Evidence map›Paper›PMID 38072192›Full record

ArticleContemporary clinical trials2024

Studying the impact of COVID-19 mitigation policies on childhood obesity, health behaviors, and disparities in an observational cohort: Protocol for the COVID-19 Family Study.

Nan Dou, Rachel Deitch, Alysse J Kowalski, Ann Kuhn, Hannah Lane, Elizabeth A Parker, Yan Wang, Zafar Zafari, Maureen M Black, Erin R Hager

Open access · greenAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Contemporary clinical trials, 2024. 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
3.1field-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

3 citing papers in PubMed, 7 citations in OpenAlex.

  1. Article
  2. Article
  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

10 authors at 6 institutions in 1 country.

Nan DouDepartment of Population, Family and Reproductive Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, 615 N Wolfe St, MD 21205, USA. Electronic address: ndou1@jhu.edu.
Rachel DeitchDepartment of Population, Family and Reproductive Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, 615 N Wolfe St, MD 21205, USA. Electronic address: rdeitch1@jhu.edu.
Alysse J KowalskiDepartment of Population, Family and Reproductive Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, 615 N Wolfe St, MD 21205, USA. Electronic address: akowals7@jhu.edu.
Ann KuhnDepartment of Exercise and Nutrition Sciences, University at Buffalo, The State University of New York, 401 Kimball Tower, Buffalo, NY 14214, USA. Electronic address: annkuhn@buffalo.edu.
Hannah LaneDepartment of Population Health Sciences, Duke University School of Medicine, 215 Morris Street, Durham, NC 27701, USA. Electronic address: hannah.lane@duke.edu.
Elizabeth A ParkerUniversity of Maryland School of Medicine, Department of Physical Therapy and Rehabilitation Science, 100 Penn Street, Baltimore, MD 21201, USA. Electronic address: Elizabeth.parker@som.umaryland.edu.
Yan WangDepartment of Prevention and Community Health, Milken Institute School of Public Health, The George Washington University, 950 New Hampshire Avenue, NW, Washington, DC 20052, USA. Electronic address: yanwang20@gwu.edu.
Zafar ZafariDepartment of Practice, Sciences, and Health Outcomes Research, University of Maryland School of Pharmacy, 20 North Pine Street, Baltimore, MD 21201, USA. Electronic address: zzafari@rx.umaryland.edu.
Maureen M BlackUniversity of Maryland School of Medicine, Department of Pediatrics, 737 West Lombard Street, Baltimore, MD 21201, USA; RTI International, Research Triangle Park, NC 27709, USA. Electronic address: mblack@som.umaryland.edu.
Erin R HagerDepartment of Population, Family and Reproductive Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, 615 N Wolfe St, MD 21205, USA. Electronic address: ehager1@jhmi.edu.
Johns Hopkins University · USUniversity of Maryland, Baltimore · USDuke University · USGeorge Washington University · USRTI International · USUniversity at Buffalo, State University of New York · US

Funding

QAQC Johns Hopkins Institute for Clinical and Translational ResearchUL1TR003098 · NCATS · JOHNS HOPKINS UNIVERSITY · PI FORD, DANIEL ERNEST · 2019 to 2023
$57.7M
Research BaseP30DK072488 · NIDDK · UNIVERSITY OF MARYLAND BALTIMORE · PI MITCHELL, BRAXTON D · 2005 to 2019
$17.3M
COVID-19 Policies: Impact Over Time on Child Health, Obesity, and DisparitiesR01HD105356 · NICHD · UNIVERSITY OF MARYLAND BALTIMORE · PI HAGER, ERIN R · 2021 to 2024
$2.7M
Building Blocks for Healthy Preschoolers: Child Care and Family ModelsR01DK107761 · NIDDK · UNIVERSITY OF MARYLAND BALTIMORE · PI BLACK, MAUREEN M · 2016 to 2019
$2.6M
NCATS NIH HHS UL1 TR003098NICHD NIH HHS R01 HD105356NIDDK NIH HHS P30 DK072488NIDDK NIH HHS R01 DK107761
6 · The paper itself

Abstract

backgroundCOVID-19 pandemic control policies, including school closures, suspended extra-curricular activities, and social distancing, were introduced to prevent viral transmission, and disrupted children's daily routines, health behaviors, and wellness. This observational cohort study among 697 families with children or adolescents, based on the Family Stress Model, aims to: 1) evaluate pre- to during-pandemic changes in child health behaviors (diet, physical activity, sleep) and weight gain, 2) identify mechanisms explaining the changes, and 3) determine projected healthcare costs on weight gain and obesity. Each aim includes an examination by racial and ethnic, socioeconomic, and geographic disparities.

methodsThe study employs a mixed methods design, recruiting children and their caregivers from two obesity prevention trials halted in 2020. Enrolled participants complete annual surveys to assess child health behaviors, family resources, routines, and demographics, and home environment in 2020-2022. Height and weight are measured annually in 2021-2022. Annual semi-structured interviews are conducted within a subsample to understand mechanisms of observed changes. Multilevel mixed models and mediation analyses are used to examine changes in child health behaviors and weight gain and mechanisms underlying the changes. Qualitative data are analyzed within and across time points and integrated with quantitative findings to further explain mechanisms. Markov models are used to determine healthcare costs for unhealthy child behaviors and weight gain.

conclusionFindings from this study will aid in understanding pandemic-related changes in child health behaviors and weight status and will provide insights for the implementation of future programs and policies to improve child and family wellness.

Indexed as

COVID-19Pediatric ObesityAdolescentChildHealth BehaviorHumansObservational Studies as TopicPandemicsWeight GainChild, adolescentsChild health behaviorsChildhood overweight/obesityCOVID-19 pandemic policiesHealthcare costsHealth disparities

Identifiers

PMID38072192
PMCPMC10922699
OpenAlexW4389513772

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.