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J. Michael Gonzalez-Campoy, MD, PhD, FACE1; Sachiko T. St. Jeor, PhD, RD2; Kristin Castorino, DO3; Ayesha Ebrahim, MD, FACE4; Dan Hurley, MD, FACE5; Lois Jovanovic, MD, MACE6; Jeffrey I. Mechanick, MD, FACP, FACN, FACE, ECNU7; Steven M. Petak, MD, JD, MACE, FCLM8; Yi-Hao Yu, MD, PhD, FACE9; Kristina A. Harris10; Penny Kris-Etherton, PhD, RD11; Robert Kushner, MD12; Maureen Molini-Blandford, MPH, RD13; Quang T. Nguyen, DO14; Raymond Plodkowski, MD15; David B. Sarwer, PhD16; Karmella T. Thomas, RD17

Sarah L. Booth, Ph.D., Vitamin K Laboratory, Jean Mayer USDAHuman Nutrition Research Center on Aging at Tufts University, Boston, MA; James F. Sallis, Ph.D., F.A.C.S.M., Department ofPsychology, San Diego State University, San Diego, CA; Cheryl Ritenbaugh, Ph.D., M.P.H., Kaiser Permanente Center for Health Research, Portland, O R James 0. Hill, Ph.D., Center for Human Nutrition, University of Colorado Health Sciences Center, Denver, CO; Leann L. Birch, Ph.D., Department ofHuman Development and Family Studies, Pennsylvania State University, University Park, PA; Lawrence D. Frank, Ph.D., College OfArchitecture, Georgia Institute of Technology, Atlanta, GA; Karen Glanz, Ph.D., M.P.H., Cancer Research Center of Hawaii, University of Hawaii, Honolulu, HI; David A. Himmelgreen, Ph.D., Department ofAnthropology, University of South Florida, Tampa, FL; Michael Mudd, Corporate Affairs, Kraft Foods, Inc., Northfield, IL; Barry M. Popkin, Ph.D., Department ofNutrition, Carolina Population Center, University of North Carolina, Chapel Hill, NC; Karyl A. Rickard, Ph.D., R.D., C.S.P., F.A.D.A., Nutrition and Dietetics Program, School ofAllied Health Sciences, Indiana University School of Medicine, Indianapolis, IN; Sachiko St. Jeor, Ph.D., R.D., Nutrition Education and Research Program, University of Nevada School of Medicine, Reno, W, Nicholas P. Hays, M.S., Energy Metabolism Laboratory, Jean Mayer USDA Human Nutrition Research Center on Aging at Tufts University, Boston, MA.

Background: Bupropion and naltrexone are centrally active drugs that have shown potential efficacy – alone and in combination – for the treatment of obesity. Objective: To explore the efficacy and safety of naltrexone and bupropion alone and in a novel combination drug that utilizes sustained-release (SR) formulations of both drugs and to evaluate their efficacy in promoting weight loss. The mechanisms of action of these centrally acting drugs are discussed. Preclinical and clinical studies of bupropion and naltrexone alone and in combination are reviewed. Results/conclusions: Both bupropion and naltrexone have been shown individually to induce weight loss. Bupropion has greater efficacy as monotherapy. Naltrexone SR potentiates the effects of bupropion SR; thus, this synergistic combination has the potential for additional weight loss compared to monotherapy. Current Phase III trials will yield further safety and efficacy information regarding these drugs in combination.

This review provides current strategies for weight management in the elderly population as it can be different from young adults due to multiple factors: co-morbidities, polypharmacy, limitation of functional activities, social issues.The recommendations for weight management for all age groups include exercise, diet, pharmacotherapy and surgery. In the elderly population, because of changes in age-related body composition, reduced energy requirement and expenditure, the standard young adult recommendations cannot be applied directly. The goal of weight management in the elderly differs from the young adult. The preferred method is maintenance of weight rather than aggressive weight loss with achieving a healthy, functional, and good quality of life.The growing prevalence of obesity in the elderly population is becoming a major health problem and can affect functional status, can contribute to frailty and decline in activity, as well as worsening co-morbid medical problems. Practical recommendations for weight management in the elderly are challenging because of the obesity paradox in the elderly, and the lack of substantial research in this population. Individualized recommendations should be considered for elderly patients with a focus on the underlying medical problems, functional status and living environments.

