Action for Health in Diabetes (Look AHEAD) Trial: Baseline Evaluation of Selected Nutrients and Food Group Intake

      Abstract

      Background

      Little has been reported regarding food and nutrient intake in individuals diagnosed with type 2 diabetes, and most reports have been based on findings in select groups or individuals who self-reported having diabetes.

      Objective

      To describe the baseline food and nutrient intake of the Look AHEAD (Action for Health in Diabetes) trial participants, compare participant intake to national guidelines, and describe demographic and health characteristics associated with food group consumption.

      Methods

      The Look AHEAD trial is evaluating the effects of a lifestyle intervention (calorie control and increased physical activity for weight loss) compared with diabetes support and education on long-term cardiovascular and other health outcomes. Participants are 45 to 75 years old, overweight or obese (body mass index [BMI]≥25), and have type 2 diabetes. In this cross-sectional analysis, baseline food consumption was assessed by food frequency questionnaire from 2,757 participants between September 2000 and December 2003.

      Statistical analysis

      Descriptive statistics were used to summarize intake by demographic characteristics. Kruskal-Wallis tests assessed univariate effects of characteristics on consumption. Multiple linear regression models assessed factors predictive of intake. Least square estimates were based on final models, and logistic regression determined factors predictive of recommended intake.

      Results

      Ninety-three percent of the participants exceeded the recommended percentage of calories from fat, 85% exceeded the saturated fat recommendation, and 92% consumed too much sodium. Also, fewer than half met the minimum recommended servings of fruit, vegetables, dairy, and grains.

      Conclusions

      These participants with pre-existing diabetes did not meet recommended food and nutrition guidelines. These overweight adults diagnosed with diabetes are exceeding recommended intake of fat, saturated fats, and sodium, which may contribute to increasing their risk of cardiovascular disease and other chronic diseases.
      The Dietary Guidelines for Americans (
      US Department of Health and Human Services, US Department of Agriculture
      Dietary Guidelines for Americans, 2000.
      ) and the Institute of Medicine Dietary Reference Intakes (
      Institute of Medicine Dietary Reference Intakes for Calcium, Phosphorus, Magnesium, Vitamin D, and Fluoride.
      ,
      Institute of Medicine Dietary Reference Intakes for Energy, Carbohydrate, Fiber, Fat, Fatty Acids, Cholesterol, Protein, and Amino Acids (Macronutrients).
      ,
      Institute of Medicine Dietary Reference Intakes for Water, Potassium, Sodium, Chloride, and Sulfate.
      ) are based on sound scientific evidence regarding consumption of foods and specific nutrients in relation to physiologic health outcomes. The American Diabetes Association models food intake recommendations in individuals with type 2 diabetes on these recommendations along with evidence-based nutrition research conducted in subjects who have type 2 diabetes (
      • Franz M.J.
      • Bantle J.
      • Beebe C.A.
      • Brunzell J.D.
      • Chiasson J.L.
      • Garg A.
      • Holzmeister Look A.H.E.A.D.
      • Hoogwerf B.
      • Mayer-Davis E.
      • Mooradian A.
      • Purnell J.Q.
      • Wheeler M.
      American Diabetes Association Position Statement: Evidence-based nutrition principles and recommendations for the treatment and prevention of diabetes and related complications.
      ,
      • Franz M.J.
      • Bantle J.P.
      • Beebe C.A.
      • Brunzell J.D.
      • Chiasson J.L.
      • Garg A.
      • Holzmeister Look A.H.E.A.D.
      • Hoogwerf B.
      • Mayer-Davis E.
      • Mooradian A.D.
      • Purnell J.Q.
      • Wheeler M.
      Evidence-based nutrition principles and recommendations for the treatment and prevention of diabetes and related complications (Technical Review).
      ). The American Diabetes Association's nutrition recommendations for people with diabetes emphasize the goals of medical nutrition therapy that encompasses the following: maintaining or achieving (a) normal glycemia, or as close to normal in a range that is safe for the patient, (b) a lipid and lipoprotein profile that reduces risk of cardiovascular disease, and (c) blood pressure in the normal range or as close to normal that can be safely achieved.
      There is an array of scientific literature pertaining to food intake and risk of developing type 2 diabetes. However, little has been reported regarding food consumption patterns and quality of food intake in people diagnosed with type 2 diabetes, and most reports have been based on findings in international populations (
      • Cruz A.F.
      • Calle-Pascual A.L.
      Diabetes and Nutrition Study Group, Spanish Diabetes Association.Diabetes Nutrition and Complications Trial: Trends in nutritional pattern between 1993 and 2000 and targets of diabetes treatment in a sample of Spanish people with diabetes.
      ,
      • Gauthier-Chelle K.
      • Mennen L.
      • Arnault N.
      • Rigalleau V.
      • Hercberg S.
      • Gin H.
      Comparison of the diet of self-declared diabetics with non-diabetic patients in the SU.VI.MAX study: Did the diabetics modify their nutritional behavior?.
      ,
      • Helmer C.
      • Bricout H.
      • Gin H.
      • Barberger-Gateau P.
      Macronutrient intake and discrepancy with nutritional recommendations in a group of elderly diabetic subjects.
      ,
      • Toeller M.
      • Klischan A.
      • Heitkamp G.
      • Schumacher W.
      • Milne R.
      • Buyken A.
      • Karamanos B.
      • Gries F.A.
      Nutritional intake of 2868 IDDM patients from 30 centres in Europe EURODIAB IDDM Complications Study Group.
      ), in very select groups (
      • Parker D.R.
      • McPhillips J.B.
      • Lapane K.L.
      • Lasater T.M.
      • Carleton R.A.
      Nutrition and health practices of diabetic and nondiabetic men and women from two southeastern New England communities.
      ,
      • Shimakawa T.
      • Herrera-Acena M.G.
      • Colditz G.A.
      • Manson J.E.
      • Stampfer M.J.
      • Willett W.C.
      • Stamper M.J.
      Comparison of diets of diabetic and nondiabetic women.
      ), or in individuals who self-reported having type 2 diabetes (
      • Nelson K.M.
      • Reiber G.
      • Boyko E.J.
      Diet and exercise among adults with type 2 diabetes: Findings from the Third National Health and Nutrition Examination Survey (NHANES III).
      ). The Action for Health in Diabetes (Look AHEAD) trial is being conducted in sites across the United States and offers a unique opportunity to evaluate the food and nutrient intake of a large number of individuals diagnosed with type 2 diabetes. Look AHEAD allows for comparison of the participants' baseline nutrient and food group consumption to the intake guidelines recommended by the Institute of Medicine and those in the US Department of Agriculture (USDA) Food Guide Pyramid (
      US Department of Health and Human Services, US Department of Agriculture
      Dietary Guidelines for Americans, 2000.
      ,
      Institute of Medicine Dietary Reference Intakes for Calcium, Phosphorus, Magnesium, Vitamin D, and Fluoride.
      ,
      Institute of Medicine Dietary Reference Intakes for Energy, Carbohydrate, Fiber, Fat, Fatty Acids, Cholesterol, Protein, and Amino Acids (Macronutrients).
      ,
      Institute of Medicine Dietary Reference Intakes for Water, Potassium, Sodium, Chloride, and Sulfate.
      ,

      The Food Guide Pyramid. Washington, DC: US Department of Agriculture Center for Nutrition Policy and Promotion 2000. Home and Garden Bulletin No. 252.

