Youth-Onset Cancer and Modifiable Risk: Quantifying the Combined Impact of Obesity and Alcohol on Breast and Colorectal Cancer in Italy (18-34 Years)

Youth-Onset Cancer and Modifiable Risk: Quantifying the Combined Impact of Obesity and Alcohol on Breast and Colorectal Cancer in Italy (18-34 Years) | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Youth-Onset Cancer and Modifiable Risk: Quantifying the Combined Impact of Obesity and Alcohol on Breast and Colorectal Cancer in Italy (18-34 Years) Bolpagni Federica, Lanati Simone, Biino Ginevra, Labrini Luca, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8927891/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 11 You are reading this latest preprint version Abstract Background Rising rates of cancers diagnosed before the age of 50 have been reported worldwide, including in Italy. Among modifiable risk factors, obesity and alcohol consumption independently and synergistically increase the risk of breast and colorectal cancers, including early-onset disease. However, the population-level burden attributable to these exposures among adolescents and young adults (AYA) remains poorly quantified. Methods We integrated a narrative review with a quantitative Population Attributable Fraction (PAF) analysis to estimate the proportion of early-onset breast and colorectal cancers attributable to overweight/obesity, high-risk alcohol consumption, and their combined exposure in the Italian population aged 18–34 years. Sex- and age-specific prevalence data were derived from the national surveillance systems (“PASSI”), while relative risks were obtained from meta-analyses and large cohort studies. Combined PAFs were estimated assuming independence between exposures and tested through sensitivity analyses varying prevalence and relative risk assumptions. Results Among young adults aged 18–34 years, overweight and obesity together accounted for a substantial proportion of early-onset colorectal cancer cases, while high-risk alcohol consumption showed the largest individual attributable fraction. The combined contribution of excess body weight and alcohol consumption reached 12.2% of early-onset colorectal cancer cases. For early-onset breast cancer in young women, obesity and high-risk alcohol consumption were associated with PAFs of 2.8% and 4.6%, respectively. Sensitivity analyses confirmed the robustness of the estimates and indicated that uncertainty in relative risk assumptions represented the main source of variability. Conclusions Obesity and alcohol consumption contribute meaningfully to the burden of early-onset breast and colorectal cancers in Italy. Integrating weight management and alcohol risk assessment into clinical practice and public health strategies targeting young adults could prevent a measurable proportion of these cancers and help counteract the rising incidence of malignancies at young ages. Early-onset cancer Young adults Population attributable fraction Obesity Alcohol consumption Breast cancer Colorectal cancer Cancer prevention Figures Figure 1 Figure 2 1. Background 1.1 Context and Rationale Early-onset cancers, defined as malignancies diagnosed before the age of 50 years, are increasing worldwide across multiple cancer sites ( 1 ). In Italy, population-based cancer registry data indicate that cancer incidence among young adults aged 20–49 years shows site specific trends, with breast cancer representing the most frequently diagnosed malignancy in young women aged 20–49 years and colorectal cancer remaining among the most common solid tumors in both sexes ( 2 ). Over the same period, obesity has remained highly prevalent among adults in Italy, including younger age groups, with national “PASSI” surveillance system data documenting widespread excess body weight among individuals aged 18–49 years, reflecting exposure patterns that often originate early in life ( 3 ). Evidence from longitudinal and cohort studies suggests that excess adiposity in early adulthood may have long term effects on colorectal carcinogenesis, supporting a life course perspective in cancer development ( 4 ). Similarly, alcohol consumption is common among adults aged 18–49 years in Italy, and a substantial proportion report drinking patterns classified as potentially risk for health according to national data “PASSI” ( 5 ). Excess body fatness is a recognized carcinogenic exposure and has been linked to colorectal cancer and breast cancer ( 6 ). Alcohol consumption is classified as a carcinogenic exposure and has been consistently associated with increased risk of both breast and colorectal cancers ( 7 ). Obesity may promote carcinogenesis by accelerating tumor development and shifting cancer occurrence toward younger ages through biological mechanisms including chronic inflammation, insulin resistance, and hormonal dysregulation ( 6 ). In parallel, population level analyses indicate that increases in early-onset incidence of selected cancers, including colon and rectal cancer, are positively correlated with rising prevalence of overweight and obesity, supporting a potential contributory role of excess body weight in early-onset carcinogenesis ( 1 ). Recent pooled analyses have also reported a positive association between alcohol consumption and the risk of early-onset colorectal cancer ( 8 ). Although multiple modifiable lifestyle related risk factors frequently co-occur, evidence on their combined association with cancer risk has been relatively limited, as most epidemiological studies have traditionally focused on single exposures ( 9 ). To the best of our knowledge, only few studies have investigated the burden of excess body weight and alcohol intake as cancer risk factors in adolescents and young adults (AYA, 15–39 years) as defined by the AYA Working Group of the European Society for Medical Oncology and the European Society for Paediatric Oncology ( 10 ). The population attributable fraction (PAF) captures this preventive potential by estimating the proportion of cancer cases in a population that could theoretically be prevented if exposure to the risk factor were reduced to a minimum-risk level ( 11 ). Quantifying the combined population level contribution of modifiable lifestyle related risk factors, including excess body weight and alcohol consumption, is therefore critical to bridge etiological evidence with actionable cancer prevention strategies and to inform public health interventions ( 9 ). The present study aims to: 1) Describe trends of obesity and alcohol use among Italian young adults (18–34 years); 2) Summarize key biological mechanisms linking these exposures to breast and colorectal cancer; 3) Quantify the Population Attributable Fraction (PAF) for overweight, obesity, high-risk alcohol use, and their combination in early-onset breast and colorectal cancer; 4) Derive actionable implications for clinical practice and public health. 1.2 Epidemiology of Obesity and Alcohol in Italian Youth Overweight and obesity are concerning issues among Italians. Overweight and obesity are here defined based on BMI (Body Mass Index, kg/m 2 ) according to WHO definitions ( 12 ), i.e. overweight as BMI over 25 kg/m 2 and obesity as BMI over 30 kg/m 2 . According to the Italian “PASSI” surveillance system for public health, trends of both these conditions have been constantly increasing since 2008. The growing trend in obesity prevalence is small but statistically significant and has been supported especially by the younger age groups (18–34 years old) ( 3 ). In 2023–2024, 5.5% of Italians aged 18–34 were affected by obesity, while 21.5% were affected by overweight. Among Italians, overweight and obesity are more common in men and in individuals with low socioeconomic status and low level of education. Also alcohol consumption among Italians younger generations represents a public health concern, as risky alcohol consumption is reported by about 36% of young adults aged 18–24 years ( 5 ). Risky consumption is defined as any intake different from moderate, i.e. habitual high intake (> 2 units/day for men, > 1 units/day for women), alcohol intake outside meals, and binge drinking (for each single occasion > 4 units for men, or > 3 units for women). Different from overweight and obesity, alcohol consumption is more frequent among people with high socioeconomic status and high educational level, and has increased especially among young women ( 13 ). In both sexes, drinking patterns among young people are characterized by binge drinking and alcohol intake outside meals. Body weight and drinking habits in Italian youths reflect global data from high-income countries, where boys have higher obesity rates, and girls follow higher quality diets but engage more in risky behaviors such as drinking ( 14 ). The early exposures to these two risk factors - overweight/obesity and alcohol consumption - often track into adulthood and are associated with increased risk of Non-Communicable Disease, including cancer. In Italy, in 2020, excess body weight accounted for 3.6% of all male cancers and for 4.0% of female ones, corresponding to nearly 7,000 and 7,200 cases, respectively ( 15 ). Although the onset of many obesity-related and alcohol-related cancers mainly occurs in adulthood, early exposures during adolescence and young adulthood could significantly be responsible for the growing incidence before age 50 ( 6 ). 