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Endocrine, Metabolic & Immune Disorders - Drug Targets

Editor-in-Chief

ISSN (Print): 1871-5303
ISSN (Online): 2212-3873

Research Article

Higher Body Mass Index, Uric Acid Levels, and Lower Cholesterol Levels are Associated with Greater Weight Loss

Author(s): Giovanni De Pergola*, ">Roberta Zupo, ">Luisa Lampignano, ">Caterina Bonfiglio, ">Gianluigi Giannelli, ">Alberto R. Osella and Vincenzo Triggiani

Volume 20, Issue 8, 2020

Page: [1268 - 1281] Pages: 14

DOI: 10.2174/1871530320666200429235830

Price: $65

Abstract

Background: Identifying predictive factors that contribute to changes in body weight may well be an interesting approach to the management of obesity.

Objective: This study was firstly aimed at examining the effect of a one-year lifestyle program based on improvements in the habitual diet and increased levels of physical activity on weight loss. Secondly, it was focused on identifying anthropometric, and serum hormonal, metabolic and haematochemical factors which can be associated with the degree of weight loss in Kg.

Methods: 488 overweight or obese subjects, 383 women and 105 men, aged 18-67 years, were enrolled in the study. Body mass index, waist circumference, serum blood glucose, lipids, uric acid, creatinine, insulin, TSH, FT3, FT4, and 24-h urine catecholamines were measured.

Results: Weight loss was positively associated with BMI (P < 0.01), waist circumference (P < 0.01), uric acid (P < 0.01), creatinine (P < 0.05), smoking (P < 0.01), and negatively correlated with age (P < 0.01), total cholesterol (P < 0.05), LDL-cholesterol (P < 0.01), HDL cholesterol (P < 0.05). In a multiple regression model considering weight loss as a dependent variable, and smoking, age, BMI, uric acid, creatinine, total cholesterol, LDL-cholesterol and HDL cholesterol as independent variables, weight loss maintained a direct independent relationship with BMI (P < 0.001), uric acid (P < 0.05), LDL-cholesterol (P < 0.05), and HDL-cholesterol (P < 0.05), and an inverse independent association with cholesterol (P < 0.01).

Conclusion: This study suggests that higher BMI and uric acid levels, and lower total cholesterol concentrations are associated with a greater potential to lose weight.

Keywords: Obesity, weight loss, uric acid, cholesterol, body mass index, waist circumference.

