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A Bayesian mixture model approach to examining neighbourhood social determinants of health in endometrial cancer care in Massachusetts

Carmen Rodríguez et al.

Journal of the Royal Statistical Society. Series A: Statistics in Society2026https://doi.org/10.1093/jrsssa/qnag047article
AJG 3
Weight
0.50

Abstract

Many studies examine social determinants of health (SDoH) in isolation, overlooking their interconnected nature. We used a multifactorial approach to construct a neighbourhood-level measure that explores how SDoH jointly impact care received for endometrial cancer (EC) patients in Massachusetts (MA). Using 2015–2019 American Community Survey data, we applied a Bayesian multivariate Bernoulli mixture model to identify MA neighbourhoods with similar SDoH characteristics. Five neighbourhood SDoH (NSDoH) profiles were derived and characterized: (1) advantaged non-Hispanic White; (2) disadvantaged racially/ethnically diverse, more renter-occupied housing with limited English proficiency; (3) working class, lower educational attainment; (4) racially/ethnically diverse and greater economic security and educational attainment; and (5) racially/ethnically diverse, more renter-occupied housing with limited English proficiency. We assigned these profiles to EC patients in the Massachusetts Cancer Registry and used them as the main exposure in a Bayesian logistic regression, adjusting for sociodemographic and clinical characteristics. NSDoH profiles were not associated with optimal care; however, patients in all other profiles had lower odds compared to Profile 1. Our findings demonstrate how a flexible model-based clustering approach captures the multidimensional nature of NSDoH in an interpretable way and may support targeted public health interventions based on neighbourhood-specific social factors to improve healthcare delivery.

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https://doi.org/https://doi.org/10.1093/jrsssa/qnag047

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@article{carmen2026,
  title        = {{A Bayesian mixture model approach to examining neighbourhood social determinants of health in endometrial cancer care in Massachusetts}},
  author       = {Carmen Rodríguez et al.},
  journal      = {Journal of the Royal Statistical Society. Series A: Statistics in Society},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1093/jrsssa/qnag047},
}

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A Bayesian mixture model approach to examining neighbourhood social determinants of health in endometrial cancer care in Massachusetts

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F · citation impact0.50 × 0.4 = 0.20
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R · text relevance †0.50 × 0.4 = 0.20

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