Sugars, Obesity, and Cardiometabolic risk

Sugars, Obesity, and Cardiometabolic risk John L Sievenpiper, MD, PhD, FRCPC 1,2,3,4 1 Consultant Physician, Division of Endocrinology, St. Michael s Hospital, University of Toronto 2 Scientist, Li Ka Shing Knowledge Institute, St. Michael s Hospital, University of Toronto 3 Knowledge Synthesis Lead, Toronto 3D Knowledge Synthesis & Clinical Trials Unit, St. Michael s Hospital, University of Toronto Advances & Controversies in Clinical Nutrition Controversy Session: Sugars and Health: Are we winning the battle, but losing the war National Harbor, MD December 4-6, 2014

Disclosures (over past 24 mos) Board Member/Advisory Panel Canadian Diabetes Association (CDA) 2013 Clinical Practice Guidelines Expert Committee for Nutrition therapy European Association for the Study of Diabetes (EASD) 2015 Clinical Practice Guidelines Expert Committee for Nutrition therapy American Society for Nutrition (ASN) writing panel for a scientific statement on sugars International Life Science Institute (ILSI) North America, Food, Nutrition, and Safety Program (FNSP) Advisory Panel Transcultural Diabetes Algorithm (tdna) Group Diabetes Nutrition Study Group (DNSG) of the European Association for the Study of Diabetes (EASD) Board Research Support American Society of Nutrition (ASN) Canadian Institutes of Health Research (CIHR) Calorie Control Council The Coca Cola Company (unrestricted, investigator initiated) Pulse Canada International Tree Nut Council Nutrition Research & Education Foundation Dr. Pepper Snapple Group (unrestricted, investigator initiated) Consulting Arrangements Tate & Lyle Winston Strawn LLP Perkins Coie LLP Honouria or Speaker fees American Society of Nutrition (ASN) National Institutes of health (NIH) American College of Physicians (ACP) American Heart Association (AHA) Canadian Nutrition Society (CNS) Canadian Diabetes Association (CDA) University of Alabama at Birmingham University of South Carolina International Life Sciences Institute (ILSI) North American International Life Sciences Institute (ILSI) Brazil Pulse Canada Abbott Laboratories Calorie Control Council The Coca Cola Company Canadian Sugar Institute Dr. Pepper Snapple Group Dairy Farmers of Canada Other Spouse is an employee of Unilever Canada Editorial Board, American Journal of Clinical Nutrition Associate Editor, Frontiers in Nutrition, Nutrition Methodology Special Issue ("Sugar and Obesity ) Editor, Nutrients

OBJECTIVES 1.Understand the role of fructose s unique biochemistry, metabolism, and endocrine responses 2.Assess the evidence from prospective cohort studies linking fructose-containing sugars with obesity 3.Discuss the role of energy in the effect of sugars on weight gain in controlled trials

Ecological relationship between fructose intake and prevalence of Overweight/Obesity:1961-2000 Bray GA, et a. Am J Clin Nutr. 2004 Apr;79(4):537-43 Flegal KM, et al. JAMA 2002;288:1723 7. Vuilleumier S.. Am J Clin Nutr 1993;58(suppl):733S 6S.

A Canadian Paradox estimated sugar intake has decreased while obesity has increased: Canadian Community Health Survey (CCHS), National Population Health Survey (NPHS), & Statistics Canada Total sugars = 21% (added sugars = 11%) Brisbois TD et al. Nutrients. 2014;6:1899-912. http://www.statcan.gc.ca/pub/82-003-x/2011003/article/11540-eng.pdf

Ecological relation of water intake with prevalence of Overweight/Obesity: 1961-2000 Kaiser et al. Obes Rev. 2013 Jun 7. doi: 10.1111/obr.12048.

Fructose as an unregulated substrate for de novo lipogenesis (DNL)

A sugar (fructose)-centric view of cardiometabolic disease emerges

Sugars the new dominant public health issue: WHO proposed update to sugars recommendations Important caveats 1.Recommendations were based exclusively on dental caries and body weight 2.The body weight effects are mediated via changes in energy intakes 3.The 10% & 5% recommendations were based exclusively on dental caries 4.The 5% recommendation was based on very low quality evidence http://www.who.int/nutrition/sugars_public_consultation/en/

What is the evidence?

