@article{27799, abstract = {{Dietary fibre is a generic term describing non-absorbed plant carbohydrates and small amounts of associated non-carbohydrate components. The main contributors of fibre to the diet are the cell walls of plant tissues, which are supramolecular polymer networks containing variable proportions of cellulose, hemicelluloses, pectic substances, and non-carbohydrate components, such as lignin. Other contributors of fibre are the intracellular storage oligosaccharides, such as fructans. A distinction needs to be made between intrinsic sources of dietary fibre and purified forms of fibre, given that the three-dimensional matrix of the plant cell wall confers benefits beyond fibre isolates. Movement through the digestive tract modifies the cell wall structure and may affect the interactions with the colonic microbes (e.g., small intestinally non-absorbed carbohydrates are broken down by bacteria to short-chain fatty acids, absorbed by colonocytes). These aspects, combined with the fibre associated components (e.g., micronutrients, polyphenols, phytosterols, and phytoestrogens), may contribute to the health outcomes seen with the consumption of dietary fibre. Therefore, where possible, processing should minimise the degradation of the plant cell wall structures to preserve some of its benefits. Food labelling should include dietary fibre values and distinguish between intrinsic and added fibre. Labelling may also help achieve the recommended intake of 14 g/1000 kcal/day.}}, author = {{Augustin, Livia S. A. and Aas, Anne-Marie and Astrup, Arnie and Atkinson, Fiona S. and Baer-Sinnott, Sara and Barclay, Alan W. and Brand-Miller, Jennie C. and Brighenti, Furio and Bullo, Monica and Buyken, Anette and Ceriello, Antonio and Ellis, Peter R. and Ha, Marie-Ann and Henry, Jeyakumar C. and Kendall, Cyril W. C. and La Vecchia, Carlo and Liu, Simin and Livesey, Geoffrey and Poli, Andrea and Salas-Salvadó, Jordi and Riccardi, Gabriele and Riserus, Ulf and Rizkalla, Salwa W. and Sievenpiper, John L. and Trichopoulou, Antonia and Usic, Kathy and Wolever, Thomas M. S. and Willett, Walter C. and Jenkins, David J. A.}}, issn = {{2072-6643}}, journal = {{Nutrients}}, title = {{{Dietary Fibre Consensus from the International Carbohydrate Quality Consortium (ICQC)}}}, doi = {{10.3390/nu12092553}}, year = {{2020}}, } @article{27800, abstract = {{ A lower 24-h urine pH (24h-pH), i.e., a higher renal excretion of free protons, at a given acid load to the body, denotes a reduction in the kidney’s capacity for net acid excretion (NAE). There is increasing evidence, not only for patients with type 2 diabetes but also for healthy individuals, that higher body fatness or waist circumference (WC) has a negative impact on renal function to excrete acids (NAE). We hypothesized that adiposity-related inflammation molecules might mediate this relation between adiposity and renal acid excretion function. Twelve biomarkers of inflammation were measured in fasting blood samples from 162 adult participants (18–25 yr old) of the Dortmund Nutritional and Anthropometric Longitudinally Designed (DONALD) study who had undergone anthropometric measurements and collected 24-h urine samples. Both Baron and Kenny’s (B&K’s) steps to test mediation and causal mediation analysis were conducted to examine the potential mediatory roles of biomarkers of inflammation in the WC-24-h pH relationship after strictly controlling for laboratory-measured NAE. In B&K’s mediation analysis, leptin, soluble intercellular adhesion molecule 1 (sICAM-1), and adiponectin significantly associated with the outcome 24-h pH and attenuated the WC-pH relation. In agreement herewith, causal mediation analysis estimated the “natural indirect effects” of WC on 24-h pH via leptin ( P = 0.01) and adiponectin ( P = 0.03) to be significant, with a trend for sICAM-1 ( P = 0.09). The calculated proportions mediated by leptin, adiponectin, and sICAM-1 were 64%, 23%, and 12%, respectively. Both mediation analyses identified an inflammatory cytokine (leptin) and an anti-inflammatory cytokine (adiponectin) along with sICAM-1 as being potentially involved in mediating adiposity-related influences on renal acid excretion capacity. }}, author = {{Hua, Yifan