern for carcinogenesis. 

Chromosome damage and mutation

Heavy charged particles are very effective at producing chromosomal exchanges with RBE values exceeding 

30 in interphase (as visualized using premature chromosome condensation) and 10 at the first post-irradiation 

mitosis for energetic Fe-ions (George et al., 2003). The detailed RBE vs. LET relationship that was found 

for total exchanges is similar to that of earlier studies of mutation (Kiefer et al., 1994; Kiefer, 2002) and in 
Human Health and Performance Risks of Space Exploration Missions Chapter 4 

Risk of Radiation Carcinogenesis 143

vitro neoplastic transformation (Yang et al., 1985). For all of these endpoints, RBE peaks at around 100 to 

200 keV/μm before it decreases at very high-LET. However, the quality of chromosome damage is different 

when heavy ions are compared to sparsely ionizing radiation. Large differences in gene expression are observed between X rays and HZE ions, thus reflecting differences in damage response pathways (Ding et al., 

2005; Chang et al., 2005). Qualitative differences in the type of gene mutations have also been reported 

(Kronenberg, 1994; Kronenberg et al., 1995). Novel multicolor fluorescence painting techniques of human 

chromosomes have clearly demonstrated that high-LET α-particles and Fe-ions induce many more complex 

types of chromosomal exchanges in human cells than low-LET radiation. Most of these complex chromosomal 

rearrangements will ultimately lead to cell death. In fact, only a small fraction of the initial damage is transmitted in mice 2 to 4 months after the mice have been exposed to energetic Fe-ions. A low RBE for the induction of late chromosomal damage has also been measured in the progeny of human lymphocytes that 

were exposed in vitro to energetic Fe-ions, with the interesting exception of terminal deletions, which occurred with much higher frequency in the progeny of cells that were exposed to heavy ions compared to 

gamma rays (Durante et al., 2002). 

Genomic instability

Genomic instability has been observed both in vitro and in vivo in the progeny of cells that are irradiated 

with heavy ions in several model systems (NCRP, 1997a). The presence of chromosomes that are lacking 

telomeres in the progeny of cells that were exposed to heavy ions is particularly interesting. Sabatier et al.

(1992; 2005) found that rearrangements involving telomere regions are associated with chromosomal instability in human fibroblasts that occur many generations after exposure to accelerated heavy ions. Telomere 

dysfunction plays a crucial role in initiating or sustaining genomic instability, which is a major step in cancer 

progression. Heavy-ion-induced effects on telomere stability have also been studied using siRNA (small interfering ribonucleic acid) knockdown for components of DNA-dependent protein kinase (DNA-PK) in human 

lymphoblasts. Differential results were found for gamma rays and HZE nuclei, with iron nuclei being much 

more effective in producing DSB-telomere fusions after knockdown of DNA-PK (Zhang et al., 2005). Cells 

containing telomere-deficient chromosomes will either senesce or undergo breakage-fusion-bridge (B/F/B) 

cycles, thereby promoting genetic instability. The fate of normal cells that contain a single terminal deletion 

is unknown, but it has been shown that the loss of a single telomere in cancer cells can result in instability 

in multiple chromosomes (Feldser et al., 2003; Maser and DePinho, 2002). These recent results suggest that 

telomere instability could be an important early event in the pathway to cancer induction by HZE nuclei. 

Cancer and tissue effects

Animal studies generally demonstrate that HZE nuclei have higher carcinogenic effectiveness than lowLET radiation. The number of studies of animal carcinogenesis with HZE nuclei is extremely limited, as 

summarized in Table 4-12. Relative biological effectiveness factors comparing gamma rays to HZE ions 

were measured in mice or rats for tumors of the skin (Burns et al., 1993) and of the Harderian (Fry et al., 

1985; Alpen et al., 1993) or mammary gland (Dicello et al., 2004), reaching values as high as 25 to 50 at 

low doses. However, the risk and detriment of cancer will not be fully characterized until the relationship 

between radiation quality and latency, where tumors appear earlier after high-LET irradiation, is adequately 

described. The earlier latency and increasing effectiveness that is found with HZE ions that are similar to 

those in earlier studies with neutrons (Ullrich, 1984; Fry and Storer, 1987), together with the lack of response 

of gamma rays that is seen in many low-dose studies, suggests that the scaling concepts that are used in 

current risk assessment approaches are unable to describe important qualitative effects, and that relative 

biological effectiveness factors may, in principle, be indefinable or a faulty concept. 
Chapter 4 Human Health and Performance Risks of Space Exploration Missions 

144 Risk of Radiation Carcinogenesis 

Table 4-12. Tumor Induction Studies with HZE Nuclei 

Tumor Model End-point HZE type Reference 

Mice (B6CF1) Life-shortening C, Ar, Fe Ainsworth (1986) 

Mice (B6CF1) Harderian gland He, C, Ar, Fe Fry et al. (1985) 

Mice (B6CF1) Harderian gland He, Ne, Fe, Nb Alpen et al. (1993) 

Rat (Sprague-Dawley) Skin tumors Ne, Ar, Fe Burns (1992) 

Rat (Sprague-Dawley) Mammary tumors Fe Dicello et al. (2004) 

Mice (carcinoma-bearing 

animal (CBA)) 

Leukemia, liver tumors Fe, p, Si Ullrich, in preparation 

Recent studies have debated the relative importance of DNA damage and mutation or extracellular matrix 

remodeling and other non-targeted effects as initiators of carcinogenesis (Barcellos-Hoff et al., 2005). Tissue 

effects that are independent of DNA damage and that have been associated with cancer initiation or progression include genomic instability (Park et al., 2003), extracellular matrix remodeling, persistent inflammation, 

and oxidative damage (Mothersill and Seymour, 2004). Other studies are exploring possible relationships 

between radiation and the activation of dormant tumors and the modulation of angiogenesis (Folkman et 

al., 1989). 

So-called bystander or non-targeted effects may have enormous consequences for space exploration. Nontargeted effects may lead to a supra-linear dose-response curve at low doses, perhaps reducing the effectiveness of spacecraft shielding; but it may also provide protection by removing damaged cells from the organism. 

Both effects challenge the conventional linear no-threshold risk model assumption, which is currently adopted 

for radioprotection on Earth and in space. These effects also suggest important targets for biological countermeasures that are likely to be more effective than are countermeasures that target DNA damage. 

Results in tissues suggest that differences in biological response between high and low LET differ 

depending on the model context that is considered (i.e., 2D vs. 3D vs. animal). As a result of the many 

types of particles, energies, and doses of interest that are in space, extensive animal experimentation has 

been prohibited by costs in the past. More recently, however, studies in 3D human coculture are proving to 

be an effective method with which to study cancer risks in a more realistic context (Barcellos-Hoff et al., 

2005; Riballo et al., 2004). 

 Models of Cancer Risks and Uncertainties 

 Life-table methodology 

The double-detriment life-table is the approach that is recommended by the NCRP (NCRP, 2000) to estimate 

radiation cancer mortality risks. In this approach, the age-specific mortality of a population is followed over its 

entire life span with competing risks from radiation and all other causes of death described (Bunger et al., 1981). 

For a homogeneous population receiving an effective dose E at age aE, the probability of dying in the age-interval 

from a to a+1 is described by the background mortality-rate for all causes of death, M(a), and the radiation 

cancer mortality rate, m(E,aE,a), as

() ( , ,) (, ,) 1

1 [ ( ) ( , , )]

2

E

E

E

Ma mEa a

qEa a

Ma mEa a

 

 

 (7) 
Human Health and Performance Risks of Space Exploration Missions Chapter 4 

Risk of Radiation Carcinogenesis 145

The survival probability to live to age, a, following an exposure, E, at age, aE, is 

1

( , , ) [1 ( , , )]

E

a

E E

u a

SEa a qEa u





   (8) 

The excess lifetime risk (ELR), which is the increased probability that an exposed individual will die from 

cancer, is defined by the difference in the conditional survival probabilities for the exposed and the unexposed 

groups as

[ ( ) ( , , )] ( , , ) ( ) (0, , )

E E

EE E

aa aa

ELR M a m E a a S E a a M a S a a

 

 

    (9) 

A minimum latency-time of 10 years is often used for low-LET radiation (NCRP, 2000); however, alternative assumptions should be considered for high-LET radiation. The REID, which is the lifetime risk that an 

individual in the population will die from a cancer that is caused by his or her radiation exposure, is defined by 

(, ,)(, ,)

E

E E

a a

REID m E a a S E a a





  (10) 

In general, the value of the REID exceeds that of the ELR by about 10% to 20%. Vaeth and Pierce (1990) 

have discussed cases in which the ELR is ill-defined and suggested that the REID is the preferred quantity for 

radiation protection. The loss of life-expectancy among exposure-induced-deaths (LLE-REID) is defined by 

(Vaeth and Pierce, 1990) 

LLE

LLE REID

REID   (11) 

where the average loss of life-expectancy, LLE, in the population is defined by 

 

(0, , ) ( , , )

E E

E E

aa aa

LLE S a a S E a a

 

 

    (12) 

 Radiation Carcinogenesis Mortality Rate 

For projecting lifetime cancer fatality risks, an age- and gender-dependent mortality rate per unit dose, 

which is estimated for acute gamma-ray exposures, is multiplied by the radiation quality factor and reduced 

by the DDREF (NCRP, 2000). The additivity of effects of each component in a radiation field is assumed. 

Radiation mortality rates are largely modeled using the Japanese atomic-bomb survivor data. For transferring 

risks from the Japanese to the U.S. population, two models are often considered. A multiplicative transfer model 

assumes that radiation risks are proportional to spontaneous or background cancer risks. The additive transfer 

model assumes that radiation risk acts independently of other cancer risks. However, the NCRP (NCRP, 2000) 

recommends that a mixture model be used that contains fractional contributions from the multiplicative risk 

model or additive risk model. The radiation mortality rate is 
Chapter 4 Human Health and Performance Risks of Space Exploration Missions 

146 Risk of Radiation Carcinogenesis 

() ()

( , , ) [ ( , ) ( ) (1 ) ( , )] L

E Ec E

QLFLL

m E a a vERR a a M a v EAR a a

DDREF

 



 (13) 

where the ERR and EAR are the excess relative risk and excess additive risk per Sievert, respectively, Mc(a) is 

the gender- and age-specific cancer mortality rate in the U.S. population, F is the tissue-weighted fluence, and 

L is the LET. In Eq(13), ν is the fractional division between the assumption of the multiplicative and additive 

risk transfer models. For solid-cancer, it is assumed that ν=1/2; for leukemia, it is assumed that ν=0. 

 Uncertainties in the Projection Model 

Equation (13) consists of a product of several factors: the ERR or EAR, the background cancer rates, Mc, 

the effective dose represented by the physical dose, F(L), times the radiation quality factor, Q(L), and the 

dose and dose-rate reduction factor, DDREF. The limiting behavior of the addition of many random variables 

is well known as the normal distribution. In contrast, the limiting behavior of the multiplication of many random 

factors will be a log-normal distribution. Equation (7) assumes that each multiplicative factor is independent. 

This assumption may not be strictly valid, however, because of the possible correlations between factors or 

non-additivity of different radiation components, since the cells will be traversed by multiple particles and 

delta rays that are produced by ions passing through adjacent cell layers (Cucinotta et al., 1998b). As the risk 

for longer-duration missions exceeds a few percent, the upper 95% C.I.s may exceed 10%. In such cases, the 

Monte-Carlo sampling of mortality rates to estimate uncertainty bands is insufficient, and the expression for 

the REID that is given by Eq(10) must be used because of competing risks from other causes of death that 

will reduce the likelihood of very large radiation risks. Therefore, in the sampling approaches that are described 

below, trials are accumulated for the REID rather than the mortality rate. A criteria that is used to formulate 

probability distribution functions (PDFs) for various factors is to ensure that the PDFs are peaked at the values 

that are recommended by the NCRP (NCRP, 2000), such as the DDREF and Q, or in the current physics 

models of radiation environments and transport that are used in mission projections or spacecraft designs. 

We next discuss the uncertainties in the projection model. 

 Uncertainties in Low-LET Epidemiology Data 

For Monte-Carlo sampling purposes, the low-LET mortality-rate per Sievert, ml, is written 

0 (, ,) (, ,) x DsT B

l x

Dr

m E a a x xxx

m Ea a

DDREF x

 (14) 

where m0 is the baseline mortality rate per Sievert (see Eq(13)) and the xα are quantiles (random variables) 

whose values are sampled from associated PDFs, P(xα). Note that the DDREF applies only to the solid cancer 

risk and not to the leukemia risk under the stated assumptions. The NCRP Report No. 126 (NCRP, 1997a) 

defines the following subjective PDFs, P(xα), for each factor that contributes to the acute low-LET risk 

projection: 

1. Pdosimetry represents the random and systematic errors in the estimation of the doses received by atomicbomb blast survivors. It is assumed as a normally distributed PDF for bias correction of random and 

systematic errors in the dosimetry (DS86) with mean 0.84 and standard deviation 0.11. 

2. Pstatistical represents the distribution in uncertainty in the point estimate of the risk coefficient, r0. It is 

assumed as a normally distributed PDF with a mean of 1 and a standard deviation of 0.15. 
Human Health and Performance Risks of Space Exploration Missions Chapter 4 

Risk of Radiation Carcinogenesis 147

3. Pbias represents any bias resulting for over- or under-reporting cancer deaths. Pbias is assumed as a 

normal distribution with a most probable value of 1.1 and a 90% C.I. from 1.02 to 1.18 corresponding 

to a standard deviation of 0.05. 

4. Ptransfer represents the uncertainty in the transfer of cancer risk following radiation exposure from the 

Japanese population to the U.S. population. Both additive and relative risk models were considered by 

NCRP Report No. 126 (NCPR, 1997a) in assessing the uncertainties in such transfer. Ptransfer is lognormal with a mean of 1 and a standard deviation of 0.26 (geometric standard deviation (GSD)=1.3). 

5. PDr represents the uncertainty in the knowledge of the extrapolation of risks to low dose and 

dose-rates, which are embodied in the DDREF. The NCRP assumes PDr to be a truncated triangle 

distribution starting at 1 and ending at 5 with a peak at 2 and a relative value of 1/4 or 1/2 at 1 or 5, 

respectively, compared to the peak values for the DDREF at 2. This PDF is used to scale the low-LET 

risk coefficient (mortality rates) in our estimates for space radiation. 

The NCRP also considered a PDF for bias correction to project cancer risks over a lifetime. It is ignored 

herein because the astronaut population is generally over age 30 years and the Japanese data are now complete for these ages. We also ignore the assumed “unknown uncertainties” from NCRP Report No. 126 

(NCRP, 1997a). 

 Uncertainties due to Dose-Rate and Protraction Effects for Ions 

For a low dose-rate and protracted proton and HZE radiation exposure of more than a few months, new 

biological factors may influence risk assessments, including redistribution in the cell cycle, repopulation, or 

promotional effects, especially when particle fluences are sufficiently large to lead to multiple hits of target 

cells or surrounding cells and tissue environments. Not only are there no human data for protons and HZE ions, 

there are also very little experimental data at low dose-rates for these particles. Confidence in using radioepidemiological data for acute (atomic-bomb survivors) or fractionated (patient) data is decreased when it is 

applied to protracted exposure. Experimental data for protracted proton or heavy ion irradiation in experimental 

models of carcinogenesis are almost nonexistent. Burns et al. (1994) found that split doses of argon ions that 

were separated by a few hours up to 1 day increased the risk of skin cancer in rats. Alpen et al. (1994) found 

that for Harderian gland tumors in mice, using seven 2-week fractions of 0.07 Gy of iron increased risk by 50% 

as compared to a single acute dose of 0.4 Gy. A study of chromosomal aberrations in human lymphocytes 

(George et al., 2001), for both acute and low dose-rates (0.08 Gy/hr) with 250 MeV protons, showed less 

sparring than was found for gamma rays. The Skyhook study (Ainsworth et al. (1986)) considered lifeshortening in mice by comparing single acute with weekly fractions of several ions, but the results were 

unclear with regards to any increase or decrease in risk. 

A good number of studies for cancer induction or life-shortening in mice exist for gamma rays and neutrons; 

these studies show both sparring effects for gamma rays and that neutron effects may be increased due to 

protraction under certain conditions in some tissues (Ullrich, 1984; NCRP, 1990). Important questions related 

to the differences in life span, cell turnover rates, or the mechanisms of initiation or promotion in humans and 

mice make estimates of the effects of protraction on risk difficult. If protraction effects do increase the risk from 

high-LET radiation, such effects would be more important for a Mars mission than for the shorter lunar missions. In space, each cell will be traversed about every 2 to 3 days by a proton or delta ray that is produced by 

ions in adjacent cells, and with a decreasing frequency of from weeks to months as the charge of the HZE 

nuclei increases (Cucinotta et al., 1998b). Studies of mixed-fields of protons and HZE ions are needed to 

understand the uncertainties in dose-rate and protraction effects from space radiation. Uncertainties that 
Chapter 4 Human Health and Performance Risks of Space Exploration Missions 

148 Risk of Radiation Carcinogenesis 

are related to radiation quality, dose-rate, and protraction could lead to correlations that will be difficult 

to describe when based on limited experimental data. Methods to treat correlation effects will be needed 

when the data on protraction effects become available. 

 Radiation Quality and Latency or Temporal Patterns of Risk 

An additional radiation quality uncertainty is introduced by the scaling assumption that is used in Eq(13) 

because the time dependence for low- and high-LET radiation is assumed to be identical. Data on tumors or 

genomic instability in mice with neutrons (Ullrich, 1984; Ulrich and Ponnaiya; NCRP, 1990) and the studies 

of rat or mammary carcinogenesis with HZE nuclei (Burns et al., 1994; Dicello et al., 2004) suggest that the 

latency time is appreciably reduced for high-LET radiation compared to low-LET radiation. Sparse data are 

available to estimate the impact of these differences on uncertainties. A radiation quality-dependent latency is 

more important in the additive transfer model than in the multiplicative transfer model, especially at younger 

ages of exposure. We ignore these uncertainties, however, and replace the 10-year minima latency assumption 

that is made for low LET with the step-in latency model (Pierce et al., 1996) that is used for the leukemia risk. 

The effects of these assumptions will need to be addressed when data and knowledge on underlying mechanisms become available. 

 Uncertainties in Quality Factors 

Radiation quality factors represent the largest uncertainty when estimating space radiation cancer risks. Past 

reviews on the relative biological effectiveness of high-LET radiation include International Commission on 

Radiation Units (ICRU) Report No. 40 (1986), NCRP Report No. 104 (1990), and, more recently, ICRP Report 

No. 92 (2003). The practice of assigning radiation quality factors that are followed by committees considers an 

average of the RBE factors at low doses (RBEmax) for the most relevant experimental endpoints. Uncertainties 

in the assignment of RBEs for protons and heavy ions arise for several reasons, including sparseness of data 

for tumorigenesis in animal models, surrogate tissue, or cellular endpoints; variability in reference radiation 

and doses and dose-rates employed; and lack of data over the LET range of interest. Linearity at low dose or 

dose-rates for the reference radiation or ions also is often not sufficiently established in experiments. Statistical limitations frequently hinder studies at the low dose-rates of interest for space radiation protection. For 

high-LET radiation, a turnover or bending that is found in the dose response for tumor induction and neoplastic transformation is observed at moderate doses, thus presenting further uncertainties in estimating the 

effectiveness of high-LET radiation at low dose-rates. 

Figure 4-9 provides representative examples of the ratio of RBEmax to Q for mouse tumors, cell transformation 

or mutations, or cytogenetic endpoints. The ratio is often two to three times higher or lower than unity, which 

indicates the expected deviation from Q in available data. 
Human Health and Performance Risks of Space Exploration Missions Chapter 4 

Risk of Radiation Carcinogenesis 149

HPBL – human peripheral blood leukocyte; HPRT – hypoxanthine-guanine phosphoribosyltransferase; 

SHE – Syrian hamster embryo; HF – human fibroblast 

Figure 4-9. Comparison of ratio of RBEmax to Q for several endpoints found with proton, α-particle, 

and heavy ion irradiations (reference experiments listed in Table 4-1).

Table 4-13 shows the LET values at the maximum RBE that was found in past studies that were selected from 

experiments in which more than five ions were employed. Large deviations from the Q peak at 100 keV/μm 

are observed in these experiments, with a range from about 50 to 190 keV/μm for the peak. These data are 

largely derived from the facilities at Berkeley, Calif., Darmstadt, Germany, Chiba, Japan, and the Alternating 

Gradient Synchrotron (AGS), Brookhaven National Laboratory, Upton, N.Y. The number of past studies and 

endpoints that were used are limited if they are viewed as surrogate endpoints for human carcinogenesis. Additional data for more appropriate endpoints should become available in the next few years from the NSRL. Track 

structure models suggest that each ion species would have distinct RBE curves that are of similar shape, with 

curves for lower-charge ions peaking at a lower LET than for higher-charged ions (Katz et al., 1971; Cucinotta 

et al., 1996; Nikjoo et al., 1999). Furthermore, above about 1 MeV/u, lower-charged ions have a higher biological effectiveness than higher-charged ions of identical LET. Based on track structure models, we expect that 

the data sets that consider only a few ions are insufficient for defining the radiation quality dependence of Q. 

LET response curves also are predicted to depend on the target size (e.g., for gene or chromosome region) 

and intrinsic radiation sensitivity, which includes competition with cell death. These factors likely vary 

between tissues. 

LET, keV/m

1 10 100 1000

RBEmax/Q

0

1

2

3

4

5

HPBL Total Exchanges

HPRT Mutations (V79 Cells)

Transformation (SHE cells)

Isochromatid Breaks (HF cells)

H. Gland Tumors

Rat Skin Cancer

RBEmax = Q
Chapter 4 Human Health and Performance Risks of Space Exploration Missions 

150 Risk of Radiation Carcinogenesis 

Table 4-13. Approximate LET in which Maximum RBE Was Found in Biological Experiments

Biological System Endpoint LET at Peak 

RBE, keV/μm 

LET range (no. of 

ions studied) Reference 

Human TK6 

lymphoblasts cells 

TK (triose-kinase) 

mutants 

60 32–190 (6) Kronenberg (1994) 

Human TK6 

lymphoblasts cells 

HPRT mutants 60 32–190 (6) Kronenberg (1994) 

Human lung 

fibroblasts 

HPRT mutants 90 20–470 (9) Cox and Masson (1979) 

Human skin 

fibroblasts 

HPRT mutants 150 25–920 (7) Tsuoboi et al. (1992) 

V79 Chinese hamster 

cells 

HPRT mutants 90 10–2,000 (16) Kiefer et al. (1994); 

Belli et al. (1993) 

Caenorhabditis 

elegans 

Recessive lethal 

mutations 

190 0.55–1,110 (14) Nelson et al. (1989) 

Human lymphocyte 

cells 

Chromosomal 

exchanges 

147 0.4–1,000 (10) George et al. (2003) 

Human fibroblast 

cells 

Chromatid breaks 80–185 13-440 (6) Kawata et al. (2001) 

C3H10T1/2 mouse 

cells 

Transformation 140 10–2,000 (10) Yang et al. (1989) 

C3H10T1/2 mouse 

cells 

Transformation 90 20–200 (10) Miller et al. (1995) 

SHE cells Transformation 90 20–200 (8) Martin et al. (1995) 

Mouse (B6CF1) H. gland tumors 185* 2–650 (6) Fry et al. (1985) 

Mouse (B6CF1) H. gland tumors 193 0.4–1,000 (7) Alpen et al. (1993) 

Mouse (CB6F1) Days life lost 52* 50–500 (6) Ainsworth (1986) 

*Track-segment or spread-out Bragg peak (SOBP) irradiations. 

To account for the uncertainties in quality factors, Cucinotta et al (2006) recommend a trial function that has 

a shape that is guided by both experimental data and biophysical models, and a sample from distributions of 

parameters that enter into the functional form. The Q(L) trial function is defined as 

0

0

1

( )

/

trial m

p

m

L L

Q L AL B L L L

CL L L



  













(15)

The values of L0, Lm, and p, and the maximum value, Qm(Lm), which are derived from the PDFs, are described 

below. Using Eq(15), one can solve for the values of the constants A, B, and C. Often-discussed issues on the 

definition of Q(L), as embodied in Eq(15), are the value of the slope p that controls the decrease in Q(L) above 

a maximum, the maximum value of Q(L), the LET where the maximum occurs, Lm, and the minimum LET 

where Q(L) rises above unity, L0 . We note that the ICRP-60 (ICRP 1991) Q-function corresponds to L0=10 

keV/μm, Lm=100 keV/μm, p = 0.5, and Qm=30 such that A=0.32, B=2.2, C=300, and the ICRP-26 Q-function, 

L0=3.5 keV/μm, Lm=172.5 keV/μm, p = 0, and Qm = 20. 
Human Health and Performance Risks of Space Exploration Missions Chapter 4 

Risk of Radiation Carcinogenesis 151

The parameter samplings are based on the following assumptions for PDFs: 

a. L0: equal probability between 5 and 10 keV/μm, and decreasing to zero at 1 keV/μm, or above 

15 keV/μm. 

b. Lm: equal probability for LET values between 75 and 150 keV/μm, and decreases to zero at 50 keV/μm 

or above 250 keV/μ m. 

c. p: equal probability between p = 1/2 and 1, and decreasing to zero at p<0 or p>2. 

d. Qm: log-normal distribution with a mean value of 30 and a geometric standard deviation (GSD) of 1.8. 

Figure 4-10 shows examples of trial Q(L) functions that contribute in the sampling procedures, and figure 

4-11 shows the resulting average Q(L) and 95% C.I. after 20,000 trials. The resulting range is smaller than in 

the previous Cucinotta et al. report (2001b); however, it should be a reasonable estimate when the effects of 

dose protraction are not included in the uncertainty analysis. 

LET, keV/m

1 10 100 1000

Qj(L)

0

20

40

60

80

100

 Uncertainties in Physics: Environments and Transport Codes 

Space dosimetry and radiation transport codes have been studied extensively in the past, and although 

no major scientific questions led to errors in the assessment of space radiation environments, there are 

uncertainties due to the limitations in the dosimetry that was flown on past space missions. For application 

of computational models, the level of detail that has been used in transport code comparisons is often limited, 

LET, keV/m

1 10 100 1000

Q(L)

0

20

40

60

80

100

Figure 4-11. Average quality factor (circles) and 

95% C.I.’s vs. LET that is derived from MonteCarlo sampling over trial function of Eq(15).

Figure 4-10. Examples of trial quality factor 

functions used in uncertainty calculations. A 

distinct curve is generated for each trial. 
Chapter 4 Human Health and Performance Risks of Space Exploration Missions 

152 Risk of Radiation Carcinogenesis 

with common simplifications including the use of an aluminum-equivalent shielding approximation, simplified geometries, and no description of orientation effects. Approaches to assess errors in space dosimetry 

include the inter-comparison of different dosimetry on the same missions and to the results of space radiation 

transport models. Although statistical errors in the assessment of physical doses are quite small (<5%), the 

inter-comparisons between laboratories have shown differences on the order of 10% for absorbed dose (Badhwar, 

1997). Comparisons of transport calculations to measurements of LET spectra or dose equivalencies should 

consider the response functions of different detector types to charged particles or neutrons (Nikjoo et al., 2002). 

Commonly used detectors are TEPCs, silicon detectors, and CR-39 plastic track detectors. Good agreement 

has been found in the limited number of comparisons that have been made (e.g., Badhwar and Cucinotta, 

2000; Kim et al., 2003; Shinn et al., 1998), especially when detector response functions are represented in 

the comparisons. 

Models of the GCR environment rely on the large number of space flight and balloon measurements that 

have been made, and apply the diffusion theory of Parker (1965) to describe the modulation of the GCR over 

the solar cycle. The root mean square error for GCR environmental models is less than 7% for the major GCR 

elements and less than 12% for most minor elements (Badhwar and O’Neill, 1994a; Badhwar et al., 1994b; 

O’Neill, 2005). Data from the advance composition explorer (ACE) are further improving these models 

(figure 4-12). 

Figure 4-12. From O’Neill (2005) Differential flux energy spectra near solar minimum 

and maximum for two of the more-abundant elements, typical of the better fits. The symbols 

represent the measured values that are described in O’Neill (2005) and lines in the BadhwarO’Neill GCR model. 

The isotopic composition of the GCR is also represented in the transport codes (Cucinotta et al., 2003b) that 

are used in risk calculations. Solar particle event spectra vary from event to event, and there is no method that 

is available to predict the fluence, energy spectra, or dose-rates of a future event. In this chapter, we discuss 

calculations for the large SPE of August 1972. Transport codes rely on databases for nuclear interaction cross 

sections, including inclusive single differential in energy or total fragment production cross sections for projectile Flux, #/m**2 sr s MeV/n

Energy, MeV/n

10 100 1000 10000 100000

1E-006

1E-005

0.0001

0.001

0.01

CARBON

IRON

+ & X - HEAO-3-C2

5% RMS

6% RMS
Human Health and Performance Risks of Space Exploration Missions Chapter 4 

Risk of Radiation Carcinogenesis 153

fragments, as well as double differential in energy and angle for lighter mass secondaries (i.e., neutrons, Hions and He-ions, and mesons). Cross-section data are sparse for some projection-target combinations and in 

the number of energies, especially above 1,000 MeV/u. Three-dimensional aspects of transport from angular 

scattering, which is a small correction for high-energy ions, are expected to be an important correction for 

neutrons and other light mass ions. Computer codes that use multigroup methods or Monte-Carlo simulations 

to describe angular effects on neutron transport have been developed for GCR shielding applications. The MonteCarlo codes are limited by the computational times that are needed to describe spacecraft with thousands of 

parts, and the multigroup methods are limited by the ability to describe complex geometries. However, because 

flight measurements and the results of the HZETRN code (Wilson et al., 1995) using the Badhwar-O’Neill 

GCR input spectra (Badhwar and O’Neill, 1994) and QMSFRG (quantum multiple scattering fragmentation) 

nuclear interaction data base (Cucinotta et al., 2003a) are in good agreement, it is unclear whether such developments will have an important impact on risk assessment. 

Differences between transport models and flight dosimetry that account for the response of the detector to 

different radiation components are generally small, with absolute differences within 10% for the GCR dose 

and 20% for the GCR dose-equivalent (Badhwar, 1997; Badhwar and Cucinotta, 2000 Cucinotta et al., 2000b; 

Cucinotta et al., 2003b). However, measurements of dose or dose-equivalent may not provide sufficient information on possible errors in predicting the LET spectra because compensating errors can occur. Neutron 

spectra also are difficult to assess within complicated spacecraft and tissue geometries. In particular, measurements or calculations of neutron spectra are expected to lead to uncertainties in LET spectra in the LET range 

from about 30 to 300 keV/m where recoil nuclei deposit the majority of the energy. Neutrons also cause a 

low-LET gamma-ray component that is often ignored in calculations. Larger errors are expected at a higher 

LET, where stopping nuclei, which may be difficult to define due to local tissue variations, dominate. We 

expect uncertainties to be larger at high-LET values, where the role of local target recoils and stopping 

GCR primaries are difficult to describe. 

The PDFs for the uncertainties in LET spectra should ensure that the resulting dose-equivalent is consistent 

with the transport code comparisons to past space flight measurements for GCR. A quantile, xL, which is associated with a normal distribution, PF(xF=F/F0) – where xF is the ratio of sampled estimate of the fluence, F, to 

the point estimate, F0, from the HZETRN code – is used with a standard error that increases with LET to represent the higher uncertainties that are expected for prediction of neutron effects and the difficulty in precisely 

defining stopping ions in complex geometries. The PDF 

is given a median of x0F=0.65 to ensure that the resulting dose-equivalent is in agreement with values from 

prior comparisons between the transport codes and 

flight measurements that were cited above. Standard 

deviations for different LET regions are given in 

Table 4-14 (right). 

Figures 4-13 and 4-14 illustrate the errors that are 

assigned to environmental and physical factors in evaluating LET spectra at tissue sites. 

 

Table 4-14. Standard Deviations for Uncertainties in 

Model LET Spectra for Several LET Regions 

LET Interval SD for dF/dL 

< 30 keV/μm 1.0 

30–300 keV/μm 2.0 

> 300 keV/μm 2.5 
Chapter 4 Human Health and Performance Risks of Space Exploration Missions 

154 Risk of Radiation Carcinogenesis 

Figure 4-13. Calculation of tissue-weighted integral LET spectra and 

90% C.I. for space environmental and transport uncertainties for a 

20-g/cm2

 aluminum shield for 1 year in deep space. 

Figure 4-14. PDF for GCR effective dose for 20-g/cm2 aluminum shield 

for 600-d Mars swing-by mission. The point estimate is 0.86 Sv, and 

the 95% C.I. for uncertainties in LET distribution at tissue sites is 

[0.78, 1.08] Sv. Only uncertainties in physics are included.

L, keV/m

1 10 100 1000

F(>L), 1/(cm2 yr)

10-2

10-1

100

101

102

103

104

105

106

107

108

109

HZETRN Model

90% CI bounds

Effective Dose, Sv

0.50 0.75 1.00 1.25 1.50

PDF(E)

0.000

0.003

0.006

0.009

0.012

0.015

0.018

Monte-Carlo results
Human Health and Performance Risks of Space Exploration Missions Chapter 4 

Risk of Radiation Carcinogenesis 155

 Uncertainties due to Life-tables and Population Cancer Rates 

Although radiation risk calculations are based on population data, they are used to estimate risks for individuals. Population data reflect gender differences, but also change with calendar year and often are used to 

make projections far into the future. For the astronaut population, the appropriateness of using the U.S. average 

population in making projections can be questioned because the so-called “healthy worker” effect is expected 

for astronauts. In the average U.S. population, females have longer life spans than males, partly due to their 

overall lower risk of cancer. The formalism of Eq(7) through Eq(13) shows two counteracting effects arising 

when one attempts to determine whether the use of population rates that are representative of a healthier population compared to the U.S. population would decrease or increase the risk of radiation carcinogenesis. 

First the population survival function acts to decrease radiation risks, especially at older ages. An improved 

survival function that acts alone will, therefore, increase the risk from radiation. However, an improved 

survival function also suggests lower background cancer rates, which makes up some fraction of the delay in 

mortality. In the multiplicative transfer model, radiation risks are reduced if a healthy worker effect is due, in 

part, to a reduced natural incidence of cancer. Thus, the portions of the risk transfer that are assigned to multiplicative and additive transfer act in opposition if a healthy worker effect is present. 

In a model where a geometric average of these two models is used, we expect a minor change if an improved life-table and background cancer rates are assumed. The role of the survival function is also reduced 

if solid cancers would display a plateau at long times after exposure (>30 years), as has been suggested in 

some studies (Preston et al., 2003). This discussion points to the need for better understanding of the biological basis for risk transfer models and dependence of risk after long follow-up times. Cucinotta et al. (2006) 

considered projections of life expectancy that were made by the Social Security Administration (SSA, 2006) 

and differences in rates between males and females to estimate errors in the life-table formalism. Uncertainties, 

which can be on the order of 25%, will increase if healthy worker effects are estimated. As these uncertainties 

are greater than those of the space environmental models and are at about the same level of uncertainty that 

was estimated for radiation transport codes, they should not be ignored. 

 Risk in Context of Exploration Mission Operational Scenarios 

The accuracy of GCR environmental models, transport codes, and nuclear interaction cross sections, as described above, allow NASA to make predictions of the space environments and organ exposures that will be 

encountered on missions to the moon or Mars. However, major questions arise due to the lack of knowledge on 

biological effects. For cancer risk projections, propagating individual uncertainties in factors that enter risk 

model calculations is used to place reasonable bounds on the cancer risks that will be encountered. 

Figure 4-15 shows predictions for the Mars surface. In this figure, the upward neutron flux, which is not included, is judged to carry the largest uncertainty in physics models for exploration. The variation in doses is 

due to the variation in atmospheric height at different geographic locations (Saganti et al., 2004). 

 
Chapter 4 Human Health and Performance Risks of Space Exploration Missions 

156 Risk of Radiation Carcinogenesis 

Figure 4-15. From Saganti et al. (2004) Predictions of skin dose-equivalent as a 

function of position on the Mars surface. Atmospheric data are taken from the 

MOLA [Mars orbiter laser altimeter] experiment.

 PDFs for space exploration missions 

The cancer risk projection for space missions is found by folding predictions of the tissue-weighted LET spectra 

behind spacecraft shielding, dF/dL, with the radiation cancer mortality rate to form a rate for a trial J. 

(, ,) (, ,) () J E lJ E trial J L J

dF

m E a a m E a a dL LQ L x

dL     (16) 

(Not shown are the quantiles that are associated with the low-LET mortality rate.) Alternatively, particlespecific energy spectra, Fj(E), for each ion, j, can be used. 

( , , ) ( , , ) ( ) ( ) ( ( )) J E lJ E j trial J L J

j

m E a a m E a a dEF E L E Q L E x     (17) 

The result of Eq(16) or Eq(17) is then inserted into the expression for the REID of Eq(10). In implementing 

a numerical procedure, we group the PDFs that are related to the risk coefficient of the normal form, which 

consist of the dosimetry, bias, and statistical uncertainties, into a combined PDF, Pcmb(x). After accumulating 

sufficient trials (~105

), the results for the REID estimates are binned, and the median values and confidence 

intervals are found. 

We use the χ

2

 test for determining whether the PDFs for two distinct shielding configurations or materials are 

significantly different. We denote the calculated PDFs for a REID of Ri for two configurations or materials as 

Saganti/Cucinotta: Space Science Reviews 2004 http://srhp.jsc.nasa.gov/
Human Health and Performance Risks of Space Exploration Missions Chapter 4 

Risk of Radiation Carcinogenesis 157

p1(Ri) and p2(Ri), respectively. Each p(Ri) follows a Poisson distribution with variance, ( ) p Ri . The chisquared, χ

2

 test for n-degrees of freedom characterizing the dispersion between the two distributions is then 

2

2 1 2

2 2

1 2

[ ( ) ( )]

() ()

n n

n n n

pR pR

p R pR

  



 (18) 

Once χ

2

 is determined, the probability P(n, χ

2

) that the two distributions are the same is calculated. If χ

2

 is 

sufficiently large such that P(n, χ

2

) is less than about 20%, this indicates that we can conclude that the two 

distributions lead to distinct cancer risks from GCR and/or SPEs, with the material with the lowest mean and 

upper 95% CL values preferred for radiation protection. However, the opposite result indicates that either the 

materials are approximately the same, or that the uncertainties in risk models prevent us from concluding that 

either configuration or material is superior in radiation protection properties. We therefore evaluate χ2 for the 

LET-dependent parts of the uncertainties (i.e., quality factors and physics) separately, as only these contributions 

explicitly depend on the modification of radiation fields by shielding. Tables 4-15 and 4-16 show fatal cancer 

risk projections at solar minimum for males and females of age 40 years at the time of the mission. Cancer 

morbidity risks that are about 50% higher than mortality risks are described here. Calculations are made for 

minimally shielded spacecraft of 5-g/cm2 aluminum and a heavily shielded spacecraft of 20 g/cm2

. Similar 

calculations that are near solar maximum are shown in Tables 4-17 and 4-18; an SPE fluence that is equivalent to the August 1972 SPE is assumed to have occurred. At solar minimum, it is seen that a four-fold 

addition of mass reduces the cancer risk by only about 15%. 

Table 4-15. Calculations of Effective Doses, REID, and 95% C.I. for Lunar or Mars 

Missions. Calculations Are at Solar Minimum for a 5-g/cm2

 Aluminum Shield 

Exploration 

Mission 

D, Gy E, Sv REID(%) 95% C.I. 

Males (40 years) 

Lunar-long 0.06 0.017 0.68 [0.20, 2.4] 

Mars swing-by 0.37 1.03 4.0 [1.0, 10.5] 

Mars surface 0.42 1.07 4.2 [1.3, 13.6] 

Females (40 years)

Lunar-long 0.06 0.17 0.82 [0.23, 3.1] 

Mars swing-by 0.37 1.03 4.9 [1.4, 16.2] 

Mars surface 0.42 1.07 5.1 [1.6, 16.4] 

 
Chapter 4 Human Health and Performance Risks of Space Exploration Missions 

158 Risk of Radiation Carcinogenesis 

Table 4-16. Calculations of Effective Doses, REID, and 95% C.I. for Lunar or Mars 

Missions. Calculations Are at Solar Minimum for a 20-g/cm2

 Aluminum Shield

Exploration 

Mission 

D, Gy E, Sv REID(%) 95% C.I. 

Males (40 years) 

Lunar-long 0.06 0.14 0.57 [0.18, 1.9] 

Mars swingby 0.36 0.87 3.2 [1.0, 10.4] 

Mars surface 0.41 0.96 3.4 [1.1, 10.8] 

Females (40 years)

Lunar-long 0.06 0.14 0.68 [0.22, 2.4] 

Mars swingby 0.36 0.87 3.9 [1.2, 12.7] 

Mars surface 0.41 0.96 4.1 [1.3, 13.3] 

Results differ at solar maximum, where a four-fold increase in shielding mass leads to a more than two-fold 

reduction in cancer risk and solar protons (Tables 4-17 and 4-18), which are less penetrating than GCR, are 

effectively mitigated by shielding. However, for heavy shielding (≥ 20 g/cm2

), GCR dominates over SPEs 

and the further addition of shielding provides marginal reductions. Each SPE is unique in that it has distinct 

fluence, energy spectra, and dose-rates; the shielding thickness where GCR doses exceed SPE doses therefore 

varies from event to event. Cancer incidence projections (not shown) are about 60% higher than those listed 

in these tables. Tables 4-17 and 4-18 show that cancer risk estimates still exceed the PELs for many Exploration mission scenarios and will remain as such until the uncertainties are reduced. 

Table 4-17. Calculations of Effective Doses, REID, and 95% C.I. for Lunar or Mars 

Missions. Calculations Are Near Solar Maximum, Assuming 1972 SPE in the Deep 

Space Segment of the Mission with a 5-g/cm2

 Aluminum Shield

Exploration 

Mission 

D, Gy E, Sv REID(%) 95% C.I. 

Males (40 years) 

Lunar-long 0.49 0.74 3.0 [0.95, 7.9] 

Mars swingby 0.62 1.21 4.4 [1.5, 13.1] 

Mars surface 0.66 1.24 4.8 [1.6, 14.2] 

Females (40 years)

Lunar-long 0.49 0.74 3.6 [1.1, 9.6] 

Mars swingby 0.62 1.21 5.7 [1.8, 17.1] 

Mars surface 0.66 1.24 5.8 [2.0, 17.3 ] 

 
Human Health and Performance Risks of Space Exploration Missions Chapter 4 

Risk of Radiation Carcinogenesis 159

Table 4-18. Calculations of Effective Doses, REID, and 95% C.I. for Lunar or Mars 

Missions. Calculations Are Near Solar Maximum, Assuming 1972 SPE in the Deep 

Space Segment of the Mission with a 20-g/cm2

 Aluminum Shield 

Exploration 

Mission 

D, Gy E, Sv REID(%) 95% C.I. 

Males (40 years) 

Lunar-long 0.08 0.18 0.72 [0.24, 2.4] 

Mars swing-by 0.22 0.54 2.0 [0.60, 6.8] 

Mars surface 0.25 0.60 2.4 [0.76, 7.8] 

Females (40 years)

Lunar-long 0.08 0.18 0.86 [0.26, 2.8] 

Mars swing-by 0.22 0.54 2.5 [0.76, 8.3] 

Mars surface 0.25 0.60 2.9 [0.89, 9.5] 

 Biological and physical countermeasures 

Identifying effective countermeasures with which to reduce the biological damage that is produced by radiation 

remains a long-term goal of space research. As noted by Durante and Cucinotta (2008), such countermeasures 

may not be needed for a lunar base, but they probably will be for the Mars mission and definitely will be needed 

for exploring Jupiter, the Saturn moon Titan, or the nearby satellites. In all of the basic radioprotection textbooks, 

the authors have stated that there are three means to reduce exposure to ionizing radiation: increasing the distance

from the radiation source, reducing the exposure time, and through use of shielding. Distance plays no role in 

space, as space radiation is omnidirectional. The time that will be spent in space by human crews is likely to be 

increased rather than decreased, given the plans for exploration and colonization. Shielding remains a plausible 

countermeasure, albeit a prohibitively costly one in light of current launch mass capabilities. Furthermore, the 

present uncertainties in risk projection prevent us from determining the true benefit of shielding. Other strategies can be effective in reducing exposure, or the effects of the irradiation, in space. These strategies include 

the choice of an appropriate time of flight, administration of drugs or dietary supplements to reduce the 

radiation effects, and crew selection. 

 Radioprotective Agents 

The search for efficient radioprotectors is a major goal of research in radiation protection and therapy. Both 

radiation injury and oxygen poisoning occur through the formation of reactive oxygen species; therefore, 

antioxidants can be efficiently used to prevent the damage (Weiss and Landauer, 2003). 

As summarized by Durante and Cucinotta (2008), 

“Phosphorothioates and other aminothiols, which are usually administered shortlybefore irradiation, 

are so effective in tissue protection against ionizing radiation that one specific compound (Ethyol, 

also known as amifostine or WR-2721) is approved in many countries for clinical use during chemotherapy and radiotherapy cancer treatments(Sasse et al., 2006). Unfortunately, amifostine (WR2721) and other thiols have significant side effects, including nausea, vomiting, vasodilatation, and 

hypotension (Boccia et al., [sic] 2002), precluding their use in spaceflights. Natural occurring antioxidants are less effective than phosphorothioate agents in protection against high-dose acute radiation 

burden. However, nutritional antioxidants have a low toxicity, can be used for prolonged time, and 

they seem to play a key role in the prevention of cancer(Halliwell, 2000; Bingham and Riboli, 2004). 

A diet rich in fruit and vegetables significantly reduced the risk of cancer in the A-bomb survivor 
Chapter 4 Human Health and Performance Risks of Space Exploration Missions 

160 Risk of Radiation Carcinogenesis 

cohort (Sauvaget et al., 2004). Retinoids and vitamins (A, C, and E) are probably the most well-known 

and studied natural radioprotectors, but hormones (e.g. melatonin), gluthatione, superoxide dismutase, 

phytochemicals from plant extracts (including green tea and cruciferous vegetables), and metals (especially selenium, zinc, and copper salts) are also under study as dietary supplements for individuals 

overexposed to radiation (Weiss and Landauer, 2000), including astronauts. In addition, there is evidence of a reduced antioxidant capacity during spaceflight, as shown by reduced superoxide dismutase 

(SOD) and total antioxidant activity in some astronauts returning from missions on the International 

Space Station (Smith et al., 2005). 

“Understanding the effectiveness of antioxidants in space is complicated by the presence of HZE 

particles. In principle, antioxidants should provide reduced or no protection against the initial damage 

from densely ionizing radiation, because the direct effect is more important than free radical-mediated 

indirect radiation damage at high LET. However, there is an expectation that some benefits should 

occur for persistent oxidative damage related to inflammation and immune responses. Some recent 

experiments suggest at least for acute high dose irradiation that an efficient radioprotection by dietary 

supplements can be achieved even in case of exposure to high-LET radiation. Ascorbate reduces the 

frequency of mutations in human-hamster hybrid cells exposed to high-LET C-ions(Waldren et al., 

2004). Vitamin A strongly reduces the induction of fibroma in rats exposed to swift Fe-ions (Burns 

et al., 2007). Dietary supplementation with Bowan-Birk protease inhibitors(Guan et al., 2006), Lselenomethionine or a combination of selected antioxidant agents(Kennedy et al., 2007) could partially or completely prevent the decrease in the total antioxidant status in the plasma of mice exposed 

to proton or HZE particle radiation, and neoplastic transformation of human thyroid cells in vitro. 

However, because the mechanisms of biological effects are different for low dose-rate compared to 

acute irradiation, new studies for protracted exposures will be needed to understand the potential 

benefits of biological countermeasures.” 

Even if antioxidants can act as radioprotectors, this does not necessarily translate as an advantage for cancer 

risk. If antioxidants protect cells by rescuing them from apoptosis, this may allow the survival of damaged 

cells, which eventually can initiate tumor progression. Concern about this possibility is sustained by a recent 

meta-study of the effects of antioxidant supplements in the diet of normal subjects(Bjelakovic et al., 2007). 

The authors of this study did not find statistically significant evidence that antioxidant supplements have beneficial effects on mortality. On the contrary, these authors concluded that β-carotene, vitamin A, and vitamin E 

seem to increase the risk of death. Concerns not only include rescuing cells that still sustain DNA mutations, 

but also the altered methylation patterns that can result in genomic instability (Kovalchuk et al., 2004). An 

approach to target damaged cells for apoptosis may be advantageous for chronic exposures to galactic cosmic 

radiation. Radioprotectors tested for acute exposures at high doses should be used with care – rescuing cells 

may make the problem worse in the long term. 

 Shielding 

For terrestrial radiation workers, additional protection against radiation exposure is usually provided through 

increased shielding. Unfortunately, shielding in space is problematic, especially when GCRs are considered. 

High-energy radiation is very penetrating: a thin or moderate shielding is generally efficient in reducing the 

equivalent dose, but, as the thickness increases, shield effectiveness drops. This is the result of the production 

of a large number of secondary particles, including neutrons, that are caused by nuclear interactions of the GCR 

with the shield. These particles have generally lower energy, but they can have higher quality factors than incident cosmic primary particle. Radiation shielding effectiveness depends on the atomic constituents of the 

material that is used. Shielding effectiveness per unit mass, which is the highest for hydrogen, decreases with 

increasing atomic number (Wilson et al. 1995). Liquid hydrogen would display the maximum performance as 

shield material, but it is not practical since it is a low-temperature liquid. Instead, polyethylene could be a good 

compromise. Secondary neutron production increases with the mass number of the atomic constituents of the 
Human Health and Performance Risks of Space Exploration Missions Chapter 4 

Risk of Radiation Carcinogenesis 161

material and can grow to be large values for materials such as aluminum or the regolith on the martian surface, or for heavier materials such as lead. Unfortunately, most of the biologically dangerous secondary 

radiation is produced in tissue by very-high-energy GCR nuclei, even behind hydrogen shielding. 

For SPE shielding, the situation is much better, and the majority of events on record can be reduced to 

reasonable dose levels (< 100 mSv) with localized shielding of polyethylene inside a lightly shielded vehicle 

or habitat (figure 4-16). 

 

 Shielding Depth, g/cm2

0 5 10 15 20 25 30 35

Dose Equivalent, rem/yr

1

10

100

1000

10000

GCR L. Hydrogen

GCR Polyethylene

GCR Graphite

GCR Aluminum

GCR Regolith

SPE Graphite

SPE Regolith

SPE L. Hydrogen

Figure 4-16. Effective doses 

vs. depth in several materials 

for GCR at solar minimum and 

the 1972 SPE (Cucinotta et al., 

2006).
Chapter 4 Human Health and Performance Risks of Space Exploration Missions 

162 Risk of Radiation Carcinogenesis 

 Conclusion 

The evidence for cancer risks from humans who are exposed to low-LET radiation is extensive for doses 

above 100 mSv. There are important uncertainties for low-LET radiation at lower doses (<100 mSv), for low 

dose-rates, and in transferring risks among populations that have different genetic, dietary, etc. attributes. Although human epidemiology can be applied to space exposures, additional uncertainties are related to the quality 

of radiation in space that is known to produce both qualitative and quantitative differences compared to lowLET radiation in experimental models. The doses that are to be expected on space missions, and the nuclear type 

and energies, are well understood. NASA has existing models that quite accurately determine radiation physics 

parameters in space. Reducing the uncertainties in risk assessment, which is required before a mission to Mars 

can be undertaken, has led to a number of investigations that are guided by molecular and genetic research on 

carcinogenesis and degenerative diseases. The large uncertainties in risk projection models will only be reduced 

by improving our basic understanding of the underlying biological processes and their disruption by space radiation. There are unique aspects involved in this approach due to the specific challenges to biological systems that 

are presented by space radiation, especially HZE ions. It is unlikely that the radiation risk problem for space exploration will be solved by a simple countermeasure, such as shielding or radioprotective drugs. Rather, the risk 

will be understood and controlled only with more basic research in the field of cancer induction by charged 

particles (Cucinotta and Durante, 2006). 

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Chapter 4 Human Health and Performance Risks of Space Exploration Missions 

170 Risk of Radiation Carcinogenesis 
Risk of Acute Radiation Syndromes Due to Solar Particle Events 171

Chapter 5: 

Risk of Acute Radiation Syndromes Due to 

Solar Particle Events 

Honglu Wu 

NASA Johnson Space Center 

Janice L. Huff 

Universities Space Research Association 

Rachel Casey 

Universities Space Research Association 

Myung-Hee Kim 

Universities Space Research Association 

Francis A. Cucinotta 

NASA Johnson Space Center 

Radiation and synergistic effects of radiation may place the crew at significant risk for acute radiation 

sickness from a major solar event or artificial event, such that the mission or crew survival may be placed in 

jeopardy. Crew health and performance may be impacted by acute solar events. Beyond Low Earth Orbit, the 

protection of the Earth's atmosphere is no longer available, such that increased shielding and protective 

mechanisms are necessary in order to prevent acute radiation sickness and impacts to mission success or 

crew survival. The primary data available at present are derived from analysis of medical patients and persons 

accidentally exposed to high doses of radiation. Data more specific to the spaceflight environment must be 

compiled to quantify the magnitude of increase of this risk and to develop appropriate protection strategies. 

– Human Research Program Requirements Document, HRP-47052, Rev. C, dated Jan 2009. 

 Research to improve estimates of the risk of acute 

radiation syndrome resulting from exposure to solar 

particle events (as pictured here) will help ensure that 

the risk is sufficiently mitigated through shielding 

protection, monitoring, and alert systems. 
172 Risk of Radiation Carcinogenesis 
Human Health and Performance Risks of Space Exploration Missions Chapter 5 

Risk of Acute Radiation Syndromes Due to Solar Particle Events 173

 Executive Summary 

The foundation of evidence for acute radiation syndrome (ARS) is ground-based observations for humans 

who were exposed to ionizing radiation, and well-defined dose projections for space explorations missions. 

Scenarios in which ARS is likely to have a major health impact entail nuclear power plant workers in the event 

of a nuclear accident; military personnel, in the event of nuclear war; and the general population, should a terrorist 

attack occur that involves nuclear devices (Waselenko et al., 2004; Pellmar et al., 2005). ARS has been documented 

in humans who were exposed to gamma or X rays, and these data have been summarized in the literature and in 

numerous committee reports (e.g., NAS/NRC, 1967; NCRP, 1982; NCRP, 1989; Baum et al., 1984; Evans et al., 

1985; ICRP, 2000; ICRP, 2002). NASA has funded several reports from the NAS and the NCRP that provided 

evidence for the radiation risks in space. Of note, the NCRP is chartered by the United States Congress to guide 

federal agencies such as NASA on the risk from radiation exposures to their workers. Reports from the NCRP 

and the NRC on space radiation risks are the foundation of the evidence that is used at NASA for research 

and operational radiation protection methods and plans. 

The risk of ARS from exposure to large SPEs during space missions was identified in the early days of 

the human space program (NAS/NRC, 1967). The ARS symptoms that appear in the prodromal phase postexposure (i.e., nausea, vomiting, anorexia, and fatigue) could potentially more significantly affect space mission 

success because of the lower threshold dose with which these occur compared to other acute risks, as well as the 

likely dose ranges from SPEs. While ARS has been well defined for gamma- and X-ray exposures, less is known 

about the acute effects from whole-body exposures to SPE protons, which are characterized by dynamic changes 

in energy distribution and dose-rates at specific locations in the human body. Protons dominate the dose inside the 

spacecraft. During EVAs, however, the helium and heavy-ion component of SPEs is also of biological importance. 

Protons with energies that are above 10 MeV are characterized as low-LET radiation. Inside tissue, a fraction of 

SPE doses is from high-LET radiation due to the slowing down of higher energy protons, and nuclear reactions 

producing neutrons and heavy ions. RBE factors for these radiation types are poorly defined. There have also 

been few investigations of the effectiveness of medical countermeasures for proton, microgravity, or reducedgravity environments. Improvements in SPE forecasting and alert systems are needed to minimize operational 

constraints, especially for EVA. While radiation shielding is an effective mitigation to ARS, the high cost of 

shielding requires precise estimates of the risk to ensure that sufficient protection is provided without overestimating shielding requirements, especially in light of the existence of a dose threshold for many ARS components. 

 Introduction 

 Description of acute risks of concern to NASA 

During an SPE, the sun releases a large amount of energetic particles. Although the composition of the particle 

type varies slightly from event to event, on average these particles consist of 96% protons, 4% helium-ions, and 

a small fraction of heavier ions (NCRP, 1989; Cucinotta et al., 1994; Townsend et al., 1994; Kim et al., 1999). 

The intensity and the energy spectrum of an SPE varies throughout the course of the event, which lasts from a 

few hours to several days. The intensity of the event can be described by particle fluence, F>E, which is the 

number of ions per unit area with energy greater than E, expressed as mega electron volts per nucleon (MeV/n). 

The energies of the protons are important because the range of penetration of these protons increases with energy. 

Protons with energies above 30 MeV have sufficient range to penetrate an EVA spacesuit, and are used as a 

simple scaling parameter to compare different SPEs. Each event has distinct temporal and energy characteristics, however. The majority of SPEs are relatively harmless to human health, with doses below 10 mGy for 
Chapter 5 Human Health and Performance Risks of Space Exploration Missions 

174 Risk of Acute Radiation Syndromes Due to Solar Particle Events 

minimal shielding protection; but the SPEs that have the highest fluence of particle of energies above 30 MeV 

are a major concern for future missions outside the protection of the magnetic field of the Earth. 

Figure 5-1 shows data that were collected in the modern era for the F>30 MeV proton fluence (bottom panel) 

from large SPEs and the solar modulation parameter (Φ) (upper panel). The solar modulation parameter describes 

the strength of the sun’s magnetic field with solar maximum where Φ>1,000 MV. The various SPEs shown in 

figure 5-1, which are characterized as large SPEs (F>30 MeV > 108 per cm2

), would contribute doses of 10 to 

500 mGy for average shielding conditions. Although the dose resulting from the majority of SPEs is small, SPEs 

nonetheless pose significant operational challenges because the eventual size of an event cannot be predicted 

until several hours after the particles are initially detected. Extraordinarily large SPEs were recorded in November 

1960, August 1972, and October 1989. In general, SPEs occur more often near solar maximum, but, as figure 

5-1 shows, the correlation between event frequency and solar conditions is not precise. To date, accurate 

short- or long-term prediction of SPEs has not been possible. 

Figure 5-1. Historical data on fluence of protons above 30 MeV per cm2

 (F(>30 MeV) 

from large SPEs relative to solar modulation parameter (). Only events with F>30 MeV

>108

 particles per cm2 are shown. 

In contrast to the constant presence of GCRs in space, SPE exposures are sporadic and occur with little warning. 

Without sufficient shielding protection, a large SPE may result in a whole-body dose of over 0.5 Gy (500 mGy) 

received over a period of several hours. Humans who are exposed to gamma or X rays at doses above 0.5 Gy 

are known to experience ARS (Anno et al., 1989). ARS can be classified clinically as hematopoietic syndrome, 

GI syndrome, and neurovascular syndrome. Based on the time of appearance, ARS can be divided into prodromal 

phase (0–24 hr), latent phase, manifest illness phase, and recovery phase. The most probable ARS effects from 

GCR Deceleration Potential

200

400

600

800

1000

1200

1400

1600

1800

1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020

Year

, MV

+ ++ + - - -

1/1/1950 1/1/1960 1/1/1970 1/1/1980 1/1/1990 1/1/2000 1/1/2010 1/1/2020 

F(>30 MeV), Protons/cm2

108

109

1010 F>108

 solar proton

events only
Human Health and Performance Risks of Space Exploration Missions Chapter 5 

Risk of Acute Radiation Syndromes Due to Solar Particle Events 175

SPE exposure in space flight that can potentially affect mission success include prodromal effects (nausea, 

vomiting, anorexia, and fatigue), skin injury, and depletion of the blood-forming organs (BFOs), possibly leading 

to death. SPEs are of much lower energy than are GCRs and occur at modest dose-rates. Shielding is an effective 

countermeasure to SPEs inside spacecraft, making ARS extremely unlikely except in EVA or combined EVA 

and intravehicular activity (IVA) scenarios. The magnitude of ARS risks on the moon has been hypothesized 

to be increased significantly due to a possible synergistic effect of reduced gravity (Todd et al., 1999) or the 

background GCR exposure. The operational impacts of ARS on space flight crew members could affect crew 

performance and lead to the possibility of mission failure. Recovery of ARS can also be hindered by changes 

of the immune status, including from combined skin burns and blood system depletion, and a slower woundhealing process. 

NASA, in past reviews, has included the risks of hereditary, fertility, and sterility effects as part of the collection of risks embodied in the acute radiation effects category. There is no perfect match of these effects with any 

of the four major identified NASA HRP radiation risks, and, based on past reviews of these effects (NCRP, 1989; 

2000), they alone are not likely to rise to the level of a major concern. As SPEs would be the primary cause of 

fertility and sterility effects, these items are included as part of the acute category of risks. 

 Current NASA permissible exposure limits 

PELs for short-term and career astronaut exposures to space radiation have been approved by the NASA 

Chief Health and Medical Officer. These PELs provide the basis for setting requirements and standards for 

mission design and crew selection. Short-term dose limits (i.e., PELs) are imposed to prevent clinically significant deterministic health effects, including performance degradation in flight. Dose limits for deterministic 

effects, which are given in units of Gray-equivalent, are listed in Table 5-1. The unit of Gray-equivalent is distinct from the unit of Sievert that is used to project cancer risk because distinct radiation quality functions occur 

for ARS and cancer. The Gray-equivalent is calculated using the RBE values that are described in NCRP Report 

No. 132 (2000) and Sievert using the LET-dependent radiation quality function. For mission planning, these limits 

should be applied with a P>0.99 success criteria for a worst-case radiation environment and available mitigation 

procedures. The basis for the PELs originated in prior reports and recommendations to NASA by the NAS 

Space Science Board (NAS/NRC, 1967; 1970) and the NCRP (NCRP, 1989; 2000). These reports are summarized below. 

Table 5-1. Dose Limits (in mGy-Eq or mGy) for Non-cancer Radiation Effects (BFO Refers to the 

Blood-forming Organs and CNS to the Central Nervous System)

Organ 30-day limit 1-year limit Career 

Lens* 1,000 mGy-Eq 2,000 mGy-Eq 4,000 mGy-Eq 

Skin 1,500 mGy-Eq 3,000 mGy-Eq 6,000 mGy-Eq 

BFO 250 mGy-Eq 500 mGy-Eq Not applicable 

Heart** 250 mGy-Eq 500 mGy-Eq 1,000 mGy-Eq 

CNS*** 500 mGy-Eq 1,000 mGy-Eq 1,500 mGy-Eq 

CNS*** (Z≥10) – 100 mGy 250 mGy 

*Lens limits are intended to prevent early (<5 years) severe cataracts (e.g., from an SPE). An additional cataract risk exists 

at lower doses from cosmic rays for subclinical cataracts, which may progress to severe types after long latency (>5 years) 

and are not preventable by existing mitigation measures; they are deemed an acceptable risk to the program, however. 

