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Published in: BMC Public Health 1/2016

Open Access 01-12-2015 | Research article

Comparison of body mass index (BMI) with the CUN-BAE body adiposity estimator in the prediction of hypertension and type 2 diabetes

Authors: Vicente Martín, Verónica Dávila-Batista, Jesús Castilla, Pere Godoy, Miguel Delgado-Rodríguez, Nuria Soldevila, Antonio J. Molina, Tania Fernandez-Villa, Jenaro Astray, Ady Castro, Fernando González-Candelas, José María Mayoral, José María Quintana, Angela Domínguez, CIBERESP Cases and Controls in Pandemic Influenza Working Group, Spain

Published in: BMC Public Health | Issue 1/2016

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Abstract

Background

Obesity is a world-wide epidemic whose prevalence is underestimated by BMI measurements, but CUN-BAE (Clínica Universidad de Navarra - Body Adiposity Estimator) estimates the percentage of body fat (BF) while incorporating information on sex and age, thus giving a better match. Our aim is to compare the BMI and CUN-BAE in determining the population attributable fraction (AFp) for obesity as a cause of chronic diseases.

Methods

We calculated the Pearson correlation coefficient between BMI and CUN-BAE, the Kappa index and the internal validity of the BMI. The risks of arterial hypertension (AHT) and diabetes mellitus (DM) and the AFp for obesity were assessed using both the BMI and CUN-BAE.

Results

3888 white subjects were investigated. The overall correlation between BMI and CUN-BAE was R2 = 0.48, which improved when sex and age were taken into account (R2 > 0.90). The Kappa coefficient for diagnosis of obesity was low (28.7 %). The AFp was 50 % higher for DM and double for AHT when CUN-BAE was used.