Purpose To compare energy intake derived from a food frequency questionnaire (FFQ) with estimated energy expenditure in postmenopausal women participating in a large clinical study. Methods A total of 161,856 women aged 50 to 79 years enrolled in the Women's Health Initiative (WHI) Observational Study (OS) or Clinical Trial (CT) [including the Diet Modification (DM) component] completed the WHI FFQ, from which energy intake (FFQEI) was derived. Population-adjusted total energy expenditure (PATEE) was calculated according to the Harris-Benedict equation weighted by caloric intakes derived from the National Health and Nutrition Examination Survey. Stepwise regression was used to examine the influence of independent variables (e.g., demographic, anthropometric) on FFQEI-PATEE. Race, region, and education were forced into the model; other variables were retained if they increased model explanatory ability by more than 1%. Results On average, FFQEI was approximately 25% lower than PATEE. Regression results (intercept = −799 kcal/d) indicated that body mass index (b = −23 kcal/day/kg·m −2 ); age (b = 15 kcal/day/year of age); and study arm (relative to women in the OS, for DM women b = 169 kcal/d, indicating better agreement with PATEE) increased model partial R 2 > .01. Results for CT women not eligible for DM were similar to those of women in the OS (b = 14 kcal/d). There also were apparent differences by race (b = −152 kcal/d in Blacks) and education (b = −67 kcal/d in women with Conclusion This large, carefully studied population confirms previous observations regarding underestimates in self-reported caloric intake relative to estimates of metabolic need in younger women, and those with higher weight, with less education, and in Blacks. These differences, along with effects related to intervention assignment, underline the need for additional research to enhance understanding of errors in dietary measurement.

Objective: To evaluate the effectiveness of meal replacements (MRs) in weight loss interventions in premenopausal women. Research Methods and Procedures: Overweight premenopausal women (n = 113; body mass index: 25 to 35 kg/m2; 30 to 50 years old) were randomized into three interventions: group A, a dietitian-led intervention; group B, a dietitian-led intervention incorporating MRs; and group C, a clinical office-based intervention incorporating MRs. In year 1, groups A and B attended 26 group sessions, whereas group C received the same educational materials during 26 10-minute office visits with a physician–nurse team. In year 2, participants attended monthly group seminars and drop-in visits with a dietitian. Results: For the 74 subjects completing year 1, weight loss in the office-based group C was as effective as the traditional dietitian-led group A (4.3 ± 6.5% vs. 4.1 ± 6.4%), while group B maintained a significantly greater weight loss (9.1 ± 8.9%; p < 0.02; mean ± SD). For the 43 subjects completing year 2, group B showed significant differences in the percentage of weight loss (−8.5 ± 7.0%) compared with group A (−1.5 ± 5.0%) and group C (−3.0 ± 7.0%; p < 0.001). Discussion: Study results showed that a traditional weight loss intervention incorporating MRs was effective as a weight loss tool in the medical office practice and in the dietitian-led group setting.

High-protein diets have recently been proposed as a “new” strategy for successful weight loss. However, variations of these diets have been popular since the 1960s. High-protein diets typically offer wide latitude in protein food choices, are restrictive in other food choices (mainly carbohydrates), and provide structured eating plans. They also often promote misconceptions about carbohydrates, insulin resistance, ketosis, and fat burning as mechanisms of action for weight loss. Although these diets may not be harmful for most healthy people for a short period of time, there are no long-term scientific studies to support their overall efficacy and safety. These diets are generally associated with higher intakes of total fat, saturated fat, and cholesterol because the protein is provided mainly by animal sources. In high-protein diets, weight loss is initially high due to fluid loss related to reduced carbohydrate intake, overall caloric restriction, and ketosis-induced appetite suppression. Beneficial effects on blood lipids and insulin resistance are due to the weight loss, not to the change in caloric composition. Promoters of high-protein diets promise successful results by encouraging high-protein food choices that are usually restricted in other diets, thus providing initial palatability, an attractive alternative to other weight-reduction diets that have not worked for a variety of reasons for most individuals. High-protein diets are not recommended because they restrict healthful foods that provide essential nutrients and do not provide the variety of foods needed to adequately meet nutritional needs. Individuals who follow these diets are therefore at risk for compromised vitamin and mineral intake, as well as potential cardiac, renal, bone, and liver abnormalities overall.

