HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS		QUICK SEARCH:   [advanced] Author: Keyword(s): Year:  Vol:  Page:

This Article Abstract Full Text (PDF) Purchase Article View Shopping Cart Alert me when this article is cited Alert me if a correction is posted Services Email this article to a friend Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Request Permissions Citing Articles Citing Articles via HighWire Citing Articles via Google Scholar Google Scholar Articles by Gilbertson, H. R. Articles by Werther, G. A. Search for Related Content PubMed PubMed Citation Articles by Gilbertson, H. R. Articles by Werther, G. A. Social Bookmarking                What's this?

The Effect of Flexible Low Glycemic Index Dietary Advice Versus Measured Carbohydrate Exchange Diets on Glycemic Control in Children With Type 1 Diabetes

¹ Department of Nutrition and Food Services, the
² Department of Clinical Epidemiology and Biostatistics, and the
³ Department of Endocrinology and Diabetes, Royal Children’s Hospital, Melbourne
⁴ Human Nutrition Unit, Department of Biochemistry, University of Sydney
⁵ Department of Medicine, University of Melbourne, Royal Melbourne Hospital, Melbourne, Australia

	ABSTRACT

TOP ABSTRACT INTRODUCTION RESEARCH DESIGN AND METHODS RESULTS CONCLUSIONS References

 
OBJECTIVE—To determine the long-term effect of low glycemic index dietary advice on metabolic control and quality of life in children with type 1 diabetes.

RESEARCH DESIGN AND METHODS—Children with type 1 diabetes (n = 104) were recruited to a prospective, stratified, randomized, parallel study to examine the effects of a measured carbohydrate exchange (CHOx) diet versus a more flexible low–glycemic index (GI) dietary regimen on HbA_1c levels, incidence of hypo- and hyperglycemia, insulin dose, dietary intake, and measures of quality of life over 12 months.

RESULTS—At 12 months, children in the low-GI group had significantly better HbA_1c levels than those in the CHOx group (8.05 ± 0.95 vs. 8.61 ± 1.37%, P = 0.05). Rates of excessive hyperglycemia (>15 episodes per month) were significantly lower in the low-GI group (35 vs. 66%, P = 0.006). There were no differences in insulin dose, hypoglycemic episodes, or dietary composition. The low-GI dietary regimen was associated with better quality of life for both children and parents.

CONCLUSIONS—Flexible dietary instruction based on the food pyramid with an emphasis of low-GI foods improves HbA_1c levels without increasing the risk of hypoglycemia and enhances the quality of life in children with diabetes.

Abbreviations: BMR, basal metabolic rate • CHOx, carbohydrate exchange • GI, glycemic index • NMES, nonmilk extrinsic sugars • RCH, Royal Children’s Hospital

	INTRODUCTION

TOP ABSTRACT INTRODUCTION RESEARCH DESIGN AND METHODS RESULTS CONCLUSIONS References

 
Type 1 diabetes is one of the most challenging medical disorders because of the demands it imposes on day-to-day life. Good glycemic control, as judged by HbA_1c levels, is clearly related to reduced risk of microvascular complications (1). Although diet plays a major role in the overall management of type 1 diabetes, it is often classed as the most difficult aspect of treatment (2,3). Furthermore, there are surprisingly few long-term studies to support current dietary recommendations. Weighed carbohydrate "exchanges," introduced in the 1950s, have been used to ensure an even distribution of complex carbohydrates throughout the day. Carbohydrate counting and higher carbohydrate intake are now recommended, although in practice, emphasis is still placed on limiting carbohydrates to a specified level and avoiding refined sugars (4,5).

