The Social Shaping of Health Disparities: The Fundamental Cause

Hypothesis

Bruce Link

Heron

April 7, 2011

U.S. All Cause Age-adjusted Death Rates Per 100,000 by Race – 2005

785.3

1016.5

0

200

400

600

800

1000

1200

whiteblack

National Center for Health Statistics – Health United States 2008

U.S. All Cause Age-adjusted Death Rates Per 100,000 People Ages 25-

64 by Education -- 2005821

606

249

472

352

165

0

100

200

300

400

500

600

700

800

900

Males Females

< 12 years12 years13+ years

National Center for Health Statistics – Health United States 2008

U.S. Percent Fair or Poor Self-Reported Health by Poverty Level

and Race/Ethnicity

21

14

6

21

14

6

26

17

10

20

15

9

0

5

10

15

20

25

30

Overall White Black Hispanic

Below 100%100%-less than 200%200% or more

National Center for Health Statistics – Health United States 2006 – From NHANES Surveys

Age Standardized Mortality Rates by SES Classification (NS-SEC) in the North East and

South West, Men 25-64, 2001-2003

210

700

195

400

0

100

200

300

400

500

600

700

North East South West

Hi Manager Prof.

Lo Manager Prof.

Intermediate

Small Employers

Lower supervisory andtechnicalSemi-Routine

Routine

NS-SEC= National Statistics Socioeconomic Classification

SES,Race

MechanismsSmoking, Diet, Exercise, Stress,

Etc, etc. ?

MortalityMorbidity

?

What Are the Mechanisms that Account for the Association?

Deaths Per 1000 Among Taxpayers andNon-Taxpayers in Rhode Island 1865

Age Categories Taxpayers Non-Taxpayers(examples)

Under 1 93.4 189.8

30-39 4.5 15.5

60-69 15.1 39.5

Chapin AJPH 1924

Deaths per 1000 (age adjusted) by SESof Census Tract -- Chicago 1930

SES Males Females

1--Lowest 15.1 12.3

2 11.6 10.2

3 10.2 9.0

4 9.2 7.9

5--Highest 8.7 6.8

Coombs, Medical Care, 1941

What is the point?

• Imagine yourself back in Rhode island in 1865 and doing what we just did for the current data – we might have asked what were the mechanisms involved?

• Contaminated water, poor sanitation, crowded substandard housing – the diseases were cholera, TB, small pox…

• We did something about the risk factors, we developed vaccines, and people don’t die of TB, small pox and cholera in Rhode Island any more.

• But the SES association is resilient.

The Concept of Fundamental Social Causes

Fundamental social causes involve resources such asknowledge, money, power, prestige and beneficial social connections that determine the extent to which people areable to avoid risks and adopt protective strategies so as toreduce morbidity and mortality.

Because such resources can be used in different ways in different situations, fundamental causes have effects ondisease even when the profile of risk and protective factors and diseases changes radically.

It is their persistent effect on health in the face ofdramatic changes in mechanisms that leads us to call them“fundamental.”

How Social and Economic Resources Affect Health – The Importance of Contexts

• Resources operate at the individual level – people use their knowledge, money, power, prestige and beneficial social connections to obtain healthy outcomes.

• But resources also provide access to generally salutary contexts – neighborhoods, occupational conditions, marriages – access to health consequential circumstances comes with access to contexts in a sort of “package deal.”

US Life Expectancy at Birth 1900-2000

47

55

61

7074

77

40

45

50

55

60

65

70

75

80

1900 1920 1940 1960 1980 2000

US: Heart Disease -- Age-adjusted Death Rates Per 100,000 People

587559

493

412

321293

258

40

140

240

340

440

540

640

1950 1960 1970 1980 1990 1995 2000

Cancer (green) and Stroke (Yellow) -- Age-adjusted Death Rates Per 100,000 People

181 178

148

96

65 63 6150

194 194 199208

216 210200

186

40

60

80

100

120

140

160

180

200

220

240

1950 1960 1970 1980 1990 1995 2000 2004

National Center for Health Statistics – Health United States 2006

US : Flu (blue) and HIV (green) -- Age-adjusted Death Rates Per 100,000 People

1016

5

4854

42

3137

33

24

0

10

20

30

40

50

60

1950 1960 1970 1980 1990 1995 2000

Percentage Self Reporting Health as Excellent or Good by Age Group (40-49 yellow and 60-69 blue)

and Decade of Birth using 1972 to 2004 General Social Surveys

74%76%

82% 82%84%

52%

57.00%

63%

74%

82%

50.00%

60.00%

70.00%

80.00%

90.00%

1900's 1910's 1920's 1930's 1940's 1950's 1960's

Age40-49

Age60-69

Adapted from: Robert Warren and Elaine Hernandez (In Press) Journal of Health and Social Behavior, Table 2

Something is Driving these Dramatic Improvements in Health

X ?

