Consumption of Sweet Beverages and Cancer Risk. A Systematic Review and Meta-Analysis of Observational Studies
Abstract
:1. Introduction
2. Materials and Methods
2.1. Search Method for Identification of Studies
2.2. Eligibility Criteria and Data Extraction
2.3. Quality Assessment of Included Studies
2.4. Data Synthesis and Statistical Analysis
3. Results
3.1. Literature Search and Study Characteristics
3.2. Sweet Beverages and Risk of Breast Cancer
3.2.1. Sweet Beverages and Risk of Pre-Menopausal Breast Cancer
3.2.2. Sweet Beverages and Risk of Post-Menopausal Breast Cancer
3.3. Sweet Beverages and Risk of Intestinal and Colorectal Cancer
3.4. Sweet Beverages and Risk of Esophageal Cancer
3.5. Sweet Beverages and Risk of Gastric Cancer
3.6. Sweet Beverages and Risk of Pancreatic Cancer
3.7. Sweet Beverages and Risk of Genitourinary Cancer
3.7.1. Bladder
3.7.2. Prostate
3.7.3. Renal and Urothelial Cell Cancer
3.8. Sweet Beverages and Risk of Gynecological Cancers
3.9. Sweet Beverages and Risk of Hepatobiliary Cancers
3.10. Sweet Beverages and Risk of Hematologic Cancers
3.11. Sweet Beverages and Risk of Upper Aerodigestive Cancers
3.12. Sweet Beverages and Risk of Other Cancers
3.13. Sweet Beverages and Risk of Overall Cancer
3.14. Quality of Included Studies
4. Discussion
4.1. Association between Consumption of Sweet Beverages and Cancer Risk
4.2. Limitations of the Current Data
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Breast Cancer (Breast, Pre- and Post-Menopausal) | |||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|
Source | Country, Study Name | Cancer Type | Study Design | Population Follow-Up (Years) | Cases | Age (Mean/SD or Range) | Sex (%) | Dietary Assessment Method | Type and Amount of Beverages Intake + | HR/RR/OR (95% CI) | Adjustments |
Chandran et al., 2006 [57] | US, WCHS | Breast | PB case-control | 3148 | 1558 | 20–75 | F (100) | 125-item FFQ | SSB: ≥152 vs. <152 mL/day | OR: 0.97 (0.74–1.27) (AA) OR:1.31 (0.91–1.89) (EA) OR: 1.17 (0.79–1.74) (AA) OR: 0.95 (0.58–1.56) (EA) OR: 0.76 (0.51–1.12) (AA) OR: 2.05 (1.13–3.7) (EA) | Age, ethnicity, country, education, age at menarche, menopause and first birth, MS, parity, BF status, history of benign breast disease, family history of BC, HRT, OC use, BMI, and study site. |
Pre-M | 797 | SSB: ≥152 vs. <152 mL/day | |||||||||
Post-M | 761 | SSB: ≥152 vs. <152 mL/day | |||||||||
Chazelas et al., 2019 [23] | France, NNS | Breast | Cohort | 101,257 5.1 (median) | 693 | 42.2/14.4 | F (78) | 24H-DR | SFJ: >123 vs. <38.1 mL/day (cut-off) SFJ: increase by 100 mL/day SSB: >57.1 vs. <13.6 mL/day (cut-off) SSB: increase by 100 mL/day ASB: >11.6 vs. <4.6 mL/day (cut-off) ASB: increase by 10 mL/day FJ: >81.9 vs. <17.0 mL/day (cut-off) FJ: increase by 100 mL/day SFJ: >123 vs. <38.1 mL/day (cut-off) SFJ: increase by 100 mL/day SSB: >57.1 vs. <13.6 mL/day (cut-off) SSB: increase by 100 mL/day ASB: >11.6 vs. <4.6 mL/day (cut-off) ASB: increase by 10 mL/day FJ: >81.9 vs. <17.0 mL/day (cut-off) FJ: increase by 100 mL/day SFJ: >123 vs. <38.1 mL/day (cut-off) SFJ: increase by 100 mL/day SSB: >57.1 vs. <13.6 mL/day (cut-off) SSB: increase by 100 mL/day ASB: >11.6 vs. <4.6 mL/day (cut-off) ASB: increase by 10 mL/day FJ: >81.9 vs. <17.0 mL/day (cut-off) FJ: increase by 100 mL/day | HR: 1.37 (1.08–1.73) HR: 1.22 (1.07–1.39) HR: 1.10 (0.87–1.39) HR: 1.23 (1.03–1.48) HR: 1.33 (0.98–1.75) HR: 0.97 (0.86–1.09) HR: 1.13 (0.91–1.39) HR: 1.15 (0.97–1.35) HR: 1.28 (1.09–1.83) HR: 1.26 (1.04–1.51) HR: 1.68 (1.45–1.74) HR: 1.34 (1.15–1.70) HR: 1.23 (0.52–2.53) HR: 0.95 (0.81–1.13) HR: 0.98 (0.67–1.43) HR: 1.10 (0.85–1.41) HR: 1.44 (1.05–1.99) HR: 1.19 (0.98–1.44) HR: 0.99 (0.72–1.39) HR: 1.08 (0.79–1.47) HR: 1.10 (0.55–2.12) HR: 1.01 (0.86–1.18) HR: 1.24 (0.95–1.61) HR: 1.19 (0.96–1.48) | Smoking, education, PA, BMI, and height. |
Pre-M | 283 | ||||||||||
Post-M | 410 | ||||||||||
Hirvonen et al., 2006 [51] | France, SUVIMAX | Breast | Cohort | 4396 6.6 | 95 | 35–60 | F (100) | 24H-DR | FJ: >150 mL/day vs. none | RR: 1.29 (0.80–2.09) | Age, smoking, number of children, OC use, family history of BC, and MS. |
Makarem et al., 2018 [52] | US | Breast | Cohort | 3184 4 | 128 | 54.3 | F (53) | FFQ | SFJ: >324 vs. <135 mL/day (cut-off) SSB: >51.4 mL/day vs. none FJ: >180 vs. <38.6 mL/day (cut-off) | HR: 1.00 (0.65–1.57) HR: 1.04 (0.64–1.71) HR: 1.03 (0.67–1.62) | Age, smoking, BMI, EI, alcohol, PA, education, MS, nº of live births, WC, DM and CVD, antioxidant use, energy from fat, and diet soda intake. |