Different carbohydrate foods affect blood glucose levels to varying degrees, as measured by their glycemic index (GI) (6,7). Foods such as legumes and dairy products have a low GI, whereas ordinary breads, potatoes, and rice have a high GI (8). Carbohydrate counting and "exchange" diets imply that equal carbohydrate portions have the same effect on glycemia. Not only is the theoretical basis of the exchange system questionable, it is difficult to understand and implement without knowing the carbohydrate content of food (9). Several studies have shown that exchange diets do not improve glycemic control (9,10) and that many children with diabetes and their parents cannot understand or follow them (111213). It has also been suggested that quantifying carbohydrate intake may be associated with some physiological and psychological problems, including disordered eating behavior (14). This information and the emerging significance of postprandial glycemia on diabetes-related complications suggest that carbohydrate quantity alone is not an adequate basis for controlling blood glucose levels. Research shows low-GI diets significantly improve metabolic control in adults with type 2 diabetes (15161718). However, there are very few studies on the use of low-GI diets in type 1 diabetes (192021) and only one small short-term study in children (22). Differences in GI between foods are just as likely to apply to children as to adults (22,23), but more studies are needed on the long-term effect of low-GI diets in children with type 1 diabetes.

We hypothesized that less regimented dietary instruction with an emphasis on the use of low-GI foods may enhance metabolic control and compliance in a pediatric population. This randomized prospective trial compares the effects of flexible, low-GI dietary advice and the measured carbohydrate exchange (CHOx) diet on glycemic control, nutritional intake, and quality-of-life measures in children with type 1 diabetes over a 12-month period.

	RESEARCH DESIGN AND METHODS

TOP ABSTRACT INTRODUCTION RESEARCH DESIGN AND METHODS RESULTS CONCLUSIONS References

 
Study design
Figure 1 summarizes the trial profile used in this study. Children attending the Melbourne Royal Children’s Hospital (RCH) Diabetes Clinic were selected using the following criteria: 1) age between 8 and 13 years, diagnosis of type 1 diabetes for longer than one year, and regular attendance at the clinic (3 monthly); 2) no additional dietary restrictions; 3) no other immediate family members with diabetes, 4) no medications that would affect appetite; and 5) family able to read and write English.

View larger version (34K): [in this window] [in a new window]   Figure 1 — Trial Profile. CC, those who only received instructions on the CHOx diet both prior and during the study; GG, those only instructed in the low-GI diet both prior and during the study; CG, those randomized to the low-GI diet who had been following a CHOx diet before the study; GC, those randomized to the CHOx diet who had been following the low-GI diet before the study.

Diet assessment and education
Individual interviews with the research dietitian were used to collect initial data, instruct the child and parent in the use of food records, and develop a rapport to enhance participation over the 12-month period. Each subject was asked to complete a 3-day food diary. Two weekdays and one weekend day were specified to account for the variation in food intake at weekends (24). Families were encouraged not to alter their usual pattern of food intake during recording periods. A sample food diary and a contact phone number were provided.

At the beginning of the study, subjects were assessed by a dietitian to categorize their existing dietary regime and ensure correct stratification before being randomized to either the CHOx or low-GI diet. Computer-generated random numbers of 1 and 2 were generated in blocks of 10 and assigned consecutively to each subject upon recruitment to the study. Of the 104 subjects recruited, 49 were assigned to the CHOx diet, and 55 were assigned to the low-GI diet (Fig. 1). Education regarding the allocated study diet was then given to the child and parent (Table 1). The diet education session was structured similarly for both groups and executed in an outpatient setting by the same clinical dietitian. A specially made flipchart was used for each of the study diets explaining the principles of the diet. Literature was also provided to reinforce the advice (Table 1). No additional education sessions were planned over the 12-month period apart from usual clinic review. The food diaries were completed at 1, 3, 6, and 12 months, and phone calls were made 2 weeks before the clinic visit to ensure compliance.

Energy intake was independently assessed as being below, within, or above range. Ranges were based on basal metabolic rate (BMR) calculations using cutoff points from published sources. BMR was calculated using Schofield’s equation (26). The minimum and maximum cutoff points were derived from the work of, respectively, Goldberg et al. (27), using a value of 0.8 x BMR x activity factor, and Torun et al. (28). Activity levels were individually assessed and defined as light (<2 organized activities per week), moderate (2–5 organized activities per week), and heavy (>5 organized activities per week). Activity factors were 1.55, 1.75, and 1.95, respectively.

