Long-term exposure to PM2.5 chemical constituents and diabesity: evidence from a multi-center cohort study in China.

Background: Long-term exposure to PM2.5 is known to increase the risks for diabetes and obesity, but its effects on their coexistence, termed diabesity, remain uncertain. This study aimed to investigate the associations of long-term exposure to PM2.5 and its chemical constituents with the risks for diabesity, diabetes, and obesity. Methods: This cross-sectional study used the baseline data of a multi-center cohort, consisting of three provincially representative cohorts comprising a total of 134,403 participants from the eastern (Fujian Province), central (Hubei Province), and western (Yunnan Province) regions of China. Obesity and diabetes, and diabesity were identified by a body mass index (BMI) ≥28 kg/m2 and fasting plasma glucose (FPG) ≥126 mg/dL. The average concentrations of PM2.5 and five chemical constituents (NO3 -, SO4 2-, NH4 +, organic matter, and black carbon) over participants' residence during the past three years were estimated using machine learning models. Logistic regression models with double robust estimators, Bayesian kernel machine regression, and weighted quantile sum regression were employed to estimate independent and joint effects of PM2.5 chemical constituents on the risks for diabesity, diabetes, and obesity, as well as the differences from the effects on obesity. Stratified analyses were performed to examine effect modification of sociodemographic and lifestyle factors. Findings: There were 129,244 participants with a mean age of 54.1 ± 13.8 years included in the study. Each interquartile range increase in PM2.5 concentration (8.53 µg/m3) was associated with an increased risk for diabesity (OR = 1.23 [1.17, 1.30]), diabetes only (OR = 1.16 [1.13, 1.19]), and obesity only (OR = 1.03 [1.00, 1.05]). Long-term exposure to each PM2.5 chemical constituent was associated with an increased risk for diabesity, where organic matter exposure, with maximum weight (48%), was associated with a higher risk for diabesity (OR = 1.21 [1.16, 1.27]). Among those with obesity, black carbon contributed most (68%) to the joint effect of PM2.5 chemical constituents on diabesity (OR = 1.16 [1.11, 1.22]). Physical activity reduced adverse effects of PM2.5 on diabesity. Also, additive rather than multiplicative effects of obesity on the PM2.5-diabetes association were observed. Interpretation: Long-term exposure to PM2.5 and its chemical constituents was associated with an increased risk for diabesity, stronger than associations for diabetes and obesity alone. The main constituents associated with diabesity and obesity were black carbon and organic matter. Funding: National Natural Science Foundation of China (42271433, 723B2017), National Key R&D Program of China (2023YFC3604702), Fundamental Research Funds for the Central Universities (2042023kfyq04, 2042024kf1024), the Science and Technology Major Project of Tibetan Autonomous Region of China (XZ202201ZD0001G), Science and technology project of Tibet Autonomous Region（XZ202303ZY0007G), Key R&D Project of Sichuan Province (2023YFS0251), Renmin Hospital of Wuhan University (JCRCYG-2022-003), Jiangxi Provincial 03 Special Foundation and 5G Program (20224ABC03A05), Wuhan University Specific Fund for Major School-level Internationalization Initiatives (WHU-GJZDZX-PT07).

Associations between residential greenness and obesity phenotypes among adults in Southwest China.

