Definition and research guide
This page combines a MeSH definition, publication statistics and selected research abstracts. It is a starting point for reading the literature, not a medical textbook or a systematic evidence review.
Content available: 4 complete abstracts (857 words), 10 references. Full article text is not stored or reproduced here; follow the PMID, DOI or PMC links to read the original sources and their access terms.
Definition
The measurement around the body at the level of the abdomen and just above the hip bone. The measurement is usually taken immediately after exhalation.
Definition: NLM Medical Subject Headings (MeSH) scope note (Public domain (U.S. National Library of Medicine); attribution requested). View the MeSH record.
Also known as: Circumferences, Waist; Circumference, Waist; Waist Circumferences.
Where it fits in the MeSH classification
- Broader topics
- Body Size
- Narrower topics
- Lipid Accumulation Product
- See also
- Waist-Hip Ratio; Sagittal Abdominal Diameter
Related concepts
- Abdomen
Research landscape
PubMed indexes 15,578 records tagged with the MeSH heading “Waist Circumference” (counts retrieved 2026-10-31). 5,106 of them (32.8%) were published from 2020 onward, and the busiest period so far is 2010-2019 with 9,739 records.
Reviews account for 759 records (4.9%) and meta-analyses for 465. Randomized controlled trials number 1,251 (8.0%) as a share of all records on the topic. Randomized trials make up a comparatively large share of this literature, which means many treatment questions have been tested directly.
Show the data
| Period | Records |
|---|---|
| through 1999 | 0 |
| 2000-2009 | 1,064 |
| 2010-2019 | 9,739 |
| 2020 onward | 5,106 |
Publication-type chart data
| Type | Records | Share |
|---|---|---|
| Reviews | 759 | 4.9% |
| Meta-analyses | 465 | 3.0% |
| Randomized controlled trials | 1,251 | 8.0% |
Method: PubMed query "Waist Circumference"[MeSH Terms] with publication-type and date filters, retrieved 2026-10-31.
Reading the evidence in anatomy and physiology
Anatomy describes how body structures are built and physiology describes how they normally work, so most findings here are descriptive or mechanistic rather than evidence about treatment. Much of what is known comes from dissection, imaging, tissue studies and experiments in animals, and measurements in healthy volunteers can differ from those in people with disease or at different ages. Normal ranges vary between individuals and populations. Check whether a result was measured in people or in another species, the age and health of the participants, and the method used.
Evidence from open-access studies
These open-access studies come from PubMed’s best-match results for this heading (papers whose main topic it is), ranked here by citation count, with one recent addition. Each abstract is reproduced in full under its recorded open licence so that you can read the authors’ own words. They illustrate the literature; they are not a systematic summary of it. Citation counts measure attention, not reliability or clinical benefit.
Association between triglyceride-glucose related indices with the all-cause and cause-specific mortality among the population with metabolic syndrome [1]
Abstract reading summary — source excerpts
- Opening excerpt
- BackgroundTriglyceride-glucose (TyG) index has been determined to play a role in the onset of metabolic syndrome (MetS).
- Closing excerpt
- TyG-related indices would be the surrogate biomarkers for the follow-up of the MetS population.
- Interpretation limits
- Verbatim excerpts from the authors’ abstract; the closing excerpt may describe a finding, limitation or recommendation. Design, population, effect size and uncertainty have not been independently extracted or appraised. Read the complete abstract and linked paper before interpreting the findings.
Read complete abstract (226 words)
BackgroundTriglyceride-glucose (TyG) index has been determined to play a role in the onset of metabolic syndrome (MetS). Whether the TyG index and TyG with the combination of obesity indicators are associated with the clinical outcomes of the MetS population remains unknown.MethodParticipants were extracted from multiple cycles of the National Health and Nutrition Examination Survey (NHANES) between 1999 and 2018 years. Three indicators were constructed including TyG index, TyG combining with waist circumference (TyG-WC), and TyG combining with waist-to-height ratio (TyG-WHtR). The MetS was defined according to the National Cholesterol Education Program (NCPE) Adult Treatment Panel III. Kaplan-Meier (KM) curves, restricted cubic splines (RCS), and the Cox proportional hazard model were used to evaluate the associations between TyG-related indices and mortality of the MetS population. The sensitive analyses were performed to check the robustness of the main findings.ResultsThere were 10,734 participants with MetS included in this study, with 5,570 females and 5,164 males. The median age of the study population was 59 years old. The multivariate Cox regression analyses showed high levels of TyG-related indices were significantly associated with the all-cause mortality of MetS population [TyG index: adjustedhazard ratio (aHR): 1.36, 95%confidence interval (CI): 1.18-1.56, p ConclusionOur study highlights the clinical value of TyG-related indices in predicting the survival of the MetS population. TyG-related indices would be the surrogate biomarkers for the follow-up of the MetS population.