Shouldn’t whatever “x” is be an important part of our explanations of health disparities?

Do Key Explanatory Variables in Theories of Disparities Account for Trends Toward Improvement

in Health Over Time?

• How about genetic factors?

• Social involvement and participation?

• How about income inequality?

• Relative position on hierarchies?

Of course, X is not any one thing but many things

• The discovery of the germ theory is a strong candidate for declines in rates of infectious diseases in the first half of the 20th century.

• Recent declines in age adjusted rates of death from lung cancer are probably influenced by the lagged effects of declines in smoking rates in earlier decades.

• The rapid decline in HIV/AIDS mortality is probably related to the new anti-retroviral drugs that were developed and disseminated in the late 1990’s

• And then screening for disease, public health efforts to increase the consumption of fruits and vegetables, promote exercise, eradicate smoking, and smog control, flu shots, seat belts, angioplasty, screening for early detection of cancer, etc. etc.

• So X is clearly not just one thing and is likely different things for different diseases…and probably different things at different times….But the confluence of all of these things has clearly had an enormously positive impact on population health.

• Clearly human beings have dramatically increased their capacity to control disease and death.

Fundamental Cause Reasoning Concerning the Sources of Disparities: The Core Proposition

• Our enormous capacity to control disease and death combined with social and economic inequality creates health disparities.

• It does so because of a very basic principle – When we develop the ability to control disease and death, the benefits of this new found capacity are not distributed equally throughout the population, but are instead harnessed more securely by individuals and groups who are less likely to be exposed to discrimination and who have more knowledge, money, power, prestige and beneficial social connections.

• People who are more advantaged with respect to resources such as these and who are less likely to be held back by discrimination benefit more and have lower death rates as a consequence. Disparities are the result.

Explanations for Race and SES Disparities that Have Different Emphases than a Social

Shaping Fundamental Cause Approach

• Genetic Differences• Health Selection• Relative Deprivation• Job Control• Stress of Lower Position

Test #1 -- SES Associations with More and Less Preventable Causes of

Death

• We say that SES differences arise because people of higher SES use flexible resources to avoid risks and adopt protective strategies

• it follows that the SES gradient should be more pronounced for diseases that we can do something about… for which there are known and modifiable risk and protective factors…

• Our first test involves ratings of the preventability of death from specific causes

US National Longitudinal Mortality Survey

• Very large study of a nationwide sample of over 350,000 people.

• Interviewed as part of the US Current Population Survey (assesses unemployment etc.) and followed for 9 years with National Death Index for mortality and cause of death

Relative Risks of Death by Income -- NationalLongitudinal Mortality Study

Income (1980 $) Men 45-64Women 45-64

< 5000 2.32 3.13

5000-9999 1.79 2.63

10000-14999 1.56 2.03

15000-19999 1.35 1.69

20000-24999 1.21 1.47

25000-49999 1.09 1.28

50000+ (reference category) 1.00 1.00

Sorlie et al. AJPH 1995

The Rating Task

• Thinking of both our ability to prevent a disease from occurring and to treat it once it occurs, to what degree was it possible, in the early 1990’s to prevent death from this disease?

• Rated on a 5 point scale from “virtually impossible to prevent death” to “virtually all deaths preventable”

• Inter-rater reliability .85. Correlation with Rutstein independent ratings .57.

Examples of Hi and Lo Preventability Diseases

• Low Preventability:

brain cancer, ovarian cancer, gallbladder cancer, multiple sclerosis, pancreatic cancer,

• High Preventability:lung cancer, ischemic heart disease,

colon cancer, pneumonia

National Longitudinal Mortality Study Percent Dying During 9 Year Follow-Up:

Men and Women 45-64

4.15

8.2

1.8 1.8 2.1

0

1

2

3

4

5

6

7

8

9

Hi Preventability Lo Preventability

16+ Years12 -15 years< 12 Years

Phelan, Link, Diez-Roux, Kawachi and Levin. 2004 JHSB

Test # 2 Evidence Bearing on the Hypothesis Trends Over Time

• If the core proposition is true we should find that disparities by SES and race emerge when new health enhancing information or technology is obtained: – E.g. Heart disease, Hodgkins Disease, Colon Cancer