For the purpose of dietary analysis, the daily GI (relative to a standard glucose value of 100) was calculated by summing the following: [grams of carbohydrate from the food item / total daily carbohydrate x 100 x GI of food item]. GI values were derived from published GI tables (8) and unpublished data from the Human Nutrition Unit, University of Sydney. Of 284 carbohydrate-containing foods, 194 were assigned a known GI, but 90 were given "estimated" values based on the GI of similar foods.

Outcome measures
The following measures were recorded at entry to the study and at 3, 6, and 12 months: HbA_1c level, weight, height, dietary intake information, and incidence of hypoglycemia (<3.5 mmol/l) and hyperglycemia (>15 mmol/l) as determined by preprandial breakfast, dinner, and supper levels charted in the child’s self-reported record book during the 1 month before each visit. In addition, a quality-of-life questionnaire was completed independently by the parent and child (via separate interview) at each time point. HbA_1c measurements were routinely performed in the clinic using the DCA 2000 Analyser (Bayer) on capillary blood samples obtained by fingerprick (mean coefficient of variation 3.8%).

Statistical analysis
The sample size of 104 families allowed for a 15% dropout rate and provided 80% power to reject the null hypothesis, which stated that mean HbA_1c levels after 12 months were the same in the two groups if a 10% difference (i.e., a difference in measured HbA_1c of 1%) was found. Significance was set at 5%. The sample size calculation was based on an effect size of 0.625 SD. A subgroup analysis was planned prospectively that divided the subjects into four subgroups, as illustrated by Fig. 1. An intent-to-treat analysis was performed on the assumption that subjects adhered to the dietary advice provided at entry to the study. Data analysis and clinical outcome measures were assessed by researchers unaware of the treatment allocation.

Results were expressed as the mean ± SD, unless otherwise stated, and were analyzed using multiple linear regression or Spearman’s correlation for continuous variables or with a combination of logistic regression or Pearson’s ² analysis for categorical data. Nonnormal data were analyzed using Wilcoxon’s rank-sum test and expressed as medians and ranges. Clinical data were adjusted for baseline values where specified. All statistical analysis was performed using the Intercooled Stata 5.0 Statistical package (Stata Corporation).

	RESULTS

TOP ABSTRACT INTRODUCTION RESEARCH DESIGN AND METHODS RESULTS CONCLUSIONS References

 
There were no significant differences in baseline measures or demographic data between the two study groups (Table 2). A total of 15 subjects (14%) dropped out during the study period: 11 from the CHOx group and 4 from the low-GI group. There was a significantly higher dropout rate from the CHOx group (22 vs. 7% in the CHOx and low-GI groups, respectively, P = 0.03). Specifically, there was a differential dropout rate of 39% for subgroup GC, who had been assigned to the CHOx diet for the study after previously following the low-GI diet, versus subgroups CC (13%), GG (15%), and CG (3%) (P < 0.01), who were, respectively, only instructed in the CHOx diet, only instructed in the low-GI diet, or randomized to the low-GI diet after following a CHOx diet prior to the study. Apart from dietary assignment, there were no other significant differences at baseline between these subjects.

View larger version (14K): [in this window] [in a new window]   Figure 2 — Mean (± SE) HbA1c measurements over 12 months for CHOx (––) and low-GI (––) subjects who completed the study (n = 38 and 51, respectively). Analysis adjusted for baseline HbA1c values.

The proportions of subjects from each study group within acceptable and unacceptable HbA_1c ranges were compared. The acceptable cutoff was <8% (29) and levels >9% were considered suboptimal. At 12 months, twice as many subjects from the low-GI group (45%) had HbA_1c values within the acceptable range compared with subjects in the CHOx group (22%) (P = 0.02 after adjustment for baseline values). Subjects in the CHOx group were 3 times more likely to have undesirable HbA_1c values compared with the low-GI group (47 vs. 18%, P = 0.004 after adjustment for baseline values).

