Background The accelerated aging trend brought great chronic diseases burdens. Disabled Adjusted Life Years (DALYs) is a novel way to measure the chronic diseases burden. This study aimed to explore the cohort, socioeconomic status (SES), and gender disparities of the DALYs trajectories. Methods A total of 15,062 participants (55,740 observations) comes from China Health and Retirement Longitudinal Study (CHARLS) from 2011 to 2018. Mixed growth curve model was adopted to predict the DALYS trajectories in 45–90 years old people influenced by different birth cohorts and SES. Results We find significant cohort, SES (resident place, education level and income) disparities differences in the chronic diseases DALYs. For individuals of earlier cohort, DALYs are developed in a late age but grow fast with age but reversed for most recent cohorts. Living in urban, having higher SES level will decrease the growth rate with age, but converges for most recent cohorts. Meanwhile, DALYs disparities of resident place and education level show gender differentials that those for female are narrowed across cohort but for male are not. Conclusions The cohort effects on chronic diseases DALYs are accumulated with China’s unique social, and political settings. There are large inequalities in early experiences, SES and DALYs. Efforts of reducing these inequalities must focus on the lower SES individuals and those living in rural areas, which greatly benefit individuals from recent cohorts.

Background: Since 2012, China has come into a new period of health development. This paper comprehensively described China’s health development and explored associated influencing factors during the last 6 years (2012-2017).Methods: Data for this study came from statistics yearbook and analysis unit were provincial regions. Comprehensive evaluation (principal component analysis and entropy weight method) was employed to calculate the comprehensive health index to evaluate the health. Then linear growth model was applied to explore factors that influenced the development.Results: Results showed that, since 2012, China’s health had a sustainable growth but inequities among provincial regions were still existing and becoming larger. For influencing factors, time was always a significant positive predictor ( ) and it was affected by geographical distributions ( ) and distance to Beijing ( ), which indicated that regions in central or far from Beijing had a lower growth. Among socioeconomics variables, urbanization level was the final factor ( ) that promoted China’s health development and caused development inequalities. Besides, health level was also influenced by the distance to Beijing ( ), regions near to Beijing had a higher health level.Conclusion: Time effect was the results of policy, during 2012 to 2017, China’s sustainable health development was brought by the policy effect and growth of urbanization level.Thus, it is crucial for one country to introduce suitable health policies and narrow the urban-rural gaps to improve its health. Distance to Beijing represented the potential political influence on health of one country’s capital due to the policy execution level which means that supervisions need to be strengthened for regions far from the capital. Besides, supports and supervisions also need to be enhanced in central regions. They were one of the reasons that caused development inequalities.