Health Effects of 

Aircraft Cabin Pressure In

Older and Vulnerable 

Passengers

Airliner Cabin Environment Research (ACER) Program

National Air Transportation Center of Excellence for Research in the 

Intermodal Transport Environment (RITE)

Eileen McNeely

John Spengler

Department of Environmental Health

Harvard School of Public Health

Boston, MA 02115

Jean Watson

Office of Aerospace Medicine

Federal Aviation Administration

Washington, DC 20591

November 2011

Final Report 

Report No. RITE-ACER-CoE-2011-1
NOTICE

This document is disseminated under the sponsorship

of the U.S. Department of Transportation in the interest

of information exchange. The United States Government

assumes no liability for the contents thereof.

_______________

This publication and all Office of Aerospace Medicine

technical reports are available in full-text from the Civil

Aerospace Medical Institute’s publications Web site:

www.faa.gov/library/reports/medical/oamtechreports/index.cfm
i

Technical Report Documentation Page

1. Report No. 2. Government Accession No. 3. Recipient's Catalog No.

DOT/FAA/AM

4. Title and Subtitle 5. Report Date

Health Effects of Aircraft Cabin Pressure for Older and Vulnerable 

Passengers

November 2011

6. Performing Organization Code

7. Author(s) 8. Performing Organization Report No.

McNeely, E, Spengler, J Watson, J

9. Performing Organization Name and Address 10. Work Unit No. (TRAIS)

Air Transportation Center of 

Excellence for Airliner Cabin 

Environment Research

FAA Office of Aerospace Medicine

800 Independence Avenue, S.W.

Washington, DC 20591

Harvard School of Public 

Health

11. Contract or Grant No.

Boston, MA 02115

12. Sponsoring Agency name and Address 13. Type of Report and Period Covered

Office of Aerospace Medicine

Federal Aviation Administration

800 Independence Ave., S.W.

Washington, DC 20591 14. Sponsoring Agency Code

15. Supplemental Notes

Work was accomplished under Public law 108-76

16. Abstract

Purpose: This report discusses a study of the physiological effects of cabin altitudes in elderly and vulnerable 

passengers. The primary aim was to determine the level of oxygen saturation in susceptible passengers during 

flight and to measure cardiopulmonary demand in the case of mild to moderate hypobaric hypoxia. Methods:

The researchers monitored 41 passengers, including passengers with stable cardiac disease, in a hypobaric 

chamber for two days; one at 7,000 feet cabin altitude and, the other day at ground level. Six of these passengers 

took 3 commercial flights as well. Results: Moderate desaturation that was associated with compensatory signs 

such as increased breathing rates and heart rates was observed in nearly half of the passengers, irrespective of 

baseline health status. Compared to healthy seniors, compensatory signs were especially exaggerated among 

cardiac patients. Age was significantly associated with desaturation also. Chamber results were similar to inflight 

for those individuals monitored in both settings. Conclusions: Typical cabin pressures resulted in moderate 

desaturation in vulnerable seniors. Importantly, current medical guidelines for determining passenger fitness to 

fly and the need for in-flight supplemental oxygen would underestimate the prevalence of desaturation during 

flight in this sample. While medical guidelines consider baseline health conditions, health status (such as healthy 

senior or cardiac patient) did not predict the degree of desaturation during flight. Health status was associated with 

the level of compensatory response, however. For example, the significantly different compensatory responses 

of cardiac patients, were suggestive of greater physiological loads. In addition, although desaturation levels were 

predicted by age, age is not typically emphasied in fitness determinations. Implications: These findings suggest 

the potential for hypoxic stress in seniors with and without chronic disease during ultra long flights, especially if 

exerting themselves walking the aisles at altitude, or when flying to altitude. FAA rules for cabin pressurization 

may need reconsideration in this light.

17. Key Words 18. Distribution Statement

Hypoxia, Passenger Health , Elderly Passengers, Cabin 

Pressure, Altitude Sickness, Heart Failure and Air Travel, 

Passenger Symptoms and Altitude, Arrhythmia in Flight,

Flight Fatigue

Document is available to the public through the 

Defense Technical Information Center, Ft. Belvior, 

VA 22060; and the National Technical Information 

Service, Springfield, VA 22161

19. Security Classif. (of this report) 20. Security Classif. (of this page) 21. No. of Pages 22. Price

Unclassified Unclassified 13

Form DOT F 1700.7 (8-72) Reproduction of completed page authorize
ii

ACKNOWLEDGMENT

The authors wish to thank The Boeing Company, Seattle, WA, for grant support for 

this project and the B/E Aerospace, Inc, Winston-Salem, NC, for the donation of airline 

seats for the hypobaric chamber at the Civil Aerospace Medicine Institute (CAMI), 

Oklahoma City, OK. Findings in this report do not represent the expressed opinions of 

these companies or their endorsement of findings. We wish to extend our special thanks 

to professionals at Boeing who assisted along the way. In particular, we wish to thank 

David Space for providing benchmarks of cabin environmental conditions for the 

chamber simulation and for assisting in seeing through the testing and certification of the 

medical equipment for use aboard commercial flights. Also, Michael Muhm and Stephen 

Jones provided many thoughtful reviews and comments of the study protocols and of the 

analyses.

In addition, we wish to recognize the other main contributors to this project, 

including members of the Harvard team who were extremely valuable for their 

contributions including, Philip Parks, Adjunct Faculty in Environmental and Occupational 

Medicine; Murray Mittleman, Associate Professor in Environmental Cardiology; Gregory 

Wellenius, Assistant Professor in Environmental Physiology (now at Brown University 

School of Public Health); Louise Ryan, formerly Chair, Biostatistics, (now Division 

Mathematics Chief at CSIRO Australia); Brent Coull, Professor of Biostatistics; John

McCracken, Research Scientist in Environmental Health; and Julie Bradley, Project 

Manager, Environmental Health. 

Integral to the conception and conduct of this work were our collaborators from 

the FAA Civil Aerospace Medicine Institute (CAMI) including Dennis Burian, Arnold 

Angeleci, and Thomas Nesthaus. We want to acknowledge also the invaluable 

contribution of Robin Germany, cardiologist and faculty from the University of Oklahoma 

College of Medicine, Oklahoma City, OK, who led the medical review of the cardiac 

patients and consulted on study protocols and data analyses. 

We are grateful to the assistance of the Department of Homeland Security and the

Transportation Security Administration (TSA), in cooperation with the FAA, for managing 

the security of the passengers equipped with monitoring equipment in the on-board 

portion of the study. We are especially grateful to Ms. Jean Watson, Aerospace Medicine, 

FAA, for shepherding the protocol review through TSA and the FAA for the on-board 

study, and for accompanying us on the initial test flight.
iii

EXECUTIVE SUMMARY

Congress mandated FAA to study the health effects of cabin pressures in 

accordance with the National Research Council (NRC) recommendation to evaluate safe 

limits (NRC 2002). The NRC reported that the currently allowed cabin altitude of 2,440

meters (8,000 feet), set decades ago, may not be adequate for cabin crew and passengers 

of varying age and health status. 

This report discusses the Harvard School of Public Health study to investigate the 

effects of cabin pressures on elderly passengers, some with chronic and stable disease, 

and all, current users of air transportation. The study investigated three potential risks 

for hypoxia: age over 50, cardiac disease, and passengers with lowered oxygen saturation 

at ground level. Health effects of cabin pressures were measured as changes in oxygen 

saturation during flight, physiological compensation for hypoxia during flight, such as 

changes in cardiopulmonary indices, and the report of symptoms during flight. These 

outcomes were first tested in 41 passengers in a hypobaric chamber over two days of 4-5

hours of simulated flight each day; one day at near sea level, and the other day blinded to 

the condition of 7,000-feet altitude. Subsequent to the chamber studies, 6 of the original 

41 passengers had cardiopulmonary responses recorded as they flew three segments 

aboard commercial flights. Their responses were subsequently compared to earlier

chamber results.

 Major findings:

 Vulnerable senior passengers experience moderate hypoxia during flight. 

