population health and health disparities - a social...

Population Health and Health Disparities -

A Social Epidemiology Perspective

Health Disparities Symposium 2003, University of Washington

John Lynch

Department of Epidemiology

Center for Human Growth and Development

Institute for Social Research

University of Michigan

“ The goal of the 2003 Health Disparities Symposium:

Social Determinants: Methods and Practice is to expose

faculty and students to research on health disparities

and the social determinants of health. ”

“social determinants”

“population health”

and

“health disparities”

US Infant Mortality over the 20th Century

0.0

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1900 1910 1920 1930 1940 1950 1960 1970 1980 1990

Infa

nt M

orta

lity

per

1000

Attempt to understand the

“social determinants” of this

marker of “population health”

Black – White Disparity in Infant Mortality over the 20th Century

0

50

100

150

200

250

300

350

400

1900 1910 1920 1930 1940 1950 1960 1970 1980 1990

Infant M

ortality

per 1

,000

0.020.040.060.080.0100.0120.0140.0160.0180.0200.0

Absolu

te D

isparity

0

50

100

150

200

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350

400

1900 1910 1920 1930 1940 1950 1960 1970 1980 1990

Infa

nt M

orta

lity

per 1

,000

0

0.5

1

1.5

2

2.5

3

Rela

tive D

isparity

Relative Disparity

Absolute Disparity

White

Black

White

Black

• “Population Health”

• “Absolute Health Disparity”

• “Relative Health Disparity”

Improved in all race/ethnic

groups

Reduced

Increased

Infant Mortality

With thanks to:

George Davey Smith, Bristol Dave Leon, LSHTM, London

Steve Kunitz, Rochester Simon Szreter, Cambridge

Yoav Ben-Shlomo, Bristol Di Kuh, UCL, London

Chris Power, UCL, London David Blane, London

Vladimir Shkolnikov, Rostock Tony McMichael, Canberra

Johan Hallqvist, Karolinska, Stockholm Juan Merlo, Lund, Malmo

Pernille Due, Copenhagen Finn Diderichsen, Copenhagen

Nancy Ross, McGill, Canada Michael Wolfson, Stat. Canada

Sam Harper, Michigan George Kaplan, Michigan

Trivellore Raghunathan, Michigan Richard Cooper, Loyola

Part 1. A brief overview of social epidemiology

Part 2. Does an appreciation of social factors actually improve our

understanding of population health?

- A “social” epidemiology of the Russian Mortality Crisis

Part 3. What are some of the lessons for understanding the social

determinants of population health?

- Considering specificity of links between social factors and health

Part 4. What are some of the lessons for understanding social

disparities in health?

- Considering heterogeneity of links between social factors and health

Part 1. A brief overview of social epidemiology

- One person’s view

You will find examples of studies of social factors and health

in many disciplines

Psychology

Sociology

Demography

Economics

Politics - Public Policy

Urban Planning

Disciplinary Perspectives on Health and Health Inequalities

Characteristics ofSocial Systems

Characteristics ofIndividuals

Health

Politics Characteristics ofPolitical Systems

Health

Psychology Characteristics ofIndividuals Health

Economics Characteristics ofIndividuals

Characteristics ofEconomic Systems

Health

Sociology Characteristics ofSocial Systems

Characteristics ofIndividuals

Health

Epidemiology HealthCharacteristics ofSocial Systems

CharacteristicsOf Individuals

“Modern” Epidemiology

Causes

“Structural”

Epidemiology

Causes

Distal

PoliticalEconomy

“Psychosocial”

Epidemiology

Causes

PsychologySociology

“Behavioral”

Epidemiology

Causes

Behaviour

< “Social” Epidemiology > < “Risk Factor” Epidemiology >

Direct StressPathway

Proximal

GeneticsBiology

“Disease”

The Scope of Social Epidemiology

SocialStructure

Individual SocialPosition

PsychosocialBehavioral

Factors

BiologicalFactors

Why are we interested?

Morbidity MortalityAdapted from Diderichsen (1997)

Epidemiological Footprint of different

Social Structures

Geoffrey Rose

Determinants of individual cases

vs

Determinants of population rate

Marmot, Lancet (1998)

0.14 0.16 0.18 0.20 0.22 0.24 0.26 0.28Median Share of Incom e

200

300

400

500

600

Wor

king

Age

(25-

64) M

orta

lity

US AUSSW EUKCAN

New York

Stockholm

Sydney

Income Inequality and W orking-Age Mortality528 Metropolitan Areas in Five Countries, 1990/91

Toronto

London

Ross, et al (in press)

US UK

CASWE

AUS


SocialStructure

SocialPosition


Factors

BiologicalFactors



Socioeconomic Position is a Powerful Risk Factor

0.5

1

1.5

2

2.5

3

3.5

Never Former Current High25%

3rd 2nd Low 25%

Rel

ativ

e H

azar

d: C

VD M

orta

lity

KIHD Study, 1984-1996

Smoking Income


SocialStructure

SocialPosition


Factors

BiologicalFactors



Hopelessness and CVD Mortality

1.0 1.0 1.0 1.0 1.0 1.0 1.0

1.8

1.6 1.6 1.51.7 1.7

1.5

2.6

2.22.0 2.0

2.3 2.3

1.7

0

1

2

3

+Biol +SEP +Behav +SR Hlth +Depr +Dx ALL

Low Medium High

RH

Everson, et al (1997)

