LinkedIn

 آمار

تعداد نشریات20
تعداد شماره‌ها1,149
تعداد مقالات10,518
تعداد مشاهده مقاله45,415,607
تعداد دریافت فایل اصل مقاله11,291,417
Hooshmand, Farhang, Rahmanian, Vahid, Shojaei, Mohammad, Rahmanian, Karamatollah. (1402). Metabolically Unhealthy Phenotype and Its Determinants: A Population-based Study in Southern Iran. سامانه مدیریت نشریات علمی, 11(3), 472-479. doi: 10.30476/jhsss.2022.94391.1536
Farhang Hooshmand; Vahid Rahmanian; Mohammad Shojaei; Karamatollah Rahmanian. "Metabolically Unhealthy Phenotype and Its Determinants: A Population-based Study in Southern Iran". سامانه مدیریت نشریات علمی, 11, 3, 1402, 472-479. doi: 10.30476/jhsss.2022.94391.1536
Hooshmand, Farhang, Rahmanian, Vahid, Shojaei, Mohammad, Rahmanian, Karamatollah. (1402). 'Metabolically Unhealthy Phenotype and Its Determinants: A Population-based Study in Southern Iran', سامانه مدیریت نشریات علمی, 11(3), pp. 472-479. doi: 10.30476/jhsss.2022.94391.1536
Hooshmand, Farhang, Rahmanian, Vahid, Shojaei, Mohammad, Rahmanian, Karamatollah. Metabolically Unhealthy Phenotype and Its Determinants: A Population-based Study in Southern Iran. سامانه مدیریت نشریات علمی, 1402; 11(3): 472-479. doi: 10.30476/jhsss.2022.94391.1536

Metabolically Unhealthy Phenotype and Its Determinants: A Population-based Study in Southern Iran

