Reduction in Weight and Cardiovascular Disease Risk Factors in Individuals with Type 2 Diabetes One-Year Results of the Look AHEAD Trial

Clinical Care/Education/Nutrition ORIGINAL ARTICLE

Reduction in Weight and Cardiovascular Disease Risk Factors in Individuals With Type 2 Diabetes One-year results of the Look AHEAD trial

THE LOOK AHEAD RESEARCH GROUP* diabetes support and education (DSE). Follow-up of Look AHEAD participants is ongoing and is planned to extend for up OBJECTIVE — The effectiveness of intentional weight loss in reducing cardiovascular disease to 11.5 years. For the study to continue (CVD) events in type 2 diabetes is unknown. This report describes 1-year changes in CVD risk for this period, two feasibility criteria factors in a trial designed to examine the long-term effects of an intensive lifestyle intervention on were set by the Look AHEAD study group the incidence of major CVD events. based on 1-year changes: 1) a difference between ILI and DSE participants of Ͼ5 RESEARCH DESIGN AND METHODS — This study consisted of a multicentered, percentage points in the average percent randomized, controlled trial of 5,145 individuals with type 2 diabetes, aged 45–74 years, with Ͼ 2 Ͼ 2 change in weight from baseline and 2)an BMI 25 kg/m ( 27 kg/m if taking insulin). An intensive lifestyle intervention (ILI) involving average absolute percent weight loss from group and individual meetings to achieve and maintain weight loss through decreased caloric baseline among ILI participants (not us- intake and increased physical activity was compared with a diabetes support and education Ͼ (DSE) condition. ing insulin at baseline) of 5%. This report documents the success of Look RESULTS — Participants assigned to ILI lost an average 8.6% of their initial weight vs. 0.7% AHEAD in meeting these 1-year feasibility in DSE group (P Ͻ 0.001). Mean fitness increased in ILI by 20.9 vs. 5.8% in DSE (P Ͻ 0.001). criteria and describes changes in the two A greater proportion of ILI participants had reductions in diabetes, hypertension, and lipid- groups at the end of the 1st year in fitness, lowering medicines. Mean A1C dropped from 7.3 to 6.6% in ILI (P Ͻ 0.001) vs. from 7.3 to 7.2% cardiovascular disease risk factors, and in DSE. Systolic and diastolic pressure, triglycerides, HDL cholesterol, and urine albumin-to- use of medicines. creatinine ratio improved significantly more in ILI than DSE participants (all P Ͻ 0.01).

CONCLUSIONS — At 1 year, ILI resulted in clinically significant weight loss in people with RESEARCH DESIGN AND type 2 diabetes. This was associated with improved diabetes control and CVD risk factors and METHODS — For inclusion in the reduced medicine use in ILI versus DSE. Continued intervention and follow-up will determine study, participants were 45–74 years of whether these changes are maintained and will reduce CVD risk. age (which was changed to 55–74 years Diabetes Care 30:1374–1383, 2007 during the 2nd year of recruitment to increase the anticipated cardiovascular event rate), had a BMI Ͼ25 kg/m2 (Ͼ27 ook AHEAD (Action for Health in objective is to determine whether cardio- 2 kg/m if currently taking insulin), A1C Diabetes) is an National Institutes of vascular morbidity and mortality in indi- Ͻ11%, blood pressure Ͻ160 (systolic) L Health–funded clinical trial, con- viduals with type 2 diabetes can be and Ͻ100 (diastolic) mmHg, and triglyc- ducted in 16 centers in the U.S., investi- reduced by long-term weight reduction, erides Ͻ600 mg/dl. gating the long-term health impact of an achieved by an ILI that includes diet, Participants completed maximal intensive lifestyle intervention (ILI) in physical activity, and behavior modifica- graded exercise tests to assess fitness be- 5,145 overweight or obese adults with tion (3). The goal of this intervention is fore randomization. The test consisted of type 2 diabetes. The design and methods for individuals to achieve and maintain a the participant walking on a motorized of this trial have been reported elsewhere loss of at least 7% of initial body weight. treadmill at a constant self-selected walk- (1), as have the baseline characteristics of Results of the ILI group will be compared ing speed (1.5, 2.0, 2.5, 3.0, 3.5, or 4.0 the randomized cohort (2). Its primary with a usual-care condition that includes ●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●● mph). The elevation of the treadmill was initially set at 0% grade and increased by Address correspondence and reprint requests to Mark Espeland, PhD, Division of Public Health Sciences, 1.0% every minute. Heart rate and rating Wake Forest University School of Medicine, Medical Center Boulevard, Winston-Salem, NC 27157. E-mail: [email protected]. of perceived exertion (RPE) using the Received for publication 12 January 2007 and accepted in revised form 5 March 2007. Borg 15-category scale (4) were measured Published ahead of print at http://care.diabetesjournals.org on 15 March 2007. DOI: 10.2337/dc07-0048. during the final 10 s of each exercise stage Clinical trial reg. no. NCT00017953, clinicaltrials.gov. and at the point of test termination. To *Authors and members of the Look AHEAD trial are listed in the APPENDIX. Abbreviations: ADA, American Diabetes Association; CVD, cardiovascular disease; DSE, diabetes sup- determine eligibility at baseline, a maxi- port and education; ILI, intensive lifestyle intervention; AHEAD, Action for Health in Diabetes; METS, mal exercise test was performed. For in- metabolic equivalents; RPE, rating of perceived exertion. dividuals not taking prescription medi- A table elsewhere in this issue shows conventional and Syste`me International (SI) units and conversion cine that would affect heart rate response factors for many substances. during exercise (e.g., ␤-blocker), the base- © 2007 by the American Diabetes Association. The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby line test was considered valid if the individ- marked “advertisement” in accordance with 18 U.S.C. Section 1734 solely to indicate this fact. ual achieved at least 85% of age-predicted

