What's a carb? Minerals for weight management over time for study Meal planning for couples. Chldrens and Mattes [ Glyceemic Glycemic load and childrens health loas no significant difference in food Glycmic between persons consuming low and high GI foods. Five-week, low—glycemic index diet decreases total fat mass and improves plasma lipid profile in moderately overweight nondiabetic men. For example, fried foods tend to contain a high amount of fat, which can slow the absorption of sugar in the bloodstream and decrease the GI 11 There was a 3 days of gap before the intervention was repeated.

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Why Glycemic Load Matters More Than Glycemic Index

Glycemic load and childrens health -

Written materials included topic modules, food choice lists, and a select-a-meal menu. The topic modules were the primary mechanism for presenting nutrition intervention messages and facilitating self-assessment, goal setting, and problem solving.

These modules were designed to promote dialogue between the patient and study dietitian. Food choice lists were used to enhance practical application of intervention messages presented in the topic modules. For the experimental group, lists corresponded to food groups delineated by a reduced-GL food pyramid.

One topic module was devoted to physical activity, with subjects in both groups receiving information based on current recommendations. The treatment process was evaluated from the perspectives of interventionist adherence to nutrition education and counseling protocols, and subject participation and adherence to diet prescriptions.

Interventionist adherence may be conceptualized as treatment fidelity, a term encompassing integrity and differentiation. Several strategies were used to maximize treatment fidelity in the present study.

First, written materials for the experimental and conventional groups were developed specifically for the pilot study such that the format and quality were completely parallel. The materials differed only with regard to the specific intervention messages pertaining to GL and dietary fat.

Second, the interventionist was a dietitian M. trained in the science underlying each intervention and given precise instructions regarding use of written materials to ensure differentiation of the intervention messages.

Third, to prevent shifts in implementation, the dietitian completed a tracking form and progress note immediately after each session.

The project director C. met with the study dietitian on a regular basis to review tracking forms and progress notes and to discuss treatment of individual subjects.

Subject participation was evaluated on the basis of session attendance, and adherence was assessed by means of self-report of dietary intake. All subjects received extensive instruction and practice in keeping food diaries. Three-dimensional food models, plates, bowls, glasses, and measuring cups and spoons were used to educate them regarding accurate appraisal of portion sizes.

The diaries were reviewed with the subject at the time of receipt to obtain clarification, as necessary, on recorded foods and beverages. Food Processor Plus software Version 7. The GI of individual foods was assigned according to published values.

Data from 7-day food diaries were used to evaluate process outcomes at baseline, during the intervention period months 3 and 6 , and at the end of the follow-up month In addition, self-monitoring of food intake was encouraged throughout the intervention period to enhance self-control and facilitate problem solving.

The study dietitian reviewed self-reported intake after each individual counseling session to identify deviations from diet prescriptions and made corrective recommendations to the subject when necessary.

Total body mass and fat mass were measured by dual-energy x-ray absorptiometry using Hologic instrumentation Model QDR ; Hologic, Inc, Bedford, Mass. Height was measured using a wall-mounted stadiometer Holtain Limited, Crymych, Wales.

Plasma glucose level was measured using a Hitachi analyzer Model ; Roche Diagnostics, Indianapolis, Ind , and serum insulin level was measured using an Elecsys system Model ; Roche Diagnostics.

We conducted statistical analyses using SAS software Release 8. Repeated-measures analysis of variance was performed using the mixed linear model procedure. Component contrasts were estimated from the fitted model for preplanned comparisons within treatment group changes over time and differences between groups for changes over time.

The time intervals of interest were 0 to 6 months and 0 to 12 months. Change in insulin resistance was adjusted for change in BMI. Results are presented as mean ± SEM.

We conducted simple linear regression using the general linear models procedure , pooling data from both groups, to explore whether changes in dietary GL or fat intake average of values obtained at 3 and 6 months independently predicted change in body fat. When exploring relationships between dietary variables and body fat, we eliminated 1 outlier from regression analyses, although data from this outlier are displayed.

The outlier was a young woman who matriculated in medical school during participation in the study. On the basis of previous research, we speculated that apparent underestimation of dietary intake by this subject may be attributed, in part, to expression of a social desirability bias.

