aterosklerozАтеросклерозAteroscleroz2078-256X2949-3633НИИТПМ-филиал ИЦиГ СО РАН10.52727/2078-256X-2021-17-52-61ateroskleroz-415Research ArticleОРИГИНАЛЬНЫЕ СТАТЬИORIGINAL ARTICLESКардиометаболические факторы риска у лиц с ожирением и риск развития сахарного диабета 2 типа в 12-летнем проспективном исследованииCardiometabolic risk factors in obese individuals and the risk of incident diabetes mellitus in 12-year prospective studyМустафинаС. В.MustafinaS. V.

Мустафина Светлана Владимировна — доктор медицинских наук, старший научный сотрудник лаборатории клинико-­популяционных и профилактических исследований терапевтических и эндокринных заболеваний

630089, Новосибирск, ул. Бориса Богаткова, 175/1

630089, Novosibirsk, Boris Bogatkov str., 175/1

svetlana3548@gmail.ruВинтерД. А.VinterD. A.

Винтер Дарья Алексеевна — аспирант

630089, Новосибирск, ул. Бориса Богаткова, 175/1

630089, Novosibirsk, Boris Bogatkov str., 175/1

kozupeevadarya@mail.ruРымарО. Д.RymarO. D.

Рымар Оксана Дмитриевна — доктор медицинских наук, главный научный сотрудник, заведующий лабораторией клинико-­популяционных и профилактических исследований терапевтических и эндокринных заболеваний

630089, Новосибирск, ул. Бориса Богаткова, 175/1

630089, Novosibirsk, Boris Bogatkov str., 175/1

orymar@mail.ruЩербаковаЛ. В.ScherbakovaL. V.

Щербакова Лилия Валерьевна — старший научный сотрудник лаборатории клинико-­популяционных и профилактических исследований терапевтических и эндокринных заболеваний

630089, Новосибирск, ул. Бориса Богаткова, 175/1

630089, Novosibirsk, Boris Bogatkov str., 175/1

9584792@mail.ruСазоноваО. В.SazonovaO. V.

Сазонова Ольга Владимировна—кандидат медицинских наук, доцент кафедры пропедевтики внутренних болезней

630091, г. Новосибирск, Красный просп., 52

630091, г. Новосибирск, Красный просп., 52 

ov_sazonova@mail.ruМалютинаС. К.MalutinaS. K.

Малютина Софья Константиновна — доктор медицинских наук, профессор, заведующий лабораторией этиопатогенеза и клиники внутренних заболеваний

630089, Новосибирск, ул. Бориса Богаткова, 175/1

630089, Novosibirsk, Boris Bogatkov str., 175/1

smalyutina@hotmail.comНИИ терапии и профилактической медицины — филиал ФГБНУ ФИЦ Институт цитологии и генетики СО РАНРоссияResearch Institute of Internal and Preventive Medicine — Branch of Federal Research Center Institute of Cytology and Genetics of SB RASRussian FederationФГБОУ ВО Новосибирский государственный медицинский университет Минздрава РоссииРоссияNovosibirsk State Medical University of Minzdrav of RussiaRussian Federation2021030520211715261Copyright © Мустафина С.В., Винтер Д.А., Рымар О.Д., Щербакова Л.В., Сазонова О.В., Малютина С.К., 20212021Мустафина С.В., Винтер Д.А., Рымар О.Д., Щербакова Л.В., Сазонова О.В., Малютина С.К.Mustafina S.V., Vinter D.A., Rymar O.D., Scherbakova L.V., Sazonova O.V., Malutina S.K.This work is licensed under a Creative Commons Attribution 4.0 License.https://ateroskleroz.elpub.ru/jour/article/view/415

Цель исследования — изучить риск развития сахарного диабета 2 типа (СД2) у лиц с метаболически здоровым (МЗФО) и нездоровым фенотипом ожирения (МНЗФО) и оценить вклад компонентов метаболического синдрома (МС) в 12-летний риск развития СД2 по данным проспективного исследования.

Материал и методы

Материал и методы. В исследование включены 1958 человек с индексом массы тела ≥ 30 кг/м² и не имеющие СД2, из числа обследованных на базовом скрининге в 2003–2005 гг. проекта HAPPIE. Новые случаи СД2 диагностировались в период с 2003 по 2018 г. по данным регистра СД и повторных скринингов. Медиана периода наблюдения составила 12,1 года. Для выделения МЗФО использованы критерии NCEP ATP III (2001 г.) и IDF (2005 г.).