Hierarchy of evidence in evidence based medicine Systematic Reviews & meta-analyses Decreasing bias RCTs Non-randomized controlled trials (NRCT) Cohorts studies Case-control studies Cross-sectional studies Case series/time series Expert opinion http://www.sign.ac.uk/guidelines/fulltext/50/annexb.html http://www.cnpp.usda.gov/publications/nutritioninsights/insight38.pdf http://www.nice.org.uk/nicemedia/pdf/gdm_chapter7_0305.pdf

PROSPECTIVE COHORTS

What about Sugar Sweetened Beverages (SSBs)?

Fructose-containing Sugar-sweetened beverages (SSBs) and Incident Cardiometabolic Disease Diabetes/MetS (epi) Hypertension (epi) SSBs Gout (epi) Overweight/Obesity (epi) CHD (epi) Important caveats Stroke (epi) 1. Relationship only seen in extreme quantiles analyses with few exceptions 2. Associations lose significance or are greatly attenuated by adjustement for energy 3. Residual confounding from important collinearity: high consumers eat more calories, exercise less, smoke more, and have a poorer dietary pattern

How do SSBs compare with other risk factors?

Increased servings of different foods contribute to weight change over 4 year intervals: NHS I (1986-2006), NHS II (1991-2003) and HPFS (1986-2006), N=120 877 +1.69lb +3.35lb +0.57lb +1.00lb +0.95 lb +0.93 lb +0.65lb **Multivariate adjustment for age, BMI, sleep, physical activity, alcohol, television watching, smoking, and all dietary factors** +0.28 to 0.36lb Mozaffarian et al. NEJM 2011;364:2392-2404

Increased servings of different foods contribute to weight change over 4 year intervals: NHS I (1986-2006), NHS II (1991-2003) and HPFS (1986-2006), N=120 877-0.49lb -0.22lb -0.57lb -0.82lb -0.37lb -0.11lb **Multivariate adjustment for age, BMI, sleep, physical activity, alcohol, television watching, smoking, and all dietary factors** Mozaffarian et al. NEJM 2011;364:2392-2404

Population attributable burden of disease for 20 leading risk factors in North America in 2010: How do SSBs compare with other risk factors? Lim et al. Lancet 2012; 380: 2224 60

Why are SSBs associated with increased obesity cardiometabolic risk? 1. is it because liquid calories are poorly compensated? 2. is it because SSBs are a marker of an unhealthy lifestyle? 3. Is it the sugars (fructose)?

Meta-analyses of Fructose-containing Sugars and Incident Cardiometabolic Disease (NCT01608620) Weight change Diabetes risk Sugars Hypertension risk (Jaylath et al. J Am Coll Nutr, in press) Gout risk CHD (epi)

Meta-analyses of Fructose-containing Sugars and Incident Cardiometabolic Disease (NCT01608620) Weight change Sugars

Consort statement (through Jan 17, 2014) Reports identified through searching (n=1076) MEDLINE (through January 17 2014): 336 EMBASE (through January 17 2014): 735 Cochrane Library (through January 17 2014): 3 Manual searches: 2 Reports reviewed in full (n=73) Reports excluded based on title or abstract (n=1003) Duplicate reports: 241 Animal or in vitro studies: 23 Case control studies: 4 Case studies: 17 Children: 133 Cross sectional studies: 14 Experimental trial: 64 Meta-analyses: 1 Published abstract: 7 Retrospective analysis: 66 Review papers: 38 Studies with no fructose-containing sugar: 359 Studies with unsuitable endpoints: 36 Reports excluded (n=71) Children: 3 Experimental trial: 3 Studies with no fructose-containing sugar: 18 Studies with unsuitable endpoints: 47 Screened: 1076 Included cohorts: 2 (n=32,405) Reports meeting criteria (n=2) Kim et al., unpublished

Lack of relation of total sugars with weight gain: A systematic review and meta-analysis of 2 cohorts (n=32,405) Difference in highest and lowest intake changes Difference in highest and lowest intake changes Study or Subgroup Weight IV, Random, 95% CI IV, Random, 95% CI Parker et al 1997 0.8% -0.20 [-1.28, 0.88] Colditz et al 1990 99.2% 0.04 [-0.06, 0.14] Total (95% CI) 100.0% 0.04 [-0.06, 0.14] Heterogeneity: Tau² = 0.00; Chi² = 0.19, df = 1 (P = 0.66); I² = 0% Test for overall effect: Z = 0.76 (P = 0.44) -2-1 0 1 2 Reduced body weight Increased body weight Relative Risk: 0.04 (-0.06, 0.14) p = 0.35 Kim et al., unpublished

