Blood Pressure About General and Central Adiposity

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Introduction

Normal blood pressure is a vital component for the normal functioning of the organism. High blood pressure (BP) is a major risk factor for coronary heart disease, stroke, and other illnesses, as well as morbidity and early death (Kjeldsen, 2018). The reasons for high blood pressure are complicated and linked to a variety of environmental and hereditary variables (Chang et al., 2018). Obesity is one such recognized and researched risk factor (Chu et al., 2018). Body mass index (BMI), a broad indicator of obesity, has previously been shown to be a predictor of high blood pressure (Nurdiantami et al., 2018). An increasing body of research shows that key indicators of obesity, such as waist and hip circumferences, the waist-to-hip ratio (WHR), and the waist-to-height ratio (WHtR), are also linked to blood pressure (Luzi, 2021). The results of several research that have already looked at the relationship between various measures of central and overall obesity and BP have been mixed (Rodgers & Gibbons, 2020). According to certain research, waist size and blood pressure are connected more closely than BMI (Fu et al, 2018). Others, however, disagreed, demonstrating that BMI was a greater predictor of blood pressure than waist circumference (Tebar et al., 2018).

Additionally, Western individuals have been used in the majority of the current investigations. Asian and Western populations have different genetic profiles and BMI-based obesity assessment standards (Fu et al., 2018). It may be possible to learn more about the relationship between blood pressure and various indicators of overall or central obesity by conducting research with a limited number of adult men and women who reside in Hong Kong. This may not only assist in guiding public health policies for the prevention of high blood pressure and associated cardiovascular disease, but it may also give important information on this subject for global cardiovascular disease research.

The current research examined cross-sectional data on a small group of 38 adults, including 27 females and 11 males were examined. The age of the participants was not recorded for privacy protection. This group of people is part-time students and has already undergone a 2-year sedentary, Zoom class study due to the pandemic. This report aims to study the relationship between general and central adiposity vs. blood pressure.

Materials & Methods

Main adiposity variables, either directly measured or derived, were assessed. They included gender (male and female), normal and infrared stadiometer measures, weight, waist-to-height ratio, waist and hip circumference, waist-to-hip ratio, bioelectrical impedance analysis, and blood pressure. Participants were wearing light clothes and no shoes. Weight was measured to the nearest 0.1 kg using a body composition analyzer (TANITA-TBF-521; Tanita Corporation). Waist circumference and hip circumference were measured to the nearest 0.1 cm using a soft non-stretchable tape. Body fat percentage was estimated to be fat weight by the Tanita body composition analyzer. Multiple linear regression has been applied to estimate the effects on systolic blood pressure (SBP) of general adiposity (body mass index, body fat percentage, weight) and central adiposity (waist circumference, hip circumference, waist-hip ratio).

Results

Among the included participants, the overall mean BMI was 21.18 kg/m2, with no one participant having a BMI higher than 30 kg/m2. The mean BMI for males is 22.17 kg/m2, while for females, it is 20.78 kg/m2. In most cases, a higher body mass index in both men and women was associated with higher blood pressure. Measurement of blood pressure in men generally showed higher results than in women. A similar trend applies to the waist-to-height. People with a higher WHtR often had higher blood pressure than people with a lower WHtR, but the difference is less significant than in the case of body mass index. In men, this relationship is much less than in women. Waist-to-hip ratio was the least associated with changes in blood pressure. Bioelectrical impedance analysis also showed no significant relationship with blood pressure.

Discussion

In this cross-sectional study of 38 adults, body mass index turned out to be the strongest predictor of blood pressure in both men and women. Among the widely used clinical measures of adiposity, waist-to-height was the next strongest predictor of high blood pressure and was largely consistent with BMI. WHR was a relatively weak predictor in the selected group. The results of this study are consistent with previous studies and confirm that BMI is a stronger predictor of high blood pressure, but differ from those stating that WHR waist height ratio was a stronger predictor of blood pressure than BMI. The reasons for these discrepancies are complex, but this study is much larger than any previous studies and uses measured blood pressure rather than a history of hypertension. These differences are not that large, and given the small sample size, this may be due to randomness or differences in levels not large enough to cause confusion.

It is also worth considering that most of the other studies were conducted with Western participants. Therefore the insignificance of the effect of WHR on blood pressure may be due to genetic differences and differences. In addition, the sample consisted of students who have been studying remotely for several years due to the COVID-19 pandemic and related lockdowns. An unaccustomed lifestyle can be reflected in various measurements of volume, as a decrease in physical activity could lead to loss of muscle mass (Saxton et al., 2019). It is unclear whether these data are sufficient to stress the association between blood pressure and their measures because very few research participants were fat. It’s also likely that the degree of this association is not biologically universal but instead varies regionally or over time, for instance as a result of interactions with other environmental variables like nutrition or genetic risk factors for either blood pressure or obesity (Maltoni et al., 2021). The results of the current study demonstrate that central obesity is a less significant predictor of blood pressure than overall obesity, and their relationship with blood pressure may be mostly or entirely because of their close relationship to measures of overall obesity.