While previous research showed around a 4% mean drop in oxygen 

saturation for most individuals at cabin altitude, our study found greater 

declines. Nearly half of the older passengers in this study desaturated to 

90% or below, levels considered as moderate hypoxia. Further, the 

changes in cardiac and pulmonary function we observed in flight were 

associated with compensatory mechanisms that aim to regulate hypoxic 

states. These observations suggest that the observed levels of hypoxia are 

consequential, in particular for passengers with cardiac disease, and 

notable, when compared with previous studies that found no evidence of 

these systemic changes. These results point to the potential for hypoxic 

stress in seniors with and without chronic disease during ultra long flights, 

especially if exerting themselves walking the aisles at altitude, or when 

flying to altitude.

 Age is an important risk factor for hypoxia in flight with almost a 1% 

decrease in oxygen saturation for every decade of life above 50 (the lower 

age limit of our sample) at cabin pressures of 7,000 feet.
iv

 Current medical guidelines that deem sea-level oxygenation greater than 

95% as generally protective against the need for in-flight supplemental 

oxygen underestimate the true risk of hypoxia for many seniors at usual 

cabin altitudes. In this study, many passengers with “sufficient” baseline 

oxygenation dropped to hypoxic levels in flight.

 Flight altitudes may place additional stress on passengers with underlying 

cardiac disease. Passengers with pre-existing arrhythmias experienced 

greater rates of arrhythmia in flight.

 At typical cruising altitudes, symptoms may be an insensitive indicator of 

hypoxia. Symptom reporting was not significantly different on flight days

versus control days. 

 Chamber simulations approximated actual flight experiences according to 

passenger responses. Passengers monitored aboard the commercial flights

responded similarly in the chamber simulation and aboard commercial 

flights in terms of oxygen saturation, heart rate, and breathing rate.

Strengths of the study:

 Blinded trial of human responses to cabin pressures while controlling 

other environmental conditions in a hypobaric chamber simulation. 

 Extensive continuous real-time physiological monitoring of passengers.

 Repeated measures of the same passengers in both control and flight 

conditions, thus, limiting noise related to the known inter-individual 

variability in hypoxic responses and focusing instead on the intraindividual variability in responses related specifically to the hypoxic 

exposure. 

 Higher cabin pressures tested (7,000 feet) compared with many prior

studies that tested only at the minimum allowable pressure (8,000 feet).

 Passenger responses compared between the flight simulations and 

commercial flights in a subsample of the study population.

Limitations of the findings:

 Small in-flight sample and cardiac sub-sample. Results should be repeated

in larger samples and over longer flight durations.
v

 Oxygen saturation measures limited by indirect measures, such as, pulse 

oximetry without co-oximetry to detect carboxyhemoglobin (COHb) in 

smokers.

 The role of prescribed medications in passenger responses to flight was not 

investigated.

 The impact of flight on chronic disease in the post-flight period was not 

examined.

Recommendations:

 In the near term:

 FAA should take a leadership role in protecting the health of passengers by 

working with airlines to evaluate how senior flyers are identified for in-flight 

oxygen use and when oxygen supplementation is used. At minimum, senior and 

vulnerable flyers should be polled to understand the incentives and disincentives 

for carrying and using personal oxygen equipment in flight.

 The FAA should extend the in-flight studies to test for the effects of prolonged 

exposure to hypoxia aboard intercontinental commercial flights of longer duration 

in order to better identify and manage risk. For example, ACER/RITE should 

conduct epidemiological studies to determine the true burden/cost of in-flight 

hypoxia to passengers in the post-flight period, such as in the management of their 

chronic disease after extended flights. These studies may be helped by the 

collaboration of health care insurers and providers. The findings would ensure 

public health protections for all passengers.

 The FAA should evaluate the physiological responses of aging cabin and cockpit 

crew to cabin pressures. Aging cabin crew who are more active at altitude, such as 

pushing service carts through the aisles, may be at greater a risk for moderate 

hypoxia.

 In the long term:

 Aircraft manufacturers and airlines should consider higher pressures to provide 

broader protection for an aging population with and without chronic disease.

 FAA should re-evaluate rules for cabin pressures to tolerate greater than 

previously expected drops in mean oxygen saturation at altitude based on past 

research from generally young and healthy populations. Higher cabin pressures 

may be more protective for vulnerable flyers. 
vi

CONTENTS

EXECUTIVE SUMMARY.................................................................................................................................. iii

INTRODUCTION .................................................................................................................................................1

APPROACH ...........................................................................................................................................................4

Overall Design..............................................................................................................................................4

Study Sample................................................................................................................................................4

Instrumentation: Measures ....................................................................................................................5

Data Analysis ................................................................................................................................................6

RESULTS................................................................................................................................................................7

Characteristics of the Sample.................................................................................................................7

Oxygen Saturation (SpO2) in Control and Flight Conditions.....................................................8

 Breathing and Heart Rate in Control and Flight Conditions ...................................................13

 Increased Rate of Ectopic Beats in Flight.......................................................................................17

 Passenger Report of Symptoms in Flight.......................................................................................20

CONCLUSIONS AND DISCUSSION.............................................................................................................22

REFERENCES....................................................................................................................................................25
1

INTRODUCTION

In the 50 years from 2000 to 2050, the world population of people age 60 and 

older will more than triple, increasing from 600 million to 2 billion (WHO, 2004). 

Researchers expect the percentage of the over-65 population who utilize air travel and 

the frequency with which they do so will be greater than previous over-65 populations 

because the Boomer generation was the first for which air travel was a common part of 

life including both low-cost business and recreational travel. This familiarity with air 

travel is expected to cause more Boomers to fly more often than previous generations

(McDougall, 1998; NERASP, 2006). 

The increase in older passengers means also an increase in unhealthy persons 

flying. In the U.S. 11.5% of the population has some type of heart disease, with over 27% 

of those 65-74 and over 37% of those 75 or older having some type of heart disease (CDC,

2006). Moreover, the National Heart Lung and Blood Institute (NHLBI) estimates that 

annually 195,000 first heart attacks occur silently, without prior symptoms or their 

recognition (AHA Statistical Update, 2011). In several observation studies, cardiac events 

caused 10%-20% of all in-flight incidents (Possick and Barry, 2004) and accounted for 12 

of 15 in-flight deaths on the five major US air carriers over a one-year period (DeJohn et 

al., 2000). The issue of cardiac health aboard aircraft has garnered enough attention to 

warrant the FAA to mandate the placement of at least one automatic external defibrillator 

on passenger aircraft (Federal Register, 2004).

Besides the higher prevalence of cardiac disease in aging Americans, these 

individuals have higher exposures to tobacco smoke from current or past cigarette 

smoking (either active or passive smoking), the number one risk factor for lung disease. 

The U.S. Surgeon General’s 2004 report on the health effects of smoking indicates that 

there is sufficient evidence to infer causal relationships between smoking and sub-clinical 

atherosclerosis, coronary heart disease, stroke, abdominal aortic aneurysm and chronic 

obstructive pulmonary disease morbidity and mortality (U.S. DHHS. 2004) . Chronic 

Obstructive Pulmonary Disease (COPD) affected 14.8 million American adults in 2009 

(CDC, 2009) and an additional 12 million demonstrate evidence of impaired lung 

function, indicating a potential under diagnosis of COPD (Mannino et al., 2002). 

Importantly, individuals with either lung or heart disease face special challenges in even 

mildly hypoxic environments such as that aboard aircraft.

Even in the absence of overt disease, older passengers may be vulnerable aboard 

aircraft. Medical scientists acknowledge that advanced age is accompanied by a general 

decline in organ function, such as the function of the heart or lungs (Priebe, 2000). 

Although the body generally exhibits compensatory mechanisms to maintain equilibrium, 

response times and performance may be compromised under stressful conditions

(Priebe, 2000). For example, vulnerability due to advanced age may be particularly true 

in an aircraft environment pressurized in accordance with research findings based on 

mostly healthy, fit, and younger subjects.
2

Many industries are studying how to best accommodate the aging population 

through innovations to make their activities both feasible and comfortable given some of 

the restrictions of older age. Boeing, for example, has worked with intergenerational 

designers to understand how to make the cabin design more attuned to the needs of the 

aging Boomer population and some of their changing capacities with respect to 

diminished vision, hearing, dexterity, flexibility, strength, and stamina (Ehrenman, 2005). 

