1. Epidemiology and Social Epidemiology
Yun-Mi Song, MD, MPH, PhD
Department of Family Medicine
Sungkyunkwan University School of Medicine, Korea

2. Epidemiology

3. Definition The study of the distribution and determinants
Epidemiology
Definition
The study of the distribution and determinants
of health-related states or events
in specified populations and
the application of this study to control health problems.
(In: Last JM. A dictionary of epidemiology. 3rd ed. New York, NY: Oxford University Press; 1995)

4. Epidemiology
Aims
To contribute information relevant to the prevention of disease and the promotion of health.
Centered around individuals and individual risk factors.

5. Epidemiology
Question
Why did this individual get sick?

6. Disease classification Scheme
Epidemiology
Disease classification Scheme
Based on a clinical approach to disease and
focused on the individual.

7. Special Areas Epidemiology Focused on Exposure Nutritional
Environmental
Genetic
Social
Focused on
Population
Clinical
Focused on Outcome
Cancer
Cardiovascular
Psychiatric
Infectious disease
Reproductive

8. Social Epidemiology

9. Background Social Epidemiology
While diseases have come and gone, some infectious diseases have been eradicated, others have emerged, and a host of noninfectious diseases have dominated the profile of causes of death and disability, social inequalities in health remain.
Social factors in the environment would not determine which individuals in the group would have health problems but they would help to explain group differences in the rate over time.
Health and well-being of a community were affected by the social milieu within which people lived. Even if the interventions on individual level were completely successful, new people would continue to enter the at-the risk population at an unaffected rate since we have done nothing to influence those forces in the community that caused the problem in the first place.

10. Question Why is this society unhealthy? Social Epidemiology
The choices that individuals make are inadequate for the purposes of explaining why some societies have high rates of heavy drinking, hypertension, obesity, and diabetes.

11. Social Epidemiology
Definition
A branch of epidemiology that studies the social distribution and
social determinants of
states of health, disease, and well-being
rather than treating such determinant
as mere background to biomedical phenomena.

12. Social Epidemiology
Aims
To conceptualize, operationalize, and test the association between aspects of social determinants (environment) and a range of population health and well-being

13. social environment/social ecology
Social Epidemiology
Social determinant vs.
social environment/social ecology
Social environment/ecology are problematic in that they can conceal the role of human agency
in creating social conditions that constitute social determinants of health

14. Social determinants of health
Social Epidemiology
Social determinants of health
A society’s past and present economic, political, and legal systems, its material and technological resources, and its adherence to norms and practices consistent with international human rights norms and standards
A society’s external political and economic relationships to other countries, as implemented through interactions among governments, international political and economic organizations and non-governmental organizations.

15. Focused on specific social phenomenon
Social Epidemiology
Focused on specific social phenomenon
Socioeconomic stratification
Social networks
Social support/cohesion
Discrimination
Work place organization
(demands and control)

16. Social Environment Social Epidemiology International Country County
City
Neighborhood
Workplace
family

17. Educational statistics
Cross-disciplinary enterprise
Theories, measurement tools, analytical techniques
Social
Epidemiology
Educational statistics
Medical geography
Demography
Political science
Sociology
Physiology
Anthropology
Economics
Biology
Social Psychology
Preventive medicine

18. From a Forword by S. Leonard Syme in Social Epidemiology
The maturation of social epidemiology is of great importance because it provides several perspectives upon
epidemiologic research that are crucial to its mission.
First, much-needed focus on the family, neighborhood, community, and social group
Second, a more appropriate way to study risk factors and diseases that can fundamentally change our approach to the concepts of etiology and intervention.
From a Forword by S. Leonard Syme in Social Epidemiology

19. in Social Epidemiology
Guiding Concepts
in Social Epidemiology

20. I. Population perspective
An individual’s risk of illness
cannot be considered in isolation
from the disease risk of the population
to which she/he belongs. (Rose G, 1992)