This document presents guidelines for reducing the risk of cardiovascular disease by dietary and other lifestyle practices. Since the previous publication of these guidelines by the American Heart Association,1 the overall approach has been modified to emphasize their relation to specific goals that the AHA considers of greatest importance for lowering the risk of heart disease and stroke. The revised guidelines place increased emphasis on foods and an overall eating pattern and the need for all Americans to achieve and maintain a healthy body weight (Table⇓). View this table: Table 1. Summary of Dietary Guidelines The major guidelines are designed for the general population and collectively replace the “Step 1” designation used for earlier AHA population-wide dietary recommendations. More individualized approaches involving medical nutrition therapy for specific subgroups (for example, those with lipid disorders, diabetes, and preexisting cardiovascular disease) replace the previous “Step 2” diet for higher-risk individuals. The major emphasis for weight management should be on avoidance of excess total energy intake and a regular pattern of physical activity. Fat intake of ≤30% of total energy is recommended to assist in limiting consumption of total energy as well as saturated fat. The guidelines continue to advocate a population-wide limitation of dietary saturated fat to

Increasing awareness of the relationship between diet and disease has prompted a notable increase in nutrition research. The focus of many of these studies continues to be on amount and type of fat in the diet. At the same time, a great deal of attention is being directed at other dietary components and their mode of action. The results are promising. More definitive answers must await future clinical trial data. However, the total dietary approach, including compliance measures, remains the foundation on which other nutrition recommendations should be based.

Why are some individuals more vulnerable to persistent weight gain and obesity than are others? Some obese individuals report factors that drive overeating, including lack of control, lack of satiation, and preoccupation with food, which may stem from reward-related neural circuitry. These are normative and common symptoms and not the sole focus of any existing measures. Many eating scales capture these common behaviors, but are confounded with aspects of dysregulated eating such as binge eating or emotional overeating. Across five studies, we developed items that capture this rewardbased eating drive (RED). Study 1 developed the items in lean to obese individuals (n = 327) and examined changes in weight over eight years. In Study 2, the scale was further developed and expert raters evaluated the set of items. Study 3 tested psychometric properties of the final 9 items in 400 participants. Study 4 examined psychometric properties and race invariance (n = 80 women). Study 5 examined psychometric properties and age/gender invariance (n = 381). Results showed that RED scores correlated with BMI and predicted earlier onset of obesity, greater weight fluctuations, and greater overall weight gain over eight years. Expert ratings of RED scale items indicated that the items reflected characteristics of reward-based eating. The RED scale evidenced high internal consistency and invariance across demographic factors. The RED scale, designed to tap vulnerability to reward-based eating behavior, appears to be a useful brief tool for identifying those at higher risk of weight gain over time. Given the heterogeneity of obesity, unique brief profiling of the reward-based aspect of obesity using a self-report instrument such as the RED scale may be critical for customizing effective treatments in the general population. © 2014 Epel et al.

Objectives To study natural weight changes and to develop a weight classification system that can identify weight maintainers, gainers, and losers. Design/outcome A prospective, observational study in which weight changes over five annual measurements were evaluated. In the weight classification system used, changes greater than 5lb defined weight maintenance, gain, or loss. Subjects/settings Subjects were healthy, normal-weight and overweight, men and women (mean age=44.1+14.1 years) in the Relationships of Energy, Nutrition, and Obesity to Cardiovascular Disease Risk Study. Prospective data for 385 of the original 508 subjects for whom actual weights were available for each of the 5 years (1985 to 1990) were used to classify and characterize subjects by weight-change categories. Statistical analyses Cross-tabulations (with χ 2 tests) and hierarchical log-linear analyses (with partial χ 2 tests) to examine the relationships of categorical variables; analyses of variance (with F tests) for continuous measures. Results Over the 4-year interval, 46% of subjects were classified as maintainers, 34% as gainers, and 20% as losers. Over shorter 1-year epochs, more subjects were maintainers (62%) and fewer subjects were gainers (22%) or losers (16%). Maintainers had fewer and smaller magnitudes of weight fluctuations and showed fewer deleterious changes in health risk factors than gainers. Applications Weight changes of greater than ±5lb can classify a person as a weight maintainer, gainer, or loser. Although annual weight changes were used in this study, a weight change of more than 5lb between any two points in time may suggest nonmaintenance of weight or weight instability that needs further evaluation.

