Evidence map›Paper›PMID 27852605›Full record

ArticleAmerican journal of epidemiology2016

The Local Food Environment and Fruit and Vegetable Intake: A Geographically Weighted Regression Approach in the ORiEL Study.

Christelle Clary, Daniel J Lewis, Ellen Flint, Neil R Smith, Yan Kestens, Steven Cummins

Abstract read
In one paragraph

Article in American journal of epidemiology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing 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

22 citing papers in PubMed.

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  13. The use and misuse of ratio and proportion exposure measures in food environment research.The international journal of behavioral nutrition and physical activity · 2020
    Article
  14. Observational
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  17. Review
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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

6 authors.

Christelle Clary
Daniel J Lewis
Ellen Flint
Neil R Smith
Yan Kestens
Steven Cummins

Funding

Department of Health 09/3005/09
6 · The paper itself

Abstract

Studies that explore associations between the local food environment and diet routinely use global regression models, which assume that relationships are invariant across space, yet such stationarity assumptions have been little tested. We used global and geographically weighted regression models to explore associations between the residential food environment and fruit and vegetable intake. Analyses were performed in 4 boroughs of London, United Kingdom, using data collected between April 2012 and July 2012 from 969 adults in the Olympic Regeneration in East London Study. Exposures were assessed both as absolute densities of healthy and unhealthy outlets, taken separately, and as a relative measure (proportion of total outlets classified as healthy). Overall, local models performed better than global models (lower Akaike information criterion). Locally estimated coefficients varied across space, regardless of the type of exposure measure, although changes of sign were observed only when absolute measures were used. Despite findings from global models showing significant associations between the relative measure and fruit and vegetable intake (β = 0.022; P < 0.01) only, geographically weighted regression models using absolute measures outperformed models using relative measures. This study suggests that greater attention should be given to nonstationary relationships between the food environment and diet. It further challenges the idea that a single measure of exposure, whether relative or absolute, can reflect the many ways the food environment may shape health behaviors.

Indexed as

EnvironmentAdultAge FactorsCross-Sectional StudiesDietFeeding BehaviorFemaleFood SupplyFruitHumansLondonMaleMiddle AgedResidence CharacteristicsSex FactorsSocioeconomic Factorsabsolute exposurefruit and vegetable intakegeographically weighted regressionlocal food environmentnonstationarityrelative exposure

Identifiers

PMID27852605
PMCPMC5152662

What OpenQuestion holds

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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.