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Border-Region Status and Diagnosed Diabetes Prevalence in Texas: A Cross-Sectional Ecological Analysis

Saha, P. R.; Khan, S.; Yahaya, Y.; Meia, M. A. A.

2026-06-02 endocrinology
10.64898/2026.05.30.26354501 medRxiv
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Diagnosed diabetes disproportionately burdens socioeconomically disadvantaged populations in the United States, particularly Hispanic communities in the Texas-Mexico border region. Few studies have quantified whether geographic border-region status is independently associated with county-level diagnosed diabetes prevalence after accounting for lifestyle and food-environment factors. This cross-sectional ecological study examined 253 Texas counties using CDC PLACES 2025 health estimates and USDA Food Environment Atlas food-access data, including the 2015 county-level low-food-access measure. Border-region counties were defined using the official La Paz Agreement 32-county definition, which includes counties within 100 km of the US-Mexico boundary. Multiple linear regression with HC3 robust standard errors was used to estimate associations between border-region status, low food access, physical inactivity, and diagnosed diabetes prevalence. Variance inflation factor analysis assessed multicollinearity, and Global Moran's I tested spatial autocorrelation in diagnosed diabetes prevalence and OLS residuals. Border-region counties had 33% higher unadjusted mean diagnosed diabetes prevalence than non-border counties (16.1% vs. 12.1%). After adjustment, border-region status remained significantly associated with a 0.625 percentage-point higher diagnosed diabetes prevalence ({beta} = 0.625, 95% CI [0.357, 0.893], p < 0.001). Physical inactivity was the strongest independent predictor ({beta} = 0.404, 95% CI [0.391, 0.417], p < 0.001). The model explained 96.0% of county-level variance (R{superscript 2} = 0.960, N = 253), reflecting ecological associations among modeled county-level health indicators. Global Moran's I confirmed strong spatial clustering of diagnosed diabetes prevalence (I = 0.5734, p = 0.001), with reduced but significant residual spatial autocorrelation after OLS adjustment (I = 0.1696, p = 0.001). These findings suggest that border-region status is associated with elevated diagnosed diabetes prevalence beyond physical inactivity and low food access, supporting targeted public health investment in the Texas-Mexico border region

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