Advertisement

NOTICE: We are experiencing technical issues with Academy members trying to log into the JAND site using Academy member login credentials. We are working to resolve the issue as soon as possible. Alternatively, if you are an Academy member, you can access the JAND site by registering for an Elsevier account and claiming access using the links at the top of the JAND site. Email us at [email protected] for assistance. Thanks for your patience!

Dietary Insulin Index and Dietary Insulin Load in Relation to Metabolic Syndrome: The Shahedieh Cohort Study

      Abstract

      Background

      Insulin resistance and hyperinsulinemia are involved in the etiology of metabolic syndrome (MetS) and its components.

      Objective

      The current study assessed the association of dietary insulin load (DIL) and dietary insulin index (DII) with the odds of having MetS among a large population of Iranian adults.

      Design

      This study was a cross-sectional analysis of the Shahedieh cohort study, which began in 2015-2016 and continues to the present day.

      Participants/setting

      A total of 5,954 Iranian adults, aged 35 to 70 years, were included in the current analysis. To collect dietary data, the validated block-format 120-item semiquantitative Food Frequency Questionnaire was used. MetS was defined using the criteria belonging to the Iranian-modified National Cholesterol Education Program for Adults.

      Main outcome measures

      Enzymatic colorimetric tests were used to measure fasting blood glucose, triglyceride, and high-density lipoprotein cholesterol concentrations; blood pressure and waist circumference were measured using the standard protocols.

      Statistical analysis

      Binary logistic regression with adjusted models was used to examine the association of DIL and DII with MetS.

      Results

      After taking potential confounders into account, moderate DIL was associated with increased odds of MetS in men, meaning that men in the third quartile of DIL had 61% greater odds for having MetS compared with those in the first quartile (odds ratio [OR]: 1.61, 95% confidence interval [CI]: 1.02-2.54). Such a significant association was not seen for DII. In women, DIL was significantly associated with increased odds of developing MetS. After controlling for potential confounders, women in the top quartile of DIL had 77% greater odds for having MetS compared with women in the bottom quartile (OR: 1.77; 95% CI: 1.08-2.91). This significant positive association was also seen for DII, such that a higher score of DII was associated with 41% greater odds of MetS (OR: 1.41, 95% CI: 1.08-1.83).

      Conclusions

      Adherence to a diet with a high DIL and DII is associated with greater odds of having MetS in women. Also, moderate DIL was associated with increased odds of MetS in men.

      Keywords

      To read this article in full you will need to make a payment

      Purchase one-time access:

      Academic & Personal: 24 hour online accessCorporate R&D Professionals: 24 hour online access
      One-time access price info
      • For academic or personal research use, select 'Academic and Personal'
      • For corporate R&D use, select 'Corporate R&D Professionals'

      Subscribe:

      Subscribe to Journal of the Academy of Nutrition and Dietetics
      Already a print subscriber? Claim online access
      Already an online subscriber? Sign in
      Institutional Access: Sign in to ScienceDirect