A significantly larger proportion of subjects from the CHOx group reported more frequent episodes of hyperglycemia at 12 months, defined as >15 episodes per month (66 vs. 35%, P = 0.006 after adjustment for baseline values). There were no significant differences in hypoglycemic episodes (Table 2).

Of the 89 subjects who completed the study, 6 did not complete a food diary. The two study groups showed no significant differences in any of the dietary variables measured at 12 months. On average, the children consumed 17% energy as protein, 34% as fat, 49% as carbohydrate, and 7% as NMES, and they consumed 21 g fiber per day. However, there was a high proportion of subjects who appeared to underreport food intake in both groups (53 vs. 46% in the CHOx and low-GI groups, respectively), casting doubt on the reliability of the food diaries. The dietary variables were reanalyzed, excluding underreporters but otherwise remaining essentially unchanged.

Surprisingly, despite differences in dietary instruction, there was no difference in mean GI between the two groups (56.5 ± 4.0 and 55.3 ± 4.8 in the CHOx and low-GI groups, respectively, P = 0.26). Because GI is not a precise measure, we compared the proportions of subjects that had a low (<55), moderate (55–60), and high (>60) GI. At all time points, the low-GI group showed a greater proportion of subjects within the low (GI <55) range (low GI: 62, 47, 47, and 44%; CHOx: 37, 40, 36, and 30% at 1, 3, 6, and 12 months, respectively), but the difference reached statistical significance only at one month (P = 0.02). The low-GI group also contained more subjects who achieved an extremely low average GI (<50%), (0 vs. 14% in the CHOx and low-GI groups, respectively, P = 0.04 at 12 months). From a food variety perspective, the average number of different carbohydrate food choices per day was similar between the two groups (9.9 ± 2.5 vs. 10.8 ± 2.4, P = 0.10).

In correlation analyses, no dietary factor correlated significantly with HbA_1c levels. The reported physical activity level was not different between the dietary groups (median number of organized activities per week [range]: 4.0[1–10] and 4.5[1–10] in the CHOx and low-GI groups, respectively, P = 0.75) and showed no relationship to HbA_1c level.

Quality of life was influenced significantly by type of dietary instruction. Twice as many parents in the low-GI group stated that their child had no difficulties in selecting their own meals at the 12-month time point (51 vs. 24% P = 0.01). Almost twice as many parents from the low-GI group reported that diabetes never limited the types of activities pursued as a family (53 vs. 27% P = 0.02) and that diabetes had never been a source of tension or conflict within the family (55 vs. 27% P = 0.01). There was a trend for the majority of parents from the low-GI group to believe that diabetes never interrupted various everyday family activities (53 vs. 32% P = 0.06).

The 53 children (and their parents) that had experienced both types of dietary approaches (subgroups CG and GC) expressed an overall preference for the low-GI diet compared with the CHOx diet (Table 3, P < 0.01 and P < 0.001 for the children and parents, respectively). The same subgroup of parents believed that the low-GI diet led to better control of blood glucose levels compared with the CHOx diet (P < 0.001). The low-GI diet was the dietary regime that most parents and children selected to continue after completion of the study (P < 0.001 and P < 0.001 for the children and parents, respectively).

	CONCLUSIONS

TOP ABSTRACT INTRODUCTION RESEARCH DESIGN AND METHODS RESULTS CONCLUSIONS References

The difference in glycemic control was greater and more significant in the children who had received the same dietary instruction both before and throughout the study. This suggests that some aspect of the flexible low-GI approach was associated with gradual but sustained improvement in HbA_1c levels. However, it is difficult to attribute the lower HbA_1c levels solely to differences in diet, particularly when there was no apparent difference in mean GI.