Результаты

Результаты. Частота впервые возникшего СД2 в группе МЗФО по всем изучаемым критериям в среднем в 1,5 раза ниже, чем у лиц с МНЗФО, p<0,001. По результатам многофакторного регрессионного анализа Кокса у лиц с МЗФО риск развития СД2 меньше, чем у пациентов с МНЗФО, в 2,3 и 2,2 раза по критериям IDF и NCEP ATP III соответственно. Риск развития СД2 увеличивается прямо пропорционально количеству компонентов метаболического синдрома: при наличии трех компонентов отношение шансов (ОШ) =3,1, 95%-й доверительный интервал (95% ДИ) 1,0–9,9 (р=0,048), при наличии четырех компонентов ОШ = 4,4, 95% ДИ 1,4–14,0 (р=0,011). Однако сочетание ожирения с одним кардиометаболическим фактором риска не ведет к развитию СД2 в течение 12 лет, р>0,05. У лиц с ожирением по абдоминальному типу (АО) риск развития СД2 в 2 раза выше, чем у обследованных с нормальной окружностью талии, причем люди без АО демонстрируют отсутствие риска развития СД2 с увеличением числа компонентов метаболического синдрома.

Заключение

Заключение. Частота впервые возникшего за 12 лет СД2 в группе МЗФО по всем изучаемым критериям в среднем в 1,5 раза ниже, чем в группе МНЗФО. Независимо от фенотипа ожирения выявлены наиболее значимые предикторы риска развития СД2: АО и гипергликемия натощак. У лиц без АО риск развития СД2 не повышается даже при увеличении числа компонентов МС. При наличии АО риск развития СД2 увеличивается в 2 раза при появлении любого компонента МС. 

Aim of the study was to investigate the risk of developing type 2 diabetes mellitus (T2DM) in individuals with metabolically healthy and unhealthy obesity phenotypes (MHO and MUO) and evaluate the contribution of metabolic syndrome (MS) components to the 12-year risk of developing T2DM according to a prospective study.

Material and methods

Material and methods. The study included 1958 people with a BMI ≥30 kg/m² and no T2DM, from among those examined at the baseline screening in 2003– 2005 of the HAPPIE project. New cases of T2DM were diagnosed between 2003 and 2018 according to the register of diabetes mellitus and repeated screenings. The median follow-up period was 12.1 years. Were used to define MHO: criteria of the NCEPATP III, 2001 and IDF, 2005.

Results

Results. The incidence of T2DM in the MHO group according to all studied criteria is on 1,5 times lower than in persons with MUO, p<0,001. According to the results of Cox regression multivariate analysis, the risk of developing T2DM in individuals with MHO is 2.3 times lower according to the IDF criteria, 2005 and 2,2 times lower according to the NCEP ATP III, 2001 criteria, compared with persons with MUO. The risk of developing T2DM increases in direct proportion to the number of MS components: 3 components—OR = 3,1 (95% CI: 1.0; 9.9), p = 0.048, 4 components—OR = 4.4 (95% CI: 1.4; 14.0), p = 0.011. However, the presence of obesity in a person with one risk factor does not lead to the development of T2DM within 12 years, p>0.05. When analyzing obese individuals who had abdominal obesity (AO), the risk of developing T2DM is 2 times higher compared to individuals with normal waist circumference (WC), and people without AO demonstrate no risk of developing T2DM, with an increase in the number of MS components, p> 0.05.

Conclusions

Conclusions. The incidence of first-­onset T2DM during 12 years in the MHO group by any used criteria is on 1.5 times lower than in the MUO group. In individuals with obesity, regardless of its phenotype, the most significant independent predictors of the risk of incident T2DM are AO and fasting hyperglycaemia. In individuals without AO, the risk of developing T2DM does not increase, even with an increase in the number of MS components. In the presence of AO, the risk of developing T2DM increases 2 times already with the appearance of any other component.