Consort statement (through Jan, 2014) Reports identified through searching (n=425) MEDLINE (through May 27 2014): 162 EMBASE (through May 27 2014): 260 Cochrane Library (through May 27 2014): 0 Manual searches: 3 Reports reviewed in full (n=45) Reports meeting criteria (n=3) Reports excluded based on title or abstract (n=380) Duplicate reports: 118 Animal or in vitro studies: 1 Case studies: 12 Children: 57 Cross sectional studies: 1 Experimental trial: 28 Published abstract: 1 Retrospective analysis: 10 Review papers: 14 Studies with no sweet foods: 102 Studies with unsuitable endpoints: 36 Reports excluded (n=42) Children: 3 Cross sectional studies: 5 Duplicate reports: 1 Experimental trial: 3 Published abstract: 3 Retrospective studies: 1 Review papers: 1 Studies with no sweet foods: 7 Studies with unsuitable endpoints: 18 Screened:425 Included cohorts: 7 (n=13,400) Kim et al., unpublished

Lack of relation of sweets with weight gain: A systematic review and meta-analysis of 13 cohorts (n=13,400) French et al. 1997 (F) French et al. 1997 (M) Hendriksen et al. 2011 (sweets A&M) Hendriksen et al. 2011 (cakes A&M) Hendriksen et al. 2011 (sweets Doetinchem) Hendriksen et al. 2011 (cakes Doetinchem) Parker et al. 1997 Relative Risk: -0.00 (-0.03, 0.03) p = 0.69 Kim et al., unpublished

CONTROLLED DIETARY TRIALS

Is it all about the fructose?

2 trial designs: To interpret results, follow the energy Substitution trials = comparisons are matched for energy with fructose substituted for other sources of carbohydrate in the diet Addition trials = comparisons are unmatched for energy with energy from fructose added to the diet

Effect of fructose on metabolic control in humans: A meta-analysis to provide evidence-based guidance for future nutrition guidelines development (NCT01363791 ) Catalytic fructose & cardiometabolic risk (Br J Nutr, 2012;108:418-23) Body weight (Ann Intern Med 2012;156:291-304) Fasting lipids (Diabetes Care 2009;32:1930-7) Blood pressure (Hypertension 2012;59:787-95) Fructose Uric acid (J Nutr 2012;142:916-23) Glycemic control (Diabetes Care 2012;35:1611-20) Postprandial lipids (Atherosclerosis 2014;232:125-133) NAFLD (Eur J Clin Nutr. 2014;68:416-423)

Effect of fructose on metabolic control in humans: A meta-analysis to provide evidence-based guidance for future nutrition guidelines development (NCT01363791 ) Body weight (Ann Intern Med 2012;156:291-304) Fructose

Sievenpiper et al. Ann Intern Med, 2012

Consort statement (Updated Nov 18, 2011) Screened: 1984 Isocaloric trials: 31 trials, N=637 Hypercaloric trials: 10 trials, N=119

