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1.
Health Aff (Millwood) ; 38(12): 1976-1984, 2019 12.
Artigo em Inglês | MEDLINE | ID: mdl-31794301

RESUMO

Rural populations disproportionately suffer from adverse health outcomes, including poorer health and higher age-adjusted mortality. We argue that these disparities are due in part to declining health care provider availability and accessibility in rural communities. Rural challenges are exacerbated by "structural urbanism"-elements of the current public health and health care systems that disadvantage rural communities. We suggest that biases in current models of health care funding, which treat health care as a service for an individual rather than as infrastructure for a population, are innately biased in favor of large populations. Until this bias is recognized, the development of viable models for care across the rural-urban continuum cannot move forward.


Assuntos
Atenção à Saúde , Acessibilidade aos Serviços de Saúde , Disparidades em Assistência à Saúde , Mortalidade/tendências , Avaliação de Resultados em Cuidados de Saúde , Saúde da População Rural/estatística & dados numéricos , Viés , Disparidades em Assistência à Saúde/etnologia , Disparidades em Assistência à Saúde/estatística & dados numéricos , Humanos , Saúde da População , Saúde da População Urbana
2.
BMC Public Health ; 16: 10, 2016 Jan 05.
Artigo em Inglês | MEDLINE | ID: mdl-26728042

RESUMO

BACKGROUND: Studies suggest that the built environment with high numbers of fast food restaurants and convenience stores and low numbers of super stores and grocery stores are related to obesity, type II diabetes mellitus, and other chronic diseases. Since few studies assess these relationships at the county level, we aim to examine fast food restaurant density, convenience store density, super store density, and grocery store density and prevalence of type II diabetes among counties in South Carolina. METHODS: Pearson's correlation between four types of food outlet densities- fast food restaurants, convenience stores, super stores, and grocery stores- and prevalence of type II diabetes were computed. The relationship between each of these food outlet densities were mapped with prevalence of type II diabetes, and OLS regression analysis was completed adjusting for county-level rates of obesity, physical inactivity, density of recreation facilities, unemployment, households with no car and limited access to stores, education, and race. RESULTS: We showed a significant, negative relationship between fast food restaurant density and prevalence of type II diabetes, and a significant, positive relationship between convenience store density and prevalence of type II diabetes. In adjusted analysis, the food outlet densities (of any type) was not associated with prevalence of type II diabetes. CONCLUSIONS: This ecological analysis showed no associations between fast food restaurants, convenience stores, super stores, or grocery stores densities and the prevalence of type II diabetes. Consideration of environmental, social, and cultural determinants, as well as individual behaviors is needed in future research.


Assuntos
Comércio , Diabetes Mellitus Tipo 2/etiologia , Meio Ambiente , Fast Foods , Diabetes Mellitus Tipo 2/epidemiologia , Ecologia , Planejamento Ambiental , Feminino , Humanos , Masculino , Obesidade/etiologia , Prevalência , Características de Residência , Restaurantes , South Carolina/epidemiologia
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