Determinants and nomogram prediction of catastrophic health expenditures on respiratory diseases and tuberculosis in Guangdong Province—based on National Health Services Surveys in China (Preprint)
Authors: Meng Xiang , Xue Yunlian , Li Sijie , Liu Guihao , Yuan Shasha , Chen Liang , Wang Xiaowan , Li Xiangyong , Zhou Lin 
Published: January 2025

BACKGROUND

Catastrophic health expenditures (CHE) severely impact families, especially in the context of respiratory diseases and tuberculosis. This study evaluates the determinants of CHE and construct nomogram prediction, with a focus on the diverse impacts of regional disparities and income levels in Guangdong Province, China, drawing from the National Health Services Surveys (NHSS) conducted in 2013 and 2023.

OBJECTIVE

To evaluate the determinants of catastrophic health expenditures (CHE) among individuals with respiratory diseases and tuberculosis in Guangdong Province, China, using data from the 2013 and 2023 National Health Services Surveys, and to develop and validate nomograms for predicting CHE while assessing the roles of regional disparities, income levels, and other socioeconomic factors.

METHODS

This multi-year, cross-sectional study utilized data from two NHSS in Guangdong Province. The study population consists of individuals aged 15 years and above with respiratory diseases or tuberculosis in Guangdong Province. CHE was defined as medical and health expenditures exceeding 40% of non-food household expenditures. We employed stepwise logistic regression analyses to identify the determinants of CHE and developed nomograms for prediction, with the Receiver operating characteristic (ROC) curves and the area under the curve (AUC), calibration plots, and decision curve analysis (DCA) utilized to evaluate the predictive accuracy and practical applicability of the models. Mediation analysis was conducted to assess the roles of income and age between regional disparities and the occurrence of CHE.

RESULTS

The incidence of CHE was relatively stable in 2013 (13.5%) and 2023 (13.6%). Significant risk factors included increasing age [OR: 2.615 (1.681, 4.069)], having other chronic diseases [OR: 1.921 (1.177, 3.133)], living in northern Guangdong region [OR: 2.043 (1.204, 6.466)], and insomnia almost every day [OR: 2.843 (1.345, 6.013)], while protective factors included higher income [OR: 0.204 (0.046, 0.918)], being widowed and divorce [OR: 0.120 (0.035, 0.415)] and so on. The mediation analysis highlighted income as a crucial mediator between region and CHE occurrence. Nomograms showed good predictive ability with areas under the curve (AUCs) ranging from 0.844 to 0.884 for training datasets across different survey years and the decision curve analysis (DCA) showing excellent clinical benefits.

CONCLUSIONS

The study highlights the significant effect of regional disparities and socioeconomic status on CHE in Guangdong Province. Income played a pivotal role in mediating these effects, emphasizing the need for targeted economic policies to reduce the burden of health expenditures. The developed nomograms offer practical tools for predicting CHE, aiding healthcare providers in resource allocation and decision-making.