Abstract reproduced from the open-access article under the recorded cc by licence; © the authors. PMID 38658993 · DOI · PMC11044377
Strong Association of Waist Circumference (WC), Body Mass Index (BMI), Waist-to-Height Ratio (WHtR), and Waist-to-Hip Ratio (WHR) with Diabetes: A Population-Based Cross-Sectional Study in Jilin Province, China [2]
Abstract reading summary — source excerpts
- Opening excerpt
- BackgroundsThe prevalence of diabetes has increased with the increase of obesity, and finding indicators to predict diabetes risk has become an urgent need.
- Closing excerpt
- ConclusionsThe WC and WHtR were more closely related to diabetes than BMI and WHR among study participants ≥ 40 years of age, especially in females.
- Interpretation limits
- Verbatim excerpts from the authors’ abstract; the closing excerpt may describe a finding, limitation or recommendation. Design, population, effect size and uncertainty have not been independently extracted or appraised. Read the complete abstract and linked paper before interpreting the findings.
Read complete abstract (225 words)
BackgroundsThe prevalence of diabetes has increased with the increase of obesity, and finding indicators to predict diabetes risk has become an urgent need. The purpose of this study is to compare the correlation between four anthropometric indices and the prevalence of diabetes.MethodsA total of 4052 participants aged 40 years and above were selected in Dehui City, Jilin Province, using a multistage stratified whole group sampling method. Face-to-face interviews and physical examinations were conducted. Multivariate logistic analysis was used. The values of BMI, waist circumference (WC), waist-to-hip ratio (WHR), and waist-to-height ratio (WHtR) were divided into quartiles (Q1: ResultsFor all four body fat-measuring indices of body mass index (adjusted OR: 3.300, 95% CI: 2.370, 4.595), WC (adjusted OR: 5.131, 95% CI: 3.433, 7.669), WHR (adjusted OR: 3.327, 95% CI: 2.386, 4.638), and WHtR (adjusted OR: 5.959, 95% CI: 3.922, 9.054), patients in the highest quartile were more likely to have diabetes than those in the lowest quartile. The areas under the curve of WHtR, WC, WHR, and BMI for diabetes were 0.683, 0.669, 0.654, and 0.629, respectively. In female participants, the areas under the curve of the waist-height ratio and WC were 0.710 (95% CI: 0.679-0.741) and 0.701 (95% CI: 0.670-0.732), respectively.ConclusionsThe WC and WHtR were more closely related to diabetes than BMI and WHR among study participants ≥ 40 years of age, especially in females.
Abstract reproduced from the open-access article under the recorded cc by licence; © the authors. PMID 34056007 · DOI · PMC8147550
Association between obstructive sleep apnea and visceral adiposity index and lipid accumulation product: NHANES 2015-2018 [3]
Abstract reading summary — source excerpts
- Opening excerpt
- BackgroundObesity refers to a significant contributor to the development of obstructive sleep apnea (OSA).
- Closing excerpt
- Subgroup analysis revealed a stronger correlation between LAP, VAI levels, and OSA among individuals aged ConclusionThis study demonstrates that elevated levels of LAP and VAI increase the risk of OSA, suggesting their potential as predictive markers for OSA and advocating for dietary and exercise interventions to mitigate OSA risk in individuals with high LAP and VAI levels.
- Interpretation limits
- Verbatim excerpts from the authors’ abstract; the closing excerpt may describe a finding, limitation or recommendation. Design, population, effect size and uncertainty have not been independently extracted or appraised. Read the complete abstract and linked paper before interpreting the findings.