and Herder, Christian and Kalhoff, Hermann and Buyken, Anette and Esche, Jonas and Krupp, Danika and Wudy, Stefan A. and Remer, Thomas}}, issn = {{1931-857X}}, journal = {{American Journal of Physiology-Renal Physiology}}, pages = {{F469--F475}}, title = {{{Inflammatory mediators in the adipo-renal axis: leptin, adiponectin, and soluble ICAM-1}}}, doi = {{10.1152/ajprenal.00257.2020}}, year = {{2020}}, } @article{27801, author = {{Nyasordzi, Juliana and Penczynski, Katharina and Remer, Thomas and Buyken, Anette}}, issn = {{1932-6203}}, journal = {{PLOS ONE}}, title = {{{Early life factors and their relevance to intima-media thickness of the common carotid artery in early adulthood}}}, doi = {{10.1371/journal.pone.0233227}}, year = {{2020}}, } @article{27803, author = {{Schwingshackl, Lukas and Neuenschwander, Manuela and Hoffmann, Georg and Buyken, Anette and Schlesinger, Sabrina}}, issn = {{0002-9165}}, journal = {{The American Journal of Clinical Nutrition}}, pages = {{917--918}}, title = {{{Reply to Khan et al.}}}, doi = {{10.1093/ajcn/nqaa006}}, year = {{2020}}, } @article{27806, abstract = {{AbstractTrend analyses based on dietary records suggest decreases in the intakes of total sugar (TS), added and free sugar since 2005 among children and adolescents in Germany. In terms of age trends, TS intake decreased with increasing age. However, self-reported sugar intake in epidemiological studies is criticised, as it may be prone to bias due to selective underreporting. Furthermore, adolescents are more susceptible to underreporting than children. We thus analysed time and age trends in urinary fructose excretion (FE), sucrose excretion (SE) and the sum of both (FE + SE) as biomarkers for sugar intake among 8·5–16·5-year-old adolescents. Urinary sugar excretion was measured by UPLC-MS/MS in 997 24-h urine samples collected from 239 boys and 253 girls participating in the Dortmund Nutritional and Anthropometric Longitudinally Designed (DONALD) study cohort between 1990 and 2016. Time and age trends of log-transformed FE, SE and FE + SE were analysed using polynomial mixed-effects regression models. Between 1990 and 2016, FE as well as FE + SE decreased (linear time trend: P = 0·0272 and P < 0·0001, respectively). A minor increase in excretion during adolescence was confined to FE (linear age trend: P = 0·0017). The present 24-h excretion measurements support a previously reported dietary record-based decline in sugar intake since 2005. However, the previously seen dietary record-based decrease in TS from childhood to late adolescence was not confirmed by our biomarker analysis, suggesting a constant sugar intake for the period of adolescence.}}, author = {{Perrar, Ines and Gray, Nicola and Kuhnle, Gunter G. and Remer, Thomas and Buyken, Anette and Alexy, Ute}}, issn = {{0007-1145}}, journal = {{British Journal of Nutrition}}, pages = {{164--172}}, title = {{{Sugar intake among German adolescents: trends from 1990 to 2016 based on biomarker excretion in 24-h urine samples}}}, doi = {{10.1017/s0007114520000665}}, year = {{2020}}, } @article{27807, abstract = {{There is no question that elevated postprandial glycemia is a significant driver of common chronic diseases globally [...]}}, author = {{Brand-Miller, Jennie and Buyken, Anette}}, issn = {{2072-6643}}, journal = {{Nutrients}}, title = {{{The Relationship between Glycemic Index and Health}}}, doi = {{10.3390/nu12020536}}, year = {{2020}}, } @article{27021, author = {{Jansen, Kathrin and Tempes, Jana and Drozdowska, Alina and Gutmann, Maike and Falkenstein, Michael and Buyken, Anette and Libuda, Lars and Rudolf, Henrik and Lücke, Thomas and Kersting, Mathilde}}, issn = {{0954-3007}}, journal = {{European Journal of Clinical Nutrition}}, pages = {{757--764}}, title = {{{Short-term effects of carbohydrates differing in glycemic index (GI) consumed at lunch on children’s cognitive function in a randomized crossover study}}}, doi = {{10.1038/s41430-020-0600-0}}, year = {{2020}}, } @article{27003, author = {{Perrar, Ines and Schmitting, Sarah and Della Corte, Karen W. and Buyken, Anette and Alexy, Ute}}, issn = {{1436-6207}}, journal = {{European Journal of Nutrition}}, pages = {{1043--1054}}, title = {{{Age and time trends in