NCHS (1998)

0

10

20

30

40

50

White, nonHispanic

Black, nonHispanic

Hispanic NativePeoples

Asian orPacific

Islander

< 12 years

12 years13-15 years

16 + years%

livebirths

Education and Smoking During PregnancyAmong Mothers Aged 20 or Older - USA 1996

NCHS (1998)

0

5

10

15

20

25

30

35

Boys Girls

High Income

Middle IncomeNear PoorPoor

%

Income and Sedentary Behavior in Adolescents - USA 1995


SocialStructure

SocialPosition


Factors

BiologicalFactors



Income and Biological Risk Factors (KIHD 1990)

900

950

1000

1050

1100

Income Quintiles

Apo B

1200

1250

1300

1350

Income Quintiles

Apo A1

4.5

4.6

4.7

4.8

4.9

5

Income Quintiles

Fasting Glucose

2.5

2.6

2.7

2.8

2.9

3

3.1

3.2

3.3

3.4

3.5

Income Quintiles

Fibrinogen

14

16

18

20

22

24

26

28

I/II III-NM III-M IV/V I/II III-NM III-M IV/V

Body

Mas

s In

dex

Social Class at Birth

WomenMen

Body Mass Index by Social Class at Birth

Power, et al. Lancet. (1997)

Age 7

Age 33

SocialStructure

SocialPosition


Factors

BiologicalFactors

Morbidity Mortality

The Landscape of Social Epidemiology

Income inequalityResidential segregationSocial capital

ClassRaceGender Support, trust, depression,

smoking, diet, physical activity

Macro-biological processes of growth and development, reproductive maturation, lipids, insulin resistance, clotting factors, P-N-E, immune function

Genetic influences

Political EconomyInstitutions

DiscriminationCultureHistory

StructuralMacrosocial

Factors

Genetics Human Biology

Pathological Biomarkers

GeneticCharacteristics

Pathobiology

Lifecourse

Conception Old Age

Individual Characteristics

SocioeconomicBehaviouralPsychosocial

Proximal Social Connections

FamilyFriends

Distal Social ConnectionsNeighborhood Community

Lynch (2000)

Health Status

Work Work

Health Status

Lifecourse

multi-time point exposures

Mechanisms

biological, behavioral,

psychological translation

multi-level exposures

Health and Health Inequalities

at the Individual and Population Levels

Context

Part 2. Does an appreciation of social factors

actually improve our understanding of

population health?

A “social” epidemiology of the Russian Mortality Crisis

A. What are the overall population patterns?

Convergence of Life Expectancy at Birth in Industrialized Countries

25

35

45

55

65

75

85

1740 1790 1840 1890 1940 1990

Industrialised countries, except Eastern Europe and Portugal

Japan

New Zealand

Life expectancy at birth

Caselli(2002)

Recent divergence between industrialized countries

35

40

45

50

55

60

65

70

75

80

85

1900 1920 1940 1960 1980 2000

New Zealand

Japan

Russia

Ukraine


Caselli(2002)

Contrasting Trends in Life Expectancy

55

60

65

70

75

80

1965 1970 1975 1980 1985 1990 1995 2000

R uss ia

Lithuania

Latvia

Ukraine

Estonia


Lithuania

R uss ia

Latvia

Ukraine

EstoniaFemales

Males

55

60

65

70

75

80

1965 1970 1975 1980 1985 1990 1995 2000

Life expec tanc y at birth

Poland

Cze ch R e p.

R omaniaHungary

B ulgaria

Slovakia

B ulgaria

Hungary

Cze ch R e p.

Slovakia

Poland

R omania

Females

Males

Soviet Republics Eastern Europe

Russia4 year decline

6+ year decline

Meslé (2002)

B. Does the pattern differ by age?

Age Contribution to Russian Life Expectancy Decline

~ 65%

1990-1994Notzon et al., JAMA, 1998

C. Does the pattern differ by cause?

Cause-specific Mortality: Russia 1984-1994

Ratio: 1987 vs 84

Ratio:1994 vs 87

Age Age

All causes Infectious and parasitic

Neoplasms Circulatory disease

Leon, et al.Leon, et al. Lancet,Lancet, 19971997

Pneumonia Other respiratory

Alcohol related diseasesAccidents and violence

Causes of Death Contributing to Russian Life Expectancy Decline

~ 70%CVD

AccidentsInjury

Violence

1990-1994Notzon et al., JAMA, 1998

D. What does our knowledge of the

individual level risk factors tell us?

What could cause a big rise in CVD mortality?

