Evidence map›Paper›PMID 27283011›Full record

ArticlePediatric obesity2017

Projecting the impact of hypothetical early life interventions on adiposity in children living in low-income households.

Roch A Nianogo, May C Wang, Aolin Wang, Tabashir Z Nobari, Catherine M Crespi, Shannon E Whaley, Onyebuchi A Arah

Abstract read
In one paragraph

Article in Pediatric obesity, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 1 pooled it
3.0field-weighted citation impact, top 8% of its field
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

12 citing papers in PubMed, 1 synthesis or guideline pooled it, 20 citations in OpenAlex.

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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

7 authors at 4 institutions in 2 countries.

Roch A NianogoDepartment of Epidemiology, Fielding School of Public Health, University of California, Los Angeles (UCLA), Los Angeles, USA.ORCID 0000-0001-5932-6169
May C WangCalifornia Center for Population Research, UCLA, Los Angeles, USA.
Aolin WangDepartment of Epidemiology, Fielding School of Public Health, University of California, Los Angeles (UCLA), Los Angeles, USA.
Tabashir Z NobariCalifornia Center for Population Research, UCLA, Los Angeles, USA.
Catherine M CrespiDepartment of Biostatistics, UCLA School of Public Health, Los Angeles, USA.
Shannon E WhaleyResearch and Evaluation Unit, Public Health Foundation Enterprises - Special Supplemental Nutrition Program for Women, Infants and Children (PHFE WIC), Irwindale, USA.
Onyebuchi A ArahDepartment of Epidemiology, Fielding School of Public Health, University of California, Los Angeles (UCLA), Los Angeles, USA.
University of California, Los Angeles · USLos Angeles County Department of Public Health · USPublic Health Foundation Enterprises · USUCLA Health · US

Funding

Women's CancersP30CA016042 · NCI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI Robert Damoiseaux · 1985 to 2026
$134.5M
UCLA Clinical and Translational Science InstituteUL1TR000124 · NCATS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI DUBINETT, STEVEN M. · 2012 to 2015
$57.0M
Statistics and Methods CoreR24HD041022 · NICHD · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI BUCHINSKY, MOSHE · 2001 to 2016
$10.1M
The impact of natural experiments on child obesity: A systems science approachR01HD072296 · NICHD · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI PRELIP, MICHAEL LEE, WANG, MAY C · 2013 to 2017
$2.4M
NCATS NIH HHS UL1 TR000124NCI NIH HHS P30 CA016042NICHD NIH HHS R01 HD072296NICHD NIH HHS R24 HD041022Wellcome Trust
6 · The paper itself

Abstract

backgroundIt is difficult to evaluate the effectiveness of interventions aimed at reducing early childhood obesity using randomized trials. Objective To illustrate how observational data can be analysed using causal inference methods to estimate the potential impact of behavioural 'interventions' on early childhood adiposity. Methods We used longitudinal data from 1054 children 1-5 years old enrolled in the Special Supplemental Nutrition Program for Women, Infants and Children and followed (WIC) from 2008 to 2010 for a mean duration of 23 months. The data came from a random sample of WIC families living in Los Angeles County in 2008. We used the parametric g-formula to estimate the impact of various hypothetical behavioural interventions. Results Adjusted mean weight-for-height Z score at the end of follow-up was 0.73 (95% CI 0.65, 0.81) under no intervention and 0.63 (95% CI 0.38, 0.87) for all interventions given jointly. Exclusive breastfeeding for 6 months or longer was the most effective intervention [population mean difference = -0.11 (95% CI -0.22, 0.01)]. Other interventions had little or no effect. Conclusions Compared with interventions promoting healthy eating and physical activity behaviours, breastfeeding was more effective in reducing obesity risk in children aged 1-5 years. When carefully applied, causal inference methods may offer viable alternatives to randomized trials in etiologic and evaluation research.

Indexed as

AdiposityBehavior TherapyBreast FeedingChild, PreschoolEarly Medical InterventionFemaleFollow-Up StudiesHumansInfantLongitudinal StudiesMalePediatric ObesityPovertyRisk Factorsadipositybreastfeedingcausal inferencechildhood obesity

Identifiers

PMID27283011
PMCPMC5290222
OpenAlexW2416821697

What OpenQuestion holds

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Read underepoch 390

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.