1374 DIABETES CARE, VOLUME 30, NUMBER 6, JUNE 2007 Look AHEAD Research Group maximal heart rate (age-predicted maximal ment components from the Diabetes Pre- were invited to three additional group heart rate ϭ 220 Ϫ age) and a minimum of vention Program (6–8) and the National sessions during the 1st year. A standard 4 metabolic equivalents (METS). For indi- Heart, Lung, and Blood Institute’s clinical protocol was used for conducting these viduals taking prescription medicine that guidelines (9). During months 1–6, par- sessions, which provided information would affect the heart rate response during ticipants were seen weekly with three and opportunities for discussing topics exercise, the baseline test was considered group meetings and one individual ses- related to diet, physical activity, and so- valid if the individual achieved an RPE of at sion per month. During months 7–12, cial support. However, the DSE group least 18 and a minimum of 4 METS. Indi- group sessions were provided every other was not weighed at these sessions and re- viduals not achieving these criteria were not week and the monthly individual session ceived no counseling in behavioral strat- eligible for randomization into Look was continued. Sessions were led by in- egies for changing diet and activity. AHEAD. METS at each exercise stage and at tervention teams that included registered test termination were estimated from a stan- dietitians, behavioral psychologists, and Ongoing clinical care dardized formula that incorporates walking exercise specialists. All participants in the ILI and DSE groups speed and grade (5). Caloric restriction was the primary continued to receive care for their diabe- The goal was to recruit approximately method of achieving weight loss. The ma- tes and all other medical conditions from equal numbers of men and women, with cronutrient composition of the diet was their own physicians. Changes in all med- Ͼ33% from racial and ethnic minority structured to enhance glycemic control icines were made by the participants’ own groups. Informed consent was obtained and to improve CVD risk factors. It in- physicians, except for temporary reduc- from all participants before screening and cluded a maximum of 30% of total calo- tions in hyperglycemia medicines during at enrollment, consistent with the Hel- ries from fat (with a maximum of 10% of periods of intensive weight loss interven- sinki Declaration and the guidelines of total calories from saturated fat) and a tion, which were made by the interven- each center’s institutional review board. minimum of 15% of total calories from tion sites following a standardized After all eligibility criteria were con- protein (10). Participants were prescribed treatment protocol aimed at avoiding firmed, participants were randomly as- portion-controlled diets, which included hypoglycemia. signed with equal probability to either the the use of liquid meal replacements (pro- ILI or the DSE comparison condition. vided free of charge) and frozen food en- Assessments Randomization was stratified by clinical treés, as well as structured meal plans Anthropometry. All participants were center. (comprised of conventional foods) for scheduled to attend baseline and 1-year those who declined the meal replace- assessments, at which time measures were Interventions ments. Monthly reviews took place at an collected by staff members who were Before randomization, all study partici- individual session to reassess progress. masked to participants’ intervention as- pants were required to complete a 2-week The physical activity program pre- signments. Weight and height were as- run-in period that included successful scribed in the ILI relied heavily on home- sessed in duplicate using a digital scale self-monitoring of diet and physical activ- based exercise with gradual progression and a standard stadiometer. Seated blood ity, and they were provided an initial ses- toward a goal of 175 min of moderate- pressure was measured in duplicate, us- sion of diabetes education with particular intensity physical activity per week. Al- ing an automated device after a 5-min emphasis on aspects of diabetes care re- though walking was encouraged, rest. Participants brought all prescription lated to the trial such as management of participants were allowed to choose other medicines to the clinic to ensure record- hypoglycemia and foot care. The session types of moderate-intensity physical ac- ing accuracy. History of cardiovascular stressed the importance of eating a tivity, and programs were tailored based disease was based on self-report of myo- healthy diet and being physically active on the results of a baseline physical fitness cardial infarction, stroke, transient isch- for both weight loss and improvement of test and safety concerns. emic event, percutaneous transluminal glycemic control. All individuals who The ILI included a “toolbox” ap- coronary angioplasty, or coronary artery smoked were encouraged to quit and proach, as used in the Diabetes Preven- bypass graft. were provided self-help materials and/or tion Program (6,7), to help participants Fitness. At 1 year, a submaximal exer- referral to local programs as appropriate. achieve and maintain the study’s weight cise test was performed and terminated The weight loss intervention pre- loss and activity goals. Use of the toolbox when the participant first achieved or ex- scribed in the 1st year has been described was based on a preset algorithm and as- ceeded 80% of age-predicted maximal ϭ in detail (3). Briefly, it combines diet sessment of participant progress. After the heart rate (HRMax in beats per min modification and increased physical ac- first 6 months, the toolbox algorithm in- 220 Ϫ age). If the participant was taking a tivity and was designed to induce a min- cluded use of a weight loss medicine (or- ␤-blocker at baseline or 1-year assess- imum weight loss of 7% of initial body listat) and/or advanced behavioral ment, the submaximal test was termi- weight during the 1st year. Individual strategies for individuals who had diffi- nated at the point when the participant participants were encouraged to lose culty in meeting the trial’s weight or ac- first reported achieving or exceeding 16 Ͼ10% of their initial body weight, with tivity goals. Specific protocols were used on the 15-category RPE scale. For partic- the expectation that aiming high would to determine when to initiate medication ipants not taking a ␤-blocker, change in ensure that a greater number of partici- or other approaches, to monitor partici- cardiorespiratory fitness was computed as pants would achieve the minimum 7% pants, and to determine when to stop a the difference in estimated METS be- weight loss. The intervention was mod- particular intervention. tween points during the baseline and eled on group behavioral programs devel- Participants assigned to DSE attended 1-year tests when Ͼ80% of age-predicted oped for the treatment of obese patients the initial prerandomization diabetes ed- maximal heart rate was attained. For par- with type 2 diabetes and included treat- ucation session (described above) and ticipants taking ␤-blockers at either base-

DIABETES CARE, VOLUME 30, NUMBER 6, JUNE 2007 1375 Reduction in weight and CVD risk factors