      References

        • Yamagishi S.
        • Nakamura K.
        • Takeuchi M.
        Inhibition of postprandial hyperglycemia by acarbose is a promising therapeutic strategy for the treatment of patients with the metabolic syndrome.
        Med Hypotheses. 2005; 65: 152-154
        • Hiyoshi T.
        • Fujiwara M.
        • Yao Z.
        Postprandial hyperglycemia and postprandial hypertriglyceridemia in type 2 diabetes.
        J Biomed Res. 2017; 30: 1-16
        • Umpierrez G.E.
        • Bailey T.S.
        • Carcia D.
        • Shaefer C.
        • Shubrook J.H.
        • Skolnik N.
        Improving postprandial hyperglycemia in patients with type 2 diabetes already on basal insulin therapy: Review of current strategies.
        J Diabetes. 2018; 10: 94-111
        • Ludwig D.S.
        The glycemic index: Physiological mechanisms relating to obesity, diabetes, and cardiovascular disease.
        JAMA. 2002; 287: 2414-2423
        • Liu Y.S.
        • Wu Q.J.
        • Xia Y.
        • et al.
        Carbohydrate intake and risk of metabolic syndrome: A dose-response meta-analysis of observational studies.
        Nutr Metab Cardiovasc Dis. 2019; 29: 1288-1298
        • Ahn J.
        • Kim N.S.
        • Lee B.K.
        • Park S.
        Carbohydrate intake exhibited a positive association with the risk of metabolic syndrome in both semi-quantitative food frequency questionnaires and 24-hour recall in women.
        J Korean Med Sci. 2017; 32: 1474-1483
        • Ang M.
        • Muller A.S.
        • Wagenlehner F.
        • Pilatz A.
        • Linn T.
        Combining protein and carbohydrate increases postprandial insulin levels but does not improve glucose response in patients with type 2 diabetes.
        Metabolism. 2012; 61: 1696-1702
        • Moghaddam E.
        • Vogt J.A.
        • Wolever T.M.
        The effects of fat and protein on glycemic responses in nondiabetic humans vary with waist circumference, fasting plasma insulin, and dietary fiber intake.
        J Nutr. 2006; 136: 2506-2511
        • Nuttall F.Q.
        • Gannon M.C.
        Plasma glucose and insulin response to macronutrients in nondiabetic and NIDDM subjects.
        Diabetes Care. 1991; 14: 824-838
        • Holt S.
        • Miller J.
        • Petocz P.
        An insulin index of foods: The insulin demand generated by 1000-kJ portions of common foods.
        Am J Clin Nutr. 1997; 66: 1264-1276
        • Bao J.
        • de Jong V.
        • Atkinson F.
        • Petocz P.
        • Brand-Miller J.C.
        Food insulin index: Physiologic basis for predicting insulin demand evoked by composite meals.
        Am J Clin Nutr. 2009; 90: 986-992
        • Anjom-Shoae J.
        • Shayanfar M.
        • Mohammad-Shirazi M.
        • et al.
        Dietary insulin index and insulin load in relation to glioma: Findings from a case-control study.
        Nutr Neurosci. 2019; : 1-9
        • Bell K.J.
        • Petocz P.
        • Colagiuri S.
        • Brand-Miller J.C.
        Algorithms to improve the prediction of postprandial insulinaemia in response to common foods.
        Nutrients. 2016; 8: 210
        • Bao J.
        • Atkinson F.
        • Petocz P.
        • Willett W.C.
        • Brand-Miller J.C.
        Prediction of postprandial glycemia and insulinemia in lean, young, healthy adults: Glycemic load compared with carbohydrate content alone.
        Am J Clin Nutr. 2011; 93: 984-996
        • Grundy S.M.
        • Cleeman J.I.
        • Daniels S.R.
        • et al.
        Diagnosis and management of the metabolic syndrome: An American Heart Association/National Heart, Lung, and Blood Institute scientific statement.
        Circulation. 2005; 112: 2735-2752
        • Balkau B.
        • Vernay M.
        • Mhamdi L.
        • et al.
        The incidence and persistence of the NCEP (National Cholesterol Education Program) metabolic syndrome. The French DESIR study.
        Diabetes Metab. 2003; 29: 526-532
        • Gluvic Z.
        • Zaric B.
        • Resanovic I.
        • et al.
        Link between metabolic syndrome and insulin resistance.
        Curr Vasc Pharmacol. 2017; 15: 30-39
        • Poustchi H.
        • Eghtesad S.
        • Kamangar F.
        • et al.
        Prospective Epidemiological Research Studies in Iran (the PERSIAN Cohort Study): Rationale, objectives, and design.
        Am J Epidemiol. 2018; 187: 647-655
        • Mirmiran P.
        • Esfahani F.H.
        • Mehrabi Y.
        • Hedayati M.
        • Azizi F.
        Reliability and relative validity of an FFQ for nutrients in the Tehran lipid and glucose study.