In addition to the increasing numbers of potentially unhealthy passengers, the 

consideration of possible physiological effects from mild hypoxic environments on pilots 

and crew is important because the public relies on their optimal functioning to protect 

passenger safety in-flight. The Aerospace Medical Association, Aviation Safety Committee, 

released a position paper (Aerospace Medical Association, 2008) recommending further 

research about the effects of mild hypoxia for passengers and for these worker groups in 

particular. A number of research studies have shown performance decrements between 

5,000 and 10,000 feet, notably at altitudes below the current requirement for 

supplemental oxygen. In addition, the aging workforce of crew and pilots may be 

vulnerable at these altitudes because of the potential for reduced oxygen capacity related 

to aging and the onset of chronic disease in later life. In addition, the work of crew 

involves increased metabolic demand for oxygen as they service passengers and push 

utility carts down the aisles of jumbo planes at 34,000 feet.

In sum, the current FAA regulations for limiting cabin pressures to 8,000-feet 

equivalent altitudes allow for mildly hypoxic conditions. These environments are 

expected to have little effect on healthy passengers, pilots or crew, however, older 

individuals and persons with compromised cardiopulmonary status may be at risk. In 

addition, even though the FAA sets the minimum pressures for flying at 8,000 feet, the 

number of excursions from these levels is unknown. More than 30 years have passed 

since the thresholds for pressure were set. In the meantime, new composite materials in 

the fuselage that withstand cabin pressures greater than 8,000 feet have been developed 

and aircraft are able to fly higher and for longer periods, extending the exposure to 

hypoxia. Also, new portable devices that concentrate and deliver personal oxygen have 

been approved for medical conditions and for in-flight use. Yet experts argue that current 

guidelines that determine medical fitness for flying or the need for in-flight oxygen lack 

sufficient scientific evidence for health protection (Aerospace Medical Association, 2008).

At the same time, the rise in older and health-compromised passengers (Figure 1)

underscores the need to establish pressure-related health effects more precisely.
3

Figure 1. Number of people age 65 and over, by age group, selected years 1900-

2006 and projected 2010-2050 

To address the need for more information about the health effects of flying in 

vulnerable passengers, the current study aimed to answer the following questions:

1. What are the physiological demands on healthy older passengers and older 

passengers with chronic disease (specifically cardiac disease) related to cabin 

pressures? For example, what is the impact of age and cardiac disease on oxygen 

levels and cardiopulmonary loads at typical cabin pressures?

2. Are current medical guidelines that recommend medical evaluation of only those 

passengers with ground level oxygen saturations below 96% protective of moderate 

hypoxia in-flight? For example, what is the risk of moderate in-flight hypoxia in 

seniors when ground level oxygen saturation is above 95%?

3. What is the effect of typical cabin pressures on the passenger’s experience of 

symptoms? 
4

APPROACH

Overall Design

To understand the effects of mild hypoxia in older passengers, including those 

with chronic stable disease, we monitored individuals before, during, and immediately 

after, a 5-hour flight in a hypobaric chamber with pressurization equivalent to a 

commercial flight at 7,000 feet altitude. (While commercial airplanes usually fly at 

altitudes around 34,000 feet, pressurization of the cabin results in a pressure equivalent 

to no less than 8,000 feet.) In addition, we monitored these individuals for the same 

period of time in the chamber on another day at near sea level altitudes.

Subjects were assigned to one of seven weeks to complete both chamber days 

(control day and exposure day), with five to six participants in each trial. Each group was 

blinded to the exposure condition (decreased pressure). The order of the exposure day 

varied among the groups.

For a subset of the participants (n=6), we repeated the physiological 

measurements over three days during three commercial flights between Oklahoma City 

and Baltimore, Baltimore and Las Vegas, and Las Vegas and Oklahoma City.

Study Sample

Participants in the study had a prior history of air travel without reports of health 

complications. These individuals were over 50 years of age, either male or female, and 

met criteria for one of three subgroups of particular study interest: “healthy” nonsmokers, “healthy” smokers (i.e. smokers without diagnosed cardiac or respiratory 

disease), and stable cardiac patients without restricted activities of daily living. These 

subgroups were chosen to represent a “typical” older passenger and to fill gaps in the 

literature about the effects of flying for these passenger groups. We targeted older 

passengers because few studies have addressed the health consequences of mildly 

hypoxic aircraft environments for older passengers specifically. We included high 

functioning cardiac patients given the prevalence of the disease in this population and the 

known risks for hypoxia with cardiovascular impairment. Finally, we selected smokers to 

evaluate the potential for heightened oxygen deprivation at altitude secondary to 

impaired oxygen uptake in smokers (Nesthus and Wise, 1997).

In 2007, subjects were recruited through medical clinics, newspapers, senior 

centers and fitness centers in the greater Oklahoma City area because of access to the 

hypobaric chamber at the Federal Aviation Administration (FAA) Civil Aerospace Medical 

Institute (CAMI) in Oklahoma City. Volunteers were screened first by a nurse practitioner 

on the telephone and scheduled for a physical exam with a doctor within two weeks if 

they met inclusion criteria: age greater than 50, recent flying experiences without health 

complications, currently well, and no major diagnosed chronic disease, except in the 

selection for stable heart failure patients. The clinical evaluation further excluded 
5

individuals with serious or unstable health conditions and documented the baseline 

health status for qualified individuals including oxygen saturation, pulmonary function 

testing, electrocardiogram, blood pressure, urine and blood tests, and measurement of 

BMI. Volunteers were accepted into the study on a rolling admission.

Selected subjects participated in two days of monitoring in a hypobaric chamber, 

with a day off in between, during one of seven weeks (seven trials in total) between 

December 2007 and June 2008. Six of these subjects participated also in three

commercial flights in 2009. For the chamber experiment, researchers provided meals 

and paid participants three hundred dollars. For the commercial flight, participants 

received their airline tickets and money for meals and travel-related expenses. All study 

participants were consented in accordance with the protocols approved by the Human 

Subjects Committees at Harvard School of Public Health, CAMI, and the University of

Oklahoma Medical Center. 

The final sample for the chamber study consisted of 14 healthy seniors (without 

acute or chronic illnesses), 13 cardiac patients (12 of the cardiac patients had a diagnosis 

of mild to moderate heart failure; Grade I or II New York State criteria), and 14 smokers

without diagnosed cardiac or respiratory disease. All subjects completed both days of the 

chamber experiment except one cardiac patient who did not return for the second day 

because of a work conflict. For the commercial flights, four of the cardiac subjects and 

two of the healthy non-smoking subjects were included. 

Instrumentation: Measures

The CAMI hypobaric chamber was outfitted with 12 commercial airline seats 

arranged in for rows with three seats across. Participants were seated in rows 2 through 

4, one on the aisle and one against the window with the middle seat empty. Chamber

gauges recorded humidity, temperature, noise, pressure, carbon dioxide, and pressure. A 

medical monitor and a research assistant were present in the chamber with the 

participants during the experiments.

While seated in the chamber and also during the commercial flights, each 

participant wore a LifeShirtTM (Vivometrics, Inc. Ventura, CA, USA) to monitor cardiac and 

respiratory function. The LifeShirt is a fitted vest made of light-weight Lycra material that 

has embedded non-invasive sensors including a single-axis electrocardiograph and two 

respiratory sensors at the level of the rib cage and abdomen. The respiratory sensors are 

used for inductive plethsmography to derive respiratory data using the individual’s initial

calibrations set at the beginning of the test session. Derived respiratory measures 

include minute ventilation (a proxy for oxygen consumption and directly related to 

metabolic activity), tidal volume, and respiratory rate. The cardiopulmonary data were 

recorded into an attached data logger that also collected data about ambulatory blood 

pressure and pulse oximetry from peripheral devices. The data logger transmitted

wirelessly to computer displays outside the chamber for monitoring of each participant’s 

respiratory and cardiac waveforms in real time. During the commercial flights, the data 
6

were recorded and later downloaded after the trip. Vivologic software® is used to 

process and analyze these data according to time, waveform or derived variables.

