1932
0
  1. Home
  2. A-Z Publications
  3. Annual Review of Nutrition
  4. Volume 44, 2024
  5. Article

Annual Review of Nutrition

Volume 44, 2024

Sugar-Sweetened Beverages and Adverse Human Health Outcomes: An Umbrella Review of Meta-Analyses of Observational Studies

Abstract

Our aim was to conduct an umbrella review of evidence from meta-analyses of observational studies investigating the link between sugar-sweetened beverage consumption and human health outcomes. Using predefined evidence classification criteria, we evaluated evidence from 47 meta-analyses encompassing 22,055,269 individuals. Overall, 79% of these analyses indicated direct associations between greater sugar-sweetened beverage consumption and higher risks of adverse health outcomes. Convincing evidence (class I) supported direct associations between sugar-sweetened beverage consumption and risks of depression, cardiovascular disease, nephrolithiasis, type 2 diabetes mellitus, and higher uric acid concentrations. Highly suggestive evidence (class II) supported associations with risks of nonalcoholic fatty liver disease and dental caries. Out of the remaining 40 meta-analyses, 29 were graded as suggestive or weak in the strength of evidence (classes III and IV), and 11 showed no evidence (class V). These findings inform and provide support for population-based and public health strategies aimed at reducing sugary drink consumption for improved health.

Keyword(s): meta-analysis, noncommunicable disease, Nova food classification system, sugar-sweetened beverages, ultraprocessed food, umbrella review
Loading

Article metrics loading...

/content/journals/10.1146/annurev-nutr-062322-020650
2024-08-29
2024-12-06
Loading full text...

Full text loading...

/deliver/fulltext/nutr/44/1/annurev-nutr-062322-020650.html?itemId=/content/journals/10.1146/annurev-nutr-062322-020650&mimeType=html&fmt=ahah