сахарный диабет 2 типаметаболически здоровый фенотип ожиренияожирениекогортаType 2 diabetes mellitusmetabolically healthy obesityobesitycohortReferencesCӑtoi A.F., Pârvu A.E., Andreicuț A.D. et al. Metabolically healthy versus unhealthy morbidly obese: chronic inflammation, nitro-oxidative stress, and insulin resistance. Nutrients, 2018; 10 (9): 1199. doi:10.3390/nu10091199Cӑtoi A.F., Pârvu A.E., Andreicuț A.D. et al. Metabolically healthy versus unhealthy morbidly obese: chronic inflammation, nitro-oxidative stress, and insulin resistance. Nutrients, 2018; 10 (9): 1199. doi:10.3390/nu10091199De Lorenzo A., Soldati L., Sarlo F. et al. New obesity classification criteria as a tool for bariatric surgery indication. World J. Gastroenterol., 2016; 22: 681– 703. doi: 10.3748/wjg.v22.i2.681De Lorenzo A., Soldati L., Sarlo F. et al. New obesity classification criteria as a tool for bariatric surgery indication. World J. Gastroenterol., 2016; 22: 681– 703. doi: 10.3748/wjg.v22.i2.681Ortega F.B., Lavie C.J., Blair S.N. Obesity and cardiovascular disease. Circ. Res., 2016; 27; 118 (11): 1752–1770. doi: 10.1161/CIRCRESAHA.115.306883Ortega F.B., Lavie C.J., Blair S.N. Obesity and cardiovascular disease. Circ. Res., 2016; 27; 118 (11): 1752–1770. doi: 10.1161/CIRCRESAHA.115.306883Stefan N., Häring H.U., Schulze MB. Metabolically healthy obesity: The low-hanging fruit in obesity treatment? Lancet Diabetes Endocrinol., 2018; 6. 249– 258. doi: 10.1016/S2213–8587(17)30292–9Stefan N., Häring H.U., Schulze MB. Metabolically healthy obesity: The low-hanging fruit in obesity treatment? Lancet Diabetes Endocrinol., 2018; 6. 249– 258. doi: 10.1016/S2213–8587(17)30292–9Van Vliet-Ostaptchouk J.V., Nuotio M.L., Slagter S.N. et al. The prevalence of metabolic syndrome and metabolically healthy obesity in Europe: A collaborative analysis of ten large cohort studies. BMC Endocr. Disord., 2014; 14 (9). doi: 10.1186/1472–6823–14–9Van Vliet-Ostaptchouk J.V., Nuotio M.L., Slagter S.N. et al. The prevalence of metabolic syndrome and metabolically healthy obesity in Europe: A collaborative analysis of ten large cohort studies. BMC Endocr. Disord., 2014; 14 (9). doi: 10.1186/1472–6823–14–9Goncalves C.G., Glade M.J., Meguid M.M. Metabolically healthy obese individuals: Key protective factors. Nutrition, 2016; 32. 14–20. doi: 10.1016/j.nut.2015.07.010Goncalves C.G., Glade M.J., Meguid M.M. Metabolically healthy obese individuals: Key protective factors. Nutrition, 2016; 32. 14–20. doi: 10.1016/j.nut.2015.07.010Bluher M. Are metabolically healthy obese really healthy? Eur. J. Endocrinol., 2014; 171: 209–219. doi: 10.1530/EJE 14–0540Bluher M. Are metabolically healthy obese really healthy? Eur. J. Endocrinol., 2014; 171: 209–219. doi: 10.1530/EJE 14–0540Wildman R.P., Muntner P., Reynolds K. et al. The obese without cardiometabolic risk factor clustering and the normal weight with cardiometabolic risk factor clustering: Prevalence and correlates of 2 phenotypes among the US population (NHANES1999–2004) Arch. Intern. Med., 2008; 168: 1617–1624. doi: 10.1001/archinte.168.15.1617Wildman R.P., Muntner P., Reynolds K. et al. The obese without cardiometabolic risk factor clustering and the normal weight with cardiometabolic risk factor clustering: Prevalence and correlates of 2 phenotypes among the US population (NHANES1999–2004) Arch. Intern. Med., 2008; 168: 1617–1624. doi: 10.1001/archinte.168.15.1617Bell J.A., Kivimaki M., Hamer M. Metabolically healthy obesity and risk of incident type 2 diabetes: a meta-analysis of prospective cohort studies. Obes. Rev., 2014; 15 (6): 504–515. doi: 10.1111/obr.12157Bell J.A., Kivimaki M., Hamer M. Metabolically healthy obesity and risk of incident type 2 diabetes: a meta-analysis of prospective cohort studies. Obes. Rev., 