Evidence map›Paper›PMID 35732401›Full record

ArticleBMJ open2022

Development and internal validation of the Edmonton Obesity Staging System-2 Risk screening Tool (EOSS-2 Risk Tool) for weight-related health complications: a case-control study in a representative sample of Australian adults with overweight and obesity.

Evan Atlantis, James Rufus John, S L Hocking, Kath Peters, Kathryn Williams, Paul Dugdale, P Fahey

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

Article in BMJ open, 2022. 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
1.4field-weighted citation impact, top 18% 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

4 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Deep phenotyping obesity using EHR data: Promise, Challenges, and Future Directions.medRxiv : the preprint server for health sciences · 2024
    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

7 authors at 4 institutions in 1 country.

Evan AtlantisSchool of Health Sciences, Western Sydney University, Penrith South, New South Wales, Australia E.Atlantis@westernsydney.edu.au.ORCID 0000-0001-5877-6141
James Rufus JohnDiscipline of Psychiatry and Mental Health, School of Clinical Medicine, University of New South Wales, Sydney, New South Wales, Australia.
S L HockingThe Boden Collaboration for Obesity, Nutrition, Exercise & Eating Disorders, Charles Perkins Centre, University of Sydney, Sydney, New South Wales, Australia.
Kath PetersSchool of Health Sciences, Western Sydney University, Penrith South, New South Wales, Australia.
Kathryn WilliamsCharles Perkins Centre - Nepean, The University of Sydney, Nepean, New South Wales, Australia.
Paul DugdaleCollege of Health and Medicine, Australian National University, Canberra, Australian Capital Territory, Australia.
P FaheySchool of Health Sciences, Western Sydney University, Penrith South, New South Wales, Australia.ORCID 0000-0002-6351-9876
The University of Sydney · AUWestern Sydney University · AUAustralian National University · AUUNSW Sydney · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveExcess weight and related health complications remain under diagnosed and poorly treated in general practice. We aimed to develop and validate a brief screening tool for determining the presence of unknown clinically significant weight-related health complications for potential application in general practice.

designWe considered 14 self-reported candidate predictors of clinically significant weight-related health complications according to the Edmonton Obesity Staging System (EOSS score of ≥2) and developed models using multivariate logistic regression across training and test data sets. The final model was chosen based on the area under the receiver operating characteristic curve and the Hosmer-Lemeshow statistic; and validated using sensitivity, specificity and positive predictive value. SETTING AND

participantsWe analysed cross-sectional data from the Australian Health Survey 2011-2013 sample aged between 18 and 65 years (n=7518) with at least overweight and obesity.

resultsAn EOSS≥2 classification was present in 78% of the sample. Of 14 candidate risk factors, 6 (family history of diabetes, hypertension, high sugar in blood/urine, high cholesterol and self-reported bodily pain and disability) were automatically included based on definitional or obvious correlational criteria. Three variables were retained in the final multivariate model (age, self-assessed health and history of depression/anxiety). The EOSS-2 Risk Tool (index test) classified 89% of those at 'extremely high risk' (≥25 points), 67% of those at 'very high risk' (7-24 points) and 42% of those at 'high risk' (<7 points) of meeting diagnostic criteria for EOSS≥2 (reference).

conclusionThe EOSS-2 Risk Tool is a simple, safe and accurate screening tool for diagnostic criteria for clinically significant weight-related complications for potential application in general practice. Research to determine the feasibility and applicability of the EOSS-2 Risk Tool for improving weight management approaches in general practice is warranted.

Indexed as

ObesityOverweightAdolescentAdultAgedAustraliaBody Mass IndexCase-Control StudiesCross-Sectional StudiesHumansMiddle AgedRisk FactorsYoung Adultdiabetes & endocrinologygeneral medicine (see internal medicine)preventive medicineprimary care

Identifiers

PMID35732401
PMCPMC9226953
OpenAlexW4283267635

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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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.