-----------------------------------------------------------
REPORT OF THE CONFERENCE ON
SOCIOECONOMIC STATUS AND
CARDIOVASCULAR HEALTH AND DISEASE
November 6-7, 1995
National Heart, Lung, and Blood Institute
National Institutes of Health
-----------------------------------------------------------
REPORT OF THE CONFERENCE ON
SOCIOECONOMIC STATUS AND
CARDIOVASCULAR HEALTH AND DISEASE
November 6-7, 1995
For Administrative Use
National Heart, Lung, and Blood Institute
National Institutes of Health
-----------------------------------------------------------
Foreword
I am pleased to present this report of the Conference on
Socioeconomic Status (SES) and Cardiovascular Health and
Disease, sponsored by the National Heart, Lung, and Blood
Institute (NHLBI).  This important meeting addressed a topic
of great timeliness and interest to those of us who are
concerned with the public health of the United States.
Participants at the conference were given the following
charge:
*  Review existing knowledge of biological, behavioral, and
   social factors related to SES variations in CVD morbidity
   and mortality and their trends, particularly with respect
   to minorities;
*  Identify scientific information that is ready for
   transfer to health care professionals and the public to
   improve the cardiovascular health of the country;
*  Determine future opportunities and needs for research on
   SES factors and their relationships with cardiovascular
   health and disease.
The Chartbook of U.S. National Data on Socioeconomic Status
and Cardiovascular Health and Disease served as background
to the conference.  The product of more than 2 years of work
by a number of distinguished nonfederal scientists and
representatives of the NHLBI, the National Center for Health
Statistics, and the Health Care Financing Administration,
the Chartbook is unique in its wealth of U.S. national data
about race-, gender-, and age-specific associations between
SES and CVD.
As this conference report indicates, current knowledge and
understanding of the behavioral, social, psychological, and
biological pathways through which SES influences CVD remains
limited.  In clarifying the association between SES and CVD,
a number of approaches must be vigorously pursued to acquire
new scientific information, validate therapeutic and
preventive approaches, and transfer new knowledge into
practice.  It is our hope that this report and its
recommendations will receive close attention by the
scientific community and serve as a starting point for
identifying ways to reduce CVD among all segments of
society.
We are grateful to conference participants for their
thoughtful contribution to our efforts.
Claude Lenfant, M.D.
Director
National Heart, Lung, and Blood Institute
-----------------------------------------------------------
Table of Contents
Executive Summary
Jeremiah Stamler, M.D.
Helen P. Hazuda, Ph.D.
Session I:  Setting the Stage
   Session I Overview
   Millicent Higgins, M.D.  -  Session Chair
     Biologic and Methodologic Approaches to the Association
       Between Socioeconomic Factors and Cardiovascular
       Disease
     George A. Kaplan, Ph.D.
     Socioeconomic Status and Cardiovascular Disease
       Mortality:  National Longitudinal Mortality Study
     Paul D. Sorlie, Ph.D., Norman J. Johnson, Ph.D.,
       Eric Backlund, M.S.
     Socioeconomic Factors in Ischemic Heart Disease
       Morbidity and Mortality
     Jacob J. Feldman, Ph.D., Diane M. Makuc, Dr.P.H.
     Socioeconomic Status and Biomedical, Lifestyle, and
       Psychosocial Risk Factors for CVD:  Selected U.S.
       National Data and Trends
     Clifford L. Johnson, M.S.P.H., Christopher T.
       Sempos, Ph.D.
     SES and Medical Care Utilization Related to CVD:
       Selected U.S. National Data and Trends
     Paul Eggers, Ph.D.
     Differences Between Occupational Classes in
       Cardiovascular Disease Mortality: A Comparison of 11
       European Countries
     Anton E. Kunst, M.A., Feikje Groenhof, M.A., Johan
       Mackenbach, M.D., Ph.D., and the European Union
       Working Group on Socioeconomic Inequalities in Health
     Socioeconomic Status and Cardiovascular Disease:
       Experience in the United Kingdom
     Michael G. Marmot, M.D., Ph.D.
     Session II:  Pathways Linking SES and CVD
     Session II Overview
     Redford B. Williams, M.D.  -  Session Chair
     Black and White Populations
     Herman A. Tyroler, M.D., Mark Massing, M.D., Marilyn
       Knowles, M.P.H.
     Pathways Linking SES and CVD:  Hispanic Populations
     Helen P. Hazuda, Ph.D.
     Socioeconomic Status and 23-Year Cardiovascular Disease
       and Total Mortality Among Middle-Aged Men:  The
       Honolulu Heart Program
     Beatriz L. Rodriguez, M.D., Ph.D., J. David Curb, M.D.,
       Cecil M. Burchfiel, Ph.D., Ka-On Fong, M.A.,
       Katsuhiko Yano, M.D., Dan S. Sharp, M.D., Ph.D.
     Socioeconomic Status and Cardiovascular Health and
       Disease in American Indians:  The Strong Heart Study
     Elisa T. Lee, Ph.D., Oscar T. Go, Ph.D., for the Strong
       Heart Study Investigators
     Socioeconomic Status and Cardiovascular Disease in
       Rural Populations
     Thomas A. Pearson, M.D., M.P.H., Ph.D.
     Socioeconomic Status, Cardiovascular Risk Factors, and
       Cardiovascular Disease:  Findings on U.S.Working
       Populations
     Jeremiah Stamler, M.D., Rose Stamler, M.A., Daniel
       Garside, Kurt Greenlund, Ph.D., Sujata Archer, Ph.D.,
       James D. Neaton, Ph.D., Deborah N. Wentworth, M.P.H.
     Psychosocial Pathways Linking SES and CVD
     James S. House, Ph.D., David R. Williams, Ph.D.
     Stress, Work, Social Supports, and Gender in Relation
       to Cardiovascular Disease
     Kristina Orth-Gomer, M.D., Ph.D.
     Medical Care:  Access, Utilization, and Cost
     Daniel B. Mark, M.D., M.P.H., Nancy Clapp-Channing,
       R.N., M.P.H., Lai Choi Lam, M.S., John C. Barefoot,
       Ph.D., Ilene C. Siegler, Ph.D., M.P.H., Redford B.
       Williams, M.D.
Session III:  Experiences in Educational and Preventive
  Interventions Across SES Groups
   Session III Overview
   L. Julian Haywood, M.D.  -  Session Chair
     What Have We Learned About Socioeconomic Status and
       Cardiovascular Disease From Large Clinical Trials?
     Jeffrey A. Cutler, M.D, M.P.H., Greg Grandits, M.S.
     Smoking Cessation, Socioeconomic Status, and Ethnicity
     Judith K. Ockene, Ph.D., John Harrington, Ph.D.
     Nutrition Intervention Studies
     Shiriki K. Kumanyika, Ph.D., R.D., M.P.H.
     Physical Activity Intervention Studies and
       Socioeconomic Status
     Daniel I. Galper, M.S., Steven N. Blair, P.E.D.
     Worksite, Community-Based, and School-Based
       Intervention
     Russell V. Luepker, M.D.
     Interventions Targeted to Ethnic Minorities, Especially
       Women
     Mary Helen Deer-Smith, R.N.
     National Cardiovascular Disease Education Programs
     Gregory J. Morosco, Ph.D., M.P.H.
Appendix
   Chairs and Speakers
   Contributing Authors
   Coordination
-----------------------------------------------------------
Executive Summary
-----------------------------------------------------------
Executive Summary
Jeremiah Stamler, M.D.
Helen P. Hazuda, Ph.D.
Cochairs
Disease prevention is an essential part of the mission of
the National Heart, Lung, and Blood Institute (NHLBI).  Over
the years, the Institute has developed some remarkably
effective preventive strategies based on research to
identify the major risk factors for cardiovascular disease
(CVD).  It is no surprise that the sharp declines in CVD
mortality that occurred during the past 30 years coincided
with our understanding that such factors as smoking,
hypertension, high blood cholesterol, obesity, and diabetes
increase a person's risk of developing CVD.
Gratifying as this progress is, we still have far to go.
Much evidence indicates that the beneficial trends in CVD
mortality have not been felt equally across all segments of
society.  Rather, the most striking improvements in
cardiovascular health have occurred among wealthier, better-
educated Americans, while progress among groups with lower
socioeconomic status (SES) has lagged.  The observation that
the gap between high-SES and low-SES populations may be
widening is particularly disturbing.
To address these important public health issues, the
Conference on Socioeconomic Status and Cardiovascular Health
and Disease was convened November 6-7, 1995, in Bethesda,
Maryland.  More than 120 persons attended, representing such
fields as cardiovascular and preventive medicine,
epidemiology and biostatistics, behavioral and social
sciences, and health policy research.  The goals of the
meeting were to assess the extent to which SES is related to
CVD mortality, morbidity, and risk factors in men and women
of various ages, races/ethnicities, and geographical
locations; to assess time trends in the SES-CVD association;
to explore possible biological, psychosocial, and lifestyle-
related pathways by which SES may relate to CVD; to identify
strategies for reducing SES-based disparities in
cardiovascular health; and to recommend promising avenues
for future research on this topic.
Several crosscutting themes emerged from the conference
presentations and discussions.  First is the need to improve
our understanding of the concept of SES and the ways in
which it reflects the conditions of everyday life for people
of various strata.  This task will involve development of
more sophisticated and refined measures of SES.  The
importance of seeking input from other related fields (e.g.,
sociology, demography, economics) was emphasized.
The conference also highlighted the importance of rapidly
transferring new scientific knowledge into practice and,
most critical, of more effectively applying what we already
know about risk reduction strategies (e.g., smoking
cessation, blood pressure control, diet), especially to
population strata that have not yet been reached.  In this
regard, the superb national leadership taken by the NHLBI
through its education programs was repeatedly acknowledged.
Irrefutable evidence that an SES gradient in CVD risk exists
-  that there is room for improvement at every SES level  -
speaks to the importance of a population-wide approach to
reducing the burden of CVD. Sustained and focused efforts
among all SES groups of various races/ethnicities are
needed.
SESSION HIGHLIGHTS
Session I:  Setting the Stage
The first session focused on U.S. national data relating SES
to CVD morbidity and mortality; to lifestyle, biomedical,
and psychosocial risk factors; and to medical care
utilization.  Presenters gave an overview of data in the
Chartbook of U.S. National Data on Socioeconomic Status and
Cardiovascular Health and Disease, which had been prepared
as background to the conference.
The national data document that SES relates to CVD, to
lifestyles, and to major lifestyle-related biomedical CVD
risk factors (with variations by age, gender, ethnicity, and
specific aspects of lifestyle, as well as with variations
over time).  The general finding is that more adverse
patterns of these variables exist for lower-SES strata than
for higher-SES strata in the U.S. population.  For instance,
a wealth of information on smoking shows strong and
consistent relationships with SES (i.e., for all age groups,
both genders, and all racial/ethnic groups, the lower the
SES, the higher the prevalence of smoking and the lower the
quit rate during recent decades).
Strong and consistent inverse relationships also prevail  -
for adults of every age and both genders, for blacks, non-
Hispanic whites, Hispanics, Asian Americans, Native
Americans  -  between SES and high blood pressure, and
between SES and obesity.  Lower-SES groups have higher rates
of both hypertension and obesity than higher-SES groups.
Upward trends in body weight and in prevalence of overweight
during the last decades have been more marked in lower- than
higher-SES strata.
Other SES-risk factor relationships are less strong and
consistent  -  for example, the relationship between SES and
serum cholesterol.  However, trend data from successive
national population surveys indicate that declines in adult
average serum cholesterol levels have been smaller in lower-
than in higher-SES strata.  National data are limited about
such relevant aspects of lifestyle as diet and physical
activity and their time trends across SES strata.
National data are also sparse with respect to psychosocial
risk factors across SES strata.  In particular, data are
lacking on psychosocial variables for SES groups of various
ethnic backgrounds.  Furthermore, little information exists
about such variables as job change, unemployment, job and
income instability, work-related psychosocial variables,
social support, and social isolation, and how these
variables influence relationships of SES to CVD, CVD risks,
and their trends.
As the Chartbook documents and the presenters noted,
national mortality data show clearly that for major ethnic
groups in the U.S. population, lower-SES strata have higher
mortality rates than higher-SES strata for coronary heart
disease (CHD), all CVD, and all causes.  National morbidity
surveys give generally concordant findings.
Discussants noted that SES is related to many aspects of
daily life, experiences at work and in the community,
stresses and strains, and access to and utilization of
medical care, including preventive services and state-of-
the-art diagnostic and therapeutic services.  To understand
better how SES influences CVD, an epidemiology of everyday
life that encompasses these phenomena needs to be developed.
Recommendations
*  Promote measurement of SES, in both observational and
   interventional research, using established, valid,
   reproducible, acceptable indices appropriate for a given
   study and its aims.  Encourage data analysis approaches
   that include use of information on SES as both a control
   and a stratification variable.
*  Develop, validate, and incorporate more sophisticated
   measures of SES and SES-related aspects of everyday life
   into research with a major focus on SES and CVD.  In
   studies of women, minorities, and rural residents, give
   explicit attention to special features that may condition
   the definition, meaning, and impact of SES.
*  Investigate the relationships between SES and CVD
   initiation, progression, prognosis, morbidity,
   disability, and death.  Emphasize greater use of methods
   to measure preclinical disease (e.g., echocardiography,
   electrocardiography, sonographic measurement of carotid
   artery intima-media wall thickness, measurement of
   ankle-arm blood pressure ratio) to achieve earlier and
   more comprehensive assessments of the impact of SES-
   related exposures on CVD.  Link such findings to data on
   nonfatal and fatal clinical CVD.
Session II:  Pathways Linking SES and CVD
Several presenters reviewed data on SES-CVD relationships
and on possible pathways of these relationships, in men and
women from specific U.S. population strata (i.e., blacks,
whites, Hispanics, Asians and Pacific Islanders, Native
Americans, rural populations, and employed groups).  Two
other presenters discussed evidence from psychosocial
studies and from research on stress, work, and social
support.  The last speaker addressed medical care access,
utilization, and costs.
In agreement with national data, findings from studies of
specific U.S. population groups generally show an inverse
relationship between SES and CVD (i.e., higher CVD rates
with lower SES).  Two broad pathways were noted linking SES
and CVD:  1) less favorable patterns of established major
lifestyle and biomedical risk factors (smoking, adverse
diet, sedentary lifestyle, high serum cholesterol, high
blood pressure, obesity, diabetes) in lower- compared with
higher-SES strata; 2) less favorable patterns of
psychosocial factors (hostility, depression, low social
support, social isolation, racism, job instability-
insecurity-strain- powerlessness, unemployment) in lower-
compared with higher-SES strata.  Data are sparse on
possible SES-related biological mediators of relationships
between psychosocial factors and CVD (e.g., altered
sympathetic and parasympathetic nervous system function,
altered  hypothalamic-pituitary-adrenal axis function,
altered cellular-molecular biology of key cells), and on
social-environmental mechanisms whereby lower SES leads
inordinately  -  from early childhood on  -  to development
of more adverse behavioral and psychosocial patterns.
Men with low levels of all established biomedical risk
factors (blood pressure, cholesterol, smoking, diabetes,
previous heart attack) have been found to experience lower
CHD and CVD mortality rates than men without such a
favorable profile.  Such a favorable profile is found in
less than 10 percent of the population.  These findings
indicate that controlling the established biomedical risk
factors has the potential to achieve low CHD-CVD rates for
all groups in the United States, including low-SES strata of
various racial/ethnic backgrounds.
These observations underscore the importance of primary
prevention and control of the established major biological
risk factors for CHD-CVD.  Improved understanding of the
reasons why lower-SES groups have more adverse levels of the
major risk factors, the pathways producing these patterns,
and the contributory role of more adverse behavioral and
psychosocial patterns is key to achieving this goal.  Also
important is improved understanding of the lifestyle,
behavioral, psychosocial, cultural, metabolic, and genetic
components of maintaining low-risk status into middle age.
Such knowledge will lead to development and application of
better approaches for the primary (including "primordial")
prevention and control of the major risk factors, with a
focused emphasis on lower- as well as higher-SES strata of
all racial/ethnic groups.
Recommendations
*  Investigate relationships between SES and
   development/evolution of lifestyles, behaviors, and risk
   factors, including both adverse and favorable patterns.
*  Analyze existing data and data currently being collected
   by trials and demonstration projects to document further
   the effectiveness of interventions in lower- and higher-
   SES groups of various races/ethnicities; report and
   disseminate such data and their implications for programs
   to control CVD in lower-SES groups.
*  Conduct research to enhance understanding of mechanisms
   underlying clustering of adverse lifestyles, behaviors,
   and risk factors in lower-SES groups of various
   races/ethnicities.
*  Study SES and precursors of adult lifestyles and
   behaviors, from childhood on, including influences of the
   family, community, school, and workplace.
*  Elucidate the mechanisms whereby conditions of everyday
   life for lower-SES groups  -  exposures during prenatal
   life, infancy, childhood, and adulthood  -  contribute to
   the development of more adverse patterns of lifestyles,
   behaviors, risk factors, and psychosocial traits.
   Include studies of the roles of racism; sexism;
   deprivation; relative and absolute income levels and
   their trends; knowledge and attitudes; home, school,
   workplace, community, and mass-media exposures; peer
   pressures; housing conditions; relationships to
   organizations; early exposures to food, alcohol, and
   drugs; and barriers to adoption of heart-healthy
   behavior.
*  Investigate the interrelationships between psychosocial
   traits and lifestyles in lower-SES groups  with the aim
   of clarifying environmental and biological mediators and
   pathways of these interrelationships (including
   neurological, endocrine, cellular, and molecular
   pathways) and thereby enhancing understanding of how
   psychosocial factors and acculturation influence CVD
   risk.
Session III:  Experience in Educational and Preventive
Interventions Across SES Groups
This session focused on preventive strategies that, if
applied more broadly, have potential to reduce the SES
gradient in CVD health and disease.  Speakers reviewed
evidence from clinical trials and a broad range of
intervention studies to determine whether observed
reductions in CVD risk factors, morbidity, and mortality
extended equally to low- and high-SES participants,
including those from ethnic minorities.  Findings clearly
indicate that, although there is more to be learned, much is
already known about how to reduce CVD in low-SES groups.
Interventions in several large NHLBI-supported primary
prevention trials were efficacious in reducing CVD risk
factors, morbidity, and mortality in multiple SES-race
substrata, although only limited special efforts were made
to tailor the interventions for lower-SES, nonwhite
participants.  Interventions consisted of antihypertensive
drug treatment involving stepped care as well as multifactor
behavioral interventions aimed at smoking cessation,
reduction of total serum cholesterol, weight control,
increased physical activity, and reduction of salt and
alcohol intake.  Lower SES was not a barrier to intervention
success for either the drug treatment or the behavioral
components.  In one antihypertensive trial, the SES gradient
in mortality was eliminated in the intervention group.
Studies in communities, worksites, and schools confirm that
public health interventions can be designed to benefit all
segments of society.  Favorable changes in lifestyles and
lifestyle-related biomedical risk factors have been achieved
across all SES groups in community interventions that have
used a broad, multimedia communication approach with special
efforts to target and involve low-SES, culturally diverse
groups.   Worksite interventions incorporating on-site
classes and payroll incentives have also achieved favorable
results in both blue- and white-collar employees.  The
success of school-based programs in achieving similar
magnitudes of risk factor reduction in both low- and high-
SES students is particularly noteworthy given the schools'
potential for building lifelong heart-healthy habits and,
thereby, contributing importantly to the key strategic goal
of preventing the development of major risk factors.
Preliminary findings from programs specifically designed to
address the need for nutrition education materials suitable
for English-speaking adults with limited literacy skills
indicate that the approaches developed result in high
utilization of intervention materials among ethnically
diverse, low-SES persons and  can lead to gradual, sustained
progress toward favorable risk factor change over time.
Most programs use multimedia, client-centered instructional
approaches that include interactive computer technology,
videotapes, audiocassettes, compact discs, and printed
materials.
Across all SES groups, self-help is the method of choice for
smoking cessation by more than 90 percent of smokers.
Programs that combine media presentations with telephone
counseling hotlines or distribution of self-help materials
have been particularly effective with lower-SES smokers.  A
community organization approach used in one study had the
greatest effect in low-SES individuals.  Counseling of
smokers by physicians or dentists has also been shown to
increase their likelihood of quitting smoking significantly.
Sedentary lifestyle is particularly prevalent among lower-
SES persons and ethnic minorities.  Experience from
community-based heart-health programs suggests that
interventions promoting moderate- rather than vigorous-
intensity activities are more likely to be successful, and
that exercise campaign events tied to preexisting community
structures or traditional community events have the greatest
participation levels.  Worksite interventions have
demonstrated that clinically significant increases in
physical activity can be achieved in both low- and high-SES
employees.
The National High Blood Pressure Education Program and
National Cholesterol Education Program have been prime
movers in the substantial progress made in achieving the
Healthy People 2000 blood pressure and cholesterol
objectives.  Their achievements underscore the effectiveness
of science-based public health strategies that rely on
broad-based cooperation between government and the private
sector in overcoming the barriers to reducing CVD in all
sectors of the population.
The overall conclusion is that more widespread application
of interventions already known to work across multiple SES
and ethnic groups can make a substantial contribution to
eliminating the SES gradient and ending the CVD epidemic in
all segments of society.
Recommendations
*  Incorporate nonsmoking messages into educational efforts
   targeting all SES-ethnic groups, with a particular focus
   on more habituated smokers and on do-it-yourself
   approaches to smoking cessation.
*  Evaluate existing obesity intervention programs; look for
   successes and develop approaches based on them, with the
   aim of achieving national goals for obesity prevention
   and control for all SES strata, including reversal of the
   decades-long rise in obesity rates among children, youth,
   and adults.
*  Intensify efforts to increase consumption of heart-
   healthy foods  -  reduced in total fat, saturated fat,
   cholesterol, salt, refined sugars, and calories  -  in
   lower-SES communities.
*  Enhance efforts to prevent and control high alcohol
   intake among lower-SES groups of various
   races/ethnicities.
*  Enhance efforts to achieve daily or near-daily physical
   activity by lower-SES groups from childhood on and to
   increase the proportion of people who regularly engage in
   moderate activity.
*  Emphasize the potential contribution of stress reduction
   to modifying risk factors and subsequent CVD morbidity
   and mortality.
*  Encourage assessment of literacy as a relevant aspect for
   improving ability to intervene effectively in lower-SES
   groups; use group-specific programs appropriate for
   literacy level and sensitive to group culture.
*  Develop effective strategies to promote favorable
   behavior changes in lower-SES groups.
*  Conduct demonstration research in communities,
   workplaces, and schools with persons from lower-SES
   groups of various ethnicities.  Include participation of
   community outreach workers (including workers trained and
   supervised by nurses and dieticians) and community
   representatives in all aspects of such projects (i.e.,
   planning, intervention, data evaluation) to enhance the
   potential for lasting accomplishments.
REPORT ORGANIZATION
The report that follows is organized in three sections that
parallel the structure of the conference.  Each section
includes an overview of the session, prepared by its chair,
and summaries of the individual topical presentations,
prepared by the presenters and their colleagues.
Rosters of conference chairs and speakers, contributing
authors, and NHLBI coordination staff are provided at the
end of this report.
-----------------------------------------------------------
Session I Overview
Setting the Stage
-----------------------------------------------------------
Session I Overview
Millicent Higgins, M.D., Chair
Session I presented highlights of the very extensive data
gathered in the Chartbook of U.S. National Data on
Socioeconomic Status and Cardiovascular Health and Disease
and included discussions of measurement of socioeconomic
status (SES) and the nature of its association with
cardiovascular disease (CVD).  These presentations, as well
as comments from conference participants, are reflected in
this overview.
Socioeconomic Status
The Chartbook used education, income, and occupation as
measures of SES; each is strongly related to some aspects of
CVD mortality, morbidity, and risk factors, and these
measures are correlated with one another.  However, each
provides some unique information and has its strengths and
weaknesses.
Completion of formal education usually precedes the onset of
CVD and is not influenced by the disease process.  Because
education is stable, it can be used over time and throughout
the adult age range.  Income, on the other hand, can vary
over time and may be a less valid measure of SES at the
extremes of the age range.  Personal income and family
income may be hard to ascertain or interpret.  Measures such
as the poverty-to-income ratio were reported in some
studies, but little attention has been given to measuring
assets such as home ownership, value of housing, and car
ownership; assets as well as income need further
consideration, especially for elderly populations.
Occupation is predominantly useful for those who are
employed and at the age where having a job is the norm.
Occupations may change over time and be influenced by the
presence of disease, as well as influence the development of
disease.  An advantage of occupation is that it has been
used extensively in Europe to define social class, but there
are issues of comparability and of combining categories for
international comparisons.  Ownership of a business and
authority in the workplace are sometimes used to classify
people according to their occupations.  Classifying married
women according to their husbands' occupation or social
class may be less appropriate now than in the past, and
inappropriate in some societies.  Education, occupation, and
income do not cover some aspects of social class and may be
inadequate to describe associations or suggest mechanisms by
which social class is related to health and disease.
Additional social and demographic variables, such as living
alone and marital status, are available from the National
Longitudinal Mortality Study; deprivation was assessed in
another study.  Most presentations and data described and
evaluated SES as an attribute of individuals, though
household income and family size were assessed in a few
studies and familial aggregation and cultural inheritance of
social class were mentioned.  SES of an individual or family
should also be considered in context with respect to place,
time, and the social environment of the community.  The
appropriateness of descriptors of SES varies with sex, age,
and race; over time; and from culture to culture.
Cardiovascular Health and Disease
Measures of CVD included extensive national mortality data
and a little information on case fatality rates. Limitations
of death certificate information are well known and include
inaccurate recording and coding of specific causes of death.
Measures of morbidity were fewer;  prevalence is often based
on self-reports of disease and is influenced by
ascertainment, by incidence and duration of illness, and by
case fatality.  Incidence data are sparse.  Measures of
severity of disease and of access to care were limited to
information on hospital admissions, physician visits, and
performance of diagnostic and therapeutic procedures for
CVD.
Recent information on biological risk factors including
blood pressure, serum cholesterol, other lipids, and body
mass index was provided by the third National Health and
Nutrition Examination Survey (NHANES III).  Lifestyle
factors are not as easy to measure precisely, but
information on diet and physical activity and their
relationships to SES variables were presented.  There is a
wealth of information on smoking that shows very strong and
consistent inverse relationships with SES.  The Chartbook
and presentations also included information on the frequency
and distribution by SES of some psychosocial risk factors
including life events, social networks, and personality
characteristics.  Some psychosocial variables were strongly
related to SES.
Although preclinical evidence of disease was not discussed
in Session I, it is an important component of CVD that can
be assessed using markers such as carotid artery intimal-
medial wall thickness and ankle-arm blood pressure ratio.
These newer measures allow studies of a broader range of
cardiovascular conditions from fatal events, to type and
severity of clinical presentations, preclinical disease, and
risk factors.
CVD-SES Relationships
Some consistent patterns were apparent, particularly in
recent U.S. data.  Low SES was related to CVD morbidity,
mortality, and some risk factors, and to less utilization of
some components of medical care.  Age, sex, and race, as
well as socioeconomic factors, are related to access and use
of medical care.  Some of the data suggest conflicting
patterns.  Outpatient visits are as frequent or more
frequent in poor people.  The literature suggests that a
given disease diagnosis costs more in poor people because
they present later in the disease and need a higher level of
care and more procedures.  Utilization data paired with
incidence, prevalence, and mortality data are needed. Some
of the risk factor relationships with SES are not as strong
or consistent in the three racial/ethnic groups (i.e.,
whites, blacks, Hispanics), in men and women, and across the
age range.  Researchers need to take these variations into
account, as well as to assess the quality and strength of
the science base in order to increase understanding of the
complex interactions between SES and CVD.
There were marked gradients in CVD among occupational groups
in European countries, and considerable variation in the
strengths of associations between SES and mortality from all
CVD, ischemic heart disease, and stroke.  Intriguing
differences were apparent in northern Europe compared with
southern Europe.  United Kingdom data provided detail about
the gradient of risk across the range of SES and the extent
to which occupational level and income provided similar or
different insights.  Information on deprivation was used as
another marker of SES differences in these studies.  Some of
the European data suggested that income was not the main
determinant of the SES gradients, which were just as great
in countries where income inequalities were smaller as in
countries in which they were large.
Time trend data were available from the United States over
recent years and from the United Kingdom over a longer
period.  There has been a reversal in the relation between
SES and CVD mortality in men, but the pattern in women has
not changed.  Prior to the mid-1960s, mortality rates were
higher for men in the upper SES groups but then the
situation reversed.  In fact, the gap between extremes of
SES strata has widened recently, especially among men in the
United States.  In some developing countries, mortality from
CVD is still greater at the upper end of the SES
distribution.
It is clear that SES differences in CVD morbidity and
mortality are mediated, in part, by the major risk factors,
but there is a component of the SES-CVD relationship that is
not explained by those associations.  Despite the
limitations of available data, and imperfect measures of
SES, there is strong evidence that SES is a major
determinant of cardiovascular health and disease and that
further research into the nature of these relationships is
warranted.
RESEARCH NEEDS AND RECOMMENDATIONS
*  Better measures of SES are needed, especially for women
   and minorities.  Definitions and methods should be
   validated and standardized.  Information is lacking or
   sparse for several racial and ethnic groups and for rural
   residents who have not been studied extensively in the
   past.  More sophisticated measures and multiple measures
   of SES and of aspects of everyday life are desirable, but
   a simple measure  -  such as education  -  would be a
   useful addition to observational studies and clinical
   trials, which cannot collect more detailed information.
*  Further investigations of relationships between SES and
   development of risk factors, severity, and course of CVD
   as well as diagnosis, treatment, and utilization of
   medical care are needed.  Such information would identify
   groups where the need for prevention or therapy is
   greatest and improve understanding of the ways in which
   SES variables influence initiation and course of CVD.
*  Circumstances are changing rapidly, and relationships
   between SES and components of CVD need continued
   monitoring.  National and regional data are needed for
   the United States and other countries to expand the range
   of experience and increase understanding of the ways in
   which SES and cardiovascular health and disease interact.
*  Relationships between psychosocial risk factors and
   biomedical risk factors are in need of further study.
   The biological pathways by which psychosocial factors and
   acculturation influence risk must be understood better to
   improve prediction and prevention of CVD.
*  More knowledge is needed about the precursors of adult
   health behaviors, including the influence of the family
   and the community on health behaviors.  Many healthy and
   unhealthy behaviors are learned in childhood in the home
   and they aggregate in families.  Children and families
   should be included in research on SES and cardiovascular
   health and disease.
*  Research is needed to identify effective strategies to
   promote behavior change in low-SES groups as well as to
   improve recruitment and retention of such people in
   observational studies and clinical trials.
*  Studies of cost should be added to our research projects.
   Information about how SES affects cost-effectiveness of
   preventive and therapeutic approaches is lacking.
   Policymakers need to know more about health care costs
   and their relationship with SES.  Measures of utilization
   such as physician visits, hospitalizations, and use of
   procedures should be related to measures of disease
   frequency and severity, but these are not generally
   available and they require well-designed investigations
   for their collection, analysis, and evaluation.
-----------------------------------------------------------
Biologic and Methodologic Approaches to the Association
Between Socioeconomic Factors and Cardiovascular Disease
George A. Kaplan, Ph.D.
Examination of the data presented in the Chartbook of U.S.
National Data on Socioeconomic Status and Cardiovascular
Health and Disease, as well as numerous other sources,
reveals an inverse gradient between various measures of
socioeconomic status (SES) and  mortality and morbidity from
the major cardiovascular diseases (CVD) (1).  The "better
off" experience less disease, and the "worse off" more
disease. This pattern of increased risk of poor health
outcomes with decreasing SES is found for most, but not all,
diseases across the world, and when using a variety of SES
measures (2).  There are some exceptions to this pattern,
and it has not always been true for all groups for CVD.
However, in virtually all the developed countries at the
current time for which there are good data, higher SES is
associated with lower CVD risk.
These are compelling and remarkably consistent findings.
The observation of consistent, patterned differences in risk
of disease between groups or places is the starting place
for epidemiological analysis. Although it is important to
continue to document the nature of SES inequalities in CVD,
a full understanding will require a clarification of the
operative biological and social pathways.  Parallel with
passage through various stages of the life course, there are
exposures to a variety of socioeconomic states and risk
factors, all linked over time (Fig. 1).  Just as risk
factors may vary in importance depending on age and stage of
disease progression, different aspects of SES may loom more
or less important over time.  Thus, researchers should not
expect either a single risk factor or a single aspect of SES
to be equally important at all stages in the natural history
of coronary heart disease (CHD).  Similarly, patterns of
exposure to socioeconomic factors and risk factors are
dynamic, not static.  Risk factor exposures change over
time, and exposures to socioeconomic conditions may also
change over time.  These changes, as well as the converse  -
the extent to which they track over time  -  may have
important implications for understanding of the links
between SES and cardiovascular health.
The links between SES and risk factors are, of course, of
paramount importance in understanding the association
between SES and CHD.  While some of the epidemiological
literature on this association attempts to establish SES as
an "independent" risk factor, it must perforce act through
more proximal pathways.  Thus, it is important to understand
these links between measures of SES and the existing risk
factors for CHD.
Socioeconomic Factors in the Natural History of Coronary
Heart Disease
In understanding how SES factors might be associated with
the development and manifestations of CHD, it is convenient
to divide the natural history of CHD into three major
stages:  preclinical disease, triggers and events, and
recovery.  What follows, a discussion of the
pathophysiological links between SES and these stages of
CHD, is based, for the most part, on consistent reports in
the literature.  In some cases, in the absence of any
information, it is based on biological plausibility.
-----------------------------------------------------------
Figure Missing
Figure 1.  -  Relationship Between Age, SES, Risk Factors,
and the Natural History of Atherosclerotic CHD.
-----------------------------------------------------------
The molecular and cellular events leading over the long term
to atherosclerotic changes have been summarized by a number
of authors (3).  The preclinical disease stage refers to the
early stages of alteration of the arterial walls and
environment in which there are neither major obstructions to
blood flow nor symptoms.  In this stage, there is the
gradual progression from fatty streaks to hard plaque with
calcification and, ultimately, clinically significant
obstruction.  The focal role of endothelial injury stemming
from mechanical, immunological, viral, or other forces is
well recognized, with subsequent endothelial dysfunction
leading to disturbances in interactions between the
endothelium and macrophages, platelets, smooth muscle cells,
T lymphocytes, among others, and changes in vasomotor
properties of the artery.  Changes in the nonthrombogenic
character of the endothelium lead to platelet adhesion,
accelerating lesion development via increased levels of
platelet-derived growth factor and other substances and
leading to smooth muscle cell proliferation and migration.
Table 1 indicates a list of factors that are related to SES,
variously measured, and are also related, in some studies,
either to coronary atherosclerosis, found on angiography or
autopsy, or, as a model of coronary atherosclerosis, to
carotid atherosclerosis or progression of carotid
atherosclerosis.  Given the recent interest in the early
origins of CVD, it is important to point out that many
maternal exposures influence prenatal development and might,
conceivably, have some impact on later atherosclerotic
developments.  While the pathways are complex, this might be
seen as the intrauterine transmission of SES.  Considerable
evidence now indicates that the standard coronary risk
factors (blood pressure, smoking, obesity, lipids, alcohol,
physical activity) are related to preclinical
atherosclerosis, and in many studies higher levels of these
risk factors are found in lower SES groups, although the
consistency of this is weakest for lipid measures.  SES is
also associated with fibrinogen levels, and possibly other
pathways influencing both fibrinolysis and coagulation (4).
Although less studied, a variety of psychosocial factors
also seem to be strongly associated with coronary and
extracoronary atherosclerosis and SES.  In one study, 4-year
progression of carotid atherosclerosis was associated with
levels of hopelessness (5).  Hopelessness, in turn, was
inversely related to income level. The effects of
psychosocial variables on atherogenesis may operate via
promoting higher levels of other, more traditional risk
factors, or by potentiating the effects of these other risk
factors via changes in lipid peroxidation, fibrinolysis, or
other mechanisms.  In addition, tendencies toward chronic
vascular hyperactivity to chronic psychological stress,
which may be more prevalent among those who are of lower
SES, may also be associated with increased atherogenesis.
When we consider the second stage, that involved in the
precipitation of acute events,  SES may also have an
important role.  In this stage of the natural history of
CHD, the important events are primarily those related to
plaque fissuring and instability, and a cascade of
additional factors and events leading to an occlusive
thrombus, or other complications (Table 1).  Of course,
coronary spasm secondary to atherogenic changes or
superimposed on these changes, and arrhythmias also are of
considerable importance in this stage.  Given the effects of
smoking, physical activity, and alcohol consumption on
coagulation and fibrinolysis, it is not surprising that
factors likely to be associated with SES could potentially
act as triggers of acute events.  Many investigators now
believe that factors such as anger, disruption of social
ties, mental stress, and emotional distress, and their
associated hemodynamic, neuroendocrine, and hemostatic
effects may be major contributors to the timing of acute
events.  Importantly, existing data suggest that these
events are more common among those with lower SES.  An
example of the magnitude is found in a study of silent
myocardial ischemia, assessed by radionuclide
ventriculography,  in response to mental stress in patients
with coronary artery disease (6).  When patients were asked
to give a short speech about personal faults and undesirable
habits in front of others, presumably a quite stressful
experience, they evidenced almost as high a frequency of
wall motion abnormalities as when they underwent a graded
maximal exercise test.
-----------------------------------------------------------
Table 1.  -  SES and CHD
SES and Preclinical CHD:
Prenatal exposures; blood pressure; smoking; obesity;
physical inactivity; diet; lipids; alcohol; hostility/anger; social
instability; depression; job strain; hopelessness; vascular
reactivity
SES and CHD Triggers:
Smoking; heavy exertion; alcohol; anger; social instability;
mental stress; intense emotional distress; hyperreactivity
SES and CHD Recovery:
Increased severity; greater comorbidity; poorer access;
poorer quality of care; poorer adherence;
socioenvironmental factors
+ + + + + + + +
Factors identified with SES are associated with CVD and
events at multiple stages.  The preclinical disease stage
(left panel) refers to the early stages of alteration of the
arterial walls and environment in which there are no
symptoms or major obstructions to blood flow.  In this stage
there is the gradual progression from fatty streaks to hard
plaque with calcification and, ultimately, clinically
significant obstruction.  Reflected at left are various
factors related to SES, linked in some studies either to
coronary atherosclerosis on angiography or autopsy, or to
carotid atherosclerosis or progression of carotid
atherosclerosis.  Certain of these factors are likely to be
associated with both SES and events that occur in the
triggering and acute stage (center panel).  Finally, SES
could be related to poorer recovery from acute events via a
number of pathways (right panel).
[end Table 1]
-----------------------------------------------------------
SES could be related to poorer recovery from acute events
via a number of pathways (Table 1).  Poorer recovery may
reflect greater severity of disease and greater comorbidity,
each of which would be expected to be present with lower
SES.  Each of these could be seen, to some extent, as a
failure of primary and secondary prevention.  For example, a
number of studies have shown relatively limited access to
preventive medical care and screening among those who are
poorer or who live in poorer areas. It is of some interest
that most of the mortality differentials associated with
educational differences in the Hypertension Detection and
Followup Program were eliminated in the stepped-care
treatment group (7).
Overall access to care and to health coverage varies by SES,
and poorer access or absence of insurance may translate to
lower quality of care.  There is also some evidence that
state-of-the-art interventions are available mainly for
those who are higher SES.  While it fits into the other
stage also, there is evidence that those who live in poorer
areas also have less access to healthy foods, and are
targeted by the tobacco and alcohol industries.  In
addition, rehabilitation and supportive services may be less
available to those who are of lower SES.  Finally, more
difficult working conditions and neighborhoods, greater
family problems, and greater demands in other domains may
all contribute to worse recovery among those in lower SES
groups. All of these factors would translate into poorer
survival and recovery after acute events.
Conceptualization and Measurement of Socioeconomic Factors
SES factors that might influence cardiovascular health
(Table 2) can be measured in many ways.  Terms that describe
such measurements are often used within epidemiological
analyses without proper recognition of their intellectual
roots in sociology (8).  While it is probably not necessary
for epidemiologists to concern themselves with the arcane
world of sociological theory, a general reading helps the
epidemiologist to be aware of differences in meaning and
emphasis that may be of some importance in understanding
both the measurement of socioeconomic factors and their
impact on health.
Not all measures of SES are equivalent.  Each carries with
it different problems in measurement,  interpretation, and
implications with respect to underlying causal pathways.
For example, education is taken by some as the best measure
because it is easy to measure with high response rates,
valued by the researcher, and not subject to reverse
causation  -  health problems in adulthood cannot logically
cause differing levels of educational achievement at an
earlier time.  However, educational achievement is often
socially patterned, so highest level of education completed
may simply be a proxy for whatever forces are important in
determining completion of school.  Because there are still
large discrepancies in educational opportunities between
groups that vary by gender, race or ethnicity, and class,
level of education should not necessarily be seen as
reflecting forces that are solely located within the
individual.  There are also large variations by birth cohort
in level of education completed  -  with a general trend
toward more and more education in more recent birth cohorts.
Thus, the behavioral, social, and psychological factors
associated with a given level of education may vary by age
and birth cohort.  In such a case, asking if the association
between education and CHD varies by age may raise numerous
interpretive problems.  Finally, the consequences of more or
less education (e.g., income, housing, job security) may
vary by age, race or ethnicity, and gender.
Income is less often measured in epidemiological studies
because of somewhat higher nonresponse rates and the
possibility that poor health might lead to declines in
income.  However, income is critically important, as it
provides access to other beneficial things (e.g., goods and
services, high-quality education, medical care, good
housing).  To not measure it is to miss the potential links
between material conditions and health.  However, measuring
income is not simple:  individual or family income can be
measured, it can be adjusted for family size or not, and
noncash benefits such as Medicare or food stamps can be
included or not.
-----------------------------------------------------------
Table 2.  -  Socioeconomic Factors Influencing
Cardiovascular Health
Socioeconomic status; social class; education;
income; occupation; employment status;
occupational grade; living conditions; wealth;
housing tenure; car ownership; deprivation;
poverty; income inequality
[end Table 2]
-----------------------------------------------------------
Economic resources as represented by wealth may also be
important to measure, although this has not been done very
much in epidemiological analyses.  Measures of wealth based
on such assets as bank accounts, stocks and bonds, pensions,
and home equity may be critical as they represent resources
that may potentially buffer the impact of stressors on
health, or may make certain health care resources more
available after acute events.  More commonly, measures of
assets such as car ownership and home ownership have been
used, although in the latter case there has seldom been
information on size of  mortgage.
Occupation is often measured, although the focus is
generally not on specific agents that might be associated
with increased risk.  Instead, categorizations are used that
involve status, roles, power, prestige, lifestyle, job
characteristics, income, education, traditions, beliefs, and
values.  For example, a reasonably consistent set of 12
categories has been used since 1910 by the U.S. Bureau of
the Census, and the Registrar General of Great Britain has
used a categorization since 1911 (currently six categories).
It is also possible to categorize people within a broad
occupation, such as the classification of civil service
workers in Great Britain as administrative, professional-
executive, clerical, or other (9).  General problems with
occupational classification include a usual lack of
occupational histories so that downward mobility due to
health problems cannot be ruled out, substantial
heterogeneity within occupational classifications, and large
secular trends in the jobs that fall in specific categories.
Most important, such broad classifications do not go very
far in pinpointing what characteristics, in particular, are
associated with increased risk.   Some progress in that
regard has been made in the recent work relating job strain
and CHD, which suggests that people in jobs characterized by
high psychological demands and low decision authority may be
at increased risk (10).  It is also important to consider
employment status because that, too, has been linked to
disease and health outcomes.
Many studies use measures of SES that are based on
characteristics of the areas in which people live.
Characteristics of areas [e.g., census tracts, block groups,
zip codes, Standard Metropolitan Statistical Areas (SMSAs)]
that are used include income, education, proportion in
poverty, occupational distribution, crowding, housing
conditions, relative equity of income distribution, and many
other indicators.  Often, the choice of an area-based
measure of SES reflects the lack of availability of
individual measures.  However, area-based measures can
capture characteristics of the locations in which people
live that are different from individual characteristics, and
these area or community characteristics may be of great
significance for health.  For example, one study showed that
residence in a poverty area was associated with increased
risk of death over and above a variety of individual
characteristics (11).
In many analyses in which information about SES is not
available, classifications of race or ethnicity are used
instead.  While SES levels do vary by race and ethnicity,
substituting race and ethnicity for social class information
leaves much to be desired.  For example, examination of the
distribution of whites, blacks, and Hispanics by quintiles
of income for the United States shows that there is
substantial overlap of the three populations in the middle
of the income distribution.  This overlap means that there
will be substantial misclassification if race or ethnicity
and SES are treated as identical.  In addition, race,
ethnicity, and SES represent different systems of
stratification with implications for health which cannot be
held equivalent.  Indeed, associations between SES
indicators and cardiovascular outcomes may vary by race and
ethnicity.  For these reasons, and others, race and
ethnicity should not be used as proxies for SES information.
Understanding the Connection between Social Class and
Cardiovascular Disease
The most common way of addressing our understanding of the
association between SES and CVD has been to use multivariate
models to examine the extent to which particular risk
factors account for the association and the extent to which
the association is "independent" of these risk factors.
Probably the most exhaustive attempt at this examined the
association between income quintiles and risk of death over
approximately 6 years, with adjustment for age and 22
additional risk factors (plasma fibrinogen, serum HDL, serum
apolipoprotein B, blood leukocytes, serum copper, mercury in
hair, serum ferritin, blood hemoglobin, serum triglycerides,
systolic blood pressure, body mass index, height,
cardiorespiratory fitness, cigarette smoking, alcohol
consumption, leisure-time conditioning physical activity,
depression, hopelessness, cynical hostility, organizational
participation, quality of social support, and marital
status) (12).  With adjustment for these 22 risk factors,
there was no longer an association between income and risk
for either all-cause or cardiovascular death.  This pattern
of results (i.e., a decrease in an association with addition
of potential confounder) is commonly taken as indicating
that the association between SES and disease has been
explained.
-----------------------------------------------------------
Figure Missing
Figure 2.  -  Critical Components of the Relationship
Between SES and CVD.
-----------------------------------------------------------
However such an approach takes on only part of the task of
understanding (12).  For example, many of these risk factors
show trajectories that reflect the influence of SES (2).
Thus, children from poorer families are more likely to begin
smoking.  Because SES is causally antecedent to smoking,
smoking cannot be said to explain the association between
SES and CVD.  What this type of analysis does is to help us
understand how SES manifests itself in increased risk of
disease.  Much more is still to be learned by such analyses,
as we dissect out the critical set of pathophysiological
pathways that result in the inverse association between SES
and cardiovascular outcomes.
From a public health point of view, it is unlikely that the
identification of these pathways will tell us much about how
to lower the excess cardiovascular mortality among those who
are less "well-off."  The problem is not likely to be solved
by pharmacological means or other physiological
interventions.  Instead, we will have to emphasize study of
why particular risk factors are differentially distributed
by SES (13).  Such an approach will require examination of
multiple factors (Fig. 2) and include an appreciation of
life-course trajectories of SES and risk factors.  Such a
perspective exposes a variety of loci in which the
connections between SES and CVD can be broken.  Many of
these loci are not the usual focus of CVD prevention
efforts.  However, as Geoffrey Rose (1992) pointed out so
eloquently in his final book, The Strategy of Preventive
Medicine, "The primary determinants of disease are mainly
economic and social, and therefore its remedies must also be
economic and social."
REFERENCES
1.  Kaplan GA, Keil JE: Socioeconomic factors and
    cardiovascular disease: a review of the literature.
    Circulation 1993;88:1973-1998.
2.  Haan MN, Kaplan GA, Syme SL:  Socioeconomic status and
    health:  old observations and new thoughts.  In Pathways
    to Health:  The Role of Social Factors, edited by JP
    Bunker, DS Gomby, BH Kehrero.  Menlo Park, CA:  Henry J.
    Kaiser Family Foundation, 1989, pp. 76-135.
3.  Ross R: The pathogenesis of atherosclerosis: a
    perspective for the 1990s.  Nature 1993;362: 801-809.
4.  Wilson TW, Kaplan GA, Kauhanen J, Cohen RD, Wu M,
    Salonen R, Salonen JT: Association between plasma
    fibrinogen concentration and five socioeconomic indices
    in the Kuopio Ischemic Heart Disease Risk Factor Study.
    Am J Epidemiol 1993;137:292-300.
5.  Everson SA, Kaplan GA, Goldberg DE, Salonen R, Salonen
    JT: Hopelessness predicts 4-year progression of carotid
    atherosclerosis among eastern Finnish men. 1995,
    submitted for publication.
6.  Rozanski A, Bairey CN, Krantz DS, Friedman J, Resser KJ,
    Morell M, Hilton-Chalfen S, Hestrin L, Bietendorf J,
    Berman DS: Mental stress and the induction of silent
    myocardial ischemia in patients with coronary artery
    disease.  New Engl J Med 1988;318:1005-1012.
7.  Tyroler HA: Socioeconomic status in the epidemiology and
    treatment of hypertension.  Hypertension 1989; 13
    (Suppl):I94-97.
8.  Susser M, Watson W, Hopper K:  Sociology in Medicine,
    third edition.  New York: Oxford University Press, 1985.
