Breastfeeding Promotion to Prevent Breast Cancer: an Economic Evaluation

Breastfeeding Promotion to Prevent Breast Cancer: an Economic Evaluation | 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 Help Center Sign In Submit a Preprint Cite Share Download PDF Short Report Breastfeeding Promotion to Prevent Breast Cancer: an Economic Evaluation Lai Ling HUI, Emily LIAO, Jin Xiao LIAO, Ching SO, Ting Ting WU, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4283403/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 24 Feb, 2025 Read the published version in International Breastfeeding Journal → Version 1 posted 11 You are reading this latest preprint version Abstract Objectives Our study aimed to estimate the healthcare cost-savings resulting from a reduction in breast cancer attributed to an increase in the breastfeeding rate in Hong Kong. Methods This is an economic evaluation. We simulated a cohort of 33500 Hong Kong women aged 20 years in 2018 using the Monte Carlo Model, to estimate with probabilistic sensitivity analysis the healthcare cost-savings, the number of deaths averted and the increase in disability-adjusted life years (DALYs) due to prevention of breast cancer attributed to a higher breastfeeding rate, assuming a discount rate of 3%. Results Increasing the proportion of parous women breastfeeding exclusively for 6 months from 22% (current rate) to 90% averted 266 (95% CI259, 273) or ~10% of all-stage breast cancer cases, 18 deaths (95% CI 17, 19) and 399 DALYs (95% CI 381, 416), over the lifetime of each annual cohort of women in Hong Kong. The lifetime medical costs that could be saved would be ~USD3 million. However cost-saving was 5-time less if the cumulative any breastfeeding (i.e. partially or exclusively) for 12 months in parous women is increased to 90%. Conclusions Promoting and protecting breastfeeding leads to cost-savings for treating breast cancer in Hong Kong. Our analysis can inform healthcare budget resources that could be allocated to promote exclusive breastfeeding for 6 months. Breastfeeding breast cancer economic evaluation the Monte Carlo Model cost-savings DALYs Figures Figure 1 Figure 2 INTRODUCTION In addition to its many benefits for infants, breastfeeding protects mothers against breast cancer.( 1 ) Given that breastfeeding, and particularly exclusive breastfeeding, is still not the norm in many places, including Hong Kong, promotion of breastfeeding could reduce future breast cancer incidence and its related healthcare costs. Treatment cost of breast cancer that could be saved by increased breastfeeding rate has been estimated in different settings. In the UK, it was estimated that £21 million (2009–2010 value), over the lifetime of a cohort of first-time mothers in 2009, could be saved as a result a reduced treatment costs for maternal breast cancer. ( 2 ) In Mexico, US $ 71.27 million (2012 value) direct healthcare treatment costs for breast cancer could be avoided for a cohort of 1.116 million Mexican women aged 15 years in 2012. ( 3 ) A US study reported total medical costs of $ 118 million (2014 value) for treating breast cancer could be saved for the cohort of US women aged 15 years in 2002 over their lifetime. ( 4 ) These results are highly setting specific due to differences in epidemiology of breast cancer and financing of healthcare. In the past 3 decades, Hong Kong has experienced a 3-fold increase in breast cancer incidence which imposes a huge burden on not only families but also the governmental healthcare system because the majority of breast cancers are treated in the heavily subsidised public system. The breast cancer incidence per 100,000 females increased from 39.4 in 1990 to 116.6 in 2019, constituting 27% of all new cancers in women.( 5 ) Meanwhile the breastfeeding rate has been suboptimal in Hong Kong, despite an improvement in recent decades compared to the 1980s when only respectively 7.6% and 3.9% infants were breastfed at 1 and 3 months.( 6 ) The exclusive breastfeeding rate was 32% at 1 month and 26% at 6 months in 2018, with a any breastfeeding rate of 46.5% at 6 months.( 7 ) Although trends in breastfeeding rates and breast cancer incidence are likely driven by a range of factors, suboptimal breastfeeding rates and high breast cancer incidence in Hong Kong offers opportunities to optimise resource allocation decisions to maximize population health among women and children by promoting breastfeeding. This study assesses healthcare costs for breast cancer treatment that could be saved by an increase in the breastfeeding rate. These data can inform decisions on the efficient utilization of healthcare resources in Hong Kong because the majority of the cancers are treated in public system. METHODS Perspective We aimed to estimate costs for breast cancer treatment due to suboptimal breastfeeding from a provider perspective. We did not consider individual costs and societal costs, such as loss of productivity due to absence from work. The Model A individual based Monte Carlo model (Figure 1) adopted from previous studies (4, 8) was constructed to simulate the development of breast cancer over a woman’s lifetime in a birth cohort aged 20 years in 2018 (n=33500), with which we compared the cases and deaths of breast cancer in the base case (breastfeeding rate in 2018) and two hypothetical optimal scenarios (1: 90% parous women exclusively/partially breastfeed at least 12 months or 2: 90% parous women exclusively breastfed for 6 months). In each scenario, the proportion of parous women in each year was simulated according to 20 to 49 year-old age-specific fertility rates in Hong Kong in 2018. The maximum parity was set at two because average fertility rate was as low as 1.1-1.3 during 2010-2019. For each simulated woman, the risk of developing breast cancer in each year from age 20 to 80 years was simulated based on her age, cumulative lifetime breastfeeding history and age-specific incidence rates of breast cancer in 2018. The case-fatality was simulated based on the age, stage at diagnosis and ten-year survival rates extrapolated from the stage-specific relative 1-to-5-year survival rates from the Hong Kong Cancer Registry, but not their breastfeeding history. The mortality of women without breast cancer was simulated using the age-specific death rates among females in Hong Kong. We assumed steady-state rates of disease incidence, disease survival, fertility, and the cost of treatment. We did not consider transitions between stages as early diagnosed breast cancers are mainly treated and we set out to provide an conservative estimates. Deaths for women surviving beyond 10 years from diagnosis were considered unrelated to breast cancer. Cost and DALYs estimation We calculated the treatment cost and DALYs associated with breast cancer in each scenario of breastfeeding rate using stage-specific aggregated one-time treatment costs reported in a local study (9) and DALYs information from the Global Burden of Disease Study (10), at an annual discount rate of 3%. Costs were converted to US dollars based on the exchange rate in 2018 (1 USD=7.8 HKD). The terminal care cost would be applied when the death due to breast cancer occurred in the simulation. We assumed all the diagnosed breast cancer cases would receive treatment. We also assumed treatment cost in public sector, which is heavily subsidised by the government is the same as private hospitals, where more expensive treatment options are maybe available. For DALYs calculation, the number of years lived with disability (YLD) and the number of years of life lost (YLL) were deduced with the formula in the DALY calculator for R. The information to calculate YLL and YLD, including age of onset and duration of disease, were derived from the simulation of the disease outcome for each woman. Survivors beyond ten years were considered cured.(10) Two sequelae (diagnosis and primary therapy, and controlled phase) were assumed for cases that were cured, and four sequelae (diagnosis and primary therapy; controlled phase; metastatic phase; terminal phase) were assumed for those did not survive beyond ten years. Age-weighting was not applied. Sensitivity analysis and validation The simulated outcomes were based on 500 iterations each with parameters including relative risks, age-specific incidence of breast cancer, aggregated treatment costs, and disability weights randomly generated from specified distributions. (Table 1) The results from probabilistic sensitivity analysis was validated by comparing deduced incidence rates from the model for the base case with the actual rates. We also carried out deterministic sensitivity analysis to assess the main cost drivers (by changing one parameter at a time) and the most/least cost-saving simulations (by changing parameters at the same time to achieve most/least cost-saving scenario). Parameters for the simulation were identified from literature and government statistics. (Table 1) Programming was performed using Python and R statistical software version 4.1.0 (Vienna, Austria; R Core Team, 2021) . RESULTS In the cohort of 33500 women aged 20 years in 2018, our model simulated 2550–2570 cases of breast cancer developed in their lifetime. The simulated stage-specific incidence rates in base case were congruent with the actual age-specific incidence rates from Hong Kong cancer registry.(Supplementary Table S4) Increasing the proportion of parous women with a cumulative breastfeeding duration of at least 12 months from current levels to 90%, i.e. optimal scenario 1, averted 59 (95% CI 54, 62) cases of breast cancer, from which 3 (95% CI 3,5) premature deaths and 84 DALYs (95% CI 70, 100) could be prevented. In optimal scenario 2 when 90% of parous women breastfeed exclusively for 6 months, 266 (95% CI 259,273) or about 10% of all-stage breast cancer cases, 18 death (95% CI 17,19) and 399 DALYs (95% CI 381, 416) could be averted. (Table 2) Using 2018 prices with 3% discount rate, the total lifetime medical treatment costs for breast cancer that could be saved in the lifetime of the women in the simulated cohort would be about US $ 0.65 (95% CI 0.60, 0.70) million when 90% parous women have cumulative breastfeeding for 12 months. The saving was estimated to be US $ 3.07 (2.98, 3.15) million when 90% parous women exclusively breastfeed for 6 months. (Table 2) The deterministic sensitivity analyses suggest the cost-savings would be made should the optimal breastfeeding rates for both scenarios be achieved for all individual scenarios and marginally for the worst-case scenario (Fig. 2 ). Discount rates have the largest impact on the estimated cost-savings over a lifetime. The relative risk of breast cancer in favour of breastfeeding was more important when exclusive breastfeeding was considered (optimal scenario 2) compared to any breastfeeding rate (optimal scenario 1), due to the wider confidence intervals of the relative risk. We compared the economic evaluations with optimal scenario 1 with similar economic evaluations in the UK, the US, and Mexico assuming a change in the duration of cumulative breastfeeding duration in the optimal scenario (Supplementary Table S5). Cases averted per 100,000 women were 392 for Mexico (when 95% of parous women breastfeed for 24 months), 252 for the US (when 90% of mothers breastfeed each infant exclusively for 6 months, with continuing breastfeeding through 12 months postpartum) and 176 for Hong Kong (when 90% of parous women breastfeed for 12 months). DISCUSSION Our findings suggested that increasing the