1.3 Biological and Epidemiological Evidence 1.3.1 Breast Cancer Breast cancer risk and progression are strongly influenced by both alcohol consumption and obesity through interconnected hormonal, metabolic, and inflammatory mechanisms. Alcohol intake enhances the invasive and metastatic potential of breast cancer cells, particularly those overexpressing Human Epidermal Growth Factor Receptor 2 (HER2) ( 16 ). A key mechanism involves estrogen metabolism: alcohol consumption is associated with higher circulating estrogen levels and increased mammographic breast density, both recognized risk factors for breast cancer ( 17 ). Experimental evidence shows that ethanol enhances estrogen receptor α (ERα) expression and signaling in breast cancer cells, thereby promoting tumor growth and metastatic behavior ( 18 ). Additionally, alcohol-induced estrogen signaling may increase matrix metalloproteinase (MMP) expression, facilitating extracellular matrix degradation and tumor dissemination ( 19 ). Oxidative stress represents another central pathway linking alcohol to breast carcinogenesis. Ethanol metabolism generates reactive oxygen species (ROS), particularly through cytochrome P450 2E1 (CYP2E1) induction, leading to lipid peroxidation, DNA damage, and mutagenesis ( 20 ). Ethanol exposure also enhances epidermal growth factor receptor (EGFR) phosphorylation, stimulating mammary epithelial cell proliferation via ROS-dependent pathways ( 21 ). Obesity further amplifies breast cancer risk by altering the adipose tissue microenvironment. Obese adipose tissue is characterized by hypoxia, chronic inflammation, and a shift toward pro-tumorigenic adipokines such as leptin, while protective adiponectin levels are reduced ( 22 ). Pro-inflammatory cytokines (e.g., IL−6, TNF-α) and free fatty acids increase aromatase expression via nuclear factor-kappa B (NF-κB) signaling, enhancing local estrogen biosynthesis and driving estrogen receptor–positive breast cancer, particularly in postmenopausal women ( 23 ). 1.3.2 Colorectal Cancer Alcohol intake and obesity significantly contribute to colorectal cancer (CRC) development, particularly in younger populations. Ethanol exerts carcinogenic effects in the colon through both oxidative and non-oxidative metabolic pathways, promoting epithelial cell proliferation and exposure to acetaldehyde ( 24 ). Alcohol-induced dysbiosis alters gut microbiota composition, favoring acetaldehyde-producing bacteria and biofilm formation, which prolongs epithelial exposure to carcinogenic metabolites ( 25 , 26 ). Additionally, alcohol increases intestinal permeability, facilitating microbial translocation and triggering chronic inflammation that enhances susceptibility to neoplastic transformation ( 27 ). Obesity promotes CRC through insulin resistance, hyperinsulinemia, and chronic inflammation. Elevated insulin and insulin-like growth factor 1 (IGF−1) levels stimulate colorectal cell proliferation and inhibit apoptosis, while hyperglycemia and lipid abnormalities increase oxidative stress and DNA damage ( 28 ). Pro-inflammatory cytokines such as IL−6 sustain tumor-promoting signaling pathways in the intestinal epithelium ( 29 ). 1.3.3 Synergistic Effects Alcohol consumption and obesity interact synergistically to amplify cancer risk through shared mechanisms including chronic inflammation, oxidative stress, insulin resistance, and hormonal dysregulation. Experimental and observational studies indicate that obesity-related metabolic and hormonal alterations enhance alcohol-induced sensitivity to insulin and estrogens, increasing breast cancer risk, particularly in postmenopausal women ( 30 ). This synergism is also evident in hepatocellular carcinoma, where the coexistence of obesity-related fatty liver disease and alcohol-induced liver injury markedly increases long-term cancer risk compared to either factor alone ( 31 ). Evidence from a large cohort study indicates that unhealthy lifestyle factors, including alcohol consumption, interact with genetic predisposition to increase the risk of early-onset breast cancer ( 32 ). These findings highlight the importance of integrated lifestyle interventions, as sustained reductions in body weight and alcohol consumption may substantially reduce cancer risk across multiple organs ( 33 ). 2. Methods For colorectal and breast cancers, PAFs were estimated using Levin’s formula ( 34 ): PAF = p × (RR − 1) / [1 + p × (RR − 1)] where p = prevalence of each risk factor (i.e. overweight/ obesity and risky alcohol consumption as previously defined), and RR = relative risk. Combined PAFs were calculated as: PAF_combined = 1 − (1 − PAF₁)(1 − PAF₂)(1 − PAF₃), assuming statistical independence between overweight/obesity and high-risk alcohol consumption. We acknowledge that these exposures are likely correlated in real populations; therefore, our estimates may under- or overestimate the true combined attributable fraction. Confidence intervals for PAF were based on approximate propagation of imprecision ( 35 ), and sensitivity analyses explored alternative prevalence and RR assumptions to assess robustness. Sex-specific prevalence of overweight, obesity and risky alcohol consumption was extracted for the Italian young adults population (18–34 years) from the national “PASSI” surveillance system ( 3 , 5 ). RRs with 95% confidence intervals (CIs) for the association between overweight, obesity, alcohol consumption and cancer sites were derived from recent meta-analyses ( 4 , 36 – 38 ). Sex-specific estimates were extracted, when available. Sensitivity analyses were conducted to assess the robustness of PAF estimates to uncertainty in both prevalence and relative risk parameters. Specifically, PAFs were recalculated across plausible ranges of prevalence and RR values, informed by the variability observed in national surveillance data and by the 95% confidence intervals reported in the literature. Results of the sensitivity analysis were visualized using contour plots, in which PAF values are represented as a topographic surface: color bands identify intervals of similar PAF magnitude, with higher intensity colors corresponding to larger attributable fractions. This approach allows the joint influence of prevalence and RR on PAF estimates to be explored allowing the identification of parameter regions associated with higher or lower population-attributable burden. 3. Results PAFs for overweight, obesity and high-risk alcohol consumption were estimated for early-onset colorectal and breast cancers using age and sex specific prevalence data and relative risk. Results are reported by cancer site, exposure, age group and sex (Table 1, Table 2, Figure 1). Primary analyses were conducted for the overall 18–34 age group, with additional stratified analyses for 18–24 and 25–34 years limited to alcohol exposure. Early-onset colorectal cancer: Among young Italian adults aged 18-34 years, overweight accounted for 3.6% (95% CI: 1.7, 5.6) of early onset colorectal cancer cases, while obesity accounted for 1.7% (95% CI: 0.6, 3). Among men, PAF for colorectal cancer was 9.8% (95% CI: 6.5, 13.1) and 4.2% (95% CI: 2, 6.8) in relation to overweight and obesity, respectively. Among women, a PAF of 4.4 (95% CI: 2.2, 6.7) for overweight and a PAF of 3.7% (95% CI: 1.7, 5.9) for obesity were estimated. High-risk alcohol consumption showed a larger attributable fraction with a PAF of 8.2% (95% CI: 0.3, 16.4) in individuals aged 18-24 years and 10.7% (95% CI: 8.9, 12.5) in those aged 25-34 years. For early-onset CRC, the combined estimated contribution of excess body weight and alcohol consumption reached 12.2%. Early-onset breast cancer: In young Italian women (18-34y), obesity accounted for 2.8% (95% CI: 1.7, 3.9) of early onset breast cancer cases, while high-risk alcohol consumption was associated with a PAF of 4.6% (95% CI: 3.8, 5.5). The negative lower confidence bound reflects statistical imprecision rather than a protective effect. Sensitivity analyses showed that PAF estimates increased with higher values of both prevalence and relative risk. Variations in RR produced larger changes in PAFs value compared with equivalent variations in prevalence, indicating a greater sensitivity of PAF to uncertainty in risk estimates. Across the full range of plausible assumptions, however, the relative contribution of overweight, obesity and high-risk alcohol consumption to early-onset colorectal and breast cancer remained consistent. Figure 2 illustrates the results of the sensitivity analyses for selected exposure–outcome associations. Table 1. Prevalence and Relative Risks (RRs) of Selected Exposures. Relative risks were primarily derived from studies in adult populations due to the limited availability of age-specific estimates for early-onset cancer. Cancer RR (95% CI) Exposure Group Prevalence (95% CI) Colon and Rectum Ref Breast Ref Overweight 18-34 y 21.5 (20.28, 22.3) 1.18 (1.08, 1.28) (4) Men 40.7 (40.0, 41.3) 1.27 (1.17, 1.37) (4) Women 24.6 (24.0, 25.2) 1.19 (1.09, 1.29) (4) Obesity 18-34 y 5.5 (5.1, 6.0) 1.32 (1.11, 1.56) (4) Men 11.2 (10.7, 11.6) 1.39 (1.18, 1.65) (4) Women 9.6 (9.3, 10) 1.22 (0.99, 1.51) (4) 1.29 (1.18, 1.42) (36) High risk Alcohol Drinking 18-24 y 14.9 (13.9, 15.9) 1.26 (1.01, 1.58) (38) 25-34 y 12.6 (11.9, 13.4) 1.49 (1.40, 1.58) (38) Men 21.9 (21.4, 22.4) 1.55 (1.46, 1.66) (37) Women 13.9 (13.5, 14.4) 1.09 (0.79, 1.50) (37) 1.35 (1.28, 1.42) (37) Abbreviations : RR, relative risk; CI, confidence interval. Table 2. Estimated Population Attributable Fractions (PAF) for Overweight, Obesity, and Alcohol PAF (95% CI), % Exposure Group Colon and Rectum Breast Overweight 18-34 y 3.6 (1.7, 5.6) Men 9.8 (6.5, 13.1) Women 4.4 (2.2, 6.7) Obesity 18-34 y 1.7 (0.6, 3) Men 4.2 (2, 6.8) Women 3.7 (1.7, 5.9) 2.8 (1.7, 3.9) High risk Alcohol Drinking 18-24 y 8.2 (0.3, 16.4) 25-34 y 10.7 (8.9, 12.5) Men 10.9 (9.1, 12.6) Women 1.2 (-3, 6.5) 4.6 (3.8, 5.5) Abbreviations : PAF, Population Attributable Fractions; CI, confidence interval. 