Artifact of death registration

Collapse of health care

Hypertension

Smoking

Obesity

Lipids – Diet

Physical activity

Alcohol

“Although factors such as nutrition and health

services may be involved, the evidence is that

substantial changes in alcohol consumption over the

period could plausibly explain the main features of

the mortality fluctuations observed.”

Leon, et al. Lancet (1997)

Coronary heart disease and acute alcohol poisoning mortality in Russia, Men 30-59

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1965 1970 1975 1980 1985 1990 19950

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140

Age

-sta

ndar

dise

d ra

te p

er 1

00,0

00

Acute alcohol poisoningAcute alcohol poisoning

CHDCHD

SimultaneousSimultaneous Anti-alcoholCampaign

Injuries, poisoning and violence mortality, Men aged 30-59 (excluding acute alcohol poisoning)

0

300

600

1965 1970 1975 1980 1985 1990 199510

11

12

13

14

15

16

Age

-sta

ndar

dise

d ra

te p

er 1

00,0

00Per capita consum

ption litres pure alcohol/year

Injury/violence mortality rateInjury/violence mortality rate

Alcohol Alcohol consumptionconsumption

Very little time lag Anti-alcoholCampaign

But …

Isn’t alcohol protective for heart disease?

Beer Bingeing and Mortality - Finland

0.5

1.5

2.5

3.5

4.5

5.5

6.5

7.5

All-cause CVD External AMI Fatal AMI

Rel

ativ

e H

azar

d

Kauhanen, et al. BMJ (1997)

< 3 bottles (Reference)

3-5 bottles per session

6+ bottles per session*

* Adjusted for average consumption

Correlates of Alcohol Bingeing in Finnish Men - KIHD

• low physical activity

• hopelessness

• depression

• cynical hostility

• poor childhood

• low education

• blue-collar job

• low income

• smoking

• poor lipid profile

• higher blood pressure

E. How does all this fit with our knowledge of the

pathophysiology of the particular outcome?

Coronary heart disease mortality in Russia

• CHRONIC component :

classic atherosclerotic/thrombotic pathology

associated with known coronary risk factors

• ACUTE component :

alcohol induced arrhythmias/cardiomyopathies

associated with binge drinking

F. Putting together a plausible population health story

that incorporates the social to the biological

“These findings paint a picture of societies in which young

and middle aged men face social and economic disruption on

a large scale, for which they are poorly prepared. For many,

their options are constrained by low levels of education, and

the societies of which they are a part have few systems of

social support.

Poor nutrition and high rates of smoking have already

reduced their chances of a long life. The availability of cheap

alcohol, however, provides a pathway not only to oblivion

but often to premature death.” McKee and Shkolnikov BMJ (2001)

Social Stress

% Fall in Male Life Expectancy

and Labor Market Turnover

Russia1990-94

Walberg, et al.Walberg, et al.BMJ BMJ 19981998

A Model for Social EpidemiologyCulturally contextualized - specific exposures - susceptibilities - outcomes

Social andStructuralUpheaval

SpecificExposure

Binge drinking

Specific Outcomes

CVDAccidents / Violence

structures exposureprobabilities

to binge drinking

Socioeconomicposition

DecreasedLife

Expectancy

Cultural Component – role of alcohol in “vodka belt” culture

Part 3. What are some of the lessons for better

understanding the social determinants of

population health?

- Considering specificity in our explanations

Trends in selected causes of death for women aged 30-59, Russia 1965-1999

0

20

40

60

80

100

120

140

160

180

1965 1970 1975 1980 1985 1990 1995 2000

SDR

per

100

000

Accidents and violence

Ischaemic heart disease

Stomach cancer Breast cancer

Rheumatic heart disease

YearShkolnikov, McKee & Leon, Lancet 2001

Reinstate Specificity

“No, some of our epidemiologic forefathers did not get the notion of

‘specificity’ quite right. But I suggest that a modified version of that

notion has a useful place, after all, as we seek to sort out causal from

non-causal associations.” p. 7

• Specificity of Exposure – an outcome associated with 1 exposure, not another

• Specificity of Outcome – an exposure associated with 1 outcome, not another

• Specificity of Susceptibility – association only in those susceptible to the effect

Weiss. Epidemiology (2002)

Why might specificity of outcome-exposure links be useful in understanding the social causation of disease?

• It may give greater flexibility and explanatory power

because it helps shift our focus toward an understanding of

population health and health disparities, as rooted in the

social and structural distribution of more specific exposures

that affect specific susceptibility to particular outcomes.

Why might specificity of outcome-exposure links be useful in understanding the social causation of disease?

• This means understanding that the social and structural

distribution of relevant risk factors is often contextualized

in regard to time, space, culture and population subgroup.

Recent divergence between industrialized countries

35

40

45

50

55

60

65

70

75

80

85

1900 1920 1940 1960 1980 2000

New Zealand

Japan

Rus s ia

Uk raine

Life expectancy at b irth

Why does Japan have the highest life expectancy in the world?

