ArticleContemporary clinical trials2019
In-home obesity prevention in low-income infants through maternal and social transmission.
Article in Contemporary clinical trials, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 3 of them syntheses that pooled it.
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
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.
Who cites it
6 citing papers in PubMed, 3 syntheses or guidelines pooled it, 6 citations in OpenAlex.
- Impact of environmental interventions based on social programs on physical activity levels: A systematic review.Frontiers in public health · 2023Pooled it
- Interventions for increasing fruit and vegetable consumption in children aged five years and under.The Cochrane database of systematic reviews · 2020Pooled it
- Interventions for increasing fruit and vegetable consumption in children aged five years and under.The Cochrane database of systematic reviews · 2019Pooled it
- Community-based diet and obesity-related policy, system, and environmental interventions for obesity prevention during the first 1000 days: A scoping review.Obesity reviews : an official journal of the International Association for the Study of Obesity · 2024Article
- Social network influences and the adoption of obesity-related behaviours in adults: a critical interpretative synthesis review.BMC public health · 2019Review
- The role of maternal social networks on the outcomes of a home-based childhood obesity prevention pilot intervention.Journal of social structure : JOSS · 2019Article
Corrections and comments
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Authors and funding
7 authors at 4 institutions in 1 country.
Funding
Abstract
backgroundExtant obesity efforts have had a limited impact among low-income underserved children, in part because existing programs are limited in terms of their short duration and low dosage, limited accessibility and sustainability; and failure to address barriers faced by diverse low-income families.
methodsThis two-arm, parallel, randomized controlled trial (RCT) tests whether delivering obesity prevention, as part of an ongoing home visitation program (HVP), is an effective approach for primary (infants) and secondary (mothers) obesity prevention among low-income, underserved families. This RCT further examines the role of maternal and social factors as key mechanisms of transmission of infants' obesity risk, and the real-life costs of delivering obesity prevention as part of HVPs. Specifically, 300 low-income mothers/infants (6mo at baseline) participating in the Healthy Families America home visitation program in Antelope Valley (CA) will be recruited and enrolled in the study. Home visitors serving families will be randomly assigned to deliver the standard HVP curriculum with or without obesity prevention as part of their weekly home visits for two years. Anthropometric, metabolic and behavioral assessments of mothers/infants will be conducted at enrollment and after 6 and 18 months of intervention. DISCUSSION: This study addresses the need to develop interventions targeting at-risk infants before they become obese. The proposed research is timely as the Institute of Medicine, the United States Department of Agriculture, and the Department of Health and Human Services are revising their recommendations to address key factors influencing obesity risk in children from birth to 24 months of age.
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Registered trials
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.