Subjects completed symptom surveys at baseline and every hour while in the 

chamber including a post-test immediately following the experiment. The surveys 

included the Environmental Symptom Questionnaire (ESQ), a survey used to detect 

symptoms of altitude sickness. The ESQ lists sixty-eight symptoms along with a rating 

scale that the subject uses to indicate how any symptom is experienced: for example, 0= 

none at all, 1= slight, 2 = somewhat, 3= moderate, 4= quite a bit and, 5=extreme. In 

addition to the ESQ, we asked a separate question about how the subject was “feeling 

now” at each time using a seven-point Likert-type scale anchored by 1= “Poor” and 7= 

“Excellent” and 4= “Average for me” in the middle of the scale. Lastly, we measured the 

level of fatigue with a summative score from eight questions that also were rated for 

severity.

While in the hypobaric chamber, participants were encouraged to behave as they 

would aboard a commercial flight. They could eat, sleep, rest, read, watch movies, move 

about or talk freely. The research assistant served meals and snacks during the time in 

the chamber. A bathroom was located in the back section. For the commercial flights, no 

restrictions were placed on the passengers and a researcher accompanied the passengers 

during the commercial flights.

When participants were exposed to altitude in the chamber, research 

phlebotomists, entering and leaving the chamber through an adjacent pressure-locked 

room, collected blood specimens for CAMI genomic studies.

Data Analysis

All data were inspected for missing values and for normality. Median values 

derived from the raw physiological data for each minute were used to trend 5-minute 

averages of the cardiac and respiratory indices.

For SpO2 (peripheral oxygen saturation as measured by pulse oximetry), values of 

0% and any measures less than 5 minutes before or after were set to missing. In addition, 

values less than 70% were set to missing. Then 5-minute averages were calculated and 

those based on less than three 1-minute measures were set to missing. The main 

analyses of SpO2 levels compared subjects according to the following baseline 

characteristics: health/smoking status, physician- assessed SpO2, and age. We were 

interested in both comparing the magnitude of SpO2 decline from control to flight 

conditions as well as the absolute level of SpO2 during flight. Using SAS Proc Mixed 

(Version 9.2), we ran linear mixed effects models including both main effects for each 

baseline characteristic and interactions between these variables and an indicator for

flight versus control day to simultaneous estimate differences in SpO2 during simulated 

flight as well as the amounts by which they changed from control to simulated flight 

conditions. A random intercept for subject was included to account for correlation within 

subject in SpO2 and another random intercept for day nested within subject was included 
7

to account for within-day correlation for each subject. Moreover, a first-order 

autoregressive term was used to account for serial correlation of measures for the same 

subject on the same day.

Respiratory data were processed to limit motion artifacts at the 1-minute level by 

restricting breath rates from 5 to 50 breaths per minute and volumes from 50 to 3500 

milliliters. Then, 5–minute averages were calculated. Heart rates below 40 were 

eliminated before generating 5-minute averages. Once again we ran simple and adjusted 

mixed effect models to include main effects for each baseline characteristic and 

interactions between these variables. The models included also an indicator variable for 

flight versus control, a random intercept for subject, a random intercept for day, and a 

first-order autoregressive term to account for serial correlation of measures for the same 

subject on the same day.

The passengers’ electrocardiograms were also reviewed manually to identify 

artifact, and supraventricular and ventricular beats. Ectopic beats were compared using 

logistic and Poisson regression adjusting for time of day, exposure versus control 

condition and average heart rate (after removing person-hours with no events). 

For the symptom surveys, we ran mixed (multilevel) models for each of the 

outcomes (“feeling now”, fatigue score, and total ESQ symptoms) that included random 

subject effects to account for the correlation among repeated measures taken on a given 

subject. For each outcome, we fit two models to probe whether symptoms increased 

during flight compared to control conditions and whether symptoms increased over time. 

The first model contained the flight variable only, which estimates the effect of flight 

versus control, averaged over the time since the first survey (using survey number as the 

proxy). We then fit a second model that included flight, survey number, and the 

interaction between the two. This model estimates the effect of flight versus control on 

linear trends in the outcomes over time (survey number). 

RESULTS

Characteristics of the Sample

At baseline (collected at the time of the initial clinic evaluation), participants across 

the subgroups of “healthy”, “cardiac”, and “smokers”, had similar sea level oxygen 

saturation and body mass index, however, the “healthy” group was slightly older on 

average and the “cardiac” group had decreased lung function as noted by the percent 

predicted of forced expiratory volume at one minute (FEV1) and the percent predicted of 

forced vital capacity (FVC) (Table 1).
8

Table 1. Baseline characteristics of the study population.

* FEV1 and FVC are percent predicted volumes based on age, gender and ethnicity

Oxygen Saturation (SpO2) in Control and Flight Conditions

Table 2 below shows the mean oxygen saturation throughout the chamber study 

stratified by subject characteristics. The mean SpO2, recorded just before or after the 

experiment (outside the specific time for either the sham exposure or the pressurized 

exposure), and noted in Table 2 as “ambient conditions”, was similar (95%) among 

subjects, except for a very slight decrease (~.5% to 1%) in the mean value for those 

subjects with a baseline SpO2 of <96% at the clinic exam or on the day of the chamber 

testing. Health status (“healthy”, “cardiac”, or “smoker”) and age (dichotomized at <65 

years) showed similar mean differences in SpO2 for both ambient conditions and control 

days of the experiment. 

On flight days, such as during exposure to 7,000 feet, the mean SpO2 of 90% was 

fairly consistent across the subject characteristics/categories except for a lower mean 

SpO2 reading in subjects with lower saturation at baseline (<96%).
9

Table 2. Summary of 5-minute average pulse oxygen saturation readings under 

ambient and chamber conditions on control and flights. 

Period/group Control Days Flight Days

Subjects 

(N)

Mean(SD); Range Subjects 

(N)

Mean (SD); Range

Ambient conditions

 Overall 40 (452) 95.7 (1.9); 87.2, 99.2 41 (866) 95.6 (2.0); 87.4, 99.3

 Healthy 14 (230) 95.6 (1.9); 87.2, 99.2 14 (350) 95.5 (2.2); 87.4, 98.8

 Cardiac disease 12 (91) 95.8 (1.6); 91.2, 99.0 13 (288) 95.9 (1.7); 87.5, 99.0

 Smoker 14 (131) 95.9 (2.1); 91.3, 99.0 14 (228) 95.6 (2.1); 89.0, 99.3

 Pre-post SpO2 ≥96% 23 (294) 96.6 (1.3); 92.2, 99.2 23 (632) 96.5 (1.3); 91.2, 99.3 

 Pre-post SpO2 <96% 17 (158) 94.0 (1.7); 87.2, 97.6 18 (234) 93.4 (1.8); 87.4, 98.0

 Baseline SpO2 ≥96% 34 (379) 95.9 (1.9); 89.8, 99.2 35 (743) 95.8 (2.0); 89.0, 99.3

 Baseline SpO2 <96% 6 (73) 95.0 (1.7); 87.2, 97.7 6 (123) 94.5 (1.7); 87.4, 98.0

 Age <65y 23 (260) 95.8 (2.1) 87.2, 99.0 24 (497) 95.7 (2.1); 87.4, 99.3 

 Age ≥65y 17 (192) 95.7 (1.7); 89.8, 99.2 17 (369) 95.6 (1.9); 89.0, 99.0

Chamber period

 Overall 40 (2057) 95.2 (1.7); 86.0, 99.2 41 (2244) 90.6 (2.5); 75.5, 97.0

 Healthy 14 (588) 95.4 (1.8); 89.6, 98.6 14 (655) 90.5 (2.4); 81.8, 96.4 

 Cardiac disease 12 (632) 95.6 (1.6); 87.0, 99.2 13 (765) 90.6 (2.2); 85.6, 96.4

 Smoker 14 (837) 94.9 (1.8); 86.0, 99.0 14 (824) 90.7 (2.8); 75.5, 97.0

 Pre-post SpO2 ≥96% 23 (1474) 95.8 (1.5); 86.0, 99.2 23 (1568) 91.4 (2.2); 75.5, 97.0

 Pre-post SpO2 <96% 17 (583) 93.7 (1.4); 89.6, 97.2 18 (676) 88.7 (1.9); 81.8, 93.6

 Baseline SpO2 ≥96% 34 (1845) 95.3 (1.8); 86.0, 99.2 35 (1998) 90.8 (2.5); 75.5, 97.0

 Baseline SpO2 <96% 6 (212) 95.0 (1.2); 89.6, 97.2 6 (246) 89.3 (2.1); 83.4, 93.6

 Age <65y 23 (1248) 95.3 (1.8); 87.0, 99.2 24 (1336) 91.1 (2.5); 81.8, 97.0

 Age ≥65y 17 (809) 95.2 (1.6); 86.0, 98.8 17 (908) 89.9 (2.3); 75.5, 95.8

To further explore the changes in SpO2 from control to flight conditions, we plotted 

the distribution of mean changes in oxygen saturation for all subjects in Figure 2 below.