Marzbani et al., 2019 [58] | Iran | Breast | HB case-control | 620 | 212 | 40.2 | F (100) | 11-item healthcare form | SB 7: favorable intake vs. ≤1 time/month | OR: 2.8 (1.9–4.3) | Age, education, and BMI |
McLaughlin et al., 1992 [69] | US | Breast | PB case-control | 3234 | 1617 | 56.7 | F (100) | SQ-interview | SB 2: ever vs. never | OR: 1.08 (0.92–1.26) | Age, alcohol, country, race, MS, age at first live birth, diagnosis of benign cancers, and family history of BC. |
Potischman et al., 2002 [80] | US | Breast | PB case-control | 2019 | 568 | 20–44 | F (100) | 100-item FFQ | SSB: ≥320 mL/day vs. none | OR: 1.09 (0.8–1.5) | Age at diagnosis, study site, race, education, alcohol consumption, years of OC use, smoking, BMI, and EI. |
Romanos-Nanclares et al., 2019 [53] | Spain | Breast | Cohort | 10,713 2 | 100 | 33.0 (median) | F (100) | FFQ | SSB: >47.1 vs. <11 mL/day | HR: 1.36 (0.74–2.50) | Age, height, family history of BC, smoking, PA, BMI, age at menarche and menopause, MS, HRT, number of pregnancies >6 month and before 30 years old, months of BF, alcohol, education, DM, GI, EI, U-P food and coffee consumption, and Med-diet adherence. |
Pre-M | 57 | SSB: ≥11 mL/day vs. none | HR: 1.16 (0.66–2.07) | ||||||||
Post-M | 43 | SSB: >47.1 vs. <11 mL/day | HR: 2.12 (1.01–4.41) | ||||||||
Hodge et al., 2018 [54] | Australia, MCCS | Post-M | Cohort | 35,593 19 | 946 | 54.6 | F (100) | 121-item FFQ | SSB: ≥200 vs. <6.7 mL/day ASB: ≥200 vs. <6.7 mL/day | HR: 1.11 (0.85–1.45) HR: 0.95 (0.73–1.25) | Socioeconomic indexes, country of birth, alcohol intake, smoking, PA, Med-diet score, and sex. ASB also for SSB consumption and WC. |
Nomura et al., 2016 [55] | US, BWHS | Breast Pre-M Post-M | Cohort | 49,103 13.8 | 1827 678 826 | 21–69 | F (100) | FFQ | SSB: ≥250 mL/day vs. none SSB: ≥250 mL/day vs. none SSB: ≥250 mL/day vs. none | HR: 0.71 (0.50–1.02) HR: 1.72 (0.91–3.23) HR: 1.11 (0.77–1.61) | Age, geographic region of residence, EI, smoking, family history of BC, education, MS, OC use, parity, HRT, BMI, alcohol, PA, and sedentary time. |
Colorectal and Rectal Cancer | |||||||||||
Source | Country, Study Name | Cancer Type | Study Design | Population Follow-Up (Years) | Cases | Age (Mean/SD or Range) | Sex (%) | Dietary Assessment Method | Type and Amount of Beverages Intake + | HR/RR/OR (95% CI) | Adjustments |
Bener et al., 2010 [88] | Qatar | Colorectal | HB case-control | 428 | 146 | 53.4 | M (58) | DQ | SB: ≥330 vs. ≤47.1 mL/day | OR: 1.62 (1.19–2.17) | Not reported |
Chazelas et al., 2019 [23] | France | Colorectal | Cohort | 101,257 5.1 (median) | 166 | 42.2 (14.4) | F (78) | 24H-DR | SFJ: >123 vs. <38.1 mL/day (F); >141.7 vs. <46.1 mL/day (M) (cut-off) increase by 100 mL/day SSB: >57.1 vs. <13.6 mL/day (F); >65.5 vs. < 14.0 mL/day (M) (cut-off) increase by 100 mL/day ASB: >11.6 vs. <4.6 mL/day (F); >7.9 vs. < 2.7 mL/day (M) (cut-off) increase by 10 mL/day FJ: >81.9 vs. <17.0 mL/day (F); >97.8 vs. <19.9 mL/day (M) (cut-off) increase by 100 mL/day | HR: 1.07 (0.63–1.80) | Smoking, education, PA, BMI, and height. |
HR: 1.10 (0.84–1.46) | |||||||||||
HR: 1.01 (0.59–1.71) | |||||||||||
HR: 1.11 (0.72–1.71) | |||||||||||
HR: 0.80 (0.44–1.46) | |||||||||||
HR: 1.02 (0.94–1.10) | |||||||||||
HR: 1.19 (0.78–1.82) | |||||||||||
HR: 1.05 (0.75–1.46) | |||||||||||
Hodge et al., 2018 [54] | Australia, MCCS | Colorectal | Cohort | 35,593 19 | 1055 | 54.6 | M/F | 121-item FFQ | SSB: ≥200 vs. <6.7 mL/day ASB: ≥200 vs. <6.7 mL/day | HR: 1.28 (1.04–1.57) HR: 0.79 (0.60–1.06) | Socioeconomic indexes, country, alcohol, smoking, PA, Med-diet score, and sex. ASB also for SSB consumption and WC. |
Makarem et al., 2018 [52] | US | Colorectal | Cohort | 3184 4 | 68 | 54.3 | F (53) | FFQ | SFJ: >362.6 vs. <154.3 mL/day (cut-off) SSB: >180 vs. <25.7 mL/day (cut-off) FJ: >180 vs. < 48.9 mL/day (cut-off) | HR: 1.39 (0.68–2.82) HR: 0.96 (0.51–1.82) HR: 1.66 (0.88–3.12) | Age, smoking, BMI, EI, alcohol, PA, education, MS, nº of live births, WC, DM and CVD, antioxidant use, energy from fat, and diet soda intake. |
Mahfouz et al., 2014 [89] | Egypt | Colorectal | HB case-control | 450 1 | 150 | <20–>60 | F (52) | DQ | SB: daily vs. not daily FJ: daily vs. not daily | OR: 4.6 (1.9–11.01) OR: 0.18 (0.09–0.36) | Not reported |
Pacheco et al., 2019 [56] | US | Colorectal | Cohort | 99,798 20.1 (median) | 1318 | 52.0 (13.5) | F (100) | FFQ | SSB: ≥60 mL/day vs. never/rare | HR: 1.14 (0.86–1.53) | Age, BMI, EI, smoking, alcohol, family history of CR polyps, multivitamin use, and HT. |
Tayyem et al., 2018 [90] | Jordan | Colorectal | HB case-control | 501 2 | 220 | 52 | F (51) | Q-DQ | SB: daily vs. rarely OJ: daily vs. rarely | OR: 1.39 (0.73–2.63) OR: 1.07 (0.45–2.55) | Age, sex, work status, income, PA, marital status, EI, education, other diseases, and history of CR cancer. |