BACKGROUND: Although exposure to greenness has generally benefited human metabolic health, the association between greenness exposure and metabolic obesity remains poorly studied. We aimed to investigate the associations between residential greenness and obesity phenotypes and the mediation effects of air pollutants and physical activity (PA) level on the associations. METHODS: We used the baseline of the China Multi-Ethnic Cohort (CMEC) study, which enrolled 87,613 adults. Obesity phenotypes were defined based on obesity and metabolic status, including metabolically unhealthy obesity (MUO), non-obesity (MUNO), metabolically healthy obesity (MHO), and non-obesity (MHNO). Greenness exposure was measured as the 3-year mean values of the normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI) within the 500-m buffer zones around the participants' residence. Multivariable logistic regression was used to estimate the associations between greenness and obesity phenotypes. Stratified analyses by age, sex, educational level, and urbanicity were performed to identify how the effect varies across different subgroups. Causal mediation analysis was used to examine the mediation effects of air pollutants and PA level. RESULTS: Compared with MHNO, each interquartile range (IQR) increase in greenness exposure was associated with reduced risks of MHO (ORNDVI [95% CI] = 0.87 [0.81, 0.93]; OREVI = 0.91 [0.86, 0.97]), MUO (ORNDVI = 0.83 [0.78, 0.88]; OREVI = 0.86 [0.81, 0.91]), and MUNO (ORNDVI = 0.88 [0.84, 0.91]; OREVI = 0.89 [0.86, 0.92]). For each IQR increase in both NDVI and EVI, the risks of MHO, MUO, and MUNO were reduced more in men, participants over 60 years, those with a higher level of education, and those living in urban areas, compared to their counterparts. Concentrations of particulate matter (PM) and PA level partially mediated the associations between greenness exposure and obesity phenotypes. CONCLUSIONS: Exposure to residential greenness was associated with decreased risks of MHO, MUO, and MUNO, which was mediated by concentrations of PM and PA level, and modified by sex, age, educational level, and urbanicity.

Effectiveness of a socioecological model-guided, smart device-based, self-management-oriented lifestyle intervention in community residents: protocol for a cluster-randomized controlled trial.

BACKGROUND: Healthy lifestyles are crucial for preventing chronic diseases. Nonetheless, approximately 90% of Chinese community residents regularly engage in at least one unhealthy lifestyle. Mobile smart devices-based health interventions (mHealth) that incorporate theoretical frameworks regarding behavioral change in interaction with the environment may provide an appealing and cost-effective approach for promoting sustainable adaptations of healthier lifestyles. We designed a randomized controlled trial (RCT) to evaluate the effectiveness of a socioecological model-guided, smart device-based, and self-management-oriented lifestyles (3SLIFE) intervention, to promote healthy lifestyles among Chinese community residents. METHODS: This two-arm, parallel, cluster-RCT with a 6-month intervention and 6-month follow-up period foresees to randomize a total of 20 communities/villages from 4 townships in a 1:1 ratio to either intervention or control. Within these communities, a total of at least 256 community residents will be enrolled. The experimental group will receive a multi-level intervention based on the socioecological model supplemented with a multi-dimensional empowerment approach. The control group will receive information only. The primary outcome is the reduction of modifiable unhealthy lifestyles at six months, including smoking, excess alcohol consumption, physical inactivity, unbalanced diet, and overweight/obesity. A reduction by one unhealthy behavior measured with the Healthy Lifestyle Index Score (HLIS) will be considered favorable. Secondary outcomes include reduction of specific unhealthy lifestyles at 3 months, 9 months, and 12 months, and mental health outcomes such as depression measured with PHQ-9, social outcomes such as social support measured with the modified Multidimensional Scale of Perceived Social Support, clinical outcomes such as obesity, and biomedical outcomes such as the development of gut microbiota. Data will be analyzed with mixed effects generalized linear models with family and link function determined by outcome distribution and accounting for clustering of participants in communities. DISCUSSION: This study will provide evidence concerning the effect of a mHealth intervention that incorporates a behavioral change theoretical framework on cultivating and maintaining healthy lifestyles in community residents. The study will provide insights into research on and application of similar mHealth intervention strategies to promote healthy lifestyles in community populations and settings. TRIAL REGISTRATION NUMBER: ChiCTR2300070575. Date of registration: April 17, 2023. https://www.chictr.org.cn/index.aspx .

Long-term effects of PM2.5 constituents on metabolic syndrome and mediation effects of serum uric acid.

