Diet Quality and Glycemic Control in Patients with Type 2 Diabetes

Published:January 17, 2019DOI:



      The overall diet quality of individuals and populations can be assessed by dietary indexes based on information from food surveys. Few studies have evaluated the diet quality of individuals with type 2 diabetes or its potential associations with glycemic control.


      To evaluate the relationship between diet quality and glycemic control.


      Cross-sectional study with consecutive enrollment from 2013 to 2016.


      Outpatients with type 2 diabetes treated at a university hospital in southern Brazil.

      Main outcome measures

      Dietary information was obtained by a quantitative food frequency questionnaire validated for patients with diabetes. Overall diet quality was evaluated by the Healthy Eating Index 2010. Glycemic control was assessed by fasting plasma glucose and glycated hemoglobin.

      Statistical analyses

      A receiver operating characteristic curve was constructed to find the optimal Healthy Eating Index cutoff point to discriminate diet quality, considering good glycemic control as glycated hemoglobin level <7%. Patients were then classified as having lower vs higher diet quality, and the two groups were compared statistically. Logistic regression models were constructed with glycated hemoglobin level ≥7% as the dependent variable, adjusted for age, current smoking, diabetes duration and treatment, physical activity, body mass index, high-density lipoprotein cholesterol level, and energy intake.


      A total of 229 patients with type 2 diabetes (median age=63.0 years [interquartile range=58.0 to 68.5 years]; diabetes duration=10.0 years [interquartile range=5 to 19 years]; body mass index 30.8±4.3; and glycated hemoglobin=8.1% [interquartile range=6.9% to 9.7%]) were evaluated. A Healthy Eating Index score >65% yielded the best properties (area under the receiver operator characteristic curve=0.60; sensitivity=71.2%; specificity=52.1%; P=0.018). Patients with lower-quality diets were younger and more likely to be current smokers than patients with higher-quality diets. After adjusting for confounders, patients with lower-quality diets had nearly threefold odds of poorer glycemic control (2.92; 95% CI 1.27 to 6.71; P=0.012) than those in the higher-quality diet group.


      Lower diet quality, defined as an Healthy Eating Index 2010 score <65%, was associated with poor glycemic control in this sample of outpatients with type 2 diabetes.


      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 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


        • American Diabetes Association
        Classification and diagnosis of diabetes: Standards of medical care in diabetes - 2018.
        Diabetes Care. 2018; 41: S13-S27
        • International Diabetes Federation
        IDF clinical practice recommendations for managing type 2 diabetes in primary care-2017.
        • Telo G.H.
        • Cureau F.V.
        • de Souza M.S.
        • Andrade T.S.
        • Copês F.
        • Schaan B.D.
        Prevalence of diabetes in Brazil over time: A systematic review with meta-analysis.
        Diabetol Metab Syndr. 2016; 8: 65
        • American Diabetes Association
        Lifestyle management: Standards of medical care in diabetes – 2018.
        Diabetes Care. 2018; 41: S38-S50
        • Evert A.B.
        • Boucher J.L.
        • Cypress M.
        • et al.
        Nutrition therapy recommendations for the management of adults with diabetes.
        Diabetes Care. 2014; 37: S120-S143
        • Schap T.
        • Kuczynski K.
        • Hiza H.
        Healthy Eating Index-beyond the score.
        J Acad Nutr Diet. 2017; 117: 519-521
        • Mangou A.
        • Grammatikopoulou M.G.
        • Mirkopoulou D.
        • Sailer N.
        • Kotzamanidis C.
        • Tsigga M.
        Associations between diet quality, health status and diabetic complications with type 2 diabetes and comorbid obesity.
        Endocrinol Nutr. 2012; 59: 109-116
        • Kim J.Y.
        • Cho Y.Y.
        • Park Y.M.
        • et al.
        Association of dietary quality indices with glycemic status in Korean patients with type 2 diabetes.
        Clin Nutr Res. 2013; 2: 100-106
        • Murray A.E.
        • McMorrow A.M.
        • O'Connor E.
        • et al.
        Dietary quality in a sample of adults with type 2 diabetes mellitus in Ireland: A cross-sectional case control study.
        Nutr J. 2013; 12: 110
      1. Definition, Diagnosis and Classification of Diabetes Mellitus and its Complications: Report of a WHO Consultation. Part 1, Diagnosis and Classification of Diabetes Mellitus. World Health Organization, Geneva, Switzerland1999
        • Associação Brasileira de Empresas de Pesquisa
        Critério de Classificação Econômica Brasil. São Paulo, 2015.
        Date accessed: July 23, 2018
      2. International Physical Activity Questionnaire.
      3. IPAQ Research Committee. Guidelines for Data Processing and Analysis of the International Physical Activity Questionnaire (IPAQ). November, 2005. Accessed December 27, 2018.