      ). This important evaluation may provide insights into dietary practices of people with type 2 diabetes across the nation.
      The purpose of this report is to: (a) describe baseline food intake of the Look AHEAD participants, (b) compare nutrient and food intake of Look AHEAD participants to the recommendations of the Institute of Medicine and those contained in the USDA Food Guide Pyramid, and (c) describe participant characteristics (ie, sex, ethnicity, age, income) associated with consumption of specific food groups. It was hypothesized that, in general, few Look AHEAD participants would meet the food and nutrient intake recommendations, and that sex, ethnicity, and age would be associated with meeting recommendations.

      Methods

      This is a cross-sectional analysis of food and nutrient intake measured at the baseline visit of the Look AHEAD trial. A comprehensive description of the Look AHEAD trial design and intervention has been published elsewhere (
      • Ryan D.H.
      • Espeland M.A.
      • Foster G.D.
      • Haffner S.M.
      • Hubbard V.S.
      • Johnson K.C.
      • Kahn S.E.
      • Knowler W.C.
      • Yanovski S.Z.
      Look AHEAD Research Group
      Look AHEAD (Action for Health in Diabetes): Design and methods for a clinical trial of weight loss for the prevention of cardiovascular disease in type 2 diabetes.
      ,
      • Wadden T.A.
      • West D.S.
      • Delahanty L.
      • Jakicic J.
      • Rejeski J.
      • Williamson D.
      • Berkowitz R.I.
      • Kelley D.E.
      • Tomchee C.
      • Hill J.O.
      • Kumanyika S.
      Look AHEAD Research Group
      The Look AHEAD study: A description of the lifestyle intervention and the evidence supporting it.
      ). Briefly, approximately 5,000 people, age 45 to 75 years, who are overweight or obese (body mass index [BMI; calculated as kg/m2] ≥25) and have type 2 diabetes are taking part in the trial, which is being conducted at 16 sites across the nation. Type 2 diabetes was confirmed by medical record, current diabetes treatment, confirmation from a primary health-care provider, fasting glucose of 126 mg/dL or more, symptoms of hyperglycemia with nonfasting plasma glucose of 200 mg/dL or more, or 2-hour plasma glucose of 200 mg/dL or more after ingestion of a 75-g oral glucose solution on at least two tests. The inclusion criteria for age changed from 45 to 75 years to 55 to 75 years during the second year of participant recruitment to increase the number of reported cardiovascular events.
      The trial is evaluating the effects of a lifestyle intervention (calorie-control and increased physical activity to achieve and maintain weight loss) compared with a diabetes support and education intervention on long-term cardiovascular and other important health outcomes. Participants will be followed up for approximately 11.5 years. Prior to randomization, all trial participants completed a 2-week run-in period that included self-monitoring of food and physical activity and attended an initial session of diabetes education that focused on aspects of diabetes care. The education session emphasized the importance of eating healthful foods and being physically active for both weight loss and improved glycemic control. All participants gave written informed consent, and clinical centers obtained local Institutional Review Board approval for use of human subjects.

       Nutrition Assessment

      The Look AHEAD semiquantitative, previously validated food frequency questionnaire (FFQ) was selected to measure food and nutrient intake in 50% of the subjects seen at each clinic site (
      • Wadden T.A.
      • West D.S.
      • Delahanty L.
      • Jakicic J.
      • Rejeski J.
      • Williamson D.
      • Berkowitz R.I.
      • Kelley D.E.
      • Tomchee C.
      • Hill J.O.
      • Kumanyika S.
      Look AHEAD Research Group
      The Look AHEAD study: A description of the lifestyle intervention and the evidence supporting it.
      ). The questionnaire is a modified version of the Diabetes Prevention Program Food Frequency Questionnaire and was designed to collect information about usual intake of food items during the preceding 6 months (
      • Mayer-Davis E.J.
      • Vitolins M.Z.
      • Carmichael S.L.
      • Hemphill S.
      • Tsaroucha G.
      • Rushing J.
      • Levin S.
      Validity and reproducibility of a food frequency interview in a multi-cultural epidemiologic study.
      ,
      • Block G.
      • Hartman A.M.
      Data collection and data management.
      ). The Diabetes Prevention Program food list, developed for regional and ethnic sensitivity, formed the basis of the Look AHEAD FFQ food list. The body of the questionnaire contains 134 line items, 20 items that are used to adjust the 134 items (type of oil used when cooking, fat added to vegetables, potatoes at the table, etc), and three quality-control questions. Meal replacement beverages and snack bars were added as line items to the Look AHEAD FFQ because the intervention component of the trial was structured to utilize these products. Information about nutritional supplements was not collected; therefore, the analyses were conducted only on foods and beverages consumed.
      The Look AHEAD FFQ is primarily self-administered with limited staff assistance. Staff instructed participants about how to complete the Look AHEAD FFQ and upon its return; staff reviewed it with the participant. For each line item, participants reported frequency of consumption and portion size. The nine frequency categories for food items included “never or less than once per month” to “2 or more times per day,” and for beverages, from “never or less than once per month” to “6 or more times per day.” Portion sizes were listed as small, medium, or large.

       Quality Control

      The implementation and management of the nutrition assessment for the trial is centralized at the Look AHEAD Diet Assessment Center. One primary diet interviewer for each site was certified by Diet Assessment Center staff to administer and edit the Look AHEAD FFQ. Certification of the primary diet interviewer is conducted annually. The Look AHEAD FFQs were edited initially at the clinical sites, and additional editing and quality-control checks, including internal consistency and range, were conducted at the Diet Assessment Center using the edit checks internal to the National Cancer Institute Health Habits and History Questionnaire (HHHQ)/DietSys program (version 3.0, 1993, National Cancer Institute, Rockville, MD) followed by a Diet Assessment Center staff review of forms in which a food or nutrient value was extreme.

       Food Groupings and Nutrients

      Estimates of food group and nutrient intake were conducted using the HHHQ/DietSys software and Look AHEAD–specific programming written to incorporate the Look AHEAD modifications to the questionnaire. The nutrient database was modified from the Diabetes Prevention Program database to incorporate foods added for the Look AHEAD FFQ. These nutrient values were obtained primarily from the Nutrition Data System for Research (version 4.01_30, 1999, Nutrition Coordinating Center, Minneapolis, MN). The portion-size database, including gram weights for small, medium, and large portions according to age and sex, was also modified to accommodate the new foods.
      The current values of the Dietary Reference Intakes established between 1997 and 2004 and written to serve as standards for nutrient intakes for individuals in the United States and Canada were used to evaluate macronutrient and micronutrient intake (
      Institute of Medicine Dietary Reference Intakes for Calcium, Phosphorus, Magnesium, Vitamin D, and Fluoride.
      ,
      Institute of Medicine Dietary Reference Intakes for Energy, Carbohydrate, Fiber, Fat, Fatty Acids, Cholesterol, Protein, and Amino Acids (Macronutrients).
      ,
      Institute of Medicine Dietary Reference Intakes for Water, Potassium, Sodium, Chloride, and Sulfate.
      ). For this analysis, to coincide with the time the baseline trial data were collected, the recommendations contained in the USDA Food Guide Pyramid were used to make decisions regarding the inclusion of foods within the main groupings (

      The Food Guide Pyramid. Washington, DC: US Department of Agriculture Center for Nutrition Policy and Promotion 2000. Home and Garden Bulletin No. 252.

