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Our goal was to examine inequality in healthcare utilization and the factors that contribute to inequality between China's floating and native populations. Based on the China Labor-force Dynamics Surveys from 2014 to 2018, which used three rounds of data, we utilized a panel probit model that included fixed effects for time and province to estimate the probability of healthcare utilization for floating and native populations. In addition, we calculated the degree of inequality in healthcare utilization by using the method of mobility-related inequality and a decomposition approach was used to explain the contribution of each factor to the inequality. The floating population utilized healthcare at a lower rate, with a 10.5% probability of visiting a hospital and a 20.9% probability of receiving hospitalized treatment. The concentration index of mobility-related inequality in healthcare utilization shows a negative coefficient of −0.137 for hospital visits and −0.356 for hospitalized treatment. Contribution decomposition shows that self-assessed health, job category and household registration account for the largest contribution to the inequality in hospital visits, contributing −0.038, 0.021 and −0.017, respectively. Age, household registration and insurance account for the largest contribution to the inequality in hospitalized treatment, contributing −0.053, 0.024 and −0.023, respectively. The floating population was less likely to use health services and faced an inequality in treatment compared with the native population.

Mobility-related inequality in healthcare utilization between floating and native populations and its influencing factors: evidence from China