Evidence mapPaperPMID 29150468Full record

ArticleBMJ open2017

Prevalence and recognition of obesity and its associated comorbidities: cross-sectional analysis of electronic health record data from a large US integrated health system.

Kevin M Pantalone, Todd M Hobbs, Kevin M Chagin, Sheldon X Kong, Brian J Wells, Michael W Kattan, Jonathan Bouchard, Brian Sakurada, Alex Milinovich, Wayne Weng and 4 more

Abstract readMulticenter Study
In one paragraph

Article in BMJ open, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 102 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
102citing papers in PubMed, 4 pooled it
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

102 citing papers in PubMed, 4 syntheses or guidelines pooled it.

  1. Effects of total diet replacement programs on mental well-being: A systematic review with meta-analyses.Obesity reviews : an official journal of the International Association for the Study of Obesity · 2022
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  18. The Economic Cost of Obesity: A Cost-of-Illness Study in Greece.Applied health economics and health policy · 2026
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42 more citing papers are in PubMed but not listed here.

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

14 authors.

Kevin M PantaloneEndocrinology and Metabolism Institute, Cleveland Clinic, Cleveland, Ohio, USA.
Todd M HobbsDiabetes, Novo Nordisk Inc., Plainsboro, New Jersey, USA.
Kevin M ChaginQuantitative Health Sciences, Cleveland Clinic, Cleveland, Ohio, USA.
Sheldon X KongHealth Economics and Outcomes Research, Novo Nordisk Inc., Plainsboro, New Jersey, USA.
Brian J WellsTranslational Science Institute, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA.
Michael W KattanQuantitative Health Sciences, Cleveland Clinic, Cleveland, Ohio, USA.
Jonathan BouchardHealth Economics and Outcomes Research, Novo Nordisk Inc., Plainsboro, New Jersey, USA.
Brian SakuradaMedical Affairs, Novo Nordisk Inc., Plainsboro, New Jersey, USA.
Alex MilinovichQuantitative Health Sciences, Cleveland Clinic, Cleveland, Ohio, USA.
Wayne WengHealth Economics and Outcomes Research, Novo Nordisk Inc., Plainsboro, New Jersey, USA.
Janine BaumanQuantitative Health Sciences, Cleveland Clinic, Cleveland, Ohio, USA.
Anita D Misra-HebertMedicine Institute, Cleveland Clinic, Cleveland, Ohio, USA.
Robert S ZimmermanEndocrinology and Metabolism Institute, Cleveland Clinic, Cleveland, Ohio, USA.
Bartolome BurgueraEndocrinology and Metabolism Institute, Cleveland Clinic, Cleveland, Ohio, USA.

Funding

AHRQ HHS K08 HS024128
6 · The paper itself

Abstract

objectiveTo determine the prevalence of obesity and its related comorbidities among patients being actively managed at a US academic medical centre, and to examine the frequency of a formal diagnosis of obesity, via International Classification of Diseases, Ninth Revision (ICD-9) documentation among patients with body mass index (BMI) ≥30 kg/m

designThe electronic health record system at Cleveland Clinic was used to create a cross-sectional summary of actively managed patients meeting minimum primary care physician visit frequency requirements. Eligible patients were stratified by BMI categories, based on most recent weight and median of all recorded heights obtained on or before the index date of 1July 2015. Relationships between patient characteristics and BMI categories were tested.

settingA large US integrated health system.

resultsA total of 324 199 active patients with a recorded BMI were identified. There were 121 287 (37.4%) patients found to be overweight (BMI ≥25 and <29.9), 75 199 (23.2%) had BMI 30-34.9, 34 152 (10.5%) had BMI 35-39.9 and 25 137 (7.8%) had BMI ≥40. There was a higher prevalence of type 2 diabetes, pre-diabetes, hypertension and cardiovascular disease (P value<0.0001) within higher BMI compared with lower BMI categories. In patients with a BMI >30 (n=134 488), only 48% (64 056) had documentation of an obesity ICD-9 code. In those patients with a BMI >40, only 75% had an obesity ICD-9 code.

conclusionsThis cross-sectional summary from a large US integrated health system found that three out of every four patients had overweight or obesity based on BMI. Patients within higher BMI categories had a higher prevalence of comorbidities. Less than half of patients who were identified as having obesity according to BMI received a formal diagnosis via ICD-9 documentation. The disease of obesity is very prevalent yet underdiagnosed in our clinics. The under diagnosing of obesity may serve as an important barrier to treatment initiation.

Indexed as

Body Mass IndexElectronic Health RecordsAcademic Medical CentersAdultCerebrovascular DisordersComorbidityCoronary Artery DiseaseCross-Sectional StudiesDelivery of Health Care, IntegratedDiabetes MellitusHeart FailureHumansHypertensionMaleMiddle AgedObesitybody mass indexdiagnosiselectronic health recordsintegrated delivery systemobesity

Identifiers

PMID29150468
PMCPMC5702021

What Socratic holds

Textmetadata
LicenceCC BY-NC
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 Socratic graph.