**Heart doses calculated as average over heart muscle and adjacent arteries. 

***CNS limits should be calculated at the hippocampus. 
Chapter 5 Human Health and Performance Risks of Space Exploration Missions 

176 Risk of Acute Radiation Syndromes Due to Solar Particle Events 

 Evidence 

 Reviews of human data in patients and accident victims 

Evidence of ARS in humans from low-LET radiation, such as gamma- or X-ray exposures, has been thoroughly 

reviewed and documented in the reports that have been generated by regulatory institutes such as NAS, NCRP, 

the ICRP, and the U.S. Nuclear Regulatory Commission. Data accumulated from the last half-century that were 

used in the construction of the dose threshold for ARS include: studies on the Japanese atomic-bomb survivors 

(Ishida and Matsubayashi, 1948; Ohkita, 1975; Oughterson and Warren, 1956); case studies of nuclear accident 

victims (Blakely, 1968; Vodopick and Andrews, 1974; Gilberti, 1980); and records of total-body therapy patients 

for cancer and other diseases (Adelstein and Dealy, 1965; Brown, 1953; Warren and Grahn, 1973). More recent 

events include the Chernobyl accident in 1986 (Bouville et al., 2006); an accident that occurred in Tokai-mura, 

Japan, in 1999 (Hirama et al., 2003); and the death of a Russian citizen after a possible internal overdose of 

radioactive materials that was reported in the popular media in 2006. 

ARS appears in various forms and has different threshold onset doses for the possible effects. The threshold 

whole-body dose for ARS is about 0.1 to 0.2 Gy for radiation that is delivered under acute conditions where 

dose-rates are more than 1 Gy/hr occur. At lower dose-rates, a reduction in effects occur, as described below. At 

doses that are slightly above this threshold, decreases in sperm counts occur that cause temporary sterility in males 

(NAS/NRC, 1967; Paulsen, 1973; NCRP, 1989). The dose range and associated patho-physiological events have 

been summarized previously (Anno et al., 1989). Doses that are in the range of 0.5 to 1 Gy cause minor acute 

damage to the hemopoietic system and mild prodromal effects (nausea, vomiting, anorexia, and fatigue) in a small 

number of irradiated persons (Anno et al., 1989). In the dose range of 1 to 2 Gy acute, prodromal effects and injury to the hemopoietic system increase significantly. Most victims will probably survive, however, with only 5% 

lethality in a population after doses of about 2 Gy (NAS/NRC, 1967; McFarland and Pearson, 1963). Survival is 

possible within the dose range of 2 to 3.5 Gy; however, prodromal effects become more pronounced, decreasing 

in latency and increasing in severity. As the dose reaches about 3.25 Gy, 50% may die within 60 days if appropriate medical care is not administered (Lushbaugh, 1969). From 3.5 to 5.5 Gy, symptoms are more severe, 

affecting nearly all who are exposed. If untreated, 50% to 99% of those who are affected may die primarily 

because of extensive injury to the hemopoietic system that is manifested by overwhelming infections and 

bleeding (NAS/NRC, 1967; Lushbaugh, 1969; Messerschmidt, 1979). At this dose range, permanent sterility 

results in both males and females (Paulsen, 1973; NCRP, 1989). 

Responses to doses between 5.5 and 7.5 Gy begin to reflect the combined effects of GI and hemopoietic 

damage. Survival is almost impossible, short of a compatible bone marrow transplant and/or extensive medical 

care. Nearly everyone who is irradiated at this level suffers severe prodromal effects during the first day after 

exposure. When doses range between 7.5 and 10 Gy, injuries are much more severe due to a greater depletion of 

bone marrow stem cells (Adelstein and Dealy, 1965; Lushbaugh, 1962), increased GI damage, and systemic 

complications from bacterial endotoxins entering the blood system. 

Doses that are between 10 and 20 Gy produce early post-exposure renal failure (Lushbaugh, 1974). Death 

results in fewer than 2 weeks from septicemia due to severe GI injury, which is complicated by complete bone 

marrow damage and the cessation of granulocyte production (Lushbaugh 1962). Above approximately 13 Gy, 

death may occur sooner from electrolyte imbalance and dehydration due to vomiting and diarrhea, especially in 

hot and humid conditions. Extremely severe GI and cardiovascular damage causes death within 2 to 5 days after 

doses of 20 to 23 Gy (Lushbaugh, 1969). 
Human Health and Performance Risks of Space Exploration Missions Chapter 5 

Risk of Acute Radiation Syndromes Due to Solar Particle Events 177

 Prodromal Effects 

Prodromal effects, which have a threshold dose of about 0.5 Gy, are the most likely acute effect to be 

experienced by crew members after exposure to SPE based on the historical record of SPE fluence and likely 

shielding conditions. Dose and onset of sickness are inversely correlated, with higher doses producing the 

shortest time for sickness to occur. The prodromal phase comprises the clinical symptoms (nausea, vomiting, 

and anorexia) and signs that appear in the first 48 hours after exposure. Prodromal vomiting is of particular 

importance because it could have catastrophic consequences in space, especially to helmeted individuals (NCRP, 

1989), and other symptoms can seriously impair mission success in space. Several sets of data on humans, 

who are mostly cancer patients, are available to make initial estimates of the likelihood and types of effects 

(e.g., Lushbaugh et al., 1967; Lushbaugh, 1974). In general, symptoms develop within a few hours of radiation exposure and rarely exceed 24 hours with low-LET radiation (Fajardo et al., 2001). Exposure to higher 

doses results in greater severity, early onset, and longer duration of the symptoms (Anno et al., 1996). 

Prodromal effects are not noted below low-LET radiation doses of 0.5 Gy (Mettler and Upton, 1995). 

Significantly smaller amounts of data are available for prodromal effects from continuous exposure at 

lower dose-rates. The current knowledge that has been collected from studies on victims who were exposed 

to radioactive fallout following the testing of nuclear devices and to other sources (Kumatori et al., 1980; 

Cronkite et al., 1956) is that dose-rates of perhaps less than a few tens of mGy/h are probably not sufficient to 

cause ARS. However, continuous dose-rates of around 100 mGy/h are probably high enough to cause significant vomiting within a period of 1 day or so. Accordingly, between a few tens of mGy/h to approximately 

100 mGy/h, a considerable amount of uncertainty exists concerning the human response to continuous 

radiation exposure, which is likely due to variations in the sensitivity of individuals as well as the quality 

of the very limited amount of existing data. 

 Skin Damage 

The skin may receive a dose that is up to a magnitude greater than that of internal organs from an SPE during 

an EVA, when minimal protection is available (Kim et al., 2006a). Risks of concern include erythema, moist 

desquamation, and epilation (NCRP, 1989). The ED10 (a dose in which 10% of a population receives the effect) 

has been estimated to be 4 Gy for erythema and 14 Gy for the more serious moist desquamation (Strom, 2003; 

Haskin et al., 1997). Protraction of exposure increases the dose that is required for a given degree of severity 

by a factor of about 3. The response of the skin depends on the number of exposures, the total dose, the dose 

per exposure, and the volume of tissue that is irradiated (Turesson and Notter, 1984). It has been noted that 

deterministic radiogenic skin injury complicates the treatment of many of the high-dose casualties at Chernobyl (Strom, 2003). Skin doses during an SPE can vary more than five-fold for different regions of the 

bodydue to the varying energies of solar protons and body self-shielding(Kim et al., 2006a). 

 Reviews of space flight issues 

Past reviews of evidence by the NAS and the NCRP form the basis for the NASA PELs. NAS first reviewed 

space flight issues in 1967 (NAS, 1967) and conducted a further review in 1970 (NAS, 1970) that led to the 

dose limits that were used at NASA until 1989. Extensive reviews of humans and experimental radiobiology 

data for ARS were provided to NASA by reports of the NCRP in 1989, 2000, and 2006 (NCRP, 1989; 2000; 

2006). The report of the NAS in 1970 is the basis for the BFO limits that are used at NASA. The rationale for 

this limit is to protect the hematopoietic system from depletion below a critical limit. Dose limits for the prodromal risks were not advocated by the NAS or the NCRP for NASA missions in the past. The BFO limit 

likely occurs at doses below that of the threshold for prodromal effects, however. 
Chapter 5 Human Health and Performance Risks of Space Exploration Missions 

178 Risk of Acute Radiation Syndromes Due to Solar Particle Events 

 Acute Risks for Protons, Neutrons, and High-Z High-energy Nuclei 

RBE and dose-rate studies in mice, rats, ferrets, and larger species

The data of ARS for high-LET radiation – e.g., neutrons and heavy ions – are collected primarily in animal 

studies. As mice and rats do not display the prodromal effects such as vomiting, limited research on this 

particular ARS has been performed on ferrets for particle types of radiation. Rabin et al. (1992; 1994) have 

studied the dose response of 600 MeV/n 56Fe-ion-induced emesis in ferrets and compared it with the dose 

response from other radiation types. Over the dose range of 0.2 to 0.5 Gy, fission spectrum neutrons and 

56Fe-ions were more effective than Co-60 gamma rays in inducing emesis, and the effects of the 56Fe-ions 

and fission neutrons could not be distinguished from each other. Co-60 gamma rays were significantly more 

effective in producing emesis than high-energy electrons or 200-MeV protons. The dose-rates ranged from 

0.1 to 1 Gy/min. The relatively large difference in LET between 56Fe-ions and fission neutrons was not associated with any difference in the effectiveness with which the two types of radiation produced emesis. 

Relative biological effectiveness and dose-rate studies in cell inactivation

Since some of the ARS effects are related to cell killing or tissue damage, the RBE and dose-rate data for 

cell inactivation by protons are insightful for ARS that is induced from SPE exposures (Cucinotta, 1999; 

Yang, 1999). Early results of cell inactivation by charged particles over a wide range of LET have been 

reviewed by Ainsworth (1986). In general, the RBE for cell inactivation in vitro peaked at LET around 100 

keV/micron, and the peak RBE value varied between 1.5 and 5 for different cell types. The maximum RBE 

for in vivo responses tended to be lower and occurred at a lower LET value in comparison to the in vitro 

data. The reported RBE-LET relationship for in vitro cell killing showed similar trends as in the early in 

vivo data (Furusawa et al., 2000). 

Factors that determine the dose-rate dependence of ARS include: the kinetics of DNA repair, apoptosis, 

cell-repopulation and proliferation, and dose distributions across critical organs. Irradiation at reduced doserates is known to reduce the probability of lethality of ARS that is induced by low-LET radiation compared 

to acute irradiation, as illustrated in figure 5-2. Differences between dose-rate effects for protons and X rays 

or gamma rays may occur due to the heterogeneous dose contribution from slowing protons or recoil nuclei 

in SPE organ doses. The heterogeneous dose distribution across the bone marrow for protons should lead to 

a sparing effect that complicates comparisons to gamma rays, where doses are more uniform. The dose distribution across the stomach and other organs in the GI-tract also varies several-fold for SPEs, which complicates the use of gamma-ray data to predict prodromal risks from SPE. 

 
Human Health and Performance Risks of Space Exploration Missions Chapter 5 

Risk of Acute Radiation Syndromes Due to Solar Particle Events 179

 Models of acute risks 

 Department of Defense and Nuclear Regulatory Commission Models 

The radiation-induced performance decrement from ARS is one of the major concerns for military personnel in a nuclear war scenario. The Defense Nuclear Agency has developed a computer model to calculate the 

dose and time-dependent human response to ionizing radiation for acute and protracted exposure conditions 

(Anno et al., 1996). A set of differential equations was mathematically developed to model the ARS for a given 

dose and the bodily repair and recovery process when the exposure takes place over a period of time. Most of 

the parameters in the equations were determined from human accident data or data of patients who were receiving whole-body radiation in medical treatment; limited data came from ferrets and other animals for protracted 

exposures. 

Two models were developed separately for upper gastrointestinal distress (UGID) and for fatigue/weakness 

(FW); these models were based on the postulated pathways. For UGID, the severity of the signs and symptoms 

was classified in five categories ranging from no noticeable effect (Severity Level 1) to vomiting and retching 

several times (Severity Level 5). For FW, Severity Level 5 is defined as exhaustion with almost no strength. 

Outputs of the computer codes are the probability of occurrence of specific symptoms as a function of input 

dose, dose-rate, and time after exposure. These radiation effects were also related to performance decrement 

for infantry tasks such as engaging a target with a rifle or walking up a rocky hill. Similar issues will be 

faced by NASA when astronauts are exposed to SPE on the surface of the moon. The mathematical model 

applies to gamma- or X-ray exposures only, but it has been adapted to proton effects at NASA (Hu et al., 

2009). 

 Cell Kinetics Models 

Cell kinetics models of the relevant cell lineages in the blood system are of interest for describing doserate effects. A group at Oak Ridge National Laboratory developed models of the blood system using a linear 

kinetics formula of cell damage, repair, and repopulation (Morris et al., 1993). The model has been fit to data 

for mice and larger species. This model, which was applied to study the risk of acute mortality following a 

large SPE (Wilson et al., 1999), indicates a very small probability for acute death for the largest SPEs, as in 

the Defense Nuclear Agency model that is described above. In addition, a nonlinear cell population kinetics 

model of ARS was developed that provides a more realistic simulation of the underlying biology of ARS 

Figure 5-2. Effects of medical treatment and 

dose-rate on the LD50 for gamma radiation; also 

shows expected region of dose-rates for SPEs 

during EVA (adapted from Haskin, 1997).
Chapter 5 Human Health and Performance Risks of Space Exploration Missions 

180 Risk of Acute Radiation Syndromes Due to Solar Particle Events 

(Smirnova and Yonezawa, 2004), including an adaptive response due to simulation of the immune defense 

mechanisms. 

 Risk in Context of Exploration Mission Operational Scenarios 

 Solar particle event environment models and doses 

Estimates of likely SPE cumulative doses and dose-rates at critical organs are important for assessing the 

probability of ARS for specific mission scenarios. Detailed spectra and temporal information are available for 

most of the SPEs that have occurred since 1955. Analysis of nitrate concentrations in Arctic ice-core samples 

provides data on integral fluences that are above 30 MeV for SPEs dating back to the 15th century (McKracken 

et al., 2001). The nitrate core samples indicate that several SPEs that are larger than the August 1972 event, which 

is considered to be the largest in modern times, have occurred in the past. The nitrate core sample data also allow 

researchers to estimate their frequency. The prediction of SPEs on Mars, taken from Earth observations, will 

require improved observational capabilities. Improved knowledge of the physics of these processes can be 

used to improve the radiation protection of crews. 

An understanding of the physical characteristics of solar disturbances is important for protecting the crews 

that are on Exploration missions. Thus, a summary from the book Safety design for space systems (Musgrave 

et al., 2009, pp. 53–58), is provided here. The solar wind is a plasma that contains both positive and negative 

particles that are trapped in a magnetic field emanating from the sun. The solar wind is an extension of the solar 

corona for at least several astronomical units (AUs) from the sun (1 AU  1.5  108

 km). It is composed mostly 

of protons and persists through variable parts of the sun’s output during less active solar phases. The solar wind 

protons have thermal energies of approximately 1 to 10 keV. Except when the sun is active, the solar wind 

constitutes the most important particulate solar radiation. 

A solar flare is an intense local brightening on the face of the sun close to a sunspot. This solar abnormality 

results in an alteration of the general outflow of solar plasma at moderate energies and local solar magnetic 

fields that are carried by that plasma. As the solar plasma envelops the Earth, the magnetic screening effects that 

are inherent in plasmas act to shield the Earth from GCRs, a process that is known as a Forbush decrease (Forbush, 

1937). When the solar plasma interacts with the geomagnetic field, a disturbance or storm occurs. During an 

intense magnetic disturbance, the magnetic field of the Earth is compressed into the atmosphere in the polar 

regions of the Earth, and electrons that are trapped in the belt are lost. These auroral electrons, which are 

observed only in the polar regions, are associated with the coronal mass ejection (CME) that occurs after 

solar flares. 

In association with many of the optical flares that occur from time to time on the solar surface, large fluxes 

of solar energetic particles are sometimes accelerated and emitted; these emissions of solar cosmic radiation 

are designated as SPEs. SPEs, with periods of several hours to days, represent one of several short-lived manifestations of the active sun. The solar wind and SPEs are composed of the same types of particles, primarily 

protons with the next significant component being α-particles. These two groups of particles are distinguished 

by their numbers as well as their speed or energy. Heavier nuclei, which are mostly in the carbon, nitrogen, and 

oxygen group (NCRP, 2006), and even heavier particles (atomic charge number, Z, between 22 and 30) have also 

been observed in major SPEs. Rare clusters of events of high intensity (i.e., of several orders of magnitude) with 

large numbers of high-energy particles are critical to space flight and EVA because the large events alone determine the yearly fluences of solar particles, and there is a much higher dose-rate effect during the short period 

of peak intensity (Kim et al., 2006b). 
Human Health and Performance Risks of Space Exploration Missions Chapter 5 

Risk of Acute Radiation Syndromes Due to Solar Particle Events 181

For recent solar cycles 19 through 21 (1955–1986), a list of major SPEs and associated proton fluences has 

been assembled by Shea and Smart (1990), who place all of the available flux and fluence data in a useful 

continuous database. From 1986 to the present (solar cycles 22 and 23), both an SPE list and the geostationary operational environmental satellite (GOES) spacecraft measurements of the 5-minute-average integral proton 

flux can be obtained through direct access to the National Oceanographic and Atmospheric Agency (NOAA) 

National Geophysical Data Center. Table 5-2 lists the large SPEs that occurred in the past five solar cycles for 

which the omnidirectional proton fluence with energy above 30 MeV, Φ30, exceeded 109

 protons/cm2. 

Table 5-2. Large SPEs during Solar Cycles 19 through 23 

Corresponding to 30 > 109

 protons/cm2 

Solar Cycle SPE >30

protons/cm2

19 11/12/1960 9.00  109

20 08/02/1972 5.00  109

22 10/19/1989 4.23  109

23 07/14/2000 3.74  109

23 10/26/2003 3.25  109

23 11/04/2001 2.92  109

19 07/10/1959 2.30  109

23 11/08/2000 2.27  109

22 03/23/1991 1.74  109

22 08/12/1989 1.51  109

22 09/29/1989 1.35  109

23 01/16/2005 1.04  109

19 02/23/1956 1.00  109

In Figure 5-3, the frequency of SPE occurrence that was recorded by the NOAA GOESs for solar cycle 23 

is shown for 3-month periods. The monthly mean number of sunspots is included in the figure to show the 

association between SPE occurrence and solar activity. The times at which the five largest SPEs with Φ30 > 

109

 protons/cm2 occurred are marked with arrows. It is expected that an increase in SPEs occurs with increasing solar activity; however, no recognizable pattern has been identified. Large events have occurred 

during solar active years, but have not always occurred during months of solar maximal activity. Moreover, 

large events are more likely to occur in the ascending or declining phases of a solar cycle. This sporadic 

behavior of SPE occurrence is a major operational problem in planning for missions to the moon and Mars. 

The shapes of the energy spectra, as well as the total fluence, vary considerably from event to event. Figure 5-4 

shows the energy spectra of the January 16, 2005 SPE, which is one of the more recent large events. At that time, 

there was a sudden increase in proton flux, especially in particles with energies that were greater than 50 MeV. 

Protons with energies that were greater than 100 MeV increased by as much as four orders of magnitude after 

they declined following the major pulse. During this sharp commencement, the fluence did not reach the value 

that was obtained at the major peak intensities; however, this type of sudden increase in high-energy particles 

may pose a greater threat than the major particle intensities. Total fluence of an SPE is the representative 

indicator of a large SPE, and the detailed energy spectra for a large SPE – especially at high energies – is 

the important parameter for assessing the risk of radiation exposure (Kim et al., 2006b). 

 
Chapter 5 Human Health and Performance Risks of Space Exploration Missions 

182 Risk of Acute Radiation Syndromes Due to Solar Particle Events 

Figure 5-3. Frequency of SPE occurrence in 3-month periods of solar cycle 23. The 

arrows indicate the times at which large SPEs with 30>109

 protons/cm2 occurred. 

Figure 5-4. Hourly-average proton flux from GOES measurements during 

the SPE of January 16–22, 2005. 

A detailed temporal analysis of dose-rate at the BFOs for the August 1972 SPE is illustrated in figure 5-5. 

This event, which was one of the largest SPEs in the modern era, had the highest dose-rate at its peak. The 

temporal behavior that is shown in figure 5-5 suggests that significant biological damage would occur in a crew 

if adequate shielding is not provided. Figure 5-6 shows the SPE doses during this same event. Estimates for the 

>30 MeV flux, which were determined from nitrate samples and then scaled to the August 1972 energy 

0

1

2

3

4

5

6

7

8

3

12

213039485766

758493

102111

120

Time from Solar Minimum, month

Frequency

0

50

100

150

200

Smoothed Monthly Sunspot Number

Frequency

Monthly sunspot number

1.E-01

1.E+00

1.E+01

1.E+02

1.E+03

1.E+04

1.E+05

0 20 40 60 80 100 120 140 160 180

Time, h

Flux, protons/cm2-s

E = 10 MeV

E = 30 MeV

E = 60 MeV

E > 100 MeV
Human Health and Performance Risks of Space Exploration Missions Chapter 5 

Risk of Acute Radiation Syndromes Due to Solar Particle Events 183

spectra, are also shown. Biological effects are expected to increase significantly for dose-rates that are 

above 0.05 Gy/h. For an extended EVA, the current recommended 30-day exposure limit for the BFOs, which 

is 0.25 Gy-Eq (NCRP, 2000), is easily exceeded. The early effects from acute exposure may not be avoided 

when only a conventional amount of spacecraft material is provided to protect the BFOs from this class of SPE. 

To avoid placing unrealistic mass on a space vehicle while at the same time increasing safety factors for the 

astronauts, one solution for shielding against SPEs would be to select optimal materials for the vehicle structure and shielding. To this end it has been shown that materials that have lower atomic mass constituents have 

better shielding effectiveness (Wilson et al., 1999, Cucinotta, 1999). Overall exposure levels from this specific 

event have been estimated to be greater than 100 mSv (10 rem) at sensitive sites, while those from other large SPEs 

that have been recorded in the modern era can be reduced to below 0.1 Sv when heavily shielded “storm shelters” 

are added to a typical spacecraft (Kim et al., 2006b). Interpretation of this result, however, should be made while 

keeping in mind the caveat that significant uncertainties are inherent in determining the source spectra of 

protons (Musgrave et al., 2009.) 

Figure 5-5. Dose-rate to the BFO for increasing levels of aluminum shielding for the 

large SPE of August 1972 (Kim et al., 2006a). 

 Solar alert and monitoring 

An effective operational procedure requires an SPE warning or alert system. This system, which would be 

activated at the onset of proton exposure, would include pertinent information concerning the event, such as 

the fluence or flux and the energy distribution. These capabilities do not exist at the current time, and forecasts 

from NOAA are limited. New capabilities for deep-space mission forecasting will be needed prior to the Mars 

mission because the alignment of the Earth and Mars does not allow all SPEs on Mars to be observed from 

Earth. A recent report by the NRC discussed research approaches in space science that should lead to improved 

forecasting and alert capabilities for SPEs (NAS/NRC, 2006), including a status of approaches supported by the 

NASA Science Mission Directorate. 
Chapter 5 Human Health and Performance Risks of Space Exploration Missions 

184 Risk of Acute Radiation Syndromes Due to Solar Particle Events 

The most likely outcome of an SPE is mission disruption with little or no harm to the crew because, despite 

the occurrence of some very large SPEs such as the 1972 event described previously, more than 90% of SPEs 

result in very small radiation doses to critical organs (<10cGy-Eq), as shown in figure 5-6. Mission disruption 

is likely because the size of the SPE cannot be determined until several hours after its initial onset. Reliable 

radiation dosimeters that can transmit to Mission Control and provide a self-alert to astronauts are required. Such 

instrumentation has been available for many years, including during the Apollo missions (NCRP, 1989). 

A recent publication (Posner, 2007) provides evidence that detection of relativistic solar electrons may enable 

as much as a 1-hour warning of proton events as well as prediction of the integral number of protons that can 

be expected, as illustrated in figure 5-7. The color matrix that is shown provides a code to predict future proton 

intensity, 1 hour ahead of time, as predicted by relativistic electron measurements. The parameter space is 

given by the current maximum electron increase parameter, which goes back in time at least 5 minutes and up 

to 60 minutes, and current relativistic electron intensity. The matrix is derived from the aggregate of all 1998 

to 2002 relativistic electron observations and their corresponding 30- to 50-MeV proton intensities that occurred 

1 hour later. Data was obtained from the comprehensive suprathermal and energetic particle analyzer (COSTEP) 

instrument on the solar and heliospheric observatory (SOHO) satellite. The color shows the average for the 

proton intensity in each locus. Statistical considerations limit the utility of the matrix at the bottom and upperright ranges. The importance of the findings of Posner (2007) cannot be overestimated as they not only provide 

up to a 1-hour early detection capability, but also may allow astronauts and Mission Control personnel to predict 

whether an event will likely be of insignificant size, which is the most likely outcome. Long-term forecasting 

from hours to days before the onset of an SPE at this time is inherently inaccurate, with a large number of false 

alarms predicted and many events not predicted at all (NCRP, 2006). 

1.E-05

1.E-04

1.E-03

1.E-02

1.E-01

1.E+00

1.E+03 1.E+04 1.E+05 1.E+06 1.E+07 1.E+08 1.E+09 1.E+10 1.E+11

Size of Event (>30)

SPE/Mission

0.1

1

10

100

1000

BFO Dose, cGy-Eq

NCRP 30-day limit at BFO for LEO mission

Figure 5-6. Probability of SPE in a 1-week 

mission (thin line: average probability of SPE 

and statistical fluctuation during space era; thick 

line: extended average probability including 

impulsive nitrate events; impulsive nitrate 

events data) and BFO dose (---- BFO dose of 

the worst-case SPE model scaled by >30 flux 

to August 1972 SPE;  BFO dose of 34 large 

SPEs during space era using actual spectra).
Human Health and Performance Risks of Space Exploration Missions Chapter 5 

Risk of Acute Radiation Syndromes Due to Solar Particle Events 185

 Mechanisms of radiation-induced vomiting 

The mechanisms by which radiation induces nausea and vomiting are not well understood. It is known 

that radiation induces the secretion of serotonin in the GI-tract. In turn, the binding of serotonin to receptors 

in the brain mediates vomiting. The physiological effects of high-dose radiation are also mediated, in part, by 

inflammatory responses. Increased secretion of inflammatory cytokines IL-12 and IL-18 was reported in mouse 

macrophages after irradiation (Shan et al., 2007). Increased production of IL-6 and TNF-α, which are also proinflammatory cytokines, has been observed in the lungs of irradiated mice (Fedorocko et al., 2002). Pro-inflammatory cytokines mediate symptoms of nausea, vomiting, anorexia, and cachexia in instances of cancer and 

other diseases as well as pregnancy. In addition, ionizing radiation directly generates numerous reactive oxygen 

species. Additional reactive oxygen species are indirectly generated by cellular responses to radiation, initiating 

long-lasting cascades of inflammatory events. How these molecules interact to induce the symptoms of prodromal syndrome is unknown. 

 Potential for biological countermeasures 

Radioprotectors, such as antioxidants, are agents that reduce the damage to various organs by radiation 

(Gudkow and Komarova, 2005). The likelihood that SPE will produce doses that are above 1 Gy is small, while 

the occurrence of doses that can induce prodromal risks are quite possible. Although prodromal syndrome may 

seem more innocuous than the other symptoms of ARS, biological countermeasures for the prodromal risks are 

a major consideration. Many radioprotectors, including antioxidants and WR-2721, are not expected to counFigure 5-7. One-hour lead time prediction of 

proton spectra that are generated from real-time 

electron measurements (Posner, 2007). 
Chapter 5 Human Health and Performance Risks of Space Exploration Missions 

186 Risk of Acute Radiation Syndromes Due to Solar Particle Events 

teract prodromal risks such as vomiting or nausea (Harding, 1988). Several classes of drugs have been used to 

treat the nausea and vomiting that are experienced by patients who are undergoing whole-body radiotherapy 

(Harding, 1988). While the molecules that regulate vomiting are not well understood, the inhibitors or antagonists of serotonin, dopamine, histamine, and substance P suppress vomiting. Clinical trials have demonstrated 

that serotonin antagonists were more effective than prochlorperazine or metoclopramide (Franzen et al., 1996; 

Priestman et al., 1993). Of the 5-HT3 class drugs, ondansetron has been best studied (Licitra et al., 2002). Studies 

of the efficacy of combinations of drugs of different classes, such as palonosetron and aprepitant when used 

with olanzapine or gabapentin, are under way to prevent acute and delayed chemotherapy-induced nausea and 

vomiting (Navari and Province, 2006). These treatments need to be investigated to determine the efficacy and 

tolerability for SPE-induced prodromal effects. Cannabinoids, anticholinergics, steroids, benzodiazepides, and 

plant extracts are also currently being evaluated for their antiemetic properties. Thus, the mechanisms of SPEinduced prodromal symptoms are unclear, but a broad spectrum of potential countermeasures is available for 

testing. 

 Conclusion 

The biological effects of space radiation, including ARS, are a significant concern. High doses of radiation can 

induce profound radiation sickness and death. Lower doses of radiation induce symptoms that are much milder 

physiologically, but that pose operational risks that are equally serious. Both scenarios have the potential to 

seriously affect crew health and/or prevent the completion of mission objectives. Radiation protection must be 

provided in the form of predictive models, shielding, and biological countermeasures when traveling outside of 

the protective magnetosphere of the Earth. Unfortunately, the development of these tools is hindered by a lack 

of relevant space radiation research. Most radiation studies focus on radiation species and doses that are unlike 

the radiation that is encountered in space. There is therefore a pressing need for research that accurately reflects 

the radiation risks that are native to the space environment and that facilitate the development of both improved 

risk assessment and effective radioprotective strategies. 

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Risk of Acute or Late Central Nervous System Effects from Radiation Exposure 191

Chapter 6: 

Risk of Acute or Late Central Nervous System 

Effects from Radiation Exposure 

Francis A. Cucinotta 

NASA Johnson Space Center 

Huichen Wang 

Emory University School of Medicine 

Janice L. Huff 

Universities Space Research Association 

Acute and late radiation damage to the central nervous system (CNS) may lead to changes in motor function 

and behavior, or neurological disorders. Radiation and synergistic effects of radiation with other space flight 

factors may affect neural tissues, which in turn may lead to changes in function or behavior. Data specific to 

the spaceflight environment must be compiled to quantify the magnitude of this risk. If this is identified as a 

risk of high enough magnitude then appropriate protection strategies should be employed. – Human Research 

Program Requirements Document, HRP-47052, Rev. C, dated Jan 2009. 

 Acute and late radiation damage to the 

central nervous system (CNS) may lead to 

changes in motor function and behavioral 

or neurological disorders. A vigorous 

ground-based cellular and animal model 

research program will help quantify the 

risk to the CNS from space radiation 

exposure on future long distance space 

missions and promote the development of

optimized countermeasures. © Sebastian 

Kaulitzki - Fotolia.com
192 Risk of Acute or Late Central Nervous System Effects from Radiation Exposure 
Human Health and Performance Risks of Space Exploration Missions Chapter 6 

Risk of Acute or Late Central Nervous System Effects from Radiation Exposure 193

 Executive Summary 

Possible acute and late risks to the CNS from GCRs and SPEs are a documented concern for human exploration of our solar system (NAS, 1973; NAS/NRC, 1996, NCRP, 2006). In the past, the risks to the CNS of adults 

who were exposed to low to moderate doses of ionizing radiation ((0 to 2 Gy (1 Gray) (Gy = 100 rad)) have not 

been a major consideration. However, the heavy ion component of space radiation presents distinct biophysical 

challenges to cells and tissues as compared to the physical challenges that are presented by terrestrial forms of 

radiation. Soon after the discovery of cosmic rays, the concern for CNS risks originated with the prediction of 

the light flash phenomenon from single HZE nuclei traversals of the retina (Tobias, 1952); this phenomenon 

was confirmed by the Apollo astronauts in 1970 and 1973. HZE nuclei are capable of producing a column of 

heavily damaged cells, or a microlesion, along their path through tissues, thereby raising concern over serious 

impacts on the CNS (Todd, 1989). In recent years, other concerns have arisen with the discovery of neurogenesis and its impact by HZE nuclei, which have been observed in experimental models of the CNS. 

Human epidemiology is used as a basis for risk estimation for cancer, acute radiation risks, and cataracts. 

This approach is not viable for estimating CNS risks from space radiation, however. At doses above a few Gy, 

detrimental CNS changes occur in humans who are treated with radiation (e.g., gamma rays and protons) for 

cancer. Treatment doses of 50 Gy are typical, which is well above the exposures in space even if a large SPE 

were to occur. Thus, of the four categories of space radiation risks (cancer, CNS, degenerative, and acute radiation syndromes), the CNS risk relies most extensively on experimental data with animals for its evidence base. 

Understanding and mitigating CNS risks requires a vigorous research program that will draw on the basic understanding that is gained from cellular and animal models, and on the development of approaches to extrapolate risks and the potential benefits of countermeasures for astronauts. 

Several experimental studies, which use heavy ion beams simulating space radiation, provide constructive 

evidence of the CNS risks from space radiation. First, exposure to HZE nuclei at low doses (<50 cGy) significantly induces neurocognitive deficits, such as learning and behavioral changes as well as operant reactions in 

the mouse and rat. Exposures to equal or higher doses of low-LET radiation (e.g., gamma or X rays) do not show 

similar effects. The threshold of performance deficit following exposure to HZE nuclei depends on both the physical characteristics of the particles, such as LET, and the animal age at exposure. A performance deficit has been 

shown to occur at doses that are similar to the ones that will occur on a Mars mission (<0.5 Gy). The neurocognitive deficits with the dopaminergic nervous system are similar to aging and appear to be unique to space radiation. 

Second, exposure to HZE disrupts neurogenesis in mice at low doses (<1 Gy), showing a significant dose-related 

reduction of new neurons and oligodendrocytes in the subgranular zone (SGZ) of the hippocampal dentate gyrus. 

Third, reactive oxygen species (ROS) in neuronal precursor cells arise following exposure to HZE nuclei and 

protons at low dose, and can persist for several months. Antioxidants and anti-inflammatory agents can possibly 

reduce these changes. Fourth, neuroinflammation arises from the CNS following exposure to HZE nuclei and 

protons. In addition, age-related genetic changes increase the sensitivity of the CNS to radiation. 

Research with animal models that are irradiated with HZE nuclei has shown that important changes to the 

CNS occur with the dose levels that are of concern to NASA. However, the significance of these results on 

the morbidity to astronauts has not been elucidated. One model of late tissue effects (Rubin and Casarett, 1968) 

suggests that significant effects will occur at lower doses, but with increased latency. It is to be noted that the 

studies that have been conducted to date have been carried out with relatively small numbers of animals (<10 per 

dose group); therefore, testing of dose threshold effects at lower doses (<0.5 Gy) has not been carried out sufficiently at this time. As the problem of extrapolating space radiation effects in animals to humans will be a challenge 

for space radiation research, such research could become limited by the population size that is used in animal 
Chapter 6 Human Health and Performance Risks of Space Exploration Missions 

194 Risk of Acute or Late Central Nervous System Effects from Radiation Exposure 

studies. Furthermore, the role of dose protraction has not been studied to date. An approach to extrapolate existing observations to possible cognitive changes, performance degradation, or late CNS effects in astronauts has 

not been discovered. New approaches in systems biology offer an exciting tool to tackle this challenge. Recently, 

eight gaps were identified for projecting CNS risks. Research on new approaches to risk assessment may be 

needed to provide the necessary data and knowledge to develop risk projection models of the CNS from 

space radiation. 

 Introduction 

Both GCRs and SPEs are of concern for CNS risks. The major GCRs are composed of protons, α-particles, 

and particles of HZE nuclei with a broad energy spectra ranging from a few tens to above 10,000 MeV/u. In 

interplanetary space, GCR organ dose and dose-equivalent of more than 0.2 Gy or 0.6 Sv per year, respectively, 

are expected (Cucinotta et al., 2003; Cucinotta and Durante, 2006). The high energies of GCRs allow them to 

penetrate to hundreds of centimeters of any material, thus precluding radiation shielding as a plausible mitigation 

measure to GCR risks on the CNS. For SPEs, the possibility exists for an absorbed dose of over 1 Gy from an 

SPE if crew members are in a thinly shielded spacecraft or performing a spacewalk (Kim et al., 2007). The 

energies of SPEs, although substantial (tens to hundreds of MeV), do not preclude radiation shielding as a 

potential countermeasure. However, the costs of shielding may be high to protect against the largest events. 

The fluence of charged particles hitting the brain of an astronaut has been estimated several times in the 

past (Craven and Rycroft, 1994; Curtis et al., 1989; Cucinotta et al., 1998). One estimate is that during a 3-year 

mission to Mars at solar minimum (assuming the 1972 spectrum of GCR), 20 million out of 43 million hippocampus cells and 230 thousand out of 1.3 million thalamus cell nuclei will be directly hit by one or more particles 

with charge Z>15 (Curtis et al., 1998; 2000). These numbers do not include the additional cell hits by energetic 

electrons (delta rays) that are produced along the track of HZE nuclei (Cucinotta et al., 1998) or correlated cellular damage (Cucinotta et al., 1999; Ponomarev and Cucinotta, 2006). The contributions of delta rays from 

GCR and correlated cellular damage increase the number of damaged cells two- to three-fold from estimates 

of the primary track alone and present the possibility of heterogeneously damaged regions, respectively. The 

importance of such additional damage is poorly understood. 

At this time, the possible detrimental effects to an astronaut’s CNS from the HZE component of GCR have 

yet to be identified. This is largely due to the lack of a human epidemiological basis with which to estimate 

risks and the relatively small number of published experimental studies with animals. RBE factors are combined 

with human data to estimate cancer risks for low-LET radiation exposure. Since this approach is not possible for 

CNS risks, new approaches to risk estimation will be needed. Thus, biological research is required to establish risk 

levels and risk projection models and, if the risk levels are found to be significant, to design countermeasures. 

 Description of central nervous system risks of concern to NASA 

Acute and late CNS risks from space radiation are of concern for Exploration missions to the moon or Mars. 

Acute CNS risks include: altered cognitive function, reduced motor function, and behavioral changes, all of 

which may affect performance and human health. Late CNS risks are possible neurological disorders such as 

Alzheimer’s disease, dementia, or premature aging. The effect of the protracted exposure of the CNS to the low 

dose-rate (< 50 mGy h–1) of proton, HZE particles, and neutrons of the relevant energies for doses up to 2 Gy is 

of concern. 
Human Health and Performance Risks of Space Exploration Missions Chapter 6 

Risk of Acute or Late Central Nervous System Effects from Radiation Exposure 195

 Current NASA permissible exposure limits 

PELs for short-term and career astronaut exposure to space radiation have been approved by the NASA Chief 

Health and Medical Officer. The PELs set requirements and standards for mission design and crew selection as 

recommended in NASA-STD-3001, Volume 1. NASA has used dose limits for cancer risks and the non-cancer 

risks to the BFOs, skin, and lens since 1970. For Exploration mission planning, preliminary dose limits for the 

CNS risks are based largely on experimental results with animal models. Further research is needed to validate 

and quantify these risks, however, and to refine the values for dose limits. The CNS PELs, which correspond to 

the doses at the region of the brain called the hippocampus, are set for time periods of 30 days or 1 year, or for a 

career with values of 500, 1,000, and 1,500 mGy-Eq, respectively. Although the unit mGy-Eq is used, the RBE 

for CNS effects is largely unknown; therefore, the use of the quality factor function for cancer risk estimates is 

advocated. For particles with charge Z>10, an addition PEL requirement limits the physical dose (mGy) for 

1 year and the career to 100 and 250 mGy, respectively. NASA uses computerized anatomical geometry 

models to estimate the body self-shielding at the hippocampus. 

 Evidence 

 Review of human data 

Evidence of the effects of terrestrial forms of ionizing radiation on the CNS has been documented from radiotherapy patients, although the dose is higher for these patients than would be experienced by astronauts in the 

space environment. CNS behavioral changes such as chronic fatigue and depression occur in patients who are 

undergoing irradiation for cancer therapy (Tolifon and Fike, 2000). Neurocognitive effects, especially in children, 

are observed at lower radiation doses (Schultheiss et al., 1995; BEIR-V, 1990). A recent review on intelligence and 

the academic achievement of children after treatment for brain tumors indicates that radiation exposure is related 

to a decline in intelligence and academic achievement, including low intelligence quotient (IQ) scores, verbal 

abilities, and performance IQ; academic achievement in reading, spelling, and mathematics; and attention functioning (Butler and Haser, 2006). Mental retardation was observed in the children of the atomic-bomb survivors 

in Japan who were exposed to radiation prenatally at moderate doses (<2 Gy) at 8 to 15 weeks post-conception, 

but not at earlier or later prenatal times (BEIR-V, 1990). 

Radiotherapy for the treatment of several tumors with protons and other charged particle beams provides ancillary data for considering radiation effects for the CNS. NCRP Report No. 153 (NCRP, 2006) notes charge 

particle usage “for treatment of pituitary tumors (Kjellberg and Kliman, 1979; Linfoot, 1979), hormone-responsive 

metastatic mammary carcinoma (Tobias, 1979), brain tumors (Castro et al., 1985; Suit et al., 1982), and intracranial 

arteriovenous malformations and other cerebrovascular diseases (Fabrikant et al., 1989; Fabrikant et al., 1985; 

Fabrikant et al., 1984; Kjellberg et al., 1983; Levy et al., 1989; Steinberg et al., 1990).” In these studies are found 

associations with neurological complications such as impairments in cognitive functioning, language acquisition, 

visual spatial ability, and memory and executive functioning, as well as changes in social behaviors. Similar effects did not appear in patients who were treated with chemotherapy. In all of these examples, the patients were 

treated with extremely high doses that were below the threshold for necrosis (Goldberg et al., 1982; KeimeGuibert et al., 1998). Since cognitive functioning and memory are closely associated with the cerebral white 

volume of the prefrontal/frontal lobe and cingulate gyrus, defects in neurogenesis may play a critical role 

in neurocognitive problems in irradiated patients (NCRP, 2006). 
Chapter 6 Human Health and Performance Risks of Space Exploration Missions 

196 Risk of Acute or Late Central Nervous System Effects from Radiation Exposure 

 Review of space flight issues 

The first proposal concerning the effect of space radiation on the CNS was made by Cornelius Tobias in his 

1952 description of light flash phenomenon caused by single HZE nuclei traversals of the retina (Tobias et al., 

1952). Light flashes, such as those described by Tobias, were observed by the astronauts during the early Apollo 

missions as well as in dedicated experiments that were subsequently performed on Apollo and Skylab missions 

(Pinsky et al., 1974). More recently, studies of light flashes were made on the Russian Mir space station and the 

ISS (Sannita et al., 2004). A 1973 report by the NAS considered these effects in detail. This phenomenon, which 

is known as a phosphene, is the visual perception of flickering light. It is considered a subjective sensation of 

light since it can be caused by simply applying pressure on the eyeball (NCRP, 2006). The traversal of a single, 

highly charged particle through the occipital cortex or the retina was estimated to be able to cause a light flash. 

Possible mechanisms for HZE-induced light flashes include direction ionization and Cerenkov radiation within 

the retina (NAS, 1973). 

The observation of light flashes by the astronauts brought attention to the possible effects of HZE nuclei 

on brain function. The microlesion concept, which considered the effects of the column of damaged cells 

surrounding the path of an HZE nucleus traversing critical regions of the brain, originated at this time (NAS, 

1973; Todd, 1989). An important task that still remains is to determine whether and to what extent such particle 

traversals contribute to functional degradation within the CNS. 

The possible observation of CNS effects in astronauts who were participating in past NASA missions is highly 

unlikely for several reasons. First, the lengths of past missions are relatively short and the population sizes of 

astronauts are small. Second, when astronauts are traveling in LEO, they are partially protected by the magnetic 

field and the solid body of the Earth, which together reduce the GCR dose-rate by about two-thirds from its free 

space values. Furthermore, the GCR in LEO has lower LET components compared to the GCR that will be encountered in transit to Mars or on the lunar surface because the magnetic field of the Earth repels nuclei with 

energies that are below about 1,000 MeV/u, which are of higher LET. For these reasons, the CNS risks are a 

greater concern for long-duration lunar missions or for a Mars mission than for missions on the ISS. 

 Radiobiology studies of central nervous system risks for protons, 

 neutrons, and high-Z high-energy nuclei 

Both GCR and SPE could possibly contribute to acute and late CNS risks to astronaut health and performance. 

This section presents a description of the studies that have been performed on the effects of space radiation in 

cell, tissue, and animal models. 

 Effects in Neuronal Cells and the Central Nervous System 

Neurogenesis

The CNS consists of neurons, astrocytes, and oligodendrocytes that are generated from multipotent stem 

cells. NCRP Report No. 153 provides the following excellent and short introduction to the composition and 

cell types of interest for radiation studies of the CNS (NCRP, 2006): “The CNS consists of neurons differing 

markedly in size and number per unit area. There are several nuclei or centers that consist of closely packed 

neuron cell bodies (e.g., the respiratory and cardiac centers in the floor of the fourth ventricle). In the cerebral 

cortex the large neuron cell bodies, such as Betz cells, are separated by a considerable distance. Of additional 

importance are the neuroglia which are the supporting cells and consist of astrocytes, oligodendroglia, and 

microglia. These cells permeate and support the nervous tissue of the CNS, binding it together like a scaffold that also supports the vasculature. The most numerous of the neuroglia are Type I astrocytes, which 

make up about half the brain, greatly outnumbering the neurons. Neuroglia retain the capability of cell 
Human Health and Performance Risks of Space Exploration Missions Chapter 6 

Risk of Acute or Late Central Nervous System Effects from Radiation Exposure 197

division in contrast to neurons and, therefore, the responses to radiation differ between the cell types. A 

third type of tissue in the brain is the vasculature which exhibits a comparable vulnerability for radiation 

damage to that found elsewhere in the body (Reinhold and Hopewell, 1980). Radiation-induced damage to 

oligodendrocytes and endothelial cells of the vasculature accounts for major aspects of the pathogenesis of 

brain damage that can occur after high doses of low-LET radiation.” Based on studies with low-LET radiation, the CNS is considered a radioresistant tissue. For example: in radiotherapy, early brain complications 

in adults usually do not develop if daily fractions of 2 Gy or less are administered with a total dose of up to 

50 Gy (NCRP, 2006). The tolerance dose in the CNS, as with other tissues, depends on the volume and the 

specific anatomical location in the human brain that is irradiated (Schultheiss et al., 1995). 

In recent years, studies with stem cells uncovered that neurogenesis still occurs in the adult hippocampus, where cognitive actions such as memory and learning are determined (Squire, 1992; Eisch, 2002). 

This discovery provides an approach to understand mechanistically the CNS risk of space radiation. Accumulating data indicate that radiation not only affects differentiated neural cells, but also the proliferation 

and differentiation of neuronal precursor cells and even adult stem cells. Recent evidence points out that 

neuronal progenitor cells are sensitive to radiation (Mizumatsu et al., 2003; Monje et al., 2002; Tofilon and 

Fike, 2000). Studies on low-LET radiation show that radiation stops not only the generation of neuronal progenitor cells, but also their differentiation into neurons and other neural cells. NCRP Report No. 153 (NCRP, 

2006) notes that cells in the SGZ of the dentate gyrus undergo dose-dependent apoptosis above 2 Gy of 

X-ray irradiation, and the production of new neurons in young adult male mice is significantly reduced by 

relatively low (>2 Gy) doses of X rays. NCRP Report No. 153 (NCRP, 2006) also notes that: “These changes 

are observed to be dose dependent. In contrast there were no apparent effects on the production of new astrocytes or oligodendrocytes. Measurements of activated microglia indicated that changes in neurogenesis 

were associated with a significant dose-dependent inflammatory response even 2 months after irradiation. 

This suggests that the pathogenesis of long-recognized radiation-induced cognitive injury may involve loss 

of neural precursor cells from the SGZ of the hippocampal dentate gyrus and alterations in neurogenesis.” 

Recent studies provide evidence of the pathogenesis of HZE nuclei in the CNS (Casadesus et al., 2004; 

2005; Rola et al., 2004; 2005). The authors of one of these studies (Casadesus et al., 2005) were the first to 

suggest neurodegeneration with HZE nuclei, as shown in figure 6-1(a). These studies demonstrate that HZE 

radiation led to the progressive loss of neuronal progenitor cells in the SGZ at doses of 1 to 3 Gy in a dosedependent manner. NCRP Report No. 153 (NCRP, 2006) notes that “Mice were irradiated with 1 to 3 Gy of 

12C or 56Fe-ions and 9 months later proliferating cells and immature neurons in the dentate SGZ were quantified. The results showed that reductions in these cells were dependent on the dose and LET. Loss of precursor 

cells was also associated with altered neurogenesis and a robust inflammatory response, as shown in figures 

6-1(a) and 6-1(b). These results indicate that high-LET radiation has a significant and long-lasting effect on 

the neurogenic population in the hippocampus that involves cell loss and changes in the microenvironment. 

The work has been confirmed by other studies (Casadesus et al., 2004; Casadesus et al., 2005). These investigators noted that these changes are consistent with those found in aged subjects, indicating that 

heavy-particle irradiation is a possible model for the study of aging.” 

 
Chapter 6 Human Health and Performance Risks of Space Exploration Missions 

198 Risk of Acute or Late Central Nervous System Effects from Radiation Exposure 

Figure 6-1(a). (Panel A) Expression of polysialic acid form of neural cell 

adhesion molecule (PSA-NCAM) in the hippocampus of rats that were 

irradiated (IR) with 2.5 Gy of 56Fe high-energy radiation and control subjects as measured by % density/field area measured. (Panel B) PSA-NCAM 

staining in the dentate gyrus of representative irradiated (IR) and control 

(C) subjects at 5 magnification (Casadesus et al., 2005). 

Figure 6-1(b). Numbers of proliferating cells (left panel) and immature 

neurons (right panel) in the dentate SGZ are significantly decreased 48 

hours after irradiation. Antibodies against Ki-67 and doublecortin (Dcx) 

were used to detect proliferating cells and immature neurons, respectively. 

Doses from 2 to 10 Gy significantly (p < 0.05) reduced the numbers of 

proliferating cells. Immature neurons were also reduced in a dosedependent fashion (p<0.001). Each bar represents an average of four 

animals; error bars, and standard error (Mizumatsu et al., 2003). 

Oxidative damage

Recent studies indicate that adult rat neural precursor cells from the hippocampus show an acute, dosedependent apoptotic response that was accompanied by an increase in ROS Limoli et al., 2004). Low-LET 

protons are also used in clinical proton beam radiation therapy, at an RBE of 1.1 relative to megavoltage 

X rays at a high dose. NCRP Report No. 153 (NCRP, 2006) notes that: “Relative ROS levels were increased 

at nearly all doses (1 to 10 Gy) of Bragg-peak 250 MeV protons at post-irradiation times (6 to 24 hours) compared to unirradiated controls (Giedzinski et al., 2005). The increase in ROS after proton irradiation was 
Human Health and Performance Risks of Space Exploration Missions Chapter 6 

Risk of Acute or Late Central Nervous System Effects from Radiation Exposure 199

more rapid than that observed with X rays and showed a well-defined dose response at 6 and 24 hours, increasing about 10-fold over controls at a rate of 3% per Gy. However, by 48 hours post-irradiation, ROS 

levels fell below controls and coincided with minor reductions in mitochondrial content. Use of the antioxidant alpha-lipoic acid (before or after irradiation) was shown to eliminate the radiation-induced rise in ROS 

levels. These results corroborate the earlier studies using X rays and provide further evidence that elevated 

ROS are integral to the radioresponse of neural precursor cells.” Furthermore, high-LET radiation led to 

significantly higher levels of oxidative stress in hippocampal precursor cells as compared to lower-LET 

radiations (X rays, protons) at lower doses (≤1 Gy) (figure 6-2). The use of the antioxidant lipoic acid was 

able to reduce ROS levels below background levels when added before or after 56Fe-ion irradiation. These 

results conclusively show that low doses of 56Fe-ions can elicit significant levels of oxidative stress in 

neural precursor cells at a low dose. 

Neuroinflammation

Neuroinflammation, which is a fundamental reaction to brain injury, is characterized by the activation of 

resident microglia and astrocytes and local expression of a wide range of inflammatory mediators. Acute 

and chronic neuroinflammation has been studied in the mouse brain following exposure to HZE. The acute 

effect of HZE is detectable at 6 and 9 Gy; no studies are available at lower doses. Myeloid cell recruitment 

appears by 6 months following exposure. The estimated RBE value of HZE irradiation for induction of an 

acute neuroinflammatory response is three compared to that of gamma irradiation (Rola et al., 2005). COX2 pathways are implicated in neuroinflammatory processes that are caused by low-LET radiation. COX-2 

up-regulation in irradiated microglia cells leads to prostaglandin E2 production, which appears to be responsible for radiation-induced gliosis (overproliferation of astrocytes in damaged areas of the CNS) 

(Kyrkanides et al., 2002; Moore et al., 2005; Hwang et al., 2006). 

 Behavioral Effects 

As behavioral effects are difficult to quantitate, they consequently are one of the most uncertain of the 

space radiation risks. NCRP Report No. 153 (NCRP, 2006) notes that: “The behavioral neurosciences 

literature is replete with examples of major differences in behavioral outcome depending on the animal 

species, strain, or measurement method used. For example, compared to unirradiated controls, X-irradiated 

mice show hippocampal-dependent spatial learning and memory impairments in the Barnes maze, but not in 

Figure 6-2. Dose response for oxidative stress after 56Fe-ion irradiation. Hippocampal precursors that are 

subjected to 56Fe-ion irradiation were analyzed for oxidative stress 6 hours after exposure. At doses ≤1 Gy a 

linear dose response for the induction of oxidative stress 

was observed. At higher 56Fe doses, oxidative stress fell 

to values that were found using lower-LET irradiations 

(X rays, protons). Experiments, which represent a 

minimum of three independent measurements (±SE), 

were normalized against unirradiated controls set to 

unity. ROS levels induced after 56Fe irradiation were 

significantly (P < 0.05) higher than controls 

(Limoli et al., 2007).
Chapter 6 Human Health and Performance Risks of Space Exploration Missions 

200 Risk of Acute or Late Central Nervous System Effects from Radiation Exposure 

the Morris water maze (Raber et al., 2004) which, however, can be used to demonstrate deficits in rats (ShukittHale et al., 2003; Shukitt-Hale et al., 2000). Particle radiation studies of behavior have been accomplished 

with rats and mice, but with some differences in the outcome depending on the endpoint measured.” 

The following studies provide evidence that space radiation affects the CNS behavior of animals in a 

somewhat dose- and LET-dependent manner. 

Sensorimotor effects

Sensorimotor deficits and neurochemical changes were observed in rats that were exposed to low doses of 

56Fe-ions (Joseph et al., 1992; 1993). Doses that are below 1 Gy reduce performance, as tested by the wire 

suspension test. Behavioral changes were observed as early as 3 days after radiation exposure and lasted up 

to 8 months. Biochemical studies showed that the K+

-evoked release of dopamine was significantly reduced 

in the irradiated group, together with an alteration of the nerve signaling pathways (Joseph and Cutler, 1994). 

A negative result was reported by Pecaut et al. (2004), in which no behavioral effects were seen in female 

C57/BL6 mice in a 2- to 8-week period following their exposure to 0, 0.1, 0.5 or 2 Gy accelerated 56Fe-ions 

(1 GeV/u56Fe) as measured by open-field, rotorod, or acoustic startle habituation. 

Radiation-induced changes in conditioned taste aversion

There is evidence that deficits in conditioned taste aversion (CTA) are induced by low doses of heavy ions 

(Hunt et al., 1989; Rabin et al., 1989; 1991; 1994; 2000). The CTA test is a classical conditioning paradigm 

that assesses the avoidance behavior that occurs when the ingestion of a normally acceptable food item is associated with illness. This is considered a standard behavioral test of drug toxicity (Riley and Tuck, 1985). 

NCRP Report No. 153 (NCRP, 2006) notes that: “The role of the dopaminergic system in radiation-induced 

changes in CTA is suggested by the fact that amphetamine-induced CTA, which depends on the dopaminergic 

system, is affected by radiation, whereas lithium chloride-induced CTA, which does not involve the dopaminergic system, is not affected by radiation. It was established that the degree of CTA due to radiation is LETdependent ([figure 6-3]) and that 56Fe-ions are the most effective of the various low and high LET radiation 

types that have been tested (Rabin et al., 1989; Rabin et al., 1991). Doses as low as ~0.2 Gy of 56Fe-ions 

appear to have an effect on CTA.” 

The RBE of different types of heavy particles on CNS function and cognitive/behavioral performance 

was studied in Sprague-Dawley rats (Rabin et al., 2007). The relationship between the thresholds for the 

HZE particle-induced disruption of amphetamine-induced CTA learning is shown in figure 6-4; and for the 

disruption of operant responding is shown in figure 6-5. These figures show a similar pattern of responsiveness to the disruptive effects of exposure to either 56Fe or 28Si particles on both CTA learning and operant 

responding. These results suggest that the RBE of different particles for neurobehavioral dysfunction 

cannot be predicted solely on the basis of the LET of the specific particle. 

 
Human Health and Performance Risks 

Risk of A

Figure 6-3.

radiation s

e– =electro 20Ne = neon

Figure 6-4. Ra

the relationshi 28Si particles a

induced CTA le

The threshold 

against particl

of Space Exploration Missions

Acute or Late Central Nervous System Effects from Radiation Exp

. ED50 for CTA as a function of LET for the following 

sources: 40Ar = argon ions, 60Co = cobalt-60 gamma rays, 

ons, 56Fe = iron ions, 4He = helium ions, n0 = neutrons, 

n ions (Rabin et al., 1991).

diation-induced disruption in CTA. This figure shows 

ip between exposure to different energies of 56Fe and 

and the threshold dose for the disruption of amphetamineearning. Only a single energy of 48Ti particles was tested. 

dose (cGy) for the disruption of the response is plotted 

le LET (keV/μm (Rabin et al., 2007).

Chapter 6 

posure 201
Chapter 6 

202 Risk of Acute or Late Cent

Figure 6-5. H

This figure sh

different ener

dose for the d

operant resp

tested. The th

response is p

et al., 2007). 

Radiation affect on operant con

Operant conditioning uses several c

et al. (2003) have examined the abil

an ascending fixed-ratio (FR) sched

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on a diet containing strawberry, but 

2005). When tested 13 and 18 mont

the irradiated rats maintained on con

the beneficial effects of antioxidant

Spatial learning and memory

The effects of exposure to HZE nu

have been tested, and threshold dos

understand the mechanisms that are

particle types, and, eventually, astr

1 month after whole-body irradiatio

tive impairment that was similar to

the amount of ROS may be respon

deficits (Shukitt-Hale et al., 2000).

Human Health and Performance Risks of Space Ex

tral Nervous System Effects from Radiation Exposure 

High-LET radiation effects on operant response. 

hows the relationship between the exposure to 

rgies of 56Fe and 28Si particles and the threshold 

disruption of performance on a food-reinforced 

onse. Only a single energy of 48Ti particles was 

hreshold dose (cGy) for the disruption of the 

plotted against particle LET (keV/μm) (Rabin 

nditioning

consequences to modify a voluntary behavior. Recent stu

lity of rats to perform an operant order to obtain food reinfo

dule. They found that 56Fe-ion doses that are above 2 Gy a

ing work requirements. NCRP Report No. 153 (NCRP, 2

e in rats was tested 5 and 8 months after exposure, but main

t not blueberry, extract were shown to prevent the disruption

ths after irradiation, there were no differences in performan

ntrol, strawberry or blueberry diets. These observations sug

t diets may be age dependent.” 

uclei on spatial learning, memory behavior, and neuronal s

ses have also been considered for such effects. It will be i

e involved in these deficits to extrapolate the results to other

ronauts. Studies on rats were performed using the Morris w

on with 1.5 Gy of 1 GeV/u 56Fe-ions. Irradiated rats demo

o that seen in aged rates. This leads to the possibility that a

sible for the induction of both radiation- and age-related c

xploration Missions 

dies by Rabin 

orcement using 

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n (Rabin et al., 

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mportant to 

r dose regimes, 

water maze test 

onstrated cognian increase in 

cognitive 
Human Health and Performance Risks of Space Exploration Missions Chapter 6 

Risk of Acute or Late Central Nervous System Effects from Radiation Exposure 203

NCRP Report No. 153 (NCRP, 2006) notes that: “Denisova et al. exposed rats to 1.5 Gy of 1 GeV/u56Feions and tested their spatial memory in an eight-arm radial maze. Radiation exposure impaired the rats’ 

cognitive behavior, since they committed more errors than control rats in the radial maze and were unable 

to adopt a spatial strategy to solve the maze (Denisova et al., 2000). To determine whether these findings 

related to brain-region specific alterations in sensitivity to oxidative stress, inflammation or neuronal plasticity, three regions of the brain, the striatum, hippocampus and frontal cortex that are linked to behavior, 

were isolated and compared to controls. Those that were irradiated were adversely affected as reflected 

through the levels of dichlorofluorescein, heat shock, and synaptic proteins (for example, synaptobrevin and 

synaptophysin). Changes in these factors consequently altered cellular signaling (for example, calciumdependent protein kinase C and protein kinase A). These changes in brain responses significantly correlated 

with working memory errors in the radial maze. The results show differential brain-region-specific sensitivity induced by 56Fe irradiation ([figure 6-6]). These findings are similar to those seen in aged rats, suggesting that increased oxidative stress and inflammation may be responsible for the induction of both 

radiation and age-related cognitive deficits.” 

 Acute Central Nervous System Risks 

In addition to the possible in-flight performance and motor skill changes that were described above, the 

immediate CNS effects (i.e., within 24 hours following exposure to low-LET radiation) are anorexia and 

nausea (Fajardo et al., 2001). These prodromal risks are dose-dependent and, as such, can provide an indicator of the exposure dose. Estimates are ED50 = 1.08 Gy for anorexia, ED50 = 1.58 Gy for nausea, and 

ED50=2.40 Gy for emesis. The relative effectiveness of different radiation types in producing emesis was 

studied in ferrets and is illustrated in figure 6-7. High-LET radiation at doses that are below 0.5 Gy show 

greater relative biological effectiveness compared to low-LET radiation (Rabin et al., 1994). The acute 

effects on the CNS, which are associated with increases in cytokines and chemokines, may lead to disruption in the proliferation of stem cells or memory loss that may contribute to other degenerative diseases. 

 

Figure 6-6. Brain-region-specific calciumdependent protein kinase C expression was 

assessed in control and irradiated rats using 

standard Western blotting procedures. Values are 

means ± SEM (standard error of mean) (Denisova 

et al., 2002). 
Chapter 6 Human Health and Performance Risks of Space Exploration Missions 

204 Risk of Acute or Late Central Nervous System Effects from Radiation Exposure 

 Computer Models and Systems Biology Analysis of 

 Central Nervous System Risks 

Since human epidemiology and experimental data for CNS risks from space radiation are limited, mammalian 

models are essential tools for understanding the uncertainties of human risks. Cellular, tissue, and genetic animal 

models have been used in biological studies on the CNS using simulated space radiation. New technologies, such 

as three-dimensional cell cultures, microarrays, proteomics, and brain imaging, are used in systematic studies on 

CNS risks from different radiation types. According to biological data, mathematical models can be used to estimate the risks from space radiation. 

Systems biology approaches to Alzheimer’s disease that consider the biochemical pathways that are important 

in CNS disease evolution have been developed by research that was funded outside of NASA. Figure 6-8 shows 

a schematic of the biochemical pathways that are important in the development of Alzheimer’s disease. The description of the interaction of space radiation within these pathways would be one approach to developing predictive 

models of space radiation risks. For example, if the pathways that were studied in animal models could be correlated with studies in humans who are suffering from Alzheimer’s disease, an approach to describe risk that uses 

biochemical degrees-of-freedom could be pursued. Edelstein-Keshet and Spiros (2002) have developed an in 

silico model of senile plaques that are related to Alzheimer’s disease. In this model, the biochemical interactions 

among TNF, IL-1B, and IL-6 are described within several important cell populations, including astrocytes, 

microglia, and neurons. Further, in this model soluble amyloid causes microglial chemotaxis and activates IL1B secretion. Figure 6-9 shows the results of the Edelstein-Keshet and Spiros model simulating plaque formation and neuronal death. Establishing links between space radiation-induced changes to the changes that are 

described in this approach can be pursued to develop an in silico model of Alzheimer’s disease that results 

from space radiation. 

