Center for Spatial Data Science, Searle Chemistry Laboratory, University of Chicago, Chicago, Illinois.
Center for Health Innovation, American Hospital Association, Chicago, Illinois.
JAMA Netw Open. 2020 Jan 3;3(1):e1919928. doi: 10.1001/jamanetworkopen.2019.19928.
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.
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 = 71 901 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.
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.
Among the 71 901 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 (R2 = 0.63; P < .001), even after accounting for violent crime and spatial structures.
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.
已经报道了社会和邻里特征与健康结果之间的关联,但由于复杂的多维因素在地理空间上各不相同,因此仍然理解不足。
以小区域分辨率量化健康的社会决定因素 (SDOH) 作为多个维度,并研究 SDOH 与伊利诺伊州芝加哥过早死亡之间的关联。
设计、设置和参与者:在这项横断面研究中,使用 2014 年美国人口普查局的普查区来开发多维 SDOH 指数和美国大陆的区域类型学,在小区域水平上(n=71901 个约有 3.12 亿人的普查区)使用降维和聚类机器学习技术(用于减少多元数据维度的无监督算法)。使用相同时期的空间回归来估计芝加哥(n=789 个约有 750 万人的普查区)的年龄调整死亡率,同时控制暴力犯罪。
选择了 15 个变量,以弱势群体的人口统计学特征、经济状况、社会和邻里特征以及住房和交通可用性的 5 年平均值来衡量 SDOH,作为小区域变化。将这个 SDOH 数据矩阵简化为 4 个反映优势、隔离、机会和混合移民凝聚力和可及性的指数,然后将其聚类为 7 个不同的多维邻里类型。通过潜在生命损失年数和聚合到 5 年平均值来衡量芝加哥 SDOH 指数与过早死亡率(定义为 75 岁之前死亡)之间的关联。数据分析于 2018 年 7 月 1 日至 2019 年 8 月 30 日进行。
在所研究的美国大陆 71901 个普查区中,中位数(四分位距)为 27.2%(47.1%)的居民为少数族裔,12.1%(7.5%)有残疾,22.9%(7.6%)为 18 岁以下,13.6%(8.1%)为 65 岁及以上。在所研究的芝加哥 789 个普查区中,中位数(四分位距)为 80.4%(56.3%)的居民为少数族裔,10.2%(8.2%)有残疾,23.2%(10.9%)为 18 岁以下,9.5%(7.1%)为 65 岁及以上。2014 年,美国大陆所有普查区中,有四个 SDOH 指数占 71%的方差。极端贫困的 SDOH 邻里类型学是医疗保健从业者和政策倡导者最关心的问题,它只占美国大陆所有普查区的 9.6%,但却描绘了已知公共卫生危机的小区域。在芝加哥,所有 SDOH 指数与年龄调整的过早死亡率之间均存在关联(R2=0.63;P<.001),即使在考虑到暴力犯罪和空间结构之后也是如此。
将 SDOH 建模为多元指数而不是单一剥夺指数可能更好地捕捉 SDOH 背后的复杂性和空间异质性。在关注 SDOH 的时代,这种分析可能为利益相关者提供有关干预重点的可操作信息。