Quantification of Neighborhood-Level Social Determinants of Health in the Continental United States
Quantification of Neighborhood-Level Social Determinants of Health in the Continental United States
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DOI：
10.1001/jamanetworkopen.2019.19928
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发表时间：
2020-01-29
影响因子：
13.8
通讯作者：
Molefe, Ayrin
中科院分区：
文献类型：
--
作者：
Kolak, Marynia;Bhatt, Jay;Molefe, Ayrin
问题 健康的社会决定因素在多个维度和地理空间中如何变化？结果 在这项针对美国大陆约 3.12 亿人的 71& x202f;901 人口普查区的横断面研究中，健康指标的多元社会决定因素被简化为反映优势、隔离、机会以及混合移民凝聚力和可达性的 4 个指数，并被聚类为 7 个社区类型，其中包括极端贫困群体。健康指数的社会决定因素与伊利诺伊州芝加哥市的过早死亡率相关。意义 使用多维地理空间方法来量化健康的社会决定因素，而不是使用单一的剥夺指数，可以更好地捕捉这些决定因素背后的复杂性和空间异质性。 重要性 社会和邻里特征与健康结果之间的关联已被报道，但由于跨地理空间变化的复杂多维因素，人们对社会和邻里特征与健康结果之间的关联仍知之甚少。目标 以小区域分辨率将美国大陆（48 个相邻州和哥伦比亚特区）的健康社会决定因素 (SDOH) 量化为多个维度，并研究 SDOH 与伊利诺伊州芝加哥市过早死亡的关联。设计、设置和参与者 在这项横断面研究中，使用来自 2014 年美国人口普查局的人口普查区，使用降维和聚类机器学习技术（用于降低多变量数据维度的无监督算法），开发多维 SDOH 指数和美国大陆小区域水平的区域类型学（n = 71&x202f;901 个人口普查区，约有 3.12 亿人）。 SDOH 指数用于估计芝加哥（n = 789 个人口普查区，约 750 万人）的年龄调整死亡率，并进行同期空间回归，同时控制暴力犯罪。主要成果和措施 选择以 5 年平均值衡量的 15 个变量，将 SDOH 描述为人口普查区层面弱势群体人口特征、经济状况、社会和邻里特征以及住房和交通可用性的小区域变化。该 SDOH 数据矩阵简化为 4 个指数，反映优势、隔离、机会以及混合移民凝聚力和可达性，然后将其聚类为 7 个不同的多维邻里类型。在芝加哥，SDOH 指数与过早死亡率（定义为 75 岁之前死亡）之间的关联是通过潜在寿命损失年数来衡量的，并汇总为 5 年平均值。数据分析于 2018 年 7 月 1 日至 2019 年 8 月 30 日期间进行。 结果 在美国大陆各地检查的 71& x202f;901 个人口普查区中，中位值（四分位数间距）为 27.2% (47.1%) 的居民为少数族裔，12.1% (7.5%) 患有残疾，22.9% (7.6%) 的居民年龄为 18 岁，年龄较年轻，13.6% (8.1%) 为 65 岁及以上。在芝加哥调查的 789 个人口普查区中，中位数（四分位距）为 80.4% (56.3%) 的居民为少数族裔，10.2% (8.2%) 的居民有残疾，23.2% (10.9%) 的居民年龄在 18 岁及以下，9.5% (7.1%) 的居民年龄在 65 岁及以上。 2014 年，四个 SDOH 指数占美国大陆所有人口普查区差异的 71%。SDOH 极端贫困社区类型是医疗保健从业者和政策倡导者最关心的，仅占美国大陆所有人口普查区的 9.6%，但其特征是存在已知公共卫生危机的小区域。即使在考虑了暴力犯罪和空间结构之后，芝加哥所有 SDOH 指数与年龄调整过早死亡率之间仍存在关联（R-2 = 0.63；P < .001）。结论和相关性 将 SDOH 建模为多元指数而不是单一剥夺指数，可以更好地捕捉 SDOH 背后的复杂性和空间异质性。在人们越来越关注 SDOH 的时期，该分析可以为关键利益相关者提供有关干预重点的可行信息。这项横断面研究使用美国人口普查局的数据和多维地理空间方法来量化美国大陆的健康社会决定因素，并研究伊利诺伊州芝加哥健康问题社会决定因素与过早死亡之间的关系。
Question How do social determinants of health vary across multiple dimensions and geographic space? Findings In this cross-sectional study of 71& x202f;901 census tracts with approximately 312 million persons across the continental United States, multivariate social determinants of health measures were reduced to 4 indices reflecting advantage, isolation, opportunity, and mixed immigrant cohesion and accessibility and were clustered into 7 neighborhood typologies that included an extreme poverty group. Social determinants of health indices were associated with premature mortality rates in Chicago, Illinois. Meaning The use of multidimensional geospatial approaches to quantify social determinants of health rather than the use of a singular deprivation index may better capture the complexity and spatial heterogeneity underlying these determinants.Importance An association between social and neighborhood characteristics and health outcomes has been reported but remains poorly understood owing to complex multidimensional factors that vary across geographic space. Objectives To quantify social determinants of health (SDOH) as multiple dimensions across the continental United States (the 48 contiguous states and the District of Columbia) at a small-area resolution and to examine the association of SDOH with premature