Figure 1—Enrollment of Look AHEAD participants. line or 1 year, change in cardiorespiratory Disease Control and Prevention reference stolic blood pressure Ͻ80 mmHg, and fitness was computed as the difference in methods. LDL cholesterol was calculated lipid control as LDL cholesterol Ͻ100 estimated METS between points during by the Friedewald equation (11). HDL mg/dl. the baseline and 1-year tests when RPE cholesterol was analyzed by the treatment Ͼ16 was attained. of whole plasma with dextran sulfate mi- Statistical methods ϩ Serum measures. The Central Biochem- nus Mg2 to precipitate all of the apoli- Cross-sectional differences between par- istry Laboratory (Northwest Lipid Re- poprotein B–containing lipoproteins. ticipants assigned to the ILI and DSE con- search Laboratories, University of Albumin and creatinine concentrations ditions were assessed using ANCOVA and Washington, Seattle, WA) conducted were measured from spot urine samples. logistic regression, with adjustment for standardized analyses of shipped frozen Participants were classified as having clinical center (the sole factor used to specimens. A1C was measured by a ded- the metabolic syndrome using the criteria stratify randomization). Changes in out- icated ion exchange high-performance proposed by the National Cholesterol Ed- come measures from baseline to 1 year liquid chromatography instrument (Bio- ucation Program Adult Treatment Pro- were compared using ANCOVA and rad Variant 11). Fasting serum glucose gram III panel (12). They also were Mantel-Haenszel tests. was measured enzymatically on a Hitachi classified according to their success in 917 autoanalyzer using hexokinase and meeting treatment goals published by the RESULTS glucose-6-phosphate dehydrogenase. To- American Diabetes Association (ADA) tal serum cholesterol and triglycerides (13). Glycemic control was defined as Participants’ baseline characteristics were measured enzymatically using A1C Ͻ7.0%, blood pressure control as Figure 1 describes trial enrollment. Of methods standardized to the Centers for systolic blood pressure Ͻ130 and dia- 28,622 individuals who provided infor-

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Table 1—Baseline characteristics of the ILI and DSE groups circumference in the ILI than DSE group, with mean decreases of 6.2 Ϯ 10.2 vs. Ϯ Ͻ Intervention assignment 0.5 8.5 cm (P 0.001). In the ILI group, the average weight Characteristic ILI DSE P value loss among baseline insulin users was 7.6 Ϯ 7.0% compared with 8.7 Ϯ 6.9% in n 2,570 2,575 ϭ Women 1,526 (59.3) 1,537 (59.6) 0.85* nonusers (P 0.002). Insulin users, com- Ethnicity pared with noninsulin users, were less likely to achieve weight losses Ͼ10% African American 399 (15.5) 404 (15.7) Ͼ American Indian/Alaskan Native 130 (5.1) 128 (5.0) (33.5 vs. 38.5%) or 7% (47.8 vs. Asian/Pacific Islander 29 (1.1) 21 (0.8) 0.28* 56.4%). In the DSE group, average weight loss was 0.3 Ϯ 5.1% among insulin users Hispanic/Latino 339 (13.2) 338 (13.2) Ϯ Non-Hispanic white 1,618 (63.1) 1,628 (63.3) versus 0.8 4.7% among noninsulin users. Other/multiple 48 (1.9) 50 (1.9) Age (years) 58.6 Ϯ 6.8 58.9 Ϯ 6.9 0.12† Changes in fitness History of cardiovascular disease‡ 371 (14.4) 351 (13.6) 0.40* Figure 2B illustrates the cumulative dis- Metabolic syndrome 2,406 (93.6) 2,431 (94.4) 0.32* tribution of measured 1-year fitness Use of insulin 381 (14.8) 408 (15.8) 0.31* changes in 4,246 participants who had BMI (kg/m2) repeat testing. Fitness tended to increase Women 36.3 Ϯ 6.2 36.6 Ϯ 6.0 0.15† in both groups; however, increases were Men 35.3 Ϯ 5.7 35.1 Ϯ 5.2 0.41† more prevalent and tended to be larger Weight (kg) among ILI participants; 70.1% of the ILI Women 94.8 Ϯ 17.9 95.4 Ϯ 17.3 0.34† participants had increased fitness at 1 year Men 108.9 Ϯ 19.0 109.0 Ϯ 18.0 0.94† compared with 46.3% of the DSE participants (P Ͻ 0.001). Fitness increases av- Waist circumference (cm) Ϯ Women 110.5 Ϯ 13.6 111.2 Ϯ 13.2 0.14† eraged 20.9 29.1% among ILI Ϯ Ϯ participants compared with 5.8 Ϯ 22.0% Men 118.7 14.0 118.4 12.9 0.62† Ͻ Fitness (METS) among DSE participants (P 0.001). Women 6.7 Ϯ 1.7 6.6 Ϯ 1.7 0.38† These changes could not be fully ac- Men 7.9 Ϯ 2.1 8.0 Ϯ 2.2 0.89† counted for by changes in weight. After covariate adjustment for weight changes, Data are means Ϯ SD or frequency (%). *␹2 test. †ANCOVA, adjusted for clinical center. ‡Self-report of prior myocardial infarction, stroke, transient ischemic attack, angioplasty/stent, coronary artery bypass graft, the fitted mean difference in fitness in- carotid endarterectomy, angioplasty of lower extremity, aortic aneurysm repair, or heart failure. creases between groups remained statisti- cally significant (15.9% for ILI vs. 10.8% for DSE, P Ͻ 0.001). mation during prescreening, 15,561 cines. Baseline BMI, weight, waist circum- (54.4%) were found to be eligible for ference, and fitness are given by sex in Changes in medicines and clinic visits to confirm eligibility. The Table 1. A BMI of Ն30.0 kg/m2 was cardiovascular risk factors most common reasons for ineligibility at present in 85.1% of participants. During the 1st year, use of glucose- this stage were related to age (13.5%), lowering medicines among ILI partici- lack of diabetes (8.6%), and the likeli- Weight loss pants decreased from 86.5 to 78.6%, hood that the diabetes was type 1 (4.4%). The 1-year examination was attended by whereas it increased from 86.5 to 88.7% Of 9,045 (58.1%) who attended clinic 2,496 (97.1%) of the ILI and 2,463 among DSE participants (P Ͻ 0.001). As visits, 5,145 (56.9%) were ultimately ran- (95.7%) of the DSE participants (P ϭ shown in Table 2, despite this difference, domized: 2,570 participants were as- 0.004). Among the factors listed in Table mean fasting glucose declined more signed to ILI and 2,575 to DSE. At this 1, only the distribution of baseline insulin among ILI participants compared with stage, individuals were most commonly use significantly varied between nonat- DSE participants (P Ͻ 0.001), as did ineligible due to staff judgment (7.6%), tendees (21.0%) versus attendees mean A1C (P Ͻ 0.001). elevated blood pressure (7.0%), or in- (15.1%) (P ϭ 0.04). Over the 1st year of As described in Table 2, the preva- complete behavioral run ins (4.8%). the trial, the ILI group lost an average of lence of antihypertensive medicine use At baseline, the characteristics of par- (means Ϯ SD) 8.6 Ϯ 6.9% of initial body remained unchanged among ILI partici- ticipants assigned to the two intervention weight compared with 0.7 Ϯ 4.8% in the pants but increased by 2.2% (0.6%) conditions were similar (Table 1). Over- DSE group (P Ͻ 0.001). Figure 2A por- among DSE participants (P ϭ 0.02). all, 14.0% reported a history of cardiovas- trays the cumulative distribution of Mean systolic and diastolic blood pres- cular disease, 94.0% met the National weight changes in the two groups. Within sure levels declined in both groups, but Cholesterol Education Program Adult the ILI group, 37.8% of participants met reductions were significantly greater in Treatment Panel III definition for the met- the individual weight loss goal (Ͼ10% of ILI than in DSE participants (both P Ͻ abolic syndrome (12), 15.3% were taking initial weight) and 55.2% met the group 0.001). insulin, 87.5% were using diabetes med- average goal (Ͼ7%) compared with 3.2 Use of lipid-lowering medicines in- icines (including insulin), 75.3% were us- and 7.0% of DSE participants, respec- creased in both groups; however, the in- ing antihypertensive medicines, and tively. These weight losses were accompa- crease was significantly smaller among ILI 51.0% were using lipid-lowering medi- nied by greater mean reductions in waist participants than in DSE participants