Graphical Abstract

[1]
Cornier, M.A.; Marshall, J.A.; Hill, J.O.; Maahs, D.M.; Eckel, R.H. Prevention of overweight/obesity as a strategy to optimize cardiovascular health. Circulation, 2011, 124(7), 840-850.
[http://dx.doi.org/10.1161/CIRCULATIONAHA.110.968461] [PMID: 21844090]
[2]
Balagopal, P.B.; de Ferranti, S.D.; Cook, S.; Daniels, S.R.; Gidding, S.S.; Hayman, L.L.; McCrindle, B.W.; Mietus-Snyder, M.L.; Steinberger, J. American Heart Association Committee on Atherosclerosis Hypertension and Obesity in Youth of the Council on Cardiovascular Disease in the Young; Council On Nutrition, Physical Activity and Metabolism; Council on Epidemiology and Prevention. Nontraditional risk factors and biomarkers for cardiovascular disease: Mechanistic, research, and clinical considerations for youth. Circulation, 2011, 123, 2749-2769.
[http://dx.doi.org/10.1161/CIR.0b013e31821c7c64] [PMID: 21555711]
[3]
Després, J.P. Body fat distribution and risk of cardiovascular disease: An update. Circulation, 2012, 126(10), 1301-1313.
[http://dx.doi.org/10.1161/CIRCULATIONAHA.111.067264] [PMID: 22949540]
[4]
De Pergola, G.; De Mitrio, V.; Giorgino, F.; Sciaraffia, M.; Minenna, A.; Di Bari, L.; Pannacciulli, N.; Giorgino, R. Increase in both pro-thrombotic and anti-thrombotic factors in obese premenopausal women: relationship with body fat distribution. Int. J. Obes. Relat. Metab. Disord., 1997, 21(7), 527-535.
[http://dx.doi.org/10.1038/sj.ijo.0800435] [PMID: 9226481]
[5]
De Pergola, G.; Giagulli, V.A.; Guastamacchia, E.; Bartolomeo, N.; Tatoli, R.; Lampignano, L.; Silvestris, F.; Triggiani, V. Platelet number is positively and independently associated with glycated hemoglobin in non-diabetic overweight and obese subjects. Nutr. Metab. Cardiovasc. Dis., 2019, 29(3), 254-259.
[http://dx.doi.org/10.1016/j.numecd.2018.12.007] [PMID: 30738641]
[6]
Ciccone, M.M.; Cortese, F.; Gesualdo, M.; Donvito, I.; Carbonara, S.; De Pergola, G. A glycemic threshold of 90 mg/dl promotes early signs of atherosclerosis in apparetly healthy overweight/obese subjects. Endocr. Metab. Immune Disord. Drug Targets, 2016, 16(4), 288-295.
[http://dx.doi.org/10.2174/1871530317666161205124955] [PMID: 27919218]
[7]
De Pergola, G.; Ciampolillo, A.; Paolotti, S.; Trerotoli, P.; Giorgino, R. Free triodothyronine and thyroid stimulating hormone serum levels are directly associated with waist circumference, independently of insulin resistance, metabolic parameters and blood pressure levels in overweight and obese women. Clin. Endocrinol. (Oxf.), 2007, 67, 265-269.
[http://dx.doi.org/10.1111/j.1365-2265.2007.02874.x] [PMID: 17547687]
[8]
De Pergola, G.; Cortese, F.; Termine, G.; Meliota, G.; Carbonara, R.; Masiello, M.; Cortese, A.M.; Silvestris, F.; Caccavo, D.; Ciccone, M.M. Uric acid, metabolic syndrome and atherosclerosis: The chicken or the egg, which comes first? Endocr. Metab. Immune Disord. Drug Targets, 2018, 18(3), 251-259.
[http://dx.doi.org/10.2174/1871530318666180212101548] [PMID: 29437024]
[9]
De Pergola, G.; Giagulli, V.A.; Bartolomeo, N.; Gaeta, F.; Petruzzella, A.; Guastamacchia, E.; Triggiani, V.; Silvestris, F. Independent relationship between serum osteocalcin and uric acid in a cohort of apparently healthy obese subjects. Endocr. Metab. Immune Disord. Drug Targets, 2017, 17(3), 207-212.
