Is industrial fructose just a marker of an unhealthy dietary pattern?
Notice bibliographique
Résumé
Industrial, not fruit fructose intake is associated with the severity of liver fibrosis in genotype 1 chronic hepatitis C patientsJournal of HepatologyVol. 59Issue 6PreviewUnhealthy food intake, specifically fructose, has been associated with metabolic alterations and with the severity of liver fibrosis in patients with non-alcoholic fatty liver disease. In a cohort of patients with genotype 1 chronic hepatitis C (G1 CHC), we tested the association of fructose intake with the severity of liver histology. Full-Text PDF Reply to: “Is industrial fructose just a marker of an unhealthy dietary pattern?”Journal of HepatologyVol. 61Issue 1PreviewWe recently reported a link between fructose intake and the severity of liver fibrosis in a cohort of Italian patients with genotype 1 (G1) chronic hepatitis C (CHC) [1]. In particular, the association holds true for “industrial” only, not for “fruit” fructose intake. Full-Text PDF Open Access We read with interest the cross-sectional study by Petta et al. [[1]Petta S. Marchesini G. Caracausi L. Macaluso F.S. Camma C. Ciminnisi S. et al.Industrial, not fruit fructose intake is associated with the severity of liver fibrosis in genotype 1 chronic hepatitis C patients.J Hepatol. 2013; 59: 1169-1176Abstract Full Text Full Text PDF PubMed Scopus (31) Google Scholar] showing that “industrial” fructose and not fruit fructose intake is associated with liver fibrosis in biopsy-proven genotype 1 chronic hepatitis C (G1CHC) patients. We are concerned that important confounders were not included in their analytical models. The authors selected their multivariate models based on the significance of variables in univariate models. Taking this approach, important confounders may have been missed. One of the most important confounders in nutrition is that of energy, a factor intrinsic to all foods. Although neither “hypercaloric” nor “energy intake” were significant in univariate models, both were significantly associated with fructose intake. Excess energy has also been shown to be an important mediating factor in the effects of fructose on cardiometabolic risk. In a series of systematic reviews and meta-analyses of controlled feeding trials, we found that fructose in isocaloric exchange for other carbohydrates (energy matched conditions) showed no signal for harm in relation to markers of non-alcoholic fatty liver disease (NAFLD) [[2]Chiu S. Sievenpiper J.L., de Souza R.J. Cozma A.I. Mirrahimi A. Carleton A.J. et al.Effect of fructose on markers of Non-Alcoholic Fatty Liver Disease (NAFLD): a systematic review and meta-analysis of controlled feeding trials.Eur J Clin Nutr. 2014; ([Epub ahead of print])https://doi.org/10.1038/ejcn.2014.8Crossref PubMed Scopus (219) Google Scholar] as well as body weight [[3]Sievenpiper J.L. de Souza R.J. Mirrahimi A. Yu M.E. Carleton A.J. Beyene J. et al.Effect of fructose on body weight in controlled feeding trials: a systematic review and meta-analysis.Ann Intern Med. 2012; 21: 291-304Crossref Scopus (234) Google Scholar], glycemic control [[4]Cozma A.I. Sievenpiper J.L. de Souza R.J. Chiavaroli L. Ha V. Wang D.D. et al.Effect of fructose on glycemic control in diabetes: a systematic review and meta-analysis of controlled feeding trials.Diabetes Care. 2012; 35: 1611-1620Crossref PubMed Scopus (165) Google Scholar], insulin [[4]Cozma A.I. Sievenpiper J.L. de Souza R.J. Chiavaroli L. Ha V. Wang D.D. et al.Effect of fructose on glycemic control in diabetes: a systematic review and meta-analysis of controlled feeding trials.Diabetes Care. 2012; 35: 1611-1620Crossref PubMed Scopus (165) Google Scholar], serum fasting lipids [[5]Sievenpiper J.L. Carleton A.J. Chatha S. Jiang H.Y. de Souza R.J. Beyene J. et al.Heterogeneous effects of fructose on blood lipids in individuals with type 2 diabetes: systematic review and meta-analysis of experimental trials in humans.Diabetes Care. 2009; 32: 1930-1937Crossref PubMed Scopus (141) Google Scholar], postprandial triglycerides [[6]Wang D.D. Sievenpiper J.L. De Souza R.J. Cozma A.I. Chiavaroli L. Ha V. et al.Effect of fructose on postprandial triglycerides: a systematic review and meta-analysis of controlled feeding trials.Atherosclerosis. 2014; 232: 125-133Abstract Full Text Full Text PDF PubMed Scopus (134) Google Scholar], blood pressure [[7]Ha V. Sievenpiper J.L. de Souza R.J. Chiavaroli L. Wang D.D. Cozma A.I. et al.Effect of fructose on blood pressure: a systematic review and meta-analysis of controlled feeding trials.Hypertension. 