DIABETES CARE, VOLUME 30, NUMBER 6, JUNE 2007 1377 Reduction in weight and CVD risk factors

Table 2—Changes in measures of diabetes control, blood pressure control, measures of lipid/ creased more among ILI (P Ͻ 0.001). The lipoproteins control, albumin-to-creatinine ratio, and prevalence of metabolic syndrome prevalence of urine albumin-to-creatinine among participants seen at year 1 ratios Ն30.0 ␮g/mg decreased more among ILI participants than DSE partici- ϭ Measure ILI DSE P value pants (P 0.002). n 2,496 2,463 Classification of participants Use of diabetes medicines (%) The percentage meeting criteria for the Baseline 86.5 Ϯ 0.7 86.5 Ϯ 0.7 0.93* metabolic syndrome decreased signifi- Year 1 78.6 Ϯ 0.8 88.7 Ϯ 0.6 Ͻ0.001* cantly more among ILI than DSE partici- Change Ϫ7.8 Ϯ 0.6 2.2 Ϯ 0.5 Ͻ0.001† pants (P Ͻ 0.001). As shown in Table 2, Fasting glucose (mg/dl) the prevalence declined from 93.6 to Baseline 151.9 Ϯ 0.9 153.6 Ϯ 0.9 0.21‡ 78.9% in the ILI group compared with a Year 1 130.4 Ϯ 0.8 146.4 Ϯ 0.9 Ͻ0.001‡ decline of 94.4 to 87.3% in the DSE Change Ϫ21.5 Ϯ 0.9 Ϫ7.2 Ϯ 0.9 Ͻ0.001‡ group. The prevalence of meeting ADA A1C (%) goals for A1C, blood pressure, and LDL Baseline 7.25 Ϯ 0.02 7.29 Ϯ 0.02 0.26‡ cholesterol increased among both ILI and Year 1 6.61 Ϯ 0.02 7.15 Ϯ 0.02 Ͻ0.001‡ DSE participants (Table 3). These in- Difference Ϫ0.64 Ϯ 0.02 Ϫ0.14 Ϯ 0.02 Ͻ0.001‡ creases were greater among ILI partici- Use of antihypertensive medicines (%) pants (P Ͻ 0.001) for A1C and blood Baseline 75.3 Ϯ 0.9 73.7 Ϯ 0.9 0.23* pressure 26.4 Ϯ 1.0% vs. 5.4 Ϯ 1.07% Year 1 75.2 Ϯ 0.9 75.9 Ϯ 0.9 0.54* and 15.1 Ϯ 1.1% vs. 7.0 Ϯ 1.2%, respec- Change Ϫ0.1 Ϯ 0.6 2.2 Ϯ 0.6 0.02† tively (both P Ͻ 0.001), but were of sim- Systolic blood pressure (mmHg) ilar magnitudes for LDL cholesterol. The Baseline 128.2 Ϯ 0.4 129.4 Ϯ 0.3 0.01‡ prevalence simultaneously meeting all Year 1 121.4 Ϯ 0.4 126.6 Ϯ 0.4 Ͻ0.001‡ three goals increased from 10.8 to 23.6% Change Ϫ6.8 Ϯ 0.4 Ϫ2.8 Ϯ 0.3 Ͻ0.001‡ among ILI participants compared with an Diastolic blood pressure (mmHg) increase from 9.5 to 16.0% among DSE Baseline 69.9 Ϯ 0.2 70.4 Ϯ 0.2 0.11‡ participants (P Ͻ 0.001). Year 1 67.0 Ϯ 0.2 68.6 Ϯ 0.2 Ͻ0.001‡ Change Ϫ3.0 Ϯ 0.2 Ϫ1.8 Ϯ 0.2 Ͻ0.001‡ CONCLUSIONS — The present re- Use of lipid-lowering medicines (%) sults show that clinically significant Baseline 49.4 Ϯ 1.0 48.4 Ϯ 1.0 0.52* weight loss is broadly achievable in sub- Year 1 53.0 Ϯ 1.0 57.8 Ϯ 1.0 Ͻ0.001* jects with type 2 diabetes and is associated Change 3.7 Ϯ 0.8 9.4 Ϯ 0.8 Ͻ0.001† with improved cardiovascular risk fac- LDL cholesterol (mg/dl) tors. At 1 year, participants in ILI Baseline 112.2 Ϯ 0.4 112.4 Ϯ 0.6 0.78‡ achieved an average loss of 8.6% of initial Year 1 107.0 Ϯ 0.6 106.7 Ϯ 0.7 0.74‡ body weight and a 21% improvement in Change Ϫ5.2 Ϯ 0.6 Ϫ5.7 Ϯ 0.6 0.49‡ cardiovascular fitness. Separate manu- HDL cholesterol (mg/dl) scripts are underway that will provide de- Baseline 43.5 Ϯ 0.2 43.6 Ϯ 0.2 0.80‡ tails on the relative contributions of Year 1 46.9 Ϯ 0.3 44.9 Ϯ 0.2 Ͻ0.001‡ individual strategies (e.g., meal replace- Change 3.4 Ϯ 0.2 1.4 Ϯ 0.1 Ͻ0.001‡ ment, orlistat) toward this successful out- Triglycerides (mg/dl) come. Even participants on insulin lost an Baseline 182.8 Ϯ 2.3 180.0 Ϯ 2.4 0.38‡ average of 7.6% of initial weight. The ILI Year 1 152.5 Ϯ 1.8 165.4 Ϯ 1.9 Ͻ0.001‡ was associated with an increase from 46 Change Ϫ30.3 Ϯ 2.0 Ϫ14.6 Ϯ 1.8 Ͻ0.001‡ to 73% in the participants who met the Albumin-to-creatinine ratio (Ͼ30.0 ADA goal of A1C Ͻ7% and a doubling in ␮g/mg) (%) the percent of individuals who met all Baseline 16.4 Ϯ 0.7 16.9 Ϯ 0.8 0.69‡ three of the ADA goals for glycemic con- Year 1 12.5 Ϯ 0.7 15.4 Ϯ 0.7 0.005‡ trol, hypertension, and dyslipidemia. Change Ϫ3.9 Ϯ 0.6 Ϫ1.5 Ϯ 0.6 0.002‡ Look AHEAD is the first large clinical Metabolic syndrome (%) trial to compare an intensive weight loss Baseline 93.6 Ϯ 0.5 94.4 Ϯ 0.5 0.23‡ intervention (i.e., ILI) with a support and Year 1 78.9 Ϯ 0.8 87.3 Ϯ 0.7 Ͻ0.001‡ education group (i.e., DSE) in individuals Change Ϫ14.7 Ϯ 0.8 Ϫ7.1 Ϯ 0.7 Ͻ0.001‡ with type 2 diabetes. As expected, partic- Data are means Ϯ SE or % Ϯ SE. *Logistic regression with adjustment for clinical site. †Mantel-Haenszel test ipants in the ILI group had significantly with adjustment for clinical site. ‡ANCOVA, with adjustment for clinical site. greater weight loss and improvement in fitness at 1 year than those in the DSE (P Ͻ 0.001). Mean levels of LDL choles- lesterol levels increased more among ILI group. Moreover, they had a significantly terol declined by similar magnitudes in than DSE participants (P Ͻ 0.001), greater decrease in the number of medi- both groups (P ϭ 0.49). Mean HDL cho- whereas mean triglyceride levels de- cines used to treat their diabetes and

