Waist-to-Height Ratio: A Sensitive Tool for Assessing the Need for Nutritional Risk Management in Elderly Populations from Brazil
Open accessAbstract
Introduction: Nutritional status assessment commonly relies on body mass index (BMI), which overlooks lean mass and adipose tissue distribution. However, waist circumference (WC) and waist-to-height ratio (WHtR) provide additional insights into fat accumulation. By combining these indices, it may be possible to identify older adults needing weight management interventions. Objectives: To assess the WC and WHtR as strategies for identifying individuals requiring weight management. Methods: A cross-sectional study was conducted with 509 elderly individuals in Northeast Brazil. Weight, height, hip circumference, and waist circumference were measured, and combined with indices such as BMI WC, WHR, and WHtR to identify those who require weight management. The DeLong test compared areas under the curves using receiver operating characteristic curves and statistical significance. Sensitivity, specificity, and positive and negative predictive values were calculated to verify usefulness for clinical application. A validation sample of 599 elderly individuals from the country’s Southern region was used to confirm the results. Results: Both WC and WHtR showed adequate diagnostic accuracy with no statistically significant difference in AUCs. WHtR ≥ 0.50 had 92% sensitivity in identifying men and women requiring nutritional management. WC presented lower sensitivity but 93% specificity, useful for excluding elderly individuals from the nutritional risk category. These results were consistent in the validation sample. Conclusion: WHtR is a valuable index for screening nutritional risk management in the elderly population, applicable to men and women. Conversely, WC performs better in excluding individuals who do not need nutritional risk management.
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Alternative metrics such as waist-to-hip ratio or waist-to-height ratio in addition to BMI could offer a more comprehensive assessment of body composition and associated health risks in diverse populations.
“Exploring alternative metrics such as waist-to-hip ratio (WHR) or waist-to-height ratio (WHtR) in addition to BMI could offer a more comprehensive assessment of body composition and associated health risks in diverse populations.”
From Advantages and Limitations of the Body Mass Index (BMI) to Assess Adult Obesity (2024) · cites this paper as [41]
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Waist circumference as a measure for indicating need for weight management
Lean, M. E. J., Han, T. S., & Morrison, C. E. (1995) · BMJ · doi:10.1136/bmj.311.6998.158 · Cited by 1,869 · see citing works
Abraham, T. M., Pedley, A., Massaro, J. M., Hoffmann, U., & Fox, C. S. (2015) · Circulation · doi:10.1161/circulationaha.114.015000 · Cited by 353 · see citing works
General and Abdominal Adiposity and Mortality in Mexico City: A Prospective Study of 150 000 Adults
Gnatiuc, L., Alegre-Díaz, J., Wade, R., Ramirez-Reyes, R., Tapia-Conyer, R., Garcilazo-Ávila, A., Chiquete, E., Gonzáles-Carballo, C., Solano-Sanchez, M., Clarke, R., et al. (2019) · Annals of Internal Medicine · doi:10.7326/m18-3502 · Cited by 43 · see citing works
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- [1]Piqueras P. Ballester A. Durá-Gil J.V. Martinez-Hervas S. Redón J. Real J.T. Anthropometric Indicators as a Tool for Diagnosis of Obesity and Other Health Risk Factors: A Literature Review Front. Psychol. 2021 12 631179 10.3389/fpsyg.2021.631179 34305707 PMC8299753 · DOI
- [2]Bramhankar M. Pandey M. Rana G.S. Rai B. Mishra N.L. Shukla A. An assessment of anthropometric indices and its association with NCDs among the older adults of India: Evidence from LASI Wave-1 BMC Public Health 2021 21 1357 10.1186/s12889-021-11421-4 34238276 PMC8268209 · DOI