Literature Cited

  1. 1.
    Ahn H, Park YK. 2021.. Sugar-sweetened beverage consumption and bone health: a systematic review and meta-analysis. . Nutr. J. 20::41
     [Crossref] [Google Scholar]
  2. 2.
    Al-Zalabani AH, Noor Elahi I, Katib A, Alamri AG, Halawani A, et al. 2019.. Association between soft drinks consumption and asthma: a systematic review and meta-analysis. . BMJ Open 9::e029046
     [Crossref] [Google Scholar]
  3. 3.
    Ambikapathi R, Schneider KR, Davis B, Herrero M, Winters P, Fanzo JC. 2022.. Global food systems transitions have enabled affordable diets but had less favourable outcomes for nutrition, environmental health, inclusion and equity. . Nat. Food 3::764–79
     [Crossref] [Google Scholar]
  4. 4.
    Ardeshirlarijani E, Jalilpiran Y, Daneshzad E, Larijani B, Namazi N, Azadbakht L. 2021.. Association between sugar-sweetened beverages and waist circumference in adult populations: a meta-analysis of prospective cohort studies. . Clin. Nutr. ESPEN 41::118–25
     [Crossref] [Google Scholar]
  5. 5.
    Atkinson FS, Foster-Powell K, Brand-Miller JC. 2008.. International tables of glycemic index and glycemic load values: 2008. . Diabetes Care 31::2281–83
     [Crossref] [Google Scholar]
  6. 6.
    Avena NM, Rada P, Hoebel BG. 2008.. Evidence for sugar addiction: behavioral and neurochemical effects of intermittent, excessive sugar intake. . Neurosci. Biobehav. Rev. 32::20–39
     [Crossref] [Google Scholar]
  7. 7.
    Bechthold A, Boeing H, Schwedhelm C, Hoffmann G, Knüppel S, et al. 2019.. Food groups and risk of coronary heart disease, stroke and heart failure: a systematic review and dose-response meta-analysis of prospective studies. . Crit. Rev. Food Sci. Nutr. 59::1071–90
     [Crossref] [Google Scholar]
  8. 8.
    Bellou V, Belbasis L, Tzoulaki I, Evangelou E, Ioannidis JP. 2016.. Environmental risk factors and Parkinson's disease: an umbrella review of meta-analyses. . Parkinsonism Relat. Disord. 23::1–9
     [Crossref] [Google Scholar]
  9. 9.
    Berk M, Köhler-Forsberg O, Turner M, Penninx BWJH, Wrobel A, et al. 2023.. Comorbidity between major depressive disorder and physical diseases: a comprehensive review of epidemiology, mechanisms and management. . World Psychiatry 22:(3):366–87
     [Crossref] [Google Scholar]
  10. 10.
    Bhupathiraju SN, Tobias DK, Malik VS, Pan A, Hruby A, et al. 2014.. Glycemic index, glycemic load, and risk of type 2 diabetes: results from 3 large US cohorts and an updated meta-analysis. . Am. J. Clin. Nutr. 100::218–32
     [Crossref] [Google Scholar]
  11. 11.
    Casanova F, O'Loughlin J, Martin S, Beaumont RN, Wood AR, et al. 2021.. Higher adiposity and mental health: causal inference using Mendelian randomization. . Hum. Mol. Genet. 30::2371–82
     [Crossref] [Google Scholar]
  12. 12.
    Chen H, Wang J, Li Z, Lam CWK, Xiao Y, et al. 2019.. Consumption of sugar-sweetened beverages has a dose-dependent effect on the risk of non-alcoholic fatty liver disease: an updated systematic review and dose-response meta-analysis. . Int. J. Environ. Res. Public Health 16:(12):2192
     [Crossref] [Google Scholar]
  13. 13.
    Choi HK, Curhan G. 2008.. Soft drinks, fructose consumption, and the risk of gout in men: prospective cohort study. . BMJ 336::309–12
     [Crossref] [Google Scholar]
  14. 14.
    Choi HK, Willett W, Curhan G. 2010.. Fructose-rich beverages and risk of gout in women. . JAMA 304::2270–78
     [Crossref] [Google Scholar]
  15. 15.
    Colchero MA, Rivera-Dommarco J, Popkin BM, Ng SW. 2017.. In Mexico, evidence of sustained consumer response two years after implementing a sugar-sweetened beverage tax. . Health Aff. 36::564–71
     [Crossref] [Google Scholar]
  16. 16.
    Dale CE, Fatemifar G, Palmer TM, White J, Prieto-Merino D, et al. 2017.. Causal associations of adiposity and body fat distribution with coronary heart disease, stroke subtypes, and type 2 diabetes mellitus: a Mendelian randomization analysis. . Circulation 135::2373–88
     [Crossref] [Google Scholar]
  17. 17.
