134 / 2019-11-05 16:00:00

Improving the evaluation of equity in health resource distribution through high-resolution mapping of disease prevalence: a study in Guangdong province, China

Prevalence of diseases,Gini coefficient,Bayesian geostatistics,Health equity,The fifth National Health Services Survey,Guangdong, China

Background: The common methods used to evaluate health equity under the Lorenz curve and Gini coefficient usually base on population and ignore the disease risk, which may more precisely represent the health demands. This study aimed to develop high-resolution maps of disease risk and apply them as health demand to improve the evaluation of equity in health resource distribution in Guangdong province, China.
Methods: Data of two-week reported prevalence of diseases and potential influencing factors were collected from the fifth National Health Services Survey in 2013 in Guangdong Province at cluster level. We developed a Bayesian geostatistical binary regression model with travel time, demographic, environmental and socioeconomic as predictors, and estimated high resolution disease risk and number of patients in Guangdong province. The estimated number of patients was further used in the calculation of the Lorenz curve and Gini coefficient to improve the evaluation of equity in health resource distribution.
Results: High-resolution risk maps of disease prevalence within two weeks were produced. It was estimated that in 2003, 14.7% (95% Bayesian credible interval [BCI] 13.0-16.8%) of people reported having a disease within two weeks, corresponding to 15.7 million (95% BCI 13.9-17.9) individuals in Guangdong. Areas with higher prevalence were mainly concentrated in the middle and northern part of the province, while areas with higher number of patients were centered in the middle and eastern part. Based on the results of disease estimates, we improved the calculation of equity and assessed a Gini coefficient of 0.4516 in Guangdong province, which indicated the inequity condition of health resource distribution.
Conclusions: The maps of disease prevalence within two weeks provide important information on understanding the spatial pattern of general disease risk in Guangdong, which will further assist disease control and intervention. The result of inequity reminds the necessity to further optimize the health resource allocation in the province.