B. Rey deCastro1, Alison S. Geyh2, Andres Houseman3, Louise Ryan4, John D. Spengler5
1Westat, Rockville, MD.
2Department of Environmental Health Sciences, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD.
3Department of Work Environment, University of Massachusetts Lowell, Lowell, MA.
4CSIRO Mathematical and Information Sciences, New South Wales, Australia.
5Department of Environmental Health, Harvard School of Public Health, Boston, MA.
Collection of time-location data is a common feature of personal exposure studies and is intended to provide a basis for time-weighted exposure averaging. Particular difficulties posed by the outcome -- multiple non-ordered microenvironments -- have precluded routine statistical analysis, but such multinomial outcomes may be modeled within a regression framework using the generalized logit model (or discrete choice model). Conveniently, this model predicts the proportion of subjects in each microenvironment at each time interval, which may be construed most usefully as exposure weights in a formulation of total exposure. This presentation demonstrates application of the generalized logit model to data from a study of schoolchildren (N = 95, 7-11 years old) in southern California who reported their time-location at 30-minute intervals in diaries for 4 days per month for 12 months (June 1995–May 1996; N = 171,000). A generalized logit model of the proportion of subjects in each of five microenvironment -- indoor-home, indoor-school, indoor-other, commuting, outdoors -- shows that while subjects spent substantial time indoor-home, there was substantial variation for other microenvironments at all temporal scales. Consistent with a daily academic schedule, indoor-school time predominates at the 30-minute timescale. Yet, at the day and month timescales most variation is in indoor-other. This suggests that important longer-term exposures may be missed because non-home and non-school indoor microenvironments are not often monitored. The model also found that autocorrelation of microenvironment location was most positively correlated with the previous 30-minute interval and tapered through the preceding 3 hours.
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Microenvironment Exposure Weights Can Be Obtained from a Straightforward Statistical Model of Time-Location Data
1. Introduction
The Model
Results
Conclusions
Microenvironment Exposure Weights Can Be Obtained from a
Straightforward Model of Time-Location Data
B. Rey de Castro, Sc.D.
Westat
Rockville, Maryland USA
October 27, 2009
reyDecastro@westat.com Exposure Weights & Time-Location @ NEPHC 2009
2. Introduction
The Model
Results
Conclusions
Outline
1 Introduction
Learning Objectives
Motivation
Time-Weighted Average Exposure
Generalized Logit Model
2 The Model
3 Results
4 Conclusions
reyDecastro@westat.com Exposure Weights & Time-Location @ NEPHC 2009
3. Introduction Learning Objectives
The Model Motivation
Results Time-Weighted Average Exposure
Conclusions Generalized Logit Model
Outline
1 Introduction
Learning Objectives
Motivation
Time-Weighted Average Exposure
Generalized Logit Model
2 The Model
3 Results
4 Conclusions
reyDecastro@westat.com Exposure Weights & Time-Location @ NEPHC 2009
4. Introduction Learning Objectives
The Model Motivation
Results Time-Weighted Average Exposure
Conclusions Generalized Logit Model
Learning Objectives
1 Describe the benefits to total exposure assessment of
generalized logit models for obtaining microenvironment
exposure weights from time-location data
2 Introduce the generalized logit model within a context of
a familiar linear regression framework
3 Demonstrate how the generalized logit model can yield
exposure weights from time-location data
reyDecastro@westat.com Exposure Weights & Time-Location @ NEPHC 2009
5. Introduction Learning Objectives
The Model Motivation
Results Time-Weighted Average Exposure
Conclusions Generalized Logit Model
Motivation
Indirect exposure assessment
reyDecastro@westat.com Exposure Weights & Time-Location @ NEPHC 2009
6. Introduction Learning Objectives
The Model Motivation
Results Time-Weighted Average Exposure
Conclusions Generalized Logit Model
Motivation
Indirect exposure assessment
Pollutant monitored in each microenvironment
reyDecastro@westat.com Exposure Weights & Time-Location @ NEPHC 2009
7. Introduction Learning Objectives
The Model Motivation
Results Time-Weighted Average Exposure
Conclusions Generalized Logit Model
Motivation
Indirect exposure assessment
Pollutant monitored in each microenvironment
Amount of time spent in each microenvironment
reyDecastro@westat.com Exposure Weights & Time-Location @ NEPHC 2009
8. Introduction Learning Objectives
The Model Motivation
Results Time-Weighted Average Exposure
Conclusions Generalized Logit Model
Motivation
Indirect exposure assessment
Pollutant monitored in each microenvironment
Amount of time spent in each microenvironment
Structured diaries
reyDecastro@westat.com Exposure Weights & Time-Location @ NEPHC 2009
9. Introduction Learning Objectives
The Model Motivation
Results Time-Weighted Average Exposure
Conclusions Generalized Logit Model
Time-Weighted Average Exposure
t th time interval
j th microenvironment
T M
Exposuretwa = exposure weighttj × concentrationtj
t j
time
exposure weighttj = time tj
total
reyDecastro@westat.com Exposure Weights & Time-Location @ NEPHC 2009
10. Introduction Learning Objectives
The Model Motivation
Results Time-Weighted Average Exposure
Conclusions Generalized Logit Model
Time-Weighted Average Exposure
When subjects each contribute the same amount of
person-time at each observational interval, the proportion of
time spent in a microenvironment is equal to proportion of
subjects in a microenvironment
timetj
exposure weighttj = timetotal
subjectstj
=
subjectstotal
= ptj
0 ≤ ptj ≤ 1
reyDecastro@westat.com Exposure Weights & Time-Location @ NEPHC 2009
11. Introduction Learning Objectives
The Model Motivation
Results Time-Weighted Average Exposure
Conclusions Generalized Logit Model
Generalized Logit Model
Outcome
“Which microenvironment are you in and when?”