Caselli(2002)

Some have used this remarkable growth in life expectancy

as evidence for the importance of social cohesion / social

capital and related psychosocial processes

Lower inequality (income) blunts perceptions of relative

disadvantage → greater social cohesion → less stress

mediated disease

Why does Japan have the highest life expectancy in the world?

“… these improvements cannot be explained in terms of changes in

nutrition, health care, preventive health policies, or any of the obvious

factors, …” p. 18

“What is important about the Japanese example is . . . the association of

a narrow income distribution with a public sphere of life which has a real

social content. Instead of a moral and social vacuum mediated only by

market relationships, life beyond the family has a well-developed social

structure.” p. 133

Richard Wilkinson. Unhealthy Societies (1996)

What if we consider the specific components of the

rise in Japanese life expectancy?

Trends in Stomach Cancer, 1950-1995

0

10

20

30

40

50

60

70

1950 1960 1970 1980 1990 1995

CubaUKSweden

Denmark

Finland

Spain

Poland

Ireland

Portugal

Japan

Rat

e pe

r 100

,000

As % of All Cancers1950 1995

Japan 59% 21% Finland 37% 7%Sweden 26% 5%UK 18% 6%USA 14% 3%

* Stomach cancer was the leading single cause of cancer mortality in all these countries in 1950

USA

0102030405060708090

10018

7218

7818

8418

9018

9619

0219

0819

1419

2019

2619

3219

3819

44

(%)

male

female

1920

Primary School Attendance Rate1900

T HasegawaNIHSM,Japan

LE in 1870s35 years

0

50

100

150

200

250

300

350

1899

1904

1909

1914

1919

1924

1929

1934

1939

1944

1949

1954

1959

1964

1969

1974

1979

1984

1989

1994

（NMR）

（IMR）

（U5MR）

(Rat

e /1

,000)

1920

Ｃ T HasegawaNIHSM,Japan

Vital Statistics

20th Century Trends in Infant, Neonatal and Under 5 Mortality, Japan

(%)

(IMR/1,000)

Rate of Primaryeducation of mother

IMR

0

10

20

30

40

50

60

70

80

90

1001899

1903

1907

1911

1915

1919

1923

1927

1931

1935

1939

1943

0

20

40

60

80

100

120

140

160

180

2001920


Infant Mortality and Education of Women, Japan 1899-1943

Infant mortality 1921-23 against stomach cancer mortality 1991-93for men aged 65-74 in 27 countries

0 50 100 150 200 2500

50

100

150

200

250

CANADA

CHILE

USA

JAPAN

AUSTRIA

BELGIUM

BULGARIACZECHOSL

DEN

FINLAND

FRAGREECE

HUNGARY

IRELANDITALY

NETHLANDSNORWAY

POLANDPORTUGAL

ROMANIA

RUSSIA

SPAIN

SWESWITZ

UK

AUSTRALIANZ

Stom

ach

canc

er m

orta

lity

rate

per

100

K, 1

991-

93

Infant mortality rate per 1000, 1921-23 Leon and Davey Smith, BMJ (2000)

Trends in Stomach Cancer, 1950-1995

0

10

20

30

40

50

60

70

1950 1960 1970 1980 1990 1995

CubaUKSweden

Denmark

Finland

Spain

Poland

Ireland

Portugal

Japan

Rat

e pe

r 100

,000

* Stomach cancer was the leading single cause of cancer mortality in all these countries in 1950

USA

Russia

Stomach cancer

begins to decline

in cohorts born

around the turn

of the century

• By 1900 - Systematic investments in education of women,

improvements in urban living, sanitary conditions especially

for children less infectious burden

• 1920s - The children of those women were the first

generations to experience lower infant mortality – a marker

for the health generating potential of early life environment

• Stomach cancer and hemorrhagic stroke - both causes

dependent on early life conditions / infection - decline

enormously after WW2

Japanese Life Expectancy - The Real Story?

0.2

0.0

0.2

0.4

0.6

0.8

1.0

1.2

0

1-4

5-9

10-14

15-19

20-24

25-29

30-34

35-39

40-44

45-49

50-54

55-59

60-64

65-69

70-74

75-79

80-84

85-89

90-94

95-99

other

suicide

accidents

perinatalperiodrespiratorydiseaseinfectiousdiseasecerebrovasculardiseaseIschemic heart diseasecancer

-0.2

0.0

0.2

0.4

0.6

0.8

1.0

1.2

0

1-4

5-9

10-14

15-19

20-24

25-29

30-34

35-39

40-44

45-49

50-54

55-59

60-64

65-69

70-74

75-79

80-84

85-89

90-94

95-99

Prolongation of Life Expectancy1965-1985Age & Disease Group by Polard’s Method

Male Female


Hemorrhagic Stroke

Japanese Life Expectancy - The Real Story?

• Enormous declines in hemorrhagic stroke and stomach

cancer, but Japan also avoids the “epidemic” of CHD

experienced in the West and Soviet Union

• The huge economic advances post WW2 are NOT

converted into increases in CHD as in the West – despite

high smoking rates post WW2 – low fat diet?

