Evidence map›Paper›PMID 26694651›Full record

ArticleInternational journal of health geographics2015

Assessing opportunities for physical activity in the built environment of children: interrelation between kernel density and neighborhood scale.

Christoph Buck, Thomas Kneib, Tobias Tkaczick, Kenn Konstabel, Iris Pigeot

Abstract read
In one paragraph

Article in International journal of health geographics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 3 pooled it
–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

11 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
  2. Access to public transport and childhood obesity: A systematic review.Obesity reviews : an official journal of the International Association for the Study of Obesity · 2021
    Pooled it
  3. Unravelling the association between accelerometer-derived physical activity and adiposity among preschool children: A systematic review and meta-analyses.Obesity reviews : an official journal of the International Association for the Study of Obesity · 2020
    Pooled it
  4. Article
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  10. Urban Moveability and physical activity in children: longitudinal results from the IDEFICS and I.Family cohort.The international journal of behavioral nutrition and physical activity · 2019
    Article
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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

5 authors.

Christoph BuckLeibniz Institute for Prevention Research and Epidemiology, BIPS, Bremen, Germany. buck@bips.uni-bremen.de.
Thomas KneibFaculty of Economic Sciences, University of Göttingen, Göttingen, Germany.
Tobias TkaczickInstitute of Geography, University of Bremen, Bremen, Germany.
Kenn KonstabelNational Institute for Health Development, Tallinn, Estonia.
Iris PigeotLeibniz Institute for Prevention Research and Epidemiology, BIPS, Bremen, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundBuilt environment studies provide broad evidence that urban characteristics influence physical activity (PA). However, findings are still difficult to compare, due to inconsistent measures assessing urban point characteristics and varying definitions of spatial scale. Both were found to influence the strength of the association between the built environment and PA.

methodsWe simultaneously evaluated the effect of kernel approaches and network-distances to investigate the association between urban characteristics and physical activity depending on spatial scale and intensity measure. We assessed urban measures of point characteristics such as intersections, public transit stations, and public open spaces in ego-centered network-dependent neighborhoods based on geographical data of one German study region of the IDEFICS study. We calculated point intensities using the simple intensity and kernel approaches based on fixed bandwidths, cross-validated bandwidths including isotropic and anisotropic kernel functions and considering adaptive bandwidths that adjust for residential density. We distinguished six network-distances from 500 m up to 2 km to calculate each intensity measure. A log-gamma regression model was used to investigate the effect of each urban measure on moderate-to-vigorous physical activity (MVPA) of 400 2- to 9.9-year old children who participated in the IDEFICS study. Models were stratified by sex and age groups, i.e. pre-school children (2 to <6 years) and school children (6-9.9 years), and were adjusted for age, body mass index (BMI), education and safety concerns of parents, season and valid weartime of accelerometers.

resultsAssociation between intensity measures and MVPA strongly differed by network-distance, with stronger effects found for larger network-distances. Simple intensity revealed smaller effect estimates and smaller goodness-of-fit compared to kernel approaches. Smallest variation in effect estimates over network-distances was found for kernel intensity measures based on isotropic and anisotropic cross-validated bandwidth selection.

conclusionWe found a strong variation in the association between the built environment and PA of children based on the choice of intensity measure and network-distance. Kernel intensity measures provided stable results over various scales and improved the assessment compared to the simple intensity measure. Considering different spatial scales and kernel intensity methods might reduce methodological limitations in assessing opportunities for PA in the built environment.

Indexed as

Environment DesignMotor ActivityResidence CharacteristicsSafetyUrban PopulationAccelerometryBody Mass IndexChildChild, PreschoolFemaleGermanyHumansLeast-Squares AnalysisMaleMonitoring, PhysiologicPopulation Density

Identifiers

PMID26694651
PMCPMC4689060

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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.