yan kestens - daily mobility and multiple exposures: collecting and using spatial data in health...

Daily Mobility and Multiple Exposures: Collecting and Using Spatial Data in Health Research

Yan KestensMontreal University, Social and Preventive MedicineMontreal Hospital University Research Center (CRCHUM)

SPHERE Lab .org

MAY 14th 2013

Context• Most health data contains limited spatial data• Yet society increasingly mobile, blurring of spatial and

temporal limits• Increasing interest in lifecycle / cumulative aspect• What methods to add spatial to epidemiology?

Context

• Various methods to collect spatial data that can be used to to feed epidemiological models and estimate multiple exposures

Mobility surveysActivity space questionnaires

Wearable sensors

Time use surveys

Context

Mobility surveys

Allowed to compute activity space exposure to multiple food sources

Estimates of multiple exposures for health survey participants

Association between activity space exposure and BMI

Context

Activity space questionnaires

Surveys regular destinations

VERITAS – Map-based interactive online questionnaire

RECORD Cohort Study, Paris, Adults

BEANZ Study, Auckland, Adolescents & children

ERA-AGE Healthy Aging, Montreal, Paris, Luxembourg

Context

Wearable sensors

Web server

Acquisition server

Outputs /Applications

End users

GISAlgorithms

GSM towerSensors

CAPTURE

PROCESSINGUSAGE

Context

Mobility surveysActivity space questionnaires

Wearable sensors

Time use surveys

What is the ‘spatio-temporal’ correspondence between one week

objective mobility tracking (GPS) and locations reported in a map-

based questionnaire of regular destinations (VERITAS)?

GPS – VERITAS spatial comparison

• Sample of 89 RECORD Cohort Study participants from which we collected:

– VERITAS activity locations

– 7-day continuous GPS monitoring

– GPS-prompted recall survey data: validation of activity locations, trips and transportation modes, nature of activities

VERITAS data

Total Home WorkOther

weekly

Other less than

weeklyAverage 15,3 1,0 1,1 7,2 5,9

Median 14,0 1,0 1,0 7,0 5,0

Total of 1,314 self-reported activity locations for 89 participants

HOME WORKPLACE OTHER DESTINATIONS

WEEKLYLESS THAN WEEKLY

Average number of reported locations

GPS data

Time weighted Within 500 m Within 1000m0

10

20

30

40

50

60

70

80

90

100

Proportion of GPS survey duration with valid GPS data

Perc

enta

ge o

f sur

vey

dura

tion

wit

h G

PS fi

xes

5 Days & 07:07:153 Days & 10:25:25

6 Days & 04:45:20

5 Days & 07:07:15

Extraction of activity places from raw GPS data using kernel-based density algorithm

SPHERELAB GPSARCTOOLBOX

1. How close are GPS data to

VERITAS location?

How close are GPS data to VERITAS locations?

GPS data- GPS valid fix (raw)

- GPS activity location (kernel density algorithm)

- GPS confirmed location (prompted recall survey)

VERITAS locations- Self-reported activity locations identified on an

interactive online map (HOME, WORK, OTHER WEEKLY, LESS THAN WEEKLY)

DISTANCE BETWEEN

AND

HOME WORK OTHER WEEKLY OTHER LESS THAN WEEKLY

0

20

40

60

80

100

120

140

Shortest distance between VERITAS location and a GPS fix

Dist

ance

in m

eter

sHow close are GPS data to VERITAS locations?


0

50

100

150

200

250

300

350

400

450

500

Shortest distance between VERITAS location and a GPS/algorithm detected activity location

Dist

ance

in m

eter



0

200

400

600

800

1000

1200

Median shortest distance between VERITAS location and GPS-prompted recall location

Dist

ance

in m

eter


HOME

SHOPPIN

GW

ORK

TRANSP

ORT

RECREA

TION

SOCIAL

0

20

40

60

80

100

120

140

Shortest distance between GPS activity location and VERITAS location by VER-

ITAS category (median value; n=1,314)

How close are GPS data to VERITAS locations?

2. How much time is spent around

VERITAS-reported locations?

