Obesity and Hypertension: A Product of BMI and WHR is a Better Predictor of Hypertension
Abstract:
Obesity is a modifiable risk factor
for hypertension. Waist-hip-ratio is favored over body mass index for assessing
truncal obesity and cardiometabolic risk. Is a product of body mass index and waist-hip-ratio
a better predictor of hypertension than waist-hip-ratio?
The objective of this study was to
determine the measure of obesity that best predicted hypertension. The study was
a cross-sectional survey of 3013 participants across the 36 states of Nigeria and
Abuja. The census sampling technique was used to collect the data. The data collecting
instruments included measuring tape, stadiometer, weighing scale, and Amron blood
pressure monitor. The data was analyzed using X2 test and correlation.
The mean body mass index of the participants
was 26.99 ± 4.89kg/m2, waist circumference 79.13 ± 26.72m, hip circumference
87.24 ± 28.57cm, waist-hip-ratio 0.91 ± 0.07, systolic blood pressure 129 ± 18mmHg,
and diastolic blood pressure 80 ± 12mmHg.
Measures of obesity had statistically
significant positive correlation with systolic and diastolic blood pressures. The
best predictor of hypertension was a product of body mass index and waist-hip-ratio
(r .228 and .200), followed by body mass index (r .191 and .180), then waist-hip-ratio
(r .187 and .135), waist circumference (r .082 and .089), and lastly hip circumference
(r .040 and .060).
A product of body mass index and
waist-hip-ratio should be used to assess obesity since it predicts hypertension
better than either of the two alone. This study should also be extended to other
risk factors of cardiovascular disease like diabetes and dyslipidemia.
Keyword: Body Mass Index,
Waist Hip Ratio, Waist Circumference, Hip Circumference, Hypertension.
References:
[1].
Adab, P., Pallan, M., & Whincup, P. H. (2018). Is BMI the
best measure of obesity? BMJ, 360, k1274.
[2].
Agbim, U., Carr, R. M., Pickett-Blakely, O., & Dagogo-Jack,
S. (2019). Ethnic disparities in adiposity: focus on non-alcoholic fatty liver disease,
visceral, and generalized obesity. Current Obesity Reports, 1-12.
[3].
Chrysant, S. G. (2019). Pathophysiology and treatment of obesity‐related hypertension. The Journal of Clinical Hypertension,
21(5), 555-559.
[4].
Fang, H. Y., Liu, D., Zhao, L. Y., Yu, D. M., Zhang, Q., Yu,
W. T., & Zhao, W. H. (2018). Epidemiological characteristics of waist circumference
and abdominal obesity among Chinese children and adolescents aged 6-17 years. Zhonghua
Liu Xing Bing Xue Za Zhi Zhonghua Liuxingbingxue Zazhi, 39(6), 715-719.
[5].
Freisling, H., Arnold, M., Soerjomataram, I., O'Doherty, M. G.,
Ordóñez-Mena, J. M., Bamia, C., & Tsilidis, K. (2017). Comparison of general
obesity and measures of body fat distribution in older adults in relation to cancer
risk: meta-analysis of individual participant data of seven prospective cohorts
in Europe. British Journal of Cancer, 116(11), 1486.
[6].
Frühbeck, G., Busetto, L., Dicker, D., Yumuk, V., Goossens, G.
H., Hebebrand, J., & Toplak, H. (2019). The ABCD of obesity: an EASO position
statement on a diagnostic term with clinical and scientific implications. Obesity
Facts, 12(2), 131-136.
[7].
Garvey, W. T. (2019). Clinical Definition of overweight and obesity.
In Bariatric Endocrinology (pp. 121-143). Springer, Cham.
[8].
Gurunathan, U., & Myles, P. S. (2016). Limitations of body
mass index as an obesity measure of perioperative risk. British Journal of Anaesthesia,
116(3), 319-321.
[9].
Hall, J. E., do Carmo, J. M., da Silva, A. A., Wang, Z., & Hall,
M. E. (2019). Obesity, kidney dysfunction and hypertension: mechanistic links. Nature
Reviews Nephrology, 1.
[10].
Heckman, K. M., Otemuyiwa, B., Chenevert, T. L., Malyarenko,
D., Derstine, B. A., Wang, S. C., & Davenport, M. S. (2019). Validation of a
DIXON-based fat quantification technique for the measurement of visceral fat using
a CT-based reference standard. Abdominal Radiology, 44(1), 346-354.
[11].
Jones, D. J., Lal, S., Gittins, M., Strauss, B. J. G., &
Burden, S. T. (2019). Practical measurement of body composition using bioelectrical
impedance, air displacement plethysmography and ultrasound in stable outpatients
with short bowel syndrome receiving home parenteral nutrition: comparison of agreement
between the methods. Journal of Human Nutrition and Dietetics, 32(3),
288-294.
[12].
Kotsis, V., Antza, C., Doundoulakis, G., & Stabouli, S. (2019).
Obesity, hypertension, and dyslipidemia. Obesity: Pathogenesis, Diagnosis, and
Treatment, 227-241.
[13].
Kutáč, P., Bunc, V., & Sigmund, M. (2019). Whole-body dual-energy
X-ray absorptiometry demonstrates better reliability than segmental body composition
analysis in college-aged students. PloS One, 14(4), e0215599.
[14].
Lalazar, G. (2015). Central obesity: redefining normal BMI. Science
Translational Medicine, 7(316), 316ec209-316ec209.
[15].
Mastroeni, S. S. D. B. S., Mastroeni, M. F., Ekwaru, J. P., Setayeshgar,
S., Veugelers, P. J., Gonçalves, M. D. C., & Rondó, P. H. D. C. (2019). Anthropometric
measurements as a potential non-invasive alternative for the diagnosis of metabolic
syndrome in adolescents. Archives of Endocrinology and Metabolism, 63(1),
30-39.
[16].
Shams-White, M., Chui, K., Deuster, P., McKeown, N., & Must,
A. (2019). A Comparison of anthropometric measures with bioelectrical impedance
analysis in the classification of overweight and obesity in US military personnel
(P21-050-19). Current Developments in Nutrition, 3(Suppl 1).
[17].
Stanford, F. C., Lee, M., & Hur, C. (2019, February). Race,
ethnicity, sex, and obesity: is it time to personalize the scale? In Mayo Clinic
Proceedings (Vol. 94, No. 2, pp. 362-363). Elsevier.
[18].
Weaver, R. G., Beets, M. W., Brazendale, K., & Hunt, E. (2019).
Disparities by household income and race/ethnicity: the utility of BMI for surveilling
excess adiposity in children. Ethnicity & Health, 1-16.
[19].
Woo, E. J., & OH, T. I. (2019). Body fat measurement apparatus
and method. U.S. Patent Application No. 16/082,566.