Risk Factors for Developing Abdominal Obesity among Young and Middle-Aged Residents of Saint Petersburg

Aim. To identify the most significant factors contributing to the development of abdominal obesity (AO) in young and middle-aged residents of St. Petersburg.
Design. A single-stage study conducted according to the “case — control” type.
Materials and methods. We examined 966 employees of various institutions of the city of St. Petersburg who underwent a dispensary examination in 2008–2009. Of these, 503 patients (366 women and 137 men) with AO were included in the study, whose diagnosis was established according to anthropometric studies (measurements of waist circumference, WC). The comparison group consisted of 50 people (38 women and 12 men) without AO, comparable in age and gender with patients with AO.
Results. 82.7% of people aged 30 to 39 years were obese, 91.3% of patients aged 40–49 years and 97.9% of participants aged 50–55 years, the prevalence of obesity increased with age (p < 0.01). Patients with AO were significantly more likely than participants in the comparison group to eat easily digestible carbohydrates (268 (53.3%) and 12 (24%), respectively, p < 0.001) and fats (248 (49.3%) and 11 (22%), respectively, p < 0.001). Among patients with AO, those who ate 1–2 times a day or, conversely, 6 or more times a day had body weight (p < 0.001) and body mass index (BMI) (p < 0.01) significantly higher than those examined who ate 4 times a day. When comparing BMI and WC in AO patients with different birth weights, it was found that AO patients whose birth weight was more than 4 kg had higher BMI and WC values. 482 (95.8 %) patients with abdominal obesity (AO) had low physical activity — less than 210 minutes weekly; 21 (4.2 %) patients with AO — at least 210 minutes weekly (р < 0.001). Almost all the examined patients without AO had higher education 49 (98%), while among patients with AO — only 297 (59%), p < 0.001. The analysis of the income level structure revealed that the income level of individuals with AO is slightly lower than in the group without AO.
Conclusion. The prevalence of AO among residents of St. Petersburg aged 30–55 years is 52.1%. We have created a model based on the calculation of the logistic regression equation to assess the risk of AO development. The most significant parameters influencing its formation are highlighted: the level of education, age, type of nutrition, number of meals per day, birth weight, gender, income level, physical activity.

1. Oguoma V.M., Coffee N.T., Alsharrah S., Abu-Farha M. et al. Prevalence of overweight and obesity, and associations with socio-demographic factors in Kuwait. BMC Public Health. 2021;21:667. DOI: 10.1186/s12889-021-10692-1

2. Zhernakova Yu.V., Zheleznova E.A., Chazova I.E., Oshchepkova E.V. et al. The prevalence of abdominal obesity and the association with socioeconomic status in Regions of the Russian Federation, the results of the epidemiological study — ESSE-RF. Therapeutic Archive. 2018;90(10):14–22. (in Russian)

3. Balanova Yu.A., Shalnova S.A., Deev A.D., Imaeva A.E. et al. Obesity in Russian population — prevalence and association with the non-communicable diseases risk factors. Russian Journal of Cardiology. 2018;23(6):123–30. (in Russian). DOI: 10.15829/1560-4071-2018-6-123-130

4. Kologrivova I.V., Vinnitskaya I.V., Koshelskaya O.A., Suslova T.E. Visceral obesity and cardiometabolic risk: features of hormonal and immune regulation. Obesity and Metabolism. 2017;14(3):3–10. (in Russian). DOI: 10.14341/omet201733-10

5. Carneiro Roriz A.K., Santana Passos L.C., Cunhade Oliveira C., Eickemberg M. et al. Anthropometric clinical indicators in the assessment of visceral obesity: an update. Nutr. Clin. Diet. Hosp. 2016;36(2):168–79. DOI:10.12873/362carneirororiz

6. Svarovskaya A.V., Garganeeva A.A. Anthropometric indices obesity and cardiometabolic risk: is there a link? Cardiovascular Therapy and Prevention. 2021;20(4): 2746. (in Russian). DOI: 10.15829/1728-8800-2021-2746