mortality within Chicago, Illinois. Design, Setting, and Participants In this cross-sectional study, census tracts from the US Census Bureau from 2014 were used to develop multidimensional SDOH indices and a regional typology of the continental United States at a small-area level (n = 71& x202f;901 census tracts with approximately 312 million persons) using dimension reduction and clustering machine learning techniques (unsupervised algorithms used to reduce dimensions of multivariate data). The SDOH indices were used to estimate age-adjusted mortality rates in Chicago (n = 789 census tracts with approximately 7.5 million persons) with a spatial regression for the same period, while controlling for violent crime. Main Outcomes and Measures Fifteen variables, measured as a 5-year mean, were selected to characterize SDOH as small-area variations for demographic characteristics of vulnerable groups, economic status, social and neighborhood characteristics, and housing and transportation availability at the census-tract level. This SDOH data matrix was reduced to 4 indices reflecting advantage, isolation, opportunity, and mixed immigrant cohesion and accessibility, which were then clustered into 7 distinct multidimensional neighborhood typologies. The association between SDOH indices and premature mortality (defined as death before age 75 years) in Chicago was measured by years of potential life lost and aggregated to a 5-year mean. Data analyses were conducted between July 1, 2018, and August 30, 2019. Results Among the 71& x202f;901 census tracts examined across the continental United States, a median (interquartile range) of 27.2% (47.1%) of residents had minority status, 12.1% (7.5%) had disabilities, 22.9% (7.6%) were 18 years and younger, and 13.6% (8.1%) were 65 years and older. Among the 789 census tracts examined in Chicago, a median (interquartile range) of 80.4% (56.3%) of residents had minority status, 10.2% (8.2%) had disabilities, 23.2% (10.9%) were 18 years and younger, and 9.5% (7.1%) were 65 years and older. Four SDOH indices accounted for 71% of the variance across all census tracts in the continental United States in 2014. The SDOH neighborhood typology of extreme poverty, which is of greatest concern to health care practitioners and policy advocates, comprised only 9.6% of all census tracts across the continental United States but characterized small areas of known public health crises. An association was observed between all SDOH indices and age-adjusted premature mortality rates in Chicago (R-2 = 0.63; P < .001), even after accounting for violent crime and spatial structures. Conclusions and Relevance The modeling of SDOH as multivariate indices rather than as a singular deprivation index may better capture the complexity and spatial heterogeneity underlying SDOH. During a time of increased attention to SDOH, this analysis may provide actionable information for key stakeholders with respect to the focus of interventions.This cross-sectional study uses data from the US Census Bureau and a multidimensional geospatial approach to quantify social determinants of health across the continental United States and to examine the association of social determinants of health with premature mortality in Chicago, Illinois.