Read complete abstract (211 words)
BackgroundObesity refers to a significant contributor to the development of obstructive sleep apnea (OSA). Early prediction of OSA usually leads to better treatment outcomes, and this study aims to employ novel metabolic markers, visceral adiposity index (VAI), and lipid accumulation product (LAP) to evaluate the relationship to OSA.MethodsThe data used in the current cross-sectional investigation are from the National Health and Nutrition Examination Survey (NHANES), which was carried out between 2015 and 2018. To examine the correlation between LAP and VAI levels and OSA, multivariate logistic regression analysis was adopted. In addition, various analytical methods were applied, including subgroup analysis, smooth curve fitting, and threshold effect analysis.ResultsAmong totally 3932 participants, 1934 were included in the OSA group. The median (Q1-Q3) values of LAP and VAI for the participants were 40.25 (21.51-68.26) and 1.27 (0.75-2.21), respectively. Logistic regression studies indicated a positive correlation between LAP, VAI, and OSA risk after adjusting for potential confounding variables. Subgroup analysis revealed a stronger correlation between LAP, VAI levels, and OSA among individuals aged ConclusionThis study demonstrates that elevated levels of LAP and VAI increase the risk of OSA, suggesting their potential as predictive markers for OSA and advocating for dietary and exercise interventions to mitigate OSA risk in individuals with high LAP and VAI levels.
Abstract reproduced from the open-access article under the recorded cc by licence; © the authors. PMID 38600516 · DOI · PMC11005189
Diagnostic Performance of BMI and Waist Circumference in Detecting Excess Adiposity [4]
Abstract reading summary — source excerpts
- Opening excerpt
- ObjectiveThis study compared the diagnostic performance of BMI, waist circumference (WC), and Lancet Commission (LC) criteria for assessing excess adiposity measured by dual-energy X-ray absorptiometry (DEXA) in US adults.
- Closing excerpt
- Incorporating WC into screening may improve the detection of excess adiposity.
- Interpretation limits
- Verbatim excerpts from the authors’ abstract; the closing excerpt may describe a finding, limitation or recommendation. Design, population, effect size and uncertainty have not been independently extracted or appraised. Read the complete abstract and linked paper before interpreting the findings.
Read complete abstract (195 words)
ObjectiveThis study compared the diagnostic performance of BMI, waist circumference (WC), and Lancet Commission (LC) criteria for assessing excess adiposity measured by dual-energy X-ray absorptiometry (DEXA) in US adults.MethodsUsing 2011-2018 NHANES data, we included 10,747 adults aged 20-59 years with relevant data. We evaluated the diagnostic performance (sensitivity, specificity, positive and negative predictive values [PPV, NPV], area under the curve [AUC]) of BMI thresholds, waist-based measures, and LC criteria for excess adiposity, as defined by DEXA.ResultsThe weighted prevalence of DEXA-defined excess adiposity was 36.4%. CDC BMI thresholds demonstrated 74.6% sensitivity and 82.2% specificity (PPV, 67.0%; NPV, 87.0%). Waist-based measures showed higher sensitivity and lower specificity than BMI; NHLBI WC thresholds produced 88.5% sensitivity and 66.7% specificity. LC criteria performed variably: BMI plus ≥ 1 waist measure had 74.6% sensitivity and 82.2% specificity, whereas ≥ 2 waist measures had 88.5% sensitivity and 66.8% specificity. The AUC values were 0.876 for BMI, 0.882 for WC, 0.887 for waist to height ratio, and 0.715 for waist to hip ratio.ConclusionsWaist-based definitions were more sensitive than BMI, whereas BMI provided greater specificity. LC criteria performed comparably to existing definitions. Incorporating WC into screening may improve the detection of excess adiposity.
Abstract reproduced from the open-access article under the recorded cc by licence; © the authors. PMID 41724736 · DOI · PMC13032046
Key reviews and meta-analyses
The most cited review-type papers among PubMed’s best-match results for this heading, listed with bibliographic details only. Follow the links for the full text and access terms.