Unordered categories
Binary logistic regression
Special case (2 categories)
Also known as
Discrete choice model
Multinomial model
reyDecastro@westat.com Exposure Weights & Time-Location @ NEPHC 2009
12. Introduction Learning Objectives
The Model Motivation
Results Time-Weighted Average Exposure
Conclusions Generalized Logit Model
Generalized Logit Model
Regression framework
Temporal predictors provide exposure weights
Subject-specific predictors
P
Pr [Yt = j]
log = β0j + βpj Xpt , j = 1, 2, 3, . . . , M
Pr [Yt = 1] p=1
reyDecastro@westat.com Exposure Weights & Time-Location @ NEPHC 2009
13. Introduction Learning Objectives
The Model Motivation
Results Time-Weighted Average Exposure
Conclusions Generalized Logit Model
Generalized Logit Model
Predicts probability of being in jth microenvironment at time t
1
Pr [Yt = 1] = P
, (ref.j = 1)
1+ p=1 exp(β0j + β1j X1t + . . . + βpj Xpt )
exp(β0j + β1j X1t + . . . + βpj Xpt )
Pr [Yt = j] = P
, (j > 1)
1+ p=1 exp(β0j + β1j X1t + . . . + βpj Xpt )
reyDecastro@westat.com Exposure Weights & Time-Location @ NEPHC 2009
14. Introduction Learning Objectives
The Model Motivation
Results Time-Weighted Average Exposure
Conclusions Generalized Logit Model
Time-Weighted Average Exposure
Predicted probabilities are time-location exposure weights
timetj
exposure weighttj = timetotal
subjectstj
=
subjectstotal
= ptj
exp(β0 j+β1j X1t +...+βpj Xpt )
= 1+ P , (j > 1)
p=1 exp(β0j +β1j X1t +...+βpj Xpt )
reyDecastro@westat.com Exposure Weights & Time-Location @ NEPHC 2009
15. Introduction
The Model
Results
Conclusions
Outline
1 Introduction
Learning Objectives
Motivation
Time-Weighted Average Exposure
Generalized Logit Model
2 The Model
3 Results
4 Conclusions
reyDecastro@westat.com Exposure Weights & Time-Location @ NEPHC 2009
16. Introduction
The Model
Results
Conclusions
Outcome: Microenvironments
Harvard Southern California Exposure Study
Indoor-home
Indoor-school
Indoor-other
Commuting
Outdoors
reyDecastro@westat.com Exposure Weights & Time-Location @ NEPHC 2009
17. Introduction
The Model
Results
Conclusions
Subjects
95 children
7- to 11-years-old
Sex
Age Male Female
7 years 8 9
8 8 12
9 6 9
10 11 13
11 8 11
reyDecastro@westat.com Exposure Weights & Time-Location @ NEPHC 2009
18. Introduction
The Model
Results
Conclusions
Time
12 months
June 1995 - May 1996
5 days per month
Thursday - Monday
30 thirty-minute intervals per day
600 to 2030
reyDecastro@westat.com Exposure Weights & Time-Location @ NEPHC 2009
19. Introduction
The Model
Results
Conclusions
Data
N = 171,000
1,800 longitudinal observations per subject
Missing observations
Multiple imputation
reyDecastro@westat.com Exposure Weights & Time-Location @ NEPHC 2009
20. Introduction
The Model
Results
Conclusions
Outline
1 Introduction
Learning Objectives
Motivation
Time-Weighted Average Exposure
Generalized Logit Model
2 The Model
3 Results
4 Conclusions
reyDecastro@westat.com Exposure Weights & Time-Location @ NEPHC 2009
21. Introduction
The Model
Results
Conclusions
Generalized Logit Model
indoor home
indoor school time of day
sex
day of week age
Pr indoor other = +
month nonwhite
commuting
lags 1-6 televisions
outdoor
reyDecastro@westat.com Exposure Weights & Time-Location @ NEPHC 2009
26. Introduction
The Model
Results
Conclusions
Parameters: Treemap Visualization
reyDecastro@westat.com Exposure Weights & Time-Location @ NEPHC 2009
27. Introduction
The Model
Results
Conclusions
Autocorrelation
Maximum at previous 30-minute interval
Tapers through previous 3 hours
reyDecastro@westat.com Exposure Weights & Time-Location @ NEPHC 2009
28. Introduction
The Model
Results
Conclusions
Subject-specific Predictors
Homes ≥ 5 televisions
21 percent less time outdoors
Nonwhites
21 percent less time indoor-school
18 percent less time commuting
reyDecastro@westat.com Exposure Weights & Time-Location @ NEPHC 2009
