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
| dc.contributor.author | Hart, Jaime E | |
| dc.contributor.author | Liao, Xiaomei | |
| dc.contributor.author | Hong, Biling | |
| dc.contributor.author | Puett, Robin C | |
| dc.contributor.author | Yanosky, Jeff D | |
| dc.contributor.author | Suh, Helen | |
| dc.contributor.author | Kioumourtzoglou, Marianthi-Anna | |
| dc.contributor.author | Spiegelman, Donna | |
| dc.contributor.author | Laden, Francine | |
| dc.date.accessioned | 2021-08-24T15:33:33Z | |
| dc.date.available | 2021-08-24T15:33:33Z | |
| dc.date.issued | 2015-05-01 | |
| dc.description.abstract | 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. 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. 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). 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. | en_US |
| dc.description.uri | https://doi.org/10.1186/s12940-015-0027-6 | |
| dc.identifier | https://doi.org/10.13016/fbvx-osjb | |
| dc.identifier.citation | Hart, J.E., Liao, X., Hong, B. et al. 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. Environ Health 14, 38 (2015). | en_US |
| dc.identifier.uri | http://hdl.handle.net/1903/27644 | |
| dc.language.iso | en_US | en_US |
| dc.publisher | Springer Nature | en_US |
| dc.relation.isAvailableAt | School of Public Health | |
| dc.relation.isAvailableAt | Maryland Institute of Applied Environmental Health | |
| dc.relation.isAvailableAt | Digital Repository at the University of Maryland | |
| dc.relation.isAvailableAt | University of Maryland (College Park, Md) | |
| dc.subject | PM2.5 | en_US |
| dc.subject | Measurement error | en_US |
| dc.subject | Mortality | en_US |
| dc.subject | Air pollution | en_US |
| dc.title | 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 | en_US |
| dc.type | Article | en_US |