9.  Rose G, Marmot MG: Social class and coronary heart
    disease.  Br Heart J 1981;45:13-19.
10. Schnall PL, Landsbergis PA, Baker D: Job strain and
    cardiovascular disease. Ann Rev Public Health
    1994;15:381-411.
11. Haan M, Kaplan GA, Camacho T:  Poverty and health:
    prospective evidence from the Alameda County Study.  Am
    J Epidemiol 1987;125:989-998.
12. Lynch JW, Kaplan GA, Cohen RD, Tuomilehto J, Salonen JT:
    Do known risk factors explain the relationship between
    socioeconomic status, risk of all-cause mortality,
    cardiovascular mortality, and acute myocardial
    infarction? 1995, submitted for publication.
13. Kaplan GA: Where do shared pathways lead?  Some
    reflections on a research agenda.  Psychosom Med
    1995;57:208-212.
14. Rose G:  The Strategy of Preventive Medicine. Oxford:
    Oxford University Press, 1992.
-----------------------------------------------------------
Socioeconomic Status and Cardiovascular Disease Mortality:
National Longitudinal Mortality Study
Paul D. Sorlie, Ph.D.
Norman J. Johnson, Ph.D.
Eric Backlund, M.S.
The National Longitudinal Mortality Study  (NLMS)  is a
prospective study of mortality in persons who were
interviewed during various Current Population Surveys
conducted monthly by the Bureau of the Census (1).
Detailed social, economic, and demographic information on a
sample of the U.S. population is obtained by household
interview.  These surveys provide, among other information,
the monthly unemployment rate in the United States.  This
analysis uses information from approximately 600,000 persons
age 25 years or more.  The National Death Index was used to
identify approximately 65,000 persons from these surveys who
died during the years 1979 through 1989.  Underlying cause
of death was obtained from the death certificate.  A person-
years approach for calculating annual death rates and a
proportional hazards model for calculating relative risks
were utilized to describe the relationship between
education, income,  and mortality from cardiovascular
disease (CVD).
Our analyses focus on the following:
*  the strength of the income and education associations
   with mortality;
*  the independence of the associations when income,
   education, and other socioeconomic status (SES)
   characteristics are considered together;
*  the consistency of the associations in ethnic and gender
   groups; and
*  the differences in the strength of associations in the
   NLMS relative to the Kitagawa-Hauser study in 1960 (2).
Figure 1 presents the relative mortality from CVD for
categories of family income for men and women 25 to 64 years
of age.  When adjusted for age and race, there is a steadily
declining mortality by increasing income so that the
mortality at $50,000 or more is one-third that of the lowest
income categories.  After further adjustment for SES (i.e.,
education, marital status, employment status, and household
size), the relationship is not as strong, as would be
expected, but there is still a substantial effect of income
independent of these other variables.
Figure 2 presents the relative mortality from CVD by
education.  Again, CVD mortality decreases with increasing
education; as seen for income, the risk at the highest
education level is about one-third that at the lowest.  This
relationship remains evident after adjustment for SES (i.e.,
income, marital status, employment status, and household
size).  It is noteworthy that the steepest declines in
mortality risk occur at the highest levels of education,
namely, beyond high school.
-----------------------------------------------------------
Figure Missing
Figure 1.  -  Relative Cardiovascular Mortality by Income.
Estimates were obtained from the proportional hazards model
using indicator variables for each income category with the
lowest income as the reference point.  The y-axis displays
the relative risk on a logarithmic scale.  Source:  NLMS.
-----------------------------------------------------------
Figure Missing
Figure 2.  -  Relative Cardiovascular Mortality by
Education.  High school graduate is used as the reference
group.  Source:  NLMS.
-----------------------------------------------------------
Figure 3 reflects CVD mortality rates for three levels of
education  -  less than high school, high school, and
greater than high school.  The annual mortality rates are
shown for blacks, whites of Hispanic background, and non-
Hispanic whites.  Each group shows strong and steady
decreases in CVD mortality with increasing education.
The last question to be addressed is how these data compare
to similar data collected in 1960 from the Kitigawa-Hauser
Study (2).  These results (Fig. 4) are courtesy of Drs.
Preston and Elo of the University of Pennsylvania, who
analyzed the NLMS data available in a public use data set
(3).  The 1960 data (left) indicate that the difference in
the death rate from the lowest education to the highest was
3.9 deaths per 1,000 for men 25 to 64 years of age.
Dividing this difference by the annual death rate (8.0 per
1,000) to obtain a ratio of the death rate reveals that the
difference is 0.49 of the death rate for that group as a
whole.  NLMS data for the 1980s (right) show a difference of
4.1 deaths per 1,000 (about the same as in 1960), but the
ratio of 0.80 is much higher  since the average death rate
is lower.  Because this graph is plotted on a log scale, the
slope for the 1980s is steeper than that for 1960.  Thus,
for this age group of men, the impact of education on
mortality is stronger now than in 1960.
-----------------------------------------------------------
Figure Missing
Figure 3.  -  Cardiovascular Mortality by Education, Sex,
and Race:  Age 45 to 64 years.  Source:  NLMS.
-----------------------------------------------------------
Figure Missing
Figure 4.  -  Estimation of Slope Index of Inequality:
White Men, 25 to 64 Years.   The slope index of inequality
represents the decrease in the death rate from the lowest
education to the highest education, with education scaled as
a percentile.  The bars indicate the death rates for each
level of education.  The width of each bar represents the
percent of population at each education category.  The line
shows the slope of a regression of the death rates on
education scaled as cumulative percentiles of the actual
education levels.  "Difference" is the difference in the
death rate from the lowest to the highest education level.
"Average death rate" is the death rate for the group as a
whole.  Source: Preston and Elo (3).
-----------------------------------------------------------
Table Missing
Table 1.  -  Magnitude of the Education Versus Mortality
Gradient: Ratio of the Decrease in the Mortality Rate  to
the Average Mortality Rate*
*Slope index of inequality / Mortality rate
Source: Preston and Elo (3).
-----------------------------------------------------------
Table 1 shows the difference in mortality across the
education scale (slope index of inequality)  as a ratio of
the death rate for each sex and age group.  This is the same
statistic that was described in the Figure 4 (note the 0.49
and the 0.80).  These results show that the mortality
differentials for men in the current NLMS data are larger
than the differentials found in 1960.  For women, the
mortality differentials do not appear that much different
from the earlier study.  Simply put, this means that for men
the mortality gap between those with high and low education
as a percent of the level of mortality has widened.
In conclusion, this summary of results from the NLMS shows
that the CVD mortality differentials by education and income
are very strong, that income and education each contribute
independently to the differentials in mortality, that this
finding is evident and consistent in men and women and in
blacks, Hispanic whites and in non-Hispanic whites.  There
is further evidence that for men, the mortality gradient by
education is stronger now than it was in 1960.
REFERENCES
1.  Sorlie PD, Backlund E, Keller JB: U.S. mortality by
    economic, demographic, and social characteristics: The
    National Longitudinal Mortality Study. Am J Public
    Health 1995;85:949-956.
2.  Kitagawa EM, Hauser PM: Differential Mortality in the
    United States: A Study in Socioeconomic Epidemiology.
    Vital and Health Statistics monographs. American Public
    Health Association.  Cambridge, MA: Harvard University
    Press, 1973.
3.  Preston SH, Elo IT: Are educational differentials in
    adult mortality increasing in the United States? J Aging
    and Health 1995;7:476-496.
-----------------------------------------------------------
Socioeconomic Factors in Ischemic Heart Disease Morbidity
and Mortality
Jacob J. Feldman, Ph.D.
Diane M. Makuc, Dr.P.H.
This report describes data on educational differentials in
morbidity from the first National Health and Nutrition
Examination Survey (NHANES I) Epidemiologic Followup Study
(NHEFS).  Point prevalence estimates are the only morbidity
data appearing in the pre-conference Chartbook on U.S.
National Data on Socioeconomic Status and Cardiovascular
Health and Disease, but incidence and case fatality are more
informative measures of morbidity.  Prevalence and death
rates can be viewed as a function of incidence and survival
(1,2).  In designing interventions to lessen the disease
burden among the disadvantaged, we need to know at what
stages in the process disparities develop.
NHEFS is the only nationally representative database that
provides information on socioeconomic status (SES)
differentials in heart disease incidence and survival for
the United States.   The study is being conducted by the
National Center for Health Statistics (NCHS) with funding
from some 12 other Federal agencies, primarily components of
the National Institutes of Health.  The basic design of this
longitudinal cohort study is depicted in Figure 1 and in
various NCHS publications (3,4).
-----------------------------------------------------------
Figure Missing
Figure 1.  -  Basic Design of the NHEFS.
-----------------------------------------------------------
Table 1.  -  Definition of Incident IHD Cases
*   No history of heart disease at baseline
*   Never had a heart attack or heart failure
*   No heart medication during past 6 months
but during followup period either:
*   Death certificate with any mention of IHD
     (ICD-9 codes 410-414)
or
*   Hospital record with an IHD diagnosis
[end Table 1]
-----------------------------------------------------------
The analysis is based on observations for the entire period
from 1971 through 1993.  As this is the first analysis that
includes the only recently collected data for the 1987-1993
period, the results are preliminary.  More intensive
analysis of these data may be expected to result in the
identification of some data errors and, therefore, a
moderate number of edits.  However, it is certain that the
basic findings will be sustained.
There have been more than 150 publications and presentations
based on the earlier waves of NHEFS; many of them have been
concerned with cardiovascular disease (CVD) and have treated
SES as a covariate in analyses focusing on other risk
factors (5).  The SES differentials themselves were the
major focus of two earlier papers of particular relevance.
Trends over the past several decades in the differentials
were examined in a paper by Feldman, Makuc, Kleinman, and
Cornoni-Huntley (6).   (Excerpts from that paper were
reprinted in the 1994 Report of the NHLBI Task Force on
Research in Epidemiology and Prevention of Cardiovascular
Diseases.)  For older white males, earlier research had
shown no relationship between educational attainment and
heart disease mortality in 1960 (7).  On the other hand, the
NHEFS observations covering the period from 1971 to 1984
showed a steep heart disease mortality gradient in relation
to educational attainment. The decline in heart disease
death rates in the 1970s and 1980s appeared, for males,  to
have occurred only among the more educated.   The rates for
the less educated older males changed very little over that
period.  It was also found that, among older white females,
the more highly educated were already experiencing lower
heart disease mortality rates in 1960 than the less
educated.  This gradient did not appear to grow steeper over
time.  Cox proportional hazards regression models for  age-
gender strata of the NHEFS data  -  assessing the
educational attainment-heart disease  mortality relationship
controlling for smoking, overweight, hypertension, and
cholesterol  -  were also presented.  Educational attainment
remained a highly significant risk factor, the estimate of
relative risk being reduced rather little in the full model.
The decrease in the risk of heart disease mortality with
increased education did not appear to be the result of the
covariates.  A number of alternative explanations of the
trend over time in the education-heart disease relationship
were discussed.
In a second paper, Makuc, Feldman, and Gillum separated into
incidence and case fatality components the educational
differentials in mortality from ischemic heart disease (IHD)
and total heart disease, again based on observations from
the 1971-1984 period of NHEFS (8).  Among both men and
women, the less educated experienced higher incidence rates
for IHD and total heart disease than did more educated
individuals.  In Cox proportional hazards regression models,
a relatively strong SES differential remained after
controlling for smoking, body mass index, hypertension,
cholesterol, and diabetes.  The less educated also
experienced appreciably shorter survival times after onset
than did the more educated.  Certain of the confidence
intervals were rather broad because of the relatively small
number of incident cases in some age-gender strata.
Extending the database to include an additional 10 years of
heart-related events facilitates analyses of survival
differentials.
-----------------------------------------------------------
Figure Missing
Figure 2.  -  Risk Ratios for IHD Incidence by Education for
White Men and Women Ages 45 to 64 and 65 to 74 at Baseline
in NHEFS, 1971-1993.  High school graduation or above is
used as the reference group.  Age at baseline, in single
years of age, has been entered as a covariate in these
proportional hazard models.  The vertical lines indicate 95
percent confidence intervals surrounding the estimates of
relative risk.
-----------------------------------------------------------
Incidence, NHEFS, 1971-1993
We require either hospital record or death certificate
evidence in ascertaining cases of IHD (Table 1).  There are
some problems of underascertainment and of dating of the
onset due to failure or delay in diagnosis, delay in
hospitalization, reporting errors, and the inability to gain
access to certain hospital records.  The likely extent of
such errors, and their potential impact on inferences based
on this database, will be considered in a later publication.
One might assume, however, that the less educated, because
of inferior access to care, would be likely to be diagnosed
and hospitalized later in the course of illness, a
phenomenon that would underestimate their relative risk.
Figure 2 presents estimates of the relative risks of IHD
incidence for white males and females in two age groups
according to educational attainment, with high school
graduation or above as the reference group.  Without
exception, estimates indicate that those who had not
graduated from high school were more likely to have
developed IHD by any given age than those who had graduated
from high school.  The risk ratios for the less educated
remain high at older ages.  The estimates presented in
Figure 2 are derived from a model parametrized in terms of
age at baseline, but we have also performed analyses based
on age at the time of risk that confirm the persistence of
the SES gradient in incidence at quite advanced ages.  These
findings are particularly noteworthy because it has been
previously observed that the impacts of many CVD risk
factors tend to diminish with increasing age (9).
Notwithstanding the fact that the SES differentiation in
atherosclerosis and other preclinical cardiovascular
pathology probably begins decades earlier in the lifespan,
the incidence differentials remain large at advanced ages.
It is conceivable that the relative weights of the various
etiological factors responsible for the incidence gradient
change over the lifespan.
-----------------------------------------------------------
Figure Missing
Figure 3.  -  Risk Ratios for IHD Deaths among IHD Cases by
Education for White Men and Women in NHEFS, 1971-1993.  Age
at onset and gender are stratifying variables; a separate
proportional hazards model was estimated for each of the six
groups.  Age at onset, in single years of age, was also
entered into the model as a covariate.
-----------------------------------------------------------
Figure Missing
Figure 4.  -  Risk Ratios for IHD Deaths by Education for
White Men and Women, Ages 45 to 64 and 65 to 74 at Baseline,
in NHEFS, 1971-1993.  Age at baseline, in single years of
age, has been entered as a covariate in these proportional
hazards models.
-----------------------------------------------------------
Case Fatality
We define survival time as the interval between the date of
onset and the date of death with IHD coded as the underlying
cause.  Deaths from causes other than IHD were treated as
observations censored at the date of death.  Differentials
in survival time for IHD are shown in Figure 3.  The more
educated had longer survival (in terms of a trajectory of
lower ischemic heart disease mortality rates) after onset in
five of the six age-gender strata.  The survival advantage
of the more educated appears, in the present dataset, to be
greatest at the youngest age at onset but the trend is not
statistically significant.  It is not possible to determine
from the present dataset the extent to which the
differentials in survival primarily reflect differences in
disease severity or whether the outcome differences reflect
other factors related to SES.
Mortality and Prevalence
Proportional hazards models for IHD mortality, following the
same structure as the incidence models in Figure 2, have
also been estimated for the 1971-1993 database (Fig. 4).
Substantial differentials by educational attainment were
found in all four age-gender strata.  Both incidence rates
and the trajectory of the mortality hazard from IHD after
disease onset were considerably less favorable among the
less educated.  These two tendencies compound to produce the
large observed age-specific mortality differentials.
The prevalence of IHD is a function of incidence and
survival time (1,2).  The educational differentials in
prevalence tend to be smaller than for incidence and
mortality, as the longer survival time of the more educated
increases the number of IHD cases alive at any given point
in time.  (Survival models shown in Figure 3 predict death
from IHD while prevalence is a function of the all-cause
mortality hazard subsequent to onset.  The estimates of the
SES risk ratios for all-cause models are consistent with
those for IHD.)  Estimates of the average point prevalence
of IHD cases among white males aged 65 or older for NHEFS
during the 1992-1993 period exhibit practically no gradient
at all for educational attainment.  Averaging over the 6-
year period 1988-1993, the National Health Interview Survey
(NHIS) shows a positive self-reported IHD point prevalence
gradient with education for non-Hispanic white males aged 65
or older (i.e., the more highly educated have somewhat
higher point prevalence rates than the less educated).  On
the other hand, in younger age groups, the more highly
educated report lower point prevalence than the less
educated.  The Medicare Current Beneficiary Survey (MCBS)
shows a flat relationship between educational attainment and
self-reported IHD point prevalence for white males aged 65
or older (10).  The NHANES III for 1988-1991 shows the
highest point prevalence of cases with either self-reported
myocardial infarction or angina (Rose Chest Pain
Questionnaire) among the more highly educated for white men
aged 65 or older.  As in the NHIS, there is a higher-order
interaction between age, educational attainment, and point
prevalence; in the age groups below 65 years, the more
highly educated have the lowest point prevalence rates.  On
the basis of the incidence and survival differentials, one
can deduce that heart disease patients among the more
educated white males age 65 or older have, on average, been
living with diagnosed IHD for a longer period of time than
those with less education.  While the mean survival times
differ, it is uncertain how similar the shapes of the
distributions of durations since onset are for the
populations with differing educational attainment.  It could
be informative to investigate the shapes of those
distributions. Analysis of the NHEFS data covering the 1971-
1984 period for the white population indicated a higher rate
of heart-related surgery among the more highly educated
(11).  Analyses of 1993 Medicare data based on SES
characteristics of the zip code of residence suggest a more
or less flat relationship between the rates for various
atherosclerosis-related surgical procedures and SES for
white beneficiaries (12).  To the extent that the size of
the pool of prevalent cases of IHD influences the surgical
procedure rate, the relatively small SES differentials in
surgical rates for the older white population are consistent
with the weak SES gradient in point prevalence.
Further Research
This is the first presentation based on the NHEFS database
extended to 1993.  A number of more detailed analyses are
under way.  Earlier analyses focused primarily on the white
population because of sample size considerations.  An
analysis  performed on the 1971-1987 data showed that
educational differentials in mortality were similar for
black and white males (11).  With the heart disease events
occurring in the 1987-1993 period added to the database,
more definitive investigations of educational differentials
in heart disease among blacks have become feasible and will
be conducted.
In the analyses of the NHEFS database thus far, the events
of the entire period from 1971 to 1993 are aggregated.
Although great changes have taken place since 1960, we have
not examined individual-level data for changes in
differentials in more recent decades.  The 1979-1989
National Longitudinal Mortality Study data presented by Dr.
Sorlie also have been treated as deriving from a single time
period (13).  As the SES gradient shifted so markedly
between 1960 and the early 1970s, it seems probable that the
gradient has continued to shift since then in one direction
or the other.  Modeling by specifying time period
stratification and the use of time as a covariate may help
clarify this question.
Medicare Part A benefit records have, since 1984, been
linked to the NHEFS database.  These will provide the basis
for the methodological research regarding the completeness
of ascertainment and problems with the accuracy of the
dating of onset.  In addition, these linked benefit records
facilitate research into SES differentials in the cost of
services related to heart disease.
In examining various risk factors as covariates in our
proportional hazards models, we have relied exclusively on
measurements from the 1971-1975 baseline examination.  Data
on potential risk factors were collected in the 1982-1984,
1986, and 1987 waves.  The inclusion of measures from these
waves in our models may well elucidate the mechanisms
through which the SES differentials operate.  In addition,
following, through successive waves, cases with onset early
in the study period should increase our understanding of SES
differences in the natural history of IHD.  While primary
prevention may be the ideal, intervention at later stages in
the disease process may also be effective in reducing SES
differentials.
Conclusions
Our analysis of the NHEFS database, extended to 1993, has
shown a strong SES gradient for the incidence of IHD in the
white population for both males and females extending
throughout the age span.  Analyses of data from the first
decade of the study were not able to account for the SES
differentials in terms of the risk factors for which data
were available.  We also found a strong SES gradient for
case fatality in the white population for both males and
females, particularly at the younger ages.  On the other
hand, there does not currently appear to be a marked SES
gradient in the prevalence of IHD among older white males.
This presentation was the first based on the extended NHEFS
database.  More detailed analysis of these data holds
promise of elucidating some of the mechanisms underlying the
SES gradients.
References
1.  Seigel DG, Krueger DE: Consistency of incidence,
    survival, and prevalence data on myocardial infarction
    from various studies.  J Chron Dis 1967;20:603-614.
2.  Freeman J, Hutchison GB: Prevalence, incidence and
    duration.  Am J Epidemiol 1980;112:707-23.
3.  Cohen BB, Barbano BE, Cox CS, et al: Plan and operation
    of the NHANES I Epidemiologic Followup Study: 1982-84.
    Vital Health Stat 1987;1(22).
4.  Cox CS, Rothwell ST, NWans JK, et al: Plan and operation
    of the NHANES I Epidemiologic Followup Study, 1987.
    Vital Health Stat 1992;1(27).
5.  Leaverton PE, Havlik RJ, Ingster-Moore LK, et al:
    Coronary heart disease and hypertension. In Health
    Status and Well-Being of the Elderly: National Health
    and Nutrition Examination Survey-I Epidemiologic
    Followup Study, edited by  JC Cornoni-Huntley, RR
    Huntley, JJ Feldman. New York: Oxford University Press,
    1990, pp. 53-70.
6.  Feldman JJ, Makuc DM, Kleinman JC, Cornoni-Huntley JC:
    National trends in educational differentials in
    mortality.  Am J Epidemiol 1989;129:919-933.
7.  Kitagawa EK, Hauser PM: Differential Mortality in the
    United States: A Study in Socioeconomic Epidemiology.
    Cambridge, Massachusetts: Harvard University Press,
    1973.
8.  Makuc DM, Feldman JJ, Gillum RF: Educational
    differentials in heart disease incidence and case
    fatality in a national sample.  Presentation at the
    Annual Conference of the Society for Epidemiological
    Research, 1988.
9.  Kannel WB, Gordon T: Cardiovascular risk factors in the
    aged: The Framingham Study. In Second Conference on the
    Epidemiology of Aging, edited by SG Haynes, M Feinleib.
    NIH Publication No. 80-969, 1980, pp.65-89.
10. National Heart, Lung, and Blood Institute: Chartbook of
    U.S. National Data on Socioeconomic Status and
    Cardiovascular Health and Disease, 1995.
11. Makuc DM, Feldman JJ: Socioeconomic differentials in
    all-cause and heart disease mortality; individual level
    data.  Presentation at the Annual Conference of the
    American Public Health Association, 1989.
12. Health Care Financing Administration: Monitoring the
    Impact of Medicare Physician Payment Reform on
    Utilization and Access. HCFA Publication No. 03379,
    1995.
13. Sorlie P: Presentation at this meeting.
-----------------------------------------------------------
Socioeconomic Status and Biomedical, Lifestyle, and
Psychosocial Risk Factors for CVD:  Selected U.S. National
Data and Trends
Clifford L. Johnson, M.S.P.H.
Christopher T. Sempos, Ph.D.
During the past 30 years, there has been a marked decline in
U.S. death rates from cardiovascular disease (CVD),
including coronary heart disease (CHD) and stroke.  Although
every segment of the population has benefited from this
decline, not all population subgroups have benefited to the
same extent.  This observation is almost certainly a result
of the differential effect of the numerous biomedical,
lifestyle, and psychosocial risk factors on the prevalence
of CVD.  The relationship between socioeconomic status (SES)
and these risk factors is important.  As noted in the
National Heart, Lung, and Blood Institute (NHLBI) Report of
the Task Force on Research in Epidemiology and Prevention of
Cardiovascular Diseases, "Membership in less affluent and
less educated groups is associated with higher levels of
cigarette smoking, high blood pressure, obesity, and
physical inactivity.  These groups also tend to consume more
adverse diets and to lack access to health care services,
particularly prevention services"(1).
The major risk factors for CVD are well known and include:
*  Abnormal blood lipids and lipoproteins
*  Elevated blood pressure
*  Smoking
*  Obesity
*  Physical inactivity
*  Diabetes mellitus
*  Adverse dietary patterns
*  Psychosocial factors
While there are other potential CVD risk factors, both old
and emerging, the list describes those risk factors with the
largest potential for reducing or preventing CVD with
improved status in the general population.  The focus of
this analysis is a review of national data and national
trends using two surveys conducted by the National Center
for Health Statistics (NCHS) of the Centers for Disease
Control and Prevention.
The National Health and Nutrition Examination Survey
(NHANES) is a complex, multistage, national probability
sample of the civilian noninstitutionalized population of
the United States.  Conducted periodically by NCHS and
unique in that it includes both an interview component and a
standardized physical examination as part of the survey (2),
each NHANES produces information on many of the risk factors
for CVD in its examination component.  The National Health
Interview Survey (NHIS), an interview survey conducted
annually by NCHS (3), obtains data on the incidence of acute
illness and injuries, the prevalence of chronic conditions
and impairments, the extent of disability, and utilization
of health care services.  Both surveys have the capability
to assess the relationship between SES and various CVD risk
factors at a given point in time, as well as to assess
trends in various CVD risk factors over time.  The ability
to assess trends is possible since many of the questions or
examination methods have remained comparable over time.
The findings are primarily based on information found in the
Chartbook of U.S. National Data on Socioeconomic Status and
Cardiovascular Health and Disease (4).  Although the
Chartbook contains information from a number of surveys and
surveillance systems, only findings from the NHIS and NHANES
surveys are used as examples in this analysis.  Findings for
the other studies shown in the Chartbook were generally
similar to those shown for the NHIS or NHANES.
A large number of biomedical, lifestyle, and psychosocial
risk factor findings are presented in the Chartbook.  All of
these variables have been implicated as risk factors for CVD
based on previous studies, and many were discussed
extensively in the NHLBI Report of the Task Force on
Research in Epidemiology and Prevention of Cardiovascular
Disease.  It was logical to believe that similar conclusions
would be found when more recent data from NHANES III and the
1993 NHIS were analyzed.  However, this was not always the
case.
Table 1 categorizes certain CVD risk factors into two groups
based on an overall assessment of their relationship to the
three SES variables used in the Chartbook analyses (i.e.
education, income, and occupation).  These SES variables
were not related in any consistent manner to at least half
of the previously defined risk factors in these two national
surveys.  Although the categorization into two groups is
possibly an oversimplification, the fact remains that the
relationship between many of these risk factors and SES is
uncertain.
One of the CVD risk factors that did show a strong
relationship with SES was smoking.  Higher levels of
cigarette smoking were associated with persons who are less
educated and less affluent.  Figure 1 shows the prevalence
of cigarette smoking among men and women ages 45 to 64 years
by education, sex, and race/ethnicity group from the 1993
NHIS.  For all six race/ethnicity-gender groups, the highest
prevalence of smoking was observed in the group with less
than high school education.  This pattern was similar to
that observed in the 25 to 44 and 65+ years age groups (not
shown).  Similar results were found when income and
occupation were used as the surrogate for SES.  The lowest
income group had the highest prevalance of cigarette use,
and the blue collar and service groups had the highest
smoking prevalences among the occupation categories.
However, the relationship between income, education, or
occupation and cigarette usage was different for the
Hispanic subgroup.  Whether this inconsistent pattern for
the Hispanic population resulted from smaller sample sizes
that did not allow for consistent patterns to be observed,
an inadequate definition of SES for this population
subgroup, or a truly different relationship within this
population group remains unresolved.
With respect to trends over time, the overall conclusion is
that for most sex-race/ethnicity-SES subgroups there has
been a decrease in the prevalence of cigarette smoking.  For
example, the prevalence of smoking among 25 to 44 year old
black and white males decreased from 1976 to 1993 in all
educational subgroups (Fig. 2).  However, the decrease is
less obvious in some of the lowest education groups.  In
contrast, among 25 to 44 year old black and white women, the
percent who smoked cigarettes actually stayed the same or
increased in the lowest educational subgroup. Thus, while a
generally decreasing pattern in cigarette smoking was
observed when comparing NHIS data for 1976 and 1993, the
decrease was much more significant in the highest SES
subgroups.  Similar patterns were observed when income was
used as the SES variable.  This finding is likely to be
related to the increasing gap in CVD death rates between
various race/ethnicity groups.
-----------------------------------------------------------
Table 1.  -  Strength of Association Between CVD Risk
Factors and SES Measures
Weak:
Blood pressure; cholesterol; diet; psychosocial factors
Strong:
Overweight; cigarette smoking; diabetes; physical activity
[end Table 1]
-----------------------------------------------------------
Figure Missing
Figure 1.  -  Current Cigarette Smoking by Race/Ethnicity
and Education: Men and Women Ages 45 to 64.    Source:
NHIS, 1993.
-----------------------------------------------------------
Figure Missing
Figure 2.  -  Trends in Cigarette Smoking by Education and
Race/Ethnicity: Men and Women Ages 45 to 64. NHB = non-
Hispanic black; NHW = non-Hispanic white. Source:  NHIS,
1976, 1993.
-----------------------------------------------------------
The relationship between the SES variables used in the
Chartbook and many other CVD risk factors was much more
complicated than that observed for cigarette smoking and was
affected by the way the analyses were conducted.  The
observed relationship between overweight and income in the
NHANES III (1988-91) data is such an example.  For these
analyses, overweight was defined as a value greater than the
age-sex specific 85th percentile cut points for body mass
index for 20 to 29 year old males and females from NHANES II
(5).  The table in the Chartbook used data from the first
phase of NHANES III, and family income was classified into
four different groups.  In general, differences were
observed in the prevalence of overweight by income status.
However, the pattern was not consistent among men and women
and among the various racial/ethnic groups.  Moreover, for
many subgroups the survey sample sizes were too small to
make meaningful comparisons.
Figure 3 presents similar analyses using another measure of
income status and fewer categories.  The alternative
definition of income status is the poverty income ratio
(PIR).  PIR is a standardized variable calculated from
annual census tables that takes into account family size,
family composition, and total family income.  It also allows
comparison of findings from various surveys over time, which
would not be possible with income data alone.
For this alternative analysis, the sample sizes were
adequate to divide PIR into three categories.  The lowest
category (less than or equal to 1.30) uses a cut point that
determines eligibility for selected government sponsored
food assistance programs.  The upper category is a
calculated PIR greater than 3.50, and the middle category is
between these two cut points.
The relationship between income status and overweight is
different for men and women.  In addition, the relationship
differs between race/ethnicity groups.  For non-Hispanic
white men, the prevalence of overweight is lower in the
upper income group, whereas, for both non-Hispanic black men
and Mexican-American men the opposite is true:  the
prevalence of overweight is lowest in the poorest income
group (Fig. 3).  For non-Hispanic white women, the pattern
is similar to that for white men, that is, the lowest
prevalence is found in the upper income category.  While
this pattern is also observed in Mexican-American women,
non-Hispanic black women show very little change in the
prevalence of overweight regardless of income status.  Thus,
the "effect" of low income on the prevalence of overweight
is not consistent among the major U.S. population groups,
and the "effect" is not the same in men as in women.  This
leads one to conclude that the relationship of SES to some
of these CVD risk factors is complex and not easily
definable.
Many more examples could be shown using other biomedical,
lifestyle, or psychosocial risk factor data found in the
Chartbook.  The relationship between these risk factors,
SES, and health outcomes such as cardiovascular health is
complex and reflects the complex manner in which social and
economic status and race interact in the United States.
This topic has been discussed recently in a number of
articles.  Dr. Gregory Pappas noted in an editorial in the
American Journal of Public Health that "the complex ways in
which social and economic class and race create
disadvantages and produce disparities in health must be more
fully investigated" (6).  Based on these findings, more
investigation is needed.  It is extremely difficult to
summarize all the findings on SES and CVD.  It is possibly
due to the lack of a consistent and agreed-upon definition
of SES or "social class."   Although "class" is a difficult
and sometimes contentious term, Dr. Pappas contended that
some measure of it is necessary in order to examine
disparities in health among various racial and ethnic
populations.  Agreement on a standard measure of "class" or
SES is critical to the process as well.
-----------------------------------------------------------
Figure Missing
Figure 3.  -  Age-adjusted Prevalence of Overweight by
Poverty Status and Race/Ethnicity: Men and Women Ages 20 and
Over.  Source:  NHANES III, 1988-91.
-----------------------------------------------------------
Similar issues and conclusions were also noted in a Public
Health Reports article by Moss and Krieger (7).  In an
introduction, Dr. Phillip R. Lee, the Assistant Secretary
for Health, acknowledged the limitations of SES measures
(especially occupation) in many of the Federal, state, and
local health data and indicated that many of the
recommendations from that conference would be implemented in
the coming months and years.
With the currently available national survey data and with
agreed-upon indicators of "social class" or SES, some
evaluation of disparities in health among population
subgroups is possible.  The recently completed second phase
of NHANES III will be available in the near future.  This
will allow analyses of the full 6-year study with increased
sample sizes that will clearly resolve some of the
limitations that were encountered by the Chartbook
developers when creating tables based on the first phase of
data from that survey.  In addition, NHANES III has a number
of SES variables (including occupation) collected in a
standardized manner, which will allow numerous analyses of
SES and cardiovascular health based on the wealth of
information collected in that survey.  Many of these
variables were consistently collected across previous NHANES
surveys and will provide the basis for assessing trends over
time.  These data, in conjunction with information from the
NHIS and other non-national or subpopulation-specific
national data sets, will greatly increase our knowledge of
the relationship between SES (or social class) and CVD. We
have the beginnings of that information data base today in
the Chartbook.  The rest remains for us to analyze,
interpret, and implement in the future.
References
1.  National Heart, Lung, and Blood Institute:  Report of
    the Task Force on Research in Epidemiology and
    Prevention of Cardiovascular Diseases, 1994.
2.  National Center for Health Statistics:  Plan and
    operation of the Third National Health and Nutrition
    Examination Survey, 1988-1994.  Vital Health Stat
    1994;1(32).
3.  National Center for Health Statistics:  Current
    estimates from the National Health Interview Survey,
    1993.  Vital Health Stat 1995; 10(190).
4.  National Heart, Lung, and Blood Institute:  Chartbook on
    U.S. National Data on Socioeconomic Status and
    Cardiovascular Health and Disease, 1995.
5.  Kuczmarski RJ, Flegal KM, Campbell SM, Johnson CL:
    Increasing prevalence of overweight among US adults: the
    National Health and Nutrition Examination Surveys, 1960
    to 1991.  JAMA 1994;272:205-211.
6.  Pappas G:  Elucidating the relationships between race,
    socioeconomic status, and health.  Am J Public Health
    1994;84:892-893.
7.  Moss N, Krieger N:  Measuring social inequalities in
    health: report on the conference of the National
    Institutes of Health.  Public Health Reports
    1995;110:302-305.
-----------------------------------------------------------
SES and Medical Care Utilization Related to CVD: Selected
U.S. National Data and Trends
Paul Eggers, Ph.D.
Although there is a great deal of research on the effects of
socioeconomic status (SES) on global utilization rates, such
as physician visits and hospitalizations, there is very
little on cardiovascular disease (CVD) specific use rates.
This is due to at least two reasons.  The first is sample
size.  Surveys are usually designed to obtain health care
use and expenditure data on overall medical services.
Rarely are diagnosis-specific use rates sufficiently sampled
for analysis, even for large categories such as CVD.
Second, many surveys rely on patient recall for the
identification of utilization.  Nonmedically trained
respondents are very poor in identifying cause-specific
utilization.  They can usually recall important medical
events, i.e., hospitalization, but the underlying diagnosis
related to the event is usually poorly understood or
remembered.
A good review of the literature on race and CVD utilization
was recently published by Earl Ford and Richard Cooper (1).
Oberman and Cutter found that blacks who received coronary
arteriography were only 40 percent as likely to receive a
coronary artery bypass graft (CABG) as were whites (2).
Maynard, et al, found that the use of CABG was 30 percent
lower for black males and 10 percent lower for black females
than for their white counterparts (3).  Gillum used the
National Hospital Discharge Survey (NHDS) to show that
blacks received angiography only one-half as frequently as
did whites and were 70 percent less likely to receive a CABG
(4).  Ford, et al, also examined NHDS data, but controlled
for the rate of CVD by using discharge rates for myocardial
infarction (MI) (5).  They estimated a two-fold racial
difference in CABG use, in contrast to the three-fold
difference shown by Gillum.  Wenneker and Epstein examined
Massachusetts hospitalizations for persons admitted with CVD
or chest pain (6).  Blacks had 20 to 30 percent fewer
angiographies and about one-half the number of
revascularizations.  This analysis included a control for
estimated income.
Maynard, using data from Seattle, showed that, although
blacks were equal to whites in use of angiography and
thrombolytic therapy, their rates of revascularization were
still only about one-half those of whites (7).  Hannon, et
al, attempted to control for potential hospital technology
bias by limiting their analysis to hospitals that actually
provide these cardiovascular procedures (8).  Still, they
found similar racial differences.
Two recent studies have used the Medicare data base to look
at the race issue.  Goldberg, et al, found that, in 1986,
aged black males were only 20 percent as likely as aged
white males to receive a CABG (9).  For black women, the
relative use rate was 40 percent.  Goldberg did not attempt
to control for the rate of catheterization.  Franks, et al,
also using Medicare data, did examine catheterization rates
(10).  They found aged black males hospitalized with an MI
to be 50 percent less likely than aged white males to
receive a catheterization.  For females the relative use
rate was 70 percent.  Contingent upon catheterization, both
black males and females were only 60 percent as likely as
their white counterparts to undergo any revascularization
(either percutaneous transluminal coronary angioplasty
[PTCA] or CABG).
Ford and Cooper reached several conclusions.  They include:
*  The question of whether race or SES accounts for many of
   the observed differences in health and health care
   utilization is controversial and remains unanswered.
*  The demonstration of racial differences in the Medicare
   data, where one could argue that economic factors should
   constitute less of a barrier, shows that factors other
   than economic ones play an important role.
*  During the 1980s, after arteriography, PTCA, and CABG
   were routinely available, blacks were far less likely to
   undergo these procedures.
*  A surveillance system, preferably one that is nationally
   based, should be established to monitor various aspects
   of health care utilization, including the use of cardiac
   procedures.
Very few of the national studies on race and cardiovascular
utilization directly address the issue of SES.  The
remaining part of this paper presents data from two national
data bases with SES variables included.
The National Medical Expenditure Survey (NMES)
The NMES was a set of surveys that collected information
about use of and expenses for health services for the year
1987.  This survey included about 14,000 households
representing the civilian, noninstitutionalized population
of the United States.  Data were collected through three
personal surveys and a single telephone survey.  Respondents
were asked to record medical events in a calendar or diary.
Physician visits were identified from "provider probes" for
visits to medical doctors, hospital emergency rooms, and
hospital outpatient departments.  Hospital admissions were
similarly identified by a probe for either an overnight stay
or an admission and discharge the same day.  Demographic
information was obtained from the primary respondent from
each family.
Figures 1 and 2 depict NMES-determined physician visit and
hospitalization rates, respectively.  For whites, there is a
fairly clear gradient for use by education level.  Persons
with more than high school education see a physician for a
cardiovascular problem less than one-half as often as those
with less than a high school education (264 and 574 visits,
respectively).  The effect of education on use rates among
blacks is less dramatic.  However, both high school
graduates and those with more education have about one-third
fewer visits than those with less.  The gradient is more
consistent for both racial groups with respect to income.
For both groups, the highest income category has less than
one-half the use rate of the lowest income group, with
intermediate levels for the other income groups.
Hospitalizations are shown in Figure 2 for all conditions,
all cardiovascular conditions, and for ischemic heart
disease by educational groupings.  The first thing that is
evident is the very low rate of cardiovascular
hospitalization  -  thus, the rates have fairly high errors
of estimation.  Nevertheless, educational gradients seem
evident.  For blacks, those with less than high school
education have approximately twice the overall
hospitalization and up to 5 times the cardiovascular
hospitalization of those with high education levels.  Among
whites the gradient is not so pronounced.  However, for all
three measures of hospitalization, decreases are associated
with increased income levels.
-----------------------------------------------------------
Figure missing
Figure 1.  -  Physician Visits for Any Cardiovascular
Condition by Education, Income, and Race.  Rates shown are
for persons ages 25 to 64, both sexes. Source: Adapted from
1987 NMES.
-----------------------------------------------------------
Figure Missing
Figure 2.  -  Hospitalizations by Education and Race for
Patients Ages 25 to 64.  Hospitalization rates are shown for
all conditions, all cardiovascular conditions, and ischemic
heart disease (IHD) in both sexes by educational groupings.
Source: Adapted from 1987 NMES.
-----------------------------------------------------------
Medicare Link With Census Data
In order to explore the issue of the effect of SES in the
Medicare population, U.S. Census data were used as a proxy
measure for SES, specifically income.  Briefly, utilization
rates were calculated for Medicare beneficiaries by the zip
code of their residence.  The median income for each zip
code obtained from the 1990 U.S. Census was used to estimate
household income for all aged persons living in a zip code.
Zip codes were then aggregated into four income levels, and
utilization rates were developed.  The population was
limited to aged Medicare beneficiaries who were not members
of health maintenance organizations (HMOs).  The counts were
based on total months of non-HMO enrollment.  These data
were taken from the Medicare denominator file for 1993.  For
each zip code, person-year equivalents (total months of
non-HMO enrollment divided by 12) were calculated for each
of three age groups (65 to 74, 75 to 84, 85 and over) for
males and females separately, and for white, black, and
other race categories.
Medicare Trends in Cardiovascular Utilization (1986 to 1993)
The Health Care Financing Administration (HCFA) is the
agency responsible for the Medicare program.  Medicare
covers almost the entire U.S. population over the age of 65
(about 31 million), as well as three million disabled
persons and 200,000 persons with end-stage renal disease.
About 90 percent of the Medicare population receives care in
a fee-for-service environment.  Each of the fee-for-service
encounters generates a bill that can be linked to the
individual beneficiary.  The fact that Medicare is almost
universally available to persons over age 65 means that
population-based use rates can be calculated for fairly
specific kinds of services.  Medicare beneficiaries account
for approximately 11 million hospitalizations annually.  For
each of these hospitalizations, information is available for
both diagnoses and procedures in ICD9-CM format.  As many as
five diagnostic conditions and up to three procedures are
reported.  All procedures were considered but only the
principal condition was examined.  Data were arrayed for the
years 1986 through 1993.
About one-fifth of all hospitalizations among aged Medicare
beneficiaries are for CVD.  Although hospitalization rates
for all heart disease do not differ greatly between black
and white beneficiaries, as seen in Figure 3, black
beneficiaries are much less likely to be hospitalized for
ischemic heart disease (Fig. 4).
-----------------------------------------------------------
Figure Missing
Figure 3.  -  All Heart Disease Hospitalizations of Medicare
Beneficiaries by Race.  Between 1986 and 1993, the
hospitalization rate for whites increased by 10 percent
while the black rate increased by 23 percent, increasing the
black-to-white use ratio from 0.92 to 1.03.  Source:  HCFA.
-----------------------------------------------------------
Revascularization rates are depicted in Figures 5 and 6.
Cardiac catheterization (not shown) increased rapidly for
both white and black beneficiaries during these years.  The
white rate increased by 75 percent, from 9.5 procedures per
1,000 to 16.4 procedures per 1,000.  The black rate more
than doubled, from 5.0 procedures per 1,000 to 11.5
procedures per 1,000.  The black-to-white use ratio
increased from 0.52 in 1986 to 0.70 in 1993.  CABG rates
(Fig. 5) increased at comparable rates (to catheterization)
during these years.  As with the other use measures, the
increase was greater for black beneficiaries than for white
beneficiaries.  In 1986, the CABG black-to-white use ratio
was 0.28.  By 1993 this had increased to 0.40.  The largest
increase in utilization during these years was for PTCA
(Fig. 6).  PTCA was performed only one-half as frequently as
CABG in 1986 but by 1993 the PTCA rate exceeded the CABG
rate for both black and white beneficiaries.  The black-to-
white differential was greater for both CABG and PTCA than
for catheterization.  This is consistent with previous
studies showing lower revascularization rates for black than
for white beneficiaries (11).
-----------------------------------------------------------
Figure Missing
Figure 4.  -  Ischemic Heart Disease Hospitalizations of
Medicare Beneficiaries by Race.  Although black Medicare
beneficiaries are much less likely than whites to be
hospitalized for IHD, their hospitalization rates increased
14 percent between 1986 and 1993, whereas those for whites
increased only 6 percent.  The result was an increase in the
relative black-to-white use ratio from 0.69 to 0.74.
Source:  HCFA.
-----------------------------------------------------------
Figure Missing
Figure 5.  -  CABG Hospitalizations of Medicare
Beneficiaries by Race.  Between 1986 and 1993,
hospitalizations for coronary artery bypass graft (CABG)
procedures rose 67 percent for white Medicare beneficiaries
and 140 percent for blacks.  The black-to-white use ratio
increased from 0.28 to 0.40.  Source: HCFA.
-----------------------------------------------------------
Figure Missing
Figure 6.  -  PTCA Hospitalizations of Medicare
Beneficiaries by Race.  The greatest increase in
hospitalization of Medicare beneficiaries for
revascularizations from 1986 to 1993 occurred among those
undergoing percutaneous transluminal coronary angioplasty
(PTCA).  Utilization increased 315 percent for whites and
503 percent for blacks; the black-to-white use ratio
increased from 0.32 to  0.46.  Source:  HCFA.
-----------------------------------------------------------
Income and Racial Differences in Cardiovascular Utilization
Figure 7 shows four measures of cardiovascular utilization
by income groupings for both white and black Medicare
beneficiaries.  The income groups are based on median income
levels of aged persons by zip code of residence.  White
beneficiaries are arrayed according to median white income
and black beneficiaries are arrayed according to median
black income.  For white persons, there appears to be an
income effect for ischemic heart disease, with rising
hospitalization associated with decreasing income.  The 37.7
hospitalizations per 1,000 persons in the lowest income
quartile is 28 percent greater than the rate for persons
living in higher income zip code areas.  Little evidence
exists of an income differential for cardiovascular
procedures.
To the extent that there is an income differential among
black beneficiaries for ischemic heart disease, it runs in
the opposite direction from that of white persons.  The rate
in the lowest income quartile (24.3 per 1,000) is 13 percent
below the rate (28.0 per 1,000) in the highest income
quartile.  As with white patients, there are no consistent
effects of income on the procedure rates.
Summary
Racial differentials between black and white persons in use
of cardiovascular health care services have been well
documented by a number of studies.  Revascularization among
black persons is about one-half that of white persons.  At
least part of this difference is due to lower rates of
catheterization among black persons.  However, even among
those who receive a catheterization, subsequent
revascularization is considerably lower among black persons.
Most of the studies on these racial differences were
performed on data from the late 1970s through the late 1980s
and were cross-sectional in nature.  There is virtually no
evidence in the literature of potential trend effects.
However, data from the Medicare program suggest that, at
least among the elderly population, the racial disparity in
use rates may be narrowing somewhat.
-----------------------------------------------------------
Figure Missing
Figure 7.  -  Cardiovascular Hospitalization by Race and
Income for Patients Ages 65 and Above, 1993. Source: HCFA.
-----------------------------------------------------------
The role of SES in racial differentials has not been
delineated and will be difficult to measure, short of
indirect aggregate methods such as linkages with census
data.  Initial data from the Medicare-Census data link show
different income patterns.  Among whites, decreasing income
is associated with an apparent increased need (as measured
by hospitalization for ischemic heart disease) for
revascularization, but a steady, if not decreasing, use of
revascularization.  Among black persons, neither the measure
of need nor level of revascularization seems to be related
to income levels.
REFERENCES
1.  Ford ES, Cooper RS: Racial/ethnic differences in health
    care utilization of cardiovascular procedures: a review
    of the evidence. Health Services Res 1995;30(1):237-252.
2.  Oberman A, Cutter G: Issues in the natural history and
    treatment of coronary heart disease in black
    populations: surgical treatment. Am Heart J 1984;108(3,
    part II):688-694.
3.  Maynard C, Fisher LD, et al: Blacks in the Coronary
    Artery Surgery Study (CASS): race and clinical decision
    making. Am J Public Health 1986;76(12):1446-1448.
4.  Gillum RF: Coronary artery bypass surgery and coronary
    angiography in the United States, 1979-1983. Am Heart J
    1987;113: 1255-1260.
5.  Ford ER, Cooper RS, et al: Coronary arteriography and
    coronary bypass surgery among whites and other racial
    groups relative to hospital based incidence rates for
    coronary artery disease: findings from NHDS. Am J Public
    Health 1989;79(4):437-440.
6.  Wenneker MB, Epstein AM: Racial inequities in the use of
    procedures for patients with ischemic heart disease in
    Massachusetts. JAMA 1989;261(2):253-257.
7.  Maynard C, Litwin PE, et al: Characteristics of black
    patients admitted to coronary care units in metropolitan
    Seattle: results from the Myocardial Infarction Triage
    and Intervention Registry (MITI). Am J Cardiol
    1991;67(1):18-23.
8.  Hannon EL, Kilburn H, et al: Interracial access to
    selected cardiac procedures for patients hospitalized
    with coronary artery disease in New York State.  Medical
    Care 1991;29(5):430-441.
9.  Goldberg KC, Hartz AJ, et al: Racial and community
    factors influencing coronary artery bypass graft surgery
    rates for all Medicare patients. JAMA
    1992;267(1):1473-1477.