- [3]Lahey R. Khan S.S. Trends in Obesity and Risk of Cardiovascular Disease Curr. Epidemiol. Rep. 2018 5 243 251 10.1007/s40471-018-0160-1 30705802 PMC6349392 · DOI
- [4]Powell-Wiley T.M. Poirier P. Burke L.E. Després J.-P. Gordon-Larsen P. Lavie C.J. Lear S.A. Ndumele C.E. Neeland I.J. Sanders P. Obesity and Cardiovascular Disease: A Scientific Statement From the American Heart Association Circulation 2021 143 e984 e1010 10.1161/CIR.0000000000000973 33882682 PMC8493650 · DOI · Paper page
- [7]Adegbija O. Hoy W.E. Wang Z. Waist circumference values equivalent to body mass index points for predicting absolute cardiovascular disease risks among adults in an Aboriginal community: A prospective cohort study BMJ Open 2015 5 e009185 10.1136/bmjopen-2015-009185 26567258 PMC4654306 · DOI
- [8]Coqueiro R.d.S. Barbosa A.R. Borgatto A.F. Anthropometric measurements in the elderly of Havana, Cuba: Age and sex differences Nutrition 2009 25 33 39 10.1016/j.nut.2008.07.007 18834720 · DOI
- [9]Santos J.L. Albala C. Lera L. García C. Arroyo P. Pérez-Bravo F. Angel B. Peláez M. Anthropometric measurements in the elderly population of Santiago, Chile Nutrition 2004 20 452 457 10.1016/j.nut.2004.01.010 15105033 · DOI
- [11]Han T.S. van Leer E.M. Seidell J.C. Lean M.E.J. Waist circumference action levels in the identification of cardiovascular risk factors: Prevalence study in a random sample BMJ 1995 311 1401 1405 10.1136/bmj.311.7017.1401 8520275 PMC2544423 · DOI
- [12]Ross R. Neeland I.J. Yamashita S. Shai I. Seidell J. Magni P. Santos R.D. Arsenault B. Cuevas A. Hu F.B. 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 16 177 189 10.1038/s41574-019-0310-7 32020062 PMC7027970 · DOI · Paper page
- [13]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. 2011 13 275 286 10.1111/j.1467-789X.2011.00952.x 22106927 · DOI · Paper page
- [14]Momin M. Fan F. Li J. Jia J. Zhang L. Zhang Y. Huo Y. Joint Effects of Body Mass Index and Waist Circumference on the Incidence of Hypertension in a Community-Based Chinese Population Obes. Facts 2020 13 245 255 10.1159/000506689 32213776 PMC7250363 · DOI
- [15]Green M.A. Do we need to think beyond BMI for estimating population-level health risks? J. Public Health 2015 38 192 193 10.1093/pubmed/fdv007 25618907 PMC5896802 · DOI
- [16]Seo D.-C. Choe S. Torabi M.R. Is waist circumference ≥ 102/88 cm better than body mass index ≥ 30 to predict hypertension and diabetes development regardless of gender, age group, and race/ethnicity? Meta-analysis Prev. Med. 2017 97 100 108 10.1016/j.ypmed.2017.01.012 28137662 · DOI
- [17]Marcadenti A. Fuchs F.D. Moreira L.B. Gus M. Fuchs S.C. Adiposity phenotypes are associated with type-2 diabetes: LAP index, body adiposity index, and neck circumference Atherosclerosis 2017 266 145 150 10.1016/j.atherosclerosis.2017.09.022 29028482 · DOI
- [18]Silveira E.A. Pagotto V. Barbosa L.S. de Oliveira C. Pena G.d.G. Velasquez-Melendez G. Accuracy of BMI and waist circumference cut-off points to predict obesity in older adults Cienc. Saude Coletiva 2020 25 1073 1082 10.1590/1413-81232020253.13762018 32159675 · DOI
- [19]Karmakar A. Garg S. Dasgupta A. Paul B. Maharana S.P. Sensitivity and specificity of waist circumference as a single screening tool for assessment of overweight and obesity Int. J. Community Med. Public Health 2017 4 4254 10.18203/2394-6040.ijcmph20174839 · DOI
- [20]Misra A. Vikram N.K. Gupta R. Pandey R.M. Wasir J.S. Gupta V.P. Waist circumference cutoff points and action levels for Asian Indians for identification of abdominal obesity Int. J. Obes. 2005 30 106 111 10.1038/sj.ijo.0803111 16189502 · DOI · Paper page
- [21]Molarius A. Seidell J.C. Sans S. Tuomilehto J. Kuulasmaa K. Varying Sensitivity of Waist Action Levels to Identify Subjects with Overweight or Obesity in 19 Populations of The WHO MONICA Project J. Clin. Epidemiol. 1999 52 1213 1224 10.1016/S0895-4356(99)00114-6 10580785 · DOI
