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- Title
Long-Term Exposure to Ambient Fine Particulate Matter and Renal Function in Older Men: The Veterans Administration Normative Aging Study.
- Authors
Mehta, Amar J.; Zanobetti, Antonella; Bind, Marie-Abele C.; Kloog, Itai; Koutrakis, Petros; Sparrow, David; Vokonas, Pantel S.; Schwartz, Joel D.
- Abstract
BACKGROUND: It is unknown if ambient fine particulate matter (PM2.5) is associated with lower renal function, a cardiovascular risk factor. OBJECTIVE: We investigated whether long-term PM2.5 exposure was associated with estimated glomerular filtration rate (eGFR) in a cohort of older men living in the Boston Metropolitan area. METHODS: This longitudinal analysis included 669 participants from the Veterans Administration Normative Aging Study with up to four visits between 2000 and 2011 (n = 1,715 visits). Serum creatinine was measured at each visit, and eGFR was calculated according to the Chronic Kidney Disease Epidemiology Collaboration equation. One-year exposure to PM2.5 prior to each visit was assessed using a validated spatiotemporal model that utilized satellite remote-sensing aerosol optical depth data. eGFR was modeled in a time-varying linear mixed-effects regression model as a continuous function of 1-year PM2.5, adjusting for important covariates. RESULTS: One-year PM2.5 exposure was associated with lower eGFRs; a 2.1-µg/m³ interquartile range higher 1-year PM2.5 was associated with a 1.87 mL/min/1.73 m² lower eGFR [95% confidence interval (CI): -2.99, -0.76]. A 2.1 µg/m³-higher 1-year PM2.5 was also associated with an additional annual decrease in eGFR of 0.60 mL/min/1.73 m² per year (95% CI: -0.79, -0.40). CONCLUSIONS: In this longitudinal sample of older men, the findings supported the hypothesis that long-term PM2.5 exposure negatively affects renal function and increases renal function decline.
- Subjects
MASSACHUSETTS; PARTICULATE matter; PHYSIOLOGY; KIDNEY disease risk factors; CARDIOVASCULAR diseases risk factors; CONFIDENCE intervals; CREATININE; GLOMERULAR filtration rate; LONGITUDINAL method; REGRESSION analysis; RESEARCH funding; ENVIRONMENTAL exposure; REPEATED measures design; DATA analysis software; OLD age
- Publication
Environmental Health Perspectives, 2016, Vol 124, Issue 9, p1353
- ISSN
0091-6765
- Publication type
Article
- DOI
10.1289/ehp.1510269