• But the future looks less bright as LE will likely stall or may

actually decline as lung cancer rates climb rapidly – 40 to 50

years after smoking taken up in great numbers

• Levels of social cohesion may well have been important in

facilitating these massive social changes but they were not

directly responsible for these unprecedented improvements

in population health in Japan - due to ↓ stomach cancer and

hemorrhagic stroke

• There were more specific social investments in the health

of women and children and urban sanitation

• Nor is it likely that these investments were rooted in ideas

about improving social equity

• More likely based on paternalistic views of the importance

of good maternal-child health conditions to future

generations and how that would feed into the aspirations of

the Japanese imperial state

• Whatever the motivation, the specific social investments in

women and children have helped deliver the highest life

expectancy on the planet, despite on-going gender

inequities in Japan

• No universal pathway to good population health?

• Should good population health trump other social values?

Factors - like social capital/cohesion and stress - that

may seem plausible (both biologically and socially) in the

cross-section sometimes fail to generate less support

a) when longer term trends in exposures and outcomes

are studied

500.00

700.00

900.00

1,100.00

1,300.00

1,500.00

1,700.00

1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 199835

37

39

41

43

45

47

49

Income inequality (gini) and sex-specific age-adjusted all-cause mortalityUSA, 1968 - 1998

Male Mortality

Female Mortality

Income Inequality

All-c

ause

mor

talit

y pe

r 100

,000

GiniC

oefficient

Lynch and Davey Smith (2003)

700.00

800.00

900.00

1,000.00

1,100.00

1,200.00

1,300.00

1,400.00

1,500.00

1,600.00

1,700.00

1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 199840.0

45.0

50.0

55.0

60.0

65.0

70.0

Race-specific Voting Participation in Presidential Elections and age-adjusted, all-cause mortality, USA, 1968 - 1998

Year

All-c

ause

mor

talit

y pe

r 100

,000

% Voting in Presidential elections

Black Mortality

White MortalityBlack Voting

White Voting

and/or

b) when the specific patho-physiology of the disease in

question is more fully understood.

Disease that have historically been linked to stress processes

• Cholera

• Pellagra

• Beri Beri

• Down’s syndrome

• Scurvy

• Yellow fever

• Typhoid

• Asthma

• Peptic ulcer

The mid-20th Century Epidemic of Peptic Ulcer

Susser and Stein. Lancet (1962)

Peptic Ulcer and Stressful Life Events

MenAny stressful events, OR = 20.3

WomenAny stressful events, OR = 21.5

Davies and Wilson. Lancet, Dec 11th 1937.

“During convalescence the patient should be given a

simple exposition of peptic ulcer. A clear understanding

of the need for maintaining a calm outlook on life, and of

the necessity for not exceeding his natural “tempo” by

accepting too much work or responsibility, will be much

more valuable than routine medication. The patient has

got to live with his ulcer-forming tendency and it is

essential to give him all the information at our disposal.”

F. Avery Jones. Progress in Clinical Medicine, 1948

“The diet should be served in as colourful and attractive a

way as possible. A bland insipid colourless diet may cause

less psychic flow of gastric juice, but it makes the patient

depressed and irritable. The sustained resentment is more

harmful than the increased psychic secretion.”

F. Avery Jones. In: Progress in Clinical Medicine, 1948

“That there has been a true decline in incidence is the most

interesting possibility. This would suggest to anyone in

sympathy with ‘psychosomatic’ theories … that the type of

personality disposed to the disease is less common –

unfortunately not a testable proposition; [or] that the

environment is less of a strain – which is scarcely

conceivable”.

Jerry Morris. Uses of Epidemiology, 3rd Edition, 1975.

What causes peptic ulcer?

“ … despite the common folk knowledge about the

emotional causes of ulcer, a major textbook of

pathology currently concludes that the origins of

peptic ulcers are ‘enigmas wrapped in mystery’ “.

Sterling and Eyer. Biological basis of stress related mortality.

Soc Sci Med 1981; 15E: 3-42.

The evidence “. . . does not exclude the possibility

that a major single causal factor awaits discovery”

Mervyn Susser. Journal of Chronic Disease

1967;20:435-456

What causes peptic ulcer?

Helicobacter PyloriHelicobacter Pylori

“H pylori eradication, without altering acid output, will

become the mainstay of duodenal ulcer treatment

because it cures the disease.”

Rauws and Tytgat. Lancet 1990;335:1233-5

Part 4. What are some of the lessons for better

understanding social disparities in health?

- Considering heterogeneity in our explanations

The Standard View of Socioeconomic Health Disparities

“Socioeconomic status is a strong and consistent predictor of mortality

and morbidity. Individuals lower in the SES hierarchy suffer

disproportionately from almost every disease … This association is found

with each of the key components of SES: income, education and

occupational status.”

Adler, et. Al., JAMA (1993) p. 3140

“Throughout history SES has been linked to health. Individuals higher in

the socioeconomic hierarchy typically enjoy better health that do those

below; SES differences are found for rates of mortality and morbidity

from almost every disease and condition.”