Theodoratou et al., 2014 [91] | Scotland | Colorectal | PB case-control | 4838 7.0 | 2062 | 64.3 | M/F | FFQ | SSB: increase by 330 mL/day FJ: increase by 200 mL/day | OR: 1.12 (1.05–1.19) OR: 1.19 (1.11–1.27) | Age, sex, BMI, PA, family history of CR cancer, EI, NSAIDs, eggs, FJ, SSB, white fish, coffee, and magnesium intake. |
Murtaugh et al., 2004 [92] | US | Rectal | PB case-control | 2157 4 | 952 | 30–79 | M (57) | Interview | SSB: yes vs. no (M) SSB: yes vs. no (F) ASB: yes vs. no (M) ASB: yes vs. no (F) J: >449 vs. ≤58.3 mL/day (M); J: >596.6 vs. ≤44.6 mL/day (F) | OR: 1.00 (0.80–1.26) OR: 0.96 (0.73–1.27) OR: 1.28 (0.98–1.68) OR: 0.90 (0.67–1.22) OR: 0.92 (0.63–1.34) OR: 1.56 (1.00–2.41) | Age, PA, EI, and dietary fiber and calcium intake. |
Esophageal Cancers (Esophagus-Gastric Junction, Esophageal Adenocarcinoma, Squamous Cell Carcinoma) | |||||||||||
Source | Country, Study Name | Cancer Type | Study Design | Population Follow-Up (Years) | Cases | Age (Mean/SD or Range) | Sex (%) | Dietary Assessment Method | Type and Amount of Beverages Intake + | HR/RR/OR (95% CI) | Adjustments |
Ibiebele et al., 2008 [93] | Australia | AEGJ | PB case-control | 2341 4 | 325 | 18–79 | M (71) | FF | SB 7: ≥375 mL/day vs. none SSB 7: yes vs. no ASB 7: yes vs. no SB 7: ≥375 mL/day vs. none SSB 7: yes vs. no ASB 7: yes vs. no SB 7: ≥375 mL/day vs. none SSB 7: yes vs. no ASB 7: yes vs. no | OR: 1.07 (0.67–1.73) OR: 0.63 (0.43–0.92) OR: 0.77 (0.46–1.29) OR: 0.94 (0.53–1.66) OR: 1.20 (0.79–1.81) OR: 0.71 (0.37–1.37) OR: 0.40 (0.20–0.78) OR: 0.70 (0.47–1.03) OR: 0.46 (0.25–0.85) | Age, sex, BMI, EI, alcohol, smoking, education, heartburn, and acid reflux symptoms. |
EAC | 294 | ||||||||||
SCC | 238 | ||||||||||
Mayne et al., 2006 [59] | US | EAC | PB case-control | 1782 | 228 | 65 Q1, 59.3 Q4 | M (78 Q1, 82 Q4) | Proxy and self-interviewed | SSB 7: ≥355 vs. 10.7 mL/day | OR: 0.47 (0.29–0.76) | Age, sex, center, race, proxy interview status, BMI, EI, alcohol and meat intake, cigarettes/day, education, income, and frequency of reflux symptoms. |
SCC | 206 | SSB 7: ≥355 vs. 10.7 mL/day | OR: 0.85 (0.48–1.52) | ||||||||
Ren et al., 2010 [34] | US, NIH-AARP-DHS | EAC | Cohort | 481,563 2 | 305 | 50–71 | M (59) | 124-item FFQ | SB: ≥355 vs. ≤355 mL/day | HR: 1.11 (0.66–1.85) | Age, sex, smoking, alcohol, EI, BMI, education, ethnicity, PA, and daily intake of fruit, vegetables, red meat, and white meat. |
SCC | 123 | SB: ≥355 vs. ≤355 mL/day | HR: 0.85 (0.46–1.56) | ||||||||
Stomach Cancers (Gastric Cardia, Gastric Noncardia) | |||||||||||
Source | Country, Study Name | Cancer Type | Study Design | Population Follow-Up (Years) | Cases | Age (Mean/SD or Range) | Sex (%) | Dietary Assessment Method | Type and Amount of Beverages Intake + | HR/RR/OR (95% CI) | Adjustments |
Hodge et al., 2018 [54] | Australia, MCCS | Gastric cardia | Cohort | 35,593 19 | 165 | 54.6 | M/F | 121-item FFQ | SSB: ≥200 vs. <6.7 mL/day ASB: ≥200 vs. 6.7 mL/day | HR: 1.17 (0.73–1.89) HR: 1.03 (0.53–1.98) | Socioeconomic indexes, country, alcohol, smoking, PA, Med-diet score, and sex. ASB also for SSB consumption and WC. |
Mayne et al., 2006 [59] | US | Gastric cardia Gastric noncardia | PB case-control | 1782 | 255 | 65 Q1, 59.3 Q4 | M (78 Q1, 82 Q4) | Proxy and self-interviewed | SSB 7: ≥355 vs. <10.7 mL/day | OR: 0.74 (0.46–1.16) | Age, sex, center, race, proxy interview status, BMI, EI, alcohol and meat intake cigarettes/day, education, incomes, and frequency of reflux symptoms. |
352 | SSB 7: ≥355 vs. <10.7 mL/day | OR: 0.65 (0.43–0.98) | |||||||||
Ren et al., 2010 [34] | US, NIH-AARP-DHS | Gastric cardia Gastric noncardia | Cohort | 481,563 2 | 231 | 50–71 | M (59) | 124-item FFQ | SB: ≤355 vs. ≥355 mL/day | HR: 0.89 (0.55–1.45) | Age, sex, smoking, alcohol, EI, BMI, education, ethnicity, PA and daily intake of fruit, vegetables, and white meat. |
224 | SB: ≥355 vs. ≤355 mL/day | HR: 0.75 (0.45–1.24) | |||||||||
Pancreatic Cancer | |||||||||||
Source | Country, Study Name | Cancer Type | Study Design | Population Follow-Up (Years) | Cases | Age (Mean/SD or Range) | Sex (%) | Dietary Assessment Method | Type and Amount of Beverages Intake + | HR/RR/OR (95% CI) | Adjustments |
Bao et al., 2008 [42] | US, NIH-AARP-DHS | Pancreatic | Cohort | 487,922 7.2 | 1258 | 50–71 | F (41) | 124-item FFQ | SB: 816.9 mL/day (median) vs. none SSB: 512.8 mL/day (median) vs. none ASB: 816.9 mL/day (median) vs. none | RR: 1.07 (0.86–1.33) RR: 1.01 (0.77–1.31) RR: 1.11 (0.86–1.44) | Age, sex, race, education, BMI, alcohol, smoking, PA, EI, and foliate intake. SSB and ASB were mutually adjusted. |