      ).

       Anthropometric Measures

      All anthropometric measurements were made with the participants wearing lightweight clothing (eg, short-sleeve shirt or blouse or surgical gown, shorts, socks) and without shoes. All measurements were taken twice and the mean of the two measures was used in the analysis. Generic wall-mounted stadiometers graduated in centimeters with a horizontal measuring block (or fixed angle) were used to measure height. Participant's height was recorded to the nearest 0.5 cm. Weight was measured using a digital scale (BWB 800, Tanita Corp, Arlington Heights, IL). Weight was recorded in kilograms to the nearest 0.1 kg. BMI was calculated as kg/m2.

       Statistical Analyses

      Descriptive statistics, means, standard deviations, medians, interquartile ranges, frequencies, and percents were used to summarize the participants' socio-demographic and health characteristics as well as the intake of nutrients and food groups. Kruskal-Wallis tests, a nonparametric analysis of variance using ranks in place of data that are not normally distributed, were used to assess the univariate effects of these characteristics on food group consumption, analysis of variance was used to assess the univariate effects of these characteristics on nutrient consumption, and χ2 tests were used to assess the effects of these characteristics on meeting recommended consumption of nutrients and food groups. Multiple linear regression models were used to assess which factors were predictive of meeting intake of each of the major food groups. Logistic regression was used to determine which factors were predictive of recommended intake, defined for each food group as consuming as much or more of the specified food group as recommended in the USDA Food Guide Pyramid guidelines. A P value of <0.05 was used to denote statistical significance. The Statistical Analysis System (version 9.2, 1998, SAS Institute, Cary, NC) was used to conduct the analyses.

      Results

      Of the 2,793 baseline Look AHEAD FFQs received, three questionnaires were deleted immediately because most of the line items had not been completed; the remaining 2,790 questionnaires were scanned. Thirty-three forms were excluded after being scanned for the following reasons: (a) less than 4 foods per day reported, (n=23); (b) more than 30 foods per day reported (n=8); and (c) more than 2 errors flagged (n=2). Therefore, only 1.2% of the forms were not included in the final dataset. The nutrition analysis reported in this paper was conducted using data obtained from 2,757 Look AHEAD FFQs.
      Table 1 illustrates demographic and health characteristics of participants who completed the Look AHEAD FFQ. Participants who completed the Look AHEAD FFQ were younger than those who did not (57.2±7.2 vs 60.5±5.9, P<0.0001) because of the change in the age inclusion criteria during year 2 of the recruitment period. There were no other significant differences between the two groups with respect to sex, race, and educational attainment.
      Table 1Demographic and health characteristics of Look AHEAD participants who completed the food frequency questionnaire (FFQ)
      Completed FFQ (n=2,757)
      n%
      Sex
      Male1,12241
      Female1,63559
      Age (y)
      45-551,19143
      56-651,18343
      66-7538314
      Race
      White1,75864
      African American41415
      Hispanic35013
      Other2348
      Education
      <High school degree53420
      High school degree to some college1,03038
      Bachelor's degree or more1,13342
      Annual income level ($)
      <40,00078031
      40,000-69,99973629
      ≥70,00099640
      Body mass index
      25 to <3039514
      30 to <3596035
      35 to <4074127
      ≥4066124
      Diabetes treatment
      No medications32312
      Oral diabetes medications1,85868
      Insulin only1174
      Insulin and oral diabetes medications41815
      Diabetes duration (y)
      0 to 246517
      >2 to 579329
      >5 to 1079029
      >1068125
      NOTE: Information from this table is available online at www.adajournal.org as part of a PowerPoint presentation.
      In Table 2, the percentage of study participants who met the recommendations for nutrient intake is illustrated. With respect to energy consumed, unadjusted total energy intake was found to be more among males (2,000 kcal/day) compared with females (1,744 kcal/day). Higher energy intake was also found in the younger age groups, Hispanic participants, more educated participants, those with higher incomes, and those with higher BMI.
      Table 2Recommended dietary nutrient intake by sex and age and overall percentage of Look AHEAD participants meeting recommendations
      NutrientRecommended dietary intakeActual dietary intake (median, IQR
      IQR=interquartile range, which shows the 25th to 75th percentiles of intake.
      )
      % Meeting recommendation
      % Total fat≤3040 (35-45)7
      % Saturated fat≤1013 (11-15)15
      Cholesterol (mg/d)≤300297 (202-422)51
       Sodium (mg/d)8
        Age 31-50 y≤1,5002,846 (2,006-3,910)
        Age 50-70 y≤1,3002,551 (1,895-3,426)
        Age >70 y≤1,2002,026 (1,400-2,744)
       Calcium (mg/d)
        Age 31-50 y≥1,000744 (522-1,087)
        Age 50-70 y≥1,200689 (484-1,014)20
        Age >70 y≥1,200604 (409-839)
       Fiber (g/d)
        Age 31-50 y, male≥3820 (16-25)
        Age 50-70 y, male≥3019 (14-25)20
        Age >70 y, male≥3016 (12-21)
        Age 31-50 y, female≥2518 (13-22)
        Age 50-70 y, female≥2117 (12-22)
        Age >70 y, female≥2115 (12-19)
      NOTE: Information from this table is available online at www.adajournal.org as part of a PowerPoint presentation.
      a IQR=interquartile range, which shows the 25th to 75th percentiles of intake.
      Table 3 enumerates the recommended servings per day for each food group, as compared with the overall actual consumption by the sample. Unadjusted comparisons of each of the five food groups (grains, fruits, vegetables, dairy, and meat), and the discretionary calories group (fats/sweets), with the characteristics of the sample were also done. Females consumed more fruits and vegetables, and males consumed more meats. Younger individuals consumed more grains, meat, and fats/sweets. Hispanic participants consumed the greatest amount of grains, fruits and vegetables, and meat, whereas non-Hispanic whites consumed the largest amount of dairy and fats/sweets. Higher levels of education and income were both associated with consumption of more dairy, meat, and fats/sweets. Higher BMI was associated with higher consumption of all food groups except fruits and vegetables, for which there are no differences in consumption between BMI groups. When sex, age, race, education, income, and BMI were simultaneously accounted for in a multiple linear regression model, results were similar, although income was no longer associated with any food group and education level was no longer associated with intake of dairy products.
      Table 3Look AHEAD participants Food Guide Pyramid food group consumption: Recommended daily servings vs actual servings
      Food groupMinimum recommended servings per dayActual servings consumed per day (median, IQR
      IQR=interquartile range, which shows the 25th to 75th percentiles of intake.
      )
      % Meeting recommendation
      Percent consuming at least the recommended intake for grains, fruit, vegetables, dairy, and meat; % consuming no more than 1 serving for fats/oils/sweets.
      Grains63 (2-4)7
      Fruits22 (1-3)36
      Vegetables33 (2-4)38
      Dairy22 (1-3)40
      Meat22 (2-3)82
      Fats, oils, sweetsLimit2 (1-3)28
      NOTE: Information from this table is available online at www.adajournal.org as part of a PowerPoint presentation.
      a IQR=interquartile range, which shows the 25th to 75th percentiles of intake.
      b Percent consuming at least the recommended intake for grains, fruit, vegetables, dairy, and meat; % consuming no more than 1 serving for fats/oils/sweets.
      Table 4 shows the number and percentage of the trial population meeting food group intake recommendations. In multiple logistic regression models (data not shown), younger age, nonwhite race, and higher BMI were significantly (P≤0.05) associated with meeting the recommended grain servings. Nonwhite race, lower income, and lower BMI were significantly (P≤0.05) associated with meeting the recommendation of 1 or fewer serving of fats/sweets per day.
      Table 4Number and percentage of Look AHEAD participants meeting daily recommended servings of Food Guide Pyramid food group intake
      nGrainFruitVegetablesDairyMeatFats, Oils, Sweets
      n%n%n%n%n%n%
      Sex
      P<0.05 based on χ2 tests.
      P<0.05 based on χ2 tests.
      P<0.05 based on χ2 tests.
      Male1,1227374033643138465417536729226
      Female1,63512686694173545645401,0056246629
      Age (y)
      P<0.05 based on χ2 tests.
      P<0.05 based on χ2 tests.
      P<0.05 based on χ2 tests.
      45-551,191119104223551743494428106830826
      56-651,1836764754050343471407456332728
      66-753831331754614638145382035312332
      Race
      P<0.05 based on χ2 tests.
      P<0.05 based on χ2 tests.
      P<0.05 based on χ2 tests.
      P<0.05 based on χ2 tests.
      P<0.05 based on χ2 tests.
      P<0.05 based on χ2 tests.
      White1,7549966153579645806461,1066341724
      African American4142151924612831110272606313432
      Hispanic34650141755115144114332447112235
      Other2332812843689387633141618336
      Education
      P<0.05 based on χ2 tests.
      P<0.05 based on χ2 tests.
      P<0.05 based on χ2 tests.
      <High school degree5344892484621140192363165916932
      High school and some college1,02969737036417403903865227727
      Bachelor's degree or more1,1327974323850344502447576729526
      Annual income ($)
      P<0.05 based on χ2 tests.
      P<0.05 based on χ2 tests.
      P<0.05 based on χ2 tests.
      P<0.05 based on χ2 tests.
      P<0.05 based on χ2 tests.
      <40,0007807293554631440288374806225433
      40,000-69,9997365372763831643298414576219727
      ≥70,0009956163533644044435446656722723
      Body mass index
      P<0.05 based on χ2 tests.
      P<0.05 based on χ2 tests.
      P<0.05 based on χ2 tests.
      P<0.05 based on χ2 tests.
      25 to <303951851684315239153392335914136
      30 to <359605663773939942367385635929431
      35 to <407415372823831943293404986717223
      ≥4066172112453729645297454647015123
      Diabetes treatment
      P<0.05 based on χ2 tests.
      P<0.05 based on χ2 tests.
      P<0.05 based on χ2 tests.
      No medications323155159491203713341181569329
      Oral diabetes medications1,85813477524171539754411,1936451328
      Insulin only1174451445345373272623328
      Insulin and oral diabetes medications41840101904617041169402886910926
      Diabetes duration (y)
      0-24603682074517438194422956414030
      2-57855983224130939298384826121628
      5-107845673264227936327424986420927
      ≥106774362884328242269404486618327
      NOTE: Information from this table is available online at www.adajournal.org as part of a PowerPoint presentation.
      low asterisk P<0.05 based on χ2 tests.