    Dekkers OM, Vandenbroucke JP, Cevallos M, Renehan AG, Altman DG, Egger M. 2019.. COSMOS-E: guidance on conducting systematic reviews and meta-analyses of observational studies of etiology. . PLOS Med. 16::e1002742
     [Crossref] [Google Scholar]
  18. 18.
    DiNicolantonio JJ, O'Keefe JH, Wilson WL. 2018.. Sugar addiction: Is it real? A narrative review. . Br. J. Sports Med. 52::910–13
     [Crossref] [Google Scholar]
  19. 19.
    Ebrahimpour-Koujan S, Saneei P, Larijani B, Esmaillzadeh A. 2020.. Consumption of sugar sweetened beverages and dietary fructose in relation to risk of gout and hyperuricemia: a systematic review and meta-analysis. . Crit. Rev. Food Sci. Nutr. 60::1–10
     [Crossref] [Google Scholar]
  20. 20.
    Ebrahimpour-Koujan S, Saneei P, Larijani B, Esmaillzadeh A. 2021.. Consumption of sugar-sweetened beverages and serum uric acid concentrations: a systematic review and meta-analysis. . J. Hum. Nutr. Diet. 34::305–13
     [Crossref] [Google Scholar]
  21. 21.
    Egger M, Davey Smith G, Schneider M, Minder C. 1997.. Bias in meta-analysis detected by a simple, graphical test. . BMJ 315::629–34
     [Crossref] [Google Scholar]
  22. 22.
    Elizabeth L, Machado P, Zinöcker M, Baker P, Lawrence M. 2020.. Ultra-processed foods and health outcomes: a narrative review. . Nutrients 12:(7):1955
     [Crossref] [Google Scholar]
  23. 23.
    Emdin CA, Khera AV, Natarajan P, Klarin D, Zekavat SM, et al. 2017.. Genetic association of waist-to-hip ratio with cardiometabolic traits, type 2 diabetes, and coronary heart disease. . JAMA 317::626–34
     [Crossref] [Google Scholar]
  24. 24.
    Fardet A, Rock E. 2018.. Perspective: Reductionist nutrition research has meaning only within the framework of holistic and ethical thinking. . Adv. Nutr. 9::655–70
     [Crossref] [Google Scholar]
  25. 25.
    Farhangi MA, Nikniaz L, Khodarahmi M. 2020.. Sugar-sweetened beverages increases the risk of hypertension among children and adolescence: a systematic review and dose–response meta-analysis. . J. Translational Med. 18::344
     [Crossref] [Google Scholar]
  26. 26.
    Farsad-Naeimi A, Asjodi F, Omidian M, Askari M, Nouri M, et al. 2020.. Sugar consumption, sugar sweetened beverages and attention deficit hyperactivity disorder: a systematic review and meta-analysis. . Complement Ther. Med. 53::102512
     [Crossref] [Google Scholar]
  27. 27.
    Fayet-Moore F, McConnell A, Cassettari T, Tuck K, Petocz P, Kim J. 2019.. Discretionary intake among Australian adults: prevalence of intake, top food groups, time of consumption and its association with sociodemographic, lifestyle and adiposity measures. . Public Health Nutr. 22::1576–89
     [Crossref] [Google Scholar]
  28. 28.
    Fayet-Moore F, McConnell A, Tuck K, Petocz P, Cassettari T, et al. 2022.. Patterns of discretionary food intake among Australian children and their association with socio-demographic, lifestyle, and adiposity measures. . Nutr. Diet. 79::623–35
     [Crossref] [Google Scholar]
  29. 29.
    Food Agric. Organ. U. N. (FAO). 2023.. Food-based dietary guidelines. . Food and Agriculture Organization of the United Nations. https://www.fao.org/nutrition/education/food-dietary-guidelines/regions/en/
    [Google Scholar]
  30. 30.
    Gaesser GA, Miller Jones J, Angadi SS. 2021.. Perspective: Does glycemic index matter for weight loss and obesity prevention? Examination of the evidence on “fast” compared with “slow” carbs. . Adv. Nutr. 12::2076–84
     [Crossref] [Google Scholar]
  31. 31.
    Gianfredi V, Nucci D, Amerio A, Signorelli C, Odone A, Dinu M. 2022.. What can we expect from an umbrella review?. Adv. Nutr. 13::684–85
     [Crossref] [Google Scholar]
  32. 32.
    Gnagnarella P, Gandini S, La Vecchia C, Maisonneuve P. 2008.. Glycemic index, glycemic load, and cancer risk: a meta-analysis. . Am. J. Clin. Nutr. 87::1793–801
     [Crossref] [Google Scholar]
  33. 33.
    Gosling CJ, Solanes A, Fusar-Poli P, Radua J. 2023.. metaumbrella: the first comprehensive suite to perform data analysis in umbrella reviews with stratification of the evidence. . BMJ Ment. Health 26::e300534
     [Crossref] [Google Scholar]
