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Gender differences in health care access indicators in an urban, low- income community

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  • Merzel, C.

Abstract

Objectives. This study examined factors associated with gender differences in health insurance coverage and having a usual source of medical care. Methods. In-person interviews were conducted with a community sample of 695 residents of Central Harlem, New York City. Predictors of the 2 outcome variables and the interaction of key variables with gender were analyzed via logistic regression. Results. No strong patterns emerged to explain gender differentials in having insurance coverage and having a usual provider. However, women employed full time had increased odds of insurance coverage, whereas employment had no similar effect among men. Public assistance evidenced a strong relationship with insurance coverage among both men and women. Socioeconomic factors and health insurance were important independent predictors of having a usual source of health care for men but had little effect among women. Conclusions. Expanding the availability of both public insurance and affordable private coverage for men living in low-income communities is an important means of reducing gender disparities in access to health care. Public assistance is an important means of enabling access to health care for men as well as women.

Suggested Citation

  • Merzel, C., 2000. "Gender differences in health care access indicators in an urban, low- income community," American Journal of Public Health, American Public Health Association, vol. 90(6), pages 909-916.
  • Handle: RePEc:aph:ajpbhl:2000:90:6:909-916_5
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    Cited by:

    1. Galea, Sandro & Freudenberg, Nicholas & Vlahov, David, 2005. "Cities and population health," Social Science & Medicine, Elsevier, vol. 60(5), pages 1017-1033, March.
    2. Mitchell, Penelope & Samsel, Steven & Curtin, Kevin M. & Price, Ashleigh & Turner, Daniel & Tramp, Ryan & Hudnall, Matthew & Parton, Jason & Lewis, Dwight, 2022. "Geographic disparities in access to Medication for Opioid Use Disorder across US census tracts based on treatment utilization behavior," Social Science & Medicine, Elsevier, vol. 302(C).

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