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BMC Public Health
Published in: BMC Public Health 1/2018

Open Access 01-12-2018 | Research article

Is waist-to-height ratio the best predictive indicator of hypertension incidence? A cohort study

Authors: Ana Carolina Rezende, Ludimila Garcia Souza, Thiago Veiga Jardim, Naiana Borges Perillo, Ymara Cássia Luciana Araújo, Samanta Garcia de Souza, Ana Luiza Lima Sousa, Humberto Graner Moreira, Weimar Kunz Sebba Barroso de Souza, Maria do Rosário Gondim Peixoto, Paulo César Brandão Veiga Jardim

Published in: BMC Public Health | Issue 1/2018

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Abstract

Background

The best anthropometric indicator to verify the association between obesity and hypertension (HTN) has not been established. We conducted this study to evaluate and compare the discriminatory power of waist-to-height ratio (WHtR) in relation to body mass index (BMI) and waist circumference (WC) in predicting HTN after 13 years of follow-up.

Methods

This study was an observational prospective cohort study performed in the city of Firminópolis, in Brazilian’s midwest. The cohort baseline (phase 1) was initiated in 2002 with the evaluation of a representative sample of the normotensive population (≥ 18 years of age). The incidence of HTN was evaluated as the outcome (phase 2). Sociodemographic, dietary and lifestyle variables were used to adjust proportional hazards models and evaluate risk of HTN according to anthropometric indices. The areas under the receiver operating characteristic (ROC) curves were used to compare the predictive capacity of these indices. The best HTN predictor cut-offs were obtained based on sensitivity and specificity.

Results

A total of 471 patients with a mean age of 38.9 ± 12.3 years were included in phase 1. The mean follow-up was 13.2 years, and 207 subjects developed HTN. BMI, WC and WHtR were associated with risk of HTN incidence and had similar power in predicting the disease. However, the associations were only significant for women. The cut-off points with a better HTN predictive capacity were in agreement with current recommendations, except for the WC in men.