  34. 34.
    Ha DH, Arora A, Harford J, Luzzi L, Chrisopoulos S, Do LG. 2022.. Population impact of sugar-sweetened beverages on dental caries and overweight/obesity in Australian children. . JDR Clin. Transl. Res. 8::224–33
     [Crossref] [Google Scholar]
  35. 35.
    Hägg S, Fall T, Ploner A, Mägi R, Fischer K, et al. 2015.. Adiposity as a cause of cardiovascular disease: a Mendelian randomization study. . Int. J. Epidemiol. 44::578–86
     [Crossref] [Google Scholar]
  36. 36.
    Higgins JP, Thompson SG, Spiegelhalter DJ. 2009.. A re-evaluation of random-effects meta-analysis. . J. R. Stat. Soc. Ser. A Stat. Soc. 172::137–59
     [Crossref] [Google Scholar]
  37. 37.
    Hu D, Cheng L, Jiang W. 2019.. Sugar-sweetened beverages consumption and the risk of depression: a meta-analysis of observational studies. . J. Affect. Disord. 245::348–55
     [Crossref] [Google Scholar]
  38. 38.
    Huang Y, Chen Z, Chen B, Li J, Yuan X, et al. 2023.. Dietary sugar consumption and health: umbrella review. . BMJ 381::e071609
     [Crossref] [Google Scholar]
  39. 39.
    Ioannidis JP. 2009.. Integration of evidence from multiple meta-analyses: a primer on umbrella reviews, treatment networks and multiple treatments meta-analyses. . Cmaj 181::488–93
     [Crossref] [Google Scholar]
  40. 40.
    Ioannidis JP, Trikalinos TA. 2007.. An exploratory test for an excess of significant findings. . Clin. Trials 4::245–53
     [Crossref] [Google Scholar]
  41. 41.
    Jager KJ, Tripepi G, Chesnaye NC, Dekker FW, Zoccali C, Stel VS. 2020.. Where to look for the most frequent biases?. Nephrology 25::435–41
     [Crossref] [Google Scholar]
  42. 42.
    Karlsen TH, Sheron N, Zelber-Sagi S, Carrieri P, Dusheiko G, et al. 2022.. The EASL-Lancet Liver Commission: protecting the next generation of Europeans against liver disease complications and premature mortality. . Lancet 399::61–116
     [Crossref] [Google Scholar]
  43. 43.
    Khademi Z, Milajerdi A, Larijani B, Esmaillzadeh A. 2021.. Dietary intake of total carbohydrates, sugar and sugar-sweetened beverages, and risk of inflammatory bowel disease: a systematic review and meta-analysis of prospective cohort studies. . Front. Nutr. 8::707795
     [Crossref] [Google Scholar]
  44. 44.
    Lanaspa MA, Ishimoto T, Li N, Cicerchi C, Orlicky DJ, et al. 2013.. Endogenous fructose production and metabolism in the liver contributes to the development of metabolic syndrome. . Nat. Commun. 4::2434
     [Crossref] [Google Scholar]
  45. 45.
    Lane MM, Davis JA, Beattie S, Gómez-Donoso C, Loughman A, et al. 2021.. Ultraprocessed food and chronic noncommunicable diseases: a systematic review and meta-analysis of 43 observational studies. . Obes. Rev. 22::e13146
     [Crossref] [Google Scholar]
  46. 46.
    Lane MM, Gamage E, Travica N, Dissanayaka T, Ashtree DN, et al. 2022.. Ultra-processed food consumption and mental health: a systematic review and meta-analysis of observational studies. . Nutrients 14::2568
     [Crossref] [Google Scholar]
  47. 47.
    Lane MM, Lotfaliany M, Forbes M, Loughman A, Rocks T, et al. 2022.. Higher ultra-processed food consumption is associated with greater high-sensitivity C-reactive protein concentration in adults: cross-sectional results from the Melbourne Collaborative Cohort Study. . Nutrients 14::3309
     [Crossref] [Google Scholar]
  48. 48.
    Le Haut Cons. santé publique (High Counc. Public Health). 2023.. Avis relatif aux objectifs quantifiés pour la politique nutritionnelle de santé publique (PNNS) 2018–2022. [Opinion relating to the quantified objectives for the public health nutritional policy (PNNS) 2018–2022]. . Le Haut Conseil de la santé publique. https://www.hcsp.fr/explore.cgi/avisrapportsdomaine?clefr=648
    [Google Scholar]
  49. 49.
    Li Y, Guo L, He K, Huang C, Tang S. 2021.. Consumption of sugar-sweetened beverages and fruit juice and human cancer: a systematic review and dose-response meta-analysis of observational studies. . J. Cancer 12::3077–88
     [Crossref] [Google Scholar]
  50. 50.