10. Franks AL, May DS, et al: Racial differences in the use
    of invasive coronary procedures after acute myocardial
    infarction in Medicare beneficiaries. Ethnicity and
    Disease 1993;3(3):213-220.
11. Ayanian AZ, Udvarhelyi IS, Gatsonis CA, et al: Racial
    differences in the use of revascularization procedures
    after coronary angioplasty. JAMA 1993;269(20):2642-2646.
-----------------------------------------------------------
Differences Between Occupational Classes in Cardiovascular
Disease Mortality:   A Comparison of 11 European Countries
Anton E. Kunst, M.A., Feikje Groenhof, M.A., Johan
Mackenbach, M.D., Ph.D., and the European Union Working
Group on Socioeconomic Inequalities in Health
Socioeconomic status (SES) differences in health exist in
Europe as well as in the United States (1-3).  The number of
studies on health differences in Europe strongly increased
during the 1980s.  There has been a parallel increase in the
concern with SES differences in health by policy makers in
some European countries.  Much of the research on health
differences in Europe has given special attention to SES
differences in cardiovascular diseases (CVD), an interest
that was stimulated by the observation that social class
differences in CVD mortality in England and Wales have
widened since World War II (4).  Parallel trends were
observed in more recent studies from several other European
countries (5-7).
This variability over time raises the question of whether a
similar regional variability exists between countries.  If
large variations are observed for place as well as time,
that would highlight the changeable nature of SES
differences in CVD.  In addition, a closer look at the
different countries may reveal which circumstances are
associated with smaller or larger inequalities in CVD.
European countries differ widely in standard of living,
socioeconomic policies, health care systems, and culture and
history.  This diversity has resulted in large differences
in the overall level of mortality from CVD and in trends
over time.  For example, the epidemic rise and decline of
ischemic heart disease (IHD) mortality occurred earlier and
was more pronounced in northern Europe than in France and
more southern countries (8).  An obvious  -  but still
unanswered  -  question is whether European countries also
differ with respect to the SES distribution of mortality
from CVD.
In this paper, 11 countries from northern and southern
Europe are compared for SES differences in CVD mortality in
men about 45 to 59 years old.  The data, from the 1980s,
come from an international project sponsored by the European
Union.  Information on mortality by SES was collected
centrally and reanalyzed using a standardized methodology.
Most European countries have nationally representative data
on CVD mortality by occupation, but surprisingly few (about
five) have similar data with education or income as the SES
indicator.  Therefore, mortality differences between
occupational classes are compared in these countries.
Materials and Methods
Nationally representative data were available on mortality
by age, sex, occupation, and cause of death.  For
England/Wales, Finland, Sweden, Norway, Denmark, and Italy,
cause-specific mortality data were available from national
longitudinal studies with approximately 10 years of
followup.  For Ireland, France, Switzerland, Spain, and
Portugal, cause-specific mortality data were obtained from
so-called unlinked cross-sectional mortality studies.  The
study period was ca. 1981-90 for most longitudinal studies
and ca. 1980-82 for the study from Italy and the cross-
sectional studies.
The data presented in this paper refer to men of working
age.  Men older than 60 years and all women were excluded
due to problems with reliability and crossnational
comparability of the measurement of occupational class.
Data from different countries refer to the same age group in
terms of age at death.  For studies where men were
classified according to their age at death, the age group 45
to 59 years was distinguished.  For longitudinal studies in
which birth cohorts were followed 10 years, we distinguished
the birth cohort aged 40 to 54 years at the start of
followup.
Men were classified on the basis of occupation according to
the Erikson-Goldthorpe (E-G) scheme (9).  This is a social
class scheme that is gaining increased acceptance in social
sciences in Europe and elsewhere.  A commonly used version
of the E-G scheme distinguishes the following seven social
classes  (the percentage of the male working population of
northern and western European countries is given in
parentheses):
*  Employers, administrators, managers, and professionals
   (20 to 30 percent)
*  Routine nonmanual employees (5 to 10 percent)
*  Self-employed workers, except professionals and farmers
   (5 to 10 percent)
*  Foremen and skilled manual workers (20 to 30 percent)
*  Semiskilled and unskilled manual workers (20 to 25
   percent)
*  Farmers (5 to 10 percent)
*  Farm laborers (0 to 5 percent)
A more condensed version of the E-G scheme collapses these
seven classes into three broad groups: all nonmanual and
self-employed workers, all wage-earning manual workers, and
farmers and farm laborers.
The seven-class version of the E-G scheme could not be
constructed for Denmark, Italy, Spain, or Portugal.
However, the occupational classifications that were
available for these countries could be used to approximate
the broad groups of the three-class version.
Ideally, economically inactive men are assigned to an
occupational class on the basis of a previous occupation.
In most data sources, however, information on previous
occupations was lacking for most of the economically
inactive men, and these men therefore had to be excluded
from the analysis of the association between mortality and
occupational class.  As a result, however, the magnitude of
mortality differences between occupational classes may be
substantially underestimated (10).  However, this problem
can be remedied in part.  We have developed adjustment
factors for estimating the size of mortality differences
among the entire male population from the mortality
differences observed among men with known occupation only.
These adjustment factors have performed well in a number of
tests (11).
The relative mortality level of men in specific occupational
classes was measured by means of standardized mortality
ratios (SMRs), using national age-specific mortality rates
as the standard.  Several summary indices were calculated to
express the magnitude of mortality differences by
occupational class (10).  In this paper, we present an
often-used summary index with a straightforward
interpretation: the (age-standardized) mortality rate ratio
(RR) that compares all manual workers to all nonmanual
workers.
Comparative research on inequalities in health is
treacherous if no extensive attention is paid to potential
data problems (10).  Three major problems with reliability
and comparability of data on mortality by occupation are
exclusion of economically inactive men from most data sets,
use of social class schemes other than the E-G scheme, and
biases inherent to "unlinked" cross-sectional studies.  Each
of these problems has been evaluated extensively for its
potential effect on the RR estimates for specific countries.
Details are given in the final report of our project (11).
Data sets were classified according to their level of
comparability:
*  Data from England/Wales and Sweden were highly
   comparable.  If manual vs. nonmanual RRs for these two
   countries differed by more than 15 percent, it is
   unlikely that systematic errors could explain that
   difference.  These two countries were comparable on the
   basis of both the three-class and the seven-class
   versions of the E-G scheme.
*  Data for most other countries were reasonably comparable.
   If manual vs. nonmanual RRs for these countries differed
   by more than about 30 percent, it is unlikely that
   systematic errors could explain that difference.  These
   countries were comparable only on the basis of the
   three-class E-G scheme.
*  Data for Ireland, Spain and Portugal were poorly
   comparable.  Only tentative comparisons can be made on
   the basis of the three-class E-G scheme.
Results
Table 1 presents the results for mortality from all CVD.
The SMRs for three broad occupational classes are given
together with the RRs that represent the magnitude of the
mortality difference between nonmanual and manual classes.
Countries are ordered from high to low RRs.
The SMRs for the nonmanual class were between 0.90 and 1.00
for most countries, but smaller for England/Wales, Finland,
Norway, and Sweden.  In most countries, the SMRs for
agricultural workers were lower than those for the nonmanual
class.  The only exceptions were Finland and Portugal.  SMRs
for the manual class were between about 1.10 and 1.20 for
most countries, but were larger for Ireland and smaller for
Switzerland and Portugal.
The RRs were largest for England/Wales and Finland.  The
confidence intervals around these RRs overlap only with
those for Sweden and Norway.  The manual vs. nonmanual
mortality differences in France and the more southern
countries were relatively small.  However, in these
countries the mortality rates of the manual classes were
also estimated to be higher than those of the nonmanual
classes.  The confidence intervals around the RRs for these
countries generally do not overlap with those for more
northern countries.
Table 2 (first column) presents the RRs for IHD mortality.
The rank order of countries from high to low RRs is the same
as for all CVD.  The manual vs. nonmanual RR was again
relatively large in England/Wales and Finland.  However, the
difference with other northern countries is small and not
statistically significant.  In all southern countries for
which data are available, IHD mortality rates were virtually
the same for manual and nonmanual classes.
-----------------------------------------------------------
Table Missing
Table 1.  -  Age-standardized CVD Mortality Ratios of Three
Broad Occupational Classes and Rate Ratios Comparing Manual
to Nonmanual Classes
-----------------------------------------------------------
Occupational differences in mortality from cerebrovascular
disease were largest in England/Wales, Finland, and Ireland
(Table 2, second column).  Due to the wide confidence
intervals around the RRs, differences with other northern
countries cannot be demonstrated with statistical
significance. Moreover, southern countries have substantial
differences between manual and nonmanual classes in
cerebrovascular disease mortality.
In Table 3, the seven-class scheme is applied to the
comparison between England/Wales and Sweden.  Since farm
laborers form a very small part of the population of these
two countries, they are combined with the class of unskilled
laborers.
In England/Wales, substantial mortality differences were
observed in both the nonmanual and  manual classes.  The
mortality rate of unskilled workers was almost twice that of
professionals,  administrators, managers, and employers.
The relative mortality level of most occupational classes in
Sweden was virtually the same as in England/Wales.  The only
exception was for routine nonmanual employees, whose
mortality level was close to the national average in
England/Wales, but relatively high in Sweden. Their
different mortality position in the two countries can
largely explain the smaller manual vs. nonmanual mortality
rate ratio in Sweden.
-----------------------------------------------------------
Table Missing
Table 2.  -  Ischemic Heart Disease and Cerebrovascular
Disease Mortality Rate Ratios for Manual and Nonmanual
Workers*
*No data are available for Italy for specific cardiovascular
diseases.
-----------------------------------------------------------
Discussion
Class differences in CVD mortality were observed for all
parts of Europe covered by this study.  The common pattern
is that CVD mortality rates are relatively high for manual
workers, relatively low for nonmanual workers, and lowest
for agricultural workers.  More detailed analysis of
England/Wales and Sweden revealed substantial mortality
differences between skilled and unskilled manual workers,
and between different classes of nonmanual workers.
Most striking are the dissimilarities among European
countries.  A north-south contrast was observed in the size
of mortality differences and in their pattern by cause of
death.  Smaller mortality differences were observed in
France, Switzerland, Italy, Spain, and Portugal.  The
contrast with northern countries was striking for IHD,
whereas no north-south contrast was observed for
inequalities in cerebrovascular disease mortality.  The
largest mortality differences were consistently observed for
England/Wales and, to a lesser extent, for Finland.
Other crossnational variations in this study were small and
might be attributable to problems with the comparability and
reliability of data from different countries. In this study,
data problems were evaluated for their potential effect on
the comparability of the RR estimates from different
countries (11).  As a general rule, only a relatively large
difference between the RR estimates for two countries
(larger than about 30 percent) could be assumed to provide
strong evidence for the existence of a real difference.
----------------------------------------------------------
Table Missing
Table 3.  -  Age-standardized CVD Mortality Ratios of 6
Occupational Classes
-----------------------------------------------------------
This general rule applied to the data available for France,
Switzerland, and Italy.  The RRs for these three countries
were substantially and consistently smaller than the RRs for
more northern countries.  It is unlikely that this
difference is attributable to data problems alone.  The same
applies to IHD mortality, but not to cerebrovascular disease
mortality.  The poorly comparable data for Spain and
Portugal could not provide strong evidence on the
international position of these countries, but the
similarity between the results for all five southern
European countries makes it highly likely that these
countries have a common pattern of class differences in CVD
mortality.
Data for the relatively large differences in CVD mortality
observed for England/Wales were of high quality.  Problems
with data reliability and comparability are probably not the
sole explanation for the larger inequality estimates for
England/Wales as compared with Sweden and Norway.  However,
adding to the uncertainty around the large inequality
estimates for England/Wales are the large confidence
intervals and the overlap of these intervals with those for
Sweden and Norway.  Therefore, the evidence for larger
inequalities in England/Wales should be considered weak.
The comparison between England/Wales and Sweden has long
attracted wide interest, for example in the Black Report and
ensuing literature.  The fact that slightly larger mortality
differences were observed for England/Wales than for Sweden
agrees with the expectation that inequalities in mortality
are smaller in more egalitarian welfare states.  However,
the broader international pattern observed in this study
does not support this expectation.  Income inequalities are
relatively large in Ireland, Switzerland, Italy, Spain, and
Portugal; intermediate in England and France; and relatively
small in the four Scandinavian countries (12).  Thus, no
country with large income inequalities has relatively large
inequalities in CVD mortality, and no country with small
income inequalities has relatively small inequalities in
mortality.  This lack of a generalized association does not
imply that egalitarian socioeconomic policies are irrelevant
to inequalities in CVD mortality.  The lack of the expected
association underscores, however, that there are other
powerful determinants of the magnitude of inequalities in
CVD mortality in Europe.
The absence of class differences in IHD mortality in France,
Switzerland, Italy, Spain, and Portugal in the early 1980s
is puzzling.  This situation reminds us of the absence of
social gradients in IHD mortality in the United States and
northern European countries in the 1950s and 1960s, before
the current inverse gradients emerged.  The analogy between
northern and southern Europe is reinforced by the
observations of recent studies from southern European
countries that during the late 1980s an inverse social
gradient in IHD mortality emerged in these countries as well
(7).  It seems that the situation in southern countries can
basically be understood as a delay in the trends that
occurred in the United States and northern European
countries one or more decades before.
To conclude, this study has identified large variations
between European countries in the association between
occupational class and CVD mortality.  A north-south
contrast was observed in both the size of mortality
differences and in its pattern by cause of death.  These
variations stress the variability of SES inequalities in CVD
-  the magnitude of inequalities in CVD is not fixed, but
susceptible to change.
The differences among European countries do not seem to be
strongly related to the egalitarian character of
socioeconomic policies in some countries.  Further
comparative studies, not only among European countries but
also between other geographical entities, may teach us under
what circumstances inequalities in CVD are large or small,
and perhaps identify circumstances that can be modified
through intervention.
In addition to the three authors, the European Union Working
Group includes the following:
  O. Andersen, Danmarks Statistik, Copenhagen, Denmark
  J.-K. Borgan, Statistics Norway, Oslo, Norway
  G. Costa, Laboratorio di Sanita Pubblica, Grugliasco
     (Turin), Italy
  G. Desplanques, INSEE, Lyon, France
  F. Faggiano, Universita degli Studi di Torino, Turin,
     Italy
  H. Filakti & S. Harding, OPCS, London, United Kingdom
  M. do R. Giraldes, National School of Public Health,
     Lisbon, Portugal
  C.E. Minder & Chr. Junker, University of Bern, Bern,
     Switzerland
  B. Nolan, Economic and Social Research Council, Dublin,
     Ireland
  F. Pagnanelli, National Institute of Statistics, Rome,
     Italy
  E. Regidor, Ministry of Health, Madrid, Spain
  D. Vagero, Swedish Institute for Social Research,
     Stockholm, Sweden
  T. Valkonen & P. Martikainen, University of Helsinki,
     Helsinki, Finland
REFERENCES
1.  Illsley R, Svensson P-G: Social inequalities in health.
    Soc Sci Med 1990;31:223-240.
2.  Inequalities in Health and Health Care.  Review of
    Selected Publications from 18 Western European
    Countries, edited by A Mielck and M do R Giraldes.
    Mnster/New York: Waxmann, 1993.
3.  Health Inequalities in European Countries, edited by J
    Fox.  Aldershot: Gower, 1989.
4.  Marmot MG, McDowall ME: Mortality decline and widening
    social inequalities.  Lancet 1986;2:274-276.
5.  Vagero D, Lundberg O: Socioeconomic mortality
    differentials among adults in Sweden.  In Adult
    Mortality in Developed Countries: From Description to
    Explanation, edited by AD Lopez, G Casselli, T Valkonen.
    Oxford: Clarendon Press, 1995, pp. 223-242.
6.  Valkonen T: Trends in regional and socioeconomic
    mortality differentials in Finland.  Int J Health Sci
    1993;3:157-166.
7.  Regidor E, Gutierrez-Fisac JL, Rodriquez C: Increased
    socioeconomic differences in mortality in eight Spanish
    provinces.  Soc Sci Med 1995;41:801-807.
8.  Uemura K, Pisa Z: Recent trends in cardiovascular
    disease mortality in 27 industrialized countries. World
    Health Stat Q 1985;38:142-162.
9.  Erikson E, Goldthorpe JH: The Constant Flux.  Oxford:
    Clarendon Press, 1992.
10. Kunst AE, Mackenbach JP: Measuring Socioeconomic
    Inequalities in Health.  Copenhagen: World Health
    Organization, 1994.
11. Kunst AE, Mackenbach JP, Cavelaars AEJM, Groenhof F,
    Geurts JJM, and the EU Working Group on Socioeconomic
    Inequalities in Health: Socioeconomic Inequalities in
    Morbidity and Mortality in Europe: A Comparative Study.
    Rotterdam: Erasmus University, 1996.
12. Atkinson AB, Rainwater L, Smeeding TM: Income
    Distribution in OECD Countries.  Paris: OECD, 1995.
-----------------------------------------------------------
Socioeconomic Status and Cardiovascular Disease:  Experience
in the United Kingdom
Michael G. Marmot, M.D., Ph.D.
Analyses of mortality differentials according to social
class have a long history in the United Kingdom.  Although
known to people working in the field in the last century,
the differentials were given public prominence by the Black
report.  This was the report of a committee established in
the 1970s to examine why social inequalities in health
should persist 30 years after the establishment of the
National Health Service (NHS).  Black and his colleagues
reported that indeed social class differences in mortality
had not narrowed and in some cases had increased.  This was
not seen as a failure of the NHS but, rather, an indication
that such social differentials in mortality were unlikely to
be much affected by equitable provision of medical care.
Black et al. concluded that these social differentials were
not the result of artifact, health selection, or cultural
factors influencing health behaviors.  They attributed these
patterns to factors related to the social structure.  It is
likely that social, structural, and health behavioral
factors are related.  Work since the Black report has
confirmed that social differentials in mortality cannot be
attributed to either health selection or artifact (1).
Socioeconomic status (SES) differences in cardiovascular and
other mortality have been neither constant over time, nor
identical in different ethnic groups.  Notably,
international differences in mortality from cardiovascular
and other diseases may share some of the same causes as SES
differences within the United Kingdom.
Part of the debate in Britain has centered on whether the
phenomenon to be explained is the relation between poverty
and disease, or between inequality and disease risk.  The
data in Figure 1, from the first Whitehall study, are
relevant (2).  There is little doubt that poverty, or
deprivation, is likely to be bad for health among other
things.  These data suggest that something else is at work.
Each employment grade has worse health and higher mortality
rates than the grade above it.  Executive-grade civil
servants are not poor by any absolute standard, yet they
have higher mortality rates than administrators.  Even
clerical officers, who are far from affluent, with earnings
at or below the national average, are not poor by comparison
with England at an earlier period in history or with
developing countries.  This social gradient in mortality
suggests the operation of factors across the whole of
society.
Although incidental to SES differences in cardiovascular
disease (CVD), the data in Figure 1 suggest that there are
similar social differentials in a range of different
diseases.  This is relevant to the search for explanations.
-----------------------------------------------------------
Figure Missing
Figure 1.  -  Relative Risk of Death by Various Causes in 10
Years by Grade of Employment in the Whitehall Study of
British Civil Servants.  Men were 40 to 65 years old at
entry.  Relative mortality of the largest group,
professionals and executives, is set to 1.
-----------------------------------------------------------
Time Trends
The traditional measure of SES used in mortality studies in
the United Kingdom has been based on occupation.  In 1842,
Chadwick reported average ages at death as follows:
"Gentlemen and persons engaged in professions, and their
families . . .45 years; tradesmen and their families . . .26
years; mechanics, servants and labourers and their families
. . .16 years."  Although for technical reasons, age of
death is not currently used, it is likely that Chadwick's
data indicated substantial mortality differentials among
occupational groups.  Since 1911, the Registrar General has
reported on mortality according to social class around each
decennial census, the last available data in the United
Kingdom being for the years around 1981.
Sir William Osler described coronary heart disease (CHD) as
being more common in his upper class patients.  He was
puzzled because he thought that work and worry were prime
causes of the disease and that work and worry were "the lot
and portion of the poor."  Our initial analyses of this
question suggested that CHD was more common in higher SES
groups in England and Wales in the 1930s and 1950s, but the
social distribution changed such that by 1961 CHD mortality
was more common in semiskilled and unskilled occupations.  A
major problem besetting these analyses was potential social
class differences in the application of diagnostic labels.
A combination of ICD codes representing nonrheumatic heart
disease and hypertension avoids much of the social class
diagnostic bias and still shows the changed social class
distribution (3).
Subsequent analyses suggest that these differentials
increased further between the years around the 1971 and the
1981 censuses (4).  As yet, national data are unavailable to
update these 1983 analyses.  There are, however, area-based
data that suggest a further widening in social differentials
in mortality.
Ethnic Groups and SES
SES differences in CVD mortality not only change over time,
but may differ in different subgroups of the population.
Figure 2 shows data on mortality by social class and country
of birth for England and Wales between 1970 and 1985.
Mortality from ischemic heart disease (IHD) has increased
among men in manual occupations for each country-of-birth
group.  Among immigrants from the Indian subcontinent and
the Caribbean, IHD mortality is higher in nonmanual than in
manual social classes.  These data suggest that we have to
go beyond social class for an explanation of mortality
differentials among immigrant groups in England and Wales,
and that the relation of social class to mortality may
differ among groups.
One cannot extrapolate from these comparisons to black-white
differences in the United States.  First, these analyses are
examining immigrants.  Second, the contribution that SES
makes to explaining differences among population subgroups
cannot necessarily be generalized from one country to
another.
Other Measures of SES
Education
There has been much interest in whether education may be a
better predictor of SES differences in health than a measure
based on occupation.  Education has appeal as a measure
because it appears to convey what it is about social
position that may be causally related to increased risk.  If
education were then shown to be a stronger predictor than,
say, occupational prestige, this could lead to the
presumption that it is education  -  not factors related to
occupation  -  that is more important in the causal chain
leading to ill health.  This can be illustrated with data
from the Whitehall II study (Fig. 3).  The prevalence of
smoking and plasma fibrinogen level are strongly related to
grade of employment in the Whitehall II study and somewhat
more weakly related to years of education.  Adjusting the
grade differences for education has little impact on the
strength of the inverse association.  Adjusting education
for grade reduces substantially the association between
education and the risk factor.  One interpretation of these
data is that grade is a more precise measure of SES in the
Whitehall II study than is the occupation-based measure in
the Registrar General's social class scheme applied to the
diversity of occupations in the country.  In other data
sets, education may be a more precise measure.
-----------------------------------------------------------
Figure Missing
Figure 2.  -  All-cause and IHD Mortality by Country of
Birth and Social Class.  Circles indicate manual occupation;
squares, nonmanual occupation for 1970-72 (first data point)
and 1979-85 (second data point).  Relative risk for persons
born in England and Wales who had nonmanual occupations and
died in 1970-72 is set to 1.
-----------------------------------------------------------
Figure Missing
Figure 3.  -  Odds Ratios for Smoking (left) and Level of
Fibrinogen (right) in Whitehall II Men by Grade and
Education.   Smoking and plasma fibrinogen are strongly
related to employment grade and more weakly related to years
of education.
-----------------------------------------------------------
Education may be causally related to cardiovascular health
but one should not draw that conclusion simply from the
strength of this association.  This point was well
demonstrated by Blane, who showed, for 107 local areas in
England, that mean scores on school examinations were highly
correlated (inversely) with measures of social deprivation
(5).
Area-Based Measures
A different approach to SES classification is to classify
not individuals, but areas of residence. This too has a long
history, going back at least to Engels.  We used the
Townsend measure of social deprivation (housing tenure,
access to cars, crowding, and unemployment) to classify over
8,000 small areas in all the regions of England (6).  This
showed a more or less linear relation between level of
deprivation and mortality from IHD (Fig. 4).  More recent
data from Scotland (7) show that social differentials, using
an area-based measure, have been widening.  Similar widening
trends have been reported from the northern region of
England.
Data from Alameda County, California, suggest that such
geographical differences cannot all be explained by the
characteristics of the individuals who reside in these
areas.  The suggestion is that there are ecological
characteristics that are causally related to SES differences
in CVD.
Differences Within and Between Countries
Though my mission is to describe SES differences within the
United Kingdom, at University College London we are also
exploring reasons for East-West differences in mortality
from cardiovascular and other diseases within Europe.  The
general proposition is that SES differences within a country
and international differences across Europe may have a
common set of causes.  A clue that this may not be
altogether fanciful is given by WHO data in Figure 5 (8).
These mortality data show that the countries of central and
eastern Europe and the so-called Newly Independent States of
the former Soviet Union have an increased mortality gap
compared with the countries of western Europe.  The only
major cause of death for which this is not the case is
breast cancer.  Interestingly, breast cancer is the most
important cause of death that is not more common in lower-
SES groups in the United Kingdom.  We have previously
speculated that the particular causes of death that show the
steepest social gradient within a country are those causes
that show the most marked variations in comparison with
other countries (9).
-----------------------------------------------------------
Figure Missing
Figure 4.  -  Mortality from Different Causes and Degree of
Social Deprivation in Men and Women for Five Representative
Regions of England.  Five strata are used in the social
deprivation scale.
-----------------------------------------------------------
Life Course
A body of work from Barker and others suggests that factors
operating early in life may make CVD risk manifest in the
middle years of life (10).  Regional variations in infant
mortality have been shown to be associated with mortality
from heart disease 50 or more years later.  In addition,
various markers of fetal and infant growth have been shown
to be associated with blood pressure, plasma fibrinogen
level, and measures suggestive of insulin resistance.  This
has sparked off a vigorous debate as to whether the major
CVD determinants operate early in life or concurrently.  For
example, it has been shown that the relation between infant
mortality and IHD subsequently could entirely be accounted
for by the relation between social deprivation and heart
disease (11).  The Barker data on risk factors are
impressive in their consistency.  They do not necessarily
mean that SES differences in CVD risk are all determined
early in life.  As Power has pointed out, there may be
accumulation of advantage and disadvantage throughout the
life course (12).
-----------------------------------------------------------
Figure Missing
Figure 5.  -  Excess Mortality in the Countries of Central
and Eastern Europe (CCEE) and the "Newly Independent States"
of the Former Soviet Union (NIS) as Compared with Mortality
in Western Europe.  The population-weighted average
standardized mortality rate for all countries of the
European region, except the CCEE, the NIS, and those for
which no data were available, is set to zero.  Source: World
Health Organization (WHO) Regional Office for Europe.
-----------------------------------------------------------
A different issue is the persistence of SES-based health
differentials into old age.  In the original Whitehall
study, SES measures continued to predict mortality
differentials at least up to age 84.  Grade of employment
was related less strongly to mortality after retirement age
than before.  By contrast, a more general measure, car
ownership, although more weakly related to mortality before
retirement, did not diminish in its predictive power after
retirement.  One interpretation of these data suggests that
factors related to work diminish in their importance after
retirement, but other more general SES measures do not.
Determinants
Whitehall mortality analyses suggest that a major task is to
determine the reasons for the SES gradient in mortality.
Data from Whitehall II offer a variety of potential
explanations (13).  Social gradients are evident in:
*  Health behaviors  -  smoking, diet, exercise;
*  Psychosocial characteristics  -  work, social
   environment, psychological measures such as hostility and
   sense of control;
*  Biological markers  -  central adiposity and insulin
   resistance syndrome, plasma fibrinogen level (but not
   plasma total cholesterol); and
*  Indicators of early environment  -  height, father's
   social class.
The research agenda is to quantify the importance of these
and other factors in generating SES differences in CVD.
REFERENCES
1.  Goldblatt P: Mortality and alternative social
    classifications.  In 1971-1981 Longitudinal Study.
    Mortality and Social Organisation, edited by P
    Goldblatt. London: HMSO, 1990, pp.163-192.
2.  Marmot MG, Shipley MJ, Rose G: Inequalities in
    death-specific explanations of a general pattern. Lancet
    1984;1:1003-6.
3.  Marmot MG, Adelstein AM, Robinson N, et al: Changing
    social class distribution of heart disease.  Br Med J
    1978;2:1109-1112.
4.  Marmot MG, McDowall ME: Mortality decline and widening
    social inequalities.  Lancet 1986;ii:274-276.
5.  Blane D, Morris JN, White IR: Education, social
    circumstances and mortality. In Health and Social
    Organisation:  Towards a Health Policy for the 21st
    Century, edited by D Blane, E Brunner, R Wilkinson.
    London: Routledge, 1996.
6.  Eames M, Ben-Shlomo Y, Marmot MG: Social deprivation and
    premature mortality: regional comparison across England.
    Br Med J 1993;307:1097-1102.
7.  McLoone P, Boddy FA: Deprivation and mortality in
    Scotland, l981 and l991.  Br Med J 1994;309:1465-1470.
8.  World Health Organization: Health In Europe: The
    1993/1994 Health For All Monitoring Report.  Copenhagen:
    World Health Organization, 1994.
9.  Marmot M, Kogevinas M, Elston MA: Socioeconomic status
    and disease. In Health Promotion Research:  Towards a
    New Social Epidemiology.  Copenhagen: WHO Regional
    Publications, European Series No.37, 1991.
10. Barker DJ: The fetal and infant origins of adult
    disease.  Br Med J 1990;301:1111.
11. Ben-Shlomo Y, Davey Smith G: Deprivation in infancy or
    adult life: which is more important for mortality risk?
    Lancet 1991;337:530-534.
12. Health and Class: The Early Years, by C Power, O Manor,
    and J Fox.  London: Chapman & Hall, 1991.
13. Marmot MG, Davey Smith G, Stansfeld S, et al: Health
    inequalities among British civil servants: the Whitehall
    II Study.  Lancet 1991;337:1387-1393.
-----------------------------------------------------------
Session II:
Pathways Linking SES and CVD
-----------------------------------------------------------
Session II Overview
Redford B. Williams, M.D., Chair
The presentations in this session addressed possible
pathways  -  including biological, behavioral, and
psychosocial mechanisms  -  through which socioeconomic
status (SES) may influence cardiovascular disease (CVD).
Session speakers presented findings from multiple studies in
specific racial and ethnic, rural, and working populations.
They also discussed access to medical care and quality of
treatment for disease and noted gender differences in the
effects of SES on CVD where data were available.
In general, there does appear to be an SES gradient of CVD
in the special populations for which data exist.  These
include black, Mexican-American, Japanese-American, Native
American, rural, and working groups.  For the most part, the
established risk factors and behaviors also show a similar
SES gradient, with worsening of the risk factors or
behaviors as SES decreases.
There are some notable special features in regard to this
generalization.  In Mexican Americans, Native Americans, and
blacks, the worsening of risk factors with decreasing SES is
more pronounced in women than in men.
Two broad pathways were noted linking SES and CVD:
*  More unfavorable patterns of established major lifestyle
   and biomedical risk factors (smoking, adverse diet,
   sedentary lifestyle, high serum cholesterol, high blood
   pressure, obesity, diabetes) in lower- compared to
   higher-SES strata; and
*  More unfavorable patterns of psychosocial factors
   (hostility, depression, low social support, social
   isolation, racism; job instability, insecurity, strain,
   and powerlessness; unemployment).
Men with low levels of all established biomedical risk
factors (blood pressure, cholesterol, smoking, diabetes,
previous heart attack) have been found to experience lower
coronary heart disease (CHD) and CVD mortality rates than
men without such a favorable profile.  Even though such a
favorable profile is found in less than 10 percent of the
population, this finding suggests that controlling the
established biomedical risk factors has the potential to
achieve low CHD-CVD rates for all groups in the United
States, including low-SES strata of various ethnic
backgrounds.
Once clinical CVD is present, the impact of low SES on
case-fatality rates and on subsequent natural history of
disease is pronounced.  Access to care and quality of care
may be contributing factors, although relevant data are
sparse and both increased and decreased use of medical
facilities have been reported among low-SES CVD patients.
Various psychosocial factors (e.g., depression, hostility,
social isolation, and high job strain) that have been linked
to increased risk of CVD or to poorer prognosis also appear
to worsen with decreasing SES.  These psychosocial factors
and the accompanying biological and behavioral risk
characteristics deserve serious attention as potential
mediators of the SES gradient of CVD.
The measures of social support that have been used in
earlier studies focus primarily on CVD in men and may not be
appropriate for women.  It may be necessary to include
measures of strain as well as of support from the social
network.
RESEARCH OPPORTUNITIES
The SES gradient of CVD and its potential mediators have not
been studied adequately in certain populations.  Data are
particularly lacking for rural populations and for subgroups
within populations (e.g., Cuban Americans and Puerto Rican
women among Hispanics).
The array of potential mediators may not be limited to the
established biomedical risk factors and access to care.  A
number of psychosocial factors also show an SES gradient.
For example, as income decreases, hostility scores increase;
but the increase with declining income is greater among
blacks than whites.  Such findings highlight the need to
evaluate the role of racism as an important psychosocial
mediator of the SES gradient of CVD in certain populations.
At low SES, access to care and quality of treatment are
likely to have a strong impact after the onset of CVD.
Measurement of the relative contributions of these and other
factors to CVD prognosis is important for the development of
interventions for established CVD in low-SES individuals.
Several potential biological mediators of CVD pathogenesis
may be involved in the mechanism of the SES gradient of CVD.
These include:
*  Altered sympathetic and parasympathetic nervous system
   function
*  Altered hypothalamic-pituitary-adrenal axis function
*  Preclinical indicators of CVD ( e.g., carotid intimal
   wall thickening, as used in the Atherosclerosis Risk in
   Communities study)
*  Altered cellular and molecular characteristics of key
   cells (e.g., monocytes and macrophages) involved in the
   pathogenesis of CVD
Another area of interest concerns the mechanisms through
which lower SES contributes to the development of the
established major biomedical risk factors, as well as
psychosocial and accompanying biobehavioral mediators of the
SES gradient of CVD.  Living conditions for lower SES groups
may foster the development of psychosocial and biobehavioral
mediators via several mechanisms, including both learning
and neurobiological phenomena (e.g., harsh environments,
particularly in early childhood, lead to reduced serotonin
function in the central nervous system).   A developmental
perspective may help efforts to understand the social and
environmental origins of these mediators.  Research is also
needed to identify the lifestyle, behavioral, psychosocial,
cultural, metabolic, and genetic components of maintaining
low-risk status into middle age.
It will also be relevant to adopt integrative approaches,
most likely using newer statistical techniques for
multivariate causal modeling.  These approaches may reveal
how potential mediators develop across the life cycle and
combine at multiple levels to  influence the pathogenesis of
CVD in lower-SES groups.  As noted above, once clinical CVD
is present, additional issues (e.g., access to care and
quality of care) come into play.
As we learn more concerning the pathways linking SES and
CVD, as outlined above, we need to use the knowledge gained
to develop and apply better approaches for the primary
(including "primordial") prevention of the established
biomedical risk factors, with a focused emphasis on lower-
as well as higher-SES strata.
RECOMMENDATIONS
*  Expand the knowledge base regarding the SES gradient of
   CVD to include additional populations, including rural
   populations.
*  Expand the array of potential mediators being studied to
   include psychosocial risk factors, risk behaviors, and
   biological factors (including those at the cellular and
   molecular level) that may be involved in mechanisms of
   the SES gradient of CVD.
*  Identify the mechanisms through which the conditions of
   everyday life for lower-SES groups contribute to the
   development of psychosocial, behavioral, and biological
   mediators of the SES gradient of CVD.
*  Develop integrative approaches to evaluate the pathways
   by which lower SES contributes to the development of CVD.
*  Evaluate the role played by access to care and quality of
   care in the high case-fatality rate and poor natural
   history among low-SES groups once clinical CVD is
   present.
*  Use our increasing understanding of the pathways linking
   SES and CVD to develop and apply more effective
   approaches to the prevention and control of the
   established biomedical risk factors, as well as potential
   psychosocial and biobehavioral mediators, in the lower-
   as well as higher-SES strata.
-----------------------------------------------------------
Black and White Populations
Herman A. Tyroler, M.D., Mark Massing, M.D.,
Marilyn Knowles, M.P.H.
The effect of low socioeconomic status (SES) on the health
of blacks is considerable and pervasive.  It is manifest
from infancy to advanced age, in both females and males,
across most categorically defined diseases and is expressed
in risk of dysfunction, disability, and death.  SES, as an
attribute of individuals, measures one's prestige, control
of material resources, and social opportunities.  Blacks are
disadvantaged with respect to each of the traditional
indicators for SES  -  education, occupation, and income
level.  Being black confers an additional and unique
dimension to one's SES as a consequence of the history of
slavery and legal segregation and persistent institutional
and individual racism.  Community-based epidemiological
studies offer insight into the individual and societal
mechanisms by which SES is related to cardiovascular disease
(CVD) in blacks.
The Evans County Study
The epidemiological study of CVD developed in Evans County,
Georgia, from a series of clinical observations by Hames,
who noted that coronary heart disease (CHD) appeared to
occur less frequently among blacks than whites even though
hypertension was more common in blacks and their diet was
higher in animal fat (1).  Hames also noted that black women
did not seem to experience the same gender protection from
CHD that white women did.  In 1960, when the baseline data
for the community survey were collected, Evans County was a
racially segregated, predominantly rural, agricultural
society.  SES was calculated based on the occupation,
education, and source of income of the head of household,
using the McGuire-White method, which was developed and
validated for southern rural communities.  White men in the
upper 50 percent of the McGuire-White score distribution
were defined as upper-class or high-SES; those in the lower
50 percent were defined as lower-class.  Ninety-five percent
of the blacks had scores below the median for whites, and
thus were not further categorized.  The age-adjusted
prevalence of CHD increased stepwise from black men to low-
SES white men to high-SES white men (Fig. 1).
Major risk factors also differed among ethnic and SES
groups.  Mean cholesterol values paralleled CHD prevalence,
but smoking was less prevalent among high-SES white men.
Blood pressure level varied inversely with SES and was
higher in black men and women of all ages than in white men
of either social class.  When occupations were ranked by
physical activity required on the job, CHD prevalence was
found to be highest in the most sedentary jobs and lowest in
the most active jobs.  In particular, farm workers had lower
rates of CHD than nonfarmers, and within nonfarm occupations
there was a gradient of decreasing CHD from the most
sedentary to the most active.  The majority of low-SES
whites, and practically all blacks, worked in physically
active occupations.
The findings in Evans County represent in microcosm the
worldwide movement from rural agrarian to town-based
nonfarming lifestyles.  They also illustrate the changing
relationship between SES and CHD risk.  A CHD incidence
study from 1960 to 1967 confirmed the importance of smoking,
blood pressure, and cholesterol as risk factors in both
whites and blacks; however, CHD incidence was lower in black
than white men after controlling for risk factor levels.  In
contrast to earlier findings of a higher prevalence of CHD
in high-SES white men, the study indicated either no
difference with SES or a possible lower incidence of CHD in
high-SES white men.  This reversal of the SES findings
accompanied both social and physiological changes between
1960 and 1967.  Serum cholesterol levels rose in blacks and
low-SES white men to levels previously characteristic of
high-SES white men, in whom the values had plateaued by
middle age (2).  Simultaneously, occupational data began to
reflect a transition away from farming and an increase in
the proportion of individuals engaged in white collar and
town-oriented occupations.  These changes may explain the
emergence of excesses in CHD in lower-SES groups.
-----------------------------------------------------------
Figure Missing
Figure 1.  -  The Prevalence of CHD and Risk Factor Levels
by Ethnicity, SES and Gender: Evans County Heart Study
Participants Age 40 to 64, 1960 to 1962.
-----------------------------------------------------------
The Charleston Heart Study
This epidemiological study of CVD began in Charleston, South
Carolina, in 1960.  Charleston, in contrast to Evans County,
is metropolitan.  Blacks in both studies had a marked excess
of hypertension.  However, in a collaborative mortality
followup study, black men from both studies had a lower
incidence of fatal CHD events than whites.
In the Charleston Heart Study, blood pressure levels were
positively related to darkness of skin color, as assessed
objectively and quantitatively by skin reflectance
photometry.  One interpretation of this finding was that the
degree of African or Caucasian ancestry was causally related
to blood pressure levels through genetic and other
biological mechanisms.  An alternate hypothesis was tested
by comparing the incidence of hypertension by social status,
which for blacks in the 1960s was inversely correlated with
darkness of skin color (3).  The incidence of hypertension
was positively associated with darkness of skin, but it also
was inversely associated with SES.  After controlling for
SES, skin color was no longer associated with incidence of
hypertension.  Conversely, controlling for skin color did
not eliminate the inverse association of SES with incidence
of hypertension.
Thus, both the Evans County and Charleston studies
identified an excess of hypertensive disease in blacks,
related it to social characteristics, and demonstrated a
relationship between SES and CHD.  The major CHD risk
factors were similarly predictive in blacks and whites, and
in both studies, black men had lower risk of CHD than whites
(4).
National Longitudinal Mortality Study (NLMS)
The NLMS presented an opportunity to assess the
representativeness of findings from the Evans County and
Charleston studies in the nation at large.  For the 1979 to
1989 followup period, ischemic heart disease (IHD) mortality
among middle-aged subjects (ages 45 to 64) decreased
stepwise with increasing education level for all four race-
gender groups.  The mortality increase between low and high
education was approximately 3-fold for women and close to
double for men.  Black-white mortality rate ratios were
slightly greater than 1 for middle-aged men and increased
with education level.  Among men age 65 and older, black-
white mortality ratios were less than 1 for all education
levels.  It is of interest that when a six-step
classification was used, the education gradient for
mortality appeared to be continuous without any threshold
for both black and white men.  Similar gradients were
apparent for income but were not as consistent for
occupational strata.  The trend in black-white mortality
ratios in women in the same age group was similar but
quantitatively somewhat stronger, increasing with education
level.  At age 65 and older, the mortality ratios for black
and white women crossed over at the highest education level.
The association of education with mortality attributed to
IHD in the NLMS was similar to that observed in the Evans
County and Charleston studies on the 30-year followup, as
were the black-white mortality rate ratios.  In the Evans
County and Charleston studies, indices of SES and ethnicity
were related to CHD prevalence, incidence, and mortality
after controlling for standard risk factors.  Data are not
available to perform similar analyses for the NLMS.
The Atherosclerosis Risk in Communities Study (ARIC)
ARIC offered the possibility of investigating preclinical
atherosclerosis as one of the intervening steps between SES,
risk factors, and clinically manifest disease.  It also
presented the first opportunity to study these phenomena in
a large cohort of blacks (2,634 women, 1,632 men).  In
subjects ages 45 to 64 the age-adjusted CHD prevalence was
5.9 percent in black men, 8.4 percent in white men, 3.1
percent in black women, and 1.8 percent in white women,
findings similar to those reported 20 years earlier from the
Evans and Charleston County studies (5).
-----------------------------------------------------------
Figure Missing
Figure 2.  -  Age-Adjusted Percent Prevalence of Coronary
Heart Disease by Gender, Race, Education, and Income: The
Atherosclerosis Risk in Communities Study, 1987 to 1989.
Data were adjusted to age 55 years.  The p-values show p for
trend in proportions.  Source: Diez-Roux, et al. (5), with
permission.
-----------------------------------------------------------
After adjusting for age and gender, there was a 3-fold
higher odds ratio of CHD prevalence between the lowest and
highest income categories, and odds ratios decreased
linearly with increasing income in both whites and blacks
(Fig. 2).  The p value for trend was significant for blacks
and whites for the association with income, and although
reduced in magnitude, the association persisted after risk
factor adjustment.  For education, the p value for trend
was statistically significant for whites both before and
after risk factor adjustment but was not significant in
either case for blacks.
After omitting subjects with evidence of clinical CHD, ARIC
examined the association of subclinical  atherosclerosis
(assessed by ultrasound and quantitative measures of carotid
wall thickness) with SES.  Carotid wall thickness increased
with decreasing income and education; the trends by
education were clearer in whites than in blacks (Fig. 3).
However, the associations of carotid wall thickness with SES
were eliminated by adjustment for risk factors.  This
suggests that the same risk factors may interact with SES
level indices to have different effects on the development
of atherosclerosis.  Alternatively, the variables or
processes that relate clinical manifestations of CHD to SES
may depend on factors different from those responsible for
the development of atherosclerosis.  The risk factors
investigated in ARIC and adjusted for in the SES studies
include smoking; diet as assessed by the Keys score; indices
of physical activity reflecting leisure time, sports, and
work; systolic blood pressure and use of antihypertensive
medication; diabetes mellitus; and serum fibrinogen.
Conspicuous by their absence are indices of personality,
social interactions, and social supports and measures of the
social environment, all of which have been invoked and
analyzed in other studies of the association of CHD with SES
in blacks.
The association of the major CVD risk factors with SES was
generally similar between blacks and whites with one
conspicuous exception, blood lipid and lipoprotein levels.
High-density lipoprotein cholesterol (HDL) levels were
higher in black than white men.  Moreover, HDL decreased in
black men but increased in white men with increasing
education level.  Low-density lipoprotein cholesterol (LDL)
levels varied little across education strata in either black
or white men.  The net effect was an unfavorable increase in
the atherogenic LDL:HDL ratio in black men and a favorable
decrease in white men with increasing education.  The
association of these lipids and lipoproteins with education
was much stronger in women; LDL decreased and HDL increased
with increasing education, resulting in a favorable decrease
in the LDL:HDL ratio for both black and white women.
-----------------------------------------------------------
Figure Missing
Figure 3.  -  Age-Adjusted Mean Intimal-Medial Carotid
Artery Wall Thickness by Gender, Race, Education, and
Income: The Atherosclerosis Risk in Communities Study, 1987
to 1989.  Data were adjusted to age 55 years.  The p-values
show p for trend.  Source: Diez-Roux, et al. (5), with
permission.
-----------------------------------------------------------
Indices of smoking, including percent ever smoked, percent
current smokers, and integrated pack-years of smoking, each
varied markedly and inversely with increasing education,
more conspicuously in men than women in both race groups.
The percentage of current smokers was higher for black than
white men at each education level.  The prevalence of
hypertension and left ventricular hypertrophy (LVH) was
markedly higher in black than white men and women at all
education levels and varied inversely with education, more
markedly in women than in men.  The prevalence of obesity
was markedly higher in black women, but decreased
considerably with increasing education for both black and
white women.  The prevalence of diabetes was also markedly
higher in black women and varied inversely with education
level for women in both ethnic groups.
Thus, the constellation of standard risk factors varied
strongly and generally inversely with education level, and
the associations appeared continuous without thresholds.
With the exception of HDL, associations with education level
appeared qualitatively similar in blacks and whites.
However, quantitative differences in levels of risk factors
and in trends across education levels varied both by
ethnicity and by gender.
Coronary Artery Risk Development in Young Adults Study
(CARDIA)
CARDIA presents the opportunity to test relationships
between SES indices and atherosclerosis in young adults.
The data have been published in two age strata, 18 to 24
years and 25 to 30 years (6).  Age, gender, and race
differences in systolic blood pressure by education level
were minimal.  Plasma total cholesterol levels were slightly
higher among those with education beyond high school for
black men and women in each of the two age strata; the
findings were less consistent for whites.  However, smoking
was strongly related to education level.  Prevalence of
smoking was approximately 30 percent in each race-gender
group and decreased from 54 percent for participants with
less than a high school education to 12 percent among those
with graduate degrees.
National Health and Nutrition Examination Survey:  Phase I
(NHANES-I) Epidemiologic Followup Study
The followup study of the NHANES-I sample included 683 black
men and 1,175 black women first examined in 1971 to 1975 and
followed to 1982 to 1984.  The predictive strength of  CHD
risk factors was reported as "remarkably similar for the
four sex-race groups" (7).  Black men and women had higher
age-adjusted CHD mortality rates than whites but lower
hospitalization rates.  Income and education were each
inversely related to CHD events in all race-gender groups,
but were no longer statistically significant in multivariate
analyses that included systolic blood pressure, serum
cholesterol, and current smoking status.  Thus, in contrast
to the other studies reviewed, the NHANES-I followup study
indicated higher CHD risk in black than white men and
suggested that the effects of SES on CHD risk were accounted
for by the mediating action of the major risk factors.  In
other studies, Ford and Cooper have also reported that not
only do blacks make less use of hospital care for CHD
events, but also fewer diagnostic procedures (e.g.,
angiography) and therapeutic interventions (e.g., coronary
bypass surgery and angioplasty) are performed for CHD in
blacks than whites.
Psychosocial Studies
Few cohort studies in blacks have examined baseline
psychological measures and incident CVD events.  However,
several studies focus on the exceptional problem of
hypertension in low-SES blacks and serve as a bridge from
studies in individuals to aggregate-level investigations.
Measures of "John Henryism," a behavioral pattern
characterizing individuals with limited material resources
who struggle to achieve, have been associated with
hypertension in low-SES blacks (8).  Incongruence of
lifestyle  -  the degree to which lifestyle exceeds
education  -  is associated with higher blood pressure
levels (9).  Indices of social disorganization derived from
county-level aggregate studies have been associated with
stroke mortality in young blacks in North Carolina (10).
Census-tract SES and social instability variables were used
to derive indices of socioecological stress in Detroit,
Michigan, and surveys have disclosed higher mean blood
pressure levels among blacks in relation to socioecological
stress (11).  Studies of this type provide an introduction
to aggregate-level investigations.  The goal of these
investigations is not to identify ecological indices as
surrogates for individual attributes, but rather to
characterize attributes of the social environment that act
as predictors of morbidity and mortality.