Weight management plays a central role in preventing many diseases that affect women. Lifelong hormonal, psychological, and environmental influences on women elicit a set of behavioral and biological responses distinctive from men that place them at increased risk for overall weight concerns, weight gain, and obesity. Limitations of current treatment call for increased research to improve our understanding and guide efforts in this important aspect of women's health. Research needs to be conducted to define realistic and obtainable weight goals and to design educational strategies to promote health and self-esteem. Research in the field of weight management should be directed to understanding gender differences, etiologies, and effective treatments.

A predictive equation for resting energy expenditure (REE) was derived from data from 498 healthy subjects, including females (n = 247) and males (n = 251), aged 19-78 y (45 +/- 14 y, mean +/- SD). Normal-weight (n = 264) and obese (n = 234) individuals were studied and REE was measured by indirect calorimetry. Multiple-regression analyses were employed to drive relationships between REE and weight, height, and age for both men and women (R2 = 0.71): REE = 9.99 x weight + 6.25 x height - 4.92 x age + 166 x sex (males, 1; females, 0) - 161. Simplification of this formula and separation by sex did not affect its predictive value: REE (males) = 10 x weight (kg) + 6.25 x height (cm) - 5 x age (y) + 5; REE (females) = 10 x weight (kg) + 6.25 x height (cm) - 5 x age (y) - 161. The inclusion of relative body weight and body-weight distribution did not significantly improve the predictive value of these equations. The Harris-Benedict Equations derived in 1919 overestimated measured REE by 5% (p less than 0.01). Fat-free mass (FFM) was the best single predictor of REE (R2 = 0.64): REE = 19.7 x FFM + 413. Weight also was closely correlated with REE (R2 = 0.56): REE = 15.1 x weight + 371.

Background: A school-wide nutrition program was established in 1982 and a required medical nutrition course (MNC) was established in 1985 at the University of Nevada School of Medicine. Emphasis was placed on developing an integrated curriculum and on using innovative methods to incorporate nutrition into the existing curriculum. Objective: The objective of this review was to establish a baseline and make positive curricular changes to comply with the recommendations of the Liaison Committee on Medical Education for accreditation. The MNC and the nutrition curriculum were evaluated as part of this 3-y comprehensive, school-wide evaluation process. Design: The MNC was invited for review (December 2004) because of its position in the curriculum (first year), special content and methods, and relation to other courses. A review team, which consisted of the Assistant Dean for Medical Education (who chaired the team), a curriculum coordinator, faculty representatives, and a medical student, was appointed. The MNC coordinator prepared a review book that included the requested documentation. The initial 3-h review meeting culminated in a formal evaluation and recommendations. Follow-up meetings at 1 mo and 1 y were scheduled. Results: The review was a positive process that reaffirmed the uniqueness of the nutrition program at the University. It supported the MNC as an important part of the required curriculum. Recommendations included use of the Web, encouragement to identify new opportunities with interested faculty, and a structure to further integrate and align nutrition into existing courses. Conclusions: A positive, proactive review process supports the importance of nutrition in the medical school curriculum and encourages further integration.

