Evidence map›Paper›PMID 30997324›Full record

ArticlePreventive medicine reports2019

A multilevel study of neighborhood disadvantage, individual socioeconomic position, and body mass index: Exploring cross-level interaction effects.

Jerome N Rachele, Christina J Schmid, Wendy J Brown, Andrea Nathan, Carlijn B M Kamphuis, Gavin Turrell

Abstract read
In one paragraph

Article in Preventive medicine reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

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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.

Jerome N RacheleMelbourne School of Population and Global Health, The University of Melbourne, Carlton, Australia.
Christina J SchmidSchool of Exercise and Nutrition Sciences, Queensland University of Technology, Brisbane 4059, Australia.
Wendy J BrownSchool of Human Movement and Nutrition Sciences, University of Queensland, Australia.
Andrea NathanMary MacKillop Institute for Health Research, Australian Catholic University, Australia.
Carlijn B M KamphuisDepartment of Human Geography and Spatial Planning, Faculty of Geosciences, Utrecht University, Netherlands.
Gavin TurrellSchool of Health and Social Development, Centre for Population Health Research, Deakin University, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study examined associations between neighborhood disadvantage and body mass index (BMI), and tested whether this differed by level of individual socioeconomic position (SEP). Data were from 9953 residents living in 200 neighborhoods in Brisbane, Australia in 2007. Multilevel linear regression analyses were undertaken by gender to determine associations between neighborhood disadvantage, individual SEP (education, occupation and household income) and BMI (from self-reported height and weight); with cross-level interactions testing whether the relationship between neighborhood disadvantage and BMI differed by level of individual SEP. Both men (Quintile 4, where Quintile 5 is the most disadvantaged β = 0.66 95%CI 0.20, 1.12) and women (Quintile 5 β = 1.32 95%CI 0.76, 1.87) from more disadvantaged neighborhoods had a higher BMI. BMI was significantly higher for those with lower educational attainment (men β = 0.71 95%CI 0.36, 1.07 and women β = 1.66 95%CI 0.78, 1.54), and significantly lower for those in blue collar occupations (men β = -0.67 95%CI -1.09, -0.25 and women β = -0.71 95%CI -1.40, -0.01). Among men, those with a lower income had a significantly lower BMI, while the opposite was found among women. None of the interaction models had a significantly better fit than the random intercept models. The relationship between neighborhood disadvantage and BMI did not differ by level of education, occupation, or household income. This suggests that individual SEP is unlikely to be an effector modifier of the relationship between neighborhood disadvantage and BMI. Further research is required to assist policy-makers to make more informed decisions about where to intervene to counteract BMI-inequalities.

Indexed as

Health inequalitiesMultilevel modellingResidence characteristicsSocial classSocioeconomic background

Identifiers

PMID30997324
PMCPMC6453828

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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.