Aggregate-Level Studies
The educational, economic, and occupational attributes of
counties and aggregates of counties called "state economic
areas" have been scaled to derive indices of the social
environment of their residents.  These aggregate-level
attributes are highly correlated with one another.
-----------------------------------------------------------
Figure Missing
Figure 4.  -  Five-Year Average Annual Age-Adjusted CHD
Mortality Rate, 1962 to 1992, by Education Profile of State
Economic Areas, White Men Ages 35 to 64.
-----------------------------------------------------------
The proportion of individuals with less than a high school
education in a given place of residence has been analyzed in
relation to levels and time trends of CVD mortality (12).
This education profile is highly associated with the
occupational structure, income level, urbanization, access
to transportation, and availability of health care
facilities in a place of residence.  In 1962, during the
ascending limb of the CHD epidemic, CHD mortality in middle-
aged white men was not clearly associated with the education
profile of place of residence, except that those with the
highest education had the  lowest CHD mortality (Fig. 4).
However, by 1969, CHD mortality rates increased with
decreasing levels of education in a clear stepwise
progression.  The gradient emerged because the onset of CHD
mortality decline occurred earlier in residential areas with
high education profiles than in areas with the lowest
education levels.  Since 1969, the inverse association has
persisted along with the continuous decline in CHD mortality
in white men.
The trends indicate an increasing mortality gradient with
social environment characteristics in the 1990s.  Between
1962 and 1992, mortality was lowest among black men residing
in areas with a high education profile.  Over time, the
highest CHD mortality rates occurred in places of residence
with the lowest education level.  Trends for black and white
women were similar.  Absolute levels of CHD mortality were
slightly higher for middle-aged black men than for middle-
aged white men, and markedly higher for black women than for
white women.
Stroke mortality varied inversely and much more strongly
than CHD mortality with place-of-residence education level.
For black men, there was a 2.5-fold stepwise gradient in
stroke mortality from highest to lowest education level in
1963 (Fig. 5).  Stroke mortality decreased in all strata
over time, but absolute decreases were greater in
residential areas with a higher initial stroke incidence,
and therefore by 1990 the absolute difference among
education strata had narrowed.  Although absolute levels of
stroke mortality were approximately two-thirds lower in
whites than in blacks, the patterns of inverse rank ordering
by education level and of the mortality decline (with
greater decline from higher starting levels) across all
education strata appeared in all four race-gender groups.
-----------------------------------------------------------
Figure Missing
Figure 5.  -  Five-Year Average Annual Age-Adjusted Stroke
Mortality Rate, 1962 to 1992, by Education Profile of State
Economic Areas, Black Men Ages 35 to 64.
-----------------------------------------------------------
Summary and Implications
Epidemiological studies indicate that SES levels are now
inversely associated with CVD in both blacks and whites.
The pathways that explain this relationship are
interrelated.  SES indicators are inversely associated with
most of the major behavioral and physiological CVD risk
factors in blacks.  Most of the CVD risk factors inversely
associated with SES are positively associated with the
prevalence of preclinical atherosclerosis, a critical
waystation on the path to clinically manifest CHD, in blacks
and whites.
Controlling for these risk factors eliminates the inverse
association of SES with carotid wall thickness, a finding
consistent with the idea that CVD risk factors are the
intervening links or pathways between SES and
atherosclerosis.  However, controlling for these risk
factors does not statistically explain the association of
SES with prevalent CHD in ARIC.  This suggests a possible
role for other factors, including psychosocial attributes of
John Henryism, lifestyle incongruity, access to and
utilization of medical care, and currently unidentified
stressors, in the transformation of silent to symptomatic
atherosclerotic disease.  However, in the NHANES-I followup,
adjustment for the major risk factors reduces the
association of income with incident CHD to statistical
nonsignificance.
At the aggregate level, SES affects the magnitude and time
trends of CVD mortality in blacks and whites.  These studies
indicate that the association of SES with CHD at both
individual and aggregate levels has varied over time and
that the present inverse association is increasing in
strength.  The inverse association of stroke mortality with
SES dates back at least 35 years and persists in blacks and
whites despite a two-thirds decrease in the absolute level
of stroke mortality.
The marked changes over time demonstrate that the SES
effects on CVD mortality in blacks are not fixed and
invariant. Although the pathways linking SES to CVD in
blacks are multicausal and interrelated, epidemiological
observation and intervention studies suggest that harmful
pathways can be interrupted and healthy ones can be
promoted.  Interventions at both the individual and the
societal level hold promise for further reducing CVD
mortality in blacks and whites.
REFERENCES
1.  Hames CG:  Evans County Cardiovascular and
    Cerebrovascular Epidemiologic Study.  Introduction.
    Arch Intern Med 1979;128:883-886.
2.  Tyroler HA, Heiss G, Heyden S, Hames CG:  Family
    followup study of serum cholesterol in Evans County,
    Georgia.  J Chron Dis 1980;33:323-330.
3.  Keil JE, Tyroler HA, Sandifer SH, Boyle E:
    Hypertension:  effects of social class and racial
    admixture.  Am J Public Health 1977;67:634-639.
4.  Keil JE, Sutherland SE, Knapp RH, Lockland DT, Gazes PH,
    Tyroler HA:  Mortality rates and risk factors for
    coronary disease in blacks as compared with white men
    and women.  N Engl J Med 1993;329:73-78.
5.  Diez-Roux AV, Nieto FJ, Tyroler HA, Crum LD, Szklo M:
    Social inequalities and atherosclerosis.  The
    Atherosclerosis Risk in Communities Study.  Am J
    Epidemiol 1995;141:960-973.
6.  Cutter GR, Burke GL, Dyer AR, Friedman GD, Hilner JE,
    Hughes GH, Hulley SB, Jacobs DR, Liu K, Manolio TA,
    Oberman A, Perkins LL, Savage PJ, Serwitz JR, Sidney S,
    Wagenknecht LE:  Cardiovascular risk factors in young
    adults.  The CARDIA Baseline Monograph.  Control Clin
    Trials 1991;12:1S-77S.
7.  Cooper R, Ford E:  CHD among blacks and whites in the
    NHANES-I Epidemiologic Followup Study:  incidence of new
    events and risk factor prediction.  Ann Epidemiol
    1992;2:637-645.
8.  James SA, Hartzett SA, Kalsbeek WD:  John Henryism and
    blood pressure differences among black men.  J Behav Med
    1983;6:259-278.
9.  Dressler WW:  Education, lifestyles, and arterial blood
    pressure.  J Psychosomatic Res 1990;34:515-523.
10. Neser WB, Tyroler HA, Cassel JC:  Social disorganization
    and stroke mortality in the black population of North
    Carolina.  Am J Epidemiol 1971;93:166-175.
11. Harburg E, Erfurt JC, Chapel C, et al:  Socioecological
    stressor areas and black-white blood pressure:  Detroit.
    J Chron Dis 1973;26:595-611.
12. Tyroler HA, Wing S, Knowles MG:  Increasing inequality
    in CHD mortality in relation to educational achievement
    profile in places of residence, United States, 1962-
    1987.  Ann Epidemiol 1993;3:S51W-S54.
-----------------------------------------------------------
Pathways Linking SES and CVD:  Hispanic Populations
Helen P. Hazuda, Ph.D.
Hispanic Americans numbered over 22 million in 1992 and
today constitute the nation's fastest growing ethnic
minority (1,2).  Among Hispanics, there are three major,
socioculturally distinct subgroups:  Mexican Americans,
Cuban Americans, and Puerto Ricans.  Mexican Americans are
the largest subgroup, comprising 62.6 percent of the total
U.S. Hispanic population (1,2).  Hispanics generally have
markedly lower socioeconomic status (SES) than non-Hispanic
whites (3).  An interesting epidemiological paradox,
observed among Mexican Americans in particular, is that this
lower SES is not associated with a consistently worse
pattern of cardiovascular disease (CVD) risk factors,
disease prevalence, or mortality (4).
Until now, little attention has been given to examining the
association of  SES and CVD within Hispanic populations.
SES data, on Hispanics as a group, are available from the
National Longitudinal Mortality Survey (NLMS) and the
National Health Interview Survey (NHIS), and data on Mexican
Americans are available from the National Health and
Nutrition Examination Survey III (NHANES III).  These data,
compiled specifically for this conference, represent the
first efforts to address this issue on a national scale.
Only a few published data are available from local studies
(5-10), perhaps because SES is often treated as a
confounding variable requiring statistical control, rather
than an independent variable of intrinsic interest.
Published data for Puerto Rican men are available from the
Puerto Rico Heart Health Program (10).  No published data
were found for Cuban Americans.
Three types of pathways may link SES to CVD:  biological,
lifestyle, and psychosocial.  Data from three large
epidemiological investigations  -  the San Antonio Heart
Study (SAHS), the Stanford Five-City Project (SFCP), and the
Puerto Rico Heart Health Program (PRHHP)  -  illustrate the
pattern of association between SES indicators and selected
variables in each pathway.
Methods
Data from the SAHS are based on the pooled sample of
Mexican-American participants in Phase I (1979 to 1981) and
Phase II (1984 to 1988) of the study.  The study populations
included 1,393 Mexican- American men and 1,908 Mexican-
American women, 25 to 64 years of age, randomly sampled from
three socioculturally distinct neighborhoods:  a low-income,
exclusively Mexican-American barrio; a middle-income
transitional neighborhood composed of about 60 percent
Mexican Americans and 40 percent non-Hispanic whites; and a
high-income suburban neighborhood composed of about 10
percent Mexican Americans and 90 percent non-Hispanic
whites.  Stratified sampling based on surname listings in
the crisscross directory for San Antonio ensured
approximately equal numbers of participants in both ethnic
groups from the transitional neighborhood and suburbs (5-8).
Data from the SFCP are based on a matched-pairs sample of
756 Hispanics and whites, 25 to 74 years of age, who resided
in households randomly sampled from four cities in
California and who participated in one of five separate
cross-sectional surveys conducted biannually from 1979 to
1990.  Subjects were matched for ethnic background, sex,
age, education, city of residence, and survey time period
(9).  Data from the PRHHS are based on 6,208 men, 45 to 64
years of age, from urban areas of Puerto Rico, who
participated in the first study examination conducted
between 1965 and 1968 (10).
For SFCP and PRHHP, the SES data presented here are for
education.  For the SAHS, three separate SES indicators  -
education, household income, and occupation  -  are
examined.  For comparison with national data presented in
the Chartbook of U.S. National Data on Socioeconomic Status
and Cardiovascular Health and Disease, these indicators were
broken into the following categories:  education  -  less
than 12 years, 12 years, greater than 12 years; household
income  -  less than $9,000, $9,000 to $29,999, greater than
or equal to $30,000; and occupation  -  white collar, blue
collar, service workers.  Correlations among the ranked
indicators using Kendall's taub were:  men  -  education and
income, 0.46; education and occupation, 0.44; income and
occupation, 0.34; and women  -  education and income, 0.46;
education and occupation, 0.50; income and occupation, 0.37.
The shared variance among SES indicators thus ranged from
11.6 to 25.0 percent, so that each indicator can be clearly
recognized as capturing discrete aspects of this underlying
construct.  Nonetheless, the patterns of association between
the three SES indicators and the biological, lifestyle, and
psychosocial variables examined were very similar,
particularly for education and household income.  Data
presented are from the SAHS unless otherwise specified.
Biological Pathways
Cholesterol
Higher levels of total cholesterol and the ratio of total to
high density lipoprotein (HDL) cholesterol are independently
associated with increased risk of coronary heart disease
(CHD).  For Mexican-American men, higher household income
was significantly associated with higher total cholesterol
(p < 0.05); for Mexican-American women, the association was
nonsignificant and in the opposite direction.  There was a
striking gender-income interaction effect (p = 0.0001), with
a successively greater gender difference in total
cholesterol at successively higher levels of household
income.  The same pattern of associations was observed for
the ratio of total to HDL cholesterol.  The primary reason
for the latter appears to be a beneficial association
between higher household income and higher HDL (p = 0.0001)
among women in combination with nonsignificant and slightly
negative association between household income and HDL among
men.
The associations of education with total cholesterol and
with the ratio of total to HDL cholesterol paralleled those
of income in both genders.  Similar associations with
occupation were observed in women but not in men.
Obesity
Higher levels of education were significantly associated
with markedly lower body mass index (BMI) (kg/m2) in
Mexican-American women (p = 0.0001), but with only slightly
lower BMI in Mexican-American men though this association is
not significant.  Parallel associations were observed for
all three SES indicators.
Blood Pressure
The pattern of association between education and diastolic
blood pressure in Mexican Americans was similar across
genders to that observed for BMI.  For systolic blood
pressure (SBP), higher education had a highly significant
and beneficial effect in both genders (men, p < 0.001;
women, p = 0.0001).  There was also a striking age-education
interaction effect that was somewhat stronger in men (p =
0.0001) than in women (p < 0.03).  The difference in SBP
across educational levels was greater for those 45 to 64
years of age (8 mmHg) than for those 25 to 64 years of age
(2-5 mmHg).  Parallel associations were observed for all
three SES indicators.
Hypertension was classified according to the Hypertension
Detection and Followup Program criteria as SBP greater than
140 mmHg or diastolic blood pressure (DBP) greater than 95
mmHg.  Persons currently taking antihypertensive medications
were also considered to have high blood pressure.  Higher
education and income, but not occupation, were significantly
associated with lower prevalence of hypertension in Mexican-
American women (p = 0.0001).  None of the SES indicators
were significantly associated with prevalence of
hypertension in Mexican-American men.
Diabetes
Diabetes was classified according to World Health
Organization (WHO) criteria as fasting glucose greater than
or equal to 140 mg/dL or 2-hr postload glucose greater than
or equal to 200 mg/dL.  Higher SES, as measured by all three
indicators, was significantly associated with lower diabetes
prevalence in Mexican-American women (for education and
income, p = 0.0001; for occupation, p < 0.001).  In Mexican-
American men, lower diabetes prevalence was significantly
associated with higher education (p < 0.001) and household
income (p < 0.05), but not with higher occupation.
Summary
In Mexican Americans, SES appears to have a greater and more
consistent impact on biological pathways to CVD in women
than in men.  Higher SES is uniformly associated with a
better profile of biological risk factors in Mexican-
American women.
Lifestyle Pathways
Saturated Fat/Cholesterol Avoidance
The association between each of the SES indicators and
saturated fat/cholesterol avoidance (FATAVOID) is
illustrated for women.  The positive gradient between SES
and FATAVOID is particularly striking for education and
income.  However, the p-value for all three indicators is
0.0001.  The FATAVOID score is about one-half point higher
in the highest SES stratum than in the lowest for
occupation, and about 1 point higher for education (scale
range: 0-6 points).  The same highly significant pattern of
association between the SES indicators and FATAVOID was
observed in men.
Leisure Time Physical Activity
Gradients for the association between weekly leisure-time
physical activity and SES are even steeper than those for
FATAVOID.  The association is most striking for income, with
Mexican-American women in the highest household income
category exercising more than twice as often per week as
women in the lowest household income category (p = 0.0001).
The association is least striking for occupation.  Mexican-
American women in the highest occupation category engage in
leisure-time physical activity about 1.6 times per week
compared to 1.2 times per week for women in the lowest
occupation category (p < 0.001).  The gradient for education
is intermediate between those for household income and
occupation (p = 0.0001).  The patterns of association are
similar for Mexican-American men.
Current Cigarette Smoking
All three SES indicators exhibit striking negative and
monotonic associations with rates of current smoking.
Across indicators, the proportion of Mexican-American women
who are current smokers declined from 26 to 30 percent in
the lowest SES category to 14 to 16 percent in the highest
SES category (p = 0.0001).  Once again, the patterns of
association are similar for Mexican-American men.
Summary
Based on these analyses, it appears that higher SES is
uniformly associated with healthier CVD lifestyle among
Mexican Americans for both men and women.
Psychosocial Pathways
Perceived Control Over Health
The association between SES and psychosocial pathways to CVD
in Mexican Americans is illustrated by education and
perceived control over health (Fig. 1).  In both gender
groups, there is a strong positive association between
education and perceived health control (p =  0.0001).  The
pattern of association is similar for household income and
occupation.
Other psychosocial variables examined include marital
status, availability of an intimate confidant, and self-
efficacy.  For each of these variables, higher SES is
associated with scores indicative of greater protection
against CVD.
Summary
Psychosocial characteristics and SES appear to travel
together.  Higher SES is associated with a more favorable
profile of psychosocial risk factors for CVD.
-----------------------------------------------------------
Figure Missing
Figure 1.  -  Education and Perceived Health Control in
Mexican Americans, San Antonio Heart Study.
-----------------------------------------------------------
SES Interaction Effects
It is important to keep in mind that the association between
SES and CVD pathways may involve interactions with age,
gender, ethnic group, economic context, and perhaps other
factors.  Examples include interactions with age, in the
case of SBP, and with gender, in the case of cholesterol.
Data from the SFCP and the PRHHP illustrate similar
interactions with ethnic group and economic context.
SES-Ethnic Group Interactions
The SFCP observed two striking education-ethnic group
interactions.  In the lowest education category, Hispanics
had lower DBP levels than whites (ethnic difference:  1-1.5
mmHg).  Although DBP levels were lower in both groups at
higher levels of education, there was a crossover in ethnic
differences in DBP.  Among those in the highest education
category, Hispanics had higher DBP than whites (ethnic
difference:  2.75-3.25 mmHg).  A similar interaction effect
was observed for education and current smoking.  Among those
in the lowest education category, almost twice as many
whites as Hispanics were current smokers (approximately 48
percent vs. 25 percent, respectively), but among those in
the highest education category fewer whites than Hispanics
were current smokers (approximately 12 percent vs. 17
percent, respectively).
SES-Economic Context Interaction Effects
The PRHHP illustrates the differential association between
SES and CVD pathways in regions with developing economies as
compared with developed economies.  For urban men in the
study, higher SES was associated with a worse profile of
biological risk factors for CVD.  SBP, serum cholesterol,
and glucose intolerance were all successively higher at
higher levels of education.  Similarly, relative weight and
weight gain since age 25 were higher at higher educational
levels, and physical activity levels were lower.  The
percentage of current smokers showed little association with
education.
These findings are consistent with the notion that the
association between SES and CVD has an ascending and
descending limb.  Developing countries are on the ascending
limb.  That is, the affluent at higher levels of SES engage
in more sedentary jobs and purchase high-fat foods, while
those at lower levels of SES are unable to engage in
similarly unhealthy lifestyles.  In developed countries,
those at higher levels of SES have learned about unhealthy
lifestyles and make appropriate changes, while those at
lower levels of SES have adopted the unhealthy lifestyles
that have been made affordable to them.  Within developed
countries, it is certainly possible that some geographic
areas provide economic contexts more similar to those of
developing countries than developed ones.
Summary
It is important to consider the possibility of SES
interactions with a variety of variables such as gender,
age, ethnic group, and economic context.  These interaction
effects indicate that the meaning of SES is not the same for
all groups or within all contexts.  SES indicators
(education, household income, occupation) are pointers that
hint at differences in the experience and context of daily
living among people who score differently on these measures.
Learning what these experiences are and which ones are
related to CVD will be essential for designing effective
interventions to improve cardiovascular health in persons
with low SES.
REFERENCES
1.  The Hispanic population in the United States:  March
    1992.  Current population reports.  Washington, D.C.,
    pp. 20-465.
2.  Lapham S:  The Hispanic population.  Current population
    reports, special studies series.  Population profile of
    the United States, 1993.  Washington, D.C., pp. 23-185.
3.  U.S. Department of Health and Human Services:  Health
    status of the disadvantaged:  Chartbook 1986.
    Washington, D.C.:  Government Printing Office, 1986.
    (DHHS publication no. (HRSA) HRS-P-DV 86-2).
4.  Markides KS, Coreil J:  The health of southwestern
    Hispanics:  an epidemiologic paradox.  Public Health
    Reports 1986;101:253-265.
5.  Hazuda HP, Haffner SM, Stern MP:  Effects of
    acculturation and socioeconomic status on obesity and
    diabetes in Mexican Americans:  the San Antonio Heart
    Study.  Am J Epidemiol 1988;128(6):
    1289-1301.
6.  Hazuda HP, Mitchell BD, Haffner SM, Stern MP:  Obesity
    in Mexican American subgroups. Am J Clin Nutr
    1991;53(6):1571S-1576S.
7.  Hazuda HP:  Hypertension in the San Antonio Heart Study
    and Mexico City Diabetes Study:  sociocultural
    correlates.  Public Health Reports 1996; submitted for
    publication.
8.  Knapp JA, Hazuda HP, Haffner SM, Young EA, Stern MP:  A
    saturated fat-cholesterol avoidance scale:  sex and
    ethnic differences in a biethnic population.  J Am Diet
    Assoc 1988;88:172-177.
9.  Winkleby MA, Fortmann SP and Rockhill B:  Health-related
    risk factors in a sample of Hispanics and whites matched
    on sociodemographic characteristics.  Am J Epidemiol
    1993;137:1365-1375.
10. Sorlie PD, Garcia-Palmieri MR:  Educational status and
    coronary heart disease in Puerto Rico:  the Puerto Rico
    Heart Health Program.  Int J Epidemiol 1990;19:59-65.
-----------------------------------------------------------
Socioeconomic Status and 23-Year Cardiovascular Disease and
Total Mortality Among Middle-Aged Men: The Honolulu Heart
Program
Beatriz L. Rodriguez, M.D., Ph.D., J. David Curb, M.D.,
Cecil M. Burchfiel, Ph.D., Ka-On Fong, M.A.,
Katsuhiko Yano, M.D., Dan S. Sharp, M.D., Ph.D.
An association between poor health and low socioeconomic
status (SES) has been observed for many years (1).  In
industrialized countries, individuals of low SES have higher
rates of cardiovascular disease (CVD) morbidity and
mortality than individuals of high SES, regardless of sex,
race, or ethnic background.  Correspondingly, low-SES groups
tend to have the least favorable health characteristics.
Much of the excess CVD risk observed in these individuals is
explained by standard risk factors (2,3).
The Honolulu Heart Program provides the opportunity to
investigate associations between various measures of SES and
23-year mortality from coronary heart disease (CHD), stroke,
and all causes among middle-aged men of Japanese ancestry.
Previously reported findings from the Honolulu Heart Program
suggest that occupation level, classified as white vs. blue
collar work, is not associated with CVD or total mortality
(4).
Baseline Examination
The Honolulu Heart Program, begun in 1965, follows 8,006 men
of Japanese ancestry, ages 45 to 68 at entry, for the
development of CHD and stroke.  Details of the selection
process for this cohort have been published previously (5).
Persons with CHD, stroke, or cancer at baseline were
excluded from these analyses.
During the first examination of this cohort in 1965, data
were collected on CVD risk factors, including anthropometric
measurements, blood pressure, electrocardiograms, serum
cholesterol levels, medical history, and behavioral
characteristics such as smoking, alcohol consumption, and
physical activity.  Several variables with a possible SES
association were also assessed at baseline.  These  included
home ownership, number of bedrooms in the home, number of
persons in the household, education, marital status,
occupation, and wife's occupation.
Surveillance Methods
The surveillance system established at the beginning of the
study continues to identify cases of CHD and stroke based on
selected hospital discharge diagnoses at major medical
facilities on the island of Oahu.  Deaths are ascertained
primarily from obituaries in island newspapers, supplemented
with death certificate listings from the state health
department.  A panel of Honolulu Heart Program physicians
reviews the medical records to identify incident cases of
CHD and stroke and to determine the cause of death based on
standardized criteria (6,7).  CHD deaths include fatal
events, as well as sudden deaths (within 1 hour of onset)
among asymptomatic or apparently healthy subjects.  The
outmigration rate from Oahu has been less than 1 in 1,000
study participants per year.   All but four of the original
8,006 study participants were located for the program's
fourth examination in 1991 to 1993.
Data Analysis
A series of stepwise Cox models (8) were used to investigate
which measures of SES were associated with mortality from
CHD, stroke, and all causes.  Age was forced in the models.
The stepwise models tested the SES indicators as possible
independent variables to determine the most important
predictors of CVD and total mortality.  After the most
important SES predictors were identified, standard risk
factors were added to determine whether the associations
between SES indicators and CVD mortality are independent or
mediated by standard risk factors.  These included pack-
years of smoking, alcohol intake, cholesterol,
triglycerides, hypertension, physical activity, birth in
Japan, years lived in Japan, glucose level, body mass index,
and percent calories from fat.
As shown in Table 1, none of the measures of SES reached the
level of statistical significance required for inclusion in
the model  for CHD mortality (p < 0.05).  Home ownership was
inversely and significantly associated with age-adjusted
stroke mortality.  After adjusting for age and the standard
risk factors, however, home ownership was no longer
significantly associated with stroke mortality, suggesting
that standard CVD risk factors mediate these associations.
Similar results were observed without adjustment for place
of birth and years lived in Japan.  Home ownership and
marital status were the strongest SES predictors for total
mortality after adjusting for age.  These variables were
inversely and significantly associated with total mortality
and remained significantly associated after adjusting for
the standard risk factors.  Nonmanual occupation was
inversely and independently associated with total mortality.
Age-adjusted mean levels for the standard risk factors were
calculated by home ownership.  Age- and risk factor-adjusted
relative risks for CVD and total mortality and 23-year age-
adjusted mortality rates were calculated by home ownership,
marital status, education, and occupation.
Higher education levels (senior high school, technical
school, or university) were protective for 23-year total
mortality (Table 2).  Education was inversely associated
with total mortality after adjusting for age, but was not
independent of other risk factors.  Home ownership had a
significant protective effect for stroke and total
mortality.  Marriage showed similar trends but was
significantly and inversely associated only with total
mortality.
-----------------------------------------------------------
Table Missing
Table 1.  -  Stepwise Cox Regression Analyses for 23-Year
CVD Morbidity and Mortality and SES
-----------------------------------------------------------
Table Missing
Table 2.  -  Age-Adjusted  23-Year Incidence Rates per 1000
Men for CVD Morbidity and Mortality
-----------------------------------------------------------
Homeowners smoked and drank significantly less than men who
did not own homes (Table 3).  They also had lower nonfasting
glucose concentrations, higher body mass and percentage of
dietary calories from fat, and lower physical activity. They
were less likely to have been born in Japan and lived there
for fewer years on average.  These differences, although
statistically significant, were small compared with the
differences in smoking and drinking.  Homeowners were also
more likely to be married, to have nonmanual occupations,
and to have completed high school.
Education, home ownership, and marriage were significantly
and inversely associated with total mortality after
adjusting for age (Table 4).  Nonmanual occupation, home
ownership, and marriage were inversely associated with total
mortality after adjusting for the standard risk factors.
Home ownership was also significantly and inversely
associated with stroke after adjusting for age, but the
magnitude of the association was reduced after adjusting for
standard risk factors.
Discussion
Some historical background is helpful to understand the
social and cultural characteristics of the Japanese
Americans living in Hawaii.  At the turn of the century,
large numbers of Japanese, recruited to work on the sugar
plantations, immigrated to Hawaii.  More than 85 percent of
the men of this cohort are second-generation Japanese
Americans and are therefore somewhat homogeneous with regard
to their education level and cultural characteristics.
In the Scottish Heart Health Study (9), home ownership was
the most discriminatory measure of SES in relation to CHD
prevalence.  In our study, it was the best predictor of 23-
year total mortality.  Home ownership may be an indicator of
wealth, stability, healthier lifestyles, and better access
to medical care.  Home owners are also more likely to have
high school or higher education, to be married, and to have
nonmanual occupations.
Winkleby et al. have suggested that education level is the
best SES predictor of CVD risk factor profiles (10).  In the
present study, education was associated with total
mortality, and this relationship was mediated by traditional
risk factors.  Education however, was not associated with
CHD or stroke mortality, possibly because of the cultural
and educational homogeneity of this population and the
relatively small incidence of CHD and stroke events as
compared with total mortality.
-----------------------------------------------------------
Table Missing
Table 3.  -  Age-Adjusted Risk Factor Levels by Home
Ownership in the Honolulu Heart Program, 1965-68
-----------------------------------------------------------
Table Missing
Table 4.  -  Age- and Risk Factor-Adjusted* Relative Risk
for 23-Year CVD Morbidity and Mortality
*Risk factors: smoking (pack-years), alcohol intake,
hypertension, cholesterol, body mass index, diabetes, and
physical activity index
-----------------------------------------------------------
The findings of this investigation underscore the importance
of SES indicators as correlates of adverse risk factors such
as smoking and drinking and as predictors of long-term
stroke and total mortality in this cohort of middle-aged
Japanese-American men.  Further research is needed to
determine how to promote better social, behavioral, and
living conditions among individuals of lower SES in order to
improve their overall health.
REFERENCES
1.  Kaplan GA, Keil J:  Socioeconomic factors and
    cardiovascular disease: a review of the literature.
    Circulation 1993;88:1973-1998.
2.  National Heart, Lung, and Blood Institute:  Report of
    the task force on research in epidemiology and
    prevention of cardiovascular disease, 1994.
3.  Luepker RV, Rosamond WD, Murphy R, Sprafka JM, Folson
    AR, McGovern P, Blackburn H: Socioeconomic status and
    coronary heart disease risk factor trends.  The
    Minnesota Heart Survey. Circulation 1993;88:2172-2179.
4.  Miller DW, Reed D, MacLean CJ:  Mortality and morbidity
    among blue and white collar workers in the Honolulu
    Heart Program cohort.  Int J Epidemiol 1993;22:834-837.
5.  Kagan A, Harris BR, Winkelstein W, Johnson KG, Kato H,
    Syme SL, et al.:  Epidemiologic studies of coronary
    heart disease and stroke in Japanese men living in
    Japan, Hawaii and California: demographic, physical,
    dietary and biochemical characteristics.  J Chron Dis
    1974;27:345-364.
6.  Yano K, Reed D, McGee D:  Ten-year incidence of coronary
    heart disease in the Honolulu Heart Program:
    relationship to biological and lifestyle
    characteristics.  Am J Epidemiol 1984;119:653-666.
7.  Rhoads GG, Kagan A, Yano K:  Usefulness of community
    surveillance for the ascertainment of coronary heart
    disease and stroke.  Int J Epidemiol 1975;4:265-270.
8.  Cox DR:  Regression models and life tables.  JR Stat Soc
    1972;344:187-220.
9.  Woodward M, Shewry MC, Smith WC, Tunstall-Pedoe H:
    Social status and coronary heart disease:  results from
    the Scottish Heart Health Study.  Prevent Med
    1992;21:136-148.
10. Winkleby MA, Jatulis DE, Frank E, Fortman SP:  SES and
    health:  how education, income and occupation contribute
    to risk factors for cardiovascular disease.  Am J Public
    Health 1992;82:816-820.
-----------------------------------------------------------
Socioeconomic Status and Cardiovascular Health and Disease
in American Indians:  The Strong Heart Study
Elisa T. Lee, Ph.D.
Oscar T. Go, Ph.D.
for the Strong Heart Study Investigators
The Strong Heart Study (SHS) is an epidemiological study of
cardiovascular disease (CVD) and its risk factors among
three American Indian populations.  These include the
Pima/Maricopa of Arizona; the Oglala and Cheyenne River
Sioux in South Dakota and the Devil's Lake Sioux in North
Dakota; and the Apache, Caddo, Comanche, Delaware, Fort Sill
Apache, Kiowa, and Wichita tribes in southwestern Oklahoma.
Phase I includes 4,549 eligible participants, ages 45 to 74
at the time of clinic visit.  Participants in Arizona and
the Dakotas live on reservations, whereas most of those in
Oklahoma reside in urban communities.  Socioeconomic status
(SES) and lifestyle data were collected through a personal
interview, and biological data such as blood pressure,
diabetes, and lipids were obtained through a physical
examination and laboratory tests.  The detailed protocol has
been published elsewhere (1).  This paper reports the
significant pathways that have been observed to link SES
factors and cardiovascular disease (CVD).
METHODS
In the literature, SES factors include education, income,
and occupation (2).  Data on current employment status and
recent occupation were not available for the SHS, so this
report focuses only on the first two factors.  For these
analyses, education level is categorized as less than 12
years, 12 years, and more than 12 years of school.  Annual
household income is grouped into five levels: less than
$5,000; $5,000 to $9,999; $10,000 to $24,999; $25,000 or
more, and "unknown," which applies to subjects who did not
know, did not respond, or refused to answer.  This last
group was included because it constitutes more than 20
percent of the SHS cohort.
The gradients for income are lower than those reported for
blacks, Mexican Americans, and whites (3).  In fact, more
than 65 percent of the participants who reported their
income had an annual household income of less than $25,000.
Education, income, and other SES variables were analyzed in
relation to blood pressure, hypertension, lipids, body mass
index (BMI), overweight, diabetes, albuminuria, cigarette
smoking, alcohol consumption, physical activity, marital
status, sufficient income to pay bills, distance to nearest
clinic and hospital, ability to speak native language, and
degree of American Indian blood.  All analyses were
stratified by gender and region.  The chi-square test was
used to compare prevalence, and analysis of variance was
used to compare means of continuous measurements.
RESULTS
Table 1 presents the frequency distributions of education
and income by gender and region.   More than 50 percent of
the participants had at least a high school education (men,
54 percent; women, 51 percent).  These percentages were
lower than the 66 percent reported based on the 1990 census
for all American Indians and Alaska Natives (4).
Participants in Oklahoma had a higher average education
level than those living in Arizona and the Dakotas.  Table 2
compares the education levels of  SHS cohorts with those of
other ethnic groups.
-----------------------------------------------------------
Table Missing
Table 1.  -  Frequency Distributions of Education and Income
Among American Indians by Gender and Region
-----------------------------------------------------------
SHS participants had very low annual household incomes  -
34 percent had a reported income of less than $5,000.  Table
3 compares the prevalence of poverty in SHS cohorts with
that in other ethnic groups.  The average poverty threshold
used for the SHS household was $15,000 and that for the
other ethnic groups was $14,225 (3).  The prevalence of
poverty among American Indians ages 45 to 64 (66 percent) is
3 times that of blacks (21 percent), nearly 4 times that of
Hispanics, and 7 times that of whites.  The comparison is
similar for those age 65 and over.  The median household
income for American Indians and Alaska Natives, according to
the 1990 census, was $20,025 (4); the median for the SHS
cohorts was less than $10,000.  Participants in Arizona and
the Dakotas had less income than those in Oklahoma.
About 34 percent of men and 42 percent of women with more
than 12 years of education live below poverty level, defined
in SHS as a household income of $15,000 per year.  For all
three regions, the prevalence of poverty decreases uniformly
with increasing education, a trend that has also been
observed in the other three ethnic groups (3).  Across all
education categories and in all three regions, more women
than men reported an income below poverty level.  Although
equal percentages of  men and women (26 percent) have more
than 12 years of education, only 9 percent of women reported
household income of $25,000 or more compared to 15 percent
of men.
Participants with more than 12 years of education tended to
be younger than those in the lowest education category (mean
age of 54 vs. 58 years, respectively, for both men and
women).  In addition, both men and women with an annual
household income of $25,000 or more had a mean age of 53,
compared with an age of  56 for men and 57 for women in the
less than $5,000 group.
Cardiovascular Morbidity
The prevalence of self-reported stroke decreased with higher
education except in Arizona women.  This decrease was
similar to that observed in white women (3).  Stroke
prevalence also decreased with higher income among men and
women in Arizona and Oklahoma.  No stroke was reported for
participants in Oklahoma or for Arizona men with $25,000 or
more in income.  For those with less than 12 years of
education or less than $5,000 in income, the highest stroke
prevalence among all three regions was observed in the
Oklahoma cohort.
-----------------------------------------------------------
Table Missing
Table 2.  -  Percent of Population with at Least High School
Education by Gender, Age, and Race
-----------------------------------------------------------
For women in all three regions combined, coronary heart
disease (CHD) prevalence (as diagnosed through EKG
examination and verified by medical charts) decreased with
increased education and with increased income.
Biological Pathways
Blood Pressure
For both genders, mean systolic blood pressures were lowest
in the North and South Dakota cohort.  Mean systolic blood
pressure decreased with higher education among women; for
all three regions, the difference in mean readings between
those with less than and those with more than 12 years of
education ranged from 2 to 8 mmHg, with the largest
difference observed  in women from the Dakotas.  A similar
downward trend was observed in the other three ethnic groups
ages 45 to 64 (3).  Systolic blood pressure also appeared to
decrease with increasing income.  For all women, those with
income $25,000 or higher had the lowest mean reading (120
mmHg).
Similar patterns existed for hypertension.  The prevalence
of hypertension for both genders was lowest in participants
from the Dakotas.  Among women, prevalence of hypertension
decreased with increasing education.  The same pattern has
been observed among blacks and non-Hispanic whites (3).
Although there was no clear-cut downward trend with
increasing income (except for women in all three regions
combined), it appeared that the lowest prevalence occurred
in those in the highest income category.  Consistent with
self-reported data, Arizona had the highest percentage of
hypertensive participants who were aware of their
hypertension.  Awareness of hypertension increased with
higher levels of education for all men and women.
An increasing trend in awareness was also observed with
higher income among all women.  In the Dakotas, only about
half of the women with incomes under $5,000 were aware of
their hypertension, compared with about 75 percent of women
in higher income groups.  The lowest income group in North
and South Dakota also had the lowest percentage of
hypertensives being treated (47 percent) and only 24 percent
had their hypertension controlled.  The percent of women
with controlled hypertension increased with years of
education; however, no such patterns were observed in men.
More hypertensive women than hypertensive men were being
treated  (47 to 77 percent vs. 25 to 69 percent).  The
percentages increased with higher education and income.
-----------------------------------------------------------
Table Missing
Table 3.  -  Percent of Population Below Poverty Level by
Gender, Age, and Race
-----------------------------------------------------------
Serum Cholesterol
Total and low-density lipoprotein (LDL) cholesterol levels
increased with higher income among men (Table 2). An upward
trend was also observed with higher education for all men.
The differences in total and LDL cholesterol between the
lowest and highest income groups were all substantial: 18
and 27 mg/dL for Arizona, 16 and 19 mg/dL for Oklahoma, 21
and 14 mg/dL for North and South Dakota, and 21 and 21 mg/dL
for all men.  An upward trend was also observed with higher
education for all men.  The differences between those with
less than and those with more than 12 years of education
were smaller than those observed for income (12 for total
cholesterol and 13 for LDL cholesterol).  Triglyceride
levels also increased with higher education or higher income
among men in all three regions combined.
The trend for men was reversed for high-density lipoprotein
(HDL) cholesterol, which decreased with higher education or
higher income.  Those with more than 12 years of education
or at least $25,000 in income had the lowest mean HDL
levels; differences between lowest and highest strata were 4
mg/dL for education and 7 mg/dL for income.  This downward
trend has not been observed for whites, blacks, or Hispanics
(3).
Among women, patterns were not clear, although in the
Dakotas, LDL cholesterol increased with higher education or
higher income.  No trend was observed with total or HDL
cholesterol.
Obesity
There was also a slightly increasing trend in BMI with
higher education or higher income in men.   Although no
trend in BMI with income was discerned in women, those with
the highest income level tended to be the leanest.
Overweight was defined as having a BMI of 27.8 or more for
men and 27.3 or more for women.  The prevalence of
overweight for men was lowest for those with less than 12
years of education and those with the lowest income level.
For women, the prevalence of overweight was lowest in the
highest income group.
Diabetes
In all three regions, the prevalence of diabetes was lowest
in the highest income group (men, 31 percent; women, 33
percent).  This pattern has also been observed among Mexican
Americans and non-Hispanic whites (3).  There was no clear
association between the prevalence of diabetes and
education, although among men, participants with 12 years of
education had the lowest diabetes prevalence and the
relationship seemed to be quadratic.
Albuminuria
There was a downward trend in the prevalence of macro- and
microalbuminuria with higher education in all three regions
combined.  A similar trend was observed in women in each
region.  The highest prevalence occurred among women in the
two lowest income groups.  However, in men there seemed to
be a region-specific quadratic relationship between
prevalence of albuminuria and education.
Lifestyle Pathways
Cigarette Smoking
The North and South Dakota region had the highest prevalence
of current smoking for both genders in all categories of
education and income.  The prevalence of current smoking was
lowest among men with more than 12 years of education in all
three regions, a finding similar to that for white, black,
and Hispanic men ages 45 to 64 (3).  There was a downward
trend in prevalence with higher income among men in Oklahoma
and the Dakotas, similar to the trend for Hispanic and white
men.
For women, prevalence of current smoking increased with
education levels.  In contrast, among non-Hispanic black and
white women ages 45 to 64, smoking prevalence was highest at
lower income levels (3).
Years of smoking decreased with years of education.  The
percentage of ex-smokers increased with education and income
in the Dakotas, implying that more people with higher
education quit smoking.
Alcohol Consumption
Among men in all three regions, participants in the lowest
income group had the highest prevalence of current drinking
(70 percent, 60 percent, 72 percent, and 69 percent
respectively in Arizona, Oklahoma, the Dakotas, and
overall).  The lowest prevalence in Arizona was among the
$10,000-$24,999 income group, whereas in North and South
Dakota, the lowest prevalence was among those with incomes
of $25,000 or more.  Most current drinkers in SHS were also
binge drinkers (i.e., five or more drinks per occasion).
The prevalence of binge drinking during the past year was
more than 60 percent (range, 61 to 98 percent) for all
levels of education and income.  The mean number of drinks
per week showed a decreasing trend with higher income.  Men
in the highest education and income groups had the lowest
number of drinks per week, 7 and 6 drinks, respectively.
Among women, there was an upward trend in the prevalence of
current drinking with higher education.  The prevalence was
significantly higher among women with more than 12 years of
education than those with less education.  In contrast with
the trend for men, current drinking was  highest among women
with incomes of $25,000 or more.  Although the prevalence of
alcohol consumption was highest in the highest income group,
the mean number of drinks per week was actually lowest for
women in that group.  Except in North and South Dakota, the
mean number of drinks per week decreased for women with
higher income.  The prevalence of binge drinking ranged from
38 to 88 percent.  Women in the $25,000 and over income
group binged less than those in the other income groups, but
their prevalence of binge drinking still exceeded 37
percent.
Physical Activity
In both genders and in all regions, the prevalence of "no
leisure activity during the past year" showed a decreasing
trend with higher education, regardless of whether walking
was included in leisure activities.  The mean number of
hours per week spent in leisure activities during the past
year was higher for those with more than 12 years of
education than for those with less education.  Inactivity
also decreased with higher income. The Oklahoma region had a
lower prevalence of inactivity than the other two regions.
These findings agree with reports obtained from the other
three ethnic groups (3).
Psychosocial Pathways
Marital Status and Ability to Pay Bills
In all regions and among both genders, the prevalence of
being currently married increased with higher education or
higher income; the highest prevalence was found in the
highest income group.  This uniform monotonic trend across
all income categories has also been observed in blacks and
non-Hispanic whites (3).  The ability to pay bills showed a
similar relationship with education and income.
Access to Medical Care
The mean distance to the closest clinic was shorter in
Arizona and the Dakotas than in Oklahoma.  For both genders
in Arizona, those with less than 12 years of education
tended to live farthest from any clinic.  In Oklahoma, men
in the lowest and highest income groups lived farthest from
the clinic, whereas women in the same groups tended to live
closer.
Due to the availability of community hospitals in Oklahoma,
the mean distance that participants traveled to the closest
hospital was shortest there.  Participants with the highest
education or income levels tended to travel a shorter
distance than those in the other groups.   For men in
Arizona and for women in the Dakotas, distances traveled did
not differ greatly by education or income, perhaps because
the participants in each region were using the same
hospitals on the reservation.
Acculturation and SES Factors
Native Language and Degree of American Indian Blood
Over 50 percent of the participants in the three regions who
spoke their native language had less than 12 years of
education.  More participants in Arizona (88 percent) and
the Dakotas (75 percent) than in Oklahoma (56 percent) spoke
their native language, and more of the native-language
speakers in those regions, both men and women, had low
education than native-language speakers in Oklahoma.
Approximately 40 percent of the SHS participants who spoke
their native language had a reported annual income of less
than $5,000.  This proportion was higher in Arizona and
North and South Dakota than in Oklahoma.  Except in
Oklahoma, full-blood American Indians had less education and
less income than those of mixed ancestry.
CONCLUSION
Although a direct relationship between education and income
with CVD is not clear, pathways between the two SES
indicators and CVD risk factors are evident in American
Indian populations.  Among men, participants with more than
12 years of education had the lowest prevalence of self-
reported stroke and current smoking, but they also had a
higher BMI.  Among women, a much stronger association
between education and CVD risk factors was observed.
Participants in the highest education group had the lowest
prevalence of stroke.  A downward trend with higher
education was observed for CHD, hypertension, systolic blood
pressure, and BMI.  A reverse trend was observed with
prevalence of current drinking.
In men with higher income, there was an increasing trend in
total cholesterol, LDL cholesterol, and BMI, and a
decreasing trend in HDL cholesterol.  Among women, the
highest income group had the lowest prevalence of
hypertension, and a downward trend existed between higher
income and obesity. Women with higher income seemed to be
leaner and had a better HDL lipid profile than men.
The results indicate that, in general, better education is
associated with cardiovascular health, and that higher
income benefits women more than men.
In addition to the two authors, the Strong Heart Study
Investigators include the following:
  Linda D. Cowan, Ph.D., University of Oklahoma Health
    Sciences Center, Oklahoma City, Oklahoma
  Richard Devereaux, M.D., Cornell University Medical
    Center, New York, New York
  Richard Fabsitz, M.A., National Heart, Lung, and Blood
    Institute, Bethesda, Maryland
  Barbara Howard, Ph.D., Medlantic Research Institute,
    Washington, District of Columbia
  Everett Rhoades, M.D., University of Oklahoma Health
    Sciences Center, Oklahoma City, Oklahoma
  David Robbins, M.D., Medlantic Research Institute,
    Washington, District of Columbia
  Thomas K. Wealty, Aberdeen Area Indian Health Service,
    Rapid City, South Dakota
  Jeunliang Yeh, Ph.D., University of Oklahoma Health
    Sciences Center, Oklahoma City, Oklahoma
  Ellie Zephier, M.P.H., R.D., Aberdeen Area Indian Health
    Service, Rapid City, South Dakota
REFERENCES
1.  Lee ET, Welty TK, Fabsitz R, Cowan LD, Le NA, Oopik AJ,
    Cucchiara AJ, Savage PJ, Howard BV: The Strong Heart
    Study, a study of cardiovascular disease in American
    Indians: design and methods.  Am J Epidemiol
    1990;136:1141-1155.
2.  Kaplan GA, Keil JE: Socioeconomic factors and
    cardiovascular disease: a review of the literature.
    Circulation 1993;88:1973-1998.
3.  National Heart, Lung, and Blood Institute:  Chartbook of
    U.S. National Data on Socioeconomic Status and
    Cardiovascular Health and Disease, June 1995.
4.  Coultas DB, Gong Jr H, Grad R, Handler A, McCurdy SA,
    Player R, Rhoades ER, Samet JM, Thomas A, Westley M:
    Respiratory diseases in minorities of the United States.
    Am J Respir Crit Care Med 1994;149:S93-S131.
-----------------------------------------------------------
Socioeconomic Status and Cardiovascular Disease in Rural
Populations
Thomas A. Pearson, M.D., M.P.H., Ph.D.
Rural inhabitants of the United States constitute a sizeable
but silent minority in which low socioeconomic status (SES)
and cardiovascular disease (CVD) are more highly prevalent
than in urban communities.
The definition of "rural" constitutes a surprisingly
difficult challenge, and has been approached in at least two
ways.  The U.S. Census Bureau defines urban inhabitants as
those living in places with 2,500 or more residents and
rural inhabitants as those living in places with fewer than
2,500 residents (1).  Using this definition, approximately
26.3 percent of the U.S. population is rural, and 85 percent
of these people live in places with fewer than 1,000
residents.  As a second definition, the Office of Management
and Budget defines a metropolitan statistical area (MSA) as
an urban population center and those adjacent communities
that have economic and social integration with the urban
center (2).  Approximately 23.4 percent of the U.S.
population lives in "nonmetro" areas.  These rural areas
constitute 83.8 percent of the U.S. land area and 77 percent
of its counties (1).  In either case, there seems to be good
agreement that approximately 25 percent of the U.S.
population resides in rural areas.  In 1990, this amounted
to 56,687,000 rural Americans (3).  In this paper, most data
will use the MSA versus nonmetro dichotomy to define urban
and rural.
The next issue is whether this sizeable rural population
differs from the rest of the nation with regard to SES.  It
has long been recognized that, using any of the measures of
SES, rural populations have greater proportions of persons
in the lowest SES stratum (3,4).  Poverty rates for non-MSA
areas annually exceed those of MSA areas for all regions of
the country, for all age groups, and for both sexes (5).
One may argue that pockets of extreme poverty in central
cities are hidden by grouping them with wealthy urban and
suburban populations.  Although this is certainly true,
pockets of rural poor can also be identified.  In 1987,
poverty rates for farm inhabitants (22.3 percent) exceeded
those even of central cities (19.0 percent) (4).  Likewise,
the trends in poverty favor urban areas.  Between 1980 and
1987, poverty rates for those under age 65 rose from 13.5
percent to 18.3 percent in rural areas, whereas the rates
rose only from 11.1 percent to 12.6 percent in urban areas
(4).  Thus, although 23.4 percent of the U.S. population is
rural, 29 percent or 9.2 million of the 31.7 million poor
people reside in rural areas (3).  Similar statistics are
available for the proportion of children living in poverty,
unemployment rates, and average per capita income (4).  All
point to a relationship between rurality and low SES.