Journal of Health Sciences & Surveillance System
دوره 11، شماره 3، مهر 2023، صفحه 472-479    اصل مقاله (455.32 K)
نوع مقاله: Original Article
شناسه دیجیتال (DOI): 10.30476/jhsss.2022.94391.1536
نویسندگان
Farhang Hooshmand1؛ Vahid Rahmanian2؛ Mohammad Shojaei1؛ Karamatollah Rahmanian* 3
1Research Center for Noncommunicable Diseases, Jahrom University of Medical Sciences, Jahrom, Iran
2Department of Public Health, Torbat Jam Faculty of Medical Sciences, Torbat Jam, Iran
3Research Center for Social Determinants of Health, Jahrom University of Medical Sciences, Jahrom, Iran
چکیده
Background: The overall prevalence of metabolically unhealthy (MU) phenotype in Iranian adults is a matter of debate. This study aimed to estimate the prevalence and determinants of metabolically unhealthystate in people over 30 years old in the general population in Southern Iran.
Methods: In this cross-sectional population-based study, 891 participants aged ≥30 were selected using a multi-stage cluster sampling method. The study examined age, sex, education, marital status, smoking behavior, weight, height, blood pressure, fasting blood sugar, and lipid profiles. MU was defined as the existence of at least two of four constituents of metabolic abnormalities based on ATP III criteria. Data analysis was carried out in Stata version 14. Finally, a logistic regression was performed to identify the risk factors for MU prevalence.
Results: The overall prevalence of MU was 49.4%, corresponding to 37.5%, 55.6%, and 60.2% of normal weight, overweight, and obese participants, respectively. MU prevalence significantly increased from 30.6% in participants aged 30-39 years to 69.7% in participants aged 60 years or older. The results of multivariate logistic regression showed that dyslipidemia (OR=2.98, CI95%:2.13-4.16), high LDL (OR=2.73, CI95%:1.77-4.20), obesity (OR=2.83, CI95%:1.84-4.36), overweight (OR=2.13, CI95%:1.53- 2.98), and higher age (OR=1.04, CI95%:1.03-1.05) was positively associated with the MU state.
Conclusion: Metabolically unhealthy state is a public health problem in the study area. In terms of public health, screening for obesity and other metabolic disorders should be regularly performed in clinical practice to take appropriate preventive measures.
کلیدواژه‌ها
Overweight؛ Prevalence؛ Obesity؛ Metabolically unhealthy؛ Dyslipidemia
مراجع
  1. Liu C, Wang C, Guan S, Liu H, Wu X, Zhang Z, et al. The Prevalence of Metabolically Healthy and Unhealthy Obesity according to Different Criteria. Obes Facts 2019; 12(1): 78-90. doi: 1159/000495852. PMCID: PMC6465689. PMID: 30814477.
  2. Song Z, Gao M, Lv J, Yu C, Guo Y, Bian Z, et al. Metabolically healthy obesity, transition to unhealthy phenotypes, and type 2 diabetes in 0.5 million Chinese adults: the China Kadoorie Biobank. Eur J Endocrinol. 2022; 186(2): 233-44. doi: 10.1530/EJE-21-0743. PMID: 34874895. PMCID: PMC8789025.
  3. Wang W, He J, Hu Y, Song Y, Zhang X, Guo H, et al. Comparison of the Incidence of Cardiovascular Diseases in Weight Groups with Healthy and Unhealthy Metabolism. Diabetes Metab Syndr Obes 2021; 14: 4155. doi: 10.2147/DMSO.S330212. PMID: 34621129. PMCID: PMC8491784.
  4. Dehghani A, Korozhdehi H, Hossein Khalilzadeh S, Fallahzadeh H, Rahmanian V. Prevalence of diabetes and its correlates among Iranian adults: Results of the first phase of Shahedieh cohort study. Health Sci Rep. 2023; 6(4): e1170. doi: 10.1002/hsr2.1170. PMID: 37021014. PMCID: PMC10069239.
  5. Mongraw-Chaffin M, Foster MC, Anderson CAM, Burke GL, Haq N, Kalyani RR, et al. Metabolically Healthy Obesity, Transition to Metabolic Syndrome, and Cardiovascular Risk. J Am Coll Cardiol 2018; 71(17): 1857-65. doi: 10.1016/j.jacc.2018.02.055. PMID: 29699611. PMCID: PMC6002856.
  6. Yu X, Wang L, Zhang W, Ming J, Jia A, Xu S, et al. Fasting triglycerides and glucose index is more suitable for the identification of metabolically unhealthy individuals in the Chinese adult population: A nationwide study. J Diabetes Investig 2019; 10(4): 1050-8. doi: 10.1111/jdi.12975. PMID: 30417578. PMCID: PMC6626942.
  7. Tian S, Xu Y, Dong H. The effect of metabolic health and obesity phenotypes on risk of hypertension: A nationwide population-based study using 5 representative definitions of metabolic health. Medicine 2018; 97: 38. doi: 10.1097/MD.0000000000012425. PMID: 30235720. PMCID: PMC6160160.
  8. Shea JL, Randell EW, Sun G. The Prevalence of Metabolically Healthy Obese Subjects Defined by BMI and Dual-Energy X-Ray Absorptiometry. Obesity 2011; 19(3): 624-30. doi: 10.1038/oby.2010.174. PMID: 20706202.
  9. Oladapo OO, Salako L, Sodiq O, Shoyinka K, Adedapo K, Falase AO. A prevalence of cardiometabolic risk factors among a rural Yoruba south-western Nigerian population: a population-based survey. Cardiovasc J Afr. 2010; 21(1): 26-31. PMID: 20224842. PMCID: PMC3721297.
  10. Hajian-Tilaki K, Heidari B. Metabolically healthy obese and unhealthy normal weight in Iranian adult population: Prevalence and the associated factors. Diabetes Metab Syndr. 2018; 12(2): 129-34. doi: 10.1016/j.dsx.2017.11.005. PMID: 29196231.
  11. Rahmanian K, Shojaie M. Prevalence of Metabolic Syndrome in an Adult Urban Population in The South of Iran. Iranian Journal of Diabetes and Obesity 2011; 3(2): 77-82.
  12. Rahmanian K, Shojaie M. The prevalence of pre-hypertension and its association to established cardiovascular risk factors in south of Iran. BMC Res Notes. 2012; 5: 386. doi: 10.1186/1756-0500-5-386. PMID: 22838639. PMCID: PMC3506467.
