种族隔离是健康的社会决定因素:来自乔治亚州的证据

Simon K. Medcalfe, Catherine P. Slade, Divesia Lee
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引用次数: 1

摘要

背景:​尽管进行了几十年的研究,但确定健康方面种族差异的原因仍然是公共卫生领域的一个有害问题。挑战包括进一步完善健康的定义,以及扩大健康的社会决定因素框架,以包括相关和相关的预测因素。种族隔离作为健康的社会决定因素,虽然研究不足,但人们对健康差距的讨论越来越感兴趣。本文实证研究了种族隔离与健康社会决定因素的其他预测因素之间的关系,以及它们对客观和主观健康结果的集体影响。方法:​使用普通最小二乘回归分析来分析Robert Wood Johnson 2018佐治亚州县健康排名的健康结果。在县一级,我们考虑了两类不同的健康结果作为因变量,包括健康状况的客观指标,如年龄调整后的死亡率,以及从个人生活质量的角度来看的更主观的指标,如自我报告的健康。代表种族隔离的自变量包括黑人-白人隔离和非白人-白人隔离指数。结果:​我们的研究结果是,种族隔离与客观的健康结果测量没有显著关联。相反,令人惊讶的是,黑人-白人和非白人-白人隔离程度较高的县表现出更好的自我报告健康状况。根据先前的文献,控制变量对健康结果具有预期影响。结论:​虽然隔离并不意味着健康状况较差,但较高的生活质量评估结果令人担忧,因为一个人对健康的看法可以预测健康行为和获得所需护理的机会。我们认为,种族隔离是健康框架和模式的社会决定因素的重要补充,值得在全国范围内继续进行多学科研究。
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Racial Segregation as a Social Determinant of Health: Evidence from the State of Georgia
Background: ​Despite decades of research, determining the causes of racial disparities in health remains a pernicious problem in the public health arena. Challenges include further refining definitions of health as well as expanding frameworks for social determinants of health to include relevant and related predictors. Racial segregation as a social determinant of health is understudied but of growing interest in the discourse on health disparities. This paper explores empirically the relationship between racial segregation and other predictors of social determinants of health and their collective impact on health outcomes defined in both objective and subjective terms. Methods: ​Ordinary least squares regression analysis was used to analyze health outcomes from the Robert Wood Johnson 2018 County Health Rankings for Georgia. At the county level we considered two distinct categories of health outcomes as the dependent variables, including objective measures of health status such as age-adjusted mortality and more subjective measures from the person’s perspective of quality of life such self-reported health. The independent variables representing racial segregation included the black-white segregation and nonwhite-white segregation indices. Results: ​Our findings are that racial segregation is not significantly associated with objective health outcome measures. Conversely and surprisingly, counties with higher levels of black-white and nonwhite-white segregation show better self-reported health. Control variables have the expected impact on health outcomes based on previous literature. Conclusions: ​While segregation does not suggest poorer health status, the findings of higher quality of life assessment is concerning as a person’s perspectives on their health predicts healthy behaviors and access to needed care. We suggest that racial segregation is an important addition to social determinants of health frameworks and models and worthy of continued multidisciplinary research on a national basis.
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