4. Discussion These findings underscore the significant, yet preventable, contribution of obesity and alcohol consumption to early-onset cancers in Italy. Taken together, these exposures may explain up to 12.2% of early-onset CRC cases among young adults aged 18-34 years. This proportion is consistent with international evidence linking early-life adiposity and alcohol intake with increasing cancer risk. The study’s main strengths include the use of nationally representative surveillance data (“PASSI”) and age-specific prevalence estimates. However, several limitations should be acknowledged: RRs were derived primarily from adult populations, and the assumption of independence between risk factors may underestimate potential synergistic effects. Additionally, prevalence estimates were limited to available national datasets, which may not fully capture temporal or regional variability among adolescents and young adults. Despite these caveats, our analysis underscores the importance of early, integrated prevention strategies. Combining interventions on weight management and alcohol reduction could prevent a measurable proportion of early-onset colorectal and breast cancer cases. These results are particularly relevant given the rising incidence of malignancies before age 50 and the shifting distribution of modifiable exposures towards younger cohorts. Findings from the sensitivity analyses provide additional insight into the robustness of the estimated PAFs. Although uncertainty in both prevalence and relative risk affects the magnitude of attributable fractions, the analysis indicates that relative risk assumptions represent the main driver of variability. After all, in the calculation, the RR has an exponential impact, whereas prevalence has a linear effect, making the PAF more sensitive to imprecise RR estimates. This highlights the importance of high-quality, age-specific risk estimates when quantifying the population-level impact of modifiable exposures in young adults. Importantly, even under conservative assumptions, the combined contribution of obesity and alcohol consumption to early-onset cancers remained substantial. Clinical and Policy Implications Our results highlight how moderate relative risks, when coupled with a high prevalence of exposure in young adults, may translate into a meaningful population-level burden, reinforcing the relevance of early preventive strategies. From a clinical perspective, routine BMI and alcohol use screening should become an integral part of both oncology and primary care settings, ensuring that early preventive interventions are systematically offered to young adults. In this context, brief motivational counselling, following the 5A model (Ask, Advise, Assess, Assist, Arrange) as described in the WHO primary care toolkit (39), together with referral to structured weight management and alcohol reduction programs, should be established as standard components of care pathways. At the policy level, population-wide interventions are equally crucial. Measures such as alcohol pricing regulation, warning labels, and restrictions on alcohol availability near educational environments could substantially reduce exposure among younger age groups and reinforce individual-level efforts. Finally, key research gaps must be addressed to strengthen the evidence base. There remains an urgent need for joint prevalence studies assessing the co-occurrence of obesity and alcohol use in youth, as well as for age-stratified relative risk estimates and longitudinal analyses exploring the combined effects of these modifiable risk factors on cancer incidence. These considerations are summarised in Box 1, which outlines key action points for clinicians, multidisciplinary teams, public health stakeholders, and researchers. Box 1. Recommendations and call to action Domain Recommended Actions Oncology Practice Screen BMI and alcohol use at first visit; integrate brief lifestyle counselling within “Percorsi Diagnostico-Terapeutici Assistenziali” for early-onset breast and colorectal cancer. Multidisciplinary Teams Include dietitians, psychologists, and health educators in care pathways to deliver personalized prevention strategies. Public Health and Policy Implement youth-targeted information campaigns in schools and universities, strengthen alcohol taxation and labelling regulations. Research Promote longitudinal cohort studies exploring combined exposure trajectories and cancer outcomes in young adults. 5. Conclusion Obesity and alcohol are preventable and measurable determinants of youth-onset cancers. Integrating lifestyle assessment and behavioral counselling into oncology and preventive pathways could substantially reduce the future burden of early-onset cancers in Italy. From a broader public health perspective, policies addressing weight control and alcohol misuse in younger populations represent a strategic opportunity to reverse current cancer trends and mitigate long-term disease risk. Abbreviations AYA Adolescents and Young Adults BMI Body Mass Index CI Confidence Interval CRC Colorectal Cancer CYP2E1 Cytochrome P450 2E1 EGFR Epidermal Growth Factor Receptor HER2 Human Epidermal Growth Factor Receptor 2 ERα Estrogen Receptor alpha IGF-1 Insulin-like Growth Factor 1 IL-6 Interleukin 6 MMP Matrix Metalloproteinase NF-κB Nuclear Factor kappa B PAF Population Attributable Fraction PASSI Progressi delle Aziende Sanitarie per la Salute in Italia RR Relative Risk ROS Reactive Oxygen Species TNF-α Tumor Necrosis Factor alpha WHO World Health Organization Declarations Ethics approval and consent to participate : Not applicable. This study is based on analyses of aggregated data derived from publicly available national surveillance systems and published literature. Consent for publication: Not applicable. Availability of data and materials: All data used in this study are derived from publicly available sources, including the Italian national surveillance system PASSI and published scientific literature. No individual-level data were used. Competing interests: The authors declare that they have no competing interests. Funding: This work was funded under the National Recovery and Resilience Plan (NRRP), Mission 4 Component 2 Investment 1.3 — Call No. 341 (15 March 2022) of the Italian Ministry of University and Research, funded by the EU — NextGenerationEU, Project PE00000003 (Decree No. 1550/2022, CUP F13C22001210007, “ON Foods — Research and Innovation Network on Food and Nutrition Sustainability, Safety and Security — Working ON Foods”). Author’s Contributions: HC conceived the study and coordinated the work. FB, SL, GB, LL contributed to data analysis and literature review. HC, FB, SL, LL contributed to writing—original draft preparation, review and editing. NM, AV, MM, LDL, FS supervised and critically revised the manuscript. All authors read and approved the final manuscript. Acknowledgments: National Recovery and Resilience Plan (NRRP), Mission 4 Component 2. Investment 1.4—Call for tender No. 3138 of 16 December 2021, rectified by Decree n.3175 of 18 December 2021 of Italian Ministry of University and Research funded by the European Union— NextGenerationEU; Project code CN_00000033, Concession Decree No. 1034 of 17 June 2022 adopted by the Italian Ministry of University and Research, CUP F13C22000720007, Project title “National Biodiversity Future Center—NBFC”. References Chen J, Dalerba P, Terry MB, Yang W. Global obesity epidemic and rising incidence of early-onset cancers. J Glob Health. 2024;14. 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The relation between obesity and breast cancer risk in women by considering menstruation status and geographical variations: a systematic review and meta-analysis. BMC Womens Health. 2023;23(1):392. Jun S, Park H, Kim UJ, Choi EJ, Lee HA, Park B, et al. Cancer risk based on alcohol consumption levels: a comprehensive systematic review and meta-analysis. Epidemiol Health. 2023;45:e2023092. Kim NH, Jung YS, Yang HJ, Park SK, Park JH, Park DI, et al. Prevalence of and Risk Factors for Colorectal Neoplasia in Asymptomatic Young Adults (20–39 Years Old). Clin Gastroenterol Hepatol Off Clin Pract J Am Gastroenterol Assoc. 2019;17(1):115–22. World Health Organization. Toolkit for delivering the 5A’s and 5R’s brief tobacco interventions in primary care [Internet]. 2014 [Accessed 11 Feb 2026]. Available from: https://iris.who.int/items/9e874a72–5ff9–47ef-ab23–28af3b274ee7 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 22 Apr, 2026 Reviews received at journal 20 Apr, 2026 Reviews received at journal 19 Apr, 2026 Reviewers agreed at journal 27 Mar, 2026 Reviewers agreed at journal 27 Mar, 2026 Reviews received at journal 19 Mar, 2026 Reviewers agreed at journal 26 Feb, 2026 Reviewers invited by journal 25 Feb, 2026 Editor assigned by journal 24 Feb, 2026 Submission checks completed at journal 24 Feb, 2026 First submitted to journal 20 Feb, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8927891","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":597421183,"identity":"12663850-34f7-42d2-b823-092762bed8be","order_by":0,"name":"Bolpagni Federica","email":"","orcid":"","institution":"University of Palermo","correspondingAuthor":false,"prefix":"","firstName":"Bolpagni","middleName":"","lastName":"Federica","suffix":""},{"id":597421184,"identity":"df06ebab-1458-469a-9460-4abb7d58718c","order_by":1,"name":"Lanati Simone","email":"","orcid":"","institution":"Istituti Clinici Scientifici Maugeri","correspondingAuthor":false,"prefix":"","firstName":"Lanati","middleName":"","lastName":"Simone","suffix":""},{"id":597421185,"identity":"a85cdbb1-5c94-47d8-bdb2-4c0292004a19","order_by":2,"name":"Biino Ginevra","email":"","orcid":"","institution":"National Research Council","correspondingAuthor":false,"prefix":"","firstName":"Biino","middleName":"","lastName":"Ginevra","suffix":""},{"id":597421186,"identity":"3078482f-1293-4875-82ad-28a4f85aedb4","order_by":3,"name":"Labrini Luca","email":"","orcid":"","institution":"Istituti Clinici Scientifici Maugeri","correspondingAuthor":false,"prefix":"","firstName":"Labrini","middleName":"","lastName":"Luca","suffix":""},{"id":597421187,"identity":"8c96e730-9745-43da-8472-b7046ad063c9","order_by":4,"name":"Madini Nagaia","email":"","orcid":"","institution":"University of Pavia","correspondingAuthor":false,"prefix":"","firstName":"Madini","middleName":"","lastName":"Nagaia","suffix":""},{"id":597421190,"identity":"f76cdc2d-5459-4a47-988c-1cccb7e76285","order_by":5,"name":"Vincenti Alessandra","email":"","orcid":"","institution":"University of Pavia","correspondingAuthor":false,"prefix":"","firstName":"Vincenti","middleName":"","lastName":"Alessandra","suffix":""},{"id":597421192,"identity":"93d92e10-95a0-4f32-b37a-517b5b84d1f7","order_by":6,"name":"Manuelli Matteo","email":"","orcid":"","institution":"Istituti Clinici Scientifici Maugeri","correspondingAuthor":false,"prefix":"","firstName":"Manuelli","middleName":"","lastName":"Matteo","suffix":""},{"id":597421193,"identity":"0c55c2e2-52e4-4304-9dc9-bfd11f7e142a","order_by":7,"name":"Sottotetti Federico","email":"","orcid":"","institution":"Istituti