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Balali A, Fathzadeh K, Askari G, Sadeghi O. Dietary intake of tomato and lycopene, blood levels of lycopene, and risk of total and specific cancers in adults: a systematic review and dose-response meta-analysis of prospective cohort studies. Front Nutr 2025; 12:1516048. [PMID: 40013157 PMCID: PMC11860085 DOI: 10.3389/fnut.2025.1516048] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2024] [Accepted: 01/27/2025] [Indexed: 02/28/2025] Open
Abstract
Background The association between tomato/lycopene intake and blood levels of lycopene with the risk of specific cancers were assessed in previous meta-analyses; however, no study evaluated the risk of overall cancer incidence/mortality. Therefore, the present systematic review and dose-response meta-analysis aimed to summarize available findings from prospective studies to examine the association between tomato/lycopene intake and lycopene levels with the risk of total and specific cancers and cancer-related mortality. Methods A comprehensive literature search was done using Scopus, PubMed, ISI Web of Science, and Google Scholar until July 2023. Results In total, 121 prospective studies were included in the systematic review and 119 in the meta-analysis. During the follow-up period of 2-32 years, a total of 108,574 cancer cases and 10,375 deaths occurred. High intakes and high levels of lycopene compared to low amounts were, respectively, associated with 5% (Pooled RR: 0.95, 95% CI: 0.92-0.98, I2 = 26.4%, p = 0.002) and 11% (Pooled RR: 0.89, 95% CI: 0.84-0.95, I2 = 15.0%, p < 0.001) reduction in overall cancer risk. Also, each 10 μg/dL increase in blood levels of lycopene was associated with a 5% lower risk of overall cancer. Moreover, we found a linear inverse association between dietary lycopene intake and prostate cancer risk (Pooled RR 0.99, 95% CI 0.97-1.00, I2 = 0, p = 0.045). Regarding cancer mortality, negative relationships were found with total tomato intake (Pooled RR: 0.89, 95% CI: 0.85-0.93, I2 = 65.7%, p < 0.001), lycopene intake (Pooled RR: 0.84, 95% CI: 0.81-0.86, I2 = 86.5%, p < 0.001) and lycopene levels (Pooled RR 0.76, 95% CI: 0.60-0.98, I2 = 70.9%, p = 0.031). Also, an inverse association was observed between blood lycopene levels and lung cancer mortality (Pooled RR: 0.65, 95% CI: 0.45-0.94, I2 = 0, p = 0.022). Conclusion Our findings show that dietary intake and blood levels of lycopene are associated with a lower risk of cancer and death due to cancer. Clinical trial registration CRD42023432400.
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Affiliation(s)
- Arghavan Balali
- Nutrition and Food Security Research Center, Department of Community Nutrition, School of Nutrition and Food Science, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Kimia Fathzadeh
- Department of Community Nutrition, School of Nutritional Sciences and Dietetics, Tehran University of Medical Sciences, Tehran, Iran
| | - Gholamreza Askari
- Nutrition and Food Security Research Center, Department of Community Nutrition, School of Nutrition and Food Science, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Omid Sadeghi
- Nutrition and Food Security Research Center, Department of Community Nutrition, School of Nutrition and Food Science, Isfahan University of Medical Sciences, Isfahan, Iran
- Research Center for Food Hygiene and Safety, School of Public Health, Shahid Sadoughi University of Medical Sciences, Yazd, Iran
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Rossi I, Mignogna C, Del Rio D, Mena P. Health effects of 100% fruit and vegetable juices: evidence from human subject intervention studies. Nutr Res Rev 2024; 37:194-238. [PMID: 37655747 DOI: 10.1017/s095442242300015x] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/02/2023]
Abstract
The health effects of 100% fruit and vegetable juices (FVJ) represent a controversial topic. FVJ contain notable amounts of free sugars, but also vitamins, minerals, and secondary compounds with proven biological activities like (poly)phenols and carotenoids. The review aimed to shed light on the potential impact of 100% FVJ on human subject health, comprehensively assessing the role each type of juice may have in specific health outcomes for a particular target population, as reported in dietary interventions. The effects of a wide range of FVJ (orange, grapefruit, mandarin, lemon, apple, white, red, and Concord grapes, pomegranate, cranberry, chokeberry, blueberry, other minor berries, sweet and tart cherry, plum, tomato, carrot, beetroot, and watermelon, among others) were evaluated on a series of outcomes (anthropometric parameters, body composition, blood pressure and vascular function, lipid profile, glucose homeostasis, biomarkers of inflammation and oxidative stress, cognitive function, exercise performance, gut microbiota composition and bacterial infections), providing a thorough picture of the contribution of each FVJ to a health outcome. Some juices demonstrated their ability to exert potential preventive effects on some outcomes while others on other health outcomes, emphasising how the differential composition in bioactive compounds defines juice effects. Research gaps and future prospects were discussed. Although 100% FVJ appear to have beneficial effects on some cardiometabolic health outcomes, cognition and exercise performance, or neutral effects on anthropometric parameters and body composition, further efforts are needed to better understand the impact of 100% FVJ on human subject health.