[http://dx.doi.org/10.2174/1871530317666170825164415] [PMID: 28847266]
[10]
Manno, C.; Campobasso, N.; Nardecchia, A.; Triggiani, V.; Zupo, R.; Gesualdo, L.; Silvestris, F.; De Pergola, G. Relationship of para- and perirenal fat and epicardial fat with metabolic parameters in overweight and obese subjects. Eat. Weight Disord., 2019, 24(1), 67-72.
[http://dx.doi.org/10.1007/s40519-018-0532-z] [PMID: 29956099]
[11]
De Pergola, G.; Nardecchia, A.; Guida, P.; Silvestris, F. Arterial hypertension in obesity: Relationships with hormone and anthropometric parameters. Eur. J. Cardiovasc. Prev. Rehabil., 2011, 18(2), 240-247.
[http://dx.doi.org/10.1177/1741826710389367] [PMID: 21450671]
[12]
Pasquali, R. The hypothalamic-pituitary-adrenal axis and sex hormones in chronic stress and obesity: pathophysiological and clinical aspects. Ann. N. Y. Acad. Sci., 2012, 1264, 20-35.
[http://dx.doi.org/10.1111/j.1749-6632.2012.06569.x] [PMID: 22612409]
[13]
Silvestris, E.; de Pergola, G.; Rosania, R.; Loverro, G. Obesity as disruptor of the female fertility. Reprod. Biol. Endocrinol., 2018, 16(1), 22.
[http://dx.doi.org/10.1186/s12958-018-0336-z] [PMID: 29523133]
[14]
Vgontzas, A.N.; Papanicolaou, D.A.; Bixler, E.O.; Hopper, K.; Lotsikas, A.; Lin, H.M.; Kales, A.; Chrousos, G.P. Sleep apnea and daytime sleepiness and fatigue: relation to visceral obesity, insulin resistance, and hypercytokinemia. J. Clin. Endocrinol. Metab., 2000, 85(3), 1151-1158.
[http://dx.doi.org/10.1210/jcem.85.3.6484] [PMID: 10720054]
[15]
De Pergola, G.; Silvestris, F. Obesity as a major risk factor for cancer. J. Obes., 2013, 2013291546
[http://dx.doi.org/10.1155/2013/291546] [PMID: 24073332]
[16]
Wadden, T.A.; Webb, V.L.; Moran, C.H.; Bailer, B.A. Lifestyle modification for obesity: new developments in diet, physical activity, and behavior therapy. Circulation, 2012, 125(9), 1157-1170.
[http://dx.doi.org/10.1161/CIRCULATIONAHA.111.039453] [PMID: 22392863]
[17]
Yancy, W.S., Jr; Westman, E.C.; McDuffie, J.R.; Grambow, S.C.; Jeffreys, A.S.; Bolton, J.; Chalecki, A.; Oddone, E.Z. A randomized trial of a low-carbohydrate diet vs orlistat plus a low-fat diet for weight loss. Arch. Intern. Med., 2010, 170(2), 136-145.
[http://dx.doi.org/10.1001/archinternmed.2009.492] [PMID: 20101008]
[18]
Stubbs, J.; Whybrow, S.; Teixeira, P.; Blundell, J.; Lawton, C.; Westenhoefer, J.; Engel, D.; Shepherd, R.; McConnon, A.; Gilbert, P.; Raats, M. Problems in identifying predictors and correlates of weight loss and maintenance: Implications for weight control therapies based on behaviour change. Obes. Rev., 2011, 12(9), 688-708.
[http://dx.doi.org/10.1111/j.1467-789X.2011.00883.x] [PMID: 21535362]
[19]
Carraça, E.V.; Santos, I.; Mata, J.; Teixeira, P.J. Psychosocial pretreatment predictors of weight control: A systematic review update. Obes. Facts, 2018, 11(1), 67-82.
[http://dx.doi.org/10.1159/000485838] [PMID: 29439252]
[20]
Hadžiabdić, M.O.; Mucalo, I.; Hrabač, P.; Matić, T.; Rahelić, D.; Božikov, V. Factors predictive of drop-out and weight loss success in weight management of obese patients. J. Hum. Nutr. Diet., 2015, 28(Suppl. 2), 24-32.
[http://dx.doi.org/10.1111/jhn.12270] [PMID: 25220046]
[21]
