Breastfeeding and subsequent risk of 24 types of maternal cancer: a cohort study of Chinese women

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We aimed to investigate these associations among parous Chinese women. Methods A total of 157,454 participants aged 40–75 years from 2012 to 2021 were recruited. Cox proportional hazards model was applied to explore the association between breastfeeding behaviors and cancer risks by hazard ratios (HRs) and corresponding 95% confidence intervals (CIs). Results 5,542 incident cancer cases were identified with a median follow-up of 4.81 years. The history of breastfeeding was statistically significantly associated with lower risk of breast cancer in the multivariate-adjusted model (HR = 0.78, 95%CI: 0.65–0.94). In addition, the risk of gallbladder cancer increased with increasing months of total breastfeeding ( P -trend = 0.039), with a 51% increase in risk for each additional 12 months of breastfeeding (HR = 1.51, 95%CI: 1.12–2.02). The risk of breast cancer decreased with increasing months of total breastfeeding ( P -trend = 0.015), with a 15% reduction in risk for each additional 12 months of breastfeeding (HR = 0.85, 95%CI: 0.76–0.95). The subgroup analyses according to menopausal status shows significant separations for colon-rectum cancer, uterus cancer, oesophagus cancer, and larynx cancer (all P -interaction < 0.05). In addition, significant linear associations were suggested concerning gallbladder cancer ( P -overall = 0.0302, P -nonlinear = 0.6558) and breast cancer ( P -overall = 0.0175, P -nonlinear = 0.5544). Conclusions This study provides further support for the role of breastfeeding behavior in overall cancer and its 24 site-specific cancers. Breastfeeding maternal cancer Chinese women cohort study preventive Figures Figure 1 Figure 2 Introduction Cancer represents a major global health challenge, with estimated 14.57% of total deaths and 8.8% of total disability-adjusted life years according to the Global Burden of Disease Study 2021. 1 The burden continues to grow, with projections suggesting 35 million new cases by 2050. 2 Beyond its direct health impacts, cancer creates significant societal and economic consequences, highlighting the urgent need for preventive strategies. While established risk factors like tobacco use and obesity contribute substantially, 1 identifying additional modifiable factors remains crucial for targeted prevention. Breastfeeding, as a major modifiable reproductive factor, plays a critical role in the health of both mother and infant. 3 Recognized worldwide as the best nutritional source for newborn infants, breastfeeding is extensively practiced, especially in low- and middle-income countries. 4 During motherhood, breastfeeding aids in the reduction of postpartum weight gain through increased caloric expenditure, promotes the release of the hormone oxytocin, facilitates the reduction of uterine size to pre-pregnancy levels, and decreases uterine bleeding. Additionally, the long-term benefits of breastfeeding may contribute to a decreased risk of certain cancers in mothers. 5 – 8 However, aside from breast cancer, the relationship between breastfeeding and the risk of other maternal cancers remains insufficient and controversial. These inconsistencies may stem from variations in populations, methodologies, tumor locations, histological types and invasiveness. 9 – 11 Furthermore, there is a paucity of comprehensive studies investigating the relationship between breastfeeding and all cancer subtypes within the same population, which could facilitate the exploration of less prevalent cancers and mitigate publication bias. Therefore, additional research is essential to explore the effect of breastfeeding on the risk of different site-specific cancers, particularly in sufficiently large cohorts. In this study, we concentrated on two breastfeeding behaviors including history of breastfeeding and total breastfeeding duration. Based on a large-scale prospective cohort study conducted in Hunan province, our main objective was to investigate the association of breastfeeding behavior with subsequent risk of 24 types of maternal cancer. Additionally, to examine the dose-response relationships of the above associations. Methods Study design and population We conducted a large-scale prospective cohort study under the framework of the Cancer Screening Program in Urban China (CanSPUC). CanSPUC is a non-profit national cancer screening program co-funded by the Chinese Ministry of Finance and the National Health Commission, launched in October 2012. The details of the CanSPUC have been presented in previously published articles. 12 In brief, the targeted population was residents aged 40–75 years living in the selected communities, and the targeted cancer types were the five most prevalent cancers in urban China, including lung cancer, liver cancer, female breast cancer, gastric cancer and colorectal cancer. All eligible participants who provided written informed consent were interviewed by trained staff to complete a questionnaire that included demographic characteristics, lifestyle factors, personal/family history of diseases, and menstrual and reproductive factors (for women only). Based on an established risk scoring system, participants at high risk for cancer were further invited to undergo clinical examinations for one or more cancer screenings. Finally, all participants who completed the questionnaire were followed up either passively or actively to collect information on their cancer incidence and mortality. In this study, we used data from CanSPUC conducted in Hunan Province between October 2012 and December 2021, covering a total of five cities (Changsha, Xiangtan, Yueyang, Zhuzhou, and Zhangjiajie). Altogether 319,592 