Dataset Information

Glycemic index, glycemic load, dietary carbohydrate, and dietary fiber intake and risk of liver and biliary tract cancers in Western Europeans.

ABSTRACT:

Background

The type and quantity of dietary carbohydrate as quantified by glycemic index (GI) and glycemic load (GL), and dietary fiber may influence the risk of liver and biliary tract cancers, but convincing evidence is lacking.

Patients and methods

The association between dietary GI/GL and carbohydrate intake with hepatocellular carcinoma (HCC; N = 191), intrahepatic bile duct (IBD; N = 66), and biliary tract (N = 236) cancer risk was investigated in 477 206 participants of the European Prospective Investigation into Cancer and Nutrition cohort. Dietary intake was assessed by country-specific, validated dietary questionnaires. Hazard ratios and 95% confidence intervals were estimated from proportional hazard models. HBV/HCV status was measured in a nested case-control subset.

Results

Higher dietary GI, GL, or increased intake of total carbohydrate was not associated with liver or biliary tract cancer risk. For HCC, divergent risk estimates were observed for total sugar = 1.43 (1.17-1.74) per 50 g/day, total starch = 0.70 (0.55-0.90) per 50 g/day, and total dietary fiber = 0.70 (0.52-0.93) per 10 g/day. The findings for dietary fiber were confirmed among HBV/HCV-free participants [0.48 (0.23-1.01)]. Similar associations were observed for IBD [dietary fiber = 0.59 (0.37-0.99) per 10 g/day], but not biliary tract cancer.

Conclusions

Findings suggest that higher consumption of dietary fiber and lower consumption of total sugars are associated with lower HCC risk. In addition, high dietary fiber intake could be associated with lower IBD cancer risk.

SUBMITTER: Fedirko V

PROVIDER: S-EPMC3551485 | biostudies-literature | 2013 Feb

REPOSITORIES: biostudies-literature

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Publications

Glycemic index, glycemic load, dietary carbohydrate, and dietary fiber intake and risk of liver and biliary tract cancers in Western Europeans.

Fedirko V V Lukanova A A Bamia C C Trichopolou A A Trepo E E Nöthlings U U Schlesinger S S Aleksandrova K K Boffetta P P Tjønneland A A Johnsen N F NF Overvad K K Fagherazzi G G Racine A A Boutron-Ruault M C MC Grote V V Kaaks R R Boeing H H Naska A A Adarakis G G Valanou E E Palli D D Sieri S S Tumino R R Vineis P P Panico S S Bueno-de-Mesquita H B As HBA Siersema P D PD Peeters P H PH Weiderpass E E Skeie G G Engeset D D Quirós J R JR Zamora-Ros R R Sánchez M J MJ Amiano P P Huerta J M JM Barricarte A A Johansen D D Lindkvist B B Sund M M Werner M M Crowe F F Khaw K T KT Ferrari P P Romieu I I Chuang S C SC Riboli E E Jenab M M

Annals of oncology : official journal of the European Society for Medical Oncology 20121102 2

<h4>Background</h4>The type and quantity of dietary carbohydrate as quantified by glycemic index (GI) and glycemic load (GL), and dietary fiber may influence the risk of liver and biliary tract cancers, but convincing evidence is lacking.<h4>Patients and methods</h4>The association between dietary GI/GL and carbohydrate intake with hepatocellular carcinoma (HCC; N = 191), intrahepatic bile duct (IBD; N = 66), and biliary tract (N = 236) cancer risk was investigated in 477 206 participants of the ...[more]

