Primary care, race, and mortality in US states

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Abstract

This study used US state-level data from 1985 to 1995 to examine the relationship of primary care resources and income inequality with all-cause mortality within the entire population, and in black and white populations. The study is a pooled ecological design with repeated measures using 11 years of state-level data (n=549). Analyses controlled for socioeconomic and demographic characteristics. Contemporaneous and time-lagged covariates were modeled, and all analyses were stratified by race/ethnicity. In all models, primary care was associated with lower mortality. An increase of one primary care doctor per 10,000 population was associated with a reduction of 14.4 deaths per 100,000. The magnitude of primary care coefficients was higher for black mortality than for white mortality. Income inequality was not associated with mortality after controlling for state-level sociodemographic covariates. The study provides evidence that primary care resources are associated with population health and could aid in reducing socioeconomic disparities in health.

Section snippets

Background

In the past decade, substantial literature suggested a significant association between income inequality and mortality both in the US and abroad (Blakely, Lochner, & Kawachi, 2002; Wilkinson, 1996; Kennedy, Kawachi, & Prothrow-Stith, 1996; Lochner, Pamuk, Makuc, Kennedy, & Kawachi, 2001; Lynch et al., 1998; McLaughlin & Stokes, 2002; Subramanian, Blakely, & Kawachi, 2003). The greater the gap in income distribution between the rich and poor in a given area, the higher the mortality rate for the

Data and measures

Data for this study came from a variety of sources including the Compressed Mortality Files (US Department of Health and Human Services National Center for Health Statistics, 2000), the US Department of Commerce and the Census Bureau (1985), US Department of Commerce and the Census Bureau (1986), US Department of Commerce and the Census Bureau (1987), US Department of Commerce and the Census Bureau (1988), US Department of Commerce and the Census Bureau (1989), US Department of Commerce and the

Results

During 1985–1995, there was a decline in all-cause mortality. The mean state age-adjusted mortality rate dropped from 821 to 762 per 100,000 population (Fig. 1, Panel 1). In the same period, there was a steady increase in primary care physicians, from 5.02 to 6.04 per 10,000 population (Fig. 1, Panel 2). Income inequality within states fluctuated during the period with an overall worsening trend: the mean of the Gini coefficient among states increased from 0.41 to 0.43 during the period (Fig. 1

Discussion

This study confirmed earlier findings that primary care was associated with lower mortality and partially mediated the association between socioeconomic variables and mortality (Shi, Starfield, Kennedy, & Kawachi (1999), Shi, Starfield, Politzer, & Regan (2002); Shi & Starfield (2001), Shi, Starfield, Kennedy, & Kawachi (1999)). These findings are significant because they provide more robust evidence of a relationship between primary care physicians and lower state mortality than was possible

References (91)

  • Physician characteristics and distribution in the United States

    (1988)
  • Physician characteristics and distribution in the United States

    (1989)
  • Physician characteristics and distribution in the United States

    (1990)
  • Physician characteristics and distribution in the United States

    (1991)
  • Physician characteristics and distribution in the United States

    (1992)
  • Physician characteristics and distribution in the United States

    (1993)
  • Physician characteristics and distribution in the United States

    (1994)
  • Physician characteristics and distribution in the United States

    (1995)
  • Physician characteristics and distribution in the United States

    (1996)
  • M. Bergner

    Measurement of health status

    Medical Care

    (1985)
  • J. Bunker

    Medicine matters after allmeasuring the benefits of medical care, a healthy lifestyle and a just social environment

    (2001)
  • J.P. Bunker et al.

    The role of medical care in determining healthcreating an inventory of benefits

  • C. Casanova et al.

    Pediatric hospitalization due to ambulatory care-sensitive conditions in Valencia (Spain)

    International Journal for Quality in Health Care

    (1996)
  • C. Casanova et al.

    Hospitalizations of children and access to primary carea cross-national comparison

    International Journal of Health Services

    (1995)
  • A.V. Diez-Roux

    Bringing context back into epidemiologyvariables and fallacies in multilevel analysis

    American Journal of Public Health

    (1998)
  • A. Donabedian

    Twenty years of research on the quality of medical care: 1964–1984

    Evaluation and the Health Professions

    (1985)
  • T.R. Dye

    Politics in states and communities

    (1991)
  • S.A. Everson et al.

    Hopelessness and risk of mortality and incidence of myocardial infarction and cancer

    Psychosomatic Medicine

    (1996)
  • A. Friede et al.

    CDC WONDERa comprehensive on-line public health information system of the Centers for Disease Control and Prevention

    American Journal of Public Health

    (1993)
  • J. Hadley

    More medical care, better health?

    (1982)
  • C. Hsiao

    Analysis of panel data

    (1986)
  • I. Kawachi et al.

    Social capital and self-rated healtha contextual analysis

    American Journal of Public Health

    (1999)
  • I. Kawachi et al.

    Social capital, income inequality, and mortality

    American Journal of Public Health

    (1997)
  • B.P. Kennedy et al.

    Income distribution and mortalitycross sectional ecological study of the Robin Hood index in the United States

    British Medical Journal

    (1996)
  • R.J. Klein et al.

    Health status indicatorsdefinitions and national data

    Healthy people 2000 statistical notes

    (1992)
  • R.C. Littell et al.

    Modelling covariance structure in the analysis of repeated measures data

    Statistics in Medicine

    (2000)
  • K. Lochner et al.

    State-level income inequality and individual mortality riska prospective, multilevel study

    American Journal of Public Health

    (2001)
  • J.W. Lynch et al.

    Understanding how inequality in the distribution of income affects health

    Journal of Health Psychology

    (1997)
  • J.W. Lynch et al.

    Income inequality and mortality in metropolitan areas of the United States

    American Journal of Public Health

    (1998)
  • J. Lynch et al.

    Is income inequality a determinant of population health? Part 1. A systematic review

    Milbank Quarterly

    (2004)
  • J. Macinko et al.

    The contribution of primary care systems to health outcomes within Organization for Economic Cooperation and Development (OECD) countries, 1970–1998

    Health Services Research

    (2003)
  • D.K. McLaughlin et al.

    Income inequality and mortality in US countiesdoes minority racial concentration matter?

    American Journal of Public Health

    (2002)
  • J.M. Mellor et al.

    Reexamining the evidence of an ecological association between income inequality and health

    Journal of Health Politics, Policy and Law

    (2001)
  • T.Q. Miller et al.

    A meta-analytic review of research on hostility and physical health

    Psychological Bulletin

    (1996)
  • Health, United States 1985

    (1985)
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