- [22]Kodama S. Horikawa C. Fujihara K. Heianza Y. Hirasawa R. Yachi Y. Sugawara A. Tanaka S. Shimano H. Iida K.T. Comparisons of the Strength of Associations With Future Type 2 Diabetes Risk Among Anthropometric Obesity Indicators, Including Waist-to-Height Ratio: A Meta-Analysis Am. J. Epidemiol. 2012 176 959 969 10.1093/aje/kws172 23144362 · DOI
- [23]Thomas D.M. Bredlau C. Bosy-Westphal A. Mueller M. Shen W. Gallagher D. Maeda Y. McDougall A. Peterson C.M. Ravussin E. Relationships between body roundness with body fat and visceral adipose tissue emerging from a new geometrical model Obesity 2013 21 2264 2271 10.1002/oby.20408 23519954 PMC3692604 · DOI · Paper page
- [24]Liu S. Cao W. Li Z. Wang S. Yang S. Lu M. Li H. Song Y. Chen S. Li X. Association between different adiposity measures and all-cause mortality risk among centenarians: A prospective cohort study Clin. Nutr. 2023 42 1219 1226 10.1016/j.clnu.2023.04.023 37236872 · DOI
- [25]Carmienke S. Freitag M.H. Pischon T. Schlattmann P. Fankhaenel T. Goebel H. Gensichen J. General and abdominal obesity parameters and their combination in relation to mortality: A systematic review and meta-regression analysis Eur. J. Clin. Nutr. 2013 67 573 585 10.1038/ejcn.2013.61 23511854 · DOI · Paper page
- [26]de Hollander E.L. Bemelmans W.J. Boshuizen H.C. Friedrich N. Wallaschofski H. Guallar-Castillón P. Walter S. Zillikens M.C. Rosengren A. Lissner L. The association between waist circumference and risk of mortality considering body mass index in 65- to 74-year-olds: A meta-analysis of 29 cohorts involving more than 58 000 elderly persons Leuk. Res. 2012 41 805 817 10.1093/ije/dys008 22467292 PMC4492417 · DOI
- [28]Neeland I.J. Poirier P. Després J.-P. Cardiovascular and Metabolic Heterogeneity of Obesity: Clinical Challenges and Implications for Management Circulation 2018 137 1391 1406 10.1161/CIRCULATIONAHA.117.029617 29581366 PMC5875734 · DOI · Paper page
- [29]Carvalho V.C.H.d.S.d. Rossato S.L. Fuchs F.D. Harzheim E. Fuchs S.C. Assessment of primary health care received by the elderly and health related quality of life: A cross-sectional study BMC Public Health 2013 13 605 10.1186/1471-2458-13-605 23800179 PMC3704970 · DOI
- [30]Fuchs S.C. Moreira L.B. Camey S.A. Moreira M.B. Fuchs F.D. Clustering of risk factors for cardiovascular disease among women in Southern Brazil: A population-based study Cad. Saude Publica 2008 24 s285 s293 10.1590/S0102-311X2008001400013 18670708 · DOI
- [31]World Health Organization Physical Status: The Use and Interpretation of Anthropometry. Report of a Who Expert Committee World Health Organization Geneva, Switzerland 1995 Volume 854 1 452 8594834
- [32]Fletcher R.H. Fletcher S.W. Wagner E.H. Clinical Epidemiology 3rd ed. Lippincott Williams and Wilkins Philadelphia, PA, USA 1996
- [33]Geng S. Chen X. Shi Z. Bai K. Shi S. Association of anthropometric indices with the development of multimorbidity in middle-aged and older adults: A retrospective cohort study PLoS ONE 2022 17 e0276216 10.1371/journal.pone.0276216 36240163 PMC9565419 · DOI
- [34]Marcadenti A. Fuchs S.C. Moreira L.B. Wiehe M. Gus M. Fuchs F.D. Accuracy of Anthropometric Indexes of Obesity to Predict Diabetes Mellitus Type 2 Among Men and Women With Hypertension Am. J. Hypertens. 2011 24 175 180 10.1038/ajh.2010.212 20885370 · DOI
- [35]Gus M. Fuchs S.C. Moreira L.B. Moraes R.S. Wiehe M. Silva A.F. Albers F. Fuchs F.D. Association between different measurements of obesity and the incidence of hypertension Am. J. Hypertens. 2004 17 50 53 10.1016/j.amjhyper.2003.08.010 14700512 · DOI
- [36]Fuchs F.D. Gus M. Moreira L.B. Moraes R.S. Wiehe M. Pereira G.M. Fuchs S.C. Anthropometric Indices and the Incidence of Hypertension: A Comparative Analysis Obes. Res. 2005 13 1515 1517 10.1038/oby.2005.184 16222051 · DOI