        Public Health Nutr. 2010; 13: 654-662
        • Ahuja J.
        • Montville J.B.
        • Omolewa-Tomobi G.
        • et al.
        USDA Food and Nutrient Database for Dietary Studies, 5.0–Documentation and User Guide.
        US Department of Agriculture, Agricultural Research Service, Food Surveys Research Group, Beltsville, MD2012
        • Dorosti Motlagh A.R.
        • Tabatabaei M.
        Iranain Food Composition Table.
        Tehran, Iran: Iran Donyaye Taghzieh Press. 2007;
        • Mohammadifard N.
        • Sajjadi F.
        • Maghroun M.
        • Alikhasi H.
        • Nilforoushzadeh F.
        • Sarrafzadegan N.
        Validation of a simplified food frequency questionnaire for the assessment of dietary habits in Iranian adults: Isfahan Healthy Heart Program.
        Iran. ARYA Atheroscler. 2015; 11: 139
        • Sadeghi O.
        • Hassanzadeh-Keshteli A.
        • Afshar H.
        • Esmaillzadeh A.
        • Adibi P.
        The association of whole and refined grains consumption with psychological disorders among Iranian adults.
        Eur J Nutr. 2019; 58: 211-225
        • Janssen I.
        • Katzmarzyk P.T.
        • Ross R.
        Body mass index, waist circumference, and health risk: Evidence in support of current National Institutes of Health guidelines.
        Arch Intern Med. 2002; 162: 2074-2079
        • Maddison R.
        • Mhurchu C.N.
        • Jiang Y.
        • et al.
        International physical activity questionnaire (IPAQ) and New Zealand physical activity questionnaire (NZPAQ): A doubly labelled water validation.
        Int J Behav Nutr Phys Act. 2007; 4: 62
        • Azizi F.
        • Hadaegh F.
        • Khalili D.
        • et al.
        Appropriate definition of metabolic syndrome among Iranian adults: Report of the Iranian National Committee of Obesity.
        Arch Iran Med. 2010; 13: 426-428
        • Grundy S.M.
        • Hansen B.
        • Smith Jr., S.C.
        • Cleeman J.I.
        • Kahn R.A.
        Clinical management of metabolic syndrome: Report of the American Heart Association/National Heart, Lung, and Blood Institute/American Diabetes Association conference on scientific issues related to management.
        Arterioscler Thromb Vasc Biol. 2004; 24: e19-e24
        • Arora H.
        Doing Data Analysis with SPSS Version 18.0.
        Abhigyan. 2014; 32: 81-83
        • Aguilar M.
        • Bhuket T.
        • Torres S.
        • Liu B.
        • Wong R.J.
        Prevalence of the metabolic syndrome in the United States, 2003-2012.
        JAMA. 2015; 313: 1973-1974
        • Ghorabi S.
        • Salari-Moghaddam A.
        • Daneshzad E.
        • Sadeghi O.
        • Azadbakht L.
        • Djafarian K.
        Association between the DASH diet and metabolic syndrome components in Iranian adults.
        Diabetes Metab Syndr. 2019; 13: 1699-1704
        • Okosun I.S.
        • Okosun B.
        • Lyn R.
        • Airhihenbuwa C.
        Surrogate indexes of insulin resistance and risk of metabolic syndrome in non-Hispanic white, non-Hispanic black and Mexican American.
        Diabetes Metab Syndr. 2019; 14: 3-9
        • Jung C.-H.
        • Choi K.M.
        Impact of high-carbohydrate diet on metabolic parameters in patients with type 2 diabetes.
        Nutrients. 2017; 9: 322
        • Hsieh C.H.
        • Wu C.Z.
        • Hsiao F.C.
        • et al.
        The impact of metabolic syndrome on insulin sensitivity, glucose sensitivity, and acute insulin response after glucose load in early-onset type 2 diabetes mellitus: Taiwan Early-Onset Type 2 Diabetes Cohort Study.
        Metabolism. 2008; 57: 1615-1621
        • Nimptsch K.
        • Brand-Miller J.C.
        • Franz M.
        • Sampson L.
        • Willett W.C.
        • Giovannucci E.
        Dietary insulin index and insulin load in relation to biomarkers of glycemic control, plasma lipids, and inflammation markers.
        Am J Clin Nutr. 2011; 94: 182-190
        • Mirmiran P.
        • Esfandiari S.
        • Bahadoran Z.
        • Tohidi M.
        • Azizi F.
        Dietary insulin load and insulin index are associated with the risk of insulin resistance: A prospective approach in Tehran lipid and glucose study.
        J Diabetes Metab Disord. 2015; 15: 23
        • Esposito K.
        • Marfella R.
        • Ciotola M.
        • et al.
        Effect of a Mediterranean-style diet on endothelial dysfunction and markers of vascular inflammation in the metabolic syndrome: A randomized trial.
        JAMA. 2004; 292: 1440-1446
        • Azadbakht L.
        • Mirmiran P.
        • Esmaillzadeh A.
        • Azizi T.