Clinici Scientifici Maugeri","correspondingAuthor":false,"prefix":"","firstName":"Sottotetti","middleName":"","lastName":"Federico","suffix":""},{"id":597421194,"identity":"ffda2dcc-8958-4124-8ab1-1e6b40eb1334","order_by":8,"name":"Locati Laura Deborah","email":"","orcid":"","institution":"Istituti Clinici Scientifici Maugeri","correspondingAuthor":false,"prefix":"","firstName":"Locati","middleName":"Laura","lastName":"Deborah","suffix":""},{"id":597421195,"identity":"d32b3518-5032-44bd-a962-7a057a2d8529","order_by":9,"name":"Cena Hellas","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA50lEQVRIiWNgGAWjYBACAwbmxgNQNuMDBgYJEN1AQAtjA0wLswFUSyNePcha2CRg1uHVYs7e2HDgxx8GeX7p5mfVvDss8gwOMLc/wKfFsudgw8HeNgbDmXOOmd3mPSNRbHCAkMNuJDYc4G1gSDC4kQDU0iaROLOBkJb7DxsO/vnDkGB/I/1bMXFabjA2HOZhA9oikWPGDNLSTzDEziQ2HJZtkzCccSOnWHJum0QxPzNj4wy8Wo4fPvjwzR8bef4Z6Rs/vG2ry2Njb3/wAZ8WKJCAsxIYmIlQjwISSNUwCkbBKBgFwx8AAK7XTd633HCrAAAAAElFTkSuQmCC","orcid":"","institution":"Istituti Clinici Scientifici Maugeri","correspondingAuthor":true,"prefix":"","firstName":"Cena","middleName":"","lastName":"Hellas","suffix":""}],"badges":[],"createdAt":"2026-02-20 16:54:42","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8927891/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8927891/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":104168405,"identity":"70bd9dfe-7322-4835-a522-ed74f3933e09","added_by":"auto","created_at":"2026-03-08 14:31:55","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":10705,"visible":true,"origin":"","legend":"\u003cp\u003eBar chart showing combined PAF highest among joint exposure.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-8927891/v1/305dc90c96d5eb9df53e58d2.png"},{"id":104168406,"identity":"6db64cf4-68eb-4e3b-b600-dd456d97ba3a","added_by":"auto","created_at":"2026-03-08 14:31:55","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":376011,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSensitivity analysis of PAFs for selected exposure-cancer associations. \u003c/strong\u003eThree-dimensional surface plots display estimated PAFs as a function of exposure prevalence (Pr) and relative risk (RR). Panel A shows overweight and early-onset colorectal cancer among young adults aged 18-34 years; Panel B shows obesity and early-onset colorectal cancer in the same age group; Panel C shows high-risk alcohol consumption and early-onset breast cancer among women aged 18-34 years. PAF values increase along both the prevalence and relative risk axes, reflecting the combined influence of exposure frequency and strength of association on population-level cancer burden.\u003c/p\u003e","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8927891/v1/5c0300d09e3c6ab95ac0258b.jpeg"},{"id":104403969,"identity":"e81ad07e-82b7-4f81-b4f4-aa8410511dde","added_by":"auto","created_at":"2026-03-11 12:19:30","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1462348,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8927891/v1/03dcb6fe-5b17-4b3e-8cf6-34800669e128.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Youth-Onset Cancer and Modifiable Risk: Quantifying the Combined Impact of Obesity and Alcohol on Breast and Colorectal Cancer in Italy (18-34 Years)","fulltext":[{"header":"1. Background","content":"\u003cdiv id=\"Sec2\" class=\"Section2\"\u003e \u003ch2\u003e1.1 Context and Rationale\u003c/h2\u003e \u003cp\u003eEarly-onset cancers, defined as malignancies diagnosed before the age of 50 years, are increasing worldwide across multiple cancer sites (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). In Italy, population-based cancer registry data indicate that cancer incidence among young adults aged 20\u0026ndash;49 years shows site specific trends, with breast cancer representing the most frequently diagnosed malignancy in young women aged 20\u0026ndash;49 years and colorectal cancer remaining among the most common solid tumors in both sexes (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). Over the same period, obesity has remained highly prevalent among adults in Italy, including younger age groups, with national \u0026ldquo;PASSI\u0026rdquo; surveillance system data documenting widespread excess body weight among individuals aged 18\u0026ndash;49 years, reflecting exposure patterns that often originate early in life (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). Evidence from longitudinal and cohort studies suggests that excess adiposity in early adulthood may have long term effects on colorectal carcinogenesis, supporting a life course perspective in cancer development (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). Similarly, alcohol consumption is common among adults aged 18\u0026ndash;49 years in Italy, and a substantial proportion report drinking patterns classified as potentially risk for health according to national data \u0026ldquo;PASSI\u0026rdquo; (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). Excess body fatness is a recognized carcinogenic exposure and has been linked to colorectal cancer and breast cancer (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). Alcohol consumption is classified as a carcinogenic exposure and has been consistently associated with increased risk of both breast and colorectal cancers (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). Obesity may promote carcinogenesis by accelerating tumor development and shifting cancer occurrence toward younger ages through biological mechanisms including chronic inflammation, insulin resistance, and hormonal dysregulation (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). In parallel, population level analyses indicate that increases in early-onset incidence of selected cancers, including colon and rectal cancer, are positively correlated with rising prevalence of overweight and obesity, supporting a potential contributory role of excess body weight in early-onset carcinogenesis (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). Recent pooled analyses have also reported a positive association between alcohol consumption and the risk of early-onset colorectal cancer (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). Although multiple modifiable lifestyle related risk factors frequently co-occur, evidence on their combined association with cancer risk has been relatively limited, as most epidemiological studies have traditionally focused on single exposures (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). To the best of our knowledge, only few studies have investigated the burden of excess body weight and alcohol intake as cancer risk factors in adolescents and young adults (AYA, 15\u0026ndash;39 years) as defined by the AYA Working Group of the European Society for Medical Oncology and the European Society for Paediatric Oncology (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). The population attributable fraction (PAF) captures this preventive potential by estimating the proportion of cancer cases in a population that could theoretically be prevented if exposure to the risk factor were reduced to a minimum-risk level (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). Quantifying the combined population level contribution of modifiable lifestyle related risk factors, including excess body weight and alcohol consumption, is therefore critical to bridge etiological evidence with actionable cancer prevention strategies and to inform public health interventions (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe present study aims to:\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003e1) Describe trends of obesity and alcohol use among Italian young adults (18–34 years);\u003c/h3\u003e\n\n\u003ch3\u003e2) Summarize key biological mechanisms linking these exposures to breast and colorectal cancer;\u003c/h3\u003e\n\u003cp\u003e3) Quantify the Population Attributable Fraction (PAF) for overweight, obesity, high-risk alcohol use, and their combination in early-onset breast and colorectal cancer;\u003c/p\u003e\n\u003ch3\u003e4) Derive actionable implications for clinical practice and public health.\u003c/h3\u003e\n\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e1.2 Epidemiology of Obesity and Alcohol in Italian Youth\u003c/h2\u003e \u003cp\u003eOverweight and obesity are concerning issues among Italians. Overweight and obesity are here defined based on BMI (Body Mass Index, kg/m\u003csup\u003e2\u003c/sup\u003e) according to WHO definitions (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e), i.e. overweight as BMI over 25 kg/m\u003csup\u003e2\u003c/sup\u003e and obesity as BMI over 30 kg/m\u003csup\u003e2\u003c/sup\u003e. According to the Italian \u0026ldquo;PASSI\u0026rdquo; surveillance system for public health, trends of both these conditions have been constantly increasing since 2008. The growing trend in obesity prevalence is small but statistically significant and has been supported especially by the younger age groups (18\u0026ndash;34 years old) (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). In 2023\u0026ndash;2024, 5.5% of Italians aged 18\u0026ndash;34 were affected by obesity, while 21.5% were affected by overweight. Among Italians, overweight and obesity are more common in men and in individuals with low socioeconomic status and low level of education.\u003c/p\u003e \u003cp\u003eAlso alcohol consumption among Italians younger generations represents a public health concern, as risky alcohol consumption is reported by about 36% of young adults aged 18\u0026ndash;24 years (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). Risky consumption is defined as any intake different from moderate, i.e. habitual high intake (\u0026gt;\u0026thinsp;2 units/day for men, \u0026gt; 1 units/day for women), alcohol intake outside meals, and binge drinking (for each single occasion\u0026thinsp;\u0026gt;\u0026thinsp;4 units for men, or \u0026gt;\u0026thinsp;3 units for women). Different from overweight and obesity, alcohol consumption is more frequent among people with high socioeconomic status and high educational level, and has increased especially among young women (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). In both sexes, drinking patterns among young people are characterized by binge drinking and alcohol intake outside meals.