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(14), but their average baseline BMI was higher. Overall, they are healthier than diabetic individuals in the National Health and Nutrition Examination Survey with regard to glucose, A1C, and lipid levels and are less likely to smoke. A large percentage was taking medicines for risk factors at study enrollment, and many had a significant history of cardiovascular disease. Despite the level of health of the sample, fewer than half met the ADA goal for A1C and only 10% met all three ADA goals (13). The ILI was extremely effective in increasing the percent of participants who met these goals. At 1 year, 72.7% met the goal for A1C and 23.6% met all three goals, compared with only 50.8 and 16.0%, respectively, for the DSE group. The ILI also was associated with significantly greater remission of the metabolic syndrome than was the DSE intervention. Several large clinical trials of individuals with impaired glucose tolerance (6,15) or hypertension (16,17) have achieved average weight losses of 4–7% at 1 year using intensive lifestyle interventions that emphasized behavior change. These weight losses were associated with marked improvement in health status. Al- though a number of smaller studies (18,19) have shown that it is possible, using strong behavioral programs, to pro- duce significant weight loss in patients with type 2 diabetes, most studies of Figure 2—Distribution of 1-year changes in percent weight (A) and fitness (B) (METS) among weight loss in such individuals have had individuals grouped by intervention assignment. Dashed lines are used to indicate the percentages only modest success. It appears that indi- of ILI participants with weight losses exceeding 10, 7, and 5%, respectively. viduals with diabetes (especially those on insulin) may have more difficulty losing blood pressure. Despite the greater reduc- Table 3—Changes in percentage of participants meeting ADA goals for risk factors tions in these medicines, the ILI group showed greater improvements in their Measure ILI DSE P value glycemic control, albumin-to-creatinine ratio, systolic and diastolic blood pres- A1C (Ͻ7%) sure, triglycerides, and HDL cholesterol Baseline 46.3 Ϯ 1.0 45.4 Ϯ 1.0 0.50* than the DSE group. Changes in LDL cho- Year 1 72.7 Ϯ 0.9 50.8 Ϯ 1.0 Ͻ0.001* lesterol were comparable in the two Difference 26.4 Ϯ 1.0 5.4 Ϯ 1.0 Ͻ0.001† groups. Of particular note is that mean Blood pressure (Ͻ130/80 mmHg) (%) A1C fell from 7.2 to 6.6%. Few studies, Baseline 53.5 Ϯ 1.0 49.9 Ϯ 1.0 0.01* even trials of newer diabetes medicines, Year 1 68.6 Ϯ 0.9 57.0 Ϯ 1.0 Ͻ0.001* have achieved levels of A1C of 6.6%. Al- Change 15.1 Ϯ 1.1 7.0 Ϯ 1.2 Ͻ0.001† though the DSE group had smaller bene- LDL cholesterol (Ͻ100 mg/dl) (%) fits than ILI, it is important to recognize Baseline 37.1 Ϯ 1.0 36.9 Ϯ 1.0 0.87* that these participants also experienced Year 1 43.8 Ϯ 1.0 44.9 Ϯ 1.0 0.45* some improvement (not worsening), on Change 6.7 Ϯ 1.0 8.0 Ϯ 1.0 0.34† average, in weight, fitness, and cardiovas- All three goals cular risk factors. Baseline 10.8 Ϯ 0.6 9.5 Ϯ 0.6 0.13* The Look AHEAD participants are of Year 1 23.6 Ϯ 0.8 16.0 Ϯ 0.7 Ͻ0.001* similar ethnic distribution to that ob- Change 12.8 Ϯ 0.9 6.5 Ϯ 0.8 Ͻ0.001† served in the National Health and Nutri- Data are % Ϯ SD. *Logistic regression with adjustment for clinical site. †Mantel-Haenszel test with adjust- tion Examination Survey 1999–2000 ment for clinical site.

