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The comparison of percent body fat estimated by different anthropometrics to predict the incidence of hypertension

Abstract

Percent body fat (%BF) is associated with the development of hypertension. However, the power of %BF estimated by different anthropometrics to predict incident hypertension was unknown. This study was from the China Health and Nutrition Survey (CHNS). %BF was calculated using the equations with BMI, WC, and skinfold thickness and divided into low and high %BF according to ROC. Cox regression was employed to evaluate the power of different %BFs to predict the development of hypertension. When not adjusting for covariates, %BFs defined by BMI, WC, and ST were the significant predictors of the development of hypertension (all P < 0.0001; crude HR: 2.238, 3.243, and 1.574; and HR 95% CI: 2.098–2.387, 2.905–3.619, and 1.464–1.692). When three %BFs entered into model simultaneously, the significance in %BF estimated by ST disappeared (P = 0.0765; adjusted HR: 1.124; and HR 95% CI: 0.988–1.280). For males, %BFs by BMI, WC, and ST significantly affected the incidence of hypertension as they were separately analyzed (all P < 0.0001; crude HR: 2.445, 2.335, and 1.828; and HR 95% CI: 2.220–2.693, 2.011–2.712, and 1.636–2.042, respectively). For females, %BFs estimated by BMI, WC, and ST were the determinants of the development of hypertension whether covariates were adjusted or not (all P < 0.0001). In conclusion, there was a poor and ineffective association of %BF estimated by triceps skinfold thickness with the development of hypertension, especially when three %BFs were analyzed together. High %BFs estimated by BMI and WC were the true and effective predictors of the incidence of hypertension.

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References

  1. Dong B, Wang H-J, Wang Z, Liu J-S, Ma J. Trends in blood pressure and body mass index among Chinese children and adolescents from 2005 to 2010. Am J Hypertens. 2013;26:997–1004.

    Article  CAS  Google Scholar 

  2. Ezzati M, Vander Hoorn S, Lawes CM, Leach R, James WPT, Lopez AD, et al. Rethinking the “diseases of affluence” paradigm: global patterns of nutritional risks in relation to economic development. PLoS Med. 2005;2:e133.

    Article  Google Scholar 

  3. Yang G, Wang Y, Zeng Y, Gao GF, Liang X, Zhou M, et al. Rapid health transition in China, 1990–2010: findings from the Global Burden of Disease Study 2010. Lancet. 2013;381:1987–2015.

    Article  Google Scholar 

  4. Jie F, LI GQ, Jing L, Wei W, Miao W, Yue Q, et al. Impact of cardiovascular disease deaths on life expectancy in Chinese population. Biomed Environ Sci. 2014;27:162–8.

    Google Scholar 

  5. Qi S-F, Zhang B, Wang H-J, Yan J, Mi Y-J, Liu D-W, et al. Prevalence of hypertension subtypes in 2011 and the trends from 1991 to 2011 among Chinese adults. J Epidemiol Community Health. 2015:70:444–51.

    Article  Google Scholar 

  6. Cassano PA, Segal MR, Vokonas PS, Weiss ST. Body fat distribution, blood pressure, and hypertension: a prospective cohort study of men in the normative aging study. Ann Epidemiol. 1990;1:33–48.

    Article  CAS  Google Scholar 

  7. Genovesi S, Antolini L, Giussani M, Pieruzzi F, Galbiati S, Valsecchi MG, et al. Usefulness of waist circumference for the identification of childhood hypertension. J Hypertens. 2008;26:1563–70.

    Article  CAS  Google Scholar 

  8. Fuchs FD, Gus M, Moreira LB, Moraes RS, Wiehe M, Pereira GM, et al. Anthropometric indices and the incidence of hypertension: a comparative analysis. Obes Res. 2005;13:1515–7.

    Article  Google Scholar 

  9. Wang S, Liu Y, Li F, Jia H, Liu L, Xue F. A novel quantitative body shape score for detecting association between obesity and hypertension in China. BMC Public Health. 2015;15:7.

    Article  CAS  Google Scholar 

  10. Bohn B, Müller MJ, Simic-Schleicher G, Kiess W, Siegfried W, Oelert M, et al. BMI or BIA: is body mass index or body fat mass a better predictor of cardiovascular risk in overweight or obese children and adolescents? Obes Facts. 2015;8:156–65.

    Article  CAS  Google Scholar 

  11. Xie D, Bollag WB. Obesity, hypertension and aldosterone: is leptin the link? J Endocrinol. 2016;230:F7–F11.

    Article  CAS  Google Scholar 

  12. Rahmouni K, Correia ML, Haynes WG, Mark AL. Obesity-associated hypertension: new insights into mechanisms. Hypertension. 2005;45:9–14.

