Factors influencing the decision to opt out of basic medical insurance among China's migrant population: a logistic regression analysis

影响中国流动人口选择退出基本医疗保险的因素:逻辑回归分析

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Abstract

BACKGROUND: For countries with large internal migrant populations, reducing the opt-out rate from basic medical insurance among this group remains a major obstacle to achieving universal health coverage (UHC). Within China's basic medical insurance system, migrants whose registered household locations differ from their places of residence have comparatively high opt-out rates. If they forgo their entitlement to basic medical insurance, they may face substantial out-of-pocket medical costs and the risk of being unable to access necessary healthcare services when suffering from serious illnesses. This study conceptualizes opting out as a multistage decision-making process influenced by rational and irrational factors. By identifying key associated factors of opting out among migrants, it aims to inform targeted policies to improve their insurance coverage. METHODS: The analytical sample originates from the 2018 China Migrant Population Dynamic Monitoring Survey. After data cleaning and excluding respondents with unclear insurance status, 144,048 valid cases were identified, including 8,355 respondents who reported no enrollment in any scheme. This study first conducted a descriptive analysis of opt-out rates across different migrant groups, across demographic, migration, economic, employment, and health characteristics. Subsequently, a binary logistic regression model was employed to explore the key determinants of opting out. The final model included 11 explanatory variables (age group, educational attainment, marital status, migration duration, mobility range, reason for migration, expected local stay duration, household income, household expenditure, employment status, and recent health status), with the region of residence as a control variable. RESULTS: Descriptive analysis revealed an overall opt-out rate of 5.80% among the migrant population. Opt-out rates varied across the demographic groups. Binary logistic regression analysis further indicated that the probability of opting out was significantly associated with multiple factors, including age, educational attainment, marital status, migration distance, income level, employment stability, and health status. For example, compared with migrants aged 15-19, those aged 60 or older had lower odds of opting out (OR = 0.403, p < 0.001). Compared with interprovincial migrants, intra-city cross-county migrants had lower odds (OR = 0.428, p < 0.001). Higher household income and employment were associated with lower odds (household income ≥20,000 yuan/month: OR = 0.470, p < 0.001; workers without a fixed employer vs. unemployed: OR = 0.736, p < 0.001). Additionally, migrants without recent illness (no recent illness vs. illness requiring hospitalization: OR = 1.320, p < 0.001) were more likely to opt out, consistent with some degree of adverse selection. CONCLUSION: Under China's current basic medical insurance system, opt-out behavior among the migrant population is the result of the combined effects of the multidimensional individual variables. To effectively reduce the opt-out rate, targeted adjustments to the current medical insurance policies should be proactively made, thereby advancing the full achievement of UHC.

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