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Effects of an ad libitum low-glycemic load diet on cardiovascular disease risk factors in obese young adults^1,2,3

¹ From the Division of Endocrinology, Department of Medicine, Children's Hospital, Boston, MA

² Supported by grant no. R01 DK59240 (to DSL) and grant no. K01 DK62237 (to CBE) from the National Institute of Diabetes and Digestive Kidney Diseases, the Charles H Hood Foundation (Boston, MA), and grant no. M01 RR02172 from the National Institutes of Health to support the General Clinical Research Center at Children's Hospital Boston (Boston, MA).

³ Reprints not available. Address correspondence to DS Ludwig, Department of Medicine, Children's Hospital, 300 Longwood Avenue, Boston, MA 02115. E-mail: david.ludwig{at}childrens.harvard.edu.

See corresponding editorial on page 949

	ABSTRACT

TOP ABSTRACT INTRODUCTION SUBJECTS AND METHODS RESULTS DISCUSSION REFERENCES

 
Background: The optimal nutritional approach for the prevention of cardiovascular disease among obese persons remains a topic of intense controversy. Available approaches range from conventional low-fat to very-low-carbohydrate diets.

Objective: The aim of this pilot study was to evaluate the efficacy of an ad libitum low-glycemic load diet, without strict limitation on carbohydrate intake, as an alternative to a conventional low-fat diet.

Design: A randomized controlled trial compared 2 dietary treatments in obese young adults (n = 23) over 12 mo. The experimental treatment emphasized ad libitum consumption of low-glycemic-index foods, with 45–50% of energy from carbohydrates and 30–35% from fat. The conventional treatment was restricted in energy (250–500 kcal/d deficit) and fat (<30% of energy), with 55–60% of energy from carbohydrate. We compared changes in study outcomes by repeated-measures analysis of log-transformed data and expressed the results as mean percentage change.

Results: Body weight decreased significantly over a 6-mo intensive intervention in both the experimental and conventional diet groups (–8.4% and –7.8%, respectively) and remained below baseline at 12 mo (–7.8% and –6.1%, respectively). The experimental diet group showed a significantly greater mean decline in plasma triacylglycerols than did the conventional diet group (–37.2% and –19.1%, respectively; P = 0.005). Mean plasminogen activator inhibitor 1 concentrations decreased (–39.0%) in the experimental diet group but increased (33.1%) in the conventional diet group (P = 0.004). Changes in cholesterol concentrations, blood pressure, and insulin sensitivity did not differ significantly between the groups.

Conclusion: An ad libitum low-glycemic load diet may be more efficacious than a conventional, energy-restricted, low-fat diet in reducing cardiovascular disease risk.

Key Words: Obesity • glycemic index • glycemic load • dietary composition • weight-reducing diet • cholesterol • triacylglycerol • plasminogen activator inhibitor 1 • PAI-1 • young adults

	INTRODUCTION

TOP ABSTRACT INTRODUCTION SUBJECTS AND METHODS RESULTS DISCUSSION REFERENCES

 
The alarming prevalence of obesity and the associated risk of cardiovascular disease (CVD) have been well documented (1) and extensively publicized in the United States. As a result, millions of obese adults are following weight-loss diets. Recently, Atkins-type very-low-carbohydrate diets have rapidly grown in popularity (2), although low-fat diets remain the cornerstone of conventional treatment based on clinical practice recommendations (3, 4). Whereas a few studies have suggested that carbohydrate-restricted diets may have significantly greater benefits than do low-fat diets in reducing CVD risk (5, 6), there is widespread concern regarding the safety and long-term efficacy of severe carbohydrate restriction (7, 8).

A low-glycemic load (GL) diet, containing unrestricted amounts of carbohydrate from low-glycemic index (GI) foods, represents an alternative to low-fat diets on the one hand and to low- carbohydrate diets on the other. The GI is defined as the incremental area under the blood glucose response curve after consumption of 50 g of available carbohydrate from a test food, divided by the area under the curve after consumption of 50 g of carbohydrate from a reference food (ie, glucose or white bread) (9). The GL is the arithmetic product of the amount of carbohydrate consumed and the GI (10) and thus describes the overall effects of both quantity and source of carbohydrate on postprandial glycemia (11). Risk of CVD has been inversely associated with dietary GI or GL in some (12–15) but not all (16) epidemiologic studies. Moreover, whereas several short-term intervention studies have described beneficial effects of low-GI diets on blood lipids in overweight adults (17–20) and on the capacity for fibrinolysis in diabetic patients (21, 22), the long-term efficacy of low-GL diets in reducing CVD risk has not previously been evaluated (23).