- [37]Moosaie F. Abhari S.M.F. Deravi N. Behnagh A.K. Esteghamati S. Firouzabadi F.D. Rabizadeh S. Nakhjavani M. Esteghamati A. Waist-To-Height Ratio Is a More Accurate Tool for Predicting Hypertension Than Waist-To-Hip Circumference and BMI in Patients With Type 2 Diabetes: A Prospective Study Front. Public Health 2021 9 726288 10.3389/fpubh.2021.726288 34692623 PMC8529190 · DOI
- [38]Sommer I. Teufer B. Szelag M. Nussbaumer-Streit B. Titscher V. Klerings I. Gartlehner G. The performance of anthropometric tools to determine obesity: A systematic review and meta-analysis Sci. Rep. 2020 10 12699 10.1038/s41598-020-69498-7 32728050 PMC7391719 · DOI
- [39]Marini E. Buffa R. Gobbo L.A. Salinas-Escudero G. Stagi S. García-Peña C. Sánchez-García S. Carrillo-Vega M.F. Interpopulation Similarity of Sex and Age-Related Body Composition Variations Among Older Adults Int. J. Environ. Res. Public Health 2020 17 6047 10.3390/ijerph17176047 32825260 PMC7503589 · DOI
- [40]Corrêa M.M. Facchini L.A. Thumé E. de Oliveira E.R.A. Tomasi E. The ability of waist-to-height ratio to identify health risk Rev. Saúde Publica 2019 53 66 10.11606/s1518-8787.2019053000895 31553376 PMC6752642 · DOI
- [41]Browning L.M. Hsieh S.D. 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 23 247 269 10.1017/S0954422410000144 20819243 · DOI · Paper page
- [42]Cai L. Liu A. Zhang Y. Wang P. Waist-to-Height Ratio and Cardiovascular Risk Factors among Chinese Adults in Beijing PLoS ONE 2013 8 e69298 10.1371/journal.pone.0069298 23874938 PMC3709905 · DOI
- [43]Wakabayashi I. Daimon T. Receiver-operated characteristics (ROCs) of the relationships between obesity indices and multiple risk factors (MRFs) for atherosclerosis at different ages in men and women Arch. Gerontol. Geriatr. 2012 55 96 100 10.1016/j.archger.2011.06.028 21871669 · DOI
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Ahmed, S. K., & Mohammed, R. A. (2025) · Metabolism Open · doi:10.1016/j.metop.2025.100375 · Cited by 432 · see citing works
Advantages and Limitations of the Body Mass Index (BMI) to Assess Adult Obesity
Wu, Y., Li, D., & Vermund, S. H. (2024) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph21060757 · Cited by 332 · see citing works
“By considering multiple metrics, healthcare practitioners can personalize interventions and risk assessments to better meet individual needs, improving the effectiveness of preventive strategies and treatment plans [41].”
Background
- Authors
- Carvalho, V. C. H. D. S., Moreira, L. B., Luft, V. C., & Fuchs, S. C.
- Affiliations
- Universidade Federal da Bahia (BR)
- Universidade Federal do Rio Grande do Sul (BR)
- Corresponding author
- Fuchs, Sandra C.
- Venue
- Healthcare
- Publisher
- MDPI AG
- Published
- 2023-08-28
- Volume
- 11
- Issue
- 17
- Pages
- 2406
- ISSN
- 2227-9032 (ISSN-L)
- PMC
- PMC10486933
- OpenAlex
- W4386224067
- Cited by
- 10
- References
- 3
- Citations by year
- 2026: 6 · 2025: 2 · 2024: 2
- FWCI
- 1.78
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Healthcare (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas) (submittedVersion, cc-by-nc-sa)
- Funders
- National Council for Scientific and Technological Development (457469/2013-7, 309023/2015-7, 316802/2021-2, 16-0187, 1973/2016)
- SCF (457469/2013-7, 309023/2015-7, 316802/2021-2, 16-0187, 1973/2016)
- Hospital de Clinicas de Porto Alegre (457469/2013-7, 309023/2015-7, 316802/2021-2, 16-0187, 1973/2016)
- Postgraduate Program in Epidemiology, from UFRGS, and DINTER Program (UFBA/UFRGS) (457469/2013-7, 309023/2015-7, 316802/2021-2, 16-0187, 1973/2016)
- Topics
- Health Sciences › Medicine › Physiology › Body Composition Measurement Techniques
- Health Sciences › Medicine › Physiology › Nutrition and Health in Aging
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Nutrition and Health Studies
- Keywords
- waist-to-height ratio, waist circumference, older adults, obesity screening, body mass index, abdominal fat, weight management, diagnostic accuracy, nutritional assessment
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