Another important consideration is the interaction between
rurality and ethnicity with respect to SES.  Sizeable
numbers of Hispanics and blacks reside in rural areas of the
West and South, respectively.  More than 1.8 million blacks
and 700,000 Hispanics live in rural poverty.  The largest
group of rural inhabitants, however, is white.  Rural
whites, who constitute 35 percent of poor whites, also
constitute the vast majority of the rural poor, although
whites constitute only about half of the urban poor.
The interaction of race and rurality with low SES is further
defined by time trends in various measures of low SES, such
as poverty rates and educational attainment.  Figure 1 shows
trends from 1969 to 1989 in poverty rates for MSA and
nonmetro residents.  In every racial and ethnic group,
poverty rates are higher for nonmetro than for MSA groups.
Between 1979 and 1989, poverty rates were stable for MSA
residents, but increased slightly for nonmetro residents in
every racial/ethnic group.
-----------------------------------------------------------
Figure Missing
Figure 1.  -  U.S. Urban and Rural Poverty Rates by Race and
Ethnicity for 1969, 1979, and 1989.  Urban and rural areas
are defined as metropolitan and nonmetro areas.  Source:
USDA (3).
-----------------------------------------------------------
Income-derived definitions may not be comparable between
urban and rural residents.  However, if another definition,
educational attainment, is used, the same results are
observed.  Although substantial gains in education have been
realized in all groups, rural residents have poorer levels
of education than urban residents in every racial/ethnic
group.  Thus, by whatever measure used, race/ethnicity and
rurality appear to act independently, if not synergetically,
in their relationship with low SES.
Finally, the American public commonly equates poverty,
especially in minority groups, with urban populations.
Media coverage of unrest in the urban ghettos of the 1960s
(and the 1990s) has generally showcased the problems of the
urban poor (5).  The current crisis in urban hospitals has
continued to focus on the needs of the poor in central
cities.  The statistics, however, identify additional needs
and challenges of the rural poor.  Widely dispersed,
geographically isolated, and politically less organized than
members of urban communities, the rural poor have been
relatively silent about the detrimental impact of poverty in
their communities.
CVD Mortality Trends:  Loss of the Rural Advantage
In the 1960s and 1970s, urban rates of CVD mortality were
well documented as being higher than rural rates in studies
in the southeastern states (6) and in Puerto Rico (7).
However, more recent analyses have identified a reversal in
the trends (Table 1) (5).  Age-adjusted rates for total and
cardiac mortality can be calculated for each of the 48
states in the continental United States for as far back as
1939.  When the mortality rates are correlated with the
percent of urbanization in these states, the results show a
startling reversal of the protective effect of rurality on
total, cardiac, and cancer mortality.  Stroke mortality
appears always to have been higher in rural states.
-----------------------------------------------------------
Table Missing
Table 1.  -  Spearman Rank Correlations* Relating Age-
Adjusted Death Rates for Whites in the Continental United
States to Percent Urban**
* For these analyses, negative rates indicate rural states
had lower rates than urban states.  Positive rates indicate
that rural states had higher rates.  Values > 0.25 or less
than or equal to -0.25 were significant at p < 0.05.
**Source: Schneider and Greenberg (5), with permission.
Copyright 1992 by Rutgers, The State University.
-----------------------------------------------------------
These data lead to speculation about the cause of this
reversal in trend.  Coronary heart disease (CHD) mortality
peaked around 1968 and national declines in mortality were
well established by 1979 to 1981.  A delay in or even an
absence of that decline in rural America may be one
explanation for the data in Table 1.  Evidence for this
possibility comes from national data at the county level for
white males (Table 2) (8).  Between 1968 and 1978, the
decline in CHD mortality in nonmetro counties lagged behind
that in metropolitan areas, and from 1979 to 1985, the gap
widened even further.  As a result, CHD mortality rates for
rural white males grew to equal or exceed those for males in
MSAs in all four regions of the country.
These correlations between CHD mortality and rurality are
prone to all the fallacies and biases of any ecologic study.
Other data, however, point to the same conclusions.  For
example, in the National Longitudinal Mortality Study,
relative risks for ischemic heart disease mortality are
greater for farm-related occupations than for white collar
occupations, especially for black men ages 45 to 64 years of
age, in whom the occupation with the highest relative risk
is farm-related work.
Findings of the National Health Interview Survey from 1988
through 1993 show the same excess of rural CHD.  The
prevalence rates of ischemic heart disease reported by
inhabitants from non-MSAs were always far in excess of those
from MSAs, even when broken down by central and noncentral
city.  Thus, of the 21.5 million Americans with CHD, 6.2
million live in rural areas, and more patients with CHD live
in rural areas than in central cities.  Similar data are
seen for stroke, with rural areas overrepresented relative
to their proportion of the population.  These data are not
age-, gender-, or race-specific.  However, they do support
the thesis that CVD is more prevalent in rural than in urban
areas.
Unfortunately, most of the more recent longitudinal studies
are distinctly urban.  Most studies conducted in the 1960s
and 1970s, with the exception of the Evans County Study (6)
and the Puerto Rico Heart Study (7), were based in medium-
to-large cities or contained relatively small rural
subpopulations.  The Strong Heart Study, a longitudinal
study of American Indians, contains substantial numbers of
rural residents, but it is unclear if the composition of the
study population lends itself to the examination of urban-
rural differences.
-----------------------------------------------------------
Table Missing
Table 2.  -  Average Annual Percent Decline in CHD by Region
and Urbanization Level, 1968-78 and 1979-85
Source: Ingram and Gillum (8).
-----------------------------------------------------------
SES Gradients in CHD:  Do They Exist in Rural America?
Many of the national surveys either do not contain sizeable
rural populations or have not analyzed the data to examine
SES gradients in rural areas.  To examine the influence of
SES on CHD and its risk factors, the data set from Health
Census '89 was examined.  Health Census '89 was a cross-
sectional survey of the entire population of Otsego County,
New York, a rural county north of the Catskill Mountains.
Over 76 percent of Otsego County's population lives in areas
with fewer than 2,500 residents.  This rural population, 98
percent white, encompasses an extraordinary range of incomes
and occupations. After mapping all residences in the county
and excluding seasonal homes and group housing (e.g.,
dormitories, institutions), field staff surveyed all 19,800
households by questionnaire.  Responses were received from
17,444 households and 44,565 people, a response rate of at
least 86.6 percent.
The survey included questions for all adults in each
household regarding demographic information, prevalent
diseases, use of preventive services, education, and
occupation.  Participants were asked if a physician had ever
told them they had heart disease.  With this used as a
definition of CHD prevalence, a sharp gradient in CHD was
observed across educational strata.  This gradient was
present in all age strata and in both men and women.
Similar gradients were observed for diabetes and cancer.
Thus, if these large gradients in SES exist in rural
populations, one logical explanation for the changing urban-
rural differences in disease rates may be the increasing
poverty in rural areas (5).
Pathways for Possible Rurality Effects on CVD
Lifestyles and Health Behaviors
Low SES is not the only risk factor presented by rurality.
Traditionally, agriculturally based rural families have
consumed a high-fat, high-calorie diet, often featuring food
grown at home.  Dairy farmers, for example, typically
consume their own whole-fat milk.  The high caloric intake
was traditionally counterbalanced by an equally high caloric
expenditure during the day and intense physical labor
required for farming, logging, and other activities.
However, mechanization of rural occupations has reduced
these levels of caloric expenditure, with resulting high
levels of obesity.  In Health Census '89, high levels of
obesity were observed, especially in young adults (Fig. 2).
The strong gradient of obesity by education level suggests
that low-SES strata have been especially prone to caloric
imbalance.  Moreover, a comparison of obesity rates between
residents of a small town (13,900 people) and rural
residents indicated that obesity rates were higher among the
rural population.
-----------------------------------------------------------
Figure Missing
Figure 2.  -  Prevalence of Obesity in Men and Women, Ages
25 to 44, in Otsego County, New York,  1989.  Data are
stratified by education level (< HS = less than high school,
HS = high school diploma, >HS = more than high school) and
by residence in a town of 13,900 (open bars) or in the
countryside (closed bars).  Obesity is defined as a self-
reported body mass index (mass/height2) of 27.8 kg/m2 in men
and 27.3 kg/m2 in women.
-----------------------------------------------------------
Isolated, rural populations with poor educational attainment
and limited literary skills may have a very different level
of reception of the health messages in video, audio, and
print media that bombard urban dwellers.  Health-promoting
organizations, including county health departments,
voluntary organizations such as the American Heart
Association, and health care providers are less visible and
more often absent in rural than in urban settings.  The
extent of health education programming in schools, churches,
and other venues may also be lower and the small single-
family businesses that characterize rural areas often do not
have worksite health promotion programs.
This lack of public health education translates into strong
gradients in deleterious health behaviors in rural areas.
For example, those in low SES strata continue to smoke at
levels virtually unchanged since the 1950s.  In Health
Census '89, more than 50 percent of adults 25 to 44 years of
age without a high school diploma were smokers, compared
with less than 24 percent of persons with education beyond
high school.  Similarly, levels of leisure time physical
activity lag among low-SES groups.  These findings all point
to a lack of effective health education messages for the
rural poor.
Access to Health Care
An important barrier to primary and preventive health
services in rural areas is the lack of health care
providers.  Rural residents are overrepresented among
persons residing in areas with health personnel shortages,
are more likely to have no usual source of care, more
frequently have to travel more than 30 minutes to their
health care provider, and have fewer physician visits per
year than the general population (4). The long waiting
period for an appointment and the extended distances needed
for travel to a provider affect all aspects of health care,
particularly the provision of preventive care such as the
detection and management of high blood pressure and
hypercholesterolemia.  In Health Census '89, the prevalence
of having been screened for blood cholesterol level was
strongly related to education level (Fig. 3).  However, in
every instance, more town residents than rural residents
received cholesterol screening.
Similarly, lower access to care given by internal medicine
or cardiology specialists may be a barrier to the diagnosis
and treatment of chronic cardiac diseases.  The poor
economic viability of rural hospitals and their frequent
closure have added to the distances rural patients must
travel to  receive either primary or specialty care (9).
From 1980 to 1987, 364 hospitals in the United States
closed, 45 percent of them in rural areas (10).
The role of rural poverty in this health care crisis has
been studied extensively.  The economic viability of a rural
community is an important determinant of its ability to
attract physicians.  Rural hospitals face a variety of
economic disadvantages, including a much higher rate of
charity care due to high rates of uninsured patients (9).
Also, the rural poor often do not request (or receive)
public assistance such as housing, food stamps, and Medicaid
(4).  Lack of health insurance not only serves as a barrier
to their seeking care but also decreases their ability to
reimburse providers and hospitals for care received.  Health
Census '89 identified low rates of preventive services such
as cholesterol screening for those without insurance or with
Medicaid (11).  Thus, a chain of causality can be
hypothesized in which rural poverty leads to reduced access
to primary care and hospital services, which in turn leads
to reduced ability to prevent and treat CVD and its
sequelae.
-----------------------------------------------------------
Figure Missing
Figure 3.  -  Prevalence of Blood Cholesterol Screening in
Men and Women, Ages 45 to 64, in Otsego County, New York,
1989.  Data are stratified by education level and residence
in a town of 13,900 (open bars) or in the countryside
(closed bars).
-----------------------------------------------------------
The importance of early identification of symptoms and
prompt transport to a medical facility and intervention
(e.g., defibrillation, thrombolysis) to improve the natural
history of acute CHD has been well described.  The closure
of rural hospitals increases the distance to an acute care
facility for many residents and can add significantly to
delays in intervention.  Possible additional barriers to
prompt treatment include lower awareness of symptoms in
rural populations, the lack of emergency (911) telephone
systems, poor roads, and frequently hostile weather
conditions (12).  Moreover, emergency personnel in rural
areas are often volunteers with minimal training in cardiac
care and infrequent opportunities to use their skills.
Community hospital emergency personnel likewise may have
minimal training for the management of acute cardiac
emergencies.  Little is known about strategies to improve
the promptness of emergency treatment in rural areas.
Conclusions
Rurality can be seen as a CVD risk factor independent of SES
and race/ethnicity.  First, the association between rural
residence and low SES is established and shown to be
additive to the association between race/ethnicity and SES.
The large number of rural poor underscores their importance
as a high-risk subgroup.  Second, there has been a dramatic
reversal in the association between rural residence and CHD
between the 1950s and the 1980s.  Third, the most obvious
pathway through which rurality may be related to CHD is its
association with low SES; that is, the increasing poverty of
rural areas leads to increasing rates of CHD.  Detrimental
trends in health behaviors, a lack of health promotion
messages, a crisis in access to rural primary health care,
and limitations in rural emergency medical systems are all
potential causes of the recent excess of CHD mortality in
rural areas.
Clearly, a great deal needs to be learned before this excess
in CHD in the rural poor can be fully understood.
Potentially fruitful areas of research include the
following:
*  Population-based studies in which both urban and rural
   populations are surveyed for CVD incidence and mortality.
   It may be necessary to design such studies to include
   sizeable groups of minorities living in rural areas.
*  Targeted surveys to compare prevalence, knowledge,
   attitudes, and beliefs about CVD and its risk factors in
   urban and rural populations with variable SES.
*  Community intervention programs to evaluate health
   education strategies or develop new ones specifically for
   the rural poor.
*  Identification of alternate care systems to provide
   preventive care to the rural poor.
*  Studies on programs to reduce delays in emergency cardiac
   care in rural communities characterized by high CVD
   mortality and high levels of poverty.
REFERENCES
1.  Hewitt M:  Defining "rural" areas.  Impact on health
    care policy and research.  In Health in Rural North
    America.  The Geography of Health Care Services and
    Delivery, edited by WM Gesler and TC Ricketts.  New
    Brunswick, New Jersey:  Rutgers University Press, 1992,
    pp. 25-54.
2.  U.S. Department of Commerce: Statistical abstract of the
    United States 1988, 108th ed.  Washington, D.C.:  U.S.
    Government Printing Office, 1988.
3.  Economic Research Services:  Rural Conditions and
    Trends. U.S. Department of Agriculture, Vol. 4, 1993.
4.  Rowland D, Lyons B:  Triple jeopardy: rural, poor, and
    uninsured.  Health Services Res 1989;23:975-1004.
5.  Schneider D, Greenberg MR:  Death rates in rural
    America, 1939-1981.  Convergence and poverty.  In Health
    in Rural North America.  The Geography of Health Care
    Services and Delivery, edited by WM Gesler and TC
    Ricketts.  New Brunswick, New Jersey:  Rutgers
    University Press, 1992, pp. 55-85.
6.  Keil J, Saunders DE: Urban and rural differences in
    cardiovascular diseases in blacks.  Cardiovasc Clin
    1991;21:17-28.
7.  Gordon T, Garcia-Palmieri MR, Kagan A, Kannel WB,
    Schiffman J:  Differences in coronary heart disease in
    Framingham, Honolulu, and Puerto Rico.  J Chron Dis
    1974;27:329-344.
8.  Ingram DD, Gillum RF: Regional and urbanization
    differentials in coronary heart disease mortality in the
    United States, 1968-85.  J Clin Epidemiol
    1989;42:857-868.
9.  Moscovice IS:  Rural hospitals: a literature synthesis
    and health services research agenda.  Health Services
    Res 1989;23:891-930.
10. DeFriese GH, Wilson G, Ricketts TC, Whitener L: Consumer
    choices and the national rural hospital crisis.  In
    Health in Rural North America.  The Geography of Health
    Care Services and Delivery, edited by WM Gesler and TC
    Ricketts.  New Brunswick, New Jersey:  Rutgers
    University Press, 1992, pp. 200-225.
11. Pearson TA, Spencer M, Jenkins P:  Who will provide
    preventive services?  The changing relationships between
    medical care systems and public health agencies in
    health care reform.  J Public Health Mgmt and Practice
    1995;1:16-27.
12. Rutledge R, Ricketts TC, Bell E:  Emergency medical
    services in rural areas.  In Health in Rural North
    America.  The Geography of Health Care Services and
    Delivery, edited by WM Gesler and TC Ricketts.  New
    Brunswick, New Jersey:  Rutgers University Press, 1992,
    pp. 226-248.
-----------------------------------------------------------
Socioeconomic Status, Cardiovascular Risk Factors, and
Cardiovascular Disease: Findings on U.S. Working Populations
Jeremiah Stamler, M.D., Rose Stamler, M.A.,
Daniel Garside, Kurt Greenlund, Ph.D.,
Sujata Archer, Ph.D., James D. Neaton, Ph.D.,
Deborah N. Wentworth, M.P.H.
Few papers in the literature address the relationship of
socioeconomic status (SES) to the major cardiovascular
diseases (CVD) and CVD risk factors in U.S. employed
populations.  In 1985, the Dupont Study reported a
differential in the decline in incident myocardial
infarction (MI) between wage and salaried male employees
between 1957 to 1959 and 1981 to 1983 (1).  Although average
annual rates for MI incidence were similar in 1957 to 1959
for these two sectors of the labor force (3.13 and 3.30 per
1,000, respectively), by 1981 to 1983 they were 2.56 and
2.06; that is, rates for wage employees were 18 percent
lower but those for salaried employees were 38 percent
lower, a decline more than twice as great.  The study of
California male physicians reported a similar SES-related
trend (2).  Between 1950 and 1954, the standardized
mortality ratio (SMR) for coronary heart disease (CHD) was
115 for California physicians compared with age-matched U.S.
white men.  In the next decades, this ratio fell
progressively.  For the periods from 1965 to 1969, 1970 to
1974, and 1975 to 1979, the SMRs for California physicians
compared with all U.S. white men were 80, 74, and 69,
respectively.  That is, CHD declined 40 percent more for
California physicians than for all U.S. white men, for whom
a decline in CHD mortality began in the 1960s.  Thus, during
the years of the general decline in the U.S. CHD death rate,
California physicians experienced a 14 percent greater
decline.  The trend for all-cause mortality was similar, so
that for California physicians life expectancy at age 25
increased by 5 years from 1950 to 1979, compared with 3
years for all U.S. white men.
CHICAGO STUDIES
Since 1957, our research group has been involved in long-
term prospective epidemiologic investigations of workplace-
based Chicago population samples (3-6).  These include the
People's Gas (PG), Western Electric (WE), and Chicago Heart
Association Detection Project in Industry (CHA) studies.
Nine cohorts of employed men and women have been under
study, totalling almost 44,000 persons:
*  PG men ages 25 to 39 and 40 to 59 years at baseline;
*  WE men ages 40 to 54;
*  CHA men ages 18 to 39, 40 to 59, and  60 to 74; and
*  CHA women ages 18 to 39, 40 to 59, and 60 to 74.
Baseline surveys of the PG and WE middle-aged men were done
in 1957 to 1959; those for PG younger men, in 1959 to 1963;
and those for the CHA cohorts, in 1967 to 1973 at 84 Chicago
area companies and organizations (6).
SES and Risk Factors at Baseline
PG Men Ages 25 to 39 and 40 to 59
There was a graded inverse relationship between education
and blood pressure (BP), both systolic and diastolic (SBP,
DBP).  Also, the greater the education level, the lower the
prevalence of cigarette smoking.  Height was directly
related to education; especially for men ages 25 to 39,
average height was progressively greater with greater
education.  In contrast to these significant associations,
body mass index (BMI)  -  weight (kg) divided by height (m)
squared  -  did not differ significantly across education
strata, nor was there clear evidence of a graded
relationship between education and serum cholesterol.
CHA Men
For all three cohorts of CHA men, as for the PG cohorts, the
higher the education, the lower the average SBP and DBP, the
lower the prevalence of smoking, and the greater the mean
height (Table 1).  Education was inversely related to BMI,
with mean BMI slightly but consistently lower in college
graduates.  For serum cholesterol, differences among
education groups were small and there was no indication of a
linear trend.
CHA Women
Again, education was inversely related to SBP, DBP,
prevalence of smoking, and BMI, and directly related to
height (Table 1).  There was no significant relationship of
serum cholesterol to education.
WE Men
Findings for the above parameters were generally concordant
with those for other cohorts.  In the WE Study, typical
eating and drinking patterns were assessed by in-depth
interview at both baseline and first annual examination in
1957 to 1958 and 1958 to 1959 (6,7).  Differences across SES
strata  -  small but statistically significant and tending
to be graded  -  were found for several macro- and
micronutrients and for alcohol.  Mean levels of dietary
total protein, animal protein, total fat, saturated fatty
acids, polyunsaturated fatty acids, dietary cholesterol,
calcium, vitamin C, riboflavin, vitamin A, and vitamin D
(8), and beta-carotene (9) were all directly related to
education level.  Intake of vegetable protein, alcohol
consumption, and dietary kilocalories were inversely related
to education.  For five WE SES strata, Keys dietary lipid
scores (10) were uniformly high and virtually identical
(range, 61.6-63.1), concordant with the almost identical
mean serum cholesterol levels of these strata.
The inverse relationship of SES to BMI and to alcohol intake
in WE men probably relates to the inverse relationship of
SES to blood pressure.  In the INTERSALT Study, which also
recorded an inverse relationship of education to BP in more
than 10,000 participants ages 20 to 59, four dietary
variables  -   higher BMI, excess alcohol intake, higher 24-
hour sodium excretion, and lower 24-hour potassium excretion
-  accounted significantly for the inverse SES-BP
relationship (11).
In the WE Study, there was a significant independent inverse
relationship between education and rise of SBP/DBP over 8
years of followup.
SES and Mortality with Long-Term Followup
-----------------------------------------------------------
Table Missing
Table 1.  -  Education and Risk Factors at Baseline*,
Chicago Heart Association Detection Project in Industry
Study
* Age-adjusted mean or percent.
-----------------------------------------------------------
PG Men
For the PG cohort ages 25 to 39 at baseline, with followup
of 29 years, age-adjusted mortality from CHD, CVD, and all
causes increased with lower education.  The relationship was
graded, and differences across education strata were
substantial  -  relative risks (RRs) were 3-fold and greater
for those with only elementary or some high school education
than for college graduates.  In Cox proportional hazards
regression analyses, with adjustment for age only and for
multiple risk factors, estimated RRs for men with 4 years
less education were 1.59 age-adjusted and 1.50 multivariate-
adjusted for CHD (Z = 2.34 and 1.97); 1.87 and 1.77 for CVD
(Z = 3.44 and 3.03); and 1.81 and 1.69 for all causes (Z =
4.61 and 3.98).  From Cox analyses for PG men ages 40 to 59
at baseline, with 31 years of followup, 4 years less
education was associated with RRs of 1.15-1.17 for CHD, CVD,
and all-cause mortality, with control both for age only and
for multiple risk factors (Z = 1.81 and 1.84 for CHD; 2.06
and 2.06 for CVD; 2.92 and 2.63 for all causes).
CHA Men
For all three cohorts, with 22-year followup, less education
was associated with higher age-adjusted mortality rates for
CHD, CVD, and all causes (Table 2).  Both age-adjusted and
multivariate-adjusted RRs with 4 years less education were
highest in younger men and lowest in older men (Table 3).
RRs decreased slightly in size with control for major CVD
risk factors.
CHA Women Ages 40 to 59 and 60 to 74
For women ages 40 to 59 at baseline, age-adjusted data
indicated an inverse relationship of education to risk of
CHD, CVD, and all-cause mortality (Tables 2 and 3).  With
multivariate adjustment, compared to age adjustment only,
RRs decreased by about one-third for CHD and CVD and by one-
fourth for all causes, but Z scores remained greater than
2.00 for CVD and all causes.  For women ages 60 to 74, there
was no evidence of a consistent relationship between
education and the three mortality end points.
-----------------------------------------------------------
Table Missing
Table 2.  -  Education and 22-Year Age-Adjusted Mortality by
Cause, Gender, and Age  at Baseline, Chicago Heart
Association Detection Project in Industry Study
-----------------------------------------------------------
Table Missing
Table 3.  -  Relationship of 4 Years Less Education to
Relative Risk of Mortality in 22 Years, by Cause, Gender,
and Age at Baseline, Chicago Heart Association Detection
Project in Industry
-----------------------------------------------------------
WE Men
With 32-year followup, age-adjusted mortality rates from
CHD, CVD, and all causes tended to be inversely related to
education in the WE men ages 40 to 55 at baseline.  In
particular, the strata with less education had higher death
rates than college graduates.  For the least educated men,
compared with college graduates, RRs were 1.67 for CHD, 1.54
for CVD, and 1.27 for all causes.  From Cox analyses, men
with 4 years less education had age-adjusted and
multivariate-adjusted RRs of 1.16 and 1.09 for CHD (Z = 1.91
and 1.09); 1.10 and 1.03 for CVD (Z = 1.45 and 0.43); 1.11
and 1.04 for all causes (Z = 2.00 and 0.70).
THE MULTIPLE RISK FACTOR INTERVENTION TRIAL (MRFIT) COHORT
Between 1973 and 1975, 361,662 men ages 35 to 57 were
screened in 18 U.S. cities for recruitment for the MRFIT.
The initial screening included standardized measurement of
serum total cholesterol, SBP and DBP, and current cigarette
use as well as two medical history questions about drug
treatment for diabetes and hospitalization for heart attack.
No SES data were collected on the individual screenees, but
1980 U.S. Census data were obtained later for race-specific
median family income by zip code of residence (12).
Income and CV Risk Factors
For both white and black men, there was a graded inverse
relationship of income to baseline SBP, DBP, and prevalence
of cigarette smoking, but mean serum cholesterol was similar
across income strata (12).
Income and 16-Year Mortality
With 16 years of followup, there was a graded inverse
relationship of  income to age-adjusted mortality from CHD,
CVD, and all causes (Table 4) (12).  For comparison between
white men in the lowest and highest income strata, Cox
analyses with age adjustment only and multivariate
adjustment yielded RRs of 1.62 and 1.39 for CHD death; 1.63
and 1.40 for CVD death; and 1.59 and 1.41 for all-cause
death (p < 0.01 for all).  A $10,000 difference in annual
income was associated with age-adjusted RR (95 percent
confidence intervals in parentheses) for each of the three
mortality end points of 1.25 (1.21-1.30), 1.26 (1.22-1.30),
and 1.26 (1.23-1.28), and multivariate-adjusted RR of 1.16
(1.12-1.21), 1.17 (1.13-1.21), and 1.18 (1.16-1.21).  For
black men, $10,000 less income per year was associated with
age-adjusted RRs of 1.32 for CHD, 1.31 for CVD, and 1.35 for
all-cause mortality, and multivariate-adjusted RRs of 1.26,
1.25, and 1.29, respectively.
-----------------------------------------------------------
Table Missing
Table 4.  -  Age-Adjusted Mortality by Income and Cause, 16-
Year Followup of White and Black Men Ages 35 to 57 at
Baseline, Multiple Risk Factor Intervention Trial
-----------------------------------------------------------
Low-Risk MRFIT Men, Income, and 16-Year Mortality
The large size of the MRFIT cohort made it possible  -  for
the first time in epidemiological research on CVD  -  to
identify a stratum with favorable levels for all major risk
factors (6).  Criteria for this low-risk designation here
are:  baseline serum total cholesterol less than 200 mg/dL,
SBP/DBP 120/80 mmHg or lower, no smoking, no history of
treatment for diabetes, and no history of hospitalization
for heart attack.  Men with all these favorable traits were
a small subset of MRFIT screenees  -  7.9 percent of higher-
income whites, 5.9 percent of lower-income whites, 4.7
percent of higher-income blacks, and 3.7 percent of lower-
income blacks.  With prevailing American lifestyles,
maintenance of low-risk status into middle age is unlikely
for all four income-ethnic groups.
Stratification based on status for all major risk factors
defines groups markedly different for average SBP/DBP and
mean serum cholesterol, as well as for prevalence of
cigarette smoking, diabetes history, and MI history (Table
5).  Thus, it was possible to go beyond analyses of the type
presented above and to explore the following questions:
What is the comparative impact of combined major risk factor
status and of SES on mortality from CHD, CVD, and all
causes?  What is the comparative impact of SES on these
mortality end points for low-risk men and for those not at
low risk?  As to the first question, at both higher and
lower income and for both whites and blacks, CHD and CVD
mortality rates were much higher for men with one or more
risk factors than for low-risk men.  RR for 16-year CHD
mortality was 5.38 for white men of higher income and 5.18
for white men of lower income.  Clearly, status with respect
to established major CVD risk factors considered together
has a quantitatively similar strong effect on long-term risk
of CHD, CVD, and all-cause mortality for both higher- and
lower-income men, white and black.
The CHD data for white men give the essence of the
interaction between lower SES and combined major risk
factors.  Low-risk higher-income men had the lowest death
rates.  In comparison with this group, the RR for low-risk
lower-income men was 1.31; for all other higher-income men,
RR was 5.56; for all other lower-income men, RR was 6.77.
Clearly, the factor that influences relative risk (and
absolute excess risk) most is unfavorable risk factor
status; lower SES (income) has a moderate synergistic
effect.  For low-risk men, CHD and CVD risk are low for both
lower-income and higher-income men.
-----------------------------------------------------------
Table Missing
Table 5.  -  CHD Risk Factors and Mortality, 16-Year
Followup by Income and Baseline Risk, MRFIT Men
-----------------------------------------------------------
DISCUSSION
The main findings reported here for SES and risk factors at
baseline are the following: graded inverse relationships of
SES to SBP and DBP and to prevalence of cigarette smoking;
little evidence of a graded relationship of SES to serum
cholesterol; a graded inverse relationship of SES to BMI in
most of the Chicago cohorts; and a graded direct
relationship of SES to height in all nine Chicago cohorts
(height and weight were not measured at first visit of the
men screened for MRFIT).
For baseline SES and long-term age-adjusted mortality from
CVD, the main findings are the following:  significant
inverse relationships of education to mortality for the PG
and CHA young adult male cohorts (age-adjusted RRs for 4
years less education of 1.74 and 1.87); smaller age-adjusted
RRs (1.15-1.53) for five of six middle-aged cohorts (CHA men
and women, PG men, and MRFIT white and black men); and an RR
of 1.16 for older CHA men.  With multivariate adjustment for
risk factors, most of these RRs were still significant, but
were smaller than with age adjustment only.
These findings on working cohorts are consistent with
similar data sets for other U.S. population samples, as is
evident from findings displayed at this conference.  The
U.S. population is generally exposed from early childhood on
to adverse primary lifestyles (poor eating habits, drinking,
smoking, inactivity), resulting in high average levels of
body mass, blood pressure, and serum cholesterol in adults.
Societally engendered differential conditioning of lifestyle
behaviors leads to even worse risk factor patterns for
lower- than for higher-SES populations.  That is, worse risk
factor patterns for lower-SES strata are an exaggerated
special case of a population-wide phenomenon  -  hence, the
population-wide CHD and CVD epidemic is aggravated for
lower-SES strata.
Low SES "adds insult to injury" not only by generating
particularly adverse primary lifestyle-related established
major risk factors, from childhood on, but also  -  probably
-  by resulting in excess exposures to other unfavorable
influences (e.g., adverse psychosocial influences at work,
home, and in the community).  Only limited data are
available on the interplay among these two sets of factors,
and valid quantification of their relative contributions is
virtually nonexistent  -  and difficult to accomplish.
In this regard, it is necessary to examine one component of
the data presented here.  With multivariate adjustment for
major risk factors, RRs of CHD and CVD mortality for lower-
vs. higher-SES strata were only moderately reduced and
remained significantly greater than 1.00 (RRs 1.17-1.37) for
7 of 10 cohorts.  Such data have been interpreted as
indicating important influences of traits other than
established major risk factors in accounting for SES-CVD
relationships.  They have also been interpreted as
indicating that established major risk factors account only
to a modest degree for these relationships.
Both these interpretations are questionable.  All
multivariate adjustments for major risk factors presented
here, and in nearly all other such analyses, are
underadjustments, for several reasons.  First, they are all
based on only one measurement per person of each major risk
factor.  Methods for measuring key risk factors such as
blood pressure and serum cholesterol may have limited
reliability and reproducibility, resulting in
misclassification, the regression dilution bias problem
(13), with consequent underadjustment.  Second, multivariate
adjustment gives only a limited one-time picture of
exposures that operate from childhood on to produce their
effects over decades, varying over time for different
people.  Again, the result is regression dilution bias and
underadjustment for influences of these major factors on
relative risks.
In this regard, the consistent direct relationship of height
to SES in all of the Chicago cohorts may be relevant, given
recent research indicating that undernourishment in middle
to late gestation, leading to disproportionate fetal growth,
can influence adult patterns of major risk factors and of
CHD in middle age (14).  Nutrition in utero and in early
postnatal life may also influence adult height, which
therefore may be a marker of more adverse gestational and
neonatal exposures for lower- than higher-SES strata,
affecting their CHD and CVD risk in addition to, and
independent of, the adverse lifestyles prevalent among
lower-SES strata.  Furthermore, these multivariate-adjusted
RRs do not include dietary composition, itself an
independent major risk factor (15), nor do they include
physical inactivity at work and leisure.  Again, the result
is underadjustment for major risk factors.
The analyses made possible by the extraordinarily large size
of the MRFIT cohort are unequivocal and reveal the
importance of the established major risk factors in the
etiology of epidemic CHD and CVD in the adult population
overall, in both lower- and higher-SES strata.  For the
small proportion ( less than 10 percent) of men with
favorable baseline status for all risk factors, regardless
of SES level, CHD and CVD death rates are very low and do
not account for a high proportion of total deaths.  This is
in marked contrast to the situation for men with one or more
of the major risk factors at baseline.  Among these men, who
make up the great majority  -  over 90 percent of the
population  -  and have several-fold greater risk (whether
lower or higher SES, white or black), components of lower
SES apparently synergize significantly with adverse major
CVD risk factors to increase CVD risk further by about 25
percent.  Whatever the specific pathways for this further
aggravation of risk, the key point on the etiology of
epidemic CHD and CVD is the lesson of the MRFIT low-risk
men:  Absent all major risk factors, there is no epidemic
CHD or CVD.
This overwhelming message from the MRFIT data has strong
practical implications for health promotion for Americans of
all SES levels and all ethnic backgrounds:  Primary
prevention of the major adverse lifestyles and lifestyle-
related risk factors beginning early in childhood  -  along
with their effective sustained control when primary
prevention has not been achieved  -  is the key to ensuring
further declines in CHD and CVD rates and ending the CHD and
CVD epidemic (16).  For lower-SES strata of all ethnicities,
strategic emphasis and sustained effective action to achieve
this goal  -  and to overcome special obstacles in the way
-  are a particular challenge that must be met if overall
declines in CHD and CVD rates are to be maintained and
accelerated.
REFERENCES
1.  Pell S, Fayerweather WE: Trends in the incidence of
    myocardial infarction and in associated mortality and
    morbidity in a large employed population, 1957-1983.  N
    Engl J Med 1985;12:1005-1011.
2.  Enstrom JE: Trends in mortality among California
    physicians after giving up smoking: 1950-79. BMJ
    1983;286:1101-1105.
3.  Stamler J:  Lectures on preventive cardiology, New York:
    Grune and Stratton, 1967.
4.  Dyer AR, Stamler J, Shekelle RB, Schoenberger J:  The
    relationship of education to blood pressure:  findings
    on 40,000 employed Chicagoans.  Circulation
    1976;54:987-992.
5.  Liu K, Cedres LB, Stamler J, Dyer A, Stamler R, Nanas S,
    Berkson DM, Paul O, Lepper M, Lindberg HA, Marquardt J,
    Stevens E, Schoenberger JA, Shekelle RB, Collette P,
    Shekelle S, Garside D:  Relationship of education to
    major risk factors and death from coronary heart
    disease, cardiovascular diseases, and all causes:
    findings of three Chicago epidemiologic studies.
    Circulation 1982;66:1308-1314.
6.  Stamler J, Dyer AR, Shekelle RB, Neaton J, Stamler R:
    Relationship of baseline major risk factors to coronary
    and all-cause mortality, and to longevity:  findings
    from long-term followup of Chicago cohorts.  Cardiology
    1993;82:191-222.
7.  Paul O, Lepper MH, Phelan WH, Dupertuis GW, MacMillan A,
    McKean H: A longitudinal study of coronary heart
    disease.  Circulation 1963;28:20-31.
8.  Greenlund KJ, Stamler J, Dyer AR, Archer S, Daviglus M,
    Shekelle RB:  Socioeconomic status, smoking status and
    nutrient intake: the Chicago Western Electric Study.
    Submission pending.
9.  Pandey DK, Shekelle R, Selwyn BJ, Tangney C, Stamler J:
    Dietary vitamin C and b-carotene and risk of death in
    middle-aged men. The Western Electric Study.   Am J
    Epidemiol 1995;142:1269-1278.
10. Keys A, Anderson JT, Grande F: Serum cholesterol
    response to changes in the diet. I. Iodine value of
    dietary fat versus 2S-P.   II. The effect of cholesterol
    in the diet.  III. Differences among individuals.  IV.
    Particular saturated fatty acids in the diet. Metabolism
    1965;14:747-758, 759-765, 766-775, 776-787.
11. Stamler R, Shipley M, Elliott P, Dyer A, Sans S, Stamler
    J, on behalf of the INTERSALT Cooperative Research
    Group: Higher blood pressure in adults with less
    education:  some explanatory factors.  Findings of the
    INTERSALT Study.  Hypertension 1992;19:237-241.
12. Smith GD, Neaton JD, Wentworth D, Stamler R, Stamler J:
    Socioeconomic differentials in mortality risk among men
    screened for the Multiple Risk Factor Intervention
    Trial: I.  White men. II. Black men. Am J Public Health
    1996;86:486-496, 497-504.
13. MacMahon S, Peto R, Cutler J, Collins R, Sorlie P,
    Neaton J, Abbott R, Godwin J, Dyer A, Stamler J:  Blood
    pressure, stroke, and coronary heart disease.  Part 1,
    Prolonged differences in blood pressure:  prospective
    observational studies corrected for the regression
    dilution bias.  Lancet 1990;335:765-774.
14. Barker DJP: Fetal origins of coronary heart disease.
    BMJ 1995;311:171-174.
15. Stamler J, Shekelle R: Dietary cholesterol and human
    coronary heart disease.  The epidemiologic evidence.
    Arch Pathol Lab Med 1988;112:1032-1040.
16. National Heart, Lung, and Blood Institute:  Report of
    the Task Force on Research in Epidemiology and
    Prevention of Cardiovascular Diseases.  Bethesda,
    Maryland:  U.S. Department of Health and Human Services,
    National Institutes of Health, 1994.
-----------------------------------------------------------
Psychosocial Pathways Linking SES and CVD
James S. House, Ph.D.
David R. Williams, Ph.D.
A strong association between socioeconomic status (SES) and
cardiovascular disease (CVD) has been established in both
cross-sectional and prospective studies.  There are
suggestions of gender and racial/ethnic variation in SES
differences in CVD, and strong evidence exists that while
lower-SES groups have been characterized by higher morbidity
and mortality from all causes in most populations for at
least a century, the currently observed excess of CVD
morbidity and mortality at lower SES levels  is a relatively
new phenomenon.  In the early 20th century, CVD morbidity
and mortality  in the economically most developed nations
were more prevalent at higher SES, but in the past 30-50
years, low-SES groups in these countries have borne the
greater CVD burden.  This secular trend is important for
understanding the pathways through which SES leads to CVD.
Significant SES differences in access to preventive and
therapeutic medical care for CVD and other diseases clearly
continue to exist in the United States  -  and perhaps even,
to a lesser degree, in countries with programs of national
health insurance or health services.  However, a variety of
evidence indicates that access to medical care explains only
a small portion (perhaps less than 10 percent) of the
currently observable SES differences in CVD, just as changes
in medical care have accounted for only a minor part of the
dramatic declines in CVD morbidity and mortality of the past
25 years (1,2).  Examples include the changing SES gradient
in CVD and the relative imperviousness of the current SES
gradient in CVD to the introduction of national health care
(e.g., in the United Kingdom) and insurance (e.g., in
Canada).
Increasing evidence shows that all or most of the major
physiological variables (e.g., diabetes, blood pressure,
blood lipids, blood glucose)  and behavioral or lifestyle
factors (e.g., smoking, alcohol consumption, diet, body
mass, and physical activity) for CVD are differentially
distributed by SES.  Low-SES groups tend to have higher
levels of each of these risk factors, especially the
psychosocial ones.  These variables appear to play a larger
role than medical care in explaining both recent declines in
CVD and SES differences in CVD, but controlling for them
still accounts for only a moderate portion (about 25
percent) of observed SES differences in CVD (3).
Thus, access to medical care and almost all of the
conventional CVD risk factors relate to SES in a way that is
consistent with the observed excess of CVD in lower SES
strata. However, multivariate analysis indicates that they
may in combination account for or explain only about one-
third of the observed SES differences in CVD morbidity and
mortality.  A growing body of research over the past 25
years suggests that a range of other psychosocial variables
may explain the remaining two-thirds of the relationship
between SES and CVD.  In order to determine the contribution
of these variables to the SES-CVD relationship, it is
important to consider what evidence is necessary, how much
evidence we now have, what future research is needed, and
the  implications of these considerations for research and
public health policy.
Psychosocial Variables as Pathways Between SES and CVD
To establish that any psychosocial variable is a pathway
explaining the impact of SES on CVD  requires four kinds of
evidence:
*  Evidence, especially from prospective studies, that the
   variable is a risk factor for CVD morbidity and
   mortality;
*  Evidence that the variable varies by SES in a manner that
   may account for or explain the relationship of SES to CVD
   (i.e., higher levels of risk should characterize lower-
   SES groups);
*  Evidence that controlling for the variable reduces the
   relationship between SES and CVD;
*  Logical or empirical evidence that the variable is caused
   or determined by SES, not by some third factor that
   produces a spurious association between the variable and
   CVD.  The psychosocial variable, in turn, must cause or
   determine CVD through plausible biobehavioral mechanisms.
Psychosocial Factors as Potential Pathways Between SES and
CVD
A variety of psychosocial variables have been proposed as
potential additional pathways between SES and CVD.  For all
those reviewed here, evidence exists that they relate to SES
in a manner that might account for the SES-CVD relationship.
However, the extent to which each has been already
established as a risk factor for CVD varies and the extent
to which they have been clearly shown to account for some
portion of the SES-CVD relationship varies even more.  In
most cases, plausible confounding factors that might produce
a spurious association between the psychosocial variable and
either CVD or SES have been appropriately controlled, and
the necessary causal ordering and mechanisms among the
variables are plausible.  However, as in any nonexperimental
research, the search for variables that produce spurious
relationships is never complete, and must be evaluated
largely in terms of how plausible the existence of currently
unmeasured, unevaluated, or unknown confounding factors is.
Evidence for CVD Risk Factor Status
As in the case for more conventional risk factors, the key
evidence in establishing these psychosocial variables as CVD
risk factors comes from prospective studies.  Such studies
are either ongoing community and national studies that
measured indicators of psychosocial risk factors even before
they were identified as putative risk factors, or newly
initiated studies that tend to be more limited in scope or
duration.
Type A behavior and anger/hostility.  Type A behavior was
the first major psychosocial variable to be established as a
risk factor for CVD (4).  Subsequent research, however,
suggests that the key aspect of Type A responsible for its
impact on CVD is a chronic disposition toward anger or
hostility, and this disposition has been quite compellingly
established as a risk factor for CVD (5).
Lack of social relationships and supports.  In the past 20
years, the relative lack of social relationships or supports
in circumstances such as social isolation has consistently
been found to constitute a significant risk factor for all-
cause mortality (6).  In all studies where CVD deaths could
be isolated, social relationships were as predictive of CVD
as they were of other major causes of death and all-cause
mortality.
Lack of personal efficacy/control.  A variety of evidence
suggests that the lack of a sense of personal
efficacy/control is associated with poor general and
cardiovascular health and is predictive of all-cause and CVD
mortality (7).  However, broad community or national
prospective studies such as those available for Type
A/anger/hostility and social supports are scarce for this
variable and constitute a major research need.
Depression/negative affect.  Findings from the past 10 years
increasingly suggest that depression or negative affect is a
risk factor for CVD and probably for other diseases as well.
This prospective research is probably at least as abundant
as that for personal efficacy/control, but has largely been
limited to very selective samples, often of patients with
coronary heart disease (5).  Again,  broader community or
national prospective studies are needed to study the impact
of depression and negative affect on CVD and other diseases.
Initial results in this regard support the risk factor
status of depression (8).
Acute and chronic stress.  The study of "life events" was a
major impetus for research on the relationships of stress
and psychosocial factors to health.  Early studies linked
the occurrence of life events to increased risk of physical
and mental disorders, albeit often relatively mild or
transient disorders.  Later work showed that major negative
events are the ones responsible for these associations, and
also demonstrated that such events can be predictive of CVD
and other forms of morbidity and mortality (9).  Again,
evidence from broader community and national prospective
studies is still lacking and should be a major direction for
future research.
Conceptual and empirical analysis clearly suggest that
chronic stress or deprivation caused by lack of income or
chronic problems in work, marriage, or parenting  may be at
least as important a determinant of health as acute or life
event stressors.  Recent developments in stress measurement
highlight the need to broaden the assessment of stress
beyond life events and chronic stressors.  This research
indicates that, independent of the effects of recent life
events and chronic stressors, other sources of stress such
as childhood traumas, earlier adult life events, daily
hassles, and even nonevents (desired events that fail to
occur) can affect physical and mental health.  Moreover,
this comprehensive measurement of stress accounts for
substantially more variability in health status than
previous studies of stress have suggested (10).  This full
range of stress variables needs to be incorporated into
research on the relationship between SES and CVD.
Finally, there is new interest in characterizing the
stressfulness or deprivation of areas as well as individuals
and evaluating their impact on all forms of health.  This is
another direction for future CVD research (8).
Evidence for SES Determination of Psychosocial Risk
Although the evidence linking putative psychosocial risk
factors to CVD and other forms of morbidity and mortality is
somewhat variable, relationships of these psychosocial risk
factors to SES are remarkably consistent.  As with more
conventional CVD risk factors, it is almost always the case
that lower-SES groups are exposed to more psychosocial risk.
This holds for education and other SES indicators that are
clearly antecedent to the psychosocial risk factors, and for
income and other SES variables that are more proximal to the
psychosocial risk variables, yet probably also antecedent to
them.
-----------------------------------------------------------
Figure Missing
Figure 1.  -  Psychosocial Risk Factor Status in U.S.
Residents, Ages 45 to 64, by Education and Income. Hostility
data are taken from the l984-86 MMPI-II Restandardization
Study.  Data for other variables come from the l986
Americans' Changing Lives Study, a national probability
sample survey conducted by the University of Michigan.
-----------------------------------------------------------
Figure 1 shows that indicators of each of the major
psychosocial variables just discussed vary almost exactly as
expected by both education and income among the U.S.
population, 45 to 64 years of age.  Results tend to be
similar for other age groups, but weaker for some variables
at older ages (11).
The prevalence of each of the putative  psychosocial risk
factors in Figure 1 is always greatest among those with the
lowest level of education or income and almost always least
among those with the highest level of education and income.
The rate ratios of the lowest education and income level to
the highest levels range from a low of 1.1 to a high of 3.8,
and average around 2.0.  Thus, as with the more conventional
biomedical and lifestyle/behavioral risk factors, the
putative psychosocial risk factors tend to be more prevalent
in lower-SES groups.
Evidence That Psychosocial Risk Factors Help Explain SES-CVD
Relationship
Too few studies, especially prospective ones, have evaluated
the ability of these various psychosocial risk factors,
taken singly or together, to explain the relationship of SES
to CVD or other health outcomes.  Several studies, however,
find that controlling for a broad range of these variables
along with physical environmental exposures and more
conventional risk factors can explain a substantial portion
of the relation of SES to CVD or other health outcomes
(11,12).  These results should be considered quite
preliminary, though promising and consistent with Redford
Williams' model for explaining the relationship of SES to
CVD (13).  More prospective studies of large community
populations are necessary to measure the individual and
combined contributions of a broad array of psychosocial,
physiological, and behavioral risk factors to the
relationships between SES and the incidence and course of
CVD.
Spurious Associations
It is plausible that SES shapes or determines exposure to
almost all risk factors for CVD.  This is especially true
for education, which in most adult populations is completed
well before the assessment of risk factors.  Greater
potential for reciprocal causality exists between more
contemporaneous measures of SES such as income and adult
health or risk factor measures, but a variety of evidence
suggests that causality generally flows from SES to risk
factors to morbidity and mortality (3).
Perhaps the main challenge to this model of causal pathways
lies in the argument that genetic factors, environment, or
their interactions early in life determine the later life
trajectory of both socioeconomic attainment and health.
Only long-term longitudinal studies can resolve these
concerns.  At this point it appears that although genes and
environmental conditions in early life can and do affect SES
and health in later life, these effects tend to be smaller
and diminishing over the life course compared to more
proximal or contemporaneous SES, psychosocial, or biomedical
influences.  Moreover, there is relatively little evidence
to suggest that such genetic or early life variables can
account for the observed relationships of SES to
psychosocial risk factors and CVD or other health outcomes
in middle or later life (3,12).  The need remains, however,
for more and better research on these issues, especially on
gene-environment interactions over the life course and the
ways in which early life deprivations or trauma may affect
SES, risk factors, and CVD in later life.
