Evidence map›Paper›PMID 28063754›Full record

ArticleAnnals of epidemiology2017

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

Dustin T Duncan, Kosuke Tamura, Seann D Regan, Jessica Athens, Brian Elbel, Julie Meline, Yazan A Al-Ajlouni, Basile Chaix

Abstract readComparative Study
In one paragraph

Article in Annals of epidemiology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

14 citing papers in PubMed.

  1. Article
  2. Neighborhood Walkability, Historical Redlining, and Childhood Obesity in Denver, Colorado.Journal of urban health : bulletin of the New York Academy of Medicine · 2023
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Dustin T DuncanDepartment of Population Health, New York University School of Medicine, New York. Electronic address: Dustin.Duncan@nyumc.org.
Kosuke TamuraDepartment of Population Health, New York University School of Medicine, New York.
Seann D ReganDepartment of Population Health, New York University School of Medicine, New York.
Jessica AthensDepartment of Population Health, New York University School of Medicine, New York.
Brian ElbelDepartment of Population Health, New York University School of Medicine, New York; Wagner Graduate School of Public Service, New York University, New York.
Julie MelineSorbonne Universités, UPMC Univ Paris 06, UMR_S 1136, Pierre Louis Institute of Epidemiology and Public Health, Paris, France; Inserm, UMR_S 1136, Pierre Louis Institute of Epidemiology and Public Health, Paris, France.
Yazan A Al-AjlouniDepartment of Population Health, New York University School of Medicine, New York.
Basile ChaixSorbonne Universités, UPMC Univ Paris 06, UMR_S 1136, Pierre Louis Institute of Epidemiology and Public Health, Paris, France; Inserm, UMR_S 1136, Pierre Louis Institute of Epidemiology and Public Health, Paris, France.

Funding

Project-005UL1TR001445 · NCATS · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI BREDELLA, MIRIAM ANTOINETTE, HOCHMAN, JUDITH S · 2015 to 2025
$103.5M
Institutional Clinical and Translational Science AwardUL1TR000038 · NCATS · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI CRONSTEIN, BRUCE NEIL, HOCHMAN, JUDITH S · 2012 to 2014
$16.8M
NCATS NIH HHS UL1 TR000038NCATS NIH HHS UL1 TR001445
6 · The paper itself

Abstract

purposeTo 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 home-based spatial buffers and Global Positioning System (GPS) daily path buffers.

methodsData 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 m and 400 m. We also used home-based buffers of 200 m and 400 m. 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.

resultsThere were differences in neighborhood noise complaints according to the selected neighborhood definitions (P < .05). For example, the mean neighborhood noise complaint count was 1196 per square kilometer for the 400-m home-based and 812 per square kilometer for the 400-m activity space buffer, illustrating how neighborhood definition influences the estimates of exposure to neighborhood noise complaints.

conclusionsThese analyses suggest that, whenever appropriate, GPS neighborhood definitions can be used in spatial epidemiology research in spatially mobile populations to understand people's lived experience.

Indexed as

Environmental ExposureFemaleGeographic Information SystemsHumansIncidenceMaleNew York CityNoisePilot ProjectsPovertyResidence CharacteristicsRisk AssessmentSpatial AnalysisUrban PopulationGeographic information systemsGlobal positioning systemsLow-income housing residentsNeighborhoodsNoise complaint exposureSpatial epidemiologySpatial misclassification

Identifiers

PMID28063754
PMCPMC5272798

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.