The aim of this pilot study was to evaluate the efficacy of an experimental ad libitum low-GL diet. We hypothesized that the experimental diet would have a more beneficial effect on CVD risk factors than would a conventional, energy-restricted, low-fat diet over a 12-mo intervention.

	SUBJECTS AND METHODS

TOP ABSTRACT INTRODUCTION SUBJECTS AND METHODS RESULTS DISCUSSION REFERENCES

 
Screening and enrollment
The protocol was approved by the institutional review board at Children's Hospital Boston, and written informed consent was obtained from each subject. Inclusion criteria included: age between 18 and 35 y, body mass index (BMI; in kg/m²) >27, body weight <136 kg (300 lb), and absence of major medical illness as assessed by physical examination and laboratory screening tests (ie, kidney and liver enzymes, thyrotropin, glycosylated hemoglobin, fasting plasma glucose, and urinalysis). After being screened for eligibility, 34 obese young adults (30 females and 4 males) were enrolled in the study. Of these, 22 females and 1 male completed assessments at the end of the 12-mo intervention (Figure 1).

View larger version (22K): [in this window] [in a new window]   FIGURE 1. Enrollment, random assignment, and follow-up of subjects.

Experimental diet
The experimental diet prescription was not energy restricted. Rather, we used an ad libitum approach based on previous research that suggested greater satiety and decreased voluntary energy intake among subjects consuming low-GL diets (24). Subjects were counseled to consume carbohydrate-containing foods with a relatively low GI (eg, nonstarchy vegetables, fruit, legumes, nuts, and dairy products; 24), to consume carbohydrate with protein and healthful fat at every meal and snack, and to eat to satiety and snack when hungry. A low-GL food pyramid provided the basis for nutrition education (25). The target macronutrient composition was 45–50% of energy from carbohydrate, 30–35% of energy from fat, and the remainder from protein.

Conventional diet
The conventional diet prescription was based on current recommendations for weight loss and CVD risk reduction, with emphasis on restricting energy intake by reducing dietary fat (3). Meal plans were based on an exchange system (26) designed to elicit an energy deficit of 250–500 kcal/d. Energy requirements were estimated by using the Harris-Benedict equation (27), multiplied by 1.5 to account for physical activity and adjusted for baseline dietary intake. The American Diabetes Association's diabetes food pyramid provided the basis for nutrition education (28). The target macronutrient composition was 55–60% of energy from carbohydrate, <30% of energy from fat, and the remainder from protein.

Behavioral therapy and physical activity recommendations
Both groups received the same behavioral therapy and physical activity recommendations. Behavioral therapy focused on enhancing self-efficacy for lifestyle change by using social cognitive theory as a conceptual framework (29). Fostering behavioral capability (ie, knowledge and skill) and self-control was the primary objective during the dietary counseling sessions. Patient expectations (ie, anticipated outcomes), expectancies (ie, values ascribed to outcomes), and perceptions of environmental influences were among the topics of discussion. To operationalize the self-control construct, the study dietitian encouraged patients to set goals around eating behaviors, to self-monitor goal attainment, and to explore solutions to problems. Physical activity recommendations were consistent with public health guidelines (30).

Process evaluation
The intervention process was evaluated on the basis of attendance at the dietary counseling sessions and adherence to respective diet prescriptions. All subjects received extensive instruction in keeping food diaries. Three-dimensional food models, plates, bowls, glasses, and measuring cups and spoons were used to educate subjects regarding accurate appraisal of portion sizes. The diaries were reviewed with each subject at the time of receipt to provide clarification, as necessary, on recorded foods and beverages. FOOD PROCESSOR PLUS software (version 8.2; ESHA Research, Salem, OR) was used to quantify intakes of fat, carbohydrate, protein, and fiber. The GI of individual carbohydrate-containing foods was assigned according to published values based on a glucose reference (31). Daily GL was calculated by multiplying the total amount of dietary carbohydrate (in g) by the weighted GI for each food and then adjusted for energy intake:

