Evidence map›Paper›PMID 28532446›Full record

ArticleBMC public health2017

Dual burden of malnutrition in US Affiliated Pacific jurisdictions in the Children's Healthy Living Program.

Rachel Novotny, Fenfang Li, Rachael Leon Guerrero, Patricia Coleman, Aifili J Tufa, Andrea Bersamin, Jonathan Deenik, Lynne R Wilkens

Registry-linked trialOpen access · goldAbstract readComparative StudyMulticenter Study
In one paragraph

Article in BMC public health, 2017. 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. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 1 pooled it
0.8field-weighted citation impact, top 27% 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.

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

9 citing papers in PubMed, 1 synthesis or guideline pooled it, 16 citations in OpenAlex.

  1. Pooled it
  2. Trial
  3. Article
  4. Article
  5. Article
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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

8 authors at 5 institutions in 3 countries.

Rachel NovotnyUniversity of Hawaii, 1955 East West Road, Honolulu, HI, 96822, USA. novotny@hawaii.edu.
Fenfang LiUniversity of Hawaii, 1955 East West Road, Honolulu, HI, 96822, USA.
Rachael Leon GuerreroUniversity of Guam, UOG Station, Mangilao, 96923, Guam.
Patricia ColemanNutrition & Health Programs, Building F, PO Box 501250, Saipan, MP, 96950, Northern Mariana Islands.
Aifili J TufaUniversity of Hawaii, 1955 East West Road, Honolulu, HI, 96822, USA.
Andrea BersaminUniversity of Alaska, AHRB, Fairbanks, AK, 228, USA.
Jonathan DeenikUniversity of Hawaii, 1955 East West Road, Honolulu, HI, 96822, USA.
Lynne R WilkensUniversity of Hawaii, UH Cancer Center, Honolulu, HI, USA.
University of Hawaii System · USCancer Center of Hawaii · USNorthern Marianas College · MPUniversity of Alaska Fairbanks · USUniversity of Guam · GU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundFew data are available on dual burden of under and over nutrition of children in the Pacific region. The objective was to examine prevalence of stunting at birth and current stunting and their relationship to obesity in US Affiliated Pacific (USAP) jurisdictions.

methodsCross sectional survey with cluster sampling by community. 5558, 2-8 years olds were measured in 51 communities in 11 USAP jurisdictions. The main outcome measures were stunting at birth, current stunting and obesity by body mass index. Prevalences of stunting at birth, current stunting and obesity were determined, adjusting for age distribution and community clustering. Differences by among age, sex, race and jurisdiction income levels were evaluated by chi-square analysis. Relationships of stunting at birth and current stunting with obesity were examined using a hierarchical model accounting for the study design.

resultsPrevalences were stunting at birth 6.8% (Standard Error, SE = 0.9%), current stunting 1.4% (SE = 0.2%) and obesity 14.03.8% (SE = 0.9%). Obesity was highest in upper middle income jurisdictions (UMIJ) at 17.5%. Stunting at birth differed by race (p = 0.0001) with highest prevalence among Native Hawaiian/Pacific Islanders (10.7%). Prevalence of stunting at birth was different by jurisdiction income level with 27.5% in lower middle income jurisdictions (LMIJ), and 22.2% in UMIJ, and 5.5% in higher than high income jurisdictions (HIJ) at 5.5% (p < 0.0001). Prevalence of current stunting was higher in LMIJ than HIJ (p = 0.001), although children with current stunting were less likely to have been stunted at birth. The association between stunting at birth and current stunting was negative (OR = 0.19, 95% CI: 0.05-0.69).

conclusionsCurrently stunted children were marginally less likely to be obese than not stunted children in the USAP, where the prevalence of current stunting is low. Stunting (at birth and current) was highest in LMIJ, while UMIJ jurisdictions had the highest dual burden of malnutrition (that is the highest combination of both stunting at birth and obesity).

trial registrationNational Institutes for Health clinical trial # NCT01881373 (clinicaltrials.gov).

Indexed as

Nutritional StatusAge FactorsChildChild, PreschoolCross-Sectional StudiesFemaleGrowth DisordersHumansMaleObesityPacific IslandsPrevalenceSex FactorsSocioeconomic FactorsCountryIncomeObesityPacificRaceStunting

Identifiers

PMID28532446
PMCPMC5440961
OpenAlexW2620278241

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.