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Measurement and Decomposition of Socioeconomic Inequality in Metabolic Syndrome: A Cross-sectional Analysis of the RaNCD Cohort Study in the West of Iran

  • Moslem Soofi (Social Development and Health Promotion Research Center, Health Institute, Kermanshah University of Medical Sciences) ;
  • Farid Najafi (Research Center for Environmental Determinants of Health, Health Institute, Kermanshah University of Medical Sciences) ;
  • Shahin Soltani (Research Center for Environmental Determinants of Health, Health Institute, Kermanshah University of Medical Sciences) ;
  • Behzad Karamimatin (Research Center for Environmental Determinants of Health, Health Institute, Kermanshah University of Medical Sciences)
  • 투고 : 2022.08.23
  • 심사 : 2022.11.22
  • 발행 : 2023.01.31

초록

Objectives: Socioeconomic inequality in metabolic syndrome (MetS) remains poorly understood in Iran. The present study examined the extent of the socioeconomic inequalities in MetS and quantified the contribution of its determinants to explain the observed inequality, with a focus on middle-aged adults in Iran. Methods: This cross-sectional study used data from the Ravansar Non-Communicable Disease cohort study. A sample of 9975 middleaged adults aged 35-65 years was analyzed. MetS was assessed based on the International Diabetes Federation definition. Principal component analysis was used to construct socioeconomic status (SES). The Wagstaff normalized concentration index (CIn) was employed to measure the magnitude of socioeconomic inequalities in MetS. Decomposition analysis was performed to identify and calculate the contribution of the MetS inequality determinants. Results: The proportion of MetS in the sample was 41.1%. The CIn of having MetS was 0.043 (95% confidence interval, 0.020 to 0.066), indicating that MetS was more concentrated among individuals with high SES. The main contributors to the observed inequality in MetS were SES (72.0%), residence (rural or urban, 46.9%), and physical activity (31.5%). Conclusions: Our findings indicated a pro-poor inequality in MetS among Iranian middle-aged adults. These results highlight the importance of persuading middle-aged adults to be physically active, particularly those in an urban setting. In addition to targeting physically inactive individuals and those with low levels of education, policy interventions aimed at mitigating socioeconomic inequality in MetS should increase the focus on high-SES individuals and the urban population.

키워드

과제정보

This study was funded by Kermanshah University of Medical Sciences (KUMS) (grant No. 980483).

