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.

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. Analysis by gender uncovered covariate-adjusted associations between SRH and both HDL-C (in men) and HbA1c (in women) (p's = 0.01), albeit these associations were no longer significant when evaluated against a Bonferroni-adjusted alpha value (p > 0.004). Sensitivity analysis indicated most findings were unaffected by the type of algorithm used to manage missing data. SEM revealed no indirect associations between SRH, metabolic abnormalities, and lifestyle factors.

CONCLUSIONS

While poor SRH can help primary care physicians identify T2DM patients with metabolic dysfunction, it may not offer added diagnostic usefulness over clinical biomarkers.