Adler, et. al., Am Psychologist (1994) p. 15

This sort of mind-set has encouraged a focus on universal processes

that make the disadvantaged “generally susceptible” to all sorts of poor

health conditions

• John Cassell’s – the “father” of US social epidemiology - ideas on

social support and general susceptibility have been influential

• Ideas on general susceptibility have been combined with later

evidence (e.g., Whitehall studies) on the apparent inability of material

conditions; and traditional risk factors and behaviors to explain

socioeconomic gradients in CHD

For example, in regard to the Whitehall study, it has been

argued that a “ . . . gradient in mortality among civil

servants who are not poor argues for the importance of

psychosocial factors linked to position in the hierarchy.”

Marmot and Bobak. BMJ 2000 (p. 1127).

The Whitehall II Study

“As predicted, the specific psychosocial work characteristic of low

control made an important contribution to the social gradient in

incident CHD in the Whitehall II study.”

“ … work is the major cause of the social gradient in CHD incidence in

this cohort, …”

“Much of the inverse social gradient in CHD incidence can be attributed

to differences in psychosocial work environment.”

Marmot et al. Lancet 1997

Explanations for Health Disparities

• Materialist “objective” conditions & life circumstancesX• Behavioral diet, smoking, exercise, alcoholX

• Psychosocial stress, negative emotions, control, social support

account for the general susceptibility of the

disadvantaged

Perceptions ofDisadvantage

Psychosocial Environment

Assumption -of “general susceptibility”

to poorer health among the disadvantaged

ControlStress

P – N – E – IBiology

Social SupportSocial Capital

Heterogeneity of links between

socioeconomic factors and different outcomes?

Heterogeneity and History

Life Expectancy at Birth - Britain (1540-1901)

Kunitz, (1987)

20

30

40

50

60

70

1541156115811601162116411661168117011721174117611781180118211841186118811901

LE

Total Population

Aristocracy

Social Advantage = LE Equality Social Advantage = LE

“… in early modern Europe rulers and their subjects seem

to have had similarly low levels of life expectancy at birth

(30-35 years) at least before 1700. Some low-income

peasant families had substantially higher levels of life

expectancy at birth than wealthy peers (40-50 years)

although some had lower (20-25 years). … what matters

most to explaining pre-transition mortality is location not

income.”Johansson (1999)

Trends in Death Rates for Selected Occupations, 1861-1911

150

250

350

450

550

650

750

1861 1871 1881 1891 1901 1911

Hotel Servants

Clergy

File MakersPotters

Coal Miners

Farmers

Teachers Doctors?

Railway Clerks

Woods and Williams (1995)

SMR

Education and IHD Mortality, Korea (1995-2000)Census Linkage Study of 15 million individuals

Kang, Lynch, et al (in press)

0

20

40

60

80

100

No Elementary Middle High College

Men35-44

45-54

55-64

Age-

adju

sted

Mor

talit

y R

ate

Heterogeneity of

Race / Ethnic Disparities in Health

Mortality Unrelated to Race, 1979-89

Disease Age strataEstimated

Hazard Disease Age strataEstimated

HazardOral CA 1.26 Oral CA 1.14Colon CA 1.12 Colon CA 0.94Rectal CA 1.21 Rectal CA 0.62Pancreatic CA 1.25 Pancreatic CA 1.34Lung CA 1.03 Bladder CA 1.24Breast CA 0.98 Kidney CA 1.15Ovarian CA 0.91 Leukemia 0.54Bladder CA 0.58 Other lymph CA 1.07Kidney CA 1.24 Hypertension [75+] 1.78Brain CA 1.11 Ischemic HD [35-54] 1.19Leukemia 0.73 Heart Failure [55-74] 1.16Other lymph CA 1.05 Heart Failure [75+] 0.81Hered. & deg. of CNS 0.67 Ill-defined HD [75+] 1.19Ischemic HD [55-74] 1.07 Stroke [75+] 0.83Heart Failure [55-74] 1.40 Art/arterio/cap 0.80Heart Failure [75+] 1.01Ill-defined HD [75+] 0.79Stroke [75+] 0.80Art/arterio/cap 0.98COPD [75+] 0.71Automobile 0.94Other accidental [55+] 0.96

