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Measuring exposure to location-based risk factors during daily activities in urban landscapesg y p
Douglas Wiebe, PhDDepartment of Biostatistics & EpidemiologyUniversity of Pennsylvania
Consortium for Education and Social Science ResearchIndiana University
Workshop in MethodsWorkshop in Methods
March 4, 2011
Source: The Broad Street Pump, Safe & Sound, Penguin, 1971 in English MP, Victorian Values -- The Life and Times of Dr. Edwin Lankester, 1990.
S Ti Ad l Ri k S dSpace-Time Adolescent Risk StudySchool of Medicine School of NursingSchool of Nursing School of Arts and SciencesSchool of Social WorkSchool of Engineering & Applied ScienceChildren’s Hospital of PhiladelphiaChildren s Hospital of Philadelphia
Paul Allison PhD, Elijah Anderson PhD*, Charles Branas PhD, Wensheng Guo PhD, Judd Hollander MD, Michael Nance MD, C. William Schwab MD, Therese Richmond PhD RN, C Dana Tomlin PhD Douglas Wiebe PhDC. Dana Tomlin PhD, Douglas Wiebe PhD
University of Pennsylvania*Yale University
Graphic provided by The HELP Network, Chicago
National Institute on Alcohol Abuse and Alcoholism, National Institute of Child Health & Human Development (R01AA014944)
STARS is a “population-based case-control study”S S s a popu at o based case co t o study
Aschengrau & Seage, Essentials of Epidemiology for Public Health 2003, p. 137 (with edits)
Design of cohort study vs case-control studyS
tudi
es
ctor
Present(exposed)
What % got disease
(risk E)(follow forward in time)
Coh
ort S Fac
Absent(not exposed)
What % got disease
(follow forward in time)
(risk E)
Design of cohort study vs case-control study
Case-Control Studies
Disease
Present(cases)
Absent(controls)
(l k b k d
What % had What % had
(look backwardin time)
been exposed been exposed
Design of cohort study vs case-control study
Case-Control StudiesCohort study RR = A/A+B
C/C+D
Disease
Case-control OR = ADstudy BC
Present(cases)
Absent(controls)
Stu
dies
ctor
Present(exposed) A B
Coh
ort S Fac
Absent(not exposed) DC
Proportion of time spent in each of six locations
Klepeis et al. J Expo Analysis & Environ Epi, 2001
These are “activity pattern data”
Radon & falloutRadon is a colorless, odorless, naturally occurring, radioactive noble gas that is formed from the decay of radium.
Radon is a significant contaminant that affects indoor air quality worldwide. Radon gas from natural sources can accumulate in buildings, especially inaccumulate in buildings, especially in confined areas such as the basement and reportedly causes 21,000 lung cancer deaths per year in the US.
Radon is the second most frequent cause of lung cancer, after cigarette smoking, and radon‐induced lung cancer i th ht t b th 6th l di fis thought to be the 6th leading cause of cancer death overall.
Radon can be found in some spring waters and hot springs.
Gatrell & Loytonen, GIS & Health 1998, p.106
RecruitmentRecruitmentCase subjects: HUP and CHOP– Screening by Academic AssociatesScreening by Academic Associates– Interviewing by full-time project staff– Interview takes place in ER, on hospital
ward, home, or research officeward, home, or research office
Control subjects: communityScreening via RDD (random digit dialing)– Screening via RDD (random digit dialing)
– Interviewing by full-time project staff– Interview takes place at home or
research officeresearch office
Time 6:00 am 6:10 6:20 6:30 6:40 6:50 7:00 am
How are you getting around? Here are some examples. Others?
7:00 am 7:10 7:20 7:30 7:40 7:50 8:00 am 8:10 8:20 8:30 8:40 8:50 9:00 am
(1) (2) (3) (4) (5) (6) (7) (0)
What are you doing? Anything else?
(1) (2) (3) (4) (5) (6) (7) (0)
9:10 9:20 9:30 9:40 9:50 10:00 am 10:10 10:20 10:30 10:40 10:50 11:00 am 11:10
(1) (2) (3) (4) (5) (6) (7) (0)
How safe do you feel? On a scale of 1-10, how safe do you feel?
10 FEELING VERY SAFE
1 FEELING VERY UNSAFE
11:10 11:20 11:30 11:40 11:50 12:00 pm 12:10 12:20 12:30 12:40 12:50 1:00 pm 1:10
10 9 8 7 6 5 4 3 2 1
1:20 1:30 1:40 1:50 2:00 pm 2:10 2:20 2:30 2:40 2:50 3:00 pm 3:10 3 20
Are any of these things involved? Anything else?
3:20 3:30 3:40 3:50 4:00 pm 4:10 4:20 4:30 4:40 4:50 5:00 pm 5:10 5:20
(1) (2) (3) (4) (5) (6) (9) (0)
Who are you with? Family, Friends, Girlfriend, Boyfriend, Someone you don’t like, anyone else?