      Discussion

      In this evaluation of dietary intake in overweight individuals diagnosed with type 2 diabetes, only a limited number of participants met nutrient intake recommendations for total fat, saturated fat, sodium, and fiber. Also, fewer than half consumed the minimum recommended daily servings of fruits, vegetables, dairy, and grains based on the year 2000 version of the Food Guide Pyramid recommendations.
      Overall, the participants consumed a diet that provided approximately 44% of energy from carbohydrates, 40% from fat, and 17% from protein. Notable is the lower contribution of carbohydrates and higher contribution of fat to their diets. Similar results have been reported showing that individuals with type 2 diabetes are not consuming healthful diets (
      • Cruz A.F.
      • Calle-Pascual A.L.
      Diabetes and Nutrition Study Group, Spanish Diabetes Association.Diabetes Nutrition and Complications Trial: Trends in nutritional pattern between 1993 and 2000 and targets of diabetes treatment in a sample of Spanish people with diabetes.
      ,
      • Gauthier-Chelle K.
      • Mennen L.
      • Arnault N.
      • Rigalleau V.
      • Hercberg S.
      • Gin H.
      Comparison of the diet of self-declared diabetics with non-diabetic patients in the SU.VI.MAX study: Did the diabetics modify their nutritional behavior?.
      ,
      • Helmer C.
      • Bricout H.
      • Gin H.
      • Barberger-Gateau P.
      Macronutrient intake and discrepancy with nutritional recommendations in a group of elderly diabetic subjects.
      ,
      • Toeller M.
      • Klischan A.
      • Heitkamp G.
      • Schumacher W.
      • Milne R.
      • Buyken A.
      • Karamanos B.
      • Gries F.A.
      Nutritional intake of 2868 IDDM patients from 30 centres in Europe EURODIAB IDDM Complications Study Group.
      ,
      • Parker D.R.
      • McPhillips J.B.
      • Lapane K.L.
      • Lasater T.M.
      • Carleton R.A.
      Nutrition and health practices of diabetic and nondiabetic men and women from two southeastern New England communities.
      ,
      • Shimakawa T.
      • Herrera-Acena M.G.
      • Colditz G.A.
      • Manson J.E.
      • Stampfer M.J.
      • Willett W.C.
      • Stamper M.J.
      Comparison of diets of diabetic and nondiabetic women.
      ,
      • Nelson K.M.
      • Reiber G.
      • Boyko E.J.
      Diet and exercise among adults with type 2 diabetes: Findings from the Third National Health and Nutrition Examination Survey (NHANES III).
      ). Nelson and colleagues (
      • Nelson K.M.
      • Reiber G.
      • Boyko E.J.
      Diet and exercise among adults with type 2 diabetes: Findings from the Third National Health and Nutrition Examination Survey (NHANES III).
      ) reported nutrient intake data of 1,480 adults age 17 years and older who self-reported type 2 diabetes in the Third National Health and Nutrition Examination Survey. Mean age of the population was 61 years old, most were white, and 20% of the sample reported income levels less than the federal poverty level and 45% had less than a high school education. Eighty-two percent of the participants had a BMI of 25 or more, 36% were overweight, and 46% were obese. Forty-two percent of the respondents reported consuming 30% to 40% of daily energy from fat, and 26% consumed more than 40% of energy from fat. Approximately two thirds consumed more than 10% of total energy from saturated fat. In addition, participants older than age 65 years consumed a lower percentage of total energy from fat than those participants who were younger than age 65 years, a finding similar to those of the current trial in which older age was associated with meeting the recommendations for percentage of energy from fat.
      Regarding food group consumption, the Look AHEAD participants consumed fewer than the recommended intake of the fruits and vegetables. Intake of diets rich in fruits and vegetables have been shown to prevent heart disease (
      • Joshipura K.J.
      • Hu F.B.
      • Manson J.E.
      • Stampfer M.J.
      • Rimm E.B.
      • Speizer F.E.
      • Colditz G.
      • Ascherio A.
      • Rosner B.
      • Spiegelman D.
      • Willett W.C.
      The effect of fruit and vegetable intake on risk for coronary heart disease.
      ,
      • Hung H.C.
      • Joshipura K.J.
      • Jiang R.
      • Hu F.B.
      • Hunter D.
      • Smith-Warner S.A.
      • Colditz G.A.
      • Rosner B.
      • Spiegelman D.
      • Willett W.C.
      Fruit and vegetable intake and risk of major chronic disease.
      ), the leading cause of death in individuals with type 2 diabetes (
      • Winer N.
      • Sowers J.R.
      Epidemiology of diabetes.
      ). Because fruits and vegetables provide fiber, are nutrient-dense, and are filled with antioxidants and other planted-based phytochemicals, counseling to increase consumption in this population has the potential to improve biochemical markers of disease risk, such as lipids and antioxidant levels (
      • Lampe J.W.
      Health effects of vegetables and fruit: Assessing mechanisms of action in human experimental studies.
      ).
      Raynor and colleagues (
      • Raynor H.A.
      • Jeffery R.W.
      • Ruggiero A.M.
      • Clark J.M.
      • Delahanty L.M.
      the Look AHEAD Research Group
      Weight loss strategies associated with body mass index in overweight adults with type 2 diabetes at entry into the Look AHEAD Trial.
      ) reported that the three most commonly reported weight-control practices in this Look AHEAD cohort at baseline were increasing consumption of fruits and vegetables, reducing intake of sweets, and eating fewer high-carbohydrate foods, each of which could impact on the overall amount and type of carbohydrate consumed. These three weight-control practices were reported by more than 50% of the participants for an average of more than 20 weeks during the previous year and yet were not the most important correlates of lower BMI (
      • Raynor H.A.
      • Jeffery R.W.
      • Ruggiero A.M.
      • Clark J.M.
      • Delahanty L.M.
