Evidence map›Paper›PMID 30887375›Full record

ArticleJournal of urban health : bulletin of the New York Academy of Medicine2019

A Local View of Informal Urban Environments: a Mobile Phone-Based Neighborhood Audit of Street-Level Factors in a Brazilian Informal Community.

Richard V Remigio, Garazi Zulaika, Renata S Rabello, John Bryan, Daniel M Sheehan, Sandro Galea, Marilia S Carvalho, Andrew Rundle, Gina S Lovasi

Abstract read
In one paragraph

Article in Journal of urban health : bulletin of the New York Academy of Medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

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  8. Using 164 Million Google Street View Images to Derive Built Environment Predictors of COVID-19 Cases.International journal of environmental research and public health · 2020
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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

9 authors.

Richard V RemigioUrban Health Collaborative, Dornsife School of Public Health, Drexel University, Philadelphia, PA, USA. rvr350@umd.edu.ORCID 0000-0001-8381-4728
Garazi ZulaikaDepartment of Epidemiology, Mailman School of Public Health, Columbia University, New York City, NY, USA.
Renata S RabelloEscola Nacional de Saúde Publica (ENSP)/Fundação Oswaldo Cruz (FIOCRUZ), Rio de Janeiro, Rio de Janeiro, Brazil.
John BryanDepartment of Epidemiology, Mailman School of Public Health, Columbia University, New York City, NY, USA.
Daniel M SheehanDepartment of Epidemiology, Mailman School of Public Health, Columbia University, New York City, NY, USA.
Sandro GaleaDepartment of Epidemiology, Boston University School of Public Health, Boston, MA, USA.
Marilia S CarvalhoPrograma de Computação Científica (PROCC), Oswaldo Cruz Foundation, Rio de Janeiro, Brazil.
Andrew RundleDepartment of Epidemiology, Mailman School of Public Health, Columbia University, New York City, NY, USA.
Gina S LovasiUrban Health Collaborative, Dornsife School of Public Health, Drexel University, Philadelphia, PA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Street-level environment characteristics influence the health behaviors and safety of urban residents, and may particularly threaten health within informal communities. However, available data on how such characteristics vary within and among informal communities is limited. We sought to adapt street audit strategies designed to characterize the physical environment for use in a large informal community, Rio das Pedras (RdP) located in Rio de Janeiro, Brazil. A smartphone-based systematic observation protocol was used to gather street-level information for a high-density convenience sample of street segments (N = 630, estimated as 86% of all street segments in the community). We adapted items related to physical disorder and physical deterioration. Measures selected to illustrate the approach include the presence of the following: (1) low-hanging or tangled wires, (2) litter, (3) structural evidence of sinking, and (4) an unpleasant odor. Intercept-only spatial generalized additive models (GAM) were used to evaluate and visualize spatial variation within the RdP community. We also examined how our estimates and conclusions about spatial variation might have been affected by lower-density sampling from random subsets street observations. Random subsets were selected to determine the robustness of study results in scenarios with sparser street sampling. Selected characteristics were estimated to be present for between 18% (unpleasant odor) to 59% (low-hanging or tangled wires) of the street segments in RdP; estimates remain similar (± 6%) when relying on a random subset created to simulate lower-density spatial sampling. Spatial patterns of variation based on predicted probabilities across RdP differed by indicator. Structural sinking and low-hanging or tangled wires demonstrated relatively consistent spatial distribution patterns across full and random subset sample sizes. Smartphone-based systematic observations represent an efficient and potentially feasible approach to systematically studying neighborhood environments within informal communities. Future deployment of such tools will benefit from incorporating data collection across multiple time points to explore reliability and quantify neighborhood change. These tools can prove useful means to assess street-level exposures that can be modifiable health determinants across a wide range of informal urban settings. Findings can contribute to improved urban planning and provide useful information for identifying potential locations for neighborhood-scaled interventions that can improve living conditions for residents in Rio das Pedras.

Indexed as

Cell PhoneHealth BehaviorBrazilCitiesCity PlanningData CollectionEnvironment DesignHumansReproducibility of ResultsResidence CharacteristicsApp-based instrumentsBuilt environmentInformal communitiesPhysical disorderSpatial variabilitySystematic social observation

Identifiers

PMID30887375
PMCPMC6890882

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Registered trials

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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.