    Lichtenstein AH, Appel LJ, Vadiveloo M, Hu FB, Kris-Etherton PM, et al. 2021.. 2021 dietary guidance to improve cardiovascular health: a scientific statement from the American Heart Association. . Circulation 144::e472–87
     [Crossref] [Google Scholar]
  51. 51.
    Lin B-B, Lin M-E, Huang R-H, Hong Y-K, Lin B-L, He X-J. 2020.. Dietary and lifestyle factors for primary prevention of nephrolithiasis: a systematic review and meta-analysis. . BMC Nephrol. 21::267
     [Crossref] [Google Scholar]
  52. 52.
    Liu H, Liu Y, Shi M, Zhou Y, Zhao Y, Xia Y. 2022.. Meta-analysis of sugar-sweetened beverage intake and the risk of cognitive disorders. . J. Affect. Disord. 313::177–85
     [Crossref] [Google Scholar]
  53. 53.
    Liu S, Manson JE, Buring JE, Stampfer MJ, Willett WC, Ridker PM. 2002.. Relation between a diet with a high glycemic load and plasma concentrations of high-sensitivity C-reactive protein in middle-aged women. . Am. J. Clin. Nutr. 75::492–98
     [Crossref] [Google Scholar]
  54. 54.
    Livesey G, Livesey H. 2019.. Coronary heart disease and dietary carbohydrate, glycemic index, and glycemic load: dose-response meta-analyses of prospective cohort studies. . Mayo Clinic Proc. Innov. Qual. Outcomes 3::52–69
     [Crossref] [Google Scholar]
  55. 55.
    Livesey G, Taylor R, Livesey HF, Buyken AE, Jenkins DJ, et al. 2019.. Dietary glycemic index and load and the risk of type 2 diabetes: a systematic review and updated meta-analyses of prospective cohort studies. . Nutrients 11::1280
     [Crossref] [Google Scholar]
  56. 56.
    Llaha F, Gil-Lespinard M, Unal P, de Villasante I, Castañeda J, Zamora-Ros R. 2021.. Consumption of sweet beverages and cancer risk. A systematic review and meta-analysis of observational studies. . Nutrients 13::516
     [Crossref] [Google Scholar]
  57. 57.
    Lo WC, Ou SH, Chou CL, Chen JS, Wu MY, Wu MS. 2021.. Sugar- and artificially-sweetened beverages and the risks of chronic kidney disease: a systematic review and dose-response meta-analysis. . J. Nephrol. 34::1791–804
     [Crossref] [Google Scholar]
  58. 58.
    Lundeen EA, Park S, Pan L, Blanck HM. 2018.. Daily intake of sugar-sweetened beverages among US adults in 9 states, by state and sociodemographic and behavioral characteristics, 2016. . Prev. Chronic Dis. 15::E154
     [Crossref] [Google Scholar]
  59. 59.
    Lyall DM, Celis-Morales C, Ward J, Iliodromiti S, Anderson JJ, et al. 2017.. Association of body mass index with cardiometabolic disease in the UK Biobank: a Mendelian randomization study. . JAMA Cardiol. 2::882–89
     [Crossref] [Google Scholar]
  60. 60.
    Machado PP, Steele EM, Levy RB, Sui Z, Rangan A, et al. 2019.. Ultra-processed foods and recommended intake levels of nutrients linked to non-communicable diseases in Australia: evidence from a nationally representative cross-sectional study. . BMJ Open 9::e029544
     [Crossref] [Google Scholar]
  61. 61.
    Malik VS, Hu FB. 2019.. Sugar-sweetened beverages and cardiometabolic health: an update of the evidence. . Nutrients 11::1840
     [Crossref] [Google Scholar]
  62. 62.
    Malik VS, Hu FB. 2022.. The role of sugar-sweetened beverages in the global epidemics of obesity and chronic diseases. . Nat. Rev. Endocrinol. 18::205–18
     [Crossref] [Google Scholar]
  63. 63.
    Malik VS, Pan A, Willett WC, Hu FB. 2013.. Sugar-sweetened beverages and weight gain in children and adults: a systematic review and meta-analysis. . Am. J. Clin. Nutr. 98::1084–102
     [Crossref] [Google Scholar]
  64. 64.
    Malik VS, Popkin BM, Bray GA, Després J-P, Hu FB. 2010.. Sugar-sweetened beverages, obesity, type 2 diabetes mellitus, and cardiovascular disease risk. . Circulation 121::1356–64
     [Crossref] [Google Scholar]
  65. 65.
    Malik VS, Willett WC, Hu FB. 2013.. Global obesity: trends, risk factors and policy implications. . Nat. Rev. Endocrinol. 9::13–27
     [Crossref] [Google Scholar]
  66. 66.
    Martini D, Godos J, Bonaccio M, Vitaglione P, Grosso G. 2021.. Ultra-processed foods and nutritional dietary profile: a meta-analysis of nationally representative samples. . Nutrients 13::3390