sugar intake among children and adolescents: results from the DONALD study}}}, doi = {{10.1007/s00394-019-01965-y}}, year = {{2019}}, } @article{27004, author = {{Wong, Tommy H. T. and Buyken, Anette and Brand-Miller, Jennie C. and Louie, Jimmy Chun Yu}}, issn = {{1436-6207}}, journal = {{European Journal of Nutrition}}, pages = {{2357--2367}}, title = {{{Is there a soft drink vs. alcohol seesaw? A cross-sectional analysis of dietary data in the Australian Health Survey 2011–12}}}, doi = {{10.1007/s00394-019-02084-4}}, year = {{2019}}, } @article{27005, abstract = {{ABSTRACT Background There is controversy on the relevance of dietary sugar intake for cardiometabolic health. Objective The aim of this network meta-analysis (NMA) was to assess how isocaloric substitutions of dietary sugar with other carbohydrates affect cardiometabolic risk factors, comparing different intervention studies. Methods We included randomized controlled trials (RCTs) investigating the isocaloric effect of substituting dietary sugars (fructose, glucose, sucrose) with other sugars or starch on cardiometabolic risk markers, including LDL cholesterol, triacylglycerol (TG), fasting glucose (FG), glycated hemoglobin (HbA1c), insulin resistance (HOMA-IR), uric acid, C-reactive protein (CRP), alanine transaminase (ALT), aspartate transaminase (AST), and liver fat content. To identify the most beneficial intervention for each outcome, random-effects NMA was conducted by calculating pooled mean differences (MDs) with 95% CIs, and by ranking the surface under the cumulative ranking curves (SUCRAs). The certainty of evidence was evaluated using the Confidence In Network Meta-Analysis tool. Results Thirty-eight RCTs, including 1383 participants, were identified. A reduction in LDL-cholesterol concentrations was shown for the exchange of sucrose with starch (MD: −0.23 mmol/L; 95% CI: −0.38, −0.07 mmol/L) or fructose with starch (MD: −0.22 mmol/L; 95% CI: −0.39, −0.05 mmol/L; SUCRAstarch: 98%). FG concentrations were also lower for the exchange of sucrose with starch (MD: −0.14 mmol/L; 95% CI: −0.29, 0.01 mmol/L; SUCRAstarch: 91%). Replacing fructose with an equivalent energy amount of glucose reduced HOMA-IR (MD: −0.36; 95% CI: −0.71, −0.02; SUCRAglucose: 74%) and uric acid (MD: −23.77 µmol/L; 95% CI: −44.21, −3.32 µmol/L; SUCRAglucose: 93%). The certainty of evidence was rated very low to moderate. No significant effects were observed for TG, HbA1c, CRP, ALT, and AST. Conclusions Our findings indicate that substitution of sucrose and fructose with starch yielded lower LDL cholesterol. Insulin resistance and uric acid concentrations were beneficially affected by replacement of fructose with glucose. Our findings are limited by the very low to moderate certainty of evidence. This review was registered at www.crd.york.ac.uk/prospero as CRD42018080297. }}, author = {{Schwingshackl, Lukas and Neuenschwander, Manuela and Hoffmann, Georg and Buyken, Anette and Schlesinger, Sabrina}}, issn = {{0002-9165}}, journal = {{The American Journal of Clinical Nutrition}}, title = {{{Dietary sugars and cardiometabolic risk factors: a network meta-analysis on isocaloric substitution interventions}}}, doi = {{10.1093/ajcn/nqz273}}, year = {{2019}}, } @article{27006, abstract = {{Trend analyses suggest that free sugar (FS) intake—while still exceeding 10%E—has decreased among German children and adolescents since 2005, yet that intakes may shift from sugars naturally occurring in foods to added sugars as children age. Thus, we analysed time and age trends in FS intake (%E) from food groups among 3–18 year-olds (1985–2016) using 10,761 3-day dietary records from 1312 DONALD participants (660 boys, 652 girls) by use of polynomial mixed-effects regression models. Among girls, FS from sugar & sweets decreased from 1985 to 2016 (linear trend p < 0.0001), but not among boys (p > 0.05). In the total sample, FS intake from juices increased until 2000 and decreased since 2005 (linear, quadratic trend p < 0.0001). FS from sugar sweetened beverages (SSB) decreased non-linearly from 1985 to 2016 (girls: linear, quadratic, cubic trend p < 0.0001; boys: linear, quadratic, cubic trend p < 0.02). Younger children consumed more FS from juices than older ones, who had a higher FS intake from SSB. FS intake from sugar & sweets increased until early adolescence and decreased afterwards. Since sugar & sweets represent the main source of FS intake and the source with the least pronounced decline in intake, public health measures should focus on these products.