 

Figure 6-7. LET dependence of RBE of radiation 

in producing emesis or retching in a ferret. B = 

bremstrahlung; e– = electrons; P = protons; 60Co = 

cobalt gamma rays; no

 = neutrons; and 56Fe = iron 
Human Health and Performance Risks of Space Exploration Missions Chapter 6 

Risk of Acute or Late Central Nervous System Effects from Radiation Exposure 205

Figure 6-8. Molecular pathways important in Alzheimer’s disease. From Kyoto Encyclopedia of 

Genes and Genomes (http://www.genome.ad.jp/kegg/pathway/hsa/hsa05010.html). 

Figure 6-9. Model of plaque formation and neuronal death in Alzheimer’s disease. From Edelstein-Keshet and 

Spiros, 2002: Top row: Formation of a plaque and death of neurons in the absence of glial cells, when fibrous amyloid 

is the only injurious influence. The simulation was run with no astrocytes or microglia, and the health of neurons was 

determined solely by the local fibrous amyloid. Shown above is a time sequence (left to right) of three stages in plaque 

development, at early, intermediate, and advanced stages. Density of fibrous deposit is represented by small dots and 

neuronal health by shading from white (healthy) to black (dead). Note radial symmetry due to simple diffusion. Bottom 

row: Effect of microglial removal of amyloid on plaque morphology. Note that microglia (small star-like shapes) are seen 

approaching the plaque (via chemotaxis to soluble amyloid, not shown). At a later stage, they have congregated at the 

plaque center, where they adhere to fibers. As a result of the removal of soluble and fibrous amyloid, the microglia 

lead to irregular plaque morphology. Size scale: In this figure, the distance between the small single dots (representing low-fiber deposits) is 10 mm. Similar results were obtained for a 10-fold scaling in the time scale of 

neuronal health dynamics. 
Chapter 6 Human Health and Performance Risks of Space Exploration Missions 

206 Risk of Acute or Late Central Nervous System Effects from Radiation Exposure 

Other interesting candidate pathways that may be important in the regulation of radiation-induced degenerative 

CNS changes are signal transduction pathways that are regulated by Cdk5. Cdk5 is a kinase that plays a key role 

in neural development; its aberrant expression and activation are associated with neurodegenerative processes, 

including Alzheimer’s disease (Catania et al., 2001; Muyllaert et al., 2008). This kinase is up-regulated in 

neural cells following ionizing radiation exposure (Cruz et al., 2003) 

 Risks in Context of Exploration Mission Operational Scenarios 

 Projections for space missions 

Reliable projections of CNS risks for space missions cannot be made from the available data. Animal behavior studies indicate that high-HZE radiation has a high RBE, but the data are not consistent. Other uncertainties include: age at exposure, radiation quality, and dose-rate effects, as well as issues regarding genetic 

susceptibility to CNS risk from space radiation exposure. More research is required before CNS risk can 

be estimated. 

 Potential for biological countermeasures 

The goal of space radiation research is to estimate and reduce uncertainties in risk projection models and, if 

necessary, develop countermeasures and technologies to monitor and treat adverse outcomes to human health 

and performance that are relevant to space radiation for short-term and career exposures, including acute or late 

CNS effects from radiation exposure. The need for the development of countermeasures to CNS risks is dependent on further understanding of CNS risks, especially issues that are related to a possible dose threshold, and if 

so, which NASA missions would likely exceed threshold doses. As a result of animal experimental studies, 

antioxidant and anti-inflammation are expected to be effective countermeasures for CNS risks from space 

radiation (Rabin et al., 2005). Diets of blueberries and strawberries were shown to reduce CNS risks after 

heavy-ion exposure. Estimating the effects of diet and nutritional supplementation will be a primary goal 

of CNS research on countermeasures. 

A diet that is rich in fruit and vegetables significantly reduces the risk of several diseases. Retinoids and 

vitamins A, C, and E are probably the most well-known and studied natural radioprotectors, but hormones (e.g., 

melatonin), glutathione, superoxide dismutase, and phytochemicals from plant extracts (including green tea and 

cruciferous vegetables), as well as metals (especially selenium, zinc, and copper salts) are also under study as 

dietary supplements for individuals, including astronauts, who have been overexposed to radiation (Durante and 

Cucinotta, 2008). Antioxidants should provide reduced or no protection against the initial damage from densely 

ionizing radiation such as HZE nuclei, because the direct effect is more important than the free-radical-mediated 

indirect radiation damage at high LET. However, there is an expectation that some benefits should occur for persistent oxidative damage that is related to inflammation and immune responses(Barcellos-Hoff et al., 2005). 

Some recent experiments suggest that, at least for acute high-dose irradiation, an efficient radioprotection by 

dietary supplements can be achieved, even in the case of exposure to high-LET radiation. Although there is evidence that dietary antioxidants (especially strawberries) can protect the CNS from the deleterious effects of high 

doses of HZE particles (Rabin et al. 2005), because the mechanisms of biological effects are different at low 

dose-rates compared to those of acute irradiation, new studies for protracted exposures will be needed to 

understand the potential benefits of biological countermeasures. 

Concern about the potential detrimental effects of antioxidants was raised by a recent meta-study of the effects 

of antioxidant supplements in the diet of normal subjects (Bjelakovic et al., 2007). The authors of this study did 
Human Health and Performance Risks of Space Exploration Missions Chapter 6 

Risk of Acute or Late Central Nervous System Effects from Radiation Exposure 207

not find statistically significant evidence that antioxidant supplements have beneficial effects on mortality. On 

the contrary, they concluded that β-carotene, vitamin A, and vitamin E seem to increase the risk of death. Concerns are that the antioxidants may allow rescue of cells that still sustain DNA mutations or altered genomic 

methylation patterns following radiation damage to DNA, which can result in genomic instability. An approach 

to target damaged cells for apoptosis may be advantageous for chronic exposures to GCR. 

 Individual risk factors 

Individual factors of potential importance are genetic factors, prior radiation exposure, and previous head 

injury, such as concussion. Apolipoprotein E (ApoE) has been shown to be an important and common factor 

in CNS responses. ApoE controls the redistribution of lipids among cells and is expressed at high levels in the 

brain (Raber et al., 1998). New studies are considering the effects of space radiation for the major isoforms of 

ApoE, which are encoded by distinct alleles (ε2, ε3, and ε4). The isoform ApoE ε4 has been shown to increase 

the risk of cognitive impairments and to lower the age for Alzheimer’s disease. It is not known whether the interaction of radiation sensitivity or other individual risks factors is the same for high- and low-LET radiation. 

Other isoforms of ApoE confer a higher risk for other diseases. People who carry at least one copy of the ApoE 

ε4 allele are at increased risk for atherosclerosis, which is also suspected to be a risk increased by radiation. 

People who carry two copies of the ApoE ε2 allele are at risk for a condition that is known as hyperlipoproteinemia type III. It will therefore be extremely challenging to consider genetic factors in a multipleradiation-risk paradigm 

 Conclusion 

Reliable projections for CNS risks from space radiation exposure cannot be made at this time due to a 

paucity of data on the subject. Existing animal and cellular data do suggest that space radiation can produce 

neurological and behavioral effects; therefore, it is possible that mission operations will be impacted. The significance of these results on the morbidity to astronauts has not been elucidated, however. It is to be noted that 

studies, to date, have been carried out with relatively small numbers of animals (<10 per dose group); this means 

that testing of dose threshold effects at lower doses (<0.5 Gy) has not yet been carried out to a sufficient extent. 

As the problem of extrapolating space radiation effects in animals to humans will be a challenge for space radiation research, such research could become limited by the population size that is typically used in animal studies. 

Furthermore, the role of dose protraction has not been studied to date. An approach has not been discovered to 

extrapolate existing observations to possible cognitive changes, performance degradation, or late CNS effects in 

astronauts. Research on new approaches to risk assessment may be needed to provide the data and knowledge 

that will be necessary to develop risk projection models of the CNS from space radiation. A vigorous research 

program, which will be required to solve these problems, must rely on new approaches to risk assessment and 

countermeasure validation because of the absence of useful human radio-epidemiology data in this area. 

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Risk of Acute or Late Central Nervous System Effects from Radiation Exposure 213

Chapter 7: 

Risk of Degenerative Tissue or Other Health 

Effects from Radiation Exposure 

Janice L. Huff 

Universities Space Research Association 

Francis A. Cucinotta 

NASA Johnson Space Center 

Occupational radiation exposure from the space environment may result in degenerative tissue diseases 

(non-cancer or non-CNS) such as cardiac, circulatory, or digestive diseases, as well as cataracts, although 

the mechanisms and the magnitude of influence of radiation leading to these diseases are not well 

characterized. Radiation and synergistic effects of radiation cause increased DNA strand and tissue 

degeneration, which may lead to acute or chronic disease of susceptible organ tissues. Data specific to the 

spaceflight environment must be compiled to quantify the magnitude of this risk to determine if additional 

protection strategies are required. – Human Research Program Requirements Document, HRP-47052, Rev. 

C, dated Jan 2009. 

 Exposure to space radiation may result 

in non-cancer or non-CNS degenerative 

tissue diseases, including cardiac, circulatory and digestive disorders, as well as 

cataracts. NASA’s research program in 

this area currently focuses on determining the risks for these diseases from low 

dose-rate exposures and for HZE nuclei 

so that appropriate countermeasures can 

be developed to mitigate these risks. 

© Sebastian Kaulitzki - Fotolia.com 
214 Risk of Degenerative Tissue or Other Health Effects from Radiation Exposure 
Human Health and Performance Risks of Space Exploration Missions Chapter 7 

Risk of Acute or Late Central Nervous System Effects from Radiation Exposure 215

 Executive Summary 

Human epidemiology studies of people who are exposed to various doses of ionizing radiation provide 

strong evidence that degenerative diseases are to be expected from exposures during long-duration space travel 

to GCRs or large SPEs in which fluences of more than 107

 protons per cm2 with energies that are above 30 MeV 

occur. The RBE factors for most degenerative diseases that are caused by space radiation are unknown. However, 

the range of doses that have been observed in human studies is sufficient to make the probability of degenerative disease risks from GCR and SPE exposure during space flight a major concern. The types of radiation that 

are in space present additional uncertainties in risk estimates for degenerative diseases, and the results of several 

studies suggest that both quantitative and qualitative differences may occur when comparing LET radiation on 

Earth, such as X rays and gamma rays, to high-LET radiation in space, such as heavy ions and recoil nuclei and 

neutrons that are produced in nuclear reactions. A shortened latency is expected for high-LET radiation in space, 

which increases the detriment above that of identical diseases in the U.S. population. Therefore, the greater likelihood of degenerative diseases presents a risk that is competitive with the already well-documented risks of 

mortality and morbidity with respect to cancer. As the focus for NASA is on understanding and mitigating risk, 

space radiation is a large obstacle to mission success. It is unknown at this time whether radiation shielding 

approaches that are distinct from those needed for the other radiation risks are needed for degenerative risks. 

Research on individual sensitivity to and biological countermeasures for degenerative risks, except for 

cataracts, is nonexistent. 

 Introduction 

The environment outside of the shield-like atmosphere and magnetosphere of the Earth contains several types 

of radiation. Most of the particles in interplanetary space are derived from the solar wind, which produces a 

constant flux of low-energy particles. Dangerous and intermittent SPEs can produce large quantities of highly 

energetic protons and heavy ions. An additional constituent of space radiation, GCRs, emanate from outside our 

solar system and comprise mostly highly energetic protons with a small component of HZE nuclei. Researchers 

have predicted that an astronaut will receive a total body dose of approximately 1 to 2 mSv each day in interplanetary space and approximately 0.5 to 1 mSv each day on the surface of Mars, and these numbers will increase in the event of an SPE (Cucinotta and Durante, 2006; Saganti et al., 2004). 

Exposure to ionizing radiation affects cells and tissues either by directly damaging cellular components or by 

producing highly reactive free radicals from water and other constituents of cells. Both of these mechanisms can 

produce sufficient damage to cause cell death, DNA mutation, or abnormal cell function. The extent of damage 

is generally believed to depend on the dose and the type of particle, and to follow a linear response to radiation 

dose for initial induction of damage. This is true for high and moderate radiation doses, but it is extremely difficult to measure for lower doses because of the challenges in distinguishing the effects of radiation exposure 

from those of normal cellular oxidative stress. 

As HZE nuclei are the components of space radiation that have the highest biological effectiveness, they are 

a large concern for astronaut safety. HZE nuclei produce highly ionizing tracks as they pass through matter. In 

addition, they leave columns of damage at the molecular level when they traverse a biological system – damage 

that is fundamentally different from the damage that is left by low-LET radiation sources such as gamma and 

X rays. HZE nuclei impart damage through the primary energetic particle and secondary delta-ray electrons as 

well as from fragmentation events that produce a spectrum of other energetic nuclei, protons, neutrons, and heavy 

fragments (Wilson et al., 1995). Therefore, a large penumbra of energy deposition extends outward from the 
Chapter 7 Human Health and Performance Risks of Space Exploration Missions 

216 Risk of Degenerative Tissue or Other Health Effects from Radiation Exposure 

primary particle track (Cucinotta et al., 2000). The lack of epidemiological data and sparse radiobiological data 

on the effects of these HZE nuclei leads to a high level of uncertainty in risk estimates for long-term health 

effects after exposure to GCRs and SPEs. 

NASA has funded several previous reports from the NAS and the NCRP that provided evidence for the 

radiation risks in space. The NCRP is chartered by the U.S. Congress to guide federal agencies such as NASA 

on the risk from radiation exposures to their workers. Reports from the NCRP and the NRC on space radiation 

risks are the foundation of how NASA views the wide scientific body of evidence that is used for its research 

and operational radiation protection methods and plans. 

 Description of degenerative risks of concern to NASA 

The major degenerative conditions of concern that could potentially result from space radiation exposure are as 

follows: 

 Cataract formation 

 Degenerative changes in the heart and vasculature (e.g., atherosclerosis and cardiomyopathy) 

 Other diseases that are related to aging, including digestive and respiratory disease 

 Other aging effects, including premature senescence and endocrine and immune system dysfunction 

Note that risks to the CNS may also involve degenerative conditions, but they are treated as a stand-alone risk 

category by NASA and are described in Chapter 6 of this document. 

 Current NASA permissible exposure limits 

PELs for short-term and career exposures to space radiation have been approved by the NASA Chief Health 

and Medical Officer, who also sets the requirements and standards for mission design and crew selection. Table 

7-1, which is taken directly from NASA-STD-3001, Volume 1 (Table 4, p. 67), lists the current short- and longterm PELs for non-cancer effects (in mGy-Eq. or mGy). The lifetime limits for cataracts and heart disease are 

imposed to limit or prevent risks of degenerative tissue diseases. The approach here, which uses an estimate of 

threshold doses for heart and cataracts risk, is quite distinct from that of cancer risk limits, in which a probabilistic 

assessment of the risk is made using a projection model. Such an approach will likely be needed in the future 

for the degenerative risks. Career limits for the heart are intended to limit the REID as a result of heart disease, 

so, those limits fall below the current estimate of a threshold dose (NCRP, 2000); however, exposure would 

lead to some risk if a linear dose response with no threshold model were established. 

 
Human Health and Performance Risks of Space Exploration Missions Chapter 7 

Risk of Acute or Late Central Nervous System Effects from Radiation Exposure 217

Table 7-1. Short- and Long-term Dose Limits for Non-cancer Effects 

Organ 30-day limit 1-year Limit Career 

Lens* 1,000 mGy-Eq 2,000 mGy-Eq 4,000 mGy-Eq 

Skin 1,500 mGy-Eq 3,000 mGy-Eq 4,000 mGy-Eq 

BFO 250 mGy-Eq 500 mGy-Eq Not applicable 

Heart** 250 mGy-Eq 500 mGy-Eq 1,000 mGy-Eq 

CNS*** 500 mGy-Eq 1,000 mGy-Eq 1,500 mGy-Eq 

CNS*** (Z≥10) – 100 mGy 250 mGy 

*Lens limits are intended to prevent early (<5 years) severe cataracts (e.g., from an SPE). An additional cataract risk – sub-clinical 

cataracts – exists at lower doses from cosmic rays, which may progress to severe types after long latency (>5 years). Although these 

cataract risks are not preventable by existing mitigation measures, they are deemed an acceptable risk to the program. 

**Heart doses calculated as average over heart muscle and adjacent arteries. 

***CNS limits should be calculated at the hippocampus. 

 Evidence 

 Review of human data 

 Cataracts 

The development of ocular cataracts, which is a degenerative opacification of the crystalline lens, is a 

well-recognized late effect of exposure to ionizing radiation. The first reports of radiation-induced cataracts 

appeared early in the 20th century, shortly after the first X-ray machines were developed (Rollins, 1903). It is 

now clear that radiation-induced cataracts exhibit relationships between radiation dose and disease severity as 

well as between dose and latency. Evidence for this link comes, most notably, from survivors of radiotherapy 

who received high doses (>5 Gy) of ionizing radiation using X rays, gamma rays, and proton beams for ocular 

tumors (Ferrufino-Ponce and Henderson, 2006; Blakely et al., 1994; Gragoudas et al., 1995) and from individuals who received whole-body therapeutic radiation (Belkacemi et al., 1996; Dunn et al., 1993; Frisk et al., 

2000). 

Evidence of cataract risk (moderate- to low-dose gamma-ray exposures) comes from epidemiological data 

from atomic-bomb survivors who were followed in the life span study, which is a longitudinal study of 

Japanese survivors of the bombings of both Hiroshima and Nagasaki, which remains one of the most valuable 

and informative epidemiological studies for evaluating long-term health effects of radiation exposure (Preston 

et al., 2003). 

Among the atomic-bomb survivors, the frequency and the severity of cataracts are dose-dependent. Severity 

refers to the size and loss of visual acuity of the cataract, or the presence of conditions requiring lens implants 

to prevent blindness. Symptoms appeared as soon as several months after exposure for severe cases and several 

years after exposure for less-severe cases. The frequency of appearance was related to the proximity of the 

subject to the hypocenter of the atomic bomb. A possible threshold dose was originally estimated to be in the 

range 0.6 to 1.5 Gy (Junk et al., 1998; Otake and Schull, 1982; 1991), but a non-threshold dose model has been 

proposed in more recent reports (Neriishi et al., 2007). In a prospective study that follows the development of 

radiation-induced cataracts in workers who were exposed to radiation during the efforts to clean up after the 

Chernobyl nuclear power plant disaster, it was found that posterior subcapsular or cortical cataracts were 

present in 25% of the examined individuals. The investigators estimated that the dose-effect threshold 

for cataract formation in exposures is less than 1 Gy (Worgul et al., 2007). 
Chapter 7 Human Health and Performance Risks of Space Exploration Missions 

218 Risk of Degenerative Tissue or Other Health Effects from Radiation Exposure 

As noted by Blakely and Chang (2007a), published data on radiation-induced human cataracts are limited 

in predicting the risk from chronic exposure to low doses of protons or low fluence of heavy ions, such as that 

encountered in space, because of the possible qualitative differences in effect. 

 Cardiovascular Diseases and Other Degenerative Changes 

A clear link has been established between exposure to high doses of ionizing radiation and the long-term 

development of cardiovascular disease and degenerative heart changes. Like the evidence described for 

cataractogenesis, the major evidence that proves a link between ionizing radiation exposure and the development of degenerative heart and vasculature changes comes from prospective studies that follow the longterm, treatment-related effects in cancer survivors. These patients received relatively high therapeutic doses 

(~5–50 Gy) of low-LET thoracic radiation exposure in the course of therapy for cancers of the head, neck, 

and chest, such as Hodgkin’s lymphoma and breast cancer (Prosnitz et al., 2005; Darby et al., 2005; Carver et 

al., 2007; Swerdlow et al., 2007). There is a dose-dependent increase in the development of a wide variety of 

cardiovascular diseases, including acute and chronic pericarditis, coronary artery disease (CAD), cardiomyopathy, valvular disease, and conduction abnormalities, that lead to arrhythmia in these individuals. A commonality in each of these disorders seems to be damage to the microvasculature and small coronary arteries that 

result from acute inflammation and ischemia and is followed by progressive degenerative fibrotic changes 

(Little et al., 2008). Impairment in nitric oxide signal transduction may contribute to degenerative vascular 

changes (Soloviev et al., 2003). Atherosclerosis that is caused in this manner, as a secondary effect to radiation treatment, looks pathologically similar to atherosclerosis that is caused by other factors. A paucity of 

data exists on doses and dose-rates that cause atherosclerosis in humans. 

Other evidence that supports a link between the occurrence of cardiovascular disease and radiation exposure 

is derived from prospective studies of atomic-bomb survivors who received moderate doses of radiation (0–2 Gy) 

as well as from occupationally exposed workers who received continuous low-dose exposure (Darby et al., 

2005; Yamada et al., 2004; Preston et al., 2003; Hayashi et al., 2003). In atomic-bomb survivors who are enrolled in the life-span study, the development of health effects has been extensively studied through continuous 

longitudinal health assessments. The average doses that were received by the atomic-bomb survivors (Preston, 

2003) are similar to the effective doses for an ISS mission and somewhat lower than the effective dose that is 

expected for a Mars mission. A significant dose-response relationship exists for hypertension, stroke, and 

heart attack in survivors who were exposed at less than 40 years of age; their ERR is estimated to be 14% per 

Sievert (Sv); but the existence of a threshold dose cannot be excluded for risks that are associated with doses 

that are less than 0.25 Sv (Table 7-2). 

For occupationally exposed workers, such as employees of nuclear power facilities, data are less convincing. 

A recent study of U.S. workers who were exposed to radiation with doses that were below 1 Sv in nuclear 

power plants showed a significant correlation between radiation dose and death from cardiovascular disease 

(Howe et al, 2004). However, similar studies (Table 7-3) have shown risks that are more similar to those of 

the atomic-bomb survivors, or no increased risk. Further studies are warranted, as evidence at doses that are 

below 0.5 Sv is suggestive at best (Vrijheid et al., 2007). Finally, follow-up studies of the health risks in 

Chernobyl recovery workers also show an increased risk for cardiovascular diseases; however, the contribution of lifestyle factors to this risk estimate cannot be eliminated at this point, and further analysis is 

needed (Ivanov et al., 2006; McGale and Darby, 2005). 

 
Human Health and Performance Risks of Space Exploration Missions Chapter 7 

Risk of Acute or Late Central Nervous System Effects from Radiation Exposure 219

Table 7-2. Estimates of Excess Relative Risk per Sievert for Non-cancer deaths from Life-span Study of the Atomicbomb Survivors (Preston et al., 2003). Life-Span Study Cause-Specific, Non-cancer Disease ERR Estimates 1968–1997

Cause ERR per Sv Deathsa

Estimated number of 

radiation-associated 

deaths 

All non-cancer diseases (0–139, 240–279, 290–799) 0.14 (0.08; 0.2)b 14,459 273 (176; 375)b

Heart disease (390–429) 0.17 (0.08; 0.26) 4,477 101 (47; 161) 

Stroke (430–438) 0.12 (0.02; 0.22) 3,954 64 (14; 118) 

Respiratory disease (640–519) 0.18 (0.06; 0.32) 2,266 57 (19; 98) 

Pneumonia (480–487) 0.16 (0.00; 0.32) 1,528 33 (4; 67) 

Digestive disease (520–579) 0.15 (0.00; 0.32) 1,292 27 (0; 58) 

Cirrhosis (571) 0.19 (–0.05; 0.5) 567 16 (–2; 37) 

Infectious disease (000–139) –0.02 (< –0.2; 0.25) 397 –1 (–14; 15) 

Tuberculosis (010–018) –0.01 (< –0.2; 0.4) 237 –0.5 (–2; 13) 

Other diseasesc (240–279; 319–389; 580–799) 0.08 (–0.04; 0.23) 2,073 24 (–12; 64) 

Urinary diseases (589–629) 0.25 (–0.01; 0.6) 515 17 (–1; 39) 

a

Deaths among potential survivors between 1968 and 1997; b90% C.I.; cExcluding diseases of the blood and BFOs. 

Table 7-3. Occupational Studies and Circulatory Disease Mortality (Hoel, 2006)

Occupationally Exposed Persons 

Study Workers (Circulatory 

deaths) 

ERR 

per Sv 

Comments 

U.K. radiologists 

(Berrington, 2001) 

U.S. radiologists 

(Matanoski, 1975) 

U.S. radiology techs 

(Hauptmann, 2003) 

Nuclear workers study 

IARC 3 country study 

(Cardis, 1995) 

U.S. power reactors 

(Howe et al., 2004) 

Mayak workers 

(Bolotnikova, 1994) 

Chernobyl emergency 

(Ivanov, 2001) 

2,698 

(514) 

30,084 

90,284 

(1,070) 

95,673 

(7,885) 

53,698 

(350) 

9,373 

(749) 

65,095 

(1,728 

< 0 

0.2 

0.01–0.42 

0.26 

8.3 

0.01 

0.79 

Time trend in cancer but not in 

CVD 

Time trend in cancer but not in 

CVD 

Time trend in both stroke and 

CHD 

5% works > 0.2 Sv 

2% workers > 0.4 Sv 

95% C.I.: (2.3, 18.2) 

Exposures 0 to 0.35 Sv 

CHD = coronary heart disease; CVD = cardiovascular disease; IARC = International Agency for Research on Cancer. 

 Digestive and Respiratory Diseases 

Figures 7-1 and 7-2 show results from Preston et al. (2003) for the ERR for death vs. dose for several diseases, 

including digestive and respiratory diseases. Significant risks are observed for doses that are above 1 Sv for 

the acute gamma-ray exposures that were received by the atomic-bomb survivors. As dose-rates in space are 

below 5 mSv/hour for GCR and, in most cases, are below 50 mSv/hour for SPE, respiratory and digestive 

diseases have not been considered a risk for ISS missions. However, for missions to Mars or lunar missions 

incurring a large SPE, doses that are above 1 Sv are likely. Average years of life-loss for these diseases is 

about 9 years in the atomic-bomb survivors. Absolute probabilities for disease morbidity will, of course, 

be higher than those for mortality risks. 

 
Chapter 7 Human Health and Performance Risks of Space Exploration Missions 

220 Risk of Degenerative Tissue or Other Health Effects from Radiation Exposure 

Figure 7-1. Preston et al. (2003): Cause-specific dose-response functions for non-cancer 

deaths. The plots display the best-fitting ERR models together with nonparametric ERR 

estimates for 20 dose categories. 

 
Human Health and Performance Risks of Space Exploration Missions Chapter 7 

Risk of Acute or Late Central Nervous System Effects from Radiation Exposure 221

Figure 7-2. Preston et al. (2003): Non-cancer dose-response function for the 

period 1968–1997. The solid line indicates the fitted linear ERR model without any 

effect modifications by age at exposure, sex, or attained age. The points are dosecategory-specific ERR estimates, the solid curve is a smoothed estimate derived 

from the points, and the dashed line indicates upper and lower one-standard-error 

bounds on the smoothed estimate. The right panel shows the low-dose portion 

of the dose-response function in more detail. 

In summary, the link between exposure to acute doses of 1 Gy or more of ionizing radiation and the development of degenerative diseases is clearly established, while the health risks of low-dose and low-doserate ionizing radiation remain largely unknown. These risks are more difficult to assess because multiple factors 

are believed to play a role in the etiology of the diseases (BEIR VII, 2006). Similarly, no human data are 

available on the effects of high-LET radiation on the development of degenerative heart and cardiovascular 

complications. 

 Evidence for Other Age-related Effects Caused by Radiation 

Several biological processes that are commonly found to be degraded with increasing age are accelerated 

by radiation exposure, including changes in endocrine function, fibrosis, and premature cellular senescence. 

Examples of studies showing radiation effects on markers of aging include the following (NCRP Report No. 

156, 2006): 

 Studies of structural changes in specific organs 

 General life-span longevity studies that are performed on animal models 

 Analyses of biochemical and molecular markers of cellular aging, including senescence 

The possibility of radiation-induced accelerated aging was noted very early on in follow-up studies of 

the atomic-bomb survivors (Anderson et al., 1974). Current studies show that atomic-bomb survivors exhibit 

a decrease in immune function that is similar to that seen during normal aging, and that the effect depends on 

the dose of radiation that was received (Kusunoki and Hayashi, 2007). This impairment may be associated with 

disease development seen in the survivors. It is also possible that the damage that was caused by oxidative 

stress is the basis for the link between radiation exposure and aging (Burhans and Weinberger, 2007; 

Toussaint et al., 2002). 

 Radiation Effects on Endocrine Function 

The endocrine system controls hormone production, secretion, metabolism, and hormone levels in circulating blood. Age-related changes to the endocrine system occur in most older people. The hypothalamus 

is responsible for releasing hormones that stimulate the pituitary gland. During aging, individuals suffer impaired secretion of some hypothalamic hormones and pituitary response, resulting in a decreased capability 
Chapter 7 Human Health and Performance Risks of Space Exploration Missions 

222 Risk of Degenerative Tissue or Other Health Effects from Radiation Exposure 

for the endocrine system to respond to the internal environment and external stresses of the body. Adenomas, 

which are hyperplasias in the parathyroid gland, are observed in patients who are treated with low-LET radiation with doses that are below 1 Gy (Tezelman et al., 1995; Tissel et al., 1985) and in the atomic-bomb 

survivors (Fujiwara et al., 1992). 

 Premature Cellular Senescence 

Radiation also increases senescence in cells, which may accelerate the aging process (Campisi, 2003). Senescent cells have exited the cell cycle and are no longer capable of cell division. The principle mechanism by 

which senescence occurs is through shortening of telomeres, which are the DNA structure that caps the ends 

of chromosomes, below a critical length (~4 kilo base-pairs). The capacity to assume this phenotype may function as an anticancer mechanism in which a genetically damaged cell is shut down before it can be converted 

to a cancer cell (Campisi and d’Adda di Fagagna, 2007; Mallette and Ferbeyre, 2007). Telomere length has 

been correlated with longevity in several studies (reviewed by Shay and Wright, 2005). 

 Reviews of space flight issues 

The NAS Space Science Board first reviewed space flight issues in 1967 (NAS/NRC, 1967) and revisited 

these issues in 1970 (NAS/NRC, 1970). These reviews led to the establishment of dose limits that were used 

at NASA until 1989. Extensive reviews of human and experimental radiobiology data for space risks were also 

provided to NASA in 1989, 2000, and 2006 via NCRP reports (NCRP 1989; 2000; 2006). The 1989 and 2000 

NCRP Reports led to updates in the NASA dose limits. The issues of cataracts and degenerative tissue effects 

have been discussed in many of these reports. Reviews on other degenerative risks have been given more priority 

in the more recent of the reports. The more recent reviews suggest that the threshold doses may be lower than 

previously estimated or do not occur, especially for high-LET radiation. A major question also remains on the 

categorization of these risks as deterministic vs. stochastic, which has major implications for radiation 

protection. 

The most recent external report of the evidence of space radiation effects was published in 2006 by the NCRP 

(NCRP Report 153, 2006). The stated purpose of this report was to identify and describe the information that is 

needed to make radiation protection recommendations for space missions beyond LEO. The report contains a 

comprehensive summary of the current body of evidence for radiation-induced health risks and makes recommendations on areas requiring future experimentation. For the non-cancer, late effects of radiation, the authors 

of this report recommend that experiments be conducted using protracted or extended exposure times and low 

dose rates of protons, heavy ions, and neutrons in energy ranges that are relevant to space radiation exposure 

scenarios. Specifically, the authors of the report recommend that analyses should be conducted on the effects 

of protracted exposures on the lens, whole-body vasculature, gastrointestinal tract, gonadal cell populations, 

and hematopoietic and immune systems, as well as fertility. 

 Cataracts in astronauts 

Cucinotta et al. (2001) reported the first epidemiological evidence for an exposure-dependent increase in 

the risk of cataract formation in astronauts. Health records for 295 astronauts who were enrolled in the NASA 

Longitudinal Study of Astronaut Health, which spans more than 3 decades, were evaluated for incidence and 

type of cataract. Data were analyzed for astronaut age at the time at which the cataract appeared or the amount 

of time after the first mission when the cataract appeared (figure 7-3). Astronauts were grouped by individual 

occupational radiation exposure records that allowed for the separation of exposures from low-LET diagnostic 

X rays, atmospheric radiation that was received during aviation training, and exposure that was received during 

space flight. These data reveal an increased cataract incidence for astronauts who have a higher lens dose-equivalent 
Human Health and Performance Risks of Space Exploration Missions Chapter 7 

Risk of Acute or Late Central Nervous System Effects from Radiation Exposure 223

(average of 45 mSv) of space radiation relative to that of other astronauts with zero or low lens dose (average 

8 mSv). These studies also show a significant association between radiation quality and cataract incidence. 

Astronauts who flew on high-inclination (>50 deg) and lunar missions, which are associated with a higher flux 

of high-LET heavy ions, had a higher incidence of cataract formation than those who flew on low-inclination 

missions, on which a large proportion of the dose is from low-LET trapped protons. Further evidence for the 

link between cataract formation and exposure to space radiation was presented in a 2002 study of cosmonauts 

and astronauts (Rastegar et al., 2002), in which a trend for increased opacification in the posterior cortical and 

posterior capsule regions of the lens was evident in a group of cosmonauts and astronauts as compared to that 

of the controls. As astronauts were screened for vision at entry into the Astronaut Corps and were observed with 

distinct methods, comparisons to other studies are inconclusive. In fact, it is very likely that astronauts, prior 

to their exposure to space radiation, have a baseline incidence of cataracts that is well below that of members 

of the general population. 

 Radiobiology studies of the risk of degenerative tissues diseases 

 Cataract Studies with Protons, Neutrons, and HZE Nuclei 

Although the largest body of information on radiation-induced cataractogenesis comes from studies using 

low-LET radiation sources, substantial data also describe the induction of cataracts in a variety of animal 

species by different types of particle radiation sources that are similar to those that are encountered in space, 

including protons and high-LET particle radiation. The United States Air Force (USAF)/NASA Proton Bioeffects Project was an effort to identify delayed or late effects of X rays, electrons, and protons of differing 

energies on the long-term health of a colony of Rhesus monkeys. A subpopulation of the primates that were 

Figure 7-3. Cucinotta et al. (2001): Results for the 

probability of survival without cataracts vs. time 

after the first space mission for NASA astronauts 

for a low-dose group (closed symbols) with a lens 

dose below 8 mSv (average 4.7 mSv) and a highdose group (open symbols) with a lens dose 

above 8 mSv (average 45 mSv). Error bars indicate 

standard errors of the mean. The upper panel is 

for all cataracts, and the lower panel is for nontrace (vision-impairing or large-area) cataracts. 

Only cataracts occurring after a first space 

mission are included. 
Chapter 7 Human Health and Performance Risks of Space Exploration Missions 

224 Risk of Degenerative Tissue or Other Health Effects from Radiation Exposure 

studied in the USAF/NASA project was monitored for about 30 years for late effects including cancer, cataracts, and shortening of life. Analyses of these primates for signs of cataractogenesis began 20 years after 

exposure, and significant opacifications of the eye lens were seen in these monkeys 20 to 24 years after exposure to 55-MeV protons at 1.25 Gy and higher levels. The results that were obtained from these experiments suggest that the dose-response relationship for induction of cataracts by protons is similar to that seen 

with low-LET radiation (Lett et al., 1991; Cox et al., 1992). These findings are supported by other studies on 

cataract formation in animal models using high-energy proton beams (Niemer-Tucker et al., 1999; Fedorenko, 

1995). In many studies of heavy ions, cataractogenesis that was induced by individual high-LET components 

of the space radiation spectrum was analyzed. The conclusions that were derived from these studies are that a 

trend exists for the latency between the exposure and the appearance of cataract lesions to decrease, and that 

this occurs at lower dose thresholds for heavy ions than for low-LET X rays and protons. Table 7-4 lists representative studies for different heavy-ion species. 

Table 7-4. References for Cataractogenesis Studies Conducted with High-LET Radiation 

High-LET 

Component Selected References 

Neutrons Ainsworth, 1986; Riley et al., 1991; Worgul et al., 1996; Christenberry et al., 

1956 

Argon Merriam et al., 1984; Lett et al., 1980; Worgul, 1986; Abrosimova et al., 2000; 

Jose and Ainsworth, 1983 

Neon Lett et al., 1980; Abrosimova et al., 2000; Jose and Ainsworth, 1983 

Iron Brenner et al., 1993; Lett et al., 1991; Medvedovsky et al., 1994; Riley et al., 

1991; Tao et al., 1994; Worgul, 1986; Worgul, 1993 

Protons Niemer-Tucker et al., 1999; Fedorenko, 1985; Lett et al., 1991; Cox et al., 1992 

Studies in animals showed an age-dependent sensitivity, with the younger animals exhibiting a lower dose 

threshold for cataract induction than the older animals (Cox et al., 1992). 

 Animal Studies and Heart Damage 

Systematic studies on the progression of radiation-induced heart diseases were first conducted in rabbits 

(Fajardo and Stewart, 1970) and in rats (Yeung and Hopewell, 1985; Lauk et al., 1985) with high doses of 

X rays in the range of 10 to 20 Gy. Similar studies were conducted for heavy ions during the course of the 

JANUS program at Argonne National Laboratory, in which ultrastructural studies of the mouse heart and 

vasculature were performed after the animals had been irradiated with neutrons (Yang et al., 1976; 1978; Stearner 

et al., 1979). The results of the studies were compared with results from irradiating mice with low-LET radiation, and showed vessel morphological changes, including marked fragmentation of vascular smooth muscle 

layers as well as an increase in deposition of extracellular matrix in vessel walls. Clear distinctions were observed between the damage that was caused by neutrons and that caused by low-LET radiation (Yang et al., 

1976; 1978; Stearner et al., 1979). RBEs for neutron effects increased with decreasing dose or fractionation of 

the dose, thus dividing the total dose into several doses that were spread out over time, and exceeded values 

of 100 when exposure protraction over 24 weekly fractions was tested. Similar results were found with low 

doses of Ne and Ar ions (Yang and Ainsworth, 1982). Further studies that were conducted on rats that had 

been irradiated in the head with low doses of heavy ions showed a clear correlation between radiation dose 

and bleeding in the cerebral cortex, with heavy ions inducing more hemorrhages than X rays at the same 

dose (Yang and Tobias, 1984). Studies of the atherogenic changes that are associated with irradiation were 
Human Health and Performance Risks of Space Exploration Missions Chapter 7 

Risk of Acute or Late Central Nervous System Effects from Radiation Exposure 225

conducted in dogs to compare the effects of fractionated doses of fast neutrons (15 MeV avg.) with those of 

low-LET photons. The RBE of neutrons was estimated at 4 to 5 from these studies (Bradley et al., 1981). 

More recently, studies that were aimed at defining the mechanisms by which radiation induces heart diseases 

were conducted using atherosclerosis-prone animal models. Increased oxidative stress (from the formation of 

ROS) and promotion of inflammation have been implicated as possible mechanisms by which radiation promotes atherogenesis. For example, accelerated formation of aortic lesions occurred in a dose-dependent manner 

in X-irradiated mice that were on a high-fat diet (figure 7-4), while smaller lesions were observed in their irradiated transgenic littermates that over-expressed CuZn-superoxide dismutase, which is expected to decrease 

chronic oxidative stress and lead to a decreased susceptibility to degeneration (Tribble et al., 1999). The lowest 

dose in these studies was 2 Gy. In another study (Stewart et al., 2006), radiation was shown to accelerate the 

formation of macrophage-rich inflammatory atherosclerotic lesions in atherosclerosis-prone mice, who were 

lacking the gene for ApoE. These mice were given a single high dose of 14 Gy to the neck, supporting the 

notion that radiation promotes degenerative heart diseases though an inflammatory mechanism. 

In summary, substantial evidence from human epidemiology data and animal studies suggests that low-LET 

radiation strongly impacts the development of degenerative heart and cardiovascular diseases, which may be 

related to the overall acceleration of aging processes. However, data on these same effects that were caused 

by irradiation with protons or heavy ions are clearly lacking. 

 Radiobiology studies on aging 

One consequence of radiation exposure and other genotoxic stressors at the cellular level is an enhancement of 

cellular senescence, which is a characteristic of aging. Studies that were conducted using low-LET irradiation in 

mouse models have shown a decline in the total number of cells and an increase in the number of cells with the 

senescent phenotype in bone marrow stem cells after radiotherapy and chemotherapy. These changes may contribute to the long-term deficits in bone marrow function that occur after these treatments (Wang et al., 2006). 

Evidence of radiation-induced signs of aging has been uncovered in several studies that use heavy-ion irradiation of CNS targets. For example, mice that received whole-body irradiation with 1 GeV/nuc iron showed a 

Figure 7-4. Dose-dependent effects of ionizing 

radiation on aortic lesion formation in fat-fed mice 

(repeated-measures analysis of variance: P = 0.02) 

(Tribble et al., 1999).
Chapter 7 Human Health and Performance Risks of Space Exploration Missions 

226 Risk of Degenerative Tissue or Other Health Effects from Radiation Exposure 

dose-dependent decrease in the number of newly formed cells in the hippocampus as well as altered expression 

of biochemical markers and alterations in the distribution of cells – changes that are consistent with the aging 

process (Rola et al., 2004; Casadesus et al., 2005). In fact, the newly formed cells that were affected by radiation 

are a type of neural stem cell. Stem cells in all tissues are of fundamental importance in the process of aging 

because any age-related decline in the number or functional capability of stem cells will impair the ability of the 

body to form and replace committed cells, with potentially deleterious cost for tissue maintenance. Genes that 

could modify individual susceptibility and radiation-induced aging would occur in the DNA damage response 

pathway, cell cycle controls, and telomere regulation, including Atm, Nbs1, Wrn, p16, and p21. 

High-LET radiation also has an enhanced ability to damage the telomeres structures that are at one end of each 

chromosome and that are believed to be involved in the aging process (Durante et al., 2006). Some investigators 

report very high levels of telomere deletion in the progeny of human lymphocytes after irradiation with low doses 

of iron nuclei (Durante et al., 2006). Bailey (2007) is studying changes to telomeres as a function of radiation 

quality. Possible quantitative differences between low- and high-LET damage in causing telomere shortening 

or premature senescence are thus a concern for space radiation risk assessment. 

 Other effects 

An additional effect of irradiation that was revealed by the proton bioeffects studies that were conducted 

in Rhesus monkeys was a significant increase in the risk of developing endometriosis, which is an abnormal 

growth of the uterine lining. This disease occurred in about 25% of all of the unirradiated female primates and 

in more than 50% of the irradiated primates. Although they are not normally life-threatening in humans, these 

conditions proved fatal to several of the animals before proper treatment plans were put into effect. Endometriosis was evident even when relatively low-energy protons (32 MeV; penetrating to a depth of about 1 cm) and 

low-exposure doses (0.2 to 1.13 Gy) were used (Yochmowitz et al., 1985; Fanton and Golden, 1991). As very 

few humans have been exposed to high-LET radiation, other health effects may arise that have not been documented to date for terrestrial forms of radiation at low to moderate doses (< 2 Gy). 

 Computer-based Simulation Information 

Computer models of degenerative risks have not been developed at this time. Epidemiological data are severely 

lacking, precluding an approach that is similar to the ones that were used to project cancer risks. Only a few biological models are available that describe the degenerative processes that are caused by ionizing radiation, and 

that would be needed to form a computer model. This is probably because these processes are less studied than 

radiation carcinogenesis and are, in many cases, complicated by other lifestyle factors that influence the disease 

process. One model that was proposed by Rubin and Casarett (1968), which is called the “vascular hypothesis,” 

states that late radiation effects are caused by damage to blood vessels. This vascular injury, which has a long 

latency that reflects the slow turnover time of the vasculature, leads to vessel occlusion, ischemia, and secondary loss of parenchymal cells, which are the cells that are specific to particular tissues and organs. 

 Risk in Context of Exploration Mission Operational Scenarios 

 Projections for space missions 

No existing biophysical model projects degenerative risks for the entire range of particle types and energies that 

are found in space. The large RBEs that are found in the few studies that have been performed suggest that organ 

dose-equivalent based on radiation quality factors can be used to make a first approximation for risk estimates; 
Human Health and Performance Risks of Space Exploration Missions Chapter 7 

Risk of Acute or Late Central Nervous System Effects from Radiation Exposure 227

however, the shape of the dose-response for specific diseases and dose-rate modifiers is unknown. Dose-rate 

modifiers could be higher than observed for cancer risks because of the possibility of threshold effects. 

The estimates for ERR per Sievert, which was provided by studies of the atomic-bomb survivors, are not sufficient alone to estimate risk for astronauts because a risk transfer approach is needed together with estimates 

of RBE and dose-rate modifiers. The baseline risk of CHD is several-fold larger in the U.S. than in Japan, while 

the risk of stroke is comparable. To determine the cancer risks, the NCRP suggests using multiplicative and additive transfer models to transfer risks between populations. Figure 7-5 (Cucinotta, unpublished) shows estimates 

of cancer and CHD risks if the RBE and the DDREF are assumed to be identical for cancer and CHD. In this calculation, the multiplicative transfer model is used to transfer the CHD risk from the Japanese to the U.S. population as well as to transfer the model of NCRP Report No. 132 (NCRP, 2000) for cancer risks. NASA uses the 

model of NCRP Report No. 132, which derives risks from the atomic-bomb survivor data using a mixture model 

that combines the arithmetic average of the additive and multiplicative transfer models to project cancer risks in 

the U.S. population. In the example calculation that is shown in figure 7-5, the CHD risk alone is about half that 

of the risk of cancer in all organs combined, and is less dependent on age than is the cancer risk. Death by CHD 

exceeds cancer deaths when an individual is 50 years or older at the time of exposure. The example that is shown 

in figure 7-5 uses many simplified assumptions, but clearly suggests the importance of collecting new data to 

estimate the factors that enter into CHD and other degenerative risk prediction models. 

Figure 7-5. Comparison of projections for risk per Sievert for cancer and heart disease as a 

function of age at exposure. Calculations are made using the multiplicative transfer model 

and baseline rates for the U.S. population. Comparisons assume that RBE (quality factor) 

and DDREF are the same for each risk. The effects of competing risks are accounted for 

in the model (Cucinotta, private communication). 
Chapter 7 Human Health and Performance Risks of Space Exploration Missions 

228 Risk of Degenerative Tissue or Other Health Effects from Radiation Exposure 

 Potential for biological countermeasures 

Excessive production of free radicals produces oxidative damage to cellular structures, which includes proteins, 

DNA, and lipids, and contributes to the radiation-induced degenerative changes that are associated with aging, 

cardiovascular disease, and cataract formation. The identification of safe and effective agents that will protect 

and mitigate against these effects of radiation exposure are a high priority both for radiotherapy purposes, where 

the sparing of normal tissue is critical, and for the health of the general public in the event of a terrorist attack 

with nuclear weapons. 

Two main types of countermeasures have been used to protect normal vasculature from ionizing radiation: the 

sulfhydryl or thiol compounds, and antioxidants. Both of these classes of compounds function by scavenging 

the free radicals that are produced by the interaction of ionizing radiation with water. WR2721 – which is also 

known as amifostine and gammaphos – is the best-described member of the sulfhydryl class and is the only drug 

that is approved by the Food and Drug Administration (FDA) to help prevent excess damage to normal tissues 

during radiotherapy. The mechanism of action of this drug is thought to be scavenging the free radicals that are 

produced by radiation and H-atom donation to protect against the damage that is done by free radicals. This compound has been tested as a countermeasure for both cataract formation and vascular damage (Kador, 1983; Mooteri 

et al., 1996; Warfield et al., 1990; Plotnikova et al., 1988). Radical scavenging vitamins such as C and E have 

also been shown to protect the lens and vascular system (Bantseev et al., 1997; Jacques et al., 1997; Taylor and 

Hobbs, 2002). In addition, growth factor treatments have been shown to decrease blood vessel stenosis (Fuks, 

1994). In all of these examples, the compounds were administered prior to radiation exposure. 

 Synergistic effects with other flight factors 

No reports have been published on the possible synergistic effects from non-radiation risk factors on the degenerative risks from space radiation. However, studies of radiation effects on bone loss due to microgravity 

have been suggested. No studies at doses that are below 1 Gy have been made in this area. Ambient oxygen 

levels may be altered in space flight. For low-LET radiation, oxygen enhancement ratios (OERs) (i.e., the ratio 

of doses to produce the same effects for varying oxygen levels) can exceed 2; however, for high-LET radiation, 

less dependence on oxygen levels is observed with OERs reducing to unity (Hall, 2000). There is only a small 

probability for low-LET radiation from SPEs to reach high enough doses to cause degenerative effects if proper 

operational procedures and radiation shielding are in place. However, chronic exposure to high-LET heavy ions 

is an important concern where a dose threshold will not likely occur. In this area, very little is known, and studies 

at nominal oxygen levels are needed to achieve a basic understanding of the mechanism and to obtain animal 

data for risk assessments. On completion of such studies, further studies at varying oxygen levels may be 

warranted. 

 Conclusion 

The association between ionizing radiation exposure and the long-term development of degenerative tissue 

effects such as heart disease, cataracts, immunological changes, and premature aging is well-established for 

moderate to high doses of low-LET radiation. The majority of this evidence is derived from epidemiological 

studies on the atomic-bomb survivors in Japan, radiotherapy patients, and occupationally exposed workers, and 

is supported by laboratory studies using animal models (Blakely and Chang, 2007a; 2007b). The risks for these 

diseases from low dose-rate exposures and for HZE nuclei are much more difficult to assess due to their multifactor nature and long latency periods; therefore, these risks remain debatable for short-term lunar missions. Note, 

however, that the risks are more likely for long-term lunar or Mars missions. It also remains unclear whether 
Human Health and Performance Risks of Space Exploration Missions Chapter 7 

Risk of Acute or Late Central Nervous System Effects from Radiation Exposure 229

low-dose (<0.5 Gy) exposures influence the same biological pathways that have been shown to be involved in 

disease progression following moderate- to high-dose radiation exposures (Little et al., 2008). Likewise, very 

little information is available on the effects of space radiation on these disease processes, the role of individual 

susceptibility, and the possible synergistic effects from other space flight factors. It will be essential to obtain 

this knowledge to successfully mitigate the degenerative risk for astronauts for lunar and Mars missions. 

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Chapter 7 Human Health and Performance Risks of Space Exploration Missions 

236 Risk of Degenerative Tissue or Other Health Effects from Radiation Exposure 
Exploration Medical 

Capabilities 

Risk of Inability to Adequately 

Treat an Ill or Injured 

Crew Member 

Risk of Inability to Adequately Treat an Ill or Injured Crew Member 239

Chapter 8: 

Risk of Inability to Adequately Treat an 

Ill or Injured Crew Member 

Diana Risin 

NASA Johnson Space Center 

Mission architecture limits the amount of equipment and procedures that will be available to treat medical 

problems. Resource allocation and technology development must be performed to ensure that the limited 

mass, volume, power, and crew training time be efficiently utilized to provide the broadest possible treatment 

capability. This allocation must also consider that not all medical conditions are treatable, given the limited 

resources, and some cases may go untreated. – Human Research Program Requirements Document, HRP47052, Rev. C, dated Jan 2009. 

 

The promotion of crew health and safety in space requires the provision of 

necessary resources, despite limitations in mass, volume, power, and crew 

time, and must be directed toward the treatment of the conditions with high 

likelihood or severe consequence. The care of the crew begins with thorough 

pre-flight health status assessments and appropriate medical training in procedures and equipment to allow care to be crew-administered, and under 

certain circumstances, completely autonomous. Autonomous, crewadministered care is exemplified here, as Scott Parazynski (left) prepares to withdraw blood from the arm of John Glenn (right) while 

on the shuttle middeck. 
240 Risk of Inability to Adequately Treat an Ill or Injured Crew Member 
Human Health and Performance Risks of Space Exploration Missions Chapter 8 

Risk of Inability to Adequately Treat an Ill or Injured Crew Member 241

 Executive Summary 

A review of published and non-published (e.g., NASA Longitudinal Study of Astronaut Health database) 

information on medical conditions that occurred during space missions (including the Russian partner experience), as well as a review of relevant information from harsh analog environments (e.g., submarine fleet health 

databases, Antarctic expeditions, mountaineers’ expeditions) provides evidence that medical conditions of different complexity, severity, and emergency will inevitably occur during long-term Exploration missions. Depending 

on the medical problem, the resources that are available, and the time that is necessary for returning to Earth, 

different levels of medical care are required. Providing medical care for these conditions will be challenging in 

the resource-constrained environment of space. Plans for care to support both the health and the safety of astronauts and mission success must be made with regard to balancing the most likely conditions with those that pose 

the most catastrophic outcome. All medical problems have the potential to affect the mission, but significant 

illnesses or trauma will result in a high probability of mission failure or loss of crew. These considerations 

justify postulating and addressing the “risk of the inability to adequately treat an ill or injured crew member” 

during an Exploration mission, including not only which capabilities will be available but also how medical 

care will be provided and performed. 

 Introduction 

The specific provision of medical services during space missions is authorized and required by the following 

documents: NPD 8900.5A, NASA Health and Medical Policy for Human Space Exploration; NPD 8900.1G, 

Medical Operations Responsibilities in Support of Human Space Flight Programs; NPD 8900.3F, Astronaut 

Medical and Dental Observation Study and Care Program; and NASA-STD-3001, NASA Spaceflight Human 

Systems Standard – Volume 1, Crew Health. 

Medical conditions of different complexity could occur during space missions, especially during long-term 

space missions to the moon and Mars. An increasing number of possible medical conditions, including trauma, 

will have to be addressed for these missions since emergency returns become unlikely or impractical as the distance from Earth increases. Return will be nearly impossible during Mars missions and severely limited for many 

lunar situations. Even teleconsulting will have certain limitations due to significant delays in real-time communication on Exploration missions to Mars. Thus, health care, including emergency care and psychological support, 

will have to be self-administered and, under certain circumstances, completely autonomous. 

Genuine difficulties in providing medical care in space include, but are not limited to: (a) resource constraints 

resulting from the boundaries of the mission design and architecture (volume, mass, power) and dictating that 

only the most critical medical equipment can be stored on board the space vehicles and delivered to the space 

habitats; (b) lack of trained medical professionals among the crew members; (c) limited pre-flight crew training 

time, necessitating the restriction of the training to only medical knowledge, techniques, and procedures that address the medical situations that are most likely to occur or that are most critical; (d) the probability that the crew 

members on the vehicle or in the habitation module may have to respond to emergency medical conditions without real-time support from Earth; (e) limited shelf-life of medical therapeutics and supplies; and (f) the possibility of encountering unpredicted illnesses and ailments that may be unique to the space exploration environment. 

The most optimal way to achieve adequate support for crew health and to secure mission success on extendedduration missions is to establish a thorough pre-flight health status assessment, including all new technological 
Chapter 8 Human Health and Performance Risks of Space Exploration Missions 

242 Risk of Inability to Adequately Treat an Ill or Injured Crew Member 

approaches (genomics, proteomics, etc.), and develop a systematic approach to a more comprehensive autonomous health care system in space. 

 Evidence 

The evidence that is needed to postulate the possibility and estimate the probability of the occurrence of medical conditions during space missions can be drawn from different sources. Some sources include: (a) records 

of medical problems that were encountered in previous space flights by U.S. and Russian crews as well as other 

international partners; (b) information on the medical conditions that occurred during short- and long-term Earth 

expeditions (submarine, alpine, Arctic and Antarctic expeditions, expeditions to other remote ground-based locations, etc.); (c) general population studies addressing the age-related probabilities of different diseases and incidence of trauma; and (d) pre- and post-flight records of the health status and medical conditions of astronauts 

and cosmonauts. 

 Space flight evidence 

In-flight illness incidence rates are partially summarized in several publications (Stewart et al., 2007; Summers 

et al., 2005; Davis, 1999). Evidence can also be obtained from the Longitudinal Study of Astronaut Health database that is maintained at NASA JSC. Tables 8-1 through 8-3, which are taken from a collaborative review report that was edited by John Ball and Charles Evans, are illustrative of the conditions that could occur and 

some estimates of the probabilities (Ball and Evans, 2001). 

Table 8-1. In-flight Medical Events for U.S. Astronauts during the Space Shuttle Program 

(STS-1 through STS-89, April 1981 to January 1998) 

Medical Event or System by ICD-9a Category Number Percent of 

Total 

Space adaptation syndrome 788 42.2 

Nervous system and sense organs 318 17.0 

Digestive system 163 8.7 

Skin and subcutaneous tissue 151 8.1 

Injuries or trauma 141 7.6 

Musculoskeletal system and connective tissue 132 7.1 

Respiratory system 83 4.4 

Behavioral signs and symptoms 34 1.8 

Infectious diseases 26 1.4 

Genitourinary system 23 1.2 

Circulatory system 6 0.3 

Endocrine, nutritional, metabolic, and immunity disorders 2 0.1 

a

International Classification of Diseases, 9th Ed. 
Human Health and Performance Risks of Space Exploration Missions Chapter 8 

Risk of Inability to Adequately Treat an Ill or Injured Crew Member 243

Table 8-2. Medical Events Among Seven NASA Astronauts on Mir, 

March 14, 1995, through June 12, 1998

Event Number of Events 

Musculoskeletal 7 

Skin 6 

Nasal congestion, irritation 4 

Bruise 2 

Eyes 2 

Gastrointestinal 2 

Psychiatric 2 

Hemorrhoids 1 

Headaches 1 

Sleep disorders 1 

Note: Data from the Russian Space Agency indicate that there were 304 in-flight medical events 

on board the space station Mir from February 7, 1987 through February 28, 1998. The numbers of 

astronauts at risk or the incidence per 100 days was not reported. 

Table 8-3. Medical Events and Recurrences Among Astronauts of All Nationalities 

on Mir, March 14, 1995, through June 12, 1998

Event Number of Events 

Superficial injury 43 

Arrhythmia 32 

Musculoskeletal 29 

Headache 17 

Sleeplessness 13 

Fatigue 17 

Contact dermatitis 5 

Surface burn 5 

Conjunctivitis 4 

Acute respiratory infection 3 

Asthenia 3 

Ocular foreign body 3 

Globe contusion 2 

Dental 2 

Constipation 1 

As most of these conditions do not represent medical emergencies, they could be treated by merely taking 

medications while on board, if available. About 75% of all astronauts have taken some form of medication 

during shuttle missions for nonemergency conditions such as motion sickness, headache, sleeplessness, and 

back pain. Other nonemergency conditions that the shuttle astronauts have experienced include minor trauma, 

burns, dermatologic and musculoskeletal conditions, respiratory illnesses, and genitourinary problems, etc. 

More important is the existing evidence of potential medical emergencies during space flight, such as potentially fatal and nonfatal arrhythmias, heart attack, stroke, embolism, massive hemorrhage, emergencies 

that are related to renal stone formation, infection, and thrombotic complications. Among these conditions, only 

arrhythmias, renal colic, and infections have been documented. The documented arrhythmias were mostly mild 

abnormalities, such as occasional premature atrial contractions (PACs) and premature ventricular contractions 

(PVCs). PACs or PVCs were present in 30% of astronauts at some point during periods of strenuous activity. 
Chapter 8 Human Health and Performance Risks of Space Exploration Missions 

244 Risk of Inability to Adequately Treat an Ill or Injured Crew Member 

Potentially serious arrhythmias (supraventricular and ventricular tachycardia) have also been reported. For 

example, during Apollo 15, one crew member experienced ventricular bigeminy; ventricular ectopy was reported on Skylab; and on Mir, a crew member experienced a 14-beat run of ventricular tachycardia (FritschYelle et al., 1998). No manifestation of coronary artery disease (CAD) was registered during any human space 

flight; however, considering the risk of cardiovascular events in older people and the increasing age of crew 

members, the possibility of such complications during long-term space missions cannot be ignored. Other 

medical emergencies that have been observed in space include rare, but real, cases of urological (Berry, 1974; 

Lebedev, 1983) and dental emergencies (Newkirk, 1990; Brown et al., 1977), as well as behavioral and 

psychiatric problems. 

Additional evidence and consideration substantiates the risk of the inability to treat crew members on Exploration missions. For example, in a few cases in the past, episodes of renal colic and arrhythmia have required that 

crew members (Russian cosmonauts) be brought back to Earth, shortening their stays in space and possibly compromising the missions (Summers et al., 2005). 

Radiation exposure could also cause other potential medical problems; for example, it might affect general 

health and cause radiation-specific pathological processes, especially given the proposed length of missions to 

Mars. If such emergencies were to occur, they would most likely be catastrophic and mission ending. 

Moreover, when designing space medical care systems, the potential for crew exposure to toxic chemicals and 

gases as well as to chemical and electrical burns must be considered. There are also risks for significant trauma, 

both on board the spacecraft and during EVAs, due to the nature of operational activities and the closed environmental systems. 

Lastly, given the length of Mars missions, there is also a certain age-related probability of the development 

of diverse medical conditions that are similar to those in the general population. These probabilities can be 

assessed based on general population health statistics as well as from information that is found in the astronaut 

pre- and post-flight health databases (Peterson et al., 1993; Hamm et al., 1998). 

 Ground-based evidence 

The ground-based incidence of illness data are derived from publications and the available databases summarizing the occurrence of different medical conditions that are encountered in groups of individuals who are 

exposed to harsh environments that could be considered as analogs of the space environment. A sample of this 

information is presented in Tables 8-4 through 8-6 (Ball and Evans, 2001). As can be seen from the tables, the 

incidence of different medical conditions in these environments was, in general, relatively low (from 10 to ~50 

events per 100,000 person-days) and mostly these were non-emergent conditions. Even these illnesses (trauma, 

infections, psychiatric disorders) required an evacuation that would be difficult, if not impossible, to provide in 

space, however, especially on future missions to the moon and Mars. 

 
Human Health and Performance Risks of Space Exploration Missions Chapter 8 

Risk of Inability to Adequately Treat an Ill or Injured Crew Member 245

Table 8-4. Incidence of Health Disorders and Medical-Surgical Procedures 

during 136 Submarine Patrols

Disorder Number/ 

100,000 Person-days 

Injury (includes accidents) 48.8

Respiratory 24.6 

Skin or soft tissue 19.0 

Ill-defined symptoms 10.5 

Infections 10.0 

Procedure Percentage of All 

Procedures Performed 

Wound care, splinting 42.0 

Suturing 18.7 

Cleansing 8.2 

Nail removal 6.8 

Fluorescein eye examination 4.2 

Incision and drainage of abscess 2.9 

Tooth restoration 2.0 

Table 8-5. Reasons for 332 Medical Evacuations from All Submarines, U.S. 

Atlantic Fleet, 1993 to 1996

Reason for Evacuation Number of Cases 

Trauma 71 

Psychiatric illness 41 

Chest pain 34 

Infection 40 

Kidney stone 23 

Appendicitis 21 

Dental problem 31 

Other 71 

Totala 332 

a

Rate = 1.9 to 2.3 per 1,000 person-months 

Table 8-6. ANARE Health Register Illnesses in Antarctica from 1988 to 1997 

Disorder Number Percent of Total 

Injury and poisoning 3,910 42.0 

Respiratory 910 9.7 

Skin, subcutaneous 899 9.6 

Nervous system or sensory organs 702 7.5 

Digestive 691 7.4 

Infection or parasitic 682 7.3 

Musculoskeletal or connective tissue 667 7.1 

Ill-defined symptoms 335 3.6 

Mental 217 2.3 

It is important to emphasize that crews that were living and working in harsh environments (Antarctic expeditions, submarines, and undersea habitats) also had medical emergencies, such as intracerebral hemorrhage, 
Chapter 8 Human Health and Performance Risks of Space Exploration Missions 

246 Risk of Inability to Adequately Treat an Ill or Injured Crew Member 

stroke, myocardial infarction, appendicitis, and bone fractures. There were also cases of cancer and psychiatric illness. However, the overall rate of these serious medical or surgical emergencies was low. The most common 

emergencies were dental. For instance, in 100 British Polaris submarine patrols, crew members required 30 

fillings and seven extractions due to intolerable pain (Glover and Taylor, 1981). Dental problems had been the 

cause for a transfer at sea in the U.S. Polaris submarine program (Tansey et al., 1979). Extractions and fillings 

have also been required in Antarctica (Lisney, 1976). 

