Disability weights measurement for 148 childhood health statuses in Hunan, China: a study based on face-to-face surveys.

BACKGROUND

Disability weight (DW) quantifies the impact of disease impairments and symptoms on health statuses, and is a key parameter for estimating disease burden. In this study, we conducted an exploratory measurement of disability weights for common health states among children and adolescents in Hunan Province using a face-to-face survey methodology. This provides preliminary data to support the study of disease burden among this age group.

METHODS

A household survey with face-to-face interviews was conducted to measure DWs for 148 children's health statuses. The questionnaire included 16 paired comparison (PC) questions and 3 population health equivalent (PHE) questions. Probit regression analysis was used to analyze PC responses, with probit regression results from the PC on the DW scale anchored using interval regression results from PHE responses.

RESULTS

The DWs resulting from the study varied from 0.065 (95% uncertainty interval (UI): 0.047-0.087) for acute tonsillitis to 0.730 (UI: 0.709-0.750) for extremely severe intellectual developmental disorders. A comprehensive analysis shows that severe traumatic injuries, such as spinal cord injuries and amputations, as well as congenital defects like hearing loss, visual impairments, and intellectual disabilities, lead to higher DWs due to the long-lasting effects of permanent functional impairments. In contrast, minor bone fractures and transient infectious diseases result in lower DWs. The study demonstrates a high level of consistency in the comparative evaluations of various health outcomes across different sociodemographic characteristics.

CONCLUSIONS

The study strengthens the empirical basis for assessing DWs in children. The PC-PHE method for assessing the DWs of children and adolescents with various health conditions within the Hunan Province population demonstrated robust logic and severity discrimination, with stable results across different population characteristics.