title: Glycemic index, glycemic load, and chronic disease risk--a meta-analysis of observational studies.
abstract: BACKGROUND
  Inconsistent findings from observational studies have prolonged the controversy over the effects of dietary glycemic index (GI) and glycemic load (GL) on the risk of certain chronic diseases.
  
  
  OBJECTIVE
  The objective was to evaluate the association between GI, GL, and chronic disease risk with the use of meta-analysis techniques.
  
  
  METHODS
  A systematic review of published reports identified a total of 37 prospective cohort studies of GI and GL and chronic disease risk. Studies were stratified further according to the validity of the tools used to assess dietary intake. Rate ratios (RRs) were estimated in a Cox proportional hazards model and combined by using a random-effects model.
  
  
  RESULTS
  From 4 to 20 y of follow-up across studies, a total of 40 129 incident cases were identified. For the comparison between the highest and lowest quantiles of GI and GL, significant positive associations were found in fully adjusted models of validated studies for type 2 diabetes (GI RR = 1.40, 95% CI: 1.23, 1.59; GL RR = 1.27, 95% CI: 1.12, 1.45), coronary heart disease (GI RR = 1.25, 95% CI: 1.00, 1.56), gallbladder disease (GI RR = 1.26, 95% CI: 1.13, 1.40; GL RR = 1.41, 95% CI: 1.25, 1.60), breast cancer (GI RR = 1.08, 95% CI: 1.02, 1.16), and all diseases combined (GI RR = 1.14, 95% CI: 1.09, 1.19; GL RR = 1.09, 95% CI: 1.04, 1.15).
  
  
  CONCLUSIONS
  Low-GI and/or low-GL diets are independently associated with a reduced risk of certain chronic diseases. In diabetes and heart disease, the protection is comparable with that seen for whole grain and high fiber intakes. The findings support the hypothesis that higher postprandial glycemia is a universal mechanism for disease progression.
authors.affiliation: Human Nutrition Unit, University of Sydney, Sydney, Australia.
authors.forename: Alan W
authors.initials: AW
authors.lastname: Barclay
authors.forename: Peter
authors.initials: P
authors.lastname: Petocz
authors.forename: Joanna
authors.initials: J
authors.lastname: McMillan-Price
authors.forename: Victoria M
authors.initials: VM
authors.lastname: Flood
authors.forename: Tania
authors.initials: T
authors.lastname: Prvan
authors.forename: Paul
authors.initials: P
authors.lastname: Mitchell
authors.forename: Jennie C
authors.initials: JC
authors.lastname: Brand-Miller
mesh_terms: D000328:Adult; D000368:Aged; D001786:Blood Glucose / Q000378:metabolism*; D015992:Body Mass Index; D001943:Breast Neoplasms / Q000097:blood / Q000453:epidemiology; D002908:Chronic Disease / Q000453:epidemiology*; D015331:Cohort Studies; D016001:Confidence Intervals; D003327:Coronary Disease / Q000097:blood / Q000453:epidemiology; D003924:Diabetes Mellitus, Type 2 / Q000097:blood / Q000453:epidemiology; D004040:Dietary Carbohydrates / Q000008:administration & dosage / Q000145:classification / Q000378:metabolism*; D018450:Disease Progression; D005260:Female; D005500:Follow-Up Studies; D005705:Gallbladder Diseases / Q000097:blood / Q000453:epidemiology; D038321:Glycemic Index; D006801:Humans; D008297:Male; D008875:Middle Aged; D016017:Odds Ratio; D016016:Proportional Hazards Models; D011446:Prospective Studies; D012307:Risk Factors
chemical_list: D001786:Blood Glucose; D004040:Dietary Carbohydrates