exclusive breastfeeding rate at 6 months from the current rate (about 22%) to 90% in Hong Kong could avert 266 cases of breast cancer and save US $ 3 million (2018 price) attributed to the prevention of breast cancer over the lifetime of each annual cohort of 33500 women. There would also be 16 premature deaths prevented and 399 DALYs averted. The benefits of having 90% parous women with cumulative any breastfeeding duration of 12 months were about 5 times less. Prioritising the exclusivity in breastfeeding promotion could avert more cases of breast cancer and lead to more governmental healthcare cost-saving in Hong Kong where majority of breast cancer are treated in public settings and heavily subsidised. We carefully considered uncertainties of inputs, including protection of breastfeeding against breast cancer, disability weight, breastfeeding rate, treatment cost per case and breast cancer stage distribution using probabilistic sensitivity analyses in the present economic evaluations. However there are some caveats in the model that require considerations. First we assumed age-specific incidences of breast cancer to be static despite breast cancer incidence has been on a rising trend. Second we assumed there was no disease progression from earlier stages to metastasis the case-fatalities were higher for stages III and IV cancers. Thirdly we assumed treatment cost in the public sector is the same as private hospitals, although some treatment in private settings may be more expensive than public hospitals. These assumptions made our economic evaluation more conservative which may underestimate the cost-saving. The actual cost-saving is likely to be higher. Similar economic evaluations in both high-income settings (the UK ( 2 ) and the US( 4 )) and a lower income setting (Mexico ( 3 )) reported that an increase in proportion of women practicing any breastfeeding is cost-saving for breast cancer treatment. The cases averted and the cost saved in each setting being dependent on the epidemiology of breast cancer (such as age-specific disease incidence and survival rate), detection rate of early breast cancer, fertility rate, breastfeeding status and assumed protection of breastfeeding. The fewer breast cancer cases averted per 100,000 women in Hong Kong than those in the US and Mexico (Supplementary Table S4) may be partly attributed to the much lower fertility rate, the early detection rate and the high survival rate of early breast cancer in Hong Kong. Our findings suggested that exclusive breastfeeding for 6 months could lead to substantial cost-savings for treating breast cancer in Hong Kong and alleviate suffering for women and their families. Promoting breastfeeding, especially exclusive breastfeeding, is an early lifestyle-related intervention for preventing breast cancer, in addition to prevention of obesity, reduction of alcohol consumption and increase in physical activity.( 11 ) Evidence-based strategies, including “The Ten Steps” of the Baby-Friendly Hospital Initiative and the International Code of Marketing of Breastmilk Substitutes in Hong Kong, can protect exclusive breastfeeding from unnecessary and uninformed choice of infant formula supplementation. Investing public money to strengthen these strategies will not only bring health benefits to the mothers and babies but also potential monetary return to the government in Hong Kong and therefore should be enthusiastically supported. CONCLUSION Promoting and protecting breastfeeding leads to cost-savings for treating breast cancer in Hong Kong and alleviates suffering for women and their families. Healthcare resources can be directed to breastfeeding promotion as an early lifestyle-related intervention for breast cancer, focusing on promoting exclusive breastfeeding for 6 months as recommended by the World Health Organization. Declarations Funding: This work is funded by the Health and Medical Research Fund, Government of the Hong Kong SAR (#07181226). Author Contribution Hui LL drafted the initial manuscript, conceptualized and designed the study, reviewed and revised the manuscriptLIAO JX, SO C, WU TT, WONG CKH and LOGANATHAN T. critically reviewed manuscript and contributed to the interpretation of data.Liao E. carried out the data analysis. Nelson EAS conceptualized and designed the study, reviewed and revised the manuscript.All authors approved the final manuscript as submitted and agree to be accountable for all aspects of the work. Acknowledgement We are grateful to the hospital admission data provided by the Central Panel on Administrative Assessment of External Data Requests, Hospital Authority & the Finance Department, Prince of Wales Hospital, Hospital Authority. References Chowdhury R, Sinha B, Sankar MJ, Taneja S, Bhandari N, Rollins N, et al. Breastfeeding and maternal health outcomes: a systematic review and meta-analysis. Acta Paediatr. 2015;104(467):96-113. Pokhrel S, Quigley MA, Fox-Rushby J, McCormick F, Williams A, Trueman P, et al. Potential economic impacts from improving breastfeeding rates in the UK. Archives of disease in childhood. 2015;100(4):334-40. Unar-Munguia M, Stern D, Colchero MA, Gonzalez de Cosio T. The burden of suboptimal breastfeeding in Mexico: Maternal health outcomes and costs. Maternal & child nutrition. 2018:e12661. Bartick MC, Schwarz EB, Green BD, Jegier BJ, Reinhold AG, Colaizy TT, et al. Suboptimal breastfeeding in the United States: Maternal and pediatric health outcomes and costs. Maternal & child nutrition. 2017;13(1). Female breast cancer in 2019. : Hong Kong Cancer Registry, Hospital Authority, Hong Kong SAR Government; [Available from: https://www3.ha.org.hk/cancereg/pdf/factsheet/2019/breast_2019.pdf. Leung GM, Ho LM, Lam TH. Breastfeeding rates in Hong Kong: a comparison of the 1987 and 1997 birth cohorts. Birth. 2002;29(3):162-8. Hong Kong Breastfeeding Survey. Breastfeeding Survey 2021: Department of Health, Hong Kong SAR Government. ; 2021 [Available from: https://www.fhs.gov.hk/english/reports/files/BF_survey_2021.pdf. Bartick MC, Stuebe AM, Schwarz EB, Luongo C, Reinhold AG, Foster EM. Cost analysis of maternal disease associated with suboptimal breastfeeding. Obstetrics and gynecology. 2013;122(1):111-9. Leung K, Wu JT, Wong IO, Shu XO, Zheng W, Wen W, et al. Using Risk Stratification to Optimize Mammography Screening in Chinese Women. JNCI Cancer Spectr. 2021;5(4). GBD 2017 Disease and Injury Incidence and Prevalence Collaborators. Global, regional, and national incidence, prevalence, and years lived with disability for 354 diseases and injuries for 195 countries and territories, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017. Lancet. 2018;392(10159):1789-858. Diet, Nutrition, Physical Activity and Breast Cancer. 2017.: World Cancer Research Fund International/American Institute for Cancer Research. ; [Available from: https://www.wcrf.org/wp-content/uploads/2021/02/Breast-cancer-report.pdf. Unar-Munguia M, Torres-Mejia G, Colchero MA, Gonzalez de Cosio T. Breastfeeding Mode and Risk of Breast Cancer: A Dose-Response Meta-Analysis. J Hum Lact. 2017;33(2):422-34. Tables Table 1 Input parameters for economic evaluation of the prevention of breast cancer through the promotion of breast feeding in Hong Kong. Input parameter Point estimate Uncertainty range Distribution Source of data and Remarks Age-specific fertility rates of 20-49-year-old females in 2018 NA NA NA Hong Kong Census and Statistics Department All-cause age-specific mortality rates in 2018 NA NA NA Hong Kong Census and Statistics Department Age-specific female invasive breast cancer incidence rate in 2018 NA NA NA Hong Kong Cancer Registry (Supplementary Table S1) Female invasive breast cancer stage distribution in 2018 I 0.62 - Dirichlet Hong Kong Cancer Registry, Hospital Authority II 0.16 III 0.13 IV 0.09 Aggregated medical treatment costs (per case, $US 2017 level) Stage I $27683 ($20,762-$34,604) Uniform Leung et al., 2021 Stage II $31831 ($23,873-$39,789) Stage III $38374 ($28,781-$47,968) Stage IV $83217 ($62,413-$104,021) Terminal Care $27208 ($20,271-$33,785) 5-year survival probability for female invasive breast cancer Stages 1-4 Stage I 0.993 NA NA Hong Kong Cancer Registry (Supplementary Table S2) Stage II 0.946 Stage III 0.762 Stage IV 0.298 Disability weight Diagnosis and primary therapy phase 0.288 (0.193, 0.399) Triangular Global Burden of Disease study 2017 Controlled phase 0.049 (0.031, 0.072) Metastatic phase 0.451 (0.307, 0.600) *Relative risk of breast cancer by duration of any breastfeeding (for Scenario 1) Never 1 - Triangular Unar-Munguía 2017(12) 1-2 months 0.9 (0.86, 0.93) 3-5 months 0.85 (0.82, 0.89) 6-8 months 0.86 (0.82, 0.91) 9-11 months 0.87 (0.82, 0.91) 12-23 months 0.86 (0.82, 0.9) 24-35 months 0.81 (0.76, 0.85) *Relative risk of breast cancer in flavour of exclusive breastfeeding for 6 months (for Scenario 2) No 1 - Yes 0.72 (0.58, 0.90) Unar-Munguía 2017(12) Duration of any breastfeeding in a woman’s lifetime (base case or scenario 1) At 1 months 76.6% (74.8%, 78.4%) Triangular Biannual breastfeeding survey 2019, Department of Health We interpolated the linearly between 2 to 4 months, 4 to 6 months, and 6 to 12 months. (Supplementary Table S3) At 2 months 66.4% (64.4%, 68.4%) At 4 months 55.7% (53.6%, 57.5%) At 6 months 46.5% (44.4%, 48.6%) At 12 months 26.1% (24.3%, 27.9%) Proportion of 6-month-old infants exclusive breastfed in Hong Kong in 2018 (Base case for scenario 2) 26% (24.50%, 28.10%) Biannual breastfeeding survey 2019, Department of Health Table 2 Cases and deaths of breast cancer averted & lifetime costs (million US$) of breast cancer saved by optimal scenario 1 (90% parous women breastfeed partially or exclusively for 12 months) & optimal scenario 2 (90% parous women breastfeed exclusively for 6 months) for a cohort of 33500 Hong Kong women aged 20 years in 2018 Cases Deaths DALYs Lifetime costs + Base^/Optimal Averted (95% CI) Base^/Optimal Averted (95% CI) Base^/Optimal Averted (95% CI) Base^/Optimal Averted (95% CI) Scenario 1 (90% parous women breastfeed partially or exclusively for 12 months) Stage I 1594/1558 36(33, 39) 85/83 2 (1, 2) 2078/2036 42 (32, 52) 15.49/15.16 0.34 (0.3, 0.37) Stage II 411/403 9(7, 10) 24/24 0 (0, 1) 567/556 11 (6, 16) 4.01/3.93 0.08 (0.07, 1) Stage III 334/325 9(7, 10) 23/22 0 (0, 1) 506/495 10 (5, 16) 3.72/3.63 0.09 (0.08, 0.11) Stage IV 232/227 5(4, 6) 44/42 1 (1, 2) 755/734 21 (14, 28) 6.79/6.65 0.14 (0.10, 0.17) Total 2571/2513 59(54, 62) 176/173 3 (3, 5) 3908/3834 84 (70, 100) 30.02/29.37 0.65 (0.60, 0.70) Scenario 2 ( 90% parous women breastfeed exclusively for 6 months) Stage I 1584/1419 164 (159, 169) 85/76 9 (8, 9) 2077/1865 212 (201, 223) 15.39/13.81 1.58 (1.53, 1.63) Stage II 411/367 44 (42, 46) 24/21 3 (2, 3) 570/508 62 (57, 67) 3.99/3.58 0.43 (0.41, 0.45) Stage III 332/298 35 (33, 36) 23/20 2 (2, 3) 510/455 55 (49, 60) 3.71/3.32 0.38 (0.36, 0.4) Stage IV 229/206 23 (22, 24) 43/39 4 (3, 4) 740/670 70 (62, 77) 6.74/6.07 0.68 (0.64, 0.71) Total 2556/2290 266 (259, 273) 174/158 18 (17, 19) 3897/3498 399 (381, 416) 29.83/26.78 3.07 (2.98, 3.15) ^Base: Actual breastfeeding rate in 2018 was used in baseline. + 2018 prices with 3% discount rate Additional Declarations No competing interests reported. Supplementary Files SUPPLEMENTARYMATERIALS.docx Cite Share Download PDF Status: Published Journal Publication published 24 Feb, 2025 Read the published version in International Breastfeeding Journal → Version 1 posted Editorial decision: Revision requested 14 Sep, 2024 Reviews received at journal 11 Sep, 2024 Reviews received at journal 09 Sep, 2024 Reviewers agreed at journal 12 Aug, 2024 Reviewers agreed at journal 09 Aug, 2024 Reviews received at journal 05 Jun, 2024 Reviewers agreed at journal 04 May, 2024 Reviewers invited by journal 23 Apr, 2024 Submission checks completed at journal 20 Apr, 2024 Editor assigned by journal 20 Apr, 2024 First submitted to journal 17 Apr, 2024 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. 