PMID: 23123507

Similar Datasets

Project description:ObjectiveTo clarify the role of dietary carbohydrate, glycemic index (GI), and glycemic load (GL) in progression from health to coronary heart disease (CHD) by determining disease-nutrient risk relation (RR) values needed for intake ranges within jurisdictions and across the globe.MethodsWe performed a literature search of MEDLINE and EMBASE for prospective cohort studies that used truly valid dietary instruments in heathy adults published from January 1, 2000, to June 5, 2018. Relevant observations were extracted by 2 reviewers independently. We used dose-response meta-analysis accounting for nonindependence of results within studies. Bradford-Hill criteria were used to assess causality.ResultsEligible studies had a mean follow-up of 11 years (range, 5-19 years), were conducted in North America, Europe, and East Asia, and yielded combined RRs of 1.44 (95% CI, 1.25-1.65) per 65 g/d GL (11 studies) and 1.24 (95% CI, 1.12-1.38) per 10 U GI (10 studies) (glucose scale). The CHD-carbohydrate RR on GI was 1.66 (95% CI, 1.23-2.25) per 98 g/d of carbohydrates per 10 units GI. The 65 g/d GL, 10 U GI, and 98 g/d carbohydrate values corresponded to oral intakes from the 10th to the 90th percentiles within sampled populations. Inconsistencies were minor (I 2 ≤20%), as were small-study effects (P=.61 for GL and P=.26 for GI). Funnel plots were symmetric. Cubic spline dose-response meta-analysis yielded RRs as follows: across the global range for GL (55-290 g/d), 5.5 (95% CI, 3.1-9.8) (I 2 =0); for GI (47-82 U), 2.71 (95% CI, 1.47-4.40) (I 2 =0); and for the CHD-carbohydrate dependence on GI (50-80 U), 4.57 (95% CI, 1.86-11.4) (I 2 =16%). Bradford-Hill criteria indicated that these relations were probably causal.ConclusionStrong and probably causal CHD-GL and GI RRs exist within populations. The RRs were remarkably higher across global exposures. The results support the consideration of these markers of carbohydrate food quality in dietary guidelines for general populations.Trial registrationPROSPERO Identifier: CRD42013004504.

Project description:Background: The potential confounding effect of different amounts and proportions of macronutrients across eating patterns on meal or dietary glycemic index (GI) and glycemic load (GL) value determinations has remained partially unaddressed.Objective: The study aimed to determine the effects of different amounts of macronutrients and fiber on measured meal GI and GL values.Design: Four studies were conducted during which participants [n = 20-22; women: 50%; age: 50-80 y; body mass index (in kg/m2): 25-30)] received food challenges containing different amounts of the variable nutrient in a random order. Added to the standard 50 g available carbohydrate from white bread was 12.5, 25, or 50 g carbohydrate; 12.5, 25, or 50 g protein; and 5.6, 11.1, or 22.2 g fat from rice cereal, tuna, and unsalted butter, respectively, and 4.8 or 9.6 g fiber from oat cereal. Arterialized venous blood was sampled for 2 h, and measured meal GI and GL and insulin index (II) values were calculated by using the incremental area under the curve (AUCi) method.Results: Adding carbohydrate to the standard white-bread challenge increased glucose AUCi (P < 0.0001), measured meal GI (P = 0.0066), and mean GL (P < 0.0001). Adding protein (50 g only) decreased glucose AUCi (P = 0.0026), measured meal GI (P = 0.0139), and meal GL (P = 0.0140). Adding fat or fiber had no significant effect on these variables. Adding carbohydrate (50 g), protein (50 g), and fat (11.1 g) increased the insulin AUCi or II; fiber had no effect.Conclusions: These data indicate that uncertainty in the determination of meal GI and GL values is introduced when carbohydrate-containing foods are consumed concurrently with protein (equal amount of carbohydrate challenge) but not with carbohydrate-, fat-, or fiber-containing foods. Future studies are needed to evaluate whether this uncertainty also influences the prediction of average dietary GI and GL values for eating patterns. This trial was registered at clinicaltrials.gov as NCT01023646.

Dataset Information

Glycemic index, glycemic load, dietary carbohydrate, and dietary fiber intake and risk of liver and biliary tract cancers in Western Europeans.

Background

Patients and methods

Results

Conclusions

Publications

Glycemic index, glycemic load, dietary carbohydrate, and dietary fiber intake and risk of liver and biliary tract cancers in Western Europeans.

Similar Datasets

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