Dataset Information

Positional error and time-activity patterns in near-highway proximity studies: an exposure misclassification analysis.

ABSTRACT:

Background

The growing interest in research on the health effects of near-highway air pollutants requires an assessment of potential sources of error in exposure assignment techniques that rely on residential proximity to roadways.

Methods

We compared the amount of positional error in the geocoding process for three different data sources (parcels, TIGER and StreetMap USA) to a "gold standard" residential geocoding process that used ortho-photos, large multi-building parcel layouts or large multi-unit building floor plans. The potential effect of positional error for each geocoding method was assessed as part of a proximity to highway epidemiological study in the Boston area, using all participants with complete address information (N?=?703). Hourly time-activity data for the most recent workday/weekday and non-workday/weekend were collected to examine time spent in five different micro-environments (inside of home, outside of home, school/work, travel on highway, and other). Analysis included examination of whether time-activity patterns were differentially distributed either by proximity to highway or across demographic groups.

Results

Median positional error was significantly higher in street network geocoding (StreetMap USA?=?23 m; TIGER?=?22 m) than parcel geocoding (8 m). When restricted to multi-building parcels and large multi-unit building parcels, all three geocoding methods had substantial positional error (parcels?=?24 m; StreetMap USA?=?28 m; TIGER?=?37 m). Street network geocoding also differentially introduced greater amounts of positional error in the proximity to highway study in the 0-50 m proximity category. Time spent inside home on workdays/weekdays differed significantly by demographic variables (age, employment status, educational attainment, income and race). Time-activity patterns were also significantly different when stratified by proximity to highway, with those participants residing in the 0-50 m proximity category reporting significantly more time in the school/work micro-environment on workdays/weekdays than all other distance groups.

Conclusions

These findings indicate the potential for both differential and non-differential exposure misclassification due to geocoding error and time-activity patterns in studies of highway proximity. We also propose a multi-stage manual correction process to minimize positional error. Additional research is needed in other populations and geographic settings.

SUBMITTER: Lane KJ

PROVIDER: S-EPMC3907019 | biostudies-literature | 2013 Sep

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Positional error and time-activity patterns in near-highway proximity studies: an exposure misclassification analysis.

Lane Kevin J KJ Kangsen Scammell Madeleine M Levy Jonathan I JI Fuller Christina H CH Parambi Ron R Zamore Wig W Mwamburi Mkaya M Brugge Doug D

Environmental health : a global access science source 20130908 1

<h4>Background</h4>The growing interest in research on the health effects of near-highway air pollutants requires an assessment of potential sources of error in exposure assignment techniques that rely on residential proximity to roadways.<h4>Methods</h4>We compared the amount of positional error in the geocoding process for three different data sources (parcels, TIGER and StreetMap USA) to a "gold standard" residential geocoding process that used ortho-photos, large multi-building parcel layout ...[more]

PMID: 24010639

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Dataset Information

Positional error and time-activity patterns in near-highway proximity studies: an exposure misclassification analysis.

Background

Methods

Results

Conclusions

Publications

Positional error and time-activity patterns in near-highway proximity studies: an exposure misclassification analysis.

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