2014; 15 (6): 504–515. doi: 10.1111/obr.12157Eckel N., Li Y., Kuxhaus O. et al. Transition from metabolic healthy to unhealthy phenotypes and association with cardiovascular disease risk across BMI categories in 90257 women (the Nurses’ Health Study): 30 year follow-up from a prospective cohort study. Lancet Diabetes Endocrinol., 2018; 6 (9):714– 724. doi:10.1016/S2213–8587(18)30137–2Eckel N., Li Y., Kuxhaus O. et al. Transition from metabolic healthy to unhealthy phenotypes and association with cardiovascular disease risk across BMI categories in 90257 women (the Nurses’ Health Study): 30 year follow-up from a prospective cohort study. Lancet Diabetes Endocrinol., 2018; 6 (9):714– 724. doi:10.1016/S2213–8587(18)30137–2PeaseyA., Bobak M., KubinovaR., et al. Determinants of cardiovascular disease and other non-communicable diseases in Central and Eastern Europe: rationale and design of the HAPIEE study. BMC Public Health, 2006; 6: 255. doi: 10.1186/1471–2458–6–255PeaseyA., Bobak M., KubinovaR., et al. Determinants of cardiovascular disease and other non-communicable diseases in Central and Eastern Europe: rationale and design of the HAPIEE study. BMC Public Health, 2006; 6: 255. doi: 10.1186/1471–2458–6–255Мустафина С.В., Винтер Д.А., Щербакова Л.В. и др. Половозрастные особенности распространенности метаболически здорового фенотипа ожирения. Бюл. сиб. медицины, 2020; 19 (1): 76–84. doi: 10.20538/1682–0363–2020–1–76–8Мустафина С.В., Винтер Д.А., Щербакова Л.В. и др. Половозрастные особенности распространенности метаболически здорового фенотипа ожирения. Бюл. сиб. медицины, 2020; 19 (1): 76–84. doi: 10.20538/1682–0363–2020–1–76–8Brandão I., Martins M.J., Monteiro R. Metabolically healthy obesity-heterogeneity in definitions and unconventional factors. Metabolites, 2020; 10 (2): 48. doi:10.3390/metabo10020048Brandão I., Martins M.J., Monteiro R. Metabolically healthy obesity-heterogeneity in definitions and unconventional factors. Metabolites, 2020; 10 (2): 48. doi:10.3390/metabo10020048CaspardH., JabbourS., HammarN. et al. Recent trends in the prevalence of type 2 diabetes and the association with abdominal obesity lead to growing health disparities in the USA: An analysis of the NHANES surveys from 1999 to 2014. Diabetes Obes. Metab., 2018; 20 (3): 667–671. doi: 10.1111/dom.13143CaspardH., JabbourS., HammarN. et al. Recent trends in the prevalence of type 2 diabetes and the association with abdominal obesity lead to growing health disparities in the USA: An analysis of the NHANES surveys from 1999 to 2014. Diabetes Obes. Metab., 2018; 20 (3): 667–671. doi: 10.1111/dom.13143Casanueva F.F., Moreno B., Rodríguez-Azeredo R. et al. Relationship of abdominal obesity with cardiovascular disease, diabetes and hyperlipidaemia in Spain. Clin. Endocrinol., 2010; 73 (1): 35–40. doi: 10.1111/j.1365–2265.2009.03727.x.Casanueva F.F., Moreno B., Rodríguez-Azeredo R. et al. Relationship of abdominal obesity with cardiovascular disease, diabetes and hyperlipidaemia in Spain. Clin. Endocrinol., 2010; 73 (1): 35–40. doi: 10.1111/j.1365–2265.2009.03727.x.Wannamethee S.G., Shaper A.G., Lennon L. et al Metabolic syndrome vs Framingham Risk Score for prediction of coronary heart disease, stroke, and type 2 diabetes mellitus. Arch. Intern. Med., 2005; 165 (22): 2644–50. doi: 10.1001/archinte.165.22.2644.Wannamethee S.G., Shaper A.G., Lennon L. et al Metabolic syndrome vs Framingham Risk Score for prediction of coronary heart disease, stroke, and type 2 diabetes mellitus. Arch. Intern. Med., 2005; 165 (22): 2644–50. doi: 10.1001/archinte.165.22.2644.Sarathy H., Henriquez G., Matthew K.Abramowitz. et al. Abdominal obesity, race and chronic kidney disease in young adults: Results from NHANES1999–2010. PLoS One, 2016; 25; 11 (5): e0153588. doi: 