Association of neighborhood-level social determinants and food environments with pediatric hypertension care

Introduction: Deeper understanding of the longitudinal associations of social determinants of health (SDOH) at younger ages with cardiovascular health (CVH) in middle age is needed to address persistent health disparities. Methods: We used repeated measures of individual and neighborhood-level SDOH data from CARDIA participants (ppts) to understand how SDOH change from ages 18-44 years. There were 48 diverse SDOH exposures measured. Using a novel, machine learning, sequential pattern mining method (Subgraph Augmented Non-negative Matrix Factorization), we identified clusters of time-dependent SDOH variables occurring in 5% or more of ppts. Clusters were then used as independent variables in logistic regression models to assess associations with CVH at age ≥45 years. CVH status was defined using the AHA’s Simple 7 metrics on diet, physical activity, smoking, BMI, cholesterol, blood pressure, and blood glucose, and summarized by a 14-point score (poor 0-7, moderate 8-11, high 12-14 points). We tested associations of clusters with the outcome of poor CVH at age ≥45 years, and identified the characteristics of significant SDOH clusters. Results: There were 3,522 ppts included (46.3% Black, 55.9% women; mean age 25.3 years at baseline). Mean CVH score (out of 14) was 10.4 ± 1.8 points at baseline and 8.9 ± 2.3 points at age ≥45 years; 483 ppts (13.7%) had high, 2026 (57.5%) had moderate, and 1013 (28.8%) had poor CVH in middle age. The best performing logistic model included 4 SDOH trend clusters (Table). SDOH Clusters 1, 2, and 3 were each associated with significant 50-80% lower odds of having poor CVH in middle age, whereas Cluster 4 was associated with 2.5-fold higher odds of poor CVH. The most informative variables over time comprising each SDOH cluster are also shown in the Table. Conclusions: Specific SDOH clusters through young adulthood are significantly associated with reaching mid-life with poor CVH status. Components of these SDOH clusters may be potential targets for social interventions and policies to improve CVH.

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Uses and Misuses of Patient- and Neighborhood-level Social Determinants of Health Data

The Permanente Journal ◽

10.7812/tpp/18-078 ◽

2018 ◽

Cited By ~ 2

Author(s):

Laura Gottlieb

Keyword(s):

Social Determinants Of Health ◽

Social Determinants ◽

Health Data ◽

Determinants Of Health ◽

Neighborhood Level

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Neighborhood-level Asian American Populations, Social Determinants of Health, and Health Outcomes in 500 US Cities

Ethnicity & Disease ◽

10.18865/ed.31.3.433 ◽

2021 ◽

Vol 31 (3) ◽

pp. 433-444

Author(s):

Ben R. Spoer ◽

Filippa Juul ◽

Pei Yang Hsieh ◽

Lorna E. Thorpe ◽

Marc N. Gourevitch ◽

...

Keyword(s):

Health Outcome ◽

Health Outcomes ◽

Social Determinants Of Health ◽

Geographic Distribution ◽

Social Determinants ◽

Asian American ◽

The City ◽

Us Cities ◽

Racial Ethnic ◽

Neighborhood Level

Introduction: The US Asian American (AA) population is projected to double by 2050, reaching ~43 million, and currently resides primarily in urban areas. Despite this, the geographic distribution of AA subgroup populations in US cities is not well-characterized, and social determinants of health (SDH) and health measures in places with significant AA/AA subgroup populations have not been described. Our research aimed to: 1) map the geographic distribution of AAs and AA subgroups at the city- and neighborhood- (census tract) level in 500 large US cities (population ≥66,000); 2) characterize SDH and health outcomes in places with significant AA or AA subgroup populations; and 3) compare SDH and health outcomes in places with significant AA or AA subgroup populations to SDH and health outcomes in places with significant non-Hispanic White (NHW) populations.Methods: Maps were generated using 2019 Census 5-year estimates. SDH and health outcome data were obtained from the City Health Dashboard, a free online data platform providing more than 35 measures of health and health drivers at the city and neighborhood level. T-tests compared SDH (unemployment, high-school completion, childhood poverty, income inequality, racial/ ethnic segregation, racial/ethnic diversity, percent uninsured) and health outcomes (obesity, frequent mental distress, cardiovascular disease mortality, life expectancy) in cities/neighborhoods with significant AA/AA subgroup populations to SDH and health outcomes in cities/neighborhoods with significant NHW populations (significant was defined as top population proportion quintile). We analyzed AA subgroups including Indian, Chinese, Filipino, Japanese, Korean, Vietnamese, and Other AA.Results: The count and proportion of AA/ AA subgroup populations varied substantially across and within cities. When comparing cities with significant AA/AA subgroup populations vs NHW populations, there were few meaningful differences in SDH and health outcomes. However, when comparing neighborhoods within cities, areas with significant AA/AA subgroup vs NHW populations had less favorable SDH and health outcomes.Conclusion: When comparing places with significant AA vs NHW populations, city-level data obscured substantial variation in neighborhood-level SDH and health outcome measures. Our findings emphasize the dual importance of granular spatial and AA subgroup data in assessing the influence of SDH in AA populations.Ethn Dis. 2021;31(3):433-444; doi:10.18865/ed.31.3.433

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