Background: China has been experiencing the largest rural to urban migration in history. Rural-to-urban migrants are those who leave their hometown for another place in order to work or live without changing their hukou status, which is a household registration system in China, categorizing people as either rural residents or urban residents. Rural-to-urban migrants typically find better job opportunities in destination cities, and these pay higher salaries than available in their home regions. This has served to improve the enrollment rates in the New Cooperative Medical Scheme (NCMS) of rural families, protecting households from falling into poverty due to diseases. However, current regulations stipulate that people who are registered in China's rural hukou can only participate in their local NCMS, which in turn poses barriers when migrants seek medical services in the health facilities of their destination cities. To examine this issue in greater depth, this study examined the associations between migration, economic status of rural households, and NCMS enrollment rate, as well as NCMS utilization of rural-to-urban migrants. Methods: A multistage cluster sampling procedure was adopted. Our sample included 9,097 households and 36,720 individuals. Chi-square test and T-test were used to examine differences between the two populations of migrants and non-migrants based on age, gender, marriage status, and highest level of education. Ordinal logistic regression was used to examine the association between migration and household economic status. Binary logistic regression was used to examine the associations between household economic status, migration and enrollment in the NCMS. Results: Migration was positively associated with improved household economic status. In households with no migrants, only 11.3% of the population was in the richest quintile, whereas the percentage was more than doubled in households with family members who migrated in 2006. Among those using in-patient medical services, 54.3% of migrants in comparison with 17.5% of non-migrants used out-of-county hospitals, many of which were not designated hospitals (Designated hospitals refer to hospitals where, if people use in patient health care, could receive reimbursement from the NCMS.); and 55.2% of migrants in comparison with 24.6% of non-migrants, who had the NCMS in 2006, received no reimbursement from the NCMS. The three main reasons of not receiving reimbursement were: staying in a hospital not designated by the NCMS, lack of knowledge of NCMS policies, and encountering difficulties obtaining reimbursement. Conclusion: Migrants to urban centers improve the economic status of their rural household economic of origin. However, obtaining reimbursement under the current NCMS for the cost of hospital services provided by undesignated providers in urban centers is limited. Addressing this challenge is an emerging policy priority.

Uncertainty remains about the long-term effects of air pollutants (AP) on multiple diseases, especially subtypes of cardiovascular disease (CVD). We aimed to assess the individual and joint associations of fine particulate matter (PM2.5), along with its chemical components, nitrogen dioxide (NO2) and ozone (O3), with risks of 32 health conditions. A total of 17,566 participants in Sichuan Province, China, were included in 2018 and followed until 2022, with an average follow-up period of 4.2 years. The concentrations of AP were measured using a machine-learning approach. The Cox proportional hazards model and quantile g-computation were applied to assess the associations between AP and CVD. Per interquartile range (IQR) increase in PM2.5 mass, NO2, O3, nitrate, ammonium, organic matter (OM), black carbon (BC), chloride, and sulfate were significantly associated with increased risks of various conditions, with hazard ratios (HRs) ranging from 1.06 to 2.48. Exposure to multiple air pollutants was associated with total cardiovascular disease (HR 1.75, 95% confidence intervals (CIs) 1.62–1.89), hypertensive diseases (1.49, 1.38–1.62), cardiac arrests (1.52, 1.30–1.77), arrhythmia (1.76, 1.44–2.15), cerebrovascular diseases (1.86, 1.65–2.10), stroke (1.77, 1.54–2.03), ischemic stroke (1.85, 1.61–2.12), atherosclerosis (1.77, 1.57–1.99), diseases of veins, lymphatic vessels, and lymph nodes (1.32, 1.15–1.51), pneumonia (1.37, 1.16–1.61), inflammatory bowel diseases (1.34, 1.16–1.55), liver diseases (1.59, 1.43–1.77), type 2 diabetes (1.48, 1.26–1.73), lipoprotein metabolism disorders (2.20, 1.96–2.47), purine metabolism disorders (1.61, 1.38–1.88), anemia (1.29, 1.15–1.45), sleep disorders (1.54, 1.33–1.78), renal failure (1.44, 1.21–1.72), kidney stone (1.27, 1.13–1.43), osteoarthritis (2.18, 2.00–2.39), osteoporosis (1.36, 1.14–1.61). OM had max weights for joint effects of AP on many conditions. Long-term exposure to increased levels of multiple air pollutants was associated with risks of multiple health conditions. OM accounted for substantial weight for these increased risks, suggesting it may play an important role in these associations. The associations between AP and multiple diseases remain unclear, especially PM2.5 components and subtypes of CVD. Various AP were found to be associated with multiple diseases. OM may be the important component accounting for these associations. Controlling specific constituents such as OM may be essential for preventing multiple diseases.

Ambient particulate matter with aerodynamic diameter ≤ 2.5 µm (PM_2.5) consists of various toxic constituents. However, the health effect of PM_2.5 may differ depending on its constituents, but the joint effect of PM_2.5 constituents remains incompletely understood. Our goal was to evaluate the joint effect of long-term PM_2.5 constituent exposures on dyslipidemia and identify the most hazardous chemical constituent. This study included 67,015 participants from the China Multi-Ethnic Cohort study. The average yearly levels of PM_2.5 constituents for all individuals at their residences were assessed through satellite remote sensing and chemical transport modeling. Dyslipidemia was defined as one or more following abnormal blood lipid concentrations: total cholesterol (TC) ≥ 6.22 mmol/L, triglycerides (TG) ≥ 2.26 mmol/L, high-density lipoprotein cholesterol (HDL-C) < 1.04 mmol/L, and low-density lipoprotein cholesterol (LDL-C) ≥ 4.14 mmol/L. The logistic regression model was utilized to examine the single effect of PM2.5 constituents on dyslipidemia, while the weighted quantile sum regression model for the joint effect. The odds ratio with a 95 % confidence interval for dyslipidemia positively related to per-SD increase in the three-year average was 1.29 (1.20-1.38) for PM_2.5 mass, 1.25 (1.17-1.34) for black carbon, 1.24 (1.16-1.33) for ammonium, 1.33 (1.24-1.43) for nitrate, 1.34 (1.25-1.44) for organic matter, 1.15 (1.08-1.23) for sulfate, 1.30 (1.22-1.38) for soil particles, and 1.12 (1.05-1.92) for sea salt. Stronger associations were observed in individuals < 65 years of age, males, and those with low physical activity. Joint exposure to PM_2.5 constituents was positively related to dyslipidemia (OR: 1.09, 95 %CI: 1.05-1.14). Nitrate was identified as the constituent with the largest weight (weighted at 0.387). Long-term exposure to PM_2.5 constituents poses a significant risk to dyslipidemia and nitrate might be the most responsible for the risk. These findings indicate that reducing PM_2.5 constituent exposures, especially nitrate, could be beneficial to alleviate the burden of disease attributed to PM_2.5-related dyslipidemia.