Post on 21-Apr-2021
transcript
Enhancing Exposure AssessmentUsing Exposure Predictions in Health Models
The Use of Spatial Exposure Predictions in HealthEffects Models: An Application to PM
Epidemiology
Chris Paciorek and Brent CoullDepartment of Biostatistics
Harvard School of Public Healthwww.biostat.harvard.edu/˜paciorek
October 14, 2008
Chris Paciorek and Brent Coull Exposure Predictions and Health 1
Enhancing Exposure AssessmentUsing Exposure Predictions in Health Models
Eastern Massachusetts Daily Black Carbon
!(
!(
!(
!(
!(
!(
!(
!(
!(
!(
!(
!(
!(
!(
!(
!(
!(
!(
!(
!(
!(
!(
!(
!(
!(
!(
!(
!(
!(
!(
!(!(
!(
!(
!(
!(!(
!(
!(
!(
!(
!(
!(
!(
!(
!(
!(
!(
!(
!(!(
!(
!(
!(
!(
!(
!(
!(
!(
!(
!(
!(
!(
!(
!(
!(
!(
!(
!(
!(
!(
!(
!(
!(
!(90
93
95
495
MIDDLESEX
PLYMOUTH
NORFOLK
ESSEX
BRISTOL
SUFFOLK
WORCESTER
95
3
495
93
90
Boston monitoring sites!( BC − Outdoor & indoor: 30 monitors (APAHRV)
!( BC − Indoor: 15 monitors (APAHRV)
BC − Ambient: 14 monitorsEC − Outdoor: 23 monitors (EPA)
..... ... ...... ...... ... .......... ...... ...... ......... .. ... ...... ... .......... ... ... ...... ... ... ...... ............ ... ... ......... ... ... ...... ... ...... ... ...... ... ... ...... ... ...... ... ..... ... ...... ... ...... ... .... ... ... ...... ... ... ..... ... ...... ..... ... . ........... ... ...... ... ... ...... ... ... ...... ......... ... ... ...... ... ...... ... ...... ... ............ ... ...... ... ... ..... ............ ... ... ......... ... ... ...... ... ...... ... ...... ... ...... ... ... ...... ... ...... ...... ... ...... ... ...... ... ... .... ... ... ...... ... ...... ...... ... . ........... ... ...... ... ... ...... ... ... ...... ......... ... ... ..... ... ...
....... ..................... ...................................................................................................................................................................................................................................................................................................................................................................................
........................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................ .............................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................
.......................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................
.....................................................................................................................................................................................................................................................................................................................................................................................................................................
...............................................................
...............................................................
..............................................................
....................................................
.............................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................
17
15
13
11
9
7
5
3
1
4/1/99 1/1/00 1/1/01 1/1/02 1/1/03 1/1/04 12/9/04
1 : Indoor BC − APAHRV study2 : Outdoor BC − APAHRV study3 : Outdoor EC − EPA4 − 18 : Outdoor BC − NESCAUM study
BC monitors in space (left) and time (right)
Chris Paciorek and Brent Coull Exposure Predictions and Health 2
Enhancing Exposure AssessmentUsing Exposure Predictions in Health Models
Model
Published model (Gryparis et al. JRSSC 2007):
Contains a spatial term, temporal term, and spatial andtemporal covariates
log BCit = Xiβ + Ztα + g(si ) + h(t) + εit
Little space-time interaction except for stratification bysummer/winter
Ongoing work:
Build in space-time smoothing and effects of covariates thatvary in space and timeAdditional data from rotating monitors and from 7-dayintegrated samples
Application
Acute and chronic health studies in eastern Massachusetts:stroke, hypertension, intermediate cardiovascular markers,mortality, birthweight
Chris Paciorek and Brent Coull Exposure Predictions and Health 3
Enhancing Exposure AssessmentUsing Exposure Predictions in Health Models
Nationwide Monthly PM
PM2.5 monitors (top) and predictions: northeast US (left) andgreater Boston (right)
Chris Paciorek and Brent Coull Exposure Predictions and Health 4
Enhancing Exposure AssessmentUsing Exposure Predictions in Health Models
Model
Published model (Yanosky et al. Atm. Env’t 2008, Pacioreket al. Annals Appl Stats in press):
Contains a spatio-temporal terms (one spatial term for eachmonth) plus spatio-temporal covariates
Combination of land-use regression and spatial smoothing
Ongoing work:
Assessment of use of remotely-sensed AOD to improve spatialcoverage (see poster)Consideration of new land use covariates and improvedspace-time characterization
Application
Chronic health effects in the Nurses’ Health Study
Chris Paciorek and Brent Coull Exposure Predictions and Health 5
Enhancing Exposure AssessmentUsing Exposure Predictions in Health Models
Prediction Uncertainty as Measurement Error
Spatial smoothing exposure models (kriging, splines, additivemodeling) produce a form of regression calibration
Result is Berkson-type error in health models
Implication of limited bias in health models
But, 1.) exposure away from home and 2.) ambientconcentrations vs. personal exposure probably adds classicalerror
Chris Paciorek and Brent Coull Exposure Predictions and Health 6
Enhancing Exposure AssessmentUsing Exposure Predictions in Health Models
Accounting for Prediction Uncertainty
Approaches that do not work:
Directly weighting by prediction uncertaintySimulating exposures based on prediction uncertainty
Approaches with more promise:
Bayesian modelsUsing held-out data to calibrate the predictions
Application
Effect of BC on birthweight in eastern MassachusettsAccounting for uncertainty in large cohort studies in survivalanalysis such as the Nurses’ Health Study is an open challenge.
Chris Paciorek and Brent Coull Exposure Predictions and Health 7
Enhancing Exposure AssessmentUsing Exposure Predictions in Health Models
References
Eastern Massachusetts BC model:
Gryparis, Coull, Schwartz and Suh. 2007. Latent variablesemiparametric regression models for spatio-temporal modelingof mobile source pollution in the greater Boston area. Journalof the Royal Statistical Society Series C 56:183.Maynard, Coull, Gryparis, and Schwartz. 2007. Mortality riskassociated with short-term exposure to traffic particles andsulfates. EHP 5:751.
National PM modeling
Yanosky, Paciorek, Schwartz, Laden, Puett, and Suh. 2008.Spatio-temporal modeling of chronic PM10 exposure for theNurses’ Sealth Study. Atmospheric Environment 42:4047.Paciorek, Yanosky, Puett, Laden, and Suh. 2008. Practicallarge-scale spatio-temporal modeling of particulate matterconcentrations. Annals of Applied Statistics, in press (HarvardBiostatistics Technical Report 76).
Chris Paciorek and Brent Coull Exposure Predictions and Health 8
Enhancing Exposure AssessmentUsing Exposure Predictions in Health Models
National PM modeling (cont’d)
Paciorek and Liu. 2008. Limitations of remotely-sensed aerosolas a proxy for fine marticulate matter. Harvard BiostatisticsTechnical Report 89; submitted.Puett et al. 2008. Chronic particulate exposure, mortality andcardiovascular outcomes in the Nurses’ Health Study.American Journal of Epidemiology in press.
Measurement Error
Gryparis, Paciorek, Zeka, Schwartz, and Coull. 2008.Measurement error caused by spatial misalignment inenvironmental epidemiology. Biostatistics, in press (HarvardBiostatistics Technical Report 87).
Chris Paciorek and Brent Coull Exposure Predictions and Health 9