The points in Figure 2 are each subject’s mean change from control to flight condition. 

The line is based on the mean 5-minute differences for the sample (subtracting the 

subject’s mean SpO2 on control day from each 5-minute measure during flight). We can 

see crudely from this plot that generally individuals with lower baseline SpO2 declined

more in flight. We see also that while this trend was true in general, for a few subjects 

with higher baselines this was not the case; some subjects with higher SpO2 baselines 

still experienced large declines in SpO2. For example, five of the subjects with baseline 

SpO2 above 96% lost ≥ 5 percentage points in oxygen saturation during flight. 
10

Figure 2. Subject-level mean changes in SpO2 during flight according to baseline 

oxygen saturation

We can see, further, the overall effect of baseline oxygen saturation on the level of

oxygen saturation in flight in Figure 3. Here we plot the proportion of time any 5-minute 

average oxygen saturation value fell within a specific SpO2 measure during flight 

according to the individual’s baseline SpO2 category (<96% vs ≥96%). In other words, 

the total person-time across all data points in flight was distributed according to whether 

the subject started below 96% SpO2 at baseline. For subjects starting with a lower 

baseline (the top box in Figure 3), the distribution of in-flight 5-minute values shifts to 

the left, and more points fall below 90% SpO2, compared with subjects that began with 

higher oxygen saturation. Importantly, even when subjects started with higher oxygen 

saturation at baseline (≥ 96%), there was still a considerable amount of person-time 

spent below 90% saturation during flight in this sample of older passengers. 
11

Figure 3. The distribution of 5-minute average SpO2 values according to baseline 

SpO2<96%

We can observe more specifically the effect of age on in-flight oxygen saturation in 

Figure 4. According to this plot, compared to age <65 years, age ≥65 is associated with a 

greater frequency of 5-minute average oxygen saturation measures below 90% 

(moderately hypoxic level and the level at which patients typically receive oxygen in the 

emergency room).

Figure 4. The distribution of 5-minute average SpO2 values according to age <65
12

While the plots displayed above point out the impact of baseline SpO2 and age on 

oxygen saturation in flight, the significance of these effects are clearly observed in the 

mixed model regressions (Table 3) that summarize the combined effects of age, health 

status, and baseline SpO2, and adjust also for day (exposure first day in the chamber or 

second day), gender, and other baseline groupings listed in the Table 3 and their 

interactions with a flight versus control day indicator variable.

Table 3. Effect of pre-flight subject characteristics on oxygen saturation during 

simulated flight, measured as both change compared to control day and absolute 

levels during simulated flight.

Period/group Crude Adjusted*

Difference in change in SpO2 from control to flight days

Healthy reference Reference = -4.0

Cardiac disease -0.01 (-1.10, 1.08) -0.02 (-1.10, 1.07)

Smoker 0.19 (-0.87, 1.24) 0.19 (-0.87, 1.25)

Baseline SpO2 ≥96% Reference = -3.9

Baseline SpO2 <96% -1.16 (-2.32, -0.00) -1.12 (-2.36, 0.12)

Age (per 10 years) -0.63 (-1.16, -0.10) -0.66 (-1.20, -0.13)

Difference in SpO2 during flight

Healthy reference Reference = 90.6

Cardiac disease 0.13 (-1.38, 1.64) -0.17 (-1.49, 1.15)

Smoker -0.27 (-1.96, 1.41) -0.85 (-2.45, 0.76)

Baseline SpO2 ≥96% Reference = 90.9

Baseline SpO2 <96% -2.11 (-3.94, -0.29) -2.01 (-3.73, -0.30)

Age (per 10 years) -0.79 (-1.55, -0.04) -0.88 (-1.62, -0.13)

* Adjusted for day (exposure first day or second day in the chamber), gender, and other baseline groupings listed in the 

table. 

Interestingly, the difference in SpO2 from control to flight days was not related to 

whether the subject was in the healthy, cardiac or smoker group. The decline in SpO2 

from control days to simulated flight days was similar for subjects in each of these

subgroups. Baseline SpO2 below 96% as assessed independently by a physician, however,

was associated with a greater decline in SpO2 between control and simulated flight days, 

and this association was borderline statistically significant after adjustment for potential 

confounders (p-value = 0.078). Each 10- year increase in age was significantly associated 

with a 0.66% (95% CI: -1.20, -0.13) greater decline in SpO2 from control to simulated

flight days (p-value = 0.015). (Refer to the top of Table 3 for overall change from control 

to flight days)
13

The lower part of Table 3 shows the absolute difference in SpO2 during flight 

according to each of the categories. There was no evidence of a difference in the absolute 

value of SpO2 during flight between the health subjects, cardiovascular disease patients, 

and smokers. Baseline SpO2 below 96%, however, was associated with a 2.42% lower 

SpO2 during flight (p-value = 0.021). Each 10-year increase in age was associated with a 

0.88% lower SpO2 during simulated flight days (p-value = 0.040). 

As further test of the effect of flight on oxygen saturation, we compared the oxygen 

saturation for each of the six chamber subjects who later flew aboard the commercial 

flights and observed similar results. We found no real differences between each subject’s

baseline oxygen saturation levels before and after all of the test periods, including the 

pre-post periods before the chamber sequence and each of the commercial flights. In 

addition, we observed no real differences in oxygen saturation levels during the 

simulated flight and each of the three actual flights (Table 4). Importantly, means tests for 

significant differences in this small sample do not rule out a chance finding.

Table 4. Comparison of chamber simulated and actual flight: summary of altitudes, oxygen 

saturation (SpO2), including same-day comparison periods before and after flights.*

Chamber Flight 

1085

Flight 

2861

Flight 1377

Before and after periods period

Number of 5-min 

measures

105 132 138 148

Altitude - test site (ft) 1,311 1,201 33 2,014

SpO2 (%) 95.9 (1.4) 96.4 (1.4) 95.4 (1.6) 94.7 (1.3)

Flight period

Flight Duration 4 h 20 m 2 h 45 m 5 h 9 m 2 h 12 m

Number of 5-min 

measures

287 96 268 80

Altitude (ft) 7,110 (146) 6,985 

(68)

7,064

(150)

7,133 

(0)

SpO2 (%) 90.9 (1.7) 90.8 (1.7) 90.7 (1.5) 90.6 (1.6)

*All variables are analyzed only for 5-minute intervals for which a valid SpO2 measure was obtained.

Measurements from commercial flight periods include those after 15 minutes of reaching a cruising 

altitude of over 6,000 feet up until 5 minutes before start of descent. Before and after periods include 

measures up to 2 hours before takeoff or 2 hours after landing for flight or simulated flight.

Breathing and Heart Rate in Control and Flight Conditions

Because the body works to maintain homeostasis in stressful environments, such 

as hypoxic conditions, we were interested in the impact of flight on breathing measures 

and heart rate. Table 5 shows the descriptive statistics for breathing and heart rate in the 

chamber according to the passenger categories of interest: age, health group, and 

baseline SpO2. Overall, breathing and heart rate appear to increase under flight 

conditions compared to control conditions. 
14

Table 5. Breathing and Heart Rate Measures – Chamber Study.