(1)

and

(2)

To ensure that treatments were delivered according to established procedures, the study dietitian completed a tracking form and progress note immediately after each session. Seven-day food diaries were obtained at baseline (month 0), during the intensive intervention period (3 and 6 mo), and at the end of follow-up (12 mo) for evaluation of process outcomes. In addition, patients were encouraged to keep food diaries throughout the intervention as a self-monitoring strategy. Patients were not given explicit information regarding the target contributions of each macronutrient to total energy intake. Rather, the study dietitian reviewed the diaries after each counseling session and provided practical advice, as necessary, to foster eating behaviors consistent with the diet prescriptions. The project director met with the study dietitian on a regular basis to review food diaries, tracking forms, and progress notes.

Assessment of study outcomes
Weight and height were assessed by using an electronic scale (model 6702; Scale-Tronix, White Plains, NY) and a wall-mounted stadiometer (Holtain Limited, Crymych, United Kingdom), respectively. Body composition was measured by dual-energy X-ray absorptiometry (DXA) with the use of Hologic instrumentation (model QDR 4500; Hologic Inc, Bedford, MA). Blood pressure was determined by using an automated system (Dinamapp, Tampa, FL) while the subject sat quietly. A blood sample was drawn by venipuncture after a 12-h overnight fast.

Laboratory analyses
Plasma lipid concentrations were measured in a laboratory certified by the Centers for Disease Control and Prevention–National Heart, Lung, and Blood Institute Lipid Standardization Program. Total cholesterol, HDL cholesterol, and triacylglycerols were measured by using a Hitachi 911 analyzer (Roche Diagnostics, Indianapolis, IN), and LDL cholesterol was measured by using a homogenous enzymatic assay (Genzyme Corp, Cambridge, MA) (32). Plasma concentrations of plasminogen activator inhibitor 1 (PAI-1) were measured by using an enzyme-linked immunosorbent assay (ELISA; Diagnostica Stago, Parsippany, NJ). Plasma glucose and serum insulin concentrations were measured by using a Hitachi 917 analyzer (Roche Diagnostics) and an Elecsys 2010 system (Roche Diagnostics), respectively. With the use of glucose (mg/dL) and insulin (µU/mL) concentrations, we calculated the quantitative insulin sensitivity check index: 1/(insulin + log glucose) (33).

Statistical analysis
We analyzed dietary data and study outcomes by repeated-measures analysis of variance. We tested each variable for change over time (0, 6, and 12 mo) and for a difference in time course between the 2 groups (experimental and conventional diet) by assessing the main effect of time and the group x time interaction, respectively. To avoid the increased risk of type I inferential error from multiple comparisons, we limited statistical testing of time trends to the overall change (from 0 to 6 to 12 mo), with the exception of 2 planned comparisons for process measures, ie, GL and dietary fat. We accounted for within-subject correlation by using a banded covariance structure, which allowed a lower correlation between the 0- and 12-mo observations than between the 0- and 6-mo or the 6- and 12-mo observations. Statistical significance was defined as P < 0.05.

The primary analysis included data from only the 23 subjects who completed the study. Secondary analyses included available data from all 34 randomly assigned subjects. Study outcomes were log transformed for analysis, and results are expressed as percentage change. Dietary data were analyzed without transformation. We used SAS software (release 9.0; SAS Institute Inc, Cary, NC) for all computations.

	RESULTS

TOP ABSTRACT INTRODUCTION SUBJECTS AND METHODS RESULTS DISCUSSION REFERENCES

 
Subjects
Baseline data for the subjects who completed the study (n = 23; 67.6% of those randomly assigned to a treatment group) are presented in Table 1. There were no significant differences in baseline measures between diet groups. The male who completed the study was in the conventional diet group.