  13. Rahmanian K, Shojaei M, Sotoodeh.Jahromi A. Relation of type 2 diabetes mellitus with gender, education, and marital status in an Iranian urban population. Rep Biochem Mol Biol. 2013; 1(2): 64-8. PMID: 26989710. PMCID: PMC4757057.
  14. Rahmanian K, Shojaei M, Sotoodeh Jahromi A, Madani A. The Association Between Pre-Diabetes With Body Mass Index and Marital Status in an Iranian Urban Population. Glob J Health Sci. 2016; 8(4): 95-101. doi: 10.5539/gjhs.v8n4p95. PMID: 26573038. PMCID: PMC4873576.
  15. Shojaei M, Jahromi AS, Rahmanian K, et.al. Gender differences in the prevalence of cardiovascular risk factors in an iranian urban population. OnLine Journal of Biological Sciences 2015; 15(3): 178-84. doi: 3844/ojbsci.2015.178.184.
  16. Rahmanian K, Shojaei M, Sotoodeh Jahromi A. Prevalence and clinical characteristics of metabolically unhealthy obesity in an Iranian adult population. Diabetes Metab Syndr Obes. 2019; 12: 1387-95. doi: 10.2147/DMSO.S197476. PMID: 31496776. PMCID: PMC6698163.
  17. Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults. Executive Summary of the Third Report of the National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III). JAMA 2001; 285: 2486–97. doi:1001/jama.285.19.2486. PMID: 11368702.
  18. Lee K. Metabolically obese but normal weight (MONW) and metabolically healthy but obese (MHO) phenotypes in Koreans: characteristics and health behaviors. Asia Pac J Clin Nutr 2009; 18 (2): 280-4. PMID: 19713189.
  19. van Vliet-Ostaptchouk JV, Nuotio ML, Slagter SN, Doiron D, Fischer K, Foco L, et al. The prevalence of metabolic syndrome and metabolically healthy obesity in Europe: a collaborative analysis of ten large cohort studies. BMC Endocrine Disorders 2014; 14: 9. doi: 10.1186/1472-6823-14-9. PMID: 24484869. PMCID: PMC3923238.
  20. Okosun IS, Boltri JM, Davis-Smith M, Ndirangu M. Premetabolic syndrome and clustering of cardiometabolic risk factors in White, Black and Mexican American adults. Diabetes & Metabolic Syndrome: Clinical Research & Reviews 2009; 3(3): 143-8. doi: 1016/j.dsx.2009.07.006.
  21. Izumida T, Nakamura Y, Ishikawa S. Impact of body mass index and metabolically unhealthy status on mortality in the Japanese general population: The JMS cohort study. PLoS ONE 2019; 14(11): e0224802. doi: 10.1371/journal.pone.0224802. PMID: 31697720. PMCID: PMC6837339.
  22. Ren H, Zhang L, Liu Z, Zhou X, Yuan G. Sleep duration and apolipoprotein B in metabolically healthy and unhealthy overweight/obese phenotypes: a cross-sectional study in Chinese adults. BMJ Open 2019; 9: e023817. doi: 10.1136/bmjopen-2018-023817. PMID: 30755447. PMCID: PMC6377547.
  23. Ortega FB, Lee DC, Katzmarzyk PT, Ruiz JR, Sui X, Church TS, et al. The intriguing metabolically healthy but obese phenotype: cardiovascular prognosis and role of fitness. Eur Heart J 2013; 34(5): 389-97. doi: 10.1093/eurheartj/ehs174. PMID: 22947612. PMCID: PMC3561613.
  24. Tsatsoulis A, Paschou SA. Metabolically healthy obesity: criteria, epidemiology, controversies, and consequences. Curr Obes Rep2020; 9(2): 109-20. doi: 10.1007/s13679-020-00375-0. PMID: 32301039.
  25. Hamer M, Bell JA, Sabia S, Batty GD, Kivimäki M. Stability of metabolically healthy obesity over 8 years: the English Longitudinal Study of Ageing. Eur J Endocrinol 2015; 173(5): 703-8. doi: 10.1530/EJE-15-0449. PMID: 26286585.
  26. Hinnouho GM, Czernichow S, Dugravot A, Nabi H, Brunner EJ, Kivimaki M, et al. Metabolically healthy obesity and the risk of cardiovascular disease and type 2 diabetes: the Whitehall II cohort study. European Heart Journal 2015; 36: 551–9. doi: 10.1093/eurheartj/ehu123. PMID: 24670711. PMCID: PMC4344958.
  27. Chang Y, Jung HS, Yun KE, Cho J, Ahn J, Chung EC, et al. Metabolically Healthy Obesity is Associated with an Increased Risk of Diabetes Independently of Nonalcoholic Fatty Liver Disease. Obesity 2016; 24: 1996–2003. doi: 10.1002/oby.21580. PMID: 27474900.
  28. Aung K, Lorenzo C, Hinojosa MA, Haffne SM. Risk of Developing Diabetes and Cardiovascular Disease in Metabolically Unhealthy Normal-Weight and Metabolically Healthy Obese Individuals. J Clin Endocrinol Metab 2014; 99: 462–8. doi: 10.1210/jc.2013-2832. PMID: 24257907. PMCID: PMC3913817.
  29. Xie J, Zhang S, Yu X, Yang Y, Liu Z, Yuan G, et al. Association between Liver Enzymes with Metabolically Unhealthy Obese Phenotype. Lipids Health Dis. 2018; 17(1): 198. doi: 10.1186/s12944-018-0847-9. PMID: 30134916. PMCID: PMC6106819.
  30. Navarro-Gonzalez D, Sanchez-Inigo L, Fernandez-Montero A, Pastrana-Delgado J, Martınez JA. Are All Metabolically Healthy Individuals with Obesity at the Same Risk of Diabetes Onset? Obesity 2016; 24: 2615-23. doi: 10.1002/oby.21667. PMID: 27804254.
  31. Dhana K, Koolhaas CM, van Rossum EF, Ikram MA, Hofman A, Kavousi M, et al. Metabolically Healthy Obesity and the Risk of Cardiovascular Disease in the Elderly Population. PLoS ONE; 11(4): e0154273. doi: 10.1371/journal.pone.0154273. PMID: 27100779. PMCID: PMC4839559.
  32. Lee H-J, Choi E-K, Lee S-H, Kim Y-J, Han K-D, Oh S. Risk of ischemic stroke in metabolically healthy obesity: A nationwide populationbased study. PLoS ONE 2018; 13(3): e0195210. doi: 10.1371/journal.pone.0195210. PMID: 29601602. PMCID: PMC5877885.
آمار
تعداد مشاهده مقاله: 209
تعداد دریافت فایل اصل مقاله: 118


سامانه مدیریت نشریات علمی. قدرت گرفته از سیناوب