Chan et al., 2009 [76] | US, SFB | Pancreatic | PB case-control | 2233 | 532 | 21–85 | M (53) | 131-item FFQ | SB: ≥355 mL/day vs. none SB 7: ≥355 mL/day vs. none SSB 7: ≥355 mL/day vs. none ASB 7: ≥355 mL/day vs. none SSB 4: ≥355 mL/day vs. none | OR: 1.0 (0.7–1.3) OR: 1.1 (0.8–1.5) OR: 0.9 (0.6–1.3) OR: 1.5 (1.1–2.1) OR: 1.0 (0.6–1.8) | Age, sex, EI, BMI, race, education, smoking, history of DM, PA, red and white meat, fruit and vegetables, eggs, dairy, whole and refine grained, and sweets. SSB and ASB were mutually adjusted. |
Gallus et al., 2011 [77] | Italy | Pancreatic | HB case-control | 978 7 | 326 | 63 (median) | M (53) | FFQ | SB 7: ≥150 vs. <150 mL/day | OR: 1.02 (0.72–1.44) | Age, sex, study center, education, BMI, smoking, alcohol, EI, family history of pancreatic cancer, and DM. |
Gold et al., 1985 [78] | US | Pancreatic | HB, PB case-control | 676 | 274 | 66.1 | F (53) | Interview | ASB: ever vs. never | OR: 0.66 (0.38–1.2) | Religion, occupation, smoking, and alcohol. |
Larsson et al., 2006 [41] | Sweden, SMC, COSM | Pancreatic | Cohort | 77,797 7.2 | 131 | 60.8 | F (45) | FFQ | SB: ≥500 mL/day vs. none | HR: 1.93 (1.18–3.14) | Age, sex, education, smoking, BMI, and EI. |
Lyon et al., 1992 [79] | US | Pancreatic | PB case-control | 512 | 149 | 40–79 | M/F | DQ | SB (caff): ever vs. never | OR: 1.31 (0.89–1.94) | Unadjusted. |
Mack et al., 1986 [81] | US | Pancreatic | PB case-control | 980 | 490 | 18–65 | M (58) | Proxy and direct Interview | SB 7: ≥1650 vs. <1320 mL/day | RR: 2.6 (0.9–7.4) | Not reported |
Mueller et al., 2010 [43] | China and Singapore, SCHS | Pancreatic | Cohort | 60,524 14 | 140 | 56.5 | F (56) | FFQ | SB: ≥67.7 mL/day vs. none J 5: ≥67.7 mL/day vs. none | HR: 1.87 (1.10–3.15) HR: 1.31 (0.74–2.30) | Age, sex, smoking, BMI, alcohol, EI, PA, DM, education, added sugar, and candy. SB and J were mutually adjusted. |
Nothlings et al., 2007 [44] | US | Pancreatic | Cohort | 162,150 8 | 434 | 59.8 | F (55) | FFQ | SSB: ≥151.4 mL/2000 kcal/day vs. none FJ: ≥120 vs. < 9.4 mL/2000 kcal/day | RR: 1.07 (0.82,1.41) RR: 1.08 (0.83,1.41) | Age, sex, smoking, BMI, EI, time on study, race, family history of pancreatic cancer, intake of red, and processed meat. |
Navarrete-Muñoz et al., 2016 [45] | 10 European countries †, EPIC | Pancreatic | Cohort | 477,206 11.4 | 865 | 51 | F (70) | DQ- country specific | SB: >196.4 vs. 0.1–13.1 mL/day SB: increase by 100 mL/day SSB: >121.4 vs. 0.1-4.5 mL/day SSB: increase by 100 mL/day ASB: >92.2 vs. 0.1-2.0 mL/day ASB: increase by 10 mL/day FJ 6: >123.1 vs. 0.1-8.3 mL/day FJ 6: increase by 100 mL/day | HR: 0.90 (0.68–1.19) HR: 1.02 (0.98–1.06) HR: 0.90 (0.65–1.25) HR: 1.02 (0.97–1.08) HR: 0.99 (0.61–1.60) HR: 1.02 (0.96–1.08) HR: 0.74 (0.57–0.97) HR: 0.91 (0.84–0.98) | Age, sex, smoking, BMI, alcohol, EI, study center, PA, and DM. FJ and SB were mutually adjusted. |
Schernhammer et al., 2005 [46] | US, HPFS, NHS | Pancreatic | Cohort | 136,587 14 HPFS, 20 NHS | 379 | 53.7 | F (65) | FFQ | SSB: <143.6 vs. > 11.2 mL/day ASB: <143.6 vs. > 11.2 mL/day | RR: 1.13 (0.81–1.58) RR: 1.02 (0.79–1.32) | Age, sex, smoking, BMI, follow-up cycle, PA, DM, and other soft drink intake. |
Genitourinary Cancers (Prostate, Renal Cell, Urinary Bladder, Urothelial Cell) | |||||||||||
Source | Country, Study Name | Cancer Type | Study Design | Population Follow-Up (Years) | Cases | Age (Mean/SD or Range) | Sex (%) | Dietary Assessment Method | Type and Amount of Beverages Intake + | HR/RR/OR (95% CI) | Adjustments |
Bruemmer et al., 1997 [60] | US | Bladder | PB case-control | 620 | 215 | 45–65 | M (62) | Interview | SSB: >240 vs. < 8 mL/day | OR: 0.4 (0.2–1.1) (M) OR: 5.7 (1.2–26.9) (F) OR: 1.6 (0.7–3.6) (M) OR: 2.3 (0.8–6.3) (F) | Age, country, and smoking. |
ASB: >240 < 8 mL/day | |||||||||||
De Stefani et al., 2007 [61] | Uruguay | Bladder | HB case-control | 756 | 255 | 30–89 | M (88) | 64-item FFQ | SB: ≥142 vs. <142 mL/day | OR: 1.1 (0.7–1.7) | Age, sex, residence, education, familiar history of UBC, BMI, occupation, smoking, intake of mate, coffee, tea, and milk. |
Hemelt et al., 2010 [62] | China | Bladder | HB case-control | 792 3 | 400 | 65.8 | M (79) | DQ | SB: consumers vs. none FJ: daily vs. none | OR: 2.01 (1.10–3.68) OR: 0.66 (0.26–1.66) | Age, sex, smoking, and frequency and duration of smoking. |
Radosavljević et al., 2003 [63] | Serbia | Bladder | HB case-control | 260 | 130 | 64.9 | M (79) | 101-item FFQ | SB: >15.7 mL/day (mean) vs. none FJ: >11.6 mL/day (mean) vs. none | OR: 4.73 (2.72–8.18) OR: 0.30 (0.18–0.50) | Smoking |