      the Look AHEAD Research Group
      Weight loss strategies associated with body mass index in overweight adults with type 2 diabetes at entry into the Look AHEAD Trial.
      ). It may be that people with type 2 diabetes are more commonly focusing on eating fewer carbohydrates, regardless of type (simple vs complex) due to the belief that restricting carbohydrates will help control blood glucose levels. In doing so, however, they need to also understand the potential adverse effects that higher cholesterol, saturated fat, and total fat intakes can have in terms of cardiovascular risk factors.
      All participants were overweight or obese, and, based on the evaluation of their nutrient intake, were overconsuming foods high in fat, saturated fat, and salt. Although the overall energy intake of the participants may seem low, it is not uncommon for energy intake levels to be surprisingly low for overweight, sedentary individuals. Over many years, small increases in energy intake on the positive side of the energy-balance equation can lead to substantial weight gain.
      Interestingly, more participants in the highest BMI range (≥40), compared with participants in the other BMI ranges, met the recommended food group intake for grains, dairy, and meat but were also more likely to consume more than one serving per day of fats, oils, and sweets. All of these participants would benefit from counseling to encourage consumption of high-fiber, low-fat grains and low-fat dairy foods, and guidance to select leaner cuts of meat. In addition, counseling to reduce consumption of discretionary calories would improve the likelihood of meeting fat and cholesterol intake guidelines and improve the overall quality of foods consumed.
      The only factor that did not affect food group intake was duration of diabetes. It would seem likely that participants who had managed diabetes over a greater length of time would be more likely to understand the importance of consuming a healthful diet, but this was not supported by the data. This also speaks to the necessity of providing ongoing nutrition education for individuals with diabetes, regardless of the duration of diabetes.
      Several limitations should be mentioned. Most participants reported having more than a high school education; therefore, these trial results may not be generalizable to less-educated populations. However, similar results were reported by Nelson and colleagues, who evaluated the Third National Health and Nutrition Examination Survey data (
      • Nelson K.M.
      • Reiber G.
      • Boyko E.J.
      Diet and exercise among adults with type 2 diabetes: Findings from the Third National Health and Nutrition Examination Survey (NHANES III).
      ). FFQs are known to underestimate energy intake overall; however, this questionnaire was used because the study investigators were focused less on the absolute value of calories, and more on the capacity of the Look AHEAD FFQ to do a reasonable job in ranking participants. Underreporting has also been found to be more common in overweight individuals and those who have diabetes, so underreporting of intake may be higher in this trial population compared with the general population (
      • Seale J.L.
      • Klein G.
      • Friedmann J.
      • Jensen G.L.
      • Mitchell D.C.
      • Smiciklas-Wright H.
      Energy expenditure measured by doubly labeled water, activity recall, and diet records in the rural elderly.
      ,
      • Goris A.H.
      • Westerterp-Plantenga M.S.
      • Westerterp K.R.
      Undereating and underrecording of habitual food intake in obese men: Selective underreporting of fat intake.
      ,
      • Briefel R.R.
      • Sempos C.T.
      • McDowell M.A.
      • Chien S.
      • Alaimo K.
      Dietary methods research in the third National Health and Nutrition Examination Survey: Underreporting of energy intake.
      ,
      • Salle′ A.
      • Ryan M.
      • Ritz P.
      Underreporting of food intake in obese diabetic and nondiabetic patients.
      ). However, although all foods seem to be underreported in general, foods that may be considered less socially acceptable, such as discretionary-calorie foods, seem to have the highest levels of underreporting (
      • Krebs-Smith S.M.
      • Graubard B.I.
      • Kahle L.L.
      • Subar A.F.
      • Cleveland L.E.
      • Ballard-Barbash R.
      Low energy reporters vs others: A comparison of reported food intakes.
      ). This could mean that consumption of discretionary-calorie servings consumed by the participants may be even more than reported. Nevertheless, this evaluation of food and nutrient intake demonstrates that overall these adults with type 2 diabetes are not meeting recommended food and nutrient intake guidelines and are consuming diets that may exacerbate cardiovascular and other chronic disease risks.

      Conclusion

      Optimizing glycemic, lipid, blood pressure, and weight control in individuals with type 2 diabetes is essential to reduce risk for long-term complications and chronic disease, including cardiovascular disease. Consuming a low–saturated fat, high-fiber diet that includes high-quality, nutrient-dense foods can assist in achieving and maintaining this type of metabolic control. Evidence-based nutrition principles and recommendations as well as national guidelines have been established to help inform and educate the public about healthful eating practices. Unfortunately, this evaluation found that the Look AHEAD participants consumed too few foods that would help them meet these guidelines. The findings illustrate that these participants need encouragement and support in their efforts to make healthful food choices. Approaches to guide their selection of foods, such as substituting highly processed foods for less-processed foods and reducing saturated fat intake may greatly improve their overall dietary quality. In addition, research efforts to better understand the types of barriers these overweight individuals with type 2 diabetes must face in their attempts to consume a healthful diet seem warranted.