DIABETES CARE, VOLUME 30, NUMBER 6, JUNE 2007 1379 Reduction in weight and CVD risk factors weight and then keeping it off than those AHEAD trial is the effect of weight loss on Prevention (to Edward W. Gregg, PhD; David without diabetes (20). For example, the development of cardiovascular dis- F. Williamson, PhD; and Ping Zhang, PhD). among adult Pima Indians receiving stan- ease. Although the difference between the The following organizations have commit- dard clinical care for type 2 diabetes, ILI and DSE groups in the change in risk ted to make major contributions to Look those treated with insulin lost less weight factors at 1-year points to the potential AHEAD: Federal Express, Health Management Resources, Johnson & Johnson, LifeScan, Op- than those treated without drugs or with cardiovascular benefits of the ILI, we will tifast-Novartis Nutrition, Roche Pharmaceuti- oral agents (21). The larger weight losses need several additional years to determine cals, Ross Product Division of Abbott in Look AHEAD than in prior clinical tri- whether the initial weight loss can be Laboratories, and Slim-Fast Foods Company. als may be attributable to the combination maintained, whether weight loss has a of group and individual contact, the long-term effect on the risk factors, and higher physical activity goal that was pre- whether the favorable risk factor changes APPENDIX scribed, and/or the more intense dietary translate into reduced cardiovascular intervention, which included not only events. This is critical information for es- Authors calorie and fat restrictions but also struc- tablishing evidence-based recommenda- Xavier Pi-Sunyer, MD; George Blackburn, tured meal plans, each of which has pre- tions with regard to weight loss for the MD, PhD; Frederick L. Brancati, MD, viously been associated with successful prevention of cardiovascular disease in MHS; George A. Bray, MD; Renee Bright, weight loss and maintenance (22–25). Al- individuals with diabetes. MS; Jeanne M. Clark, MD, MPH; Jeffrey though Look AHEAD participants using M. Curtis, MD, MPH; Mark A. Espeland, insulin achieved less average weight loss PhD; John P. Foreyt, PhD; Kathryn than those not on insulin (7.6 vs. 8.7%), Graves, MPH, RD, CDE; Steven M. Acknowledgments— This study is sup- Haffner, MD; Barbara Harrison, MS; the weight loss of the participants on in- ported by the Department of Health and Hu- sulin demonstrates that use of insulin man Services through the following James O. Hill, PhD; Edward S. Horton, does not prevent successful weight loss. A cooperative agreements from the National In- MD; John Jakicic, PhD; Robert W. Jeffery, recent meta-analysis (26) found that the stitutes of Health: DK57136, DK57149, PhD; Karen C. Johnson, MD, MPH; use of meal replacements increased both DK56990, DK57177, DK57171, DK57151, Steven Kahn, MB, ChB; David E. Kelley, short- and long-term average weight loss DK57182, DK57131, DK57002, DK57078, MD; Abbas E. Kitabchi, MD, PhD; Wil- by ϳ2.5 kg, compared with prescription DK57154, DK57178, DK57219, DK57008, liam C. Knowler, MD, DrPH; Cora E. DK57135, and DK56992. The following fed- of a conventional reducing diet with the Lewis, MD, MSPH; Barbara J. Maschak- eral agencies have contributed support: Na- Carey, MSN, CDE; Brenda Montgomery, same calorie goals. Our findings that par- tional Institute of Diabetes and Digestive and ticipants in the ILI had significant im- RN, MS, CDE; David M. Nathan, MD; Kidney Diseases; National Heart, Lung, and Jennifer Patricio, MS; Anne Peters, MD; J. provements in cardiovascular risk factors Blood Institute; National Institute of Nursing confirms prior studies showing that initial Research; National Center on Minority Health Bruce Redmon, MD; Rebecca S. Reeves, weight loss in type 2 diabetes is associated and Health Disparities; Office of Research on DrPH, RD; Donna H. Ryan, MD; Monika with improved glycemic control and car- Women’s Health; and the Centers for Disease Safford, MD; Brent Van Dorsten, PhD; diovascular risk factors at 1 year (27,28). Control and Prevention. This research was Thomas A. Wadden, PhD; Lynne Wagen- However, the long-term impact of such supported in part by the Intramural Research knecht, DrPH; Jacqueline Wesche- weight losses remains unclear. Program of the National Institute of Diabetes Thobaben, RN, BSN, CDE; Rena R. Wing, and Digestive and Kidney Diseases. PhD; Susan Z. Yanovski, MD. Estimated fitness improved in both Additional support was received from the groups over the year, but it improved sig- Johns Hopkins Medical Institutions Bayview nificantly more in the ILI group. It is un- General Clinical Research Center Clinical sites known how much of the improvement in (M01RR02719); the Massachusetts General The Johns Hopkins Medical Institutions: either treatment group was due to mea- Hospital Mallinckrodt General Clinical Re- Frederick L. Brancati, MD, MHS; Jeff Ho- surement variability and greater familiar- search Center (M01RR01066); the University nas, MS; Lawrence Cheskin, MD; Jeanne ity with the testing procedure at the of Colorado Health Sciences Center General M. Clark, MD, MPH; Kerry Stewart, EdD; 1-year visit and how much represented Clinical Research Center (M01RR00051) and Richard Rubin, PhD; Jeanne Charleston, physiologic change. The difference in im- Clinical Nutrition Research Unit (P30 RN; Kathy Horak, RD. provement between the ILI and DSE DK48520); the University of Tennessee at Pennington Biomedical Research Memphis General Clinical Research Center groups, however, can be taken as a mea- (M01RR0021140); the University of Pitts- Center: George A. Bray, MD; Kristi Rau; sure of the ILI treatment effect. This treat- burgh General Clinical Research Center Allison Strate, RN; Brandi Armand, LPN; ment effect persisted even after (M01RR000056 44); National Institutes of Frank L. Greenway, MD; Donna H. Ryan, adjustment for the 1-year weight change. Health Grant DK 046204; the University of MD; Donald Williamson, PhD; Amy Bac- The changes in fitness compared favor- Washington/VA Puget Sound Health Care Sys- hand; Michelle Begnaud; Betsy Berhard; ably with those observed in prior studies tem Medical Research Service, Department of Elizabeth Caderette; Barbara Cerniaus- with both diabetic (29,30) and nondia- Veterans Affairs; and Frederic C. Bartter Gen- kas; David Creel; Diane Crow; Helen betic (29,31,32) participants. Thus, the eral Clinical Research Center (M01RR01346). Guay; Nancy Kora; Kelly LaFleur; Kim modest increase in physical activity, pri- Federal support: National Institute of Dia- Landry; Missy Lingle; Jennifer Perault; marily walking, had a very beneficial ef- betes and Digestive and Kidney Diseases (to Mandy Shipp, RD; Marisa Smith; Eliza- Barbara Harrison, MS; Van S. Hubbard, MD fect. This may translate into a lower rate of PhD; and Susan Z. Yanovski, MD); the Na- beth Tucker. cardiovascular events, including mortal- tional Heart, Lung, and Blood Institute (to The University of Alabama at Bir- ity, as suggested in some observational Lawton S. Cooper, MD, MPH; Jeffrey Cutler, mingham: Cora E. Lewis, MD, MSPH; studies (33,34). MD, MPH; and Eva Obarzanek, PhD, MPH, Sheikilya Thomas, MPH; Monika Safford, The primary outcome of the Look RD); and the Centers for Disease Control and MD; Vicki DiLillo, PhD; Charlotte Bragg,

