Skip to main navigation Skip to search Skip to main content

Unveiling causal connections: Long-term particulate matter exposure and type 2 diabetes mellitus mortality in Southern China

  • Tong Guo
  • , Xi Cheng
  • , Jing Wei
  • , Shirui Chen
  • , Yuqin Zhang
  • , Shao Lin
  • , Xinlei Deng
  • , Yanji Qu
  • , Ziqiang Lin
  • , Shimin Chen
  • , Zhiqiang Li
  • , Jie Sun
  • , Xudan Chen
  • , Zhibing Chen
  • , Xurui Sun
  • , Dan Chen
  • , Xingling Ruan
  • , Shaniduhaxi Tuohetasen
  • , Xinyue Li
  • , Man Zhang
  • Yongqing Sun, Shuming Zhu, Xueqing Deng, Yuantao Hao, Qinlong Jing, Wangjian Zhang
  • Sun Yat-Sen University
  • University of Maryland, College Park
  • National Institutes of Health
  • Guangdong Academy of Medical Sciences
  • Jinan University
  • Capital Medical University
  • Peking University
  • Guangzhou Municipal Health Commission

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

Abstract

Evidence of the potential causal links between long-term exposure to particulate matters (PM, i.e., PM1, PM2.5, and PM1–2.5) and T2DM mortality based on large cohorts is limited. In contrast, the existing evidence usually suffers from inherent bias with the traditional association assessment. A prospective cohort of 580,757 participants in the southern region of China were recruited during 2009 and 2015 and followed up through December 2020. PM exposure at each residential address was estimated by linking to the well-established high-resolution simulation dataset. Hazard ratios (HRs) were calculated using time-varying marginal structural Cox models, an established causal inference approach, after adjusting for potential confounders. During follow-up, a total of 717 subjects died from T2DM. For every 1 μg/m3 increase in PM2.5, the adjusted HRs and 95% confidence interval (CI) for T2DM mortality was 1.036 (1.019–1.053). Similarly, for every 1 μg/m3 increase in PM1 and PM1–2.5, the adjusted HRs and 95% CIs were 1.032 (1.003–1.062) and 1.085 (1.054–1.116), respectively. Additionally, we observed a generally more pronounced impact among individuals with lower levels of education or lower residential greenness which as measured by the Normalized Difference Vegetation Index (NDVI). We identified substantial interactions between NDVI and PM1 (P-interaction = 0.003), NDVI and PM2.5 (P-interaction = 0.019), as well as education levels and PM1 (P-interaction = 0.049). The study emphasizes the need to consider environmental and socio-economic factors in strategies to reduce T2DM mortality. We found that PM1, PM2.5, and PM1–2.5 heighten the peril of T2DM mortality, with education and green space exposure roles in modifying it.

Original languageEnglish
Article number116212
JournalEcotoxicology and Environmental Safety
Volume274
DOIs
StatePublished - Apr 1 2024

Keywords

  • T2DM
  • causal modeling
  • effect modification
  • large cohort
  • long-term PM exposure

Fingerprint

Dive into the research topics of 'Unveiling causal connections: Long-term particulate matter exposure and type 2 diabetes mellitus mortality in Southern China'. Together they form a unique fingerprint.

Cite this