Conclusions

The results suggest that both overall obesity (BMI) and central obesity (WC and WHtR) anthropometric indicators can be used in this population to evaluate the risk of developing hypertension.
Appendix
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Literature
1.
World Health Organization. Global status report on noncommunicable. Geneva: WHO; 2014.
2.
World Health Organization. A global brief on hypertension: silent killer, global public health crisis. Geneva: WHO; 2013.
3.
Krauss RM, Winston M, Fletcher BJ, Grundy SM. Obesity: impact on cardiovascular disease. Circulation. 1998;98:1472–6.CrossRef
4.
Stokes J, Kannel WB, Wolf PA, D’agostino RB, Cupples LA. Blood pressure as a risk factor for cardiovascular disease. The Framingham study – 30 years of follow-up. Hypertension. 1989;13:13–8.CrossRef
5.
Simone G, Devereux RB, Chinali M, Roman MJ, Best LG, Welty TK, Lee ET, Howard BV, Strong Heart Study Investigators. Risk factors for arterial hypertension in adults with initial optimal blood pressure: the strong heart study. Hypertension. 2006;47:162–7.CrossRefPubMed
6.
Li WC, Chen IC, Chang YC, Loke SS, Wang SH, Hsiao KY. Waist-to-height ratio, waist circumference, and body mass index as indices of cardiometabolic risk among 36,642 Taiwanese adults. Eur J Nutr. 2013;52:57–65.CrossRefPubMed
7.
Munaretti DB, Barbosa AR, Marucci MFN, Lebrão ML. Self-rated hypertension and anthropometric indicators of body fat in elderly. Rev Assoc Med Bras. 2011;57:25–30.PubMed
8.
Sánchez A, Muhn MA, Lovera M, Ceballos B, Bonneau G, Pedrozo W, Medina G, Leiva R, Humeres C, Castillo Rascón MS. Anthropometric indexes predicting Cardiometabolic risk. Prospective cohort study in a population of employees of public hospitals. Rev Argent Endocrinol Metab. 2014;51:186–91.
9.
Bastien M, Poirier P, Lemieux I, Despres JP. Overview of epidemiology and contribution of obesity to cardiovascular disease. Prog Cardiovasc Dis. 2014;56:369–81.CrossRefPubMed
10.
World Health Organization (2000) Obesity: preventing and managing the global epidemic. Report of a WHO consultation. World Health Organ Tech Rep Ser 894:i–xii, 1–253.
11.
World Health Organization. Waist circumference and waist-hip ratio. Report of a WHO expert consultation. Geneva: WHO; 2008.
12.
13.
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;23:247–69.CrossRefPubMed
14.
Koch E, Bravo M, Romero C, Díaz A, Castañeda H, Aguilera H, Nivelo M, Romero T. Height, an early life predictor of cardiovascular risk factors and mortality in chilean adults: the San Francisco project cohort study. Rev Chil Cardiol. 2011;30:198–206.CrossRef
15.
Mccarron P, Okasha M, Mcewen J, Smith GD. Height in young adulthood and risk of death from cardiorespiratory disease: a prospective study of male former students of Glasgow University, Scotland. Am J Epidemiol. 2002;155:683–7.CrossRefPubMed
16.
Smith GD, Hart C, Upton M, Hole D, Gillis C, Watt G, Hawthorne V. Height and risk of death among men and women: aetiological implications of associations with cardiorespiratory disease and cancer mortality. J Epidemiol Community Health. 2000;54:97–103.CrossRefPubMedCentral
17.
Schneider HJ, Klotsche J, Silber S, Stalla GK, Wittchen HU. Measuring abdominal obesity: effects of height on distribution of cardiometabolic risk factors risk using waist circumference, waist-to-height ratio. Diabetes Care. 2011;34:e7.CrossRefPubMed
18.
Misra A, Wasir JS, Vikram NK. Waist circumference criteria for the diagnosis of abdominal obesity are not applicable uniformly to all populations and ethnic groups. Nutrition. 2005;21:969–76.CrossRefPubMed
19.
Alberti KG, Eckel RH, Grundy SM, Zimmet PZ, Cleeman JI, Donato KA, Fruchart JC, James WP, Loria CM, Smith SC Jr, International Diabetes Federation Task Force on Epidemiology and Prevention; Hational Heart, Lung, and Blood Institute; American Heart Association; World Heart Federation; International Atherosclerosis Society; International Association for the Study of Obesity. 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;120:1640–5.CrossRefPubMed
20.
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;13:275–86.CrossRefPubMed
21.
Arnaiz P, Grob F, Cavada G, Domínguez A, Bancalari R, Cerda V, Zamorano J, Fernández M, García H. Waist-to-height ratio does not change with gender, age and pubertal stage in elementary school children. Rev méd Chile. 2014;142:574–8.CrossRefPubMed
22.
Liu Y, Tong G, Tong W, Lu L, Qin X. Can body mass index, waist circumference, waist-hip ratio and waist-height ratio predict the presence of multiple metabolic risk factors in Chinese subjects? BMC Public Health. 2011;11:1–10.CrossRef
23.
Silva DAS, Petroski EL, Peres MA. Accuracy and measures of association of anthropometric indexes of obesity to identify the presence of hypertension in adults: a population-based study in southern Brazil. Eur J Nutr. 2013;52:237–46.CrossRefPubMed
24.
Hori A, Nanri A, Sakamoto N, et al. Comparison of body mass index, waist circumference, and waist-to-height ratio for predicting the clustering of Cardiometabolic risk factors by age in Japanese workers. Cir J. 2014;78:1160–8.CrossRef
25.
Lo K, Wong M, Khalechelvam P, Tam W. Waist-to-height ratio, body mass index and waist circumference for screening paediatric cardio-metabolic risk factors: a meta-analysis. Obes Rev. 2016;17:1258–75.CrossRefPubMed
26.
Nascente FMN, Jardim PCBV, Peixoto MRG, Monego ET, Moreira HG, Vitorino PVO, Souza WKSB, Scala LN. Arterial hypertension and its correlation with some risk factors in a small Brazilian town. Arq Bras Cardiol. 2010;95:502–9.CrossRefPubMed
27.