Women Men

Howard et al., Annals of Epidemiology, 2000; 10: 214-223

Mortality Related to Race, With and Without Adjustment for SEP, 1979-89

Disease Age strataUnadjusted

H.R. Adjusted H.R. Disease Age strataUnadjusted

H.R. Adjusted H.R. Infections 2.50 2.33 Infections 2.21 1.87Stomach CA 2.23 2.06 Stomach CA 1.65 1.46Diabetes 2.11 1.70 Lung CA 1.28 1.15Hypertension [55-74] 4.86 4.17 Prostate CA 2.11 2.15Hypertension [75+] 1.71 1.79 Brain CA 0.22 0.24Ischemic HD [35-54] 2.36 1.63 Diabetes 1.48 1.36Ischemic HD [75+] 0.72 0.71 Hered. & deg. CNS 0.42 0.43Pulmonary 2.49 2.19 Hypertension 4.04 3.60Cardiomyopathy 2.59 2.26 Ischemic HD [55-74] 0.85 0.76Ill-defined HD [55-74] 1.76 1.55 Ischemic HD [75+] 0.50 0.49Stroke [55-74] 1.71 1.53 Pulmonary [55-74] 2.55 2.34COPD [55-74] 0.40 0.37 Cardiomyopathy 2.02 1.84Cirrhosis 2.64 2.25 Ill-defined HD [55-74] 2.66 2.26Suicide 0.34 0.37 Stroke [55-74] 1.77 1.51Homicide 4.60 3.28 COPD [55-74] 0.65 0.52Other accidental [25-54] 1.98 1.32 COPD 75+ 0.35 0.33

Cirrhosis 1.72 1.52Automobile 0.78 0.65Suicide 0.49 0.41Homicide 8.18 5.94Other accidental 1.67 1.30

Women Men


Hazard Ratio for Black versus White Race for Death Related to Race, 1979-89


-80

-60

-40

-20

0

20

40

60

80

0.12

5

0.25

0

0.50

0

1.00

0

2.00

0

4.00

0

8.00

0

16.0

00

COPD (55-74)

Suicide

Ischemic HD (75+)Hypertension (75+)

InfectionsStomach CA

Hypertension (55-74)Stroke (55-74)

PulmonaryCardiomyopathy

Ill-defined HD (55-74) Cirrhosis

DiabetesHomicide

IHD (35-54)

Other Accidental (25-54)

WOMENPe

rcen

t Cha

nge

afte

r adj

ustm

ent f

or S

EP

Hazard Ratio (Unadjusted)

-80

-60

-40

-20

0

20

40

60

80

0.12

5

0.25

0

0.50

0

1.00

0

2.00

0

4.00

0

8.00

0

16.0

00

COPD (55-74)

Suicide

I HD (75+)

Infections

Stomach CA

Hypertension (55-74)

Stroke (55-74)

Pulmonary

CardiomyopathyIll-defined HD (55-74)

CirrhosisDiabetes

Homicide

IHD (55-74)

Other Accidental (25-54)

MEN

Hazard Ratio (Unadjusted)

Automobile

COPD (75+) Prostate CA

Brain CA Hered&Deg of CNS

Lung CA


Perc

ent C

hang

e af

ter a

djus

tmen

t for

SEP

Hazard Ratio for Black versus White Race for Death Related to Race, 1979-89

Change in the Disparity in Life Expectancy if Selected Diseases were Eliminated

-0.25

-0.2

-0.15

-0.1

-0.05

0

0.05

0.1

Hom

icide

Suicide

Motor vehicle accident

Alcohol-related diseases

Rheum

atologic diseases

Liver disease

Renal disease

Diabetes m

ellitus

Lung disease

HIV

disease

Sepsis

Viral hepatitis

Pneumonia

Tuberculosis

Leukemia or lym

phoma

Urinary cancer

Prostate cancer

Cervical cancer

Breast cancer

Lung cancer

Stomach cancer

Esophageal cancer

Uterine or ovarian cancer

Pancreatic cancer

Liver cancer

Colon cancer

Congestive heart failure

Hypertension

Cerebrovascular stroke

Ischemic heart disease

Cha

nge

in D

ispa

rity

in L

ife E

xpec

tanc

y (y

ears

per

per

son)

Wong et al., New England Journal of Medicine, 2002; Vol.347, No.20: 1585-1592

Change racial disparity

HomicideHypertension

HIV35% of the racial disparity

Heterogeneity of

Socioeconomic Disparities in Health

Causes of death and median income of Zip Code area of residence in the men screened for MRFIT: relative risk for $10,000 lower income

RR > 1.50 RR 1.21-1.50 RR 1.00-1.20 RR < 1.00AIDS Infection Aortic aneurysm Blood diseaseDiabetes Coronary Heart Suicide Motor neurone

Disease diseaseRheumatic Stroke Nervous system Flying accidentsHeart Disease diseaseHeart failure Cirrhosis Oesophageal Lymphoma

cancerCOPD Genitourinary Stomach cancer Hodgkin’s disease

diseasePneumonia/ SR Symptoms Pancreatic cancer MelanomaInfluenzaHomicide Accidents Prostate cancer Bone/connective

tissue cancerLung cancer Bladder cancerLiver cancer Kidney cancerColorectal cancer Brain cancer

MyelomaLeukaemia Davey Smith (1996)

Parental Occupation and Relative Risk for Injury, Sweden, 1990-1994

0

0.5

1

1.5

2

High Low Employees Skilled Workers Unskilled Workers

Traffic Injuries Falls

Ages 15-19OR

Engerström, Diderichsen, Laflamme. Injury Prevention (2002)