}}, author = {{Perrar, Ines and Schadow, Alena M. and Schmitting, Sarah and Buyken, Anette and Alexy, Ute}}, issn = {{2072-6643}}, journal = {{Nutrients}}, title = {{{Time and Age Trends in Free Sugar Intake from Food Groups among Children and Adolescents between 1985 and 2016}}}, doi = {{10.3390/nu12010020}}, year = {{2019}}, } @article{27758, abstract = {{Published meta-analyses indicate significant but inconsistent incident type-2 diabetes (T2D)-dietary glycemic index (GI) and glycemic load (GL) risk ratios or risk relations (RR). It is now over a decade ago that a published meta-analysis used a predefined standard to identify valid studies. Considering valid studies only, and using random effects dose–response meta-analysis (DRM) while withdrawing spurious results (p < 0.05), we ascertained whether these relations would support nutrition guidance, specifically for an RR > 1.20 with a lower 95% confidence limit >1.10 across typical intakes (approximately 10th to 90th percentiles of population intakes). The combined T2D–GI RR was 1.27 (1.15–1.40) (p < 0.001, n = 10 studies) per 10 units GI, while that for the T2D–GL RR was 1.26 (1.15–1.37) (p < 0.001, n = 15) per 80 g/d GL in a 2000 kcal (8400 kJ) diet. The corresponding global DRM using restricted cubic splines were 1.87 (1.56–2.25) (p < 0.001, n = 10) and 1.89 (1.66–2.16) (p < 0.001, n = 15) from 47.6 to 76.1 units GI and 73 to 257 g/d GL in a 2000 kcal diet, respectively. In conclusion, among adults initially in good health, diets higher in GI or GL were robustly associated with incident T2D. Together with mechanistic and other data, this supports that consideration should be given to these dietary risk factors in nutrition advice. Concerning the public health relevance at the global level, our evidence indicates that GI and GL are substantial food markers predicting the development of T2D worldwide, for persons of European ancestry and of East Asian ancestry.}}, author = {{Livesey, Geoffrey and Taylor, Richard and Livesey, Helen F. and Buyken, Anette and Jenkins, David J. A. and Augustin, Livia S. A. and Sievenpiper, John L. and Barclay, Alan W. and Liu, Simin and Wolever, Thomas M. S. and Willett, Walter C. and Brighenti, Furio and Salas-Salvadó, Jordi and Björck, Inger and Rizkalla, Salwa W. and Riccardi, Gabriele and Vecchia, Carlo La and Ceriello, Antonio and Trichopoulou, Antonia and Poli, Andrea and Astrup, Arne and Kendall, Cyril W. C. and Ha, Marie-Ann and Baer-Sinnott, Sara and Brand-Miller, Jennie C.}}, issn = {{2072-6643}}, journal = {{Nutrients}}, title = {{{Dietary Glycemic Index and Load and the Risk of Type 2 Diabetes: A Systematic Review and Updated Meta-Analyses of Prospective Cohort Studies}}}, doi = {{10.3390/nu11061280}}, year = {{2019}}, } @article{27759, abstract = {{While dietary factors are important modifiable risk factors for type 2 diabetes (T2D), the causal role of carbohydrate quality in nutrition remains controversial. Dietary glycemic index (GI) and glycemic load (GL) have been examined in relation to the risk of T2D in multiple prospective cohort studies. Previous meta-analyses indicate significant relations but consideration of causality has been minimal. Here, the results of our recent meta-analyses of prospective cohort studies of 4 to 26-y follow-up are interpreted in the context of the nine Bradford-Hill criteria for causality, that is: (1) Strength of Association, (2) Consistency, (3) Specificity, (4) Temporality, (5) Biological Gradient, (6) Plausibility, (7) Experimental evidence, (8) Analogy, and (9) Coherence. These criteria necessitated referral to a body of literature wider than prospective cohort studies alone, especially in criteria 6 to 9. In this analysis, all nine of the Hill’s criteria were met for GI and GL indicating that we can be confident of a role for GI and GL as causal factors contributing to incident T2D. In addition, neither dietary fiber nor cereal fiber nor wholegrain were found to be reliable or effective surrogate measures of GI or GL. Finally, our cost–benefit analysis suggests food and nutrition advice favors lower GI or GL and would produce significant potential cost savings in national healthcare budgets. The high confidence in causal associations for incident T2D is sufficient to consider inclusion of GI and GL in food and nutrient-based recommendations.