Implications
The psychosocial risk factors discussed here, and others
that remain to be identified, are critical to understanding
the pathways linking SES  to CVD and other health outcomes.
For all of these psychosocial variables, plausible
biobehavioral mechanisms have been posited to explain their
effects on CVD or other health outcomes (3,5,6).  However,
it is important to recognize that with or without full
understanding of these biological pathways, SES and
associated psychosocial risk factors remain important
determinants of CVD and other health outcomes, and hence are
important potential avenues for efforts at CVD prevention
and control.  For example, we do not yet fully understand
the biological mechanisms by which cigarette smoking
produces CVD morbidity and mortality, but we have been able
to reduce smoking and hence have a significant preventive
effect on CVD and other health problems.
Most important, SES is a kind of "master status" that
influences exposure to almost all major physiological,
behavioral, and psychosocial risk factors for CVD. Thus, we
need to examine the role of SES as a "fundamental cause" of
CVD (14).  As such, changes in the SES of individuals or
larger subgroups of the population could result in the
simultaneous reduction of a broad array of risk factors and
hence diseases, as general improvements in nutrition and
public sanitation have done.  Addressing these broad and
fundamental or "upstream" determinants of health has the
likely advantage of affecting not only current or known risk
factors but unknown or future ones as well.  Thus, for
example, as CVD has become a more important cause of
morbidity and mortality and its risk factors better
understood, persons of higher SES have been increasingly
able and likely to reduce their exposure to these risk
factors and hence to CVD.
The SES of individuals and groups can and does change in
response to unplanned or natural SES cycles or events and as
a result of social policy.  The greater success of many
other industrialized countries, relative to the United
States, in reducing SES deprivation and inequality has been
posited as a major reason that population health and life
expectancy in those countries has come over the last several
decades to improve more rapidly and reach higher absolute
levels than in this country, despite the fact that none of
the other countries approach the United States in either
spending for or advances in medical care and biomedical
research (15).  Thus, SES policy may increasingly be a major
instrument of health policy.  Both researchers and public
health policy makers must pay increasing attention to
understanding the pathways by which SES, or changes in SES
at the level of both individuals and populations, affects
CVD.  This knowledge will serve as the basis of preventive
efforts to reduce not only risk factor pathways but also SES
deprivation and inequality.
REFERENCES
1.  Adler NE, Boyce T,  Chesney MA, Folkman S, Syme SL:
    Socioeconomic regularities in health:  no easy solution.
    JAMA 1993;269:3140-3145.
2.  Traven ND, Kuller LH, Ives DG, Rutan GH, Pepper JA:
    Coronary heart disease and sudden death: trends and
    patterns in 35 to 44 year old white males.  Am J
    Epidemiol 1995;142:45-52.
3.  Kaplan GA, Keil JE: Socioeconomic factors and
    cardiovascular disease: a review of the literature.
    Circulation 1993;88:1973-1993.
4.  Review Panel on Coronary-Prone Behavior and Coronary
    Heart Disease: Coronary-prone behavior and coronary
    heart disease: a critical review.  Circulation
    1981;63:1199-1215.
5.  Scheier MF, Bridges MW:  Person variables and health:
    personality predispositions and acute psychological
    states as shared determinants for disease. Psychosomat
    Med 1995;57:255-268.
6.  House JS, Landis K, Umberson D:  Social relationships
    and health. Science 1988;241:540-541.
7.  Rodin  J:  Aging and health: effects of the sense of
    control.  Science l986;233:1271-1276.
8.  Kaplan GA:  Where do shared pathways lead?  Some
    reflections on a research agenda. Psychosomat Med
    1995;57:208-212.
9.  Theorell TGT: Review of research on life events and
    cardiovascular illness. Adv Cardiol 1982;29:140-149.
10. Tyrner RJ, Wheaton B, Lloyd DA:  The epidemiology of
    social stress.  Am Soc Rev 1995;
    60:104-125.
11. House JS, Lepkowski JM, Kinney AM, Mero RP, Kessler RC,
    Herzog AR:  The social stratification of aging and
    health.  J Health Soc Behav 1994;35:213-234.
12. Lynch JW, Kaplan GA, Cohen RD, Tuomilehto J, Salonen JT:
    Do known risk factors explain the relationship between
    socioeconomic status, risk of all-cause mortality,
    cardiovascular mortality, and acute myocardial
    infarction?  l995; submitted for publication.
13. Williams RB: Socioeconomic inequalities, health, and
    disease:  an integrative theoretical review of potential
    neurobiological, psychosocial, biobehavioral, and
    cellular/molecular mediators.  l995; under review.
14. Link B, Phelan J: Social conditions as fundamental
    causes of disease.  J Health Soc Behav  l995; extra
    issues: 80-94.
15. Wilkinson RG: National mortality rates:  the impact of
    inequality? Am J Pub Health l992;82:1082-1084.
-----------------------------------------------------------
Stress, Work, Social Supports, and Gender in Relation to
Cardiovascular Disease
Kristina Orth-Gomer, M.D., Ph.D.
Because traditional risk factors explain only a portion of
coronary heart disease (CHD) risk, other less well
established CHD risk factors, including social,
psychological, and behavioral factors, are under
investigation. Stressors in work and in social life, for
example, are important psychosocial contributors to CHD risk
(1,2).  The combination of high demand and low control at
work is particularly harmful.  Lack of social support and
deficiencies in the social network seem to be strong risk
factors for new CHD events and for mortality after a heart
attack (2).
The roles of psychosocial risk factors have been
investigated more extensively in men than in women (3).  The
purpose of this paper is to address the relative importance
of psychosocial and traditional CHD risk factors and explore
their relationship to socioeconomic status (SES) and gender.
Psychosocial Work Strain
Karasek originally defined job strain according to a model
that combined psychological demands with decision latitude
at work (1).  According to his hypothesis, the worst
possible combination for adverse health effects was high job
demand with low job decision latitude, whereas the best
combination was low demand with high decision latitude.  The
other two combinations in this model were assigned
intermediate levels of risk.
A large number of cross-sectional, case-control, and cohort
studies have examined the validity of this hypothesis for
CHD outcome variables.  Most of these studies show definite
effects of job strain on all-cause mortality, CHD mortality,
and incidence of myocardial infarction (MI).  Schnall and
Landsbergis have found effects of similar magnitude and
consistency across outcome variables among male and female
working populations in response to job strain (4).  However,
most studies have focused on northern European populations.
The role of ethnic and cultural influences on the
relationship is relatively unknown.
Similarly, the role of low SES in these associations remains
controversial. The idea that high job strain equals low SES
is often expressed. According to Karasek's hypothesis,
however, low-status jobs as assessed by occupational grade
can be either high demand/low decision latitude or low
demand/low decision latitude occupations, also referred to
as high-strain active work and low-strain passive work,
respectively (1).
In an ongoing large-scale population study, comprising over
11,000 men and women living in Malmo, South Sweden, high-
strain jobs were found among 10 percent of white collar men
and 35 percent of blue collar men.  Corresponding
differences between white and blue collar women were almost
equally strong, 17 percent versus 38 percent.  A similar
social class gradient was evident for low-strain, passive
jobs: 12 percent of white collar men had such jobs as
compared with 30 percent of blue collar men.  A social
gradient in passive work was also found in women: 18 percent
of white collar women as compared to 35 percent of blue
collar women had such jobs.  Thus it seems that SES is
mainly associated with lack of decision latitude and control
over work, whereas the work strain associated with increased
CHD risk is characterized by both high demand and low
control.  In fact, many studies that have controlled for SES
through such factors as educational level have still shown a
significant effect of job strain on CHD risk (4).  Part of
the risk, in particular in relation to lack of control, is
dependent on low SES.
Social Supports in Men
Lack of social support is defined primarily as a lack of, or
possession of relatively few, social contacts among family,
friends, coworkers, and neighbors.  Several studies from the
United States and Scandinavia have shown, using quantitative
measures, that men with few social contacts are prone to die
earlier than men with an extended network. Some of the
studies have found lack of social support to be almost as
strong a predictor of CHD mortality as of all-cause
mortality (5).
In the Swedish Survey of Living Conditions, 17,400 men and
women were interviewed about quantitative aspects of their
social networks and then followed for 6 years.  For both men
and women, those with few social contacts experienced excess
mortality risk from cardiovascular disease (CVD). After age,
smoking, lack of exercise, low education, unemployment, and
presence of hypertension or CVD at entry were taken into
account, subjects in the lowest third of the social network
index had an excess CHD mortality risk of 50 percent.  Thus
it seems that both men and women benefit from having a
certain crucial number of social contacts (6).  However, the
effects of social network on outcome measures were modest
and nonspecific.
In our attempt to understand these relationships, we asked
whether the quality and function of the contacts are more
important than the number of available persons in the
network or the frequency of interaction with network
members. We wanted to know whether these contacts are
actually supportive or whether they are perhaps also
demanding and stressful.  Few studies have linked functional
measures of social support and prospective prediction of CVD
end points.
We examined the following dimensions of social support:
*  emotional support or attachment, usually provided by
   close friends or family members;
*  tangible support (practical help);
*  appraisal support (good advice and help for proper
   recognition and estimation of problems and difficulties);
   and
*  the need to belong to groups of people with whom one
   shares interests and values.
The last three functions are usually provided by the
extended social network, whereas emotional support is
typically found within the family and among close friends
(7).
The studies of 50-year-old men born in Gothenburg are well
known and respected for their representativity,
methodological accuracy, and conclusiveness.  Therefore, it
is particularly useful to examine this study group in terms
of socially supportive functions to determine whether they
predict the incidence of MI in previously healthy middle-
aged men.  Lack of social integration  -  the extended
network functions that provide guidance, advice, practical
help, and sense of belonging  -  had the strongest effect on
MI risk and was associated with a 3-fold higher incidence of
MI.
It is perhaps not surprising that these functions were
highly correlated with social class.  Men at higher
occupational levels had more support and were better
socially integrated.  Only 12 percent of men with higher-
level nonmanual occupations had poor social integration, as
compared with 34 percent of unskilled manual laborers.
By contrast, emotional support and attachment  -  the very
close emotional relationships that provide comfort, trust,
love and self-esteem  -  were only marginally predictive of
MI in these men.  The social gradient for attachment was
small and nonsignificant.  However, a smaller group of men
(23 percent) really lacked this kind of support and had a
moderate increase in MI risk (2).
Social Supports in Women
The relationships between social support and CHD risk
derived from large-scale population studies are more
ambiguous for women than for men (5).  In the Swedish Survey
of Living Conditions, women were as much in need as men of a
basic number of contacts for their survival (6). The same
was found in the Alameda County Study in California, where
women who lacked social ties had an excess mortality risk
that was slightly higher than that of men (8).  Most of the
participants in these studies were from urban or
cosmopolitan areas.  In contrast, rural women in the North
Karelia Study in eastern Finland and the Evans County Study
in Georgia did not seem to be endangered if they had smaller
networks and fewer contacts.  Both of these populations are
characterized by stable living conditions and well-defined
female roles in society (9,10).  It may be that women who
lead a more unstable life and who are subjected to more
changes and contradictory demands from multiple social roles
are in greater need of social networks. Therefore it seems
necessary to try to disentangle the roles of strain and
support in women's lives and their significance for
cardiovascular health. Furthermore, these aspects should be
examined in relation to SES as well as to occupational
status.
The Framingham Heart Study and other population studies have
shown that low SES and relative social deprivation are risk
factors in women as well as in men.  Framingham women who
had too little leisure time and too few of their own
resources to take a single vacation in 6 years had an
increased risk of MI. Furthermore, employed Framingham women
had a lower MI risk than homemakers.  Loneliness, anxieties,
and sleep disturbances increased the risk of MI for
homemakers.  In employed Framingham women, economic
difficulties were the main factor that increased MI risk
(11).  Possible mechanisms for the difference include a
social gradient and a healthy worker effect. Women who were
able to work outside the home may have been socially and
economically better equipped from the beginning.  Many women
also benefited from increased economical resources as a
consequence of their employment.
In Sweden the situation is different. Since the end of the
1970s, nearly all Swedish women are employed outside the
home. There is even formal legislation requiring every
citizen, man or woman, to work and to provide an income for
himself or herself. Under these circumstances it is not
surprising that we found only two homemakers among 600 women
in the greater Stockholm area.
Employment outside the home means an additional workload for
most Swedish women, as Frankenhauser and coworkers have
demonstrated (12).  In their studies of male and female
employees in large companies, they have estimated the total
number of hours per week spent on paid work and on work at
home for the service of the family.  Childless men and women
employed full-time both work an average of 60 hours per
week.  Women with three small children increase their total
workload to 90 hours per week, but men in the same situation
increase their total workload only to 70 hours per week.
The Swedish Study of Female Coronary Risk Factors (Fem Cor
Risk Study)
The health effects of chronically increased workload in
women are not yet known. In the Fem Cor Risk Study in
Stockholm, one objective was to investigate the
circumstances and the form in which multiple roles and a
double burden of employment and homemaking may be
detrimental to health.
All female residents in the greater Stockholm area who were
admitted to a hospital for an acute CHD event between
February 1991 and February 1994 were asked to participate in
the study.  The study group was restricted to Swedish-
speaking patients age 65 or younger.  The Swedish health
care system provides care to all residents regardless of
income, SES, or insurance status. Thus we were certain to
reach all patients who needed and sought acute hospital care
for a CHD event in this time period.  Control subjects were
selected from the census register of greater Stockholm.  For
each case, a healthy woman born the same day as or as close
as possible to the birthdate of the patient and living in
the same hospital catchment area was chosen as a control.
"Healthy" was defined as being free from symptoms of heart
disease and without hospitalization for any illness during
the past 5 years.  Participation in the study was 87 percent
among cases and 83 percent among controls.
The methods used to study social support and major risk
factors for CHD were identical with those for the Gothenburg
Study. The only difference was the longitudinal design in
the Gothenburg Study.  The Gothenburg men were 50 years old
at the beginning of the study and were followed for CHD
incidence for 6 years.  To study women in this age group
prospectively would require a sample at least 3 times that
of men. We therefore used a population-based case-control
design for the Fem Cor Risk Study. The mean age of the
Stockholm women with CHD was 56 years (+/- 7.0) at
examination.
-----------------------------------------------------------
Figure Missing
Figure 1.  -  Social Integration and CHD in Women from the
Fem Cor Risk Study.  Reported data are for 292 cases with
age- and sex-matched controls. The odds ratio for CHD in
women with low social integration is 1.65 (95 percent
confidence levels: 1.16, 2.35).
-----------------------------------------------------------
Figure Missing
Figure 2.  -  Emotional Attachment and CHD in Women from the
Fem Cor Risk Study.  Reported data are for 292 cases with
age- and sex-matched controls. The odds ratio for CHD in
women with low levels of emotional attachment is 1.06 (95
percent confidence levels: 0.72, 1.55).
-----------------------------------------------------------
The effects of social support were generally weaker for
women than for men. Only the scale describing social
integration, which for men was the best predictor of MI,
showed a small but significant difference between cases and
controls (Fig. 1).  The scale describing lack of emotional
attachment, which was a marginal predictor of CHD in men,
showed absolutely no difference between women with and
without CHD (Fig. 2).  Furthermore, when results in women
were adjusted for standard risk factors including education
level, the net effect of lack of social integration was no
longer significant.  However, after controlling for standard
risk factors in Gothenburg men, the effect of lack of social
integration remained significant.
Social Networks and Social Strain
Because of the contradictory patterns of social network
structure and function, an interview procedure was used to
explore not just the level and kind of social support, but
also the presence of strain from the social sphere. The
general goal of the interview was to describe all possible
sources of strain.  The concept of family strain was similar
to those used by Karasek et al. for work strain, and
included dimensions of demand and control.
The interview was structured to describe work and family
life in terms of concrete and "objective" issues that were
relatively unsusceptible to retrospective reinterpretation.
It specifically addressed employment; marriages, divorces,
and separations; births and childrearing; and caretaking
responsibilities for elderly and other relatives.
Most pronounced in women with CHD were the excess strain
scores for current occupation and insufficient leisure time
(Fig. 3)  Women with CHD had more children (cases/controls =
1.11; p less than or equal to 0.10) and experienced more
spousal separations (cases/controls = 1.75; p less than or
equal to 0.01) than healthy controls.  They also reported
more strain from problems with children and much more strain
from problems associated with their spousal relationships,
particularly from separations.  Because these women already
had CHD at the time of interview, it is possible that their
perception of family strain was compromised by the knowledge
that they had heart disease, but it is unlikely that these
women would consciously blame their heart disease on family
problems.  When asked directly, most blamed their heart
disease on their own unhealthy lifestyle behaviors (e.g.,
smoking, lack of exercise).  It is also unlikely that for
many of the women, their disease could have had a directly
contaminating effect on family life. Most of the women had
their first symptoms of heart disease only a few years
before the interview. Their mean age at interview was 56
years, so most of them had already passed reproductive age
and had finished rearing their children.
-----------------------------------------------------------
Figure Missing
Figure 3.  -  Psychosocial Strain and CHD in Women from the
Fem Cor Risk Study.  Reported data are for 292 cases with
age- and sex-matched controls.
-----------------------------------------------------------
Lack of social support from the extended network and from
close family has been strongly associated with CVD risk in
Swedish men.  Among both men and women, lack of social
support was found to be more prevalent in low SES.  For men,
lack of social integration is a stronger risk factor for MI
and more prevalent in low SES than lack of emotional
support.  In Swedish women, however, these associations are
weak and confounded by standard risk factors.  Instead,
women perceive many of their social contacts as stressful.
Taken together, lack of control in the workplace and lack of
social integration and social anchorage in society seem to
explain an important part of the social gradient in CVD.
The fact that these effects persist even after controlling
for lifestyle and standard risk factors suggests new
possibilities for preventive measures.  Progress in
interdisciplinary research on the modification of behavioral
and psychosocial factors is giving rise to new intervention
methods that appear to be effective but need to be
implemented and tested in large-scale epidemiological
studies (2).
REFERENCES
1.  Healthy Work, edited by R Karasek and T Theorell.  New
    York: Basic Books, 1990.
2.  Behavioral Medicine Approaches to Cardiovascular Disease
    Prevention, edited by K Orth-Gomer and N Schneiderman.
    Hillsdale, New Jersey:  Lawrence Erlbaum Associates,
    1996.
3.  LaCroix AZ:  Psychosocial factors and risk of coronary
    heart disease in women: an epidemiologic perspective.
    Fertility and Sterility 1994;62:133S-139S.
4.  Schnall PL, Landsbergis PA: Job strain and
    cardiovascular disease.  Ann Rev Pub Health
    1994;15:381-411.
5.  House JS, Landis KR, Umberson D: Social relationships
    and health.  Science 1988;241:540-545.
6.  Orth-Gomer K, Johnsson JV: Social network interaction
    and mortality.  A 6-year followup study of a random
    sample of the Swedish population.  J Chronic Dis
    1987;40:949-957.
7.  Social Support and Health, edited by S Cohen and SL
    Syme.  New York: Academic Press, 1985.
8.  Berkman LF, Syme SL: Social networks, host resistance,
    and mortality.  A 9-year followup study of Alameda
    County residents. Am J Epidemiol 1979;109:186-204.
9.  Kaplan GA, Salonen JT, Cohen RD, Brand RJ, Syme SL,
    Puska P: Social connections and mortality from all
    causes and from cardiovascular disease: prospective
    evidence from eastern Finland.  Am J Epidemiol
    1988;128:370-380.
10. Schoenbach VR, Kaplan BH, Fredman L, Kleinbaum DG:
    Social ties and mortality in Evans County, Georgia.  Am
    J Epidemiol 1986;123:577-591.
11. Eaker ED, Pinsky J, Castelli WP: Myocardial infarction
    and coronary death among women: psychosocial predictors
    from a 20-year followup of women in the Framingham
    Study.  Am J Epidemiol 1992;135:854-864.
12. Women, Work, and Health: Stress and Opportunities,
    edited by M Frankenhaeuser, U Lundberg, and M Chesney.
    New York: Plenum Press, 1991.
-----------------------------------------------------------
Medical Care: Access, Utilization, and Cost
Daniel B. Mark, M.D., M.P.H., Nancy Clapp-Channing, R.N.,
M.P.H., Lai Choi Lam, M.S., John C. Barefoot, Ph.D.,
Ilene C. Siegler, Ph.D., M.P.H., Redford B. Williams, M.D.
The observation that low socioeconomic status (SES), as
reflected by various measures, is associated with increased
total and cardiovascular disease (CVD) mortality has been
made repeatedly (1-3), but the explanation for this
relationship remains incomplete.  Proposed mediators fall
into several classes.  One of those cited most often is
reduced access to medical care.  This includes preventive
care, disease management, and emergency care.  Both
financial and nonfinancial considerations may be important
when examining the role of access to care, since the effect
of low SES on health is seen even in countries with
universal access (4).  Harmful behaviors related to
development of clinically manifest disease and to its
prognosis constitute another class of potential mediators.
These behaviors or risk factors fall into biological (e.g.,
poor management of hypertension, diabetes, or
hypercholesterolemia) and lifestyle (e.g., smoking,
exercise, diet) categories (5).  A third class of potential
mediators involves compliance with prescribed medical
regimens.
Most investigations of the relationship between SES markers
and coronary heart disease (CHD) outcomes have involved
large populations and lacked detailed measures of disease
stage or severity.  For example, relatively few studies have
controlled for left ventricular function and extent of
atherosclerotic coronary obstructive disease in their
examinations of the adverse health effects of low SES.  For
this report, the SES-outcome relationship has been examined
with careful control for disease severity using two
different populations from the Duke Cardiovascular Disease
Database.
Prognostic Importance of SES in the Duke Database
Initial Investigations
Between October 1974 and February 1980, we administered a
battery of questions concerning psychosocial, economic, and
functional status to 1,368 symptomatic patients undergoing
coronary angiography at Duke University (6).  All patients
had significant CHD, defined at angiography as at least 75
percent stenosis of at least one major coronary artery.  As
part of the routine for the Duke Cardiovascular Disease
Database, all patients were followed at 6 and 12 months
after their angiogram and annually thereafter.  At the time
of data analysis, the median followup was 9 years.  The
major SES measures available in this data set were years of
education, family income, employment status, and number of
people dependent on the income.  A previously derived hazard
score with the Cox proportional hazards regression model
allowed control for confounding by disease severity.  The
hazard score is calculated by summing the products of the
value of each of the prognostically important
characteristics identified in this population and their
corresponding Cox model regression coefficients.  This
hazard score has been validated as a predictor of prognosis
in several populations and serves as an efficient means of
"leveling the playing field."
-----------------------------------------------------------
Table Missing
Table 1.  -  SES Profile of Study Population, Duke
Cardiovascular Disease Database
Source: Adapted from Williams RB, et al (6) with permission.
Copyright 1992, American Medical Association.
-----------------------------------------------------------
The study population consisted of 245 women and 1,123 men
(99 percent white) with a median age of 52 years (6).  The
distribution of major economic characteristics for this
group is shown in Table 1.  In Cox regression analysis
controlling for disease severity, patients with higher
household income had better survival than those with lower
incomes (adjusted chi-squared = 10.9, p = 0.001).  Patients with
annual household incomes of $40,000 or more had an average
5-year survival rate of 0.91, whereas patients with incomes
below $10,000 had a 5-year survival rate of 0.76 (Fig. 1).
In relative terms, those with the lowest incomes were almost
twice as likely to die within 5 years of enrollment in this
study as those in the highest income class (Cox model
adjusted hazard ratio, 1.9; 95 percent confidence interval,
1.57-2.32).  Additionally, survival was inversely related to
the number of individuals dependent on the household income
(adjusted chi-squared = 5.6, p = 0.018).
None of the other economic variables or the prespecified
interactions were statistically significant.  Gender was not
a significant predictor either alone or in interactions with
income or number of dependents.  Thus in this study SES
measures identified a significant population (23 percent)
who were at substantially increased risk after taking into
account all standard measures of disease severity.  In this
early study, we were not able to evaluate issues about
mechanism or to identify potentially modifiable correlates
of low SES.
Ongoing Investigations
More recently we have initiated a detailed prospective
psychosocial evaluation, the Mediators of Social Support
(MOSS) Study, in our angiographic patient population.  The
main purpose of this investigation is to confirm and
elaborate on previous observations about the relationship
between psychosocial factors and CVD outcomes, after
adjusting for standard measures of disease severity.  A
strong secondary goal is to identify putative mediators that
may lead to the elucidation of mechanisms or point to
effective interventions. Although the study is still
enrolling and following patients, results of preliminary
data analysis from the initial 2,360 patients (30 percent
women, 13 percent black) are available.  All patients had
angiographically documented CHD.  The population had a mean
age of 62 years and a mean education level of 11.4 years.
The mean income class was $20,000-$30,000 per year.
-----------------------------------------------------------
Figure Missing
Figure 1.  -  Survival and Family Income.  Source: (6) with
permission.
-----------------------------------------------------------
Because education and income have been proposed as markers
of SES, these variables were studied in the MOSS population
(Fig. 2).  As expected, there was a monotonically increasing
relationship between income class and years of education.
Each income class was associated with an increment of
approximately 1-2 years in mean education level relative to
the next lower income class (r = 0.58).
To understand the implications of SES, we examined its
correlation with a spectrum of demographic, clinical, and
health status measures assessed at the time of enrollment.
In general, evident correlations were significantly stronger
with income than with education.  Baseline correlations of
more than 0.3 with higher income were seen for patients with
higher functional status (measured using either the Duke
Activity Status Index [DASI] or the SF-36 Physical
Functioning Scale), patients with higher general health
perceptions (measured using the SF-36 scale), and married
patients.  Weaker correlates included lower hostility levels
(using the Cook-Medley scale), younger age, male sex, more
regular exercise, more favorable psychological status (using
the SF-36 scale), increased optimism, and decreased
perceived stress.  In general, the major medical prognostic
factors were either very weakly correlated with SES (e.g.,
ejection fraction) or were not correlated at all (e.g.,
number of diseased vessels).
MOSS also examines patients' perceived access to various
aspects of medical care. In a subset of patients undergoing
medical treatment, several measures of access were lower in
patients with lower SES.  For example, patients who said the
cost of medical care kept them from going to the doctor as
often as they should had lower education and income levels
than the patients who did not view cost as a barrier to
seeing their doctor (Fig. 3).  The same trend was seen for
cost as a prohibitive factor for seeking necessary emergency
room or hospital care, with the lower-SES patients
indicating lower perceived access to care (Fig. 4).
At the 1-year followup, we examined the frequency of
physician visits that patients reported within the previous
6 weeks as an approximate measure of the relationship
between SES and actual medical care utilization.  Low-SES
patients had more physician visits than their higher-SES
counterparts.  This modest but definite trend was based on
both education and income levels.  Ongoing investigations
are examining the nature of these visits (e.g., primary
care, specialty care, emergency department).
-----------------------------------------------------------
Figure Missing
Figure 2.  -  Measures of Socioeconomic Status: Relationship
between Education and Income.  Education vs. income class in
patients from the Duke MOSS Study.
-----------------------------------------------------------
Figure Missing
Figure 3.  -  Effect of Cost of Medical Care on Perceived
Access to Physician Care by SES Level.
-----------------------------------------------------------
Figure Missing
Figure 4.  -  Effect of Cost of Medical Care on Perceived
Access to Emergency or Hospital Care by SES Level.
-----------------------------------------------------------
Relationships between SES and several potential mediators of
CVD are also being examined in this population.  SES had no
effect on the quit rate of patients who were smoking at the
time of enrollment (Fig. 5).  In contrast, comparison of
patients' self-reported frequency of exercise at baseline
and at 1 year showed that patients with higher SES
(particularly higher income) were significantly more likely
to increase their physical activity during the year after
their angiography than lower-SES patients (Fig. 6).
Finally, we examined the relationship between the two SES
markers and 1-year survival in this population.  The
unadjusted relationship between years of education and
survival was highly significant (p = 0.0004) with a hazard
ratio of 0.78 for a 4-year difference in education.  After
adjustment for baseline measures that included disease
severity, age, functional status (using DASI) and general
health perceptions (using the SF-36 scale), education was no
longer a significant predictor of 1-year survival (p =
0.95).  Income class was also a strong predictor of 1-year
survival in the unadjusted Cox model (p < 0.0001), with a
hazard ratio of 0.73 for a one-income class difference.
After adjusting for the four covariates above, income
remained marginally significant in the Cox model (p = 0.04)
and the hazard ratio increased to 0.89, indicating a reduced
prognostic effect of the residual income term in the model.
In general, these findings are in agreement with our
previous analyses (6).  Income was an independent predictor
of outcome in the CHD population after adjustment for
disease severity, but education was not.  In our new
analyses, much of the prognostic importance of income
appears to be accounted for by other variables, including
functional status and general health perceptions.  These
variables may in turn be dependent on other elements of
disease severity or general physical and psychological
disability (7).  Other analyses indicate that patients who
engage in cardiac rehabilitation improve their DASI scores.
This may provide an important clue about at least one of the
needs of lower-SES patients who, according to our data, do
not appear to respond to CHD diagnosis by increasing
exercise levels on their own (8).
Conclusions
Analyses from the Duke Cardiovascular Diseases Database
confirm larger population-based studies in showing that
measures of SES are important prognostic factors.  In
addition, income appears to be a significantly stronger
predictor of outcome than education in patients with
established CHD, but may be confounded by the effect of
disease on the patient's income prior to presentation.
Lower SES does appear to be a marker for reduced perceived
access to medical care, although some preliminary data
suggest that utilization rates of outpatient care may
actually be higher among low-SES patients.  New prognostic
analyses suggest that differences in patient functional
status and health perceptions account for at least part of
the relationship between lower SES and poorer survival in
CHD and may reflect unmeasured aspects of disease severity
or resultant disability.
-----------------------------------------------------------
Figure Missing
Figure 5.  -  Effect of SES on Smoking Cessation Rates in
CHD Patients Over 1 Year of Followup.
-----------------------------------------------------------
Figure Missing
Figure 6.  -  Effect of SES on Exercise Behavior in CHD
Patients Over 1 Year of Followup.
-----------------------------------------------------------
REFERENCES
1.  Kaplan GA, Keil JE: Socioeconomic factors and
    cardiovascular disease: a review of the literature.
    Circulation 1995;88:1973-1998.
2.  Feinstein JS: The relationship between socioeconomic
    status and health: a review of the literature. Milbank
    Quarterly 1993;71:279-322.
3.  Syme SL, Berkman LF: Social class, susceptibility and
    sickness. Am J Epidemiol 1976;104:1-8.
4.  Adler NE, Boyce T, Chesney MA, Folkman S, Syme SL:
    Socioeconomic inequalities in health: no easy solution.
    JAMA 1993;269:3140-3145.
5.  Lynch J, Kaplan GA, Salonen R, Cohen RD, Salonen JT:
    Socioeconomic status and carotid atherosclerosis.
    Circulation 1995;92:1786-1792.
6.  Williams RB, Barefoot JC, Califf RM, Haney TL, Saunders
    WB, Pryor DB, Hlatky MA, Siegler IC, Mark DB: Prognostic
    importance of social and economic resources among
    medically treated patients with angiographically
    documented coronary artery disease. JAMA
    1992;267:520-524.
7.  Cohen G, Forbes J, Garraway M: Interpreting self-
    reported limiting long-term illness. BMJ
    1995;311:722-724.
8.  Harlan WR, Sandler SA, Lee KL, Lam LC, Mark DB:
    Importance of baseline functional and socioeconomic
    factors for participation in cardiac rehabilitation. Am
    J Cardiol 1995;76:36-39.
-----------------------------------------------------------
Session III:
Experiences in Educational and Preventive Interventions
Across SES Groups
-----------------------------------------------------------
Session III Overview
L. Julian Haywood, M.D., Chair
The goal of this session was to examine the effectiveness of
educational and preventive interventions for control of
cardiovascular disease (CVD) across socioeconomic groups
and, in the process, to determine whether common problems
and opportunities exist for intervention design and
implementation.  The interventions discussed here, which
include programs for smoking cessation, reduction of dietary
fats, and increased physical activity, have been or are
currently being tested in a variety of clinical and
community settings.  A striking finding in many studies is
that individuals in all socioeconomic status (SES) groups
appear to respond similarly to effective interventions when
the interventions use solid experimental and clinical
investigative methods.  The challenge is to apply these
interventions effectively in real-life settings so that
their potential for improving public health can be realized
among all SES groups throughout the whole population.
Speakers and discussion participants pointed to the growing
need for appropriately designed CVD interventions and
assessment tools for all SES groups, particularly for low-
SES communities.  Clustering of interrelated behavioral and
environmental risk factors makes determining specific
influences of SES factors extremely difficult in these
communities. For instance, among inner-city populations in
high-crime neighborhoods, access to heart-healthy foods is
limited and simple exercise activities such as walking
around the block can be prohibitively dangerous.  Lower
literacy rates among adults in low-SES communities
complicate communication efforts.  These factors require
special consideration in the design of CVD interventions,
but they are not insurmountable.
Studies of CVD risk generally show a gradient between the
lowest and highest SES levels rather than specific SES
thresholds for risk.  These trends suggest that public
interventions should not be targeted solely at the lowest-
SES populations but at all SES levels to provide the maximum
public health benefit.  The participants stressed the need
to develop culturally appropriate intervention tools for
individuals and communities at each SES level using
appropriate measures.
The conferees also noted that the real mark of efficacy for
a given intervention lies in the ability to sustain its
promotion of healthy behaviors and reduction of CVD events
after the study or demonstration project concludes. To that
end, public outreach programs should include representatives
from the study communities as partners in project design and
implementation.  Many programs do so already.
The participants in this session urged the implementation of
public health policies and intervention methods with proven
efficacy.  They recommended directing resources and efforts
toward hypothesis-driven research in new areas of interest
as well as on issues that have received inadequate attention
in the past.  Many of the observations and recommendations
presented at this conference parallel recently reported
findings of an NHLBI Task Force on Epidemiology and
Prevention (1).  Specific observations included the
following:
Smoking.  Cessation is a long-term process.  About 75
percent of quitters are light or infrequent smokers and stop
"on their own."  Less-educated smokers, however, are less
likely to quit.  More needs to be learned about the quitting
process for these smokers.
Weight Loss.  Obesity is closely related to the combined
effects of excessive calories and sedentary lifestyle, both
of which are highly prevalent in low-SES groups.  Cultural
and individual beliefs about the value of large body size
are also important factors.  Many studies have shown that
self-help groups are often as successful at losing weight as
groups that receive special interventions.  Self-help models
require further study.
Physical Activity.  Obesity is increasing despite decreasing
fat intake and flat caloric intake; therefore, decreasing
energy expenditure (the result of a sedentary lifestyle)
must be a cause.  Just as efforts to give smoking a "bad"
public image through the mass media have been effective at
changing smoking behavior, efforts to give exercise a "good"
image may be successful in boosting physical activity
levels.  A campaign is needed to encourage moderate
exercise, with the minimal goal of increasing average
physical activity to walking at least 30 minutes per day for
at least 5 days per week.
Culture.  The influence of culture is poorly recognized and
is especially important for some ethnic and racial groups.
Smoking, for example, may have religious significance (e.g.,
for Native Americans).   Food is often symbolic of welcome
and acceptance, and obesity may be considered physically
attractive.  Interventions must recognize local community
factors.
Clinical Trials.  Much has been learned from large clinical
trials regarding effectiveness of specific interventions
such as treatment of high blood pressure and lipid lowering
across populations.  However, low-SES groups have been
underrepresented in most trials, as have minority groups.
Existing databases are underutilized and should be examined
more closely to explore findings by ethnicity/race and SES.
Interventions in Worksites, Communities, and Schools.
Experience to date indicates that each of these locales may
be an effective forum for intervention.  Low-SES and
minority groups can be actively involved in these programs
and can achieve similar or even greater benefits than
majority groups.  More attention is needed in interventions
at all these sites to achieve primary and secondary
prevention with regard to adverse lifestyles and related
risk factors (1).
National Education Programs.  These programs, such as the
National High Blood Pressure Education Program (NHBPEP) and
the National Cholesterol Education Program (NCEP), have
contributed to a reduction in morbidity and mortality
through effective physician and public education and can
serve as models for beneficial risk factor reduction in many
segments of the population.  A similar physical activity
advocacy program is needed.
Research Recommendations
*  Efforts should be directed at developing better
   definitions of SES that will facilitate model development
   and data analysis.  An interdisciplinary effort involving
   physicians, economists, health educators,
   epidemiologists, psychologists, and sociologists is
   needed to conceptualize SES in greater depth and
   formulate hypotheses related to CVD, outcomes, and
   intervention success.  Family and generational influences
   should be considered in this process.
*  Research should be directed at improving self-help and
   intervention models.  Appropriate models should be
   developed and tested for different SES groups.  Program
   effectiveness may be improved by applying the lessons
   learned in this process.
*  Cost analysis should be incorporated into major clinical
   trials and other intervention studies, in addition to
   SES-related data, to facilitate estimation of the cost
   and benefits of broad applications, including those for
   disadvantaged populations.
*  Continued collaboration between researchers from physical
   and mental health fields should be encouraged for
   investigations of SES effects on health.
*  Communities with high risk factor indices should be
   targeted for in-depth study and should be the focus of
   efforts for improving availability of and access to
   resources.  Factors such as knowledge, attitudes, and
   behaviors should be studied in low-SES populations, rural
   and urban.  These populations should be targeted for
   studying interventions that address obesity, nutrition,
   physical activity, and smoking.
*  Studies should examine and identify barriers to adoption
   of heart-healthy lifestyles and behaviors within
   high-strain employment settings and poor communities.
   Cultural and broad community factors and institutions
   should be included, and unemployment must be addressed as
   a factor in intervention design.
*  Studies should be designed with the goal of developing
   interventions that will foster sustained behavior and
   risk factor changes once the research project has ended.
   Analysis of outcomes should be carried out over extended
   periods, and time trend analysis should be included in
   study designs.  Community members must be included as
   active participants in developing and carrying out
   intervention programs that they can sustain.
Opportunities for Practical Application
*  Concise smoking prevention, cessation, and relapse
   prevention interventions should be provided through
   community health centers, Federal Women, Infants, and
   Children (WIC) clinics, public hospitals, and other
   health care providers for children, adolescents, and
   adults of lower SES.
*  For adolescents of lower SES who remain in school,
   school-based smoking prevention, cessation, and relapse
   prevention programs that emphasize the immediate benefits
   of not smoking are appropriate.  For adolescents who have
   left school, such interventions should be community-,
   media-, and worksite-based.
*  Linkage of mass media antismoking messages to smoking
   cessation hotlines and to sources of self-help materials
   tailored to different SES and racial groups may be
   particularly cost-effective.
*  Interventions should recognize existing resources in the
   community.  Dietary education and intervention programs
   should be designed with consideration of foods available
   through WIC and commodity programs as well as a knowledge
   of culturally important foods.
*  The Institute's national CVD education programs and
   initiatives offer an effective and rapid means of
   translating research results into practical applications
   for health care.  Examples include the Coronary Heart
   Disease in Blacks Initiative and the Latino Community
   Cardiovascular Disease Prevention and Outreach
   Initiative.  New interventions to improve the health of
   target populations should take advantage of Institute
   expertise and resources in developing and utilizing
   information dissemination networks.
*  The well-documented intervention methods for changing
   smoking habits, dietary behavior, and physical activity
   used in the Multiple Risk Factor Intervention Trial
   (MRFIT), the Treatment of Mild Hypertension Study
   (TOMHS), and similar clinical trials should be made more
   widely available.  It may be necessary to modify these
   methods for use in specific low-SES groups.
*  The effectiveness of diuretic-based stepped care for
   blood pressure control in all SES groups should receive
   continued and enhanced emphasis through the NHBPEP.
*  If results from the NHLBI-supported projects on
   nutritional intervention for low-literacy populations are
   found to be positive, the intervention methods and
   information on their effectiveness should be disseminated
   through the NHBPEP and NCEP.
*  School health education should be encouraged at lower
   grade levels and with all SES groups in attendance.
*  Partnerships should be encouraged between Federal,
   voluntary, and local agencies that have similar goals.
*  Work in encouragement of healthy food choices at
   institutional cafeterias should be supported.
REFERENCE
1.  National Heart, Lung, and Blood Institute, Report of the
    Task Force on Research in Epidemiology and Prevention of
    CVD, 1994.
-----------------------------------------------------------
What Have We Learned About Socioeconomic Status  and
Cardiovascular Disease From Large Clinical Trials?
Jeffrey A. Cutler, M.D., M.P.H.
Greg Grandits, M.S.
Little published information is available about the
influence of socioeconomic status (SES) of participants on
the findings of large clinical trials.  The main exception
is the Hypertension Detection and Followup Program (HDFP)
(1,2).  This and other NHLBI-supported primary prevention
trials arguably have the greatest relevance to differential
rates and outcomes of cardiovascular disease (CVD) in the
general population.
Key questions addressed are the following:
*  Since findings are always conditioned by the population
   studied, how does recruitment affect SES distribution of
   trial participants?
*  How does SES affect adherence to interventions tested in
   clinical trials?
*  Are morbidity and mortality benefits the same across
   different levels of SES?
Highest educational attainment is used, for the most part,
as the main indicator of SES.
Recruitment
The three large primary prevention trials initiated by NHLBI
in the early 1970s present contrasts in recruitment methods
and results.  The HDFP recruited men and women, 45 percent
of whom were black, from enumerated residential and worksite
populations using home visits for initial screening, an
approach that contributed to a broad SES distribution (40
percent with less than high school education, 22 percent
with some post-secondary education) (2).  The Multiple Risk
Factor Intervention Trial (MRFIT) and the Lipid Research
Clinics Coronary Primary Prevention Trial (CPPT) recruited
during the same period, but targeted men only and generally
utilized a volunteer approach.  This approach yielded study
groups of which only 16 percent and 12 percent had less than
high school education, while 27 percent and 38 percent were
college graduates in MRFIT and CPPT respectively (3,4).
Internal evidence from the CPPT indicates that the
educational distribution of randomized participants depended
on screening source:  among those from medical sources
(e.g., clinical labs, medical referrals), 32 to 36 percent
were college graduates and 12 to 18 percent had 7th to 11th
grade education; while among those identified from mass
mailings and media, 40 to 44 percent were college graduates
and only 10 to 11 percent had 7th to 11th grade education
(4).  Evidence that coming into a trial through a medical
care source exerts less selection by SES is further
illustrated by data from a secondary prevention trial, the
Beta-blocker Heart Attack Trial (BHAT).  The BHAT sample,
largely men and from a birth cohort similar to that of the
MRFIT, had 37 percent with post-secondary education as
compared with 63 percent in MRFIT (3,5).
Age, or more precisely birth cohort, is probably the
strongest influence on educational levels of trial
participants.  Although the Systolic Hypertension in the
Elderly Program (SHEP) recruited a sample about 15 years
older than that of the HDFP, because SHEP was begun almost
15 years later, participants were drawn from approximately
the same birth cohort, and a similar proportion had post-
secondary education (31 percent in SHEP, 22 percent in HDFP)
(6).  The slightly higher education distribution of SHEP
probably reflects recruitment of volunteers and smaller
numbers of blacks.  In contrast, two primary prevention
trials involving young adults that recruited during the same
period as SHEP  -  the Trials of Hypertension Prevention
Phase II (7) and the Dietary Intervention Study in Children,
which recruited parents of 8- to 10-year-old children (8)  -
drew participants more than 85 percent of whom had post-
secondary education.  The fact that these protocols promised
to be quite demanding probably had an influence as well.
Adherence to Interventions
We could find no results published from large trials on
adherence according to SES.  Therefore, we further analyzed
data from two large primary prevention trials involving both
pharmacologic and behavioral interventions: the MRFIT and
the Treatment of Mild Hypertension Study (TOMHS).
According to the MRFIT design, the primary targets of the
Special Intervention (SI) were reduction of diastolic blood
pressure (DBP) using largely diuretic-based stepped-care
drug treatment, cessation of cigarette smoking through
behavior modification methods, and reduction of total serum
cholesterol by dietary means (9).  Changes in these risk
factors after 6 years of followup are shown in Table 1
according to education level, race, and randomized group (SI
vs. Usual Care, or UC).  It is evident that for nonblack men
(98 percent of whom were white) changes in DBP were very
similar across education levels within both SI and UC
groups, and thus yielded constant SI-UC differences.  For
black men, however, SI-UC differences were larger at lower
education levels (p=0.002 by ANOVA), mainly due to larger
reductions within the SI group.  Results were similar for
systolic blood pressure (SBP, data not shown).
For smoking cessation, results for nonblack men were again
quite uniform across education levels, especially for SI-UC
differences, although quit rates tended to be largest among
college graduates in both SI and UC.  Similarly, although
among blacks the lowest quit rates were seen for the least
educated, especially in the SI group, the SI-UC differences
did not vary significantly across education levels.
Overall, the intervention effect (SI vs. UC) was larger in
black than nonblack men, due to greater cessation in SI and
less quitting in UC participants for black men.
Changes in LDL cholesterol among nonblack men were similar
by education.  A trend was seen among black men for greater
intervention effects for the less-educated groups, but this
was not statistically significant.  For all races combined,
SI-UC differences for changes (baseline to year 6) in intake
of saturated fatty acids and dietary cholesterol, measured
by single 24-hour recalls, were also similar across
education levels (data not shown).
-----------------------------------------------------------
Table Missing
Table 1.  -  Risk Factor Changes in MRFIT by Education
Level, Race, and Randomized Group
-----------------------------------------------------------
Table Missing
Table 2.  -  Risk Factor Changes and Medication Adherence
Over 4 Years in TOMHS, by Education Level, Race, and Gender
-----------------------------------------------------------
Thus, the overall conclusion from MRFIT is that net
improvements in risk factors (SI vs. UC) were at least as
great for participants with lower education levels as for
those with higher levels for the major racial groups,
separately and combined.  It is of further interest to note
that SI-UC differences in CVD mortality over 16 years were
also similar across the same education levels: these
differences in CVD deaths per 1,000 participants were, from
lowest to highest education, respectively:  -5.3, -6.7,
+2.9, and -6.8.
The TOMHS randomized 902 men and women, 45 to 69 years of
age with Stage 1 diastolic hypertension, to placebo or to
one of five antihypertensive drugs, each from a different
drug class.  All participants also received multifactor
lifestyle intervention aimed at weight control, increased
physical activity, and reduction of sodium and alcohol
intake.  Average followup was 4.5 years.  Twenty percent of
participants were black.  The main results have been
published (10).
We examined medication compliance (percent remaining on
randomized drug assignment at 12 and 48 months in the five
active drug groups) and measures of change in each lifestyle
component, with followup measures averaged over all visits,
by education level.  When participants' education was
dichotomized into college graduation compared with lower
levels, increased physical activity (in all subgroups except
black men), weight loss (in nonblack men), change in DBP (in
black women), and medication compliance (at 12 months in
blacks) were significantly greater in the group with a
lesser education level (Table 2).  Otherwise for these
measures, and for overnight sodium excretion, differences by
educational attainment were generally not observed.
With years of education used as a continuous variable,
physical activity demonstrated consistent trends.  These are
illustrated according to five categories of education,
analyzed separately for each of four race-sex subgroups
(Fig. 1).  At baseline, education was directly associated
with reported level of physical activity in three of the
four subgroups (all except the small sample of black men).
However, changes from baseline to followup were inversely
associated with education in the same three subgroups.  In
each of these race-sex subgroups, the participants with less
than high school or with high school education made the
largest changes.  Thus, although this pattern could be
explained in terms of the groups with the most room for
improvement making the largest changes, modest educational
achievement was clearly not a barrier to responding to this
lifestyle intervention program.
Mortality and Morbidity Outcomes
We focus here on the treatment of hypertension, because the
population burden of this condition was shown 20 years ago
to be inversely related to SES among individuals screened
for the HDFP; moreover, its association with race is well
known. (1).  Data in the NHLBI Chartbook from NHANES III
show that this is still the case.  In the 45- to 64-year-old
stratum, SBP was consistently higher in those with less than
12 years of education than those with more than high school
education for each of the major race-sex groups (i.e., by 7,
8, 3, and 4 mmHg, for black men and women and white men and
women, respectively).  Similar trends were evident in
comparisons by income.
In further analyses from the HDFP, it was shown that all-
cause mortality among participants in the Referred Care (RC)
group was inversely and significantly related to education
level.  In both black and white hypertensive persons exposed
to customary care in the community, there was approximately
a 2-fold gradient in risk of death among those with less
than high school compared with those with more than high
school education.  In contrast, among both blacks and whites
these gradients were essentially nonexistent in the Stepped
Care (SC) group, who received systematic, blood pressure
(BP) goal-directed drug treatment (2).  When 5-year
mortality rates in those with less than high school
education were directly compared, the SC and RC rates were
6.9 and 9.0 percent respectively, for an absolute difference
of -2.1 percent (95 percent confidence interval, -0.6, -
3.6).  However, a direct statistical test of whether the
mortality benefit (SC vs. RC) differed across educational
levels found no significant interaction, a result supporting
the conclusion that the 16.9 percent overall relative
reduction in mortality in the HDFP SC group was applicable
to the subgroup with lower education as well.  Because the
HDFP was an unblinded trial, and questions are occasionally
raised whether nonspecific aspects of care received by the
SC group could have contributed to the mortality benefit,
the HDFP investigators conducted further analyses.  They
constructed regression models to try to account for the
mortality reduction with variables related to the
hypertension treatment protocol, and concluded that SC
"explained" 44 percent of the benefit in the least educated
subgroup (2).
