Background and objectives The global epidemic of type 2 diabetes mellitus (T2DM) is disproportionately severe in rural and agricultural populations, driven by the complex interplay of socioeconomic, behavioural, and genetic risk factors. While these determinants are acknowledged individually, few studies have validated a parsimonious, integrated measurement model to effectively structure and assess their collective influence on glycaemic control within a rural primary care context. We aimed to address this critical gap. Methods We conducted a cross-sectional, observational study utilising a purposive sample of 1,011 patients with uncontrolled T2DM recruited from a rural diabetic healthcare setting. To empirically test the structural relationships among key risk factors, we employed a confirmatory factor analysis (CFA) to validate a four-factor measurement model. This model integrated 14 observed indicators across the latent constructs of alcohol addiction, economic conditions, dietary habits, and family history of T2DM. Results The proposed four-factor model demonstrated an excellent practical fit to the observed data, confirming its structural validity. All factor loadings were statistically significant ( P <0.001). The magnitude of practical misfit was medium (Cohen’s w=0.37), validating the model’s overall explanatory power. Factor intercorrelations revealed a significant positive correlation between alcohol addiction and economic condition (r=0.109, P =0.006), and a significant negative relationship between diet and family history of T2DM (r=-0.154, P =0.014). Interpretation and conclusions Our findings establish alcohol addiction, economic conditions, dietary habits, and family history as robust, interrelated determinants of glycaemic control in rural primary care. The validated structural model provides an evidence-based tool for risk stratification and personalised intervention.
Ananthakumar et al. (Tue,) studied this question.