The association of long-term exposure to PM2.5 on all-cause mortality in the Nurses’ Health Study and the impact of measurement-error correction

Autor: Francine Laden, Donna Spiegelman, Xiaomei Liao, Robin C. Puett, Jaime E. Hart, Marianthi-Anna Kioumourtzoglou, Biling Hong, Helen Suh, Jeff D. Yanosky
Rok vydání: 2015
Předmět:
Adult
Health
Toxicology and Mutagenesis
Air pollution
Nurses
PM2.5
010501 environmental sciences
complex mixtures
01 natural sciences
03 medical and health sciences
Measurement error
0302 clinical medicine
Environmental health
Statistics
Humans
Medicine
Prospective Studies
030212 general & internal medicine
Particle Size
Mortality
General Environmental Science
0105 earth and related environmental sciences
Exposure assessment
Observational error
Ambient air pollution
Proportional hazards model
business.industry
Research
Incidence
Hazard ratio
Confounding
Public Health
Environmental and Occupational Health
Environmental Exposure
Environmental exposure
Particulates
United States
Confidence interval
Term (time)
3. Good health
13. Climate action
General Earth and Planetary Sciences
Female
Particulate Matter
Nurses' Health Study
business
All cause mortality
Environmental Monitoring
Zdroj: Environmental Health
ISSN: 1476-069X
DOI: 10.1186/s12940-015-0027-6
Popis: Background Long-term exposure to particulate matter less than 2.5 μm in diameter (PM2.5) has been consistently associated with risk of all-cause mortality. The methods used to assess exposure, such as area averages, nearest monitor values, land use regressions, and spatio-temporal models in these studies are subject to measurement error. However, to date, no study has attempted to incorporate adjustment for measurement error into a long-term study of the effects of air pollution on mortality. Methods We followed 108,767 members of the Nurses’ Health Study (NHS) 2000–2006 and identified all deaths. Biennial mailed questionnaires provided a detailed residential address history and updated information on potential confounders. Time-varying average PM2.5 in the previous 12-months was assigned based on residential address and was predicted from either spatio-temporal prediction models or as concentrations measured at the nearest USEPA monitor. Information on the relationships of personal exposure to PM2.5 of ambient origin with spatio-temporal predicted and nearest monitor PM2.5 was available from five previous validation studies. Time-varying Cox proportional hazards models were used to estimate hazard ratios (HRs) and 95 percent confidence intervals (95%CI) for each 10 μg/m3 increase in PM2.5. Risk-set regression calibration was used to adjust estimates for measurement error. Results Increasing exposure to PM2.5 was associated with an increased risk of mortality, and results were similar regardless of the method chosen for exposure assessment. Specifically, the multivariable adjusted HRs for each 10 μg/m3 increase in 12-month average PM2.5 from spatio-temporal prediction models were 1.13 (95%CI:1.05, 1.22) and 1.12 (95%CI:1.05, 1.21) for concentrations at the nearest EPA monitoring location. Adjustment for measurement error increased the magnitude of the HRs 4-10% and led to wider CIs (HR = 1.18; 95%CI: 1.02, 1.36 for each 10 μg/m3 increase in PM2.5 from the spatio-temporal models and HR = 1.22; 95%CI: 1.02, 1.45 from the nearest monitor estimates). Conclusions These findings support the large body of literature on the adverse effects of PM2.5, and suggest that adjustment for measurement error be considered in future studies where possible.
Databáze: OpenAIRE
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