21. Geographical variation in life expectancy at birth in England and Wales is largely explained by deprivation Woods LM et al. J Epidemiology Comm Health 2005;59: )
To describe the population mortality profile by deprivation in each government office region (GOR) during 1998, / To quantify the influence of geography and deprivation in determining life expectancy.
Design: Construction of life tables describing age specific mortality rates and life expectancy at birth from death registrations and estimated population counts.
Life tables were created for (a) quintiles of income deprivation based on the income domain score of the index of multiple deprivation 2000, (b) each GOR and Wales, and (c) every combination of deprivation and geography.
Conclusions: Geographical patterns of life expectancy are mainly attributable to variations in deprivation status

22. Annual deprivation specific mortality rates per and the mortality rate ratio between the smoothed rates of the deprived and the affluent (right hand axis), by single year of age and sex, England and Wales, 1998.

23. (b) life tables by sex and deprivation quintile (squares)
Estimates of life expectancy at birth (England and Wales, 1998) derived from
(a) life tables by sex and government office for the region with Wales (diamonds) and
(b) life tables by sex and deprivation quintile (squares)
Copyright ©2005 BMJ Publishing Group Ltd.

24. II. Social context of behavior
Most behaviors are not randomly distributed in the population. Rather they are socially patterned and often cluster with one another by.
(1) shaping norm
(2) enforcing patterns of social control
(3) providing or not providing environmental
opportunities to engage in certain behaviors
(4) reducing or producing stress for which certain
behaviors may be an effective coping strategy

25. A prospective observational study on the smoking behavior
Trends in socioeconomic differentials in cigarette smoking behaviour between 1990 and 1998: a large prospective study in Korean men (Song YM, et al. Public Health, 2004;118: )
To investigate the magnitude and time trends in socioeconomic differentials in smoking behaviour.
A prospective observational study on the smoking behavior
Subjects: 322,991 men on whom information on monthly salary was available followed up for eight years.
Conclusions: An increasing trend in socioeconomic inequalities in smoking behavior was observed in this study.

26. Trend in smoking status during 8 years of follow-up by age and socio-economic level

27. Trends in relative inequality of smoking status during 8-year of follow-up according to socioeconomic level* at baseline measurement.
Age Group
Years of follow up
P value for trend
1990
1992
1994
1996
1998
RII
95% CI
Relative index of inequality for all-smoking
All subjects‡
0.60
( )
0.59
( )
0.57
( )
0.56
( )
0.01
30-34 year
0.66
( )
0.64
( )
( )
0.61
( )
( )
0.09
35-39 year
0.54
( )
0.52
( )
0.53
( )
0.50
( )
0.49
( )
0.03
40-44 year
0.55
( )
( )
( )
0.51
( )
45-49 year
( )
( )
( )
0.46
( )
0.48
( )
1.91
( )
2.04
( )
2.08
( )
2.13
( )
( )
1.70
( )
1.77
( )
1.86
( )
1.84
( )
1.85
( )
0.06
2.12
( )
2.29
( )
( )
2.37
( )
2.42
( )
0.02
1.97
( )
( )
2.19
( )
2.25
( )
2.26
( )
( )
2.32
( )
2.34
( )
2.54
( )
2.49
( )

28. Job Stress and Breast Cancer Risk: The Nurses’ Health Study (Shernhammer ES, et al.,Am J Epidemiology 2004; 160(11): )
Prospectively (1992–2000) assessed the association between job strain, measured by Karasek and Theorell’s job content questionnaire in four categories (low strain, active, passive, and high strain), and breast cancer risk
Participants in the Nurses’ Health Study (37,562 US nurses)
Multivariate relative risks adjusted for age, reproductive history, and other breast cancer risk factors, the of breast cancer (1,030 cases)
Conclusion: Findings from this study indicate that job stress is not related to any increase in breast cancer risk.

