Journal of epidemiology and community health · 2025
Heterogeneity in associations between food insecurity and diabetes outcomes.
СтатьяПоддержка исследования: вне правительства СШАПоддержка NIH: внешняя программаПоддержка службы здравоохранения СШАНазвание и аннотация: Перевод пока не подготовлен
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Berkowitz Seth A, Gao Mufeng, Ochoa Aileen, Kuhn Marlena L, Dankovchik Jenine, Donovan Jenna M, LaPoint Myklynn, Basu Sanjay, Hudgens Michael G, Gold Rachel
Аннотация
BACKGROUND: Food insecurity is associated with worse diabetes outcomes, but how that association may vary across individuals is unclear. We sought to better understand possible heterogeneity in the association between food insecurity and diabetes outcomes.
METHODS: Longitudinal cohort study of adults with type 2 diabetes assessed for food insecurity in community-based health centres. Diabetes outcomes were haemoglobin A1c (HbA1c), systolic and diastolic blood pressure, and low-density lipoprotein cholesterol (LDL), 12 months after food insecurity assessment. We used three machine learning methods (generalised random forest (GRF), X-Learner and Doubly Robust Learner) to assess outcome heterogeneity across the following variables: age, sex, race and ethnicity, health insurance, income, comorbidity, baseline outcome and social vulnerability index.
RESULTS: Among 41 581 individuals (mean age 56.2 (SD: 12.8) years, 56.9% female), mean baseline HbA1c was 7.8% (SD: 1.9%) and 10 399 (25.0%) reported food insecurity. Food insecurity was associated with 0.1% greater HbA1c at 12 months, with little heterogeneity. For example, using GRF, the mean difference in HbA1c in the quartile with the lowest estimated HbA1c difference associated with experiencing, versus not experiencing, food insecurity was 0.0%, while the mean difference in the quartile with the greatest estimated difference was 0.2%. Results were similar for other outcomes, except that there was no association between food insecurity and LDL.
CONCLUSIONS: In this study, we did not observe meaningful heterogeneity in the associations between food insecurity and diabetes outcomes.
METHODS: Longitudinal cohort study of adults with type 2 diabetes assessed for food insecurity in community-based health centres. Diabetes outcomes were haemoglobin A1c (HbA1c), systolic and diastolic blood pressure, and low-density lipoprotein cholesterol (LDL), 12 months after food insecurity assessment. We used three machine learning methods (generalised random forest (GRF), X-Learner and Doubly Robust Learner) to assess outcome heterogeneity across the following variables: age, sex, race and ethnicity, health insurance, income, comorbidity, baseline outcome and social vulnerability index.
RESULTS: Among 41 581 individuals (mean age 56.2 (SD: 12.8) years, 56.9% female), mean baseline HbA1c was 7.8% (SD: 1.9%) and 10 399 (25.0%) reported food insecurity. Food insecurity was associated with 0.1% greater HbA1c at 12 months, with little heterogeneity. For example, using GRF, the mean difference in HbA1c in the quartile with the lowest estimated HbA1c difference associated with experiencing, versus not experiencing, food insecurity was 0.0%, while the mean difference in the quartile with the greatest estimated difference was 0.2%. Results were similar for other outcomes, except that there was no association between food insecurity and LDL.
CONCLUSIONS: In this study, we did not observe meaningful heterogeneity in the associations between food insecurity and diabetes outcomes.