-----------------------------------------------------------
Figure Missing
Figure 1.  -  Physical Activity Level in TOMHS by
Educational Level, Race, and Sex.
-----------------------------------------------------------
The most compelling evidence to confirm the efficacy of
antihypertensive treatment per se in reducing adverse
outcomes in a lower-SES hypertensive population would come
from a double-blind randomized trial.  The SHEP was such a
trial, and some relevant analyses have recently been
conducted (11).  The differences between randomized groups
for rates of major end points generally parallel the HDFP
mortality findings.  Specifically, in the subgroup with less
than high school education, the relative risks (active
treatment vs. placebo) for nonfatal plus fatal stroke,
nonfatal myocardial infarction plus fatal coronary heart
disease (CHD), all major CHD events, and all major CVD
events were in the range of 0.62 to 0.65, all with 95
percent confidence intervals that did not overlap 1.0.
Moreover, in every case the relative risks were smaller (but
not significantly so) in those with less than high school
education than in those with greater than high school
education, (i.e., the data suggest that the active treatment
was more effective in reducing adverse outcomes in the
lower-SES hypertensive participants).  A similar trend
across education levels was present for all-cause mortality,
but as for the overall SHEP data, subgroups lacked
statistical power to show significant effects.
Conclusions
Large clinical trials seek to enroll broadly representative
study populations, but their protocols and management teams
have traditionally emphasized recruiting adequate numbers of
participants overall in order to answer the main study
question.  Primary prevention trials usually target broad
segments of the community to elicit volunteers, an approach
that tends to result in underrepresentation of low-SES
persons.  Participants recruited from medical care sources,
especially hospitals, are likely to have a broader SES
distribution.  The population-based approach used by the
HDFP  -  unique among large U.S. trials  -  along with
targeting of the black population, led to a broad SES
distribution.  This composition of the screened and
randomized study groups facilitated the several SES-related
analyses in the HDFP.  While other trial data sets may not
be as well suited for such analyses, investigators should
nonetheless consider using them for this purpose.
The MRFIT Research Group has previously published findings
for black and white subgroups showing similar responses to
the SI program regarding risk factor changes (3).  Data
presented in this paper extend these conclusions to
subgroups defined by educational attainment.  The only
significant variation by education was seen for BP change in
black men, largest among the least educated.  In a study of
a broader array of treatments for hypertension than in
MRFIT, the TOMHS also tended to find greater adherence in
the less educated, especially for change in physical
activity.  A limitation in these conclusions is the absence
of a parallel control group for lifestyle change in TOMHS.
Nevertheless, these findings strengthen the broad
conclusion, based on the MRFIT, that modest educational
attainment does not necessarily represent a major impediment
to intervention success.  In addition (and most important),
the findings from HDFP and SHEP indicate that successful
intervention on BP translates into morbidity and mortality
reduction in the less educated that is at least as great as
in the more educated.  The results also suggest that
systematic treatment produces some attenuation of the risk
gradient associated with SES.
Limitations in generalizability of the foregoing conclusions
include the possibility that self-selection into trials
operates more strongly in lower-SES strata, leading to a
study subgroup with more coping and social support resources
than individuals not enrolled, and thus better adherence.
In addition, there are gaps in our knowledge base about
interventions to reduce disparities in CVD among SES strata,
some of which are being addressed by ongoing NHLBI
intervention research.  With regard to classical risk
factors and their behavioral determinants, five NHLBI
grantees are studying strategies to improve hypertension
control in inner-city populations.  Another six groups of
investigators are funded to develop and test methods of
nutrition education for low-literacy populations to improve
blood lipid and blood pressure levels.  Finally, to address
the apparent role of such psychosocial risk determinants as
social isolation and depression, a multicenter NHLBI-
sponsored clinical trial, Enhancing Recovery In Coronary
Heart Disease, has recently begun.  These efforts will
expand our knowledge and should lead to more effective ways
to influence risk favorably in lower-SES groups.
REFERENCES
1.  Hypertension Detection and Followup Program Cooperative
    Group:  Race, education, and prevalence of hypertension.
    Am J Epidemiol 1977;106:351-361.
2.  Hypertension Detection and Followup Program Cooperative
    Group:  Educational level and 5-year all-cause mortality
    in the Hypertension Detection and Follow-up Program.
    Hypertension 1987;9:641-646.
3.  Connett JE, Stamler J:  Responses of black and white
    males to the special intervention program of the
    Multiple Risk Factor Intervention Trial.  Am Heart J
    1984;108:839-848.
4.  Agras WS, Bradford RH, Marshall GD (eds):  Recruitment
    for clinical trials: the Lipid Research Clinics Coronary
    Primary Prevention Trial Experience  -  its implications
    for future trials.  Circulation 1982;66(II):IV-1-IV-78.
5.  Byington RP:  Beta-blocker Heart Attack Trial: design,
    methods, and baseline results. Unpublished monograph,
    BHAT Coordinating Center, Houston, 1982.
6.  Vogt TM, Schron E, Pressel S, Wassertheil-Smoller S,
    Eddleman EE, Miller S, Stamler J:  Part 3:
    Sociodemographic characteristics.  Hypertension
    1991;17(Suppl II):II-24-II-34.
7.  Appel LJ, Hebert PR, Cohen JD, Obarzanek E, Yamamoto M,
    Buring J, Stevens V, Kirchner K, Borhani NO:  Baseline
    characteristics of participants in Phase II of the
    Trials of Hypertension Prevention (TOHP II).  Ann of
    Epidemiol 1995;5:149-155.
8.  Personal communication, Eva Obarzanek, Ph.D.
9.  Benfari RC, Sherwin R (eds):  Forum: The Multiple Risk
    Factor Intervention Trial. The methods and impact of
    intervention over four years.  Preventive Medicine
    1981;10:387-553.
10. Neaton JD, Grimm RH Jr, Prineas RJ, Stamler J, Grandits
    GA, Elmer PJ, Cutler JA, Flack JM, Schoenberger JA,
    McDonald R, Lewis CB, Liebson PR, for the Treatment of
    Mild Hypertension Study Research Group:  Treatment of
    Mild Hypertension Study: final results. JAMA
    1993;270:713-724.
11. Personal communication, Sara Pressel, M.S.
-----------------------------------------------------------
Smoking Cessation, Socioeconomic Status, and Ethnicity
Judith K. Ockene, Ph.D.
John Harrington, Ph.D.
Our ultimate goal is to contribute to the cardiovascular
health of the nation by highlighting the scientific
information on smoking intervention that is ready for
transfer to health care professionals and the public.  To
achieve this goal, the relationship of smoking to
socioeconomic status (SES) and the outcomes of clinical and
community interventions for smoking cessation, with a focus
on SES and ethnicity, will be reviewed.  The utilization of
"assisted methods" for smoking cessation by various SES and
ethnic groups will be considered, as will barriers to
utilization of smoking interventions for low-income and
culturally diverse populations.  In addition, research
opportunities and smoking intervention needs for low-SES and
culturally diverse individuals will be identified.
Smoking, SES, and Ethnicity
The prevalence of cigarette smoking varies among ethnic
groups, and within each ethnic group and special population
(e.g., pregnant smokers) it varies by education.  In 1993,
the prevalence of cigarette smoking among U.S. adults was
highest for American Indians and Alaska Natives (39
percent), intermediate for blacks (26 percent) and whites
(25 percent), and lowest for Hispanics (20 percent) and
Asian Americans and Pacific Islanders (18 percent) (1).  For
adolescents, the prevalence of current cigarette smoking was
also highest for American Indians and Alaska Natives,
intermediate for white adolescents, and lowest for Hispanic
and black adolescents.
The strong predictive relationship of education to smoking
applies to all racial and ethnic groups, all special
populations, and all age groups.  For example, in 1993, for
25- to 44-year-olds who had gone beyond a high school
education the smoking rates for blacks, whites, and
Hispanics were very close (approximately 20 percent).  For
persons with 9 to 11 years of education and those with at
least 16 years of education, 37 percent and 14 percent were
smokers, respectively.
Among adolescents, those doing well in school and planning
to complete college are much less likely to smoke than are
their counterparts (2).  In recent years, the prevalence of
cigarette smoking decreased more rapidly among American
Indian and Alaska Native adolescents than among white
adolescents.  Among black adolescents it has declined
sharply since the 1970s, while for white adolescents it has
increased slightly.  This difference is maintained after
adjustment for parents' education, number of parents in the
household, college plans, employment, and degree of
religious observance.
For adolescents who have left school, black adolescents are
significantly less likely than white adolescents to report
current smoking.  Black youths initiate smoking at slightly
later ages than white youths, and an accelerated rate of
decline in smoking has been observed for black youths aged
18 through 24 years, suggesting a cohort effect (3).
Twenty to 35 percent of the general population of pregnant
women smoke (4), and rates vary by ethnicity and education.
Of low-income pregnant women enrolled in urban Women,
Infants, and Children (WIC) programs, 42 percent smoked (5)
and, among pregnant smokers, unmarried women with fewer than
12 years of education were least likely to quit smoking
spontaneously during pregnancy (4).  Over time, the
prevalence of smoking has had a 5-fold greater decline for
the more educated than the less educated, clearly making it
an issue defined by education.
Smoking Treatment Outcome, SES, and Ethnicity
Most small-scale clinical studies have not assessed the
efficacy of their smoking interventions across SES and
ethnic groups.  Therefore, information regarding the
efficacy of interventions across SES and ethnic groups is
derived from large studies of heterogeneous populations and
smaller studies of relatively homogeneous populations of
interest.  Differing methodologies make comparisons of the
latter difficult.
Smoking intervention studies can be grouped by type of
intervention or channel (sector) through which the
intervention is delivered or both.  There is overlap between
the groupings, since a channel may have several types of
interventions delivered through it.  For example, a worksite
can have available any of the interventions listed under
type. The following intervention groupings are discussed
here:
Channel/Sector:
* Community Intervention
* Media
* Worksite
* Self-help
Type:
* Intensive (group or individual)
* Physician/Dentist-based
* Telephone Counseling
Two large collaborative trials using intensive group and
individual interventions delivered over an extended period
of time are the Multiple Risk Factor Intervention Trial
(MRFIT) and the Lung Health Study.  In both trials,
education level had a significant effect on smoking
cessation, with more-educated smokers being more likely to
stop smoking (6, 7).  However, even less-educated smokers
were more likely to stop smoking with special intensive
intervention than in the usual-care conditions.  Thus,
intensive interventions can have a positive effect on
smokers with less education.  Unfortunately, utilization of
intensive interventions is low among all education groups,
and this problem and attrition are perhaps greater for
ethnic minorities than in the general population (8).
Hispanics and Asian Americans, for example, rarely
participate in smoking cessation groups (8).  Telephone and
face-to-face consultation may be an appropriate alternative,
especially among Hispanics whose culture traditionally
values personal attention.
Using 11 matched community pairs, the Community Intervention
Trial for Heavy Smokers (COMMIT) tested the effect of a
community organizational intervention approach on smoking
cessation rates across different education and ethnic groups
(9).  Communities were randomized to intervention and
comparison conditions.  There was no significant
intervention effect on the heavy smokers, with quit rates of
17.9 percent and 18.6 percent in the intervention and
comparison conditions, respectively.  For the light-to-
moderate smokers, the greatest effect on cessation was for
those individuals who had a high school education or less,
demonstrating a 5.5 percentage point difference in cessation
between the intervention and comparison conditions.  It is
encouraging that a community-wide intervention had a
significant effect for less-educated smokers, making it
important to use what we can learn from this study and to
build on it.
Mass media smoking interventions are potentially cost-
effective and can provide a structured program within the
privacy of the home.  Mass media also can create a social
milieu supportive of behavioral change and may increase
knowledge, awareness, and motivation.  In addition,
television and radio can provide demonstrations of
behavioral skills not possible in written self-help
materials, and resulting behavioral change can be attributed
to one's own efforts.  Many smokers who might not otherwise
receive assistance can be reached through the media.  Thus,
even small program effects can have a very large public
health impact (10).  However, mass media programs alone have
not been found to be particularly effective.  The mass media
may be most effective for disseminating information and
providing access to quit lines and self-help materials.
In Massachusetts, calls to the Massachusetts Tobacco Control
Program quit line, funded by the Massachusetts Tobacco Tax
Initiative, increased when the Food and Drug Administration
(FDA) indicated that it might regulate tobacco and when a
television advertising campaign began.  This suggests that
coordination of media presentations with other interventions
can have a substantial effect.
Televised media programs and the distribution of self-help
materials have been combined, since self-help is the method
of choice of more than 90 percent of smokers (11) .  Flay
demonstrated that self-help materials introduced through a
media format can be twice as effective as self-help
materials alone (10).  The studies reviewed by Flay support
the conclusion that televised self-help programs can improve
the effectiveness of self-help manuals and have the
potential for a large public health impact.  However,
research must isolate the elements required for successful
mass media intervention, especially if programs are to
target minority, lower-SES, or less-educated smokers.
The National Cancer Institute-funded Programa Latino Para
Dejar de Fumar (Hispanic Program to Quit Smoking) has used
radio and television public service announcements and the
distribution of self-help smoking cessation materials.
Through public education, the program has promoted
participation in smoking cessation interventions and
significantly decreased the prevalence of smoking among the
target group of less acculturated Hispanic smokers in San
Francisco (12).
Physician-delivered interventions targeted at minority, low-
SES, or less-educated smokers have not been well developed
and investigated.  Much of what is known about health care
provider-based intervention with these groups comes from
studies of smoking among pregnant women.  Smoking among
pregnant women is of concern due to smoking's impact on the
fetus, the mother, and young children.  There have been 15
randomized clinical trials testing interventions with
pregnant women, eight of them with women in the low-SES
strata.  Interventions with pregnant smokers are generally
effective, but postpartum relapse is high.  One study of
women receiving public prenatal care (13) reported prenatal
quit rates of 8.5 percent among controls compared with 14.3
percent among women receiving counseling and a self-help
guide with supplemental mailings.  Black women had higher
prenatal quit rates than white women.  Unfortunately, at 6
months postpartum, cessation rates were the same in both
conditions due to postpartum relapse, making the postpartum
period an important time for intervention.
In summary, smoking intervention studies support the
conclusions that intensive interventions have a greater
impact on more-educated smokers, however, they do have an
effect on less-educated smokers; community interventions can
have a positive impact on less-educated smokers, but must be
tailored to the needs of the target population;  self-help
interventions and media campaigns, when used together, have
demonstrated potential; self-help may be the intervention of
choice in some ethnic groups and may be effective when
combined with other interventions; interventions targeting
pregnant women have promise, but must include the
continuation of intervention postpartum; and physician-
delivered interventions targeted at low-SES or less-educated
populations have demonstrated potential, but they have not
been well developed and investigated.
Use of "Assisted Methods" in Smoking Cessation, SES, and
Ethnicity
To be efficacious, interventions must be available to,
tailored to, and utilized by smokers.  Although a variety of
intensive interventions have proven efficacy, they are not
well utilized by the smokers who need them.  Using data from
the 1986 Adult Use of Tobacco Survey, Fiore and colleagues
(11) found that about 90 percent of successful quitters and
80 percent of unsuccessful quitters used individual methods
rather than organized programs.  Female, middle-aged, and
more-educated smokers with more quit attempts and heavier
smokers were most likely to use a program.  Among smokers
who had attempted cessation within the previous 10 years,
47.5 percent who tried on their own and 23.6 percent who
used programs succeeded.  This reflects the fact that
heavier smokers are more likely to use programs.
When smokers are counseled by physicians or dentists, their
likelihood of stopping smoking significantly increases.
Such advice is as cost-effective per year of life saved as
other preventive medical practices.  Unfortunately, smokers
often report that advice to quit has not been provided to
them by a physician.  The 1991 National Health Interview
Survey (NHIS) collected self-report information from a
representative sample of U.S. adults regarding smoking
status and visits to and receipt of advice to quit from
health care professionals (14).  An estimated 70.2 percent
(95 percent confidence interval [CI] =  +-1.0 percent) of the
51 million persons who smoke had at least one outpatient
visit to a healthcare professional during the preceding 12
months.  However, about 20 million of these smokers reported
that they did not receive advice to quit smoking.  Among
persons with four or more visits, 45.5 percent (CI = +-2.0
percent) reported being counseled to quit compared with 28.1
percent (CI = +-1.9 percent) of those with one visit.
Counseling rates were slightly lower for Hispanics than for
white non-Hispanics, but otherwise did not vary by race-
ethnicity, education, or SES (Tables 1 and 2).
-----------------------------------------------------------
Table Missing
Table 1.  -  Percentage of Adult Smokers* Receiving Advice
to Quit from a Health Care Professional in a 12-Month
Period, by Number of Visits and Income
* Persons aged greater than or equal to 18 years who
reported they had smoked during the preceeding 12 months.
Poverty statistics are based on definitions developed by the
Social Security Administration that include a set of income
thresholds that vary by family size and composition.
**Sample size = 8778; excludes 369 respondents with an
unknown number of physician visits.
Source:  National Health Interview Survey  -  Health
Promotion and Disease Prevention Supplement, 1991.**
-----------------------------------------------------------
Table Missing
Table 2.  -  Percentage of Adult Smokers* Who Received
Advice to Quit from a Health Care Professional in a 12-Month
Period, by Number of Visits and Education
* Persons aged greater than or equal to 18 years who
reported they had smoked during the preceeding 12 months.
**Sample size = 8778; excludes 369 respondents with an
unknown number of physician visits.
Source:  National Health Interview Survey  -  Health
Promotion and Disease Prevention Supplement, 1991.
-----------------------------------------------------------
Health care professionals also have an important role in
adolescent smoking intervention.  The 1993 Teenage Attitudes
and Practices Survey (TAPS II) collected data from a
weighted sample of adolescents to derive national estimates
of tobacco use knowledge, attitudes, and practices, and of
health care providers discussing tobacco use with young
people (ages 10 to 22) (15).  Only 25.1 percent of
respondents reported that a health care professional had
mentioned cigarette smoking, and 11.8 percent said the same
about smokeless tobacco (SLT).  The strongest correlate of
an affirmative response was having a history of tobacco use.
Still, only 24 percent of respondents who had tried a
cigarette and only 13.2 percent of those who had tried SLT
recalled being advised about tobacco use.  No significant
differences were found by race-ethnicity, poverty status, or
region of the county.  Therefore, it appears that more can
be done to provide information to adolescents of all SES and
ethnic backgrounds before they begin to experiment with
tobacco.  To date, there have been no reported studies
testing the efficacy of pediatricians' office-based smoking
interventions.
Telephone quit lines are another important vehicle for
intervention.  Data from the Massachusetts quit line
indicate that smokers with less than high school education
are less likely to access it than smokers with high school,
some college, or a completed college education.  As quit
lines are free, the barriers to use are not likely economic.
Therefore, it is important to investigate the barriers to
the use of quit lines and develop interventions to enhance
such use.
Barriers to Smoking Interventions, SES, and Ethnicity
In low-income and culturally diverse populations, smoking is
often one of several disease-related lifestyle behaviors.
Through available, accessible, and appropriate health
education about lifestyle issues and adherence to clinical
preventive services guidelines and medical regimens, the
number of excess deaths and illnesses among low-income
culturally diverse populations can be substantially reduced.
However, the co-occurrence of smoking with other risk
factors makes effective intervention more difficult.
An optimal public health approach could improve delivery of
services and access for all consumers.  Such an approach
includes five major components.  First, education for
smokers and providers about smoking treatment, the most
important aspect of the public health approach, must be
delivered in a mode that is acceptable to the target
population.  Second, the development of social norms and an
environment that supports change is also necessary since
individual change, for smokers and health care providers,
does not occur in a vacuum.  Several studies that utilized
focus groups have found an unsupportive environment to be a
barrier to cessation (16).
A third important component of a public health approach
requires efforts in worksites, health care settings,
voluntary organizations, and the media to be coordinated and
integrated so that services and programs can be optimized.
More research is needed to study the efficacy of integrated
services delivered through multiple channels.  The creation
of an infrastructure, the fourth important component, makes
possible the delivery of information and services to health
care providers and smokers.  Without the infrastructure,
efficacious interventions cannot be implemented.  One way to
provide an infrastructure is to earmark tobacco tax funds,
as was done for the Massachusetts Tobacco Control Program.
Finally, regulations mandating services and standards of
performance are needed to provide incentives for the
delivery of high-quality interventions to economically and
ethnically diverse smokers.  Without the incentives and the
infrastructure to deliver services, interventions will not
be delivered.
Conclusions
Differences between more- and less-educated people in
smoking prevalence, quitting, and initiation have increased
over time, and education is now the best demographic
predictor of smoking patterns.  Approximately 60 percent of
adult smokers, and 50 percent of young (10 to 22 years old)
smokers report ever having been advised by a physician to
stop smoking.  This rate does not vary by race-ethnicity,
education or SES.  Although every smoker should be advised
by his or her physician to quit or not to start and offered
assistance to quit, more research is needed to examine the
impact of such interventions in the low-SES strata and
various ethic groups.  In addition, coordinated intervention
programs, such as media campaigns combined with self-help
materials, may assist smokers to quit, but more research is
needed to investigate the effect of tailoring interventions
for low-SES groups.
The fact that only 15 percent of smokers use programs to
quit and that program users are more often white, highly
educated, and female must be recognized.  Assisted methods
need to be tailored to and made available to smokers of
lower SES and educational attainment.  Barriers to
intervention, including lack of social support for
cessation, low perceived health risks of smoking, social
norms that support smoking, and limited usable information
on smoking, need to be kept in mind (16).  Broader social
support efforts and educational materials should be tailored
for smokers of low educational attainment and combined with
other interventions.  Smoking must be seen as a long-term
problem requiring long-term solutions.
REFERENCES
1.  Centers for Disease Control and Prevention: Cigarette
    smoking among adults  -  United States, 1993.  MMWR
    1994;43:925-930.
2.  Centers for Disease Control and Prevention:  Recent
    trends in adolescent smoking, smoking uptake correlates,
    and expectations about the future.  Advance data from
    vital health statistics of the CDC National Center for
    Health Statistics, No. 221. 1992.
3.  Centers for Disease Control and Prevention: Preventing
    tobacco use among young people. In Publication of the
    Surgeon General's Report on Smoking and Health.  MMWR
    1994;43:125-126.
4.  Fingerhut L, Kleinman J, Kendrick J: Smoking before,
    during and after pregnancy. Am J Pub Health
    1990;80:541-544.
5.  Mayer J, Hawkins B, Todd R: A randomized evaluation of
    smoking cessation interventions for pregnant women at a
    WIC clinic.  Am J Pub Health 1990;80:76-78.
6.  Hymowitz N, Sexton M, Ockene J, et al: Baseline factors
    associated with smoking cessation and relapse.  Prevent
    Med 1991;20:590-601.
7.  Bjornson W, Rand C, Connett J, et al: Gender differences
    in smoking cessation after 3 years in the lung health
    study.  Am J Pub Health 1995;85:223-230.
8.  Perez-Stable E, Marin B, Marin G: A comprehensive
    smoking cessation program for the San Francisco Bay Area
    Latino community: Programa Latino para Dejar de Fumar.
    Am J Health Promotion 1993;7:430-442.
9.  COMMIT Research Group: Community intervention trial for
    smoking cessation (COMMIT): I. Cohort results from a
    four-year community intervention.  Am J Pub Health
    1995;85:183-200.
10. Flay B: Mass media and smoking cessation: a critical
    review.  Am J Pub Health 1987;77:153-160.
11. Fiore M, Novotny T, Pierce J, et al:  Methods used to
    quit smoking in the United States: do cessation programs
    help? JAMA. 1990;263:2760-2765.
12. Marin G, Perez-Stable E: Effectiveness of disseminating
    culturally appropriate smoking cessation information:
    Programa Latino para Dejar de Fumar.  J Natl Cancer Inst
    (in press).
13. Windsor R, Boyd N, Orleans T: A meta-evaluation of
    smoking cessation intervention research among pregnant
    women:  improving the science and art. Health Educ Q (in
    press).
14. Centers for Disease Control and Prevention: Physician
    and other health care professional counseling of smokers
    to quit  -  United States, 1991.  MMWR 1991;42:854-857.
15. Centers for Disease Control and Prevention: Smoking
    cessation during previous year among adults  -  United
    States, 1990 and 1991.  MMWR 1993;42:504-507.
16. Lacey L, Manfredi C, Balch G, et al: Social support in
    smoking cessation among black women in Chicago public
    housing. Public Health Reports 1993;165:387-394.
-----------------------------------------------------------
Nutrition Intervention Studies
Shiriki K. Kumanyika, Ph.D., R.D., M.P.H.
Limited literacy skills affect over 50 percent of adults in
the United States, are strongly associated with low
socioeconomic status (SES), and undoubtedly contribute to
the increased health risks of low-SES individuals (1,2).  In
addition to the general association of low literacy with
variables such as education level, earning potential, and
the ability to pay for health care, low literacy skills
specifically limit access to nutrition and health
information, most of which is written at a tenth grade or
even college level (3-6).  Literacy may be particularly
relevant to SES differentials between minority and majority
populations because the marginalization associated with
literacy problems may be additive with or even synergistic
with problems related to racial and ethnic discrimination or
cultural alienation.
The National Heart, Lung, and Blood Institute (NHLBI) has
funded several projects that address the need for
cardiovascular nutrition education materials suitable for
English-speaking adults with limited literacy skills (7).
These projects have developed and tested strategies for
reaching racial-ethnic minority or multiethnic populations
in various settings across the United States with education
to foster healthy eating; reduce dietary intakes of fat,
saturated fat, cholesterol, and sodium; or improve weight
management. These educational strategies utilize interactive
computer technology, video, audiocassettes, compact disks,
and a variety of printed media:
*  CARDES  -  Cardiovascular Dietary Education System
   (Hershey, Pennsylvania, and Washington, D.C.) is a
   self-help program consisting of a motivational video,
   food picture cards and accompanying workbook, and a
   12-program audiocassette series designed for use in the
   outpatient management of  high blood pressure and high
   cholesterol.
*  HEALTHTALK  (Chapel Hill, North Carolina) is a user-
   friendly, interactive computer-assisted video
   instructional program that allows individualized
   counseling of individuals with high cholesterol in an
   outpatient clinic setting.
*  IDEA  -  Innovative Dietary Education Approaches
   (Minneapolis, Minnesota), is designed to be incorporated
   into the U.S. Department of Agriculture (USDA) Expanded
   Food and Nutrition Education Program (EFNEP), which
   reaches low-income persons (primarily women) responsible
   for food preparation.
*  SNAP  -  Stanford Nutrition Action Program (Stanford,
   California) was designed primarily for women, ages 20 to
   35, from diverse ethnic and economic backgrounds.  SNAP
   recruited participants from EFNEP.
*  Language for Health (San Diego, California) is a
   nutrition curriculum for low-literate adults designed for
   integration into adult English-as-a-Second-Language (ESL)
   classes.
*  The Lightway  -  Living in God's Healthy Temple
   (Baltimore, Maryland) is a community-based cardiovascular
   disease (CVD) nutrition intervention program designed and
   implemented in cooperation with a network of inner-city
   black churches.
*  Minimal Contact Education for Cholesterol Change
   (Pawtucket, Rhode Island), involves several interventions
   designed for use in worksites, public sites, religious
   organizations, medical facilities, or other community
   settings and utilizing  printed materials, a compact disk
   audio intervention, or brief face-to-face counseling.
*  Computer-Assisted Instruction for Weight Management
   (Amherst, New York) offers an approach to nutrition
   education for weight management for use with adults in
   various inner-city settings.
Some of the learning (e.g., Language for Health in the ESL
classes)  is provided in the context of performing life
skills functions such as using money or requesting job
information.  HEALTHTALK uses the popular talk-show format
to increase familiarity and appeal of the learning
encounter.   CARDES maintains a narrative story line,
initially introduced in the motivational video, involving
members of an extended family, through a series of short,
instructionally oriented vignettes on the 12-program
audioseries.
All programs have incorporated the guidance of experts in
adult education and literacy skills training (some of whom
are project coinvestigators) as to how best to work around
functional literacy problems (3).  In brief, this advice
involves:
*  keeping the presentation of information direct and
   conceptually simple;
*  providing for extensive opportunities for interaction
   between the learner and the instructor or
   instructional medium;
*  judicious use of illustrations that enhance recognition
   and comprehension;
*  formatting printed materials with sufficient white space,
   color, and guidance to make the reading order clear;
*  where useful, incorporation of a story line to facilitate
   interest in and retention of the information; and
*  making the information relevant to the cultural
   perspectives of the client group(s).
Most projects have used multiple media.  All have emphasized
the systematic development of educational materials and
evaluation strategies that include assessment of the impact
of using the educational materials in one or more ways on
objectively measured risk factors such as serum cholesterol.
Each project also includes an assessment of literacy levels
using either standardized tests or validated proxy measures.
This enables characterization of intervention processes and
outcome results according to the reading levels of those
involved.   Some programs used existing literacy tests while
others developed specially designed instruments to assess
CVD nutrition literacy.  For example, CARDES developed a 20-
item word recognition test (in this type of test the
respondent's ability to pronounce words correctly correlates
with reading comprehension) (8). The 20 words were selected
systematically, by reference to scores on the standardized
Tests of Adult Basic Education (TABE) for the same set of
individuals, from a pool of 200 words commonly found in CVD
nutrition education materials.   When the word recognition
test was administered to 339 black adults enrolling the
CARDES evaluation trial, 164 (48 percent) scored at or below
the 8th grade reading level, including 37 who had completed
more than 12 years of school and 117 with 8 to 12 years of
schooling.  This finding emphasizes that, although literacy
levels are generally associated with education level,
schooling cannot be equated with having attained basic
literacy skills (9).
Selected Findings
Preliminary findings from these projects illustrate the
general impression that the effort spent in developing these
client-centered instructional approaches is yielding success
in enrolling and counseling individuals with limited
literacy skills in CVD risk reduction programs.  Not only is
this success contrary to the common perception that such
populations are hard to reach (9), but it also offers
concrete potential for working around a functional aspect of
lower SES that may hinder improvements in health.
*  SNAP reached a multiethnic population of EFNEP
   participants in 24 different settings.  Sixty percent had
   literacy levels below the 8th grade level, as ascertained
   with the Wide Range Achievement Test (WRAT-R).  The
   interactive SNAP CVD nutrition curriculum involved
   discussions, group problem-solving activities,
   experiential learning, food tastings and demonstrations
   and utilized various printed and audiovisual materials.
   SNAP was compared with a standard nutrition education
   program.
*  The Minimal Contact Education for Cholesterol Change
   Project is reaching a population of more than 10,000
   individuals across a wide distribution of educational
   levels, including a substantial number of persons of
   Hispanic or Portuguese descent as well as some blacks,
   Asian Americans, and Native Americans.  Preliminary data
   on 4,000 individuals indicate that return rates for the
   3-month followup visits were highest (89 to 91 percent)
   among those with a high school education or more, but
   were almost as high  (85 percent) among those with an 8th
   grade education or less. Three-month followup rates were
   above 75 percent for every ethnic subgroup.
-----------------------------------------------------------
Figure Missing
Figure 1.  -  Reported Use of CARDES Materials at 4-Month
Followup by Literacy Screening Instrument (LSI) Score
(n=238).  Participants are 40- to 70-year-old black men and
women in Washington, DC.
Source:  Cardiovascular Dietary Education System
-----------------------------------------------------------
*  The CARDES evaluation trial is comparing two formats for
   using the take-home educational package designed to
   facilitate dietary change in an entertaining,
   nonquantitative, self-help format.  It enrolled men and
   women, ages 40 to 70, with hypertension or elevated
   cholesterol (n = 339), recruited primarily through
   community-based screening in local supermarkets in the
   Washington, D.C., community.  Participants are followed
   at intervals over a 12-month period.  Risk factors are
   monitored and brief nutrition counseling is given to all
   participants at a community-based clinic site.  All
   CARDES participants receive a deck of 100 full-color food
   picture cards coded with symbols to indicate whether the
   food is low, medium, or high in fat, sodium, and
   cholesterol, with an accompanying booklet that includes
   replicas of the cards and additional nutrition
   information.  Half also attend four initial monthly
   nutrition education classes where they watch and discuss
   a motivational video and receive instructional
   audiocassettes for home learning.
   Based on preliminary 4-month followup data as shown in
   Figure 1, CARDES participants reported a high frequency
   of using the provided materials during the first 4
   months, with greater use reported by the subset with
   lower scores on the literacy screening instrument.
   Figure 2 shows preliminary data on risk factor changes in
   the overall CARDES sample.  The improvements in total
   cholesterol and low-density lipoprotein cholesterol (LDL)
   and the lack of adverse changes in either high-density
   lipoprotein cholesterol (HDL) or triglyceride levels are
   noteworthy.  Also noteworthy is the apparent gradual
   progress in risk factor change over time.  This is an
   encouraging departure from the frequently observed
   pattern of a large initial change followed by a gradual
   loss of effect and return to baseline at followup.
-----------------------------------------------------------
Figure Missing
Figure 2.  -  Total Sample Data for Risk Factor Changes in
CARDES Participants; Preliminary Data (10/95).  Participants
are 40- to 70-year-old black men and women in Washington,
DC.
Source:  Cardiovascular Dietary Education System
-----------------------------------------------------------
Conclusions
The projects conducted under the low-literacy initiative can
serve as a model for focused research that addresses
modifiable aspects of SES-related CVD risk.  These projects
are illustrating effective ways to reach individuals who are
typically characterized as hard to reach (10).  The known
limitations in literacy in these study populations have
forced investigators to address systematically the need to
adhere to established principles of adult education as a
part of these nutrition interventions.  This may lead to
particularly favorable or long-lasting results.  In
addition, the methodological aspects of the projects and the
descriptive data collected on these diverse populations in
conjunction with literacy assessments provide a beginning
data base for specifying SES-related differentials according
to literacy skills  -  a functional variable that is
directly related to the potential for benefiting from
lifestyle risk reduction programs.
REFERENCES
1.  Kirsch IS, Jungeblut A, Jenkins L, and Kolstad A: Adult
    literacy in America.  A first look at the results of the
    National Adult Literacy Survey:  Washington, D.C.: U.S.
    Government Printing Office, 1993.
2.  Weiss BD, Hart G, McGee DL, D'Estelle S: Health status
    of illiterate adults.  Relationship between literacy and
    health status among persons with low literacy skills.  J
    Am Board Family Practice 1992;5:257-264.
3.  Doak C, Doak L, Root J: Teaching Patients with Low
    Literacy Skills.  Philadelphia:  J. B. Lippincott, 1985.
4.  Glanz K, Rudd J: Readability and content analysis of
    print cholesterol education materials.  Patient
    Education and Counseling 1990;16:109-117.
5.  Hynak-Hankinson MT: Literacy crisis.  Implications for
    nutrition and dietetic professionals.  Topics Clin Nutr
    1989;4(4):63-70.
6.  Doak  LG, Doak CC:  Patient comprehension profiles.
    Recent findings and strategies.  Patient Education and
    Counseling 1980;2(3):101-106.
7.  U.S. Department of Health and Human Services, National
    Institutes of Health, National Heart Lung and Blood
    Institute Programs in Nutrition: A Report on Research,
    Training, Career Development, Education, and Other
    Activities Related to Nutrition, Fiscal Year 1994.
8.  Ten Have TR, Van Horn B, Kumanyika S, Askov E, Adams-
    Campbell LL:  Development of a literacy screening tool
    for use in a cardiovascular nutrition education program.
    Presented at the 123rd Annual Meeting of the American
    Public Health Association, San Diego, California,
    October 1995.
9.  Newman AP, Beaverstock C: Adult Literacy.  Contexts and
    Challenges. Newark, Delaware:  International Reading
    Association, 1990.
10. Freimuth VS, Mettger W: Is there a hard-to-reach
    audience?  Public Health Reports 1990;
    105:232-238.
-----------------------------------------------------------
Physical Activity Intervention Studies and Socioeconomic
Status
Daniel I. Galper, M.S.
Steven N. Blair, P.E.D.
Sedentary living is a major modifiable contributor to
disease morbidity and mortality, including coronary heart
disease (CHD) (1).  This observation is supported by both
epidemiological data and controlled clinical trials.  A
recent meta-analysis of more than 40 studies indicates that
CHD is nearly twice as likely to develop in sedentary
individuals as in active persons independent of other risk
factors (2).
Furthermore, when one considers that the
population-attributable risks for unfit individuals are
equal to or greater than that for other traditional
cardiovascular disease risk factors (e.g., hypertension,
obesity, hypercholesterolemia), it follows that physical
inactivity represents a considerable public health burden.
From the perspective of physical activity intervention, it
is encouraging to realize the major health and economic
impact that can be achieved by increasing participation in
regular physical activity.
Several recent epidemiological studies illustrate this
point.  Recent findings from the Aerobics Center
Longitudinal Study (ACLS) indicate that men who changed from
unfit to fit between two physical examinations
(approximately 5 years apart) had a 44 percent reduction in
mortality compared with unfit men who did not improve (3).
This finding is particularly promising considering the men
only needed to achieve a moderate level of fitness to be
placed into the "fit" category.  Therefore, the degree of
fitness and hence physical activity required for substantial
health benefits appears to be modest.  Likewise, increased
physical activity has been reported to produce a CHD risk
reduction equal to that identified with favorable changes in
smoking, weight, and blood pressure (4).  Given the
potential of physical activity to influence health, it is
evident that programs to increase physical activity should
be treated with the same urgency as the problems of
hypertension, hypercholesterolemia, and cigarette smoking.
Patterns of physical activity vary among population segments
with different sociodemographic characteristics (1).
However, few intervention studies examine the relation
between socioeconomic status (SES) and physical activity.
Moreover, the overall picture is obscured by the variety of
SES indicators in physical activity research and the
inconsistent measurement of physical activity across
research studies.
SES indicators within the physical activity literature
include education level, income, occupation, and race-
ethnicity.  Although minority status and lower SES often co-
vary, differences in physical activity associated with race
(as with other health behaviors) can largely be accounted
for by differences in education, income, and occupation (5).
This is not to minimize the importance of targeting minority
groups in physical activity research.  Minority populations
are generally underserved in the area of health promotion
(6), and a better understanding of the relation between
physical activity and race-ethnicity is necessary to
maximize the effectiveness of physical activity programs for
these population segments.  The complex relation between
race-ethnicity and SES may require special considerations in
physical activity promotion.
The use of various definitions and measurement techniques
for physical activity across studies is also problematic
because different SES groups tend to participate in
different forms of physical activity.  As noted by King et
al, the classification of certain population subgroups as
sedentary may be a function of the type of physical activity
being measured.  For instance, research studies indicate
that higher-SES men tend to do more leisure-time physical
activity, and lower-SES men spend more time walking and
doing household chores (1).  How the activities are
classified will affect the degree of activity ascribed to
different populations.  It also should be acknowledged that
commonly used measures of physical activity may lack the
precision and reliability to detect true differences across
sociodemographic variables such as SES.
Despite the aforementioned problems in physical activity
research, several trends are apparent in the literature on
SES and physical activity (1):
*  Lower education is associated with a more sedentary
   lifestyle;
*  Lower income is associated with a more sedentary
   lifestyle;
*  Blue collar occupations are associated with a more
   sedentary lifestyle; and
*  Ethnic minorities (e.g., blacks, American Indians) appear
   to be less active than whites.
By virtue of their physical inactivity and given the
demonstrated dose-response relation between physical
activity and health benefits (1), lower-SES individuals have
much to gain from becoming  physically active.
Nevertheless, lower-SES individuals are less likely to
attend the types of programs usually offered in communities
throughout the United States, and interventions designed
specifically to meet the unique demands and preferences of
lower-SES groups are rare.  The pressing need for effective
physical activity interventions in lower-income populations
is highlighted by specific national objectives for
increasing physical activity and decreasing inactivity in
lower-income people outlined in Healthy People 2000 (6).
Data from the few programs that explicitly targeted poor,
unemployed, or disadvantaged population segments demonstrate
the appropriateness of such interventions despite concern
from some members of the health community that there are
more pressing problems, such as poverty or violence (5).
The promotion of physical activity within lower-SES groups
can be approached with less skepticism and more optimism.
Although blue collar workers are less physically active in
leisure-time, physical activity programs for blue collar
workers can be successful if structured creatively to
overcome certain unique barriers.  For instance,
lower-income environments replete with crime, unemployment,
and violence may limit the opportunities for the
economically or educationally disadvantaged to engage in
some forms of physical activity.  However, few research
projects examine how changes in the community environment
influence physical activity participation, despite evidence
suggesting that such changes can increase health behaviors
(7).  Few programs target lower-SES individuals, partly
because of inconvenience (i.e., difficulty recruiting and
accessing lower-SES groups), partly due to differential
attrition, and perhaps because of public policy.
The study of physical activity models and determinants is
based in part on the understanding that physical activity
interventions can be tailored (type, format, intensity,
location) to meet the needs and overcome the unique barriers
(i.e., special programs) of different population segments
(5).  Moreover, the complexity of physical activity behavior
and the difficulty of producing and maintaining changes
necessitate a conceptual formulation and a detailed
knowledge of mediators of behavioral change.  Over the past
20 years several health behavior models have been applied to
physical activity (e.g., Social Cognitive Theory,
Transtheoretical Model of Stages of Change [5]).  Although
no single model has proven superior to others, much has been
learned about the operation of particular physical activity
determinants that could not have been achieved through a
nonconceptual approach.
Current understanding suggests that physical activity
determinants vary in strength in different population
segments; however, there is an unfortunate dearth of studies
that specifically investigate the possible differential
influence of various determinants, including SES, among
diverse subgroups.  This is particularly true for youth (8).
Self-efficacy for physical activity, perceived barriers
(e.g., lack of time), and enjoyment are important predictors
of involvement in physical activity; low- to
moderate-intensity activities are more likely to be adhered
to than high-intensity activities; and self-regulatory
skills contribute to maintenance across all age groups (1).
Individualized approaches to promote physical activity are
insufficient given the breadth and complexity of the
physical activity problem (5).  Here we review selected
physical activity studies from two basic sites of
intervention: the community and the worksite.
Community Approaches
Until recently, most physical activity studies applied
unidimensional interventions to physical activity with
select groups rather than following a public health approach
(5).  Community interventions based on behavior change
theories gained popularity because they can most effectively
target diverse and difficult-to-access population segments
by including organizational, environmental, and social
components.  However, physical activity was not the
centerpiece of community-based interventions, and these
studies did not produce sizeable increases in physical
activity behavior.
To understand the unfavorable outcomes and the untapped
potential of community-based physical activity
interventions, it is helpful to examine two recent NHLBI
community-wide multifactorial cardiovascular risk reduction
projects that involved a physical activity component: the
Stanford Five-City Project (SFCP) (9) and the Minnesota
Heart Health Program (MHHP) (10).  Each of these projects
incorporated a broad range of strategies and theories aimed
at multiple levels (e.g., individual, group, societal).
Despite a population-based approach and a primary prevention
focus, programs for risk factor reduction in the SFCP were
relatively intensive.  Nevertheless, 6 years of
community-wide health education demonstrated only small
increases in physical activity (9).  Based on these
findings, Young et al cited the need to develop more
effective approaches to increase physical activity than can
be provided by a broad-based, community-wide health
education program.  This may be possible by segmenting the
community into demographically homogenous subgroups (e.g.,
neighborhoods) that can be specifically targeted.  The
results of the SFCP suggest that adults may be more
receptive to adopting moderately intense activities rather
than vigorous activities.
Similar to the SFCP, the MHHP was a 13-year,
population-wide, community-based program to prevent and
reduce CHD.  Consistent with the population-based approach,
exposure data from the MHHP suggest that the project
successfully reached multiple sociodemographic groups (10).
Although the MHHP had only a moderate impact on physical
activity (i.e., a small increase in kilocalories per day
expended in leisure-time physical activity was noted in the
early years of the study), the process data from the study
are important.  For instance, exercise campaign events that
occurred in pre-existing community structures or were
associated with traditional community events had the
greatest participation (11).  This underscores the
importance of utilizing existing settings (e.g., worksites)
and recognized events for community-based exercise
promotion.
Segments of the population that were more specifically
targeted through tailored strategies demonstrated better
outcomes (12).  In light of the MHHP goal of increasing
"active lifestyles," the message "to engage in [physical
activity] at least three times per week, for 30 minutes, at
an intensity sufficient to cause increased breathing and/or
induce sweating" (11) was probably not the most appropriate
one for this trial.  Although few ethnic or low-income
communities currently receive tailored programs to increase
physical activity, some interventions demonstrate promising
outcomes with these population segments.  The Community
Health Assessment and Promotion Project (CHAPP) (13) was a
multifaceted intervention for women in a predominantly black
community in Atlanta.  To meet specific needs of this
population segment, the CHAPP provided multiple offerings of
moderate-intensity physical activity and related health
topics.  At 4-month followup, 60 to 70 percent of the
participants were still active.
Worksite Approaches
The worksite continues to be an important location for
reaching a large portion of the adult population with health
promotion programs (6).  There is a notable increase in the
number of work sites offering physical activity programs
over the past 15 years in the United States.  The outcomes
of physical activity research in the worksite are positive.
Two selected studies demonstrate the applicability of
worksite interventions for various SES groups.
Brill and colleagues (14) examined the recruitment,
retention, and success among various demographic groups in a
large clinical worksite health promotion program.  Overall,
participants improved in physical fitness and, perhaps most
important, changes were consistent across SES groups.  The
Johnson & Johnson Live for Life program (15) took a public
health approach to increase formal and informal physical
activity for the entire work force.  At 24-month followup,
employees in companies offering Live for Life more than
doubled their physical activity.  As in the Brill study,
changes were distributed across SES groups  -
demonstrating that clinically significant changes can be
achieved through worksite interventions in both lower- and
higher-SES groups.
The limitations of worksite physical activity promotion
programs include lower enrollment of  blue collar and
less-educated workers (5).  In the Brill study, recruitment
rates were significantly lower for nondegree (20 percent)
and bachelor's degree (31 percent) employees as compared
with employees with advanced degrees (41 percent).
Significantly fewer blacks than whites enrolled in the
program.  More baseline social marketing research and
segmentation on SES to tailor worksite programs to at-risk
groups are likely to yield better results.
Conclusions
*  A need exists for additional physical activity research
   in various SES groups. This research should utilize
   measures with demonstrated reliability and sensitivity in
   different demographic groups in a manner that allows for
   comparison across studies.  In particular, the mechanisms
   that produce differences in physical activity across SES
   indicators must be identified to develop greater
   understanding and improved interventions.
*  Some progress has been made since the 1992
   NHLBI-sponsored workshop, Physical Activity and
   Cardiovascular Health: Special Emphasis on Women and
   Youth (16), but there remains a need to develop
   theoretically based interventions that are effective for
   specific population subgroups.  Special emphasis should
   be placed on lower-SES groups and minorities, because
   these are the groups with the highest absolute and
   relative risk for inactivity, and we know relatively
   little about physical activity interventions for them.
*  Although recent research suggests that positive
   experiences with health behavior change in one area might
   favorably influence commitment to changing other risk
   behaviors, it is not clear whether physical activity is
   more successfully promoted by itself or as part of a
   multiple risk factor program (5).  Furthermore, because
   physical activity has the potential to facilitate the
   lowering of other risk factors, there is a need to
   further examine physical activity within a comprehensive
   approach to health promotion and CHD risk reduction.
*  Development, implementation, and testing of various
   physical activity interventions for specific SES groups
   is strongly indicated.  Issues such as ethnicity, income,
   education, gender, and the possible interaction of these
   variables should be investigated.
REFERENCES
1.  Pate RR, Pratt M, Blair SN, Haskell WL, et al: Physical
    activity and public health: a recommendation from the
    Centers for Disease Control and Prevention and the
    American College of Sports Medicine. JAMA
    1995;273:402-407.
2.  Berlin JA, Colditz GA: A meta-analysis of physical
    activity in the prevention of coronary heart disease. Am
    J Epidemiol 1990;132:612-628.
3.  Blair SN, Kohl HW, Barlow CE, Paffenbarger RS, Gibbons
    LW, Macera CA: Changes in physical fitness and all-cause
    mortality: a prospective study of healthy and unhealthy
    men. JAMA 1995;273:1093-1098.
4.  Paffenbarger RS, Hyde RT, Wing AL, Lee I, Jung DL,
    Kampert JB: The association of changes in physical
    activity level and other lifestyle characteristics with
    mortality among men. N Eng J Med 1993;328:538-545.
5.  King AC, Blair SN, Bild DE, et al: Determinants of
    physical activity interventions in adults. Med Sci
    Sports Exerc 1992;24:S221-S236.
6.  U.S. Dept of Health and Human Services:  Healthy People
    2000:  National Health Promotion and Disease Prevention
    Objectives. Washington, D.C.: DHHS publication PHS
    91-50212, 1991.
7.  Iverson DC, Fielding JE, Crow RS, Christenson GM: The
    promotion of physical activity in the United States
    population: The status of programs in medical, worksite,
    community, and school settings.  Public Health Rep
    1985;100:212-224.
8.  Sallis JF, Simons-Morton BG, Stone E, et al:
    Determinants of physical activity in youth.  Med Sci
    Sports Exerc 1992;24:S248-S257.
