Evidence map›Paper›PMID 26251559›Full record

ArticleApplied geography (Sevenoaks, England)2015

Multilevel built environment features and individual odds of overweight and obesity in Utah.

Yanqing Xu, Ming Wen, Fahui Wang

Abstract read
In one paragraph

Article in Applied geography (Sevenoaks, England), 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed, 1 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

23 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Environmental Risk Factors for Developing Type 2 Diabetes Mellitus: A Systematic Review.International journal of environmental research and public health · 2018
    Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Contextual and Individual Determinants of Mental Health: A Cross-sectional Multilevel Study in Tehran, Iran.Journal of preventive medicine and public health = Yebang Uihakhoe chi · 2020
    Article
  12. Review
  13. Article
  14. Walk ScoreInternational journal of environmental research and public health · 2019
    Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Associations of neighbourhood walkability indices with weight gain.The international journal of behavioral nutrition and physical activity · 2018
    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

3 authors.

Yanqing XuDepartment of Geography & Anthropology, Louisiana State University, USA.
Ming WenDepartment of Sociology, University of Utah, USA.
Fahui WangDepartment of Geography & Anthropology, Louisiana State University, USA ; School of Urban and Environmental Studies, Yunnan University of Finance and Economics, Kunming, Yunnan 650221, China.

Funding

Neighborhood Built and Social Environment and Physical Activity and Weight StatusR01CA140319 · NCI · UNIVERSITY OF UTAH · PI WEN, MING · 2010 to 2014
$1.2M
NCI NIH HHS R01 CA140319
6 · The paper itself

Abstract

Based on the data from the Behavioral Risk Factor Surveillance System (BRFSS) in 2007, 2009 and 2011 in Utah, this research uses multilevel modeling (MLM) to examine the associations between neighborhood built environments and individual odds of overweight and obesity after controlling for individual risk factors. The BRFSS data include information on 21,961 individuals geocoded to zip code areas. Individual variables include BMI (body mass index) and socio-demographic attributes such as age, gender, race, marital status, education attainment, employment status, and whether an individual smokes. Neighborhood built environment factors measured at both zip code and county levels include street connectivity, walk score, distance to parks, and food environment. Two additional neighborhood variables, namely the poverty rate and urbanicity, are also included as control variables. MLM results show that at the zip code level, poverty rate and distance to parks are significant and negative covariates of the odds of overweight and obesity; and at the county level, food environment is the sole significant factor with stronger fast food presence linked to higher odds of overweight and obesity. These findings suggest that obesity risk factors lie in multiple neighborhood levels and built environment features need to be defined at a neighborhood size relevant to residents' activity space.

Indexed as

Built environmentCountyMultilevel modelingObesityUtahZip code

Identifiers

PMID26251559
PMCPMC4523305

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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.