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Affiliation(s)
- Irene Rossi
- Human Nutrition Unit, Department of Food and Drug, University of Parma, Parma, Italy
| | - Cristiana Mignogna
- Human Nutrition Unit, Department of Food and Drug, University of Parma, Parma, Italy
| | - Daniele Del Rio
- Human Nutrition Unit, Department of Food and Drug, University of Parma, Parma, Italy
| | - Pedro Mena
- Human Nutrition Unit, Department of Food and Drug, University of Parma, Parma, Italy
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Cui H, Zhang W, Zhang L, Qu Y, Xu Z, Tan Z, Yan P, Tang M, Yang C, Wang Y, Chen L, Xiao C, Zou Y, Liu Y, Zhang L, Yang Y, Yao Y, Li J, Liu Z, Yang C, Jiang X, Zhang B. Risk factors for prostate cancer: An umbrella review of prospective observational studies and mendelian randomization analyses. PLoS Med 2024; 21:e1004362. [PMID: 38489391 PMCID: PMC10980219 DOI: 10.1371/journal.pmed.1004362] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/19/2023] [Revised: 03/29/2024] [Accepted: 02/16/2024] [Indexed: 03/17/2024] Open
Abstract
BACKGROUND The incidence of prostate cancer is increasing in older males globally. Age, ethnicity, and family history are identified as the well-known risk factors for prostate cancer, but few modifiable factors have been firmly established. The objective of this study was to identify and evaluate various factors modifying the risk of prostate cancer reported in meta-analyses of prospective observational studies and mendelian randomization (MR) analyses. METHODS AND FINDINGS We searched PubMed, Embase, and Web of Science from the inception to January 10, 2022, updated on September 9, 2023, to identify meta-analyses and MR studies on prostate cancer. Eligibility criteria for meta-analyses were (1) meta-analyses including prospective observational studies or studies that declared outcome-free at baseline; (2) evaluating the factors of any category associated with prostate cancer incidence; and (3) providing effect estimates for further data synthesis. Similar criteria were applied to MR studies. Meta-analysis was repeated using the random-effects inverse-variance model with DerSimonian-Laird method. Quality assessment was then conducted for included meta-analyses using AMSTAR-2 tool and for MR studies using STROBE-MR and assumption evaluation. Subsequent evidence grading criteria for significant associations in meta-analyses contained sample size, P values and 95% confidence intervals, 95% prediction intervals, heterogeneity, and publication bias, assigning 4 evidence grades (convincing, highly suggestive, suggestive, or weak). Significant associations in MR studies were graded as robust, probable, suggestive, or insufficient considering P values and concordance of effect directions. Finally, 92 selected from 411 meta-analyses and 64 selected from 118 MR studies were included after excluding the overlapping and outdated studies which were published earlier and contained fewer participants or fewer instrument variables for the same exposure. In total, 123 observational associations (45 significant and 78 null) and 145 causal associations (55 significant and 90 null) were categorized into lifestyle; diet and nutrition; anthropometric indices; biomarkers; clinical variables, diseases, and treatments; and environmental factors. Concerning evidence grading on significant associations, there were 5 highly suggestive, 36 suggestive, and 4 weak associations in meta-analyses, and 10 robust, 24 probable, 4 suggestive, and 17 insufficient causal associations in MR studies. Twenty-six overlapping factors between meta-analyses and MR studies were identified, with consistent significant effects found for physical activity (PA) (occupational PA in meta: OR = 0.87, 95% CI: 0.80, 0.94; accelerator-measured PA in MR: OR = 0.49, 95% CI: 0.33, 0.72), height (meta: OR = 1.09, 95% CI: 1.06, 1.12; MR: OR = 1.07, 95% CI: 1.01, 1.15, for aggressive prostate cancer), and smoking (current smoking in meta: OR = 0.74, 95% CI: 0.68, 0.80; smoking initiation in MR: OR = 0.91, 95% CI: 0.86, 0.97). Methodological limitation is that the evidence grading criteria could be expanded by considering more indices. CONCLUSIONS In this large-scale study, we summarized the associations of various factors with prostate cancer risk and provided comparisons between observational associations by meta-analysis and genetically estimated causality by MR analyses. In the absence of convincing overlapping evidence based on the existing literature, no robust associations were identified, but some effects were observed for height, physical activity, and smoking.