    Article  CAS  Google Scholar 

  13. Garrison RJ, Kannel WB, Stokes J 3rd, Castelli WP. Incidence and precursors of hypertension in young adults: the Framingham Offspring Study. Prev Med. 1987;16:235–51.

    Article  CAS  Google Scholar 

  14. Must A, Spadano J, Coakley EH, Field AE, Colditz G, Dietz WH. The disease burden associated with overweight and obesity. JAMA. 1999;282:1523–9.

    Article  CAS  Google Scholar 

  15. Spiegelman D, Israel RG, Bouchard C, Willett WC. Absolute fat mass, percent body fat, and body-fat distribution: which is the real determinant of blood pressure and serum glucose? Am J Clin Nutr. 1992;55:1033–44.

    Article  CAS  Google Scholar 

  16. Deurenberg P, Weststrate JA, Seidell JC. Body mass index as a measure of body fatness: age- and sex-specific prediction formulas. Br J Nutr. 1991;65:105–14.

    Article  CAS  Google Scholar 

  17. Gallagher D, Heymsfield SB, Heo M, Jebb SA, Murgatroyd PR, Sakamoto Y. Healthy percentage body fat ranges: an approach for developing guidelines based on body mass index. Am J Clin Nutr. 2000;72:694–701.

    Article  CAS  Google Scholar 

  18. Lean ME, Han TS, Deurenberg P. Predicting body composition by densitometry from simple anthropometric measurements. Am J Clin Nutr. 1996;63:4–14.

    Article  CAS  Google Scholar 

  19. Santos Silva DA, Petroski EL, Peres MA. Is high body fat estimated by body mass index and waist circumference a predictor of hypertension in adults? A population-based study. Nutr J. 2012;11:112.

    Article  Google Scholar 

  20. Popkin BM, Du S, Zhai F, Zhang B. Cohort Profile: The China Health and Nutrition Survey—monitoring and understanding socio-economic and health change in China, 1989–2011. Int J Epidemiol. 2010;39:1435–40.

    Article  Google Scholar 

  21. World Health Organization. Brief intervention for hazardous and harmful drinking: a manual for use in primary care. Geneva: World Health Organization; 2001.

  22. Chobanian AV, Bakris GL, Black HR, Cushman WC, Green LA, Izzo JL Jr., et al. The Seventh Report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure: the JNC 7 report. JAMA. 2003;289:2560–72.

    Article  CAS  Google Scholar 

  23. Chandra A, Neeland IJ, Berry JD, Ayers CR, Rohatgi A, Das SR, et al. The relationship of body mass and fat distribution with incident hypertension: observations from the Dallas Heart Study. J Am Coll Cardiol. 2014;64:997–1002.

    Article  Google Scholar 

  24. Durnin JV, Womersley J. Body fat assessed from total body density and its estimation from skinfold thickness: measurements on 481 men and women aged from 16 to 72 years. Br J Nutr. 1974;32:77–97.

    Article  CAS  Google Scholar 

  25. WHO. Global health risks: mortality and burden of disease attributable to selected major risks. World Health Organization, 2009. https://apps.who.int/iris/handle/10665/44203.

  26. Gus M, Fuchs SC, Moreira LB, Moraes RS, Wiehe M, Silva AF, et al. Association between different measurements of obesity and the incidence of hypertension. Am J Hypertens. 2004;17:50–3.

    Article  Google Scholar 

  27. Wang T-D, Goto S, Bhatt DL, Steg PG, Chan JC, Richard AJ, et al. 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. Metab Clin Exp. 2010;59:400–8.

    Article  CAS  Google Scholar 

  28. 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.

    Article  Google Scholar 

Download references

Acknowledgements

This research uses data from China Health and Nutrition Survey (CHNS). We thank the National Institute of Nutrition and Food Safety, China Center for Disease Control and Prevention, Carolina Population Center, the University of North Carolina at Chapel Hill, the NIH (R01-HD30880, DK056350, and R01-HD38700) and the Fogarty International Center, NIH for financial support for the CHNS data collection and analysis files from 1989 to 2006 and both parties plus the China-Japan Friendship Hospital, Ministry of Health for support for CHNS 2009 and future surveys.

Funding

This work was supported by the National Natural Science Foundation of China (71704131).

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Correspondence to Wenli Lu.

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Chen, Y., Liang, X., Zheng, S. et al. The comparison of percent body fat estimated by different anthropometrics to predict the incidence of hypertension. J Hum Hypertens 34, 51–58 (2020). https://doi.org/10.1038/s41371-019-0240-9

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