}}, author = {{Livesey, Geoffrey and Taylor, Richard and Livesey, Helen F. and Buyken, Anette and Jenkins, David J. A. and Augustin, Livia S. A. and Sievenpiper, John L. and Barclay, Alan W. and Liu, Simin and Wolever, Thomas M. S. and Willett, Walter C. and Brighenti, Furio and Salas-Salvadó, Jordi and Björck, Inger and Rizkalla, Salwa W. and Riccardi, Gabriele and Vecchia, Carlo La and Ceriello, Antonio and Trichopoulou, Antonia and Poli, Andrea and Astrup, Arne and Kendall, Cyril W. C. and Ha, Marie-Ann and Baer-Sinnott, Sara and Brand-Miller, Jennie C.}}, issn = {{2072-6643}}, journal = {{Nutrients}}, title = {{{Dietary Glycemic Index and Load and the Risk of Type 2 Diabetes: Assessment of Causal Relations}}}, doi = {{10.3390/nu11061436}}, year = {{2019}}, } @article{27772, author = {{Oluwagbemigun, Kolade and Buyken, Anette and Alexy, Ute and Schmid, Matthias and Herder, Christian and Nöthlings, Ute}}, issn = {{1475-2840}}, journal = {{Cardiovascular Diabetology}}, title = {{{Developmental trajectories of body mass index from childhood into late adolescence and subsequent late adolescence–young adulthood cardiometabolic risk markers}}}, doi = {{10.1186/s12933-019-0813-5}}, year = {{2019}}, } @article{27981, author = {{Weber, KS and Simon, MC and Strassburger, K and Markgraf, DF and Buyken, Anette and Szendroedi, J and Müssig, K and Roden, M and Group, GDS}}, issn = {{2072-6643}}, journal = {{Nutrients}}, number = {{6}}, title = {{{Habitual Fructose Intake Relates to Insulin Sensitivity and Fatty Liver Index in Recent-Onset Type 2 Diabetes Patients and Individuals without Diabetes.}}}, doi = {{10.3390/nu10060774}}, volume = {{10}}, year = {{2018}}, } @article{25929, author = {{Buyken, Anette and Mela, DJ and Dussort, P and Johnson, IT and Macdonald, IA and Stowell, JD and FJPH, Brouns}}, issn = {{0954-3007}}, journal = {{Eur J Clin Nutr}}, number = {{12}}, pages = {{1625--1643}}, title = {{{Dietary carbohydrates: a review of international recommendations and the methods used to derive them.}}}, doi = {{10.1038/s41430-017-0035-4}}, volume = {{72}}, year = {{2018}}, } @article{26890, author = {{Buyken, Anette and Cheng, Guo and Günther, Anke LB and Liese, Angela D and Remer, Thomas and Karaolis-Danckert, Nadina}}, issn = {{0002-9165}}, journal = {{The American Journal of Clinical Nutrition}}, pages = {{755--762}}, title = {{{Relation of dietary glycemic index, glycemic load, added sugar intake, or fiber intake to the development of body composition between ages 2 and 7 y}}}, doi = {{10.1093/ajcn/88.3.755}}, year = {{2018}}, } @article{26928, author = {{Penczynski, Katharina J. and Herder, Christian and Krupp, Danika and Rienks, Johanna and Egert, Sarah and Wudy, Stefan A. and Roden, Michael and Remer, Thomas and Buyken, Anette}}, issn = {{1436-6207}}, journal = {{European Journal of Nutrition}}, pages = {{1159--1172}}, title = {{{Flavonoid intake from fruit and vegetables during adolescence is prospectively associated with a favourable risk factor profile for type 2 diabetes in early adulthood}}}, doi = {{10.1007/s00394-018-1631-3}}, year = {{2018}}, } @article{26999, author = {{Della Corte, Karen and Perrar, Ines and Penczynski, Katharina and Schwingshackl, Lukas and Herder, Christian and Buyken, Anette}}, issn = {{2072-6643}}, journal = {{Nutrients}}, title = {{{Effect of Dietary Sugar Intake on Biomarkers of Subclinical Inflammation: A Systematic Review and Meta-Analysis of Intervention Studies}}}, doi = {{10.3390/nu10050606}}, year = {{2018}}, } @article{27000, author = {{Koch, Stefanie A. J. and Alexy, Ute and Diederichs, Tanja and Buyken, Anette and Roßbach, Sarah}}, issn = {{1932-6203}}, journal = {{PLOS ONE}}, title = {{{The relevance of restrained eating behavior for circadian eating patterns in adolescents}}}, doi = {{10.1371/journal.pone.0197131}}, year = {{2018}}, }