Exploring Anthropometric, Biochemistry and Nutritional Attributes in Overweight and Obese Women: Insights from the Serbian Cohort
Keywords:
anthropometric measurements; BMI; Castelli’s risk ratio; obesity; VAI
Abstract
Summary:
Introduction: Anthropometric measurements (AMs), such as waist circumference and body mass index (BMI), are dominant indicators of overweight and obesity. Nevertheless, other AMs, such as waist‒hip ratio, waist circumference and indices of visceral adiposity index (VAI), body mass fat index (BMFI), cardiometabolic index (CMI) and waist‒to‒height ratio (WtHR) have been shown to be more significant and discriminatory than BMI in predicting cardiometabolic risk.
Methods: The aim of this study was to comprehensively investigate the anthropometric, biochemical and nutritional characteristics a sample of overweight and obese women in Serbia, focusing on potential differences related to AM and its association with specific biochemical markers.
Results: The final analytical sample consisted of 57 females (average age 37.16 ± 7.27 years, range: 21–55 years). A strong positive correlation was observed between triglycerides (TG) and both the VAI (r = 0.896, p < 0.001) and the CMI (r = 0.896, p < 0.001), both with high statistical significance. Conversely, a strong negative correlation was found between high-density lipoprotein cholesterol (HDLc) and both VAI (r = −0.601, p < 0.001) and CMI (r = −0.566, p < 0.001). Systolic blood pressure (SBP) and diastolic blood pressure (DBP) were significantly positively correlated with both WtHR and BMFI: SBP and WtHR (r = 0.343, p = 0.009), SBP and BMFI (r = 0.310, p = 0.019), DBP and WtHR (r = 0.368, p = 0.005), and DBP and BMFI (r = 0.377, p = 0.004). The analysis of biochemical parameters indicated no significant differences between groups, except for TG levels, which were significantly higher in the obese group (p = 0.045).
Conclusion: Although the AMs of the subjects were significantly different, energy intake and macronutrient intake were not significantly different. We did not find significant differences in the intake of most vitamins or minerals between the groups. Additionally, there is inadequate intake of essential nutrients such as vitamin D, iron and selenium, which are critical for overall health. Both groups did not meet the recommended folate intake, which may increase the risk of fetal neural tube defects.
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2. Милан Д, Батут Ј, Jovanovic Batut M. ИНСТИТУТ ЗА ЈАВНО ЗДРАВЉЕ СРБИЈЕ HEALTH STATISTICAL YEARBOOK OF THE REPUBLIC OF SERBIA. [cited 2024 Aug 6]; Available from: https://www.batut.org.rs/download/publikacije/pub2021a.pdf
3. Consalvo V, Krakauer JC, Krakauer NY, Canero A, Romano M, Salsano V. ABSI (A body shape index) and ARI (anthropometric risk indicator) in bariatric surgery. First application on a bariatric cohort and possible clinical use. Obes Surg. 2018 Jan 29;28(7):1966–73.
4. Lavie CJ, Milani R V., Ventura HO. Obesity and Cardiovascular Disease. Risk Factor, Paradox, and Impact of Weight Loss. Vol. 53, Journal of the American College of Cardiology. 2009. p. 1925–32.
5. Lampignano L, Zupo R, Donghia R, Guerra V, Castellana F, Murro I, et al. Cross-sectional relationship among different anthropometric parameters and cardiometabolic risk factors in a cohort of patients with overweight or obesity. PLoS One. 2020 Nov 1;15(11 November).
6. Waist circumference and waist–hip ratio: report of a WHO expert consultation G. https://apps.who.int/iris/bitstream/handle/10665/44583/9789241501491_eng.pdf?sequence=1 . 2008.
7. Ross R, Neeland IJ, Yamashita S, Shai I, Seidell J, Magni P, et al. Waist circumference as a vital sign in clinical practice: a Consensus Statement from the IAS and ICCR Working Group on Visceral Obesity. Nat Rev Endocrinol. 2020 Mar 1;16(3):177–89.
8. Pischon T, Boeing H, Hoffmann K, Bergmann M, Schulze MB, Overvad K, et al. General and Abdominal Adiposity and Risk of Death in Europe. New England Journal of Medicine. 2008 Nov 13;359(20):2105–20.
9. Després JP, Couillard C, Gagnon J, Bergeron J, Leon AS, Rao D, et al. Race, Visceral Adipose Tissue, Plasma Lipids, and Lipoprotein Lipase Activity in Men and Women The Health, Risk Factors, Exercise Training, and Genetics (HERITAGE) Family Study [Internet]. 2000. Available from: http://www.atvbaha.org
10. Kang JH, Kim H, Kim J, Seo JH, Cha S, Oh H, et al. Interaction of genetic and environmental factors for body fat mass control: observational study for lifestyle modification and genotyping. Sci Rep. 2021 Dec 1;11(1).
11. Milinković N, Bogavac-Stanojević N, Vekić J, Jovičić S, Kotur-Stevuljević J. Biochemistry and laboratory diagnosis of obesity. Arh Farm (Belgr). 2024;74(3):348–74.