       The Look AHEAD Research Group at Baseline

       Clinical Sites

      The Johns Hopkins Medical Institutions: Frederick Brancati, MD, MHS; Debi Celnik, MS, RD, LD; Jeff Honas, MS; Jeanne Clark, MD, MPH; Jeanne Charleston, RN; Lawrence Cheskin, MD; Kerry Stewart, EdD; Richard Rubin, PhD; Kathy Horak, RD
      Pennington Biomedical Research Center: George A. Bray, MD; Kristi Rau; Allison Strate, RN; Frank L. Greenway, MD; Donna H. Ryan, MD; Donald Williamson, PhD; Elizabeth Tucker; Brandi Armand, LPN; Mandy Shipp, RD; Kim Landry; Jennifer Perault
      The University of Alabama at Birmingham: Cora E. Lewis, MD, MSPH; Sheikilya Thomas, MPH; Vicki DiLillo, PhD; Monika Safford, MD; Stephen Glasser, MD; Clara Smith, MPH; Cathy Roche, RN; Charlotte Bragg, MS, RD, LD; Nita Webb, MA; Staci Gilbert, MPH; Amy Dobelstein; L. Christie Oden; Trena Johnsey
      Harvard Center, Massachusetts General Hospital: David M. Nathan, MD; Heather Turgeon, RN; Kristina P. Schumann; Enrico Cagliero, MD; Kathryn Hayward, MD; Linda Delahanty, MS, RD; Barbara Steiner, EdM; Valerie Goldman, MS, RD; Ellen Anderson, MS, RD; Laurie Bissett, MS, RD; Alan McNamara; Richard Ginsburg, PhD; Virginia Harlan, MSW; Theresa Michel, MS
      Harvard Center, Joslin Diabetes Center: Edward S. Horton, MD; Sharon D. Jackson, MS, RD, CDE; Osama Hamdy, MD, PhD; A. Enrique Caballero, MD; Sarah Ledbury, MEd, RD; Maureen Malloy; Ann Goebel-Fabbri, PhD; Kerry Ovalle, MS, RCEP, CDE; Sarah Bain; Elizabeth Bovaird, RN; Lori Lambert, MS, RD
      Harvard Center, Beth Israel Deaconess Medical Center: George Blackburn, MD, PhD; Christos Mantzoros, MD, DSc; Ann McNamara, RN; Heather McCormick, RD
      University of Colorado Health Sciences Center: James O. Hill, PhD; Marsha Miller, MS, RD; Brent VanDorsten, PhD; Judith Regensteiner, PhD; Robert Schwartz, MD; Richard Hamman, MD, DrPH; Michael McDermott, MD; JoAnn Phillipp, MS; Patrick Reddin; Kristin Wallace, MPH; Paulette Cohrs, RN; April Hamilton; Salma Benchekroun; Susan Green; Loretta Rome, TRS; Lindsey Munkwitz
      Baylor College of Medicine: John P. Foreyt, PhD; Rebecca S. Reeves, DrPH, RD; Henry Pownall, PhD; Peter Jones, MD; Ashok Balasubramanyam, MD; Molly Gee, MEd, RD
      University of California at Los Angeles School of Medicine: Mohammed F. Saad, MD; Ken C. Chiu, MD; Siran Ghazarian, MD; Kati Szamos, RD; Magpuri Perpetua, RD; Michelle Chan; Medhat Botrous
      The University of Tennessee Health Science Center, University of Tennessee East: Karen C. Johnson, MD, MPH; Leeann Carmichael, RN; Lynne Lichtermann, RN
      The University of Tennessee Health Science Center, University of Tennessee Downtown: Abbas E. Kitabchi, PhD, MD; Jackie Day, RN; Helen Lambeth, RN; Debra Force, MS, RD, LDN; Debra Clark, LPN; Andrea Crisler, MT, Donna Green, RN; Gracie Cunningham; Maria Sun, MS, RD, LDN; Robert Kores, PhD; Renate Rosenthal, PhD; Judith Soberman, MD
      University of Minnesota: Robert W. Jeffery, PhD; Carolyn Thorson, CCRP; John P. Bantle, MD; J. Bruce Redmon, MD; Richard S. Crow, MD; Jeanne Carls, MEd; Carolyne Campbell; La Donna James; T. Ockenden, RN; Kerrin Brelje, MPH, RD; M. Patricia Snyder, MA, RD; Amy Keranen, MS; Cara Walcheck, RD; Emily Finch, MA; Birgitta I. Rice, MS, RPh, CHES; Vicki A. Maddy, RD; Tricia Skarphol
      St Luke's Roosevelt Hospital Center: Xavier Pi-Sunyer, MD; Jennifer Patricio, MS; Jennifer Mayer, MS; Stanley Heshka, PhD; Carmen Pal, MD; Mary Anne Holowaty, MS, CN; Diane Hirsch, RNC, MS, CDE
      University of Pennsylvania: Thomas A. Wadden, PhD; Barbara J. Maschak-Carey, MSN, CDE; Gary D. Foster, PhD; Robert I. Berkowitz, MD; Stanley Schwartz, MD; Shiriki K. Kumanyika, PhD, RD, MPH; Monica Mullen, MS, RD; Louise Hesson, MSN; Patricia Lipschutz, MSN; Anthony Fabricatore, PhD; Canice Crerand, PhD; Robert Kuehnel, PhD; Ray Carvajal, MS; Renee Davenport; Helen Chomentowski
      University of Pittsburgh: David E. Kelley, MD; Jacqueline Wesche-Thobaben, RN, CDE; Lewis Kuller, MD, DrPH; Andrea Kriska, PhD; Daniel Edmundowicz, MD; Mary L. Klem, PhD, MLIS; Janet Bonk, RN, MPH; Jennifer Rush, MPH; Rebecca Danchenko; Barb Elnyczky, MA; Karen Vujevich, RN-BC, MSN, CRNP; Janet Krulia, RN, CDE; Donna Wolf, MS; Juliet Mancino, MS, RD, CDE, LDN; Pat Harper, MS, RD, LDN; Anne Mathews, MS, RD, LDN
      Brown University: Rena R. Wing, PhD; Vincent Pera, MD; John Jakicic, PhD; Deborah Tate, PhD; Amy Gorin, PhD; Renee Bright, MS; Pamela Coward, MS, RD; Natalie Robinson, MS, RD; Tammy Monk, MS; Kara Gallagher, PhD; Anna Bertorelli, MBA, RD; Maureen Daly, RN; Tatum Charron; Rob Nicholson, PhD; Erin Patterson; Julie Currin, MD; Linda Foss, MPH; Deborah Robles; Barbara Bancroft, RN, MS; Jennifer Gauvin; Deborah Maier, MS; Caitlin Egan, MS; Suzanne Phelan, PhD; Hollie Raynor, PhD, RD; Don Kieffer, PhD; Douglas Raynor, PhD; Lauren Lessard; Kimberley Chula-Maguire, MS; Erica Ferguson, RD; Richard Carey; Jane Tavares; Heather Chenot, MS; JP Massaro
      The University of Texas Health Science Center at San Antonio: Steve Haffner, MD; Maria Montez, RN, MSHP, CDE; Connie Mobley, PhD, RD; Carlos Lorenzo, MD
      University of Washington/VA Puget Sound Health Care System: Steven E. Kahn, MB, ChB; Brenda Montgomery, MS, RN, CDE; Robert H. Knopp, MD; Edward W. Lipkin, MD, PhD; Matthew L. Maciejewski, PhD; Dace L. Trence, MD; Roque M. Murillo; S. Terry Barrett
      Southwestern American Indian Center, Phoenix, AZ, and Shiprock, NM: William C. Knowler, MD, DrPH; Paula Bolin, RN, MC; Tina Killean; Cathy Manus, LPN; Carol Percy, RN; Rita Donaldson; Bernadette Todacheenie, EdD; Justin Glass, MD; Sarah Michaels, MD; Jonathan Krakoff, MD; Jeffrey Curtis, MD, MPH; Peter H. Bennett, MB, FRCP; Tina Morgan; Ruby Johnson; Janelia Smiley; Sandra Sangster; Shandiin Begay, MPH; Minnie Roanhorse; Didas Fallis, RN; Nancy Scurlock, MSN, ANP; Leigh Shovestull, RD