        • Azizi F.
        Beneficial effects of a Dietary Approaches to Stop Hypertension eating plan on features of the metabolic syndrome.
        Diabetes Care. 2005; 28: 2823-2831
        • Anjom-Shoae J.
        • Keshteli A.H.
        • Sadeghi O.
        • et al.
        Association between dietary insulin index and load with obesity in adults.
        Eur J Nutr. 2019; : 1-13
        • Lovejoy J.
        • Sainsbury A.
        • Group S.C.W.
        Sex differences in obesity and the regulation of energy homeostasis.
        Obes Rev. 2009; 10: 154-167
        • Song Q.B.
        • Zhao Y.
        • Liu Y.Q.
        • Zhang J.
        • Xin S.J.
        • Dong G.H.
        Sex difference in the prevalence of metabolic syndrome and cardiovascular-related risk factors in urban adults from 33 communities of China: The CHPSNE study.
        Diab Vasc Dis Res. 2015; 12: 189-198
        • Pelletier G.
        • Li S.
        • Luu-The V.
        • Labrie F.
        Oestrogenic regulation of pro-opiomelanocortin, neuropeptide Y and corticotrophin-releasing hormone mRNAs in mouse hypothalamus.
        J Neuroendocrinol. 2007; 19: 426-431
        • Clegg D.J.
        • Brown L.M.
        • Zigman J.M.
        • et al.
        Estradiol-dependent decrease in the orexigenic potency of ghrelin in female rats.
        Diabetes. 2007; 56: 1051-1058
        • Adamczak M.
        • Rzepka E.
        • Chudek J.
        Wi,cek A. Ageing and plasma adiponectin concentration in apparently healthy males and females.
        Clin Endocrinol (Oxf). 2005; 62: 114-118
        • Kahn S.E.
        • Hull R.L.
        • Utzschneider K.M.
        Mechanisms linking obesity to insulin resistance and type 2 diabetes.
        Nature. 2006; 444: 840
        • Hellstrom P.M.
        Satiety signals and obesity.
        Curr Opin Gastroenterol. 2013; 29: 222-227
        • Llewellyn C.H.
        • Trzaskowski M.
        • van Jaarsveld C.H.M.
        • Plomin R.
        • Wardle J.
        Satiety mechanisms in genetic risk of obesity.
        JAMA Pediatr. 2014; 168: 338-344
        • Prescott J.
        • Bao Y.
        • Viswanathan A.N.
        • Giovannucci E.L.
        • Hankinson S.E.
        • De Vivo I.
        Dietary insulin index and insulin load in relation to endometrial cancer risk in the Nurses' Health Study.
        Cancer Epidemiol Biomarkers Prev. 2014; 23: 1512-1520
        • Bao Y.
        • Nimptsch K.
        • Wolpin B.M.
        • et al.
        Dietary insulin load, dietary insulin index, and risk of pancreatic cancer.
        Am J Clin Nutr. 2011; 94: 862-868
        • Bahreynian M.
        • Esmaillzadeh A.
        Quantity and quality of carbohydrate intake in Iran: A target for nutritional intervention.
        Arch Iran Med. 2012; 15: 648-649
        • Ansarimoghaddam A.
        • Adineh H.A.
        • Zareban I.
        • Iranpour S.
        • HosseinZadeh A.
        • Kh F.
        Prevalence of metabolic syndrome in Middle-East countries: Meta-analysis of cross-sectional studies.
        Diabetes Metab Syndr. 2018; 12: 195-201
        • Kalan Farmanfarma K.
        • Kaykhaei M.A.
        • Adineh H.A.
        • Mohammadi M.
        • Dabiri S.
        • Ansari-Moghaddam A.
        Prevalence of metabolic syndrome in Iran: A meta-analysis of 69 studies.
        Diabetes Metab Syndr. 2019; 13: 792-799

      Biography

      O. Sadeghi is an academic researcher, Students’ Scientific Research Center,and the Department of Community Nutrition, School of Nutritional Sciences and Dietetics, both at Tehran University of Medical Sciences, Tehran, Iran.

      Biography

      H. Hasani is an academic researcher, Department of Community Nutrition, School of Nutritional Sciences and Dietetics, both at Tehran University of Medical Sciences, Tehran, Iran.

      Biography

      H. Mozaffari-Khosravi is a professor of nutrition, Nutrition and Food Security Research Center and Department of Nutrition, School of Public Health, Shahid Sadoughi University of Medical Sciences, Yazd, Iran.

      Biography

      M. H. Lotfi is a professor of biostatistics and epidemiology, Department of Biostatistics and Epidemiology, School of Public Health, Shahid Sadoughi University of Medical Sciences, Yazd, Iran.

      Biography

      M. Mirzaei is an associate professor of biostatistics and epidemiology, Department of Biostatistics and Epidemiology, School of Public Health, Shahid Sadoughi University of Medical Sciences, Yazd, Iran.

      Biography

      V. Maleki is an academic researcher, Student Research Committee, Tabriz University of Medical Sciences, Tabriz, Iran.