Table 2

Table 3

	DISCUSSION

TOP ABSTRACT INTRODUCTION SUBJECTS AND METHODS RESULTS DISCUSSION REFERENCES

To our knowledge, the randomized controlled trial presented herein is the first long-term study comparing a low-GL diet, with emphasis on consumption of low-GI sources of carbohydrate, with a low-fat diet for decreasing CVD risk in obese young adults. We hypothesized that less hunger or greater satiety in response to an ad libitum low-GL diet may facilitate a decrease in energy intake (45), without the need for externally imposed energy restriction. Our hypothesis is supported, in that mean weight loss among persons following the ad libitum low-GL diet and mean weight loss among persons following the energy-restricted low-fat diet did not differ significantly during the intensive 6-mo intervention (–8.4% and –7.8%, respectively), and there was no significant weight rebound during the follow-up. Moreover, we previously observed greater decreases in BMI and fat mass among adolescents in response to a low-GL diet than in response to a low-fat diet (46). Differences in the response to an energy-restricted diet between adolescents and adults, particularly women, may partially explain the varied patterns of weight loss between our 2 studies. Adolescents have a strong desire for autonomy and seem to resist the use of an exchange system that imposes energy restriction; for this reason, the flexibility of an ad libitum approach may be especially beneficial in this age group. In contrast, many young women are accustomed to following conventional energy-restricted diets, which may limit the likelihood of seeing a group effect over a 12-mo period in this patient population. Additional studies are needed to examine group effects with longer-term follow-up. Nevertheless, our findings compare favorably with those of studies evaluating the effect of severe carbohydrate restriction on weight loss (5, 6). Foster et al (5) observed decreases in body weight of 4.4% and 2.5% at 12 mo among patients prescribed carbohydrate-restricted and low-fat diets, respectively. In a similar 12-mo study, Stern et al (6) observed decreases of 3.5% and 2.4%.

A low-GL diet, such as that used in the present study, may represent an optimal compromise between low-fat diets at one end of the spectrum and carbohydrate-restricted diets at the other. Although changes in body weight did not differ between the 2 groups, the metabolic benefits of a low-GL diet in decreasing CVD risk may be significantly greater than those achieved with either of the more restrictive approaches. The low-fat diet had a significantly less favorable effect on circulating triacylglycerol and PAI-1 concentrations than did the low-GL diet. Indeed, low-fat diets typically have a high carbohydrate content, which causes postprandial hyperglycemia and hyperinsulinemia (47). In turn, these episodes may enhance hepatic triacylglycerol production or reduce peripheral clearance (39, 48) and also promote the synthesis and secretion of PAI-1 (49) via plausible physiologic and molecular mechanisms. Attention has been directed toward controlling triacylglycerol and PAI-1 concentrations in light of the direct associations between these variables and cardiovascular events (50, 51). Whereas very-low-carbohydrate diets have beneficial effects on triacylglycerol concentrations (perhaps as a result of their low GL), the sustainability of such highly restrictive diets over the long term is questionable (5, 6). A low-GL diet,containing moderate amounts of carbohydrate and fat, offers a potentially more flexible approach. In contrast to very-low-carbohydrate diets, the reduction in GL in the experimental group was achieved by a relatively small decrease in carbohydrate intake that was accompanied by a substantial reduction in GI. Nevertheless, the mean decrease in triacylglycerol concentration in the experimental group over 12 mo (37.2%) compares favorably with decreases of 17.0% (5) and 28.6% (6) in previous studies of very-low-carbohydrate diets. Data from metabolic studies, epidemiologic investigations, and clinical trials lend support to the efficacy of eating patterns that are consistent with a low-GL diet (38), including consumption of vegetables, fruit, and whole grains as primary sources of carbohydrate. Moreover, our findings extend data from previous short-term studies showing beneficial reductions in triacylglycerol concentrations with low-GI diets (52–55).

Several issues pertaining to study design warrant consideration. Strengths of the study include the use of treatments of equal intensity in both experimental and control diet groups, which would eliminate this factor as a source of confounding; excellent attendance at counseling sessions among those who completed the study; a longer follow-up than in previous studies of GL or GI and CVD risk factors (17, 18, 20–22); and careful attention to process evaluation. Moreover, changes in dietary fiber, a frequently cited confounder in evaluations of GI or GL (56, 57), were similar between groups. Limitations include the self-reporting of dietary intakes for process evaluation, reliance on published GI values for calculating dietary GL (31), and a small, predominately female sample from which there was some attrition. Underreporting of dietary intake is a well-recognized phenomenon in all outpatient studies aiming to assess the effects of diet composition on weight loss, although adjustment of other dietary variables for energy intake may partially correct for underreporting. When calculating GL from self-report data, we relied on published GI values (31), many which were derived from studies conducted in countries where foods may differ from those consumed in the United States. An attrition rate of 32.4%, although considered problematic in terms of drawing unbiased conclusions (58), is similar to rates observed in previous long-term dietary intervention studies (5, 6).

