Evidence map›Paper›PMID 29992765›Full record

Observational studyPediatric obesity2018

Community characteristics modify the relationship between obesity prevention efforts and dietary intake in children: the Healthy Communities Study.

G Woodward-Lopez, W Gosliner, L E Au, J Kao, K L Webb, R D Sagatov, W J Strauss, A J Landgraf, J Nagaraja, D K Wilson and 5 more

Open access · bronzeAbstract readObservational Study
In one paragraph

Observational study in Pediatric obesity, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
2.3field-weighted citation impact, top 12% 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

6 citing papers in PubMed, 14 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Observational
  5. Article
  6. Review
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

15 authors at 7 institutions in 1 country.

G Woodward-LopezNutrition Policy Institute, Division of Agriculture and Natural Resources, University of California, Berkeley, California, USA.ORCID 0000-0002-2745-1077
W GoslinerNutrition Policy Institute, Division of Agriculture and Natural Resources, University of California, Berkeley, California, USA.
L E AuNutrition Policy Institute, Division of Agriculture and Natural Resources, University of California, Berkeley, California, USA.
J KaoNutrition Policy Institute, Division of Agriculture and Natural Resources, University of California, Berkeley, California, USA.
K L WebbNutrition Policy Institute, Division of Agriculture and Natural Resources, University of California, Berkeley, California, USA.
R D SagatovBattelle Health and Analytics, Baltimore, Maryland, USA.ORCID 0000-0001-9524-4486
W J StraussHealth Analytics Hub, LLC, Lewis Center, Ohio, USA.
A J LandgrafBattelle Health and Analytics, Columbus, Ohio, USA.
J NagarajaBattelle Health and Analytics, Columbus, Ohio, USA.
D K WilsonDepartment of Psychology, University of South Carolina, Columbia, South Carolina, USA.
H L NicastroNational Heart, Lung, and Blood Institute, Bethesda, Maryland, USA.
L C NebelingNational Cancer Institute, Bethesda, Maryland, USA.
J A SchultzCenter for Community Health and Development, University of Kansas, Lawrence, Kansas, USA.ORCID 0000-0002-2325-958X
L D RitchieNutrition Policy Institute, Division of Agriculture and Natural Resources, University of California, Berkeley, California, USA.ORCID 0000-0002-8038-1821
Healthy Communities Study Team
University of California Division of Agriculture and Natural Resources · USBattelle · USEP Analytics (United States) · USNational Cancer Institute · USNational Heart Lung and Blood Institute · USUniversity of Kansas · USUniversity of South Carolina · US

Funding

NHLBI NIH HHS HHSN268201000041CNIH HHS HHSN268201000041C
6 · The paper itself

Abstract

backgroundThe influence of community characteristics on the effectiveness of childhood obesity prevention efforts is not well understood.

objectiveExamine the interaction of community characteristics with the relationship between community programmes and policies (CPPs) and dietary intake.

methodsAn observational study of 5138 children in grades K-8 in 130 US communities was conducted in 2013-2015. Key informant interviews identified and characterized CPPs. CPP scores were generated for the number of target behaviours (CPP-Behav) and the number of behaviour change strategies (CPP-Strat) addressed by all CPPs and CPPs with nutrition goals over the prior 6 years in each community. Dietary intake was assessed by dietary screener and included intake of sugar from sugar-sweetened beverages; energy-dense foods; fruits and vegetables; whole grains; and fibre. Multivariate statistical models assessed the interactions between US region, urbanicity, community-level income, and community-level race/ethnicity and CPP scores in relation to dietary intake.

resultsCPP-Strat was positively associated with healthier dietary intakes in the Northeast and West, and in high Hispanic communities; the reverse was true in the South, and in high African-American and low-income communities. The CPP-Behav was positively associated with healthier dietary intakes in the South and rural areas, and the reverse was true in the West.

conclusionThe relationships between CPP index scores and dietary intake were most strongly influenced by region and urbanicity and to a lesser extent by community-level race/ethnicity and income. Findings suggest that different considerations may be needed for childhood obesity prevention efforts in communities with different characteristics.

Indexed as

Feeding BehaviorAdolescentChildChild, PreschoolDietFemaleHumansMalePediatric ObesityPreventive Health ServicesPublic HealthResidence CharacteristicsSocial ClassUnited Stateschildhoodnutritionobesitypolicy

Identifiers

PMID29992765
PMCPMC6382075
OpenAlexW2872032891

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.