HYGIENIC ASSESSMENT OF EARLY MANIFESTATIONS OF DYSMETABOLIC DISORDERS IN WOMEN
The purpose of the study is to identify in healthy women of different ages the features of anthropometric indicators, body constitution and blood pressure, which can serve as risk factors and lead to the further development of the metabolic syndrome. Materials and methods. 39 women were examined, who were completely healthy, who applied to the AgeFree Center for Health and Longevity Technology (Kiev) during 2018-2019 in order to assess their health status and further recommendations for correction according to the revealed deviations and existing changed indicators. The average age of women was (40.37 ± 1.56) years. In the first group at the age of 21-30 years old there were 7
people, in the second group at the age of 31-40 years old - 13 people, 41-50 years old - 12 people and 50-60 years old - 7 people. In a comprehensive study, non-invasive methods were used - determination of anthropometric indicators - height, body weight, waist circumference, abdominal circumference, waist / hips ratio, body mass index, body shape index. Body composition components were measured with an InBody 220 apparat with impedance analysis. The metabolic profile was evaluated using FITMATE, a portable metabolograph. Indicators of the cardiovascular profile were determined in the CARDIOLAB + HRV system. The obtained digital data was processed by the method of variation statistics using application programs Microsoft Excel 7.0. It was found that in 27 (72.6%) of the examined women, the waist circumference exceeded 85 cm. In the examined women, in terms of the distribution of fat - waist circumference / hip circumference (for women the norm is 0.65-0.84) - it was found that in two individuals, the indicator had normal values, in one it was high, and in 36 it was low. With age, the number of women with exceeded rates is growing. According to the body mass index, the number of women with obesity of varying severity increases with age, but decreases with normal and overweight. With age, changes in body composition indicators occur: the amount of
bone mass between different age groups differs insignificantly (p> 0.05), the volume of skeletal muscle decreases; the volume and percentage of fat mass at the age of 21-30 years is the smallest - (15.50 ± 0.53)%, and after 30 years it increases and remains so up to 60 years, the value of the body mass index should be taken into account when analyzing. The difference in the value of the index of body shape between a group of young people and groups of older women is established. Perhaps the body shape index is one of the first to respond to changes in metabolic status. That is, with age, the main exchange shows a deviation in the direction of decrease / increase in an increasing number of women, mainly, in the direction of decrease. Having analyzed such a sign as arterial hypertension (above 130/85 mm Hg), it was found that there was no increase in systolic blood pressure in the first group, in the second group was observed in 3 people, in the third - in 3 people and the fourth - in 3 human. Changes in diastolic blood pressure were found in the second, third and fourth groups, in 4, 4 and 3 women, respectively. In each group there are different in magnitude indicators, but with age they are transformed upward.
литературы). Вестн новых мед технологий. 2011;18(4):121-3.
2. Информационный бюллетень Всемирной организации здравоохранения. 2014:311.
3. Ослопов ВН, Богоявленская ОВ. Индекс формы тела - новый индикатор риска преждевременной смерти. Казан мед ж. 2015.96(2):253-256.
4. Abd El-Wahab EW, Shatat HZ, Charl F. Adapting a prediction rule for metabolic syndrome risk assessment suitable for developing countries. J Prim Care Community Health. 2019 JanDec;10:2150132719882760.
5. Cheng JB. A body shape index in middle-aged and older Indonesian population: scaling exponents and association with incident hypertension. PLoS One. 2014; 9(1): e85421.
6. Desprйs JP, Lemieux I. Abdominal obesity and metabolic syndrome. Nature. 2006 Dec 14;444(7121):881-7.
7. Duncan MG, Mota G, Vale S. Assotiations between body mass index, waist circumference and body shape index with resting blood pressure in Portuguence adolescents. Ann Hum Biol. 2013; 40:163-7.
8. Esmailnasab N, Moradi G, Delaveri A. Risk factors of non-communicable diseases and metabolic syndrome. Iran J Public Health. 2012;41(7):77-85.
9. Fedeli U, Schievano E, Targher G, Bonora E, Corti MC, Zoppini G. Estimating the real burden of cardiovascular mortality in diabetes. Eur Rev Med Pharmacol Sci. 2019 Aug;23(15):6700-6706. doi: 10.26355/eurrev_201908_18561.
10. Joshi R, Peiris D. Task-sharing for the prevention and control of non-communicable diseases. Lancet Glob Health. 2019 Jun;7(6):e686-e687. doi: 10.1016/S2214-109X(19)30161-5/.
11. He S, Chen X. Could the new body shape index predict the new onset of diabetes mellitus in the Chines population. PLoS One. 2013;8(1):P.50573.
12. Matsha TE, Hassan VS, Hon GM. Derivation and Validation of a waist circumference optimal out off for diagnosting metabolic syndrome in a South Africa mixed ancestry population. Intern J Cardiol. 2013;168:2954-5.
13. McCracken E, Monaghan M, Sreenivasan S. Pathophysiology of the metabolic syndrome. Clin Dermatol. 2018 Jan - Feb;36(1):14-20. doi: 10.1016/ j.clindermatol.2017.09.004.
14. Mensah GA, Roth GA, Fuster V. The global burden of cardiovascular diseases and risk factors: 2020 and beyond. J Am Coll Cardiol. 2019 Nov 19;74(20):2529-2532.
15. Rocha E. Metabolic syndrome and cardiovascular risk. Rev Port Cardiol. 2019 May;38(5):333-335. doi: 10.1016/j.repc.2019.06.003.
16. Rochlani Y, Pothineni NV, Kovelamudi S, Mehta JL. Metabolic syndrome: pathophysiology, management, and modulation by natural compounds. Ther Adv Cardiovasc Dis. 2017 Aug;11(8):215-225..
17. Sponholtz TR, Van den Heuvel ER, Xanthakis V, Vasan RS. Association of variability in body mass index and metabolic health with cardiometabolic disease risk. J Am Heart Assoc. 2019 Apr 2;8(7):e010793. doi: 10.1161/JAHA.118.010793.
18. Wolk R, Somers VK. Obesity-related cardiovascular disease: implications of obstructive sleep apnea. Diabetes Obes Metab. 2006 May;8(3):250-60.