Innovation in aging · 2026
Simulation modeling of neighborhood-level differences in life course health outcomes: a proof of concept.
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Dalton Jarrod E, Gunsalus Paul R, Perzynski Adam T, Mourany Lyla, Pfoh Elizabeth R, Blazel Madeleine M, Gunzler Douglas D, Martinez Kathryn A, Taksler Glen B
Аннотация
BACKGROUND AND OBJECTIVES: Adults in low-resource neighborhoods face greater burden of preventable diseases than the general population. Methodologies to measure the impact of population-level efforts to reduce neighborhood-level disparities in health outcomes are lacking. We introduce a simulation modeling approach for incident disease and mortality risk over the life course and apply the model to assess the impact of a hypothetical population health initiative to reduce neighborhood-level disparities.
RESEARCH DESIGN AND METHODS: Using electronic health records, we constructed a probabilistic dynamic systems model that simulated the life course of each patient in a large primary care population, taking into account specific relationships by sex and Area Deprivation Index (ADI) quintile. The model predicted long-term incidence of 10 chronic conditions and all-cause mortality.
RESULTS: The model was reliable, with strong discrimination (C-statistic for 10-year mortality: 0.871) and calibration. Predicted median life expectancy was nearly a decade lower for patients ages 40-45 who resided in the highest (ADI quintile 5) vs the lowest (quintile 1) deprivation neighborhoods (difference [95% CI]; women, 8.6 [8.2, 9.0] years; men, 10.0 [9.6, 10.3]. A hypothetical initiative to reduce the number of smokers by 10% had minimal effect on disparities in life expectancy when implemented in the general patient population (women, -0.4 years; men, -0.2), but meaningfully narrowed disparities when focused on high-deprivation neighborhoods (women, -0.8 years; men, -0.6).
DISCUSSION AND IMPLICATIONS: In a broad patient population, it was feasible to measure socioeconomic disparities in health outcomes and life expectancy and evaluate interventions to improve health equity.
RESEARCH DESIGN AND METHODS: Using electronic health records, we constructed a probabilistic dynamic systems model that simulated the life course of each patient in a large primary care population, taking into account specific relationships by sex and Area Deprivation Index (ADI) quintile. The model predicted long-term incidence of 10 chronic conditions and all-cause mortality.
RESULTS: The model was reliable, with strong discrimination (C-statistic for 10-year mortality: 0.871) and calibration. Predicted median life expectancy was nearly a decade lower for patients ages 40-45 who resided in the highest (ADI quintile 5) vs the lowest (quintile 1) deprivation neighborhoods (difference [95% CI]; women, 8.6 [8.2, 9.0] years; men, 10.0 [9.6, 10.3]. A hypothetical initiative to reduce the number of smokers by 10% had minimal effect on disparities in life expectancy when implemented in the general patient population (women, -0.4 years; men, -0.2), but meaningfully narrowed disparities when focused on high-deprivation neighborhoods (women, -0.8 years; men, -0.6).
DISCUSSION AND IMPLICATIONS: In a broad patient population, it was feasible to measure socioeconomic disparities in health outcomes and life expectancy and evaluate interventions to improve health equity.