참고문헌

  1. Maaten S, Kephart G, Kirkland S, Andreou P. Chronic disease risk factors associated with health service use in the elderly. BMC Health Serv Res 2008;8:237.
  2. Miranda PJ, DeFronzo RA, Califf RM, Guyton JR. Metabolic syndrome: definition, pathophysiology, and mechanisms. Am Heart J 2005;149(1):33-45. https://doi.org/10.1016/j.ahj.2004.07.013
  3. Beltran-Sanchez H, Harhay MO, Harhay MM, McElligott S. Prevalence and trends of metabolic syndrome in the adult U.S. population, 1999-2010. J Am Coll Cardiol 2013;62(8):697-703. https://doi.org/10.1016/j.jacc.2013.05.064
  4. Saklayen MG. The global epidemic of the metabolic syndrome. Curr Hypertens Rep 2018;20(2):12.
  5. Wilson PW, D'Agostino RB, Parise H, Sullivan L, Meigs JB. Metabolic syndrome as a precursor of cardiovascular disease and type 2 diabetes mellitus. Circulation 2005;112(20):3066-3072. https://doi.org/10.1161/CIRCULATIONAHA.105.539528
  6. Pischon T, Hu FB, Rexrode KM, Girman CJ, Manson JE, Rimm EB. Inflammation, the metabolic syndrome, and risk of coronary heart disease in women and men. Atherosclerosis 2008; 197(1):392-399. https://doi.org/10.1016/j.atherosclerosis.2007.06.022
  7. Al-Daghri NM, Alkharfy KM, Al-Attas OS, Khan N, Alfawaz HA, Alghanim SA, et al. Gender-dependent associations between socioeconomic status and metabolic syndrome: a cross-sectional study in the adult Saudi population. BMC Cardiovasc Disord 2014;14:51.
  8. Cameron AJ, Shaw JE, Zimmet PZ. The metabolic syndrome: prevalence in worldwide populations. Endocrinol Metab Clin North Am 2004;33(2):351-375. https://doi.org/10.1016/j.ecl.2004.03.005
  9. Cornier MA, Dabelea D, Hernandez TL, Lindstrom RC, Steig AJ, Stob NR, et al. The metabolic syndrome. Endocr Rev 2008; 29(7):777-822. https://doi.org/10.1210/er.2008-0024
  10. Blanquet M, Legrand A, Pelissier A, Mourgues C. Socio-economics status and metabolic syndrome: a meta-analysis. Diabetes Metab Syndr 2019;13(3):1805-1812. https://doi.org/10.1016/j.dsx.2019.04.003
  11. Pan WH, Yeh WT, Weng LC. Epidemiology of metabolic syndrome in Asia. Asia Pac J Clin Nutr 2008;17 Suppl 1:37-42.
  12. Hajian-Tilaki K. Metabolic syndrome and its associated risk factors in Iranian adults: a systematic review. Caspian J Intern Med 2015;6(2):51-61.
  13. Shafiee G, Qorbani M, Heshmat R, Mohammadi F, Sheidaei A, Motlagh ME, et al. Socioeconomic inequality in cardio-metabolic risk factors in a nationally representative sample of Iranian adolescents using an Oaxaca-Blinder decomposition method: the CASPIAN-III study. J Diabetes Metab Disord 2019; 18(1):145-153. https://doi.org/10.1007/s40200-019-00401-6
  14. Pasdar Y, Najafi F, Moradinazar M, Shakiba E, Karim H, Hamzeh B, et al. Cohort profile: Ravansar Non-Communicable Disease cohort study: the first cohort study in a Kurdish population. Int J Epidemiol 2019;48(3):682-683f.
  15. Poustchi H, Eghtesad S, Kamangar F, Etemadi A, Keshtkar AA, Hekmatdoost A, et al. Prospective Epidemiological Research Studies in Iran (the PERSIAN Cohort Study): rationale, objectives, and design. Am J Epidemiol 2018;187(4):647-655. https://doi.org/10.1093/aje/kwx314
  16. International Diabetes Federation (IDF). IDF consensus worldwide definition of the metabolic syndrome; 2020 [cited 2021 Dec 14]. Available from: https://www.idf.org/e-library/consensus-statements/60-idfconsensus worldwide-definitionofthe-metabolic-syndrome.html.
  17. Vyas S, Kumaranayake L. Constructing socio-economic status indices: how to use principal components analysis. Health Policy Plan 2006;21(6):459-468. https://doi.org/10.1093/heapol/czl029
  18. McKenzie DJ. Measuring inequality with asset indicators. J Popul Econ 2005;18(2):229-260. https://doi.org/10.1007/s00148-005-0224-7
  19. Jette M, Sidney K, Blumchen G. Metabolic equivalents (METS) in exercise testing, exercise prescription, and evaluation of functional capacity. Clin Cardiol 1990;13(8):555-565. https://doi.org/10.1002/clc.4960130809
  20. Ainsworth BE, Haskell WL, Herrmann SD, Meckes N, Bassett DR Jr, Tudor-Locke C, et al. 2011 Compendium of Physical Activities: a second update of codes and MET values. Med Sci Sports Exerc 2011;43(8):1575-1581. https://doi.org/10.1249/MSS.0b013e31821ece12