Period/group Control Days Flight Days

Subjects (N) Mean(SD); Range Subjects(N) Mean (SD); Range

Breathing rate (breaths per minute]

 Overall 40 (2289) 20.4 (4.9); 6.8, 41.9 41 (2334) 22.0 (5.2); 7.3, 45.7

 Healthy 14 (682) 20.7 (4.5); 6.8, 37.6 14 (696) 21.1 (5.1); 7.3, 45.7

 Cardiac disease 12 (748) 22.6 (5.3); 10.9, 41.9 13 (798) 23.1 (5.8); 11.4, 45.3

 Smoker 14 (859) 21.0 (4.7); 9.3, 40.8 14 (840) 21.6 (4.5); 11.3, 39.5

 Baseline SaO2 ≥96% 34 (1954) 21.7 (5.1); 6.8, 41.9 35 (2021) 22.0 (5.4); 7.3, 45.3

 Baseline SaO2 <96% 6 (335) 20.2 (3.0); 14.2, 32.3 6 (313) 21.7 (4.3); 12.3, 45.7

 Age <65y 23 (1345) 21.5 (5.0); 9.3, 40.8 24 (1378) 21.9 (5.5); 10.8, 45.7

 Age ≥65y 17 (944) 21.4 (4.8); 6.8, 41.9 17 (956) 22.1 (4.8); 7.3, 39.5

Tidal volume (ml)

 Overall 40 (2289) 612 (282); 55, 2218 41 (2334) 698 (286); 162, 2663

 Healthy 14 (682) 611 (251); 164, 1526 14 (696) 671 (284); 187, 2663

 Cardiac disease 12 (748) 624 (310); 185, 2218 13 (798) 678 (315); 162, 2153

 Smoker 14 (859) 602 (281); 55, 1994 14 (840) 741 (254); 282, 2274

 Baseline SaO2 ≥96% 34 (1954) 609 (291); 55, 2218 35 (2021) 715 (271); 202, 2274

 Baseline SaO2 <96% 6 (335) 628 (225); 216, 1772 6 (313) 589 (353); 162, 2663

 Age <65y 23 (1345) 581 (299); 55, 2218 24 (1378) 709 (320); 162, 2663

 Age ≥65y 17 (944) 657 (251); 218, 1997 17 (956) 684 (229); 298, 2274

Minute ventilation (L/min)

 Overall 40 (2289) 13.5 (7.6); 0.9, 68.1 41 (2334) 15.8 (8.6); 3.4, 79.2

 Healthy 14 (682) 12.6 (5.4); 2.4, 37.3 14 (696) 14.4 (7.7); 3.4, 78.9

 Cardiac disease 12 (748) 14.5 (8.4); 3.0, 57.1 13 (798) 16.4 (9.9); 3.4, 67.4

 Smoker 14 (859) 13.3 (28.9); 0.8, 296.1 14 (840) 16.5 (7.9); 5.5, 79.2

 Baseline SaO2 ≥96% 34 (1954) 13.5 (7.8); 0.9, 68.1 35 (2021) 16.2 (8.4); 3.9, 79.2

 Baseline SaO2 <96% 6 (335) 13.3 (6.4); 4.3, 52.9 6 (313) 13.2 (9.2); 3.4, 78.9

 Age <65y 23 (1345) 13.1 (8.3); 0.9, 64.6 24 (1378) 16.2 (9.6); 3.4, 78.9

 Age ≥65y 17 (944) 14.0 (6.3); 4.3, 68.1 17 (956) 15.3 (6.9); 5.2, 79.2

Heart rate (beats per min [bpm])

 Overall 40 (2287) 78 (11); 44, 109 41 (2288) 80 (12); 44, 119

 Healthy 14 (681) 77 (11); 50, 109 14 (681) 81 (12); 54, 119

 Cardiac disease 12 (717) 78 (9); 44, 106 13 (756) 80 (12); 44, 112

 Smoker 14 (888) 78 (12); 56, 109 14 (851) 80 (11); 59, 115

 Baseline SaO2 ≥96% 34 (1997) 78 (11); 44,109 35 (2003) 80 (12); 44, 115

 Baseline SaO2 <96% 6 (290) 75 (7); 59, 105 6 (285) 78 (9); 60, 119

 Age <65y 23 (1361) 80 (11); 44, 109 24 (1391) 82 (12); 44, 119

 Age ≥65y 17 (926) 75 (10); 50, 109 17 (897) 78 (10); 54, 111
15

In the fully adjusted multi-level mixed models (Table 6) breathing does in fact 

increase in flight with borderline significance and heart rate significantly increases 2.4 

beats per minute over the flight also.

Table 6. Effect of flight on respiratory parameters and heart rate. Comparison of 5-

min average measures during simulated flight at altitude and control days in the 

chamber*.

Crude Adjusted for experimental order

Effect (95% CI) p-value Effect (95% CI) p-value

 Breathing rate 0.51 (0.02, 1.05) 0.060 0.64 (0.00,1.28) 0.050

 Tidal volume (ml) 79 (-18,176) 0.107 66 (-50,183) 0.258

 Minute ventilation (L) 2.1 (-0.1,4.3) 0.061 1.7 (-0.9, 4.3) 0.185

 Heart rate (bpm) -0.27 (-0.61, 0.06) 0.113 2.4 (0.7, 4.1) 0.007

* Models include random intercept for subject, random flight for subject for effect of flight, and 

autoregressive correlation among subsequent 5-minute measures. 

Although we observed increased breathing rates and heart rates in flight, we 

were interested to know if these events were related to the passenger’s level of hypoxia. 

These mixed model regression results are presented in Table 7. 

Only breathing rate was borderline significantly positively associated with 

SpO2 levels during flight across the entire sample. Notably, cardiac patients showed 

significantly larger increases in all respiratory indices (rate, volume and minute 

ventilation) in association with SpO2 when compared to the other health groups. In 

addition, heart rate was inversely associated with oxygen levels in cardiac patients, 

although these changes were minor and insignificant. 

We were surprised by the direction of these relationships if increased 

breathing rate and heart rate were expected to compensate for hypoxia (decreased 

oxygenation). The pattern we observed instead was that breathing rates increased when 

oxygen levels increased. Further, for cardiac patients specifically, that breathing response 

was exaggerated and followed the same unexpected pattern; the rise in all of the 

breathing indices (breathing rate, tidal volume and minute ventilation) was significantly 

associated with an increase in oxygen saturation. 

This intensified breathing response in the cardiac patients may make more 

sense as hypoxic compensation if one considers that these heart patients may depend 

more on respiratory responses when compensatory cardiac stimulation is depressed 

under the influence of beta blocker medications prescribed for these patients. In 

addition, the contemporaneous associations we observed would not account for lagged 

effects in hypoxic compensation. In this light, increased respiratory effort as SpO2 rises

may be a logical compensatory response pattern in hypoxia.
16

Table 7. Association between SpO2 during simulated flight and cardiopulmonary 

indices. Effects expressed per 1% change in 5-minute average SpO2.

Crude Adjusted*

Effect (95% CI) p-value Effect (95% CI) p-value

All 

 Breathing rate 0.16 (-0.3, 0.36) 0.102 0.18 (-0.01, 0.37) 0.062

 Tidal volume (ml) 6.0 (-5.3, 17.2) 0.298 6.8 (-3.8, 17.3) 0.207

 Minute ventilation (L) 0.16 (-0.23, 0.55) 0.426 0.19 (-0.18, 0.56) 0.307

 Heart rate (bpm) -0.27 (-0.61, 0.06) 0.113 -0.27 (-0.60, 0.07) 0.120

Cardiac disease

 Breathing rate 0.40 (0.06, 0.75) 0.023 0.39 (0.05, 0.74) 0.027

 Tidal volume (ml) 23.6 (4.5, 42.6) 0.015 20.4 (1.0, 39.8) 0.039

 Minute ventilation (L) 0.82 (0.20, 1.43) 0.009 0.72 (0.07, 1.36) 0.029

 Heart rate (bpm) -0.30 (-1.04, 0.44) 0.423 -0.32 (-1.09, 0.44) 0.410

*Age, gender, time in chamber since start of flight or control conditions. 