       Coordinating Center

      Wake Forest University School of Medicine: Mark A. Espeland, PhD; Judy Bahnson; Lynne Wagenknecht, DrPH; David Reboussin, PhD; W. Jack Rejeski, PhD; Wei Lang, PhD; Alain Bertoni, MD, MPH; Mara Vitolins, DrPH; Gary Miller, PhD; Paul Ribisl, PhD; Kathy Dotson; Amelia Hodges; Patricia Hogan, MS; Kathy Lane; Carrie Combs; Christian Speas; Delia S. West, PhD; William Herman, MD, MPH

       Central Resources Centers

      DXA Reading Center, University of California at San Francisco: Michael Nevitt, PhD; Ann Schwartz, PhD; John Shepherd, PhD; Jason Maeda, MPH; Cynthia Hayashi; Michaela Rahorst; Lisa Palermo, MS, MA
      Central Laboratory, Northwest Lipid Research Laboratories: Santica M. Marcovina, PhD, ScD; Greg Strylewicz, MS
      ECG Reading Center, EPICARE, Wake Forest University School of Medicine: Ronald J. Prineas, MD, PhD; Zhu-Ming Zhang, MD; Charles Campbell, AAS; Sharon Hall
      Diet Assessment Center, University of South Carolina, Arnold School of Public Health, Center for Research in Nutrition and Health Disparities: Elizabeth J. Mayer-Davis, PhD; Cecilia Farach, DrPH

       Federal Sponsors

      National Institute of Diabetes and Digestive and Kidney Diseases: Barbara Harrison, MS; Susan Z. Yanovski, MD; Van S. Hubbard, MD, PhD
      National Heart, Lung, and Blood Institute: Lawton S. Cooper, MD, MPH; Eva Obarzanek, PhD, MPH, RD; Denise Simons-Morton, MD, PhD
      Centers for Disease Control and Prevention: David F. Williamson, PhD; Edward W. Gregg, PhD
      STATEMENT OF POTENTIAL CONFLICT OF INTEREST: No potential conflict of interest was reported by the authors.
      FUNDING/SUPPORT: This study is supported by the Department of Health and Human Services through the following cooperative agreements from the National Institutes of Health: DK57136, DK57149, DK56990, DK57177, DK57171, DK57151, DK57182, DK57131, DK57002, DK57078, DK57154, DK57178, DK57219, DK57008, DK57135, and DK56992. The following federal agencies have contributed support: National Institute of Diabetes and Digestive and Kidney Diseases; National Heart, Lung, and Blood Institute; National Institute of Nursing Research; National Center on Minority Health and Health Disparities; Office of Research on Women's Health; and the Centers for Disease Control and Prevention.
      This research was supported in part by the Intramural Research Program of the National Institute of Diabetes and Digestive and Kidney Diseases.
      Additional support was received from The Johns Hopkins Medical Institutions Bayview General Clinical Research Center (M01-RR-02719); the Massachusetts General Hospital Mallinckrodt General Clinical Research Center (M01-RR-01066); the University of Colorado Health Sciences Center General Clinical Research Center (M01 RR00051) and Clinical Nutrition Research Unit (P30 DK48520); the University of Tennessee at Memphis General Clinical Research Center (M01RR00211-40); the University of Pittsburgh General Clinical Research Center (M01 RR000056 44) and NIH grant (DK 046204); and the University of Washington/VA Puget Sound Health Care System Medical Research Service, Department of Veterans Affairs.
      The following organizations have committed to make major contributions to Look AHEAD: Federal Express; Health Management Resources; Johnson & Johnson, LifeScan Inc.; Optifast-Novartis Nutrition; Roche Pharmaceuticals; Ross Product Division of Abbott Laboratories; Slim-Fast Foods Company; and Unilever.

      Online Extra

      References

        • US Department of Health and Human Services, US Department of Agriculture
        Dietary Guidelines for Americans, 2000.
        US Department of Health and Human Services, US Department of Agriculture, Washington, DC2000
      1. Institute of Medicine Dietary Reference Intakes for Calcium, Phosphorus, Magnesium, Vitamin D, and Fluoride.
        National Academies Press, Washington, DC1997
      2. Institute of Medicine Dietary Reference Intakes for Energy, Carbohydrate, Fiber, Fat, Fatty Acids, Cholesterol, Protein, and Amino Acids (Macronutrients).
        National Academies Press, Washington, DC2002
      3. Institute of Medicine Dietary Reference Intakes for Water, Potassium, Sodium, Chloride, and Sulfate.
        in: National Academies Press, Washington, DC2004: 270
        • Franz M.J.
        • Bantle J.
        • Beebe C.A.
        • Brunzell J.D.
        • Chiasson J.L.
        • Garg A.
        • Holzmeister Look A.H.E.A.D.
        • Hoogwerf B.
        • Mayer-Davis E.
        • Mooradian A.
        • Purnell J.Q.
        • Wheeler M.
        American Diabetes Association Position Statement: Evidence-based nutrition principles and recommendations for the treatment and prevention of diabetes and related complications.
        J Am Diet Assoc. 2002; 102: 109-118
        • Franz M.J.
        • Bantle J.P.
        • Beebe C.A.
        • Brunzell J.D.
        • Chiasson J.L.
        • Garg A.
        • Holzmeister Look A.H.E.A.D.
        • Hoogwerf B.
        • Mayer-Davis E.
        • Mooradian A.D.
        • Purnell J.Q.
        • Wheeler M.
        Evidence-based nutrition principles and recommendations for the treatment and prevention of diabetes and related complications (Technical Review).
        Diabetes Care. 2002; 25: 148-198
        • Cruz A.F.
        • Calle-Pascual A.L.
        Diabetes and Nutrition Study Group, Spanish Diabetes Association.Diabetes Nutrition and Complications Trial: Trends in nutritional pattern between 1993 and 2000 and targets of diabetes treatment in a sample of Spanish people with diabetes.
        Diabetes Care. 2004; 27: 984-987
        • Gauthier-Chelle K.
        • Mennen L.
        • Arnault N.
        • Rigalleau V.
        • Hercberg S.
        • Gin H.
        Comparison of the diet of self-declared diabetics with non-diabetic patients in the SU.VI.MAX study: Did the diabetics modify their nutritional behavior?.
        Diabetes Metab. 2004; 30: 535-542
        • Helmer C.
        • Bricout H.
        • Gin H.
        • Barberger-Gateau P.
        Macronutrient intake and discrepancy with nutritional recommendations in a group of elderly diabetic subjects.
        Br J Nutr. 2007; 29: 1-7
        • Toeller M.
        • Klischan A.
        • Heitkamp G.
        • Schumacher W.
        • Milne R.
        • Buyken A.
        • Karamanos B.
        • Gries F.A.
        Nutritional intake of 2868 IDDM patients from 30 centres in Europe.
        Diabetologia. 1996; 39: 929-939
        • Parker D.R.
        • McPhillips J.B.
        • Lapane K.L.
        • Lasater T.M.
        • Carleton R.A.
        Nutrition and health practices of diabetic and nondiabetic men and women from two southeastern New England communities.
        Nutr Health. 1995; 10: 255-268
        • Shimakawa T.
        • Herrera-Acena M.G.
        • Colditz G.A.
        • Manson J.E.
        • Stampfer M.J.
        • Willett W.C.
        • Stamper M.J.
        Comparison of diets of diabetic and nondiabetic women.
        Diabetes Care. 1993; 16: 1356-1362
        • Nelson K.M.
        • Reiber G.
        • Boyko E.J.
        Diet and exercise among adults with type 2 diabetes: Findings from the Third National Health and Nutrition Examination Survey (NHANES III).
        Diabetes Care. 2002; 25: 1722-1728
      4. The Food Guide Pyramid. Washington, DC: US Department of Agriculture Center for Nutrition Policy and Promotion 2000. Home and Garden Bulletin No. 252.

