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Background & aimsAccumulating studies have demonstrated associations between single lifestyle exposures and metabolic dysfunction-associated fatty liver disease (MAFLD). However, the joint effects of lifestyle exposures remain unclear, hindering the development of targeted prevention and control strategies. We aimed to investigate the joint associations between lifestyle exposomes and MAFLD.MethodsThis study included 5,002 participants from NHANES 2017–2020. Lifestyle exposomes, including sleep duration, metabolic equivalent of task (MET), Healthy Eating Index (HEI)-2015 score, alcohol consumption, and smoke exposure, were identified from questionnaire data. MAFLD was diagnosed by vibration-controlled transient elastography measurements and laboratory data. A logistic regression model and the weighted quantile sum method were used to evaluate the associations of single and joint lifestyle exposomes, respectively, with MAFLD. The population attributable fractions (PAFs) were calculated to assess the population benefits of different intervention strategies.ResultsPer-quartile range increases in sleep duration (OR=0.883, 95% CI: 0.826–0.944), MET (0.916, 0.871–0.963), and HEI-2015 score (0.827, 0.756–0.904) were significantly associated with MAFLD. The joint exposure of sleep duration, MET, and HEI-2015 score was associated with MAFLD (0.772, 0.688–0.865), with the highest weight (importance) for MET (0.526). PAFs revealed greater intervention benefits for sleep and the HEI-2015 when the majority of the population (>5%) had a low MAFLD risk (weak intervention targets), whereas MET was the most efficient intervention strategy when minority populations (≤5%) had a low MAFLD risk (strong intervention targets).ConclusionThis study demonstrated significant associations between MAFLD and single and joint exposures to sleep duration, MET, and HEI-2015 and identified physical activity as the most important lifestyle factor. Further population benefit analyses may provide evidence and suggestions for population-level interventions.

In environmental epidemiological research, extensive non-random environmental exposures and complex confounding biases pose significant challenges when attempting causal inference. In recent years, the introduction of causal inference methods into observational studies has provided a broader range of statistical tools for causal inference research in environmental epidemiology. The instrumental variable (IV) approach, as a causal inference technique for effectively controlling unmeasured confounding factors, has gradually found application in the field of environmental epidemiological research. This article reviewed the basic principles of IV and summarized the current research progress and limitations of applying IV for causal inference in environmental epidemiology. IV application in the field of environmental epidemiology is still in the initial stage. Rational use of IV and effective integration with other causal inference methods will become the focus of the development of causal inference in environmental epidemiology. The aim of this paper is to provide a methodological reference and basis for future studies involving causal inference to target population health effects of environmental exposures in China.

Background & Aims: Existing evidence suggests that long-term exposure to ambient fine particulate pollution (PM2.5) may increase metabolic dysfunction-associated fatty liver disease (MAFLD) risk. However, there is still limited evidence on the association of PM2.5 constituents with MAFLD. Therefore, this study explores the associations between the five main chemical constituents of PM2.5 and MAFLD to provide more explicit information on the liver exposome. Methods: A total of 76,727 participants derived from the China Multi-Ethnic Cohort, a large-scale epidemic survey in southwest China, were included in this study. Multiple linear regression models were used to estimate the pollutant-specific association with MAFLD. Weighted quantile sum regression was used to evaluate the joint effect of the pollutant-mixture on MAFLD and identify which constituents contribute most to it. Results: Three-year exposure to PM2.5 constituents was associated with a higher MAFLD risk and more severe liver fibrosis. Odds ratios for MAFLD were 1.480, 1.426, 1.294, 1.561, 1.618, and 1.368 per standard deviation increase in PM2.5, black carbon, organic matter, ammonium, sulfate, and nitrate, respectively. Joint exposure to the five major chemical constituents was also positively associated with MAFLD (odds ratio 1.490, 95% CI 1.360–1.632). Nitrate contributed most to the joint effect of the pollutant-mixture. Further stratified analyses indicate that males, current smokers, and individuals with a high-fat diet might be more susceptible to ambient PM2.5 exposure than others. Conclusions: Long-term exposure to PM2.5 and its five major chemical constituents may increase the risk of MAFLD. Nitrate might contribute most to MAFLD, which may provide new clues for liver health. Males, current smokers, and participants with high-fat diets were more susceptible to these associations. Impact and implications: This large-scale epidemiologic study explored the associations between constituents of fine particulate pollution (PM2.5) and metabolic dysfunction-associated fatty liver disease (MAFLD), and further revealed which constituents play a more important role in increasing the risk of MAFLD. In contrast to previous studies that examined the effects of PM2.5 as a whole substance, this study carefully explored the health effects of the individual constituents of PM2.5. These findings could (1) help researchers to identify the specific particles responsible for hepatotoxicity, and (2) indicate possible directions for policymakers to efficiently control ambient air pollution, such as targeting the sources of nitrate pollution.