Qin Jingyi, Xia Wei, Liang Gaodao, Xu Shunqing, Zhao Xiuge, Wang Danlu, Sun Xiaojie, Li Yuanyuan, Liu Hongxiu
Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubation), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubation), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
Occup Environ Med. 2021 Feb 26. doi: 10.1136/oemed-2020-107039.
This study aimed to evaluate whether PM exposure in a highly polluted area (>100 µg/m) affects glucose and lipid metabolism in healthy adults.
We recruited 110 healthy adults in Baoding city, Hebei, China, and followed them up between 2017 and 2018. Personal air samplers were used to monitor personal PM levels. Eight glucose and lipid metabolism parameters were quantified. We performed the linear mixed-effect models to investigate the relationships between PM and glucose and lipid metabolism parameters. Stratified analyses were further performed according to sex and body mass index (BMI).
The concentration of PM was the highest in spring, with a median of 232 μg/m and the lowest in autumn (139 μg/m). After adjusting for potential confounders, we found that for each twofold increase in PM, the median of insulin concentration decreased by 5.89% (95% CI -10.91% to -0.58%; p<0.05), and ox-LDL increased by 6.43% (95% CI 2.21% to 10.82%; p<0.05). Stratified analyses indicated that the associations were more pronounced in females, overweight and obese participants.
Exposure to high PM may have deleterious effects on glucose and lipid metabolism. Females, overweight and obese participants are more vulnerable.
本研究旨在评估在高污染地区(>100μg/m)暴露于细颗粒物(PM)是否会影响健康成年人的糖脂代谢。
我们在中国河北省保定市招募了110名健康成年人,并在2017年至2018年期间对他们进行随访。使用个人空气采样器监测个人PM水平。对八个糖脂代谢参数进行定量分析。我们采用线性混合效应模型来研究PM与糖脂代谢参数之间的关系。并根据性别和体重指数(BMI)进一步进行分层分析。
PM浓度在春季最高,中位数为232μg/m,秋季最低(139μg/m)。在调整潜在混杂因素后,我们发现,PM每增加一倍,胰岛素浓度中位数下降5.89%(95%CI -10.91%至-0.58%;p<0.05),氧化型低密度脂蛋白(ox-LDL)增加6.43%(95%CI 2.21%至10.82%;p<0.05)。分层分析表明,这种关联在女性、超重和肥胖参与者中更为明显。
暴露于高浓度PM可能对糖脂代谢产生有害影响。女性、超重和肥胖参与者更易受影响。