5:20 5:30 5:40 5:50 GO TO NEXT
PAGE
Time-varying exposures and covariatesTime varying exposures and covariates
4
Yes
0
Expo
sed
No
Y
06 12 18 24
Hours preceding shooting
Figure 1. Dichotomous variable
0.8
1
1.2
e le
vel
H
igh
0
0.2
0.4
0.6
6 12 18 24
Expo
sure
Low
Hours preceding shooting
Figure 3. Gravity measure
Hours preceding shooting
Figure 2. Continuous variable
Median
Characteristics of one‐day activity paths of 15‐19 year‐old subjects (n=55)
Min Max Mean (SD) (25%, 75%)Time (hrs) spent outside home during one‐day reporting period 0.0 23.5 7.9 (5.6) 8.3 (3.5, 10.9)
Greatest linear distance from home (mi) 0.0 7.2 1.4 (1.7) 0.9 (0.2, 2.4)
Distance travelled (mi) 0.0 20.6 4.5 (4.7) 3.2 (0.7, 9.1)
Time (hrs) spent outside census tract of residence during one‐day reporting period 0.0 19.8 6.3 (5.5) 7.0 (0.0, 9.4)
P ti f t id th h ti th tProportion of outside‐the‐home time that was spent outside census tract of residence (%) 0.0 99.4 71.0 (36.5) 91.5 (56.9, 96.7)
Number of census tracts intersected by subject's y jone‐day activity path 1 34 8.1 (8.5) 6 (1, 10)
25% and 75% denote the twenty‐fifth and seventy‐fifth percentiles, respectively.
In most instances (87.8%), it was one of four types of locations that constituted the place along a subject’s path that was the farthest point (ie, linear distance) from their home: school, work, places of recreation, and food stores and restaurants.
Basta, Richmond, WiebeSoc Sci Med 2010
Median values of the greatest linear distances Interview days
Monday 18%Tuesday 20%Wednesday 6%
gtraveled from home:
1.1 mi on weekdays vs 0.4 mi on weekends (Mann-Whitney z=1.83, p=0.07)
bj t ’ ti iti ll i l d t i l t
y
Wednesday 6%Thursday 11%Friday 15%Saturday 13%
- subjects’ activities generally involved staying closer to home on weekends
Cumulative distances travelled were generallySaturday 13%Sunday 18%
Cumulative distances travelled were generally shorter on weekends also (medians):
4.2 mi on weekdays vs 1.2 mi on weekends(Mann-Whitney z=1.89, p=0.09)
Basta, Richmond, WiebeSoc Sci Med 2010
Various measures of exposure to alcohol outlets for 15‐19 year‐old subjects (n=55)
Min Max Mean (SD)Median
(25%, 75%)l h l l lAlcohol outlet prevalence in
subject's census tract of residencePer 1000 residents 0.0 46.4 5.1 (8.9) 2.3 (0.8, 4.3)Per road kilometer 0.0 5.2 1.0 (1.0) 0.8 (0.3, 1.1)
Alcohol outlets contacted during one‐day activities
Walked within 18 meters 0 54 3.2 (7.8) 1 (0, 3)
Walked within 200 meters 0 120 12.1 (19.0) 5 (2, 16)
d d h f f h d f f h l l25% and 75% denote the twenty‐fifth and seventy‐fifth percentiles, respectively.
Basta, Richmond, WiebeSoc Sci Med 2010
00
200
s)Spearman’s rho=0.06
p=0.660
150
ed (1
8 m
eter
s0
10ut
lets
con
tact
e0
50Ou
0
0 10 20 30 40 50Outlets per 1000 residents in subject's home census tract
Relation between alcohol outlet prevalence in subjects’ census tracts of residence and alcohol outlets contacted during one‐day activities
100
Experiences in their neighborhoods: 13‐17 controls vs. case subjects*
70
80
90p<0.05
40
50
60
70
Perc
ent
Shot
Control
p<0.05
10
20
30
40 p<0.05
0
10
I've heardgunshots
I've seenpeople using or
selling drugs
I often seedrunk people on
the street
I've seensomeone get
stabbed
I've seensomeone pull a
gun on
I've seensomeone get
shotg g gsomebody
*Partial data; preliminary
KEY POINTSThe notion that exposure levels can vary in meaningful ways over the course of dailyThe notion that exposure levels can vary in meaningful ways over the course of daily activities has been noted in some research fields, but may remain under-appreciated in large-scale studies of neighborhoods and health.
These results illustrate how individuals’ daily activities frequently occur in locations f th i h d i i t ti b d i d lik l lt iaway from their homes, cross administrative boundaries, and likely result in exposure
to environmental exposures at very different levels than at their home.
Measuring exposure should thus be carefully considered in light of the exposure-disease relation under study and the induction period of the exposure of interest.disease relation under study and the induction period of the exposure of interest.
CONCLUSIONIn studies of environmental exposures that are encountered outside the home and that vary in etiologically meaningful ways over the course of daily activitiesthat vary in etiologically meaningful ways over the course of daily activities, classifying subjects as exposed based solely on the prevalence of the exposure in the administrative geographic unit of their residence (e.g. a Census tract or ZIP code) will likely result in exposure misclassification.
Ask, Where do subjects spend time? And how much time do they spend there? Both will be key to better understanding “neighborhood.”do they spend there? Both will be key to better understanding neighborhood.
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