Evidence map›Paper›PMID 34045506›Full record

ArticleScientific reports2021

The impact of hypothetical interventions on adiposity in adolescence.

Mekdes K Gebremariam, Roch A Nianogo, Nanna Lien, Mona Bjelland, Knut-Inge Klepp, Ingunn H Bergh, Yngvar Ommundsen, Onyebuchi A Arah

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2021. 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
1.2field-weighted citation impact, top 21% 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

3 citing papers in PubMed, 7 citations in OpenAlex.

  1. Article
  2. Causal models and causal modelling in obesity: foundations, methods and evidence.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2023
    Review
  3. 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

8 authors at 4 institutions in 2 countries.

Mekdes K GebremariamDepartment of Nutrition, Faculty of Medicine, University of Oslo, Oslo, Norway. mekdes.gebremariam@medisin.uio.no.
Roch A NianogoDepartment of Epidemiology, Fielding School of Public Health, University of California, Los Angeles (UCLA), Los Angeles, CA, USA.
Nanna LienDepartment of Nutrition, Faculty of Medicine, University of Oslo, Oslo, Norway.
Mona BjellandDepartment of Nutrition, Faculty of Medicine, University of Oslo, Oslo, Norway.
Knut-Inge KleppDepartment of Nutrition, Faculty of Medicine, University of Oslo, Oslo, Norway.
Ingunn H BerghDepartment of Health and Inequality, Norwegian Institute of Public Health, Oslo, Norway.
Yngvar OmmundsenDepartment of Coaching and Psychology, Norwegian School of Sport Sciences, Oslo, Norway.
Onyebuchi A ArahDepartment of Epidemiology, Fielding School of Public Health, University of California, Los Angeles (UCLA), Los Angeles, CA, USA.
University of Oslo · NONorwegian Institute of Public Health · NOUniversity of California, Los Angeles · USNorwegian School of Sport Sciences · NO

Funding

Scientific and Technical CoreP2CHD041022 · NICHD · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI Martha Jane Bailey · 2016 to 2026
$6.9M
NICHD NIH HHS P2C HD041022
6 · The paper itself

Abstract

In order to develop effective public health initiatives aimed at promoting healthy weight development, identifying the interventions/combination of interventions with the highest beneficial effect on body weight is vital. The study aimed to estimate the mean BMI at age 13 under hypothetical interventions targeting dietary behavior, physical activity and screen time at age 11. We used data from a school-based cohort study of 530 participants followed between the ages of 11 and 13. We used g-computation, a causal modeling method, to estimate the impact of single and combined hypothetical behavioral interventions at age 11 on BMI at age 13. Of the hypothetical interventions, the one with the largest population mean difference in BMI was the one combining all interventions (dietary behavior, physical activity and screen time interventions) and assuming 100% intervention adherence, with a population mean differences of - 0.28 (95% CI - 0.59, 0.07). Isolated behavioral interventions had a limited impact on BMI. This study demonstrated that a combination of healthy dietary behavior and physical activity promotion, as well as screen time reduction interventions at age 11 could have the highest beneficial effect on the reduction of BMI at age 13, although the change in BMI was small. The findings highlight the importance of a systems approach to obesity prevention focusing on multicomponent interventions.

Indexed as

DietHealth BehaviorModels, TheoreticalAdiposityAdolescentBody Mass IndexChildExerciseFemaleHumansLife StyleMalePediatric ObesityScreen Time

Identifiers

PMID34045506
PMCPMC8160144
OpenAlexW3164167304

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.