The dietary records showed that macronutrient and fiber intakes were very close to that of children in the general Australian population (30) and were similar in both groups. However, the dietary data need to be interpreted cautiously because of the unacceptably high prevalence of underreporting. About half the records revealed energy intakes that were not likely to reflect the child’s habitual intake. This criticism plagues all dietary assessment studies (31,32) and is especially true of those in children. The high rate of underreporting may have affected the ability to detect subtle differences in carbohydrate quality (mean GI) between the two study groups. The large number of foods with estimated GI values may also have contributed. Despite these limitations, the assumption that a low-GI diet might restrict food variety and increase fat or sugar intake was not borne out by the data (33). Many low-GI foods were particularly favored by the children, including peanut butter, pasta, baked beans, and dairy foods. Given the documented differences in hyperglycemic episodes between the two groups, the dietary data on the whole suggest that individuals in the low-GI group were consuming more low-GI foods than those in the CHOx group.

The quality-of-life questions revealed an obvious preference for the flexible low-GI dietary regimen among the children (and parents) who had experienced both types of dietary instruction. There were significant differences in measures such as family conflict, limitations placed on family activities, difficulties for the child in selecting their own meals, and a clear preference to continue on the low-GI diet. These findings are important and challenge the belief that low-GI diets might be difficult to follow and a burden for people with diabetes. Furthermore, they need to be considered alongside the fact that glycemic control was superior among those who received the simpler, less regimented dietary advice. Using CHOx is often quoted as the most challenging aspect of managing diabetes (2,3).

The findings of this large long-term prospective study suggest that more flexible dietary instruction based on the food pyramid and with an emphasis on low-GI foods has demonstrable benefits for children with diabetes. Weighed-carbohydrate exchange dietary advice was associated with inferior glycemic control and measures of quality of life.

	ACKNOWLEDGMENTS

 
This study was supported by a grant from the Diabetes Australia Research Trust. We would like to thank Kay Gibbons (Nutrition and Food Services Department, RCH) for her advice, encouragement, and support; Rebecca Gebert and Warren Lee (Department of Endocrinology and Diabetes, RCH) for assistance with the questionnaire design; and Alison Caifai (Monash Medical Center, Clayton) for the initial study diet education sessions. We also extend a special thank you to the patients and families who participated in the study.

	FOOTNOTES

 
Address correspondence and reprint requests to Heather R. Gilbertson, Department of Nutrition and Food Services, Women’s and Children’s Health Care Network, Royal Children’s Hospital, Melbourne, Parkville, VIC, Australia 3052. E-mail: gilberth{at}cryptic.rch.unimelb.edu.au.

Received for publication 19 October 2000 and accepted in revised form 26 March 2001.

A table elsewhere in this issue shows conventional and Système International (SI) units and conversion factors for many substances.

	References

TOP ABSTRACT INTRODUCTION RESEARCH DESIGN AND METHODS RESULTS CONCLUSIONS References

 

1. The Diabetes Control and Complications Trial Research Group: The effect of intensive treatment of diabetes on the development and progression of long-term complications in insulin-dependent diabetes mellitus. N Engl J Med 329:977–986, 1993[Abstract/Free Full Text]
   
2. Brink SJ: Pediatric, adolescent and young-adult nutrition issues in IDDM. Diabetes Care 11:192–200, 1988[Abstract]
   
3. Lockwood D, Frey ML, Gladish NA, Hiss RG: The biggest problem in diabetes. Diabetes Educ 12:30–33, 1986
   
4. Court J: Modern Living With Diabetes: For All Ages. 2nd ed. Melbourne, Australia, Diabetes Australia Victoria, 1991
   
5. National Health and Medical Research Council: Dietary Guidelines for Australians. Commonwealth of Australia, Canaberra, Australia, Australian Government Publishing Service, 1992, p. 58–59
   
6. Jenkins DJA, Wolever TMS, Jenkins AL: Starchy foods and glycemic index. Diabetes Care 11:149–159, 1988[Abstract]
   
7. Jenkins DJA, Wolever TMS, Taylor RH, Barker H, Fielden H, Baldwin JM, Bowling A, Newman HC, Jenkins AL, Goff DV: Glycemic index of foods: a physiological basis for carbohydrate exchange. Am J Clin Nutr 34:362–366, 1981[Abstract/Free Full Text]
   
