Social determinants of racial health inequities.
Social determinants of racial health inequities.
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种族健康不平等的社会决定因素。
DOI：
10.1016/s2468-2667(23)00100-7
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发表时间：
2023
期刊：
影响因子：
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通讯作者：
Brandt,EricJ
中科院分区：
文献类型：
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作者：
Brandt,EricJ
在《柳叶刀公共卫生》中，约书亚D邦迪和同事报告了健康的社会决定因素（SDoH）如何影响美国大型成年人队列中种族与过早死亡之间的关联。1通过将1999年至2018年美国国家健康和营养检查调查的数据与国家死亡指数的数据联系起来，作者探讨了过早死亡率之间的关联。（定义为75岁之前死亡）和SDoH，分为八个类别：就业状况、家庭收入与贫困比率、粮食安全、教育水平、获得保健的机会、健康保险状况以及已婚或与伴侣生活。SDoH负担的增加与过早死亡的风险增加相关。此外，在调整年龄、性别和不利的SDoH数量后，与白色成年人相比，未观察到黑人成年人的死亡风险增加（仅调整年龄和性别时，风险比为1.00 [95%CI 0.91 - 1.10] vs 1.59 [1.44 - 1.76]）。SDoH完全减弱了黑人种族与死亡率之间的关联，这一发现有助于不断发展的结构性种族主义及其对健康结果的影响的讨论。这些数据是对以下认识的重要补充：造成卫生方面种族和族裔不平等的根本原因是系统性的种族主义，而不是种族或族裔的生物效应。[2]在临床医学中，这些发现很重要，因为我们不再把种族作为临床决策的变量。3最近的一个例子是计算肾功能的方法的变化。2021年，美国国家肾脏基金会和美国肾脏病学会的一个联合工作组宣布了一个新的方程，从方程中删除了种族来估计肾功能。[4]另一个整合种族的方程的例子是用于估计动脉粥样硬化心血管事件风险的合并队列方程，它可以产生跨种族和种族群体的广泛不同的估计。5这些例子表明，使用种族作为其他SDoH的代理可能会导致不同的结果。而以前的公式来估计肾功能更可能导致延迟护理管理晚期肾脏疾病的黑人成年人，合并队列方程更可能导致早期治疗或过度治疗，以预防动脉粥样硬化性心血管疾病的黑人成年人。这两种方法都说明了如何利用种族来做出临床决策，这可能导致医疗服务的不公平。Bundy及其同事建议，我们应该继续改进我们对变量的使用，这些变量可以更好地解释与健康结果的关联，例如SDoH。虽然结构性种族主义通过SDoH导致健康结果的不平等，但仍然存在需要进一步考虑的重要差距。首先，更多的研究可以探索个体SDoH是如何相互关联的。许多SDoH发生在同一个人身上，Bundy和他的同事认识到他们的研究的局限性，没有全面评估这些决定因素的相互联系。当单个协变量被纳入单个模型时，他们能够显示出不同的效应大小;然而，更全面的理解可以更好地指导改善SDoH负面影响的努力。其次，这项研究没有解决SDoH和死亡之间的额外中介变量的问题。已知SDoH与不良心血管健康标志物的患病率增加有关，这些标志物可包括高血压、高血压和烟草使用等。7，8更彻底的...
In The Lancet Public Health, Joshua D Bundy and colleagues report on how social determinants of health (SDoH) affect the association between race and premature mortality in a large cohort of adults in the USA. 1 By linking data from the US National Health and Nutrition Examination Survey from 1999 to 2018 to data from the National Death Index, the authors explored the associations between premature mortality (defined as death before 75 years of age) and SDoH across eight categories: employment status, family income-to-poverty ratio, food security, education level, health-care access, health insurance status, and being married or living with a partner. An increasing burden of SDoH was associated with higher risk of premature death. Additionally, after adjusting for age, gender, and number of unfavourable SDoH, no increased risk of mortality was observed among Black adults compared with White adults (hazard ratio 1· 00 [95% CI 0· 91–1· 10] vs 1· 59 [1· 44–1· 76] when adjusting only for age and gender). This finding that SDoH completely attenuated the association between Black race and mortality contributes to the evolving discussion of structural racism and its effects on health outcomes. Data such as these are an important addition to the recognition that underlying contributors to racial and ethnic inequities in health are driven by systemic racism rather than a biological effect of race or ethnicity. 2 Within clinical medicine, these findings are important as we move away from the use of race as a variable in clinical decision making. 3 One recent example of this is a change in methods to calculate renal function. In 2021, a joint task force of the National Kidney Foundation and the American Society of Nephrology announced a new equation that removed race from equations to estimate renal function. 4 Another example of equations that integrate race are the pooled cohort equations for estimating the risk for atherosclerotic cardiovascular events, which can produce widely different estimates across racial and ethnic groups. 5 These examples show that use of race as a proxy for other SDoH can result in varied outcomes. Whereas the previous equations to estimate renal function were more likely to lead to delayed care in managing advanced renal disease in Black adults, the pooled cohort equations are more likely to lead to earlier treatment or overtreatment for the prevention of atherosclerotic cardiovascular disease among Black adults. Both exemplify how use of race to make clinical decisions can lead to inequities in care delivery. Bundy and colleagues suggest that we should continue to improve our use of variables that better explain associations with health outcomes, 6 such asSDoH. Although structural racism causes inequities in health outcomes through SDoH, there remain important gaps that require additional consideration. First, additional studies could explore how individual SDoH are interconnected. Many SDoH occur within the same individuals, and Bundy and colleagues recognise their study’s limitation in not comprehensively evaluating the interconnectedness of these determinants. They were able to show varying effect sizes for individual covariates when they were included in a single model; however, a more comprehensive understanding could better guide efforts to ameliorate the negative effects of SDoH. Second, this study does not address the problem of additional intermediary variables that lie between SDoH and death. SDoH are known to be connect to an increased prevalence of poor cardiovascular health markers, which can include hypertension, hyperglycaemia, and tobacco use, among others. 7, 8 A more thorough …