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Travel patterns during pregnancy: comparison between Global Positioning System (GPS) tracking and questionnaire data
BACKGROUND: Maternal exposures to traffic-related air pollution have been associated with adverse pregnancy outcomes. Exposures to traffic-related air pollutants are strongly influenced by time spent near traffic. However, little is known about women’s travel activities during pregnancy and whether...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3907015/ https://www.ncbi.nlm.nih.gov/pubmed/24107241 http://dx.doi.org/10.1186/1476-069X-12-86 |
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author | Wu, Jun Jiang, Chengsheng Jaimes, Guillermo Bartell, Scott Dang, Andy Baker, Dean Delfino, Ralph J |
author_facet | Wu, Jun Jiang, Chengsheng Jaimes, Guillermo Bartell, Scott Dang, Andy Baker, Dean Delfino, Ralph J |
author_sort | Wu, Jun |
collection | PubMed |
description | BACKGROUND: Maternal exposures to traffic-related air pollution have been associated with adverse pregnancy outcomes. Exposures to traffic-related air pollutants are strongly influenced by time spent near traffic. However, little is known about women’s travel activities during pregnancy and whether questionnaire-based data can provide reliable information on travel patterns during pregnancy. OBJECTIVES: Examine women’s in-vehicle travel behavior during pregnancy and examine the difference in travel data collected by questionnaire and global positioning system (GPS) and their potential for exposure error. METHODS: We measured work-related travel patterns in 56 pregnant women using a questionnaire and one-week GPS tracking three times during pregnancy (<20 weeks, 20–30 weeks, and >30 weeks of gestation). We compared self-reported activities with GPS-derived trip distance and duration, and examined potentially influential factors that may contribute to differences. We also described in-vehicle travel behavior by pregnancy periods and influences of demographic and personal factors on daily travel times. Finally, we estimated personal exposure to particle-bound polycyclic aromatic hydrocarbon (PB-PAH) and examined the magnitude of exposure misclassification using self-reported vs. GPS travel data. RESULTS: Subjects overestimated both trip duration and trip distance compared to the GPS data. We observed moderately high correlations between self-reported and GPS-recorded travel distance (home to work trips: r = 0.88; work to home trips: r = 0.80). Better agreement was observed between the GPS and the self-reported travel time for home to work trips (r = 0.77) than work to home trips (r = 0.64). The subjects on average spent 69 and 93 minutes traveling in vehicles daily based on the GPS and self-reported data, respectively. Longer daily travel time was observed among participants in early pregnancy, and during certain pregnancy periods in women with higher education attainment, higher income, and no children. When comparing self-reported vs. GPS data, we found that estimated personal exposure to PB-PAH did not differ remarkably at the population level, but the difference was large at an individual level. CONCLUSION: Self-reported home-to-work data overestimated both trip duration and trip distance compared to GPS data. Significant differences in PAH exposure estimates were observed at individual level using self-reported vs. GPS data, which has important implications in air pollution epidemiological studies. |
format | Online Article Text |
id | pubmed-3907015 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-39070152014-01-31 Travel patterns during pregnancy: comparison between Global Positioning System (GPS) tracking and questionnaire data Wu, Jun Jiang, Chengsheng Jaimes, Guillermo Bartell, Scott Dang, Andy Baker, Dean Delfino, Ralph J Environ Health Research BACKGROUND: Maternal exposures to traffic-related air pollution have been associated with adverse pregnancy outcomes. Exposures to traffic-related air pollutants are strongly influenced by time spent near traffic. However, little is known about women’s travel activities during pregnancy and whether questionnaire-based data can provide reliable information on travel patterns during pregnancy. OBJECTIVES: Examine women’s in-vehicle travel behavior during pregnancy and examine the difference in travel data collected by questionnaire and global positioning system (GPS) and their potential for exposure error. METHODS: We measured work-related travel patterns in 56 pregnant women using a questionnaire and one-week GPS tracking three times during pregnancy (<20 weeks, 20–30 weeks, and >30 weeks of gestation). We compared self-reported activities with GPS-derived trip distance and duration, and examined potentially influential factors that may contribute to differences. We also described in-vehicle travel behavior by pregnancy periods and influences of demographic and personal factors on daily travel times. Finally, we estimated personal exposure to particle-bound polycyclic aromatic hydrocarbon (PB-PAH) and examined the magnitude of exposure misclassification using self-reported vs. GPS travel data. RESULTS: Subjects overestimated both trip duration and trip distance compared to the GPS data. We observed moderately high correlations between self-reported and GPS-recorded travel distance (home to work trips: r = 0.88; work to home trips: r = 0.80). Better agreement was observed between the GPS and the self-reported travel time for home to work trips (r = 0.77) than work to home trips (r = 0.64). The subjects on average spent 69 and 93 minutes traveling in vehicles daily based on the GPS and self-reported data, respectively. Longer daily travel time was observed among participants in early pregnancy, and during certain pregnancy periods in women with higher education attainment, higher income, and no children. When comparing self-reported vs. GPS data, we found that estimated personal exposure to PB-PAH did not differ remarkably at the population level, but the difference was large at an individual level. CONCLUSION: Self-reported home-to-work data overestimated both trip duration and trip distance compared to GPS data. Significant differences in PAH exposure estimates were observed at individual level using self-reported vs. GPS data, which has important implications in air pollution epidemiological studies. BioMed Central 2013-10-09 /pmc/articles/PMC3907015/ /pubmed/24107241 http://dx.doi.org/10.1186/1476-069X-12-86 Text en Copyright © 2013 Wu et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Wu, Jun Jiang, Chengsheng Jaimes, Guillermo Bartell, Scott Dang, Andy Baker, Dean Delfino, Ralph J Travel patterns during pregnancy: comparison between Global Positioning System (GPS) tracking and questionnaire data |
title | Travel patterns during pregnancy: comparison between Global Positioning System (GPS) tracking and questionnaire data |
title_full | Travel patterns during pregnancy: comparison between Global Positioning System (GPS) tracking and questionnaire data |
title_fullStr | Travel patterns during pregnancy: comparison between Global Positioning System (GPS) tracking and questionnaire data |
title_full_unstemmed | Travel patterns during pregnancy: comparison between Global Positioning System (GPS) tracking and questionnaire data |
title_short | Travel patterns during pregnancy: comparison between Global Positioning System (GPS) tracking and questionnaire data |
title_sort | travel patterns during pregnancy: comparison between global positioning system (gps) tracking and questionnaire data |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3907015/ https://www.ncbi.nlm.nih.gov/pubmed/24107241 http://dx.doi.org/10.1186/1476-069X-12-86 |
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