10.1371/journal.pone.0153588.Sarathy H., Henriquez G., Matthew K.Abramowitz. et al. Abdominal obesity, race and chronic kidney disease in young adults: Results from NHANES1999–2010. PLoS One, 2016; 25; 11 (5): e0153588. doi: 10.1371/journal.pone.0153588.Bhupathiraju S.N., Hu F.B. Epidemiology of obesity and diabetes and their cardiovascular complications. Circ. Res., 2016; 118 (11): 1723–1735. doi: 10.1161/CIRCRESAHA.115.306825.Bhupathiraju S.N., Hu F.B. Epidemiology of obesity and diabetes and their cardiovascular complications. Circ. Res., 2016; 118 (11): 1723–1735. doi: 10.1161/CIRCRESAHA.115.306825.KivimäkiM., KuosmaE., Ferrie J.E. et al. Overweight, obesity, and risk of cardiometabolic multimorbidity: pooled analysis of individual-level data for 120813 adults from 16 cohort studies from the USA and Europe. Lancet Public Health, 2017; 2 (6): e277-e285. doi: 10.1016/S2468–2667(17)30074–9.KivimäkiM., KuosmaE., Ferrie J.E. et al. Overweight, obesity, and risk of cardiometabolic multimorbidity: pooled analysis of individual-level data for 120813 adults from 16 cohort studies from the USA and Europe. Lancet Public Health, 2017; 2 (6): e277-e285. doi: 10.1016/S2468–2667(17)30074–9.Kuk J.L, Rotondi M., Sui X. et al. Individuals with obesity but no other metabolic risk factors are not at significantly elevated all-cause mortality risk in men and women. Clin. Obes., 2018; 8 (5): 305–312. doi: 10.1111/cob.12263Kuk J.L, Rotondi M., Sui X. et al. Individuals with obesity but no other metabolic risk factors are not at significantly elevated all-cause mortality risk in men and women. Clin. Obes., 2018; 8 (5): 305–312. doi: 10.1111/cob.12263Moussa O., Arhi C., Ziprin P. et al. Fate of the metabolically healthy obese-is this term a misnomer? A study from the Clinical Practice Research Datalink. Int. J. Obes. (Lond.), 2019; 43 (5): 1093–1101. doi: 10.1038/s41366–018–0096-zMoussa O., Arhi C., Ziprin P. et al. Fate of the metabolically healthy obese-is this term a misnomer? A study from the Clinical Practice Research Datalink. Int. J. Obes. (Lond.), 2019; 43 (5): 1093–1101. doi: 10.1038/s41366–018–0096-zCaleyachetty R., Thomas G.N., Toulis KA. Metabolically healthy obese and incident cardiovascular disease events among 3.5 million men and women. J. Am. Coll. Cardiol., 2017; 70 (12): 1429–1437. doi: 10.1016/j.jacc.2017.07.763. PMID: 28911506Caleyachetty R., Thomas G.N., Toulis KA. Metabolically healthy obese and incident cardiovascular disease events among 3.5 million men and women. J. Am. Coll. Cardiol., 2017; 70 (12): 1429–1437. doi: 10.1016/j.jacc.2017.07.763. PMID: 28911506Hinnouho G.M., Czernichow S., Dugravot A. et al. Metabolically healthy obesity and the risk of cardiovascular disease and type 2 diabetes: the Whitehall II cohort study. Eur. Heart. J., 2015; 36 (9): 551–559. doi: 10.1093/eurheartj/ehu123Hinnouho G.M., Czernichow S., Dugravot A. et al. Metabolically healthy obesity and the risk of cardiovascular disease and type 2 diabetes: the Whitehall II cohort study. Eur. Heart. J., 2015; 36 (9): 551–559. doi: 10.1093/eurheartj/ehu123Espinosa de Ycaza A.E, Donegan D., Jensen MD. Long-term metabolic risk for the metabolically healthy overweight/obese phenotype. Int. J. Obes. (Lond.), 2018; 42 (3): 302–309. doi: 10.1038/ijo.2017.233Espinosa de Ycaza A.E, Donegan D., Jensen MD. Long-term metabolic risk for the metabolically healthy overweight/obese phenotype. Int. J. Obes. (Lond.), 2018; 42 (3): 302–309. doi: 10.1038/ijo.2017.233WilsonP.W., D’Agostino R.B., PariseH. et al Metabolic syndrome as a precursor of cardiovascular disease and Type 2 diabetes mellitus. Circulation, 2005; 112. 3066– 3072. doi: 10.1161/CIRCULATIONAHA.105.539528WilsonP.W., D’Agostino R.B., PariseH. et al Metabolic syndrome as a precursor of cardiovascular disease and Type 2 diabetes mellitus. Circulation, 2005; 112. 