In conclusion, a low-GL diet containing moderate amounts of carbohydrate from low-GI sources may be more efficacious than a conventional low-fat diet in reducing CVD risk. The greater benefits in response to an ad libitum diet, compared with an energy-restricted diet, are particularly noteworthy. This pilot study provides a rationale for conducting long-term, larger-scale studies comparing the effects of low-GL, low-fat, and very-low-carbohydrate diets on CVD risk among obese persons.

	ACKNOWLEDGMENTS

 
We thank Gary Bradwin for analysis of plasma lipids and plasminogen activator inhibitor 1, Catherine Murphy for help with data collection, and Irena Clark and Erica Garcia-Lago for technical assistance.

All authors contributed to the interpretation of results. CBE and DSL designed the study, provided oversight, and wrote the manuscript. MML was responsible for dietary counseling. KBS and LGS conducted the process evaluations to assess adherence to diet prescriptions. HAF provided consultation on statistical analysis of the data. None of the authors had any personal or financial conflict of interest.

	REFERENCES

TOP ABSTRACT INTRODUCTION SUBJECTS AND METHODS RESULTS DISCUSSION REFERENCES

 

1. Hedley AA, Ogden CL, Johnson CL, Carroll MD, Curtin LR, Flegal KM. Prevalence of overweight and obesity among US children, adolescents, and adults, 1999–2002. JAMA 2004;291:2847–50.[Abstract/Free Full Text]
2. Butler D. Science of dieting: slim pickings. Nature 2004;428:252–4.[Medline]
3. Clinical guidelines on the identification, evaluation, and treatment of overweight and obesity in adults: executive summary. Am J Clin Nutr 1998;68:899–917.[Medline]
4. Klein S, Sheard NF, Pi-Sunyer X, et al. Weight management through lifestyle modification for the prevention and management of type 2 diabetes: rationale and strategies. Diabetes Care 2004;27:2067–73.[Free Full Text]
5. Foster GD, Wyatt HR, Hill JO, et al. A randomized trial of a low-carbohydrate diet for obesity. N Engl J Med 2003;348:2082–90.[Abstract/Free Full Text]
6. Stern L, Iqbal N, Seshadri P, et al. The effects of low-carbohydrate versus conventional weight loss diets in severely obese adults: one-year follow-up of a randomized trial. Ann Intern Med 2004;140:778–85.[Abstract/Free Full Text]
7. St. Jeor ST, Howard BV, Prewitt TE, Bovee V, Bazzarre T, Eckel RH. Dietary protein and weight reduction: a statement for healthcare professionals from the Nutrition Committee of the Council on Nutrition, Physical Activity, and Metabolism of the American Heart Association. Circulation 2001;104:1869–74.[Abstract/Free Full Text]
8. Bravata DM, Sanders L, Huang J, et al. Efficacy and safety of low-carbohydrate diets: a systematic review. JAMA 2003;289:1837–50.[Abstract/Free Full Text]
9. Wolever TMS, Jenkins DJA, Jenkins AL, Josse RG. The glycemic index: methodology and clinical implications. Am J Clin Nutr 1991;54:846–54.[Abstract/Free Full Text]
10. Salmeron J, Ascherio A, Rimm EB, et al. Dietary fiber, glycemic load, and risk of NIDDM in men. Diabetes Care 1997;20:545–50.[Abstract]
11. Brand-Miller JC, Thomas M, Swan V, Ahmad ZI, Petocz P, Colagiuri S. Physiological validation of the concept of glycemic load in lean young adults. J Nutr 2003;133:2728–32.[Abstract/Free Full Text]
12. Ford ES, Liu S. Glycemic index and serum high-density lipoprotein cholesterol concentration among US adults. Arch Intern Med 2001;161:572–6.[Abstract/Free Full Text]
13. Frost G, Leeds AA, Dore CJ, Madeiros S, Brading S, Dornhorst A. Glycemic index as a determinant of serum HDL-cholesterol concentration. Lancet 1999;353:1045–8.[Medline]
14. Liu S, Willett WC, Stampfer MJ, et al. A prospective study of dietary glycemic load, carbohydrate intake, and risk of coronary heart disease in women. Am J Clin Nutr 2000;71:1455–61.[Abstract/Free Full Text]