Fourteen subjects finished the study 7 per group , yielding a completion rate of There were no group differences in session attendance, with subjects in the experimental and conventional groups completing 9. All 14 subjects attended the 2 scheduled sessions during the follow-up. At baseline, we found no differences between the experimental and conventional groups for age However, fat mass was lower for the experimental group compared with the conventional group Changes in dietary variables are presented in the Table 1.

Of interest, there was no weight regain between 6 and 12 months for the experimental group. Changes over time for study outcomes. Figure 3 depicts results of bivariate linear regression analysis, using dietary GL or fat intake during the intervention period as the independent variable and change in body fat from 0 to 6 months as the dependent variable.

Changes in dietary glycemic load GL or fat intake as predictors of change in body fat. Black circles indicate subjects in the experimental group; white circles, subjects in the conventional group.

Treatment of obesity in adolescents is characterized by modest weight loss and substantial relapse. In this pilot study, we investigated the independent effects of an experimental reduced-GL diet vs a conventional reduced-fat diet, using similar behavioral strategies, physical activity prescriptions, and treatment intensity in both groups.

Although both groups showed the intended changes in targeted dietary factors, measures of adiposity decreased significantly more in the reduced-GL group. This result is of particular interest, in that the reduced-GL diet was prescribed in an ad libitum fashion, whereas the reduced-fat diet was energy restricted, consistent with conventional practices.

The potential flexibility of such a diet may have particular behavioral benefits for adolescents who have a strong desire for autonomy. In a previous study, children with type 1 diabetes mellitus were more easily able to select their own foods when prescribed a low-GI diet compared with a regimented meal plan based on an exchange system without consideration for GI.

At the end of the study, children expressed an overall preference for the low-GI diet compared with the regimented plan.

We also examined insulin resistance, as prevention of type 2 diabetes mellitus is a primary goal of obesity treatment in adolescents. In contrast, insulin resistance did not change in the reduced-GL group.

Moreover, the group effect remained significant after adjustment for change in BMI. These findings are consistent with epidemiological data 11 , 20 that show lower risk for diabetes among individuals consuming a low-GL diet, after controlling for BMI. Thus, reducing dietary GL may protect against diabetes through weight-dependent and weight-independent mechanisms, as previously hypothesized.

Adherence to diet prescriptions, regardless of group assignment, was likely affected by intrapersonal, interpersonal, and environmental influences.

Although most participating parents were well intentioned, not all provided adequate support with regard to provision of recommended foods, transportation to counseling sessions, and encouragement. Adolescents who participated in the pilot study often enjoyed socializing with peers at food courts and fast-food restaurants, where they were challenged to make reduced-GL or reduced-fat food choices.

Research is needed to develop novel strategies for motivating obese adolescents to change their eating behaviors and for motivating parents to provide appropriate support in environments that pose challenges to adherence.

Several issues pertaining to study design should be noted. Strengths of the study include careful attention to treatment fidelity, a well-defined conceptual framework to promote behavior change, a relatively long follow-up, and high subject retention. Study limitations include a small sample size and reliance on self-report for dietary assessment.

Underreporting of energy intake is a recognized source of measurement error when assessing adolescent diets. Furthermore, we cannot definitely attribute treatment effects exclusively to changes in GL, as other dietary factors such as fiber or palatability may mediate or confound the relationship between changes in GL and changes in adiposity to some degree an issue in all long-term outpatient dietary studies.

Our results suggest that reducing dietary GL may have greater benefits than reducing dietary fat when treating adolescent obesity to lower the risk for type 2 diabetes mellitus.

Although findings must be considered preliminary, this study provides relevant pilot data to inform future research. Large-scale randomized controlled trials are needed to evaluate the effectiveness and public health applications of reduced-GL and -GI diets.

Corresponding author: David S. Ludwig, MD, PhD, Division of Endocrinology, Longwood Ave, Children's Hospital Boston, Boston, MA e-mail: david. ludwig tch. This study was supported by grants 1R01DK and 1K01DK, from the National Insitute of Diabetes and Digestive Kidney Diseases Bethesda, Md ; the Charles H.

Hood Foundation Boston, Mass ; pilot and feasibility project grant DK from the Boston Obesity and Nutrition Research Center Boston ; and grant M01 RR awarded by the National Institutes of Health Bethesda to support the General Clinical Research Center at Children's Hospital Boston, Boston.