8. Brand Miller J, Foster-Powell K, Colagiuru S: The GI Factor: The Glucose Revolution. Australia, Hodder and Stoughton, 1998
   
9. Mitchell RD, Nowakowska JA, Hurst AJ: Comparison of official 10g carbohydrate "exchange" system with simplified dietary advice in insulin dependent diabetics. J Hum Nutr Dietetics 3:19–26, 1990
   
10. Price KJ, Lang JD, Eiser C, Tripp JH: Prescribed versus unrestricted carbohydrate diets in children with type 1 diabetes. Diabet Med 10:962–967, 1993[Medline]
    
11. Hackett AF, Court S, McCowen C, Parkin JM: Dietary survey of diabetics. Arch Dis Child 61:67–71, 1986[Abstract]
    
12. Lorenz RA, Christensen NK, Pichert JW: Diet related knowledge, skill and adherence among children with insulin dependent diabetes mellitus. Pediatrics 75:872–876, 1985[Abstract/Free Full Text]
    
13. West KM: Diet therapy of diabetes: an analysis of failure. Ann Intern Med 79:425–434, 1973
    
14. Waldron S: Current controversies in the dietary management of diabetes in childhood and adolescence. Br J Hosp Med 56:450–455, 1996[Medline]
    
15. Brand Miller JC: Importance of glycemic index in diabetes. Am J Clin Nutr 59(Suppl. 1):747–752, 1994
    
16. Jenkins DJA, Wolever TMS, Collier GR, Ocana A, Rao AV, Buckley G, Lam Y, Mayer A, Thompson LU: Metabolic effects of a low glycemic index diet. Am J Clin Nutr 46:968–975, 1987[Abstract/Free Full Text]
    
17. Brand JC, Colagiuri S, Crossman S, Allen A, Roberts D, Truswell AS: Low-glycemic index foods improve long-term glycemic control in NIDDM. Diabetes Care 14:95–101, 1991[Abstract]
    
18. Frost G, Wilding J, Beecham J: Dietary advice based on the glycemic index improves dietary profile and metabolic control in type 2 diabetic patients. Diabet Med 11:397–401, 1994[Medline]
    
19. Fontvieille AM, Acosta M, Rizkalla SW, Bornet F, David P, Letanoux M, Tchobroutsky G, Slama G: A moderate switch from high to low glycaemic index foods for three weeks improves the metabolic control of type 1 (IDDM) diabetic subjects. Diabet Nutr Metab 1:139–143, 1988
    
20. Giacco R, Parillo M, Rivellese AA, Lasorella G, Giacco A, D’Episcopo L, Riccardi G: Long-term dietary treatment with increased amounts of fiber-rich low-glycemic index natural foods improves blood glucose control and reduces the number of hypoglycemic events in type 1 diabetic patients. Diabetes Care 23:1461–1466, 2000[Abstract]
    
21. Chiasson J-L: Glycemic index of foods and glycemic control in type 1 diabetes. Curr Opin Endocrinol Diabet 7:25–30, 2000
    
22. Collier GR, Giudici S, Kalmusky J, Wolever TMS, Helman G, Wesson V, Ehrlich RM, Jenkins DJA: Low glycemic index starchy foods improve glucose control and lower serum cholesterol in diabetic children. Diab Nutr Metab 1:11–19, 1988
    
23. Wolever TMS, Jenkins DJA, Collier GR, Ehrlich RM, Josse RG, Wong GS, Lee R: The glycaemic index: effect of age in insulin dependent diabetes mellitus. Diabetes Res 7:71–74, 1988[Medline]
    
24. Hackett AF, Appleton DR, Rugg-Gunn AJ, Eastoe JE: Some influences on the measurement of food intake during a dietary survey of adolescents. Hum Nutr Appl Nutr 39:167–177, 1985[Medline]
    