As further test of the effect of flight on heart rate and breathing indices, we 

compared the chamber results to the findings from the commercial flights for each of the 

six chamber subjects who participated in these tests. Interestingly, we found the results 

were remarkably similar between both conditions (Table 8). 

We found no real differences between each subject’s baseline measures of 

breathing and heart rates (as measured before the test and included also the period 

immediately after the test), except for in the case of the Flight 2861. In this case, tidal 

volumes were higher at baseline and in flight. Flight 2861 was the longest low pressure 

exposure time by approximately one hour for the study participants, even when 

compared to chamber times. Given that the baseline measures for the commercial flights 

included readings from both pre and post flight periods, we considered that increased 

baseline tidal volumes for Flight 2861 may have captured residual spillover effects of

increased tidal volumes during the flight in this composite baseline measure. 

To understand what was happening to breathing during Flight 2861, we ran a 

mixed model with random intercepts accounting for autocorrelation to test for the slope 

over time during Flight 2861 among the six passengers. There is a statistically significant 

increase associated with time in flight of about 33 ml in tidal volume per hour (p-value = 

0.019). This slope is only significant for this long flight and not the other two.

Importantly, means tests for significant differences in this small sample do not rule out a 

chance finding. 
17

Table 8. Comparison of chamber simulated and actual flight: heart rate, and 

breathing indices, including same-day comparison periods before and after 

flights*. 

Chamber Flight 1085 Flight 2861 Flight 1377

Before and after periods period

Number of 5-min measures 105 132 138 148

Heart rate 79 (8) 75 (14) 77 (12) 84 (14)

Breathing rate 22 (7) 29 (6) 28 (7) 28 (7)

Tidal Volume (ml) 712 (239) 763 (336) 1112 (383) 708 (294)

Minute ventilation (L/Min) 16 (8) 22 (13) 32 (16) 21 (13)

Flight period

Flight Duration 4 h 20 m 2 h 45 m 5 h 9 m 2 h 12 m

Number of 5-min measures 287 96 268 80

Altitude (ft) 7,110 (146) 6,985 (68) 7,064(150) 7,133 (0)

Heart rate 77 (12) 75 (12) 73 (11) 76 (12)

Breathing rate 22 (5) 22 (5) 21 (5) 21 (6)

Tidal Volume (ml) 642 (336) 579 (237) 780 (189) 569 (222)

Minute ventilation (L/Min) 14 (9) 13 (7) 17 (7) 12 (9)

*All variables are analyzed only for 5-minute intervals for which a valid SpO2 measure was 

obtained.

Increased Rates of Ectopic Beats in Flight

As discussed previously, we observed a significant effect of flight on heart rate. 

We found also a combined effect of flight and time in flight on heart rate (Figure 5). As 

seen below, the heart rate increases steadily over time only on flight days.

Figure 5. The effect of the interaction between the exposure of flight and the 

duration of flight passenger on heart rate
18

To further evaluate the consequences of cardiac stimulation in flight, we plotted 

the frequencies of ectopic (extra) beats in the control period versus flight periods from

the chamber experiments. (Figure 6 and Figure 7)

We found that the odds of having any ventricular or atrial ectopy were not 

significantly different between simulated flight and control days. However the rate of 

ventricular couplets or runs of 3 or more beats were significantly higher during simulated 

flight compared to control conditions. 

Importantly, arrhythmias occurred only in those subjects who had arrhythmias in 

the control period and all of these subjects were heart failure patients.

Figure 6. Frequency of ventricular couplets during flight compared to control 

(ground) conditions

0 1 2 3 4

1 2 - 4 5 - 8 9 - 16 17 - 32 33 - 64 65 - 128

Control period

Ventricular couplets per hour

0 1 2 3 4

1 2 - 4 5 - 8 9 - 16 17 - 32 33 - 64 65 - 128

Simulated flight Number of person-hours
19

Figure 7. Frequency of ventricular runs (3 or more extra beats) during flight 

compared to control (ground) conditions

Ventricular ectopic beats occurred in couplets among eight of the subjects, during 

32 subject-hour intervals, at an average rate of 22 (SD=33) within these intervals, and in 

runs of three or more among seven subjects, during 26 of the subject-hours, at an average 

rate of 9 (SD=19). Table 9 displays the counts of ectopy under control and flight 

conditions.

Table 9. Number of persons and person-hours with ectopic beat events and rates of 

events per hour during periods when events occurred.

Subjects with any 

event (%)

Periods with any 

event (%)

Rate per hour (SD)*

Control 

Period

(n=38)

Simulated 

Flight

(n=38)

Control 

Period

(n=172)

Simulated 

Flight

(n=182)

Control 

Period

Simulated 

Flight

VE couplets 4 (11) 5 (13) 13 (8) 14 (8) 15 (14) 33 (46)

VE runs 5 (13) 4 (11) 10 (6) 13 (7) 4 (4) 14 (25)

SVE couplets 9 (24) 11 (29) 15 (9) 20 (11) 1.4 (1.0) 1.8 (1.4)

SVE runs 5 (13) 3 (8) 7 (4) 5 (3) 1.5 (0.6) 1.2 (0.4)

VE – ventricular ectopy SVE – suprventricular ectopy

* During person hours when events occurred.

0 2 4 6 8

1 2 - 4 5 - 8 9 - 16 17 - 32 33 - 64

Control period

Ventricular runs per hour

0 2 4 6 8

1 2 - 4 5 - 8 9 - 16 17 - 32 33 - 64

Simulated flight Number of person-hours
20

Among subject-hours when couplets of ectopic ventricular beats occurred, the 

adjusted rate ratios were 3.5 (95% CI: 1.3, 9.5) for couplets and 9.4 (95% CI: 3.2, 27.3) for 

runs of three or more ventricular ectopic beats after removing one outlier in Model 2 in 

Table 10. Also adjusting for average heart rate during each subject-hour resulted in a 

similar rate ratio for couplets and a larger effect estimate for runs, but the confidence 

intervals were wider. 

Table 10. Rate ratios for hourly counts of ventricular ectopic events associated 

with simulated flight versus control period in chamber.

Outcome Subjects (N) and 

person-hours

Model 1 Model 2

Ventricular 

ectopic couplets

6 (27) 8.9 (1.7, 46.1) 3.5 (1.3, 9.5)

Ventricular 

ectopic runs

6 (23) 26.4 (6.2, 112.2) 9.4 (3.2, 27.3)

1 Model 1: generalized estimating equations for Poisson counts of couplets or runs of ectopic beats, 

accounting for correlation within subjects and adjusting for week, time of day at start of each 1-hour 

interval

2 Model 2: same as Model 1 except one outlier removed from simulated flight exposure

Passenger Reports of Symptoms in Flight

The association between symptom reporting and altitude was not differentiated at 

the chamber pressures (7,000 feet). Either an increase in symptoms or an increase in the 

severity of symptoms, were not associated with flight versus control conditions. Instead, 

symptoms reports were more closely associated with the passage of time.

Figure 8 is the plot of the mean scores across the different conditions of flight 

(7,000 feet) and control (sea-level), the time (hour), and the three different symptom 

measures (“feelingnow”, fatigue, and ESQ). These scales were previously described under 

“Approaches” in the “Instrumentation: Measures” sub-section.
21

Figure 8. Survey scores by time period

None of these symptom outcomes were normally distributed. The feelingnow and 

fatigue outcome (based on Likert scales) were quite discrete, and so we fit these with a 

mixed cumulative logit model for ordinal outcomes. The resulting coefficients (Table 11) 

represent the log odds ratio of falling in a high category versus falling in a low category. 

For feelingnow, the main effect of flight was marginally insignificant (p=07), with flight 

associated with lower scores. The estimated odds ratio of falling in a higher category 

versus a lower category associated with flight (versus control) is 0.72 (95% CI: 0.51, 

1.04). There were strong effects of time (i.e. survey number) overall (p<0.001), with later 

times associated with lower feelingnow scores. The estimated odds ratio for a higher 

(versus lower) score associated with each additional survey number is 0.76 (95% CI: 

0.67, 0.86). There were no effects of flight on trends over time for feelingnow. There were 

no effects of flight (either overall or on trend over time) on fatigue. 

