Literature DB >> 22611656

Not just smoking and high-tech medicine: socioeconomic inequities in U.S. mortality rates, overall and by race/ethnicity, 1960-2006.

Nancy Krieger1, Jarvis T Chen, Anna Kosheleva, Pamela D Waterman.   

Abstract

Recent research on the post-1980 widening of U.S. socioeconomic inequalities in mortality has emphasized the contribution of smoking and high-tech medicine, with some studies treating the growing inequalities as effectively inevitable. No studies, however, have analyzed long-term trends in U.S. mortality rates and inequities unrelated to smoking or due to lack of basic medical care, even as a handful have shown that U.S. socioeconomic inequalities in overall mortality shrank between the mid-1960s and 1980. The authors accordingly analyzed U.S. mortality data for 1960-2006, stratified by county income quintile and race/ethnicity, for mortality unrelated to smoking and preventable by 1960s' standards of medical care. Key findings are that relative and absolute socioeconomic inequalities in U.S. mortality unrelated to smoking and preventable by 1960s' medical care standards shrank between the 1960s and 1980 and then increased and stagnated, with absolute rates on a par with several leading causes of death, and with the burden greatest for U.S. populations of color. None of these findings can be attributed to trends in smoking-related deaths and access to high-tech medicine, and they also demonstrate that socioeconomic inequities in mortality can shrink and need not inevitably rise.

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Year:  2012        PMID: 22611656      PMCID: PMC3359870          DOI: 10.2190/HS.42.2.i

Source DB:  PubMed          Journal:  Int J Health Serv        ISSN: 0020-7314            Impact factor:   1.663


  16 in total

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Authors:  H M Rosenberg; J D Maurer; P D Sorlie; N J Johnson; M F MacDorman; D L Hoyert; J F Spitler; C Scott
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9.  Geographical variation in mortality from conditions amenable to medical intervention in England and Wales.

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10.  Maximum likelihood estimation of the attributable fraction from logistic models.

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  3 in total

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Journal:  J Urban Health       Date:  2016-06       Impact factor: 3.671

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Journal:  SSM Popul Health       Date:  2016-12
  3 in total

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