Evidence map›Paper›PMID 31245526›Full record

ArticleSSM - population health2019

Methods of measuring associations between the Retail Food Environment and weight status: Importance of classifications and metrics.

Emma Wilkins, Michelle Morris, Duncan Radley, Claire Griffiths

Abstract read
In one paragraph

Article in SSM - population health, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.

0numbers the graph read from it
0cells of the map it votes in
26citing 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

26 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Review
  18. Article
  19. Article
  20. Article
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

4 authors.

Emma WilkinsCarnegie School of Sport, Leeds Beckett University, Leeds, UK.
Michelle MorrisLeeds Institute for Data Analytics, School of Medicine, University of Leeds, Leeds, UK.
Duncan RadleyCarnegie School of Sport, Leeds Beckett University, Leeds, UK.
Claire GriffithsCarnegie School of Sport, Leeds Beckett University, Leeds, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Despite considerable research, evidence supporting associations between the 'Retail Food Environment' (RFE) and obesity remains mixed. Differences in the methods used to measure the RFE may explain this heterogeneity. Using data on a large (n = 10,111) sample of adults from the Yorkshire Health Study (UK), we modelled cross-sectional associations between the RFE and weight status using (i) multiple definitions of 'Fast Food', 'Convenience' and 'Supermarkets' and (ii) multiple RFE metrics, identified in a prior systematic review to be common in the literature. Both the choice of outlet definition and the choice of RFE metric substantively impacted observed associations with weight status. Findings differed in relation to statistical significance, effect sizes, and directions of association. This study provides novel evidence that the diversity of RFE measurement methods is contributing to heterogeneous study findings and conflicting policy messages. Greater attention is needed when selecting and communicating RFE measures in research.

Indexed as

Community nutrition environmentFood accessFoodscapeGISMethodologyObesogenic environmentUnited Kingdom

Identifiers

PMID31245526
PMCPMC6582068

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.