Turati et al., 2015 [64] | Italy | Bladder | HB case-control | 1355 | 665 | 67 (median) | M (76) | DQ | SB 2: ≥47 mL/day vs. none | OR: 1.04 (0.73–1.49) | Age, sex, study center, year of interview, smoking, education, alcohol, BMI, and family history of UBC and cystitis. |
Wang, 2013 [65] | US | Bladder | HB case-control | 2306 | 1007 | 64.4 | M (78) | FFQ | SB: ≥255.6 mL/day vs. none SSB: ≥126 mL/day vs. none ASB: ≥309.6 mL/day vs. none | OR: 1.34 (1.05–1.70) OR: 1.27 (1.02–1.58) OR: 1.06 (0.85–1.32) | Age, sex, ethnicity, EI, and smoking. |
Chazelas et al., 2019 [23] | France | Prostate | Cohort | 101,257 5.1 (median) | 291 | 42.2/4.4 | M (100) | 24H-DR | SFJ: >141.7 vs. <46.1 mL/day (cut-off) SFJ: increase by 100 mL/day SSB: >65.5 vs. <14.0 mL/day (cut-off) SSB: increase by 100 mL/day ASB: >7.9 vs. <2.7 mL/day (cut-off) ASB: increase by 10 mL/day FJ: >97.8 vs. <19.9 mL/day (cut-off) FJ: increase by 100 mL/day | HR: 1.39 (0.96–2.02) HR: 1.10 (0.92–1.31) HR: 1.19 (0.83–1.72) HR: 1.24 (0.95–1.62) HR: 1.33 (1.01–1.75) HR: 0.57 (0.24–1.34) HR: 1.04 (0.76–1.42) HR: 0.97 (0.79–1.2) | Smoking, education, PA, BMI, and height. |
Drake et al., 2012 [35] | Sweden, MDC | Prostate | Cohort | 8128 14.9 | 817 | 45–73 | M (100) | 168-item FFQ, 7-d menu book Interview | SSB: 297.8 mL/day (median) vs. none FJ: 200 mL/day (median) vs. none | HR: 1.13 (0.92–1.38) HR: 0.99 (0.81–1.22) | Age, year of study entry, time of data collection, EI, height, WC, PA, smoking, education, birth in Sweden, alcohol, calcium and selenium intake, and risk by death from all causes except PC. |
Ellison et al., 2000 [36] | Canada, NCSS | Prostate | Cohort | 3400 23 | 201 | 50–84 | M (100) | FFQ | SB 2: ≥100 mL/day vs. none SB 2: ≥any vs. none | RR: 1.29 (0.74–2.26) RR:1.09 (0.78–1.35) | Age, alcohol, smoking, BMI, fiber, and EI. |
Hodge et al., 2018 [54] | Australia, MCCS | Prostate | Cohort | 35,593 19 | 433 | 54.6 | M (100) | 121-item FFQ | SSB: ≥200 vs. <6.7 mL/day ASB: ≥200 vs. <6.7 mL/day | HR: 1.08 (0.78–1.50) HR: 0.81 (0.49–1.33) | Socioeconomic indexes, country of birth, alcohol, smoking, PA, and Med-diet score. ASB also for SSB consumption and WC. |
Jain et al., 1998 [66] | Canada | Prostate | PB case-control | 1253 | 617 | 69.8 | M (100) | Q-DH | SB 2: >200 mL/day vs. none | OR: 0.79 (0.53–1.17) | Age, EI |
Makarem et al., 2018 [52] | US | Prostate | Cohort | 3184 4 | 157 | 54.3 | M (100) | FFQ | SFJ: >401 vs. <212.1 mL/day (cut-off) SSB: >180 vs. <25.7 mL/day (cut-off) FJ: >180 vs. <48.9 mL/day (cut-off) | HR: 1.06 (1.03–1.09) HR: 1.38 (0.80–2.38) HR: 1.03 (1.01–1.06) | Age, smoking, BMI, EI, alcohol, PA, education, WC, DM, CVD, antioxidant use, and energy from fat and diet soda intake. |
Miles et al., 2018 [31] | US | Prostate | Cohort | 22,720 9 | 1996 | 65.6 (5.9) | M (100) | FFQ | SSB: >183 vs. <6 mL/day (cut-off) FJ: >190 vs. <24 mL/day (cut-off) | HR: 1.21 (1.06–1.39) HR: 1.07 (0.94–1.22) | Age, sex, smoking, BMI, EI, DM, education, race, family history of PC, and PSA screens. |
Sharpe et al., 2002 [67] | Canada | Prostate | PB case-control | 875 | 399 | 61.5 | M (100) | Interviews or DQ | SB 7: daily drank vs. never drank weekly | OR: 1.0 (0.7–1.4) | Age, ethnicity, socioeconomic status, BMI, cumulative cigarette smoking, and alcohol. |
Hodge et al., 2018 [54] | Australia, MCCS | Renal cell | Cohort | 35,593 19 | 146 | 54.6 | M/F | 121-item FFQ | SSB: ≥200 vs. <6.7 mL/day ASB: ≥200 vs. <6.7 mL/day | HR: 1.48 (0.87–2.53) HR: 0.92 (0.46–1.84) | Socioeconomic indexes, country of birth, alcohol, smoking, PA, Med-diet score, and sex. ASB also for SSB consumption and WC |
Hu et al., 2009 [68] | Canada | Renal cell | PB case-control | 6177 | 1138 | 20–80 | M (51) | FFQ | SB: >230 mL/day vs. none SB: increase by 230 md J: >236 vs. ≤23 mL/day J: increase by 118 mL/day | OR: 1.26 (0.96–1.67) OR: 1.05 (0.97–1.13) OR: 1.53 (1.18–1.99) OR: 1.08 (1.04–1.13) | 10-year age groups, province, education, BMI, sex, EI, smoking, intake of alcohol meat, vegetables, and fruits. |
Lee et al., 2006 [37] | US | Renal cell | Cohort | 136,587 14 HPFS 20 NHS | 248 | 53.7 | F (65) | FFQ | SB: ≥670 vs. <47.9 mL/day SSB: increase by 335 mL/day ASB: increase by 335 mL/day FJ: increase by 335 mL/day | RR: 1.03 (0.64–1.68) RR: 0.95 (0.69–1.31) RR: 0.97 (0.82–1.15) RR: 1.06 (0.88–1.28) | BMI, EI, alcohol, smoking, history of HT, DM, multivitamin use, and parity. |