2012; 59: 787-795Crossref PubMed Scopus (149) Google Scholar], and uric acid [[8]Wang D.D. Sievenpiper J.L. de Souza R.J. Chiavaroli L. Ha V. Cozma A.I. et al.The effects of fructose intake on serum uric acid vary among controlled dietary trials.J Nutr. 2012; 142: 916-923Crossref PubMed Scopus (166) Google Scholar]. A lack of harm is seen even under conditions of fructose overfeeding (positive energy balance) at high doses, as long as the comparison with the carbohydrate comparator remains matched for the excess calories. There may, however, be a dose threshold for some fasting lipid effects in some high dose subgroup analyses [[5]Sievenpiper J.L. Carleton A.J. Chatha S. Jiang H.Y. de Souza R.J. Beyene J. et al.Heterogeneous effects of fructose on blood lipids in individuals with type 2 diabetes: systematic review and meta-analysis of experimental trials in humans.Diabetes Care. 2009; 32: 1930-1937Crossref PubMed Scopus (141) Google Scholar]. A consistent signal for harm is not seen until one examines fructose in imbalanced, hypercaloric comparisons. If fructose supplements background diets with excess energy compared with the same diets without the excess energy, then one sees adverse effects on markers of NAFLD and other cardiometabolic risk factors [2Chiu S. Sievenpiper J.L., de Souza R.J. Cozma A.I. Mirrahimi A. Carleton A.J. et al.Effect of fructose on markers of Non-Alcoholic Fatty Liver Disease (NAFLD): a systematic review and meta-analysis of controlled feeding trials.Eur J Clin Nutr. 2014; ([Epub ahead of print])https://doi.org/10.1038/ejcn.2014.8Crossref PubMed Scopus (219) Google Scholar, 3Sievenpiper J.L. de Souza R.J. Mirrahimi A. Yu M.E. Carleton A.J. Beyene J. et al.Effect of fructose on body weight in controlled feeding trials: a systematic review and meta-analysis.Ann Intern Med. 2012; 21: 291-304Crossref Scopus (234) Google Scholar, 4Cozma A.I. Sievenpiper J.L. de Souza R.J. Chiavaroli L. Ha V. Wang D.D. et al.Effect of fructose on glycemic control in diabetes: a systematic review and meta-analysis of controlled feeding trials.Diabetes Care. 2012; 35: 1611-1620Crossref PubMed Scopus (165) Google Scholar, 5Sievenpiper J.L. Carleton A.J. Chatha S. Jiang H.Y. de Souza R.J. Beyene J. et al.Heterogeneous effects of fructose on blood lipids in individuals with type 2 diabetes: systematic review and meta-analysis of experimental trials in humans.Diabetes Care. 2009; 32: 1930-1937Crossref PubMed Scopus (141) Google Scholar, 6Wang D.D. Sievenpiper J.L. De Souza R.J. Cozma A.I. Chiavaroli L. Ha V. et al.Effect of fructose on postprandial triglycerides: a systematic review and meta-analysis of controlled feeding trials.Atherosclerosis. 2014; 232: 125-133Abstract Full Text Full Text PDF PubMed Scopus (134) Google Scholar, 7Ha V. Sievenpiper J.L. de Souza R.J. Chiavaroli L. Wang D.D. Cozma A.I. et al.Effect of fructose on blood pressure: a systematic review and meta-analysis of controlled feeding trials.Hypertension. 2012; 59: 787-795Crossref PubMed Scopus (149) Google Scholar, 8Wang D.D. Sievenpiper J.L. de Souza R.J. Chiavaroli L. Ha V. Cozma A.I. et al.The effects of fructose intake on serum uric acid vary among controlled dietary trials.J Nutr. 2012; 142: 916-923Crossref PubMed Scopus (166) Google Scholar]. In the absence of a clear effect on markers of NAFLD and its related cardiometabolic risk factors in isocaloric comparisons (especially under conditions of positive energy balance), the effects seen in the hypercaloric comparisons appear to relate more to the excess energy than the fructose. Adjustment for total energy intake would therefore seem essential in understanding whether an association with fructose exists beyond the energy it contributes. Other lifestyle factors associated with NAFLD were also not adjusted for in their multivariate models. These include smoking, exercise, total fat, trans fat, saturated fat, cholesterol, the n-6:-3 ratio of polyunsaturated fatty acids, total carbohydrate, animal protein, dietary fibre, and an overall Western dietary pattern which embodies these variables. Even if some of these factors were not significant in univariate analyses, each has been shown to have an equal or stronger association with NAFLD [9Mouzaki M. Allard J.P. The role of nutrients in the development, progression, and treatment of nonalcoholic fatty liver disease.J Clin Gastroenterol. 2012; 46: 457-467Crossref PubMed Scopus (88) Google Scholar, 10Zein C.O. Unalp A. Colvin R. Liu Y.C. McCullough A.J. Nonalcoholic steatohepatitis clinical research network. Smoking and severity of hepatic fibrosis in nonalcoholic fatty liver disease.J Hepatol. 