Mouth/Pharynx ? •Oesophagus • •Stomach • •Liver • •Nasal • •Larynx • •Lung • •Cervix • •

Incidence Mortality

More Common Among Poor

Melanoma • •Breast • •?Colon • •Ovarian • •Testis •? •

Incidence Mortality

More Common Among Rich

Rectum, Pancreatic, Bone, Connective Tissue, Prostate, Bladder, Kidney, Brain, Thyroid, Lymphomas, Leukemia

No Evidence for Socioeconomic Patterns

IARC (1997)

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

2

10-29

Constance, Int J Cancer (1990)

30-4950-69

70+

Men

AgeAge--specific Melanoma Risk and Census Tract Incomespecific Melanoma Risk and Census Tract IncomeWashington State, 1974Washington State, 1974--8585

HighLow Income

RR

International Heterogeneity in the Magnitude and

Direction of Social Inequalities in Health

Manual vs Non-Manual Health Inequalities, Europe

1

1.1

1.2

1.3

1.4

1.5

1.6

1.7

1.8

1.9

2

France

Finland

England

/Wale

sSwed

enIre

land

Spain

Portuga

l

Italy

Switzerla

ndNorw

ayDen

mark

2

7

12

17

22

27

32

KunstKunst, , BMJBMJ (1998)(1998)

RR

: Mor

talit

y (M

an v

sN

on-M

an) Men 45-59Probability of Dying

Rate Ratio: Manual vs Non-manual

1

1.1

1.2

1.3

1.4

1.5

1.6

1.7

1.8

1.9

2

France

Finland

England

/Wale

sSwede

n

Irelan

d

Spain

Portugal Ita

lySwitz

erland

Norway

Denmark


RR

Men 45-59Cancer MortalityCancer Mortality

Rate Ratio: Manual vs Non-manual

0.75

0.85

0.95

1.05

1.15

1.25

1.35

1.45

1.55

1.65

1.75


RR

Men 45-59IHD MortalityIHD Mortality

France

Finland

Norway

SwedenEngland/W

ales

Switzerla

nd

Ireland

SpainPortu

gal

Denmark

Italy

Implies differing socioeconomic distributions of the risk factors for IHD across countries

So what have we learned?

This is your quiz

Can You Explain this Health Disparity?

What process generated this health disparity?

0

5

10

15

20

25

30

35

40

45

50

2.8

16

45

Upper Class Middle Class Lower Class

Fata

lity

Rat

e pe

r 100

• Very famous and occurred in 1st decades of 20th C

• This entire population was susceptible

• Despite this, lower class women had 20 times higher

death rate - 45% of lower class women died

• And men died at even higher rates than women

Some Clues

0

5

10

15

20

25

30

35

40

45

50

1st Class 2nd Class 3rd Class

2.8

16

45

Fatality Rates per 100 Women Passengers: HMS Titanic

Class of Travel

How should we understand this health disparity?• Why were poorer women more likely to die?

- Drowning gene?

- More stressed?

- Low self-efficacy?

- Lack of exercise?

- Targetted intervention?

swimming lessonsFata

lity

Rat

e pe

r 100

Nature of theSocial Structure

distribution of specific health

protective resources

Lifeboats

Social disparityin the death rates

Various socioeconomic positions within that structure

Can apply the same idea to understanding this pattern

50

60

70

80

90

100

110

120

1975 1980 1985 1990 1995

Breast Cancer Incidence

0

5

10

15

20

25

30

1975 1980 1985 1990 1995

Breast Cancer Mortality

White Women

Black Women

White Women

Black Women

How does the social structure distribute risk factors for breast cancer incidence?

How does the social structure distribute risk factors for breast cancer mortality?

National Center for Health Statistics, USA (1998)

We need to include heterogeneity in our explanations for social disparities

in health

The direction and extent of social disparities in health differs

• by outcome

• by exposure – education, income

• by place

• over time

This may help make the problem of health disparities seem less intractable

and suggests that social disparities in health are rooted in the nature of

the social structures created by humans and thus amenable to change

Conclusion

• The example of the Russian mortality crisis and the rise in Japanese LE

show how social factors can strongly affect levels and trends in population

health BUT they do so specifically through their links to risk factors for

specific outcomes.

• Applied to health disparities, this suggests we can use the underlying

heterogeneity of associations to suggest more specific links between

socioeconomic markers and race/ethnicity and risk factors and specific

health outcomes

• This may weaken the case for general psychosocial processes in

determining population health or health disparities

Lynch and Davey Smith (2003)

Where do psychosocial factors fit?

• The case for the importance of psychosocial factors to health does not

need to be made on the grounds that they are key determinants in the

etiology of diseases like CVD and cancer, although they may be

etiologically important to some outcomes such as homicide.

• They are also important outcomes in their own right because of their

contributions to quality of life in affluent societies.

• The quantity of life may well be a relatively unimportant contributor to

the quality of life in affluent societies and this means psychosocial

phenomena are important as population health outcomes.

Lynch and Davey Smith. IJE (2003)

Thank you

population health and health disparities - a social...

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