     [Crossref] [Google Scholar]
  67. 67.
    Marx W, Veronese N, Kelly JT, Smith L, Hockey M, et al. 2021.. The Dietary Inflammatory Index and human health: an umbrella review of meta-analyses of observational studies. . Adv. Nutr. 12:(5):1681–90
     [Crossref] [Google Scholar]
  68. 68.
    Mattes RD, Shikany JM, Kaiser KA, Allison DB. 2011.. Nutritively sweetened beverage consumption and body weight: a systematic review and meta-analysis of randomized experiments. . Obes. Rev. 12::346–65
     [Crossref] [Google Scholar]
  69. 69.
    Meng Y, Li S, Khan J, Dai Z, Li C, et al. 2021.. Sugar- and artificially sweetened beverages consumption linked to type 2 diabetes, cardiovascular diseases, and all-cause mortality: a systematic review and dose-response meta-analysis of prospective cohort studies. . Nutrients 13::2636
     [Crossref] [Google Scholar]
  70. 70.
    Minist. Health Brazil. 2014.. Dietary guidelines for the Brazilian population. Rep. , Minist. Health Brazil, Brasília:. https://bvsms.saude.gov.br/bvs/publicacoes/dietary_guidelines_brazilian_population.pdf
    [Google Scholar]
  71. 71.
    Monteiro CA, Cannon G, Levy RB, Moubarac JC, Louzada ML, et al. 2019.. Ultra-processed foods: what they are and how to identify them. . Public Health Nutr. 22::936–41
     [Crossref] [Google Scholar]
  72. 72.
    Monteiro CA, Cannon G, Moubarac J-C, Levy RB, Louzada MLC, Jaime PC. 2018.. The UN Decade of Nutrition, the NOVA food classification and the trouble with ultra-processing. . Public Health Nutr. 21::5–17
     [Crossref] [Google Scholar]
  73. 73.
    Muñoz-Cabrejas A, Guallar-Castillón P, Laclaustra M, Sandoval-Insausti H, Moreno-Franco B. 2023.. Association between sugar-sweetened beverage consumption and the risk of the metabolic syndrome: a systematic review and meta-analysis. . Nutrients 15::430
     [Crossref] [Google Scholar]
  74. 74.
    Muth ND, Dietz WH, Magge SN, Johnson RK. 2019.. Public policies to reduce sugary drink consumption in children and adolescents. . Pediatrics 143::e20190282
     [Crossref] [Google Scholar]
  75. 75.
    Nakagawa T, Tuttle KR, Short RA, Johnson RJ. 2005.. Hypothesis: fructose-induced hyperuricemia as a causal mechanism for the epidemic of the metabolic syndrome. . Nat. Clin. Practice Nephrol. 1::80–86
     [Crossref] [Google Scholar]
  76. 76.
    Nikniaz L, Abbasalizad-Farhangi M, Vajdi M, Nikniaz Z. 2021.. The association between sugars sweetened beverages (SSBs) and lipid profile among children and youth: a systematic review and dose-response meta-analysis of cross-sectional studies. . Pediatr. Obes. 16::e12782
     [Crossref] [Google Scholar]
  77. 77.
    Nordestgaard BG, Palmer TM, Benn M, Zacho J, Tybjaerg-Hansen A, et al. 2012.. The effect of elevated body mass index on ischemic heart disease risk: causal estimates from a Mendelian randomisation approach. . PLOS Med. 9::e1001212
     [Crossref] [Google Scholar]
  78. 78.
    Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, et al. 2021.. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. . BMJ 372::n71
     [Crossref] [Google Scholar]
  79. 79.
    Pan B, Ge L, Lai H, Wang Q, Wang Q, et al. 2022.. Association of soft drink and 100% fruit juice consumption with all-cause mortality, cardiovascular diseases mortality, and cancer mortality: a systematic review and dose-response meta-analysis of prospective cohort studies. . Crit. Rev. Food Sci. Nutr. 62::8908–19
     [Crossref] [Google Scholar]
  80. 80.
    Rogers NT, Pell D, Mytton OT, Penney TL, Briggs A, et al. 2023.. Changes in soft drinks purchased by British households associated with the UK soft drinks industry levy: a controlled interrupted time series analysis. . BMJ Open 13:(12):e077059
     [Crossref] [Google Scholar]
  81. 81.
    Popkin BM, Hawkes C. 2016.. Sweetening of the global diet, particularly beverages: patterns, trends, and policy responses. . Lancet Diabetes Endocrinol. 4::174–86
     [Crossref] [Google Scholar]
  82. 82.
    Richette P, Bardin T. 2010.. Gout. . Lancet 375::318–28
     [Crossref] [Google Scholar]
  83. 83.