Garaulet, M.; Gómez-Abellán, P.; Alburquerque-Béjar, J.J.; Lee, Y.C.; Ordovás, J.M.; Scheer, F.A. Timing of food intake predicts weight loss effectiveness. Int. J. Obes., 2013, 37(4), 604-611.
[http://dx.doi.org/10.1038/ijo.2012.229] [PMID: 23357955]
[22]
Geidenstam, N.; Al-Majdoub, M.; Ekman, M.; Spégel, P.; Ridderstråle, M. Metabolite profiling of obese individuals before and after a one year weight loss program. Int. J. Obes., 2017, 41(9), 1369-1378.
[http://dx.doi.org/10.1038/ijo.2017.124] [PMID: 28529327]
[23]
Gallus, S.; Odone, A.; Lugo, A.; Bosetti, C.; Colombo, P.; Zuccaro, P.; La Vecchia, C. Overweight and obesity prevalence and determinants in Italy: an update to 2010. Eur. J. Nutr., 2013, 52(2), 677-685.
[http://dx.doi.org/10.1007/s00394-012-0372-y] [PMID: 22645105]
[24]
D’Alessandro, A.; De Pergola, G. Mediterranean diet pyramid: A proposal for Italian people. Nutrients, 2014, 6(10), 4302-4316.
[http://dx.doi.org/10.3390/nu6104302] [PMID: 25325250]
[25]
Resta, O.; Pannacciulli, N.; Di Gioia, G.; Stefàno, A.; Barbaro, M.P.; De Pergola, G. High prevalence of previously unknown subclinical hypothyroidism in obese patients referred to a sleep clinic for sleep disordered breathing. Nutr. Metab. Cardiovasc. Dis., 2004, 14(5), 248-253.
[http://dx.doi.org/10.1016/S0939-4753(04)80051-6] [PMID: 15673058]
[26]
Friedewald, W.T.; Levy, R.I.; Fredrickson, D.S. Estimation of the concentration of low-density lipoprotein cholesterol in plasma, without use of the preparative ultracentrifuge. Clin. Chem., 1972, 18(6), 499-502.
[http://dx.doi.org/10.1093/clinchem/18.6.499] [PMID: 4337382]
[27]
Matthews, D.R.; Hosker, J.P.; Rudenski, A.S.; Naylor, B.A.; Treacher, D.F.; Turner, R.C. Homeostasis model assessment: Insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia, 1985, 28(7), 412-419.
[http://dx.doi.org/10.1007/BF00280883] [PMID: 3899825]
[28]
Drummen, M.; Tischmann, L.; Gatta-Cherifi, B.; Adam, T.; Westerterp-Plantenga, M. Dietary protein and energy balance in relation to obesity and co-morbidities. Front. Endocrinol. (Lausanne), 2018, 9, 443.
[http://dx.doi.org/10.3389/fendo.2018.00443] [PMID: 30127768]
[29]
Karl, J.P.; Meydani, M.; Barnett, J.B.; Vanegas, S.M.; Goldin, B.; Kane, A.; Rasmussen, H.; Saltzman, E.; Vangay, P.; Knights, D.; Chen, C.O.; Das, S.K.; Jonnalagadda, S.S.; Meydani, S.N.; Roberts, S.B. Substituting whole grains for refined grains in a 6-wk randomized trial favorably affects energy-balance metrics in healthy men and postmenopausal women. Am. J. Clin. Nutr., 2017, 105(3), 589-599.
[http://dx.doi.org/10.3945/ajcn.116.139683] [PMID: 28179223]
[30]
Al-Mana, N.M.; Robertson, M.D. Acute effect of resistant starch on food intake, appetite and satiety in overweight/obese males. Nutrients, 2018, 10(12), 1993.
[http://dx.doi.org/10.3390/nu10121993] [PMID: 30558330]
[31]
Foster-Schubert, K.E.; Overduin, J.; Prudom, C.E.; Liu, J.; Callahan, H.S.; Gaylinn, B.D.; Thorner, M.O.; Cummings, D.E. Acyl and total ghrelin are suppressed strongly by ingested proteins, weakly by lipids, and biphasically by carbohydrates. J. Clin. Endocrinol. Metab., 2008, 93(5), 1971-1979.
[http://dx.doi.org/10.1210/jc.2007-2289] [PMID: 18198223]
[32]
Finkler, E.; Heymsfield, S.B.; St-Onge, M.P. Rate of weight loss can be predicted by patient characteristics and intervention strategies. J. Acad. Nutr. Diet., 2012, 112(1), 75-80.