25. Paul AA, Southgate DAT: McCance and Widdowson’s The Composition of Foods. 4th ed. London, Her Majesty’s Stationery Office, 1978
    
26. Schofield WN: Predicting basal metabolic rate, new standards and review of previous work. Hum Nutr Clin Nutr 39(Suppl. 1):5–41, 1985
    
27. Goldberg GR, Black AE, Jebb S, Cole TJ, Murgatroyd PR, Coward WA, Prentice AM: Critical evaluation of energy intake using fundamental principles of energy physiology. I. Derivation of cut-off limits to identify under-recording. Eur J Clin Nutr 45:569–581, 1991[Medline]
    
28. Torun B, Davies PSW, Livingstone MBE, Paolisso M, Sackett R, Spurr GB: Energy requirements and dietary energy recommendations for children and adolescents 1 to 18 years old. Eur J Clin Nutr 50(Suppl. 1):37–81, 1996
    
29. NSW Health Department: Principles of Care and Consensus Guidelines for the Management of Diabetes Mellitus in Children and Adolescents. New South Wales Health Department, Sydney, 1998
    
30. Australian Bureau of Statistics: National Nutrition Survey; Selected Highlights 4802. 0 Canberra, Australia, Commonwealth Department of Health and Family Services, 1995
    
31. Stuff JE, Garza C, O’Brian Smith E, Nichols BL, Montandon CM: A comparison of dietary methods in nutritional studies. Am J Clin Nutr 37:300–306, 1983[Abstract/Free Full Text]
    
32. Block G: A review of validations of dietary assessment methods. Am J Epidemiol 115:492–505, 1982[Free Full Text]
    
33. Franz MJ: In defence of the American Diabetes Association’s recommendations on the glycemic index. Nutr Today 34:78–81, 1999
    

CiteULike

Del.icio.us

Digg

Reddit

Technorati

This article has been cited by other articles:

				K. Marsh and J. Brand-Miller State of the Art Reviews: Glycemic Index, Obesity, and Chronic Disease American Journal of Lifestyle Medicine, April 1, 2008; 2(2): 142 - 150. [Abstract] [PDF]

				G. Livesey, R. Taylor, T. Hulshof, and J. Howlett Glycemic response and health a systematic review and meta-analysis: the database, study characteristics, and macronutrient intakes Am. J. Clinical Nutrition, January 1, 2008; 87(1): 223S - 236S. [Abstract] [Full Text] [PDF]

				Weight Loss Requires Drop in Calories, Not Low GI DOC News, November 1, 2007; 4(11): 4 - 4. [Full Text]

				F. Mohsin, M. E Craig, J. Cusumano, A. K.F. Chan, S. Hing, J. W. Lee, M. Silink, N. J. Howard, and K. C. Donaghue Discordant Trends in Microvascular Complications in Adolescents With Type 1 Diabetes From 1990 to 2002 Diabetes Care, August 1, 2005; 28(8): 1974 - 1980. [Abstract] [Full Text] [PDF]

				S. Scaglioni, M. Sala, G. Stival, M. Giroli, C. Raimondil, M. Salvioni, G. Radaelli, C. Agostoni, E. Riva, and M. Giovannini Dietary Glycemic Load and Macronutrient Intake in Healthy Italian Children Asia Pac J Public Health, January 1, 2005; 17(2): 88 - 92. [Abstract] [PDF]

				N. F. Sheard, N. G. Clark, J. C. Brand-Miller, M. J. Franz, F. X. Pi-Sunyer, E. Mayer-Davis, K. Kulkarni, and P. Geil Dietary Carbohydrate (Amount and Type) in the Prevention and Management of Diabetes: A statement by the American Diabetes Association Diabetes Care, September 1, 2004; 27(9): 2266 - 2271. [Full Text] [PDF]