- Research article Harmonizing the metabolic syndrome: a joint interim statement of the International Diabetes Federation Task Force on Epidemiology and Prevention; National Heart, Lung, and Blood Institute; American Heart Association; World Heart Federation; International Atherosclerosis Society; and International Association for the Study of Obesity [5]
- Research article Waist circumference as a vital sign in clinical practice: a Consensus Statement from the IAS and ICCR Working Group on Visceral Obesity [6]
- Research article Waist-to-height ratio is a better screening tool than waist circumference and BMI for adult cardiometabolic risk factors: systematic review and meta-analysis [7]
- Research article A systematic review of waist-to-height ratio as a screening tool for the prediction of cardiovascular disease and diabetes: 0·5 could be a suitable global boundary value [8]
- Research article Body mass index, waist circumference and waist:hip ratio as predictors of cardiovascular risk--a review of the literature [9]
- Research article Obesity and risk of colorectal cancer: a systematic review of prospective studies [10]
References
- Wei X, Min Y, Song G, Ye X, Liu L. Association between triglyceride-glucose related indices with the all-cause and cause-specific mortality among the population with metabolic syndrome. . 2024. PMID 38658993 · DOI · PMC11044377
- Zhang FL, Ren JX, Zhang P, Jin H, Qu Y, Yu Y, et al.. Strong Association of Waist Circumference (WC), Body Mass Index (BMI), Waist-to-Height Ratio (WHtR), and Waist-to-Hip Ratio (WHR) with Diabetes: A Population-Based Cross-Sectional Study in Jilin Province, China. . 2021. PMID 34056007 · DOI · PMC8147550
- Zhou T, Chen S, Mao J, Zhu P, Yu X, Lin R. Association between obstructive sleep apnea and visceral adiposity index and lipid accumulation product: NHANES 2015-2018. . 2024. PMID 38600516 · DOI · PMC11005189
- Lin JC, Tandar CE, Bajaj SS, Stanford FC. Diagnostic Performance of BMI and Waist Circumference in Detecting Excess Adiposity. . 2026. PMID 41724736 · DOI · PMC13032046
- Alberti KG, Eckel RH, Grundy SM, Zimmet PZ, Cleeman JI, Donato KA, et al.. Harmonizing the metabolic syndrome: a joint interim statement of the International Diabetes Federation Task Force on Epidemiology and Prevention; National Heart, Lung, and Blood Institute; American Heart Association; World Heart Federation; International Atherosclerosis Society; and International Association for the Study of Obesity. Circulation. 2009. PMID 19805654 · DOI
- Ross R, Neeland IJ, Yamashita S, Shai I, Seidell J, Magni P, et al.. Waist circumference as a vital sign in clinical practice: a Consensus Statement from the IAS and ICCR Working Group on Visceral Obesity. Nat Rev Endocrinol. 2020. PMID 32020062 · DOI · PMC7027970
- Ashwell M, Gunn P, Gibson S. Waist-to-height ratio is a better screening tool than waist circumference and BMI for adult cardiometabolic risk factors: systematic review and meta-analysis. Obes Rev. 2012. PMID 22106927 · DOI
- Browning LM, Hsieh SD, Ashwell M. A systematic review of waist-to-height ratio as a screening tool for the prediction of cardiovascular disease and diabetes: 0·5 could be a suitable global boundary value. Nutr Res Rev. 2010. PMID 20819243 · DOI
- Huxley R, Mendis S, Zheleznyakov E, Reddy S, Chan J. Body mass index, waist circumference and waist:hip ratio as predictors of cardiovascular risk--a review of the literature. Eur J Clin Nutr. 2010. PMID 19654593 · DOI
- Ma Y, Yang Y, Wang F, Zhang P, Shi C, Zou Y, et al.. Obesity and risk of colorectal cancer: a systematic review of prospective studies. PLoS One. 2013. PMID 23349764 · DOI · PMC3547959
About this article
- Sources
- NLM Medical Subject Headings (definition, synonyms); NCBI PubMed (counts, identifiers); Europe PMC (open-access abstracts and citation counts).
- Verification
- Every reference was resolved against PubMed on 2026-10-31; title, year and DOI matched.
- Review state
- automated source verified; no human expert review has been recorded yet.
- Version
- 1, last updated 2026-10-31.
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Evidence strength
EvidenceHelix's computed view of the study designs behind this topic: how common meta-analyses, randomized trials and reviews are, how recent the literature is, and a plain-language reading. It describes the design mix of the literature. It is not a quality appraisal of any study, and it is not medical advice.