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Also discoverable on Platform About Our Team In Review Editorial Policies 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-4283403","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Short Report","associatedPublications":[],"authors":[{"id":294360508,"identity":"2e1b0e3e-f85d-4525-8e42-951f3de59b41","order_by":0,"name":"Lai Ling HUI","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA6klEQVRIiWNgGAWjYLCCBBBiZj7AwFAA5hswMDYkEKOFLQGkmEgtEF08BsRp4W/vPfbgQQVDnsFxnm8PPhgcTmxgb94mwbgjDacWiTPn0g0SzjAUGxzm3W44A6SF51iZBOOZHJxaDCRyzCQS2xgSNxzm3SbNA9ICEmFsqyCg5R9IC88ziBb5N8RoaQBrYYPawgPSgtthEmfOmEkkHJNInHmYzRzol3TjNp60YovENtze52/vMZP8UWOT2Hf+8LMHHyqsZfvZD2+88bEtGacWmGUggg2Im8EkKJqIAiDFdUSqHQWjYBSMgpEEAOroUN4jwTq8AAAAAElFTkSuQmCC","orcid":"","institution":"The Hong Kong Polytechnic University","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Lai","middleName":"Ling","lastName":"HUI","suffix":""},{"id":294360509,"identity":"f48d6f4e-61e8-4593-b712-8f83d87fa4cf","order_by":1,"name":"Emily LIAO","email":"","orcid":"","institution":"The Hong Kong Polytechnic University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Emily","middleName":"","lastName":"LIAO","suffix":""},{"id":294360510,"identity":"e47e25eb-9b1a-408c-92d6-f788359c51ed","order_by":2,"name":"Jin Xiao LIAO","email":"","orcid":"","institution":"The Hong Kong Polytechnic University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Jin","middleName":"Xiao","lastName":"LIAO","suffix":""},{"id":294360511,"identity":"6aceffbf-88b1-4119-8f7f-dc600c6276da","order_by":3,"name":"Ching SO","email":"","orcid":"","institution":"The Hong Kong Polytechnic University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Ching","middleName":"","lastName":"SO","suffix":""},{"id":294360512,"identity":"63c44e8c-0087-41d2-8b4c-f4d91c93997e","order_by":4,"name":"Ting Ting WU","email":"","orcid":"","institution":"The University of Hong Kong","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Ting","middleName":"Ting","lastName":"WU","suffix":""},{"id":294360513,"identity":"b287070e-b096-4a6f-91e9-ed1cc81dbeab","order_by":5,"name":"Carlos . K.H. WONG","email":"","orcid":"","institution":"The University of Hong Kong","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Carlos","middleName":". K.H.","lastName":"WONG","suffix":""},{"id":294360514,"identity":"08b9fc4f-9511-4896-89ad-917af5ea1314","order_by":6,"name":"Tharani LOGANATHAN","email":"","orcid":"","institution":"The University of Hong Kong","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Tharani","middleName":"","lastName":"LOGANATHAN","suffix":""},{"id":294360515,"identity":"f7aeee2a-9476-47bd-9356-ed387c633646","order_by":7,"name":"Edmund Anthony S. NELSON","email":"","orcid":"","institution":"Chinese University of Hong Kong, Shenzhen","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Edmund","middleName":"Anthony S.","lastName":"NELSON","suffix":""}],"badges":[],"createdAt":"2024-04-17 17:29:10","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4283403/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4283403/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s13006-024-00689-y","type":"published","date":"2025-02-24T15:57:55+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":55523291,"identity":"63d36af8-8016-4a6c-9693-7774d4100cd6","added_by":"auto","created_at":"2024-04-29 14:30:25","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":117599,"visible":true,"origin":"","legend":"\u003cp\u003eDiagram of simulation model\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-4283403/v1/9ae0f8ac6a5b6640d2b42e78.png"},{"id":55523290,"identity":"101b8eec-05e7-4502-8fc3-fe32d84df130","added_by":"auto","created_at":"2024-04-29 14:30:25","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":72498,"visible":true,"origin":"","legend":"\u003cp\u003eTornado diagram for deterministic sensitivity analyses of cost-savings (million US$) in optimal scenario 1 (90% parous women breastfeed partially or exclusively for 12 months) \u0026amp; optimal scenario 2 (90% parous women breastfeed exclusively for 6 months), 2018 prices with 3% discount rate.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-4283403/v1/bea31d65f464eebd56e5894c.png"},{"id":77622504,"identity":"b5bb04a2-39e9-4f39-9520-0d3043fd985f","added_by":"auto","created_at":"2025-03-03 16:07:38","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1145728,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4283403/v1/4648805c-17ae-4d85-8cb0-615da5645fc9.pdf"},{"id":55523289,"identity":"464de41b-61bf-4f0b-9349-5357fc97a7e6","added_by":"auto","created_at":"2024-04-29 14:30:25","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":27291,"visible":true,"origin":"","legend":"","description":"","filename":"SUPPLEMENTARYMATERIALS.docx","url":"https://assets-eu.researchsquare.com/files/rs-4283403/v1/32b9e4008d1fe8c51496d1a5.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eBreastfeeding Promotion to Prevent Breast Cancer: an Economic Evaluation\u003c/p\u003e","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eIn addition to its many benefits for infants, breastfeeding protects mothers against breast cancer.(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) Given that breastfeeding, and particularly exclusive breastfeeding, is still not the norm in many places, including Hong Kong, promotion of breastfeeding could reduce future breast cancer incidence and its related healthcare costs.\u003c/p\u003e \u003cp\u003eTreatment cost of breast cancer that could be saved by increased breastfeeding rate has been estimated in different settings. In the UK, it was estimated that \u0026pound;21\u0026nbsp;million (2009\u0026ndash;2010 value), over the lifetime of a cohort of first-time mothers in 2009, could be saved as a result a reduced treatment costs for maternal breast cancer. (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) In Mexico, US\u003cspan\u003e$\u003c/span\u003e71.27\u0026nbsp;million (2012 value) direct healthcare treatment costs for breast cancer could be avoided for a cohort of 1.116\u0026nbsp;million Mexican women aged 15 years in 2012. (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) A US study reported total medical costs of \u003cspan\u003e$\u003c/span\u003e118\u0026nbsp;million (2014 value) for treating breast cancer could be saved for the cohort of US women aged 15 years in 2002 over their lifetime. (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e) These results are highly setting specific due to differences in epidemiology of breast cancer and financing of healthcare.\u003c/p\u003e \u003cp\u003eIn the past 3 decades, Hong Kong has experienced a 3-fold increase in breast cancer incidence which imposes a huge burden on not only families but also the governmental healthcare system because the majority of breast cancers are treated in the heavily subsidised public system. The breast cancer incidence per 100,000 females increased from 39.4 in 1990 to 116.6 in 2019, constituting 27% of all new cancers in women.(\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e) Meanwhile the breastfeeding rate has been suboptimal in Hong Kong, despite an improvement in recent decades compared to the 1980s when only respectively 7.6% and 3.9% infants were breastfed at 1 and 3 months.(\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e) The exclusive breastfeeding rate was 32% at 1 month and 26% at 6 months in 2018, with a any breastfeeding rate of 46.5% at 6 months.(\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e) Although trends in breastfeeding rates and breast cancer incidence are likely driven by a range of factors, suboptimal breastfeeding rates and high breast cancer incidence in Hong Kong offers opportunities to optimise resource allocation decisions to maximize population health among women and children by promoting breastfeeding.\u003c/p\u003e \u003cp\u003eThis study assesses healthcare costs for breast cancer treatment that could be saved by an increase in the breastfeeding rate. These data can inform decisions on the efficient utilization of healthcare resources in Hong Kong because the majority of the cancers are treated in public system.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cp\u003e\u003cstrong\u003ePerspective\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe aimed to estimate costs for breast cancer treatment due to suboptimal breastfeeding from a provider perspective. We did not consider individual costs and societal costs, such as loss of productivity due to absence from work. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eThe Model\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA individual based Monte Carlo model (Figure 1) adopted from previous studies (4, 8) was constructed to simulate the development of breast cancer over a woman\u0026rsquo;s lifetime in a birth cohort aged 20 years in 2018 (n=33500), with which we compared the cases and deaths of breast cancer in the base case (breastfeeding rate in 2018) and two hypothetical optimal scenarios (1: 90% parous women exclusively/partially breastfeed at least 12 months or 2: 90% parous women exclusively breastfed for 6 months). \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn each scenario, the proportion of parous women in each year was simulated according to 20 to 49 year-old age-specific fertility rates in Hong Kong in 2018. The maximum parity was set at two because average fertility rate was as low as 1.1-1.3 during 2010-2019. For each simulated woman, the risk of developing breast cancer in each year from age 20 to 80 years was simulated based on her age, cumulative lifetime breastfeeding history and age-specific incidence rates of breast cancer in 2018. The case-fatality was simulated based on the age, stage at diagnosis and ten-year survival rates extrapolated from the stage-specific relative 1-to-5-year survival rates from the Hong Kong Cancer Registry, but not their breastfeeding history. The mortality of women without breast cancer was simulated using the age-specific death rates among females in Hong Kong. We assumed steady-state rates of disease incidence, disease survival, fertility, and the cost of treatment. We did not consider transitions between stages as early diagnosed breast cancers are mainly treated and we set out to provide an conservative estimates. Deaths for women surviving beyond 10 years from diagnosis were considered unrelated to breast cancer. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCost and DALYs estimation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe calculated the treatment cost and DALYs associated with breast cancer in each scenario of breastfeeding rate using stage-specific aggregated one-time treatment costs reported in a local study (9) and DALYs information from the Global Burden of Disease Study (10), at an annual discount rate of 3%. Costs were converted to US dollars based on the exchange rate in 2018 (1 USD=7.8 HKD). The terminal care cost would be applied when the death due to breast cancer occurred in the simulation. We assumed all the diagnosed breast cancer cases would receive treatment. We also assumed treatment cost in public sector, which is heavily subsidised by the government is the same as private hospitals, where more expensive treatment options are maybe available.