ArticlePreventive medicine reports2019
Overweight/obesity among social network members has an inverse relationship with Baltimore public housing residents' BMI.
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 4 papers.
What it found
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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.
The trial behind it
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Who cites it
4 citing papers in PubMed, 8 citations in OpenAlex.
- Predictive Utility of Alternate Measures of Physical Activity and Diet for Overweight and Obesity in Low-Income Minority Women.American journal of health promotion : AJHP · 2022Article
- Assessing impacts of redeveloping public housing communities on obesity in low-income minority residents: Rationale, study design, and baseline data from the Watts Neighborhood Health Study.Contemporary clinical trials communications · 2022Article
- Social network factors and cardiovascular health among baltimore public housing residents.Preventive medicine reports · 2020Article
- Social Influences on Obesity: Current Knowledge, Emerging Methods, and Directions for Future Research and Practice.Current nutrition reports · 2020Review
Corrections and comments
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Authors and funding
7 authors at 1 institution in 1 country.
Funding
Abstract
The American Heart Association has encouraged networks research focused on cardiovascular disease and its risk factors, such as obesity. However, little network research has focused on minorities or low-income populations. Our objective was to characterize the relationship between body mass index (BMI) with social network overweight/obesity among public housing residents in Baltimore, MD - a predominantly black, low-income group. We conducted a cross-sectional survey of randomly selected public housing residences (8/2014-8/2015). Adults had their height and weight measured and reported their network members' weight statuses using pictograms. Our dependent variable was respondents' BMI, and independent variable was perceived exposure to overweight/obesity in the social network. We also explored network exposure to overweight/obesity among 1) family members and 2) friends. We used multivariable linear regression adjusted for significant covariates. Our sample included 255 adults with mean age of 44.4 years, 85.5% women, 95.7% black, and mean BMI of 33.2 kg/m
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Registered trials
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