Maclure and Willet, 1990 [70] | US | Renal cell | PB case-control | 430 | 203 | 30–>80 | M (67) | FFQ | SB: >480 vs. <68.6 mL/day ASB: >480 vs. <68.6 mL/day FJ: ≥ 480 vs. ≤ 34.3 mL/day | OR: 2.6 (1.4–4.8) OR: 2.7 (1.1–6.5) OR: 0.56 (0.22–1.4) | Age, sex, body weight/height, EI, and education |
Ros et al., 2011 [38] | 10 European countries †, EPIC | Urothelial cell | Cohort | 233,236 9.3 | 513 | 25–70 | F (71) | DQ-country specific | SB: ≥99 vs. <8 mL/day (M); ≥20 vs. <8 mL/day (F) FJ: ≥72 vs. <8 mL/day (M); ≥79 vs. 8 mL/day (F) | HR: 1.03 (0.83–1.30) HR: 1.32 (1.05–1.66) | Smoking, EI from fat and nonfat sources. Stratified by age at entry, sex, and center. |
Gynecological Cancers (Cervical, Endometrial, Epithelial Ovarian, Ovarian) | |||||||||||
Source | Country, Study Name | Cancer Type | Study Design | Population Follow-Up (Years) | Cases | Age (Mean/SD or Range) | Sex (%) | Dietary Assessment Method | Type and Amount of Beverages Intake + | HR/RR/OR (95% CI) | Adjustments |
Herrero et al., 1991 [71] | Colombia, Costa Rica, Mexico and Panama | Cervical | HB, PB case-control | 2033 | 622 | 46.5 | F (100) | FFQ | FJ: >240 vs. <0.8 mL/day | OR: 0.90 (0.7–1.2) | Age, study site, age at 1st intercourse, number of sexual partners and pregnancies, presence of HPV 16/18, interval since last Pap smear, and number of household facilities. |
Verreault et al. 1989 [72] | US | Cervical | PB case-control | 416 | 189 | 20–74 | F (100) | 66-items FFQ | FJ: ≥ 355 vs. ≤ 48 mL/day | RR: 0.3 (0.2–0.6) | Age, education, smoking, frequency of Pap smears, use of barrier and OC, history of cervical-vaginal infection, age at first intercourse, and number of sexual partners. |
Inoue-Choi et al., 2013 [39] | US | Endometrial type I | Cohort | 23,039 14 | 506 | 61.6 | F (100) | FFQ | SFJ: >424.3 vs. ≤55.7 mL/day SSB: >87.4 mL/day vs. none ASB: >144 mL/day vs. none FJ: >288 vs. ≤20.6 mL/day SFJ: >424.3 vs. ≤55.7 mL/day SSB: >87.4 mL/day vs. none ASB: >144 mL/day vs. none FJ: >288 vs. ≤20.6 mL/day | HR: 1.48 (1.09–2.00) HR: 1.78 (1.32–2.40) HR: 0.77 (0.59–1.01) HR: 1.16 (0.87–1.56) HR: 1.09 (0.55–2.15) HR: 1.31 (0.63–2.69) HR: 0.89 (0.48–1.68) HR: 0.97 (0.50–1.88) | Age, smoking, BMI, PA, alcohol, HRT, age at menarche and at menopause, number of live births, DM, and coffee intake. |
Endometrial type II | 89 | ||||||||||
Hodge et al., 2018 [54] | Australia, MCCS | Endometrial | Cohort | 35,593 19 | 167 | 54.6 | F (100) | 121-item FFQ | SSB: ≥200 vs. <6.7 mL/day ASB: ≥200 vs. <6.7 mL/day SSB: ≥200 vs. <6.7 mL/day ASB: ≥200 vs. <6.7 mL/day | HR: 1.02 (0.54–1.91) HR: 0.81 (0.42–1.55) HR: 1.35 (0.71–2.56) HR: 1.37 (0.72–2.61) | Socioeconomic indexes, country of birth, alcohol, smoking, PA, Med-diet score, and sex. ASB also for SSB consumption and WC. |
Ovarian | 130 | ||||||||||
King et al., 2013 [73] | US | Epithelial ovarian | PB case-control | 595 7 | 205 | >21 | F (100) | FFQ and Interview | SSB: ≥151.2 vs. <21.6 mL/2000 kcal/day SSB: increase by 360 mL/day | OR: 1.31 (0.77–2.24) OR: 1.63 (0.94–2.83) | Age, education, race, age at menarche, MS, parity, OC use, HRT, BMI, smoking, PA, DM, tubal ligation, intake of fiber, fat, and saturated fat. |
Leung et al., 2016 [74] | Canada | Epithelial ovarian | PB case-control | 2111 11 | 524 | 40–79 | F (100) | FFQ and Interview | SB: >9.9 mL/day vs. none | OR: 0.97 (0.72–1.31) | Age, race, education, BMI, smoking, alcohol, history of ovarian/breast cancer, OC use, parity, MS, HRT, and study site. |
Song et al., 2008 [75] | US | Epithelial ovarian | PB case-control | 2050 3 | 781 | 35–74 | F (100) | FFQ | SB 3 (caff): ≥720 mL/day vs. none SB 3 (not caff): ≥720 mL/day vs. none | OR: 1.51 (1.03–2.22) OR: 2.60 (1.25–5.39) | Age, BMI, education, smoking, race, country, years of diagnosis, number of pregnancies, OC use, hysterectomy, and family history of breast/ovarian cancer. |
Hepatobiliary Cancers (Biliary Tract, Gallbladder, Liver) | |||||||||||
Source | Country, Study Name | Cancer Type | Study Design | Population Follow-Up (Years) | Cases | Age (Mean/SD or Range) | Sex (%) | Dietary Assessment Method | Type and Amount of Beverages Intake + | HR/RR/OR (95% CI) | Adjustments |
Stepien et al., 2014 [28] | 10 European countries †, EPIC | Biliary tract | Cohort | 477,206 11.4 | 236 | 51 | F (70) | DQ-country specific | SB: 282.9 mL/day vs. none FJ 1: 171.7 mL/day vs. none SB: 282.9 mL/day vs. none FJ 1: 171.7 mL/day vs. none SB: 282.9 mL/day vs. none SB: increase by 300 mL/wk SSB: increase by 330 mL/wk ASB: increase by 330 mL/wk FJ 1: 171.4 mL/day vs. none FJ 1: increase by 200 mL/wk | HR: 0.96 (0.90–1.00) HR: 0.99 (0.95–1.03) HR: 0.97 (0.90–1.06) HR: 1.04 (1.00–1.08) HR: 1.83 (1.11–3.02) HR: 1.05 (1.02–1.07) HR: 1.00 (0.95–1.06) HR: 1.06 (1.03–1.09) HR: 1.38 (0.80–2.38) HR: 1.03 (1.01–1.06) | BMI, alcohol, EI, PA, DM, and education. |