15. Liu S, Manson JE, Stampfer MJ, et al. Dietary glycemic load assessed by food-frequency questionnaire in relation to plasma high-density-lipoprotein cholesterol and fasting plasma triacylglycerols in postmenopausal women. Am J Clin Nutr 2001;73:560–6.[Abstract/Free Full Text]
16. van Dam RM, Visscher AWJ, Feskens EJM, Verhoef P, Kromhout D. Dietary glycemic index in relation to metabolic risk factors and incidence of coronary heart disease: the Zutphen Elderly Study. Eur J Clin Nutr 2000;54:726–31.[Medline]
17. Bouche C, Rizkalla SW, Luo J, et al. Five-week, low-glycemic index diet decreases total fat mass and improves plasma lipid profile in moderately overweight nondiabetic men. Diabetes Care 2002;25:822–8.[Abstract/Free Full Text]
18. Dumesnil JG, Turgeon J, Tremblay A, et al. Effect of a low-glycaemic index–low-fat–high protein diet on the atherogenic metabolic risk profile of abdominally obese men. Br J Nutr 2001;86:557–68.[Medline]
19. Sloth B, Krog-Mikkelsen I, Flint A, et al. No difference in body weight decrease between a low-glycemic-index and a high-glycemic-index diet but reduced LDL cholesterol after 10-wk ad libitum intake of the low-glycemic-index diet. Am J Clin Nutr 2004;80:337–47.[Abstract/Free Full Text]
20. Wolever TMS, Jenkins DJA, Vuksan V, Jenkins AL, Wong GS, Josse RG. Beneficial effect of low-glycemic index diet in overweight NIDDM subjects. Diabetes Care 1992;15:562–4.[Abstract]
21. Jarvi AE, Karlstrom BE, Granfeldt YE, Bjorck IE, Asp N-GL, Bessby BOH. Improved glycemic control and lipid profile and normalized fibrinolytic activity on a low-glycemic index diet in type 2 diabetic patients. Diabetes Care 1999;22:10–8.[Abstract/Free Full Text]
22. Rizkalla SW, Taghrid L, Laromiguiere M, et al. Improved plasma glucose control, whole-body glucose utilization, and lipid profile on a low-glycemic index diet in type 2 diabetic men. Diabetes Care 2004;27:1866–72.[Abstract/Free Full Text]
23. Ludwig DS. Glycemic load comes of age. J Nutr 2003;133:2695–6.[Free Full Text]
24. Ebbeling CB, Ludwig LS. Treating obesity in youth: should dietary glycemic load be a consideration? Adv Pediatr 2001;48:179–212.[Medline]
25. Ludwig DS. Dietary glycemic index and obesity. J Nutr 2000;130:280S–3S.
26. Holler HJ, Barrier P, Cronmiller N, Delahanty L, Franz M, Wheeler M. Exchange lists for weight management. Alexandria, VA: American Diabetes Association, American Dietetic Association, 1995.
27. Harris JA, Benedict FG. A biometric study of basal metabolism in man. Publication no. 279. Washington, DC: Carnegie Institution, 1919.
28. Warshaw H. Diabetes meal planning made easy: how to put the food pyramid to work for your busy lifestyle. 2nd ed. Alexandria, VA: American Diabetes Association, 2000.
29. Baranowski T, Perry CL, Parcel GS. How individuals, environments, and health behavior interact: social cognitive theory. In: Glanz K, Rimer BK, Lewis FM, eds. Health behavior and health education. 3rd ed. San Francisco, CA: Jossey-Bass, 2002:165–84.
30. Pate RR, Pratt M, Blair SN, et al. Physical activity and public health: a recommendation from the Centers for Disease Control and Prevention and the American College of Sports Medicine. JAMA 1995;273:402–7.[Abstract]
31. Foster-Powell K, Holt SHA, Brand-Miller JC. International table of glycemic index and glycemic load values: 2002. Am J Clin Nutr 2002;76:5–56.[Abstract/Free Full Text]
32. Rifai N, Iannotti E, DeAnagelis K, Law T. Analytical and clinical performance of a homogenous enzymatic LDL-cholesterol assay compared with the ultracentrifugation-dextran sulfate-Mg++ method. Clin Chem 1998;44:1242–50.[Abstract/Free Full Text]
33. Katz A, Nambi SS, Mather K, et al. Quantitative insulin sensitivity check index: a simple, accurate method for assessing insulin sensitivity in humans. J Clin Endocrinol Metab 2000;85:2402–10.[Abstract/Free Full Text]