    Rocha LL, Pessoa MC, Gratão LHA, Carmo ASD, Cunha CF, et al. 2021.. Health behavior patterns of sugar-sweetened beverage consumption among Brazilian adolescents in a nationally representative school-based study. . PLOS ONE 16::e0245203
     [Crossref] [Google Scholar]
  84. 84.
    Rosinger A, Herrick K, Gahche J, Park S. 2017.. Sugar-sweetened beverage consumption among U.S. adults, 2011–2014. . NCHS Data Brief 270::1–8
     [Google Scholar]
  85. 85.
    Schlesinger S, Neuenschwander M, Schwedhelm C, Hoffmann G, Bechthold A, et al. 2019.. Food groups and risk of overweight, obesity, and weight gain: a systematic review and dose-response meta-analysis of prospective studies. . Adv. Nutr. 10::205–18
     [Crossref] [Google Scholar]
  86. 86.
    Scrinis G, Monteiro C. 2022.. From ultra-processed foods to ultra-processed dietary patterns. . Nat. Food 3::671–73
     [Crossref] [Google Scholar]
  87. 87.
    Sempos CT, Liu K, Ernst ND. 1999.. Food and nutrient exposures: what to consider when evaluating epidemiologic evidence. . Am. J. Clin. Nutr. 69::1330S–38S
     [Crossref] [Google Scholar]
  88. 88.
    Shea BJ, Reeves BC, Wells G, Thuku M, Hamel C, et al. 2017.. AMSTAR 2: a critical appraisal tool for systematic reviews that include randomised or non-randomised studies of healthcare interventions, or both. . BMJ 358::j4008
     [Crossref] [Google Scholar]
  89. 89.
    Silver LD, Ng SW, Ryan-Ibarra S, Taillie LS, Induni M, et al. 2017.. Changes in prices, sales, consumer spending, and beverage consumption one year after a tax on sugar-sweetened beverages in Berkeley, California, US: a before-and-after study. . PLOS Med. 14::e1002283
     [Crossref] [Google Scholar]
  90. 90.
    Speed MS, Jefsen OH, Børglum AD, Speed D, Østergaard SD. 2019.. Investigating the association between body fat and depression via Mendelian randomization. . Transl. Psychiatry 9::184
     [Crossref] [Google Scholar]
  91. 91.
    Stanaway JD, Afshin A, Gakidou E, Lim SS, Abate D, et al. 2018. Global, regional, and national comparative risk assessment of 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks for 195 countries and territories, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017. . Lancet 392::1923–94
     [Crossref] [Google Scholar]
  92. 92.
    Sterne JA, Egger M. 2001.. Funnel plots for detecting bias in meta-analysis: guidelines on choice of axis. . J. Clin. Epidemiol. 54::1046–55
     [Crossref] [Google Scholar]
  93. 93.
    Sun T, Zhang Y, Ding L, Zhang Y, Li T, Li Q. 2023.. The relationship between major food sources of fructose and cardiovascular outcomes: a systematic review and dose-response meta-analysis of prospective studies. . Adv. Nutr. 14::256–69
     [Crossref] [Google Scholar]
  94. 94.
    Tey S, Salleh N, Henry J, Forde C. 2017.. Effects of aspartame-, monk fruit-, stevia-and sucrose-sweetened beverages on postprandial glucose, insulin and energy intake. . Int. J. Obes. 41::450–57
     [Crossref] [Google Scholar]
  95. 95.
    The Israeli Minist. Health. 2019.. Nutritional recommendations. Rep. , The Israeli Minist. Health, Jerusalem:. https://www.health.gov.il/PublicationsFiles/dietary%20guidelines%20EN.pdf
    [Google Scholar]
  96. 96.
    Tyrrell J, Mulugeta A, Wood AR, Zhou A, Beaumont RN, et al. 2018.. Using genetics to understand the causal influence of higher BMI on depression. . Int. J. Epidemiol. 48::834–48
     [Crossref] [Google Scholar]
  97. 97.
    U. S. Dep. Health Human Serv., U. S. Dep. Agric. 2015.. 2015–2020 Dietary Guidelines for Americans. Rep. , U. S. Dep. Agric., Washington, DC:. http://health.gov/dietaryguidelines/2015/guidelines/
    [Google Scholar]
  98. 98.
    U. S. Dep. Agric. 2014.. A series of systematic reviews on the relationship between dietary patterns and health outcomes. Rep. , U. S. Dep. Agric., Washington, DC:. https://nesr.usda.gov/sites/default/files/2019-06/DietaryPatternsReport-FullFinal2.pdf
    [Google Scholar]
  99. 99.
    Valenzuela MJ, Waterhouse B, Aggarwal VR, Bloor K, Doran T. 2021.. Effect of sugar-sweetened beverages on oral health: a systematic review and meta-analysis. . Eur. J. Public Health 31::122–29