The calculated rate of significant illness or injury that is based on the meta-analysis of data from submarines, 

Antarctic expeditions, military aviation, and U.S. and Russian space flight experience was found to be approximately 0.06 event/person-year (Billica, 1996). Extrapolation of these data to a 2.5-year Mars mission involving 

six crew members provides an expected rate of a significant medical event of 0.9 people/mission (Billica, 1996). 

In other words, one significant medical event could be expected per Mars mission. It is understandable that risk 

estimations that are made by using the data from analog populations have certain limitations for Mars mission 

risk assessments. These estimates are likely to be conservative, as they do not account for the unique problems 

that are associated with the spacecraft environments, possible radiation effects, as well as exposure and physiological adaptation to low gravity (Buckey, 2006). 

Of particular interest is the incidence of cardiovascular events in the harsh-environment populations. For 

example, the reported 5-year annual cardiac events rate by age group among USAF aviators was: 0.0054% 

(30–34 years), 0.018% (35–39 years), 0.038% (40–44 years), 0.14% (45–49 years), and 0.13% (50–54 years) 

(Osswald et al., 1996). Of all of these events, 21% were cases of sudden death and 61% were diagnosed and 

treated as myocardial infarction. Therefore, despite the rigorous screening that USAF aviators undergo, very often the first manifestation of CAD in this population was a significant cardiac event (Buckey, 2006). It is believed 

that these data are applicable to the Astronaut Corps as well, despite the fact that astronauts undergo a moreextensive medical assessment. In fact, this information emphasizes the risk of occurrence of sudden death or 

heart attack in space despite thorough screening (Buckey, 2006). 

In the submarine program, the most common general surgical condition has been appendicitis (Tansey et al., 

1979), and even a case of death due to appendicitis has been reported among the participants of the Antarctic 

expeditions (Ball and Evans, 2001). Other serious conditions that were also reported in the submarine program 

were traumatic amputations, fractures, and dislocations (Buckey, 2006). Furthermore, depression and anxiety 

reactions are found to be the most common two psychiatric diagnoses that are made on submarines (Tansey et 

al., 1979), and are also frequent among researchers who are enduring long Antarctic winters (Lugg, 2000). 

 Computer-based Simulation Information 

Computer-based simulation of the likelihood and consequences of medical conditions is a decision tool that 

is used to assess medical risks. Although this methodology has not yet been used effectively to develop a probabilistic approach to support the medical management decision process, it is a promising tactic. Based on the 

premise that an optimal resolution is needed to synthesize the many incongruous factors and circumstances that 

are involved in providing medical care in space, this methodology could be used as a planning tool to address 

the likelihood of occurrence of different medical conditions and identify the required resources to treat these 

conditions. The integrated medical model (IMM), a tool of this type that quantifies the probability and consequences of medical risks, is in development. 
Human Health and Performance Risks of Space Exploration Missions Chapter 8 

Risk of Inability to Adequately Treat an Ill or Injured Crew Member 247

 Risk in Context of Exploration Mission Operational Scenarios 

A review of the medical conditions that occurred during space missions in the past, as well as a review of 

relevant information from harsh analog environments, provides sufficient evidence that medical conditions 

of different complexity, severity, and emergency may inevitably occur during long-term Exploration mission. 

Understandably, the type and severity of the risks that would contribute to these conditions might fluctuate depending on the actual configuration of a mission, its longevity, and the complexity of the tasks that are to be 

performed on it. The major goals of the Exploration medical support system for the Constellation Program are 

to define the levels and specifics of risk factors for each mission to ensure that adequate health monitoring and 

maintenance systems are developed and implemented. The medical support system should also ensure that medical care, if needed, could be delivered with support from Earth or autonomously when communications with 

support personnel on Earth are excessively delayed or unavailable. The need for autonomous medical care puts 

additional emphasis on astronaut training and the development of computerized guides to facilitate the delivery 

of care. The identification of risks must be derived from a comprehensive analysis of all of the available sources 

of information, including analog environments. Medical care for Exploration missions will be based on the current understanding of the pathogenesis of the anticipated conditions in reduced gravity and on state-of-the-art 

diagnostic and treatment capabilities that are available on Earth. These diagnostic and treatment capabilities 

have to be modified and adjusted to the specifics of the space environments and comply with the NASA space 

flight health standards. 

The development of appropriate risk context and the goals that are laid out within the ExMC Element necessitate identification of the “gaps” that exist between the anticipated in-flight medical conditions and the ability 

to mitigate or treat the conditions adequately. Documented in-flight conditions and conditions that are derived 

from comparable terrestrial populations will provide the basis for the Exploration medical condition list. This 

list will be prioritized based on the projected occurrence, possibility of being adequately diagnosed and treated 

on Exploration-class missions, consequences, and constrained resources (mass, volume, power, shelf-life, etc.) 

to diagnose and treat illnesses and injuries. This gap identification will facilitate the ability to articulate these 

difficult and complex problems and risk characterizations as well as to seek innovative solutions. 

 Conclusion 

The review of the available published and non-published (JSC database) medical information that is related 

to astronaut health and in-flight medical conditions as well as records of medical conditions occurring in analog 

environments provides strong support for risk justification for both emergent and non-emergent medical events 

in space. At the same time, the data analysis reveals significant gaps in risk assessment, knowledge concerning 

potential medical conditions, and diagnostic and treatment capabilities on Exploration missions. 

An Exploration medical condition list is being developed, in close collaboration with the Space Medicine 

Division at JSC, to focus the ExMC Element work further. This list will be further specified by Exploration 

mission design to assist with the planning of research and development activities so that Constellation Program 

development milestones and Space Life Sciences standards and requirements are met by the space vehicles. The 

identification and documentation of Exploration medical conditions and the associated gaps is essential for focusing and prioritizing ongoing studies in this field and for guiding the NASA HRP strategy. 
Chapter 8 Human Health and Performance Risks of Space Exploration Missions 

248 Risk of Inability to Adequately Treat an Ill or Injured Crew Member 

 References 

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participants. Aviat. Space Environ. Med., 69(2):142–144. 

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Lugg DJ. (2000) Antarctic medicine. J. Am. Med. Assoc., 283(16):2082–2084. 

Newkirk D. (1990) Almanac of Soviet manned space flight. Gulf Publishing Company, Houston. 

Osswald S, et al. (1996) Review of cardiac events in USAF aviators. Aviat. Space Environ. Med., 67(11):1023–

1027. 

Peterson LE, Pepper LJ, Hamm PB, et al. (1993) Longitudinal study of astronaut health: mortality in the years 

1959–1991. Radiat. Res., 133(2):257–264. 

Stewart LH, Trunkey D, Rebagliati GS. (2007) Emergency medicine in space. J. Emerg. Med., 32(1):45–54. 

Summers RL, Johnston SL, Marshburn TH, Williams DR. (2005) Emergencies in space. Ann. Emerg. Med., 

46(2):177–184. 

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patrols. Undersea Biomed. Res., 6(Suppl.):S217–S246. 
Human Health and Performance Risks of Space Exploration Missions Chapter 8 

Risk of Inability to Adequately Treat an Ill or Injured Crew Member 249

 Acknowledgments 

Jeffrey A. Jones, M.D.; Operations Discipline Team Co-Lead; Space Medicine Division, Medical Operations 

Branch, Flight Surgeon; NASA Johnson Space Center, Houston 

Richard A. Scheuring, D.O.; Operations Discipline Team Co-Lead; Space Medicine Division, Constellation 

Medical Operations Specialist, Exploration Medical Capability Flight Surgeon, HRP; NASA Johnson Space 

Center, Houston 

Jay C. Buckey, Jr., M.D.; NSBRI Discipline Team Co-Lead; Professor of Medicine, Dartmouth Medical 

School, Lebanon, N.H. 

Lawrence A. Crum, Ph.D.; NSBRI Discipline Team Co-Lead; Research Professor, Department of 

Bioengineering, The University of Washington School of Medicine, Seattle, Wash. 

Babs R. Soller, Ph.D.; NSBRI Discipline Team Co-Lead; Professor of Anesthesiology, Department of 

Anesthesiology, University of Massachusetts Medical School, Worcester, Mass. 

David K. Baumann, Space Medicine Division; Exploration Medical Capability Program Element Manager, 

HRP; NASA Johnson Space Center, Houston 

Jonathan B. Clark, M.D.; NSBRI/NASA Space Medicine Liaison, Houston. 

Mary A. Fitts; Space Medicine Division; Exploration Medical Capability Deputy Program Element Manager, 

HRP; NASA Johnson Space Center, Houston 

Kathy A. Johnson-Throop, Ph.D.; Space Medicine Division; Medical Informatics and Health Care Systems 

Branch Chief; NASA Johnson Space Center, Houston 

Jennifer A. Fogarty, Ph.D.; JSC Health and Medical Technical Authority Coordinator; NASA Johnson Space 

Center, Houston 

 
Chapter 8 Human Health and Performance Risks of Space Exploration Missions 

250 Risk of Inability to Adequately Treat an Ill or Injured Crew Member 
Space Human Factors 

and Habitability 

Risk of Error Due to Inadequate 

Information 

Risk of Reduced Safety and 

Efficiency Due to Inadequately 

Designed Vehicle, Environment, 

Tools, or Equipment 

Risk of Error Due to Poor 

Task Design 

Risk Factor of Inadequate 

Food System 

Risk of Adverse Health Effects 

from Lunar Dust Exposure 

Risk of Error Due to Inadequate Information 253

Chapter 9: 

Risk of Error Due to Inadequate Information 

Abbe Barr 

Lockheed Martin Corporation 

Susan Schuh

Wyle Integrated Science and Engineering Group 

Janis H. Connolly

NASA Johnson Space Center 

Barbara Woolford

NASA Johnson Space Center 

Mary Kaiser

NASA Ames Research Center 

Information presentation, acquisition and processing significantly affect human task performance. Effective 

information availability directly impacts all aspects of communication, which is a vital element to all space 

missions. Task errors during human spaceflight missions could have significant consequences to performance 

of mission objectives as well as human safety. Therefore further research regarding proper information 

presentation will allow for opportunities to optimize presentation of information, its timeliness, the user’s level 

of awareness of the information, modes of information presentation, proper information comprehension, 

training methods, and development of procedures. – Human Research Program Requirements Document, 

HRP-47052, Rev. C, dated Jan 2009. 

 Astronauts must monitor systems and perform critical operations daily while in space. 

Data monitoring in the past has required the 

review of numerous pages of paper data, as 

pictured here. Extensive ongoing NASA activity 

mitigates the risk of operator error by improving 

the display of information, the types of controls 

that interface between the human and the displays, and the procedures necessary to 

accomplish tasks. 
254 Risk of Error Due to Inadequate Information 
Human Health and Performance Risks of Space Exploration Missions Chapter 9 

Risk of Error Due to Inadequate Information 255

 Executive Summary 

Human-centered design is essential to implement effective information management. The inadequate provision 

of information can increase the probability of operator error, thus impacting the safety and productivity of space 

flight missions. Evidence that is relevant to the risk of error due to inadequate information illustrates that effective information management and communications are critical to mission success. 

Although operator errors are common in all work environments, task errors that occur during human space 

flight missions could have drastic consequences. Errors can be due to inadequate information, which, in turn, 

may be caused by (a) a lack of situational awareness, (b) forgetting, (c) an inability to access appropriate data 

and procedures, or (d) a failure of judgment. The causation trail that is engendered by errors leads to (a) a lack 

of situational awareness that can result from poorly designed interfaces, poorly designed tasks, or cognitive decrements that are caused by, for example, fatigue or exposure to toxic environments; (b) forgetting, which can result 

from inadequate training, poorly designed procedures, or cognitive decrements; (c) an inability to access appropriate data and procedures, which can be a result of poorly designed interfaces, poorly designed tasks, or cognitive 

decrements; and (d) a failure of judgment that can be the product of incorrectly perceived or interpreted cues, 

inappropriately estimated results of decisions, or inadequate data. 

This chapter focuses on identifying the causes of risk that are associated with error due to inadequate information, and on developing information presentation standards for reducing operator errors in space flight 

through adequate understanding of the causes. Mitigating this risk involves addressing the display of information, the types of controls that provide an interface between the human and the displays, and the procedures that 

are necessary to accomplish tasks. 

 Introduction 

 Human factors and human-centered design 

The study of human factors engineering embraces the design of tools, machines, systems, tasks and environments to ensure safety, efficiency, habitability, and optimized human performance (Chapanis, 1996). The study 

of space human factors focuses on the need for safe, efficient, and cost-effective operations, maintenance, and 

training in flight, on orbit, and on the ground. The purpose of space human factors is to create and maintain a 

safe and productive environment for humans in space. The domain of space human factors engineering consists 

of three sub-domains of knowledge: task design; the design of the vehicle, the environment, the tools, and the 

equipment; and information. 

The SHFH Element contains five risks, three of which are associated with space human factors engineering. 

These are: (a) the risk of error due to inadequate information, (b) the risk that is associated with poor task design, and (c) the risk of reduced safety and efficiency due to an inadequately designed vehicle, environment, 

tools, or equipment. All of these risks have the same underlying root cause: the lack of human-centered design 

(figure 9-1). 

Human-centered, or user-centered, design is a design approach that focuses on humans and their interaction with procedures, products, equipment, facilities, and environments. It seeks to use known information 

concerning human capabilities and develop designs that better match systems with human capabilities. To do 

this, practitioners of human-centered design capitalize on the strengths of the human in the system design while 
Chapter 9 

256 Risk of Error Due to Inade

limiting the potential impacts resulting

throughout the planning, concept develo

tem. Good human-centered design prac

human-machine system and improve th

cluding the human. 

Figure 9-1. Fault tree for lack of human-c

Multiple contributing components can ca

tasks and procedures, poorly designed h

lack of task analysis and understanding

the lack of an integrated system design a

Without proper integration between the

poor human factors design may arise. If

hardware and software integrity, and m

Evidence that will be presented in this a

and depth of the risks that are associate

due to inadequate information, the risk t

and efficiency due to an inadequately d

Human Health and Performance Risks of Space Ex

quate Information 

g from human limitations. Human-centered design focus

opment, design, and final implementation phases of a pro

ctices reduce the elements of risk that can lead to human e

he efficiency of operation and safety of all system compon

centered design. 

ause a lack of human-centered design. These include poorly

hardware and software, poorly designed habitats and envi

 of operations, disregard for the human in the human-mac

approach, and a lack of user evaluations and iterative know

e human and the system, the risk of reduced safety and eff

f risks are not mitigated, the safety of the flight, the health

mission success may be significantly affected. 

and the next two SHFH chapters effectively illustrates the

d with a lack of human-centered design. These are: the ris

that is associated with poor task design, and the risk of red

designed vehicle, environment, tools, or equipment. The i

xploration Missions 

es on the users 

oduct or a syserror in the 

nents, iny designed 

ronments, a 

chine system, 

wledge capture. 

ficiency due to 

h of the crew, 

e breadth 

sk of error 

duced safety

intention of 
Human Health and Performance Risks of Space Exploration Missions Chapter 9 

Risk of Error Due to Inadequate Information 257

the SHFH chapters is to provide a narrative discussion of the risk, together with the evidence that supports 

its existence or the potential for risk. This evidence provides the basis for analysis of the risk likelihood and 

consequence, and may provide the information that is needed to eventually develop standards for reducing 

operator errors in space flight through adequate understanding of the causes and mitigations of operator 

errors. 

The review of these risks is important, as space flight crew performance is heavily influenced by the way 

in which the crews are able to obtain situational awareness and safely and effectively perform tasks. Current 

and future missions will require that the crews perform a wide variety of tasks under dramatically different 

conditions: i.e., 1g, hypergravity, microgravity, unsuited, suited, and pressurized. Mission success will require a more complete understanding of information and how it is best presented, acquired, and processed. 

 Evidence 

The evidence that is presented in this chapter encompasses the lessons learned from 50 years of space flight 

experience related to the risk of error due to inadequate information. It is classified in this chapter, as it is in the 

other chapters, by categories and topic areas. Category I and II16 evidence consists of quantitative and 

qualitative findings from research and development. Data are classified as Category I or II, depending on the 

specific testing protocol that is used and the data that are sought. Category III evidence consists of summaries of 

subjective experience data, as well as nonexperimental observations and comparative, correlation, and case or 

case-series studies. It should be noted that evidence that is derived from the ISS Life Sciences Crew Comments 

Database is essentially Category III evidence. Although summaries of ISS crew comments are presented as 

evidence, the Life Sciences Crew Comments Database, due to the sensitive nature of the raw crew data that it 

contains, is protected and not publicly available. Category IV evidence consists of expert committee reports and 

respected authority opinion based on clinical experiences, bench research, or “first principles.” 

The evidence that is presented here details human space flight issues that are related to inadequate information, specifically those that address presentation, acquisition, and processing. Inefficiencies and impacts that are 

related to information can restrict human performance in space flight conditions and affect safety and habitability. Therefore, these issues must be assessed and properly addressed to ensure that all potential hazards are mitigated or monitored. If the information that is necessary to complete the tasks is not presented, acquired, or 

processed appropriately, the likelihood of errors or the inability to successfully complete a task increases. 

 Information acquisition 

Information acquisition is defined as the way in which a user or a system obtains information. This acquisition 

can occur through various means. Most of the information that is needed for space flight missions is obtained 

through training, both on the ground and on orbit. Information is also obtained on orbit via crew-to-crew and 

 

16To help characterize the kind of evidence that is provided in each of the risk reports in this book, the authors were encouraged to 

label the evidence that they provided according to the “NASA Categories of Evidence.” 

 Category I data are based on at least one randomized controlled trial. 

 Category II data are based on at least one controlled study without randomization, including cohort, case-controlled or subject

operating as own control. 

 Category III data are non-experimental observations or comparative, correlation and case, or case-series studies. 

 Category IV data are expert committee reports or opinions of respected authorities that are based on clinical experiences, bench 

research, or “first principles.” 
Chapter 9 Human Health and Performance Risks of Space Exploration Missions 

258 Risk of Error Due to Inadequate Information 

crew-to-ground communication, as well as through robotics and automation. Regardless of the mode that is used 

to acquire information, it is important that the process be refined to ensure that the right methods are being used, 

the method duration is appropriate for the type of information that is being transferred, and the amount of time between receiving and processing the information is adequate. Proper definition and execution of these elements 

will ensure the successful acquisition of information in the space environment, thus leading to mission success. 

The paragraphs below describe cases in which the acquisition of information was unsuccessful or improvements 

should have been made. 

Improved information acquisition is needed with ISS task procedures. As documented in the ISS Life Sciences 

Crew Comments Database, ISS crew members have consistently commented that the procedures are too complex, lengthy, and difficult to follow. Procedures can often complicate or impede the performance of daily tasks 

because they may call for an inadequate number of crew members to perform a task, or the specified duration for 

a task may be inappropriate. Progress is being made in improving procedures and in enhancing the crew members’ 

abilities to acquire information by including more graphic content (diagrams and images). The goal is to improve 

the procedures so that they can better reflect how operations are actually conducted. Other types of improvements will also be needed to adequately inform the crew. 

Paper checklists are an example of inadequate information acquisition. They have been used by on-orbit crews 

for many years, but navigating through paper checklists has been difficult. Procedures are coded with specialized 

symbols, abbreviations, boundary delimiters, and spatial configurations that collectively require extensive training to decipher and understand. Individual instructions in these cue cards and checklists frequently take the form 

of conditional expressions (i.e., IF-THEN-ELSE statements), which crew members must evaluate by manually 

cross-checking systems or flight status information on cockpit instruments and displays. The outcome of this 

evaluation of the logical expression determines which path should be taken through the remainder of the checklist; and that path, in turn, determines which subsequent instructions must be carried out, and in what order. 

Wrong choices that are based on an inappropriate assessment of the state of information that was presented 

can endanger the crew (Hudy and Woolford, 2007) (Category III). 

Data that are contained in the (ISS) Life Sciences Crew Comments Database indicate that the ISS crews rely 

heavily on auditory information and warnings on orbit. Auditory information has as its main advantage that the 

crew does not need to be looking at a display to be aware of an alarm. The acoustic levels on board the ISS have 

been historically high and have impacted communication and the receipt of some information. These high levels 

of continuous and intermittent noise require the use of earplugs or noise-canceling headsets to mitigate noise exposure. Although this protection assists with decreasing detrimental noise exposure, communications among crew 

members and between the crew and the ground may be degraded. On a few occasions, the elevated noise levels 

have prevented the crew from hearing caution-and-warning alarms and other monitoring signals. In addition, 

crew members may also become uncomfortable while wearing this protection (Rando et al., 2005) (Category 

III). 

Effective information acquisition has also been decreased by other communication issues that have been encountered on the ISS, such as miscommunications, unrealistic demands, ineffective interpersonal communication 

techniques, and a lack of understanding of on-orbit life. Inadequate communication between the ground and the 

crew can cause frustration that can, in turn, negatively affect performance. Ground operators have, in the past, 

had difficulty understanding how much time it actually takes to complete tasks on orbit, which frustrates both the 

crew and the ground personnel. Many times crew members have been unaware of what the ground personnel 

could assist with and what tasks could be automated to facilitate crew productivity. There have also been cases 
Human Health and Performance Risks of Space Exploration Missions Chapter 9 

Risk of Error Due to Inadequate Information 259

in which ground personnel should have relied on the crew to do many things and should not have overridden 

crew member suggestions (Rando et al., 2005) (Category III). 

 Information presentation and processing 

Information is presented most effectively when the users’ interests, needs, and knowledge are considered. 

Effective presentation of information can be accomplished by ensuring that (a) operations concepts are fully 

developed, (b) task analysis is conducted at a low enough level of detail, and (c) task analysis is accurate and 

its completeness is verified. The designer must also ensure that the user has complete awareness by considering 

both perceptual thresholds and good information display design. Lastly, information must be presented using the 

correct mode. If information is not presented clearly, the user may process the message incorrectly, and may 

misinterpret, overlook, or ignore the original intent of the information. 

Information processing can be accomplished either through individual or multi-agent distribution. In designing 

for individual information processing, the thought process of the receiver should be considered, as well as how 

the individual may execute the information. This consideration is critical for successful task execution. Although 

for multi-agent or distributed processing the elements for individual processing also apply, the processing is more 

complex because additional users and/or automation are involved. When information is not processed as intended, the outcome of a task can be jeopardized and mission success can be put at risk. The following examples 

are cases in which the presentation or processing of information was degraded or unsuccessful, or could have 

been improved to be more effective. 

As simulated environments and ground-based full-scale models or mockups cannot be completely representative of flight conditions, representing a true zero-g environment on the ground has presented many challenges 

for training and information presentation. Thus, simulations may not provide adequate information during preflight training. As documented in the ISS Lessons Learned Database, a true representation of the stowage of 

equipment and materials aboard the ISS is very difficult to achieve on the ground and can create issues for the 

crew. Stowage mockups in 1g are limited because gravity restricts operations and translation in the training facilities. Given the constraints of a 1g-based translation path, it is neither possible nor safe to place things where 

they would potentially be stowed on board the ISS. The weightless environment on orbit benefits the crew in that 

it allows items to be stowed on any axis with proper restraint. In addition, the crew members can translate through 

the available volume and position their bodies to move around obstructions or protrusions in the translation 

paths. 

In summary, given the gravitational differences between Earth and orbit and the disconnect between ground 

training and actual life on orbit, crew members often experience steep learning curves once they are on board 

the ISS because the simulators and mockups, which are not completely representative of zero-g conditions, do 

not provide adequate information. The result is that on arrival on board the ISS, crew members often experience 

difficulty managing stowage and operating nominally, and errors result (see figures 9-2 and 9-3) (Category III). 

 
Chapter 9 Human Health and Performance Risks of Space Exploration Missions 

260 Risk of Error Due to Inadequate Information 

Computer displays and software technology that are on the 

ground are constantly changing and improving. Computer 

and software technologies on board the ISS have historically 

lagged behind these available ground-based technologies. 

Displays and software platforms often differ from application to application, depending on the task that is being supported. Many interfaces on the ISS are not the same as those 

that are commonly used on Earth. This inconsistency between 

ground and space has been a source of operational frustration 

for crewmembers. Therefore, it is important to provide crews 

with systems that are similar to those used on the ground to 

improve in-flight information presentation and avoid impacts 

on human and system efficiency and performance in space. 

As documented in the ISS Life Sciences Crew Comments 

Database, usability issues have occurred that are associated 

with the use of displays that lack a common overall infrastructure and layout that would promote ease of use and understanding of intended operations. Valuable ISS crew time has been 

lost in trying to understand the use of disparate displays, which 

has led to incorrect data entry, navigational errors, or inaccurate interpretation of data in the displays. When display interfaces are dissimilar and the information is not presented 

consistently, crew members may require additional training 

and time to master the use of the displays. Crew members 

may also revert to an uncomplimentary skill base from another display design. This natural human tendency may 

override training and lead to errors that can compromise 

crew safety, especially in the event of an emergency 

(Category III). 

ISS crews are inundated daily with information concerning procedures. Some ISS electronic procedures and 

formats have been especially difficult to use. Frequently, crew members have spent excessive amounts of time 

Figure 9-2. JSC2007-E-46438 (September 2007) —

Astronaut Peggy A. Whitson, Expedition 16 

commander, and cosmonaut Yuri I. Malenchenko, 

flight engineer representing the Russian Federal 

Space Agency, participate in a training session at 

the Gagarin Cosmonaut Training Center, Star City, 

Russia (NASA Human Spaceflight Gallery, 2008). 

Figure 9-3. ISS016-E-022130 — Cosmonaut 

Yuri I. Malenchenko, Expedition 16 flight engineer 

representing the Russian Federal Space Agency, 

uses a communication system while working in 

the Zvezda service module of the ISS (NASA 

Human Spaceflight Gallery, 2008). 
Human Health and Performance Risks of Space Exploration Missions Chapter 9 

Risk of Error Due to Inadequate Information 261

navigating among various menus because the procedures were difficult and lengthy or contained unnecessary 

information. In many cases, the content of a procedure contributed to inadvertent skipping of steps in the 

procedure and poor task execution. 

A number of complaints have been received from ISS crew members concerning the implementation and 

overabundance of cautions and warnings (C&Ws) in procedures. The primary reason for using C&W advisory 

blocks in procedures is to protect the crew members and the hardware from potentially unsafe conditions or incidents. The overuse of C&Ws in procedures has contributed to the desensitization of the crew to C&W (as shown 

by accidental procedure step-skipping and inattention to important C&Ws because they are embedded in trivial 

warnings). 

Issues that are associated with procedures have occurred during ISS missions and are directly related to the 

provision of too much information, lack of diagrams and schematics to illustrate necessary information, and 

confusion and missed steps caused by multiple links in procedures. These issues have frustrated crew members 

and directly affected the efficient performance of tasks because the information that was needed for a given task 

was not presented in a usable format (Rando et al., 2005) (Category III). 

As documented in the ISS Life Sciences Crew Comments Database, other issues occurred because electronic 

updates to procedures often have to be printed out to update procedure books with new information, costing the 

crew time to print and change out the affected pages. Moreover, printing compounds the issues with information 

processing as issues often arise with printers on orbit, leading to frustration among crew members. These crew 

members have commented that although the ISS printing procedure worked during ground training in the simulator, it did not work on orbit because the on-orbit printer was not the same printer as the one that was used during 

training. Clearly, therefore, the information and hardware that are provided for training must be as similar as 

possible to what will be provided on orbit to avoid learning curves once crew members arrive at the ISS (see 

figure 9-4). 

On Apollo 10, at the end of the second pass over lunar landing site 2, the two crew members were preparing 

to separate the two stages of the lunar lander and return to the command module in orbit around the moon when 

the mode of the guidance and navigation system was inadvertently changed by one of the crew members. A couple 

Figure 9-4. ISS015-E-17702 —

Cosmonaut Fyodor N. Yurchikhin, 

Expedition 15 commander representing 

the Russian Federal Space Agency, holds 

a camera while looking over procedures 

checklists in the Zvezda service module 

of the ISS (NASA Human Spaceflight 

Gallery, 2008). 
Chapter 9 Human Health and Performance Risks of Space Exploration Missions 

262 Risk of Error Due to Inadequate Information 

of seconds later, the other crew member reached up, without looking, and changed the mode of the guidance 

system, which canceled the change that had been made by the first crew member. As a result, the lunar module, 

Snoopy, began firing thrusters in all axes, pushing the gyroscopes into gimbal lock and making the navigation 

system useless until it was reset. The crew member then toggled the navigation system switch again and, although he now put it into the mode it should have been in to start with, it made things worse. At this point 

the crew overrode the computer and took manual control. 

The incident lasted about 15 seconds, during which Snoopy made eight complete rolls. It was estimated that if the 

crew members had not regained control within another 2 seconds, it would have been too late to avoid impact 

with the moon. Without clear information processing and communication between crew members concerning 

their dedicated duties, there is real risk to safety from accidental operations (Shayler, 2000) (Category III). 

 Computer-based Simulation Information 

Understanding human integration with systems and identifying the risks that may be inherent in a concept or 

a design is often achieved via computer-based simulation. Computer-based simulation tools have multiple uses 

including detection of potential risks to the human. Computer-based simulation and virtual environments create 

a metaphor for the real world with which the user interacts. With the aid of equipment such as head-mounted 

displays, data gloves, three-dimensional audio, and haptic or tactile feedback, the individual can interact with a 

virtual world as that world simulates reality. These virtual environments can be used to create simulations for 

training or, perhaps, interacting with prototypes that do not yet exist in the real world. 

Inefficient or inadequate presentation of information presents a risk to crew effectiveness and safety, especially 

during off-nominal operations. In 1999, NASA JSC initiated the process of upgrading the cockpits of the space 

shuttle orbiters. The primary impetus for this upgrade was the perceived risk of reduced safety and efficiency of 

shuttle operations due to the lack of a human-centered design approach to information conveyance by the 1970sera display formats. 

The product of the cockpit avionics upgrade (CAU) effort was a new suite of explicitly task-oriented display 

formats that (a) consolidated and integrated task-related information; (b) more clearly supported fault detection, 

isolation, and recovery operations; (c) used color-coding to guide and manage the attention of operators; and 

(d) streamlined display navigation with new display control devices. 

As part of the CAU project, engineers conducted a thorough human-in-the-loop evaluation of the CAU display 

formats in the Shuttle Mission Simulator that directly measured operational efficiency and error rate in a series 

of full-mission simulations of off-nominal ascent and entry scenarios. The scenarios were completed with both 

the existing (i.e., 1970s-era format) display suite and cockpit interface devices and the upgraded displays and interfaces. The results provided an empirical database quantifying the performance benefits and enhanced operational efficiency that accompanied the human-centered redesigns. When questioned concerning conditions during 

their just-completed scenarios, crew members who had trained in the CAU cockpit answered almost 75% of the 

questions correctly as compared to the typically less than 40% who had trained in the existing cockpit. The workload was rated 38% lower with the CAU cockpit. The incidence of a particularly safety-critical form of operator 

error (the percentage of system malfunctions and flight anomalies that went unrecognized) stood at 30% in the 

existing cockpit; however, in the CAU cockpit, the rate of error was only 10%, which is a 67% reduction. 

Finally, while little difference was apparent between the existing and CAU cockpits when crew members diagnosed the easiest malfunctions, there was a distinct latency advance for the CAU cockpit for the more difficult 
Human Health and Performance Risks of Space Exploration Missions Chapter 9 

Risk of Error Due to Inadequate Information 263

malfunctions. In the very slowest (most difficult) cases, the average CAU advantage was 40 seconds. This 

demonstrates how improved display formats can reduce the risk of operation error due to inadequate information (McCandless et al., 2005; Hayashi et al., 2005) (Category II). Figure 9-5 demonstrates how Manmachine Integration Design and Analysis System (MIDAS) simulations reproduced the findings of the 

CAU display suite evaluation. 

 Risk in Context of Exploration Mission Operations Scenarios 

Future Exploration missions will increase in length. Lunar missions will provide a substantial set of independent lessons learned, experiences, and more definitive knowledge gaps that will apply to Mars exploration. Crews 

will face the challenges of physical deconditioning, prolonged isolation and confinement, significant communication latencies, environmental stressors, and increased responsibility and autonomy. Effective design solutions 

for vehicles, habitats, and missions need to allow the management and control of all aspects of Exploration 

mission operational scenarios. 

Human-centered design must be implemented in all aspects of the design process to mitigate or prevent space 

human factors engineering risks from occurring. Designing for reduced gravity will be critical. Lunar and martian environmental conditions – air quality, lunar or martian dust, radiation exposure, and lighting – must be 

addressed. Stowage provisions need to ensure that appropriate spares and stowage volumes are available and 

accessible in a timely manner. Intuitive human-computer interaction will be necessary owing to increasingly 

complex task demands and the need for autonomy. A reduction in required maintenance and interface with 

complex systems should be implemented. Commonality in design and implementation should cross all 

hardware and tool designs. Procedures and training should accommodate the increased autonomy to provide appropriate information and avoid excessive workload. 

 Conclusion 

The risk of error due to inadequate information stems from a broader cause of human error: the lack of humancentered design. To reduce or eliminate this risk requires that designers focus on the user throughout the design 

process. Good human-centered design practices strive to improve the efficiency of operation and safety of all 

system components, including the human, and should reduce the life cycle cost of the project. The risk that is 

Figure 9-5. MIDAS simulations were conducted to reproduce the 

findings of the CAU display suite evaluation. Task timelines and 

workload outputs were examined as part of these simulations 

(NASA Human Spaceflight Gallery, 2008).
Chapter 9 Human Health and Performance Risks of Space Exploration Missions 

264 Risk of Error Due to Inadequate Information 

associated with error due to inadequate information focuses on identifying the causes of that risk – e.g., the lack 

of situational awareness that might be due to poorly designed interfaces or tasks – and the subsequent development of information presentation standards for reducing operator errors in space flight through the development 

of an adequate understanding of the causes and mitigations of the errors. 

The human-machine system emphasizes the importance of the human element as the central focus of the 

human-centered design process. This includes consideration for human capabilities, limitations, and interaction 

with automation and hardware. Knowledge gaps or holes that are related to the lack of an integrated system design 

approach for information acquisition, presentation, and processing must be addressed to ensure quality standards, requirements, tools, and techniques are developed that will allow positive crew-system integration and 

interaction, and, ultimately, mission success. 

The evidence that is discussed in the SHFH chapters identifies risks. To alleviate these risks, “knowledge gaps” 

or “holes” and future research directions have been identified. Some of these knowledge gap considerations are 

related to the constant need for efficient information acquisition, presentation, and processing, and an improved 

understanding of the crew and mission requirements and constraints for task design and training. 

 References 

Chapanis A. (1996.) Human factors in systems engineering. Wiley series in systems engineering. John Wiley 

and Sons, Inc., N.Y. 

Hayashi M, Huemer V, Renema F, Elkins S, McCandless JW, McCann RS. (2005) Effects of the space shuttle 

cockpit avionics upgrade on crewmember performance and situation awareness. In: Proceedings of the Human 

Factors and Ergonomics Society 49th Annual Meeting. Human Factors and Ergonomics Society, Orlando, Fla., 

Sep 26–30, 2005, pp. 54–58. 

Hudy C, Woolford B. (2007) Space Human Factors Engineering Gap Analysis Project final report. Retrieved 

Feb 12, 2008 from the following Website: 

http://ntrs.nasa.gov/archive/nasa/casi.ntrs.nasa.gov/20070020456_2007018857.pdf. 

McCandless JW, McCann RS, Berumen KW, Gauvain SS, Palmer VJ, Stahl WD, Hamilton AS. (2005) 

Evaluation of the space shuttle cockpit avionics upgrade (CAU) displays. In: Proceedings of the Human Factors 

and Ergonomics Society 49th Annual Meeting. Human Factors and Ergonomics Society, Orlando, Fla., Sep 26–

30, 2005, pp. 10–14. 

NASA. Human Spaceflight Gallery [photographs on the Internet]. Retrieved Jan 26, 2008 from the following 

Website: http://spaceflight.nasa.gov/gallery/index.html. 

Rando C, Baggerman SD, Duvall LE. (2005) Habitability in space. In: Proceedings of the Human Factors 

and Ergonomics Society 49th Annual Meeting, Aerospace Systems. Human Factors and Ergonomics Society; 

Orlando, Fla., Sep 26–30, 2005, p. 59. 

Shayler DJ. (2000) Lunar module checkout-mode error. In: Mason J (Ed.), Disasters and accidents in manned 

spaceflight. Springer-Praxis, Chichester, U.K., pp. 216–220. 
Human Health and Performance Risks of Space Exploration Missions Chapter 9 

Risk of Error Due to Inadequate Information 265

 Acknowledgments 

Alicia Foerster, B.S., Marine Biology; Project Manager, SHFH Element, HRP; NASA Johnson Space Center, 

Houston. 

Carlton D. Donahoo, B.A., M.A., Human Factors; Usability Testing and Analysis Facility Human Factors 

Engineer, Habitability and Environmental Factors Division; NASA Johnson Space Center, Houston. 

Immanuel Barshi, Ph.D., Linguistics and Cognitive Psychology, Communication, Decision Making, Spatial 

Reasoning, Human Error, Team Cognition; Senior Principal Investigator; Human System Integration Division; 

NASA Ames Research Center, Moffett Field, Calif. 

Michael Feary, Ph.D., Human Factors Engineering; Automation Design and Analysis; Research Psychologist; 

NASA Ames Research Center, Mountain View, Calif. 

Keith V. Holubec, B.S., Marine Biology; SHFH Element, HRP; NASA Johnson Space Center, Houston. 

Victor Ingurgio, Ph.D., Experimental Psychology; Senior Human Factors Design Engineer for the 

Anthropometry and Biomechanics Facility; NASA Johnson Space Center, Houston.

Robert S. McCann, Ph.D., Cognitive Psychology; Human-System Interface Design and Evaluation; Group 

Lead, Intelligent Spacecraft Interface Systems (ISIS) Lab; NASA Ames Research Center; Moffett Field, Calif. 

Cindy Rando, M.S., Human Factors; ISS Flight Crew Integration Human Factors Engineer, Habitability and 

Environmental Factors Division; NASA Johnson Space Center, Houston. 

Dane Russo, Ph.D., Experimental Psychology; Space Systems Development and Project Management, Manager 

for SHFH Element, HRP; NASA Johnson Space Center; Houston. 

Barry Tillman, M.S.; M.S., Systems and Industrial Engineering; B.A., Psychology; Senior Human Factors 

Engineer, Habitability and Human Factors Branch; NASA Johnson Space Center, Houston. 

 
Chapter 9 Human Health and Performance Risks of Space Exploration Missions 

266 Risk of Error Due to Inadequate Information 
Risk of Reduced Safety and Efficiency Due to Inadequately Designed 

Vehicle, Environment, Tools, or Equipment 267

Chapter 10: 

Risk of Reduced Safety and Efficiency 

Due to Inadequately Designed Vehicle, 

Environment, Tools, or Equipment 

Susan Schuh

Wyle Integrated Science and Engineering Group 

Abbe Barr 

Lockheed Martin Corporation 

Janis H. Connolly

NASA Johnson Space Center 

Barbara Woolford

NASA Johnson Space Center 

Mary Kaiser

NASA Ames Research Center 

The habitability of the architecture, habitable environment, tools, and equipment is critical for the existence of 

humans in space. Any inadequacies in the design of the environment or architecture can restrict or prevent the 

user from surviving in such extreme conditions and may impact safety and performance. Factors that affect the 

habitability must be assessed and properly addressed to ensure all potential hazards are mitigated or 

monitored. If the workspace, equipment and tools are not designed to be usable by the full range of crew 

members, and are not properly laid out, the likelihood of errors or crew inability to complete a task in a timely 

manner increases. Inconsistent design among subsystems and vehicles leads to negative transfer of training 

and increased likelihood of errors. – Human Research Program Requirements Document, HRP-47052, Rev. 

C, dated Jan 2009. 

 The ISS (photographed by the departing STS-127 

astronauts as they begin their return to Earth) is a 

highly visible example of a successful cooperative 

endeavor. Integrating human factors principles into 

environmental and architectural designs for hardware, 

software, vehicles, and habitats is required to ensure 

the usability of space systems and the safety of

space travelers.
268 Risk of Reduced Safety and Efficiency Due to Inadequately Designed 

Vehicle, Environment, Tools, or Equipment 
Human Health and Performance Risks of Space Exploration Missions Chapter 10 

Risk of Reduced Safety and Efficiency Due to Inadequately Designed 

Vehicle, Environment, Tools, or Equipment 269

 Executive Summary 

The primary goal of the SHFH Element for human space exploration is to preserve the safety of the crew, promote human performance, and increase efficiency while on orbit. This goal is achieved by integrating human 

factors principles into the environmental and architectural design for hardware, software, vehicles, and habitats. 

In particular, optimal on-orbit environmental conditions and architectural design are critical for the health and 

well-being of space flight crew members as well as the habitability of vehicles and habitats. Optimized usability 

in the design of workspaces, equipment, and tools for the remote space flight environment is also important. Evidence that is captured in this chapter emphasizes the importance of human factors design considerations, and also 

illustrates how operator safety and efficiency can be jeopardized when these considerations are not addressed 

throughout the system life-cycle process for vehicles, environments, tools, and equipment. For a more detailed 

summary of overall concepts that are related to space flight human factors and human-centered design, refer to 

Chapter 9 of this document.

 Introduction 

The purpose of the space human factors discipline is to create and maintain a safe and productive environment for humans in space, which requires an understanding of human performance and limitations. Inadequate 

implementation of human factors design in work environments will result in reduced human performance, an 

increased likelihood of human errors, and decreased mission safety and effective mission execution. These potential, negative outcomes emphasize the need for focused, human-centered design that will assist in the development 

of hardware, software, and tools that are better designed to fit the human and reduce overall human safety risks 

to the program. With missions using new technologies at an ever-increasing rate, it is imperative that these advances enhance crew performance without increasing crew workload, stress, or risk. It is important to identify 

concerns that require a space human factors assessment and highlight the value of space human factors and 

safety on orbit. 

This chapter focuses on evidence that is related to the risk of reduced safety and efficiency due to inadequately 

designed vehicles, environments, tools, and equipment. This evidence emphasizes the importance of human 

factors design considerations, and illustrates how operator safety and efficiency can be jeopardized when these 

considerations are not addressed throughout the life cycle of vehicles, environments, tools, and equipment. 

 Evidence 

Evidence that is presented in this chapter encompasses lessons learned from 50 years of space flight experience 

that is related to the risk of reduced safety and efficiency due to inadequately designed vehicles, environments, 

tools, or equipment. As with the rest of this book, evidence is classified by categories. Category I and Category 

II evidence consists of quantitative and qualitative findings from research and development. Data are classified 

as Category I or Category II, depending on the specific testing protocol that was used and the data that were sought. 

Category III evidence consists of summaries of subjective experience data, as well as non-experimental observations and comparative, correlation, case, and case-series studies. It should be noted that some evidence, which is 

essentially Category III evidence, is derived from the ISS Life Sciences Crew Comments Database. Although 

summaries of ISS crew comments are presented as evidence here, the Life Sciences Crew Comments Database is 

protected and, therefore, is not publicly available due to the sensitive nature of the raw crew data that it contains. 
Chapter 10 Human Health and Performance Risks of Space Exploration Missions 

270 Risk of Reduced Safety and Efficiency Due to Inadequately Designed 

Vehicle, Environment, Tools, or Equipment 

Category IV17 evidence consists of expert committee reports and respected authorities’ opinions that are based 

on clinical experiences, bench research, and “first principles.” 

Evidence that is described in this chapter details human space flight safety and human performance efficiency 

issues that are related to environmental and architectural design as well as to the usability and design of workspaces, equipment, and tools. When these aspects of design are inadequate, overall habitability is affected; these 

issues must therefore be assessed and properly addressed to ensure that all potential hazards are mitigated or monitored. If the workspace, equipment, and tools are not designed to be usable by the full range of crew members 

and are not properly laid out, the likelihood of errors or of the inability of the crew to complete a task in a 

timely manner increases. Inconsistent design of subsystems and vehicles leads to negative transfer of training 

and an increased likelihood of errors. 

 Environmental and architectural design 

Optimal on-orbit environmental conditions and architectural design are critical for the health and well-being 

of space flight crew members and the habitability of vehicles and habitats. Any inadequacies in the design of 

the architecture or the environment that is built can affect the safety and performance of the human. The environmental and architectural factors affecting habitability must be assessed and properly addressed to ensure that 

all potential hazards are mitigated or, at a minimum, monitored. Noise and lighting issues are specific environmental issues that are experienced on orbit that affect habitability. Issues that are related to environment depend 

on the manner and extent of exposure to environmental elements. Architecture issues that impact habitability are 

related to the design, configuration, and topology of the interior volume of space vehicles and modules and to the 

co-location of systems and tasks. They include issues that are related to human translation (movement from one 

location to another) and orientation information as well as problems that have occurred when vehicles, habitats, 

or other hardware designs did not accommodate the user. 

For example, noise is a pervasive aspect of all living and working environments that can, at times, present 

hazards. The ISS acoustic environment, in particular, is complex, and includes many types of noise-generating 

hardware because the ISS provides not only home for the space flight crew, but also their workshop and laboratory (Rando et al., 2005). The cumulative effects of the ISS acoustic environment manifest themselves in two 

forms: continuous and intermittent noise (Baggerman et al., 2004). Continuous noise is generated by the operation of pumps, fans, compressors, avionics, and other noise-producing hardware or systems. Intermittent noise is 

caused by hardware that operates cyclically, e.g., exercise equipment or the carbon dioxide removal system. Onboard acoustics measurements in various ISS modules often exceed the ISS flight rules for noise exposure and 

can be at 67 dB or higher over a cumulative 24-hour period (Goodman, 2000; Clark and Allen, 2008). Issues 

and constraints that are related to the acoustics environment increase the risk of impacts on crew safety as the 

crew may not be able to hear the C&Ws. Although C&W tones are typically audible, noise within the ISS 

from daily operations and activities has sometimes impeded the crew’s ability to hear the C&W tones. 

 

17To help characterize the kind of evidence that is provided in each of the risk reports in this book, the authors were encouraged to 

label the evidence that they provided according to the “NASA Categories of Evidence.” 

 Category I data are based on at least one randomized controlled trial. 

 Category II data are based on at least one controlled study without randomization, including cohort, case-controlled or subject

operating as own control. 

 Category III data are non-experimental observations or comparative, correlation and case, or case-series studies. 

 Category IV data are expert committee reports or opinions of respected authorities that are based on clinical experiences, bench 

research, or “first principles.” 
Human Health and Performance Risks of Space Exploration Missions Chapter 10 

Risk of Reduced Safety and Efficiency Due to Inadequately Designed 

Vehicle, Environment, Tools, or Equipment 271

This inability to hear can also affect efficient mission performance by interfering with communication between crew members as well as between the crew and the ground. As documented in the ISS Life Sciences 

Crew Comments Database, noise has interfered with communication between crew members in different modules as well as between crew members in the same module. Noise has cost crew members time as they translate 

between modules to communicate directly. Wearing hearing protection because of high noise levels also impacts 

communication (figure 10-1). In addition, some crew members have reported that excessive noise on station has 

negatively contributed to their perception of ISS habitability. For instance, on-board noise has wakened some 

sleeping crew members. These examples show the need for optimal environmental conditions, such as acoustic 

levels that are below unacceptable noise thresholds, and the appropriate provision of auditory information 

(Category III). 

The provision of adequate lighting conditions is also essential for any living and working environment, 

including on board ISS. Although the station has increased substantially in size, it still remains a confined 

environment in which crew members live and work. It limits them to only the lights that are provided in modules and the additional lighting that is provided by portable and handheld lights. The evidence that is described 

below emphasizes the importance of providing appropriate lighting conditions. 

Several issues have arisen with lighting on board the ISS (Baggerman et al., 2004). Lighting in some of the 

ISS modules was not originally installed in a manner that would provide the maximum amount of light output 

that had been designed into the lighting fixture. In addition, lights have failed throughout the life of the ISS, and 

limits on shuttle and Soyuz launch mass and volume have prevented the delivery of replacement light fixtures. 

Lighting in the ISS Node 1 module has been further affected by excessive stowage that has blocked operational 

lights, thus reducing the reflectivity of the surrounding surfaces. Because of the low lighting levels, some crew 

members have had to move certain tasks out of Node 1 to perform them, which both increases the time that is 

necessary to perform tasks and decreases efficiency. Working behind panels or racks without dedicated lighting 

has been difficult for some of the crew members. This situation forces them to accommodate and make up for 

the poor design by using other types of portable lighting while they are searching for items or working behind 

Figure 10-1. ISS018-E-027439 — Cosmonaut Yury Lonchakov, 

Expedition 18 flight engineer, wears a hearing-protection device as he 

uses an oscilloscope to measure voltage in the Pirs docking compartment 

of the ISS (NASA Human Spaceflight Gallery, 2008). 
Chapter 10 Human Health and Performance Risks of Space Exploration Missions 

272 Risk of Reduced Safety and Efficiency Due to Inadequately Designed 

Vehicle, Environment, Tools, or Equipment 

panels. In summary, these impedances and inadequacies related to the ISS lighting have contributed to risks to 

efficiency on board the station (Category III).

Inefficiencies in space flight vehicle and habitat architectural design as well as the co-location of systems and 

tasks can affect crew safety, efficiency, and habitability. The co-location of certain functional habitability areas 

has been problematic throughout long-duration space flight due to vehicle size and topology constraints (figure 

10-2). Lessons-learned summaries from the data that were collected in the ISS Life Sciences Crew Comments 

Database provide evidence that, on board the ISS, the adjacency of sleeping quarters with waste and hygiene facilities has not proven optimal due to the noise that is made by the equipment, which disrupts crew sleep. The colocation of the dining facilities near the exercise equipment and waste collection facilities compromises meal 

scheduling by influencing when food preparation and dining can be done. Although it is still possible to conduct 

dining activities while other crew members are exercising or using the Waste Collection System, it is not optimal. 

In addition, locating the dining facilities near the laboratory work jeopardizes both the habitability of the station 

and the integrity of its science activities. The integrity of science can be compromised by the introduction of 

foreign debris (e.g., food products), which can alter the results of an experiment by contaminating an environment that should be controlled. 

The movement of crew and hardware through the confined spaces of the ISS has been an ongoing topic of 

concern. As documented in the ISS Life Sciences Crew Comments Database, frequently used ISS translation 

passages have been blocked by large items, such as stowage or exercise equipment, which has contributed to 

congestion (figure 10-3). The location of the dining table in a high-traffic area such as the Zvezda service module (pictured in figure 10-2(a) and (b), above), with other colocated habitability hardware, has made translation 

difficult for crews. These co-location issues are caused by the lack of available habitable volume and resources 

that is endemic when living in space. This design concept has been suboptimal, however, and will not benefit 

future space habitat designs, as it presents numerous operational hazards to crews. Indeed, these vehicle design 

and topology constraints can affect daily tasks, habitability, and overall mission objectives so much that they 

impede crew safety; clearly, therefore, they must be improved (Category III). 

Figure 10-2b. ISS019-E-010232 — Japan Aerospace 

Exploration Agency astronaut Koichi Wakata, Expedition 

19/20 flight engineer, floats in the Zvezda service 

module of the ISS (NASA Human Spaceflight 

Gallery, 2008).

Figure 10-2a. ISS008-E-21921 — Astronaut C. Michael Foale, 

Expedition 8 commander and NASA ISS science officer, equipped with a bungee harness, performs squat exercises on the 

Treadmill Vibration Isolation System in the Zvezda service 

module (NASA Human Spaceflight Gallery, 2008). 
Human Health and Performance Risks of Space Exploration Missions Chapter 10 

Risk of Reduced Safety and Efficiency Due to Inadequately Designed 

Vehicle, Environment, Tools, or Equipment 273

Issues can also arise when safety precautions for the space environment do not take into account pre-flight 

ground activities. An example of what can occur when on-orbit and pre-flight activities are not well melded 

took place during the Apollo Program on January 27, 1967, when the Apollo 1 crew initiated what should have 

been a routine countdown drill. Disaster struck when a flash fire erupted in the command module at the NASA 

Kennedy Space Center, Pad 34 (figure 10-4). All three of the crew members lost their lives because they were 

unable to open the hatch and escape the command module to safety (Kranz, 2000). Numerous factors contributed 

to this incident, including an inadequate hatch design. The hatch, which had been designed to open inward, was 

impossible for a human to open at the pressure levels that were extant within the vehicle. Procedures or processes 

had not been put in place to deal with this type of emergency event because little consideration had been given 

to the risks and hazards that were associated with any of the pre-flight activities, only with those pertaining to 

space flight. This oversight contributed to the unsafe situation in the capsule and, ultimately, led to the crew 

members’ deaths (Category III). 

Figure 10-3. ISS011-E-06401 — Astronaut John L. Phillips, Expedition 11 

NASA ISS science officer and flight engineer, is photographed among 

stowage bags in an airlock on the ISS. This photograph illustrates the 

physical transition/movement difficulties that are encountered on board 

station (NASA Human Spaceflight Gallery, 2008).

Figure 10-4. Apollo 1 crew prior to the tragic fire (left; from left, Virgil I. Grissom, Edward H. White II, and Roger B. Chaffee) 

and the vehicle after the fire (right) (United States Centennial of Flight Commission, 2003).
Chapter 10 Human Health and Performance Risks of Space Exploration Missions 

274 Risk of Reduced Safety and Efficiency Due to Inadequately Designed 

Vehicle, Environment, Tools, or Equipment 

The data that have been amassed on space flight crew postural changes are limited. Currently, space flight researchers are attempting to assess postural changes in zero g and related effects on crew health and safety for 

future Constellation Program missions. These postural changes directly affect the architectural design constraints 

and considerations for these future missions in which crew members will experience an increase in height of about 

3% during the first day or two of weightlessness. These crew members will retain this increase throughout the 

mission until they are exposed again to 1g, at which time the process is reversed (Anthropometric source book, 

1978). Current research indicates that weightless posture differs from any normal 1g posture on Earth, and that 

the body rebels with fatigue and discomfort against any attempts to force it into 1g postures or appliances that 

are consistent with 1g postures. The occurrence of crew member height changes was recognized when height data 

were collected on Skylab 4 and during the Apollo-Soyuz Test Project (ASTP) and were then compared to preand post-flight data. The design and usability of any human-machine interface can be affected by changes in the 

height and length of the trunk (Brown 1975; 1977). Examples of design problems include the design of pressure 

suits, clothing, workstations, and cockpit seating. New research is planned for upcoming shuttle missions to determine the potential for increased impacts on future vehicle crews from postural limitations on seated height 

and changes in it, and from the architectural design constraints of the vehicle. These assessments are aimed 

at increasing safety and efficiency for future missions (Category II). 

 Usability and design of workspaces, equipment, and tools 

The importance of optimized usability and the design of workspaces, equipment, and tools increases in the 

remote space flight environment. As stated by the authors of the SHFH Risk description, if the workspace, 

equipment, and tools are not designed to be usable by the full range of crew members and are not properly laid 

out, the likelihood increases of errors or the inability of the crew to complete a task in a timely manner. Inconsistent design among subsystems and vehicles can also lead to the negative transfer of training, which risks the 

safety of the crew, and an increased likelihood of errors. 

A high level of human-machine interdependence exists in space systems. To promote safe and efficient human 

factors designs, it is important to consider in the design process not only the biological effects of microgravity, 

but also the capabilities and limitations of both people and machines. For example, when tools are designed for 

use during an EVA, the strength that is required to use the equipment should be guided by that of the weakest 

and smallest individuals (i.e., the 1st-percentile female), as all crew members will have an equal likelihood of 

needing to use the equipment in an emergency (Category III). 

The poor design of workspaces, equipment, and tools on orbit, which will result in poor usability, can lead to 

performance degradation and reduced situational awareness. As documented in the ISS Life Sciences Crew 

Comments Database, some ISS hardware items and tools do not have common or consistent interfaces. In 

addition some hardware items require unique tools, and the metric and English systems are used inconsistently 

because station hardware and tools are designed by U.S. and International Partners. 

Spacesuits are an essential tool for crew members who are living and working in extreme environments such 

as the moon or Mars as well as for space shuttle and ISS EVAs. Achieving suit comfort has been a challenge for 

designers. In a study that was conducted in January 2008, data were collected on three subjective measures of comfort in the advanced crew escape suit (ACES), the Mark III suit, and the rear entry ILC Dover suit (REI) (Harvey 

et al., 2007). With regard to overall discomfort, subjects documented that no matter which spacesuit they were 

in, they experienced some level of discomfort, and this level of discomfort increased during pressurized testing. 

Specific anatomical regions where discomfort was noted were the shoulders, back, neck, knees, and lower arms. 

Discomfort while suited was attributed to the pressure demand regulator in the ACES and to bearing and resting 
Human Health and Performance Risks of Space Exploration Missions Chapter 10 

Risk of Reduced Safety and Efficiency Due to Inadequately Designed 

Vehicle, Environment, Tools, or Equipment 275

weight in the two planetary suits (i.e., the Mark III suit and the REI). These concerns will figure more prominently for long-duration planetary habitation because of the large number of anticipated EVAs that will be required. Suit discomfort can reduce the safety and efficiency of all aspects of crew performance (Category II). 

Stowage is a critical component of the usability and design of space flight vehicle and habitat workspaces 

(Clark and Allen, 2008).On-orbit stowage includes not only the location of, but also the organization of, stowed 

items. Operations are impeded if stowed items cannot be easily located or identified (figures 10-5 through 10-7). 

With increased and accumulating stowage on board the ISS, there has been a need to stow items in front of 

panels and in translation paths, resulting in the crew members’ reduced ability to access items quickly. In 

addition, cable routing blocks access to panels and stowage locations. 

 

Figure 10-5. S118-E-07630 — Astronaut 

Alvin Drew, STS-118 mission specialist, 

moves a stowage container through the 

Destiny laboratory of the ISS while Space 

Shuttle Endeavour remains docked 

with the station (NASA Human 

Spaceflight Gallery, 2008).

Figure 10-6. ISS010-E-25228 — This view 

shows supplies and equipment stowed in 

the functional cargo block (FGB) or Zarya 

photographed by a crew member on the ISS. 

(NASA Human Spaceflight Gallery, 2008).
Chapter 10 Human Health and Performance Risks of Space Exploration Missions 

276 Risk of Reduced Safety and Efficiency Due to Inadequately Designed 

Vehicle, Environment, Tools, or Equipment 

ISS accessibility problems are caused both by obstructions and by the design and integration of hardware 

(Clark and Allen, 2008). The interior components of the U.S. segment of the ISS are grouped into a series of 

“racks” that individually rotate, or tip over, to provide crew access to the rack utility connections and the module wall. However, crew feedback has indicated that rotating the racks is not an effective way to access utilities 

and connectors in the microgravity environment on station. The clearance that is required for human accessibility 

has been repeatedly cited as an issue in rack rotation capability. The design of the panels and drawers with these 

racks has compromised crew accessibility because many of them “stick” on orbit because the design does not 

operate as intended in zero g, or too many items are placed in the stowage locations and are not organized to 

afford easy operation. 

Finally, overall topology of workspaces has negatively affected crew accessibility. As an example, the U.S. cycle 

ergometer blocks access to the U.S. Laboratory window. As physical and visual access to on-board windows is 

very important to crew members for their mental health and overall judgment of habitability, restricted access and 

blocked translation paths contribute negatively to the overall safety and efficiency of the crew, especially in the 

event of an emergency (Category III).

The ISS on-board stowage accumulation has also been exacerbated by the buildup of packing materials that 

arrive with each shipment (by either space shuttle or a resupply vehicle, such as the Russian Progress module) 

(Baggerman et al., 2004). The limitations that are associated with the ability to dispose of packing materials on 

station result in excessive amounts of space being used to stow waste. The amount of stowage on board the ISS 

has increased to the point that all of the designated stowage areas are full and items are now being stowed in areas 

that were intended for habitability and work-related functions. Items are now stowed in passageways as well as 

in front of other stowage areas. In some instances, the stowage violates the allowable limits requirements that 

were originally set for the habitable volume areas. The result of this is that when crew members are searching for 

items, they must move many other stowed items out of the way to gain access to the place in which a desired 

item is located. During some ISS Expeditions, stowage has been located in the translation aisle, thereby blocking the emergency fire ports. This specific issue serves as an example of the risk that excessive stowage can 

impose on crew safety (Category III). 

Figure 10-7. ISS016-E-028889 — Cosmonaut 

Yuri I. Malenchenko, Expedition 16 flight engineer representing the Russian Federal Space 

Agency, works in the Unity node of the ISS 

while Space Shuttle Atlantis (STS-122) is 

docked with the station. (NASA Human 

Spaceflight Gallery, 2008). 
Human Health and Performance Risks of Space Exploration Missions Chapter 10 

Risk of Reduced Safety and Efficiency Due to Inadequately Designed 

Vehicle, Environment, Tools, or Equipment 277

Balancing the launching of ISS supplies (manifest) with the ability to dispose of waste and to return items 

to Earth (down mass) is necessary to maintain habitable conditions on the ISS (Baggerman et al., 2004). The 

stowage situation became a habitability issue because of an imbalance between the space shuttle launch and 

return mass limits due to the grounding of the shuttle fleet after the Columbia accident and the reluctance of ISS 

Program personnel to dispose of unused hardware and supplies. As the amount of on-board stowage has, at times, 

exceeded the allowable ISS requirements for acceptable levels of stowage in the habitable volume, stowage levels 

are constantly tracked and evaluated. Over time, the on-board inventory of supplies (e.g., clothing and hygiene 

supplies) has increased, and the manifesting of these supplies still continues. Each ISS Expedition crew member 

brings a selection of personal items with him or her to station, and at the end of that crew member’s stay the unused items remain. This increase in inventory contributes to crew safety risks, as ample stowage space is not available to accommodate placement of items outside of the habitable volume and translation paths. As the inventory 

management function has improved and the manifesting process has been streamlined, this situation has improved 

somewhat; stowage nevertheless continues to be a problem due to the lack and inconsistent nature of disposal 

capability due to space shuttle flights and inconsistent practices for tracking hardware and supplies (Category 

III). 

 Computer-based Simulation Information 

Understanding human integration with systems and identifying risks that may be inherent in a concept or a 

design is often achieved via computer-based simulation. Computer-based simulation tools have multiple uses, 

including detection of potential risks to humans that are associated with reduced safety and efficiency due to 

inadequately designed space vehicles, environments, tools, or equipment. Computer-based simulation and 

virtual environments create a representation of the real world, and the user interacts with this representation with 

the aid of head-mounted displays, data gloves, and three-dimensional audio, haptic, or tactile feedback. Such 

environments can be used for training or, perhaps, interacting with prototypes that do not yet exist in the real 

world. 

In the 1990s, NASA and the Federal Aviation Administration (FAA) engaged in several joint research efforts 

with the goal of providing safer, faster, and more fuel-efficient routing operation in flight management through 

use of automation in air traffic control (Pisanich and Corker, 1995). It was thought that integrating automation 

technologies into the air traffic control system could optimize routing, sequencing, and scheduling in the terminal 

areas and, ultimately, improve efficiency while relaxing constraints during flight to accommodate user-preferred 

routing and schedules. Man-machine Integration Design and Analysis System (MIDAS) was adapted to model a 

predictive flight crew performance (figure 10-8) that focused on predicting the performance of a two-pilot flight 

crew responding to information that was generated by an automated air traffic control system, the Center 

Terminal Radar Approach Control (TRACON) Automation System (CTAS). 