Substitution trials

Effect of fructose on body weight in isocaloric trials: 31 trials (n=637), dose=69-g/d [30-300-g/d]), FU=4-wk(1-52-wk) Study or Subgroup Year N N Mean difference (95% CI) in weight (kg) Mean Difference Mean Difference (any CHO) (fructose) Study or Subgroup Weight IV, Random, 95% CI Year IV, Random, 95% CI Diabetes 8.1.1 Diabetes Pelkonen et Pelkonen al. [30] et al.[30] 1972 Mcateer et al. Mcateer [31] et al. [31] 1987 Osei et al.[32] Osei et al. [32] 1987 Grigoresco et Grigoresco al. [33] et al. 1988 [33] Osei and Bosetti Thorburn [36] et al.[34] 1989 Anderson et Anderson al. [35] et al. 1989 [35] Thorburn et al. Osei [34] and Bosetti 1989 [36] Thorburn et al. Thorburn [37] et al. 1990 [37] Blayo et al. [38] 1990 Blayo et al. [38] Bantle et al. [39] 1992 Bantle et al. [39] Koivisto et al. [40] 1993 Koivisto et al. [40] Malerbi et al. [41] 1996 Malerbi et al. [41] Vaisman et al. [42] 2006 Vaisman et al. [42] 4.8% 8 10 6.9% 0.1% 9 1.8% 8 13 0.0% 14 2.6% 0.7% 8 1.8% 6 14 3.3% 18 2.6% 10 1.9% 16 3.3% 13 0.1% -0.25 8[-1.01, 0.51] -0.251972 [-1.01, 0.51] 0.20 10[-0.30, 0.70] 0.201987 [-0.30, 0.70] 0.80 9[-6.92, 8.52] 0.801987 [-6.92, 8.52] -0.10 8[-1.62, 1.42] -0.101988 [-1.62, 1.42] 0.10 [-23.24, 13 23.44] 2.501989 [-0.04, 5.04] 2.05 14 [0.84, 3.25] 2.05 1989 [0.84, 3.25] 2.50 8 [-0.04, 5.04] 0.10 [-23.24, 1989 23.44] -0.50 6 [-2.02, 1.02] -0.50 1990 [-2.02, 1.02] 6 0.17 [-0.85, 1.20] 0.17 [-0.85, 1.20] 1990 18-0.20 [-1.41, 1.01] -0.20 [-1.41, 1.01] 1992 10-0.90 [-2.38, 0.58] -0.90 [-2.38, 0.58] 1993 16-0.35 [-1.38, 0.68] -0.35 [-1.38, 0.68] 1996 12 0.00 [-6.93, 6.93]] 0.00 [-6.93, 6.93] 2006 Subtotal Subtotal (95% CI) 29.9% 0.12 [-0.32, 0.56] 0.12 [-0.32, 0.56] Hetrerogeneity: Heterogeneity: Tau 2 = 0.18; Chi 2 = Tau² 17.78, = 0.18; df = 12 Chi² (P=0.12), = 17.78, I 2 = 33% df = 12 (P = 0.12); I² = 33% Test for overall Test effect: for Z = overall 0.54 (P effect: = 0.59) Z = 0.54 (P = 0.59) Overweight/obese 8.1.2 Overweight/obese Rizkalla et al. [43] (T1) 1986 Rizkalla et al. [43] (T1) Rizkalla et al. [43] (T2) 1986 Rizkalla et al. [43] (T2) Swarbrick et al.[44] 2008 Swarbrick et al. [44] Stanhope et al.