IHBT | 66 | ||||||||||
HCC | 191 | ||||||||||
Larsson et al., 2016 [49] | Sweden, SMC, COSM | IHBT EHBT Gallbladder | Cohort | 70,832 13.4 | 21 127 71 | 45–83 | M (56) | 96-item FFQ | SB: ≥400 mL/day vs. none SB: ≥400 mL/day vs. none SB: ≥400 mL/day vs. none | HR: 1.69 (0.41–7.03) HR: 1.79 (1.02–3.13) HR: 2.24 (1.02–4.89) | Age, sex, education, smoking, BMI, dietary protein intake, and EI. |
Hematologic Cancers (Leukemia, Lymphoma, Myeloma) | |||||||||||
Source | Country, Study Name | Cancer Type | Study Design | Population Follow-Up (Years) | Cases | Age (Mean/SD or Range) | Sex (%) | Dietary Assessment Method | Type and Amount of Beverages Intake + | HR/RR/OR (95% CI) | Adjustments |
Schernhammer et al., 2012 [24] | US, HPFS, NHS | Leukemia | Cohort | 136,587 14 HPFS 20 NHS | 339 | 53.7 | F (65) | FFQ | SSB: ≥335 mL/day vs. none ASB: ≥335 mL/day vs. none SSB: ≥335 mL/day vs. none ASB: ≥335 mL/day vs. none SSB: ≥335 mL/day vs. none ASB: ≥335 mL/day vs. none | RR: 1.06 (0.56–2.00) RR: 1.42 (1.00–2.02) RR: 1.47 (0.76–2.83) RR: 1.29 (0.89–1.89) RR: 1.34 (0.98–1.83) RR: 1.13 (0.94–1.34) | Age, BMI, EI, PA, alcohol, race, fruit and vegetables consumption, menopause, and HT. SSB were adjusted for use of ASB and vice-versa. |
Multiple myeloma | 285 | ||||||||||
NHL | 1324 | ||||||||||
McCullough et al., 2014 [40] | US, CPS-II NCH | NHL | Cohort | 100,442 10 | 1196 | 47–95 | F (57) | Willett FFQ | ASB: >355 mL/day vs. none SSB: >355 mL/day vs. none | RR: 0.92 (0.73–1.17) RR: 1.10 (0.77–1.58) | Education, race, WC, PA, BMI, EI, DM, family history of cancer, HTR and NSAIDs use, cholesterol-lowering medication, intake of alcohol, read and processed meat, milk, saturated fat, fruits and vegetables, and tea and coffee. |
Upper Aerodigestive Cancers (Larynx, Oral Cavity, Oropharyngeal Squamous Cell, Pharynx) | |||||||||||
Source | Country, Study Name | Cancer Type | Study Design | Population Follow-Up (Years) | Cases | Age (Mean/SD or Range) | Sex (%) | Dietary Assessment Method | Type and Amount of Beverages Intake + | HR/RR/OR (95% CI) | Adjustments |
Zvrko et al., 2008 [82] | Montenegro | Larynx | HB case-control | 216 2 | 108 | 59.9 (9.7) | M (82) | DQ | SB: yes vs. no | OR: 0.38 (0.16–0.92) | Age, sex, smoking, alcohol, coffee, diet, personal and familiar medical history, education, housing and work conditions, and exposure to toxic components. |
Ren et al., 2010 [34] | US, NIH-AARP-DHS | Larynx Pharynx Oral cavity | Cohort | 481,563 2 | 307 178 391 | 50–71 | M (59) | 124-item FFQ | SB: ≥355 vs. ≤355 mL/day SB: ≥355 vs. ≤355 mL/day SB: ≥355 vs. ≤355 mL/day | HR: 0.82 (0.55–1.23) HR: 0.76 (0.46–1.25) HR: 0.77 (0.54–1.09) | Age, sex, smoking, alcohol drinking, BMI, EI, education, ethnicity, PA, intake of fruit, vegetables, and red and white meat. |
Lissowska et al., 2003 [83] | Poland | Oral cavity | HB case-control | 246 | 122 | 23–80 | M (64) | 25-item DQ | FJ: >57 vs. <28.6 mL/day | OR: 0.35 (0.15–0.80) | Age, sex, residence, drinking, and smoking habit. |
Kreimer et al., 2006 [84] | 9 countries ‡, IARC-MOCS | OOSC | HB case-control | 3402 | 1670 | NR | M/F | FFQ | FJ: height vs. low intake | OR: 0.8 (0.6–1.1) | Age, sex, country, education, BMI, smoking, chewing, and alcohol. |
Other Cancers | |||||||||||
Source | Country, Study Name | Cancer Type | Study Design | Population Follow-Up (Years) | Cases | Age (Mean/SD or Range) | Sex (%) | Dietary Assessment Method | Type and Amount of Beverages Intake + | HR/RR/OR (95% CI) | Adjustments |
Vincenti et al., 2008 [85] | Italy | Cutaneous melanoma | PB case-control | 118 | 59 | 56 | F (53) | 188-item FFQ | FJ (no OJ): increase by 10 mL/day OJ: increase by 10 mL/day | RR: 0.95 (0.87–1.03) RR: 0.94 (0.88–1.00) | EI, family history of melanoma, skin type, history of sunlight exposure, and sunburns. |
Dubrow et al., 2012 [47] | US | Glioma | Cohort | 545,771 10 | 904 | 62.8 (median) | M (60) | FFQ | SB: >720 mL/day vs. none | HR: 0.87 (0.65–1.15) | Age, sex, race, EI, height, fruit and vegetables intake, and nitrite intake from plants |
Luqman et al., 2014 [86] | Pakistan | Lung | HB case-control | 1200 | 400 | <40–>70 | M (73) | DQ | J: yes vs. no | OR: 0.3 (0.3–0.4) | Not reported |
Wu A. et al., 1997 [87] | US | Small intestine | PB case-control | 1034 | 36 | 30–65 | M (69) | Interview | SSB 7: daily vs. never | OR: 3.6 (1.3–9.8) | Age, ethnicity, and sex. |