During the course of research, experimenters conducted two computer simulations. The first of these employed 

a model of top of descent (TOD). This model was developed with the goal of determining an optimal range of 

time in which the CTAS descent clearance would be issued so that the aircrew would be likely to accept the 

clearance and enact it using flight deck automation rather than by manually commanding the descent. This model 

confirmed that as the TOD point draws closer, the aircrew will select the less-automated alternative mode of 

control. In this study, as the aircraft approached within 5 to 8 miles of the CTAS-required TOD point, the number 

of successes in any clearance compliance was reduced significantly. It was found that multiple simulated trials 

could be conducted without compromising human safety when determining the optimal range of time in which 

to issue CTAS descent clearance. Moreover, multiple scenarios could be tested that did not require the use of 

an aircraft, and the aircrew’s trust in the automation could also be determined. Results of the study assisted 
Chapter 10 Human Health and Performance Risks of Space Exploration Missions 

278 Risk of Reduced Safety and Efficiency Due to Inadequately Designed 

Vehicle, Environment, Tools, or Equipment 

designers in integrating automation technologies into the system to improve crew efficiency by optimizing 

routing, sequencing, and scheduling. This provides evidence that inadequately designed equipment could 

lead to a risk of reduced safety and efficiency (Category II). 

Figure 10-8. Full MIDAS closed-loop model (Pisanich and Corker, 1995). 

 Risk in Context of Exploration Mission Operational Scenarios 

Future Exploration mission durations will substantially lengthen. During this extended timeframe, crews will 

face the challenges of physical deconditioning, prolonged isolation and confinement, significant communication 

latencies, environmental stressors, and increased responsibility and autonomy. Effective human-centered design 

techniques for vehicles, habitats, and missions allow Exploration mission operational scenarios to be managed 

and controlled. For further information, see Chapter 9 of this report. 

Human-centered design must be implemented in all aspects of the design process to mitigate or prevent space 

human factors engineering risks from occurring and specifically to ensure the safety and efficiency of the crew. 

Designing for reduced gravity will be critical. Lunar and martian environmental conditions – air quality, dust, 

radiation exposure, and lighting – must be addressed. The interior configuration of the spacecraft must support 

expected crew tasks. Hardware commonality and standardization will support interchangeability and reduce the 

amount of time that is needed for training. Spacecraft designers need to ensure that appropriate spares and stowage volumes are available and can be accessed in a timely manner. A reduction in required maintenance and 

interface with complex systems should also be implemented. 

 Conclusion 

The risk of reduced safety and efficiency due to inadequately designed vehicle, environment, tools, or equipment stems from a broader cause of human error – the lack of human-centered design, which requires a focus on 

the user throughout the design process. Good human-centered design practices will result in improved efficiency 

of operation and safety of all system components, including the human, and should reduce the life-cycle cost of 

the project. The evidence that is discussed in this chapter identifies concerns that are associated with the risk. To 

alleviate these concerns, knowledge gaps, or “holes,” and future research directions have been identified. Some 
Human Health and Performance Risks of Space Exploration Missions Chapter 10 

Risk of Reduced Safety and Efficiency Due to Inadequately Designed 

Vehicle, Environment, Tools, or Equipment 279

of these knowledge gaps are related to poorly designed hardware, software, environments, and habitats as 

well as the lack of appropriate design considerations, guidelines, and countermeasures for systems on future 

vehicles. 

The human-machine system emphasizes the importance of the human as the central focus of the humancentered design process. This focus includes consideration for human capabilities, limitations, and interaction 

with automation and hardware. Knowledge gaps, or “holes,” that are related to the lack of an integrated system 

design approach for environmental and architectural design and usability and the design of workspaces, equipment, and tools must be addressed to ensure that quality standards, requirements, tools, and techniques are developed to allow positive crew-system integration and interaction to occur and, ultimately, mission success. 

 References 

Baggerman SD, Rando C, Duvall LE. (2004) Habitability and human factors: lessons learned in long duration 

spaceflight. In: Proceedings of the American Institute of Aeronautics and Astronautics Space 2004 Conference 

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Brown J. (1975) ASTP002: Skylab 4 and ASTP crew height. Retrieved Dec 28, 2007 from the following 

Website: http://lsda.jsc.nasa.gov. 

Brown J. (1977) Crew height measurement. In: Nicogossian A (Ed.), The Apollo-Soyuz Test Project medical 

report. NASA, Washington, D.C., pp. 119–121. 

Clark JB, Allen CS. (2008) Acoustics issues. In: Barratt MR, Pool SL (Eds.), Principles of clinical medicine for 

spaceflight. Springer-Verlag, N.Y., pp. 521–534. 

Goodman JR. (2000) International Space Station acoustics. J. Acoust. Soc. Am., 108(5):2475. 

Harvey C, Jones J, Whitmore M, Gernhardt M. (2007) Wearability, comfort and field of view findings from the 

integrated launch suit test. TP-2007-214754. NASA Johnson Space Center, Houston. 

Kranz G. (2000) A fire on the pad. In: Failure is not an option. Simon & Schuster, N.Y., pp. 191–207. 

NASA. Human Spaceflight Gallery [photographs on the Internet]. Retrieved Jan 26, 2008 from the following 

Website: http://spaceflight.nasa.gov/gallery/index.html. 

Pisanich GM, Corker KM (Eds.). (1995) A predictive model of flight crew performance in automated air traffic 

control and flight management operations. Proceedings of the 8th International Symposium on Aviation 

Psychology, Columbus, Ohio, Apr 24–27, 1995. 

Rando C, Baggerman SD, Duvall LE. (2005) Habitability in space. In: Proceedings of the Human Factors 

and Ergonomics Society 49th Annual Meeting, Aerospace Systems. Human Factors and Ergonomics Society, 

Orlando, Fla., Sep 26–30, 2005, pp. 5–9. 

Staff of Anthropology Research Project (Eds.) (1978) Anthropometric source book; Vol. I: Anthropometry for 

designers. NASA 1024. Webb Associates, Yellow Springs, Ohio. 

United States Centennial of Flight Commission. (2003) Born of dreams – inspired by freedom. Retrieved 

Jan 28, 2008 from the following Website: http://www.centennialofflight.gov. 
Chapter 10 Human Health and Performance Risks of Space Exploration Missions 

280 Risk of Reduced Safety and Efficiency Due to Inadequately Designed 

Vehicle, Environment, Tools, or Equipment 

 Acknowledgments 

Immanuel Barshi, Ph.D., Linguistics and Cognitive Psychology; Senior Principal Investigator, Human System 

Integration Division; NASA Ames Research Center, Moffett Field, Calif. 

Carlton Donahoo, M.A., Human Factors; Usability Testing and Analysis Facility Human Factors Engineer, 

Habitability and Environmental Factors Division; NASA Johnson Space Center, Houston. 

Michael Feary, Ph.D., Human Factors Engineering; Automation Design and Analysis; Research Psychologist; 

Ames Research Center, Mountain View, Calif. 

Alicia Foerster, B.S., Marine Biology; Project Manager, SHFH Element, HRP; NASA Johnson Space Center, 

Houston. 

Keith V. Holubec, B.S.; Project Manager, SHFH Element, HRP; NASA Johnson Space Center, Houston. 

Victor Ingurgio, Ph.D., Experimental Psychology; Senior Human Factors Design Engineer for the 

Anthropometry and Biomechanics Facility; NASA Johnson Space Center, Houston.

Robert S. McCann, Ph.D., Cognitive Psychology; Human-System Interface Design and Evaluation; Group 

Lead, ISIS Lab; NASA Ames Research Center, Moffett Field, Calif. 

Cindy Rando, M.S., Human Factors; ISS Flight Crew Integration Human Factors Engineer, Habitability and 

Environmental Factors Division; NASA Johnson Space Center, Houston. 

Dane Russo, Ph.D., Experimental Psychology; Space Systems Development and Project Management; SHFH 

Element Manager, HRP; NASA Johnson Space Center, Houston. 

Barry Tillman, M.S., Systems and Industrial Engineering, B.A., Psychology; Senior Human Factors Engineer, 

Habitability and Human Factors Branch; NASA Johnson Space Center, Houston. 
Risk of Error Due to Poor Task Design 281

Chapter 11: 

Risk of Error Due to Poor Task Design 

Susan Schuh

Wyle Integrated Science and Engineering Group 

Abbe Barr 

Lockheed Martin Corporation 

Carlton Donahoo

Wyle Integrated Science and Engineering Group 

Janis H. Connolly

NASA Johnson Space Center 

Barbara Woolford

NASA Johnson Space Center 

Mary Kaiser

NASA Ames Research Center 

If roles and responsibilities for accomplishing tasks are not clearly defined, there will be a risk of serious errors 

of omission or commission. This risk may relate to interaction between multiple crew members, to interactions 

between crew and robotics/automation, and between crew and ground control. Understanding the 

characteristics of the elements involved, how each communicates, and establishing guidelines to adhere to 

during task design and procedure development are all essential to mission success. – Human Research 

Program Requirements Document, HRP-47052, Rev. C, dated Jan 2009. 

 EVAs are accomplished by human-robotic teams, where 

EVA crew members work outside of the vehicle with the 

robot arm and additional crew members work inside the 

vehicle at the robotics workstation. Using human-robotic 

teams for tasks reduces human workload and increases 

task efficiency. 
282 Risk of Error Due to Poor Task Design 
Human Health and Performance Risks of Space Exploration Missions Chapter 11 

Risk of Error Due to Poor Task Design 283

 Executive Summary 

Many human performance errors that have been experienced in long-duration space flight have been directly 

related to poor system and task design. Poor task design results from a lack of integration and consideration of 

the human throughout the operational process. The human-system interface and tasks that require human performance must be designed to elicit appropriate inputs from the operator. If the roles and responsibilities for 

accomplishing tasks are not clearly defined, there will be a risk of serious errors of omission or commission. This 

risk may relate to interactions among multiple crew members, to interactions between crew and robotics/automation, and between crew and ground control personnel. Evidence for the risk that is associated with poor task 

design is related to both human and automated tasks. The authors of this chapter emphasize that the success of 

long-duration missions with highly complex systems relies heavily on effective task design. For a more detailed 

summary of the overall concepts related to space flight human factors and human-centered design, refer to 

Chapter 9 of this document. 

 Introduction 

The risk of errors due to poor task design relates to the definition and development of mission tasks, and to the 

interactions among multiple crew members, between the crew and robotics/automation, and between the crew 

and ground control personnel. Accomplishing mission-related tasks involves multiple crew members, robotic or 

automated systems, and ground control personnel. To achieve successful task performance, each person and system must have clearly defined roles and responsibilities. If the roles and responsibilities for a task are not correctly assigned, serious errors of omission or commission can occur. 

To design mission tasks for optimal performance, task designers often must integrate human and automated 

tasks or integrate the actions of more than one crew member or the actions of crew members and ground support personnel. The interactions among crew members, between crew members and ground support personnel, 

and between crew members and robotics and automated systems depend on the humans’ understanding of their 

assigned roles and responsibilities. It is crucial for designers also to have an understanding of the appropriate 

allocation of roles and responsibilities to the various participants in a task. Appropriate allocation of roles and 

responsibilities is facilitated by the task designers’ ability to understand the characteristics and limitations of all 

of the humans and automated systems that are involved in the task, and how each of them communicates. The 

use of such knowledge to allocate roles and responsibilities should be included in the guidelines to which the 

designers will adhere during task design and procedure development. 

 Evidence 

The evidence that is described in this chapter encompasses the lessons learned from 50 years of space flight 

experience as these lessons learned relate to the risk of error due to poor task design. Evidence is classified by 

specific categories and topic areas. Specifically, Category I and Category II evidence consist of quantitative and 

qualitative findings from research and development. Data are classified as Category I or Category II, depending 

on the specific testing protocol that was used and the data that were sought. Category III evidence consists of 

summaries of subjective experience data as well as non-experimental observations or comparative, correlation, 

and case or case-series studies. It should be noted that some evidence in this chapter is derived from the ISS Life 

Sciences Crew Comments Database, which is made up essentially of Category III evidence. Although summaries of the ISS crew comments are presented as evidence, the ISS Life Sciences Crew Comments Database 
Chapter 11 Human Health and Performance Risks of Space Exploration Missions 

284 Risk of Error Due to Poor Task Design 

is protected and not publicly available due to the sensitive nature of the raw crew data that it contains. 

Category IV18 evidence consists of expert committee reports or respected authorities’ opinions based 

on clinical experiences, bench research, or “first principles.” 

If the number of task errors increases, task performance decreases. Task performance, which may or may 

not involve a person, is the outcome of a task. It can be quantified by the results and the duration of the task 

(Sanders and McCormick, 1993). 

The evidence that is presented here focuses on the concept that the root cause of task performance error is the 

poor design of human and automated tasks. Without proper consideration for task design, the task performance 

of both humans and automated systems will degrade, and the mission will be unsuccessful. 

 Human task design and performance 

Poor task design can result in human errors and, possibly, degraded overall performance. These errors can be 

related to the type and purpose of tasks, the level of completion, and who or what is performing the task. Some 

tasks are best suited for humans and should not be automated. Humans are generally better at recognizing unexpected events, reasoning, and developing solutions (Sanders and McCormick, 1993). To achieve optimal human 

task performance for space missions, adequate workload and situational awareness levels of humans must be maintained. Humans who are given too many responsibilities to perform may become overloaded, and their performance may degrade. Conversely, if all tasks are automated, humans can become complacent and lose situational 

awareness. When tasks are automated, it is important to keep a crew member “in the loop” to ensure that the automation is performing as anticipated. Maintaining even low-level crew involvement provides crew members 

with a complete understanding of both manual and automated tasks and allows them to efficiently and appropriately conduct their tasks, which include monitoring automated tasks for issues or failures. A few examples 

of poor performance due to poor human task design follow. 

In June 1997, the Russian spacecraft Progress 234 collided with the Russian Mir space station, causing the 

pressure hull to rupture and nearly causing the Mir to be abandoned (figure 11-1). A number of contributing 

factors were cited in the post-accident analysis of the incident, including the condition of the vehicle and the 

decision to shut the Kurs radar system down during Progress 234 docking because of concern that the radar 

system had caused radio interference during a previous flight. This action deprived the crew of the necessary 

range data that would have prevented the collision. It was later determined that the crash had three immediate 

causes: an initial closing rate that was higher than planned, a late realization that the closing rate was too high, 

and incorrect final avoidance maneuvering. 

 

 

18To help characterize the kind of evidence that is provided in each of the risk reports in this book, the authors were encouraged to 

label the evidence that they provided according to the “NASA Categories of Evidence.” 

 Category I data are based on at least one randomized controlled trial. 

 Category II data are based on at least one controlled study without randomization, including cohort, case-controlled or subject

operating as own control. 

 Category III data are non-experimental observations or comparative, correlation and case, or case-series studies. 

 Category IV data are expert committee reports or opinions of respected authorities that are based on clinical experiences, bench 

research, or “first principles.” 
Human Health and Performance Risks of Space Exploration Missions Chapter 11 

Risk of Error Due to Poor Task Design 285

Several types of human factors task design issues may have contributed to this incident; among these are: 

psychophysical (manual docking system display issues), sensory-motor (issues with the tele-operation of the 

Progress and difficulty determining the relative velocity from visual information), and cognitive (lack of information about the position of the crew and the range and range rate, thereby decreasing spatial awareness) (Ellis, 

2000). The crew also experienced stress because of an overly demanding workload and repeated system failures, 

which continuously commanded their attention and contributed to reduced vigilance (Ellis, 2000). In addition, 

the last formal training that the crew members received took place 4 months before the docking event, and they 

may not have had sufficient or timely practice in task design to handle the conditions. After the Progress collision 

with Mir, the emergency situation required closing the hatch of a module that was leaking air. This task took extra 

time because the cables that were running through the open hatch did not have easily operable disconnects and, 

therefore, the crew had to cut them. All of the aforementioned factors contributed to the degraded overall task 

performance of the crew (Category III). 

Crew performance of tasks on the ISS, such as EVAs, maintenance, and medical tasks, relies heavily on the 

provision of adequate procedures (figure 11-2) (Rando et al., 2005). Poor design of procedures for station tasks 

has impeded crew task performance by preventing the completion of scheduled activities within the allotted 

time. Well-designed procedures play a critical role in ensuring optimal, on-schedule crew task performance. 

Inadequately structured procedures will ultimately lead to a reduction in human task performance. 

Figure 11-1. Spektr module showing 

the damaged radiator and solar array on Mir

(NASA photograph).

Figure 11-2. ISS009-E-19837 —

Astronaut E. Michael Fincke, Expedition 9 NASA ISS science officer and 

flight engineer, looks over a procedures 

checklist while working with an extravehicular mobility unit (EMU) spacesuit in the Quest airlock of the ISS. 
Chapter 11 Human Health and Performance Risks of Space Exploration Missions 

286 Risk of Error Due to Poor Task Design 

ISS crew members have often reported that the procedures with which they deal are complex, lengthy, and 

contain too many C&Ws (Baggerman, 2004). In general, procedures are felt to be too detailed, especially for 

simple operations. Pictures and diagrams, which are considered helpful for many procedures, are not always 

integrated appropriately. In addition, some of the procedures reference multiple steps in other procedures. Locating the necessary steps costs the crew additional time and has resulted in missed or skipped steps (Category 

III). The overall usability of procedures has been an ongoing issue for ISS crew members and mission designers, 

which emphasizes the need for common standards and simplification where possible in procedure development. 

Performance degradation that is due to poor ISS task design was illustrated during a ground-based study to 

test the usability of a procedure (as written on a “cue card,” figure 11-3) for the respiratory support pack (RSP), 

which is a piece of ISS medical equipment, to support redesign of the cue card (Hudy et al., 2005). The RSP 

was designed for use during medical contingencies involving respiratory distress; therefore, the complicated 

RSP cue card procedure would be used in time-critical situations in which a crew member’s life could depend 

on the outcome. During the study, data were collected as subjects executed the procedure checklists, and results 

demonstrated that some procedures and training could be both a source of errors and, ultimately, a risk to crew 

health. The procedures and the sequence of using the equipment did not enable a crew member to establish a patient’s airway in the time necessary to prevent irreversible brain damage. The CMO typically receives very limited 

training in using the medical equipment, and the cue cards thus hold vital information on how to execute the procedures. This example illustrates the importance of appropriate procedures and training to ensure that tasks can 

be performed successfully, especially in case of an emergency. The cue card was subsequently redesigned to 

support a simpler task (figure 11-4) (Category III). 

Figure 11-3. Respiratory support pack information card before evaluation. 
Human Health and Performance Risks of Space Exploration Missions Chapter 11 

Risk of Error Due to Poor Task Design 287

Human-computer interaction brings together humans and technology to accomplish a certain task. Future 

human exploration vehicles, including lunar and Mars habitats, will be highly dependent on computerized, 

automated systems, necessitating the development of accurate methods for crew members to use to interact with 

computers. Human-computer interaction involves the processes, dialogs, and actions that a user employs to 

interact with a computer in any given environment. 

Human-computer interfaces allow the user to input an instruction to the computer. In turn, the computer should 

provide a response or feedback to the user’s input. Through input devices and output devices such as displays, 

the user is able to see, hear, touch, and recognize the interaction. Many different kinds of input devices can facilitate human-computer interaction. These include keyboards, mice, joysticks, and other devices. Historically, 

output devices have consisted of various types of displays, ranging from computer monitors to the headmounted displays that are worn by users to interact with virtual environments, for example. 

Figure 11-4. Respiratory support pack information card after evaluation. 

Human-computer interfaces should match the physiological characteristics and expertise of the user, be 

appropriate for the task that is to be performed, and be suitable for the intended work environment. It is thus 

critical to determine the characteristics of the user, what tasks are to be performed, and the characteristics of the 

work environment. Designers can then determine which human-computer interfaces are suitable and appropriate 

to the task at hand. 

If the performance of controls that operate optimally in a 1g setting become degraded in a microgravity or 

partial-gravity environment, task performance can be affected. Interfaces need to be designed that will operate 

and respond in all gravity environments in which they might be used. The selection of appropriate interfaces that 
Chapter 11 Human Health and Performance Risks of Space Exploration Missions 

288 Risk of Error Due to Poor Task Design 

allow direct manipulation by the user provides the best solution to operating computer systems in a microgravity 

environment. Designers must still consider and accommodate the specific tasks that are to be performed. 

Different control devices are suited for different tasks. 

The design of a cursor control device illustrates some of the issues that are associated with human-computer 

interface task design. Designers of cursor control devices have to consider a number of environmental factors, 

including g-forces, vibration, and gloved operations, as well as task specificity. The participants in eight flight 

studies (both parabolic and space flight) performed structured cursor control tests that involved pointing, clicking, 

and dragging of on-screen objects of various sizes (Holden et al., 1992). The cursor control devices that were 

used in these flight studies included mouse devices and trackballs. The general findings from these studies were 

that the mouse did not function in microgravity, and the trackballs (both attached and unattached) had too much 

or little to no “play.” A follow-up study was conducted, in which data that involved performance timing and error 

were collected on several commercial and proprietary cursor control devices, in both gloved and ungloved conditions (Sandor and Holden, 2007). The selected devices included a roll bar device, four different trackball devices, a 

track pad mouse, two optical air mouse devices, and a joystick. For both the gloved and the ungloved conditions, 

the results indicated that, overall, the trackball devices performed better (with regard to accuracy and timing) 

than the other devices, and that different devices were preferred for different tasks. This example illustrates how 

important the design of the human-computer interface is in dictating which support items will be needed to 

achieve optimal operational efficiency (Category II). 

Maintenance of equipment and vehicles is often a difficult and labor-intensive task (Baggerman, 2004). The 

difficulty is compounded when maintenance is performed on orbit (figure 11-5). A typical maintenance task 

will require that the maintainer use various tools and hardware. Many tools and hardware items are required to 

successfully complete the maintenance tasks on complex systems. This situation can be problematic in the 

reduced-gravity environment of current and future space vehicles and habitats. Unstowed tools can easily 

become misplaced or damaged or interfere with the task, unnecessarily increasing the time that is needed 

in which to repair the system and ultimately degrading the performance of the task. 

Figure 11-5. (top) ISS019-E-009823 — Japan Aerospace 

Exploration Agency astronaut Koichi Wakata, Expedition 

19/20 flight engineer, performs in-flight maintenance on 

the Treadmill Vibration Isolation System in the Zvezda 

service module of the ISS;(right) ISS018-E-019725 —

Astronaut E. Michael Fincke, Expedition 18 commander, 

works on hardware in the Destiny laboratory of the ISS.
Human Health and Performance Risks of Space Exploration Missions Chapter 11 

Risk of Error Due to Poor Task Design 289

Human-centered design of whole systems for maintainability can also improve the performance of individual 

tasks, as well as system reliability, and can prevent system failures. Maintainability of systems on a long-duration 

orbiting vehicle such as the ISS is critical (Baggerman, 2004). Many hardware items require frequent maintenance and multiple tools with which to effect maintenance. The ISS toolkit has improved greatly since the early 

ISS Expeditions, but the quantity of tools that are required for a designated task is excessive for a microgravity 

environment. This situation significantly impacts crew time, particularly when the need for frequent maintenance 

is coupled with the problems that are encountered when accessing hardware for repair. Poor maintainability has 

also resulted from the initial perspective of system designers that the systems would not need to be maintained 

because they were reliable. In reality, however, system failures and reliability issues have been experienced, 

ultimately requiring additional maintenance time and unanticipated task redesign (Category III). 

 Automation task design and performance 

The core human factors issues for task design are determining the necessary tasks and how these tasks are 

expected to be performed. Task analysis and human factors guidelines should ensure that tasks do not exceed 

human capabilities. As increasing numbers of automated systems are designed to assist the human, a synergistic 

relationship must be developed between the human and the automation to allow them to work together to accomplish tasks. 

Machines and automation are often used to monitor systems, collect information, and repeat actions (Sanders 

and McCormick, 1993). Machines, however, are not always reliable. When designers are allocating increasing 

numbers of tasks to automation, they must maintain awareness that the machines are not always reliable. When 

an automation failure occurs, it is imperative for the humans who rely on that automated system to be prepared 

to take over its functions and tasks. This contingency must be reflected in task design requirements for both the 

human and the automated systems. In addition, when automation fails, especially in the early stages of use, operator trust can decrease and the humans who were meant to rely on the automated system may prefer to perform 

the automated tasks themselves. Conversely, an operator may come to rely too heavily on the automation and, 

thus, fail to monitor the performance of the system. When assigning roles to humans and automation within 

systems, it is important to allocate appropriately and facilitate human situational awareness when tasks are 

automated. This is especially true when those responsibilities were once performed by humans. 

As documented in the ISS Life Sciences Crew Comments Database, which is not publicly available, ISS crews 

currently rely on ground support teams for most of the planning and scheduling of daily tasks. Software tools 

such as the Onboard Short Term Plan Viewer provide crew members with detailed schedules for daily activities. 

Although the crew can provide input into these schedules, ground support is often relied on to adapt and change 

the schedules as needed (Category III). The higher level of autonomy that is required for lunar and Mars missions 

will increase the need for automated planning capabilities and tools. These tools would provide the requisite 

automated support to determine alternative plans and solutions for managing daily tasks. Although crew input 

and ground support, as available, would still be helpful, automated support for these planning tasks will allow 

crew members to manage daily tasks on their own, thus ensuring that these tasks are performed appropriately 

when ground support is unavailable. 

One example of a current, poorly designed ISS task is the management of stowage. The ISS Inventory 

Management System (IMS) was designed to act as a crew-driven series of tasks using a barcode reader and a 

database. As noted in the ISS Life Sciences Crew Comments Database, the tracking methodology for items that 

are stowed on ISS has historically been unique for each Expedition. As it is not well designed, the IMS has not 

been used consistently to track items that are to be stowed, and not all items have been scanned or tracked. When 

items were moved, they were subsequently not replaced in their designated area, and the IMS is not always 
Chapter 11 Human Health and Performance Risks of Space Exploration Missions 

290 Risk of Error Due to Poor Task Design 

updated to reflect the new location. Stowage locations of items have not always been based on their functional 

use, causing crew members to search at opposite ends of the ISS for equipment that is needed to perform a single 

task. This has resulted in the crew spending time searching for items that they needed for daily tasks, and has 

contributed to a poor task structure in terms of how things are stowed and collected. 

In summary, issues with the ISS IMS have stemmed from both problems with the use of the IMS and the design 

of the system and its related tasks. ISS IMS-related stowage management tasks have been rife with errors, and 

this has decreased crew efficiency. Stowage management could benefit from increased automation (Category 

III). 

Additional examples of ISS tasks that are deemed poorly designed and that are cited in the ISS Life Sciences 

Crew Comments Database are the daily tasks of sampling microbial growth and water, as well as providing medical, exercise, and acoustics measurement or photographic data to the ground. These can be time-consuming tasks 

for crew members. Collecting samples and providing data to the ground are often perceived by the crew as occurring too frequently. Sampling and measurements could be automated to require minimal crew effort or input; 

this would allow crew members to conduct more critical tasks while still avoiding performance errors and 

ensuring efficient communication of data for ground support (Category III). 

 Computer-based Simulation Information 

Understanding human integration with systems and the identifying risks that may be inherent in a concept or 

a design is often achieved via computer-based simulation. During the evaluation of possible locations for the 

second treadmill to be placed on board the ISS to support a crew of six, the Boeing Human Modeling System 

(BHMS) software identified risks to the ability to install a treadmill in each of the possible locations chosen 

(figure 11-6) (Rice, 2007). One location would have the treadmill co-located with the crew quarters in the ISS 

Node 2 module; accessibility was identified as a problem there, however, because of the configuration of the 

crew quarters bump-outs, which extended into the translation paths for astronauts and the access area for the 

planned second treadmill. The BHMS modeling software was thus successfully used to identify accessibility 

Figure 11-6. BHMS sample photo. (Photograph from 

http://www.boeing.com/assocproducts/hms/case4.htm.) 
Human Health and Performance Risks of Space Exploration Missions Chapter 11 

Risk of Error Due to Poor Task Design 291

issues and a noncompliance with ISS requirements for accessibility. After the evaluation was complete, it was 

established that the location would not allow the crew to conduct the installation task successfully, and new tool 

options would need to be pursued to reduce the risk that was associated with the poor task design (Category III).

 Risk in Context of Exploration Mission Operational Scenarios 

Current space flight crews rely on on-board automated systems to perform tasks, and future crews, who will 

be facing increased flight duration and increased autonomy, will rely even more on these systems to provide 

information that is appropriate, accurate, and recent. This increased reliance on automation will result in the 

need for additional training to ensure that the crew members can perform the automated tasks in the event of 

automation failure. Automated tasks must be carefully designed to prevent the crew from becoming unaware of, 

or complacent about, potential hazards. This situation could ultimately result in system errors, degraded crew 

performance, and compromised crew and vehicle safety. 

A specific requirement for increased autonomy for lunar and Mars missions is automated planning capabilities 

and tools. These tools would provide the necessary automated support to determine alternative plans and solutions for managing daily tasks. For further information, see Chapter 9 of this document. 

 Conclusion 

The risk of error due to poor task design stems from a broader cause of human error; namely, the lack of 

human-centered design. This type of design requires a focus on the user throughout the design process. Good 

human-centered design practices will result in improved efficiency of operation and safety of all system components, including the human element, and should reduce the lifecycle cost of the project. The evidence that is 

discussed in this chapter demonstrates why this risk is a concern. 

Knowledge gaps that are related to this risk have, and will continue to be, defined, and future research directions should lead to filling these gaps and, eventually, to alleviating the concerns that have been identified. 

Some of these knowledge gaps are related to a lack of task analysis and understanding of operations, which is 

necessary to ensure awareness of crew and ground personnel functions, and how autonomy and automation will 

be integrated and applied. Knowledge gaps that are associated with a lack of user evaluations and iterative knowledge capture have also been identified. These gaps emphasize the need for the development of methods to evaluate human and system performance, especially with the expected increased requirement for automation and 

autonomy in future long-duration space flights. 

The human-centered design process emphasizes the importance of the human as the central focus of the 

human-machine system. This focus includes consideration of human capabilities, limitations, and interaction 

with automation and hardware. Knowledge gaps, or holes, that are related to the lack of an integrated system 

design approach for human and automated task design must be addressed to ensure that quality standards, 

requirements, tools, and techniques are developed that will allow positive crew-system integration and 

interaction, and, ultimately, mission success. 
Chapter 11 Human Health and Performance Risks of Space Exploration Missions 

292 Risk of Error Due to Poor Task Design 

 References 

Baggerman SD, Rando C, Duvall LE. (2004) Habitability and human factors: Lessons learned in long duration 

spaceflight. In: Proceedings of the American Institute of Aeronautics and Astronautics Space 2004 Conference 

Exhibit. San Diego, Calif., Sep 2004. 

Ellis S. (2000) Collision in space. Ergon. Des., 8(1):4–9. 

Holden KL, Wilmington RP, Whitmore M. (1992) Cursor control device evaluations for Space Station 

Freedom: A summary. CR-185690. NASA Johnson Space Center, Houston. Internal document. 

Hudy C, Byrne V, Smith D, Whitmore M (Eds.). (2005) Human factors assessment of respiratory support 

pack (RSP) cue card. In: Proceedings of the Annual Scientific Meeting of the Aerospace Medical Association. 

Kansas City, Mo., May 9–12, 2005. 

Rando C, Baggerman SD, Duvall LE. (2005) Habitability in space. In: Proceedings of the Human Factors 

and Ergonomics Society 49th Annual Meeting, Aerospace Systems. Human Factors and Ergonomics Society. 

Orlando, Fla., Sep 26–30, 2005, pp. 5–9. 

Rice SM. (2007) Case study 1 – pilot reach accommodation. Boeing [document on the Internet]. [updated Jun 

18, 2007; Jan 28, 2008]. Available on line at: http://www.boeing.com/assocproducts/hms/index.html. 

Sanders MS, McCormick EJ. (1993) Human factors in engineering and design. 7th Ed. McGraw-Hill, 

Maidenhead, U.K., pp. 730–732. 

Sandor A, Holden K. (2007) Determining desirable cursor control device characteristics for NASA exploration 

missions. NASA-JSC SF/UTAF report. NASA Johnson Space Center, Houston. Internal document. 

 Acknowledgments 

Immanuel Barshi, Ph.D., Linguistics and Cognitive Psychology; Senior Principle Investigator, Human System 

Integration Division, NASA Ames Research Center, Moffett Field, Calif. 

Michael Feary, Ph.D., Human Factors Engineering, Automation Design and Analysis; Research Psychologist, 

NASA Ames Research Center, Mountain View, Calif. 

Alicia Foerster, B.S.; Project Manager, SHFH Element, HRP, NASA Johnson Space Center, Houston. 

Keith V. Holubec, B.S.; Project Manager, SHFH Element, HRP, NASA Johnson Space Center, Houston. 

Victor Ingurgio, Ph.D., Experimental Psychology; Senior Human Factors Design Engineer for the 

Anthropometry and Biomechanics Facility, NASA Johnson Space Center, Houston. 

Robert S. McCann, Ph.D., Cognitive Psychology, Human-System Interface Design and Evaluation; Group 

Lead, Intelligent Spacecraft Interface Systems Lab, NASA Ames Research Center, Moffett Field, Calif. 

Cindy Rando, M.S., Human Factors; ISS Flight Crew Integration Human Factors Engineer, Habitability and 

Environmental Factors Division, NASA Johnson Space Center, Houston. 

Dane Russo, Ph.D., Experimental Psychology, Space Systems Development and Project Management; SHFH 

Element Manager, HRP, NASA Johnson Space Center, Houston. 
Human Health and Performance Risks of Space Exploration Missions Chapter 11 

Risk of Error Due to Poor Task Design 293

Barry Tillman, M.S., Systems and Industrial Engineering, B.A., Psychology; Senior Human Factors Engineer, 

Habitability and Human Factors Branch, NASA Johnson Space Center, Houston. 

 
Chapter 11 Human Health and Performance Risks of Space Exploration Missions 

294 Risk of Error Due to Poor Task Design 
Risk Factor of Inadequate Food System 295

Chapter 12: 

Risk Factor of Inadequate Food System 

Michele Perchonok

NASA Johnson Space Center 

Grace Douglas 

North Carolina State University 

If the food system does not adequately provide for food safety, nutrition and taste, then crew health and 

performance and the overall mission may be adversely affected. Furthermore, if the food system uses more 

than its allocated mission resources, then total required mission resources may exceed capabilities, the mission deemed unfeasible, or allocation of resources to other systems may be unduly constrained. – Human 

Research Program Requirements Document, HRP-47052, Rev. C, dated Jan 2009. 

 

Ongoing advances in space food nutrition, palatability, and storage will continue to provide astronauts 

with meals that promote their health and safety, while 

minimizing the use of vehicle and crew resources.

Here, astronaut Leland Melvin displays several 

food items while orbiting the Earth on board 

the space shuttle.
296 Risk Factor of Inadequate Food System 
Human Health and Performance Risks of Space Exploration Missions Chapter 12 

Risk Factor of Inadequate Food System 297

 Executive Summary 

An adequate food system is required to enable safe, reliable, and productive human space exploration. This 

food system will be required to deliver safe, nutritious, and acceptable provisions to the crew while efficiently 

balancing appropriate vehicle resources such as mass, volume, waste, and food preparation time for Exploration 

missions. A dual system consisting of a packaged food system (with a shelf-life of 3 to 5 years) and a bioregenerative food system on the planetary surface is being considered for the Mars missions. Understanding the 

potential risks to the food system for long-duration missions is an important step on this path. 

The safety of food is of highest importance as the incidence of food-borne illness could compromise the success 

of a mission. While current pre-flight procedures have ensured food safety so far, the ongoing development of 

the mission architecture for lunar and Mars explorations necessitates a reexamination of these existing procedures as well as the development of new processes. 

Since the food system is the sole source of nutrition to the crew, a significant loss in nutrition, either through 

the loss of nutrients in the food or inadequate food intake, may also significantly compromise the performance 

of the crew. The nutritional content of food may be inadequate due to losses during processing or environmental 

factors (e.g., temperature and radiation) encountered over the shelf-life of the food. Providing adequate levels of 

acceptability, variety, and usability is important to prevent inadequate caloric intake. 

The ineffective use of vehicle resources such as mass, waste, and crew time can affect mission success. The 

mass of the packaged food system is based on the mass of the food and the packaging surrounding the food, 

which could produce a significant amount of waste. A bioregenerative food system that could provide the crew 

with fresh foods will use more crew time, so the benefit to the performance of the crew must be shown to offset 

this additional burden. 

The paramount importance of the food system in a long-duration human Exploration mission should not be 

underestimated. Vehicle resources must be balanced with safety, nutrition, and acceptability to provide an 

adequate food system. The food system will provide not only the nutrients that will be needed for the survival 

of the astronauts, but also will enhance the psychological well-being of the crew by serving as a familiar element in an unfamiliar and hostile environment. 

This document presents the evidence that supports the risk factor of an inadequate food system as well as the 

knowledge gaps that still remain and that need to be filled. 

 Introduction 

The primary goal of the Advanced Food Technology (AFT) Project is to develop the requirements and technologies that will enable NASA personnel to provide an adequate food system that is characterized by the provision 

of safe, nutritious, and acceptable food while also efficiently balancing appropriate vehicle resources such as mass, 

volume, waste, and crew time in the Exploration missions. AFT, which is a project within the SHFH Element, 

is expected to directly relate to the HRP objective of developing capabilities and technologies in support of 

human space exploration, focusing on mitigating the highest risks to crew health and performance. Further 

details on the HRP can be found at http://humanresearch.jsc.nasa.gov/about.asp. 
Chapter 12 Human Health and Performance Risks of Space Exploration Missions 

298 Risk Factor of Inadequate Food System 

The authors of space program food system literature have documented the evolution of the space food system. 

Several types of food and beverage packaging have been used in NASA space programs. With the exception of 

Skylab, there has not been a refrigerator or freezer on board a spaccraft that was dedicated to food storage. Therefore, the food must be shelf-stable. This requires inactivation of the microorganisms in the food during ground 

processing before flight. While processing the packaged foods to commercial sterility provides a safe food system, this level of processing can reduce the quality of the food, including nutritional content and acceptability. 

The different forms in which food has been provided include the following: 

1. Thermostabilized – This process, which is also known as the retort process, heats food to a temperature 

that renders it free of pathogens, spoilage microorganisms, and enzyme activity. Food items are placed in 

cans or pouches and are heat-processed with steam- or water-overpressure to remove excess air/oxygen 

for specified times and temperatures to render the food commercially sterile. 

2. Irradiated – Although irradiation is not typically used to process foods to commercial sterility, NASA has 

special dispensation from the FDA to prepare nine irradiated meat items to commercial sterility (21CFR179, 

2008). Irradiation involves the use of gamma rays, x rays, or electrons, and uses energy levels that assure 

the negative induction of radioactivity in the irradiated product. It controls naturally occurring processes 

such as ripening or senescence of raw fruits and vegetables, and is effective for inactivation of spoilage 

and pathogenic microorganisms. 

3. Rehydratable – A number of technologies are available that allow for the drying of foods. Examples of 

these technologies are drying with heat, osmotic drying, and freeze drying. These processes reduce the 

water activity of foods, which results in the inability of microorganisms to thrive. 

4. Natural form – Natural-form foods are commercially available and shelf-stable. The moisture of the 

foods may range from low moisture (e.g., almonds and peanuts) to intermediate moisture (e.g., brownies 

and dried fruit). These foods rely on reduced water activity to prevent microbial activity. 

5. Extended shelf-life bread products – Items such as scones, waffles, and dinner rolls can be formulated 

and packaged to give them a shelf-life of up to 18 months. 

6. Fresh food – Fresh fruit, vegetables, tortillas, and other foods that have a short shelf-life are provided on 

a limited basis, more for psychological support than as part of meeting dietary requirements. 

7. Beverages – The beverages that are currently being used on the ISS and shuttle are either freeze-dried 

beverage mixes (e.g., coffee or tea) or flavored drinks (e.g., lemonade or orange drink). The drink mixes 

are prepared and vacuum-sealed inside a beverage pouch. In the case of coffee or tea, sugar or powdered 

cream can be added. Empty beverage pouches are also provided for drinking water. 

One of the goals of the Constellation Program (CxP) lunar long missions is to use the lunar surface as a test 

bed for future Mars missions. Although it is possible for CxP mission planners to continue using current food 

technologies, a change in missions will necessitate a change in the food system. The CxP missions will require 

longer shelf-life packaged foods with improved nutrition and acceptability. These missions will also require more 

attention to resource utilization such as mass, volume, power, crew time, and water use. The Mars missions, in particular, will require that technologies be developed so that the crew is more self-sufficient and less dependent on 

resupply missions. In addition, once the crew is out of LEO, space radiation is higher, and space-irradiated food 

may lose nutritional content and acceptability. The research that AFT conducts will allow for the food system to 

change when necessary. 
Human Health and Performance Risks of Space Exploration Missions Chapter 12 

Risk Factor of Inadequate Food System 299

To further address the limitations in vehicle resources to accommodate prepackaged foods, mission designers 

also envision that once the crew is on the lunar or Mars surface, crops will be grown. Fresh fruits and vegetables, 

such as spinach, lettuce, tomatoes, carrots, bell peppers, onions, potatoes, and strawberries, could be grown hydroponically in environmentally controlled chambers. In addition, baseline crops, such as soybeans, wheat, rice, 

peanuts, and dried beans, could be grown on the surface or launched in bulk from Earth. These crops would 

be processed into edible ingredients. These edible ingredients, the freshly grown fruits and vegetables, and 

packaged food items would be used to prepare meals in the galley. Dependence on the processing and 

preparation of bioregenerative and bulk commodity foods presents unique risks for these missions. 

A mission to Mars will use prepackaged foods, which are similar to those that are used on ISS, for transit and 

may include positioning food on Mars prior to crew arrival. Prepositioned food may be 3 to 5 years old at the 

time of consumption. Currently, prepackaged foods have a stated shelf-life of 18 months but will need a 5-year 

shelf-life for the Mars missions. Shelf-life criteria are safety, nutrition, and acceptability. Any of these criteria 

can be the limiting factor in determining the shelf-life of food. 

 Safety 

Food safety is the protection of food from physical, chemical, and microbiological contamination. The food 

system must be designed to ensure that the initial provisions are safe from contamination and are packaged to 

remain safe from contamination for up to 5 years of storage in multi-environments. Good manufacturing practices, which include employee qualifications and training, sanitation, recordkeeping, process validation, and 

facilities and equipment maintenance and verification, are followed to prevent food contamination during 

processing and packaging (21CFR110, 2008). 

Microbiological contamination of food can negatively affect crew health and possibly compromise crew 

survival. Most food items are monitored by the NASA JSC Microbiology Laboratory (as specified in JSC 

16888 (publicly unavailable)) to ensure that preparation and packaging procedures result in products that 

conform to established microbial standards for flight foods. Table 12-1 lists the items that are tested and the 

associated limits. 

NASA adheres to the hazard analysis and critical control point (HACCP) system, which is a systematic 

and preventive approach to food safety that was developed by NASA, the United States Army Laboratory, and 

the Pillsbury Company in the 1960s. Both the Centers for Disease Control (CDC) and the United States Department of Agriculture (USDA) cite the implementation of the HACCP system of inspection as a principal reason 

why the incidence of food-borne illness appears to be declining (PBS Frontline, 2002). The use of HACCP, including the strict use of good manufacturing practices, standard operating procedures, and testing of processed 

foods, is associated with the prevention of food-borne illness events during space missions. 

 Nutrition 

Adequate nutrition has two components: necessary nutrients and energy in the form of calories. Without 

adequate nutrition, there is a risk of not being able to live a healthy, productive life. It is possible to consume 

enough calories without a well-balanced selection of individual nutrients. This can result in diseases that are 

noticeably different from those resulting from an overall insufficiency of nutrients and energy. For example, a 

vitamin C deficiency may result in scurvy while a deficiency in niacin may result in pellagra. It is important that 

crew members who are on a long-duration mission are provided with the required level of nutrition throughout 

their mission. Table 12-2 summarizes the required nutritional requirements as stated in the CxP 70024, HumanSystems Integration Requirements document, section 3.5.1.3.1 (publicly unavailable). 
Chapter 12 Human Health and Performance Risks of Space Exploration Missions 

300 Risk Factor of Inadequate Food System 

Table 12-1. Microbiological Testing for Flight Food Production

Area/Item Microorganism Tolerances 

Food Production Area Samples Collected* Limits 

Surfaces Three surfaces sampled per day 

3 CFU/cm2

 

(Total aerobic count) Packaging Film Before use 

Food Processing Equipment Two pieces sampled per day 

Air One sample of 320 liters 113 CFU/320 liters 

(Total aerobic count) 

Food Product Factor Limits 

Non-thermostabilized** 

Total aerobic count 

20,000 CFU/g for any single 

sample (or if any two samples from 

a lot exceed 10,000 CFU/g) 

Coliform 100 CFU/g for any single sample 

(or if any two samples from a lot 

exceed 10 CFU/g) 

Coagulase positive staphylococci 100 CFU/g for any single sample 

(or if any two samples from a lot 

exceed 10 CFU/g) 

Salmonella 0 CFU/g for any single sample 

Yeasts and molds 

1,000 CFU/g for any single sample 

(or if any two samples from a lot 

exceed 100 CFU/g, or if any two 

samples from a lot exceed 10 

CFU/g Aspergillis flavus) 

Commercially Sterile Products 

(thermostabilized and irradiated) 

No sample submitted for 

microbiological analysis 

100% inspection for package 

integrity 

*Samples collected only on days that the food facility is in operation. 

**Food samples that are considered “finished” products that require no additional repackaging are only tested for total aerobic

counts. 

Table 12-2. Nutrition Composition Breakdown

Nutrients Daily Dietary Intake 

Protein 0.8 g/kg 

And ≤ 35% of the total daily energy intake 

And two-thirds of the amount in the form of animal protein, 

and one-third in the form of vegetable protein 

Carbohydrate 50%–55% of the total daily energy intake 

Fat 25%–35% of the total daily energy intake 

Ω-6 Fatty Acids 14 g 

Ω-3 Fatty Acids 1.1–1.6 g 

Saturated fat < 7% of total calories 

Trans fatty acids < 1% of total calories 

Cholesterol < 300 mg/day 

Fiber 10–14 grams/4187 kJ 

Fluid 1–1.5 mL/4187 kJ 

And ≥ 2000 mL 

Vitamin A 700–900 g 
Human Health and Performance Risks of Space Exploration Missions Chapter 12 

Risk Factor of Inadequate Food System 301

Table 12-2. Nutrition Composition Breakdown (Concluded) 

Nutrients Daily Dietary Intake 

Vitamin D 25 g 

Vitamin K Women: 90 μg 

Men: 120 μg 

Vitamin E 15 mg 

Vitamin C 90 mg 

Vitamin B12 2.4 g 

Vitamin B6 1.7 mg 

Thiamin Women: 1.1 mol 

Men: 1.2 mol 

Riboflavin 1.3 mg 

Folate 400 g 

Niacin 16 mg NE 

Biotin 30 g 

Pantothenic Acid 30 mg 

Calcium 1,200–2,000 mg 

Phosphorus 700 mg 

And ≤ 1.5  calcium intake 

Magnesium Women: 320 mg 

Men: 420 mg 

And ≤ 350 mg from supplements only 

Sodium 1,500–2,300 mg 

Potassium 4.7 g 

Iron 8–10 mg 

Copper 0.5–9 mg 

Manganese Women: 1.8 mg 

Men: 2.3 mg 

Fluoride Women: 3 mg 

Men: 4 mg 

Zinc 11 mg 

Selenium 55–400 g 

Iodine 150 g 

Chromium 35 g 

The ability of the food system to meet the nutritional requirements of a crew can only be determined when the 

nutritional profile of the entire space food system is known at the time at which the food is consumed. However, 

there has only been limited measurement of the nutritional content of the flight food items. Macronutrients and 

some minerals are determined chemically at the NASA JSC Water and Food Analytical Laboratory (WAFAL). 

Other nutrients, such as vitamins, are currently calculated with a computerized nutrient database that was developed by the USDA and the food industry. However, the level of processing that is done by NASA can reduce 

the quality of the food, including its nutritional content and acceptability. In addition, it is unknown whether 

processed foods will maintain nutritional adequacy for 3 to 5 years. 

Nutrient losses may also occur due to environmental conditions, such as the higher radiation levels that will be 

encountered during planetary missions. The addition of antioxidants to the food may help prevent the formation 
Chapter 12 Human Health and Performance Risks of Space Exploration Missions 

302 Risk Factor of Inadequate Food System 

of free radicals that contribute to food spoilage (Wilson et al., 2007; Gandolph et al., 2007). In the case of a bioregenerative food system, in the absence of sufficient protection, radiation may affect the ability of plants to 

germinate and grow, and it may also affect their resulting functionality (Wilson et al., 2007). 

During the short-duration lunar missions, it is assumed that EVAs will be scheduled to occur not less than 

every other day for 8-hour periods during surface missions (NASA, 2005). As stated in the CxP 70024, HumanSystems Integration Requirements document, these EVAs will require no less than an additional 200 kilocalories 

per EVA hour above the nominal metabolic intake, with a similar nutrient composition to the rest of the diet. 

Requirements for long-duration lunar or Mars missions have not been determined but would likely be similar to 

those for the short-duration lunar missions. 

 Acceptability 

Food acceptability can be defined and determined in several ways. The first way is in terms of appearance, 

flavor, texture, aroma, and serving temperature. Currently, flight foods are evaluated using sensory analysis, for 

acceptability on the ground, by a panel of 30 or more consumers. The products are rated based on appearance, 

flavor, texture, and aroma using a 9-point Hedonic Scale.19 Food products must receive an overall score of 6 or 

higher to be included in the space food system. Similarly, prior to flight, a crew member will evaluate the foods 

on the 9-point Hedonic Scale. If the score that is assigned to a food item is less than 6.0, that food item will not 

be on the crew member’s personal preference menu. 

Product acceptability can also be affected by factors such as product formulation, product age, how the product 

is stored, and where the product is consumed. Menu variety and usability of the food system also contributes to 

food acceptability. A large variety of food items is recommended to provide the crew choices and to avoid menu 

fatigue. If the food is difficult to prepare or eat, the overall acceptability of the food is reduced (Smith et al., 1975). 

Finally, food acceptability can also be affected by social context and the timing of meals. Food and mealtimes 

can play a primary role in psychological-social benefit, such as reducing the stress and boredom of prolonged 

space missions or promoting unity by dining together. 

 Resource utilization 

During the development of a space flight food system, several resources must be considered including: mass, 

volume, power, crew time, and waste disposal capacity. Misuse of these resources may affect mission success. 

The balancing of resources with food quality is dependent on the specific mission. For example, the 2-week 

initial missions to the moon will consider mission resource utilization more important due to the small usable 

volume in the vehicle. Since the missions will be shorter, nutrition and acceptability may not be as critical. 

Food packaging is a major contributor to mass, volume, and waste allocations for NASA missions. Packaging 

is integral to maintaining the safety, nutritional adequacy, and acceptability of food, as it protects the food from 

foreign material, microorganisms, oxygen, light, moisture, and other modes of degradation. The higher the barrier properties of the packaging, the more that packaging can protect the enclosed food from oxygen and water 

ingress from the outside environment. Oxygen ingress can result in oxidation of the food and loss of quality or 

nutrition. Water ingress can result in quality changes such as difficulty in rehydrating the freeze-dried foods. 

 

19The Hedonic Scale is used by tasting panels to indicate the extent of the like or dislike of panel members for a particular food item.
Human Health and Performance Risks of Space Exploration Missions Chapter 12 

Risk Factor of Inadequate Food System 303

The current packaging that is used for the freeze-dried foods and natural-form foods for the ISS does not have 

adequate oxygen and moisture barrier properties to allow for an 18-month shelf-life. Therefore, these foods are 

overwrapped with a second foil-containing package that has higher barrier properties. The packaging materials 

that are used for the thermostabilized, irradiated, and beverage items that are consumed on station contain a foil 

layer to maintain product quality beyond the required 18-month shelf-life. Although the foil layer provides excellent protection, it is not compatible with all of the technologies that produce commercially sterile foods. For 

example, two emerging technologies – high-pressure processing and microwave sterilization – cannot use the 

foil package. This will require NASA to continue using the foil packaging and forego those emerging technologies or to acquire packaging that is compatible with both of those technologies. 

Tables 12-3 and 12-4 list the oxygen and water vapor permeability of the current NASA food packaging 

materials. 

Table 12-3. Oxygen Permeability of Packaging Materials (CC/100IN2/DAY)

73.4oF@100% Relative 

Humidity 

Overwrap 0.0065 

Thermostabilized and Irradiated Pouch < 0.0003 

Rehydratable Lid and Natural Form 5.405 

Rehydratable Bottom (heat formed) 0.053 

Table 12-4. Water Vapor Permeability of Packaging Materials (G/100IN2/DAY)

100oF@100% Relative 

Humidity 

Overwrap < 0.0003 

Thermostabilized and Irradiated Pouch 0.0004 

Rehydratable Lid and Natural Form 0.352 

Rehydratable Bottom (heat formed) 0.1784 

The food system generates both wet and dry waste. Dry waste may include items such as dry food packaging. As it is cost prohibitive to plan on launching the trash from the lunar or Mars surface, another alternative is 

required for trash disposal. Although the foil layer that is within a food package protects that food from oxygen 

and water migration, it may provide complications if the decision is made to incinerate the trash on the lunar or 

martian surface. Wet waste may include cleaning materials and wet food packaging. Because of the spoilage 

of food substances that are left on cleaning materials and in packaging, food system wet waste materials must 

be properly disposed of to limit microbial contamination to the crew. 

If a bioregenerative food system is used during the lunar or Mars surface missions, some mass and volume 

savings will be seen from the use of less packaged foods. However, the processing and preparation equipment 

will contribute to the mass and volume of the habitat. In addition, the use of this equipment will require more 

water, power, and crew time than would be required by simply heating or hydrating packaged foods. The benefits of bioregenerative food systems will require a vigorous defense if the resources that they require are to be 

allocated on such resource-constrained missions. 
Chapter 12 Human Health and Performance Risks of Space Exploration Missions 

304 Risk Factor of Inadequate Food System 

 Evidence 

 Safety 

Good manufacturing practices, including microbiological testing of food products pre-flight, have likely prevented food-borne illness in the past. Freeze-drying prevents food-borne illness by eliminating the water that is 

necessary for microorganisms to grow. Safe freeze-dried foods depend, at the beginning of the process, on highquality ingredients and clean surfaces with minimal microorganism contamination. However, there still can be 

viable microorganisms in the food. These foods are therefore tested for viable microorganisms pre-flight. There 

have been instances in which freeze-dried foods did not pass microbiological testing due to contamination from 

mold, yeast, or bacterial pathogens. Mark Ott from the NASA JSC Microbiology Laboratory reported at the 2006 

Spring Meeting of the American Society for Microbiology, Texas Regional Branch, Wimberley, Texas, that 14 

items over several years – including chicken salad and shrimp – failed to meet the microbiological testing for flight 

food production specifications (see Table 12-1) and, hence, were not approved for shuttle and ISS flights. Although this is a small number based on the number of samples that were tested in the JSC Microbiology Laboratory, 

even one food lot can result in several crew members becoming sick during a mission (Category I)20. 

Thermally processed foods are processed to a high enough temperature for a long enough time to provide commercial sterilization. As with the freeze-dried foods, safe foods are still dependent on good HACCP practices. 

After processing, the thermostabilized pouches are tested for pouch integrity and swelling to determine whether 

adequate heat was applied to the food to produce commercial sterility (Category IV). 

 Nutrition 

Crew members during Apollo missions often experienced reduced appetite, possibly due to a combination 

of effects such as fluid shifts, pressure changes, nausea, and workload. Rambaut et al. (1975) state that the 

importance of nutrition in the adaptation of astronauts to weightlessness has been recognized since Project 

Gemini. Smith et al. (1975) note that throughout the Mercury, Gemini, and Apollo missions, weight losses among 

the flight crews were noticed with few exceptions, including two crew members on Apollo 14. Food intake during 

these missions was consistently below the quantities that were necessary to maintain body weight. Although the 

energy intake from the NAS, NRC Recommended Daily Dietary Allowance (RDA) is 2,870 kcal/day, the mean 

energy intake during these missions was only 1,880 ± 415 kcal/day. Rambaut et al. (1975) also state that Apollo 

nutrition guidelines provided only marginal amounts of nicotinate, pantothenate, thiamine, and folic acid. The occurrence of arrhythmias in Apollo 15 astronauts was attributed to a potassium deficiency due to inadequate nutrition in the space food system (Smith et al., 1975). The potassium deficiency in this short-term mission was 

mitigated in later missions through potassium supplementation. Instances of scurvy, rickets, and other nutritional deficiency conditions occurred in the earlier explorer expeditions due to poor nutrition. Therefore, an 

unexpected deficiency of one or more nutrients in a long-duration space mission may significantly affect 

mission success (Category III). 

 

20To help characterize the kind of evidence that is provided in each of the risk reports in this book, the authors were encouraged to 

label the evidence that they provided according to the “NASA Categories of Evidence.” 

 Category I data are based on at least one randomized controlled trial. 

 Category II data are based on at least one controlled study without randomization, including cohort, case-controlled or subject

operating as own control. 

 Category III data are non-experimental observations or comparative, correlation and case, or case-series studies. 

 Category IV data are expert committee reports or opinions of respected authorities that are based on clinical experiences, bench 

research, or “first principles.” 
Human Health and Performance Risks of Space Exploration Missions Chapter 12 

Risk Factor of Inadequate Food System 305

Longer-term effects of space travel on nutrition have been documented through physiological changes during 

the 6-month-long ISS Expeditions, in which urine, blood, plasma, and serum nutrient contents and body mass 

were measured post-flight and statistically compared to pre-flight baselines. Of particular concern were the decreased levels of several vitamins and minerals in the urine, blood, plasma, and serum. For example, vitamin D 

levels, antioxidant capacity, γ-tocopherol levels, and folate levels were all significantly lower after flight, creating 

concern for weight loss and associated malnutrition during ISS Expeditions 1 through 8 (Smith et al., 2005). The 

results detail a reduced caloric intake (around 80% of recommended intake during space flight) leading to an 

average of a 5% weight decrease and potentially explaining some, or all, of the measured nutrient decrease. It 

has also been suggested that dietary intake may have been low due to time constraints for meal preparation 

and consumption (Smith et al., 2005). The Skylab crews, who were required to eat enough to meet their 

caloric needs, preserved body mass (Thornton and Ord, 1975) (Category III). More information on inadequate nutrition through inadequate caloric intake can be found in Chapter 12 on the HRP Website at: 

http://humanresearch.jsc.nasa.gov/elements/smo/hrp_evidence_book.asp. 

Inadequate intake is not the only reason for inadequate nutrition. If the food loses nutrients through processing 

or storage, a crew member will not have adequate nutritional intake. Available data on the vitamin content of 

certain processed foods at various temperatures over 2 years of storage demonstrate the potential for significant 

vitamin loss (Kamman et al., 1981; Kim et al., 2000; Kramer, 1974; Lund, 1975; Pachapurkar and Bell, 2005). 

Cameron et al. (1955) compiled data on the loss of ascorbic acid, riboflavin, and thiamine over 2 years in several 

canned fruits and vegetables, showing vitamin losses as great as 58% in some canned products that were held at 

80°F, while the same products that were held at 50°F only showed maximum losses of 38% (Category I). Therefore, nutritional loss at 3 to 5 years, which has not been studied, could likely result in inadequate nutrition in the 

food system (Category I). 

Nutrient changes during processing and over the shelf-life of processed foods include isomerization of vitamins 

or vitamin precursors, changes in the bioavailability of amino acids and vitamins as the food structure is broken 

down, and nutrient degradation, including oxidation of several vitamins and amino acids (Gregory, 1996; Chen 

et al., 1995; Rock et al., 1998; Dewanto et al., 2002; Graziani et al., 2003; Seybold et al., 2004). The bioavailability of vitamins may be more important than overall quantity in a food, as other components in the diet and the 

form of the vitamin may influence absorption and function. Therefore, the bioavailability of vitamins in individual 

foods may vary, making it important to have an understanding of the available nutrients as well as the overall 

quantity (Gregory, 1996) (Category I). 

Some emerging technologies will be approved by the FDA for commercial sterility in the next few years. 

The two technologies with the most promise are high-pressure processing (HPP) and microwave sterilization. 

HPP is a method of food processing in which the food is subjected to elevated pressures (up to 87,000 psi or 

approximately 6,000 atmospheres), with or without the addition of heat, to achieve microbial inactivation or 

alter the food attributes to achieve consumer-desired qualities. Pressure inactivates most vegetative bacteria at 

pressures that are above 60,000 psi. HPP retains food quality, maintains natural freshness, and extends the microbiological shelf-life (Balasubramaniam, 2007). Microwave sterilization is a high-temperature, short-time process in which packaged food is cooked at 265°F for 10 minutes (U.S. Army Soldiers System Center (Natick), 

2004). Current thermostabilized NASA food products are cooked to about 250o

F, but for a much longer time. 

Preliminary studies suggest that the quality of the foods is much higher using these promising technologies. 

Lund (1988) determined that food quality (i.e., color, texture, etc.) may provide a general indication of the 

nutritional loss of the food. 
Chapter 12 Human Health and Performance Risks of Space Exploration Missions 

306 Risk Factor of Inadequate Food System 

While lower temperatures during storage could help alleviate the storage issues, ISS and space shuttle missions 

do not have the mass or power capabilities to provide cold storage (Perchonok and Bourland, 2002) (Category I). 

Currently, the commercial food industry does not require foods to have shelf-lives longer than 2 years (Category 

III). 

 Acceptability 

The acceptability of the food system has been linked to caloric intake and associated nutritional benefits. 

If food is not acceptable to a crew, the crew will not eat an adequate amount of it and will be compromised 

nutritionally. Large improvements and advances in space food systems were achieved during the Apollo food 

program. Nevertheless, the majority of the Apollo astronauts did not consume sufficient nutrients. Loss of body 

weight, fluids, and electrolytes were the rule, with few exceptions (Smith et al., 1975). 

A thorough review of the Apollo experience was provided by Scheuring et al. in the NASA document 

TM-2007-214755, The Apollo Medical Operations Project: recommendations to improve crew health and 

performance for future Exploration missions and lunar surface operations (not publicly available). The objective of the study was to provide evidence to modify medical requirements for future Exploration missions by 

identifying Apollo 7 through 17 mission medical issues. This historical database was generated based on the 

responses of 14 of 22 surviving Apollo astronauts to 285 questions. Among the 11 categories that were addressed, 

Food/Nutrition had 76 responses and eight recommendations. Scheuring et al., in addition to Rambaut et al. (1975), 

report that reduced food consumption may be partially attributed to a combination of physiological effects such 

as fluid shifts, pressure changes, nausea, issues with preparing food and with the water system, and workload, but 

acceptability of and familiarity with the food are also critical to consumption. Scheuring et al. also report that 

changes in the sensory perception of the food have been noted between ground-based taste test participants and 

Apollo and shuttle mission crew members, making it important to understand the effect of pressure and fluid 

shifts on sensory perception. Apollo crew members have also stated that having hot water with which to prepare hot drinks (e.g., having coffee in the morning) was important, providing them with a psychological boost 

(Category III). 

Consistently during ISS crew debriefings (the documents are not available externally due to confidentiality 

issues), the crews have stated that their food preferences change from pre-flight to flight. Similar to the Apollo 

and space shuttle experiences, the ISS crews have also noted that their tastes for certain foods changed in microgravity, and that they may crave different foods on orbit as compared to on Earth (Category III). 