How much time is spent around


t0 t1 t2 t3 t5 t6 t7 t8 t9 t10 t11 t12 t13

5 5 5 5 10 5 5 5

t14 t15 t16

20 5 5

Ellapsed time attributed to second of two consecutive GPS data fixesSum of individual fix durations = total survey duration

1) Calculation of duration from GPS fixes

x x xx

2) Computation of proportion of survey duration spent within…100 m250 m500 m1000 m

…of a VERITAS self-reported location


VERITAS-reported locations?1000

250

500

100

Within 100 m Within 250 m Within 500 m Within 1000m0.00

0.10

0.20

0.30

0.40

0.50

0.60

0.70

0.80

0.90

1.00

Proportion of total survey time spent within range of VERITAS locations



87%

85%

78%



66%

1000

250

500

1000

Participants spent 85% of their time

within 500 m of a VERITAS location

100

3. What is the spatial correspondence

between the two point distributions?

What is the spatial correspondence between the two

point distributions?

Convex hulls

Standard deviation ellipse

VERITAS locations



CONVEX HULLAreaPerimeterForm factor





GPS tracks

GPS activity location

X



Standard Deviation Ellipse



VERITAS Convex Hull

GPS Convex Hull VERITAS 1 STD ELLIPSE

GPS 1STD ELLIPSE0

20

40

60

80

100

120

140

160

180

200

Convex hull and 1 STD ellipse sizeAr

ea in

km

2

30

163

23 23



Overlap Veritas convex hull

Overlap GPS convex hull

Overlap Veritas ellipse Overlap GPS ellipse0.00

0.10

0.20

0.30

0.40

0.50

0.60

0.70

0.80

0.90

1.00

Spatial overlap (Convex hull, Standard devia-tion ellipse)

Prop

ortio

n of

ove

rlap

30

163

4257

95

11

95



95

Unweighted Time weighted Within 500 m Within 1000m0

2

4

6

8

10

12

14

16

18

20

Distance between ellipse geographic centersD

ista

nce

in k

m

2.35 1.43




1. How close are GPS data to VERITAS location?

Quite close!

2. How much time is spent around VERITAS locations?





Quite close!

A lot!

2. How much time is spent around VERITAS locations?




3. What is the spatial correspondence between the two point distributions?


Quite close!

A lot!

All depends!

CONCLUSIONS

VERITAS an efficient tool to collect precise spatial information on regular destinations

GPS provides objective measures of mobility, can prompt recall surveys

Increasing use of embedded GPS sensors, health surveys and remote patient monitoring

CONCLUSIONS

CAPTURE

PROCESSINGUSAGE

CONCLUSIONS

Web server

Acquisition server

Outputs /Applications

End users

GISAlgorithms

GSM towerSensors

Thank you!

SPHERE Lab .org Benoit Thierry from SPHERELAB Julie Méline from RECORD

All the study participants!

ReferencesChaix, B., Kestens, Y., Perchoux, C., Karusisi, N., Merlo, J., & Labadi, K. (2012). An interactive mapping tool to assess individual mobility patterns in neighborhood studies. Am J Prev Med, 43(4), 440-450. doi: 10.1016/j.amepre.2012.06.026Chaix, B., Méline, J., Duncan, S., Merrien, C., Karusisi, N., Perchoux, C., Lewin, A., Labadi, K., Kestens, Y. (2013). GPS tracking in neighborhood and health studies: A step forward for environmental exposure assessment, a step backward for causal inference? Health & Place, 21(0), 46-51. Kestens, Y., Lebel, A., Chaix, B., Clary, C., Daniel, M., Pampalon, R., . . . SV, P. S. (2012). Association between activity space exposure to food establishments and individual risk of overweight. PLoS One, 7(8)Kestens, Y., Lebel, A., Daniel, M., Theriault, M., & Pampalon, R. (2010). Using experienced activity spaces to measure foodscape exposure. Health Place, 16(6), Thierry, B., Chaix, B., & Kestens, Y. (2013). Detecting activity locations from raw GPS data: a novel kernel-based algorithm. Int J Health Geogr, 12(1), 14. doi: 10.1186/1476-072X-12-14Perchoux, C., Chaix, B., Cummins, S., & Kestens, Y. (2013). Conceptualization and measurement of environmental exposure in epidemiology: Accounting for activity space related to daily mobility. Health Place, 21C, 86-93. doi: 10.1016/j.healthplace.2013.01.005

yan kestens - daily mobility and multiple exposures: collecting and using spatial data in health...

Health & Medicine

veritas locationand

raw gps data

gps activitylocation

veritas activity locations

veritas selfreported

limited spatial data

health data

recall survey data