Conclusions

The overall correlation between BMI and CUN-BAE was not good. The AFp of obesity for AHT and DM may be underestimated if assessed using the BMI, as may the prevalence of obesity when estimated from the percentage of BF.
Literature
1.
2.
3.
Bastien M, Poirier P, Lemieux I, Després J. Overview of epidemiology and contribution of obesity to cardiovascular disease. Prog Cardiovasc Dis. 2014;56(4):369–81.CrossRefPubMed
4.
Okorodudu D, Jumean M, Montori V, Romero-Corral A, Somers V, Erwin P, et al. Diagnostic performance of body mass index to identify obesity as defined by body adiposity: a systematic review and meta-analysis. Int J Obes. 2010;34(5):791–9.CrossRef
5.
6.
7.
Romero-Corral A, Somers V, Sierra-Johnson J, Thomas R, Collazo-Clavell M, Korinek J, et al. Accuracy of body mass index in diagnosing obesity in the adult general population. Int J Obes. 2008;32(6):959–66.CrossRef
8.
Gómez-Ambrosi J, Silva C, Catalán V, Rodríguez A, Galofré J, Escalada J, et al. Clinical usefulness of a new equation for estimating body fat. Diabetes Care. 2012;5(2):383.CrossRef
9.
Domínguez A, Alonso J, Astray J, Baricot M, Cantón R, Castilla J, et al. Factores de riesgo de hospitalización por gripe (H1N1) 2009 y efectividad de intervenciones farmacológicas y no farmacológicas en su prevención. Estudio de casos y controles. Rev Esp Salud Publica. 2011;85(1):3–15.PubMed
10.
World Health Organization. Obesity: preventing and managing the global epidemic. Report of a WHO consultation. Report of a WHO Consultation. Geneva: Technical Report Series, No. 894; 2000.
11.
Salas-Salvadó J, Rubio M, Barbany M, Moreno B, Grupo colaborativo de la SEEDO. SEEDO 2007 Consensus for the evaluation of overweight and obesity and the establishment of therapeutic intervention criteria. Med Clin (Barc). 2007;128(5):184–96.CrossRef
12.
Romero-Corral A, Lopez-Jimenez F, Sierra-Johnson J, Somers VK. Differentiating between body fat and lean mass-how should we measure obesity? Nat Clin Pract Endocrinol Metab. 2008;4(6):322–3.PubMed
13.
De Lorenzo A, Deurenberg P, Pietrantuono M, Di Daniele N, Cervelli V, Andreoli A. How fat is obese? Acta Diabetol. 2003;40 Suppl 1:S254–7.CrossRefPubMed
14.
Llorca J, Fariñas-Alvarez C, Delgado-Rodríguez M. Fracción atribuible poblacional: cálculo e interpretación. Gac Sanit. 2001;15(1):61–7.CrossRefPubMed
15.
Sardinha L, Lohman T, Teixeira P, Guedes D, Going S. Comparison of air displacement plethysmography with dual-energy X-ray absorptiometry and 3 field methods for estimating body composition in middle-aged men. Am J Clin Nutr. 1998;68(4):786–93.PubMed
16.
17.
Vasconcelos F, Cordeiro B, Rech C, Petroski E. Sensitivity and specificity of the body mass index for the diagnosis of overweight/obesity in elderly. Cad Saude Publica. 2010;26(8):1519–27.CrossRef
18.
Gallagher D, Visser M, Sepúlveda D, Pierson R, Harris T, Heymsfield S. How useful is body mass index for comparison of body fatness across age, sex, and ethnic groups? Am J Epidemiol. 1996;143:228–39.CrossRefPubMed
19.
Jackson A, Stanforth P, Gagnon J, Rankinen T, Leon A, Rao D, et al. The effect of sex, age and race on estimating percentage body fat from body mass index: The Heritage Family Study. Int J Obes. 2001;26(6):789–96.
20.
Heydari S, Ayatollahi S, Zare N. Diagnostic value of bioelectrical impedance analysis versus body mass index for detection of obesity among students. Asian J Sports Med. 2011;2(2):68–74.CrossRefPubMedPubMedCentral
21.
Grundy S. Obesity, metabolic syndrome, and cardiovascular disease. J Clin Endocrinol Metab. 2004;89(6):2595–600.CrossRefPubMed
22.
Pongchaiyakul C, Nguyen T, Kosulwat V, Rojroongwasinkul N, Charoenkiatkul S, Pongchaiyakul C. Defining obesity by body mass index in the Thai population: an epidemiologic study. Asia Pac J Clin Nutr. 2006;15(3):293–9.PubMed
23.
Rodríguez-Rodríguez E, López-Plaza B, López-Sobaler A, Ortega R. Prevalencia de sobrepeso y obesidad en adultos españoles. Nutr Hosp. 2011;26(2):355–63.PubMed
24.
Dervaux N, Wubuli M, Megnien J, Chironi G, Simon A. Comparative associations of adiposity measures with cardiometabolic risk burden in asymptomatic subjects. Atherosclerosis. 2008;201(2):413–7.CrossRefPubMed
25.
Haghighatdoost F, Sarrafzadegan N, Mohammadifard N, Asgari S, Boshtam M, et al. Assessing body shape index (ABSI) as a predictor for the risk of cardiovascular diseases and metabolic syndrome among Iranian adults. Nutrition. 2014;30(6):636–44.CrossRefPubMed
26.
Jiang Y, Chen Y, Manuel D, Morrison H, Mao Y. Obesity Working Group. Quantifying the impact of obesity category on major chronic diseases in Canada. Sci World J. 2007;7:1211–21.CrossRef
27.
Wilson P, D'Agostino R, Sullivan L, Parise H, Kannel W. Overweight and obesity as determinants of cardiovascular risk: the Framingham experience. Arch Intern Med. 2002;162(16):1867–72.CrossRefPubMed
28.
Gómez-Ambrosi J, Silva C, Galofré J, Escalada J, Santos S, Millán D, et al. Body mass index classification misses subjects with increased cardiometabolic risk factors related to elevated adiposity. Int J Obes. 2012;36(2):286–94.CrossRef
29.
Zubiaga Toro L, Ruiz-Tovar Polo J, Díez-Tabernilla M, Giner Bernal L, Arroyo Sebastián A, Calpena RR. CUN-BAE formula and biochemical factors as predictive markers of obesity and cardiovascular disease in patients before and after sleeve gastrectomy. Nutr Hosp. 2014;30(2):281–6.PubMed
30.
Fuster-Parra P, Bennasar-Veny M, Tauler P, Yañez A, López-González A, Aguiló A. A comparison between multiple regression models and CUN-BAE equation to predict body fat in adults. PLoS ONE. 2015;10(3):e0122291.CrossRefPubMedPubMedCentral
31.
32.
Van Kerkhove M, Vandemaele K, Shinde V, Jaramillo-Gutierrez G, Koukounari A, Donnelly C, et al. Risk factors for severe outcomes following 2009 influenza A (H1N1) infection: a global pooled analysis. PLoS Med. 2011;8(7):e1001053.CrossRefPubMedPubMedCentral
Metadata
Title
Comparison of body mass index (BMI) with the CUN-BAE body adiposity estimator in the prediction of hypertension and type 2 diabetes
Authors
Vicente Martín
Verónica Dávila-Batista
Jesús Castilla
Pere Godoy
Miguel Delgado-Rodríguez
Nuria Soldevila
Antonio J. Molina
Tania Fernandez-Villa
Jenaro Astray
Ady Castro
Fernando González-Candelas
José María Mayoral
José María Quintana
Angela Domínguez
CIBERESP Cases and Controls in Pandemic Influenza Working Group, Spain
Publication date
01-12-2015
Publisher
BioMed Central
Published in
BMC Public Health / Issue 1/2016
Electronic ISSN: 1471-2458
DOI
https://doi.org/10.1186/s12889-016-2728-3

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