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Environment
Original research
Association of fine particulate matter with glucose and lipid metabolism: a longitudinal study in young adults
  1. Jingyi Qin1,
  2. Wei Xia1,
  3. Gaodao Liang2,
  4. Shunqing Xu1,
  5. Xiuge Zhao3,
  6. Danlu Wang3,
  7. Xiaojie Sun1,
  8. Yuanyuan Li1,
  9. Hongxiu Liu1
  1. 1 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
  2. 2 Institute of Environmental Health, Wuhan Centers for Disease Prevention & Control, Wuhan, Hubei, China
  3. 3 State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, China
  1. Correspondence to Dr Wei Xia, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China; xiawei{at}hust.edu.cn; Dr Gaodao Liang, Institute of Environmental Health, Wuhan Centers for Disease Prevention & Control, Wuhan, China; lgd{at}whcdc.org

Abstract

Objectives This study aimed to evaluate whether PM2.5 exposure in a highly polluted area (>100 µg/m3) affects glucose and lipid metabolism in healthy adults.

Methods 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 PM2.5 levels. Eight glucose and lipid metabolism parameters were quantified. We performed the linear mixed-effect models to investigate the relationships between PM2.5 and glucose and lipid metabolism parameters. Stratified analyses were further performed according to sex and body mass index (BMI).

Results The concentration of PM2.5 was the highest in spring, with a median of 232 μg/m3 and the lowest in autumn (139 μg/m3). After adjusting for potential confounders, we found that for each twofold increase in PM2.5, 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.

Conclusions Exposure to high PM2.5 may have deleterious effects on glucose and lipid metabolism. Females, overweight and obese participants are more vulnerable.

  • epidemiology
  • public health
  • air pollution
  • environmental pollution
  • particulate matter

Data availability statement

There are no data in this work.

https://doi.org/10.1136/oemed-2020-107039

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    Data availability statement

    There are no data in this work.

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    Footnotes

    • Contributors HL and SX took part in the planning and design of the study. JQ performed the statistical analyses and wrote the first draft of the manuscript. XZ, DW, XS and YL implemented the study and monitored data collection. All authors contributed to the interpretation of the results, revision of the manuscript and final approval of the manuscript.

    • Funding This work was supported by the National Natural Science Foundation of China (grant numbers 91643207), the Special Project of Chinese Ministry of the Environmental Protection (2111101), and the National Key Research and Development Plan of China (grant numbers 2016YFC0206203, 2016YFC0206700).

    • Competing interests None declared.

    • Provenance and peer review Not commissioned; externally peer reviewed.

    • Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.