Assessing the degree of concordance in self-reported diabetes diagnosis: DICA Study 2022-23

Abstract Background Early detection of diabetes mellitus (DM) is important for prevention of cardiovascular risk. In epidemiological studies, disease prevalence is often estimated through self-reported diagnoses obtained via surveys. The validity of this approach compared with a gold standard (biochemical criteria or pharmacological treatment) is uncertain. This study aims to assess the agreement between self-reported diabetes and diabetes defined by biochemical parameters and/or treatment. Methods These results are part of the DICA 2022-23 Study, a population-based cross-sectional survey of cardiovascular risk factors in the Region of Murcia (Spain). A total of 2020 participants aged ≥ 20 years were selected through two-stage stratified sampling (health area, sex, age, urban/rural residence). Diabetes was defined as fasting glucose ≥ 126 mg/dL, HbA1c ≥ 6.5 %, or reported diagnosis/treatment. Cohen's Kappa was used to evaluate agreement between self-report and our gold standard. Results 2,020 individuals were analyzed (957 men, 47.3%; 1,063 women, 52.6%). Overall diabetes prevalence was 13.6%. Self-reported diabetes was 12.4%, while 11.3% met the laboratory/treatment definition. Cohen's κ was 0.83 (95% CI: 0.79-0.86), indicating excellent agreement. Sensitivity of the self-reported diagnosis was 0.89 (95% CI: 0.84-0.93) and specificity 0.97 (95% CI: 0.96-0.98). The positive predictive value was 0.81 (95% CI: 0.75-0.85) and the negative predictive value 0.99 (95% CI: 0.98-0.99). Conclusions The high agreement observed shows that self-reported diabetes is a reliable measure for identifying cases. The study's representativeness supports the external validity of self-reported diabetes, reinforcing its use in epidemiological surveys. Nevertheless, biochemical testing remains valuable for refining case identification, classification, and assessment of disease control. Funding Ref. PI20/00068, Carlos III Health Institute. Key messages • Surveys accurately flags diabetes in adult population, enabling for large-scale monitoring. • Biochemical testing remains vital to catch silent cases of diabetes.