ISS crews have also noted in crew debriefings that they would prefer more food variety for the length of the 

missions, and that they tire of certain foods over 6 months. When the menu cycle repeated after only 8 days (as 

opposed to the current 16-day menu cycle for ISS missions), the crews noted that there was not enough variety 

in the menu (document not available externally due to confidentiality). As the diets of the crew members during 

a mission are limited to just the available items, the long-term acceptability may decrease for some of the menu 

items. Vickers (1999) reports that studies that were conducted by the U.S. armed forces in the 1950s showed 

that most foods decreased in acceptability when they were repeatedly consumed. The degree of loss of 

acceptability depended on the specific food (Category III). 

The next-generation NASA space vehicle, Orion, is considerably smaller than the shuttle and the ISS. For this 

reason, the food system for the Orion vehicle is being challenged with the possibility of no food warmer or hot 

water. A study that was conducted in 2006 at the NASA JSC Space Food Systems Laboratory measured the acceptability of food, which is normally consumed hot, when it is hydrated with ambient water or not heated. Using 

a 9-point Hedonic Scale (in which food scores of 6.0 or better suggest acceptability), the study showed that the 
Human Health and Performance Risks of Space Exploration Missions Chapter 12 

Risk Factor of Inadequate Food System 307

food lost about 20% of its acceptability when it was consumed at room temperature and about 17% of the food 

items were determined to be unacceptable. Hence, there is a risk of decreased in-flight nutrition for astronauts 

on an Orion vehicle due to lower acceptability and fewer foods available for the mission. 

Perchonok and Antonini (not publicly available) reported at the 2008 Human Research Program Investigators Workshop on the results of an accelerated shelf-life study of seven thermostabilized items and three bulk 

ingredients. These items were stored at 40°F (control), 72°F (storage temperature of actual flight food), and 

95°F (accelerated temperature). Sensory evaluations were conducted every 4 months for the first 2 years and 

every 6 months for the third year. The conclusions of the study were that the shelf-lives of the thermostabilized 

items range from 0 months for egg products to 87 months for a representative meat product. The thermostabilization process does not result in acceptable products for all formulations. For example, thermostabilized egg products 

tend to be rubbery and darken in color (Juliano et al., 2007). Meat products have been thermostabilized (canned) 

for many years and tend to maintain their quality even after processing (Category II). 

Furthermore, if food preparation takes too much crew time, the consumption of that food may also decrease 

(Smith et al., 1975). Providing adequate sensory attributes and ease of use (preparation difficulty and time) with 

respect to crew scheduling will be necessary to prevent inadequate caloric intake and associated nutritional and 

psychological issues (Category III). 

It can be concluded that if a food system has adequate levels of acceptability, variety, and usability, crew 

members will consume more food during their mission. 

 Resource utilization 

The ineffective use of vehicle resources such as mass, waste, and crew time can affect mission success. Mass 

of the packaged food system is based on the mass of the food and the packaging that is surrounding the food. 

The mass of the food is dependent on the type of food and the quantity that is required to meet the caloric requirements of a crew. Smith et al. (1975) noted that the mass of the Apollo 7 food system for the crew was 

1.8 lbs. of food per person per day. By the time of the Apollo 14 mission, the mass of the food for the crew 

averaged 2.48 lbs. per person per day. The Apollo 8 crew, in 1968, preferred the newly added thermostabilized 

foods, which were referred to as “wetpack foods.” According to Smith et al. (1975), the improved crew acceptance of the thermostabilized product justified the weight increase. Even with the added “wetpack foods,” the 

Apollo food system still contained a significant number of freeze-dried foods since water from the fuel cells 

was available for food rehydration (Category III). 

Perchonok, at the 2002 annual meeting of the International Conference of Environmental Systems (not 

publicly available), reported that the ISS and shuttle crew members receive about 4 lbs. of food plus packaging 

per person per day. A higher percentage of the food on the shuttle and the ISS is thermostabilized compared 

to the Apollo flights due to the higher acceptability of thermostabilized food. Since ISS uses solar panels for a 

power source and not fuel cells that produce water as a by-product, there is no mass advantage to using freezedried foods. Furthermore, the average number of calories for ISS crew members is based on the actual caloric 

needs of a crew member based on that crew member’s body weight and height, which results in an average 

caloric requirement of 3,000 kcal as opposed to the 2,500 kcal that were provided to Apollo crew members. 

Based on mass challenges, CxP designers are considering the possibility of reducing the food system mass 

while still providing the crew with adequate calories (Category III). 
Chapter 12 Human Health and Performance Risks of Space Exploration Missions 

308 Risk Factor of Inadequate Food System 

The results of a preliminary study that was conducted at NASA JSC by French and Perchonok suggest that the 

total mass of a food system may be reduced in a long-duration surface mission if that food system moves more 

towards a bioregenerative and bulk commodity food system. (The food system that would be used in transit between Earth and Mars would remain a packaged food system to be compatible with the microgravity environment.) 

French and Perchonok, at the 2006 Habitation Conference, reported on a preliminary study – the Bulk Ingredient 

Menu project. The designers of this project assumed that fresh fruit and vegetables would be grown in the crew 

habitat on a planetary surface; however, the mass of the environmental growth chambers was not included in the 

project mass calculations. It was projected that some food processing would be conducted using bulk ingredients 

(e.g., turning soybeans into tofu and milling wheat into wheat flour for bread production). The study assumed a 

600-day stay on a planetary surface with six crew members. French and Perchonok report that the mass of a food 

system using food preparation would be about 4,200 kg. For the same length of a surface stay mission (600 days) 

with a crew of six, the mass of an ISS-style food system would be about 6,600 kg (Category I). 

Food packaging produces a significant amount of waste. In the course of confidential crew debriefings, the 

NASA Mir crew members stated that the overwrapped foods created a trash management problem as there were 

two food packages per food item for the rehydratable and natural-form foods. Although the foods are not overwrapped on shuttle missions, the trash that is produced by the food system can still be significant. Lee (2000) 

reports that 60% of the mass that was measured from waste on STS-99 was generated from the food system (including food, drinks, and packaging) while STS-101 demonstrated an even greater percentage (i.e., 86% of the 

mass). An analysis of the food waste on STS-51D showed a total trash mass of 50.7 lbs. that included 26.9 lbs. 

of uneaten food and 23.8 lbs. of food packaging. Eighty-five percent of the trash by volume on STS-29 and 

STS-30 was food packaging, and 7% of the trash volume was food (Wydeven and Golub, 1991) (Category II). 

In a 2001 trade study (not publicly available), Levri et al. evaluate five potential menus for use during a Mars 

mission. From the study it was determined that for prepackaged foods, generally 3% of the food would be left in 

the package if an attempt were made to eat everything. As packaging is about 9.5% of the mass of the total food 

system, it would therefore be expected that, at a minimum, 12.5% of the rehydrated food system on a Mars 

mission would become waste (Category I). 

To avoid the issues that are associated with trash accumulation on a lunar or Mars surface mission, the trash 

will need to be disposed of. One option is to incinerate it; however, the foil layer within the food package will 

not incinerate completely and will leave some ash from the foil (Perchonok, 2007) (Category IV). 

Several studies, which attempt to balance mass, volume, crew time, and power requirements with nutrition 

and acceptability, have been conducted to determine the effect of a bioregenerative food system on a lunar or 

Mars mission. In the Levri et al. (2001) trade study, five menus were evaluated (Table 12-5) that use equivalent 

system mass (ESM). ESM converts mass, volume, power, cooling, and sometimes crew time requirements into 

one mass value. The volume, power, cooling, and crew time requirements are converted to mass using equivalency factors. These equivalency factors are based on mission length and location. 

The Shuttle Training Menu was similar to the menu for the shuttle and ISS food system. The various menus 

supplemented the Shuttle Training Menu with frozen foods, bulk-packaged snack foods, and/or salad and/or 

potatoes. The salad and potatoes would be grown on the Mars surface. Levri et al. (2001) determined that if only 

ESM was considered in choosing a menu, either case 2, case 4, or case 5 would be chosen (Table 12-6). However, 

the authors also concluded that non-quantifiable issues (with respect to ESM), such as food palatability and the 

psychological benefits of plant-crew interaction, must come into play in making a decision (Category I). 
Human Health and Performance Risks of Space Exploration Missions Chapter 12 

Risk Factor of Inadequate Food System 309

Table 12-5. Food System Options (Levri et al., 2001) 

Case Food System Packaging 

Approach 

Crop 

Growth 

1 ISS Assembly Complete (some 

frozen food) 

Individual 

Servings 

Salad 

2 Shuttle Training Menu Individual and 

Multiple 

Servings 

Salad 

3 Shuttle Training Menu Individual 

Servings 

Salad and 

White 

Potato 

4 Shuttle Training Menu Individual 

Servings 

Salad 

5 Shuttle Training Menu 

w/reduced water content 

Individual 

Servings 

Salad 

Table 12-6. Non-crew -time ESM, Crew-time ESM, and Total ESM (Levri et al., 2001) 

ESM 1 

(frozen) 

2 

(multiple serving) 

3 

(potato) 

4 

(indiv) 

5 

(reduced 

water content) 

ESMNCT* 27,587 23,246 27,198 23,324 23,351 

ESMCT** 4,398 3,635 4,848 3,650 3,654 

ESMTOTAL 31,984 26,881 32,047 26,974 27,005 

*Non-crew time 

**Crew time 

During a Lunar Mars Life Support Test Project simulation in a closed chamber, a four-person crew tested a 

10-day vegetarian diet that was based on crops that were expected to be grown during long-duration missions. 

These crops were processed into ready-to-use ingredients outside of the chamber, leaving general cooking activities and cleanup to the crew. The general preparation and cleaning activities required 4.6 crew hours total per 

day. The amount of waste, which was accrued mostly from leftovers, ranged between 20% and 80%. This experience demonstrated a need for automated processes, a diverse menu, and improvements in recipe scaling 

based on crew size (Kloeris, 1998) (Category I). 

French and Perchonok, at the 2006 Habitation Conference (not publicly available), reported that the preliminary 

Bulk Ingredient Menu project determined that food preparation would require, for a crew of six, about 3 hours 

per day. However, in addition to the 3 hours actively spent preparing food, about 6 hours per day of passive time 

was required for food preparation. Passive time was defined as the preparation time that did not require a crew 

member to constantly watch over the process, such as the time that is involved in baking. Note that only 30 

minutes are set aside for crew preparation on ISS missions (Category I). 

 Computer-based Simulation Information 

Shelf-life can be defined as the time at which a product no longer maintains its specified quality. Changes in 

food, whether nutritionally or in quality, occur through chemical reactions and can be modeled to determine the 

theoretical shelf-life. Actual shelf-life testing is required not only to confirm the rate of reactions, but also to de-
Chapter 12 Human Health and Performance Risks of Space Exploration Missions 

310 Risk Factor of Inadequate Food System 

termine which chemical reaction in the food will determine the ultimate endpoint of the shelf-life. For example, 

the endpoint may be the Maillard Browning reaction21 or the loss of a vitamin. 

All chemical reactions in food adhere to the simple general rate equation of 

    d A n

k A

dT  

where A is the quality attribute that is being measured, T is the time, k is the rate constant, and n is the reaction 

order (Labuza and Schmidl, 1985). Most quality reactions in food are zero or first order. Zero-order reactions 

exhibit a constant change in quality over time. Typical zero-order reactions (n = 0) are enzymatic browning, 

non-enzymatic browning, and lipid oxidation. Typical first-order reactions (n = 1) are protein and most vitamin 

deterioration as well as microbial growth. Although there are not many second-order reactions (n = 2) in food, it 

has been reported that, in limited oxygen, the degradation of vitamin C is second order (Labuza, 1982). 

Q10, which is a measure of how the rate changes for every 10°C (50°F) change in temperature, is defined as 

Q10 = Shelf life at temperature T°C 

Shelf life at temperature (T°C + 10) 

If the color change reaction happens in half the time at 10°C higher temperature, then Q10 = 2 (Perchonok, 

2002). 

Since food is not a model system, it is not simple to estimate Q10; but typical Q10 values are shown in Table 

12-7. Table 12-7 shows that there is no definitive Q10 for a given type of food such that each food must be tested 

to determine its own Q10. Note that a given type of food may have several Q10s. The lipid oxidation may have 

one Q10 value and the Maillard browning may be a different Q10 (Perchonok, 2002). 

Table 12-7. Q10 Values for Various Food Preservation 

Methods 

Food Preservation Method Q10 

Thermally Processed 1–4 

Dehydrated 2–10 

Frozen 3–40 

With the Q10 values calculated, product shelf-life can be projected using the formula 

ts = t0e

–aT 

 

21The Maillard-Browning reaction is a chemical reaction, usually requiring heat, which takes place between an amino acid and a 

reducing sugar. 
Human Health and Performance Risks of Space Exploration Missions Chapter 12 

Risk Factor of Inadequate Food System 311

where: 

ts = desired shelf-life 

t0 = shelf at a reference temperature 

a = slope of the line equal to lnQ10/10 

T = temperature difference between temperature at which the shelf-life, ts, is desired and the 

reference temperature 

Shelf-life information may be collected at a faster rate using accelerated shelf-life testing and the Q10 value. 

Accelerated shelf-life testing requires a control temperature in which no changes are expected to occur through 

the shelf-life. The product may also be stored at the current storage temperature and an accelerated temperature, 

in which the reaction rates and resulting shelf-life at the accelerated temperature are used to determine the shelflife at the current temperature using the Q10 value (Evans et al., 1981). However, the accelerated temperature 

may cause changes that would not normally occur in foods at regular storage temperature, such as melting, 

protein denaturation, and increased water activity (Labuza and Schmidl, 1985). These changes must be 

considered when analyzing shelf-life data. 

The complexities of food structure and variety of components make food a dynamic system, which increases 

the difficulty in quantifying changes with kinetic models. The loss of vitamins to leaching (even when the 

vitamins are consumed in the leach liquid), the loss of nutrients during thermal processing, and the potential for 

increases in nutrient bioavailability as the food matrix is broken down during processing create an ambiguous 

picture of the actual nutritional content of processed foods. While the literature attempts to quantify the changes 

in nutritional content, the answers are not always obvious. However, the literature data provide an estimate for 

kinetic changes in the space food system and insight into the potential countermeasures, such as alternative 

processing methods and formulation interactions. 

While kinetic data are available for the loss of nutrition during processing and storage, the rate constants that 

are provided are specific to the food and conditions in each test (Evans et al., 1981; Feliciotti and Esselen, 1957; 

Mulley et al., 1975; Kirk et al., 1977; Lanthrop and Leung, 1980; Rao et al., 1981; Kamman et al., 1981) (Category 

I). Therefore, the use of the models that are in the literature will only provide a rough estimate of the remaining 

nutrition if kinetic models were prepared using these data. Accurate nutrition loss data on the thermostabilized 

pouches that are specific to the space food system need to be acquired over a 3- to 5-year shelf-life to avoid the 

use of a food system that has inadequate nutrition for a Mars mission. Food quality (i.e., color, texture, etc.) 

may provide a general indication of the nutritional loss of the food, as quality factors have a similar temperature dependence to that of many nutrients (Lund, 1988). 

 Risk in Context of Exploration Mission Operational Scenarios 

 Safety 

As long as the use of HACCP (including the strict use of good manufacturing practices, standard operating 

procedures, and testing of processed foods) continues for packaged flight food approval, food-borne illness 

events should be prevented during missions. There is always a small risk of food-borne illness during flight. 

Once NASA builds the lunar habitat to use as a test bed for Mars missions and travels to Mars, the source of 

food for the crew may not be limited to only packaged food, so the risk of food-borne illness will increase. 

During surface preparation of fresh food, safety is no longer ensured as it is through ground operations. 

Consideration must therefore be given to food safety from microbial, chemical, and physical sources during 
Chapter 12 Human Health and Performance Risks of Space Exploration Missions 

312 Risk Factor of Inadequate Food System 

food processing and preparation on the surface to prevent adverse effects on crew health and performance. If 

fresh fruits and vegetables are consumed without a heat step (cooking), there is a potential for food contamination and, hence, food-borne illness. There may be a need to wash or sanitize the fresh fruits and vegetables. The 

risk still needs to be quantified for a closed environment, especially in light of the fact that from 1991 to 2002, 

there were several produce-related Escherichia coli O157:H7 outbreaks reported for field-grown produce 

(Aruscavage et al., 2006). 

If the prepackaged food or bulk ingredients are prepositioned on the Mars surface, there is a risk that the food 

will have been compromised prior to the arrival of the crews. Packaging can be torn or the food may be adversely 

affected by the martian environment. 

Fresh food and bulk ingredients processing and subsequent preparation of meals from edible ingredients and 

packaged foods during the long-duration lunar and Mars missions will provide the crew with more variety and 

fresh foods. However, during these processes, it is necessary to reach a certain temperature/time combination to 

ensure safety and functionality. It is being proposed by mission designers that the lunar habitat will maintain an 

8-psi atmospheric pressure. Heat and mass transfer are affected by partial gravity and reduced atmospheric pressure. At an 8-psi pressure, the boiling temperature for water is 181°F. Consideration must therefore be given to 

changes in the environment and the required processing equipment and procedures to ensure safe food processing on the lunar surface. 

It is critical to quantify and reduce the risk of food preparation and processing safety before sending out human 

crews on a long-duration lunar mission. This risk could delay a long-duration lunar mission even if all other elements of the mission are ready. Mission loss or major impact to post-mission crew health would likely occur if 

this risk is not quantified and reduced. 

 Nutrition 

Although it is common for crew members to lose weight during ISS missions, the crew members have still been 

able to perform their duties. The degree of weight loss for the 6-month lunar missions is assumed to be similar 

to that for the ISS missions. However, for the Mars missions, the food will need to have a shelf-life of about 5 years 

(as opposed to 18 months for ISS missions) to accommodate the 1,000-day Mars mission. The packaging will also 

have to maintain its physical and chemical barrier properties for 5 years. Any pre-positioning of the food or delay in the consumption of the food will potentially decrease the nutritional content of the food even more. With 

no resupply options, it is critical to quantify and potentially reduce the risk of inadequate nutritional content of 

the food prior to a Mars mission. Once the crew members begin their mission, they will have no opportunity to 

mitigate a loss of nutrition with resupplied foods or supplements. 

The lunar short-duration missions may require that each crew member perform 8-hour EVAs every other day. 

If the crew members cannot access adequate nutrition during the EVAs, the risk of loss of performance can 

increase. 

Unique to space travel are nutrient losses due to space radiation. Although the extent of loss is unknown, one 

flight study is currently examining the nutritional loss of five food items that were stored on board the ISS for 

about 2 years. Ground controls are also being analyzed to help determine the effect of radiation. There is also a 

potential risk of nutritional loss of the chamber-grown fresh fruits and vegetables and the bulk ingredients that 

may be launched for use in food processing and preparation during surface missions. 
Human Health and Performance Risks of Space Exploration Missions Chapter 12 

Risk Factor of Inadequate Food System 313

The use of bulk ingredients and fresh fruits and vegetables on the lunar and martian surfaces can provide the 

crew with a variety of fresh foods and associated nutrients. These fresh foods should provide at least some of 

the vitamins that may be lost over time in the processed foods, thereby enhancing the nutritional intake of the 

crew members and their associated health and well-being while reducing the risk. While the processing of bulk 

ingredients and preparation of edible ingredients and fresh vegetables into meals can provide some of the lost 

nutrients, any failure in the growth, processing, and preparation of the foods could increase the risk of loss of 

nutrition. The overall risk of this type of food system has not been quantified yet. 

 Acceptability 

Although the acceptability of the food, including its variety and usability, is important in the 6-month ISS and 

lunar missions, it will be critical in the 1,000-day Mars missions. For the Mars missions, as the acceptability of 

the food system must be ensured for 5 years, enough variety and ease of use must be provided to ensure that the 

crew consumes adequate quantities throughout the period. With the addition of food processing and preparation 

during surface missions, there is an increased risk that the additional crew time that will be involved will counteract the increased acceptability of the overall food system. This risk could delay a Mars mission even if all other 

elements of the mission are ready. Mission loss or major impact to post-mission crew health would likely occur 

if this risk is not quantified and reduced. 

The addition of freshly grown fruits and vegetables may increase the acceptability of the lunar and Mars 

mission food systems. These fresh foods would increase the acceptability of the food system by introducing 

bright colors, crunchy textures, and fresh aromas, thus encouraging more caloric intake and boosting crew 

morale by creating a more familiar food system in a hostile and unfamiliar environment. 

 Resource utilization 

The Orion food system is being challenged to reduce the mass due to the smaller Orion vehicle. The high 

volumes of packaging material that will be required to keep food safe, nutritious, and acceptable as well as 

the power and weight requirements for heating the water and food will need to be minimized to meet the mass 

requirements. The challenge will be to bring the mass from its current level of 4 lbs. per crew member per day 

to 2.5 lbs. per crew member per day; that is, to the mass of the Apollo food system. It is not obvious that this 

goal is attainable; moreover, as noted previously, the Apollo crews were not provided with adequate calories. 

The variety of foods provided is also at risk because the galley equipment (e.g., hot water and the food warmer) 

may be removed from the Orion manifest. Without food mass reduction, other systems may not be able to 

launch their required equipment. 

There is a further risk that radiation or simply age may affect the functionality of the bulk ingredients that 

are launched for food processing during a Mars mission. For example, the soybean proteins may chemically 

change, resulting in a reduced yield in the production of tofu. 

As resupply will not be an option for Mars missions, it is especially critical that the food system be robust in its 

use of resources for 3 to 5 years. This includes the packaged food system and the bioregenerative food system. 

There is a danger that the packaged food system may be too high in mass. There is also a risk that acceptable 

food may not grow on Mars or the moon, given the reduced gravity, available water, radiation, and other aspects 

of the growing environment. Moreover, the equipment may not work or the water quantities may be inadequate 

for food hydration, processing, or preparation. Finally, there is the risk that the bioregenerative food system could 

require too much crew time, or that there will be too much food and packaging waste during a Mars mission. 
Chapter 12 Human Health and Performance Risks of Space Exploration Missions 

314 Risk Factor of Inadequate Food System 

It is worth repeating that any of these constraints on the system could delay a Mars mission, even if all other 

elements of the mission are ready. The risks increase with the increased length of the Mars mission; longer-term 

effects of radiation, especially during transit; and the lack of resupply. 

 Conclusion 

It is a possible that on a lunar or Mars mission crew health and performance will be compromised without an 

adequate food system. In developing future NASA food systems, a balance must be maintained between the use 

of resources (e.g., power, mass, and crew time) and the safety, nutrition, and acceptability of the food system to 

provide an adequate food system. Each of the four components – safety, nutrition, acceptability, and resource 

utilization –may take on different priorities based on mission duration and distance from the Earth. The incorporation of fresh foods and/or food processing and food preparation during long-duration missions may increase 

the risk in safety and resource utilization, but it may decrease the risk of inadequate nutrition and acceptability. 

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Risk of Adverse Health Effects from Lunar Dust Exposure 317

Chapter 13: 

Risk of Adverse Health Effects from 

Lunar Dust Exposure 

John T. James

NASA Johnson Space Center 

Noreen Kahn-Mayberry 

NASA Johnson Space Center 

The toxicological effects of lunar dusts have not been studied in sufficient depth to develop an exposure 

standard for operations on the lunar surface. Lunar dusts have a high content in the respirable size range, they 

have a high surface area that is chemically reactive, and elemental iron "nano-particles" are imbedded in the 

dust grains. These unusual properties may cause the respirable dusts to be at least moderately toxic to the 

respiratory system, and larger grains to be abrasive to the skin & eye. NASA needs to set an airborne exposure 

standard based on scientific evidence so that vehicle designs can effectively control exposure. – Human 

Research Program Requirements Document, HRP-47052, Rev. C, dated Jan 2009. 

 

During an Apollo 17 EVA, lunar dust is obviously 

seen to cling to astronaut Harrison Schmitt while 

he uses an adjustable sampling scoop to retrieve 

lunar samples. Efforts to understand the properties of lunar dust and to prevent its introduction 

into vehicles and habitats will minimize the risk 

of inhalation, dermal, and ocular injuries on 

future lunar missions. 
318 Risk of Adverse Health Effects from Lunar Dust Exposure 
Human Health and Performance Risks of Space Exploration Missions Chapter 13 

Risk of Adverse Health Effects from Lunar Dust Exposure 319

 Executive Summary 

The respirable fraction of lunar dusts may be toxic to humans. NASA has therefore determined that an exposure standard is necessary to limit the amount of respirable airborne lunar dusts to which astronauts will be 

exposed. The nominal toxicity that is expected from ordinary mineral dust may be increased for lunar dust due 

to the large and chemically reactive surfaces of the dust grains. Human exposures to mineral dusts during industrial operations and from volcanic eruptions give researchers some sense of the relative toxicity of lunar dust, 

although the Earth-based analogs have serious limitations. Animal and cellular studies provide further evidence 

that mineral dusts can be somewhat toxic. Earth-based research of mineral dust has shown that freshly fractured 

surfaces are chemically reactive and can elicit an increased toxic response. Since lunar dust is formed in space 

vacuum from highly energetic processes, we expect the grain surfaces to be reactive indefinitely on the lunar surface. We predict that this chemical reactivity will change once the dust is brought into a habitable environment. 

Dust from lunar soil that was carried into spacecraft during the Apollo missions proved to be a nuisance. The 

lack of gravity, or the existence of gravity at a small fraction of the gravitational force of the Earth, increases the 

time during which dust remains airborne, thereby increasing the probability that these dust particles will be inhaled. 

Lunar dust particles that are generated by impaction in a deep vacuum have complex shapes and highly reactive 

surfaces that are coated with a thin layer of vapor-deposited mineral phase. Airborne mineral dust in a variety of 

forms has been shown to present a serious health hazard to ground-based workers. The health hazards that are associated with volcanic ash, which is a commonly used analog of lunar dust, have not been reported to be especially 

serious; however, this type of ash quickly loses its reactive surfaces and is often aggregated into particles that are 

not readily respirable into the deep lung. Crew members who will be at a lunar outpost can be directly exposed 

to lunar dust in several ways. After crew members perform spacewalks or EVAs, they will introduce into the habitat a large quantity of dust that will have collected on spacesuits and boots. Cleaning of the suits between EVAs 

and changing of the Environmental Control Life Support System filters are other operations that could result in 

direct exposure to lunar dusts. In addition, if the final spacesuit design is based on the current spacesuit design, 

EVAs may cause dermal injuries, and the introduction of lunar dusts into the suits’ interior, which may enhance 

skin abrasions. When the crew leaves the lunar surface and returns to microgravity, the dust that is introduced 

into the crew return vehicle will “float,” thus increasing the opportunity for ocular and respiratory injury. 

 Introduction 

In 2004, President George W. Bush unveiled a plan directing NASA to return humans to the moon by the 

year 2015, and to use the lunar outpost as a stepping-stone for future human trips to Mars and beyond. To 

meet this objective, NASA will build an outpost on the lunar surface near the south pole for long-duration human 

habitation and research. Because of the various activities that will require the astronauts to go in and out of this 

habitat on numerous spacewalks (EVAs), the living quarters at the lunar outpost are expected to be contaminated by lunar dust. 

The president’s Vision for Space Exploration and charge to return to the moon have resulted in questions about 

health hazards from exposure to lunar dust. Lunar dust resides in near-vacuum conditions, so the grain surfaces 

are covered in “unsatisfied” chemical bonds, thus making them very reactive (Taylor and James, 2006). When 

the reactive dust is inhaled, it can be expected to react with lung surfactant and pulmonary cells. The fine, respirable lunar dust could thus be toxic if the astronauts are exposed to it during mission operations at a lunar base. 

Although a few early attempts were made to understand the toxicity of the lunar dust that was obtained by the 
Chapter 13 Human Health and Performance Risks of Space Exploration Missions 

320 Risk of Adverse Health Effects from Lunar Dust Exposure 

Apollo astronauts or the Luna probes, no scientifically defensible toxicological studies have been performed on 

authentic lunar dust. 

Awareness of the toxicity of terrestrial dusts has increased greatly since the original Apollo flights, which occurred circa 1970, in which the crew members were exposed to lunar dust for a relatively brief time. The first 

National Ambient Air Quality Standard (NAAQS) was issued by the Environmental Protection Agency (EPA) 

in 1971 and was indexed to total suspended particles (TSP) on a mass per unit volume basis. In 1987, this NAAQS 

was refined to include only particles that were of less than 10 μm in aerodynamic diameter (PM10) because this 

was the size that was most likely to reach the bronchial tree and deeper into the lung. Finally, in 1997, the EPA 

Administrator issued standards for particles that were less than 2.5 μm in aerodynamic diameter (PM2.5) based 

primarily on epidemiological associations of increased mortality, exacerbation of asthma, and increased hospital 

admissions for cardiopulmonary symptoms. None of these standards specified the composition of the particles. 

In fact, the last standard was a bit contentious because mechanisms of toxic action were not understood (NRC, 

1998). 

In a review article, Schlesinger et al. (2006) list the properties of particulate matter that might elicit adverse 

effects. The properties that seem pertinent to lunar dust include: size distribution, mass concentration, particle 

surface area, number concentration, acidity, particle surface chemistry, particle reactivity, metal content, water 

solubility, and geometric form. In attempting to consider each of these properties, one property emerges as the 

most difficult to study; particle surface chemistry may be difficult to understand because the environment on the 

lunar surface is unlike any on Earth, and is likely to alter the surface of dust grains in a way that will render them 

highly reactive. Recreating the processes that could affect grain surface reactivity on the moon is not easy to do 

in an Earth-bound laboratory. Although this problem will be discussed in detail later, we note here that freshly 

fractured quartz is distinctly more toxic to the rat respiratory system than aged quartz (Vallyathan et al., 1995). 

Our point is not that quartz and lunar dust may have similar toxic properties, but that breaking of surface bonds 

on mineral substrates has been shown to increase the toxicity of the well-studied mineral quartz. 

The site at which various sizes of particles are deposited is critical to an understanding of any aspect of their 

toxic action. The fractional regional deposition of particles shows that between 10 and 1 μm, the portion of 

particles that is deposited in the upper airways falls off from 80% to 20%, whereas the pulmonary deposition 

increases from near zero to about 20%. Pulmonary deposition, after falling off near 1 μm, peaks again near 40% 

for particles of 0.03 μm, whereas upper airway deposition remains low until a new peak deposition is found at 

less than 0.01 μm. The portion and pattern of deposition can be modified under conditions of reduced gravity; 

however, human data during flights of the gravity research aircraft show that particles in the 0.5 to 1 μm range 

are deposited less in the respiratory system at lunar gravity than at Earth gravity. This finding is consistent with 

the reduced sedimentation of the particles when the gravity is less. However, a larger portion of the particles is 

deposited peripherally in reduced gravity (Darquenne and Prisk, 2008). 

The first encounter in which a particle deposits in the distal airways occurs with the bronchoalveolar lining 

fluid (BALF). The thickness of this fluid in the lung varies as the alveolar sacs expand and contract, but lies in 

the range of 0.1 to 0.9 μm (Bastacky et al., 1995). In the case of biological particles such as bacteria, this fluid 

opsonizes the particles to facilitate ingestion by macrophages. A similar process has been demonstrated for nonbiological carbonaceous particles (Kendall et al., 2004). This process removes some components of the BALF 

that participate in opsonization, and it is postulated that this might enhance the toxicity of particles with a surface 

chemistry that is capable of selectively removing opsonizing components. The agglomeration of the grains is 

also affected by the interactions between the BALF and the grains. Preliminary data on authentic lunar dust 
Human Health and Performance Risks of Space Exploration Missions Chapter 13 

Risk of Adverse Health Effects from Lunar Dust Exposure 321

has shown that in aqueous suspension, lunar particles agglomerate rapidly. Artificial surfactant has been 

found to greatly reduce this particulate agglomeration. 

Particles that are deposited in the pulmonary region are eliminated according to their surface area and chemical composition. If a particle is relatively soluble, its dissolution products end up in the bloodstream. Relatively 

insoluble particles are ingested by macrophages and removed by mucociliary clearance or the lymphatic system, 

or they persist in the interstitial areas of the lung. Ultrafine particles (<0.1 μm) that deposit in the upper airways 

have been shown, under some conditions, to translocate to the brain (Oberdörster et al., 2004), whereas similar 

particles reaching the pulmonary regions can translocate to adjacent organs such as the liver (Oberdörster et al., 

2002). 

The effects of particles on the respiratory system include de novo causation of clinical disease as well as 

exacerbation of existing disease. If particulate inhalation is to directly cause disease, the exposure levels 

typically must be at levels that are encountered in industrial settings. For example, silicosis is a well-known 

disease of persons working for years in conditions in which dust containing quartz is inhaled. Epidemiological 

studies show that ambient dust levels such as those that are encountered in some cities can exacerbate respiratory 

conditions such as asthma and chronic obstructive pulmonary disease. At certain times, sand dust that originates 

in Asia or Arizona, for example, has been associated with exacerbation of allergenic respiratory inflammation 

(Ichinose et al., 2008). 

 

Of particular concern in addition to the respiratory system is the ability of small particles to affect the cardiovascular system. Epidemiological studies suggest that exposure to ambient particulate matter increases the 

incidence of angina, arrhythmia, and myocardial infarctions. The increased acute mortality that is associated 

with particle “events” is attributed to cardiovascular disease (NRC, 2004). Clinical studies involving concentrated ambient air particulate have shown increased blood fibrinogen and reduced heart-rate variability (Devlin 

et al., 2003); exposure to ultrafine particles causes “blunted” repolarization response following exercise (Frampton 

et al., 2002). The role of C-reactive protein in mediating the effect of ambient particle exposures on the causation 

of CAD has been reviewed (Sandu et al., 2005). Batalha (2002) has drawn attention to the ability of particles to 

elicit vasoconstriction of small pulmonary arteries. Although the mechanistic details have not been fully elucidated, 

the evidence favors a strong link between exposure to particulates and to both acute and chronic heart disease 

(NRC, 2004). There is some evidence from the Apollo missions that, in susceptible individuals, lunar dust exposure may lead to cardiovascular effects that are similar to those produced through exposure to air pollution 

(Rowe, 2000). 

The fact that no accepted health standards or policies exist concerning exposure limits to lunar dust is a 

critical challenge to the design of vehicle systems in the CxP. The multi-center Lunar Airborne Dust Toxicology 

Assessment Group (LADTAG) was formed and responded to a request from the Office of the Chief Health and 

Medical Officer to “... develop recommendations for defining risk criteria for human lunar dust exposure and a 

plan for the subsequent development of a lunar dust permissible exposure limit.” The LADTAG is comprised of 

technical experts in lunar geology, inhalation toxicology, biomedicine, cellular chemistry, and biology from within 

the agency as well as of leading U.S. experts in these fields. Based on the opinions that were expressed by the 

LADTAG experts, NASA scientists will develop and execute a plan to build a database on which a defensible 

exposure standard can be set (Khan-Mayberry, 2008). 

LADTAG experts recommend that the toxicity of lunar dust on the lungs (pulmonary toxicity), eyes (ocular 

toxicity), and skin (dermal toxicity) be investigated, and that this investigation is to be conducted by the Lunar 

Dust Toxicity Research Project (LDTRP) using various assays including in vivo and in vitro methods. In an initial 
Chapter 13 Human Health and Performance Risks of Space Exploration Missions 

322 Risk of Adverse Health Effects from Lunar Dust Exposure 

LADTAG workshop that was held in 2005, experts noted that they were unable to reconcile individual expert 

opinions to set an inhalation standard. The array of opinions from these experts spanned a 300-fold range (i.e., 

0.01 to 3 mg/m3). The members of the LADTAG concluded that research is necessary to narrow this wide uncertainty range, the lower end of which cannot be met by known methods of environmental control, and that 

there is an urgency to determine the standard so that environmental systems for the lunar vehicle can be appropriately designed. Therefore, in keeping with the LADTAG experts’ recommendations, members of the LDTRP 

have reviewed first-hand accounts of Apollo astronauts who were exposed to lunar dust during their missions as 

well as of terrestrial-based human exposures to dust generated in the mining industry and to volcanic ash. In 

accordance with the LADTAG recommendations to increase our evidence base, the LDTRP is conducting 

studies of Apollo spacesuits, filters, vacuum bags, and rock-collection boxes. These studies will enable us to 

focus our understanding of the grain-size distribution that is present in the lunar surface samples and in the 

habitat, but the dust surfaces are expected to be fully passivated. 

 Evidence 

 Ground-based evidence 

Ground-based evidence includes data that are derived from people who are exposed occupationally to mineral 

dusts in industrial settings, from people who live in close proximity to active volcanoes and have been exposed 

to volcanic ash, and from animals and cells that are in controlled experimental studies. Mechanistic insights also 

guide our thinking concerning the potential toxicity of lunar dusts. 

 Evidence from Human Exposures During Industrial Operations 

Workers in the mining industry are often exposed to dust from freshly fractured mineral deposits. When 

these workers use inadequate, or lack, respiratory protection completely, the consequences are devastating. 

A prime example of this is the Hawks Nest mining activity in West Virginia beginning in 1927. During the 

boring of a tunnel, deposits of silica were identified and mined; however, the workers did not use respiratory 

protection during the operations. Estimates of the proportion of workers who died, often within a few years, 

are typically about 30% of the 2,000 exposed workers (Cherniack, 1986). This rapidly lethal form of silicosis 

has been called “acute silicosis,” which is characterized by alveolar proteinosis and interstitial inflammation 

(Driscol and Guthrie, 1997). The respiratory effects are not exactly like those one would expect from simple 

silicosis, a disease that usually requires decades to develop after prolonged exposure to lower concentrations 

of silica dust. The latter disease is characterized by silicotic nodules that are clearly distinct from surrounding 

tissue and often surrounded by an inflammatory response (Driscol and Guthrie, 1997). 

 Evidence from Humans and Laboratory Animals Exposed to Volcanic Ash 

Volcanic ash originates from processes resulting in explosive eruptions into the atmosphere or pyroclastic 

flows oozing from the surface and discharging ash as they cool, or some combination thereof. Under any 

plausible condition, the ash will have had hours to days to react with the oxygen and water vapor of the atmosphere to passivate all surfaces before being inhaled by humans. The mineral composition of ash is determined 

by the composition of the magma. The particle size, mineral composition, and form of the minerals vary considerably from volcano to volcano as well as from one eruption to another eruption of the same volcano. 

Shortly after Mount St. Helens erupted in 1980, a number of experts began to investigate the effects of volcanic ash on those who had been exposed to the dust (Bernstein et al., 1986). The crystalline silica content of 

this dust ranged from 3% to 7%. The primary acute effects were reflected in increased emergency room visits 

for asthma, bronchitis, and eye discomfort (Baxter et al., 1981). The ash was noted to exacerbate chronic 
Human Health and Performance Risks of Space Exploration Missions Chapter 13 

Risk of Adverse Health Effects from Lunar Dust Exposure 323

respiratory conditions. The increase in hospital admissions lasted approximately 3 weeks (Nania and Bruya, 

1982), and immune parameters were affected even 1 year later (Olenchock et al., 1983). The British West Indian Montserrat volcano began erupting in 1995, causing an ash fall from pyroclastic flows that contained 

10% to 24% crystalline silica (Baxter et al., 1999). Recorded incidences of childhood wheezing increased as 

a result of relatively intense exposures to the ash (Forbes et al., 2003). To our knowledge, sustained long-term 

health effects have not been reported in association with exposures to volcanic ash, although there is speculation that the high cristobalite content of the Montserrat ash could lead to silicosis many years later. 

Animal studies that focused on the biological effects of chronic inhalation exposure to Mount St. Helens 

volcanic ash or quartz, under controlled laboratory conditions, indicate significant dose-response to both 

materials (Wehner et al., 1986). The quartz that came from the volcano was found to be markedly toxic and 

fibrogenic; by contrast, the volcanic ash was much less toxic (Martin et al., 1984; 1986). Similar results were 

noted in other animal studies (Wiester et al., 1985; Raub et al., 1985; Beck et al., 1981), suggesting that quartz 

is a much more potent pulmonary toxicant than volcanic ash (Martin et al., 1986; Raub et al., 1985; Beck et 

al., 1981). However, the presence of volcanic ash in the inhaled air did increase the “histamine sensitivity” of 

the epithelial irritant receptors (Wiester et al., 1985) as well as inhibit the ability of alveolar macrophages to 

protect against infection (Vallyathan et al., 1995). 

The toxicity of volcanic ashes has been evaluated in rats that were dosed once by intratracheal instillation 

(Lam et al., 2002). Ashes that were obtained from the San Francisco volcano field in Arizona (lunar dust 

simulant) and from a Hawaiian volcano (martian dust simulant) were compared to the toxicity of titanium 

dioxide and quartz. Lungs of mice that have been harvested 90 days after receiving a dose of 1 mg of lunar 

simulant showed chronic inflammation, septal thickening, and some fibrosis. No changes were seen at the 

low dose of 0.1 mg/mouse (Lam et al., 2002). The martian dust simulant elicited a response that was similar 

to that of the lunar simulant, except that there was an inflammatory and fibrotic response even at a dose of 

0.1 mg/mouse. The response of the mouse lungs to 0.1-mg quartz was comparable to the response to the martian dust simulant. In another study, the effect of these same simulants was assessed on human alveolar macrophages (Latch et al., 2008). The lunar dust simulant was comparable in cell viability reduction and apoptosis 

induction to the TiO2 (titanium dioxide) negative control. Both were less toxic than the quartz positive control. Both simulants showed a dose-dependent increase in cytotoxicity. 

 Evidence that Surface Activation and Trace Impurities Increase Toxicity 

Inhalation of freshly ground quartz, when compared to inhalation of aged quartz, results in a significant increase in animal lung injury (Lam et al., 2002; Shoemaker et al., 1995). Freshly ground quartz has increased 

reactive silicon-based oxygen radicals, and animals that are exposed to freshly ground quartz have been found 

to have decreased concentrations of antioxidant enzymes (Vallyathan et al., 1995; Dalal et al., 1990). Activated 

quartz particles decay with age in ambient air (Dalal et al., 1990). Quartz dusts containing surface iron as an 

impurity have been shown to deplete cellular glutathione, contributing to the oxidative damage that is caused 

by particle and cell-derived ROS (Fenoglio et al., 2003). Castranova et al. (1997) suggest that freshly ground 

quartz dust that is contaminated with trace levels of iron may be more pathogenic than quartz dust alone. 

Crystalline silica exposure studies indicate that the generation of oxidants and nitric oxide, which play an 

important role in the initiation of silicosis (Castranova et al., 2002), has been shown to cause pulmonary 

inflammation in rats (Porter et al., 2002). Other studies indicate that the mode of action of crystalline silica 

cytotoxicity and pathogenicity lies in the ability of the mineral to induce lipid peroxidation (Vallyathan, 

1994). Respiratory exposure to freshly ground silica causes greater generation of ROS from macrophages 
Chapter 13 Human Health and Performance Risks of Space Exploration Missions 

324 Risk of Adverse Health Effects from Lunar Dust Exposure 

than exposure to aged silica, which is one piece of evidence that proves that freshly fractured silica is more 

toxic than aged silica (Porter et al., 2002; Vallyathan et al., 1988). 

Further evidence linking increased toxicity to surface activation must await data that show that lunar dust 

that is activated by methods other than grinding adversely affects cells. We have been able to demonstrate 

that dust that is activated by processes that are analogous to those that are understood to be present at the lunar 

surface (i.e., ultraviolet [UV] irradiation in a vacuum) are able to produce more ROS in aqueous solution than 

dust that is not activated by these processes (Wallace, unpublished data). In addition, mineral coupons that are 

activated by proton and alpha-particle bombardment that is analogous to the solar wind show increased ROS 

(Kuhlman, unpublished data). We expect to assess the impact of these activation techniques on cellular systems in early 2009. 

 Evidence from Mechanistic Understandings 

As we know from lunar geologists (Category I22 evidence) that iron is present in lunar dust, especially in the 

fraction of its smallest particles (nano-Fe), we can postulate that a reaction involving iron could be important 

for activated lunar dust when it comes in contact with the mucous lining of the respiratory system. A good model of the issues and problems that are associated with testing surface-activated dust can be found in the studies 

of freshly fractured silica, which is highly toxic to the respiratory system via oxidative damage, and perhaps 

also in the testing of volcanic ash. The problem of the enhancement of toxicity in quartz by freshly fractured 

surfaces has been extensively investigated in animal and cellular systems (Castranova, 2004; Porter et al., 2002; 

Ding et al., 1999; Vallyathan et al., 1991). Fracturing silica cleaves the Si-O bonds, leaving Si and SiO radicals, 

which, in turn, produce OH radicals in an aqueous environment. Aged crystalline silica still produces radicals, 

but at a much lower level, perhaps by the Fenton reaction that occurs between iron and H2O2 that is generated 

by macrophage phagocytosis of the particles (Castranova, 2004). 

 Passivation of Reactive Surfaces as Dust Surfaces Age 

Since surface activation, which is produced primarily by grinding, is known to increase the toxicity of 

various mineral dusts, it is critical to ask how quickly surface activation disappears once the dust encounters 

an oxygen- and water-vapor-rich environment. Vallyathan et al. (1988) demonstrated a bimodal decay by 

measuring the rate of disappearance of hydroxyl radical formation in an aqueous medium from silicon-based 

radicals on the surface of ground silica, when that ground silica was kept in air until the time of assay. The 

half-life of the fast decay was approximately 30 hours, whereas even after 4 weeks approximately 20% of the 

original activity that was induced by grinding was present on the surface of the quartz. This is similar to the 

ability of the 24-hour half-life in air of freshly fractured quartz to produce OH radicals (Castranova, 2004). 

Although quartz is not lunar dust and grinding is merely a surrogate for activation of dust at the lunar surface, 

the longevity of the surface reactivity requires careful attention to better understand how surface-activated 

lunar dust becomes passivated in a habitable environment. 

 

22To help characterize the kind of evidence that is provided in each of the risk reports in this book, the authors were encouraged to 

label the evidence that they provided according to the “NASA Categories of Evidence.” 

 Category I data are based on at least one randomized controlled trial. 

 Category II data are based on at least one controlled study without randomization, including cohort, case-controlled or subject

operating as own control. 

 Category III data are non-experimental observations or comparative, correlation and case, or case-series studies. 

 Category IV data are expert committee reports or opinions of respected authorities that are based on clinical experiences, bench 

research, or “first principles.” 
Human Health and Performance Risks of Space Exploration Missions Chapter 13 

Risk of Adverse Health Effects from Lunar Dust Exposure 325

 Space flight evidence 

Samples of lunar dust that have been returned to Earth have enabled NASA to learn the mineralogical properties of the dust at several lunar landing sites. First and foremost, one must keep in mind that the properties of 

the lunar dust may vary considerably depending on location; hence, lunar dusts may show a range of toxicity. 

Initially, NASA assessed the expected nature of dust at the proposed South Pole landing site on the rim of 

Shackleton crater. 

All space flight evidence pertaining to the effect of lunar dust on astronauts is anecdotal (Category III). The 

post-flight debriefing reports of the Apollo astronauts serve as a base of evidence (Portree and Trevino, 1997). 

Although the astronauts attempted to remove the lunar dust before they reentered the command module (CM) by 

brushing the spacesuits or vacuuming, a significant amount of dust was returned to the spacecraft, which caused 

various problems. For instance, astronaut Harrison Schmitt complained of “hay fever” effects caused by the dust 

(Portree and Trevino, 1997), and the abrasive nature of the material was found to cause problems with various 

joints and seals of the spacecraft and spacesuits (Wagner, 2006). In these reports, the Apollo crews provided 

several accounts of problems with lunar dust exposure as follows: 

 During Apollo 11, crew members reported: “Particles covered everything and a stain remained even 

after our best attempts to brush it off”; a “[d]istinct pungent odor like gunpowder [was] noted when 

helmet [was] removed”; and “[t]exture like graphite” (Portree and Trevino, 1997). 

 During Apollo 12, regarding dust in the lunar module (LM), the crew members noted several issues: 

“Both LM and CM contaminated with lunar dust”; “[LM] was filthy dirty and had so much dust that 

when I took my helmet off, I was almost blinded. Junk immediately got into my eyes”; and “[t]he whole 

thing was just a cloud of fine dust floating around in there.” After the LM docked to the CM, dust infiltrated the CM. Crew members gave the following account of this period of contamination: “On the way 

back in the CM the system could not handle the dust, so it was continuously spread inside the spacecraft 

by the system”; “[w]e chose to remain in the suit loop as much as possible because of the dust and debris 

floating around”; and “[t]o keep our eyes from burning and our noses from inhaling these small particles, 

we left our helmet sitting on top of our heads” (Portree and Trevino, 1997). 

 By contrast, the Apollo 14 crew members stated: “Dust was not a problem for us in the cabin”; and “[t]he 

dust control procedures were effective” (Portree and Trevino, 1997). 

 The Apollo 15 crew members stated: “Cabin smelled like gunpowder when we first came into LM 

from EVA”; “[p]article matter floated around in spacecraft”; “[l]unar dust is ‘soluble’ in water”; and 

“[t]he vacuum cleaner did a good job of clearing the dust from the LM” (Portree and Trevino, 1997). 

 Apollo 16 crew members provided the following accounts: “The LM was extremely clean until the first 

EVA and then it was extremely dirty”; “I question whether the vacuum cleaner ever worked properly”; 

and “I thought it was quite a hazard over there floating through the LM with all the dust and debris. A 

number of times I got my eyes full of dust and particles. I felt like my right eye was scratched slightly 

once” (Portree and Trevino, 1997). 

 The Apollo 17 crew members recalled: “You knew [that] you were in a very heavily infiltrated atmosphere in the LM because of the lunar dust”; “[t]he dust clearing was remarkable considering the 

amount of dust we had”; “[a]lthough there was a lot of irritation to my sinuses and nostrils soon after 

taking the helmet off, by 2 hours that had decreased considerably”; “I did all the transfer with my helmet 
Chapter 13 Human Health and Performance Risks of Space Exploration Missions 

326 Risk of Adverse Health Effects from Lunar Dust Exposure 

off and I am sorry I did because the dust really bothered my eyes and throat. I was tasting it and eating 

it”; and “[w]hen I climbed in the tunnel I could tell there was a lot of dust in the LM and you could smell 

it” (Portree and Trevino, 1997). 

We also have the observations of a crew surgeon (Category IV), Dr. Bill Carpentier (Scheuring et al., 2007), 

detailing his own, as well as crew members’, post-flight allergic-type responses. Dr. Carpentier recalls an increase in eosinophil and basophil blood cell counts after the crew members were exposed to lunar dust, which 

may have indicated an allergic response. 

Although no substantive evidence exists that astronaut performance was impaired by lunar dust (Wagner, 2006), 

one can imagine that if a crew member were “almost blinded” and had to “remain in the suit loop as much as possible because of the dust and debris floating around,” the dust did have some impact on performance. 

Dust from the lunar soil that was carried into the spacecraft during the Apollo missions proved to be a 

significant, intermittent problem. With the return to the moon and planned long-duration stays on the lunar 

surface, the dust toxicity and contamination problems are potentially much more serious than those that were 

experienced during the Apollo missions. Physical evidence also suggests that lunar dust could be a health hazard at a lunar outpost. Gravity at one-sixth that of the gravitational force of the Earth increases the time in which 

dust remains airborne, thereby increasing the probability that these dust particles will be inhaled. 

Some examples of lunar dust grains are provided in figure 13-1. 

Figure 13-1. Examples of lunar dust grains. – LEFT: Scanning electron microscope (SEM) 

image of a typical lunar agglutinate. Note the sharp edges, reentrant surfaces, and microcraters. Smaller grains, which are less than 1 μm in diameter, are attached to this particle, 

and are also seen as loose grains in the upper portion of the image. RIGHT: SEM image of 

a lunar agglutinate fragment that was removed from the outer surface of Harrison 

Schmitt’s EVA suit. 
Human Health and Performance Risks of Space Exploration Missions Chapter 13 

Risk of Adverse Health Effects from Lunar Dust Exposure 327

 Computer-based Simulation Information 

This section is not applicable to this risk. 

 Risk in Context of Exploration Mission Operational Scenarios 

Multiple, probable scenarios exist in which crew members could be exposed to lunar dust during both lunar 

sortie and lunar outpost missions. Further, there are opportunities for crew members to be directly exposed to 

lunar dust after they perform EVAs. Post EVA, lunar crew members will introduce into the habitat and lunar 

lander the dust that has collected on their spacesuits and boots. Cleaning of the suits between EVAs may also 

directly expose crew members to lunar dust. For crew members, changing of Environmental Control and Life 

Support System filters is yet another potential route of direct exposure to lunar dusts. These episodic periods of 

increased lunar dust exposure must be taken into account when long-term exposure limits are calculated. As missions become longer, the greater dose and/or duration of lunar dust exposure will increase the potential human 

health risk. When a crew returns to microgravity, if lunar dust is introduced into the crew return vehicle, there 

will be an increased opportunity for ocular exposure if particles of dust are floating throughout the cabin. EVAs 

cause dermal injuries when suits that are based on the current design are used, and the introduction of lunar 

dusts may enhance injuries that will be sustained from contact with the EVA suit. In addition, NASA is considering the use of a rover design that will allow shirtsleeve operation of the vehicle. Thus, the rover, which 

must be kept in an interior space to be entered without a spacesuit, may also bring dust into the habitat. 

 Conclusion 

Our evidence base shows that prolonged exposure to respirable lunar dust could be detrimental to human health. 

Lunar dust is known to have a large surface area (i.e., it is porous), and a substantial portion is in the respirable 

range. The surface of the lunar dust particles is known to be chemically activated by processes ongoing at the 

surface of the moon. We predict that this reactivity will disappear on entry into the habitable volume; however, 

we do not know how quickly the passivation of chemical reactivity will occur, nor do we know how toxic the 

deactivated dust may prove to be. Although many Apollo astronauts seemed to tolerate lunar dust, their exposure times were brief and time (duration) exposure factors need to be determined. Other Apollo crew members 

and ground support personnel noted that the lunar dust was a sensory irritant. Finally, the size characteristics of 

the dust that actually was present in the atmosphere of the lunar lander have never been determined. Obtaining 

these data will help us understand the size distribution of the particles that are expected to be found in future 

lunar habitats. It is important to design experiments that will close or, at a minimum, narrow our knowledge 

gaps so that a scientifically defensible exposure standard can be set by NASA for protection of crew health. 

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Exercise and 

Extravehicular Activity 

Risk of Compromised EVA 

Performance and Crew Health 

Due to Inadequate EVA Suit 

Systems 

Risk of Operational Impact of 

Prolonged Daily Required 

Exercise 

Risk of Compromised EVA Performance and Crew Health 

Due to Inadequate EVA Suit Systems 333

Chapter 14: 

Risk of Compromised EVA Performance 

and Crew Health Due to Inadequate 

EVA Suit Systems 

Michael L. Gernhardt 

NASA Johnson Space Center 

Jeffrey A. Jones 

NASA Johnson Space Center 

Richard A. Scheuring 

NASA Johnson Space Center 

Andrew F. Abercromby 

Wyle Integrated Science and Engineering Group 

Jennifer A. Tuxhorn 

Wyle Integrated Science and Engineering Group 

Jason R. Norcross 

Wyle Integrated Science and Engineering Group 

Improperly designed EVA suits can result in the inability of the crew to perform as expected, and can cause 

mechanical and decompression injury. Suit developers must fully understand the impact of the suit design on 

crew performance and health to ensure properly designed mobility, pressures, nutrition, life support, etc. – 

Human Research Program Requirements Document, HRP-47052, Rev. C, dated Jan 2009. 

 

Although the Apollo EVA suits performed very 

well on the short missions for which they were 

designed, longer missions to the moon and 

Mars will require more robust suit designs. An 

integrated human testing program across multiple environments aims to correct or mitigate 

many of the problems with the Apollo EVA 

suits, thus maximizing human performance 

and efficiency while minimizing crew member

health and safety risks on future missions.
334 Risk of Compromised EVA Performance and Crew Health 

Due to Inadequate EVA Suit Systems 
Human Health and Performance Risks of Space Exploration Missions Chapter 14 

Risk of Compromised EVA Performance and Crew Health 

Due to Inadequate EVA Suit Systems 335

 Executive Summary 

Constellation Program missions to the moon and Mars will include as many as 24 hours of EVA per crew 

member per week, which will involve the performance of exploration, science, construction, and maintenance 

tasks. The effectiveness and success of these missions is dependent on designing EVA systems and protocols 

that maximize human performance and efficiency while minimizing health and safety risks for crew members. 

The Apollo EVA suits performed very well in the short-duration missions for which they were designed. However, the longer-duration missions, more frequent EVAs, and more varied EVA tasks that are anticipated during 

the CxP will require EVA suits and systems that are more robust than those used during the Apollo Program. 

Many of the problems that were encountered with the Apollo EVA suits (e.g., limited mobility and dexterity, 

high and aft center of gravity (CG), and other features requiring significant crew compensation) will need to 

be corrected or mitigated to optimize EVA objectives. 

It is critical to understand the effects of EVA system design variables such as suit pressure, weight/mass, CG 

location, joint ranges of motion, and biomedical monitoring on the ability of astronauts to perform safe, efficient, and effective EVAs. To achieve this understanding, the EVA Physiology, Systems, and Performance 

(EPSP) Project is working with the CxP to develop and execute an integrated human testing program across 

multiple environments. This program will provide objective data that will enable informed design decisions, 

thereby ensuring a Constellation EVA system that optimizes crew member health, safety, efficiency, and 

performance. 

This report describes the risks to crew health, safety, performance, and efficiency that an inadequate EVA suit 

system design would bring, and provides the evidence base to substantiate the importance of the risks. 

 Introduction 

Fewer than 20 lunar EVAs were performed during the entire Apollo Program. Current architectures under 

consideration by the NASA Constellation Architecture Team-Lunar (CxAT-Lunar) could involve as many as 

30,000 hours of lunar exploration EVA time. As demonstrated in figure 14-1, these plans represent an enormous 

increase in EVA hours in an extreme and challenging environment. No previous astronaut or spacesuit has performed more than three lunar EVAs, yet future astronauts and their EVA suits must be capable of performing 

as many as 76 lunar EVAs during a 6-month mission. 

Providing the capability for humans to work productively and safely while performing an EVA involves many 

important, medically related considerations. Maintaining sufficient total pressure and oxygen partial pressure is 

vital not only to human health, but also to survival. Pre-breathe protocols must adequately reduce the amount of 

inert gas in astronauts’ blood and tissues to prevent DCS (also known as “the bends”) while minimizing the impact on crew efficiency. The EVA suit must be ventilated to remove expired carbon dioxide (CO2), both perspired 

and respired water vapor, and metabolically generated heat. Since ventilation flow alone may not be sufficient to 

control core body temperature and prevent unwanted heat storage, cooling water is typically circulated through 

small tubes that are located in garments worn close to the skin. Heat influx also must be controlled, and the EVA 

crew member must be protected from harmful solar and other radiation. Nourishment and water must be 

available for ingestion, and accommodations must be provided for liquid and solid waste collection. 

 
Chapter 14 Human Health and Performance Risks of Space Exploration Missions 

336 Risk of Compromised EVA Performance and Crew Health 

Due to Inadequate EVA Suit Systems 

Figure 14-1. EVA estimates for current lunar architecture. 

Considerable evidence shows that the inadequate design of any aspect of an EVA suit system can have serious consequences. A large body of evidence in this area consists of astronaut first-hand experience and nonexperimental observations (e.g., Category III and Category IV23). More recent evidence has been gathered in a 

rigorous, controlled manner in which subjects serve as their own controls from shirt-sleeved to suited conditions 

and across repeated measures trials in which a single parameter is varied (e.g., Category II). This report identifies and describes the various risks and associated evidence as follows: 

 Risks to Crew Performance: EVA Suit Design Parameters 

 Risks to Crew Performance, Health, and Safety: EVA Biomedical Monitoring and Consumables 

Management 

 Risks to Crew Health: EVA Suit Design Parameters 

 Risks to Crew Health: Decompression Sickness 

 Risk to Work Efficiency: EVA Suit Design Parameters 

 

23To help characterize the kind of evidence that is provided in each of the risk reports in this book, the authors were encouraged to 

label the evidence that they provided according to the “NASA Categories of Evidence.” 

 Category I data are based on at least one randomized controlled trial. 

 Category II data are based on at least one controlled study without randomization, including cohort, case-controlled or subject

operating as own control. 

 Category III data are non-experimental observations or comparative, correlation and case, or case-series studies. 

 Category IV data are expert committee reports or opinions of respected authorities that are based on clinical experiences, bench 

research, or “first principles.” 

0

500

1000

1500

2000

2500

3000

3500

4000

4500

5000

196619681970197219741976197819801982198419861988199019921994199619982000200220042006200820102012201420162018202020222024202620282030

Year

EVA Hours
Human Health and Performance Risks of Space Exploration Missions Chapter 14 

Risk of Compromised EVA Performance and Crew Health 

Due to Inadequate EVA Suit Systems 337

 Evidence 

 Risks to crew performance: extravehicular activity suit design parameters 

 Space Flight Evidence 

Throughout the history of space flight, astronauts and cosmonauts have performed nearly 300 EVAs. However, only 14 of those EVAs have been conducted on the lunar surface in one-sixth gravity. Accordingly, the 

current understanding of suited human performance in partial-gravity environments is limited. A recent faceto-face summit with some of the Apollo astronauts provided valuable insight and yielded recommendations 

for the next-generation lunar EVA suit. Fourteen of the 22 surviving Apollo astronauts participated in the Apollo 

Medical Operations Project to identify Apollo operational issues that impacted crew health and performance. 

In the category of EVA Suit Operations using the shuttle/ISS EMU, recommendations centered on improving 

the functionality of the suit as well as improving human factors and safety features. The astronauts recommended increasing ambulatory and functional capability through increased suit flexibility, decreased suit 

mass, lower CG, and reduced internal pressure (Scheuring et al., 2007). 

The following excerpt from Scheuring et al. (2007) describes the astronauts’ view on the need for increased suit mobility: “EVA suit mobility was more of an issue in terms of surface locomotion and energy 

expenditure. The crews often felt they were fighting the resistance in the suit. This was fatiguing, especially 

in the thighs. The astronauts pointed out that the lunar surface is more similar to an ocean than a desert. The 

undulating surface posed a number of challenges, including ambulating against a suit that did not allow mobility 

at the hip. Normal human locomotion includes flexion at the hip and the Apollo A7LB {lunar surface EVA suit} 

had limited ability to bend the suit at the hip and to rotate within the suit. The crewmember had to bend forward 

from the knee joint, which demanded considerably more work load on the quadriceps muscles. Therefore, 

recommendations on mobility centered on adding hip mobility and improving knee flexibility. One comment 

summarized this point well, ‘Bending the knee was difficult in the suit. We need a better [more flexible] knee 

joint’.” 

The Apollo astronauts also strongly recommended improving glove flexibility, dexterity and fit. According to 

the crews, the most fatiguing part of surface EVA tasks was repetitive gripping. One crew member stated that 

“efficiency was no more than 10% of the use of the hand” (Scheuring et al., 2007). The crew also sustained significant fingernail and hand trauma, as described in “Risks to crew health: EVA suit design parameters” below. 

 Ground-based Evidence 

Physiologists and physicians are using various analog environments to study the effects of suit weight, mass, 

CG, pressure, biomechanics, and mobility on human performance. Test activities are designed to characterize 

performance during ambulation and exploration-type tasks such as ambulation on both level and inclined surfaces, ambulation while carrying a load, rock collecting, shoveling, and kneeling. Other studies examine recovering from a fall and simple exploration and construction tasks using hand tools and power tools. Data 

collected include metabolic rates, subject anthropometrics, time series motion capture, ground reaction forces 

(GRFs), subjective ratings of perceived exertion (RPEs) (Borg, 1982), and operator compensation using a relative subjective scale. The operator compensation scale, the gravity compensation and performance scale 

(GCPS), is modeled after the Cooper-Harper rating scale (Cooper and Harper, 1969) and is described in 

Appendix A. 