• If death from a disease remains unpreventable – disparities will not change dramatically with time– E.G. Brian cancer, Ovarian Cancer, Pancreatic Cancer

Trends by County-Level SES and Race in the US

Brain Cancer -- Age-adjusted Death Rates Per 100,000 1950-1999 (Males) US

2.843.21

2.91 3.1 3.08

3.864.18

4.54.81 4.97

5.17 5.045.26 5.47

0

1

2

3

4

5

6

50-54 55-59 60-64 65-69 70-74 75-79 80-84 85-89 90-94 95-99

White Males

Black Males

Ovarian Cancer -- Age-adjusted Death Rates Per 100,000 1950-1999 (Females) US

7.216.66 6.56 6.43 6.72

8.358.91 8.9 9.03 8.88 8.58

8.11 8.08 8.13

0

1

2

3

4

5

6

7

8

9

10

50-54 55-59 60-64 65-69 70-74 75-79 80-84 85-89 90-94 95-99

White Females

Black Females

Pancreatic Cancer -- Age-adjusted Death Rates Per 100,000 1981-2002 US

11

12.311.7

12.3 12.111.5 11.3 11

8.4 8.3 8.2 8.2 8.2 8 8.2 8.2

0

2

4

6

8

10

12

14

1981 1984 1987 1990 1993 1996 1999 2002

White

Black

Heart Disease -- Age-adjusted Death Rates Per 100,000 1950-2000 US

586.7

548.3

512

455.3

391.5

324.8

584.8559

492.2

409.4

317

253.4

200

250

300

350

400

450

500

550

600

1950 1960 1970 1980 1990 2000

White

Black

Breast Cancer-- Age-adjusted Death Rates Per 100,000 1950-2000

25.327.9 28.9

31.7

38.134.5

32.232.4 32 32.5 32.1 33.2

26.323.9

0

5

10

15

20

25

30

35

40

45

1950 1960 1970 1980 1990 2000 2004

White

Black

Colon, Rectum and Anus -- Age-adjusted Death Rates Per 100,000 1960-2000 US

22.8

26.1

28.3

30.6

28.2

30.9

29.2

27.4

24.1

20.320

22

24

26

28

30

32

34

1960 1970 1980 1990 2000

White

Black

Age-, sex-, race-adjusted pancreatic cancer mortality per 10,000 persons 45 or more years, 1968-2005

Age-, sex-, race-adjusted pancreatic cancer mortality per 10,000 persons 45 or more years, 1968-2005

Age-, sex-, race-adjusted lung cancer mortality per 10,000 persons 45 or more years, 1968-2005

Age-, sex-, race-adjusted lung cancer mortality per 10,000 persons 45 or more years, 1968-2005

Age-, sex-, race-adjusted lung cancer mortality per 10,000 persons 45 years and over by county SES percentile, 1968-2005

What do These Tests Tell Us?

• This is consistent with the social shaping perspective and it says that the scope of problem is large… BUT

• The link to new knowledge and technology is not as direct we would like. Let me turn now to three stories where the linking is somewhat better….

Income Disparities in Cholesterol

• Chang and Lauderdale use data on cholesterol levels from NHANES before (1976-1980) and after the introduction of highly effective statins (1999 -2004)

• Income is assessed as the poverty income ratio

Income Gradients for Total Cholesterol 1976-80 and 1999-2004: Predicted Lipid Levels from NHANES

for Women

213

216

195

200

194

199

204

209

214

219

0 1 2 3 4 5

1976-1980

1999-2004

Chang, Virginia and Diane Lauderdale. 2009. Journal of Health andSocial Behavior 50:245-260

Income Gradients for Total Cholesterol 1976-80 and 1999-2004: Predicted Lipid Levels from NHANES

for Men

212

218

200

205

194

199

204

209

214

219

0 1 2 3 4 5

1976-1980

1999-2004

Chang, Virginia and Diane Lauderdale. 2009. Journal of Health andSocial Behavior 50:245-260

Medical Advances and Race/ Ethnic Disparities in Cancer Survival

• Tehranifar, Neugut, Phelan, Link, Liao, Desai and Terry. 2009. Cancer Epidemiology Biomarkers Prevention.

• Cancer cases (N=580,225) in SEER ages 20+ diagnosed with one invasive cancer in 1995-1999.