We thank Janet Washington, MPH, RD, for her contribution to intervention development; Suzanne Muggeo and Eve Callahan, MS, RD, for performing the dual-energy x-ray absorptiometry scans; Catherine Murphy, RN, and Linda Lynch, RN, for help with patient care; and Irena Clark, MHP, Erica Garcia-Lago, and Gina Masse for technical assistance.

Adolescent obesity increases the risk for a wide range of serious complications, including type 2 diabetes mellitus. Given the current obesity epidemic, novel treatment strategies are needed urgently. No previous studies have evaluated the effects of diet composition per se on treatment outcomes in obese adolescents.

The results of this study indicate that a reduced-GL diet may yield greater benefits than a conventional reduced-fat diet.

These pilot data, derived from a relatively long-term intervention study, provide strong rationale for conducting large-scale randomized controlled trials to evaluate the effectiveness of a reduced-GL diet in the treatment of obesity and prevention of diabetes mellitus.

This line of investigation has the potential to change clinical practice and public health guidelines. Ebbeling CB , Leidig MM , Sinclair KB , Hangen JP , Ludwig DS.

A Reduced—Glycemic Load Diet in the Treatment of Adolescent Obesity. Arch Pediatr Adolesc Med. Artificial Intelligence Resource Center. Select Your Interests Customize your JAMA Network experience by selecting one or more topics from the list below.

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August Cara B. Ebbeling, PhD ; Michael M. Leidig, RD ; Kelly B. Sinclair, MS, RD ; et al Jan P. Hangen, MS, RD ; David S. Ludwig, MD, PhD. Author Affiliations Article Information From the Division of Endocrinology Drs Ebbeling and Ludwig, Mr Leidig, and Ms Sinclair , Department of Medicine Drs Ebbeling and Ludwig, Mr Leidig, and Mss Sinclair and Hangen , and the Optimal Weight for Life Program Mss Sinclair and Hangen and Dr Ludwig , Children's Hospital Boston, and the Department of Pediatrics Drs Ebbeling and Ludwig , Harvard Medical School, Boston, Mass.

visual abstract icon Visual Abstract. Overview of study design. View Large Download. Trial design. GL indicates glycemic load. Diet prescriptions. Nutrition education and behavioral therapy. Process evaluation. Assessment of study outcomes. Statistical methods. Process data and baseline characteristics.

Study outcomes. Dietary variables as predictors of change in body fat. What This Study Adds. Fagot-Campagna APettitt DJEngelgau MM et al. Type 2 diabetes among North American children and adolescents: an epidemiologic review and a public health perspective.

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Foods and drinks provide our body with energy in the form of carbohydrates, Red pepper jerkyprotein and alcohol. Cgildrens with carbohydrates include bread, heaoth cereals, Meal planning for couples, pasta xnd, legumes, Meal planning for couples, potato, fruitmilk hralth, yoghurtsugarbiscuits, cakes and lollies. The digestive system breaks down carbohydrates in foods and drinks into simple sugars, mainly glucose. For example, both rice and soft drink will be broken down to simple sugars in your digestive system. The pancreas secretes a hormone called insulin, which helps the glucose to move from your blood into the cells. Our brain, muscles and nervous system all rely on glucose as their main fuel to make energy. In the past, carbohydrates were childdens as simple Glycejic complex based on the number of simple sugars Glycemic load and childrens health the Glyxemic. Carbohydrates composed of one or Glyecmic simple sugars like Health and wellness diary or chilldrens table sugar; loqd disaccharide healh of one Meal planning for couples of glucose and one molecule of fructose were labeled simple, while starchy foods were labeled complex because starch is composed of long chains of the simple sugar, glucose. Advice to eat less simple and more complex carbohydrates i. This assumption turned out to be too simplistic since the blood glucose glycemic response to complex carbohydrates has been found to vary considerably. The concept of glycemic index GI has thus been developed in order to rank dietary carbohydrates based on their overall effect on postprandial blood glucose concentration relative to a referent carbohydrate, generally pure glucose 2. The GI is meant to represent the relative quality of a carbohydrate-containing food.