2011; 54: 753-759Abstract Full Text Full Text PDF PubMed Scopus (161) Google Scholar] and may contribute to residual confounding. These factors individually and collectively may also contribute to important collinearity effects, as high consumers of added sugars (in the form of sugar sweetened beverages) tend to smoke more, exercise less, and eat more calories in the form of a Western dietary pattern characterized by increased red meat, processed meat, potato products, and refined grains. The lack of adjustment for these factors greatly complicates the interpretation of the results. In the absence of adjustment for factors associated with NAFLD, one cannot conclude with confidence that “industrial” fructose is a risk factor for liver fibrosis in biopsy-proven G1CHC patients. Added fructose from industrial sources may simply represent a marker of an unhealthy lifestyle pattern in these patients. To understand whether fructose is an independent predictor of liver fibrosis, the authors must address these confounders in future models. There also remains an urgent need for higher quality evidence from well-conducted prospective observational studies with good measurements of exposure and the ability to adjust for known confounders as well as longer, larger, higher quality randomized controlled trials of the effect of fructose on the progression of NAFLD. LC has received research support from the Canadian Institutes of Health Research (CIHR) and is a clinical research coordinator at Glycemic Index Laboratories, Toronto, Ontario, Canada. VH has received a Province of Ontario Graduate Scholarship and research support from the Canadian Institutes of Health Research (CIHR) and World Health Organization (WHO) for work on a systematic review and meta-analysis commissioned by the WHO of the relation of saturated fatty acids with health outcomes. She also received a travel award to attend the “Journey Through Science Day” hosted by PepsiCo and the New York Academy of Sciences (NYAS). RJdS is funded by a CIHR Postdoctoral Fellowship Award and has received research support from the CIHR, Calorie Control Council, the Canadian Foundation for Dietetic Research (CFDR), and The Coca-Cola Company (investigator initiated, unrestricted grant). He has served as an external resource person to the World Health Organization’s (WHO) Nutrition Guidelines Advisory Group (NUGAG), and is the lead author of two systematic reviews and meta-analyses commissioned by the WHO of the relation of saturated fatty acids and trans fatty acids with health outcomes. The WHO paid for his travel and accommodation to attend NUGAG Meetings in Hangzhou, China and Copenhagen, Denmark. CWCK has received research grants, travel funding, consultant fees, honoraria, or has served on the scientific advisory board for Abbott Laboratories, Advanced Food Materials Network, Agrifoods and Agriculture Canada (AAFC), Almond Board of California, American Peanut Council, American Pistachio Growers, Barilla, California Strawberry Commission, Bayer, Calorie Control Council, Canadian Institutes of Health Research (CIHR), Canola Council of Canada, The Coca Cola Company (investigator initiated, unrestricted), Danone, General Mills, Hain Celestial, International Tree Nut Council, Kellogg, Kraft, Loblaw Brands Ltd, Nutrition Foundation of Italy, Oldways Preservation Trust, Orafti, Paramount Farms, Peanut Institute, Pepsi-Co, Pulse Canada, Sabra Dipping Co., Saskatchewan Pulse Growers, Solae, Sun-Maid, Tate & Lyle and Unilever. JLS has received research support from the Canadian Institutes of Health Research (CIHR), Calorie Control Council, The Coca-Cola Company (investigator initiated, unrestricted educational grant), Dr. Pepper Snapple Group (investigator initiated, unrestricted educational grant), Pulse Canada, and The International Tree Nut Council Nutrition Research & Education Foundation. He has received travel funding, speaker fees, and/or honoraria from the American Heart Association (AHA), American College of Physicians (ACP), American Society for Nutrition (ASN), National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) of the National Institutes of Health (NIH), Canadian Diabetes Association (CDA), Canadian Nutrition Society (CNS), University of South Carolina, University of Alabama at Birmingham, Calorie Control Council, Diabetes and Nutrition Study Group (DNSG) of the European Association for the Study of Diabetes (EASD), International Life Sciences Institute (ILSI) North America, ILSI Brazil, Abbott Laboratories, Pulse Canada, Canadian Sugar Institute, Dr. Pepper Snapple Group, and The Coca-Cola Company. He is on the Clinical Practice Guidelines Expert Committee for Nutrition Therapy of both the CDA and EASD, as well as being on the ASN writing panel for a scientific statement on the metabolic and nutritional effects of fructose, sucrose and high fructose corn syrup. He is a member of the International Carbohydrate Quality Consortium (ICQC) and an unpaid scientific advisor for the ILSI North America, Food, Nutrition, and Safety Program (FNSP). His wife is an employee of Unilever Canada.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,018 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,001 | 0,002 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,004 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».