Since its release in 1992, the Food Guide Pyramid has become one of the most recognized nutrition education tools in US history. As such, it has been subject to criticism, particularly in several recent media reports that implicate it as the culprit in America's current obesity epidemic. What these reports often overlook, however, is that the diets of many Americans do not adhere to the dietary guidelines illustrated by the Pyramid, refuting the notion that the Pyramid is the cause of the nation's obesity problem. Data indicate that the more likely causes of escalating obesity rates are increased per capita caloric consumption and larger portion sizes, along with a lack of adequate physical activity. Although the Pyramid graphic was designed more than a decade ago, it still communicates three key concepts that continue to be the cornerstone of federal dietary guidance: variety, proportionality, and moderation. As such, it remains a viable and relevant nutrition education tool, especially when used by dietetics professionals as a component of individualized, comprehensive nutrition education and behavior modification interventions. As the United States Department of Agriculture begins to investigate whether the food intake patterns illustrated by the Pyramid are in need of updating, research is urgently needed to determine how nutrition education tools, including the Pyramid, can be most effectively implemented to help consumers adopt healthful eating behaviors and to improve the public health of America.

Most physicians do not have the benefit of in-house registered dietitians to facilitate patient evaluation and create treatment plans. Fortunately, with the new tools that are available to physicians and patients, energy balance can be evaluated. Then, a balanced deficit diet can be encouraged to achieve a weight management goal while maintaining healthy food intake patterns. Patients should also be counseled regarding weight maintenance diets to prevent weight gain. A low-fat diet is preferred because the patient will benefit from improved cardiac risk as a result of weight loss and a restricted saturated fat content is healthier. Other diets and approaches are acceptable if they are hypocaloric and do not negatively impact the patient's health (eg, some high-protein, high-fat diets can increase lipid levels; high-carbohydrate diets can increase triglycerides in patients who have type 2 diabetes). As patients lose weight, further increases in physical activity and exercise should be emphasized to help maintain lost weight. It is also helpful from a behavioral perspective to encourage patients to monitor their weight, food intake, and physical activity. Medical offices can support patients by providing weekly or biweekly weigh-ins to track progress and provide ongoing feedback. Patients should be reminded that the ultimate goal of any weight management program is gradual, incremental weight losses that are maintained over time. Sustainable and enjoyable changes in eating practices and physical activity patterns must be made along with a lifelong commitment to health.

Background: Evidence suggests substantial comorbidity between symptoms of somatization and depression in clinical as well as nonclinical populations. However, as most existing research has been retrospective or cross-sectional in design, very little is known about the specific nature of this relationship. In particular, it is unclear whether somatic complaints may heighten the risk for the subsequent development of depressive symptoms. Methods: We report findings on the link between symptoms of somatization (assessed using the SCL-90-R) and depression 5 years later (assessed using the CES-D) in an initially healthy cohort of community adults, based on prospective data from the RENO Diet-Heart Study. Results: Gender-stratified multiple regression analyses revealed that baseline CES-D scores were the best predictors of subsequent depressive symptoms for men and women. Baseline scores on the SCL-90-R somatization subscale significantly predicted subsequent self-reported symptoms of depressed mood 5 years later, but only in women. However, somatic complaints were a somewhat less powerful predictor than income and age. Conclusions: Our findings suggest that somatic complaints may represent one, but not necessarily the most important, risk factor for the subsequent development of depressive symptoms in women in nonclinical populations. The results also highlight the importance of including social variables in studies on women’s depression as well as conducting additional research to further examine predictors of depressive symptoms in men.

This study investigated whether symptoms of depression and anxiety were related to the development of elevated blood pressure in initially normotensive adults. The study's hypothesis was addressed with an existing set of prospective data gathered from an age-, sex-, and weight-stratified sample of 508 adults. Four years of follow-up data were analyzed both with logistic analysis, which used hypertension (blood pressure > or =140 mm Hg systolic or 90 mm Hg diastolic) as the dependent variable, and with multiple regression analysis, which used change in blood pressure as the dependent variable. Five physical risk factors for hypertension (age, sex, baseline body mass index, family history of hypertension, and baseline blood pressure levels) were controlled for in the regression analyses. Use of antidepressant/antianxiety and antihypertensive medications were controlled for in the study. Of the 433 normotensive participants who were eligible for our study, 15% had missing data in the logistic regression analysis focusing on depression (n = 371); similarly, 15% of the eligible sample had missing data in the logistic regression using anxiety as the psychological variable of interest (n = 370). Both logistic regression analyses showed no significant relationship for either depression or anxiety in the development of hypertension. The multiple regression analyses (n = 369 for the depression analysis; n = 361 for the anxiety analysis) similarly showed no relationship between either depression or anxiety in changes in blood pressure during the 4-year follow-up. Thus, our results do not support the role of depressive or anxiety symptoms in the development of hypertension in our sample of initially normotensive adults.