29. Person-years of follow-up
Adjusted relative risk of breast cancer according to category of job strain* (n = 37,562), Nurses’ Health Study, 1992–2000
Job strain category
No. of cases
Person-years of follow-up
Age-adjusted
Multivariate RR
95% CI
Low demand/high control (low strain)
242
60,455
1.0
Low demand/low control (passive)
336
91,172
0.89
0.76, 1.06
0.90
0.76,1.06
High demand/low control (high strain)
250
72,842
0.87
0.73,1.04
0.73, 1.04
High demand/high control (active)
202
63,336
0.83
0.69, 1.01
0.69, 0.99
* Assessed by means of Karasek and Theorell’s job content questionnaire.
(REF: Schernhammer ES et al. Job Stress and Breast Cancer Risk: The Nurses’ Health Study. American Journal of Epidemiology (11): )

30. Psychological distress, physical illness, and risk of coronary heart disease (F Rasul F, et al., J Epidemiology Comm Health 2005;59: )
To confirm the association between psychological distress and coronary heart disease (CHD) and to examine if any association is explained by existing illness.
Prospective cohort study in 6575 men and women aged 45–64 years from Paisley.
30 item general health questionnaire (GHQ),
Conclusion: The association of psychological distress with an increased risk of five year CHD risk in men could be a function of baseline physical illness but an effect independent of physical illness cannot be ruled out. Its presence among physically ill men greatly increases CHD risk.

31. Risk of 0–5, 5–10 year CHD in men and women by baseline psychological distress
CHD events
RR*
95% CI RR
Men
    5
115
1.78
1.15 to 2.75
1.14 to 2.79
1.61
1.02 to 2.55
    10 78
0.43
0.17 to 1.06
0.42
0.17 to 1.04
0.39
0.15 to 0.98
Women 33
1.60
0.74 to 3.44
1.55
0.70 to 3.42
1.37
0.59 to 3.19 77
1.11
0.64 to 1.93
1.05
0.60 to 1.85
0.76
0.42 to 1.36
* Age adjusted; baseline sociodemographic (SD), CHD risk factor adjusted; baseline SD, CHD risk factor and physical illness adjusted.

32. III. Contextual multilevel analysis
The assessment of exposures at an environmental or community level , when coupled with individual level data offer the critical advantages available in the form of multilevel analyses

33. Neighborhood of Residence and Incidence of Coronary Heart Disease (Diez Roux A et al. NEJM 200l;345:99-106)
Examined the relation between characteristics of neighborhoods and the incidence of coronary heart disease using data from the Atherosclerosis Risk in Communities Study in 13,009 participants aged 45 to 64 years.
Neighborhoods: block groups containing an average of 1000 people.
A summary score for the socioeconomic environment of neighborhood: wealth and income, education, and occupation.
Conclusions: Even after controlling for personal income, education, and occupation, we found that living in a disadvantaged neighborhood is associated with an increased incidence of coronary heart disease.

34. Incidence Rates of Coronary Heart Disease, Adjusted for Age, Study Site, and Sex According to Race-Specific Groups of Neighborhoods, defined According to Summary Socioeconomic Scores, and According to Personal Income in Whites and Blacks.
Group 1- the most
disadvantaged
neighborhoods Group 3 - the most
advantaged
neighborhoods.

35. Hazard ratio* for coronary heart disease according to race-specific groups of neighborhood scoresHR
(95% CI)
White Men
Black Men
1 (low)
1.6
( )
1.4
( ) 2
( )
1.1
( )
3 (high)
1.0
White Women
Black Women
( )
1.8
( )
( )
2.4
( )
All White
All Black
( )
1.5
( )
( )
( )
P value for trend
0.008
0.09
* Adjusted for age, study site, income, education, occupation, and behavioral and biomedical risk factors

36. IV. Life-course perspective
Early life influences the onset of disease in middle and later life
H1. Some exposure in early childhood could influence developmental processes.
H2. Disadvantage in early life sets in motion a series of subsequent experiences that accumulate over time to produce disease after 30, 40, 50, or 60 years of disadvantages
H3. While early experiences set the stage for adult experiences, it really only the adult experiences that are directly related to health outcomes.