\u003c/p\u003e \u003cp\u003eBody weight and drinking habits in Italian youths reflect global data from high-income countries, where boys have higher obesity rates, and girls follow higher quality diets but engage more in risky behaviors such as drinking (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe early exposures to these two risk factors - overweight/obesity and alcohol consumption - often track into adulthood and are associated with increased risk of Non-Communicable Disease, including cancer. In Italy, in 2020, excess body weight accounted for 3.6% of all male cancers and for 4.0% of female ones, corresponding to nearly 7,000 and 7,200 cases, respectively (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). Although the onset of many obesity-related and alcohol-related cancers mainly occurs in adulthood, early exposures during adolescence and young adulthood could significantly be responsible for the growing incidence before age 50 (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e1.3 Biological and Epidemiological Evidence\u003c/h2\u003e \u003cdiv id=\"Sec8\" class=\"Section3\"\u003e \u003ch2\u003e1.3.1 Breast Cancer\u003c/h2\u003e \u003cp\u003e \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eBreast cancer risk and progression are strongly influenced by both alcohol consumption and obesity through interconnected hormonal, metabolic, and inflammatory mechanisms. Alcohol intake enhances the invasive and metastatic potential of breast cancer cells, particularly those overexpressing\u003c/span\u003e Human Epidermal Growth Factor Receptor 2 (HER2) (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eA key mechanism involves estrogen metabolism: alcohol\u003c/span\u003e consumption is associated with higher \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003ecirculating estrogen levels and increased mammographic breast density, both recognized risk factors for breast cancer\u003c/span\u003e (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eExperimental evidence shows that ethanol enhances estrogen receptor α (ERα) expression and signaling in breast cancer cells, thereby promoting tumor growth and metastatic behavior\u003c/span\u003e (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eAdditionally, alcohol-induced estrogen signaling may increase matrix metalloproteinase (MMP) expression, facilitating extracellular matrix degradation and tumor dissemination\u003c/span\u003e (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eOxidative stress represents another central pathway linking alcohol to breast carcinogenesis. Ethanol metabolism generates reactive oxygen species (ROS), particularly through cytochrome P450 2E1 (CYP2E1) induction, leading to lipid peroxidation, DNA damage, and mutagenesis\u003c/span\u003e (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eEthanol exposure also enhances epidermal growth factor receptor (EGFR) phosphorylation, stimulating mammary epithelial cell proliferation via ROS-dependent pathways\u003c/span\u003e (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eObesity further amplifies breast cancer risk by altering the adipose tissue microenvironment. Obese adipose tissue is characterized by hypoxia, chronic inflammation, and a shift toward pro-tumorigenic adipokines such as leptin, while protective adiponectin levels are reduced\u003c/span\u003e (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003ePro-inflammatory cytokines (e.g., IL\u0026minus;6, TNF-α) and free fatty acids increase aromatase expression via nuclear factor-kappa B (NF-κB) signaling, enhancing local estrogen biosynthesis and driving estrogen receptor\u0026ndash;positive breast cancer, particularly in postmenopausal women\u003c/span\u003e (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section3\"\u003e \u003ch2\u003e1.3.2 Colorectal Cancer\u003c/h2\u003e \u003cp\u003e \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eAlcohol intake and obesity significantly contribute to colorectal cancer (CRC) development, particularly in younger populations. Ethanol exerts carcinogenic effects in the colon through both oxidative and non-oxidative metabolic pathways, promoting epithelial cell proliferation and exposure to acetaldehyde\u003c/span\u003e (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e). \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eAlcohol-induced dysbiosis alters gut microbiota composition, favoring acetaldehyde-producing bacteria and biofilm formation, which prolongs epithelial exposure to carcinogenic metabolites\u003c/span\u003e (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e). \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eAdditionally, alcohol increases intestinal permeability, facilitating microbial translocation and triggering chronic inflammation that enhances susceptibility to neoplastic transformation\u003c/span\u003e (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e). \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eObesity promotes CRC through insulin resistance, hyperinsulinemia, and chronic inflammation. Elevated insulin and insulin-like growth factor 1 (IGF\u0026minus;1) levels stimulate colorectal cell proliferation and inhibit apoptosis, while hyperglycemia and lipid abnormalities increase oxidative stress and DNA damage\u003c/span\u003e (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e). \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003ePro-inflammatory cytokines such as IL\u0026minus;6 sustain tumor-promoting signaling pathways in the intestinal epithelium\u003c/span\u003e (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section3\"\u003e \u003ch2\u003e1.3.3 Synergistic Effects\u003c/h2\u003e \u003cp\u003e \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eAlcohol consumption and obesity interact synergistically to amplify cancer risk through shared mechanisms including chronic inflammation, oxidative stress, insulin resistance, and hormonal dysregulation. Experimental and observational studies indicate that obesity-related metabolic and hormonal alterations enhance alcohol-induced sensitivity to insulin and estrogens, increasing breast cancer risk, particularly in postmenopausal women\u003c/span\u003e (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eThis synergism is also evident in hepatocellular carcinoma, where the coexistence of obesity-related fatty liver disease and alcohol-induced liver injury markedly increases long-term cancer risk compared to either factor alone\u003c/span\u003e (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e). Evidence from a large cohort study indicates that unhealthy lifestyle factors, including alcohol consumption, interact with genetic predisposition to increase the risk of early-onset breast cancer (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e). \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eThese findings highlight the importance of integrated lifestyle interventions, as sustained reductions in body weight and alcohol consumption may substantially reduce cancer risk across multiple organs\u003c/span\u003e (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"2. Methods","content":"\u003cp\u003eFor colorectal and breast cancers, PAFs were estimated using Levin\u0026rsquo;s formula (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e):\u003c/p\u003e \u003cp\u003ePAF\u0026thinsp;=\u0026thinsp;p \u0026times; (RR\u0026thinsp;\u0026minus;\u0026thinsp;1) / [1\u0026thinsp;+\u0026thinsp;p \u0026times; (RR\u0026thinsp;\u0026minus;\u0026thinsp;1)]\u003c/p\u003e \u003cp\u003ewhere p\u0026thinsp;=\u0026thinsp;prevalence of each risk factor (i.e. overweight/ obesity and risky alcohol consumption as previously defined), and RR\u0026thinsp;=\u0026thinsp;relative risk.\u003c/p\u003e \u003cp\u003eCombined PAFs were calculated as:\u003c/p\u003e \u003cp\u003ePAF_combined\u0026thinsp;=\u0026thinsp;1 \u0026minus; (1\u0026thinsp;\u0026minus;\u0026thinsp;PAF₁)(1\u0026thinsp;\u0026minus;\u0026thinsp;PAF₂)(1\u0026thinsp;\u0026minus;\u0026thinsp;PAF₃),\u003c/p\u003e \u003cp\u003eassuming statistical independence between overweight/obesity and high-risk alcohol consumption. We acknowledge that these exposures are likely correlated in real populations; therefore, our estimates may under- or overestimate the true combined attributable fraction.\u003c/p\u003e \u003cp\u003eConfidence intervals for PAF were based on approximate propagation of imprecision (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e), and sensitivity analyses explored alternative prevalence and RR assumptions to assess robustness. Sex-specific prevalence of overweight, obesity and risky alcohol consumption was extracted for the Italian young adults population (18\u0026ndash;34 years) from the national \u0026ldquo;PASSI\u0026rdquo; surveillance system (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). RRs with 95% confidence intervals (CIs) for the association between overweight, obesity, alcohol consumption and cancer sites were derived from recent meta-analyses (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan additionalcitationids=\"CR37\" citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e). Sex-specific estimates were extracted, when available.\u003c/p\u003e \u003cp\u003eSensitivity analyses were conducted to assess the robustness of PAF estimates to uncertainty in both prevalence and relative risk parameters. Specifically, PAFs were recalculated across plausible ranges of prevalence and RR values, informed by the variability observed in national surveillance data and by the 95% confidence intervals reported in the literature. Results of the sensitivity analysis were visualized using contour plots, in which PAF values are represented as a topographic surface: color bands identify intervals of similar PAF magnitude, with higher intensity colors corresponding to larger attributable fractions. This approach allows the joint influence of prevalence and RR on PAF estimates to be explored allowing the identification of parameter regions associated with higher or lower population-attributable burden.