[45] 2009 Stanhope et al. [45] Madero et al. [46] 2011 Madero et al. [46] Subtotal Subtotal (95% CI) Heterogeneity: Tau² Heterogeneity: = 0.18; Chi² = Tau² 7.92, = df 0.18; = 4 (P Chi² = 0.09); = 7.92, I² = 49% df = 4 (P = 0.09); I² = 49% Test for overall Test effect: for Z = overall 2.02 (P effect: = 0.04) Z = 2.02 (P = 0.04) Normal-weight 8.1.3 Normal-weight Kaufmann et al. [47] 1966 Kaufmann et al. [47] Forster et al. [48] 1973 Forster et al. [48] Turner et al. [49] (LC) 1979 Turner et al. [49] (LC) Turner et al. [49] (HC) 1979 Turner et al. [49] (HC) Beck-Nielsen et al. [50] 1980 Beck-Nielsen et al. [50] Swanson et al. [51] 1992 Swanson et al. [51] Bantle et al. [52] 2000 Bantle et al. [52] Ngo Sock et al. [53] 2010 Ngo Sock et al. [53] Aeberli et al. [54] (HD) 2011 Aeberli et al. [54] (HD) Silbernagel et al. [56] 2011 Silbernagel et al. [56] Stanhope et al. [57] 2011 Stanhope et al. [57] Aeberli et al. [54] (LD) 2011 Aeberli et al. [54] (LD) Brymora et al. [55] 2011 Brymora et al. [55] Subtotal Subtotal (95% CI) 15 2.1% 12 2.8% 7 4.4% 15 6.2% 66 5.2% 20.8% 9 4.5% 12 0.6% 6 1.8% 5 1.6% 7 0.1% 14 3.8% 24 5.7% 11 5.9% 29 7.1% 10 1.7% 32 3.9% 29 6.8% 28 5.7% 49.4% 8-0.06 [-1.45, 1.33] -0.06 [-1.45, 1.33] 1986 6 0.35 [-0.79, 1.49] 0.35 [-0.79, 1.49] 1986 7-1.10 [-1.91, -0.29] -1.10 [-1.91, -0.29] 2008 17-0.30 [-0.88, 0.28] -0.30 [-0.88, 0.28] 2009 65-1.13 [-1.83, -0.43] -1.13 [-1.83, -0.43] 2011-0.55 [-1.09, -0.02] -0.55 [-1.09, -0.02] 9-0.18 [-0.97, 0.62] -0.18 [-0.97, 0.62] 1966 12-0.35 [-3.13, 2.43] -0.35 [-3.13, 2.43] 1973 6 0.40 [-1.11, 1.91] 0.40 [-1.11, 1.91] 1979 5-0.10 [-1.75, 1.55] -0.10 [-1.75, 1.55] 1979 8 0.60 [-5.91, 7.11] 0.60 [-5.91, 7.11] 1980 14 1.10 [0.18, 2.02] 1.10 [0.18, 2.02] 1992 24 0.10 [-0.54, 0.74] 0.10 [-0.54, 0.74] 2000 11-0.40 [-1.01, 0.21] -0.40 [-1.01, 0.21] 2010 29-0.20 [-0.69, 0.29] -0.20 [-0.69, 0.29] 2011 10-1.50 [-3.05, 0.05] -1.50 [-3.05, 0.05] 2011 16-0.50 [-1.39, 0.39] -0.50 [-1.39, 0.39] 2011 29-0.30 [-0.82, 0.22] -0.30 [-0.82, 0.22] 2011 28 0.00 [-0.64, 0.64] 0.00 [-0.64, 0.64] 2011-0.13 [-0.37, 0.10] -0.13 [-0.37, 0.10] Heterogeneity: Tau² Heterogeneity: = 0.01; Chi² = Tau² 13.00, = df 0.01; = 12 Chi² (P = = 0.37); 13.00, I² = df 8% = 12 (P = 0.37); I² = 8% Test for overall Test effect: for Z = overall 1.12 (P effect: = 0.26) Z = 1.12 (P = 0.26) Total -0.14 [-0.37, 0.08] Total (95% CI) 100.0% -0.14 [-0.37, 0.08] Heterogeneity: Tau² Heterogeneity: = 0.12; Chi² = Tau² 47.28, = df 0.12; = 30 Chi² (P = = 0.02); 47.28, I² = df 37% = 30 (P = 0.02); I² = 37% Test for overall Test effect: for Z = overall 1.25 (P effect: = 0.21) Z = 1.25 (P = 0.21) Test for subgroup differences: Chi² = 8.58, df = 2 (P = 0.01), I² = 76.7% -4-2 0 2 4 Favours Favors Favors Favours fructose fructose Favors any CHO

