Calibrated prevalence of disabling chronic pain according to different approaches: a face-to-face cross-sectional population-based study in Southern Spain

OBJECTIVES: To calculate the prevalence of disabling chronic pain (DCP) and to offer a more representative and accurate estimation by applying different calibration techniques. SETTINGS: 2011 Andalusian Health Survey, a cross-sectional population survey based on face-to-face home interviews. PARTICIPANTS: 6507 people aged 16 years or older and living in Andalusia, Spain. OUTCOMES: Design weights, linear calibration based on marginals and on crossings, and model-assisted calibration were used to estimate the prevalence and variance of DCP, for the whole sample and for the domains of sex and age groups (16–44; 45–64; +65). RESULTS: Calibration variables were sex, age groups and educational level. In the whole sample, DCP prevalence calibration reduced by more than 5.2% and 8.2% the estimated prevalences and variances, respectively, obtained with the design weights. Regarding the domains, prevalence reductions are from 33% to 1%, and variance reductions are from 0.2% to 1%. Model-assisted calibration is the best technique to estimate DCP prevalence for the whole population and crossing calibration for their domains, although with almost no differences compared to marginal calibration. CONCLUSIONS: The validity and accuracy of estimations of DCP prevalence are improved by calibration adjustments. Model-assisted calibrated prevalence of DCP is 10.78% for the whole population, being at least 2-fold higher in women in all age groups. The results and methodology developed could be useful in clinical and population-based studies on chronic pain and disability.