\u003c/p\u003e"},{"header":"3. Results","content":"\u003cp\u003ePAFs for overweight, obesity and high-risk alcohol consumption were estimated for early-onset colorectal and breast cancers using age and sex specific prevalence data and relative risk. Results are reported by cancer site, exposure, age group and sex (Table 1, Table 2, Figure 1). Primary analyses were conducted for the overall 18\u0026ndash;34 age group, with additional stratified analyses for 18\u0026ndash;24 and 25\u0026ndash;34 years limited to alcohol exposure.\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eEarly-onset colorectal cancer:\u003c/u\u003e Among young Italian adults aged 18-34 years, overweight accounted for 3.6% (95% CI: 1.7, 5.6) of early onset colorectal cancer cases, while obesity accounted for 1.7% (95% CI: 0.6, 3). \u0026nbsp;Among men, PAF for colorectal cancer was 9.8% (95% CI: 6.5, 13.1) and 4.2% (95% CI: 2, 6.8) in relation to overweight and obesity, respectively. Among women, a PAF of 4.4 (95% CI: 2.2, 6.7) for overweight and a PAF of 3.7% (95% CI: 1.7, 5.9) for obesity were estimated. High-risk alcohol consumption showed a larger attributable fraction with a PAF of 8.2% (95% CI: 0.3, 16.4) in individuals aged 18-24 years and 10.7% (95% CI: 8.9, 12.5) in those aged 25-34 years. For early-onset CRC, the combined estimated contribution of excess body weight and alcohol consumption reached 12.2%.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eEarly-onset breast cancer:\u003c/u\u003e In young Italian women (18-34y), obesity accounted for 2.8% (95% CI: 1.7, 3.9) of early onset breast cancer cases, while high-risk alcohol consumption was associated with a PAF of 4.6% (95% CI: 3.8, 5.5). \u0026nbsp;The negative lower confidence bound reflects statistical imprecision rather than a protective effect.\u003c/p\u003e\n\u003cp\u003eSensitivity analyses showed that PAF estimates increased with higher values of both prevalence and relative risk. Variations in RR produced larger changes in PAFs value compared with equivalent variations in prevalence, indicating a greater sensitivity of PAF to uncertainty in risk estimates. Across the full range of plausible assumptions, however, the relative contribution of overweight, obesity and high-risk alcohol consumption to early-onset colorectal and breast cancer remained consistent. Figure 2 illustrates the results of the sensitivity analyses for selected exposure\u0026ndash;outcome associations. \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1.\u003c/strong\u003e Prevalence and Relative Risks (RRs) of Selected Exposures. Relative risks were primarily derived from studies in adult populations due to the limited availability of age-specific estimates for early-onset cancer.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"636\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 105px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"bottom\" style=\"width: 289px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Cancer RR (95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 36px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 105px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eExposure\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGroup\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePrevalence (95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 139px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eColon and Rectum\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 42px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRef\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBreast\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 36px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRef\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"bottom\" style=\"width: 105px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOverweight\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e18-34 y\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 142px;\"\u003e\n \u003cp\u003e21.5 (20.28, 22.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 139px;\"\u003e\n \u003cp\u003e1.18 (1.08, 1.28)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 42px;\"\u003e\n \u003cp\u003e(4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 36px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMen\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 142px;\"\u003e\n \u003cp\u003e40.7 (40.0, 41.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 139px;\"\u003e\n \u003cp\u003e1.27 (1.17, 1.37)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 42px;\"\u003e\n \u003cp\u003e(4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 36px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWomen\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 142px;\"\u003e\n \u003cp\u003e24.6 (24.0, 25.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 139px;\"\u003e\n \u003cp\u003e1.19 (1.09, 1.29)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 42px;\"\u003e\n \u003cp\u003e(4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 36px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"bottom\" style=\"width: 105px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eObesity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e18-34 y\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 142px;\"\u003e\n \u003cp\u003e5.5 (5.1, 6.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 139px;\"\u003e\n \u003cp\u003e1.32 (1.11, 1.56)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 42px;\"\u003e\n \u003cp\u003e(4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 36px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMen\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 142px;\"\u003e\n \u003cp\u003e11.2 (10.7, 11.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 139px;\"\u003e\n \u003cp\u003e1.39 (1.18, 1.65)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 42px;\"\u003e\n \u003cp\u003e(4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 36px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWomen\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 142px;\"\u003e\n \u003cp\u003e9.6 (9.3, 10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 139px;\"\u003e\n \u003cp\u003e1.22 (0.99, 1.51)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 42px;\"\u003e\n \u003cp\u003e(4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 108px;\"\u003e\n \u003cp\u003e1.29 (1.18, 1.42)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 36px;\"\u003e\n \u003cp\u003e(36)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" valign=\"bottom\" style=\"width: 105px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHigh risk Alcohol Drinking\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e18-24 y\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 142px;\"\u003e\n \u003cp\u003e14.9 (13.9, 15.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 139px;\"\u003e\n \u003cp\u003e1.26 (1.01, 1.58)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 42px;\"\u003e\n \u003cp\u003e(38)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 36px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e25-34 y\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 142px;\"\u003e\n \u003cp\u003e12.6 (11.9, 13.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 139px;\"\u003e\n \u003cp\u003e1.49 (1.40, 1.58)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 42px;\"\u003e\n \u003cp\u003e(38)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 36px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMen\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 142px;\"\u003e\n \u003cp\u003e21.9 (21.4, 22.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 139px;\"\u003e\n \u003cp\u003e1.55 (1.46, 1.66)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 42px;\"\u003e\n \u003cp\u003e(37)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 36px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWomen\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 142px;\"\u003e\n \u003cp\u003e13.9 (13.5, 14.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 139px;\"\u003e\n \u003cp\u003e1.09 (0.79, 1.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 42px;\"\u003e\n \u003cp\u003e(37)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 108px;\"\u003e\n \u003cp\u003e1.35 (1.28, 1.42)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 36px;\"\u003e\n \u003cp\u003e(37)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eAbbreviations\u003c/strong\u003e: RR, relative risk; CI, confidence interval.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2.\u003c/strong\u003e Estimated Population Attributable Fractions (PAF) for Overweight, Obesity, and Alcohol\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"607\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 131px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 110px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 366px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;PAF (95% CI), %\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 131px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eExposure\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 110px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGroup\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 184px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eColon and Rectum\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 182px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBreast\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"bottom\" style=\"width: 131px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOverweight\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 110px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e18-34 y\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 184px;\"\u003e\n \u003cp\u003e3.6 (1.7, 5.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 182px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 110px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMen\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 184px;\"\u003e\n \u003cp\u003e9.8 (6.5, 13.