     [Crossref] [Google Scholar]
  100. 100.
    van den Broek N, Treur JL, Larsen JK, Verhagen M, Verweij KJH, Vink JM. 2018.. Causal associations between body mass index and mental health: a Mendelian randomisation study. . J. Epidemiol. Commun. Health 72::708–10
     [Crossref] [Google Scholar]
  101. 101.
    Vandevijvere S, Jaacks LM, Monteiro CA, Moubarac J-C, Girling-Butcher M, et al. 2019.. Global trends in ultraprocessed food and drink product sales and their association with adult body mass index trajectories. . Obes. Rev. 20::10–19
     [Crossref] [Google Scholar]
  102. 102.
    Veronese N, Demurtas J, Thompson T, Solmi M, Pesolillo G, et al. 2020.. Effect of low-dose aspirin on health outcomes: an umbrella review of systematic reviews and meta-analyses. . Br. J. Clin. Pharmacol. 86::1465–75
     [Crossref] [Google Scholar]
  103. 103.
    Veronese N, Solmi M, Caruso MG, Giannelli G, Osella AR, et al. 2018.. Dietary fiber and health outcomes: an umbrella review of systematic reviews and meta-analyses. . Am. J. Clin. Nutr. 107::436–44
     [Crossref] [Google Scholar]
  104. 104.
    von Hippel PT. 2015.. The heterogeneity statistic I2 can be biased in small meta-analyses. . BMC Med. Res. Methodol. 15::35
     [Crossref] [Google Scholar]
  105. 105.
    Wang Y, Zhao R, Wang B, Zhao C, Zhu B, Tian X. 2022.. The dose-response associations of sugar-sweetened beverage intake with the risk of stroke, depression, cancer, and cause-specific mortality: a systematic review and meta-analysis of prospective studies. . Nutrients 14::777
     [Crossref] [Google Scholar]
  106. 106.
    Wasserstein RL, Schirm AL, Lazar NA. 2019.. Moving to a world beyond “p<0.05.”. Am. Stat. 73::1–19
     [Crossref] [Google Scholar]
  107. 107.
    World Health Organ. (WHO). 2015.. Guideline: sugars intake for adults and children. Rep. , WHO, Geneva:. https://www.who.int/publications/i/item/9789241549028
    [Google Scholar]
  108. 108.
    Wray NR, Ripke S, Mattheisen M, Trzaskowski M, Byrne EM, et al. 2018.. Genome-wide association analyses identify 44 risk variants and refine the genetic architecture of major depression. . Nat. Genet. 50::668–81
     [Crossref] [Google Scholar]
  109. 109.
    Yin J, Zhu Y, Malik V, Li X, Peng X, et al. 2021.. Intake of sugar-sweetened and low-calorie sweetened beverages and risk of cardiovascular disease: a meta-analysis and systematic review. . Adv. Nutr. 12::89–101
     [Crossref] [Google Scholar]
  110. 110.
    Yu J, Huang F, Zhang X, Xue H, Ni X, et al. 2023.. Association of sugar-sweetened beverage consumption and moderate-to-vigorous physical activity with childhood and adolescent overweight/obesity: findings from a surveillance project in Jiangsu Province of China. . Nutrients 15::4164
     [Crossref] [Google Scholar]
  111. 111.
    Zhang X, Li X, Liu L, Hong F, Zhao H, et al. 2021.. Dose-response association between sugar- and artificially sweetened beverage consumption and the risk of metabolic syndrome: a meta-analysis of population-based epidemiological studies. . Public Health Nutr. 24::3892–904
     [Crossref] [Google Scholar]
  112. 112.
    Zhang YB, Jiang YW, Chen JX, Xia PF, Pan A. 2021.. Association of consumption of sugar-sweetened beverages or artificially sweetened beverages with mortality: a systematic review and dose-response meta-analysis of prospective cohort studies. . Adv. Nutr. 12::374–83
     [Crossref] [Google Scholar]
/content/journals/10.1146/annurev-nutr-062322-020650
Loading
Sugar-Sweetened Beverages and Adverse Human Health Outcomes: An Umbrella Review of Meta-Analyses of Observational Studies
Annual Review of Nutrition 44, 383 (2024); https://doi.org/10.1146/annurev-nutr-062322-020650
/content/journals/10.1146/annurev-nutr-062322-020650
/content/journals/10.1146/annurev-nutr-062322-020650
Loading

Data & Media loading...

Supplemental Materials

  • Supplemental Material

file format download
  • Article Type: Review Article

Most Cited Most Cited RSS feed

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error