TY - JOUR
T1 - Joint exposure to air pollution, ambient temperature and residential greenness and their association with metabolic syndrome (MetS)
T2 - A large population-based study among Chinese adults
AU - Feng, Shiyu
AU - Meng, Qiong
AU - Guo, Bing
AU - Guo, Yuming
AU - Chen, Gongbo
AU - Pan, Yongyue
AU - Zhou, Jing
AU - Pengcuociren, null
AU - Xu, Jingru
AU - Zeng, Qibing
AU - Wei, Jing
AU - Xu, Huan
AU - Chen, Lin
AU - Zeng, Chunmei
AU - Zhao, Xing
N1 - Funding Information:
This research was funded by the National Key Research and Development Program of China (Grant No. 2017YFC0907305 ); the National Natural Science Foundation of China (Grant No. 81973151 ); the China Postdoctoral Science Foundation (Grant No. 2020M683335 ); and Sichuan Science and Technology Program (Grant No. 2020JDJQ0014 ). The funders had no role in the study design, data collection, data analysis and interpretation, report writing, or decision to publication.
Publisher Copyright:
© 2022 Elsevier Inc.
PY - 2022/11
Y1 - 2022/11
N2 - Previous studies assessing adverse health have traditionally focused on a single environmental exposure, failing to reflect the reality of various exposures present simultaneously. Air pollution, ambient temperature and greenness have been proposed as critical environmental factors associated with metabolic syndrome (MetS). However, evidence exploring their joint relationships with MetS is needed for identifying interactive factors and developing more targeted public health interventions. The baseline data was obtained from China Multi-Ethnic Cohort (CMEC). Environmental data of air pollutants (PM2.5, O3) and NDVI for greenness was calculated from satellites data. Ambient temperature data were obtained from European Center for Medium-Range Weather Forecasts (ECMWF). MetS was classified based on National Cholesterol Education Program Adult Treatment Panel III (NCEP ATP III) using anthropometric measures and biomarkers. Logistic regression models were utilized to examine the combined relationship of MetS with three-year exposure to air pollutants, temperature and NDVI. Relative excess risk due to interaction (RERI) was calculated to evaluate interaction on an additive scale. We found associations between prevalent MetS and interquartile range (IQR) increases in PM2.5 (OR: 1.38; 95% confidence interval [95% CI]: 1.23, 1.55) and O3 (OR: 1.15; 95% CI: 1.09, 1.22). Additive and multiplicative interactions were observed between air pollutants and temperature exposure. Compared to low-temperature level, the relationship between PM2.5 and MetS attenuated (RERI: 0.22, 95% CI: 0.44, −0.04) at high-temperature level, while the relationship between O3 and MetS enhanced (RERI: 0.05, 95% CI: 0.02, 0.11). At low NDVI 250 m, the association between PM2.5 and MetS was stronger (RERI: 0.13, 95% CI: 0.05, 0.19) with high NDVI 250 m as the reference group. Our findings showed that ambient temperature and residential greenness could affect the relationship between air pollutants and MetS.
AB - Previous studies assessing adverse health have traditionally focused on a single environmental exposure, failing to reflect the reality of various exposures present simultaneously. Air pollution, ambient temperature and greenness have been proposed as critical environmental factors associated with metabolic syndrome (MetS). However, evidence exploring their joint relationships with MetS is needed for identifying interactive factors and developing more targeted public health interventions. The baseline data was obtained from China Multi-Ethnic Cohort (CMEC). Environmental data of air pollutants (PM2.5, O3) and NDVI for greenness was calculated from satellites data. Ambient temperature data were obtained from European Center for Medium-Range Weather Forecasts (ECMWF). MetS was classified based on National Cholesterol Education Program Adult Treatment Panel III (NCEP ATP III) using anthropometric measures and biomarkers. Logistic regression models were utilized to examine the combined relationship of MetS with three-year exposure to air pollutants, temperature and NDVI. Relative excess risk due to interaction (RERI) was calculated to evaluate interaction on an additive scale. We found associations between prevalent MetS and interquartile range (IQR) increases in PM2.5 (OR: 1.38; 95% confidence interval [95% CI]: 1.23, 1.55) and O3 (OR: 1.15; 95% CI: 1.09, 1.22). Additive and multiplicative interactions were observed between air pollutants and temperature exposure. Compared to low-temperature level, the relationship between PM2.5 and MetS attenuated (RERI: 0.22, 95% CI: 0.44, −0.04) at high-temperature level, while the relationship between O3 and MetS enhanced (RERI: 0.05, 95% CI: 0.02, 0.11). At low NDVI 250 m, the association between PM2.5 and MetS was stronger (RERI: 0.13, 95% CI: 0.05, 0.19) with high NDVI 250 m as the reference group. Our findings showed that ambient temperature and residential greenness could affect the relationship between air pollutants and MetS.
KW - Air pollution
KW - China multi-Ethnic cohort
KW - Greenness
KW - Interaction
KW - Metabolic syndrome
KW - Temperature
UR - http://www.scopus.com/inward/record.url?scp=85134583250&partnerID=8YFLogxK
U2 - 10.1016/j.envres.2022.113699
DO - 10.1016/j.envres.2022.113699
M3 - Article
C2 - 35714687
AN - SCOPUS:85134583250
SN - 0013-9351
VL - 214
JO - Environmental Research
JF - Environmental Research
M1 - 113699
ER -