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 182px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 110px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWomen\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 184px;\"\u003e\n \u003cp\u003e4.4 (2.2, 6.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 182px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"bottom\" style=\"width: 131px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eObesity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 110px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e18-34 y\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 184px;\"\u003e\n \u003cp\u003e1.7 (0.6, 3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 182px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 110px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMen\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 184px;\"\u003e\n \u003cp\u003e4.2 (2, 6.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 182px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 110px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWomen\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 184px;\"\u003e\n \u003cp\u003e3.7 (1.7, 5.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 182px;\"\u003e\n \u003cp\u003e2.8 (1.7, 3.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" valign=\"bottom\" style=\"width: 131px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHigh risk Alcohol Drinking\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 110px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e18-24 y\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 184px;\"\u003e\n \u003cp\u003e8.2 (0.3, 16.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 182px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 110px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e25-34 y\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 184px;\"\u003e\n \u003cp\u003e10.7 (8.9, 12.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 182px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 110px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMen\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 184px;\"\u003e\n \u003cp\u003e10.9 (9.1, 12.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 182px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 110px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWomen\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 184px;\"\u003e\n \u003cp\u003e1.2 (-3, 6.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 182px;\"\u003e\n \u003cp\u003e4.6 (3.8, 5.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eAbbreviations\u003c/strong\u003e: PAF, Population Attributable Fractions; CI, confidence interval.\u003c/p\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThese findings underscore the significant, yet preventable, contribution of obesity and alcohol consumption to early-onset cancers in Italy.\u003c/p\u003e\n\u003cp\u003eTaken together, these exposures may explain up to 12.2% of early-onset CRC cases among young adults aged 18-34 years. This proportion is consistent with international evidence linking early-life adiposity and alcohol intake with increasing cancer risk.\u003c/p\u003e\n\u003cp\u003eThe study’s main strengths include the use of nationally representative surveillance data (“PASSI”) and age-specific prevalence estimates. However, several limitations should be acknowledged: RRs were derived primarily from adult populations, and the assumption of independence between risk factors may underestimate potential synergistic effects. Additionally, prevalence estimates were limited to available national datasets, which may not fully capture temporal or regional variability among adolescents and young adults.\u003c/p\u003e\n\u003cp\u003eDespite these caveats, our analysis underscores the importance of early, integrated prevention strategies. Combining interventions on weight management and alcohol reduction could prevent a measurable proportion of early-onset colorectal and breast cancer cases. These results are particularly relevant given the rising incidence of malignancies before age 50 and the shifting distribution of modifiable exposures towards younger cohorts.\u003c/p\u003e\n\u003cp\u003eFindings from the sensitivity analyses provide additional insight into the robustness of the estimated PAFs. Although uncertainty in both prevalence and relative risk affects the magnitude of attributable fractions, the analysis indicates that relative risk assumptions represent the main driver of variability. After all, in the calculation, the RR has an exponential impact, whereas prevalence has a linear effect, making the PAF more sensitive to imprecise RR estimates. This highlights the importance of high-quality, age-specific risk estimates when quantifying the population-level impact of modifiable exposures in young adults. Importantly, even under conservative assumptions, the combined contribution of obesity and alcohol consumption to early-onset cancers remained substantial.\u003c/p\u003e\n\u003ch3\u003e\u003cem\u003eClinical and Policy Implications\u003c/em\u003e\u003c/h3\u003e\n\u003cp\u003eOur results highlight how moderate relative risks, when coupled with a high prevalence of exposure in young adults, may translate into a meaningful population-level burden, reinforcing the relevance of early preventive strategies.\u003c/p\u003e\n\u003cp\u003eFrom a clinical perspective, routine BMI and alcohol use screening should become an integral part of both oncology and primary care settings, ensuring that early preventive interventions are systematically offered to young adults. In this context, brief motivational counselling, following the 5A model (Ask, Advise, Assess, Assist, Arrange) as described in the WHO primary care toolkit (39), together with referral to structured weight management and alcohol reduction programs, should be established as standard components of care pathways.\u003c/p\u003e\n\u003cp\u003eAt the policy level, population-wide interventions are equally crucial. Measures such as alcohol pricing regulation, warning labels, and restrictions on alcohol availability near educational environments could substantially reduce exposure among younger age groups and reinforce individual-level efforts.\u003c/p\u003e\n\u003cp\u003eFinally, key research gaps must be addressed to strengthen the evidence base. There remains an urgent need for joint prevalence studies assessing the co-occurrence of obesity and alcohol use in youth, as well as for age-stratified relative risk estimates and longitudinal analyses exploring the combined effects of these modifiable risk factors on cancer incidence.\u003c/p\u003e\n\u003cp\u003eThese considerations are summarised in Box 1, which outlines key action points for clinicians, multidisciplinary teams, public health stakeholders, and researchers.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBox 1. Recommendations and call to action\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"665\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDomain\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eRecommended Actions\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eOncology Practice\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eScreen BMI and alcohol use at first visit; integrate brief lifestyle counselling within “Percorsi Diagnostico-Terapeutici Assistenziali”\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;for early-onset breast and colorectal cancer.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMultidisciplinary Teams\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eInclude dietitians, psychologists, and health educators in care pathways to deliver personalized prevention strategies.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePublic Health and Policy\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eImplement youth-targeted information campaigns in schools and universities, strengthen alcohol taxation and labelling regulations.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eResearch\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePromote longitudinal cohort studies exploring combined exposure trajectories and cancer outcomes in young adults.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e5. Conclusion\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eObesity and alcohol are preventable and measurable determinants of youth-onset cancers. Integrating lifestyle assessment and behavioral counselling into oncology and preventive pathways could substantially reduce the future burden of early-onset cancers in Italy. From a broader public health perspective, policies addressing weight control and alcohol misuse in younger populations represent a strategic opportunity to reverse current cancer trends and mitigate long-term disease risk.