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MS, RD, LD; Amy Dobelstein; Stacey Gil- elle Chan, BS; Kati Konersman, MA, RD, Barbara Bancroft, RN, MS; Anna Ber- bert, MPH; Stephen Glasser, MD; Sara CDE; Magpuri Perpetua, RD. torelli, MBA, RD; Richard Carey, BS; Ta- Hannum, MA; Anne Hubbell, MS; Jen- The University of Tennessee Health tum Charron, BS; Heather Chenot, MS; nifer Jones, MA; DeLavallade Lee; Ruth Science Center: Karen C. Johnson, MD, Kimberley Chula-Maguire, MS; Pamela Luketic, MA, MBA, MPH; Karen Marshall; MPH; Helen Lambeth, RN, BSN; Carolyn Coward, MS, RD; Lisa Cronkite, BS; Julie L. Christie Oden; Janet Raines, MS; Cathy M. Gresham, RN; Abbas E. Kitabchi, MD, Currin, MD; Maureen Daly, RN; Caitlin Roche, RN, BSN; Janet Truman; Nita PhD; Stephanie A. Connelly, MD, MPH; Egan, MS; Erica Ferguson, BS, RD; Linda Webb, MA; Audrey Wrenn, MAEd. Lynne Lichtermann, RN, BSN. Foss, MPH; Jennifer Gauvin, BS; Don Harvard center: Massachusetts Gen- University of Minnesota: Robert W. Kieffer, PhD; Lauren Lessard, BS; Debo- eral Hospital: David M. Nathan, MD; Jeffery, PhD; Carolyn Thorson, CCRP; rah Maier, MS; J.P. Massaro, BS; Tammy Heather Turgeon, RN, BS, CDE; Kristina John P. Bantle, MD; J. Bruce Redmon, Monk, MS; Rob Nicholson, PhD; Erin Schumann, BA; Enrico Cagliero, MD; MD; Richard S. Crow, MD; Scott Crow, Patterson, BS; Suzanne Phelan, PhD; Hol- Linda Delahanty, MS, RD; Kathryn Hay- MD; Susan K. Raatz, PhD, RD; Kerrin lie Raynor, PhD, RD; Douglas Raynor, ward, MD; Ellen Anderson, MS, RD; Lau- Brelje, MPH, RD; Carolyne Campbell; PhD; Natalie Robinson, MS, RD; Deborah rie Bissett, MS, RD; Richard Ginsburg, Jeanne Carls, MEd; Tara Carmean-Mihm, Robles; Jane Tavares, BS. PhD; Valerie Goldman, MS, RD; Virginia BA; Emily Finch, MA; Anna Fox, MA; The University of Texas Health Sci- Harlan, MSW; Charles McKitrick, RN, Elizabeth Hoelscher, MPH, RD, CHES; La ence Center at San Antonio: Steven M. BSN, CDE; Alan McNamara, BS; Theresa Donna James; Vicki A. Maddy, BS, RD; Haffner, MD; Maria G. Montez, RN, Michel, DPT, DSc, CCS; Alexi Poulos, BA; Therese Ockenden, RN; Birgitta I. Rice, MSHP, CDE; Carlos Lorenzo, MD. Barbara Steiner, EdM; Joclyn Tosch, BA. MS, RPh CHES, BS; Ann D. Tucker, BA; University of Washington/VA Puget Joslin Diabetes Center: Edward S. Hor- Mary Susan Voeller, BA; Cara Walcheck, Sound Health Care System: Steven Kahn ton, MD; Sharon D. Jackson, MS, RD, BS, RD. MB, ChB; Brenda Montgomery, RN, MS, CDE; Osama Hamdy, MD, PhD; A. En- St. Luke’s Roosevelt Hospital Center: CDE; Robert Knopp, MD; Edward Lipkin, rique Caballero, MD; Sarah Bain, BS; Eliz- Xavier Pi-Sunyer, MD; Jennifer Patricio, MD; Matthew L. Maciejewski, PhD; Dace abeth Bovaird, BSN, RN; Ann Goebel- MS; Stanley Heshka, PhD; Carmen Pal, Trence, MD; Terry Barrett, BS; Joli Bartell, Fabbri, PhD; Lori Lambert, MS, RD; Sarah MD; Lynn Allen, MD; Diane Hirsch, RNC, BA; Diane Greenberg, PhD; Anne Murillo, Ledbury, MEd, RD; Maureen Malloy, BS; MS, CDE; Mary Anne Holowaty, MS, CN. BS; Betty Ann Richmond, MEd; April Kerry Ovalle, MS, RCEP, CDE. Beth Israel University of Pennsylvania: Thomas Thomas, MPH, RD. A. Wadden, PhD; Barbara J. Maschak- Southwestern American Indian Cen- Deaconess Medical Center: George Black- Carey, MSN, CDE; Stanley Schwartz, ter, Phoenix, Arizona, and Shiprock, New burn, MD, PhD; Christos Mantzoros, MD, MD; Gary D. Foster, PhD; Robert I. Mexico: William