TY - JOUR
T1 - Air pollution and mortality
T2 - Estimating regional and national dose-response relationships
AU - Dominici, F.
AU - Daniels, M.
AU - Zeger, S. L.
AU - Samet, J. M.
N1 - Funding Information:
FrancesDocminiciaisAsPsroisr,fDtearsmentestpontoBfsitocast,isti Bloomberg School of Public Health, The Johns Hopkins Un, Bivaelrtsi-ity more,MD21205(E-am:fdiomlinic@jhsph.e)Michd. aulDenielsaisAssistant Profser,sDepartmento ofStatisti,cIosaSwtaUtresnity,AivsmIA,e(E-mail:e mdaniels@iastate.eu)Scod.tt L. Zeger is Professor and Chairman, Dpartmente of Biostistics,taJnos Hohpkins Unive, Baltimorsre,itMDy21205 (E-mail: sgzeesprh.ed@u)J.naothjhMa.Snais PmrofesersandtoCahin,rDmeapart-mentofEpidemiology,JohnsHopkinsUniversity,Balimore,t MD21205(E-mail: jsamet@jhsph.e)Thd.e ruerscdeehrsbedaicin this article ws partiaally supported by a contract and grntafrom the Health EfefIncitustet(HEst I)an, organizantjoiintoly funded by the EvironnmetalnProtection Agency (EAP; R824835) and automotivmanuefcarers.tuThe contents of this article do not nescseraeertciehlvtiyweandspolicies of HEI, EAoPr mot, or vehicle or engine mnufaarcretsFuu.dinnfor FgcrsaecDnmaociwinpraiiosdbvy ed the HEIs WaerlA.tRosenblith Nw IneversAwtiFugandinragdoftMicho. al e Daniels wapsireddoby NvtionalaScience Foundation grant DMS9816630. Funding was also provided by Johns Hopkins Center in Urban Evironnmen-tal Health grant 5P30ES03819-12. The authors thank John Bhmannacof the EPA for kindly providing us with the data on particulate matter composition, GionnivParmigaiani for comments and suggesionts on the statistilcmoadels, and IvaCounrsac for assistance with data base dvepemelt. no
Copyright:
Copyright 2008 Elsevier B.V., All rights reserved.
PY - 2002/3
Y1 - 2002/3
N2 - We analyzed a national data base of air pollution and mortality for the 88 largest U.S. cities for the period 1987-1994, to estimate relative rates of mortality associated with airborne particulate matter smaller than 10 microns (PM10) and the form of the relationship between PM10 concentration and mortality. To estimate city-specific relative rates of mortality associated with PM10, we built log-linear models that included nonparametric adjustments for weather variables and longer term trends. To estimate PM10 mortality dose-response curves, we modeled the logarithm of the expected value of daily mortality as a function of PM10 using natural cubic splines with unknown numbers and locations of knots. We also developed spatial models to investigate the heterogeneity of relative mortality rates and of the shapes of PM10 mortality dose-response curves across cities and geographical regions. To determine whether variability in effect estimates can be explained by city-specific factors, we explored the dependence of relative mortality rates on mean pollution levels, demographic variables, reliability of the pollution data, and specific constituents of particulate matter. We implemented estimation with simulation-based methods, including data augmentation to impute the missing data of the city-specific covariates and the reversible jump Markov chain Monte Carlo (RJMCMC) to sample from the posterior distribution of the parameters in the hierarchical spline model, We found that previous-day PM10 concentrations were positively associated with total mortality in most the locations, with a .5% increment for a 10 μg/m3 increase in PM10. The effect was strongest in the Northeast region, where the increase in the death rate was twice as high as the average for the other cities. Overall, we found that the pooled concentration-response relationship for the nation was linear.
AB - We analyzed a national data base of air pollution and mortality for the 88 largest U.S. cities for the period 1987-1994, to estimate relative rates of mortality associated with airborne particulate matter smaller than 10 microns (PM10) and the form of the relationship between PM10 concentration and mortality. To estimate city-specific relative rates of mortality associated with PM10, we built log-linear models that included nonparametric adjustments for weather variables and longer term trends. To estimate PM10 mortality dose-response curves, we modeled the logarithm of the expected value of daily mortality as a function of PM10 using natural cubic splines with unknown numbers and locations of knots. We also developed spatial models to investigate the heterogeneity of relative mortality rates and of the shapes of PM10 mortality dose-response curves across cities and geographical regions. To determine whether variability in effect estimates can be explained by city-specific factors, we explored the dependence of relative mortality rates on mean pollution levels, demographic variables, reliability of the pollution data, and specific constituents of particulate matter. We implemented estimation with simulation-based methods, including data augmentation to impute the missing data of the city-specific covariates and the reversible jump Markov chain Monte Carlo (RJMCMC) to sample from the posterior distribution of the parameters in the hierarchical spline model, We found that previous-day PM10 concentrations were positively associated with total mortality in most the locations, with a .5% increment for a 10 μg/m3 increase in PM10. The effect was strongest in the Northeast region, where the increase in the death rate was twice as high as the average for the other cities. Overall, we found that the pooled concentration-response relationship for the nation was linear.
KW - Air pollution
KW - Data augmentation
KW - Generalized additive model
KW - Hierarchical model
KW - Natural cubic spline
KW - Particulate matter
KW - Relative rate
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U2 - 10.1198/016214502753479266
DO - 10.1198/016214502753479266
M3 - Article
AN - SCOPUS:0036489049
SN - 0162-1459
VL - 97
SP - 100
EP - 111
JO - Journal of the American Statistical Association
JF - Journal of the American Statistical Association
IS - 457
ER -