37. To investigate stroke risk by socioeconomic measures.
Influence of Socioeconomic Circumstances in Early and Later Life on Stroke Risk Among Men in a Scottish Cohort Study (Hart CL et al. Stroke 2000;31: )
To investigate stroke risk by socioeconomic measures.
A 25-year follow-up cohort study of 5765 working men, from 27 workplaces in Scotland, who were screened between 1970 and 1973.
Conclusions: Poorer socioeconomic circumstance was associated with greater stroke risk, with adverse early-life circumstances of particular importance.

38. Relative rates of stroke by father’s social class, adjusted for risk factors
Father’s social class, category
Trend across group
I, II, III
Nonmanual
III
Manual
IV, V
Men, n
1370
2462
1821
Strokes, n 69
189
146
Age adjusted RR 1
1.64( )
1.78( )
0.0002
Multivariate adjusted RR
1.37( )
1.46( )
0.019
* Age, smoking, adjusted FEV1, diastolic and systolic blood pressures, height, alcohol consumption, and preexisting CHD.

39. V. General susceptibility to disease
Social factors influence disease processes by creating a vulnerability or susceptibility to disease in general rather than to any specific disorder.
Whether individuals became ill or died at earlier ages or whether specific socially defined groups had greater rates of disease depended on socially stressful conditions.

40. Subjective socioeconomic position, gender and cortisol responses to waking in an elderly population (Wright CE, et al. Psychoneuroendocrinology 2005;30(6): )
To evaluate whether the cortisol response to awakening (CAR) differed between lower and higher cotisol status.
Ninety three men and women aged 65–80 years took saliva samples on waking, and then 10, 20, 30 and 60 min after waking.
Subjective social status was assessed using the ‘ladder’ measure.
Conclusion: The results are consistent with the notion that higher socioeconomic position protects against stress-related activation of psychobiological pathways which may contribute to variation in disease risk evident in old age.

41. Mean levels of salivary cortisol after waking
for lower (solid line) and higher (dashed line) social status groups.
Error bars are standard errors of the mean.
Lower SEP
Higher SEP

42. References
Krieger N. A glossary for social epidemiology. J Epidemiol comm Health 2001;55:
Bingenheimer JB. Multilevel models and scientific progress in social epidemiology, J Epidemiol comm Health 2005;59:
Kawachi I. Social epidemiology(Editorial). Social Science & Medicine 2002;54:
Vineis P. epidemiology between social and natural sciences. J Epidemiol comm Health 1998;52:
Beckman L, Kawachi I. Editors. Social epidemiology. Oxford University Press, Oxford, 2000
Woods LM, et al. Geographical variation in life expectancy at birth in England and Wales is largely explained by deprivation. J Epidemiology Comm Health 2005;59:
Song YM. Trends in socioeconomic differentials in cigarette smoking behaviour between 1990 and 1998: a large prospective study in Korean men. Public Health, 2004;118:
Shernhammer ES, et al. Job Stress and Breast Cancer Risk: The Nurses’ Health Study. Am J Epidemiology 2004; 160(11):
Rasul F, et al., Psychological distress, physical illness, and risk of coronary heart disease. J Epidemiology Comm Health 2005;59:
Hart CL, et al. Influence of Socioeconomic Circumstances in Early and Later Life on Stroke Risk Among Men in a Scottish Cohort Study. Stroke 2000;31:
Diez Roux A, et al. Neighborhood of Residence and Incidence of Coronary Heart Disease. NEJM 2001;345:
Wright CE, et al., Subjective socioeconomic position, gender and cortisol responses to waking in an elderly population Psychoneuroendocrinology 2005;30(6):