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFor DALYs calculation, the number of years lived with disability (YLD) and the number of years of life lost (YLL) were deduced with the formula in the DALY calculator for R. The information to calculate YLL and YLD, including age of onset and duration of disease, were derived from the simulation of the disease outcome for each woman. Survivors beyond ten years were considered cured.(10) Two sequelae (diagnosis and primary therapy, and controlled phase) were assumed for cases that were cured, and four sequelae (diagnosis and primary therapy; controlled phase; metastatic phase; terminal phase) were assumed for those did not survive beyond ten years. Age-weighting was not applied.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSensitivity analysis and validation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe simulated outcomes were based on 500 iterations each with parameters including relative risks, age-specific incidence of breast cancer, aggregated treatment costs, and disability weights randomly generated from specified distributions. (Table 1) The results from probabilistic sensitivity analysis was validated by comparing deduced incidence rates from the model for the base case with the actual rates. We also carried out deterministic sensitivity analysis to assess the main cost drivers (by changing one parameter at a time) and the most/least cost-saving simulations (by changing parameters at the same time to achieve most/least cost-saving scenario). \u003c/p\u003e\n\u003cp\u003eParameters for the simulation were identified from literature and government statistics. (Table 1) Programming\u0026nbsp;was performed using Python and R statistical software version 4.1.0 (Vienna, Austria; R Core Team, 2021)\u003cstrong\u003e.\u003c/strong\u003e\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cp\u003eIn the cohort of 33500 women aged 20 years in 2018, our model simulated 2550\u0026ndash;2570 cases of breast cancer developed in their lifetime. The simulated stage-specific incidence rates in base case were congruent with the actual age-specific incidence rates from Hong Kong cancer registry.(Supplementary Table S4) Increasing the proportion of parous women with a cumulative breastfeeding duration of at least 12 months from current levels to 90%, i.e. optimal scenario 1, averted 59 (95% CI 54, 62) cases of breast cancer, from which 3 (95% CI 3,5) premature deaths and 84 DALYs (95% CI 70, 100) could be prevented. In optimal scenario 2 when 90% of parous women breastfeed exclusively for 6 months, 266 (95% CI 259,273) or about 10% of all-stage breast cancer cases, 18 death (95% CI 17,19) and 399 DALYs (95% CI 381, 416) could be averted. (Table\u0026nbsp;2)\u003c/p\u003e \u003cp\u003eUsing 2018 prices with 3% discount rate, the total lifetime medical treatment costs for breast cancer that could be saved in the lifetime of the women in the simulated cohort would be about US\u003cspan\u003e$\u003c/span\u003e 0.65 (95% CI 0.60, 0.70) million when 90% parous women have cumulative breastfeeding for 12 months. The saving was estimated to be US\u003cspan\u003e$\u003c/span\u003e3.07 (2.98, 3.15) million when 90% parous women exclusively breastfeed for 6 months. (Table\u0026nbsp;2)\u003c/p\u003e \u003cp\u003eThe deterministic sensitivity analyses suggest the cost-savings would be made should the optimal breastfeeding rates for both scenarios be achieved for all individual scenarios and marginally for the worst-case scenario (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Discount rates have the largest impact on the estimated cost-savings over a lifetime. The relative risk of breast cancer in favour of breastfeeding was more important when exclusive breastfeeding was considered (optimal scenario 2) compared to any breastfeeding rate (optimal scenario 1), due to the wider confidence intervals of the relative risk.\u003c/p\u003e \u003cp\u003eWe compared the economic evaluations with optimal scenario 1 with similar economic evaluations in the UK, the US, and Mexico assuming a change in the duration of cumulative breastfeeding duration in the optimal scenario (Supplementary Table S5). Cases averted per 100,000 women were 392 for Mexico (when 95% of parous women breastfeed for 24 months), 252 for the US (when 90% of mothers breastfeed each infant exclusively for 6 months, with continuing breastfeeding through 12 months postpartum) and 176 for Hong Kong (when 90% of parous women breastfeed for 12 months).\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eOur findings suggested that increasing the exclusive breastfeeding rate at 6 months from the current rate (about 22%) to 90% in Hong Kong could avert 266 cases of breast cancer and save US\u003cspan\u003e$\u003c/span\u003e3\u0026nbsp;million (2018 price) attributed to the prevention of breast cancer over the lifetime of each annual cohort of 33500 women. There would also be 16 premature deaths prevented and 399 DALYs averted. The benefits of having 90% parous women with cumulative any breastfeeding duration of 12 months were about 5 times less. Prioritising the exclusivity in breastfeeding promotion could avert more cases of breast cancer and lead to more governmental healthcare cost-saving in Hong Kong where majority of breast cancer are treated in public settings and heavily subsidised.\u003c/p\u003e \u003cp\u003eWe carefully considered uncertainties of inputs, including protection of breastfeeding against breast cancer, disability weight, breastfeeding rate, treatment cost per case and breast cancer stage distribution using probabilistic sensitivity analyses in the present economic evaluations. However there are some caveats in the model that require considerations. First we assumed age-specific incidences of breast cancer to be static despite breast cancer incidence has been on a rising trend. Second we assumed there was no disease progression from earlier stages to metastasis the case-fatalities were higher for stages III and IV cancers. Thirdly we assumed treatment cost in the public sector is the same as private hospitals, although some treatment in private settings may be more expensive than public hospitals. These assumptions made our economic evaluation more conservative which may underestimate the cost-saving. The actual cost-saving is likely to be higher.\u003c/p\u003e \u003cp\u003eSimilar economic evaluations in both high-income settings (the UK (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) and the US(\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e)) and a lower income setting (Mexico (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e)) reported that an increase in proportion of women practicing any breastfeeding is cost-saving for breast cancer treatment. The cases averted and the cost saved in each setting being dependent on the epidemiology of breast cancer (such as age-specific disease incidence and survival rate), detection rate of early breast cancer, fertility rate, breastfeeding status and assumed protection of breastfeeding. The fewer breast cancer cases averted per 100,000 women in Hong Kong than those in the US and Mexico (Supplementary Table S4) may be partly attributed to the much lower fertility rate, the early detection rate and the high survival rate of early breast cancer in Hong Kong.\u003c/p\u003e \u003cp\u003eOur findings suggested that exclusive breastfeeding for 6 months could lead to substantial cost-savings for treating breast cancer in Hong Kong and alleviate suffering for women and their families. Promoting breastfeeding, especially exclusive breastfeeding, is an early lifestyle-related intervention for preventing breast cancer, in addition to prevention of obesity, reduction of alcohol consumption and increase in physical activity.(\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e) Evidence-based strategies, including \u0026ldquo;The Ten Steps\u0026rdquo; of the Baby-Friendly Hospital Initiative and the International Code of Marketing of Breastmilk Substitutes in Hong Kong, can protect exclusive breastfeeding from unnecessary and uninformed choice of infant formula supplementation. Investing public money to strengthen these strategies will not only bring health benefits to the mothers and babies but also potential monetary return to the government in Hong Kong and therefore should be enthusiastically supported.\u003c/p\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003ePromoting and protecting breastfeeding leads to cost-savings for treating breast cancer in Hong Kong and alleviates suffering for women and their families. Healthcare resources can be directed to breastfeeding promotion as an early lifestyle-related intervention for breast cancer, focusing on promoting exclusive breastfeeding for 6 months as recommended by the World Health Organization.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eFunding:\u003c/h2\u003e \u003cp\u003eThis work is funded by the Health and Medical Research Fund, Government of the Hong Kong SAR (#07181226).\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eHui LL drafted the initial manuscript, conceptualized and designed the study, reviewed and revised the manuscriptLIAO JX, SO C, WU TT, WONG CKH and LOGANATHAN T. critically reviewed manuscript and contributed to the interpretation of data.Liao E. carried out the data analysis. Nelson EAS conceptualized and designed the study, reviewed and revised the manuscript.All authors approved the final manuscript as submitted and agree to be accountable for all aspects of the work.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eWe are grateful to the hospital admission data provided by the Central Panel on Administrative Assessment of External Data Requests, Hospital Authority \u0026amp; the Finance Department, Prince of Wales Hospital, Hospital Authority.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eChowdhury R, Sinha B, Sankar MJ, Taneja S, Bhandari N, Rollins N, et al. Breastfeeding and maternal health outcomes: a systematic review and meta-analysis. Acta Paediatr. 2015;104(467):96-113.\u003c/li\u003e\n\u003cli\u003ePokhrel S, Quigley MA, Fox-Rushby J, McCormick F, Williams A, Trueman P, et al. Potential economic impacts from improving breastfeeding rates in the UK. Archives of disease in childhood. 2015;100(4):334-40.\u003c/li\u003e\n\u003cli\u003eUnar-Munguia M, Stern D, Colchero MA, Gonzalez de Cosio T. The burden of suboptimal breastfeeding in Mexico: Maternal health outcomes and costs. Maternal \u0026amp; child nutrition. 2018:e12661.\u003c/li\u003e\n\u003cli\u003eBartick MC, Schwarz EB, Green BD, Jegier BJ, Reinhold AG, Colaizy TT, et al. Suboptimal breastfeeding in the United States: Maternal and pediatric health outcomes and costs. Maternal \u0026amp; child nutrition. 2017;13(1).\u003c/li\u003e\n\u003cli\u003eFemale breast cancer in 2019. : Hong Kong Cancer Registry, Hospital Authority, Hong Kong SAR Government; [Available from: https://www3.ha.org.hk/cancereg/pdf/factsheet/2019/breast_2019.pdf.\u003c/li\u003e\n\u003cli\u003eLeung GM, Ho LM, Lam TH. Breastfeeding rates in Hong Kong: a comparison of the 1987 and 1997 birth cohorts. Birth. 2002;29(3):162-8.\u003c/li\u003e\n\u003cli\u003eHong Kong Breastfeeding Survey. Breastfeeding Survey 2021: Department of Health, Hong Kong SAR Government. ; 2021 [Available from: https://www.fhs.gov.hk/english/reports/files/BF_survey_2021.pdf.