Purpose.To examine compliance with the guideline for dietary fat (i.e., 30% of total daily calories) and covariates of fat intake in a cohort of adults using both 24-hour recall and food frequency questionnaire (FFQ).Design.Prospective, observational cohort study over 5 years.Setting.Community-based sample in Reno, Nevada.Subjects.Equal numbers of male and female, lean and overweight adults (n = 508), recruited from 1985 to 1986, of whom 348 completed all relevant surveys.Measures.Subjects underwent repeated anthropometric measures and completed extensive surveys on diet, weight cycling, lifestyle, and physical activity.Results.Mean fat intake by 24-hour recall declined from 36.9% to 33.6% of calories between years 1 and 5 (p < .001), while calorie intake increased (p = .2). As measured by FFQ at year 2, mean fat intake was 39.1 % of calories, and only 11.8% of subjects were in compliance with the guideline for dietary fat intake. Fat intake by FFQ at year 2 was statistically higher than by 24-hour recall in year 1 for lean women (p = .02) and lean men (p = .02), but not for the overweight of either gender, and was significantly higher than the year 5 24-hour recall for all categories of gender and weight (p < .001). Calorie intake, gender, and body mass index were significant in regression models that explained less than 10% of total variability in fat intake (r2= .08; p < .01).Conclusions.Compliance with the nationally recommended level of dietary fat intake was poor in this cohort, especially as measured by FFQ. Variability in fat intake was largely unexplained by host characteristics, including education. Further study is required to corroborate secular trends in population fat intake, elucidate the determinants of such intake, and identify cost-effective strategies for reducing the consumption of dietary fat.

OVERVIEW The Expert Panel on Healthy Weight was faced with an extraordinary challenge: to arrive at a consensus on what is a healthy weight, which in and of itself is an elusive term. However, the opportunity to tackle a health problem that confronts the medical community every day helped motivate the panel to arrive at reasonable and responsible recommendations. To initiate discussion, two key questions were posed from which a public health recommendation for healthy weight could be derived: 1) What should the target be for healthy weight? and 2) How much weight loss is enough to reduce disease risk? Concern regarding the definition of a healthy weight and its application was widely expressed. Additionally, the concept of guidelines and the broad applications to individuals and population groups raised further debate. Ranges are often cxpressed to reflect a statistically derived best weight associated with the least mortality, morbidity, and disease onset. How these guidelines are interpreted in the health care setting, particularly for those individuals falling outside the range, were

To characterize people who maintain weight over long periods of time, normal weight and obese adults (n = 385) were studied over five annual visits. Subjects were classified using a +/- 5 lb change between the first and the fifth year visits to determine overall maintenance (M), with gain (G) or loss (L) being any change outside this range. This MGL status was cross-tabulated with a Fluctuation Index which counted the number of successive year-to-year weight changes of more than +/- 5 lbs (F0 through F4). True maintainers were defined as those having all weight changes within +/- 5 lbs during the 5-year period (M and F0). Nineteen percent (n = 73) of the subjects were classified as True Maintainers and included three times as many normal weight as obese subjects. Obese subjects comprised only 25% of the True Maintainer group but 60% of the Non-Maintainer group. Age had no association with Maintainer status. Standard measures of weight variability were lowest among True Maintainers and highest in Non-Maintainers. In addition, True Maintainers had lower BMI, Percent Body Fat, and Waist-Hip Ratios than Non-Maintainers. Subjects classified as Non-Maintainers were more likely to engage in dieting, by a variety of measures, than True Maintainers--this was particularly true among obese subjects. Finally, changes in total cholesterol, LDL and HDL cholesterol, and systolic and diastolic blood pressure were not reliably associated with Maintainer status, although the ordering of the group means suggested that True Maintainers had slightly healthier levels of "risk" variables. Overall, the results suggest that True Maintainers comprise a potentially important and interesting group of individuals who need further study.