Zamora-Ros et al., 2018 [48] | 10 European countries †, EPIC | Thyroid | Cohort | 477,206 11.4 | 748 | 51 | F (70) | DQ- country specific | FJ 1: > 94 vs. < 1 mL/day FJ 1: increase by 50 mL/day | HR: 1.23 (0.98–1.53) HR: 1.02 (0.99–1.06) | Age, sex, smoking status, BMI, EI, alcohol, PA, education, center, menopausal status and type, OC use, and infertility problems. |
Overall Cancers | |||||||||||
Source | Country, Study Name | Cancer Type | Study Design | Population Follow-Up (Years) | Cases | Age (Mean/SD or Range) | Sex (%) | Dietary Assessment Method | Type and Amount of Beverages Intake + | HR/RR/OR (95% CI) | Adjustments |
Bassett et al., 2020 [50] | Australia, MCCS | Non-obesity related * | Cohort | 35,109 19 | 4789 | 27–76 | F (61) | 121-item FFQ | SSB: >375 vs. none or < 12.5 mL/day ASB: >375 vs. none or < 12.5 mL/day | HR: 1.02 (0.86–1.21) HR: 1.23 (1.02–1.48) | Alcohol, country of birth, Med-diet score, PA, socio-economic position, sex, and smoking. ASB also adjusted for SSB intake. |
Makarem et al., 2018 [52] | US | Breast, Colorectal, Prostate | Cohort | 3184 4 | 565 | 54.3 | F (53) | FFQ | SFJ: >501 vs. <73.2 mL/day SSB:>180 mL/day vs. none FJ: >216 vs. <23 mL/day (cut-off) | HR: 1.28 (0.97–1.70) HR: 1.00 (0.79–1.27) HR: 1.05 (0.80–1.38) | Age, sex, EI, alcohol, smoking, and BMI. |
Hodge et al., 2018 [54] | Australia, MCCS | Obesity-related | Cohort | 35,593 19 | 3283 | 54.6 | F (100) | 121-item FFQ | SSB: ≥200 vs. <6.7 mL/day ASB: ≥200 vs. <6.7 mL/day | HR: 1.14 (0.93–1.39) HR: 1.00 (0.79–1.27) | Socioeconomic indexes, country of birth, alcohol, smoking, PA, Med-diet score, and sex. ASB also for SSB consumption and WC. |
Chazelas et al., 2019 [23] | France, NNS | Breast, Colorectal, Prostate | Cohort | 101,257 5.1 (median) | 2193 | 42.2/14.4 | F (78) | 24H-DR | SFJ: >141.7 vs. <46.1 mL/day (cut-off) SFJ: increase by 100 mL/day SSB: >65.5 vs. <14.0 mL/day (cut-off) SSB: increase by 100 mL/day ASB: >7.9 vs. <2.7 mL/day (cut-off) ASB: increase by 10 mL/day FJ: >97.8 vs. <19.9 mL/day (cut-off) FJ: increase by 100 mL/day | HR: 1.30 (1.17–1.52) HR: 1.18 (1.10–1.27) HR: 1.06 (1.02–1.21) HR: 1.19 (1.08–1.32) HR: 1.00 (0.84–1.19) HR: 1.02 (0.94–1.10) HR: 1.14 (1.01–1.29) HR: 1.12 (1.03–1.23) | Smoking, education, PA, BMI, and height. |
Cancer Type | Exposure | N° of Studies | RR (95% CI) | I2 (%) | Tau2 | p within Group + | 95% PI | |
---|---|---|---|---|---|---|---|---|
Cohort | Case-Control | |||||||
Breast | SSB | 4 | 3 | 1.14 (1.01−1.30) | 0.0 | 0.0073 | 0.69 | 0.88, 1.47 |
Breast | FJ | 3 | 0 | 1.13 (0.93−1.38) | 0.0 | 0.0017 | 0.79 | 0.52, 2.46 |
Breast Pre-M | SSB | 3 | 2 | 1.37 (0.99−1.88) | 55.7 | 0.0358 | 0.06 | 0.68, 2.76 |
Breast Post-M | SSB | 4 | 2 | 1.18 (0.79−1.75) | 54.8 | 0.1080 | 0.05 | 0.43, 3.23 |
Colorectal | SSB | 4 | 0 | 1.18 (0.99−1.41) | 0.0 | 0.0039 | 0.71 | 0.82, 1.69 |
Colorectal | FJ | 2 | 2 | 0.79 (0.16−3.87) | 88.5 | 0.8629 | <0.001 | 0.008, 73.94 |
Colorectal * | FJ | 2 | 1 | 1.29 (0.78−2.12) | 0.0 | 0.0120 | 0.63 | 0.17, 9.81 |
Colorectal | SB | 0 | 3 | 2.02 (0.45−9.01) | 62.9 | 0.2711 | 0.07 | 0.00, 5753.1 |
Colorectal * | SB | 0 | 2 | 1.57 (0.74−3.35) | 0.0 | 0.0010 | 0.67 | – |
Bladder | SB | 0 | 5 | 1.66 (0.78−3.56) | 83.4 | 0.3226 | <0.001 | 0.22, 12.37 |
Bladder * | SB | 0 | 4 | 1.27 (0.85−1.90) | 25.3 | 0.0425 | 0.26 | 0.45, 3.60 |
Prostate | SSB | 5 | 0 | 1.18 (1.10−1.27) | 0.0 | 0.0012 | 0.92 | 1.03, 1.35 |
Prostate | FJ | 4 | 0 | 1.03 (1.01−1.05) | 0.0 | 0.0001 | 0.93 | 0.98, 1.09 |
Prostate | SB | 1 | 2 | 0.97 (0.56−1.69) | 2.9 | 0.0241 | 0.36 | 0.07, 12.7 |
Renal cell | SB | 1 | 2 | 1.44 (0.46−4.50) | 65.4 | 0.1559 | 0.056 | 0.00, 604.16 |
Pancreatic | SB | 4 | 4 | 1.28 (0.95−1.72) | 58.6 | 0.0962 | 0.02 | 0.56, 2.90 |
Pancreatic | SSB | 4 | 2 | 1.01 (0.92−1.11) | 0.0 | 0.0016 | 0.92 | 0.87, 1.17 |
Pancreatic | ASB | 3 | 2 | 1.07 (0.77−1.48) | 43.6 | 0.0480 | 0.13 | 0.48, 2.36 |
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Llaha, F.; Gil-Lespinard, M.; Unal, P.; de Villasante, I.; Castañeda, J.; Zamora-Ros, R. Consumption of Sweet Beverages and Cancer Risk. A Systematic Review and Meta-Analysis of Observational Studies. Nutrients 2021, 13, 516. https://doi.org/10.3390/nu13020516
Llaha F, Gil-Lespinard M, Unal P, de Villasante I, Castañeda J, Zamora-Ros R. Consumption of Sweet Beverages and Cancer Risk. A Systematic Review and Meta-Analysis of Observational Studies. Nutrients. 2021; 13(2):516. https://doi.org/10.3390/nu13020516
Chicago/Turabian StyleLlaha, Fjorida, Mercedes Gil-Lespinard, Pelin Unal, Izar de Villasante, Jazmín Castañeda, and Raul Zamora-Ros. 2021. "Consumption of Sweet Beverages and Cancer Risk. A Systematic Review and Meta-Analysis of Observational Studies" Nutrients 13, no. 2: 516. https://doi.org/10.3390/nu13020516