Weight-for-height was a reliable predictor, but without using weight-for-height tables again, it is difficult to use this variable in clinical practice. However, each of the indications supplemented the other with some independent prediction data (Fowokan, 2019). These findings demonstrate that adipose tissue, in general, rather than simply that located around the abdomen or specifically in the intra-abdominal area, can contribute to elevated blood pressure (He et al., 2019). This may be a counterargument to the theory that adiposity primarily raises blood pressure through physical kidney compression or systemic inflammation and oxidative stress, which are highly dependent on the quantity of intra-abdominal fat (Hall et al., 2019). High blood pressure may instead be brought on by other theories that are mostly independent of intra-abdominal fat, such as adipose tissue malfunction and sympathetic nervous system activation (Valenzuela et al., 2021).

Conclusion

The best predictor of blood pressure in both men and women was found to be body mass index. The second best predictor of high blood pressure among the commonly used clinical measures of adiposity was waist-to-height, which was essentially consistent with BMI. WHR performed poorly as a predictor in the chosen group. The findings of this study differ from those claiming that waist height ratio (WHR) was a better predictor of blood pressure than BMI, but they are in line with other studies in that they demonstrate that BMI is a greater predictor of high blood pressure. Suppose BMI is a particularly effective predictor of blood pressure. In that case, the capacity of BMI and WC to predict the risk of CVD may also change among communities and over time, as may be seen in Western nations as diabetes becomes more common increases. However, the typical arterial pressure falls as people get older. These theories should be tested by large prospective cohort studies that are now being conducted in a variety of populations (Ramírez Manent et al., 2022). There may also be a need for more research on the association of BIA with elevated blood pressure, as only one Tanita analyzer was used. A study with several analyzers from different manufacturers would have given more accurate results and made it possible to establish such a relationship. In addition, the sample was quite small and uneven in terms of gender. Increasing the number of participants could help to reveal clearer patterns in the ratio of different measurements to blood pressure.

References

Chang, L., Xiong, W., Zhao, X., Fan, Y., Guo, Y., Garcia-Barrio, M. & Chen, Y. E. (2018). . Circulation, 138(1), 67-79. Web.

Chu, D. T., Nguyet, N. T. M., Dinh, T. C., Lien, N. V. T., Nguyen, K. H., Ngoc, V. T. N. & Pham, V. H. (2018). . Diabetes & Metabolic Syndrome: Clinical Research & Reviews, 12(6), 1095-1100. Web.

Fowokan, A. (2019). Elevated blood pressure and hypertension in South Asian Children: A mixed-methods analysis exploring associated factors and behavioural influences. Simon Fraser University.

Fu, W., Cao, S., Liu, B., Li, H., Song, F., Gan, Y., & Lu, Z. (2018). . Journal of hypertension, 36(12), 2406-2413. Web.

Hall, J. E., do Carmo, J. M., da Silva, A. A., Wang, Z., & Hall, M. E. (2019). . Nature reviews nephrology, 15(6), 367-385. Web.

He, M., Xian, Y., Lv, X., He, J., & Ren, Y. (2021). . Disaster medicine and public health preparedness, 15(2), 23-28. Web.

Kjeldsen, S. E. (2018). . Pharmacological research, 129, 95-99. Web.

Linderman, G., Lu, J., Lu, Y., Sun, X., Xu, W., Nasir, K., Schulz, W., Jiang, L., Krumholz, H. (2018). . JAMA network open, 1(4), 181271. Web.

Luzi L. (2021). Thyroid, obesity and metabolism: Exploring links between thyroid function, obesity, metabolism and lifestyle. Springer Nature.

Maltoni, G., Zioutas, M., Deiana, G., Biserni, G. B., Pession, A., & Zucchini, S. (2021). . Nutrition, Metabolism and Cardiovascular Diseases, 31(7), 2181-2185. Web.

Nurdiantami, Y., Watanabea, K., Tanakaa, E., Pradonob, J., Anmea, T. (2018). . Clinical nutrition, 37(4), 1259-1263. Web.

Ramírez Manent, J. I., Altisench Jané, B., Sanchís Cortés, P., Busquets-Cortés, C., Arroyo Bote, S., Masmiquel Comas, L., & López González, Á. A. (2022). . Nutrients, 14(6), 1237. Web.

Rodgers, G. P., & Gibbons, G. H. (2020). . Jama, 324(12), 1163-1165. Web.

Saxton, S., Clark, B., Withers, S., Eringa, E., & Heagerty, A. (2019). . Physiological reviews, 99(4), 1701-1763. Web.

Tebar, W. R., Ritti-Dias, R. M., Farah, B. Q., Zanuto, E. F., Vanderlei, L. C. M., & Christofaro, D. G. D. (2018). . Hypertension Research, 41(2), 135-140. Web.

Valenzuela, P. L., Carrera-Bastos, P., Gálvez, B. G., Ruiz-Hurtado, G., Ordovas, J. M., Ruilope, L. M., & Lucia, A. (2021). . Nature Reviews Cardiology, 18(4), 251-275. Web.

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