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eAYA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAdolescents and Young Adults\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eBMI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eBody Mass Index\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eConfidence Interval\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCRC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eColorectal Cancer\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCYP2E1\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCytochrome P450 2E1\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eEGFR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eEpidermal Growth Factor Receptor\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHER2\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eHuman Epidermal Growth Factor Receptor 2\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eERα\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eEstrogen Receptor alpha\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eIGF-1\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eInsulin-like Growth Factor 1\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eIL-6\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eInterleukin 6\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMMP\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eMatrix Metalloproteinase\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eNF-κB\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eNuclear Factor kappa B\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePAF\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePopulation Attributable Fraction\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePASSI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eProgressi delle Aziende Sanitarie per la Salute in Italia\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eRR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eRelative Risk\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eROS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eReactive Oxygen Species\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eTNF-α\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eTumor Necrosis Factor alpha\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eWHO\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eWorld Health Organization\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e: Not applicable. This study is based on analyses of aggregated data derived from publicly available national surveillance systems and published literature.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication:\u0026nbsp;\u003c/strong\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials:\u0026nbsp;\u003c/strong\u003eAll data used in this study are derived from publicly available sources, including the Italian national surveillance system PASSI and published scientific literature. No individual-level data were used.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests:\u003c/strong\u003e The authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u0026nbsp;\u003c/strong\u003eThis work was funded under the National Recovery and Resilience Plan (NRRP), Mission 4 Component 2 Investment 1.3 — Call No. 341 (15 March 2022) of the Italian Ministry of University and Research, funded by the EU — NextGenerationEU, Project PE00000003 (Decree No. 1550/2022, CUP F13C22001210007, “ON Foods — Research and Innovation Network on Food and Nutrition Sustainability, Safety and Security — Working ON Foods”).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor’s Contributions:\u0026nbsp;\u003c/strong\u003eHC conceived the study and coordinated the work. FB, SL, GB, LL contributed to data analysis and literature review. HC, FB, SL, LL contributed to writing—original draft preparation, review and editing. NM, AV, MM, LDL, FS supervised and critically revised the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments:\u003c/strong\u003e National Recovery and Resilience Plan (NRRP), Mission 4 Component 2. Investment 1.4—Call for tender No. 3138 of 16 December 2021, rectified by Decree n.3175 of 18 December 2021 of Italian Ministry of University and Research funded by the European Union— NextGenerationEU; Project code CN_00000033, Concession Decree No. 1034 of 17 June 2022 adopted by the Italian Ministry of University and Research, CUP F13C22000720007, Project title “National Biodiversity Future Center—NBFC”.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eChen J, Dalerba P, Terry MB, Yang W. Global obesity epidemic and rising incidence of early-onset cancers. 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IL\u0026ndash;6 and Stat3 Are Required for Survival of Intestinal Epithelial Cells and Development of Colitis-Associated Cancer. Cancer Cell. 2009;15(2):103\u0026ndash;13.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHong J, Holcomb VB, Dang F, Porampornpilas K, N\u0026uacute;\u0026ntilde;ez NP. Alcohol Consumption, Obesity, Estrogen Treatment and Breast Cancer. ANTICANCER Res. 2010.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLoomba R, Yang HI, Su J, Brenner D, Iloeje U, Chen CJ. Obesity and alcohol synergize to increase the risk of incident hepatocellular carcinoma in men. Clin Gastroenterol Hepatol Off Clin Pract J Am Gastroenterol Assoc. 2010;8(10):891\u0026ndash;8. 898.e1\u0026ndash;2.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang Y, Lindstr\u0026ouml;m S, Kraft P, Liu Y. Genetic risk, health-associated lifestyle, and risk of early-onset total cancer and breast cancer. J Natl Cancer Inst. 2025;117(1):40\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAnderson AS, Renehan AG, Saxton JM, Bell J, Cade J, Cross AJ, et al. Cancer prevention through weight control-where are we in 2020? Br J Cancer. 2021;124(6):1049\u0026ndash;56.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLevin ML. The occurrence of lung cancer in man. Acta - Unio Int Contra Cancrum. 1953;9(3):531\u0026ndash;41.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFerguson J, Alvarez-Iglesias A. Confidence intervals using approximate propagation of imprecision. In 2023 [Accessed 12 Feb 2026]. 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Prevalence of and Risk Factors for Colorectal Neoplasia in Asymptomatic Young Adults (20\u0026ndash;39 Years Old). Clin Gastroenterol Hepatol Off Clin Pract J Am Gastroenterol Assoc. 2019;17(1):115\u0026ndash;22.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWorld Health Organization. Toolkit for delivering the 5A\u0026rsquo;s and 5R\u0026rsquo;s brief tobacco interventions in primary care [Internet]. 2014 [Accessed 11 Feb 2026]. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://iris.who.int/items/9e874a72\u0026ndash;5ff9\u0026ndash;47ef-ab23\u0026ndash;28af3b274ee7\u003c/span\u003e\u003cspan address=\"https://iris.who.int/items/9e874a72\u0026ndash;5ff9\u0026ndash;47ef-ab23\u0026ndash;28af3b274ee7\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Early-onset cancer, Young adults, Population attributable fraction, Obesity, Alcohol consumption, Breast cancer, Colorectal cancer, Cancer prevention","lastPublishedDoi":"10.21203/rs.3.rs-8927891/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8927891/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eRising rates of cancers diagnosed before the age of 50 have been reported worldwide, including in Italy. Among modifiable risk factors, obesity and alcohol consumption independently and synergistically increase the risk of breast and colorectal cancers, including early-onset disease. However, the population-level burden attributable to these exposures among adolescents and young adults (AYA) remains poorly quantified.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eWe integrated a narrative review with a quantitative Population Attributable Fraction (PAF) analysis to estimate the proportion of early-onset breast and colorectal cancers attributable to overweight/obesity, high-risk alcohol consumption, and their combined exposure in the Italian population aged 18\u0026ndash;34 years. Sex- and age-specific prevalence data were derived from the national surveillance systems (\u0026ldquo;PASSI\u0026rdquo;), while relative risks were obtained from meta-analyses and large cohort studies. Combined PAFs were estimated assuming independence between exposures and tested through sensitivity analyses varying prevalence and relative risk assumptions.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eAmong young adults aged 18\u0026ndash;34 years, overweight and obesity together accounted for a substantial proportion of early-onset colorectal cancer cases, while high-risk alcohol consumption showed the largest individual attributable fraction. The combined contribution of excess body weight and alcohol consumption reached 12.2% of early-onset colorectal cancer cases. For early-onset breast cancer in young women, obesity and high-risk alcohol consumption were associated with PAFs of 2.8% and 4.6%, respectively. Sensitivity analyses confirmed the robustness of the estimates and indicated that uncertainty in relative risk assumptions represented the main source of variability.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eObesity and alcohol consumption contribute meaningfully to the burden of early-onset breast and colorectal cancers in Italy. Integrating weight management and alcohol risk assessment into clinical practice and public health strategies targeting young adults could prevent a measurable proportion of these cancers and help counteract the rising incidence of malignancies at young ages.\u003c/p\u003e","manuscriptTitle":"Youth-Onset Cancer and Modifiable Risk: Quantifying the Combined Impact of Obesity and Alcohol on Breast and Colorectal Cancer in Italy (18-34 Years)","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-08 14:31:50","doi":"10.21203/rs.3.rs-8927891/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-04-22T07:12:45+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-20T04:03:50+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-19T22:00:34+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"214616984067621248423319790959312514288","date":"2026-03-27T17:24:48+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"163591707648171510681669916906106307357","date":"2026-03-27T15:54:42+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-19T12:15:19+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"126555521904952258470259829930272438324","date":"2026-02-26T08:52:19+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-02-25T18:47:01+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-02-24T05:17:53+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-02-24T05:17:46+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Public Health","date":"2026-02-20T16:49:37+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"73e8b188-bf17-49f9-8a50-902dfee96ad2","owner":[],"postedDate":"March 8th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-13T13:38:50+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-08 14:31:50","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8927891","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8927891","identity":"rs-8927891","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}