Evidence map›Paper›PMID 29402536›Full record

ArticleAnnals of epidemiology2018

A demographic, clinical, and behavioral typology of obesity in the United States: an analysis of National Health and Nutrition Examination Survey 2011-2012.

Marcia P Jimenez, Mark A Green, S V Subramanian, Fahad Razak

Abstract read
In one paragraph

Article in Annals of epidemiology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

4 authors.

Marcia P JimenezDepartment of Epidemiology, Brown School of Public Health, Brown University, Providence, RI.
Mark A GreenDepartment of Geography & Planning, University of Liverpool, Liverpool, UK.
S V SubramanianDepartment of Social and Behavioral Sciences, Harvard School of Public Health, Boston, MA; Harvard Centre for Population and Development Studies, Harvard University, Cambridge, MA.
Fahad RazakLi Ka Shing Knowledge Institute of St Michael's Hospital, Toronto, ON, Canada; St Michael's Hospital, University of Toronto and Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, ON, Canada; Harvard Centre for Population and Development Studies, Harvard University, Cambridge, MA. Electronic address: fahad.razak@mail.utoronto.ca.

Funding

TRAINING IN DEMOGRAPHYT32HD007338 · NICHD · BROWN UNIVERSITY · PI ANDREW D. FOSTER · 1987 to 2026
$7.0M
Sensitive Periods: Prospective Associations of Childhood and Adulthood Neighborhoods with Life Course Obesity and Blood Presure TrajectoriesF31HL134300 · NHLBI · BROWN UNIVERSITY · PI PESCADOR JIMENEZ, MARCIA IXCHEL · 2016 to 2018
$56k
NHLBI NIH HHS F31 HL134300NICHD NIH HHS T32 HD007338
6 · The paper itself

Abstract

purposePublic health reporting, randomized trials, and epidemiologic studies of obesity tend to consider it as a homogeneous entity. However, obesity may represent a heterogeneous condition according to demographic, clinical, and behavioral factors. We assessed the heterogeneity of individuals with obesity in the United States.

methodsWe analyzed data from the 2011-2012 wave of the National Health and Nutrition Examination Survey, a nationally representative sample of adults in the United States with detailed physical examination and clinical data (n = 1380). We used cluster analysis to identify subgroups classified as obese according to demographic factors, clinical conditions, and behavioral characteristics.

resultsWe found significant heterogeneity among participants with obesity according to six distinct clusters (P < .001): affluent men with sleep disorders (16% of sample); older smokers with cardiovascular disease (16%); older women with high comorbidity (20%); healthy white women (13%); healthy non-white women (14%); and active men who drink higher amounts of alcohol (21%).

conclusionsObesity in the United States is not a homogeneous condition. Current research and treatment may fail to account for complex and interrelated factors, with implications for prevention strategies and diverse risks of obesity.

Indexed as

Body Mass IndexNutrition SurveysAdultAgedCardiovascular DiseasesCluster AnalysisComorbidityDemographyFemaleHumansMaleMiddle AgedObesityPopulation SurveillanceUnited StatesBody mass indexCluster analysisObesityPopulation heterogeneity

Identifiers

PMID29402536
PMCPMC5986075

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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.