\u003c/li\u003e\n\u003cli\u003eBartick MC, Stuebe AM, Schwarz EB, Luongo C, Reinhold AG, Foster EM. Cost analysis of maternal disease associated with suboptimal breastfeeding. Obstetrics and gynecology. 2013;122(1):111-9.\u003c/li\u003e\n\u003cli\u003eLeung K, Wu JT, Wong IO, Shu XO, Zheng W, Wen W, et al. Using Risk Stratification to Optimize Mammography Screening in Chinese Women. JNCI Cancer Spectr. 2021;5(4).\u003c/li\u003e\n\u003cli\u003eGBD 2017 Disease and Injury Incidence and Prevalence Collaborators. Global, regional, and national incidence, prevalence, and years lived with disability for 354 diseases and injuries for 195 countries and territories, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017. Lancet. 2018;392(10159):1789-858.\u003c/li\u003e\n\u003cli\u003eDiet, Nutrition, Physical Activity and Breast Cancer. 2017.: World Cancer Research Fund International/American Institute for Cancer Research. ; [Available from: https://www.wcrf.org/wp-content/uploads/2021/02/Breast-cancer-report.pdf.\u003c/li\u003e\n\u003cli\u003eUnar-Munguia M, Torres-Mejia G, Colchero MA, Gonzalez de Cosio T. Breastfeeding Mode and Risk of Breast Cancer: A Dose-Response Meta-Analysis. J Hum Lact. 2017;33(2):422-34.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTable 1 Input parameters\u0026nbsp;for economic evaluation of the prevention of breast cancer through the promotion of breast feeding in Hong Kong.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"674\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.22222222222222%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eInput parameter\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.444444444444445%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003ePoint estimate\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.40740740740741%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eUncertainty range\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.74074074074074%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eDistribution\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.037037037037038%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eSource of data and Remarks\u0026nbsp; \u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0.14814814814814814%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.22222222222222%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge-specific fertility rates of 20-49-year-old females in 2018\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.444444444444445%\" valign=\"top\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.40740740740741%\" valign=\"top\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.74074074074074%\" valign=\"top\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.037037037037038%\" valign=\"top\"\u003e\n \u003cp\u003eHong Kong Census and Statistics Department\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0.14814814814814814%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.22222222222222%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAll-cause age-specific mortality rates in 2018\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.444444444444445%\" valign=\"top\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.40740740740741%\" valign=\"top\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.74074074074074%\" valign=\"top\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.037037037037038%\" valign=\"top\"\u003e\n \u003cp\u003eHong Kong Census and Statistics Department\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0.14814814814814814%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.22222222222222%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge-specific female invasive breast cancer incidence rate in 2018\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.444444444444445%\" valign=\"top\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.40740740740741%\" valign=\"top\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.74074074074074%\" valign=\"top\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.037037037037038%\" valign=\"top\"\u003e\n \u003cp\u003eHong Kong Cancer Registry\u003c/p\u003e\n \u003cp\u003e(Supplementary Table S1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0.14814814814814814%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"6\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eFemale invasive breast cancer stage distribution in 2018\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.22222222222222%\" valign=\"top\"\u003e\n \u003cp\u003eI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.444444444444445%\" valign=\"top\"\u003e\n \u003cp\u003e0.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.40740740740741%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.74074074074074%\" valign=\"top\"\u003e\n \u003cp\u003eDirichlet\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.037037037037038%\" rowspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003eHong Kong Cancer Registry, Hospital Authority\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0.14814814814814814%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"43.33958724202627%\" valign=\"top\"\u003e\n \u003cp\u003eII\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.694183864915573%\" valign=\"top\"\u003e\n \u003cp\u003e0.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.577861163227016%\" rowspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.20075046904315%\" rowspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0.18761726078799248%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"79.93079584775087%\" valign=\"top\"\u003e\n \u003cp\u003eIII\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.72318339100346%\" valign=\"top\"\u003e\n \u003cp\u003e0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0.3460207612456747%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"79.93079584775087%\" valign=\"top\"\u003e\n \u003cp\u003eIV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.72318339100346%\" valign=\"top\"\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0.3460207612456747%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"6\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAggregated medical treatment costs (per case, $US 2017 level)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.22222222222222%\" valign=\"top\"\u003e\n \u003cp\u003eStage I\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.444444444444445%\" valign=\"top\"\u003e\n \u003cp\u003e$27683\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.40740740740741%\" valign=\"top\"\u003e\n \u003cp\u003e($20,762-$34,604)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.74074074074074%\" valign=\"top\"\u003e\n \u003cp\u003eUniform\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.037037037037038%\" valign=\"top\"\u003e\n \u003cp\u003eLeung et al., 2021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0.14814814814814814%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.22222222222222%\" valign=\"top\"\u003e\n \u003cp\u003eStage II\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.444444444444445%\" valign=\"top\"\u003e\n \u003cp\u003e$31831\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.40740740740741%\" valign=\"top\"\u003e\n \u003cp\u003e($23,873-$39,789)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.74074074074074%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.037037037037038%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0.14814814814814814%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.22222222222222%\" valign=\"top\"\u003e\n \u003cp\u003eStage III\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.444444444444445%\" valign=\"top\"\u003e\n \u003cp\u003e$38374\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.40740740740741%\" valign=\"top\"\u003e\n \u003cp\u003e($28,781-$47,968)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.74074074074074%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.037037037037038%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0.14814814814814814%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.22222222222222%\" valign=\"top\"\u003e\n \u003cp\u003eStage IV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.444444444444445%\" valign=\"top\"\u003e\n \u003cp\u003e$83217\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.40740740740741%\" valign=\"top\"\u003e\n \u003cp\u003e($62,413-$104,021)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.74074074074074%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.037037037037038%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0.14814814814814814%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.22222222222222%\" valign=\"top\"\u003e\n \u003cp\u003eTerminal Care\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.444444444444445%\" valign=\"top\"\u003e\n \u003cp\u003e$27208\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.40740740740741%\" valign=\"top\"\u003e\n \u003cp\u003e($20,271-$33,785)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.74074074074074%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.037037037037038%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0.14814814814814814%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"6\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e5-year survival probability for female invasive breast cancer Stages 1-4\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.22222222222222%\" valign=\"top\"\u003e\n \u003cp\u003eStage I\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.444444444444445%\" valign=\"top\"\u003e\n \u003cp\u003e0.993\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.40740740740741%\" valign=\"top\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.74074074074074%\" valign=\"top\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.037037037037038%\" rowspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003eHong Kong Cancer Registry\u003c/p\u003e\n \u003cp\u003e(Supplementary Table S2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0.14814814814814814%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"43.33958724202627%\" valign=\"top\"\u003e\n \u003cp\u003eStage II\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.694183864915573%\" valign=\"top\"\u003e\n \u003cp\u003e0.946\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.577861163227016%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.20075046904315%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0.18761726078799248%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"43.33958724202627%\" valign=\"top\"\u003e\n \u003cp\u003eStage III\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.694183864915573%\" valign=\"top\"\u003e\n \u003cp\u003e0.762\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.577861163227016%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.20075046904315%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0.18761726078799248%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"43.33958724202627%\" valign=\"top\"\u003e\n \u003cp\u003eStage IV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.694183864915573%\" valign=\"top\"\u003e\n \u003cp\u003e0.298\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.577861163227016%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.20075046904315%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0.18761726078799248%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.22222222222222%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDisability weight\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.444444444444445%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.40740740740741%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.74074074074074%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.037037037037038%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0.14814814814814814%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.22222222222222%\" valign=\"top\"\u003e\n \u003cp\u003eDiagnosis and primary therapy phase\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.444444444444445%\" valign=\"top\"\u003e\n \u003cp\u003e0.288\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.40740740740741%\" valign=\"top\"\u003e\n \u003cp\u003e(0.193, 0.399)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.74074074074074%\" rowspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003eTriangular\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.037037037037038%\" rowspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003eGlobal Burden of Disease study 2017\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0.14814814814814814%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"55%\" valign=\"top\"\u003e\n \u003cp\u003eControlled phase\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.571428571428571%\" valign=\"top\"\u003e\n \u003cp\u003e0.049\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"31.19047619047619%\" valign=\"top\"\u003e\n \u003cp\u003e(0.031, 0.072)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0.23809523809523808%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"55%\" valign=\"top\"\u003e\n \u003cp\u003eMetastatic phase\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.571428571428571%\" valign=\"top\"\u003e\n \u003cp\u003e0.451\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"31.19047619047619%\" valign=\"top\"\u003e\n \u003cp\u003e(0.307, 0.600)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0.23809523809523808%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"6\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e*Relative risk of breast cancer by duration of any breastfeeding (for Scenario 1)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.22222222222222%\" valign=\"top\"\u003e\n \u003cp\u003eNever\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.444444444444445%\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.40740740740741%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.74074074074074%\" rowspan=\"7\" valign=\"top\"\u003e\n \u003cp\u003eTriangular\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.037037037037038%\" rowspan=\"7\" valign=\"top\"\u003e\n \u003cp\u003eUnar-Mungu\u0026iacute;a 2017(12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0.14814814814814814%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"55%\" valign=\"top\"\u003e\n \u003cp\u003e1-2 months\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.571428571428571%\" valign=\"top\"\u003e\n \u003cp\u003e0.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"31.19047619047619%\" valign=\"top\"\u003e\n \u003cp\u003e(0.86, 0.93)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0.23809523809523808%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"55%\" valign=\"top\"\u003e\n \u003cp\u003e3-5 months\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.571428571428571%\" valign=\"top\"\u003e\n \u003cp\u003e0.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"31.19047619047619%\" valign=\"top\"\u003e\n \u003cp\u003e(0.82, 0.89)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0.23809523809523808%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"55%\" valign=\"top\"\u003e\n \u003cp\u003e6-8 months\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.571428571428571%\" valign=\"top\"\u003e\n \u003cp\u003e0.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"31.19047619047619%\" valign=\"top\"\u003e\n \u003cp\u003e(0.82, 0.91)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0.23809523809523808%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"55%\" valign=\"top\"\u003e\n \u003cp\u003e9-11 months\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.571428571428571%\" valign=\"top\"\u003e\n \u003cp\u003e0.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"31.19047619047619%\" valign=\"top\"\u003e\n \u003cp\u003e(0.82, 0.91)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0.23809523809523808%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"55%\" valign=\"top\"\u003e\n \u003cp\u003e12-23 months\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.571428571428571%\" valign=\"top\"\u003e\n \u003cp\u003e0.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"31.19047619047619%\" valign=\"top\"\u003e\n \u003cp\u003e(0.82, 0.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0.23809523809523808%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"55%\" valign=\"top\"\u003e\n \u003cp\u003e24-35 months\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.571428571428571%\" valign=\"top\"\u003e\n \u003cp\u003e0.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"31.19047619047619%\" valign=\"top\"\u003e\n \u003cp\u003e(0.76, 0.85)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0.23809523809523808%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"6\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e*Relative risk of breast cancer in flavour of exclusive breastfeeding for 6 months (for Scenario 2)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.22222222222222%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.444444444444445%\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.40740740740741%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.74074074074074%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.037037037037038%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0.14814814814814814%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.22222222222222%\" valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.444444444444445%\" valign=\"top\"\u003e\n \u003cp\u003e0.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.40740740740741%\" valign=\"top\"\u003e\n \u003cp\u003e(0.58, 0.90)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.74074074074074%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.037037037037038%\" valign=\"top\"\u003e\n \u003cp\u003eUnar-Mungu\u0026iacute;a 2017(12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0.14814814814814814%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"6\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDuration of any breastfeeding in a woman\u0026rsquo;s lifetime (base case or scenario 1)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.22222222222222%\" valign=\"top\"\u003e\n \u003cp\u003eAt 1 months\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.444444444444445%\" valign=\"top\"\u003e\n \u003cp\u003e76.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.40740740740741%\" valign=\"top\"\u003e\n \u003cp\u003e(74.8%, 78.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.74074074074074%\" valign=\"top\"\u003e\n \u003cp\u003eTriangular\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.037037037037038%\" rowspan=\"6\" valign=\"top\"\u003e\n \u003cp\u003eBiannual breastfeeding survey 2019, Department of Health\u003c/p\u003e\n \u003cp\u003eWe interpolated the linearly between 2 to 4 months, 4 to 6 months, and 6 to 12 months.\u003c/p\u003e\n \u003cp\u003e(Supplementary Table S3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0.14814814814814814%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"43.33958724202627%\" valign=\"top\"\u003e\n \u003cp\u003eAt 2 months\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.694183864915573%\" valign=\"top\"\u003e\n \u003cp\u003e66.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.577861163227016%\" valign=\"top\"\u003e\n \u003cp\u003e(64.4%, 68.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.20075046904315%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0.18761726078799248%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"43.33958724202627%\" valign=\"top\"\u003e\n \u003cp\u003eAt 4 months\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.694183864915573%\" valign=\"top\"\u003e\n \u003cp\u003e55.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.577861163227016%\" valign=\"top\"\u003e\n \u003cp\u003e(53.6%, 57.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.20075046904315%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0.18761726078799248%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"43.33958724202627%\" valign=\"top\"\u003e\n \u003cp\u003eAt 6 months\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.694183864915573%\" valign=\"top\"\u003e\n \u003cp\u003e46.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.577861163227016%\" valign=\"top\"\u003e\n \u003cp\u003e(44.4%, 48.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.20075046904315%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0.18761726078799248%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"43.33958724202627%\" valign=\"top\"\u003e\n \u003cp\u003eAt 12 months\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.694183864915573%\" valign=\"top\"\u003e\n \u003cp\u003e26.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.577861163227016%\" valign=\"top\"\u003e\n \u003cp\u003e(24.3%, 27.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.20075046904315%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0.18761726078799248%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"43.33958724202627%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.694183864915573%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.577861163227016%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.20075046904315%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0.18761726078799248%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.22222222222222%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eProportion of 6-month-old infants exclusive breastfed in Hong Kong in 2018\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(Base case for scenario 2)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.444444444444445%\" valign=\"top\"\u003e\n \u003cp\u003e26%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.40740740740741%\" valign=\"top\"\u003e\n \u003cp\u003e(24.50%, 28.10%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.74074074074074%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.037037037037038%\" valign=\"top\"\u003e\n \u003cp\u003eBiannual breastfeeding survey 2019, Department of Health\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0.14814814814814814%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" valign=\"top\"\u003e\n \u003cp\u003eTable 2 Cases and deaths of breast cancer averted \u0026amp; lifetime costs (million US$) of breast cancer saved by\u0026nbsp;optimal scenario\u0026nbsp;1 (90% parous women breastfeed partially or exclusively for 12 months) \u0026amp; optimal scenario 2 (90% parous women breastfeed exclusively for 6 months) for a cohort of 33500 Hong Kong women aged 20 years in 2018\u003c/p\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"897\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.35412026726058%\" valign=\"bottom\" style=\"width: 2.8215%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.465478841870825%\" valign=\"bottom\" style=\"width: 