7. Li M., Zhu P., Wang S. Risk for cardiovascular death associated with waist circumference and diabetes: a 9-year prospective study in the Wan Shou Lu cohort. Front. Cardiovasc. Med. 2022;9:856517. DOI: 10.3389/fcvm.2022.856517

8. Alferova V.I., Mustafina S.V. The prevalence of obesity in the adult population of the Russian Federation (literature review). Obesity and Metabolism. 2022;19(1):96–105. (in Russian)

9. Kobalava Z.D., Konradi A.O., Nedogoda S.V., Shlyakhto E.V. et al. Arterial hypertension in adults. Clinical guidelines 2020. Russian Journal of Cardiology. 2020;25(3):3786. (in Russian). DOI: 10.15829/1560-4071-2020-3-3786

10. The Task Force for the management of arterial hypertension of the European Society of Cardiology (ESC) and the European Society of Hypertension (ESH). 2018 ESC/ESH Guidelines for the management of arterial hypertension. Russian Journal of Cardiology. 2018;23(12):143–228. (in Russian). DOI: 10.15829/1560-4071-2018-12-143-228

11. Gupta A., Reddy B.V., Semwal V., Singh A.K. Epidemiology of general obesity and abdominal obesity among people in Hilly areas of North India: a hospital based study. Nat. J. Community Med. 2017;8(05):230–5.

12. Hu L., Huang X., You C., Li J. et al. Prevalence of overweight, obesity, abdominal obesity and obesity-related risk factors in southern China. PloS One. 2017;12(9):e0183934. DOI: 10.1371/journal.pone.0183934

13. Mamedov M.N., Sushkova L.T., Isakov R.V., Kutsenko V.A. et al. Identification of sex characteristics of obesity and hypertension in the adult population of the Vladimir Region. Russian Journal of Cardiology. 2023;28(4):5425. (in Russian). DOI: 10.15829/1560-4071-2023-5425

14. Cattafesta M., Petarli G.B., Zandonade E., Bezerra O.M.P.A. et al. Prevalence and determinants of obesity and abdominal obesity among rural workers in Southeastern Brazil. Plos One. 2022;17(7):e0270233. DOI: 10.1371/journal.pone.0270233

15. Malyutina S.K., Serova N.V., Nikitin Yu.P., Nasonova N.V. Monitoring of cardiovascular morbidity, mortality and their risk factors in different regions of the world (WHO MONICA project). Novosibirsk: Academic Publishing House “Geo”; 2016: 275–92. (in Russian)

16. Mustafina S.V., Malyutina S.K., Rymar O.D., Shcherbakova L.V. et al. The epidemiology of obesity and the development of disorders of glucose metabolism according to a prospective study in Siberia. Obesity and Metabolism. 2015;12(4):14–28. (in Russian). DOI: 10.14341/omet2015414-28

17. Simonova G.I., Mustafina S.V., Shcherbakova L.V. Prevalence of abdominal obesity in the Siberian population. Siberian Scientific Medical Journal. 2015;35(1):60–4. (in Russian). DOI: 10.15372/SSMJ20180617

18. Karamnova N.S., Shalnova S.A., Rytova A.I., Shvabskaya O.B. et al. Associations of dietary patterns and abdominal obesity in the adult population. Results of the Russian epidemiological ESSE-RF study. Russian Journal of Cardiology. 2021;26(5):4363. (in Russian). DOI: 10.15829/1560-4071-2021-4363

19. Tsygankova D.P., Barbarash O.L. Socioeconomic determinants of eating behavior. Russian Journal of Cardiology. 2021;26(5):4403. (in Russian). DOI: 10.15829/1560-4071-2021-4403

20. Silveira E.A., Mendonça C.R., Delpino F.M., Elias Souza G.V. et al. Sedentary behavior, physical inactivity, abdominal obesity and obesity in adults and older adults: a systematic review and metaanalysis. Clin. Nutr. ESPEN. 2022;50:63–73. DOI: 10.1016/j.clnesp.2022.06.001