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Affiliation(s)
- Huijie Cui
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Wenqiang Zhang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Li Zhang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Yang Qu
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Zhengxing Xu
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Zhixin Tan
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Peijing Yan
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Mingshuang Tang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Chao Yang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Yutong Wang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Lin Chen
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Chenghan Xiao
- Department of Maternal, Child and Adolescent Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Yanqiu Zou
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Yunjie Liu
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Ling Zhang
- Department of Iatrical Polymer Material and Artificial Apparatus, School of Polymer Science and Engineering, Sichuan University, Chengdu, China
| | - Yanfang Yang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Yuqin Yao
- Department of Occupational and Environmental Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Jiayuan Li
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Zhenmi Liu
- Department of Maternal, Child and Adolescent Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Chunxia Yang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Xia Jiang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
- Department of Nutrition and Food Hygiene, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
- Department of Clinical Neuroscience, Karolinska Institute, Stockholm, Sweden
| | - Ben Zhang
- Hainan General Hospital and Hainan Affiliated Hospital, Hainan Medical University, Haikou, China; West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
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Bergengren O, Pekala KR, Matsoukas K, Fainberg J, Mungovan SF, Bratt O, Bray F, Brawley O, Luckenbaugh AN, Mucci L, Morgan TM, Carlsson SV. 2022 Update on Prostate Cancer Epidemiology and Risk Factors-A Systematic Review. Eur Urol 2023; 84:191-206. [PMID: 37202314 PMCID: PMC10851915 DOI: 10.1016/j.eururo.2023.04.021] [Citation(s) in RCA: 263] [Impact Index Per Article: 131.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2023] [Revised: 03/29/2023] [Accepted: 04/20/2023] [Indexed: 05/20/2023]
Abstract
CONTEXT Prostate cancer (PCa) is one of the most common cancers worldwide. Understanding the epidemiology and risk factors of the disease is paramount to improve primary and secondary prevention strategies. OBJECTIVE To systematically review and summarize the current evidence on the descriptive epidemiology, large screening studies, diagnostic techniques, and risk factors of PCa. EVIDENCE ACQUISITION PCa incidence and mortality rates for 2020 were obtained from the GLOBOCAN database of the International Agency for Research on Cancer. A systematic search was performed in July 2022 using PubMed/MEDLINE and EMBASE biomedical databases. The review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines and was registered in PROSPERO (CRD42022359728). EVIDENCE SYNTHESIS Globally, PCa is the second most common cancer, with the highest incidence in North and South America, Europe, Australia, and the Caribbean. Risk factors include age, family history, and genetic predisposition. Additional factors may include smoking, diet, physical activity, specific medications, and occupational factors. As PCa screening has become more accepted, newer approaches such as magnetic resonance imaging (MRI) and biomarkers have been implemented to identify patients who are likely to harbor significant tumors. Limitations of this review include the evidence being derived from meta-analyses of mostly retrospective studies. CONCLUSIONS PCa remains the second most common cancer among men worldwide. PCa screening is gaining acceptance and will likely reduce PCa mortality at the cost of overdiagnosis and overtreatment. Increasing use of MRI and biomarkers for the detection of PCa may mitigate some of the negative consequences of screening. PATIENT SUMMARY Prostate cancer (PCa) remains the second most common cancer among men, and screening for PCa is likely to increase in the future. Improved diagnostic techniques can help reduce the number of men who need to be diagnosed and treated to save one life. Avoidable risk factors for PCa may include factors such as smoking, diet, physical activity, specific medications, and certain occupations.
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Affiliation(s)
- Oskar Bergengren
- Department of Surgery (Urology Service), Memorial Sloan Kettering Cancer Center, New York, NY, USA; Department of Surgical Sciences, Uppsala University, Uppsala, Sweden.
| | - Kelly R Pekala
- Department of Surgery (Urology Service), Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | | | - Jonathan Fainberg
- Department of Surgery (Urology Service), Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Sean F Mungovan
- Westmead Private Physiotherapy Services and The Clinical Research Institute, Westmead Private Hospital, Sydney, Australia
| | - Ola Bratt
- Department of Urology, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Freddie Bray
- Cancer Surveillance Branch, International Agency for Research on Cancer, Lyon, France
| | - Otis Brawley
- Department of Oncology, Johns Hopkins School of Medicine, Baltimore, MD, USA; Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | | | - Lorelei Mucci
- Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Todd M Morgan
- Department of Urology, University of Michigan, Ann Arbor, MI, USA
| | - Sigrid V Carlsson
- Department of Surgery (Urology Service), Memorial Sloan Kettering Cancer Center, New York, NY, USA; Department of Urology, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden; Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
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