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    Original Investigation
    Public Health
    January 29, 2020

    Quantification of Neighborhood-Level Social Determinants of Health in the Continental United States

    Author Affiliations
    • 1Center for Spatial Data Science, Searle Chemistry Laboratory, University of Chicago, Chicago, Illinois
    • 2Center for Health Innovation, American Hospital Association, Chicago, Illinois
    JAMA Netw Open. 2020;3(1):e1919928. doi:10.1001/jamanetworkopen.2019.19928
    Key Points español 中文 (chinese)

    Question  How do social determinants of health vary across multiple dimensions and geographic space?

    Findings  In this cross-sectional study of 71 901 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.

    Abstract

    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 = 71 901 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 71 901 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.

    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.

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