1. Patients with diabetes struggling to afford food and control their HbA1c in food-insecure areas in Bronx, NY.
- Author
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Chambers EC, Levano SR, Cohen N, Maroko AR, Telzak A, Stephenson-Hunter C, and Fiori KP
- Subjects
- Humans, Female, Male, Cross-Sectional Studies, Middle Aged, Retrospective Studies, Aged, New York City epidemiology, Food Supply statistics & numerical data, Adult, Self Report, Diabetes Mellitus, Type 2 blood, Food Insecurity, Glycated Hemoglobin analysis, Glycemic Control statistics & numerical data, Glycemic Control methods
- Abstract
Objective: To characterise the association between risk of poor glycaemic control and self-reported and area-level food insecurity among adult patients with type 2 diabetes., Design: We performed a retrospective, observational analysis of cross-sectional data routinely collected within a health system. Logistic regressions estimated the association between glycaemic control and the dual effect of self-reported and area-level measures of food insecurity., Setting: The health system included a network of ambulatory primary and speciality care sites and hospitals in Bronx County, NY., Participants: Patients diagnosed with type 2 diabetes who completed a health-related social need (HRSN) assessment between April 2018 and December 2019., Results: 5500 patients with type 2 diabetes were assessed for HRSN with 7·1 % reporting an unmet food need. Patients with self-reported food needs demonstrated higher odds of having poor glycaemic control compared with those without food needs (adjusted OR (aOR): 1·59, 95 % CI: 1·26, 2·00). However, there was no conclusive evidence that area-level food insecurity alone was a significant predictor of glycaemic control (aOR: 1·15, 95 % CI: 0·96, 1·39). Patients with self-reported food needs residing in food-secure (aOR: 1·83, 95 % CI: 1·22, 2·74) and food-insecure (aOR: 1·72, 95 % CI: 1·25, 2·37) areas showed higher odds of poor glycaemic control than those without self-reported food needs residing in food-secure areas., Conclusions: These findings highlight the importance of utilising patient- and area-level social needs data to identify individuals for targeted interventions with increased risk of adverse health outcomes.
- Published
- 2024
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