  21. Wagstaff A. The bounds of the concentration index when the variable of interest is binary, with an application to immunization inequality. Health Econ 2005;14(4):429-432. https://doi.org/10.1002/hec.953
  22. Wagstaff A, Paci P, van Doorslaer E. On the measurement of inequalities in health. Soc Sci Med 1991;33(5):545-557. https://doi.org/10.1016/0277-9536(91)90212-U
  23. Wagstaff A. The concentration index of a binary outcome revisited. Health Econ 2011;20(10):1155-1160. https://doi.org/10.1002/hec.1752
  24. O'Donnell O, O'Neill S, Van Ourti T, Walsh B. Conindex: estimation of concentration indices. Stata J 2016;16(1):112-138. https://doi.org/10.1177/1536867X1601600112
  25. "O'Donnell O, van Doorslaer E, Wagstaff A, Lindelow M. Analyzing health equity using household survey data: a guide to techniques and their implementation; 2008 [cited 2021 Jan 14]. Available from: https://openknowledge.worldbank.org/handle/10986/6896.
  26. Nikbakht HA, Rezaianzadeh A, Seif M, Ghaem H. Factor analysis of metabolic syndrome components in a population-based study in the South of Iran (PERSIAN Kharameh Cohort Study). Iran J Public Health 2021;50(9):1863-1871.
  27. Ferns GA, Ghayour-Mobarhan M. Metabolic syndrome in Iran: a review. Transl Metab Syndr Res 2018;1:10-22. https://doi.org/10.1016/j.tmsr.2018.04.001
  28. Najafi F, Soltani S, Karami Matin B, Kazemi Karyani A, Rezaei S, Soofi M, et al. Socioeconomic - related inequalities in overweight and obesity: findings from the PERSIAN cohort study. BMC Public Health 2020;20(1):214.
  29. Najafi F, Pasdar Y, Hamzeh B, Rezaei S, Moradi Nazar M, Soofi M. Measuring and decomposing socioeconomic inequalities in adult obesity in Western Iran. J Prev Med Public Health 2018; 51(6):289-297. https://doi.org/10.3961/jpmph.18.062
  30. Yang JJ, Yoon HS, Lee SA, Choi JY, Song M, Han S, et al. Metabolic syndrome and sex-specific socio-economic disparities in childhood and adulthood: the Korea National Health and Nutrition Examination Surveys. Diabet Med 2014;31(11):1399-1409. https://doi.org/10.1111/dme.12525
  31. Joshi C, Thanikachalam M, Bermudez OI, Chui KK. Disparities in prevalence of metabolic syndrome: a cross-sectional analysis of Indian adults. Eur J Public Health 2020;30(Suppl 5):ckaa166.1078.
  32. Nguyen TH, Tang HK, Kelly P, van der Ploeg HP, Dibley MJ. Association between physical activity and metabolic syndrome: a cross sectional survey in adolescents in Ho Chi Minh City, Vietnam. BMC Public Health 2010;10:141.
  33. Chen MS, Chiu CH, Chen SH. Risk assessment of metabolic syndrome prevalence involving sedentary occupations and socioeconomic status. BMJ Open 2021;11(12):e042802.
  34. Moreno-Ulloa J, Moreno-Ulloa A, Martinez-Tapia M, DuqueRodriguez J. Comparison of the prevalence of metabolic syndrome and risk factors in urban and rural Mexican Tarahumara-foot runners. Diabetes Res Clin Pract 2018;143:79-87.  https://doi.org/10.1016/j.diabres.2018.06.015
  35. Prabhakaran D, Chaturvedi V, Shah P, Manhapra A, Jeemon P, Shah B, et al. Differences in the prevalence of metabolic syndrome in urban and rural India: a problem of urbanization. Chronic Illn 2007;3(1):8-19. https://doi.org/10.1177/1742395307079197
  36. Noshad S, Abbasi M, Etemad K, Meysamie A, Afarideh M, Khajeh E, et al. Prevalence of metabolic syndrome in Iran: a 2011 update. J Diabetes 2017;9(5):518-525. https://doi.org/10.1111/1753-0407.12438
  37. Kazemi Karyani A, Karmi Matin B, Soltani S, Rezaei S, Soofi M, Salimi Y, et al. Socioeconomic gradient in physical activity: findings from the PERSIAN cohort study. BMC Public Health 2019;19(1):1312.
  38. Costa AC, Duarte YA, Andrade FB. Metabolic syndrome: physical inactivity and socioeconomic inequalities among non-institutionalized Brazilian elderly. Rev Bras Epidemiol 2020;23: e200046.
  39. He D, Xi B, Xue J, Huai P, Zhang M, Li J. Association between leisure time physical activity and metabolic syndrome: a meta-analysis of prospective cohort studies. Endocrine 2014;46(2): 231-240. https://doi.org/10.1007/s12020-013-0110-0
  40. Ebrahimi H, Emamian MH, Shariati M, Hashemi H, Fotouhi A. Metabolic syndrome and its risk factors among middle aged population of Iran, a population based study. Diabetes Metab Syndr 2016;10(1):19-22. https://doi.org/10.1016/j.dsx.2015.08.009