The spatial difference in the healthcare-seeking behaviour and influencing factors among the migrant population with chronic diseases in China

Abstract

Under the long-term household registration system and social segmentation, the migrant population cannot enjoy equal medical services with the local population in the cities. The number of migrant populations with chronic diseases (MPCDs) is increasing, and emerging problems such as unreasonable medical treatment behaviour. Previous studies mainly explored the influencing factors of the prevalence of chronic diseases and the health-seeking behaviour of the migrant population at the individual level. However, the factors that influence health outcomes and care-seeking behaviour need to be considered at both the macro and micro levels. This study is of great significance to formulating strategies and measures for the prevention and control of chronic diseases, rationally allocating health resources, and weakening health inequity. Methods The dataset in this research is China Migrants Dynamic Survey conducted by the China National The dataset in this research is China Migrants Dynamic Survey conducted by the China National Health Commission in 2017, which contained 169,989 samples from 31 provinces/municipalities/autonomous regions. Spatial auto-correlation (global spatial auto-correlation and local spatial auto-correlation) is used to analyze the spatial aggregation of a migrant population with chronic diseases. Geographically Weighted Regression was used to analyze the influencing factors of the health-seeking behaviour of the migrant population with chronic diseases after illness or injury. The selected variables from individual and regional levels include 23 indicators in seven dimensions(Population variables, migrant feature variables, Social variables, Economic variables, Health knowledge variables, Family variables, and Medical environment variables). Results MPCDs with hypertension, diabetes, and comorbidity are accounting for 77.82%, 12.93%, and 9.25% respectively. The regions with the largest number of each disease and comorbidity are Inner Mongolia, Xinjiang, Jiangsu, and the least regions are Hainan. There is a spatial correlation in the spatial distribution of migrant population with chronic diseases, Guangxi, and Jiangxi .Heilongjiang, Inner Mongolia and Jilin show high-high clustering. There are spatial variations in the influencing factors of irrational healthcare-seeking behaviours (no treatment, local pharmacies treatment, and community medical institutions). The main factors can be summarized as population variables (Age, school), family variables (Living together, I-E ratio, Difficult), Migrant feature variables (Unemployed, Stay ), Personal income, Health education, and Medical accessibility. Conclusion MPCDs have a high prevalence within two weeks and poor initiative to seek medical care. Effective measures to control MPCDs strengthen health education and health promotion. Family factors also significantly affect the MPCDs' health-seeking behaviour. Regional medical and security departments should ensure MPCDs and their migrating families can enjoy equal rights and interests of medical services as the local registered population. In addition, according to the population structure and the distribution of the migrant population, the rational allocation of corresponding health education resources and medical resources in different areas is also an effective measure to guide MPCDs to seek medical treatment reasonably. This study provides a reference for managing chronic diseases in the spatial dimension of the migrant population in China.