6.9205%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cu\u003eCases\u003c/u\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.688195991091314%\" valign=\"bottom\" style=\"width: 3.8329%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.465478841870825%\" valign=\"bottom\" style=\"width: 6.9205%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cu\u003eDeaths\u003c/u\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.35412026726058%\" valign=\"bottom\" style=\"width: 4.0991%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.465478841870825%\" valign=\"bottom\" style=\"width: 6.9205%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cu\u003eDALYs\u003c/u\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.024498886414253%\" valign=\"bottom\" style=\"width: 4.1523%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.164810690423163%\" colspan=\"2\" valign=\"top\" style=\"width: 11.1261%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLifetime costs\u003csup\u003e+\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.0044543429844097%\" style=\"width: 0.4791%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.35412026726058%\" valign=\"bottom\" style=\"width: 2.8215%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.465478841870825%\" valign=\"bottom\" style=\"width: 6.9205%;\"\u003e\n \u003cp\u003eBase^/Optimal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.688195991091314%\" valign=\"bottom\" style=\"width: 3.8329%;\"\u003e\n \u003cp\u003eAverted (95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.465478841870825%\" valign=\"bottom\" style=\"width: 6.9205%;\"\u003e\n \u003cp\u003eBase^/Optimal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.35412026726058%\" valign=\"bottom\" style=\"width: 4.0991%;\"\u003e\n \u003cp\u003eAverted\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.465478841870825%\" valign=\"bottom\" style=\"width: 6.9205%;\"\u003e\n \u003cp\u003eBase^/Optimal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.024498886414253%\" valign=\"bottom\" style=\"width: 4.1523%;\"\u003e\n \u003cp\u003eAverted\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.024498886414253%\" valign=\"bottom\" style=\"width: 6.9205%;\"\u003e\n \u003cp\u003eBase^/Optimal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.140311804008908%\" valign=\"bottom\" style=\"width: 4.2056%;\"\u003e\n \u003cp\u003eAverted\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.0044543429844097%\" style=\"width: 0.4791%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"97.9933110367893%\" colspan=\"9\" valign=\"bottom\" style=\"width: 47.2194%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eScenario 1\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e(90% parous women breastfeed partially or exclusively for 12 months)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.0066889632107023%\" style=\"width: 0.4791%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.343715239154616%\" valign=\"bottom\" style=\"width: 2.8215%;\"\u003e\n \u003cp\u003eStage I\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.454949944382648%\" valign=\"bottom\" style=\"width: 6.9205%;\"\u003e\n \u003cp\u003e1594/1558\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.67741935483871%\" valign=\"bottom\" style=\"width: 3.8329%;\"\u003e\n \u003cp\u003e36(33, 39)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.454949944382648%\" valign=\"bottom\" style=\"width: 6.9205%;\"\u003e\n \u003cp\u003e85/83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.343715239154616%\" valign=\"bottom\" style=\"width: 4.0991%;\"\u003e\n \u003cp\u003e2 (1, 2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.454949944382648%\" valign=\"bottom\" style=\"width: 6.9205%;\"\u003e\n \u003cp\u003e2078/2036\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.012235817575084%\" valign=\"bottom\" style=\"width: 4.1523%;\"\u003e\n \u003cp\u003e42 (32, 52)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.012235817575084%\" valign=\"bottom\" style=\"width: 6.9205%;\"\u003e\n \u003cp\u003e15.49/15.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.239154616240267%\" colspan=\"2\" valign=\"bottom\" style=\"width: 4.6847%;\"\u003e\n \u003cp\u003e0.34 (0.3, 0.37)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.343715239154616%\" valign=\"bottom\" style=\"width: 2.8215%;\"\u003e\n \u003cp\u003eStage II\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.454949944382648%\" valign=\"bottom\" style=\"width: 6.9205%;\"\u003e\n \u003cp\u003e411/403\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.67741935483871%\" valign=\"bottom\" style=\"width: 3.8329%;\"\u003e\n \u003cp\u003e9(7, 10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.454949944382648%\" valign=\"bottom\" style=\"width: 6.9205%;\"\u003e\n \u003cp\u003e24/24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.343715239154616%\" valign=\"bottom\" style=\"width: 4.0991%;\"\u003e\n \u003cp\u003e0 (0, 1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.454949944382648%\" valign=\"bottom\" style=\"width: 6.9205%;\"\u003e\n \u003cp\u003e567/556\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.012235817575084%\" valign=\"bottom\" style=\"width: 4.1523%;\"\u003e\n \u003cp\u003e11 (6, 16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.012235817575084%\" valign=\"bottom\" style=\"width: 6.9205%;\"\u003e\n \u003cp\u003e4.01/3.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.239154616240267%\" colspan=\"2\" valign=\"bottom\" style=\"width: 4.6847%;\"\u003e\n \u003cp\u003e0.08 (0.07, 1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.343715239154616%\" valign=\"bottom\" style=\"width: 2.8215%;\"\u003e\n \u003cp\u003eStage III\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.454949944382648%\" valign=\"bottom\" style=\"width: 6.9205%;\"\u003e\n \u003cp\u003e334/325\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.67741935483871%\" valign=\"bottom\" style=\"width: 3.8329%;\"\u003e\n \u003cp\u003e9(7, 10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.454949944382648%\" valign=\"bottom\" style=\"width: 6.9205%;\"\u003e\n \u003cp\u003e23/22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.343715239154616%\" valign=\"bottom\" style=\"width: 4.0991%;\"\u003e\n \u003cp\u003e0 (0, 1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.454949944382648%\" valign=\"bottom\" style=\"width: 6.9205%;\"\u003e\n \u003cp\u003e506/495\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.012235817575084%\" valign=\"bottom\" style=\"width: 4.1523%;\"\u003e\n \u003cp\u003e10 (5, 16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.012235817575084%\" valign=\"bottom\" style=\"width: 6.9205%;\"\u003e\n \u003cp\u003e3.72/3.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.239154616240267%\" colspan=\"2\" valign=\"bottom\" style=\"width: 4.6847%;\"\u003e\n \u003cp\u003e0.09 (0.08, 0.11)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.343715239154616%\" valign=\"bottom\" style=\"width: 2.8215%;\"\u003e\n \u003cp\u003eStage IV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.454949944382648%\" valign=\"bottom\" style=\"width: 6.9205%;\"\u003e\n \u003cp\u003e232/227\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.67741935483871%\" valign=\"bottom\" style=\"width: 3.8329%;\"\u003e\n \u003cp\u003e5(4, 6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.454949944382648%\" valign=\"bottom\" style=\"width: 6.9205%;\"\u003e\n \u003cp\u003e44/42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.343715239154616%\" valign=\"bottom\" style=\"width: 4.0991%;\"\u003e\n \u003cp\u003e1 (1, 2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.454949944382648%\" valign=\"bottom\" style=\"width: 6.9205%;\"\u003e\n \u003cp\u003e755/734\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.012235817575084%\" valign=\"bottom\" style=\"width: 4.1523%;\"\u003e\n \u003cp\u003e21 (14, 28)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.012235817575084%\" valign=\"bottom\" style=\"width: 6.9205%;\"\u003e\n \u003cp\u003e6.79/6.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.239154616240267%\" colspan=\"2\" valign=\"bottom\" style=\"width: 4.6847%;\"\u003e\n \u003cp\u003e0.14 (0.10, 0.17)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.343715239154616%\" valign=\"bottom\" style=\"width: 2.8215%;\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.454949944382648%\" valign=\"bottom\" style=\"width: 6.9205%;\"\u003e\n \u003cp\u003e2571/2513\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.67741935483871%\" valign=\"bottom\" style=\"width: 3.8329%;\"\u003e\n \u003cp\u003e59(54, 62)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.454949944382648%\" valign=\"bottom\" style=\"width: 6.9205%;\"\u003e\n \u003cp\u003e176/173\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.343715239154616%\" valign=\"bottom\" style=\"width: 4.0991%;\"\u003e\n \u003cp\u003e3 (3, 5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.454949944382648%\" valign=\"bottom\" style=\"width: 6.9205%;\"\u003e\n \u003cp\u003e3908/3834\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.012235817575084%\" valign=\"bottom\" style=\"width: 4.1523%;\"\u003e\n \u003cp\u003e84 (70, 100)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.012235817575084%\" valign=\"bottom\" style=\"width: 6.9205%;\"\u003e\n \u003cp\u003e30.02/29.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.239154616240267%\" colspan=\"2\" valign=\"bottom\" style=\"width: 4.6847%;\"\u003e\n \u003cp\u003e0.65 (0.60, 0.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.35412026726058%\" valign=\"bottom\" style=\"width: 2.8215%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.465478841870825%\" valign=\"bottom\" style=\"width: 6.9205%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.688195991091314%\" valign=\"bottom\" style=\"width: 3.8329%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.465478841870825%\" valign=\"bottom\" style=\"width: 6.9205%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.35412026726058%\" valign=\"bottom\" style=\"width: 4.0991%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.465478841870825%\" valign=\"bottom\" style=\"width: 6.9205%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.024498886414253%\" valign=\"bottom\" style=\"width: 4.1523%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.024498886414253%\" valign=\"top\" style=\"width: 6.9205%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.140311804008908%\" valign=\"top\" style=\"width: 4.2056%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.0044543429844097%\" style=\"width: 0.4791%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"97.9933110367893%\" colspan=\"9\" valign=\"bottom\" style=\"width: 47.2194%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eScenario 2 (\u003c/strong\u003e\u003cstrong\u003e90% parous women breastfeed exclusively for 6 months)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.0066889632107023%\" style=\"width: 0.4791%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.35412026726058%\" valign=\"bottom\" style=\"width: 2.8215%;\"\u003e\n \u003cp\u003eStage I\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.465478841870825%\" valign=\"bottom\" style=\"width: 6.9205%;\"\u003e\n \u003cp\u003e1584/1419\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.688195991091314%\" valign=\"bottom\" style=\"width: 3.8329%;\"\u003e\n \u003cp\u003e164 (159, 169)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.465478841870825%\" valign=\"bottom\" style=\"width: 6.9205%;\"\u003e\n \u003cp\u003e85/76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.35412026726058%\" valign=\"bottom\" style=\"width: 4.0991%;\"\u003e\n \u003cp\u003e9 (8, 9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.465478841870825%\" valign=\"bottom\" style=\"width: 6.9205%;\"\u003e\n \u003cp\u003e2077/1865\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.024498886414253%\" valign=\"bottom\" style=\"width: 4.1523%;\"\u003e\n \u003cp\u003e212 (201, 223)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.024498886414253%\" valign=\"bottom\" style=\"width: 6.9205%;\"\u003e\n \u003cp\u003e15.39/13.