        • Ryan D.H.
        • Espeland M.A.
        • Foster G.D.
        • Haffner S.M.
        • Hubbard V.S.
        • Johnson K.C.
        • Kahn S.E.
        • Knowler W.C.
        • Yanovski S.Z.
        • Look AHEAD Research Group
        Look AHEAD (Action for Health in Diabetes): Design and methods for a clinical trial of weight loss for the prevention of cardiovascular disease in type 2 diabetes.
        Controlled Clinical Trials. 2003; 24: 610-628
        • Wadden T.A.
        • West D.S.
        • Delahanty L.
        • Jakicic J.
        • Rejeski J.
        • Williamson D.
        • Berkowitz R.I.
        • Kelley D.E.
        • Tomchee C.
        • Hill J.O.
        • Kumanyika S.
        • Look AHEAD Research Group
        The Look AHEAD study: A description of the lifestyle intervention and the evidence supporting it.
        Obesity. 2006; 1: 737-752
        • Mayer-Davis E.J.
        • Vitolins M.Z.
        • Carmichael S.L.
        • Hemphill S.
        • Tsaroucha G.
        • Rushing J.
        • Levin S.
        Validity and reproducibility of a food frequency interview in a multi-cultural epidemiologic study.
        Ann Epidemiol. 1999; 9: 314-324
        • Block G.
        • Hartman A.M.
        Data collection and data management.
        in: Block G. Hartman A.M. DIETSYS Version 3.0 User's Guide. National Cancer Institute, Bethesda, MD1994: 15
        • Joshipura K.J.
        • Hu F.B.
        • Manson J.E.
        • Stampfer M.J.
        • Rimm E.B.
        • Speizer F.E.
        • Colditz G.
        • Ascherio A.
        • Rosner B.
        • Spiegelman D.
        • Willett W.C.
        The effect of fruit and vegetable intake on risk for coronary heart disease.
        Ann Intern Med. 2001; 134: 1106-1114
        • Hung H.C.
        • Joshipura K.J.
        • Jiang R.
        • Hu F.B.
        • Hunter D.
        • Smith-Warner S.A.
        • Colditz G.A.
        • Rosner B.
        • Spiegelman D.
        • Willett W.C.
        Fruit and vegetable intake and risk of major chronic disease.
        J Natl Cancer Inst. 2004; 96: 1577-1584
        • Winer N.
        • Sowers J.R.
        Epidemiology of diabetes.
        J Clin Pharmacol. 2004; 44: 397-405
        • Lampe J.W.
        Health effects of vegetables and fruit: Assessing mechanisms of action in human experimental studies.
        Am J Clin Nutr. 1999; 70: S475-S490
        • Raynor H.A.
        • Jeffery R.W.
        • Ruggiero A.M.
        • Clark J.M.
        • Delahanty L.M.
        • the Look AHEAD Research Group
        Weight loss strategies associated with body mass index in overweight adults with type 2 diabetes at entry into the Look AHEAD Trial.
        Diabetes Care. 2008; 31: 1299-1304
        • Seale J.L.
        • Klein G.
        • Friedmann J.
        • Jensen G.L.
        • Mitchell D.C.
        • Smiciklas-Wright H.
        Energy expenditure measured by doubly labeled water, activity recall, and diet records in the rural elderly.
        Nutrition. 2002; 18: 568-573
        • Goris A.H.
        • Westerterp-Plantenga M.S.
        • Westerterp K.R.
        Undereating and underrecording of habitual food intake in obese men: Selective underreporting of fat intake.
        Am J Clin Nutr. 2000; 71: 130-134
        • Briefel R.R.
        • Sempos C.T.
        • McDowell M.A.
        • Chien S.
        • Alaimo K.
        Dietary methods research in the third National Health and Nutrition Examination Survey: Underreporting of energy intake.
        Am J Clin Nutr. 1997; 65: S1203-S1209
        • Salle′ A.
        • Ryan M.
        • Ritz P.
        Underreporting of food intake in obese diabetic and nondiabetic patients.
        Diabetes Care. 2006; 12: 2726-2727
        • Krebs-Smith S.M.
        • Graubard B.I.
        • Kahle L.L.
        • Subar A.F.
        • Cleveland L.E.
        • Ballard-Barbash R.
        Low energy reporters vs others: A comparison of reported food intakes.
        Eur J Clin Nutr. 2000; 54: 281-287

      Biography

      M. Z. Vitolins is an associate professor, Department of Epidemiology and Prevention, Division of Public Health Sciences, Wake Forest University School of Medicine, Winston-Salem, NC.
      A. M. Anderson is a biostatistician, Department of Biostatistical Sciences, Division of Public Health Sciences, Wake Forest University School of Medicine, Winston-Salem, NC.
      L. Delahanty is director of nutrition and behavioral research, Massachusetts General Hospital, Boston.
      H. Raynor is an assistant professor, Department of Nutrition, University of Tennessee, Knoxville.
      G. D. Miller is an assistant professor, Department of Health and Exercise Science, Wake Forest University, Winston-Salem, NC.
      C. Mobley is associate dean of research and a professor, Department of Professional Studies, University of Nevada Las Vegas School of Dental Medicine, Las Vegas.
      R. Reeves is an assistant professor, Baylor College of Medicine, Houston, TX.
      M. Yamamoto is an assistant professor, Department of Epidemiology, Graduate School of Public Health University of Pittsburgh, Pittsburgh, PA.
      C. Champagne is a professor and chief, Nutrition Epidemiology/Dietary Assessment and Counseling, Pennington Biomedical Research Center, Dietary Assessment and Food Analysis Core, Baton Rouge, LA.
      R. R. Wing is a professor, Brown University, Department of Psychiatry and Human Behavior, Providence, RI.
      E. Mayer-Davis is a professor, Department of Nutrition, University of North Carolina at Chapel Hill.