        • O'Brien E.
        • Waeber B.
        • Parati G.
        • Staessen J.
        • Myers M.G.
        Blood pressure measuring devices: Recommendations of the European Society of Hypertension.
        BMJ. 2001; 322: 531-536
        • Whelton P.K.
        • Carey R.M.
        • Aronow W.S.
        • et al.
        2017 ACC/AHA/AAPA/ABC/ACPM/AGS/APhA/ASH/ASH/ASPC/NMA/PCNA guideline for the prevention, detection, evaluation, and management of high blood pressure in adults: Executive summary: A report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines.
        Hypertension. 2018; 71: 1269-1324
        • American Diabetes Association
        Microvascular complications and foot care: Standards of medical care in diabetes.
        Diabetes Care. 2018; 41: S105-S118
        • Gibson R.S.
        Anthropometric assessment of body composition.
        in: Principles of Nutritional Assessment. 2nd ed. Oxford University Press, New York, NY2005: 282
        • International Diabetes Federation
        The IDF consensus worldwide definition of the metabolic syndrome, 2006.
        • World Health Organization
        Global database on body mass index. BMI classification. 2006.
        • Lipschitz D.A.
        Screening for nutritional status in the elderly.
        Prim Care. 1994; 21: 55-67
        • Sarmento R.A.
        • Riboldi B.P.
        • da Costa Rodrigues T.
        • de Azevedo M.J.
        • de Almeida J.C.
        Development of a quantitative food frequency questionnaire for Brazilian patients with type 2 diabetes.
        BMC Public Health. 2013; 13: 740
        • Sarmento R.A.
        • Antonio J.P.
        • Riboldi B.P.
        • et al.
        Reproducibility and validity of a quantitative FFQ designed for patients with type 2 diabetes mellitus from southern Brazil.
        Public Health Nutr. 2013; 17: 2237-2245
        • Guenther P.M.
        • Casavale K.O.
        • Reedy J.
        • et al.
        Update of the Healthy Eating Index: HEI-2010.
        J Acad Nutr Diet. 2013; 113: 569-580
        • Tabela Brasileira de Composição de Alimentos/ NEPA-UNICAMP
        4a edição revisada e ampliada.
        • Willet W.
        Issues in analysis and presentation of dietary data.
        in: Nutritional Epidemiology. 3rd ed. Oxford University Press, New York, NY2013: 306
        • Trinder P.
        Determination of blood glucose using an oxidase-peroxidase system with a noncarcinogenic chromogen.
        J Clin Pathol. 1969; 22: 148-161
        • Camargo J.L.
        • Zelmanovitz T.
        • Paggi A.
        • Friedman R.
        • Gross J.L.
        Accuracy of conversion formulae for estimation of glycohaemoglobin.
        Scand J Clin Lab Invest. 1998; 58: 521-558
        • Farish E.
        • Fletcher C.D.
        A comparison of two micro-methods for the determination of HDL2 and HDL3 cholesterol.
        Clin Chim Acta. 1983; 129: 221-228
        • Friedewald W.T.
        • Levy R.L.
        • Fredrickson D.S.
        Estimation of the concentration of low-density lipoprotein cholesterol in plasma, without use of the preparative ultracentrifuge.
        Clin Chem. 1972; 18: 499-502
        • Fabiny D.L.
        • Ertingshousen G.
        Automated reaction-rate method for determination of serum creatinine with the centrifichem.
        Clin Chem. 1971; 15: 696-704
        • Chronic Kidney Disease Epidemiology Collaboration
        GFR calculator.
        • Camargo J.L.
        • Lara G.M.
        • Wendland A.E.
        • Gross J.L.
        • de Azevedo M.J.
        Agreement of different immunoassays for urinary albumin measurement.
        Clin Chem. 2008; 54: 925-927
      4. PASW Statistics for Windows. Version 18.0. SPSS Inc, Chicago, IL2009
        • Moreira P.R.S.
        • Rocha N.P.
        • Milagres L.C.
        • Novaes J.F.
        Critical analysis of the diet quality of the Brazilian population according to the Healthy Eating Index: A systematic review.
        Cien Saude Colet. 2015; 20: 3907-3923
        • Hu F.B.
        Dietary pattern analysis: A new direction in nutritional epidemiology.
        Curr Opin Lipidol. 2002; 13: 3-9
        • Volp A.C.P.
        • Alfenas R.C.G.
        • Costa N.M.B.
        • Minim V.P.R.
        • Stringueta P.C.
        • Bressan J.
        Dietetic indices for assessment of diet quality.
        Rev Nutr. 2010; 23: 281-295
        • Møller G.
        • Andersen H.K.
        • Snorgaard O.
        A systematic review and meta-analysis of nutrition therapy compared with dietary advice in patients with type 2 diabetes.
        Am J Clin Nutr. 2017; 106: 1394-1400
        • Shim J.-S.
        • Oh K.
        • Kim H.C.
        Dietary assessment methods in epidemiologic studies.
        Epidemiol Health. 2014; 36: e2014009
        • Reedy J.
        • Lerman J.L.
        • Krebs-Smith S.M.
        • et al.
        Evaluation of the Healthy Eating Index-2015.
        J Acad Nutr Diet. 2018; 118: 1622-1633


      J. P. Antonio is researchers, Endocrinology Division, Hospital de Clínicas de Porto Alegre, Porto Alegre, Rio Grande do Sul, Brazil, dietitians, Food and Nutrition Research Center, Hospital de Clínicas de Porto Alegre, Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil.


      R. A. Sarmento is researchers, Endocrinology Division and Food and Nutrition Research Center, Hospital de Clínicas de Porto Alegre, Porto Alegre, Rio Grande do Sul, Brazil, dietitians, Hospital de Clínicas de Porto Alegre, Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil.


      J. C. de Almeida is a professor, Endocrinology Division, Hospital de Clínicas de Porto Alegre, Porto Alegre, Rio Grande do Sul, Brazil, and a professor, Department of Nutrition, Faculdade de Medicina, Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil.