Evidence map›Paper›PMID 22836530›Full record

ArticleJournal of public health management and practice : JPHMP

Where is obesity prevention on the map?: distribution and predictors of local health department prevention activities in relation to county-level obesity prevalence in the United States.

Katherine A Stamatakis, Scott T Leatherdale, Christine M Marx, Yan Yan, Graham A Colditz, Ross C Brownson

Abstract read
In one paragraph

Article in Journal of public health management and practice : JPHMP. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing 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.

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

16 citing papers in PubMed.

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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

6 authors.

Katherine A StamatakisDivision of Public Health Sciences, Department of Surgery, Washington University School of Medicine, St Louis, Missouri 63110, USA. stamatakisk@wustl.edu
Scott T Leatherdale
Christine M Marx
Yan Yan
Graham A Colditz
Ross C Brownson

Funding

Washington University Institute of Clinical and Translational Sciences (UL1)UL1RR024992 · NCRR · WASHINGTON UNIVERSITY · PI EVANOFF, BRADLEY A · 2007 to 2011
$45.4M
Washington University Institute of Clinical and Translational SciencesUL1TR000448 · NCATS · WASHINGTON UNIVERSITY · PI EVANOFF, BRADLEY A · 2012 to 2016
$41.4M
Washington University Center for Diabetes Translation Research P30DK092950 · NIDDK · WASHINGTON UNIVERSITY · PI Ross C Brownson, Debra Haire-Joshu · 2011 to 2026
$11.7M
Washington University Institute of Clinical and Translational SciencesKL2TR000450 · NCATS · WASHINGTON UNIVERSITY · PI EVANOFF, BRADLEY A · 2012 to 2016
$8.8M
Washington University Institute of Clinical and Translational Sciences (KL2)KL2RR024994 · NCRR · WASHINGTON UNIVERSITY · PI EVANOFF, BRADLEY A · 2007 to 2011
$8.6M
Health Promotion and Disease Prevention Research Center*U48DP000060 · DP · SAINT LOUIS UNIVERSITY · PI BAKER, ELIZABETH A · 2004 to 2008
$6.1M
NCATS NIH HHS KL2 TR000450NCATS NIH HHS UL1 TR000448NCCDPHP CDC HHS DP000060-04NCCDPHP CDC HHS U48 DP000060NCCDPHP CDC HHS U48/DP000060NCRR NIH HHS KL2 RR024994NCRR NIH HHS UL1 RR024992NCRR NIH HHS UL1RR024992NIDDK NIH HHS P30 DK092950
6 · The paper itself

Abstract

contextThe system of local health departments (LHDs) in the United States has the potential to advance a locally oriented public health response in obesity control and reduce geographic disparities. However, the extent to which obesity prevention programs correspond to local obesity levels is unknown.

objectiveThis study examines the extent to which LHDs across the United States have responded to local levels of obesity by examining the association between jurisdiction-level obesity prevalence and the existence of obesity prevention programs.

designData on LHD organizational characteristics from the Profile Study of Local Health Departments and county-level estimates of obesity from the Behavioral Risk Factor Surveillance System were analyzed (n = 2300). Since local public health systems are nested within state infrastructure, multilevel models were used to examine the relationship between county-level obesity prevalence and LHD obesity prevention programming and to assess the impact of state-level clustering.

settingTwo thousand three hundred local health department jurisdictions defined with respect to county boundaries.

participantsPractitioners in local health departments who responded to the 2005 Profile Study of Local Health Departments.

main outcome measuresLikelihood of having obesity prevention activities and association with area-level obesity prevalence.

resultsThe existence of obesity prevention activities was not associated with the prevalence of obesity in the jurisdiction. A substantial portion of the variance in LHD activities was explained by state-level clustering.

conclusionsThis article identified a gap in the local public health response to the obesity epidemic and underscores the importance of multilevel modeling in examining predictors of LHD performance.

Indexed as

Health Planning GuidelinesInterinstitutional RelationsLocal GovernmentPublic Health AdministrationCatchment Area, HealthCommunity NetworksEvidence-Based PracticeHealth Care SurveysHealth Plan ImplementationHealth PromotionHealth Status DisparitiesHumansObesityPrevalenceProgram EvaluationResidence Characteristics

Identifiers

PMID22836530
PMCPMC3711616

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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.