9.  Young DR, Haskell WL, Taylor CB, Fortmann SP: Community
    education and physical activity knowledge, attitudes,
    and behavior: The Stanford Five-City Project. In press.
10. Luepker RV, Murray DM, Jacobs DR, et al: Community
    education for cardiovascular disease prevention: risk
    factor changes in the Minnesota Heart Health Program. Am
    J Public Health 1994;84:1383-1393.
11. Blake SM, Jeffery RW, Finnegan JR, et al: Process
    evaluation of a community-based physical activity
    campaign: the Minnesota Heart Health Program experience.
    Health Ed Res 1987;2:115-121.
12. Crow R, Blackburn H, Jacobs D, et al: Population
    strategies to enhance physical activity: the Minnesota
    Heart Health Program. Acta Med Scand Suppl
    1986;71:93-112.
13. Lasco RA, Curry RH, Dickson VJ, Powers J, Menes S,
    Merritt RK: Participation rates, weight loss, and blood
    pressure changes among obese women in a
    nutrition-exercise program.  Public Health Rep
    1989;104:640-646.
14. Brill PA, Kohl HW, Rogers T, Collingwood TR, Sterling
    CL, Blair SN: The relationship between sociodemographic
    characteristics and recruitment, retention, and health
    improvements in a worksite health program.  Am J Health
    Promot 1992;5:215-221.
15. Blair SN, Piserchia PV, Wilbur CS, Crowder JH: A public
    health intervention model for worksite health promotion:
    impact on exercise and physical fitness in a health
    promotion plan after 24 months.  JAMA 1986;255:921-926.
16. Sopko G, Obarzanek E, Stone E: Overview of the National
    Heart, Lung, and Blood Institute workshop on physical
    activity and cardiovascular disease.  Med Sci Sports
    Exerc 1992;24:S192-S195.
-----------------------------------------------------------
Worksite, Community-Based, and School-Based Intervention
Russell V. Luepker, M.D.
Increased cardiovascular disease (CVD) risk and poor disease
outcomes in lower socioeconomic status (SES) groups have
been observed for many years.  However, the difficulty in
engaging and improving the health of low-SES populations is
also well known.  Few programs are seen as effective,
resulting in discouragement in the ability to narrow the
health gap between high- and low-SES groups.  The community,
worksite, and school experience with reaching and changing
the CVD risk profiles of low-SES groups is presented and
reviewed here.  The examples presented are population
strategies that focus on educating all groups in society
simultaneously,  many with particular attention to the needs
of the high-risk, low-SES segment.  Information in this area
is extensive and arguably overwhelming.
COMMUNITY TRIALS
Stanford Three-Community Study
The Stanford Three-Community Study was one of the earliest
interventions to focus on improving CVD risk characteristics
in whole communities.  It involved three northern California
towns studied in the early 1970s.  The main results have
been presented.  This study emphasized mass media methods in
the intervention towns and demonstrated a reduction in CVD
risk factors.  It recognized the importance of low SES and
minority groups (1).  The towns had a high percentage of
Spanish-speaking citizens, principally of Mexican origin.
The Stanford group tailored their program specifically to
target these Mexican Americans, using native Spanish-
speaking experts as part of the intervention team.  Baseline
data collection in the community found that the Spanish-
speaking radio stations were the primary source of
information for this population group.  Thus, educational
advertising in Spanish used radio heavily.
Table 1 presents data for cholesterol intake from the study.
It is apparent from this table that the highest consumption
of cholesterol is among lower-SES, Spanish-speaking
individuals.  At the end of the 2-year program, the decline
in cholesterol intake was similar across all groups in the
population.  There is even some suggestion of an increased
response among the low-SES Spanish-speaking group.  Although
not shown here, there are similar baseline and outcome
results for diet, weight, and plasma cholesterol.  The
Stanford authors conclude that a mass media program that
recognizes SES and minority issues can be effective at
changing behaviors and CVD risk.
Stanford Five-City Project (SFCP)
The SFCP was an extension of the Three-Community Study to
larger and more complex urban areas.  It involved two
intervention and three control communities over 8 years in
the 1980s (2).  The main results were published recently
(2,3).  Again, the Stanford group recognized the need to
develop messages and communication channels that involve
low-SES and minority groups in these northern California
communities.  The results of this effort are shown in Table
2.  For men, comparison is made between the least educated
and most educated.  Declines are noted in smoking, blood
pressure, and blood cholesterol in both intervention and
comparison communities.  They are greater, on average, in
the intervention communities.  Both high- and low-SES groups
lowered their risk factors.  For men, it appears that the
less-educated groups did moderately better than the more-
educated groups.  For women, the results were generally
similar except for cholesterol, which actually rose in the
intervention group.  The Stanford authors conclude that one
of the outcomes of a broad-based multimedia program is that
all segments of society are reached and make changes.
-----------------------------------------------------------
Table Missing
Table 1.  -  Dietary Cholesterol (mg/day) at Baseline and 2
Years, by SES and Language Group, Stanford Three-Community
Study
Source:  Adapted from Fortmann, et al. (1), with permission.
Copyright 1982, American Heart Association.
-----------------------------------------------------------
The Pawtucket Heart Health Program (PHHP)
The PHHP was a community intervention study in Rhode Island
begun in 1980.  The results were published recently (4).
The populations of both intervention and control communities
in this study have a high concentration of low-SES groups,
recent immigrants, and unemployed persons.  High school
graduation rates in these communities among adults are less
than 50 percent.  The proportion of foreign-born residents
ranges from 16 to 24 percent, and unemployment ranges from
14 to 18 percent.  The PHHP intervention group recognized
that this population has unique characteristics, and that
interventions would need to be tailored accordingly.
The PHHP reported positive differences in the intervention
community at midpoint, but these disappeared later in the
setting of strong and beneficial secular trends in the
control town.  However, evaluation by SES  -  with education
as a measure  -  demonstrated increased effects in the less-
educated groups.  Less-educated women had a greater
cholesterol decrease and less-educated men had lower
systolic blood pressure and less weight gain.  These group
differences, however, were not significant.  Contrary to
these positive findings, the less-educated had smaller
declines in smoking.  Nonetheless, a combined risk score for
CVD showed that the less-educated benefitted significantly
more from this program, (risk ratio 0.63, confidence
interval 0.41-0.98).
The PHHP investigators also concluded that community
programs that recognize and target low-SES and minority
groups in the setting of a broad community effort can
produce beneficial changes.
-----------------------------------------------------------
Table Missing
Table 2.  -  Change in Risk Factors by Education Level,
Stanford Five-City Project
Source:  Adapted from Winkleby, et al. (3), with permission.
-----------------------------------------------------------
The Minnesota Heart Health Program (MHHP)
The MHHP was a six-community, three-pair study involving
500,000 people, beginning in 1980.  The main results have
been published (5).
A particular attempt was made to involve low-SES individuals
in the Minnesota program.  Although there is considerable
population homogeneity in the upper midwest, SES differences
in CVD risks and outcomes are reported to be similar to
other populations.
The MHHP produced modest changes in risk in the setting of
strong and beneficial secular trends.  The greatest
differences were at midpoint in the program.  Physical
activity, blood cholesterol, systolic blood pressure, and
cigarette smoking all showed modest but favorable changes.
Evaluation of these changes by education and income levels
indicated no independent effects and no interactions.  It
appeared as if lower-SES individuals received the same
benefits as high-SES individuals.  The MHHP also concluded
that community programs that target and involve low-SES
groups can effectively reach them.
COMMIT
The COMMIT involved 11 pairs of communities across the
United States.  Its goal was to reduce heavy smoking in
intervention communities compared with control communities
(6).  The trial showed an 18 percent decrease in heavy
smoking between baseline and 4-year followup.  However,
these results did not differ between intervention and
control communities.  The COMMIT investigators concluded
that their primary goal was not met.  Nonetheless, light-to-
moderate smoking did fall significantly, more in the
intervention towns compared with the controls.  This
difference in smoking was concentrated in the lower-
education groups (6).  Apparently, the more-educated groups
did not significantly benefit from this community
intervention program, but less-educated groups did.
WORKSITE PROGRAMS
There is a large literature on worksite risk reduction
programs with varying results.  Most have been tested in
large, stable companies.  Unfortunately, many low-SES, high-
risk people are transient, part-time workers who lack
benefits or live in rural settings.  These are not included
in traditional worksite programs and may constitute an
important portion of the problem.
Healthy Worker Project
The Healthy Worker Project involved 32 randomized sites in
the Minneapolis-St. Paul metropolitan area (7).  These sites
had a significant blue collar population.  On-site classes
and a payroll incentive program were part of a 2-year
intervention aimed at cigarette smoking and weight
reduction.
As shown in Table 3, significant effects were found for
reduction in cigarette smoking.  However, no significant
changes were observed in weight as represented by body mass
index.  This occurred despite the fact that weight control
programs were very popular.  The authors concluded that
smoking cessation programs can have an effect in the
traditional factory setting but that weight control programs
are unlikely to be as successful.
MHHP  -  Bloomington Project
Eight factories in Bloomington, Minnesota, with 38 percent
blue collar workers, were targeted for a smoking
intervention or control status (8).  The intervention
included on-site smoking cessation classes, nonsmoker helper
classes, and smoking restriction consultation.  The authors
observed increased levels of quit attempts and cessation,
including among blue collar workers.  They concluded that
one can engage factories with blue collar workers in a
smoking cessation program.
SCHOOL PROGRAMS
School is one place where all segments of society join
regardless of minority or SES status.  It is rightly viewed
as a place where quality health education can occur.  Many
believe that the school setting has the potential for
building lifelong healthy habits.
-----------------------------------------------------------
Table Missing
Table 3.  -  Healthy Worker Project Outcomes
Source:  Adapted from Jeffery, et al. (7), with permission.
Copyright 1993, American Public Health Association.
-----------------------------------------------------------
Know Your Body (KYB)
The KYB program was a complex and intense program focusing
on grades four through eight in the New York schools in the
1980s (9).  A unique aspect of the program is a comparison
of high-SES Westchester schools with low-SES Bronx schools.
Notwithstanding concerns about measurement and analysis of
the KYB program, the comparison of the high- and low-SES
groups is of considerable interest.
As shown in Table 4, KYB reported blood cholesterol changes
favoring the intervention schools over the comparison
schools.  Of equal importance is the observation that these
changes appeared to affect the Bronx schools at a similar
magnitude to that observed in the more affluent Westchester
schools.  Health knowledge paralleled these changes.  In
addition, dietary intake changes had similar trends between
the two types of schools (not shown).  Although other risk
factors were not significantly altered, this study suggests
that programs aimed at low-SES schools can produce changes
similar to those in more affluent school districts.
Child and Adolescent Trial for Cardiovascular Health (CATCH)
CATCH involves 96 schools in four sites across the United
States (10).  The population is ethnically diverse,
comprising substantial portions of Hispanic and black
students.  It also includes many low-SES students,
particularly at the Louisiana and Texas sites.
Although CATCH was not allowed to collect definitive SES
data in the student populations, other relevant information
is available.  Students who ate more subsidized meals in the
school tended to have higher calorie and fat consumption.
Low-SES students are much more likely to have both breakfast
and lunch in the schools.
Interim results of the CATCH cafeteria intervention program
are shown in Figure 1.  A directed cafeteria intervention
with food service workers produces significant reduction in
the fat calories served and consumed by students.  The CATCH
Program indicates that schools continue to serve less-than-
healthy diets to students, but a focused intervention
program can modify this food service environment and provide
healthier foods to all students.
-----------------------------------------------------------
Table Missing
Table 4.  -  Know Your Body Program 5-Year Results*
*All results are given as changes in factor values between
baseline and 5-year followup.
Source: Adapted from Walter, et al. (9), with permission.
Copyright 1988, Massachusetts Medical Society.
-----------------------------------------------------------
Class of 1989
The Class of 1989 Program was part of the MHHP (11).  All
school students in the Fargo-Moorhead (North Dakota and
Minnesota) district were involved in a multiyear
intervention that focused on major cardiovascular health
behaviors.
Sioux Falls, South Dakota, a town of similar population size
(100,000) served as the reference.  There were striking
differences in smoking behaviors through 12th grade.  The
intervention schools had rates that were less than half of
those in the comparison schools.  These results were
confirmed by a chemical measure of cigarette smoking.
These results are among the most dramatic of any school-
based smoking prevention program.  The authors conclude that
student curriculum plays one important role; however, the
integration of the school program with a community-wide
program in Fargo-Moorhead may account for a significant
portion of the positive results.  Fargo-Moorhead was part of
the MHHP at the time the Class of 1989 project was
initiated, so many elements in society were simultaneously
directed toward similar health goals.
SUMMARY AND CONCLUSIONS
This review leads naturally to several conclusions.  First,
well-designed community or population interventions can
produce healthy changes in CVD risk both in high- and low-
SES and minority groups.  At times, the effect has been even
greater in the less educated and less affluent.  These
groups do, however, start at higher levels of risk.
-----------------------------------------------------------
Figure Missing
Figure 1.   -  Fat Reduction in School Lunch Menus, Child
and Adolescent Trial for Cardiovascular Health.
-----------------------------------------------------------
Several elements are associated with these favorable
results.  Population studies that recognize differing
cultural norms, including language, and target them for
particular attention were effective.  Studies using material
written at comprehension levels appropriate to the intended
audiences also were more successful.  The inclusion in a
population study of communication channels appropriate to
all SES groups, including those of lower-SES strata, appears
to be of particular importance.
Another element is recognition of the need to involve whole
communities in these programs.  The successful programs were
sensitive to the unique needs of low-SES groups, but the
message was delivered to all individuals living in that
population.  CVD is a population-wide epidemic and, although
higher rates are observed in low-SES groups, the burden to
all society is great.  An important observation here is that
programs that work best involve all groups in society, not
just high-risk, low-SES groups.
Finally, sustained programs that can be accessed by everyone
and those that involve environmental alterations such as
offering healthier food choices are needed.
In summary, progress has been made in the population control
of  CVD risk in all societal groups over the past decades.
However, low-SES groups remain at higher risk than those in
the upper strata.  There is a need to reduce this
differential.  Methods are available at the population level
to induce favorable changes; however, they are not widely or
effectively applied.  One of the important public health
missions is to ensure wider application of known knowledge.
RECOMMENDATIONS
*  Regular ongoing surveillance of CVD risk and outcomes
   should be maintained.  Patterns are changing and
   education programs need to be tailored to current, not
   past, data.
*  Research is needed to understand the effects of broad
   community programs on the cardiovascular health of
   individuals.  This is particularly true of large-scale
   environmental programs and includes change in citizen
   access, change in regulations and development of healthy
   choices for nonsmoking, healthy eating patterns, and
   physical activity.
*  Methods to disseminate current information and successful
   community efforts need to be maintained and even
   increased.
REFERENCES
1.  Fortmann SP, Williams PT, Hulley SB, Maccoby N, Farquhar
    JW:  Does dietary health education reach only the
    privileged?  The Stanford Three Community Study.
    Circulation  1982;66:77-82.
2.  Farquhar JW, Fortmann SP, Flora JA, Taylor CB, Haskell
    WL, Williams PT, Maccoby N, Wood PD:  Effects of
    community-wide education on cardiovascular disease risk
    factors:  the Stanford Five-City Project.  JAMA
    1990;264:359-365.
3.  Winkleby MA, Fortmann SP, Rockhill B:  Trends in
    cardiovascular disease risk factors by educational
    level:  the Stanford Five-City Project.  Prev Med
    1992;21:592-601.
4.  Carleton RA, Lasater TM, Assaf AR, Feldman HA, McKinlay
    S, and the Pawtucket Heart Health Program Writing Group:
    The Pawtucket Heart Health Program:  community changes
    in cardiovascular risk factors and projected disease
    risk.  Am J Public Health  1995;85:777-785.
5.  Luepker RV, Murray DM, Jacobs DR Jr, Mittelmark MB,
    Bracht N, Carlaw R, Crow R, Elmer P, Finnegan J, Folsom
    AR, Grimm R, Hannan PJ, Jeffery R, Lando H, McGovern P,
    Mullis R, Perry CL, Pechacek T, Pirie P, Sprafka JM,
    Weisbrod R, Blackburn H:  Community education for
    cardiovascular disease prevention:  risk factor changes
    in the Minnesota Heart Health Program.  Am J Public
    Health  1994;84:1383-1393.
6.  The COMMIT Research Group:  Community intervention trial
    for smoking cessation (COMMIT):  I.  Cohort results from
    a four-year community intervention.  Am J Public Health
    1995;85:183-192.
7.  Jeffery RW, Forster JL, French SA, Kelder SH, Lando HA,
    McGovern PG, Jacobs DR Jr, Baxter JE:  The Healthy
    Worker Project:  a work-site intervention for weight
    control and smoking cessation.  Am J Public Health
    1993;83:395-401.
8.  Sorensen G, Lando H, Pechacek TF:  Promoting smoking
    cessation at the workplace:  results of a randomized
    controlled intervention study.  JOM  1993;35:121-126.
9.  Walter HJ, Hofman A, Vaughan RD, Wynder EL:
    Modification of risk factors for coronary heart disease:
    five-year results of a school-based intervention trial.
    N Engl J Med  1988;318:1093-1100.
10. Perry CL, Stone EJ, Parcel GS, Ellison RC, Nader PR,
    Webber LS, Luepker RV:  School-based cardiovascular
    health promotion:  the Child and Adolescent Trial for
    Cardiovascular Health (CATCH).  J School Health
    1990;60:406-413.
11. Perry CL, Kelder SH, Murray DM, Klepp KI:  Community-
    wide smoking prevention:  long-term outcomes of the
    Minnesota Heart Health Program and the Class of the 1989
    Study.  Am J Public Health  1992;82:1210-1216.
-----------------------------------------------------------
Interventions Targeted to Ethnic Minorities, Especially
Women
Mary Helen Deer-Smith, R.N.
Minorities, by definition "less than," are always
disadvantaged, numerically or otherwise.  Health statistics
show a great disparity in health status between the various
ethnic groups and the majority population.  However,
awareness of the magnitude of this disparity provides
insufficient motivation for individuals and health
professionals to close the gap.
The most accepted explanation for the gap in health status
is differences in socioeconomic status (SES).  There is a
well-recognized relationship between poverty and ill health;
moreover, because poverty, unlike genetic factors, may be
remedied, universal access to health care with a strong
emphasis on prevention would appear to have potential for
closing the gap in health status.
Concern for health is universal.  However, the pursuit of
health, perception of health problems, presentation of
symptoms, care-seeking behavior, length of time in care, and
evaluation of care are also culturally influenced.  Another
factor known to contribute to health disparities is
difference in health behaviors, shifting the burden toward
the individual.  Although lifestyle has often been
emphasized, one must recognize that, even if minorities
implemented all the recommended preventive behaviors, a gap
would still appear in health status.
Health of a community is not exclusively an individual
affair.  Discriminatory attitudes of the white population
toward minority groups have contributed to the disparity in
health status.  Minorities are discouraged not by the
magnitude of the difference in health status but by their
recognition that they are at a disadvantage, no matter how
hard they try.  In an aggressively competitive society,
those with greater resources will always surpass those with
fewer, yet the inherent injustices multiply when the
majority criticizes the disadvantaged for not achieving the
same results, whether in health status, education level, or
employment.
Working for 20 years in an urban American Indian health
program, I criticized the young mothers for not being more
compliant in bringing their children back for regular well-
baby checks or followup visits, until I realized the
subsistence-level conditions in which many of these patients
lived.  It is difficult to prioritize coming to clinic with
more than one child and waiting to see the doctor or nurse,
when you may not know if you will have a place to sleep that
night or where you will find the money to feed your children
that day.
But we try.  Programs with funding from the foundations and
federal agencies now provide not only a set of statistics
but resources that will help communities become healthier.
Emerging Patterns of Diabetes and Obesity
A study of the prevalence of diabetes/hyperglycemia and
associated cardiovascular disease (CVD) risk factors in
blacks and whites began with vital statistics records
demonstrating that death rates from CVD are higher among
blacks than whites in the United States.  Diabetes mellitus
is an important CVD risk factor, and death rates from
diabetes are higher among blacks than whites.  The study
reported the prevalence rates of diabetes, asymptomatic
hyperglycemia, and CVD risk factors in an employed
population of 28,895 whites and 2,607 blacks, ages 25 to 64
years.  A divergent pattern of obesity was observed, with
black females being by far the most overweight.  Preliminary
mortality data for males suggest that both blacks and whites
with diabetes have sizeably higher death rates than those
without diabetes; a black-white differential is not
apparent.
Diabetes was rare in Oklahoma Indians before 1940.  In the
19th century, they were typically very lean.  Most were
active in outdoor activities; many were nomadic hunters and
meat eaters.  In the past several decades, however, Indian
lifestyles have changed completely.  Outdoor activities have
declined drastically, but the Indian diets, concepts of
ideal weight, and metabolic system are largely unchanged.
Apparently, the consumption of calories is excessive in
relation to energy expenditure.  This excess is
substantially derived from a high-fat diet, which was
necessary in the past.
Attitudes toward adiposity also play an important role.  It
is believed by middle-aged Plains Indian women that they
should weigh about 50 pounds more than what would be
considered ideal by upper-class white women.  This concept
may have originated during the era of confinement at the
Fort Sill brigade, when most of the Indians living there
were very lean, and overweight or abundant women were
considered beautiful.  It is interesting to find that
diabetes rates and obesity levels increase significantly as
the degree of "Indianness" increases.
There is no doubt that both genetic and environmental
factors contribute to the high prevalence of diabetes in
Oklahoma Indians.  The diets, opinions, and attitudes toward
obesity are essential environmental factors.  Thus, in
addition to basic research on genetic, metabolic, and
biochemical characteristics related to diabetes, the
importance of cultural effects cannot be ignored.
Diet and Culture
Nutritional management is the cornerstone of any treatment
program for diabetes mellitus, either insulin-dependent
(IDDM) or noninsulin-dependent (NIDDM).  However, compliance
with the diet prescription by American Indians with diabetes
is low.  A study found that of 90 Cherokee Indians with
NIDDM, only 14 percent reported themselves in compliance
with the diet order.  Nearly one-fifth of the sample had
difficulty using the exchange system for meal planning, and
12 percent did not follow the diet because they wanted to
use local foods and cooking methods.
All people use food in culturally defined ways.  Everyone
must eat, but what people eat, how they eat it, and with
whom vary from one culture to another.  Culturally
determined food behaviors include food production,
processing, and preservation; consumption; ritual use of
foods; food taboos; and sharing food with others.
In many American Indian cultures, food has great religious
and social value.  Food is an integral part of the numerous
celebrations and the main attraction at feast day
celebrations, powwows, and religious ceremonies.
Hospitality, which includes serving food, is a serious
obligation.  It is socially and culturally unacceptable for
a guest to refuse food offered at these occasions.
Food also has a significant role in traditional medicine.
Sioux Indians have a high regard for traditional foods and
medicinal plants.  Florida Seminole Indians using Indian
medicine revealed that they could not follow diets as
prescribed by biomedical practitioners because many fruits
and vegetables are forbidden while using traditional
medicine.
Targeted Interventions
Obesity is a major health concern for most American Indian
tribes.  The increasing rates of obesity and diabetes may be
related to recent changes in lifestyle among many American
Indian tribes.  Modernization has resulted in three major
lifestyle changes: 1) reduced energy expenditure due to
sedentary lifestyles; 2) change from a diet high in fiber
and unrefined carbohydrates to one high in refined and
simple carbohydrates and low in fiber; and 3) stress due to
acculturation.
It is important to note the wide use of the commodity
program in Indian country.  Peanut butter, butter, cheese,
canned meats, flour, rice, and canned vegetables and fruit
are nutritious if prepared properly and in proper amounts.
These foods, along with food from the federal Women,
Infants, and Children Program (WIC) vouchers (i.e., milk,
cheese, cereal, eggs), are high in fat content.  Poverty
rates in the Indian community are high and families rely on
these food supplement programs to feed their children.  It
would be beneficial for the nutritionists in these
communities to teach cooking techniques and menu preparation
using available foods rather than preferred foods.
For many centuries the Zunis and other Pueblo Indians prided
themselves on a tradition of fitness; many tribal members
were runners of great strength and endurance.  During the
last century their lifestyle has become sedentary, resulting
in obesity and diabetes.  In 1976, the diabetes rate for
Zuni Indians over age 45 was 25 percent.  In an effort to
reduce obesity, prevent diabetes, and revitalize cultural
values, a fitness program was initiated on the Zuni Indian
Reservation in 1983.  It includes weight control programs,
exercise classes, running clubs, and a variety of other
fitness activities.  And it began with one woman and the
health educator.  Persistence and positive results expanded
the program, and it has been very successful.  Overweight
Zuni Indians have lost weight, tribal members with diabetes
have stopped taking medications because their fasting blood
sugar levels have gone down, and the Zuni tradition of
fitness has been rekindled.
Cultural diversity challenges health practitioners and
educators.  We must become aware of our own health beliefs,
attitudes, and values to bridge crosscultural gaps with our
clients successfully.  Health care providers must recognize
and respect clients' cultural heritage and adapt their
education and treatment programs appropriately.  Some
techniques and approaches that address the challenges posed
in providing culturally relevant preventative medicine and
health education include the following:
*  Recognize and respect each client's health care beliefs;
*  Learn about the community's cultural food behaviors;
*  Develop culturally relevant education programs to teach
   self-care skills;
*  Develop community and family support; and
*  Increase involvement by the minority population.
We must recognize the power of culture to prevent disease
and promote health.  Cooperation and receptivity increase
when the client knows that the health care provider values
and respects cultural differences.  This respect, along with
a genuine interest in each client, can lead to better health
outcomes.
REFERENCES
1.  Cooper R, Liu K, Stamler J, Schoenberger J, Shekelle R,
    Collette P, Shekelle S: Prevalence of
    diabetes/hyperglycemia and associated cardiovascular
    risk factors in black and whites: Chicago Heart
    Association Detection Project in Industry.  Am Heart J
    1984;108:827-833.
2.  Lee ET, Anderson PS Jr., Bryan J, Bahr C, Coniglione T,
    Cleves M: Diabetes, parental diabetes, and obesity in
    Oklahoma Indians.  Diabetes Care 1985;8:107-113.
3.  Jackson MY, Broussard B: Cultural challenges in
    nutrition education among American Indians. Diabetes
    Educ 1987;13:47-50.
4.  Centers for Disease Control and Prevention: Community-
    based exercise intervention: the Zuni Diabetes Project.
    MMWR 1987;36:661-664.
-----------------------------------------------------------
National Cardiovascular Disease Education Programs
Gregory J. Morosco, Ph.D., M.P.H.
The National Heart, Lung, and Blood Institute (NHLBI) serves
as the lead agency for the Heart Disease and Stroke Priority
Area of the Healthy People 2000 national disease prevention
and health promotion objectives. Since launching the Healthy
People 2000 objectives for the nation, the United States has
witnessed noteworthy declines in the death toll of coronary
heart disease (CHD) and stroke.  Prevention  -  lifestyle
improvements by the American public and better control of
the risk factors for cardiovascular disease (CVD)  -  has
been a major factor in these declines.  Blood lipid levels,
specifically total cholesterol, have been reduced as
Americans have adopted heart-healthy eating patterns.
Average blood pressure levels have dropped, and blood
pressure control in the United States is among the best in
any industrialized nation.  Cigarette smoking rates  -
although now appearing to level off  -  have declined over
the years, with fewer people beginning to smoke.
During the past 15 years, these improvements have been
associated with a continuing decline in population levels of
CHD and stroke.  Most of these positive changes, however,
still fall short of the national goals set forth in Healthy
People 2000.  The prevalence of overweight has increased,
moving away from rather than toward the Healthy People 2000
target.  Prevention efforts have not reached all segments of
American society equally:  Minorities and persons of low
socioeconomic status (SES) have not seen the same degree of
improvement in lifestyle and risk factor control.
Predictably, these differences also are reflected in death
rates for CHD and stroke:  The rates are higher, and the
decline has not been as substantial for some special
populations.  If this phenomenon persists, it will
jeopardize achievement of the nation's goals for the year
2000.
These challenges are being addressed by a broad-based,
twofold strategy for risk reduction that involves a high-
risk approach for persons at increased risk for CHD and
stroke, as well as population-wide efforts that emphasize
primary prevention.  The high-risk approach through the
medical model seeks to improve identification and treatment
of individuals at increased risk for CHD and stroke through
development of treatment guidelines for health professionals
and patient education materials.  The population-based
strategy uses the public health approach to reduce the
prevalence of risk factors in the population.  Both
approaches rely on three central principles that have served
as a foundation for effective prevention strategies of the
past.
The first principle is that prevention programs must rest
squarely on a base of scientific evidence ranging from basic
science and animal models to epidemiological, clinical, and
prevention demonstration studies.  Thus the NHLBI  -  as the
lead agency  -  is strategically linked to the science base.
This science base provides the crucial evidence that
interventions aimed at lowering CVD risk factors actually
will reduce the toll of CHD and stroke in the general
population, as well as the risk for those at high risk for
CHD and stroke.
The success of these strategies relies on a two-way
relationship between prevention education and research.
Epidemiologic and other studies have identified CVD risk
factors.  Clinical trials have assessed new therapies and
potential benefits of treatment.  Community-wide studies
have demonstrated that population-wide strategies of disease
prevention and health promotion are feasible and that the
environmental change programs in the community are
effective.  Survey research has assisted the NHLBI in
understanding the target audience and evaluating the program
progress by documenting changes over time in public and
professional knowledge, attitudes, and behaviors.  As the
science base changes, recommendations for medical practice
or population-wide education efforts change to reflect the
new knowledge.  The research responds by addressing gaps in
the knowledge, barriers to reaching particular targets of
these education efforts, or barriers to applying this
research to practice.
The second principle is that effective prevention strategies
must involve a variety of organizations that operate as a
partnership.  The mission to reduce death and disability
from CHD and stroke is larger than all the organizations
involved  -  heart disease is the leading cause of death in
the nation, and stroke is the third leading cause of death.
To meet this challenge, the NHLBI coordinates the National
High Blood Pressure Education Program (NHBPEP) and the
National Cholesterol Education Program (NCEP).  Both operate
by building partnerships with a broad network of
organizations to reach a wide audience.  The most salient
example of partnerships in the national programs is that of
the NHBPEP and NCEP Coordinating Committees.  These two
committees serve as the Healthy People 2000 Working Group
for CHD and Stroke.  Representatives of more than 40
nonprofit organizations constitute the coordinating
committee of each program.  The membership includes major
medical and health organizations, voluntary health
organizations, community programs, and government agencies
committed to improving the health of the nation through
education, better treatment, and prevention.
Partnerships with these organizations are forged to meet the
special needs of specific minority populations, to reach
children and young adults to encourage healthy eating and
increase physical activity, and to disseminate patient
education materials of the NHBPEP and NCEP to the
appropriate target audience.  The year 2000 objectives
address all Americans, and special alliances are joined to
reach Americans outside the traditional health care system
-  children, minorities, and the underserved.
Other examples of partnerships include the state and
community alliances to reduce the burden of CVD nationwide.
On February 1, 1995, the Association of State and
Territorial Health Officials and its state affiliates for
chronic disease, health promotion and education, and public
health nutrition unveiled an action plan for preventing and
controlling CHD and stroke.
The third principle is that public, professional, and
patient education relies on the use of effective
communication strategies.  The programs utilize the efforts
of all the coordinating committee organizations to carry out
these education activities.  All three audiences are
important targets for messages about CVD risk factors.  In
professional education, the programs use materials and kits
for physicians, continuing medical education activities, and
presentations at professional meetings.  Educational
materials for patients are distributed both through
professionals and directly by the NHLBI Information Center.
For the public, the programs develop public service
announcements for radio and television, print ads for
newspapers and magazines, airport posters, billboards, fact
sheets, and other publications.
The remarkable coalescence of scientific evidence on the
causes and prevention of CHD and stroke and community
studies on the dissemination of prevention messages has
resulted in strategies that have changed medical practice,
public health policy, and attitudes and lifestyles among
large numbers of Americans.
More intensified outreach efforts will be needed, however,
to reduce the disparity of disease burden seen in certain
minority and lower-SES populations.  For example, blacks
have the highest risk of developing and dying from a stroke.
Blacks also have a higher prevalence of the major modifiable
risk factors for stroke  -  high blood pressure and
cigarette smoking.  Eleven states (Alabama, Arkansas,
Georgia, Indiana, Kentucky, Louisiana, Mississippi, North
Carolina, South Carolina, Tennessee, and Virginia) have age-
adjusted stroke mortality rates that are more than 10
percent higher than the national average.  All except
Indiana are in the Southeast.  The above-average stroke
death rate in this "Stroke Belt" exists for each sex-race
group (black and white men and black and white women).
The NHLBI designed a Stroke Belt Initiative to assist state
health departments in delivering more effective
interventions to reduce the overall risk of stroke in the
region. The projects fall in one of four general education
and intervention categories:  (1) intervention in health
department clinics and outreach services, (2) church-based
risk factor intervention programs, (3) community education
and intervention programs, and (4) public education
campaigns using the mass media.
Interventions in Health Department Clinics and Outreach
Services
The Alabama project uses quality assurance audits and
patient recruitment strategies to improve and expand
existing hypertension detection, treatment, and followup
interventions.  Quality assurance audits are used to
increase the rate of hypertension control among underserved
populations by improving the level of care in 42 county
health department clinics.  An audit team visits the clinics
and reviews patient charts for compliance with 27 standards.
For any standard that is more than 10 percent deficient, a
plan of action to correct it must be developed.  Counties
with excessive deficiencies receive followup audits to
determine whether they have implemented the corrective plan
of action.  The second strategy is patient recruitment and
coordination.  A patient coordinator-recruiter works with
four selected county health units with low patient loads to
increase patient enrollment.  Thus, more patients receive an
improved level of care.
The Indiana State Department of Health has expanded its
emphasis beyond hypertension control to include smoking
cessation.  The project targets low-income and minority
populations in two health centers and their adjacent housing
projects in Indianapolis.  Physicians refer patients with
one or both risk factors.  Health educators work with
patients with high blood pressure to set goals for lifestyle
change.  They meet with patients during regular office
visits with the primary care provider.  They also follow up
on missed office visits and try to solve adherence problems.
Patients with difficulties may receive additional counseling
by the health educator and free nicotine patches.  The
health educators also promote the use of social and family
support for all patients.
The Kentucky project consists of three components.  The
first is a training program on the role of the community
health nurse in CVD.  The nurses receive a 6-hour course on
how to give effective smoking cessation advice to patients.
The second component is a smoking cessation program that
includes smoking cessation classes and support groups for
local health department staff, especially the 800 nurses
employed by the Kentucky Department of Health Services.  The
third component provides extended followup to smokers who
agree to quit and receive a prescription for nicotine
patches from the health department.  The program requires
all smokers to attend a support group.  Public health nurses
conduct followup by telephone and mail beginning on the date
the patient's prescription expires and continuing for 6
months.
Church-based Risk Factor Intervention Programs
The Louisiana Office of Public Health promotes the control
of high blood pressure and other risk factors (diet,
exercise, and smoking) in churches throughout the state.
Health department staff support and maintain 26 church
programs in the New Orleans area and subcontract with a
medical center to support programs in 60 churches in
northern Louisiana.  The intervention strategy includes the
following: (1) establishing and training volunteer
coordinators in each church, (2) certifying lay blood
pressure workers in each congregation, (3) conducting focus
groups and taste tests to promote dietary changes, and (4)
conducting outreach activities to develop community support
and encourage collaboration among local churches.
The Virginia project is a cooperative effort between the
Virginia Department of Health and the Baptist General
Convention to promote stroke risk reduction programs in
black churches.  The project focuses on delivering
hypertension control, smoking cessation, and nutrition and
weight loss programs to black churches.  The project (1)
recruits and trains nurses and blood pressure measurement
specialists in the Baptist General Convention churches to
serve as area coordinators and to train other volunteers in
hypertension detection and control, smoking cessation, and
nutrition programs, (2) develops, produces, and distributes
an easy-to-read manual on high blood pressure, smoking
cessation, and nutrition, (3) develops, produces, and
distributes with church pastors and members, a health-
related brochure for churches, (4) provides incentives for
pastoral and congregational participation, and (5) provides
training to Baptist General Convention coordinators as well
as health department staff members, who often assist in
blood pressure screening and referral activities.
Community Education and Intervention Programs
The state of Arkansas is applying community organization
approaches to help 10 communities in 14 counties to promote
stroke prevention activities.  Two graduate school interns,
a health educator, and a social worker organize planning
groups and prepare them to carry out stroke risk reduction
activities.  They work with area managers and local health
unit administrators to identify local leaders and form
planning groups.  The planning group in each community
selects the education program and the methods of delivery.
The Mississippi hypertension education and intervention
program targets high-risk populations in the state's largest
health districts.  The project placed blood pressure
measurement machines in the six southernmost counties,
offering people a way to check their blood pressure for
free.  The machines display a message instructing persons
with elevated blood pressure to see a doctor and advise
those without a source of care or resources to pay for care
to call a toll-free number.  The project nurse helps callers
find a source of care, and also arranges for drugs,
nutrition counseling, and social services as needed.  During
6 months of operation, the machines recorded 22,277 blood
pressure readings.  The project also has a community
education component to support the use of hypertension
detection and referral services by arranging or conducting
presentations and other education activities at churches,
schools, businesses, community agencies, and other
appropriate groups.
The South Carolina Strike Out Stroke Project is a 3-year
effort to improve hypertension awareness, treatment, and
control among blacks and increase the number of community-
based hypertension control programs serving blacks.
Churches, fraternities and sororities, barber shops and
beauty shops, and black colleges are the targets for
education and intervention programs by local health
departments.  The project trains local health department
staff to identify black institutions and organizations to
target, conduct training workshops, and provide technical
assistance in carrying out hypertension education and
control activities.
In Tennessee, smoking reduction efforts are promoted in
three major metropolitan communities with large black
populations (68.6 percent of all the state's blacks live in
the three counties).  The role of the Tennessee Department
of Health is to coordinate services of three independent but
related projects managed by the Chattanooga-Hamilton County
Health Department, the Metropolitan-Davidson County Health
Department, and the Preventing African American Strokes From
the Use of Tobacco (PAAST, Inc.) coalition.
In Chattanooga, the health department incorporated a smoking
cessation component into a state-funded hypertension project
at a community health center.  The project also works with
the Tobacco Use Project Task Force to train individuals in
housing projects to lead smoking cessation groups for other
residents.  Working with the Minority Involvement Committee
of the American Heart Association, the project offers
smoking cessation and hypertension control programs in black
churches.
In Nashville, the health department helps black churches
establish smoking cessation and weight reduction programs.
Members at five churches formed health promotion teams to
coordinate project activities.  The teams developed a
children's letter-writing campaign, a stage play about risk
factors, and food-tasting demonstrations.  In the letter-
writing campaign, children from the churches wrote letters
asking a significant adult in their lives to stop smoking.
Each child follows up at 3, 6, and 12 months to see if the
adult has stopped smoking.  A playwright from a
participating church agreed to write a play about CVD and
stroke risk factors that actors perform during church
services.  The play, when perfected, will be videotaped for
wider distribution.
PAAST, Inc., also located in Tennessee, is a coalition
established to educate the black community about the harmful
effects of smoking and overweight and to stimulate
community-based smoking and weight control programs.  The
coalition targeted three black churches for health promotion
activities.  During the first year, the weight control
component enrolled 136 members of the congregation, compared
with only 14 for the smoking cessation program.  The Youth
Mentor Program consists of 20 black teenagers who make
presentations on risk factors to adult and youth
organizations.  They encourage smoking cessation and lead
support groups for adults who want to quit.
Public Education Campaigns Using the Mass Media
The Georgia project encourages persons aware of their high
blood pressure to stay on treatment.  The Georgia Department
of Human Resources subcontracted with a communications firm
to assist in developing and promoting a mass media campaign,
which involves TV, radio, and print media.  The project
trains local health department staff to work with local
media to promote the campaign, and it also conducts the
successful Strike Out Stroke campaign with the Atlanta
Braves professional baseball team.  This includes public
service announcements, live TV coverage, and blood pressure
screening and other activities at the stadium during
selected games.  A working relationship is being developed
with smaller TV stations outside Atlanta and with the Black
Radio Network of Gospel and Talk Radio Stations.  The print
campaign includes feature articles, health reports, human
interest stories, and letters to the editor for small-town
newspapers.  Finally, the Georgia Department of Human
Resources installed automated blood pressure, pulse rate,
and weight monitoring equipment in one of the state office
buildings providing service to more than 1,700 state
employees.
The North Carolina project targets blacks and features a
mass media education campaign, distribution of culturally
sensitive educational materials, and training for local
health department staff members.  The project targets the 36
county health departments that receive funds to implement
hypertension control programs.  The community awareness and
mass media activities concentrate on radio and target the
four major media markets with large black audiences.  The
campaign emphasizes the importance of hypertension control
as the most important step to reduce the risk of stroke.
Local health department staff members also received training
on using mass media approaches.  The project staff developed
and is mass-producing culturally sensitive materials and
providing them to local health department clinics, rural
health centers, and worksite health promotion programs.
The progress made toward meeting the Healthy People 2000
objectives suggests that CVD prevention programs are having
a substantial effect.  Of the 17 objectives in the CHD and
stroke priority area, data for 14 objectives show progress
toward meeting the year 2000 targets, including one
objective that has already been met.  From 1972 to 1992, the
CHD death rate declined about 58 percent.  In 1990, 76
percent of the population had their blood pressure measured
within the previous 2 years and could state whether it was
normal or high.  The year 2000 target of 90 percent is
attainable.  Eighty percent of those who have been told they
have high blood pressure are taking action to control their
blood pressure; the target for the year 2000 is 90 percent.
From 1978 to 1990, the mean serum cholesterol level fell
from 213 mg/dL to 205 mg/dL, and the percentage of the
population with high blood cholesterol fell from 26 percent
to the year 2000 target of 20 percent.
The progress that has been made demonstrates the
effectiveness of science-based public health strategies that
rely on partnership between government and the private
sector in combating the barriers to reducing CHD and stroke
in the population.  Although the challenges ahead must be
addressed to reach the Healthy People 2000 objectives, the
progress to date shows what can be accomplished when the
different sectors of society join forces to address a common
problem.
-----------------------------------------------------------
Appendix
-----------------------------------------------------------
Chairs and Speakers
Steven N. Blair, P.E.D.
Cooper Institute for Aerobics Research
Dallas, Texas
Jeffrey A. Cutler, M.D., M.P.H.
National Heart, Lung, and Blood Institute
Bethesda, Maryland
Mary Helen Deer-Smith, R.N.
American Indian Center
Euless, Texas
Paul Eggers, Ph.D.
Health Care Financing Administration
Baltimore, Maryland
Jacob J. Feldman, Ph.D.
National Center for Health Statistics
Hyattsville, Maryland
L. Julian Haywood, M.D.
LAC + USC Medical Center
Los Angeles, California
Helen P. Hazuda, Ph.D.
University of Texas Health Science Center at San Antonio
San Antonio, Texas
Millicent Higgins, M.D.
National Heart, Lung, and Blood Institute
Bethesda, Maryland
James S. House, Ph.D.
University of Michigan
Ann Arbor, Michigan
Clifford L. Johnson, M.S.P.H.
National Center for Health Statistics
Hyattsville, Maryland
George A. Kaplan, Ph.D.
California Department of Health Services
Berkeley, California
Shiriki K. Kumanyika, Ph.D., R.D., M.P.H.
University of Illinois at Chicago
Chicago, Illinois
Anton E. Kunst, M.A.
Erasmus University Rotterdam
The Netherlands
Elisa T. Lee, Ph.D.
University of Oklahoma Health Sciences Center
Oklahoma City, Oklahoma
Russell V. Luepker, M.D.
University of Minnesota
Minneapolis, Minnesota
Daniel B. Mark, M.D., M.P.H.
Duke University Medical Center
Durham, North Carolina
Michael G. Marmot, M.D., Ph.D.
University College London Medical School
London, England
Gregory J. Morosco, Ph.D., M.P.H.
National Heart, Lung, and Blood Institute
Bethesda, Maryland
Judith K. Ockene, Ph.D.
University of Massachusetts Medical School
Worcester, Massachusetts
Kristina Orth-Gomer, M.D., Ph.D.
National Institute of Psychosocial Factors in Health
Stockholm, Sweden
Thomas A. Pearson, M.D., Ph.D.
Mary Imogene Bassett Research Institute
Cooperstown, New York
Beatriz L. Rodriguez, M.D., Ph.D.
Kuakini Medical Center
Honolulu, Hawaii
Paul D. Sorlie, Ph.D.
National Heart, Lung, and Blood Institute
Bethesda, Maryland
Jeremiah Stamler, M.D.
Northwestern University Medical School
Chicago, Illinois
Rose Stamler, M.A.
Northwestern University Medical School
Chicago, Illinois
Herman A. Tyroler, M.D.
University of North Carolina
Chapel Hill, North Carolina
Redford B. Williams, M.D.
Duke University Medical Center
Durham, North Carolina
-----------------------------------------------------------
Contributing Authors
Sujata Archer, Ph.D.
Northwestern University Medical School
Chicago, Illinois
Eric Backlund, M.S.
U.S. Bureau of the Census
Suitland, Maryland
John C. Barefoot, Ph.D.
Duke University Medical Center
Durham, North Carolina
Cecil M. Burchfiel, Ph.D.
Kuakini Medical Center
Honolulu, Hawaii
Nancy Clapp-Channing, R.N., M.P.H.
Duke University Medical Center
Durham, North Carolina
J. David Curb, M.D.
Kuakini Medical Center
Honolulu, Hawaii
Ka-On Fong, M.A.
Kuakini Medical Center
Honolulu, Hawaii
Daniel I. Galper, M.S.
Virginia Polytechnic Institute and State University
Blacksburg, Virginia
Daniel Garside, B.S.
Northwestern University Medical School
Chicago, Illinois
Oscar T. Go, Ph.D.
Center for American Indian Health Research
Oklahoma City, Oklahoma
Greg Grandits, M.S.
University of Minnesota
Minneapolis, Minnesota
Kurt Greenlund, Ph.D.
Northwestern University Medical School
Chicago, Illinois
Feikje Groenhof,  M.A.
Erasmus University Rotterdam
The Netherlands
John Harrington, Ph.D.
University of Massachusetts Medical School
Worcester, Massachusetts
Norman J. Johnson, Ph.D.
U.S. Bureau of the Census
Suitland, Maryland
Marilyn Knowles, M.P.H.
University of North Carolina at Chapel Hill
Chapel Hill, North Carolina
Lai Choi Lam, M.S.
Duke University Medical Center
Durham, North Carolina
Johan Mackenbach, M.D., Ph.D.
Erasmus University Rotterdam
The Netherlands
Diane M. Makuc, Dr.P.H.
National Center for Health Statistics
Hyattsville, Maryland
Mark Massing, M.D.
University of North Carolina at Chapel Hill
Chapel Hill, North Carolina
James D. Neaton, Ph.D.
University of Minnesota
Minneapolis, Minnesota
Christopher T. Sempos, Ph.D.
University of Illinois at Urbana-Champaign
Urbana, Illinois
Dan S. Sharp, M.D., Ph.D.
Kuakini Medical Center
Honolulu, Hawaii
Ilene C. Siegler, Ph.D., M.P.H.
Duke University Medical Center
Durham, North Carolina
Deborah N. Wentworth, M.P.H.
University of Minnesota
Minneapolis, Minnesota
David R. Williams, M.A., Ph.D.
University of Michigan
Ann Arbor, Michigan
Katsuhiko Yano, M.D.
Kuakini Medical Center
Honolulu, Hawaii
-----------------------------------------------------------
Coordination
Barbara Marzetta Liu, S.M.
Director
Science and Legislation Program
Office of Science and Technology, NHLBI
Bethesda, Maryland
Barbara Packard, M.D., Ph.D.
Associate Director for Scientific Program Operation, NHLBI
Bethesda, Maryland
Elizabeth Brenyo
Secretary
Office of Science and Technology, NHLBI
Bethesda, Maryland
Judy Corbett
Program Analyst
Office of Science and Technology, NHLBI
Bethesda, Maryland
Steven LeBlanc
Program Analyst
Office of Science and Technology, NHLBI
Bethesda, Maryland
Deborah Noble
Program Analyst
Office of Science and Technology, NHLBI
Bethesda, Maryland
-----------------------------------------------------------
Discrimination Prohibited:
Under provisions of applicable public laws enacted by
Congress since 1964, no person in the United States shall,
on the grounds of race, color, national origin, handicap, or
age, be excluded from participation in, be denied the
benefits of, or be subjected to discrimination under any
program or activity (or, on the basis of sex, with respect
to any education program or activity) receiving Federal
financial assistance.  In addition, Executive Order 11141
prohibits discrimination on the basis of age by contractors
and subcontractors in the performance of Federal contracts,
and Executive Order 11246 states that no federally funded
contractor may discriminate against any employee or
applicant for employment because of race, color, religion,
sex, or national origin.  Therefore, the National Heart,
Lung, and Blood Institute must be operated in compliance
with these laws and Executive Orders.
-----------------------------------------------------------
U.S. Department of Health and Human Services
Public Health Services
National Health Institutes
National Heart, Lung, and Blood Institute