3066– 3072. doi: 10.1161/CIRCULATIONAHA.105.539528Wannamethee S.G., Shaper A.G., Lennon L. et al. Metabolic syndrome vs Framingham Risk Score for prediction of coronary heart disease, stroke, and type 2 diabetes mellitus. Arch.Intern. Med., 2005; 165: 2644– 2650. doi: 10.1001/archinte.165.22.2644Wannamethee S.G., Shaper A.G., Lennon L. et al. Metabolic syndrome vs Framingham Risk Score for prediction of coronary heart disease, stroke, and type 2 diabetes mellitus. Arch.Intern. Med., 2005; 165: 2644– 2650. doi: 10.1001/archinte.165.22.2644Sattar N., Gaw A., Scherbakova O. et al. Metabolic syndrome with and without C‐reactive protein as a predictor of coronary heart disease and diabetes in the West of Scotland Coronary Prevention Study. Circulation, 2003; 108 (4): 414–419. doi: 10.1161/01.CIR.0000080897.52664.94Sattar N., Gaw A., Scherbakova O. et al. Metabolic syndrome with and without C‐reactive protein as a predictor of coronary heart disease and diabetes in the West of Scotland Coronary Prevention Study. Circulation, 2003; 108 (4): 414–419. doi: 10.1161/01.CIR.0000080897.52664.94Klein B.E., Klein R., Lee K.E. Components of the metabolic syndrome and risk of cardiovascular disease and diabetes in Beaver Dam. Diabetes Care, 2002; 25 (10): 1790–1794. doi: 10.2337/diacare.25.10.1790Klein B.E., Klein R., Lee K.E. Components of the metabolic syndrome and risk of cardiovascular disease and diabetes in Beaver Dam. Diabetes Care, 2002; 25 (10): 1790–1794. doi: 10.2337/diacare.25.10.1790Cameron A.J., Zimmet P.Z., Soderberg S. et al. The metabolic syndrome as a predictor of incident diabetes mellitus in Mauritius. Diabet. Med., 2007; 24 (12): 1460–1469. doi: 10.1111/j.1464–5491.2007.02288.xCameron A.J., Zimmet P.Z., Soderberg S. et al. The metabolic syndrome as a predictor of incident diabetes mellitus in Mauritius. Diabet. Med., 2007; 24 (12): 1460–1469. doi: 10.1111/j.1464–5491.2007.02288.xМустафина С.В. Риск сахарного диабета и метаболический синдром: популяционное исследование в Сибири: дис. … д-ра мед. наук, Новосибирск, 2016.Мустафина С.В. Риск сахарного диабета и метаболический синдром: популяционное исследование в Сибири: дис. … д-ра мед. наук, Новосибирск, 2016.Lorenzo C., Williams K., Hunt K.J. et al. The National Cholesterol Education Program ‐ Adult Treatment Panel III, International Diabetes Federation, and World Health Organization definitions of the metabolic syndrome as predictors of incident cardiovascular disease and diabetes. Diabetes Care, 2007; 30 (1): 8–13. doi: 10.2337/dc06–1414Lorenzo C., Williams K., Hunt K.J. et al. The National Cholesterol Education Program ‐ Adult Treatment Panel III, International Diabetes Federation, and World Health Organization definitions of the metabolic syndrome as predictors of incident cardiovascular disease and diabetes. Diabetes Care, 2007; 30 (1): 8–13. doi: 10.2337/dc06–1414Casimiro Pérez J.A., Fernández Quesada C., Del Val Groba Marco M. et al. Obesity Surgery Score (OSS) for prioritization in the bariatric surgery waiting list: a need of public health systems and a literature review. Obes. Surg., 2018; 28 (4): 1175–1184. doi: 10.1007/s11695–017–3107–6Casimiro Pérez J.A., Fernández Quesada C., Del Val Groba Marco M. et al. Obesity Surgery Score (OSS) for prioritization in the bariatric surgery waiting list: a need of public health systems and a literature review. Obes. Surg., 2018; 28 (4): 1175–1184. doi: 10.1007/s11695–017–3107–6Blüher M. Metabolically Healthy Obesity. Endocr Rev., 2020; 41 (3): 405–420. doi: 10.1210/endrev/bnaa004Blüher M. Metabolically Healthy Obesity. Endocr Rev., 2020; 41 (3): 405–420. doi: 10.1210/endrev/bnaa004

The authors declare that there are no conflicts of interest present.