The lunar analogs used include the Partial Gravity Simulator (Pogo) and Neutral Buoyancy Laboratory 

(NBL) at NASA JSC, parabolic flight, Desert Research and Technology Studies (D-RATS), the Haughton 

Mars Project (HMP), and NEEMO. 
Chapter 14 Human Health and Performance Risks of Space Exploration Missions 

338 Risk of Compromised EVA Performance and Crew Health 

Due to Inadequate EVA Suit Systems 

Results from early tests conducted on the Pogo have begun to characterize the metabolic cost, biomechanics, 

and subjective factors that are associated with ambulation and task performance in the Mark III Advanced 

Spacesuit Technology Demonstrator (MKIII), which is a prototype EVA suit that was designed for multiaxial mobility in planetary environments. 

These tests have characterized the baseline metabolic cost of suited ambulation in lunar gravity across a 

wide variety of speeds, and have considered factors such as suit weight, inertial mass, suit pressure, and suit 

kinematic constraints and stability. Figure 14-2 shows the current understanding of how these factors contribute to the increased metabolic cost of suited ambulation in the MKIII suit (Gernhardt et al., in preparation 

(a)). 

Figure 14-2. Suit design parameters that contribute to the metabolic cost of the suit.

The parameter that has the largest impact on metabolic rate has been suit weight. Variations in suit pressure 

make little difference, but varying suit weight has led to significant differences in metabolic rate across speeds. 

Figure 14-3 shows how varying suit weight affects metabolic rate as a function of level ground ambulation 

speed (Gernhardt et al., in preparation (a)). 

 
Human Health and Performance Risks of Space Exploration Missions Chapter 14 

Risk of Compromised EVA Performance and Crew Health 

Due to Inadequate EVA Suit Systems 339

Figure 14-3. Effect of suit weight on metabolic rate across speed of ambulation. 

This is just one example of how lunar operational concepts will play a large role in determining requirements. 

If a crew member is only expected to walk slowly, the suit weight may not be a critical design parameter; but 

if a long (e.g., 10-km/6.2-mile) walkback contingency must be prepared for, the suit weight will be absolutely 

critical to mission success. 

Based on the Pogo test results, a predictive equation for metabolic rate has been proposed that includes 

factors such as subject anthropometrics, locomotion speed, suit pressure, and suit weight. As more data 

are collected, this algorithm will be expanded into an EVA consumables calculator in which inputs on the 

subject, suit, and type and duration of tasks can predict a metabolic profile and the expected consumables 

usage. This algorithm is an example of a design tool that can help to develop suits that increase efficiency in 

crew health and performance based on different operational concepts. 

In addition to ambulation, the effect of varying suit weight and pressure has been examined across a variety 

of exploration-type tasks, such as shoveling and picking up rocks. Figure 14-4 describes the metabolic rate 

and GCPS ratings for six subjects averaged over three different tasks (i.e., shoveling, picking up and moving 

rocks, and a construction task busy board) as a function of 1g-equivalent suit weight. Both the objective and 

the subjective ratings show the same trends, which surprisingly indicate that a heavier suit weight is associated 

with better performance. The GCPS quantifies the suit operator compensation that is required for optimal task 

performance, which is defined as being equivalent to 1g shirt-sleeved (i.e., unsuited) performance. Ratings of 

1 to 3 indicate acceptable performance, 4 to 6 indicate that modifications are recommended for optimal performance, and 7 to 9 indicate that modifications are required; a rating of 10 indicates that the task cannot be 

performed under the current conditions. (See Appendix A for further explanation of the GCPS subjective 

assessment tool.) 

-7.0

-3.5

0.0

3.5

7.0

10.5

14.0

17.5

0 1 2 3 4 5 6 7 8 9 10 11

Speed (km/h)

Δ VO2 (ml·kg-1·min-1)

Intrasite 

Translation

Site to Site

Walkback 

63 kg

186 kg

247 kg

308 kg

121 kg Baseline

± 3.5 ml·kg-1·min-1

 Translation
Chapter 14 Human Health and Performance Risks of Space Exploration Missions 

340 Risk of Compromised EVA Performance and Crew Health 

Due to Inadequate EVA Suit Systems 

Figure 14-4. Effect of suit weight on metabolic rate and subjective GCPS ratings during exploration tasks. 

Biomechanical impacts of the suit are more difficult to differentiate; however, they may be critical to understanding skeletal muscle and bone loss in fractional gravity and for developing countermeasures against such 

losses. A key biomechanical finding relates to the GRF, which was higher in suited conditions than in unsuited 

conditions and also increased as suit weight increased. However, the GRFs were still lower than those that a crew 

member would normally experience on Earth. This suggests that EVA performance on the lunar surface may 

not provide sufficient loading to protect against bone loss, thus indicating the continued need for exercise 

countermeasures (Gernhardt et al., in preparation (a); in preparation (b)). 

Recognizing that not all ambulation on the moon will be similar to that on a level treadmill, EPSP personnel have initiated studies to characterize the effects of incline and terrain on metabolic rate. Inclined walking 

trials have shown that the metabolic cost of the suit that is due to factors other than suit weight goes to almost 

zero, indicating an energy recovery component of the suit that is currently not well understood (Gernhardt et 

al., in preparation (c)). 

Beyond the above stated parameters, the Apollo Program demonstrated that suit CG is an important variable 

that affects human performance. Recent studies have evaluated CG in the underwater environments at NEEMO 

and the NBL. These studies assessed crew performance of representative planetary exploration tasks using a 

single EVA suit weight with six different CG locations. A reconfigurable backpack that has repositionable 

weight modules was used to simulate perfect, low, forward, high, aft, and NASA baseline CG locations under 

the assumption of a 60-lb. suit, a 135-lb. Portable Life Support System (PLSS), and a reference 6-ft, 180-lb 

subject. Subjects used the GCPS rating tool to evaluate the CG locations. As shown in figure 14-5, subjects 

preferred (with lower GCPS score) the perfect, low, and forward CGs over the high, aft, or NASA baseline 

0

1

2

3

4

5

6

7

8

9

10

0 50 100 150 200 250 300 350

Metabolic Cost [L O2 per task)] or GCPS

1-g Equivalent Suit Weight (kgf)

Metabolic Cost

GCPS
Human Health and Performance Risks 

(Crew and Thermal Systems Div

findings suggest that a conventio

should be considered (Jadwick e

Figure 14-5. GCPS ratings for

 Risks to crew performan

biomedical monitoring a

 Overview 

The physiologic cost of performin

the same work without a suit. Hi

in turn, increase the usage rate of

and consumables is critical. Fligh

to overheating or exhaustion, and

to conserve consumables that are

1975). 

 Space Flight Evidence 

Energy expenditure (metabolic ra

clear that, in several cases, the as

gas-cooled life support system (W

astronaut Ed White found that op

he perspired enough to fog the h

hours for White to return to therm

of Space Exploration Missions

Risk of Compromised EVA Performance and Crew 

Due to Inadequate EVA Suit Sy

vision (CTSD)) CGs (both high and aft, similar to the Apo

onal backpack PLSS may not be optimal and that alternati

et al., 2008). 

r suit center of gravity.

nce, health, and safety: extravehicular activit

and consumables management 

ng work in a pressure garment is significantly greater than t

igh workloads result in energy expenditure and the produc

f suit consumables. Accordingly, monitoring of crew phy

ht surgeons must ensure that an astronaut is not working at

d EVA planners must be able to make real-time adjustmen

e required for life support (Waligora and Horrigan, 1975; 

ate) was not measured during the Project Gemini EVAs. It

stronauts worked at levels that were above the heat remov

Waligora and Horrigan, 1975; Kelley et al., 1968). During

pening and closing the hatch was much more difficult than

elmet visor. Although the duration of the EVA was short,

mal equilibrium. 

C

TSD 

Chapter 14 

Health 

ystems 341

ollo suit CG). These 

ive configurations 

y 

that of performing 

ction of heat, which, 

siologic parameters 

t levels that may lead 

nts to crew activity 

Waligora et al., 

t was nonetheless 

val capability of the 

g the first U.S. EVA, 

n planned and that 

, it took several 
Chapter 14 Human Health and Performance Risks of Space Exploration Missions 

342 Risk of Compromised EVA Performance and Crew Health 

Due to Inadequate EVA Suit Systems 

Thermal homeostasis of the crew member is crucial for safe and effective EVA performance. Heat storage 

above 480 Btu/hr leads to performance decrements, such as a loss of tracking skills and increased errors in 

judgment, and tissue damage begins at 800 Btu heat storage (Jones, 2007). The observations from the Gemini 

experience led to the development of a liquid cooling system that could accommodate high heat production in 

the suit from high EVA workloads. This liquid cooling garment (LCG) consists of a system of plastic cooling 

tubes that run along the inside of an undergarment that is worn inside the suit. The temperature of the coolant 

(water) running through the tubes regulates the amount of heat that is removed from the surface of the skin. 

The Apollo LCG had three temperature settings: minimum (69.8°F/21°C), intermediate (59°F/15°C), and 

maximum (44.6°F/7°C) (Waligora et al., 1975). 

Astronaut energy expenditure rates during Apollo lunar surface EVAs ranged from 780 to 1,200 Btu/hr, as 

determined by three independent methods (Waligora et al., 1975). The lowest metabolic rates occurred while 

the astronauts drove and rode in the lunar rover vehicle, while the highest metabolic rates were observed during egress/ingress through the tight-fitting hatch of the lunar module, offloading and setup of equipment, drilling, 

and stowage of lunar samples. It is estimated that 60% to 80% of the heat that was generated with these workloads was dissipated through the LCG. The minimum and intermediate LCG settings were most commonly 

used; however, the maximum setting was frequently used during the high workload periods that were experienced during Apollo 15 and Apollo 17 EVAs (Waligora and Horrigan, 1975). In a simulation (figure 14-6) 

using a validated thermoregulatory model (41 Node Metabolic Man; Pisacane, et al., 2007), the relationship 

between heat storage and metabolic rate was examined as a function of LCG inlet temperature (tracings, showing 21°C (69.8°F) and 24°C(75.2°F)) (Kuznetz, 2004). These data suggest that at metabolic rates above 

~1,200 Btu/hr, LCG inlet temperatures exceeding 21°C (69.8°F) may induce crew member heat storage rates 

above the 480 Btu/hr that lead to performance impairment. Although Apollo metabolic rates rarely exceeded 

1,200 Btu/hr and the LCG inlet temperature minimal setting was 21°C (69.8°F), these data are instructive for 

the design of future lunar EVA suits, which may be used in situations in which crew metabolic rates exceed 

levels seen during Apollo. 

It is important to note that although the metabolic rates experienced during the Apollo EVAs were lower than 

had been predicted before the missions, there were several cases in which the PLSS consumables were nearly 

depleted, according to the Summary of Apollo G Mission Lunar Surface EMU Post Flight Thermal Analysis 

-500

0

500

1000

1500

0 1000 2000 3000

Metabolic Rate (Btu/hr)

Heat Storage (Btu)

24° C

Performance Impaired 21° C

480 Btu Heat Storage

-500

0

500

1000

1500

0 1000 2000 3000

Metabolic Rate (Btu/hr)

Heat Storage (Btu)

-500

0

500

1000

1500

0 1000 2000 3000

Metabolic Rate (Btu/hr)

Heat Storage (Btu)

24° C

Performance Impaired 21° C

480 Btu Heat Storage

Figure 14-6. Heat storage based on metabolic rate and LCG inlet 

water temperature. 
Human Health and Performance Risks of Space Exploration Missions Chapter 14 

Risk of Compromised EVA Performance and Crew Health 

Due to Inadequate EVA Suit Systems 343

Results, Table E1 (MOD, unpublished internal report). During Apollo 14, Apollo 15, and Apollo 17, there 

were six cases in which less than 10% usable oxygen remained at the end of the EVAs. During Apollo 14, 

Apollo 16, and Apollo 17, there were seven cases in which 12% or less power remained (in one case, power 

was at < 4%), and four cases in which 11% or less usable feed water remained. Two crew members, on 

Apollo 15 and Apollo 16, completed their EVAs with only 4% and 2% remaining, respectively, of their 

CO2 removal capability (lithium hydroxide (LiOH)). 

Although each of the Apollo missions was limited to two or three EVAs, future lunar missions are expected 

to consist of three EVAs per week for up to 6 months. The increased number and frequency of exploration 

EVAs, coupled with labor-intensive construction and exploration tasks, will require a better understanding of 

energy requirements, heat dissipation technologies, and consumables management. 

Nutrition, hydration, and waste management

The longer and work-intensive EVAs that are planned for future Exploration missions will also need to 

account for astronaut nutrition, hydration, and waste management. Specifically, dehydration is an issue that 

can lead to poor crew performance. The Apollo suit had a 15-oz drink bag; however, this amount of fluid is 

considered insufficient for crews that are performing surface EVA. Scheuring et al. (2007) provide several 

citations regarding the need for more water. As the authors write: “The astronauts strongly agreed the 

amount of liquid beverage contained in the suit needed to be increased for future crewmembers, including 

separate capabilities for plain water and non-caffeinated high-energy drink.” 

The delivery systems for nutrition and hydration need to be improved as well. One Apollo astronaut 

commented: “The fruit bar mounted inside the suit was sometimes problematic because you couldn’t 

always get to it, but it’s nice to have something solid to eat” (Scheuring et al., 2007). Similar issues have 

been reported with the current EVA suit, used for microgravity EVA in the Space Shuttle and ISS Programs. 

Furthermore, the time that is required to prepare the nutrition and hydration systems prior to conducting an 

EVA must be decreased. Filling and degassing the drink bag that is used in the current U.S. suit is timeconsuming and contributes to the poor work efficiency index (WEI) of shuttle and ISS EVAs. 

Additionally, the development of an improved in-suit urine collection device was recommended by the 

Apollo astronauts. In some cases during lunar surface EVAs, astronaut urine was not fully contained and 

resulted in skin irritation (Scheuring et al., 2007). Improved in-suit waste management systems will become 

critical in the event a crew is required to be suited for as many as 152 hours during a contingency return to 

Earth should the vehicle be unable to maintain pressure. Exposure to urine and fecal waste products for that 

length of time may lead to skin breakdown, cellulitis, and sepsis. 

Biomedical monitoring

Flight surgeons and biomedical engineers (BMEs) in the Mission Control Center monitor astronaut 

physical parameters during EVAs to assess workload and performance. Real-time medical monitoring can 

provide emergency medical assistance in response to off-nominal situations. However, bioinstrumentation 

systems that were used in the Apollo Program and are being used in the Space Shuttle Program have been 

problematic. Scheuring et al. (2007) provide approximately 75 citations from the flight surgeon logs, BME 

logs, and medical mission debriefings that relate to issues associated with bioinstrumentation. These range 

from complaints of skin irritation due to the electrode paste to signal dropouts and sensor failure (Scheuring 

et al., 2007). Both Apollo and shuttle/ISS EVA crew members have expressed frustration with the cumbersome and time-consuming process of donning/doffing their biomedical sensor systems. Improvements 

to the biomedical sensor systems for future missions are therefore warranted. 
Chapter 14 Human Health and Performance Risks of Space Exploration Missions 

344 Risk of Compromised EVA Performance and Crew Health 

Due to Inadequate EVA Suit Systems 

 Ground-based Evidence 

At the request of the Constellation EVA Systems Project Office (formerly known as the Advanced EVA 

Office) management, a study was conducted to determine whether it is possible for a suited crew member to 

walk back to a terrestrial habitat in the event of a failed rover. As a starting point that is based on the Apollo 

Program and anticipated lunar surface operational concepts, it was assumed that 10 km (6.2 miles) would be 

the maximum EVA excursion distance from the lander or habitat. Results from this EVA Walkback Test 

(EWT) using the Pogo provide key insight into how human performance may be impaired by inadequate 

consumables and/or inadequate cooling. 

For the EWT, six suited subjects were instructed to attempt to translate 10 km on a level treadmill at a rapid, 

but sustainable, pace using a self-selected gait strategy and speed. Prior to this test, the investigators expected 

that crew members could only complete half of that distance or that the total duration would exceed 3 hours. 

However, all of the crew members finished the test, and the mean time to complete 10 km was only 96 minutes. 

The metabolic work level for the entire test averaged 51% of VO2pk [volume of oxygen consumption, peak], 

with a range of 45% to 61%. Physiological and consumables usage data are summarized in Table 14-1. RPEs 

(11.8 ± 1.57 (SD)) equated to a feeling between “light” (RPE=11) and “somewhat hard” (RPE=13) on the 6- 

to 20-point Borg RPE scale, which is used to gauge how much effort a person feels that he or she must exert 

to perform a task. Similarly, subjects averaged 3.5 ± 1.44 (SD) on the 10-point GCPS, indicating “fair” to 

“moderate” operator compensation was required to perform the task (Gernhardt et al., in preparation (b)). 

Table 14-1. Summary Data for the Lunar 10-km Walkback Portion of the Test

10k Walkback Summary Data 

(averaged across enter 10 km unless noted) 

Mean SD 

Avg Walkback Velocity (mph) 3.9 0.5 

Time to Complete 10 km (min) 95.8 13.0 

Avg %VO2pk 50.8% 0.3% 

Avg Absolute VO2 (1/min) 2.0 0.3 

Avg Metabolic Rate (Btu/hr) 2,374.0 303.9 

Max. 15-min-avg Metabolic Rate (Btu/hr) 2,617.2 314.6 

Total Energy Expenditure (kcal) 944.2 70.5 

Water used for drinking (oz) ~24–32 N/A 

*Water used for cooling (lb.) 4.91 N/A 

Oxygen Used (lb) 0.635 N/A 

Planning/PLSS Sizing Data Walkback Apollo 

Oxygen Usage (lb/hr) 0.4 0.15 

Btu Average (Btu/hr) 2,374 932.8 

Cooling Water (lb/hr) 3.1 0.98 

Energy Expenditure (kcal/hr) 599 233 

*Assumes thermally neutral case and sublimator cooling 

Subjects’ heat production rates ranged from 1,918 to 2,667 Btu/hour, and averaged 2,374 Btu/hour, a 

rate that would exceed the heat removal rates of the Apollo or space shuttle EVA suits. Core temperature 

measurements indicated an average rise (Δ) of 33.8°F/1°C from normal (98.6°F/37°C) across the entire test, 

although one subject’s core temperature (103.6°F/39.8°C) peaked near a level of concern. Subjects unanimously reported cooling to be inadequate at the higher workloads (Gernhardt et al., in preparation (b)). 
Human Health and Performance Risks of Space Exploration Missions Chapter 14 

Risk of Compromised EVA Performance and Crew Health 

Due to Inadequate EVA Suit Systems 345

This limited cooling capacity will impede the improved efficiency that was observed at higher speeds. Efficiency of locomotion can be determined by the transport cost, which is expressed as oxygen consumption 

per kilogram per kilometer, and can be thought of as a human’s “gas mileage.” In suited conditions in lunar 

gravity, there was a clear trend of decreasing transport cost as speed increased. So while a crew member 

might expend more energy on a per-minute basis by traveling at faster speeds, the metabolic cost per 

kilometer would actually be less (Gernhardt et al., in preparation (b)). 

Unfortunately, at speeds above 3 mph (figure 14-7) the heat production, which is shown on the right axis 

and the red tracing, begins to exceed the 2,000 Btu/hr cooling limit of both the Apollo and the shuttle EVA 

suits, resulting in increased core body heat storage. Without improvements in cooling for future suits, crew 

members performing lunar EVAs would not be able to exploit the increased efficiency (figure 14-7, on the 

blue tracing as decreasing oxygen transport cost) available at faster ambulation speeds. This would result in 

increased consumable requirements to cover the same distance (Gernhardt et al., in preparation (b)). 

Figure 14-7. Relationship between transport cost and heat production for lunar 

suited ambulation. 

While life support consumables are an important consideration for EVA excursions, the 10-km Walkback 

also provided important insight into hydration and nutritional requirements for a task of similar duration or 

intensity. All subjects were provided with 32 oz of water in an in-suit drink bag, standard for use of the MKIII 

suit. Crew members consumed 50% to 100% of the water that was provided, and one crew member would 

have preferred to have an additional 20% of that volume available. In addition, the 10-km Walkback required 

an average of 944 kcal. All of the crew members felt that a nutritional item, either food (e.g., an energy bar or 

a gel) or a flavored electrolyte drink might improve their performance and/or endurance (Gernhardt et al., in 

preparation (b)). These observations were in accordance with the Apollo recommendations cited above. 
Chapter 14 Human Health and Performance Risks of Space Exploration Missions 

346 Risk of Compromised EVA Performance and Crew Health 

Due to Inadequate EVA Suit Systems 

Because the EWT was limited to 10 km on a level treadmill, additional studies were performed to understand how a more realistic simulation would affect the results. Factors such as incline/decline, lunar-like 

terrain, and real-time navigation will all contribute to the performance of a 10-km traverse. Results of these 

Pogo tests have indicated that inclined ambulation does increase metabolic rate, but at a rate that is much less 

than experienced in the 1g environment. To classify the effect of lunar terrain and navigation of human performance, subjects completed a series of 10-km traverses at the HMP site, which is an international interdisciplinary field research project centered on scientific study of the Haughton impact crater and surrounding 

terrain on Devon Island, Canada. The rocky polar desert setting and geologic features provide a good analog 

of the lunar surface for EVA translation and navigation studies. At HMP, unsuited subjects began at a location that was 10 km from the finish point and were instructed to return at a rapid, but sustainable, pace using 

a global positioning satellite (GPS) receiver for navigation and tracking speed and grade. Three separate 

starting points, each equidistant from the finish point, were defined, and the subjects completed each route 

once. The straight-line distance between starting and ending points was 9.91±0.22 km/6.16 ± 0.14 miles 

(mean ± SD), and the actual distance traveled was 10.61±0.61 km/6.59 ± 0.38 miles. Completion time 

averaged 126.5 ± 28.7 min, which was longer that the EWT average of 95.8 ± 13.0 min (Norcross et 

al., 2008). 

Comparison between these field tests and speed/grade matched treadmill controls has provided a crude 

correction factor for terrain, suggesting that metabolic rates in the actual environment were an average of 

56% higher than in controlled treadmill conditions. Further studies are needed to understand whether this 

increase would be as high in lunar gravity (Norcross et al., 2008). 

 Risks to crew health: extravehicular activity suit design parameters 

 Space Flight Evidence 

A comprehensive analysis was recently completed of all musculoskeletal injuries and minor trauma sustained 

in flight throughout the U.S. space program (Scheuring et al., 2009). This study identified 219 in-flight injuries, 

of which 50 resulted from wearing the EVA suit, making this the second leading cause of in-flight injuries. 

The incidence rate of EVA injuries was 0.05 per hour for 1,087.8 hours of EVA activity. This equates to an 

incidence rate of 1.21 injuries per day, or 0.26 injuries per EVA. The following excerpts from this study are 

illustrative of the types of EVA-induced injury: 

“Hand injuries were most common among EVA crewmembers, often due to the increased 

force needed to move pressurized, stiff gloves or repetitive motion for task completion. Many 

astronauts described the gloves causing small blisters and pain across their metacarpophalangeal 

(MCP) joints. This could be due to dorsal displacement of the MCP joints against the glove in order 

to flex the fingers [Viegas et al., 2004]. While not mission impacting injuries, they can potentially distract an astronaut from important EVA tasks. Astronauts frequently develop onycholysis (separation of nail from nail bed) after Neutral Buoyancy Laboratory training sessions, and it 

is possible some of these injuries represent exacerbations of underlying ground-based injuries.” 

However, the authors later state that pre-flight conditions were not strong predisposing factors for these 

injuries. 

“Foot injuries also caused problems for EVA astronauts. One astronaut described an episode 

of ‘excruciating, searing, knife-like pain’ during an EVA. The astronaut attributed the pain to 

excess suit pressure bladder material inside the boot, but despite attempts at correcting the 
Human Health and Performance Risks of Space Exploration Missions Chapter 14 

Risk of Compromised EVA Performance and Crew Health 

Due to Inadequate EVA Suit Systems 347

problem, the pain persisted with the development of a blister...Though the EVA was completed 

successfully, the astronaut described the pain from this injury as ‘on the forefront of my mind’. 

Another astronaut had similar symptoms after his second EVA with resultant numbness and 

pain on the dorsum of his feet.” 

Pressure-associated erythema developed on the dorsal surfaces of each foot, and symptoms persisted 

throughout the mission and 2 to 3 weeks post-landing (Scheuring et al., 2009). 

Nine of the 219 in-flight injuries were sustained by Apollo astronauts who were performing lunar surface 

EVAs. One Apollo astronaut suffered a wrist laceration from the suit wrist ring while working with drilling 

equipment, and another crew member sustained wrist soreness due to the suit sleeve rubbing repeatedly. One 

crew member injured his shoulder during a lunar EVA while attempting to complete multiple surface activities on a tight mission timeline. Unbeknownst to his flight surgeon, this crew member later took large doses 

of aspirin to relieve the pain. Many Apollo astronauts noted problems with their hands. One astronaut remarked: “EVA 1 was clearly the hardest ... particularly in the hands. Our fingers were very sore.” Another 

Apollo astronaut remarked that his hands were “very sore after each EVA”; while another astronaut stated 

that following the third lunar EVA, his MCP and proximal interphalangeal joints (knuckles) were so swollen 

and abraded from a poor-fitting glove and/or lack of inner liner or comfort glove that he is certain that a 

further EVA would have been very difficult if not impossible. Accordingly, it is no surprise that the Apollo 

astronauts were adamant that the glove flexibility, dexterity, and fit be improved (Scheuring et al., 2007). 

 Ground-based Evidence 

To adequately prepare for mission EVAs, astronauts undergo extensive ground-based training at 

the NBL, which provides controlled neutral buoyancy operations to simulate the zero-g or weightless 

condition. Articles are configured to be neutrally buoyant by using a combination of weights and flotation 

devices so these articles seem to “hover” under water, thus enabling large, neutrally buoyant items to be 

easily manipulated much as they would be in orbit. The significant increase in EVA NBL training to support 

the construction and maintenance of the ISS led to an apparent increase in the incidence of symptoms and 

injuries experienced by crew members operating in the EVA suit. 

A study that was conducted from July 2002 to January 2004 identified the frequency and incidence rates of 

symptoms by general body location and characterized the mechanisms of injury and effective countermeasures 

(Strauss, 2004). During this study, 86 astronaut-subjects were evaluated in the NBL during 770 suited test 

sessions. Symptoms were reported by the test subjects in 352, or 45.7%, of the sessions. Of these symptoms, 

47% involved hands; 21% involved shoulders; 11% involved feet; 6% each involved arms, legs, and neck; 

and 3% involved the trunk. Hand symptoms were primarily fingernail delamination, which was thought to be 

secondary to excess moisture in the EVA gloves and axial loading of the fingertips (figure 14-8). There were 

also abrasions, contusions, and two cases of peripheral nerve impingements related to glove fit and hard point 

contact compressions. Shoulder symptoms were due to hard contact with suit components (figure 14-8) and 

strain mechanisms. Elbows were the most common area of pain or injury in the arms, as were knees in the 

legs. While most of the symptoms and injuries sustained during EVA training were “mild, self-limited, and 

controlled by available countermeasures,” some “represented the potential for significant injury with shortand long-term consequences regarding astronaut health and interference with mission objectives.” (Strauss, 

2004) 

 
Chapter 14 Human Health and Performance Risks of Space Exploration Missions 

348 Risk of Compromised EVA Performance and Crew Health 

Due to Inadequate EVA Suit Systems 

Figure 14-8. Fingernail and shoulder trauma sustained during EVA training (Jones et al., 2006). 

A shoulder injury tiger team was created in December 2002 at NASA JSC to evaluate the possible relationship between shoulder injuries and EVA training at the NBL (Williams and Johnson, 2003). This team 

surveyed 22 astronauts who had participated in EVA training. In this group, 14 astronauts (64%) had experienced some degree of shoulder pain that they attributed to EVA training. A majority of these cases were classified as minor, resolving within 48 to 72 hours. However, two of the 14 subjects required surgical repair after 

injury. It was determined that the major risk factors leading to injury were: limited range of motion in the 

shoulder joint due to use of the “planar” hard upper torso (HUT) of the EVA suit, performing tasks in inverted 

body positions during NBL training, performance of overhead tasks, repetitive motions, the use of heavy tools, 

and frequent training sessions. Additional minor risk factors included suboptimal suit fit and lack of appropriate padding or load alleviation (Williams and Johnson, 2003; Jones et al., in review 2009). While the astronauttool-EMU simulation package may be neutrally buoyant as a whole, the astronaut is not weightless within the 

suit. In the inverted (head-down) position, gravity causes the astronaut to “fall into” the head of the spacesuit, 

pressing the shoulders into the HUT of the suit. This further limits the scapulothoracic motion of the shoulder 

(Viegas et al., 2004). Key elements in the risk mitigation of shoulder injuries that are associated with EVA 

training include redesign of the EMU shoulder joint or development of the next-generation suit for ISS EVA, 

reduction of high-risk NBL activities, optimization of suit fit, and continued emphasis on physical conditioning (Williams and Johnson, 2003). 

During the 10-km EWT, subject discomfort levels were recorded, and a medical monitor examined the subjects for signs of suit-induced trauma at the completion of the test. In terms of discomfort, the mean rating was 

1.5  1.1 (SD), which is “very low” to “low” on the 10-point discomfort scale. The knee area and the feet/toes 

were the most frequent sites of discomfort during and after the test (figure 14-9). Fatigue and/or muscular tightness were reported most commonly in the quadriceps, thighs, gluteal muscles, and lower back (Gernhardt et 

al., in preparation (b)). 
Human Health and Performance Risks of Space Exploration Missions Chapter 14 

Risk of Compromised EVA Performance and Crew Health 

Due to Inadequate EVA Suit Systems 349

Figure 14-9. Knee and foot trauma sustained during 10-km EWT. 

 Risks to crew health: decompression sickness 

 Overview 

Decompression sickness represents a risk to the successful performance of EVAs as well as to the health 

and safety of the astronauts. Type I (pain-only) DCS symptoms can range from awareness in a joint or muscle 

to pain in which the performance of a task is affected. Symptoms of Type II (serious) DCS can include confusion, memory loss, headache, impaired vision, extreme fatigue, seizures, vomiting, shortness of breath, 

unconsciousness, paralysis, and, ultimately, death. 

The risk of developing DCS is decreased by performing an oxygen pre-breathe to reduce the amount of 

inert gas (usually nitrogen) in the blood and tissues before a crew member is subjected to decompression in 

the spacesuit. Many factors influence the required duration of the pre-breathe protocol. During the Apollo 

missions, the environment inside the lunar module was 34.5 kPa (5.0 psia) and 100% oxygen. The absence of 

inert gas in the environment meant that pre-breathe was unnecessary to reduce DCS risk. However, concerns 

over flammability mean that Orion, Altair, and any surface assets during future lunar exploration will likely 

operate at 101 kPa (14.7 psia) and 20.8% oxygen; 70.3 kPa (10.2 psia) and 26.5% oxygen; and/or 55.2 kPa 

(8.0 psia) and 32% oxygen with the balance nitrogen. In any of these environments, the partial pressure of 

nitrogen will require some amount of oxygen pre-breathe prior to a crew member performing an EVA at 

29.6 kPa (4.3 psia) to reduce the amount of inert gas that is dissolved in that crew member’s blood and 

tissues. 

The risk of DCS during EVAs performed during CxP missions will be quantified and mitigated using the 

same combination of mathematical decompression stress modeling, statistical analysis of relevant groundbased and space flight data, expert judgment, and rigorous validation of pre-breathe protocols using prospective ground-based hypobaric EVA simulation studies. Through this process, pre-breathe protocols will be 

developed that will reduce the DCS risk to within acceptable limits while minimizing the impact on crew 

work efficiency. 

Protocols are designed to reduce the risk of DCS to within acceptable limits. The NASA DCS Risk Definition 

and Contingency Plan (1998) criteria specify acceptable limits as a total incidence of DCS ≤ 15% at a 95% 

CL, with < 20% Grade IV venous gas emboli (VGE) and 95% CL, and no Type II (serious) instances of DCS. 
Chapter 14 Human Health and Performance Risks of Space Exploration Missions 

350 Risk of Compromised EVA Performance and Crew Health 

Due to Inadequate EVA Suit Systems 

The 1/6g environment, the increased time to return to Earth in the event of serious DCS, and the more frequent EVAs planned for lunar surface missions may necessitate the development of new limits of acceptability for DCS risk for these missions. 

Pre-breathe protocols are typically developed by experts using models of decompression stress and by 

considering relevant data from past experiences in ground-based studies and space flight. Before they are 

implemented in space flight, pre-breathe protocols are typically tested in ground-based hypobaric chamber 

EVA simulation studies to verify that the observed incidence of DCS and VGE are indeed within the agreedto acceptable limits. Analysis of the ground-based data using Bayesian statistical methods ensures that a prebreathe protocol is approved for use in space flight only when the incidence of DCS and VGE are within 

acceptable limits and the level of confidence in the estimate of true DCS and VGE risk is 95% or greater. 

 Space Flight Evidence 

Two different spacesuits are currently used to perform EVAs from the ISS: the Russian Orlan and the U.S. 

EMU. Differences in operating pressures between the U.S. and Russian spacesuits have led to different EVA 

preparations. The Russian Orlan spacesuit system operates at 40.0 kPa (5.8 psia). By contrast, the U.S. EMU 

system operates at 29.6 kPa (4.3 psia) of oxygen, with traces of CO2 and water vapor. 

The Russian EVA preparation protocol includes a 30-minute oxygen pre-breathe in the Orlan spacesuit at a 

pressure of 73 kPa (10.6 psia) to partially wash out nitrogen from crew members’ blood and tissues (Barer and 

Filipenkov, 1994). Literature from the Russian program shows that of approximately 114 EVAs that had been 

performed in the Russian spacesuit, including 18 EVAs from the ISS, crew members showed no signs of DCS 

(Malkin, 1994; Davis et al., 1977; Fulton, 1951). 

Three different pre-breathe protocols may be used before performing an EVA in the U.S. EMU: an exercise 

pre-breathe, a 4-hour in-suit pre-breathe, or a campout pre-breathe. The protocols vary in effectiveness and, 

hence, in risk of DCS. Selection of a particular method depends on the particulars of the EVA, including the 

DCS risk, the timeline, and the operational risk. However, no symptoms of DCS have been reported to date 

by astronauts who have performed EVAs in the EMU spacesuits following any of the three pre-breathe 

protocols (Horrigan et al., 1997; Waligora and Pepper, 1995). 

 Ground-based Evidence 

According to ground-based studies of the U.S. pre-breathe protocols, exercise pre-breathe is the method that 

has the lowest predicted risk of DCS. It has been tested extensively under laboratory conditions and meets the 

NASA DCS Risk Definition and Contingency Plan (1998) criteria of a total incidence of DCS ≤ 15% at a 

95% CL, with < 20% Grade IV VGE and 95% CL, and no Type II (serious) instances of DCS. 

The 4-hour in-suit pre-breathe protocol resulted from many years of experience with 4-hour in-suit pre-breathe 

testing. This was primarily gained from ground testing of suited subjects and crew members in preparation for 

altitude chamber runs. More than 300 such exposures have been completed with < 1.5% instances of DCS observed, with no Type II DCS. However this method has not been subjected to the same level of controlled 

laboratory evaluation as the exercise pre-breathe method. 

When simulating U.S. pre-breathe protocols in ground-based studies using volunteers wearing regular 

clothing, the rate at which DCS symptoms developed was 17% to 26%. Given these data and the lack of any 

observed DCS symptoms during space flight using the same protocols, the conclusion can be drawn that the 
Human Health and Performance Risks of Space Exploration Missions Chapter 14 

Risk of Compromised EVA Performance and Crew Health 

Due to Inadequate EVA Suit Systems 351

risk of DCS occurring in actual weightless EVA conditions is significantly lower compared to ground simulation. Russian physiologists explain this by citing the inhibiting effect of the spacesuit and microgravity on 

nucleation mechanisms in human tissues. The hard shell of the spacesuit prevents a crew member from making 

abrupt movements during an EVA, thus decreasing amplitude/speed characteristics, lowering the intensity of 

cavitations, and lessening the possibility of developing gas bubbles in tissues. Moreover, removing the mass 

load and decreasing the muscular exertion when performing static or dynamic tasks in microgravity decreases 

the number of pre-EVA gas bubble formations. The effect of these factors leads to a decrease in the intensity 

of and the rate at which pathogenic gas bubbles develop in the body as a causative agent of DCS (Conkin et 

al., 1987; Kumar et al., 1993; Powell et al., 1993). 

 Ground-based Simulation Information 

A physics-based tissue bubble dynamics model (TBDM) will be used in the development of pre-breathe 

protocols. The TBDM provides a time-varying index of theoretical physiological decompression stress, 

referred to as a Bubble Growth Index (BGI), which is based on variations in pressure and gas composition 

(Gernhardt, 1991). BGI is defined as the radius of a theoretical gas bubble, r, divided by the initial radius of 

the bubble. The TBDM models the rate of change of bubble radius (dr/dt) according to Equation 1. Thus, the 

predicted decompression stress (BGI) at time t can be calculated throughout the entire time course of any 

decompression profile. 

 (1) 

where: 

r = bubble radius (cm) 

t = time (sec) 

α = gas solubility ((mL gas)/(mL tissue)) 

D = diffusion coefficient (cm2

/sec) 

h(r,t) = bubble film thickness (cm) 

Pa = initial ambient pressure (dyne/cm2

) 

v = ascent/descent rate (dyne/cm2

cm3) 

 = surface tension (dyne/cm) 

M = tissue modulus of deformability (dyne/cm2

cm3) 

PTotal = total inert gas tissue tension (dyne/cm2

) 

Pmetabolic = total metabolic gas tissue tension

The TBDM’s index of decompression stress, BGI, can be quantitatively related to the percentage of DCS risk 

using a logistic regression model. Previous analysis has shown the TBDM to provide good prediction of DCS 

risk (Gernhardt, 1991). For example, a logistic regression was performed using DCS and VGE data from 

NASA Bends Tests 1–7 (n=345, 57 DCS cases, 16.5% DCS, 41.4% VGE). Data that were derived from the 

pre-breathe staged decompressions, all with exercise at altitude, included data points at 70.3, 41.3, and 29.6 

kPa (10.2, 6.0, and 4.3 psia), and did not include adynamic or exercise pre-breathe data. BGI provided signifi4 Pa – vt + 3r

+ r

3 M dt

dr =

Pa – vt + 

r

2

3

4

r

3 M – PTotal – Pmetabolic + 3

rv

+

D

h(r,t)

3

4 8 Pa – vt + 3r

+ r

3 M 4 Pa – vt + 3r

+ r Pa – vt + 3 M 3r+ r

3 M dt

dr =

Pa – vt + 

r

2

3

4

r

3 M – PTotal – Pmetabolic + 3

rv

+

D

h(r,t)

3

8
Chapter 14 Human Health and Performance Risks of Space Exploration Missions 

352 Risk of Compromised EVA Performance and Crew Health 

Due to Inadequate EVA Suit Systems 

cant prediction of DCS and VGE data (p < 0.01). The Hosmer-Lemeshow Goodness-of-Fit statistic: p=.35 for 

DCS, p=.55 for VGE, indicates a good fit of the data (Abercromby, 2008). (Note: For the Hosmer-Lemeshow 

statistic, p >.05 rejects the hypothesis that there is a significant difference between the model predictions and 

the observed data.) A 360-minute half-time compartment was assumed. 

 Conclusion 

The combination of space flight and ground-based experience points to a high degree of safety in both 

approaches being used to mitigate the risk of DCS. The U.S. approach to DCS risk management enables 

greater crew mobility than does the Russian approach due to lower pressure in the EMU spacesuit; however, 

the simpler and shorter Russian protocol is preferable in terms of work efficiency. Over time, these prebreathe protocols will need to be streamlined to optimize both crew mobility and work efficiency. 

 Risks to work efficiency: extravehicular activity suit design parameters 

The total WEI is defined as 

 EVA Time .

(Total suit and airlock prep + pre-breathe + airlock depress, repress + post EVA) 

The current NASA EVA total WEI is 0.39 to 0.51. Constellation EVA Systems Project documentation contains requirements stating that EVA WEI shall be 3.0. Many factors contribute to WEI, including vehicle systems, 

suit systems, and operational procedures. Future EPSP studies will evaluate WEI based on current knowledge 

and concepts of operations, and will provide data to make recommendations to improve WEI. These studies will 

include: (1) an evaluation of suit components that may improve WEI (e.g., integrated biosensor systems that are 

quick don/doff; drink bags that require less preparation time); (2) development of improved pre-breathe protocols; (3) studies in lunar analogs that will evaluate the efficiency of different mission operations concepts and 

measure the trends in WEI over time; and (4) an evaluation of suit prototypes and the development of operational concepts to meet WEI requirements. 

 Computer-based Simulation Information 

Computer-based simulation data are discussed above in the Decompression Sickness section. 

 Risk in Context of Exploration Mission Operational Scenarios 

Extravehicular activity is a critical factor in the success of the construction, maintenance, scientific, and 

exploration aspects of every lunar architecture concept being considered by the CxAT-Lunar team. Current 

plans call for each crew member to perform up to 24 hours of EVA per week for missions lasting up to 6 months. 

This corresponds to as many as 624 hours of EVA per crew member in a single mission. As described in the Evidence section of this chapter, the risks that are associated with any inadequacies that exist in current EVA suit 

designs – particularly with respect to suit-induced trauma – will be greatly amplified by such frequent EVAs. 

Current CxAT-Lunar mission architectures include small pressurized rovers (SPRs) as a core element of the 

surface mobility system. The implications of SPRs on crew health, safety, productivity, and efficiency are potentially enormous. The availability of a pressurized safe-haven within 20 minutes at all times to provide DCS 
Human Health and Performance Risks of Space Exploration Missions Chapter 14 

Risk of Compromised EVA Performance and Crew Health 

Due to Inadequate EVA Suit Systems 353

treatment, SPE protection, and on-site treatment of or medication for an injured crew member would significantly reduce many of the risks associated with planetary exploration. Furthermore, because crew members 

would be inside the SPRs during most surface translations, the overall number of in-suit EVA hours to achieve 

the same (or greater) science/exploration return would be reduced. The possibility of performing single-person 

EVAs with a second crew member inside the SPR would further reduce total EVA hours during the lunar architecture to the same order of magnitude as during ISS construction. As a result, the number of cycles on the EVA 

suits would be decreased, thereby increasing the life of each EVA suit and reducing EVA risk for crew members. 

 Conclusion 

The CxP will be more dependent on EVA excursions away from a pressurized habitat or vehicle than any 

program in the history of NASA. EVAs will be required to conduct planned scientific expeditions, assemble 

structures, perform nominal maintenance, and intervene and solve problems outside of the vehicle that cannot 

be solved either robotically or remotely. The ultimate success of future Exploration missions is dependent on 

the ability to perform EVA tasks efficiently and safely in these challenging environments. 

With lunar missions planned for up to 30 times more EVA hours than during the Apollo era, exploration 

missions to the moon and Mars will present many new challenges with regard to crew health, safety, and 

performance. To date, our understanding of human health and performance parameters in partial-gravity environments is limited to observations of, and lessons learned from, Apollo-era astronauts who performed EVAs 

on the lunar surface. Since the Apollo Program, and using lessons learned from microgravity EVAs aboard the 

space shuttle and ISS, new prototype suits have been in development for future space exploration activities. However, to date there has been limited quantification of the physiological and biomechanical variables associated 

with suited activities in unit and partial gravity. The integrated human testing program that is under way at 

NASA will help to better characterize the impacts to crew health and performance of the various parameters 

that are involved in EVA suit design. 

Collaborative work is also under way to enable the development of suit technologies that enhance crew comfort 

and efficiency; provide for optimal nutrition, hydration, and waste management; and reduce suit-induced trauma 

and fatigue. These efforts will provide objective data to enable informed requirements and the design of Constellation suit systems that will provide sufficient protection and life support for nominal zero-G and surface 

activities, as well as survival for contingency operations. 

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Biomedical results of Apollo. (1975) SP-368. NASA Headquarters, Washington, D.C. 

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 Acknowledgments 

The following individuals contributed to the preparation of this report: 

Johnny Conkin, Ph.D.; Senior Scientist; Universities Space Research Association; Houston. 

Nancy House, B.S.; NASA Constellation Program; Stinger Ghaffarian Technologies, Inc.; Houston. 

Jennifer Jadwick, B.S.; Bioastronautics Contract Project Coordinator, EVA Physiology, Systems and 

Performance Project; Wyle Integrated Science and Engineering Group; Houston. 

Lawrence H. Kuznetz, Ph.D.; Senior Scientist, Thermal Systems lead, EVA Physiology, Systems and 

Performance Project; Universities Space Research Association; Houston. 

Lesley R. Lee, M.S.; Bioastronautics Contract Project Scientist, EVA Physiology, Systems and Performance 

Project; Wyle Integrated Science and Engineering Group; Houston. 
Human Health and Performance Risks of Space Exploration Missions Chapter 14 

Risk of Compromised EVA Performance and Crew Health 

Due to Inadequate EVA Suit Systems 357

 Appendix A: Gravity Compensation and Performance Scale24

The Cooper-Harper scale, which has been in wide use since the late 1960s, permits quantification of pilot 

perceptions of aircraft handling characteristics. Most of the participants in EPSP studies are astronauts, many 

of whom are pilots and familiar with the use of this scale; however, the scale itself assumes a certain level of 

consistency in both pilot skills and specifications of the desired aircraft performance. In the development of 

next-generation EVA suits for Exploration missions, NASA requires controlled evaluations of varied suit 

concepts across an ambitious range of activities. These evaluations must be performed by astronauts or test 

subjects whose skills are limited to microgravity and/or simulated partial-gravity environments – far from 

equivalent to the skilled pilot population for whom the Cooper-Harper scale was originally designed. 

EVA suit development for lunar and martian surface operations will require a wide range of evaluations 

encompassing tasks as varied as habitat building, traversing rocky terrain, core sampling, shoveling, and, 

potentially, rescuing an incapacitated crew member. In addition, suit concepts vary widely in mass, weight, 

CG, and pressure, and each must be evaluated across this range of tasks. NASA does not currently have rigorous 

performance measures for such tasks, and the EPSP Project personnel have begun the process of characterizing 

human-suit system performance under a variety of conditions and suit concepts using available analog facilities. 

Due to the many limitations of using the Cooper-Harper scale under these circumstances, scientists in the EPSP 

Project adapted the Cooper-Harper scale to reflect handling/controllability characteristics of task performance in 

reduced-gravity environments when compared relative to one’s own shirt-sleeved performance of the same task 

in 1g. This modified scale, the GCPS, is shown on the following page. Using this scale, a rating of 2 during a 

suited experimental trial is perceived by the subject to be equivalent to his/her unsuited performance of the 

same task in 1g, thereby providing a quantitative rating of desired task performance in the suit. 

As an example, a subject who is performing a shoveling task while wearing a suit that has a high-and-aft CG 

may rate the task performance as a 5 because the selected CG setting requires considerable effort/compensation 

compared to performing the same task unsuited with nominal CG. This new tool is useful for comparing multiple subjects’ ratings of operator compensation that is required to perform a variety of simulated surface 

exploration tasks across a wide range of suit concepts, configurations, and gravity levels. 

 

24Modified from the Cooper-Harper scale. 
Chapter 14 Human Health and Performance Risks of Space Exploration Missions 

358 Risk of Compromised EVA Performance and Crew Health 

Due to Inadequate EVA Suit Systems 

GRAVITY COMPENSATION AND PERFORMANCE SCALE (GCPS) 

CONTROL
Risk of Operational Impact of Prolonged Daily Required Exercise 359

Chapter 15: 

Risk of Operational Impact of Prolonged 

Daily Required Exercise 

Jancy C. McPhee 

Universities Space Research Association 

John B. Charles

NASA Johnson Space Center 

Muscle atrophies in microgravity and strength decreases. Currently, significant daily time is scheduled to 

crew exercise. Making the exercise more efficient may allow similar beneficial effects to be achieved more 

simply, and in shorter time, which would provide more crew time for operational support. Benchmarking crew 

strength requirements, and testing exercise equipment and regimens against these benchmarks, will 

promote the development of more efficient, yet equally safe, exercise regimens. – Human Research Program 

Requirements Document, HRP-47052, Rev. C, dated Jan 2009. 

 Exercise is performed in space to promote musculoskeletal, cardiovascular, and psychological health. Research efforts seek to optimize exercise hardware, prescriptions, and physiological performance targets to support the 

provision of activities promoting health and fitness without 

compromising crew time or operations. 
360 Risk of Operational Impact of Prolonged Daily Required Exercise 
Human Health and Performance Risks of Space Exploration Missions Chapter 15 

Risk of Operational Impact of Prolonged Daily Required Exercise 361

 Executive Summary 

After the submission of the risk Evidence Reports to the IOM for review in 2008, the program determined 

that the tasks that are within this risk were already covered by the HRP Program Requirements Document 

(PRD) Requirement 6.4. In Revision C of the PRD, therefore, the requirement was rewritten to better express 

this fact: “Each HRP research element must focus the research on producing countermeasures and technologies 

that fit within the extremely limited resource envelopes anticipated for the exploration mission. An example is 

the reduction in time dedicated to exercise prescriptions. Present exercise prescriptions present a large burden on 

the overall mission timeline.” In addition, the risk was deleted from the list of risks in the newer PRD Revision 

C version, and the exercise time that is required to maintain measured aerobic capacity will be optimized as part 

of the activities that are associated with the risk of reduced physical performance capabilities due to reduced 

aerobic capacity. In addition, the exercise volume that is required to maintain fitness and performance will be 

further optimized through the activities that are associated with the risk of impaired performance errors due to 

reduced muscle mass, strength, and endurance. Despite the deletion of the risk of operational impact of prolonged daily exercise from newer versions of the PRD, a brief summary of the issues that are associated with 

this risk is included in this chapter.

The only countermeasure that is used consistently to date in the U.S. human space program to counteract 

the skeletal muscle atrophy and loss of muscle strength and endurance that is associated with microgravity 

exposure is physical exercise. On the ISS, each U.S. crew member is scheduled to exercise for as many as 

2.5 hours per day for 6 days per week. This almost daily time commitment is significant and represents a potential risk to the accomplishment of other mission operational tasks. While no evidence exists that the currently 

required exercise regimen has negatively impacted mission operations, future missions would benefit from optimized exercise protocols that provide needed outcomes in a shorter time period, thus allowing crew members 

more time in which to complete mission operations. The development of a benchmark for the requisite level of 

crew strength and endurance is required to accomplish this objective. Once this benchmark is developed, exercise hardware and safe exercise regimens with equivalent or improved benefits that reduce the time that is 

dedicated to daily physical exercise must be created. Such efforts should have a high priority, particularly if 

operational time requirements for future missions are predicted to increase substantially over current levels. 

 Introduction 

For long-duration missions aboard the ISS, U.S. crew members have been required to complete a 2.5-hour 

bout of combined aerobic and resistance exercise on 6 of 7 days during their assigned mission. This period 

includes the time that is needed for hardware setup, stowage, and personal hygiene. Typically, through 2008, 

approximately 1.5 hours were devoted to resistive exercise on the interim resistive exercise device (iRED) and a 

further approximately 1 hour was devoted to either the Treadmill with Vibration Isolation System (TVIS) or the 

Cycle Ergometer with Vibration Isolation System (CEVIS) or a combination of the two. On days when crew 

members were scheduled to conduct operations outside the ISS (i.e., EVAs), they were not scheduled for exercise, since EVAs typically require a significant amount of the duty day (6 to 7.5 hours) and strenuous physical 

effort. Thus, the exercise session that was normally scheduled was waived for crew members who were participating in an EVA. 

The current suite of U.S. exercise equipment and the associated exercise regimens do not target maintenance 

of a specific level of skeletal muscle strength or endurance, nor are they particularly optimized to produce 

beneficial results in the shortest time possible. To our knowledge, the current exercise time requirements have 
Chapter 15 Human Health and Performance Risks of Space Exploration Missions 

362 Risk of Operational Impact of Prolonged Daily Required Exercise 

not negatively impacted mission operations, but such a risk exists, particularly if the time that is needed to 

complete future daily mission operations increases above that of present levels. 

 Evidence 

As far as we are aware, no published scientific or anecdotal evidence exists that demonstrates that the exercise time that is scheduled for ISS crew members has negatively impacted the accomplishment of mission 

objectives. The long daily sessions of scheduled exercise do represent a risk to the accomplishment of other 

tasks, however, particularly within the confines of the flight rules that define the crew duty day that are available for all scheduled activities. In brief, crew members are scheduled daily for an 8-hour sleep period, leaving 

a 16-hour duty day. That duty day is divided into a post-sleep period with time for personal hygiene and a morning meal, a midday meal, and a pre-sleep period with further time for an evening meal and other activities. Time 

for daily planning conferences, private medical conferences, and other activities is also scheduled. Generally, 

the rest of the 16-hour duty date is allocated to mission operations (6.5 hours) and exercise (2.5 hours). Thus, 

the potential exists for competition between scheduled mission tasks and exercise sessions. 

 Computer-based Simulation Information 

No computer-based simulation pertaining to this risk is available. 

 Risk in Context of Exploration Mission Operational Scenarios 

Without knowledge of the details of Exploration mission operational scenarios, assessing the level of risk that 

prolonged periods of daily exercise might represent is difficult. However, since the time that is scheduled for 

exercise cannot be used for other purposes within the confines of duty day limitations, if duty day restrictions 

for Exploration missions do not differ significantly from those that are imposed for ISS crew members, the 

combined time that will be available in which to complete daily mission objectives and exercise will be only 

about 9 hours. Thus, the time that is spent for daily exercise sessions will decrease by an equivalent amount 

to the time that is available in which to complete mission operational tasks. 

 Conclusion 

Prolonged daily exercise sessions compete with the time that is available for mission operations and thus 

represent a potential risk to the timely completion of mission objectives. Key gaps exist in our knowledge 

concerning the level of skeletal muscle strength and endurance that should be maintained by crew members 

during long-duration space flight and how to optimize exercise hardware and protocols to achieve and maintain 

that maintenance level. Research is needed to define a skeletal muscle performance benchmark and to develop 

exercise hardware and regimens that will allow the benchmark to be met and sustained for future human space 

flight missions. 
Appendices 

Authors and Affiliations 

Acronyms and Abbreviations 

Human Health and Performance Risks of Space Exploration Missions Authors and Affiliations 

Appendices 365

Authors and Affiliations 

Abercromby, Andrew F. Wyle Integrated Science and Engineering Group, Houston, USA 

Barger, Laura National Space Biomedical Research Institute, Houston, USA; Harvard 

Medical School and Brigham and Women’s Hospital, Boston, USA 

Barr, Abbe Lockheed Martin Corporation, Houston, USA 

Brainard, George National Space Biomedical Research Institute, Houston, USA; Jefferson 

Medical College, Thomas Jefferson University, Philadelphia, USA 

Casey, Rachel Universities Space Research Association, Houston, USA 

Charles, John B. NASA Johnson Space Center, Houston, USA (Ed.) 

Connolly, Janis H. NASA Johnson Space Center, Houston, USA 

Cucinotta, Francis A. NASA Johnson Space Center, Houston, USA 

Dinges, David F. National Space Biomedical Research Institute, Houston, USA; University 

of Pennsylvania School of Medicine and Drexel University, 

Philadelphia, USA 

Donahoo, Carlton Wyle Integrated Science and Engineering Group, Houston, USA 

Douglas, Grace North Carolina State University, Raleigh, USA 

Durante, Marco GSI, Darmstadt, Germany 

Gernhardt, Michael L. NASA Johnson Space Center, Houston, USA 

Huff, Janice L. Universities Space Research Association, Houston, USA 

James, John T. NASA Johnson Space Center, Houston, USA 

Jones, Jeffrey A. NASA Johnson Space Center, Houston, USA 

Kaiser, Mary NASA Ames Research Center, Moffett Field, USA 

Keeton, Kathryn Wyle Integrated Science and Engineering Group, Houston, USA 

Khan-Mayberry, Noreen NASA Johnson Space Center, Houston, USA 

Kim, Myung-Hee Universities Space Research Association, USA 

Klerman, Elizabeth National Space Biomedical Research Institute, Houston, USA; Brigham and 

Women’s Hospital, Boston, USA 

Leveton, Lauren B. NASA Johnson Space Center, Houston, USA 

McPhee, Jancy C. Universities Space Research Association, Houston, USA (Ed.) 