[http://dx.doi.org/10.1016/j.jada.2011.08.034] [PMID: 22717178]
[33]
Zhou, L.; Cai, X.; Yang, W.; Han, X.; Ji, L. The magnitude of weight loss induced by metformin is independently associated with BMI at baseline in newly diagnosed type 2 diabetes: Post-hoc analysis from data of a phase IV open-labeled trial. Adv. Clin. Exp. Med., 2017, 26(4), 671-677.
[http://dx.doi.org/10.17219/acem/63025] [PMID: 28691423]
[34]
Tsushima, Y.; Nishizawa, H.; Tochino, Y.; Nakatsuji, H.; Sekimoto, R.; Nagao, H.; Shirakura, T.; Kato, K.; Imaizumi, K.; Takahashi, H.; Tamura, M.; Maeda, N.; Funahashi, T.; Shimomura, I. Uric acid secretion from adipose tissue and its increase in obesity. J. Biol. Chem., 2013, 288(38), 27138-27149.
[http://dx.doi.org/10.1074/jbc.M113.485094] [PMID: 23913681]
[35]
Zheng, R.; Chen, C.; Yang, T.; Chen, Q.; Lu, R.; Mao, Y. Serum uric acid levels and the risk of obesity: A longitudinal population-based epidemiological study. Clin. Lab., 2017, 63(10), 1581-1587.
[http://dx.doi.org/10.7754/Clin.Lab.2017.170311] [PMID: 29035437]
[36]
Mele, C.; Tagliaferri, M.A.; Saraceno, G.; Mai, S.; Vietti, R.; Zavattaro, M.; Aimaretti, G.; Scacchi, M.; Marzullo, P. Serum uric acid potentially links metabolic health to measures of fuel use in lean and obese individuals. Nutr. Metab. Cardiovasc. Dis., 2018, 28(10), 1029-1035.
[http://dx.doi.org/10.1016/j.numecd.2018.06.010] [PMID: 30139687]
[37]
Duicu, C.; Mărginean, C.O.; Voidăzan, S.; Tripon, F.; Bănescu, C. FTO rs 9939609 SNP Is associated with adiponectin and leptin levels and the risk of obesity in a cohort of romanian children population. Medicine (Baltimore), 2016, 95(20)e3709
[http://dx.doi.org/10.1097/MD.0000000000003709] [PMID: 27196486]
[38]
Lous, J.; Freund, K.S. Predictors of weight loss in young adults who are over-weight or obese and have psychosocial problems: a post hoc analysis. BMC Fam. Pract., 2016, 17, 43.
[http://dx.doi.org/10.1186/s12875-016-0437-8] [PMID: 27068690]
[39]
Näslund, E.; Andersson, I.; Degerblad, M.; Kogner, P.; Kral, J.G.; Rössner, S.; Hellström, P.M. Associations of leptin, insulin resistance and thyroid function with long-term weight loss in dieting obese men. J. Intern. Med., 2000, 248(4), 299-308.
[http://dx.doi.org/10.1046/j.1365-2796.2000.00737.x] [PMID: 11086640]
[40]
Baxter, K.A.; Ware, R.S.; Batch, J.A.; Truby, H. Predicting success: factors associated with weight change in obese youth undertaking a weight management program. Obes. Res. Clin. Pract., 2013, 7(2), e147-e154.
[http://dx.doi.org/10.1016/j.orcp.2011.09.004] [PMID: 24331776]
[41]
McDade, T.W. Early environments and the ecology of inflammation. Proc. Natl. Acad. Sci. USA, 2012, 109(Suppl. 2), 17281-17288.
[http://dx.doi.org/10.1073/pnas.1202244109] [PMID: 23045646]
[42]
Kong, L.C.; Wuillemin, P.H.; Bastard, J.P.; Sokolovska, N.; Gougis, S.; Fellahi, S.; Darakhshan, F.; Bonnefont-Rousselot, D.; Bittar, R.; Doré, J.; Zucker, J.D.; Clément, K.; Rizkalla, S. Insulin resistance and inflammation predict kinetic body weight changes in response to dietary weight loss and maintenance in overweight and obese subjects by using a Bayesian network approach. Am. J. Clin. Nutr., 2013, 98(6), 1385-1394.
[http://dx.doi.org/10.3945/ajcn.113.058099] [PMID: 24172304]

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