Substitution trials (matched overfeeding)

Positive energy balance in isocaloric trials A. Body weight (kg) Study Mean Difference Weight IV, Random, 95% CI 0.3% Beck-Nielsen 0.60 et al. [-5.91, 19807.11] [42] 40.8% Stanhope et -0.30 al. 2009 [-0.88, [43] 0.28] 36.1% Ngo Sock et -0.40 al. 2010 [-1.01, [44] 0.21] 5.7% Silbernagel -1.50 et al. [-3.05, 2011 [45] 0.05] 17.1% Stanhope et -0.50 al. 2011 [-1.39, [46] 0.39] Year 1980 2009 2010 2011 2011 Mean MD Difference (95%CI) IV, Random, 95% CI 100.0% Total (95%-0.44 CI) [-0.80, -0.07] 00; Chi² Heterogeneity: = 2.15, df = 4 (P (P = = 0.71); 0.71); I² I² = = 0% 0% 2.31 Test (P = for 0.02) overall effect: (P = 0.02) -4-2 0 2 4 Favours fructose Favours glucose

Addition trials

Effect of fructose on weight in hypercaloric (+18-97%E) trials: 10 trials (n=119), dose=+182g/d (+100-250g/d) FU=1.5wk(1-10wk) Study or Subgroup Year N (any CHO) Overweight/obese Rizkalla et al. [58] Stanhope et al. [45] Subtotal Study or Subgroup Weight N (fructose) Mean Difference IV, Random, 95% CI Year 5.2.1 Overweight/obese 1986 7 7 1.10 [-0.08, 2.28] Rizkalla et al. [58] 4.4% 1.10 [-0.08, 2.28] 1986 2009 17 17 1.30 [0.67, 1.93] Stanhope et al. [45] 12.0% 1.30 [0.67, 1.93] 2009 Subtotal (95% CI) 16.5% 1.26 [0.70, 1.81] 1.26 [0.70, 1.81] Heterogeneity: Tau² = 0.00; Chi² = 0.09, Heterogeneity: df = 1 (P = 0.77); Tau² = I² 0.00; = 0% Chi² = 0.09, df = 1 (P = 0.77); I² = 0% Test for overall effect: Z = 4.44 (P < 0.00001) Test for overall effect: Z = 4.44 (P < 0.00001) Normal-weight Beck-Nielsen et al. [50] 5.2.2 Normal-weight Beck-Nielsen 1980 et al. [50] 8 5.5% 80.50 [-0.54, 1.54] 0.50 1980 [-0.54, 1.54] Le et al. [59] Le et al. [60] (ODM2) Le 2006 et al. [59] Le 2009 et al. [60] (N) 7 8 8.3% 12.7% 70.20 [-0.61, 1.01] 0.20 2006 [-0.61, 1.01] 8 0.60 [-0.00, 1.20] 1.00 2009 [-0.26, 2.26] Le et al. [60] (N) Ngo Sock et al. [53] Sobrecases et al. [61] Silbernagel et al. [56] Stanhope et al. [57] Subtotal Le 2009 et al. [60] (ODM2) 16 Ngo 2010Sock et al. [53] 11 Sobrecases 2010 et al. [61] 12 Silbernagel 2011 et al. [56] 10 Stanhope 2011 et al. [57] 16 Subtotal (95% CI) 3.9% 15.0% 24.6% 4.5% 9.0% 83.5% 16 1.00 [-0.26, 2.26] 0.60 2009 [-0.00, 1.20] 11 0.60 [0.07, 1.13] 0.60 2010 [0.07, 1.13] 12 0.30 [-0.01, 0.61] 0.30 2010 [-0.01, 0.61] 10 0.20 [-0.98, 1.38] 0.20 2011 [-0.98, 1.38] 16-0.10 [-0.87, 0.67] -0.10 2011 [-0.87, 0.67] 0.37 [0.16, 0.59] 0.37 [0.15, 0.58] Heterogeneity: Tau² = 0.00; Chi² = 4.19, df = 7 (P = 0.76); I² = 0% Heterogeneity: Tau² = 0.00; Chi² = 4.19, df = 7 (P = 0.76); I² = 0% Test for overall effect: Z = 3.46 (P = 0.0005) Test for overall effect: Z = 3.46 (P = 0.0005) Mean difference (95% CI) in weight (kg) Mean Difference IV, Random, 95% CI Total Total (95% CI) 100.0% 0.53 [0.26, 0.79] 0.53 [0.26, 0.79] Heterogeneity: Tau² = 0.05; Chi² = 12.79, Heterogeneity: df = 9 (P = Tau² 0.17); = 0.05; I² = 30% Chi² = 12.79, df = 9 (P = 0.17); I² = 30% Test for overall effect: Z = 3.91 (P < 0.0001) Test for overall effect: Z = 3.91 (P < 0.0001) Test for subgroup differences: Chi² = 8.51, df = 1 (P = 0.004), I² = 88.2% -4-2 0 2 4 Favors Favours fructose Favours Favors control any CHO

Substitution trials

Lack of harm in SUBSTITUTION trials: >50 trials (N >1000), dose = 22.5-300g/d, FU = 1-52wk Cardiometabolic endpoint Comparisons N Standardized Mean Difference (SMD) with 95% CI I 2 Body weight (22) 31 637-0.22 (-0.58, 0.13) 37%* Fasting Lipids (16,159) TG TC LDL-C HDL-C 48 31 20 27 809 569 313 425 0.24 (-0.05, 0.52) 0.30 (-0.05, 0.65) -0.09 (-0.53, 0.35) 0.38 (0.00, 0.75) 77%* 96%* 100%* 100%* Postprandial TG (160) 14 290 0.14 (-0.02, 0.30) 54%* Glycemic control (20,158) GBP FBG FBI 19 43 32 276 823 563-0.28 (-0.45, -0.11) -0.10 (-0.40, 0.20) -0.32 (-0.66, 0.03) 50%* 78%* 87%* Blood pressure (21) SBP DBP MAP 13 13 13 352 352 352-0.39 (-0.93, 0.16) -0.68 (-1.23, -0.14) -0.64 (-1.19, -0.10) 31% 47%* 97%* Uric acid (157) 18 390 0.04 (-0.43, 0.50) 0% NAFLD (161) IHCL ALT 4 6 95 164-0.09 (-0.36, 0.18) 0.07 (-0.73, 0.87) 0% 0% -4-3 -2-1 0 1 2 3 4 Benefit Harm