Norcross, Jason R. Wyle Integrated Science and Engineering Group, Houston, USA 

Perchonok, Michele NASA Johnson Space Center, Houston, USA 
Authors and Affiliations Human Health and Performance Risks of Space Exploration Missions 

366 Appendices 

Risin, Diana NASA Johnson Space Center, Houston, USA 

Scheuring, Richard A. NASA Johnson Space Center, Houston, USA 

Schmidt, Lacey L. Wyle Integrated Science and Engineering Group, Houston, USA 

Schuh, Susan Wyle Integrated Science and Engineering Group, Houston, USA 

Shea, Camille Universities Space Research Association, Houston, USA 

Slack, Kelly J. Wyle Integrated Science and Engineering Group, Houston, USA 

Tuxhorn, Jennifer A. Wyle Integrated Science and Engineering Group, Houston, USA 

Wang, Huichen Emory University School of Medicine, Atlanta, USA 

Whitmire, Alexandra M. Wyle Integrated Science and Engineering Group, Houston, USA 

Woolford, Barbara NASA Johnson Space Center, Houston, USA 

Wu, Honglu NASA Johnson Space Center, Houston, USA 
Human Health and Performance Risks of Space Exploration Missions Acronyms and Abbreviations 

Appendices 367

Acronyms and Abbreviations 

A 

ACE advance composition explorer 

ACES advanced crew escape suit 

AFT Advanced Food Technology 

[Project] 

AGARD Advisory Group for Aerospace 

Research and Development 

AGS Alternating Gradient Synchrotron 

ALARA as low as reasonably achievable 

ANARE Australian National Antarctic 

Research Expeditions 

ARI Army Research Institute 

APA American Psychiatric Association 

ApoE Apolipoprotein E 

ARS acute radiation syndrome 

ASG Astronaut Spouses Group 

ASTP Apollo-Soyuz Test Project 

AT ataxia telangiectasia 

ATM ataxia telangiectasia mutated 

AU astronomical unit 

B 

B/F/B breakage-fusion-bridge 

BALF bronchoalveolar lining fluid 

BEIR Biological Effects of Ionizing 

Radiation 

BFO blood-forming organ 

BGI Bubble Growth Index 

BHMS Boeing Human Modeling System 

BHP Behavioral Health and Performance 

[Element] 

BME biomedical engineer 

C 

C carbon 

 control 

C&W caution and warning 

CAD coronary artery disease 

CAU cockpit avionics upgrade 

CBA carcinoma-bearing animal 

CDC Centers for Disease Control 

CEVIS Cycle Ergometer with Vibration 

Isolation System 

CG center of gravity 

CHD coronary heart disease 

C.I. confidence interval 

CL confidence level 

CM command module [Apollo] 

CME coronal mass ejection 

CMO crew medical officer 

CNS central nervous system 

CO2 carbon dioxide 

COSTEP comprehensive suprathermal and 

energetic particle analyzer 

CTA conditioned taste aversion 

CTAS Center TRACON Automation 

System 

CTSD Crew and Thermal Systems 

Division 

CVD cardiovascular disease 

CxAT- Constellation Architecture TeamLunar Lunar 

CxP Constellation Program 

D 

D-RATS Desert Research and Technology 

Studies 

DCS decompression sickness 

DCX doublecortin 

DDREF dose and dose-rate effectiveness 

factor 

DNA deoxyribonucleic acid 

DNA-PK DNA-dependent protein kinase 

DSB double strand break 

DSM-IV-TR Diagnostic and Statistical Manual 

Fourth Edition Text Revision 

DT dual task 

E 

EAR excess absolute risk 
Acronyms and Abbreviations Human Health and Performance Risks of Space Exploration Missions 

368 Appendices 

EEG electroencephalogram 

ELR excess lifetime risk 

EMU extravehicular mobility unit 

EPA Environmental Protection Agency 

EPSP EVA Physiology, Systems, and 

Performance [Project] 

ERR excess relative risk 

ESM equivalent system mass 

EVA extravehicular activity 

EWT EVA Walkback Test 

ExMC Exploration Medical Capabilities 

[Element] 

F 

F/W fatigue/weakness 

FAA Federal Aviation Administration 

fc foot-candles 

FDA Food and Drug Administration 

Fe iron 

FGB functional cargo block 

FR fixed ratio 

FSO Family Support Office 

G 

GCPS gravity compensation and 

performance scale 

GCR galactic cosmic ray 

GI gastrointestinal 

GOES geostationary operational 

environmental satellite 

GPS global positioning satellite 

GRF ground reaction force 

GRT grammatical reasoning task 

GSD geometric standard deviation 

H 

HACCP hazard analysis and critical control 

point 

HBP Human Behavior and Performance 

He helium 

HF human fibroblast 

HHC Human Health and 

Countermeasures [Element] 

HIDH Human Integration Design 

Handbook 

HMP Haughton Mars Project 

HPA hypothalamic-pituitary-adrenal 

HPBL human peripheral blood leukocyte 

HPP high-pressure processing 

HPRT hypoxanthine-guanine 

phosphoribosyltransferase 

HRP Human Research Program 

HUT hard upper torso 

HZE high-Z high-energy 

I 

I/O industrial and organizational 

IARC International Agency for Research 

on Cancer 

ICD-10 International Classification of 

Diseases-10

ICE isolated, confined, and extreme 

ICRP International Commission on 

Radiation Protection 

ICRU International Commission on 

Radiation Units 

IMM integrated medical model 

IMS Inventory Management System 

IOM Institute of Medicine 

IP internet protocol 

IQ intelligence quotient 

IR irradiated 

iRED interim resistive exercise device 

IRP Integrated Research Plan 

ISIS Intelligence Spacecraft Interface 

Systems 

ISS International Space Station 

IVA intravehicular activity 

J 

JHPEE Journal of Human Performance in 

Extreme Environments 

JSC [NASA] Johnson Space Center 

K 

KSS Karolinska Sleepiness Scale 

L 

LADTAG Lunar Airborne Dust Toxicology 

Assessment Group 

LCG liquid cooling garment 

LDTRP Lunar Dust Toxicity Research 

Project 
Human Health and Performance Risks of Space Exploration Missions Acronyms and Abbreviations 

Appendices 369

LEO low-Earth orbit 

LET linear energy transfer 

LiOH lithium hydroxide 

LM lunar module [Apollo] 

LSS life span study 

M 

MCP metacarpophalangeal 

MER Mars exploration rover 

MeV/n mega electron volts per nucleon 

Mg magnesium 

MIDAS Man-machine Integration Design 

and Analysis System 

MKIII Mark III Advanced Spacesuit 

Technology Demonstrator 

MOD Mission Operations Directorate 

MOLA Mars orbiter laser altimeter 

MPSL Mars Phoenix scout lander 

MST memory search task 

mSv milli-Sievert 

N 

NAAQS National Ambient Air Quality 

Standard 

NAS National Academy of Sciences 

NBL Neutral Buoyancy Laboratory 

NCRP National Council on Radiation 

Protection and Measurements 

Ne neon 

NEEMO NASA Extreme Environment 

Mission Operations 

NEO neuroticism, extroversion, and 

openness to experience 

NFT neurofibrillary tangle 

NIMH National Institute of Mental Health 

NOAA National Oceanographic and 

Atmospheric Agency 

NOLS National Outdoor Leadership 

School 

NRC National Research Council 

NSBRI National Space Biomedical 

Research Institute 

NSRL NASA Space Radiation Laboratory 

NTSB National Transportation Safety 

Board 

O 

O oxygen 

OER oxygen enhancement ratio 

Op Psy Operational Psychology 

P 

PAC premature atrial contraction 

PAO Public Affairs Office 

PAWS Performance Assessment 

Workstation 

PBS Public Broadcasting System 

PCI Personality Characteristics 

Inventory 

PDF probability distribution function 

PEL permissible exposure limit 

PHF paired helical filament 

PLSS Portable Life Support System 

Pogo Partial Gravity Simulator 

PRD Program Requirements Document 

PSA-NCAM polysialic acid form of neural cell 

adhesion molecule 

PVC premature ventricular contraction 

PVT psychomotor vigilance task 

Q 

QMSFRG quantum multiple scattering 

fragmentation 

R 

RBE relative biological effectiveness 

RDA Recommended Daily Dietary 

Allowance 

REI rear entry ILC Dover suit 

REID risk of exposure-induced death 

REM rapid eye movement 

ROS reactive oxygen species 

RPE rating of perceived exertion 

RSP respiratory support pack 

S 

SD standard deviation 

SEM scanning electron microscope 

standard error of mean 

SGR Small Group Research

SGZ subgranular zone 

SHE Syrian hamster embryo 
Acronyms and Abbreviations Human Health and Performance Risks of Space Exploration Missions 

370 Appendices 

SHFH Space Human Factors and 

Habitability 

Si silicon 

SIR standard incidence ratio 

siRNA small interfering ribonucleic acid 

SMM shared mental model 

SOBP spread-out Bragg peak 

SOD superoxide dismutase 

SOHO solar and heliospheric observatory 

SPE solar particle event 

SPR small pressurized rover 

SSA Social Security Administration 

SSB single-strand break 

STRES simulated training requirements 

effectiveness report 

Sv Sievert 

SWA slow wave activity 

SWS slow wave sleep 

T 

2D two-dimensional 

3D three-dimensional 

TBDM tissue bubble dynamics model 

TEPC tissue-equivalent proportional 

counter 

TIB time in bed 

TiO2 titanium dioxide 

TK triose-kinase 

TLD thermoluminscent dosimeter 

TOD top of descent 

TRACON Terminal Radar Approach Control 

TSP total suspended particles 

TVIS Treadmill with Vibration Isolation 

System 

U 

UGID upper gastrointestinal distress 

UNSCEAR United Nations Scientific 

Committee on the Effects of 

Atomic Radiation 

USAF United States Air Force 

USDA United States Department of 

Agriculture 

UTT unstable tracking task 

UV ultraviolet 

V 

VAS Visual Analog Scale 

VGE venous gas emboli 

VO2pk volume of oxygen consumption, 

peak 

W 

WAFAL Water and Food Analytical 

Laboratory 

WEI work efficiency index 

WHO World Health Organization 

WinSCAT space flight cognitive assessment 

tool for Windows 
Index 

 

Human Health and Performance Risks of Space Exploration Missions Index 

Index 373

Index 

A 

α-particles 149, 180, 194 

 high-LET 143 

ability 16, 51, 53, 63 

 high cognitive 66, 69 

 individual 66 

 low cognitive 66 

 mental 51, 52, 53 

 predictive 23 

 team/teamwork 53, 54, 57 

accident(s) 22, 61, 64, 68, 88, 89, 90, 94, 95, 103, 

107 

accuracy 25, 91, 100, 102 

actigraphy, use of 87, 95, 96, 115 

Actiwatch 96, 97 

acute radiation syndrome (ARS) 173–176, 178, 

179, 185, 186 

 cause of 177 

 clinical classification of 174 

 phases of 174, 176 

 probability of 180 

 symptoms 173 

 threshold whole-body dose 176 

adaptability/adaptation 5, 12, 19, 48, 57, 60, 62, 

64, 65, 66, 67 

 space flight 13, 105 

adenomas 

definition of 222 

adjustment disorder 8 

aerobic capacity 361 

age 6, 14, 29, 53, 54, 66 

aging 193, 197, 203, 221, 225, 228 

and radiation exposure 221, 222, 225, 226 

 diseases related to 216 

 effects 216 

 premature 194, 228 

air pollution 321 

air quality 263, 278 

Aldrin Jr., Edwin E. (Buzz) 22 

alertness 20, 88, 91, 93, 94, 95, 98, 104, 106, 108 

 decreased 102, 106 

Altair 349 

Alzheimer’s disease 194, 204, 204, 206, 207 

amino acid(s) 305, 310 

analog populations (see ground-based analogs and

lunar analogs) 

anecdotal evidence/report(s) 5, 7, 11, 12, 13, 20, 

21, 31, 58, 66, 70, 88, 105 

angina 321 

animal research/studies 15, 122, 126, 143, 144, 

148, 178, 179, 193, 194, 195, 204, 206, 207, 220, 

224, 225, 228, 322, 323 

anorexia 173, 175, 176, 177, 185, 203 

Antarctic/Antarctica (see ground-based analogs) 

anthropometrics 337, 339 

anti-inflammatory agents 193, 206 

antioxidant(s) 159, 160, 185, 186, 193, 206, 207, 

228, 301, 305 

anxiety 6, 9, 10, 14, 29, 69, 88, 246 

apolipoprotein E (ApoE) 207, 225 

Apollo [flights] 88, 100, 141, 184, 193, 196, 304, 

306, 307, 313, 319–322, 325, 326, 327, 335, 337, 

340–344, 349, 353 

 1 273 

 7 307 

 7 through 17 306 

 8 307 

 10 261 

 11 13, 22 

 12 325 

 13 13 

 14 304, 307, 325, 343 

 15 244, 304, 325, 342, 343 

 16 325, 343 

 17 325, 342, 343 

and lunar EVAs 100, 325, 335, 337, 342, 

343, 347, 353 

Apollo Medical Operations Project 337 

Apollo-Soyuz (Test Project (ASTP)) 141, 274 

apoptosis 160, 197, 207 

appendicitis 245, 246 

arrhythmia(s) 11, 218, 243, 244, 304, 321 

ascorbic acid 305 

as low as reasonably achievable (ALARA), the 

principle of 128, 135, 137 

aspirin, use of 347 

assertive/assertiveness 19, 57, 66, 69 

asthenia 8, 11, 14, 15, 243 

asthenization (see asthenia) 

asthma 320, 321, 322 

astronaut(s) 5, 6, 8, 67, 71, 87, 96, 102, 103, 107, 

115, 136, 140, 155, 160, 184, 194, 195, 196, 202, 

215, 223, 307, 337, 357 

 cancer risks to 121, 122, 123, 131, 147, 227 
Index Human Health and Performance Risks of Space Exploration Missions 

374 Index 

 career radiation dose 127, 128, 130, 134–138, 

175, 177, 195, 206, 217, 222 

 age-dependent 135 

 gender-dependent 135 

 cataracts in (see cataracts) 

 classes for 

 Conflict Management 25 

 Cross-cultural Training 25 

 In-flight Resource Plans 1 and 2 24 

 ISS Crew/Family Psychological Support 

Familiarization 25 

 Practical Planning for Long-duration 

Missions 25 

 Psychological Support Planning 1 and 2 25 

 Psychology Factors 1 and 2 24 

Self-care/self-management 24 

 [daily] sleep logs 87, 95, 98 

 dietary supplements 123, 159, 160, 206, 

297, 307 

 endurance of 49, 345, 361, 362 

 exercise 26, 270, 272, 290, 321, 340, 351, 

361, 362 

health 241, 247, 269, 270, 312, 313, 327, 

336, 347, 349, 352, 353 

post-flight 242, 244, 312, 313 

pre-flight 242, 244 

“healthy worker effect” 155 

hydration 343, 345 

 interpersonal skills (see interpersonal skills) 

 late CNS effects 194, 207 

 medical assessment/treatment 241, 244, 246 

 morbidity 193, 207 

 nutrition 343, 345 

 personal preference menu 302 

 pre-flight assessments 23 

 procedures 13, 24, 122, 128, 175, 228, 241, 

255, 256, 258 

 psychological support services for 5, 16, 

22–28 

 radiation risks to 126, 134, 135, 175 

 re-adaptation 25 

 reintegration 27, 28 

 relations with Mission Control 10, 21, 

22, 100 

 safety 126, 128, 215, 241, 255, 256, 260, 

262, 269, 272, 274, 277, 278, 291, 336, 349, 

352, 353 

 screening 127 

 select-in 23, 31 

 select-out 23 

 selection/selection process 5, 6, 23, 49, 52 

 suitability (see also suitability score) 23 

 teamwork (see teamwork) 

 training 5, 25, 49, 247, 260, 274, 278, 

285, 347 

 well-being 269, 270, 276, 313 

Astronaut Office (JSC) 24, 25, 71 

ataxia telangiectasia (AT) 126 

ataxia telangiectasia mutated (ATM) 127 

atherogenesis 225 

atherosclerosis 207, 216, 218, 225 

atomic-bomb survivors/survivor data 121, 122, 

126, 132, 134, 135, 136, 145, 147, 159, 176, 195, 

217, 218, 219, 221, 222, 227 

Australian National Antarctic Research 

Expeditions (ANARE) 15, 245 

automation 258, 259, 264, 279, 283, 284, 

289, 291 

autonomy 21, 65, 71, 263, 278, 291 

 lack of 5 

 operational 65 

Avdeyev, Sergei 31 

B 

behavioral conditions/problems 9, 16, 32 

 prevention of 5 

 treatment of 5 

Behavioral Health and Performance (BHP) 7, 

8, 13, 23–29, 41, 42, 47, 49, 50, 71, 89, 98, 103, 

107, 115 

 “best practices” 70 

BEIR VII report 131, 134 

Big Five (see personality factors, Big Five) 

biochemical pathways 204 

biodosimetry 128, 138 

biological markers 128 

biomathematical models 

 Astronaut Scheduling Assistant 103, 114, 115 

 Circadian, Neurobehavioral Performance, 

and Subjective Alertness Model 103, 104, 

114, 115 

Biosphere 2 16, 20 

blood-forming organs (BFOs) 175, 182, 184, 219 

 cancer risks 195 

 non-cancer risks 195 

body temperature 88, 93, 94, 98, 99 

bone 

 fractures 246 

 loss 340 

 marrow 176, 178 

boredom 20, 41, 302 

brain imaging 204 

breakage-fusion-bridge (B/F/B) cycles 143 

bremstrahlung 204 

bronchitis 322 

Brookhaven National Laboratory 122, 149 
Human Health and Performance Risks of Space Exploration Missions Index 

Index 375

Bubble Growth Index (BGI) 

definition of 351 

Bush, George W. 319 

C 

cachexia 85 

cancer 88, 95, 126, 135, 146, 175, 224, 246 

 hallmarks of 141, 142, 185 

 induction 141 

 morbidity 121, 215 

 mortality (rates) 121, 144, 156, 215 

 patients 177 

 prevention of 159 

 rates (of occurrence) 138, 146, 155, 194 

 risk 121, 122, 128, 129, 131, 141, 144, 146, 

147, 148, 155, 157, 158, 160, 162, 193, 195, 

226, 227 

 solid 130, 132, 133, 146, 155 

 survivors 133, 217, 218 

 total body therapy 176 

types of (including tumors) 

 adrenal 129 

 bladder 121, 126, 129, 139 

 bone marrow 139 

 bone surface 129, 139 

 brain 129, 133, 139, 195 

 breast 121, 126, 129, 133, 134, 218 

 central nervous system (CNS) 133 

 chest 139, 218 

 colon/colorectal 121, 126, 129, 133, 139 

 esophagus 129, 133, 139 

 gallbladder 133 

 gonads 129, 139 

 head 218 

 heart 139 

 kidney 129 

 liver 121, 126, 129, 133, 139 

 lung 121, 126, 129, 133, 134, 139, 150 

 muscle 129 

 neck 218 

 ovaries 121, 126, 133 

 pancreas 129, 133 

 prostate 133 

 rectum 133 

 skin 129, 139, 147, 150 

 small intestine 129 

 spleen 129 

 stomach 121, 126, 129, 133, 139 

 thymus 129 

 thyroid 129, 139 

 upper intestine 129 

 uterus 129, 133 

carcinogens/carcinogenesis 123, 142, 144, 

149, 162 

 environmental factors of 121 

 experimental models of 147 

 genetic factors of 121 

 mammary 148 

 radiation 145, 155, 218, 226 

cardiac arrhythmia 11 

cardiomyopathy 216, 218 

cardiovascular diseases/health 108, 176, 218, 219, 

225, 228 

cardiovascular system 321 

career effective dose 127 

Carpentier, Bill 326 

cataracts 127, 175, 193, 215, 216, 217, 222, 

224, 228 

 formation 228 

 incidence of 223 

 lifetime limits 216 

 ocular 217 

 definition of 217 

studies 223 

cataractogenesis 127, 218, 224 

catastrophic failure 

 avoidance of 63 

Category 

definitions of 6, 47, 87, 257, 270, 284, 304, 

324, 336 

 I 6, 20, 50, 51, 53, 57, 60, 61, 62, 64, 87, 90–

93, 96, 99, 257, 269, 283, 284, 304, 305, 

306, 308, 309, 311, 324 

 II 6, 26, 48–53, 55–62, 64–69, 87, 90, 91, 93, 

95, 96, 97, 99, 100, 102, 257, 263, 269, 274, 

275, 277, 278, 283, 284, 288, 307, 308, 336 

 III 6, 8, 10, 20, 47–55, 57–62, 64–69, 87, 90, 

91, 94, 95, 96, 98, 100, 257–262, 269–274, 

276, 283–286, 289, 290, 291, 304–307, 325, 

336 

 IV 6, 7, 9, 12, 15, 22, 24, 31, 50, 58, 60, 61, 

64, 68, 69, 87, 99, 100, 257, 270, 284, 304, 

308, 326, 336 

cell mutation 148 

cellulitis 343 

central nervous system (CNS) 133, 179, 195, 196, 

200, 225 

 astrocytes 196, 197, 199, 204, 205 

 astronaut 194 

 disease evolution 204 

 functional degradation within 196 

 microglia 196, 197, 199, 204, 205 

 neurons 196, 197, 198, 204, 205 

 oligodendrocytes 196, 197 

 radiation studies 196, 203, 206 
Index Human Health and Performance Risks of Space Exploration Missions 

376 Index 

 responses 207 

 risk(s) to 193, 194, 197, 216 

cerebral cortex 224 

Chaffee, Roger B. 273 

checklist(s) 25, 258, 286 

Chernobyl 121, 176, 177, 217, 218 

chemokines 203 

chemotherapy 159, 195, 225 

chromosomal damage/aberrations 142, 143, 147 

chronic fatigue syndrome 11, 89 

chronic obstructive pulmonary disease 321 

circadian 

 biological clock 103, 104 

 desynchronization 5, 7, 49, 87, 88, 89, 93, 95, 

98, 99, 100, 102, 103, 105–108 

 entrainment 106 

 misalignment 87, 88 

 and shift work 88 

 pacemaker 94, 99, 115 

 rhythm(s) 19, 20, 87, 93, 94, 98, 99, 100, 

102, 105, 108, 114, 115 

 entrainment of 106 

 shifting 87, 93, 107, 108 

 system 106, 108 

 timing 103 

cirrhosis 219 

cognitive changes/cognition 15, 25 

cognitive deficit(s) 88, 91, 104, 195, 202, 203 

cohesion 62 

definition of 59, 82 

color, use of 21 

communication(s) 19, 21, 25, 26, 50, 54, 61, 65, 

71, 255 

 crew-to-crew 257, 262, 270, 283 

 crew-to-ground 258, 270, 283, 290 

 latencies 263, 278 

competency model 71 

concentration 20, 88, 106 

conditions 

 behavioral 5, 7, 108 

 psychiatric 7 

confidence interval(s) (C.I.’s) 123, 131, 134 

confinement 10, 16, 17, 21, 24, 30, 48, 64, 68, 69, 

71, 263, 278 

conflict(s) 11, 21, 25 

 interpersonal 15, 19, 20, 23, 54, 60, 62 

 management 71 

 personality 49 

 role 54 

 task 62 

 team 54, 55, 71 

confusion 349 

conjunctivitis 243 

Constellation [Program] (CxP) 70, 71, 89, 247, 

274, 298, 307, 321, 335, 344, 349, 353 

constipation 243 

contact dermatitis 243 

coping behavior(s)/mechanism(s) 68 

 disruptive 13 

coronal mass ejection (CME) 180 

coronary artery disease (CAD) 218, 244, 246, 321 

coronary heart disease 219 

 risk of 227 

cosmonaut(s) 9–13, 20, 22, 51, 67, 97, 100, 223, 

242, 244, 337 

COSTEP 184 

countermeasures 5, 8, 11, 13, 16, 23, 26, 31, 32, 

53, 71, 72, 88, 89, 99, 103, 106, 107, 108, 115, 

121, 173, 193, 194, 206, 279, 311, 340, 361 

 behavioral medicine 28 

 biological 122, 141, 144, 159, 160, 186, 206 

 exercise 340, 347, 361 

 physical 159 

 prevention 22 

 treatment 22 

crew(s)/crew member(s) 

 cohesion 48, 49 

 comfort 353 

 composition 48, 122 

 definition of 82 

functions 291 

 health 5, 312, 327, 335, 336, 352, 353 

 nutritional requirements 301, 304–307, 353 

 performance 5, 269, 312, 335, 336 

 quarters 21 

 rotation(s) 105 

 schedule shifting 105 

 selection 48, 49, 122, 127 

 training 48, 49, 70 

 weight loss(es) 304, 305, 312 

 welfare 5 

“crew error” 61 

crew exploration vehicle 105 

crew medical officer (CMO) 8, 25, 286 

cue(s) 20, 87, 99, 103–106, 255 

 cards 258, 286 

 day-night 87, 99, 105, 106 

 environmental/external 99, 103, 104 

 gravitational 20 

Culbertson Jr., Frank L. 20, 22 

cultural norms (see norms) 

cut-scores 51 

definition of 82 

cytokines 185, 203 
Human Health and Performance Risks of Space Exploration Missions Index 

Index 377

D 

death 16, 89, 107, 160, 175, 207, 218, 219, 

246, 349 

 cancer 137 

 causes of 144 

 cell/cellular 125, 142, 143, 149, 215 

 family member 9, 10, 22, 29 

 neuronal 204, 205 

 non-cancer 132, 219, 220 

 occupational rates 136 

 radiation-induced 135, 138, 145, 176, 186 

 risk of exposure-induced (REID) 127, 138, 

146, 156–159, 216 

 definition of 145 

decision-making 50, 54, 61 

decompression sickness (DCS) 25, 335, 336, 

349–352 

 treatment, provision of 352 

 Type I 

 definition of 349 

 Type II 350 

 definition of 349 

degenerative diseases 122, 162, 203, 215, 216, 

220, 222 

dehydration 343 

delirium 8, 9 

delta rays 142, 146, 147, 194 

dementia 194 

deoxyribonucleic acid (DNA) 123, 222 

 damage to 142, 144, 226, 228 

 double-strand break (DSB) 125, 142, 143 

 mutation(s) 125, 142, 144, 160, 207, 215 

 repair of 126, 142, 178 

 single-strand break (SSB) 142 

depression (see also major depression) 6, 10, 11, 

14, 16, 19, 29, 30, 31, 64, 67, 88, 195, 246 

design 

 human-/user-centered 256, 262, 263, 264, 

269, 278, 279, 283, 289, 291 

 definition of 255 

 integrated system 256, 264, 279, 291 

 task 255, 256, 264, 283, 284, 285, 291 

deviant behavior 13 

Dezhurov, Vladimir Nikolaevich 22, 97 

diabetes 88 

Diagnostic and Statistical Manual Fourth Edition

Text Revision (DSM-IV-TR) 8, 9, 14 

diarrhea 176 

diffusion of responsibility 63 

definition of 82 

digestive disease(s) 216, 219 

discord 13 

disorders 

 adjustment 11 

 anxiety 11 

 depressive 11 

 major depressive 11 

 mood 60 

 personality 60 

 psychiatric 5, 14 

displacement 21 

diversity (see team) 

dogs 225 

dopamine 186, 200 

Drew, Alvin 275 

drug toxicity 200 

drugs, use of 159, 186 

 5-HT3 class 186 

 radioprotective 162 

drying 

 freeze 298 

 heat 298 

 osmotic 298 

dust(s) 13 

 analog (volcanic ash) 319, 322, 323, 324 

 ambient 321 

 contamination problems 326 

 health hazard caused by 319 

 lunar 263, 278, 319, 320, 322, 324, 326 

 exposure to 319, 325, 327 

 impact on astronaut performance 325, 

 326 

 long-term exposure limits 321, 327 

 properties 325, 327 

 respirable 319, 327 

 simulant 323 

 martian 106, 263, 278 

 simulant 323 

 mineral 319, 322 

 quartz 320, 321, 323 

 aged 323 

 freshly ground 323 

 sand 321 

 silica 322 

 aged 324 

 freshly fractured 324 

 surface-activated 324 

 toxicity 324, 326 

 terrestrial 320, 322 

dysthymia 11 

E 

ED10 

definition of 177 
Index Human Health and Performance Risks of Space Exploration Missions 

378 Index 

efficiency 255, 256, 269, 274, 277, 278, 335, 345, 

352, 353 

 risks to 272, 276 

 time-sharing 102 

 work 57, 271, 336, 352 

Element(s) 7, 50 

 BHP 7, 27, 47, 49, 72, 89, 90 

 ExMC 89, 247 

 HHC 89 

 HRP 7, 27, 49, 89, 90, 361 

 SHFH 89, 269, 297 

embolism 244 

emergency 

 behavioral 14 

 dental 246 

 medical care 241 

 psychiatric 14 

emesis (also vomiting) 159, 173, 175–178, 185, 

186, 203, 204 

emotional stability 23, 52 

endogenous circadian pacemaker 94 

endometriosis 

 definition of 226 

 development 226 

energy [personal] 18, 20, 106 

environment(s) 56 

 analog 5, 13, 30, 51, 58, 107 

 extreme 5, 6, 14, 16, 18, 19, 31, 51, 55, 58, 

62, 65, 66, 68 

 isolated 6, 15 

 martian 312 

 microgravity 173, 289, 308, 357 

 partial-gravity 337, 353, 357 

 planetary 337 

 proton 173 

 reduced-gravity 173 

 space flight 95, 98, 108, 195, 258, 269, 313 

 virtual 277, 287 

environmental conditions 65, 98 

epidemiological studies 215 

equipment 11, 26, 64, 241, 255, 256, 259, 262, 

269, 270, 272, 274, 277, 279, 288, 290, 299, 303, 

312, 342, 347 

 exercise 361 

 galley 313 

 medical 286 

equivalent system mass (ESM) 309 

definition of 308 

erythema 347 

Escherichia coli O157:H7 outbreaks 312 

excess absolute risk (EAR) 132, 133, 146 

excess lifetime risk (ELR) 

definition of 145 

excess relative risk (ERR) 132, 133, 134, 146, 

218–221, 227 

exercise protocols 361 

Exploration medical condition list 247 

extravehicular activity (EVA) (also spacewalk) 

56, 96, 100, 105, 173, 175, 177, 179, 180, 194, 

244, 274, 275, 285, 302, 312, 319, 325, 326, 327, 

335, 337, 343, 345, 346, 349, 350, 352, 353, 361 

 consumables calculator 339 

 extended 182 

 performance 340 

 single-person 353 

 suit design 335 

 training 347, 348 

extroversion (see personality factors, Big Five) 

eyestrain 99 

F 

family issues 5, 9, 10, 22, 23, 25, 50, 137 

Family Support Office (see NASA Family Support 

Office) 

fatigue 5, 7, 20, 23, 25, 49, 67, 69, 87, 88, 89, 91, 

98, 100–103, 105–108, 173, 175, 176, 179, 243, 

255, 274, 337, 348, 353 

 chronic 195 

 extreme 349 

56Fe-ion(s) 178, 197–203 

Fenton reaction 324 

ferrets 178, 179, 203, 204 

fertility 175, 222 

fibroblasts 125, 143, 149, 150 

film badges 128 

Fincke, E. Michael 31, 285, 288 

fingernail delamination 347 

first principles 6, 47, 87, 257, 270, 284, 304, 

324, 336 

Fitness for Duty Standard(s) 70, 88 

Flight Medicine Clinic (JSC) 23, 24 

flight rules 98, 270, 362 

flight surgeons 8, 9, 22, 23, 25, 28, 71, 96, 

100, 107 

fluid shifts 304, 306 

Foale, C. Michael 31, 272 

food(s) 16, 23, 200, 202 

 acceptability of 297, 298, 299, 302, 308, 

313, 314 

 bioregenerative 297, 299, 302, 303, 308, 313 

 consumption 306 

 contamination 299 

 freeze-dried 298, 302, 303, 304, 307 

 fresh 297, 298, 299, 308, 311–314 

 hydration 313, 345, 353 

 intake 297, 304, 305, 306 

 irradiated 298, 303 
Human Health and Performance Risks of Space Exploration Missions Index 

Index 379

 nutrition 297, 298, 299, 302, 308, 311–314, 

 345 

 components of 299 

 packaged/prepackaged 299, 308, 312, 313 

 preparation/dining 297, 309, 312, 313, 314 

 processing 312, 313, 314 

 rehydratable 298, 308 

 safety 297, 298, 299, 311, 313, 314 

 definition of 299 

 shelf-life/shelf-stable 241, 247, 297, 298, 

299, 303, 305, 310, 311, 312 

 definition of 309 

 system 297–303, 306, 308, 311, 313, 314 

 thermostabilized 298, 303, 305, 307 

 wetpack 307 

Forbush decrease 180 

free radicals 125, 206, 215, 228, 302 

 excessive production of 228 

free riding 63 

definition of 82 

functions 

 cognitive 20, 94 

 psychomotor 20 

G 

galactic cosmic ray(s) (GCR(s)) 121, 123, 131, 

152, 157, 158, 161, 174, 180, 193 

 1972 spectrum 194 

 chronic exposures to 207 

 dose-rate 196 

 effective dose 121, 154, 157, 158, 159 

 environment 123, 138, 152, 155 

 exposure to 126, 128, 138, 175, 215, 216, 219 

 shielding from 153, 160 

gamma rays 121, 122, 123, 125, 126, 131, 141, 

143, 147, 153, 173, 201, 215 

 cobalt 204 

 exposure(s) to 145, 174, 176, 178, 193, 

215, 219 

 treatment with 193, 217, 298 

gas bubble formation 351 

gastrointestinal function 108, 222 

GE [General Electric] 50 

Gemini/Project Gemini 141, 304 

 extravehicular activities 341, 342 

gender 14, 29, 53, 54, 67, 122, 126, 127, 137, 155 

 career dose limits related to 135, 222 

 differences 155 

 mortality rates 130, 145, 146 

 variations (inter-gender) 121 

gene mutation(s) 142, 143 

genetic factors 121, 123, 126, 162, 207 

General Adaptation Syndrome 23 

genomic(s) 242 

 instability 143 

gliosis, radiation-induced 199 

definition of 199 

goal-setting 56, 60 

gravity 173, 259, 287, 319 

 Earth 320 

 low 246 

 lunar 320, 337, 346 

 partial 287, 312 

 reduced 173, 175, 247, 263, 278, 288, 

313, 320 

Grissom, Virgil I. 273 

ground-based analogs 13, 31, 241, 242, 244, 

247, 319 

 alpine 242 

 Antarctic/Antarctica 13, 14, 18, 30, 62, 66, 

67, 68, 241, 242, 245, 246 

 Arctic 13, 105, 180, 242 

 aviation 246 

 hyperbaric chambers 17 

 military 17, 62, 246 

 mining 136, 137, 322 

 mountaineer 241 

 NEEMO 107 

 offshore drilling rigs 64 

 polar stations (also Antarctic/Antarctica) 17, 

 64 

 space analogs (see space analogs) 

 submarines 14, 17, 64, 241, 242, 245, 246 

 undersea habitats 13, 245 

 winter-over (see winter-over crews) 

ground-based 

 evidence 47, 56, 61, 63–66, 68, 69, 87, 90, 

95, 103, 105, 107 

 experimentation 122 

 observations 173 

 occupational safety 136, 138 

 studies 47, 51, 53, 61, 67, 96, 98, 99, 

106, 350 

ground control/support/team(s) 25, 50, 56, 58, 

68, 71, 87, 100, 103, 106, 107, 184, 258, 283, 

289, 291 

ground reaction force 337, 340 

group 

definition of 82 

group cohesiveness 

definition of 59 

 characteristics of 59 

“group think” 54 

growth hormone 88, 94 
Index Human Health and Performance Risks of Space Exploration Missions 

380 Index 

H 

habitability 20, 255, 257, 270, 272, 277 

 ISS 271, 276 

habitat(s) 13, 108, 161, 241, 245, 256, 263, 269, 

270, 272, 275, 278, 279, 286, 288, 303, 308, 311, 

312, 319, 322, 344, 353, 357 

hadrontherapy 142 

hamster(s) 149, 150, 160 

Hanover 50 

Harderian gland 143, 144, 147, 150 

Haughton impact crater 346 

Hawks Nest mining 322 

hazard(s) 15, 257, 270, 272, 273, 291 

headache(s) 45, 243, 349 

health 47, 65, 66 

 behavioral 5, 89 

 long-term 87 

heart attack 88, 218, 244, 246 

heart disease 219, 224, 225, 227, 228 

 acute 321 

 chronic 321 

 degenerative 225 

 lifetime limits 216 

heavy ions 122, 125, 136, 143, 147, 148, 149, 

173, 177, 200, 215, 218, 222, 223, 228 

Hedonic Scale 306 

definition of 302 

hemorrhage 244 

 intracerebral 245 

hemorrhoids 243 

heterogeneity 53, 54 

hippocampus 15, 16, 175, 194, 195, 197, 203, 226 

Hiroshima 121, 132, 217 

Hodgkin’s lymphoma 218 

homeostatic drive/decay 100, 103, 115 

Hosmer-Lemeshow Goodness-of-Fit statistic 352 

Human Behavior and Performance (HBP) Training 

Working Group 56, 71 

human-computer interaction 263, 286, 287, 288 

human factors/human factors engineering 255, 

283 

Human Integration Design Handbook (HIDH) 70, 

71 

human-machine system 256, 264, 274, 277, 279, 

283, 291 

human performance 18, 47, 48, 62, 90, 255, 257, 

269, 270 

 errors 71, 106, 283 

hydroponics 299 

hyperlipoproteinemia type III 207 

hypersomnia 19 

hypertension 88, 218 

hypotension 159 

hypothalamic-pituitary-adrenal (HPA) index 19 

hypothalamus 

definition of 221 

HZE ions/nuclei 121, 122, 123, 125, 126, 127, 

131, 141, 142, 143, 147, 148, 160, 162, 178, 193, 

194, 196, 199, 202, 206, 215, 216, 227, 228 

 neurodegeneration of 197 

 pathogenesis of 197 

HZETRN code 138, 153 

I 

IBM 50 

illness(es) 8, 9, 11, 27, 68, 241 

 food-borne 297, 299, 304, 311, 312 

 psychiatric 23, 25 

 somatic 11, 64 

immune 

 response(s) 160, 206 

 status, changes of 175 

 system 19, 216, 222 

immunology 108 

impotence, fear of 12 

infectious disease 219, 244 

inflammation 144, 160, 193, 203, 206 

information management 255, 259 

injury/injuries 8, 9, 27, 43, 68, 83, 88, 89, 94, 95, 

103, 107, 353 

 foot 346 

 in-flight 346 

 metacarpophalangeal 346 

 shoulder 347, 348 

insomnia 19 

integrated medical model (IMM) 10, 29, 30, 246 

Integrated Research Plan (IRP) 7, 50 

International Space Station (ISS) 8, 20, 21, 23, 

25, 26, 31, 51, 55, 70, 87, 96, 98, 99, 105, 114, 

121, 124, 131, 137, 138, 140, 141, 160, 196, 218, 

219, 259, 270, 271, 272, 285, 286, 289, 298, 299, 

305, 306, 307, 309, 313, 337, 343, 347, 350, 353, 

361, 362 

 Expeditions 1 through 8 305 

 Expedition 2 139 

 Expedition 3 20, 97 

 Expeditions 4 through 11 12, 272, 273, 

285, 288 

 Expedition 15 261 

 Expedition 16 29, 260, 276 

 Expedition 18 271 

 Expedition 19/20 272, 288 

 Life Sciences Crew Comments Database 

257, 258, 260, 261, 269, 270, 272, 274, 283, 

289, 290 

 stowage 259, 271, 272, 275–278, 289, 290 

 toolkit 289 
Human Health and Performance Risks of Space Exploration Missions Index 

Index 381

interpersonal interaction 

definition of 82 

intravehicular activity 175 

irradiation 159, 160, 178, 195, 197, 202, 206, 

226, 298 

 acute 178, 206 56Fe 203 

 gamma 199 

 heavy ion 225 

 HZE 199 

 proton 198, 225 

 ultraviolet 324 

 X-ray 197, 199 

irritability 67, 106 

isolated, confined, and extreme (ICE) (see

environment(s), extreme) 

isolation (see stress/stressors) 

ISS Behavioral Medicine Training 25 

J 

JANUS program 224 

joints 

 metacarpophalangeal 346, 347 

 proximal interphalangeal 347 

Jupiter 159 

JSC Family Support Office (see NASA Family 

Support Office) 

K 

Kaleri, Alexander 31 

kidney stone 245 

kinase 143, 150, 203, 206 

Karolinska Sleepiness Scale 101 

knowledge gap(s) 263, 264, 278, 279, 291 

Krikalev, Sergei 31 

L 

leadership 48, 50, 54, 55, 62 

definition of 63 

Lebedev, Valentin 12, 13, 21, 22, 28 

lessons learned 23, 24, 25, 263, 269, 272, 283 

 ISS database 259 

leukemia 121, 126, 130, 132, 134, 135, 144, 146 

 acute myeloid 126 

 risk of 146, 148 

life span study 132, 217, 218, 219 

life-table 121, 127, 128, 130, 144, 155 

light/dark cycles 102, 104 

light/lightingconditions 20, 98, 99, 103, 106, 108, 

114, 115, 263, 270, 271, 272, 278 

 artificial 99, 108 

 fluorescent 99, 114 

 handheld 271 

 incandescent 99 

 portable 271 

light flash phenomenon 193, 196 

lighting cues 99, 105 

light wavelength(s) 99, 104, 106 

Linenger, Jerry M. 13 

liquid cooling garment 342 

Lonchakov, Yury 271 

Longitudinal Study for Astronaut Health 29, 223, 

241, 242 

low-Earth orbit (LEO) 31, 87, 107, 127, 135, 137, 

196, 298 

 acceptable radiation levels for 136, 222 

lunar analogs 352, 357 

 Desert Research and Technology Studies 

(D-RATS) 337 

 Haughton Mars Project (HMP) 337, 346 

 NASA Extreme Environment Mission 

Operations (NEEMO) 337, 340 

 Neutral Buoyancy Laboratory (NBL) 337, 

340, 346, 347, 348 

 parabolic flight 337 

 Partial Gravity Simulation (Pogo) 337, 338, 

339, 344, 346 

Luna probes 320 

lunar 

 lander 105 

 outpost 87, 319, 326, 327 

lymphoma 

 acute lymphatic 126 

lymphocytes 143, 147 

M 

Maillard-Browning reaction 

definition of 310 

maintenance 52, 115, 255, 263, 278, 285, 288, 

289, 347, 352, 353 

 equipment 299 

 health 247 

 physical 361, 362 

 tasks 335 

 tissue 226 

major depression (see also depression) 19, 29 

Malenchenko, Yuri I. 260, 275 

malnutrition 305 

manic depressive disorder 29 

Mars exploration rover 106 

Mars Phoenix scout lander 106 

Mars sol 103, 106 

maze 

 Barnes 199 

 Morris water 199, 202 

 radial 203 

McMurdo (Station) 14, 15 
Index Human Health and Performance Risks of Space Exploration Missions 

382 Index 

medical 

 care 176 

 autonomous 247 

 provision of 241, 246 

 history 66 

 kits 27 

medication(s) 11, 108 

 antidepressants 28 

 antipsychotics 28 

 anxiolytics 28 

 backache 27, 28, 243 

 headache 27, 243 

 insomnia 28, 243 

 motion sickness 243 

 sedatives 28 

 sinus congestion 27 

 sleep (see sleep medications) 

 space motion sickness 27 

melatonin 88, 94, 95, 115, 160, 206 

memory 19, 67, 88, 91, 101, 102, 195, 197, 202 

 loss 203, 349 

 spatial 203 

mental retardation 195 

menu 261, 302, 306 

 Bulk Ingredient Menu project 308, 309 

 Shuttle Training Menu 308, 309 

Mercury [planet] 141 

Mercury [Project Mercury] 51, 304 

meta-analyses/meta-analysis 18, 51, 52, 56, 59, 

61, 90, 134, 160, 206, 246 

metabolic rate(s) 337–340, 342, 345, 346 

mice/mouse 144, 147, 148, 150, 178, 179, 193, 

197, 199, 200, 224, 225, 323 

 irradiated 185, 197, 199, 225 

 macrophages 185 

 tumors 148, 149 

microbiological testing 300 

microgravity 17, 101, 124, 228, 247, 276, 287, 

319, 327, 351 

 adaption to 5, 102, 246 

 biological effects of 274, 306 

microlesion 193, 196 

microorganism(s) 297, 298 

 pathogenic 298 

Military Liaison Office 24 

Mir 9, 11, 15, 22, 25, 26, 31, 43, 53, 56, 67, 98–

101, 138, 140, 141, 196, 243, 244, 284, 285, 308 

mission(s) 

 Exploration 13, 14, 29–32, 54, 56, 71, 87, 

89, 96, 105, 132, 136, 158, 180, 194, 195, 

206, 226, 241, 244, 247, 263, 278, 291, 297, 

306, 311, 327, 343, 353, 357, 362 

 high-risk 141 

 Hubble repair 138 

 long-duration 5, 6, 9, 14, 19, 20, 21, 24, 30, 

31, 47, 48, 50, 55, 58, 59, 64, 65, 67–70, 96, 

99, 100, 102, 106, 127, 135, 146, 272, 283, 

289, 291, 297, 299, 302, 304, 308, 309, 314, 

335, 361 

 lunar (moon) 6, 32, 49, 70, 87, 89, 107, 121, 

122, 124, 127, 138, 147, 155, 179, 194, 196, 

219, 223, 228, 229, 262, 263, 286, 289, 297, 

302, 303, 308, 312, 313, 314, 319, 335, 340, 

343, 344, 349, 350, 353, 357 

 long-duration 105, 106, 157, 158, 159, 

181, 228, 241, 298, 326, 362 

 short-duration 312 

 sortie 105, 327 

 Mars (long- and short-stay) 6, 12, 16, 30, 32, 

49, 70, 87, 89, 104–107, 121, 122, 124, 127, 

138, 147, 154, 155, 162, 181, 183, 193, 194, 

196, 215, 218, 219, 228, 229, 241, 244, 246, 

263, 286, 289, 297, 298, 299, 302, 303, 308, 

311–314, 319, 335, 353, 357 

 risk assessment 246 

 surface 155–159 

 swing-by 154, 157, 158, 159 

 short-duration 5, 24, 50, 87, 96, 100, 

102, 335 

Mission Operations Directorate 56 

monotony 5, 17, 20, 41 

Monte-Carlo simulation(s) 146, 153 

Montserrat 323 

mood, mood disorders 10, 14, 19, 25, 90, 101 

 negative 10 

 positive 10 

morale 9, 28, 60, 71 

mortality 57, 121, 127, 132, 133, 138, 144, 155, 

157, 160, 207, 320 

 cancer 135, 136, 156 

 non-cancer 122, 127 

 rates 64, 69, 122, 130, 145, 146, 147 

motion sickness 91 

motivation 10, 19, 20, 56 

Mount St. Helens 322, 323 

myocardial infarction (see also heart attack) 246, 

321 

N 

Nagasaki 121, 132, 217 

NASA Categories of Evidence (see Category) 

NASA Family Support Office 22, 23, 24, 25, 31 

NASA Space Radiation Laboratory 122, 141, 149 

NASA Space Radiation Program 122 

NAS Space Science Board 222 

National Geophysical Data Center 181 

National Outdoor Leadership School 70 

National Space Biomedical Research Institute 25 
Human Health and Performance Risks of Space Exploration Missions Index 

Index 383

National Transportation Safety Board (NTSB) 61 

nausea 173, 175, 176, 177, 185, 186, 203, 

304, 306 

 chemotherapy-induced 186 

necrosis 195 

NEO PI-R6 52 

neurasthenia (see asthenia) 

neurobehavioral performance 91, 93, 98 

neurocognitive deficits 193, 195 

neurogenesis 193, 195, 197 

neuroinflammation 193 

definition of 199 

 acute 199 

 chronic 199 

neuroticism (see personality factors, Big Five) 

neutron(s) 121, 125, 126, 129, 131, 143, 147, 148, 

152, 153, 160, 173, 177, 196, 215, 222, 224 

 flux 155 

nitric oxide 218, 323 

noise levels, effect of 98, 258, 270, 271 

 continuous 270 

 intermittent 270 

norm(s) 13, 25, 51, 53, 54 

“no stuff” 17, 52 

nuclear 

 industry 137 

 interaction cross sections 138, 152, 155 

 reactor workers 121, 134, 137, 173, 218 

 weapons 121, 228 

Nuclear Regulatory Commission 179 

nutrient(s) 297, 299–302, 304, 306 

 bioavailability of 311 

 contents 305 

O 

Oak Ridge National Laboratory 179 

obesity 88 

obsessive compulsive disorder 29 

ondansetron 186 

onycholysis 

definition of 346 

Operational Psychology (Op Psy) 24, 26 

Orion 306, 307, 313, 349 

Ott, Mark 304 

overheating 341 

oxidants 301, 323 

oxygen enhancement ratio (OER) 

definition of 228 

oxygen poisoning 159 

P 

paralysis 349 

parathyroid gland 222 

parenchymal cells 

definition of 226 

paper checklists, use of 258 

Parkinson’s disease 205 

partial sleep deprivation 

definition of 90 

particulate inhalation 321 

pathogenesis 12 

pellagra 299 

perceived injustices 66 

performance 47, 50, 54, 56, 62, 65, 66, 91, 93, 95, 

98, 102, 104, 106, 114, 335, 337, 343, 353 

 Bayesian 115 

 cognitive 67, 88, 90, 91, 93, 100, 101, 

102, 103 

 deficit(s) 91, 98, 99, 102 

 definition of 82 

degradation 286 

error(s) 47, 87, 88, 91, 95, 100, 103, 105, 107 

 definitions of 82 

 Level 1 70, 105 

 Level 2 70, 105 

 Level 3 70, 105 

 operator 255, 256 

 group 66 

 levels of 47 

 maintenance of 361 

 memory-search 102 

 motor 93 

 neurobehavioral 102, 115 

 on-orbit 102 

 optimal, achievement of 48, 72, 89, 255 

 physical 361 

 sleep-loss-related 87, 91 

 team 7. 49, 54, 55, 57, 59, 61. 63, 65, 66, 71 

 thresholds 107 

performance-anxiety relationship 67 

Performance Assessment Workstation 101 

performance standard 

definition of 83 

pericarditis 218 

permeability 

 oxygen 303 

 water vapor 303 

permissible exposure limit (PEL) 158 

 BFO limits 177, 217 

 career exposure 127, 128, 130, 131, 135, 136, 

137, 175, 195, 206, 216 

 [central nervous system] CNS 195, 217 

 short-term exposure 127, 137, 175, 195, 

206, 216 

personality 23 

definition of 83 

 conflicts 11, 15, 49, 62 
Index Human Health and Performance Risks of Space Exploration Missions 

384 Index 

 factors, Big Five 18, 51, 53, 83 

 agreeableness 17, 18, 19, 51, 52, 53, 

55, 83 

 conscientiousness 17, 18, 19, 51, 52, 83 

 extroversion 17, 18, 19, 51, 53, 55, 66, 

69, 83 

 neuroticism 17, 18, 19, 51, 83 

 openness 17, 18, 51, 52, 83 

Personality Characteristics Inventory 52 

personality tests 17 

Pettit, Donald 14 

phantom torso 138, 139 

Phillips, John L. 273 

Pillsbury Company 299 

plaque 

 development, stages of 205 

 formation of 205 

phosphene 196 

definition of 196 

plant-crew interaction 308 

pneumonia 219 

polyethylene 121, 160, 161 

polysomnography, use of 87, 95, 97 

post-traumatic stress 6, 67 

posture 

 changes (induced by space flight) 274 

 on Earth 274 

potassium deficiency 304 

pre-breathe protocol(s) 335, 349–352 

 campout 350 

 exercise 350 

 4-hour in-suit 350 

 Russian 350, 352 

precursor cells 193, 197, 198, 199 

predictions 

 organ dose 138, 139 

 dose-equivalent 138, 139 

pre-flight health status assessment 241 

premature contraction(s) 

 atrial 243 

 ventricular 243 

prescreening 60 

primary reference risk 135 

probed recall memory test 102 

problem-solving 10 

procedure(s) 24, 122, 128, 139, 156, 188, 241, 

260, 261, 285 

 development 283 

 mitigation 175 

 operational 183, 228 

 poorly designed 255, 256, 286 

 safety 13 

 sampling 155 

productivity 65, 352 

Process S 98 

prodromal 

 effects (see also nausea, vomiting, anorexia, 

fatigue) 175–178, 186, 203 

 syndrome 185, 186 

Progress 11, 276, 285 

 [Progress] 234 284 

prostatitis, perceived 12 

protein 300, 310, 311, 313 

 C-reactive 321 

 synaptic 203 

proteomics 204, 242 

proton(s) 121, 125, 131, 141, 147, 148, 149, 158, 

160, 173, 178, 180, 183, 184, 193, 194, 196, 199, 

215, 218, 222 

 beams 217 

 effects 179 

 fluence 174 

 high-energy 122, 123, 129 

 low-energy 198, 223, 224, 226 

 source spectra 182 

 spectra 185 

 treatment with 193 

psychiatric disorders/problems 9, 16, 32, 244, 

245, 246 

psychological support 241 

psychomotor vigilance task 91, 94, 102, 104 

psychosomatic reaction(s) 11, 14 

psychosocial adaptation 7, 12, 47, 48, 49, 65, 66, 

68–72, 108 

definition of 65, 83 

 ground-studies of 67 

 to space flight 10, 14, 53, 65 

psychosocial disorder(s) 12, 14 

pulmonary cells 319 

R 

rabbits 224 

radiation 

 acute risk 193 

 and activation of dormant tumors 144 

 atmospheric 222 

 biological effects of 186 

 Cerenkov 196 

 damage 142, 159, 185 

 dose(s)/dose rate(s) 122, 136, 138, 148, 173, 

184, 206, 217 

 dosimetry 128, 129, 131, 138, 151, 152, 

153, 184 

 effects 175, 178, 200, 226, 246, 297, 314 

 fertility 175 

 non-cancer 175, 222 

 sterility 175, 176 
Human Health and Performance Risks of Space Exploration Missions Index 

Index 385

 exposure to 16, 121, 125, 130, 135, 160, 177, 

181, 195, 206, 207, 215, 217, 218, 221, 228, 

229, 244, 263, 278, 301 

 symptoms of 176, 177 

 gamma 179 

 high-dose 185 

 high-LET 126, 127, 128, 142–145, 147, 148, 

153, 160, 177, 196, 197, 199, 200, 202, 203, 

206, 207, 215, 220, 222, 223, 224, 226, 228 

 HZE/high-HZE 197, 206 

 individual sensitivity to 141 

 injury caused by 159 

 ionizing 121, 142, 143, 159, 160, 173, 179, 

185, 193, 195, 206, 215, 217, 220, 228 

 low-LET 121, 123, 125–128, 131, 132, 134, 

138, 142–145, 148, 153, 156, 162, 173, 176, 

177, 178, 193, 194, 197, 199, 200, 203, 207, 

215, 222–225, 228 

 quality/quality factors 148 

 risk, levels of 137, 138, 145, 146, 175, 216, 

226 

 sensitivity to 149 

 shielding/protection (e.g., spacecraft) 121, 

135, 144, 145, 148, 156–160, 162, 173, 174, 

180, 182, 186, 194, 215, 216, 222, 228, 335 

 sickness 177, 186 

 skin damage 

 epilation 177 

 erythema 177 

 moist desquamation 177 

 space 121, 123, 124, 126, 127, 138, 141, 148, 

151, 162, 173, 186, 193, 194, 195, 197, 199, 

200, 204, 206, 207, 215, 216, 222, 226, 228, 

229, 298, 312, 313 

 composition of 123 

 therapeutic treatment with 121, 159, 198 

 transport codes 151 

 types of 122 

 whole-body 179, 217, 225 

radiation-induced risks 127, 130, 135, 137, 138, 

142, 179, 185, 197, 199, 200, 201, 204, 206, 217, 

218, 221, 222 

radioactivity 298 

radioprotector(s) 159, 160, 185, 186, 206 

radiotherapy 159, 186, 195, 197, 225, 228 

rapid eye movement 97, 102 

rating of perceived exertion 337 

rats 147, 148, 160, 178, 193, 202, 203, 224, 

320, 323 

 and a fixed-ratio schedule 202 

 hippocampus 198 

 neurochemical changes 200 

 sensorimotor deficits 200 

 Sprague-Dawley 144, 200 

reactive oxygen species (ROS) 193, 198, 202, 

225, 323, 324 

recall task [memory] 101, 102 

recoil nuclei 121, 153, 178, 215 

regolith (martian) 161 

relative biological effectiveness (RBE) 126, 141, 

142, 143, 148, 149, 173, 178, 194, 195, 198, 199, 

200, 204, 206, 215, 224–227 

renal colic 244 

respiratory 

 disease(s) 216, 219 

 system 44, 133, 242, 320, 321, 324 

response time 91, 100, 102 

resupply mission(s) 26, 99, 115, 276, 298 

 lack of 313, 314 

 options 312 

retching 179, 203 

retina 193, 196 

Rhesus monkeys 223, 226 

rickets 304 

“right stuff” 17, 32, 52, 53, 55 

risk(s) 7, 8, 9, 11, 13, 14, 16, 19, 22, 23, 27, 

29–32, 43, 48, 49, 65, 68, 115, 173, 175, 246, 

255, 269, 327, 352 

definition of 5 

 assessment(s) 147, 162, 180, 186, 194, 207, 

246, 247 

 BHP 49 

 cancer (see cancer, risk) 

CNS 193, 194, 204, 206, 207 

 acute 194, 206 

 late 194, 206 

 degenerative 216 

 estimate/estimation 121–124, 126,135, 158, 

193, 194, 195, 215, 216, 218, 226, 246 

 elements 256 

 health 70, 138, 335, 341 

 levels 194 

 mitigation 122, 347, 352, 353 

 non-cancer 195 

performance 20, 341 

 performance errors 47 

 projection 122, 123, 124, 127, 128, 134, 194 

 safety 335, 341 

 SHFH 274 

 Team 71 

 transfer model(s) 146, 155 

robotic mission 87, 107 

robotics 56, 258, 283 

Russian space station Mir (see Mir) 
Index Human Health and Performance Risks of Space Exploration Missions 

386 Index 

S 

salmonella 300 

salutogensis/salutogenic conditions 10, 12, 14, 

15, 64 

Salyut [flights] 

-5 9, 22 

-7 10, 12, 13, 28 

San Francisco volcano field, Arizona 323 

Saturn 159 

 moon (Titan) 159 

scales 

 Borg RPE 344 

 Cooper-Harper 337, 357 

 gravity compensation and performance 

(GCPS) 337, 339, 340, 341, 344, 357, 358 

schedule(s) 87, 100, 103, 104, 106 

 change(s) to 100 

 sleep/wake 95, 99, 103, 115 

 work 20, 103, 115 

 work-rest 25, 98 

Schmitt, Harrison 325, 326 

scurvy 299, 304 

Seasonal Affective Disorder 108 

secondary radiation 

 neutrons 121 

 recoil nuclei 121 

seizures 349 

selection 

definition of 83 

self-esteem 67, 69 

self-report/self-reporting 12, 57, 87, 96, 98, 106 

senescence 126, 216, 220, 298 

 premature 222, 226 

senile plaque(s) (also amyloid plaque) 204, 205 

sepsis 343 

serotonin 185, 186 

Shackleton crater 105, 325 

shared mental model 62 

definition of 83 

Shell [Company] 50 

shielding [spacecraft] 

 aluminum, use of 121 

 polyethylene, use of 121 

shift work 88, 103, 106 

shuttle (see space shuttle) 

silicosis 321, 322, 323 

 initiation of 323 

Silver Snoopy awards 29 

simulated training requirements effectiveness 

report (STRES) 101 

simulation(s) 15, 58, 59, 179, 180, 205, 259 

 chambers 52 

 computer-based 103, 226, 246, 262, 267, 277, 

290, 309 

 emergency 59 

 flight 62 

 laboratory 13 

 mathematical 104 

 Monte-Carlo 153 

 researchers 57 

siRNA 143 

situational awareness 255, 257, 264, 274, 284 

skeletal muscle 340, 361, 362 

skills 

 cognitive 57, 90 

 interpersonal 56, 57, 58 

 motor 90 

 psychomotor 57 

 teamwork 50, 52, 58 

Skyhook study 147 

Skylab 11, 21, 31, 95, 100, 141, 196, 244, 

298, 305 

 [Skylab] 3 100 

 [Skylab] 4 274 

slam shifting 20, 100, 103, 104, 106 

definition of 99 

sleep 19, 20, 25, 87, 89, 94, 100, 102, 106, 107, 

115, 271, 362 

 content of 97 

 debt 91 

 deprivation 90, 92, 99, 100, 104 

 desynchronization 93 

 disorders 87, 243 

 disruption(s)/disturbance(s) 5, 6, 15, 19, 89, 

96, 97, 98, 106, 108, 272 

 duration 96, 107 

 impairment, levels of 91, 92 

 loss 6, 20, 49, 87, 88, 91, 95, 98, 99, 100, 

103–106, 107, 108, 115 

 acute 96, 115 

 chronic 88, 96, 103, 115 

 cumulative 88, 103 

 medications 91, 96, 97, 108 

 on-orbit 102 

 quality 95–98 

 quantity 95, 96, 98 

 restricted 91, 92 

see also total sleep deprivation 

sleep/wake shifts/schedule 91, 95, 99, 104, 107 

sleepiness 106 

sleeping quarters 272 

sleeplessness 243 

slow wave 

 activity 98 

 sleep 97, 98 

small pressurized rover 352, 353 

Snoopy (Apollo 10 lunar module) 262 
Human Health and Performance Risks of Space Exploration Missions Index 

Index 387

social 

 capabilities 51 

 isolation 64 

 loafing 63 

 definition of 83 

 support 68 

SOHO satellite 184 

solar 

 corona 180 

 cycle 181 

 flare 

 definition of 180 

 maximum 157, 158, 174 

 near 159 

 minimum 161, 194 

 plasma 180 

 proton(s) 121, 158 

 wind 180, 215, 324 

solar particle event(s) (SPE(s)) 121, 130, 131, 

180, 181, 182, 185, 193, 194, 217, 228 

 1972 SPE 152, 157, 158, 159, 161, 174, 180, 

182, 183, 184 

 dose-rates 121, 179 

 energy spectrum 173 

 exposure to 126, 173, 174, 175, 176, 178, 

179, 215, 219 

 forecasting of 173, 184 

 intensity of 173 

 January 2005 181, 182 

 on Mars 180 

 organ doses 178 

 prediction of 173, 174, 178 

 protons, exposure to 173 

 shielding 161, 182, 183, 353 

 spectra 152 

 warning or alert system 183 

South Pole 14 

 moon 105, 325 

Soyuz 20, 99, 101, 271 

[Soyuz]-21 9 

T-14 10 

TM-2 10 

space adaptation syndrome 43, 242 

space analog/space analog studies 7, 8, 47, 48, 61, 

62, 66, 72 

spacecraft “storm shelters” 182 

space flight(s) (see missions) 

space flight evidence 5, 47, 50, 56, 58, 61, 63, 87, 

95, 102, 105 

Spaceflight Human System Standards (Standard 

5.2.3) 70 

Space Medicine Division 42, 43, 82, 113, 114, 

247, 249 

Space Mission Directorate 183 

space motion sickness (see also medications) 27 

space radiation (see radiation, space) 

space shuttle 11, 20, 26, 43, 53, 87, 88, 95, 96, 98, 

104, 138, 140, 141, 242, 243, 271, 274, 298, 306, 

307, 309, 337, 343, 353 

Atlantis 276 

Challenger 61 

cockpit upgrade 262 

Columbia 61, 277 

 Endeavour 275 

 STS-29 308 

 STS-30 308 

STS-51D 308 

 STS-90 (Neurolab) 102 

 STS-91 139 

 STS-95 102 

 STS-99 308 

 STS-101 308 

 STS-114 114 

 STS-118 275 

 STS-122 276 

spacesuit(s) 173, 319, 327, 351 

 A7LB 337 

 ACES 274 

 Apollo 322, 325, 326, 335, 343, 344, 345 

 center of gravity (CG) 340, 341 

 EVA (lunar) design 335, 336, 337, 342, 352, 

353, 357 

 extravehicular mobility unit (EMU) 285, 337, 

344–347, 350, 352 

 Mark III suit (MKIII) 274, 275, 338, 345 

 Orlan 350 

 rear entry ILC Dover suit (REI) 274, 275 

spatial learning 202 

spectra 

 energy 123, 152, 156, 158 

 GCR input 153 

 LET 152, 153, 154, 156 

 neutron 153 

 SPE 152 

stability 19, 23, 50 

strain 

definition of 83 

stem cells (e.g., bone marrow) 176, 196, 203, 

225, 226 

 studies of 197 

stowage 259, 263, 271, 272, 275, 276, 277 

stress/stressors 5, 16, 17, 19, 21, 22, 23, 30, 48, 

58, 62, 64, 67, 83, 124, 269, 285, 302 

definition of [stress] 67, 83 

 definition of [stressor] 83 

 acoustic 21 

 boredom 20, 302 

 confinement 10, 16, 17, 48, 67, 69, 278 
Index Human Health and Performance Risks of Space Exploration Missions 

388 Index 

 emotional 21, 68 

 environmental 101, 263, 277 

 genotoxic 225 

 interpersonal conflict 21, 49, 70 

 isolation 10, 16, 17, 48. 64, 67, 69, 71, 262, 

263, 278 

 monotony 5, 17, 20, 21, 48, 278 

 physiological 66 

 psychological 16 

 reactions to 67 

 workload (see workload) 

stress management 24 

stroke 87, 218, 219, 244, 246 

 risk of 227 

suitability score 23 

surfactant, lung 319, 321 

Syrian hamster embryo (SHE) 149, 150 

T 

3M 50 

Tani, Daniel M. 20, 97 

task(s) 10, 19, 22, 24, 50, 51, 56, 60, 65, 71, 88, 

94, 100, 101, 102, 115, 179, 196, 247, 255, 260, 

263, 270, 274, 278, 283, 357 

 analysis 256, 259 

 automated 283, 284 

 cognitive 90, 100 

 complex 88, 107 

 conflict 54, 62 

 critical 93, 99, 100, 105 

 daily 16, 258, 271, 272 

 design (see design, task) 

 execution 259, 261 

 goals 62, 63 

 ISS 258, 290 

 long-duration 57 

 maintenance 285, 288 

 manual 284 

 medical 285 

 memory 102 

 motor 90 

 nonessential 21 

 performance 30, 62, 102, 257, 258, 261, 271, 

284, 285, 339 

 poor 255, 256 

 roles and responsibilities 283 

 team 57, 59, 60 

team 50 

definition of 83 

 ability 63 

 breakdowns 61 

 building 58 

 coaching 47 

 cohesion/cohesive 7, 47, 48, 49, 55, 60–64, 

68, 71, 89, 108 

 composition 47, 50, 53, 55, 71 

 conflict (see conflict, team) 

 context 

 definition of 63 

 coordination 61, 63, 65 

 cross-training 57 

 diversity 53, 54 

 deep-level 53, 54, 55 

 surface-level 53, 54, 55 

 motivation 63 

 performance (see performance, team) 

 psychosocial adaptation 49, 89 

 selection 47, 71, 89 

 skills training 

 definition of 83 

 training 7, 47, 48, 49, 55, 56, 58, 59, 68, 

71, 89 

 definition of 83 

teamwork 5, 47, 51, 59, 65 

 competencies 50 

 skills (see skills, teamwork) 

 training 56 

teleconsulting 241 

telomere(s) 

definition of 222 

 dysfunction 143 

 regulation 226 

Thagard, Norman E. 21 

thalamus 194 

“the bends” (see decompression sickness (DCS)) 

thermoluminescent dosimeter 128 

thiamin 301, 304, 305 

third-quarter effect 15 

three-dimensional cell cultures 204 

time series motion capture 337 

tissue-equivalent proportional counter 128, 152 

Tokai-mura, Japan 176 

tools 13, 25, 27, 28, 71, 103, 107, 186, 204, 255, 

256, 262, 264, 269, 270, 274, 277, 279, 288 

toothache(s) 12 

total [chromosome] exchanges 138, 140 

total sleep deprivation 91 

 long-term 90 

 definition of 90 

short-term 90 

 definition of 90 

toxic environment/gases 25, 255 

training 255 

definition of 83 

EVA 347, 348 

 pre-flight 241, 257, 259 

 in orbit 257 
Human Health and Performance Risks of Space Exploration Missions Index 

Index 389

training criteria 

 behavior 57 

 learning 57 

 reaction (also self-report) 57 

 results 57 

translocations 140 

definition of 138 

trauma 241, 244, 245, 352, 353 

tuberculosis 219 

tumors (see cancer) 

tumorigenesis in animal models 148 

Twin Towers, the 22 

U 

unconsciousness 349 

United States Army Laboratory 299 

United States Department of Agriculture (USDA) 

299, 301 

United States Office of Personnel Management 50 

unstable tracking task (UTT) 101 

urinary disease 219 

urine collection device 343 

U.S. Air Force 57, 224, 226 

U.S. Marine (Corps) 67 

U.S. Medical Events Tables 9 

U.S. Navy 52 

V 

“vascular hypothesis” 226 

Vasyutin, Vladimir 10 

venous gas emboli 349, 350, 352 

Verizon 50 

vigilance 95 

virtual environments 54, 262 

Visual Analog Scale 101 

vitamin(s) 309, 311, 313 

 A 160, 206, 207, 300 

 B6 301 

 B12 301 

 C 160, 206, 228, 299, 301, 309 

 D 301, 305 

 E 160, 206, 207, 228, 301 

 K 301 

vomiting 173, 175–179, 185, 349 

 chemotherapy-induced 186 

 prodromal 177, 186 

Vostok, Russian Antarctic Station of 16 

W 

Wakata, Koichi 272, 288 

waste 272, 276, 277, 297, 302, 308, 309 

 collection 335 

 dry 303 

 management 343, 353 

 wet 303 

Waste Management [company] 50 

White II, Edward H. 273, 341 

Whitson, Peggy A. 260 

WinSCAT 25, 26, 27 

winter-over 

 crews 13, 15, 19, 22, 66 

 syndrome 15 

wire suspension test 200 

work 

 extended 93, 94, 95, 105, 106, 108 

 overload 7, 49, 87, 93, 100, 102, 103, 

105–108 

 schedule 20 

work efficiency index 343 

definition of 352 

workload 5, 10, 21, 23, 25, 30, 89, 101, 102, 105, 

106, 107, 262, 263, 269, 285, 304, 306, 337, 341 

 assessment of 101, 343, 344 

 high EVA 342 

work-rest schedules/cycles 98, 99, 107 

work-sleep schedules 106, 107 

workspace(s) 269, 270, 274, 275, 276, 279 

WR2721 228 

“wrong stuff” 17, 52 

X 

X rays 121, 123, 125, 126, 143, 173, 215, 

223, 224 

 doses of 197, 199, 217 

 exposure to 174, 176, 178, 193, 215, 216, 222 

 treatment with 298 

Y 

Yurchikhin, Fyodor N. 261