Evidence map›Paper›PMID 32919827›Full record

ArticleAmerican journal of preventive medicine2020

Identification of Measurement Needs to Prevent Childhood Obesity in High-Risk Populations and Environments.

Kathryn E Foti, Crystal L Perez, Emily A Knapp, Anna Y Kharmats, Amanda S Sharfman, S Sonia Arteaga, Latetia V Moore, Wendy L Bennett

Open access · greenAbstract read
In one paragraph

Article in American journal of preventive medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.6field-weighted citation impact, top 15% 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

7 citing papers in PubMed, 12 citations in OpenAlex.

  1. Trial
  2. Article
  3. Article
  4. Article
  5. Article
  6. Desafíos de medición para la investigación de la obesidad infantil en y entre América Latina y Estados Unidos.Obesity reviews : an official journal of the International Association for the Study of Obesity · 2021
    Article
  7. Measurement challenges for childhood obesity research within and between Latin America and the United States.Obesity reviews : an official journal of the International Association for the Study of Obesity · 2021
    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 1 country.

Kathryn E FotiDepartment of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland.
Crystal L PerezDepartment of Health Policy and Management, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland.
Emily A KnappDepartment of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland.
Anna Y KharmatsDepartment of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland.
Amanda S SharfmanFHI 360, Washington, District of Columbia.
S Sonia ArteagaEnvironmental influences on Child Health Outcomes, Office of the Director, NIH, formerly at the Division of Cardiovascular Diseases, National, Heart, Lung, and Blood Institute, NIH, Bethesda, Maryland.
Latetia V MooreDivision of Nutrition, Physical Activity, and Obesity, Centers for Disease Control and Prevention, Atlanta, Georgia.
Wendy L BennettDepartment of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland; Department of Epidemiology and Population, Johns Hopkins University School of Medicine, Baltimore, Maryland; Department of Family and Reproductive Health, Johns Hopkins University School of Medicine, Baltimore, Maryland. Electronic address: wendy.bennett@jhmi.edu.
Johns Hopkins University · USCenters for Disease Control and Prevention · USFamily Health International 360 · USNational Heart Lung and Blood Institute · US

Funding

Intramural CDC HHS CC999999
6 · The paper itself

Abstract

introductionChildren at highest obesity risk include those from certain racial/ethnic groups, from low-income families, with disabilities, or living in high-risk communities. However, a 2013 review of the National Collaborative for Childhood Obesity Research Measures Registry identified few measures focused on children at highest obesity risk. The objective is to (1) identify individual and environmental measures of diet and physical activity added to the Measures Registry since 2013 used among high-risk populations or settings and (2) describe methods for their development, adaptation, or validation.

methodsInvestigators screened references in the Measures Registry from January 2013 to September 2017 (n=351) and abstracted information about individual and environmental measures developed for, adapted for, or applied to high-risk populations or settings, including measure type, study population, adaptation and validation methods, and psychometric properties.

resultsA total of 38 measures met inclusion criteria. Of these, 30 assessed individual dietary (n=25) or physical activity (n=13) behaviors, and 11 assessed the food (n=8) or physical activity (n=7) environment. Of those, 17 measures were developed for, 9 were applied to (i.e., developed in a general population and used without modification), and 12 were adapted (i.e., modified) for high-risk populations. Few measures were used in certain racial/ethnic groups (i.e., American Indian/Alaska Native, Hawaiian/Pacific Islander, and Asian), children with disabilities, and rural (versus urban) communities.

conclusionsSince 2013, a total of 38 measures were added to the Measures Registry that were used in high-risk populations. However, many of the previously identified gaps in population coverage remain. Rigorous, community-engaged methodologic research may help researchers better adapt and validate measures for high-risk populations.

Indexed as

Pediatric ObesityAlaskaChildDietHumansPovertyRisk Factors

Identifiers

PMID32919827
PMCPMC8722431
OpenAlexW3083961545

What OpenQuestion holds

Textmetadata
LicenceTDM
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.