C. Knowler, MD, DrPH; DSc; Kristina Day, RD; Ann McNamara, Berkowitz, MD; Henry Glick, PhD; Paula Bolin, RN, MC; Tina Killean, BS; RN. Shiriki K. Kumanyika, PhD, RD, MPH; Jonathan Krakoff, MD; Jeffrey M. Curtis, University of Colorado Health Sci- Johanna Brock; Helen Chomentowski; MD, MPH; Justin Glass, MD; Sara ences Center: James O. Hill, PhD; Marsha Vicki Clark; Canice Crerand, PhD; Michaels, MD; Peter H. Bennett, MB, Miller, MS, RD; JoAnn Phillipp, MS; Rob- Renee Davenport; Andrea Diamond, FRCP; Tina Morgan; Shandiin Begay, ert Schwartz, MD; Brent Van Dorsten, MS, RD; Anthony Fabricatore, PhD; MPH; Bernadita Fallis, RN, RHIT, CCS; PhD; Judith Regensteiner, PhD; Salma Louise Hesson, MSN; Stephanie Jeanette Hermes, MS, RD; Diane F. Hol- Benchekroun, MS; Ligia Coelho, BS; Pau- Krauthamer-Ewing, MPH; Robert Kueh- lowbreast; Ruby Johnson; Cathy Manus, lette Cohrs, RN, BSN; Elizabeth Daen- nel, PhD; Patricia Lipschutz, MSN; LPN; Maria Meacham, BSN, RN, CDE; inck, MS, RD; Amy Fields, MPH; Susan Monica Mullen, MS, RD; Leslie Julie Nelson, RD; Carol Percy, RN; Patri- Green; April Hamilton, BS, CCRC; Jere Womble, PhD, MS; Nayyar Iqbal, MD. cia Poorthunder; Sandra Sangster; Nancy Hamilton, BA; Eugene Leshchinskiy; Mi- University of Pittsburgh: David E. Scurlock, MSN, ANP-C, CDE; Leigh A. chael McDermott, MD; Lindsey Munk- Kelley, MD; Jacqueline Wesche- Shovestull, RD, CDE; Janelia Smiley; Ka- witz, BS; Loretta Rome, TRS; Kristin Thobaben, RN, BSN, CDE; Lewis Kuller, tie Toledo, MS, LPC; Christina Tomchee, Wallace, MPH; Terra Worley, BA. MD, DrPH; Andrea Kriska, PhD; Janet BA; Darryl Tonemah, PhD. Baylor College of Medicine: John P. Bonk, RN, MPH; Rebecca Danchenko, BS; University of Southern California: Foreyt, PhD; Rebecca S. Reeves, DrPH, Daniel Edmundowicz, MD; Mary L. Anne Peters, MD; Valerie Ruelas, MSW, RD; Henry Pownall, PhD; Ashok Balasu- Klem, PhD, MLIS; Monica E. Yamamoto, LCSW; Siran Ghazarian Sengardi, MD; bramanyam, MBBS; Peter Jones, MD; DrPH, RD, FADA; Barb Elnyczky, MA; Kathryn Graves, MPH, RD, CDE; Kati Michele Burrington, RD; Chu-Huang George A. Grove, MS; Pat Harper, MS, Konersman, MA, RD, CDE; Sara Seraﬁn- Chen, MD, PhD; Allyson Clark, RD; RD, LDN; Janet Krulia, RN, BSN, CDE; Dokhan. Molly Gee, MEd, RD; Sharon Griggs; Juliet Mancino, MS, RD, CDE, LDN; Anne Michelle Hamilton; Veronica Holley; Mathews, MS, RD, LDN; Tracey Y. Mur- Coordinating center Jayne Joseph, RD; Patricia Pace, RD: ray, BS; Joan R. Ritchea; Jennifer Rush, Wake Forest University: Mark A. Es- Julieta Palencia, RN; Olga Satterwhite, MPH; Karen Vujevich, RN-BC, MSN, peland, PhD; Judy L. Bahnson, BA; Lynne RD; Jennifer Schmidt; Devin Volding, CRNP; Donna Wolf, MS. Wagenknecht, DrPH; David Reboussin, LMSW; Carolyn White. The Miriam Hospital/Brown Medical PhD; W. Jack Rejeski, PhD; Alain Bertoni, University of California at Los Ange- School: Rena R. Wing, PhD; Renee Bright, MD, MPH; Wei Lang, PhD; Gary Miller, les School of Medicine: Mohammed F. MS; Vincent Pera, MD; John Jakicic, PhD; PhD; David Lefkowitz, MD; Patrick S. Saad, MD; Siran Ghazarian Sengardi, MD; Deborah Tate, PhD; Amy Gorin, PhD; Reynolds, MD; Paul Ribisl, PhD; Mara Vi- Ken C. Chiu, MD; Medhat Botrous; Mich- Kara Gallagher, PhD; Amy Bach, PhD; tolins, DrPH; Michael Booth, MBA; Kathy

DIABETES CARE, VOLUME 30, NUMBER 6, JUNE 2007 1381 Reduction in weight and CVD risk factors

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