Due to the aggregation of multiple questions, the ESQ was approximately lognormally distributed. Therefore, we fit a linear mixed model for the transformed 

log(ESQ+1) outcome. There were no significant effects of flight on ESQ and no effect of 

flight over all times or with respect to trends over time. ESQ did decrease significantly 

over time, approximately a 5.6% increase in ESQ score per additional survey. 
22

Table 11. Models of symptom outcomes, flight effect and time (surveynum), and 

interaction effects

Outcome: log(ESQ+1)

 Model 1. Flight only

Estimate Std. Error t value

(Intercept) 2.66879 0.09873 27.032

Flight 0.03500 0.04455 0.786

Model 1. Flight, surveynum, interaction

Estimate Std. Error t value

(Intercept) 2.505989 0.108435 23.110

Flight 0.001369 0.076526 0.018

surveynum 0.054351 0.014941 3.638

Flight:surveynum 0.011676 0.021244 0.550 

Outcome: feelingnow

 Model 1: 

 Location coefficients:

 Estimate Std. Error z value Pr(>|z|)

Flight -0.3224 0.1827 -1.7649 .077584

Model 2: 

Estimate Std. Error z value Pr(>|z|) 

Flight -0.4507 0.3250 -1.3867 0.1655419

surveynum -0.2740 0.0654 -4.1919 2.7657e-05

Flight:surveynum 0.0335 0.0914 0.3661 0.7142647

Outcome: fatigue

 Model 1: 

 Location coefficients:

 Estimate Std. Error z value Pr(>|z|) 

Flight 0.1613 0.1601 1.0075 0.31369404

 Model 2: 

 Location coefficients:

 Estimate Std. Error z value Pr(>|z|) 

Flight -0.1972 0.2734 -0.7215 0.47060620

surveynum -0.0039 .0503 -0.0773 0.93837379

Flight:surveynum 0.1250 0.0766 1.6307 0.10295707

CONCLUSIONS AND DISCUSSION

This study is the first single-blind investigation we know to include a broad 

accounting of physiological effects of cabin pressure in older and susceptible passengers. 

The results suggest that a significant portion of older passengers may be moderately 

hypoxic (≤ 90% oxygen saturation) at 7,000 feet equivalent cabin pressures, pressures 

still slightly above the regulated limit to 8,000 feet. 
23

Although we do not know the full extent of health impact for seniors from the

hypoxia we observed in flight, several of the physiological markers that we tracked 

suggest that the flying experience may be more stressful than previously understood. In 

this sample, moderate hypoxia was common with almost half of the older passengers 

reaching SpO2 levels ≤90 for a significant amount of time during the flight in addition to

changes in breathing rates. Further, cardiac stimulation was apparent by an average 

increase in heart rate of 2.4 beats per minute over the medium flight time (4- 5 hours).

Also at these cabin pressures, the rate of ectopic beats increased in passengers with heart 

failure. Interestingly, according to current medical guidelines, most of the seniors in our 

study would have been considered low risk for moderate hypoxia according to their sea 

level oxygen saturations (Mortazavi et al., 2003; British Thoracic Society Standards of 

Care Committee, 2002).

Prior studies have found that in-flight oxygen saturations are typically higher than

what we observed. One comprehensive study found a maximum decrease in oxygen 

saturation of 4.4% but the sample was younger and healthier than the participants in our 

study (Muhm et al., 2007). Another recent study with a sample matching our own, 

including cardiac patients, found that while the overall probability of achieving moderate 

hypoxia was low for the sample, the risk was higher in the 60 years and over age group

(Grun et al., 2008).

Past studies have found, also, that hypoxic levels at cruise altitudes did dip as low as 

in our study (Kelly, 2009; Schacke et al., 2007; Seccombe et al., 2006; Akero et al., 2005; 

Dillard et al., 1989). However, some of these findings are limited pulse oximetry is the 

only outcome measure and often, only a single measurement of saturation (Humphreys 

et al., 2005) or small sample sizes (Kelly et al., 2006; Christensen et al., 2002; Christensen 

et al., 2000).

The results of studies that have looked at compensatory signs of cabin altitudes, 

such as cardiac and respiratory biomarkers, are mixed. However, many of these studies 

are limited to pulse rate only. In contrast, Akero et al. (2005) examined a number of 

cardio-pulmonary responses and found evidence for hypoxia induced sympathetic 

arousal including increased heart rate and evidence of hyperventilation after four hours 

with mean oxygen saturation drops to 87%, compared with 95% at ground level in the 

subjects. These results are in line with our findings and argue that at moderate saturation 

levels experienced at cabin altitudes over medium range flights (4-5 hours), seniors and 

vulnerable passengers are working harder to compensate. What this means for them over

longer flights is still to be determined. Nonetheless, these signs correspond to 

sympathetic arousal that may be worrisome in vulnerable passengers, such as heart 

failure patients (Silverman and Gendreau, 2009; Mortazavi et al., 2003).

Despite this evidence for system loading, such as cardiopulmonary arousal in flight, 

researchers still disagree about the level of “tolerable” hypoxia. Some authors have 

argued that because passengers reported “feeling fine”, that the decreased oxygen 

saturations were tolerable (Muhm et al., 2007). We caution about this interpretation 
24

based on our finding that symptom reports do not differentiate between control or flight 

conditions. Thus, symptom reports may be an insensitive indicator of the physiological 

load of flight and results from at least a few other studies would support this finding 

(Schwartz et al., 1984; Kelly et al., 2006).

Ours is not the first study to find that diagnostic categories are not particularly 

helpful in predicting oxygen saturation levels in flight (Robson et al., 2008). We found no 

difference in oxygen saturations for the healthy seniors compared to the cardiac and 

smoker groups. A more important differentiator between groups was how individuals 

responded to hypoxic states physiologically and this response was related to their disease 

state. The ability to compensate for hypoxia was notably different for the cardiac patients.

In particular, the heart rate and breathing changed more with oxygen saturations in this 

group compared to healthy seniors and senior smokers.

Taking note of the difference in the responses to hypoxia underscores the subtle but 

important point that most of what we know about cabin pressure effects is based more 

on oxygen saturation levels than on the sequelae. But this is beginning to change. We 

believe our own study is a step in this direction by following signs of compensatory 

mechanisms in the presence of hypoxic conditions. More recent studies are looking at

health outcomes in the 48-hour time span after air travel to show health impacts ranging 

from exacerbation of symptoms in COPD patients to myocardial infarction (Edvardsen et 

al., 2011; von Klot et al., 2011).

Finally, the evaluation of in-flight hypoxia has been limited in the past to young and 

healthy passengers on the one hand, and very sick, usually pulmonary patients, on the 

other. Our study has attempted to consider other sources of risk that apply to a broader 

spectrum of the flying public, and that include a more informed understanding about how 

senior age affects responses at cabin altitudes. The study of risk related to hypoxia at 

usual cabin altitudes is not well understood for other groups, especially for cabin crew 

that expend more energy at altitude and may present with concomitant occupational 

problems like sleep deprivation secondary to shift work that would further complicate 

hypoxia. This issue in particular has not been studied. Therefore, future studies should 

target this group in particular.

In summary, this study found moderate hypoxia, sufficient to produce 

compensatory mechanisms, to be prevalent in senior passengers. The study is a first of 

this kind to profile a full range of physiological signs, however, more work still needs to 

be done. For instance, we still know little about the health of passengers following long 

flights. The research on the risks of thromboembolism after travel is a good template for 

investigations about other health outcomes after flight (Gallus, 2005; Kelman et al., 

2003).

Our study was innovative in that we collected comprehensive, continuous, and 

repeated measures from passengers over several days (prescreening, chamber days and 

for some subjects, additional in-flight days). However, we wish to acknowledge several 

limitations. First, the sample size was small, especially with regard to the cardiac patients 
25

and the number of passengers that were tested aboard commercial flights. Also we

recognize that pulse-oximetry is an indirect measure of oxygen saturation and may not 

have been accurate for the smokers in our sample. In any case, the problem would be to 

overestimate the level of oxygen saturation.

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