12. Khanna D, Khanna S, Khanna P, Kahar P, Patel BM. Obesity: A Chronic Low-Grade Inflammation and Its Markers. Cureus. 2022 Feb 28;
13. Cena H, Calder PC. Defining a healthy diet: Evidence for the role of contemporary dietary patterns in health and disease. Vol. 12, Nutrients. MDPI AG; 2020.
14. Stoś K, Rychlik E, Woźniak A, Ołtarzewski M, Jankowski M, Gujski M, et al. Prevalence and Sociodemographic Factors Associated with Overweight and Obesity among Adults in Poland: A 2019/2020 Nationwide Cross-Sectional Survey. Int J Environ Res Public Health. 2022 Feb 1;19(3).
15. WHO Press WHOGS. World Health Organization. Waist Circumference and Waist–Hip Ratio Report of a WHO Expert Consultation. Geneva. Geneva; 2011.
16. World Health Organization. A healthy lifestyle - WHO recommendations. 2010 May.
17. InBody user manual: https://inbodyusa.zendesk.com/hc/en-us/articles/360021187812-InBody-270-User-s-Manual.
18. Mirjana Gurinović; Jelena Milešević; Agnes Kadvan; Marina Nikolić; Milica Zeković; Marija Djekić-Ivanković; Eleonora Dupouy; Paul Finglas; Maria Glibetić. Development, features and application of DIET ASSESS & PLAN (DAP) software in supporting public health nutrition research in Central Eastern European Countries (CEEC). Food Chem. 2018 Jan 1;238:186–94.
19. Gurinović M, Milešević J, Novaković R, Kadvan A, Djekić-Ivanković M, Šatalić Z, et al. Improving nutrition surveillance and public health research in Central and Eastern Europe/Balkan Countries using the Balkan Food Platform and dietary tools. Food Chem. 2016 Feb 15;193:173–80.
20. Amato MC, Giordano C, Galia M, Criscimanna A, Vitabile S, Midiri M, et al. Visceral adiposity index: A reliable indicator of visceral fat function associated with cardiometabolic risk. Diabetes Care. 2010 Apr;33(4):920–2.
21. Lazzer S, D’Alleva M, Isola M, De Martino M, Caroli D, Bondesan A, et al. Cardiometabolic Index (CMI) and Visceral Adiposity Index (VAI) Highlight a Higher Risk of Metabolic Syndrome in Women with Severe Obesity. J Clin Med. 2023 May 1;12(9).
22. Salcedo-Cifuentes M, Belalcazar S, Acosta EY, Medina-Murillo JJ. Conventional biomarkers for cardiovascular risks and their correlation with the castelli risk index-indices and tg/hdl-c. Archivos de Medicina (Manizales). 2019 Dec 14;20(1):11–22.
23. Macek P, Biskup M, Terek-Derszniak M, Stachura M, Krol H, Gozdz S, et al. Optimal body fat percentage cut-off values in predicting the obesity-related cardiovascular risk factors: A cross-sectional cohort study. Diabetes Metab Syndr Obes. 2020;13:1587–97.
24. Piqueras P, Ballester A, Durá-Gil J V., Martinez-Hervas S, Redón J, Real JT. Anthropometric Indicators as a Tool for Diagnosis of Obesity and Other Health Risk Factors: A Literature Review. Vol. 12, Frontiers in Psychology. Frontiers Media S.A.; 2021.
25. Głuszek S, Ciesla E, Głuszek-Osuch M, Kozieł D, Kiebzak W, Wypchło Ł, et al. Anthropometric indices and cut-off points in the diagnosis of metabolic disorders. PLoS One. 2020 Jun 1;15(6 June).
26. Oh YH, Choi S, Lee G, Son JS, Kim KH, Park SM. Changes in body composition are associated with metabolic changes and the risk of metabolic syndrome. J Clin Med. 2021 Feb 2;10(4):1–14.
27. Tamini S, Bondesan A, Caroli D, Sartorio A. The Lipid Accumulation Product Index (LAP) and the Cardiometabolic Index (CMI) Are Useful for Predicting the Presence and Severity of Metabolic Syndrome in Adult Patients with Obesity. J Clin Med. 2024 May 1;13(10).
28. Gol RM, Rafraf M, Jafarabadi MA. Assessment of atherogenic indices and lipid ratios in the apparently healthy women aged 30-55 years. Arterial Hypertension (Poland). 2021;25(4):172–7.
29. Babu P, Professor A, Professor A. Impact of Obesity on Castelli’s Risk Index I and II, in Young Adult Females. Int J Physiol. 8(1).
30. Bhardwaj S, Pharm IJ, Sci B, Bhardwaj S, Bhattacharjee J, Bhatnagar MK, et al. ATHEROGENIC INDEX OF PLASMA, CASTELLI RISK INDEX AND ATHEROGENIC COEFFICIENT-NEW PARAMETERS IN ASSESSING CARDIOVASCULAR RISK [Internet]. International Journal of Pharmacy and Biological Sciences. Available from: www.diabetes.com.au/pdf/obesity_report.pdf].
31. Jamil S, Siddiq A. Comparison of CVD risk associated with the long term use of contraceptives in young females. J Appl Pharm Sci. 2012;2(11):62–6.
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