Can self-rated health be useful to primary care physicians as a diagnostic indicator of metabolic dysregulations amongst patients with type 2 diabetes? A population-based study

Abstract

Background Although most of the management of type 2 diabetes (T2DM) occurs in primary care, and physicians are tasked with using a ‘whole person’ approach, there is currently a lack of research on psychosocial diagnostic indicators for detecting metabolic abnormalities in T2DM patients. This study examined relations between SRH and metabolic abnormalities in patients with type 2 diabetes, adjusting for metabolic comorbidity. Method A total of 583 adults with type 2 diabetes were identified from the 2019 HSE (Health Survey for England). Data on metabolic syndrome (MetS) was extracted, including lipids (high density lipoprotein cholesterol (HDL-C)), glycated haemoglobin (HbA1c), blood pressure (systolic/diastolic), and anthropometric measures (BMI, waist/hip ratio). Bootstrapped hierarchical regression and structural equation modelling (SEM) were used to analyse the data. Results Adjusting for metabolic covariates attenuated significant associations between SRH and metabolic abnormalities (HDL-C, HbA1c), regardless of MetS status. However, relations between SRH and HbA1c remained marginally significant, after metabolic adjustments (β = -0.15, p = 0.04). Analysis by gender uncovered covariate-adjusted associations between SRH and both HDL-C (in men) and HbA1c (in women) (p’s = 0.01). SEM revealed no indirect associations between SRH, metabolic abnormalities, and lifestyle factors. Conclusions SRH may help primary care physicians identify T2DM patients with HDL-C and HbA1c abnormalities, irrespective of comorbid metabolic biomarkers.