Evidence map›Paper›PMID 39989394›Full record

Trial reportActa paediatrica (Oslo, Norway : 1992)2025

Diet, Activity and Sleep Clusters Associated With Obesity Markers of Children in the US-Affiliated Pacific.

Dorothea Dumuid, Ashley B Yamanaka, Kar Hau Chong, Anthony D Okely, Lynne R Wilkens, Yurii B Shvetsov, Chloe P Lozano, Rachel Novotny

Registry-linked trialAbstract readRandomized Controlled Trial
In one paragraph

Trial report in Acta paediatrica (Oslo, Norway : 1992), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT01881373 (Children's Healthy Living Program for Remote Underserved Minority Populations in the Pacific Region), which is not on this map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–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.

NCT01881373 nacompletednot on this map

Children's Healthy Living Program for Remote Underserved Minority Populations in the Pacific Region

TypeinterventionalSponsorUniversity of HawaiiRan2012 to 2020Enrolled9,840ConditionsObesity, Acanthosis Nigricans, Central ObesityArmsCHL program, Delayed Optimized CHL program
3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Dorothea DumuidAlliance for Research in Exercise, Nutrition and Activity, Allied Health & Human Performance, University of South Australia, Adelaide, South Australia, Australia.ORCID 0000-0003-3057-0963
Ashley B YamanakaCollege of Tropical Agriculture and Human Resilience, University of Hawaii at Manoa, Honolulu, Hawaii, USA.
Kar Hau ChongSchool of Social Sciences, Early Start, Faculty of the Arts, Social Sciences and Humanities, University of Wollongong, Wollongong, New South Wales, Australia.
Anthony D OkelySchool of Social Sciences, Early Start, Faculty of the Arts, Social Sciences and Humanities, University of Wollongong, Wollongong, New South Wales, Australia.
Lynne R WilkensCancer Center, University of Hawaii at Manoa, Honolulu, Hawaii, USA.
Yurii B ShvetsovCancer Center, University of Hawaii at Manoa, Honolulu, Hawaii, USA.
Chloe P LozanoCancer Center, University of Hawaii at Manoa, Honolulu, Hawaii, USA.
Rachel NovotnyCollege of Tropical Agriculture and Human Resilience, University of Hawaii at Manoa, Honolulu, Hawaii, USA.

Funding

Selenium Metabolism in the Heart: Impact of High Fructose and Low SeleniumP20GM139753 · NIGMS · UNIVERSITY OF HAWAII AT MANOA · PI Marla J Berry · 2022 to 2026
$13.3M
Australian Research Council Discovery Early Career Award (DECRA) DE230101174Centre of Research Excellence Driving Global Investment in Adolescent HealthNational Health and Medical Research Council GNT1171981National Health and Medical Research Council GNT1176858NIGMS NIH HHS P20 GM139753NIH NIGMS 1P20GM139753-01A1USDA National Institute of Food and Agriculture 2011-68001-30335USDA National Institute of Food and Agriculture 2018-69001-27551USDA National Institute of Food and Agriculture 2021-68012-35899USDA National Institute of Food and Agriculture 2022-09708
6 · The paper itself

Abstract

aimAmong children in the US-Affiliated Pacific, we aimed to identify lifestyle clusters and associations with obesity.

methodsMovement behaviours, diet and anthropometrics were from the Children's Healthy Living Program (n = 1780; 2012-2015). Partitioning-around-medoids identified clusters; regression examined differences in anthropometrics.

resultsAmong 2-5-year-olds, boys' clusters were: (1) high %energy from (E%) fat and sedentary behaviour; (2) high screen time and energy intake and (3) long sleep. Body mass index z-score (zBMI) was lower in Cluster 3 versus 1 (-0.28 [-0.50; -0.07], p = 0.01). Girls' clusters were: (1) high energy intake; (2) low E% fat and (3) high physical activity and sleep. zBMI was lower in Cluster 3 versus 1 (-0.34 [-0.55; -0.13], p = 0.002). Among 6-8-year-olds, boys' clusters were: (1) high screen time; (2) high energy intake; (3) high E% protein; (4) long sleep and (5) high sedentary time and low E% saturated fat. Compared with Cluster 1, zBMI was lower in Clusters 3 (-0.43 [-0.84; -0.02], p = 0.04), 4 (-0.64 [-1.08; -0.20], p = 0.004) and 5 (-0.93 [-1.35; -0.51], p < 0.001). Girls' clusters were: (1) high E% fat and protein; (2) high screen time and energy intake; (3) short sleep and high physical activity (4) long sleep and (5) low sedentary time. Compared with Cluster 1, zBMI was lower in Clusters 2 (-0.57 [-0.98; -0.17], p = 0.006), 3 (-0.48 [-0.81; -0.14], p = 0.005) and 5 (-0.50 [-0.83; -0.18], p = 0.003).

conclusionVarious lifestyle patterns support healthy body weight.

trial registrationClinicalTrials.gov identifier: NCT01881373.

Indexed as

DietExercisePediatric ObesitySleepBody Mass IndexChildChild, PreschoolFemaleHumansMaleSedentary Behaviorenergy balancemacronutrient compositionmovement behaviourphysical activityscreen timesleep

Identifiers

PMID39989394
PMCPMC12147416

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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.