34. US Department of Health and Human Services. Healthy people 2010: understanding and improving health. Washington, DC: Government Printing Office, 2000.
35. Sturm R, Wells KB. Does obesity contribute as much to morbidity as poverty or smoking? Public Health 2001;115:229–35.[Medline]
36. Finkelstein EA, Fiebelkorn IC, Wang G. State-level estimates of annual medical expenditures attributable to obesity. Obes Res 2004;12:18–24.[Medline]
37. Bray GA, Popkin BM. Dietary fat does affect obesity! Am J Clin Nutr 1998;68:1157–73.[Abstract]
38. Hu FB, Willett WC. Optimal diets for prevention of coronary heart disease. JAMA 2002;288:2569–78.[Abstract/Free Full Text]
39. Parks EJ, Hellerstein MK. Carbohydrate-induced hypertriacylglycerolemia: historical perspective and review of biological mechanisms. Am J Clin Nutr 2000;71:412–33.[Abstract/Free Full Text]
40. Reaven GM. Do high carbohydrate diets prevent the development or attenuate the manifestations (or both) of syndrome X? A viewpoint strongly against. Curr Opin Lipidol 1997;8:23–7.
41. Willett WC. Is dietary fat a major determinant of body fat? Am J Clin Nutr 1998;67(suppl):556S–62S.[Abstract]
42. Flegal KM, Carroll MD, Ogden CL, Johnson CL. Prevalence and trends in obesity among US adults, 1999–2000. JAMA 2002;288:1723–7.[Abstract/Free Full Text]
43. Wright JD, Kennedy-Stephenson J, Wang CY, McDowell MA, Johnson CL. Trends in intake of energy and macronutrients—United States, 1971–2000. MMWR Morb Mortal Wkly Rep 2004;53:80–2.[Medline]
44. Nielsen SJ, Siega-Riz AM, Popkin BM. Trends in energy intake in U.S. between 1977 and 1996: similar shifts seen across age groups. Obes Res 2002;10:370–8.[Medline]
45. Ludwig DS. The glycemic index: physiological mechanisms relating to obesity, diabetes, and cardiovascular disease. JAMA 2002;287:2414–23.[Abstract/Free Full Text]
46. 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 2003;157:773–9.[Abstract/Free Full Text]
47. Ludwig DS, Majzoub JA, Al-Zahrani A, Dallal GE, Blanco I, Roberts SB. High glycemic index foods, overeating, and obesity. Pediatrics 1999;103:e26.[Abstract/Free Full Text]
48. Fried SK, Rao SP. Sugars, hypertriglyceridemia, and cardiovascular disease. Am J Clin Nutr 2003;78(suppl):873S–80S.[Abstract/Free Full Text]
49. Kohler HP, Grant PJ. Plasminogen-activator inhibitor type 1 and coronary artery disease. N Engl J Med 2000;342:1792–801.[Free Full Text]
50. Austin MA, Hokanson JE, Edwards KL. Hypertriglyceridemia as a cardiovascular risk factor. Am J Cardiol 1998;81:7B–12B.[Medline]
51. Thogersen AM, Jansson JH, Boman K, et al. High plasminogen activator inhibitor and tissue plasminogen activator levels in plasma precede a first acute myocardial infarction in both men and women: evidence for the fibrinolytic system as an independent primary risk factor. Circulation 1998;98:2241–7.[Medline]
52. Fontvieille AM, Rizkalla SW, Penfornis A, Acosta M, Bornet FRJ, Slama G. The use of low glycaemic index foods improves metabolic control of diabetic patients over five weeks. Diabetic Med 1992;9:444–50.[Medline]
53. Frost G, Wilding J, Beecham J. Dietary advice based on the glycaemic index improves dietary profile and metabolic control in type 2 diabetic patients. Diabet Med 1994;11:397–401.[Medline]
54. Jenkins DJA, Wolever TMS, Kalmusky J, et al. Low-glycemic index diet in hyperlipidemia: use of traditional starchy foods. Am J Clin Nutr 1987;46:66–71.[Abstract/Free Full Text]
55. Wolever TMS, Jenkins DJA, Vuksan V, et al. Beneficial effect of a low glycaemic index diet in type 2 diabetes. Diabet Med 1992;9:451–8.[Medline]
56. Pi-Sunyer FX. Glycemic index and disease. Am J Clin Nutr 2002;76(suppl):290S–8S.[Abstract/Free Full Text]
57. Raben A. Should obese patients be counselled to follow a low-glycaemic index diet? No. Obes Rev 2002;3:245–56.[Medline]
58. Ware JH. Interpreting incomplete data in studies of diet and weight loss. N Engl J Med 2003;348:2136–7.[Free Full Text]

