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In the Balance |

Social Conditions and Self-Management Are More Powerful Determinants of Health Than Access to Care

Theodore Pincus, MD; Robert Esther, MD; Darren A. DeWalt, MD; and Leigh F. Callahan, PhD
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From Vanderbilt University School of Medicine, Nashville, Tennessee; and Thurston Arthritis Research Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina. For current author addresses, see end of text. Note: This manuscript emerged from an elective course, “Medicine as a Social Science,” at Vanderbilt University. Grant Support: By the Jack C. Massey Foundation; the Maury County Lupus Fund; Showa Denko KK; The Arthritis Foundation; National Institutes of Health grant 21393 to the Arthritis, Rheumatism and Aging Medical Information System (ARAMIS); and grant AR30701 from the National Institutes of Health. Requests for Reprints: Theodore Pincus, MD, Vanderbilt University School of Medicine, Division of Rheumatology and Immunology, 203 Oxford House, 1313 21st Avenue South, Nashville, TN 37232. Current Author Addresses: Dr. Pincus: Vanderbilt University School of Medicine, Division of Rheumatology and Immunology, 203 Oxford House, 1313 21st Avenue South, Nashville, TN 37232.

Copyright ©2004 by the American College of Physicians

Ann Intern Med. 1998;129(5):406-411. doi:10.7326/0003-4819-129-5-199809010-00011
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Professional organizations advocate universal access to medical care as a primary approach to improving health in the population.Access to medical services is critical to outcomes of acute processes managed in an inpatient hospital, the setting of most medical education, research, and training, but seems to be limited in its capacity to affect outcomes of outpatient care, the setting of most medical activities. Persistent and widening disparities in health according to socioeconomic status provide evidence of limitations of access to care. First, job classification, a measure of socioeconomic status, was a better predictor of cardiovascular death than cholesterol level, blood pressure, and smoking combined in employed London civil servants with universal access to the National Health Service. Second, disparities in health according to socioeconomic status widened between 1970 and 1980 in the United Kingdom despite universal access (similar trends were seen in the United States). Third, in the United States, noncompletion of high school is a greater risk factor than biological factors for development of many diseases, an association that is explained only in part by age, ethnicity, sex, or smoking status. Fourth, level of formal education predicted cardiovascular mortality better than random assignment to active drug or placebo over 3 years in a clinical trial that provides optimal access to care. Increased recognition of limitations of universal access by physicians and their professional societies may enhance efforts to improve the health of the population.


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Figure 1.

Mortality rate over 7.5 years from coronary heart disease (CHD) in 17 530 London civil servants according to type of employment at study entry. Relative risk for death from coronary heart disease according to employment grade explained by blood pressure, cholesterol level, and smoking as recognized risk factors at entry. Reproduced with permission from Marmot and colleagues .

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Figure 2.
Mortality rates from all causes, lung cancer, coronary artery disease (CAD), and cerebrovascular disease (Cerebro VD) from 1970 to 1972 and 1979 to 1983 among men 20 to 64 years of age (top) according to occupational status and among married women 20 to 54 years of age (bottom) according to their husbands' occupations.[29]

SMR = standardized mortality ratio. White circles = manual workers; black circles = nonmanual workers; dashed line = standard mortality (that is, 100). Reproduced with permission from Marmot and colleagues .

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Figure 3.
Comparison of mortality rates in the β-Blocker Heart Attack Trial according to random assignment to placebo or drug, level of formal education, life stress, and social isolation.[30]

Numbers in parentheses are numbers of patients. Solid lines = least favorable values for prognostic variable; dashed lines = intermediate values for prognostic variable; dotted lines = most favorable values for prognostic variable. Reproduced with permission from Ruberman and colleagues .

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