Quantifying spatial misclassification in exposure to noise complaints among low-income housing residents across New York City neighborhoods: a Global Positioning System (GPS) study - Sorbonne Université Access content directly
Journal Articles Annals of Epidemiology Year : 2017

Quantifying spatial misclassification in exposure to noise complaints among low-income housing residents across New York City neighborhoods: a Global Positioning System (GPS) study

Abstract

Purpose-To examine if there was spatial misclassification in exposure to neighborhood noise complaints among a sample of low-income housing residents in New York City, comparing homebased spatial buffers and Global Positioning Systems (GPS) daily path buffers. Methods-Data came from the community-based NYC Low-Income Housing, Neighborhoods and Health Study, where GPS tracking of the sample was conducted for a week (analytic n=102). We created a GPS daily path buffer (a buffering zone drawn around GPS tracks) of 200-meters and 400-meters. We also used home-based buffers of 200-meters and 400-meters. Using these "neighborhoods" (or exposure areas) we calculated neighborhood exposure to noisy events from 311 complaints data (analytic n=143,967). Friedman tests (to compare overall differences in neighborhood definitions) were applied. Results-There were differences in neighborhood noise complaints according to the selected neighborhood definitions (p<0.05). For example, the mean neighborhood noise complaint count was 1196 per square kilometer for the 400-meter home-based and 812 per square kilometer for the 400-meter activity space buffer, illustrating how neighborhood definition influences the estimates of exposure to neighborhood noise complaints.
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Dates and versions

hal-03882262 , version 1 (02-12-2022)

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Dustin T Duncan, Kosuke Tamura, Seann D Regan, Jessica Athens, Brian Elbel, et al.. Quantifying spatial misclassification in exposure to noise complaints among low-income housing residents across New York City neighborhoods: a Global Positioning System (GPS) study. Annals of Epidemiology, 2017, 27 (1), pp.67-75. ⟨10.1016/j.annepidem.2016.09.017⟩. ⟨hal-03882262⟩
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