Exposure to particulate matter with aerodynamic diameter ≤2.5 µm (PM2.5) was associated with the risk for metabolic syndrome (MetS) in the general population, but the contributions of individual PM2.5 constituents to this association and the potential pathway between PM2.5 constituents and MetS risk are not well elaborated. This study aimed to investigate associations between PM2.5 constituents and MetS in general populations, relative importance of PM2.5 constituents to and mediation effects of serum uric acid (SUA) on those associations. The 48,148 participants from a provincially representative cohort established in southwest China were included. The 3-year average concentrations of PM2.5 and its constituents (nitrate [NO3-], sulfate [SO42-], ammonium [NH4+], organic matter [OM], and black carbon [BC]) were estimated using a series of machine-learning models. Multivariate logistic regression and weighted quantile sum regression were used to estimate effects of independent PM2.5 constituents on MetS and their contributions to the joint effect. Mediation analysis examined the potential mediation effects of SUA on the associations between PM2.5 constituents and MetS. Each interquartile range (IQR) increase in the concentration of PM2.5 constituents was all positively associated with the increased MetS odds, including SO42- (OR = 1.15 [1.11, 1.19]]), NO3- (OR = 1.12 [1.08, 1.16]), NH4+ (OR = 1.13 [1.09, 1.17]), OM (OR = 1.09 [1.06, 1.13]), and BC (OR = 1.09 [1.06, 1.13]). Their joint associations on MetS were mainly attributed to SO42- (weight=46.1%) and NH4+ (44.0%). The associations of PM2.5 constituents with abnormal MetS components were mainly attributed to NH4+ for elevated BP (51.6%) and reduced HDL-C (97.0%), SO42- for elevated FG (68.9%), NO3- for elevated TG (51.0%), and OM for elevated WC (63.0%). Percentages mediated by SUA for the associations of PM2.5, SO42-, NO3-, and BC with MetS were 13.6%, 13.1%, 10.6%, and 11.1%, respectively. Long-term exposure to PM2.5 constituents, mainly NH4+ and SO42-, was positively associated with MetS odds, partially mediated by SUA.

Associations between long-term exposure to PM2.5 chemical constituents and allergic diseases: evidence from a large cohort study in China.

BACKGROUND: Exposure to air pollutants may cause immune responses and further allergic diseases, but existing studies have mostly, if not all, focused on effects of short-term exposure to PM2.5 on allergic diseases. OBJECTIVES: We estimated associations of long-term exposure to PM2.5 chemical constituents with allergic disease risks and effect modification. METHODS: We used the baseline of a newly established, provincially representative cohort of 51,480 participants in southwest China. The presence of allergic rhinitis, allergic asthma, urticaria, and allergic conjunctivitis was self-reported by following a formed questionnaire in face-to-face interviews. The average concentrations of PM2.5 chemical constituents (NO3-, SO42-, NH4+, organic matter [OM], and black carbon [BC]) over participants' residence were estimated using machine learning models. Logistic regression with double robust estimator and weighted quantile sum regression were used to estimate the effects of PM2.5 chemical constituents on allergic disease risks, as well as relative importance of each PM2.5 chemical constituent. RESULTS: Per interquartile range increase in the concentration of all PM2.5 chemical constituents was associated with the elevated risks for allergic asthma (OR = 1.79 [1.41-2.26]), allergic conjunctivitis (1.54 [1.19-2.00]), urticaria (1.36 [1.25-1.48]), and allergic rhinitis (1.18 [1.11-1.26]). NO3- contributed more to risks for allergic asthma (weight = 46.05 %), urticaria (72.29 %), and allergic conjunctivitis (47.65 %), while NH4+ contributed more to allergic rhinitis (78.07 %). OM contributed most to the risks for allergic asthma (30.81 %) and allergic conjunctivitis (31.40 %). BC was also associated with allergic rhinitis, urticaria, and allergic conjunctivitis, only with a considerable weight for urticaria (24.59 %). Joint effects of PM2.5 chemical constituents on risks for allergic rhinitis and urticaria were stronger in minorities and farmers than their counterparts. CONCLUSION: Long-term exposure to PM2.5 chemical constituents was associated with the increased allergic disease risks, with NO3- and NH4+ accounting for the largest variance of the associations. Our findings would serve as scientific evidence for developing more explicit strategies of air pollution control.