21. Sakurai T., Iimuro S., Araki A., Umegaki H. et al. Age-associated increase in abdominal obesity and insulin resistance, and usefulness of AHA/NHLBI definition of metabolic syndrome for predicting cardiovascular disease in Japanese elderly with type 2 diabetes mellitus. Gerontology. 2010;56(2):141–9. DOI: 10.1159/000246970

22. Ball K., Crawford D. Socioeconomic status and weight change in adults: a review. Soc. Sci. Med. 2005;60(9):987–2010. DOI: 10.1016/j.socscimed.2004.08.056

23. Ball K., Crawford D. Socio-economic factors in obesity: a case of slim chance in a fat world? Asia Pac. J. Clin. Nutr. 2006;15(suppl): 15–20.

24. Hemmingsson E., Ekblom Ö., Kallings L.V., Andersson G. et al. Prevalence and time trends of overweight, obesity and severe obesity in 447,925 Swedish adults, 1995–2017. Scand. J. Public Health. 2021;49(4):377–83. DOI: 10.1177/1403494820914802

25. Mazariegos M., Auchincloss A.H., Braverman-Bronstein A., Kroker- Lobos M.F. et al. Educational inequalities in obesity: a multilevel analysis of survey data from cities in Latin America. Public Health Nutr. 2022;25(7):1790–8. DOI: 10.1017/S1368980021002457

26. Witkam R., Gwinnutt J.M., Humphreys J., Gandrup J. et al. Do associations between education and obesity vary depending on the measure of obesity used? A systematic literature review and meta-analysis. SSM Popul. Health. 2021;15:100884. DOI: 10.1016/j.ssmph.2021.100884

27. García-Mendizábal M.J., Carrasco J.M., Pérez-Gómez B., Aragonés N. et al. Role of educational level in the relationship between body mass index (BMI) and health-related quality of life (HRQL) among rural Spanish women. BMC Public Health. 2009;9:120. DOI: 10.1186/1471-2458-9-120

28. Gensthaler L., Felsenreich D.M., Jedamzik J., Eichelter J. et al. Trends of overweight and obesity in male adolescents: prevalence, socioeconomic status, and impact on cardiovascular risk in a central European country. Obes. Surg. 2022;32(4):1024–33. DOI: 10.1007/s11695-021-05867-z

29. Nam G.E., Kim Y.H., Han K., Jung J.H. et al. Obesity fact sheet in Korea, 2019: prevalence of obesity and abdominal obesity from 2009 to 2018 and social factors. J. Obes. Metab. Syndr. 2020;29(2):124. DOI: 10.7570/jomes20058

30. Mayén A.L., Marques-Vidal P., Paccaud F., Bovet P. et al. Socioeconomic determinants of dietary patterns in low- and middle-income countries: a systematic review. Am. J. Clin. Nutr. 2014;100(6):1520–31. DOI: 10.3945/ajcn.114.089029

31. Miller V., Yusuf S., Chow C.K., Dehghan M. et al. Availability, affordability, and consumption of fruits and vegetables in 18 countries across income levels: findings from the Prospective Urban Rural Epidemiology (PURE) study. Lancet Global Health. 2016;4(10):e695–703. DOI: 10.1016/S2214-109X(16)30186-3

32. Gmoshinskaya A.A., Kaseka G.R., Babina T.D. Serum leptin levels and several other clinical and hormonal indices in men with different eating behaviour. Siberian Scientific Medical Journal. 2003;107(1):40–4. (in Russian)

33. Toschke A.M., Küchenhoff H., Koletzko B., von Kries R. Meal frequency and childhood obesity. Obes. Res. 2005;13(11):1932–8. DOI: 10.1038/oby.2005.238

34. Jenkins D.J., Wolever T.M., Vuksan V., Brighenti F. et al. Nibbling versus gorging: metabolic advantages of increased meal frequency. N. Engl. J. Med. 1989;321(14):929–34. DOI: 10.1056/NEJM198910053211403