Evidence map›Paper›PMID 24503301›Full record

ArticleBMJ open2014

Anthropometric measurements of general and central obesity and the prediction of cardiovascular disease risk in women: a cross-sectional study.

Louise G H Goh, Satvinder S Dhaliwal, Timothy A Welborn, Andy H Lee, Phillip R Della

Abstract read
In one paragraph

Article in BMJ open, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 61 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
61citing papers in PubMed, 1 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

61 citing papers in PubMed, 1 synthesis or guideline pooled it.

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  11. Association Between Neck-to-Limb Length Ratio and Cardiovascular Events in a Chinese Population.Diabetes, metabolic syndrome and obesity : targets and therapy · 2025
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1 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

5 authors.

Louise G H GohSchool of Public Health, Curtin Health Innovation Research Institute, Curtin University, Perth, Western Australia, Australia.
Satvinder S Dhaliwal
Timothy A Welborn
Andy H Lee
Phillip R Della

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesIt is important to ascertain which anthropometric measurements of obesity, general or central, are better predictors of cardiovascular disease (CVD) risk in women. 10-year CVD risk was calculated from the Framingham risk score model, SCORE risk chart for high-risk regions, general CVD and simplified general CVD risk score models. Increase in CVD risk associated with 1 SD increment in each anthropometric measurement above the mean was calculated, and the diagnostic utility of obesity measures in identifying participants with increased likelihood of being above the treatment threshold was assessed.

designCross-sectional data from the National Heart Foundation Risk Factor Prevalence Study.

settingPopulation-based survey in Australia.

participants4487 women aged 20-69 years without heart disease, diabetes or stroke. OUTCOME MEASURES: Anthropometric obesity measures that demonstrated the greatest increase in CVD risk as a result of incremental change, 1 SD above the mean, and obesity measures that had the greatest diagnostic utility in identifying participants above the respective treatment thresholds of various risk score models.

resultsWaist circumference (WC), waist-to-hip ratio (WHR) and waist-to-stature ratio had larger effects on increased CVD risk compared with body mass index (BMI). These central obesity measures also had higher sensitivity and specificity in identifying women above and below the 20% treatment threshold than BMI. Central obesity measures also recorded better correlations with CVD risk compared with general obesity measures. WC and WHR were found to be significant and independent predictors of CVD risk, as indicated by the high area under the receiver operating characteristic curves (>0.76), after controlling for BMI in the simplified general CVD risk score model.

conclusionsCentral obesity measures are better predictors of CVD risk compared with general obesity measures in women. It is equally important to maintain a healthy weight and to prevent central obesity concurrently.

Indexed as

Risk AssessmentAdultAgedAnthropometryAustraliaCardiovascular DiseasesCross-Sectional StudiesFemaleHumansMiddle AgedObesityObesity, AbdominalPredictive Value of TestsPrevalenceRisk FactorsEpidemiologyPublic Health

Identifiers

PMID24503301
PMCPMC3918987

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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.