Lohman TG, Roche AF, Martorell R. Anthropometric standardization reference manual. USA, Champaign: Human Kinetics Books; 1998.
28.
World Health Organization. Physical status: the use and interpretation of anthropometry. Report of a WHO expert committee. World Health Organ Tech Rep Ser. 1995;854:1–452.
29.
Lipschitz DA. Screening for nutritional status in the elderly. Prim Care. 1994;21:55–67.PubMed
30.
31.
32.
Fornés NS, Stringhini MLF. Development of a food frequency questionnaire (FFQ) and characterization of the food pattern consumption for low income workers in the city of Goiânia, Goiás state, Brazil. Acta Sci Health Sci. 2005;27:69–75.
33.
Fornes NS, Martins IS, Velasquez-Melendez G, Latorre MRDO. Food consumption scores and serum lipids levels in the population of São Paulo. Brazil Rev Saúde Pública. 2002;36:12–8.CrossRefPubMed
34.
Brazil, Health Ministry, Assistance to Health Secretary, Basic Assistance Department. Food guidelines for Brazilian population. Brasília: Federal District; 2014.
35.
Sacks FM, Svetkey LP, Vollmer WM, Appel LJ, Bray GA, Harsha D, Obarzanek E, Conlin PR, Miller ER, Simons-morton DG, Karanja N, Lin PH, DASH–Sodium Collaborative Research Group. Effects on blood pressure of reduced dietary sodium and the dietary approaches to stop hypertension (DASH) diet. N Engl J Med. 2001;344:3–10.CrossRefPubMed
36.
Hanley JA, McNeil BJ. The meaning and use of the area under a receiver operating characteristic (ROC) curve. Radiology. 1982;143:29–36.CrossRefPubMed
37.
Bovet P, Arlabosse T, Viswanathan B. Myers G (2012) association between obesity indices and cardiovascular risk factors in late adolescence in the Seychelles. BMC Pediatr. 2012;12:2–9.CrossRef
38.
Muraro AP, Santos DF, Rodrigues PRM, Braga JU. Factors associated with self-reported systemic arterial hypertension according to VIGITEL in 26 Brazilian capitals and the Federal District in 2008. Ciênc Saúde Coletiva. 2013;18:1387–98.CrossRef
39.
Carmo JM, Silva AA, Wang Z, Fang T, Aberdein N, Lara Rodriguez CEP, Hall JE. Obesity-induced hypertension: brain signaling pathways. Curr Hypertens Rep. 2016;18:1–9.CrossRef
40.
Kotsis V, Nilsson P, Grassi G, Mancia G, Redon J, Luft F, Schmieder R, Engeli S, Stabouli S, Antza C, Pall D, Schlaich M, Jordan J, WG on Obesity, Diabetes, the High Risk Patient, European Society of Hypertension. New developments in the pathogenesis of obesity-induced hypertension. J Hypertes. 2015;33:1499–508.CrossRef
41.
Chei CL, Iso H, Yamagishi K, Tanigawa T, Cui R, Imano H, Kiyama M, Kitamura A, Sato S, Shimamoto T. Body fat distribution and the risk of hypertension and diabetes among Japanese men and women. Hypertens Res. 2008;31:851–7.CrossRefPubMed
42.
Fuchs FD, Gus M, Moreira LB, Moraes RS, Wiehe M, Pereira GM, Fuchs SC. Anthropometric indices and the incidence of hypertension: a comparative analysis. Obes Res. 2005;13:1515–7.CrossRefPubMed
43.
Barbosa LS, Scala LCN, Ferreira MG. Association between anthropometric markers of body adiposity and hypertension in an adult population of Cuiabá, Mato Grosso. Rev Bras Epidemiol. 2009;12:237–47.CrossRef
44.
Peixoto MRG, Benicio MHA, Latorre MRDO, Jardim PCBV. Waist circumference and body mass index as predictors of hypertension. Arq Bras Cardiol. 2006;87:462–70.CrossRef
45.
Sakurai M, Miura K, Takamura T, Ota T, Ishizaki M, Morikawa Y, Kido T, Naruse Y, Nakagawa H. Gender differences in the association between anthropometric indices of obesity and blood pressure in Japanese. Hypertens Res. 2006;29:75–80.CrossRefPubMed
46.
Valenzuela K, Bustos P. Índice cintura estatura como predictor de riesgo de hipertensión arterial en población adulta joven: ¿Es mejor indicador que la circunferencia de cintura? Arch Latinoam Nutr. 2012;62:220–6.PubMed
47.
Xavier Pi-Sunyer F. The epidemiology of central fat distribution in relation to disease. Nutr Rev. 2004;62:120–6.CrossRef
48.
Wang TD, Goto S, Bhatt DL, Steg PG, Chan JC, Richard AJ, Liau CS, REACH Registry Investigators. Ethnic differences in the relationships of anthropometric measures to metabolic risk factors in Asian patients at risk of atherothrombosis: results from the REduction of Atherothrombosis for continued health (REACH) registry. Metabolism. 2010;59:400–8.CrossRefPubMed
49.
Guasch-Ferré M, Bulló M, Martínez-González MÁ, Corella D, Estruch R, Covas MI, Arós F, Wärnberg J, Fiol M, Lapetra J, Muñoz MÁ, Serra-Majem L, Pintó X, Babio N, Díaz-López A, Salas-Salvadó J. Waist-to-height ratio and cardiovascular risk factors in elderly individuals at high cardiovascular risk. PLoS One. 2012;7:1–6.
50.
51.
Battie CA, Hart NB, Ancheta IB, Flores R, Rao G, Palaniappan L. Comparison of body mass index, waist circumference, and waist to height ratio in the prediction of hypertension and diabetes mellitus: Filipino-American women cardiovascular study. Prev Med Rep. 2016;4:608–13.CrossRefPubMedPubMedCentral
52.
Tuan NT, Adair LS, Stevens J, Popkin BM. Prediction of hypertension by different anthropometric indices in adults: the change in estimate approach. Public Health Nutr. 2010;13:639–46.CrossRefPubMed
Metadata
Title
Is waist-to-height ratio the best predictive indicator of hypertension incidence? A cohort study
Authors
Ana Carolina Rezende
Ludimila Garcia Souza
Thiago Veiga Jardim
Naiana Borges Perillo
Ymara Cássia Luciana Araújo
Samanta Garcia de Souza
Ana Luiza Lima Sousa
Humberto Graner Moreira
Weimar Kunz Sebba Barroso de Souza
Maria do Rosário Gondim Peixoto
Paulo César Brandão Veiga Jardim
Publication date
01-12-2018
Publisher
BioMed Central
Published in
BMC Public Health / Issue 1/2018
Electronic ISSN: 1471-2458
DOI
https://doi.org/10.1186/s12889-018-5177-3

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