Long-term air pollution exposure and diabetes risk in American older adults: A national secondary data-based cohort study.

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  • Maayan Yitshak Sade
  • Liuhua Shi
  • Elena Colicino
  • Heresh Amini
  • Joel D. Schwartz
  • Qian Di
  • Robert O. Wright
Type 2 diabetes is a major public health concern. Several studies have found an increased diabetes risk associated with long-term air pollution exposure. However, most current studies are limited in their generalizability, exposure assessment, or the ability to differentiate incidence and prevalence cases. We assessed the association between air pollution and first documented diabetes occurrence in a national U.S. cohort of older adults to estimate diabetes risk. We included all Medicare enrollees 65 years and older in the fee-for-service program, part A and part B, in the contiguous United States (2000–2016). Participants were followed annually until the first recorded diabetes diagnosis, end of enrollment, or death (264, 869, 458 person-years). We obtained annual estimates of fine particulate matter (PM2.5), nitrogen dioxide (NO2), and warm-months ozone (O3) exposures from highly spatiotemporally resolved prediction models. We assessed the simultaneous effects of the pollutants on diabetes risk using survival analyses. We repeated the models in cohorts restricted to ZIP codes with air pollution levels not exceeding the national ambient air quality standards (NAAQS) during the study period. We identified 10, 024, 879 diabetes cases of 41, 780, 637 people (3.8% of person-years). The hazard ratio (HR) for first diabetes occurrence was 1.074 (95% CI 1.058; 1.089) for 5 μg/m3 increase in PM2.5, 1.055 (95% CI 1.050; 1.060) for 5 ppb increase in NO2, and 0.999 (95% CI 0.993; 1.004) for 5 ppb increase in O3. Both for NO2 and PM2.5 there was evidence of non-linear exposure-response curves with stronger associations at lower levels (NO2 ≤ 36 ppb, PM2.5 ≤ 8.2 μg/m3). Furthermore, associations remained in the restricted low-level cohorts. The O3-diabetes exposure-response relationship differed greatly between models and require further investigation. In conclusion, exposures to PM2.5 and NO2 are associated with increased diabetes risk, even when restricting the exposure to levels below the NAAQS set by the U.S. EPA.
OriginalsprogEngelsk
Artikelnummer121056
TidsskriftEnvironmental Pollution
Vol/bind320
Antal sider7
ISSN0269-7491
DOI
StatusUdgivet - 2023

Bibliografisk note

Funding Information:
Medicare is the largest health insurance provider in the U.S., covering over 95% of the population over 65 years of age. It is an open cohort that enrolls new members every year and contains a representative sample of older adult population in the U.S. We included all Medicare enrollees who were 65 years and older in the fee-for-service (FFS) program, part A and part B, in the contiguous U.S. between the years 2000–2016. Medicare part A provides inpatient (i.e., hospital) coverage and Medicare part B provides outpatient coverage. Most beneficiaries receive these services through the FFS program offered through the federal government. We limited the data to person-years included in these programs because the algorithm used to identify chronic conditions utilizes claims covered by these three programs. We entered participants into the cohort on January 1 after they became Medicare participants and followed participants for each calendar year within the observation period until the first recorded diabetes diagnosis, end of enrollment in either of the mentioned Medicare programs, or death – whichever came first. Medicare coverage is renewed annually and annual enrollment in these three programs is documented for each participant, allowing us to identify individuals who are no longer enrolled. To avoid gaps in follow-up, once enrollment in the FFS, Medicare part A or B programs was terminated, those participants were no longer included in the cohort even if they renewed their enrollment in later years within the observation period.This study was approved by the Center for Medicare and Medicade services, 2015 (CMS) under the data use agreement (#RSCH-2020-55,733), the Institutional Review Board of Emory University (#STUDY00000316), and the Institutional Review Board of Mount Sinai (STUDY 20–01344), and a waiver of informed consent was granted. The Medicare dataset was stored and analyzed in the Rollins High-Performance Computing (HPC) Cluster at Emory University, in compliance with Health Insurance Portability and Accountability Act (HIPAA).The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Maayan Yitshak Sade, Liuhua Shi, Robert Wright, Elena Colicino, Joel Schwartz reports financial support was provided by National Institute of Environmental Health Sciences. Liuhua Shi reports financial support was provided by the national institute of aging. Joel Schwartz reports financial support was provided by United States Environmental Protection Agency. Heresh Amini reports financial support was provided by Novo Nordisk Foundation Challenge Programme.This study was supported by the HERCULES Center (P30 ES019776), the Mount Sinai transdisciplinary center on early environmental exposures (P30 ES023515 and P30 AG021342), the National Institute on Aging (NIA/NIH R01 AG074357), the National Institute of Environmental Health Sciences (R21 ES032606, R01 ES032242, 5U2CES026555-03, and R01 ES013744, P30 ES000002, R01 ES032418), and the United States Environmental Protection Agency (US EPA) (RD-83587201). Its contents are solely the responsibility of the grantee and do not necessarily represent the official views of the US EPA. Furthermore, the US EPA does not endorse the purchase of any commercial products or services mentioned in the publication. Finally, H.A. is supported by Novo Nordisk Foundation Challenge Programme: Harnessing the Power of Big Data to Address the Societal Challenge of Aging (NNF17OC0027812).

Funding Information:
This study was supported by the HERCULES Center ( P30 ES019776 ), the Mount Sinai transdisciplinary center on early environmental exposures ( P30 ES023515 and P30 AG021342 ), the National Institute on Aging ( NIA/NIH R01 AG074357 ), the National Institute of Environmental Health Sciences (R21 ES032606, R01 ES032242, 5U2CES026555-03, and R01 ES013744, P30 ES000002, R01 ES032418), and the United States Environmental Protection Agency (US EPA) ( RD-83587201 ). Its contents are solely the responsibility of the grantee and do not necessarily represent the official views of the US EPA. Furthermore, the US EPA does not endorse the purchase of any commercial products or services mentioned in the publication. Finally, H.A. is supported by Novo Nordisk Foundation Challenge Programme: Harnessing the Power of Big Data to Address the Societal Challenge of Aging ( NNF17OC0027812 ).

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