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.140311804008908%\" valign=\"bottom\" style=\"width: 4.2056%;\"\u003e\n \u003cp\u003e1.58 (1.53, 1.63)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.0044543429844097%\" style=\"width: 0.4791%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.35412026726058%\" valign=\"bottom\" style=\"width: 2.8215%;\"\u003e\n \u003cp\u003eStage II\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.465478841870825%\" valign=\"bottom\" style=\"width: 6.9205%;\"\u003e\n \u003cp\u003e411/367\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.688195991091314%\" valign=\"bottom\" style=\"width: 3.8329%;\"\u003e\n \u003cp\u003e44 (42, 46)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.465478841870825%\" valign=\"bottom\" style=\"width: 6.9205%;\"\u003e\n \u003cp\u003e24/21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.35412026726058%\" valign=\"bottom\" style=\"width: 4.0991%;\"\u003e\n \u003cp\u003e3 (2, 3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.465478841870825%\" valign=\"bottom\" style=\"width: 6.9205%;\"\u003e\n \u003cp\u003e570/508\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.024498886414253%\" valign=\"bottom\" style=\"width: 4.1523%;\"\u003e\n \u003cp\u003e62 (57, 67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.024498886414253%\" valign=\"bottom\" style=\"width: 6.9205%;\"\u003e\n \u003cp\u003e3.99/3.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.140311804008908%\" valign=\"bottom\" style=\"width: 4.2056%;\"\u003e\n \u003cp\u003e0.43 (0.41, 0.45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.0044543429844097%\" style=\"width: 0.4791%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.35412026726058%\" valign=\"bottom\" style=\"width: 2.8215%;\"\u003e\n \u003cp\u003eStage III\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.465478841870825%\" valign=\"bottom\" style=\"width: 6.9205%;\"\u003e\n \u003cp\u003e332/298\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.688195991091314%\" valign=\"bottom\" style=\"width: 3.8329%;\"\u003e\n \u003cp\u003e35 (33, 36)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.465478841870825%\" valign=\"bottom\" style=\"width: 6.9205%;\"\u003e\n \u003cp\u003e23/20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.35412026726058%\" valign=\"bottom\" style=\"width: 4.0991%;\"\u003e\n \u003cp\u003e2 (2, 3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.465478841870825%\" valign=\"bottom\" style=\"width: 6.9205%;\"\u003e\n \u003cp\u003e510/455\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.024498886414253%\" valign=\"bottom\" style=\"width: 4.1523%;\"\u003e\n \u003cp\u003e55 (49, 60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.024498886414253%\" valign=\"bottom\" style=\"width: 6.9205%;\"\u003e\n \u003cp\u003e3.71/3.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.140311804008908%\" valign=\"bottom\" style=\"width: 4.2056%;\"\u003e\n \u003cp\u003e0.38 (0.36, 0.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.0044543429844097%\" style=\"width: 0.4791%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.35412026726058%\" valign=\"bottom\" style=\"width: 2.8215%;\"\u003e\n \u003cp\u003eStage IV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.465478841870825%\" valign=\"bottom\" style=\"width: 6.9205%;\"\u003e\n \u003cp\u003e229/206\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.688195991091314%\" valign=\"bottom\" style=\"width: 3.8329%;\"\u003e\n \u003cp\u003e23 (22, 24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.465478841870825%\" valign=\"bottom\" style=\"width: 6.9205%;\"\u003e\n \u003cp\u003e43/39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.35412026726058%\" valign=\"bottom\" style=\"width: 4.0991%;\"\u003e\n \u003cp\u003e4 (3, 4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.465478841870825%\" valign=\"bottom\" style=\"width: 6.9205%;\"\u003e\n \u003cp\u003e740/670\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.024498886414253%\" valign=\"bottom\" style=\"width: 4.1523%;\"\u003e\n \u003cp\u003e70 (62, 77)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.024498886414253%\" valign=\"bottom\" style=\"width: 6.9205%;\"\u003e\n \u003cp\u003e6.74/6.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.140311804008908%\" valign=\"bottom\" style=\"width: 4.2056%;\"\u003e\n \u003cp\u003e0.68 (0.64, 0.71)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.0044543429844097%\" style=\"width: 0.4791%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.35412026726058%\" valign=\"bottom\" style=\"width: 2.8215%;\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.465478841870825%\" valign=\"bottom\" style=\"width: 6.9205%;\"\u003e\n \u003cp\u003e2556/2290\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.688195991091314%\" valign=\"bottom\" style=\"width: 3.8329%;\"\u003e\n \u003cp\u003e266 (259, 273)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.465478841870825%\" valign=\"bottom\" style=\"width: 6.9205%;\"\u003e\n \u003cp\u003e174/158\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.35412026726058%\" valign=\"bottom\" style=\"width: 4.0991%;\"\u003e\n \u003cp\u003e18 (17, 19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.465478841870825%\" valign=\"bottom\" style=\"width: 6.9205%;\"\u003e\n \u003cp\u003e3897/3498\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.024498886414253%\" valign=\"bottom\" style=\"width: 4.1523%;\"\u003e\n \u003cp\u003e399 (381, 416)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.024498886414253%\" valign=\"bottom\" style=\"width: 6.9205%;\"\u003e\n \u003cp\u003e29.83/26.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.140311804008908%\" valign=\"bottom\" style=\"width: 4.2056%;\"\u003e\n \u003cp\u003e3.07 (2.98, 3.15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.0044543429844097%\" style=\"width: 0.4791%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e^Base: Actual breastfeeding rate in 2018 was used in baseline.\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003csup\u003e+\u003c/sup\u003e2018 prices with 3% discount rate\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"international-breastfeeding-journal","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ibfj","sideBox":"Learn more about [International Breastfeeding Journal](http://internationalbreastfeedingjournal.biomedcentral.com/)","snPcode":"13006","submissionUrl":"https://submission.nature.com/new-submission/13006/3","title":"International Breastfeeding Journal","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Breastfeeding, breast cancer, economic evaluation, the Monte Carlo Model, cost-savings, DALYs","lastPublishedDoi":"10.21203/rs.3.rs-4283403/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4283403/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eObjectives\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOur study aimed to estimate the healthcare cost-savings resulting from a reduction in breast cancer attributed to an increase in the breastfeeding rate in Hong Kong.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis is an economic evaluation. We simulated a cohort of 33500 Hong Kong women aged 20 years in 2018 using the Monte Carlo Model, to estimate with probabilistic sensitivity analysis the healthcare cost-savings, the number of deaths averted and the increase in disability-adjusted life years (DALYs) due to prevention of breast cancer attributed to a higher breastfeeding rate, assuming a discount rate of 3%.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIncreasing the proportion of parous women breastfeeding \u003cem\u003e\u003cstrong\u003eexclusively \u003c/strong\u003e\u003c/em\u003efor 6 months from 22% (current rate) to 90% averted 266 (95% CI259, 273) or ~10% of all-stage breast cancer cases, 18 deaths (95% CI 17, 19) and 399 DALYs (95% CI 381, 416), over the lifetime of each annual cohort of women in Hong Kong. The lifetime medical costs that could be saved would be ~USD3 million. However cost-saving was 5-time less if the cumulative any breastfeeding (i.e. partially or exclusively) for 12 months in parous women is increased to 90%.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePromoting and protecting breastfeeding leads to cost-savings for treating breast cancer in Hong Kong. Our analysis can inform healthcare budget resources that could be allocated to promote exclusive breastfeeding for 6 months.\u003c/p\u003e","manuscriptTitle":"Breastfeeding Promotion to Prevent Breast Cancer: an Economic Evaluation","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-04-29 14:30:20","doi":"10.21203/rs.3.rs-4283403/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-09-14T08:30:22+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-09-11T12:03:06+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-09-09T16:49:51+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"61214014854169661975855444463666729503","date":"2024-08-12T13:28:44+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"272797621013678387157140778754318175700","date":"2024-08-09T08:08:41+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-06-05T04:22:50+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"290d6f14-dff3-4204-b1a5-f2d177ab421f","date":"2024-05-04T05:12:57+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-04-23T05:05:14+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-04-20T15:43:13+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-04-20T15:43:13+00:00","index":"","fulltext":""},{"type":"submitted","content":"International Breastfeeding Journal","date":"2024-04-17T17:27:50+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"international-breastfeeding-journal","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ibfj","sideBox":"Learn more about [International Breastfeeding Journal](http://internationalbreastfeedingjournal.biomedcentral.com/)","snPcode":"13006","submissionUrl":"https://submission.nature.com/new-submission/13006/3","title":"International Breastfeeding Journal","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"3e328f94-89ac-4f39-ab73-8b54a04fc680","owner":[],"postedDate":"April 29th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-03-03T16:02:14+00:00","versionOfRecord":{"articleIdentity":"rs-4283403","link":"https://doi.org/10.1186/s13006-024-00689-y","journal":{"identity":"international-breastfeeding-journal","isVorOnly":false,"title":"International Breastfeeding Journal"},"publishedOn":"2025-02-24 15:57:55","publishedOnDateReadable":"February 24th, 2025"},"versionCreatedAt":"2024-04-29 14:30:20","video":"","vorDoi":"10.1186/s13006-024-00689-y","vorDoiUrl":"https://doi.org/10.1186/s13006-024-00689-y","workflowStages":[]},"version":"v1","identity":"rs-4283403","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4283403","identity":"rs-4283403","version":["v1"]},"buildId":"CiT4i_kKBbxQbnFL0ufpk","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}