Addition trials

Harm in ADDITION trials: An effect more attributable to energy (up to +250g/d +50% E) Cardiometabolic endpoint Comparisons N Standardized Mean Difference (SMD) with 95% CI I 2 Body weight (22) 10 119 1.24 (0.61, 1.85) 30% Fasting lipids (16,159) TG TC LDL-C HDL-C 7 5 4 4 122 102 95 79 1.05 (0.31, 1.79) 0.39 (-0.50, 1.25) 0.22 (-0.77, 1.19) 0.00 (0.00, 0.00) 87%* 89%* 96%* 100%* Postprandial TG (160) 2 32 0.65 (0.30, 1.01) 22% Glycemic control (20,158) GBP FBG FBI 2 8 8 31 98 98-0.33 (-0.62, -0.04) 1.32 (0.63, 2.02) 0.95 (0.26, 1.64) 0% 59%* 41% Blood pressure (21) MAP 2 24-0.76 (-2.15, 0.62) 24% Uric acid (157) 3 35 2.26 (1.13, 3.39) 0% NAFLD (161) IHCL ALT 5 4 60 59 0.45(0.18, 0.72) 0.99 (0.01, 1.97) 51%* 28% -4-3 -2-1 0 1 2 3 4 Benefit Harm

What about other fructose-containing sugars?

3 trial designs: To interpret results, follow the energy Substitution trials = Energy from sugars substituted for other sources of energy in the diet Addition trials = Energy from sugars added to the diet Subtraction trials = Energy from sugars subtracted from the diet

Substitution trials

Isoenergetic exchange of free sugars with other macronutrients does not affect body weight: WHO-commissioned systematic review and meta-analysis of 13 RCTs (n=144) Te Morenga et al. BMJ. 2012;345:e7492

Addition trials

Addition of excess energy from sugars increases weight in adults: WHO commissioned systematic review and meta-analysis of 30 RCTs Te Morenga et al. BMJ. 2012;345:e7492

Addition of excess energy from SSBs results in weight gain proportional to the increase in excess energy: A systematic review and meta-analysis of 7 RCTs (n=333) Mattes et al. Obes Rev. 2011;12:346-65 Kaiser et al. Obes Rev. 2013 Jun 7. doi: 10.1111/obr.12048.

Addition of excess energy from SSBs results in weight gain: A systematic review and meta-analysis of 5 RCTs in adults (n=272) Adults Malik et al. AJCN. 2013 Oct;98(4):1084-102.

Subtraction trials

Reduction in energy from sugar reduces excess body fatness in adults but not children: WHO commissioned systematic review and meta-analysis of 30 RCTs Te Morenga et al. BMJ. 2012;345:e7492

Reduction in energy from SSBs does not affect weight across trials but leads to less weight gain in overweight/obese subjects: A systematic review and meta-analysis of 8 RCTs (n=3281) Mattes et al. Obes Rev. 2011;12:346-65 Kaiser et al. Obes Rev. 2013 Jun 7. doi: 10.1111/obr.12048.

Reduction in energy from SSBs may not reduce weight in children: A systematic review and meta-analysis of 5 RCTs (n=2772) Children Malik et al. AJCN. 2013 Oct;98(4):1084-102.

Take away messages

Take away messages 1. Like with the earlier fat story, it is difficult to separate the contribution of fructose-containing sugars from that of other factors in the epidemic of obesity and cardiometabolic disease, owing to the small effect sizes and lack of demonstrated harm over other sources of excess energy in the diet. 2. Any threshold for the effect of sugars on body weight and cardiometabolic risk is highly dependent on energy balance. 3. There are many pathways to overconsumption leading to weight gain and its downstream consequences. Dietary patterns that bring these pathways together have the greatest influence on weight gain and cardiometabolic risk and represent the best opportunity for successful interventions. 4. Attention needs to remain focused on reducing overconsumption of all caloric foods (including those high in added sugars!), promoting healthier dietary patterns, and increasing physical activity.

Acknowledgements