ArticleCureus2025
Impact of Health Insurance Status on HbA1c Control Among United States Adults With Type 2 Diabetes: A Cross-Sectional Analysis of Nationally Representative Data.
Article in Cureus, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundGlycemic control is essential for reducing complications in individuals with type 2 diabetes. Health insurance is a known determinant of access to care, yet its relationship with glycemic outcomes remains underexplored in nationally representative data. Therefore, the objective of this study is to assess the association between health insurance status and glycemic control among United States (US) adults with diagnosed type 2 diabetes (diagnostic A1c cutoff ≥ 6.5%) using National Health and Nutrition Examination Survey (NHANES) data. We hypothesized that uninsured adults with type 2 diabetes would have higher odds of poor glycemic control.
methodsA cross-sectional analysis was conducted using data from the NHANES 2013-2018 cycles. Adults aged ≥18 years with diagnosed type 2 diabetes were included. Survey-weighted logistic regression models examined the association between insurance status and poor glycemic control (glycated hemoglobin (HbA1c) ≥ 7%), adjusting for demographic, clinical, and behavioral covariates. Descriptive and inferential statistics accounted for the complex survey design.
resultsAmong 229 million weighted US adults with diagnosed type 2 diabetes, 195,397,912 (85%) were insured. Among those with poor glycemic control, 18,684,942 (87%) were insured and 2,901,970 (13%) were uninsured. Insurance status was not significantly associated with glycemic control in either the demographically adjusted model (odds ratio (OR) = 1.15, 95% confidence interval (CI): 0.91-1.45) or the fully adjusted model (OR = 1.12, 95% CI: 0.89-1.41). Significant predictors of poor glycemic control included age, gender, body mass index (BMI), income, and race/ethnicity.
conclusionHealth insurance alone may not ensure optimal glycemic control. Addressing broader social and clinical factors is essential to improving outcomes in diabetes care.
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