• Used 5-year relative survival rates to measure degree to which mortality from each cancer is amenable to medical interventions (early detection and treatment) – ranged from 5% for pancreatic cancer to 99% for prostate cancer.

Do Racial/Ethnic Differences in Survival Increase as Cancers

become more amenable to medical interventions?

0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 100

0.80

1.00

1.20

1.40

1.60

1.80

American Indian/Alaska Na-tive

Asian or Pacific Islander

African American

Hispanic

Haz

ard

Rat

io

<<<<<Less Amenable More Amenable >>>>>

HIV Mortality

• One potentially dramatic example might be HIV-AIDS mortality.

• In particular Highly Active Anti-Retroviral Therapy (HARRT) as a new life saving technology.

HIV Mortality 1987-2005

• Rubin, Colen and Link. 2010. American Journal of Public Health

• HIV mortality in every county in the United States from the National Center for Health Statistics by Age, Race and Gender.

• Constructed rates for every year using mortality data for the numerator and census data for the denominator.

• Constructed SES measures for each county using indicators of education, income, occupation and poverty.

• We identified a pre (1987-1994), a peri (1995-1998) and a post (1999-2005) HARRT period.

• We expect an interaction between SES and period and between race and period such that the benefit HAART is more pronounced in high SES counties and among Whites as opposed to low SES counties and among Blacks

HIV Deaths among Whites per 100,000 by Age

0

5

10

15

20

25

30

35

40

1987

1988

1989

1990

1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

Year

Dea

ths

per

100

,000

15-24 years

25-34 years

35-44 years

45-54 years

55-64 years

HIV Deaths among Blacks per 100,000 by Age

0

20

40

60

80

100

120

140

160

1987

1989

1991

1993

1995

1997

1999

2001

2003

2005

Year

Dea

ths

per

100

,000 15-24 years

25-34 years

35-44 years

45-54 years

55-64 years

Incidence Rate Ratios – Blacks Versus Whites Before (Pre), During (Peri) and After (Post) the Introduction of Highly Active Anti-Retroviral Therapy in the United States

1

3.66

1

5.64

1

7.84

012

3

45

67

89

10

Pre HAART Peri HAART Post HAART

WhiteBlack

IRRs adjusted for age, sex, and SES and urbanicity of county of residence.

Incidence Rate Ratios – Comparing a County at the 95th Percentile of SES to a County at the 5th Percentile of SES Pre, Peri and Post the Introduction of Highly Active Anti-Retroviral Therapy (HAART) in the United States

1

1.41

1

1.91

1

2.72

0

0.5

1

1.5

2

2.5

3

3.5

4

Pre HAART Peri HAART Post HAART

High SES County (5thpercentile)Low SES County (95thpercentile)

IRRs adjusted for age, sex, race, and urbanicity of county of residence

010

2030

1985 1990 1995 2000 2005Year

95% CI Fitted Values for WhitesFitted Values for Blacks

Conclusions

• When we examine Race and SES disparities in mortality by particular diseases we find dramatic evidence that such disparities are created over time.

• Groups with more resources and who face less discrimination benefit more greatly from our new found capacity and disparities emerge

• This means that explanations that propose relatively unchanging causes of disparities like genes, health selection due to health induced disability, relative deprivation, job control etc. cannot be the main reasons for health disparities.

Colon, Rectum and Anus -- Age-adjusted Death Rates Per 100,000 1950-2000

22.8

26.1

28.3

30.629.3

28.2

30.9

29.2

27.4

24.1

22

20.320

22

24

26

28

30

32

34

1950 1960 1970 1980 1990 1995 2000

White

Black

Age-, sex-, race-adjusted lung cancer mortality per 10,000 persons 45 years and over by county SES percentile, 1968-2005

Puzzles • Combinations of SES and gender, race, ethnicity,

immigration status and sexual preference sometimes produces “paradoxes.” Understanding these paradoxes can be a door to newer and deeper knowledge.– Women disadvantaged compared to men but live

longer.– African Americans disadvantaged with respect to SES

but have lower rates of major depression.– Some immigrants groups --though disadvantaged with

respect to SES -- enjoy longer life.

Conclusion

• Many prominent disparities are created when the benefits of new knowledge about disease causation and new approaches to prevention and cure are distributed unequally in populations.

• The HERON’s Gaze needs to be fixed on these unequal distributions and it needs tobe ready to strike when the processes that enable their emergence are evident.