29. Introduction
The Model
Results
Conclusions
Outline
1 Introduction
Learning Objectives
Motivation
Time-Weighted Average Exposure
Generalized Logit Model
2 The Model
3 Results
4 Conclusions
reyDecastro@westat.com Exposure Weights & Time-Location @ NEPHC 2009
30. Introduction
The Model
Results
Conclusions
Conclusions
1 Most time spent indoor-home
reyDecastro@westat.com Exposure Weights & Time-Location @ NEPHC 2009
31. Introduction
The Model
Results
Conclusions
Conclusions
1 Most time spent indoor-home
2 Yet, there was substantial variation in time-location that
differentiated exposure
reyDecastro@westat.com Exposure Weights & Time-Location @ NEPHC 2009
32. Introduction
The Model
Results
Conclusions
Conclusions
1 Most time spent indoor-home
2 Yet, there was substantial variation in time-location that
differentiated exposure
3 Influence of school schedule was clearly evident
reyDecastro@westat.com Exposure Weights & Time-Location @ NEPHC 2009
33. Introduction
The Model
Results
Conclusions
Conclusions
1 Most time spent indoor-home
2 Yet, there was substantial variation in time-location that
differentiated exposure
3 Influence of school schedule was clearly evident
4 Most time exchanged between indoor-home,
indoor-school, and outdoors
reyDecastro@westat.com Exposure Weights & Time-Location @ NEPHC 2009
34. Introduction
The Model
Results
Conclusions
Conclusions
1 Most time spent indoor-home
2 Yet, there was substantial variation in time-location that
differentiated exposure
3 Influence of school schedule was clearly evident
4 Most time exchanged between indoor-home,
indoor-school, and outdoors
5 Temporal factors strongest predictor of time-location
reyDecastro@westat.com Exposure Weights & Time-Location @ NEPHC 2009
35. Introduction
The Model
Results
Conclusions
Conclusions
1 Most time spent indoor-home
2 Yet, there was substantial variation in time-location that
differentiated exposure
3 Influence of school schedule was clearly evident
4 Most time exchanged between indoor-home,
indoor-school, and outdoors
5 Temporal factors strongest predictor of time-location
6 To a lesser degree, television viewing & race predicted
time-location
reyDecastro@westat.com Exposure Weights & Time-Location @ NEPHC 2009
36. Introduction
The Model
Results
Conclusions
Conclusions
1 Most time spent indoor-home
2 Yet, there was substantial variation in time-location that
differentiated exposure
3 Influence of school schedule was clearly evident
4 Most time exchanged between indoor-home,
indoor-school, and outdoors
5 Temporal factors strongest predictor of time-location
6 To a lesser degree, television viewing & race predicted
time-location
7 Autocorrelation was statistically significant
reyDecastro@westat.com Exposure Weights & Time-Location @ NEPHC 2009
37. Introduction
The Model
Results
Conclusions
Learning Questions
1 Why is the generalized logit model useful and how is it
related to other regression models?
2 How do you estimate total time-weighted exposure from
the generalized logit model’s predicted proportion of
subjects in each microenvironment at each time interval?
reyDecastro@westat.com Exposure Weights & Time-Location @ NEPHC 2009
38. Introduction
The Model
Results
Conclusions
Next Steps
Microenvironment exposure weights
Microenvironment pollutant concentrations
Estimate total exposures
Another manuscript
Longitudinal effect of temperature & precipitation?
reyDecastro@westat.com Exposure Weights & Time-Location @ NEPHC 2009
39. Introduction
The Model
Results
Conclusions
Acknowledgements
Alison S. Geyh Louise Ryan
Andres Houseman John D. Spengler
Battelle-EPA grant
On SlideShare: http://cli.gs/LAO3diary
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240-453-2947
reyDecastro@westat.com Exposure Weights & Time-Location @ NEPHC 2009