				J. L. Sievenpiper and V. Vuksan Glycemic Index in the Treatment of Diabetes: The Debate Continues J. Am. Coll. Nutr., February 1, 2004; 23(1): 1 - 4. [Full Text] [PDF]

				J. W. Anderson, K. M. Randles, C. W. C. Kendall, and D. J. A. Jenkins Carbohydrate and Fiber Recommendations for Individuals with Diabetes: A Quantitative Assessment and Meta-Analysis of the Evidence J. Am. Coll. Nutr., February 1, 2004; 23(1): 5 - 17. [Abstract] [Full Text] [PDF]

				M. J. Franz Meta-Analysis of Low-Glycemic Index Diets in the Management of Diabetes: Response to Brand-Miller et al. and Mann Diabetes Care, December 1, 2003; 26(12): 3364 - 3365. [Full Text] [PDF]

				J. Brand-Miller, S. Hayne, P. Petocz, and S. Colagiuri Low-Glycemic Index Diets in the Management of Diabetes: A meta-analysis of randomized controlled trials Diabetes Care, August 1, 2003; 26(8): 2261 - 2267. [Abstract] [Full Text] [PDF]

				M. J. Franz The Glycemic Index: Not the most effective nutrition therapy intervention Diabetes Care, August 1, 2003; 26(8): 2466 - 2468. [Full Text] [PDF]

				C. B. Ebbeling, M. M. Leidig, K. B. Sinclair, J. P. Hangen, and D. S. Ludwig A Reduced-Glycemic Load Diet in the Treatment of Adolescent Obesity Arch Pediatr Adolesc Med, August 1, 2003; 157(8): 773 - 779. [Abstract] [Full Text] [PDF]

				A. Jimenez-Cruz, M. Bacardi-Gascon, W. H. Turnbull, P. Rosales-Garay, and I. Severino-Lugo A Flexible, Low-Glycemic Index Mexican-Style Diet in Overweight and Obese Subjects With Type 2 Diabetes Improves Metabolic Parameters During a 6-Week Treatment Period Diabetes Care, July 1, 2003; 26(7): 1967 - 1970. [Abstract] [Full Text] [PDF]

				H. R Gilbertson, A. W Thorburn, J. C Brand-Miller, P. Chondros, and G. A Werther Effect of low-glycemic-index dietary advice on dietary quality and food choice in children with type 1 diabetes Am. J. Clinical Nutrition, January 1, 2003; 77(1): 83 - 90. [Abstract] [Full Text] [PDF]

				OTHER ARTICLES NOTED (Nov 01 to 18 Oct 02) Evid. Based Nurs., January 1, 2003; 6(1): e1 - 1. [Full Text] [PDF]

				K. Foster-Powell, S. H. Holt, and J. C Brand-Miller International table of glycemic index and glycemic load values: 2002 Am. J. Clinical Nutrition, July 1, 2002; 76(1): 5 - 56. [Abstract] [Full Text] [PDF]

				D. J. Jenkins, C. W. Kendall, L. S. Augustin, S. Franceschi, M. Hamidi, A. Marchie, A. L Jenkins, and M. Axelsen Glycemic index: overview of implications in health and disease Am. J. Clinical Nutrition, July 1, 2002; 76(1): 266S - 273. [Abstract] [Full Text] [PDF]

				D. S. Ludwig The Glycemic Index: Physiological Mechanisms Relating to Obesity, Diabetes, and Cardiovascular Disease JAMA, May 8, 2002; 287(18): 2414 - 2423. [Abstract] [Full Text] [PDF]

This Article Abstract Full Text (PDF) Purchase Article View Shopping Cart Alert me when this article is cited Alert me if a correction is posted Services Email this article to a friend Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Request Permissions Citing Articles Citing Articles via HighWire Citing Articles via Google Scholar Google Scholar Articles by Gilbertson, H. R. Articles by Werther, G. A. Search for Related Content PubMed PubMed Citation Articles by Gilbertson, H. R. Articles by Werther, G. A. Social Bookmarking                What's this?