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				E. B Levitan, M. A Mittleman, N. Hakansson, and A. Wolk Dietary glycemic index, dietary glycemic load, and cardiovascular disease in middle-aged and older Swedish men Am. J. Clinical Nutrition, June 1, 2007; 85(6): 1521 - 1526. [Abstract] [Full Text] [PDF]

				C. B. Ebbeling, M. M. Leidig, H. A. Feldman, M. M. Lovesky, and D. S. Ludwig Effects of a Low-Glycemic Load vs Low-Fat Diet in Obese Young Adults: A Randomized Trial JAMA, May 16, 2007; 297(19): 2092 - 2102. [Abstract] [Full Text] [PDF]

				S. E Kasim-Karakas, W. M Cunningham, and A. Tsodikov Relation of nutrients and hormones in polycystic ovary syndrome Am. J. Clinical Nutrition, March 1, 2007; 85(3): 688 - 694. [Abstract] [Full Text] [PDF]

				K. C Maki, T. M Rains, V. N Kaden, K. R Raneri, and M. H Davidson Effects of a reduced-glycemic-load diet on body weight, body composition, and cardiovascular disease risk markers in overweight and obese adults Am. J. Clinical Nutrition, March 1, 2007; 85(3): 724 - 734. [Abstract] [Full Text] [PDF]

				S. H. Duncan, A. Belenguer, G. Holtrop, A. M. Johnstone, H. J. Flint, and G. E. Lobley Reduced Dietary Intake of Carbohydrates by Obese Subjects Results in Decreased Concentrations of Butyrate and Butyrate-Producing Bacteria in Feces Appl. Envir. Microbiol., February 15, 2007; 73(4): 1073 - 1078. [Abstract] [Full Text] [PDF]

				H. Hare-Bruun, A. Flint, and B. L Heitmann Glycemic index and glycemic load in relation to changes in body weight, body fat distribution, and body composition in adult Danes. Am. J. Clinical Nutrition, October 1, 2006; 84(4): 871 - 879. [Abstract] [Full Text] [PDF]

				J. McMillan-Price, P. Petocz, F. Atkinson, K. O'Neill, S. Samman, K. Steinbeck, I. Caterson, and J. Brand-Miller Comparison of 4 diets of varying glycemic load on weight loss and cardiovascular risk reduction in overweight and obese young adults: a randomized controlled trial. Arch Intern Med, July 24, 2006; 166(14): 1466 - 1475. [Abstract] [Full Text] [PDF]

				M. N Woods Nutrition Academic Award: nutrition education in graduate medical education. Am. J. Clinical Nutrition, April 1, 2006; 83(4): 971S - 975S. [Abstract] [Full Text] [PDF]

				A. G. Pittas, S. K. Das, C. L. Hajduk, J. Golden, E. Saltzman, P. C. Stark, A. S. Greenberg, and S. B. Roberts A Low-Glycemic Load Diet Facilitates Greater Weight Loss in Overweight Adults With High Insulin Secretion but Not in Overweight Adults With Low Insulin Secretion in the CALERIE Trial Diabetes Care, December 1, 2005; 28(12): 2939 - 2941. [Full Text] [PDF]

				Low-Glycemic-Load Diet Lowers CV Risk DOC News, September 1, 2005; 2(9): 16 - 17. [Full Text]

				J. Brand-Miller Optimizing the cardiovascular outcomes of weight loss Am. J. Clinical Nutrition, May 1, 2005; 81(5): 949 - 950. [Full Text] [PDF]

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