Background Lifestyle changes involving diet, behavior, and physical activity are the cornerstone of successful weight control. Incorporating meal replacements (1-2 per day) into traditional lifestyle interventions may offer an additional strategy for overweight patients in the primary care setting. Methods One hundred thirteen overweight premenopausal women (mean ± SD age, 40.4 ± 5.5 years; weight, 82 ± 10 kg; and body mass index, 30 ± 3 kg/m 2 ) participated in a 1-year weight-reduction study consisting of 26 sessions. The women were randomly assigned to 3 different traditional lifestyle-based groups: (1) dietitian-led group intervention (1 hour per session), (2) dietitian-led group intervention incorporating meal replacements (1 hour per session), or (3) primary care office intervention incorporating meal replacements with individual physician and nurse visits (10-15 minutes per visit). Results For the 74 subjects (65%) completing 1 year, the primary care office intervention using meal replacements was as effective as the traditional dietitian-led group intervention not using meal replacements (mean ± SD weight loss, 4.3% ± 6.5% vs 4.1% ± 6.4%, respectively). Comparison of the dietitian-led groups showed that women using meal replacements maintained a significantly greater weight loss (9.1% ± 8.9% vs 4.1% ± 6.4%) ( P = .03). Analysis across groups showed that weight loss of 5% to 10% was associated with significant ( P = .01) reduction in percentage of body fat, body mass index, waist circumference, resting energy expenditure, insulin level, total cholesterol level, and low-density lipoprotein cholesterol level. Weight loss of 10% or greater was associated with additional significant ( P = .05) improvements in blood pressure and triglyceride level. Conclusions A traditional lifestyle intervention using meal replacements can be effective for weight control and reduction in risk of chronic disease in the physician's office setting as well as in the dietitian-led group setting.

The gastric inhibitory polypeptide (GIP) response to certain stimuli may be exaggerated in patients with obesity and noninsulin-dependent diabetes mellitus. To explore the effects of increased caloric intake and dietary composition on GIP secretion, 20 normal lean volunteers underwent a 4-week ambulatory study. A baseline week (usual diet) was followed by 3 weeks in which the usual diet was supplemented with 45 g fat (diet A), 100 g carbohydrate in the form of sucrose (diet B), or 50 g protein (diet C) for 1 week each. Almost equal numbers of subjects followed sequence ABC, BCA, or CAB in this cross-over study. At the end of the baseline week and each study week, serum glucose, insulin, and GIP were measured in response to a 500-cal liquid test meal. Daily intake of carbohydrate, protein, or fat, as monitored by food records, increased significantly (P less than 0.01) during the appropriate dietary periods, whereas body weight changed slightly, but not significantly, during the 3 study periods. No changes occurred in the total integrated serum glucose concentrations, whereas integrated insulin concentrations changed significantly (P less than 0.05), being 32.5 +/- 3.1 (+/- SEM), 37.2 +/- 4.0, and 30.3 +/- 3.1 microU/ml min-1 during periods A, B, and C, respectively. Insulin secretion was greatest during period B, the carbohydrate week, when insulin concentrations 15-60 min after the test meal were significantly greater (P less than 0.05 to P less than 0.01) than after the baseline period. Total integrated incremental serum GIP concentrations were also significantly different (P less than 0.01) during the 3 study periods, being 1.93 +/- 0.13, 2.53 +/- 0.24, and 1.90 +/- 0.11 ng/ml min-1 during A, B, and C, respectively. Serum GIP was highest during period B (carbohydrate), when average concentrations were significantly higher (P less than 0.01) 15-60 min after the meal compared to those during the baseline study. Similar changes did not occur with the other diets. Thus, GIP and insulin secretion were substantially altered by an acute increase in sucrose intake. The exaggerated GIP response to a meal in some patients with obesity may possibly be the result of adaptation of intestinal GIP cells to diet, particularly one rich in sucrose.