Agreement between self-reported diseases from health surveys and national health registry data: a Danish nationwide study

BACKGROUND: Agreement may be low when comparing self-reported diseases in health surveys with registry data. The aim of the present study was to examine the agreement between seven self-reported diseases among a representative sample of Danish adults aged ≥16 years and data from medical records. Moreover, possible associations with sociodemographic variables were examined.

METHODS: Nationally representative data on self-reported current or previous diabetes, asthma, rheumatoid arthritis, osteoporosis, myocardial infarction, stroke and cancer, respectively, were derived from the Danish National Health Survey in 2017 (N=183 372). Individual-level data were linked to data on the same diseases from medical records in registries. Logistic regression models were used to explore potential associations between sociodemographic variables and total agreement.

RESULTS: For all included diseases, specificity was >92% and sensitivity varied between 66% (cancer) and 95% (diabetes). Negative predictive value (NPV) was >96% for all diseases and positive predictive value (PPV) varied between 13% (rheumatoid arthritis) and 90% (cancer). Total agreement varied between 91% (asthma) and 99% (diabetes), whereas the kappa value was lowest for rheumatoid arthritis (0.21) and highest for diabetes (0.88). Sociodemographic variables were demonstrated to be significantly associated with total agreement for all diseases, with sex, age and educational level exhibiting the strongest associations. However, the directions of the associations were inconsistent across diseases.

CONCLUSION: Overall, self-reported data were accurate in identifying individuals without the specific disease (ie, specificity and NPV). However, sensitivity, PPV and kappa varied greatly between diseases. These findings should be considered when interpreting similar results from surveys.