J Prev Med Public Health.
2023 Jul;56(4):291-302. 10.3961/jpmph.23.192.
Updating Korean Disability Weights for Causes of Disease: Adopting an Add-on Study Method
- Affiliations
-
- 1Department of Preventive Medicine, Ulsan University Hospital, University of Ulsan College of Medicine, Ulsan, Korea
- 2Department of Family and Community Medicine, Faculty of Medicine, Public Health, and Nursing, Universitas Gadjah Mada, Yogyakarta, Indonesia
- 3Department of Preventive Medicine, Korea University College of Medicine, Seoul, Korea
- 4Big Data Department, National Health Insurance Service, Wonju, Korea
- 5Research & Statistics Team, Korean Health Promotion Institute, Seoul, Korea
- 6Artificial Intelligence and Big-Data Convergence Center, Gil Medical Center, Gachon University College of Medicine, Incheon, Korea
- 7Department of Preventive Medicine, University of Ulsan College of Medicine, Seoul, Korea
- KMID: 2544634
- DOI: http://doi.org/10.3961/jpmph.23.192
Abstract
Objectives
Disability weights require regular updates, as they are influenced by both diseases and societal perceptions. Consequently, it is necessary to develop an up-to-date list of the causes of diseases and establish a survey panel for estimating disability weights. Accordingly, this study was conducted to calculate, assess, modify, and validate disability weights suitable for Korea, accounting for its cultural and social characteristics.
Methods
The 380 causes of disease used in the survey were derived from the 2019 Global Burden of Disease Collaborative Network and from 2019 and 2020 Korean studies on disability weights for causes of disease. Disability weights were reanalyzed by integrating the findings of an earlier survey on disability weights in Korea with those of the additional survey conducted in this study. The responses were transformed into paired comparisons and analyzed using probit regression analysis. Coefficients for the causes of disease were converted into predicted probabilities, and disability weights in 2 models (model 1 and 2) were rescaled using a normal distribution and the natural logarithm, respectively.
Results
The mean values for the 380 causes of disease in models 1 and 2 were 0.488 and 0.369, respectively. Both models exhibited the same order of disability weights. The disability weights for the 300 causes of disease present in both the current and 2019 studies demonstrated a Pearson correlation coefficient of 0.994 (p=0.001 for both models). This study presents a detailed add-on approach for calculating disability weights.
Conclusions
This method can be employed in other countries to obtain timely disability weight estimations.
- Full Text Links
-
- Actions
-
Cited
- CITED
-
- Close
- Share
-
- Similar articles
-
- Review of Issues for Disability Weight Studies
- Disability Weights Measurement for 289 Causes of Disease Considering Disease Severity in Korea
- Disability Weights for Cancers in Korea
- Disability Weights Measurement for 228 Causes of Disease in the Korean Burden of Disease Study 2012
- Disability Weights for the Korean Burden of Disease Study: Focused on Comparison with Disability Weights in the Australian Burden of Disease Study