eligible participants were enrolled, of whom 167,308 were females. According to the given exclusion criteria, 157,454 females with valid information were finally included in this study. The flow chart of the included participants in this study is shown in eFigure 1. The study was approved by the Ethics Committee of National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College (number of IRB:CH-PRE-004). The procedure of the study was conducted in accordance with the Declaration of Helsinki, and the informed consent was obtained from all participants. Cohort follow-up and case identification Follow-up for each participant began at the end of the baseline questionnaire and ended with the first diagnosis of cancer, death, the last documented follow-up contact, or December 31, 2021, whichever came first. The system of our program was linked with Hunan Provincial cancer registration system and death surveillance system to access information on the incidence of cancer. The information was also cross-checked with the records of the provincial medical registration system from the Hunan Provincial Health Commission. All cancer cases were coded according to the International Classification standards (ICD-10) (see eTable 1) and further classified as 24 site-specific cancers. 13 In accordance with methodological recommendations from prior studies, 14 – 16 cancer subtypes with sufficient case numbers (≥ 200) were included in our primary analysis. Detailed results for rarer cancers (< 200 cases) have been moved to Supplementary Material to preserve full data accessibility and future meta-analyses. Exposure assessment Information on menstrual and reproductive factors was collected by self-reported questionnaire at baseline entry. Menstrual and reproductive factors include age at menarche ( 14 years), menopause status (no, yes), surgeries on the reproductive system (no, yes), history of breastfeeding (no, yes), and total breastfeeding duration. Total breastfeeding duration was considered as both continuous and multi-categorical (0, 1–6, 7–12, or > 12 months). Potential risk factors for cancer were selected based on experience and reports from previous studies. 17 , 18 Marital status was classified as married or others (including unmarried, widowed, or divorced). Educational level was classified as low (elementary school or below), medium (junior or high school or equivalent), and high (college or above). Smoking status was defined as current (> 1 cigarette/day for at least 6 months), former (previously smoked and have quit for at least 6 months), and never smoking. Alcohol drinking status was classified as never and ever (current alcohol drinking and former alcohol drinking). Regular exercise (no, yes) was defined as an average of more than 3 times per week for more than 30 minutes per session. History of hypertension (no, yes) and diabetes (no, yes) referred to previous clinical diagnoses of hypertension and diabetes, respectively. Family history of cancer (no, yes) was defined as previous clinical diagnosis of cancer within participants’ three generations. Body mass index (BMI) was calculated as weight in kilograms divided by the square of height in meters, and was further classified into four categories according to the Chinese standard: underweight (< 18.5 kg/m 2 ), normal (18.5–23.9 kg/m 2 ), overweight (24.0-27.9 kg/m 2 ) or obese (≥ 28.0 kg/m 2 ). Statistical analysis Descriptive analyses were described as counts and proportions for categorical variables, and mean ± standard deviation (SD) for continuous variables. Chi-square tests and t-tests were applied to compare the differences between groups. The hazard ratios (HRs) and 95% confidence intervals (CIs) of developing cancer in relationship to baseline breastfeeding behavior were evaluated using Cox proportional hazards models. Unadjusted model did not include any covariates; Age-adjusted model only adjusted for age at enrollment (continuous); Multivariate-adjusted model further adjusted for educational level (low, medium, high), marital status (married, others), smoking status (never, current, ever), alcohol drinking status (never, ever), regular exercise (no, yes), BMI (underweight, normal, overweight, obese), family history of cancer (no, yes), hypertension (no, yes), diabetes (no, yes), and age at menarche ( 14 years), and menopause status (no, yes). For the continuous variable (total breastfeeding duration), both the dose-response relationship and tests for non-linear associations were performed using restricted cubic spline models with three knots. 19 To examine effect modification, we conducted subgroup analyses for menopausal status. The associations were further investigated in multivariable models among premenopausal and postmenopausal females. Statistical differences between subgroups were investigated by including an interaction term of breastfeeding behaviors and menopausal status in the model. 20 A series of sensitivity analyses were additionally conducted. Considering the surgeries on the reproductive system, an important influencing factor of cancer incidence, was only collected in 2012–2019, we further adjusted for surgeries on the reproductive system based on multivariate-adjusted model (2012–2019). To evaluate the robustness of the main findings, we included nulliparous female participants into analysis, and took the history of breastfeeding and total breastfeeding duration as none/zero. Tests in this study were all two-sided and P < 0.05 was considered statistically significant. All statistical analyses were conducted using the R software, version 4.2.2. Results During a median follow-up of 4.81 years, 5,542 of 157,454 women were diagnosed with cancer in the cohort, with an incidence density of 82.67/10 5 person-years. Table 1 presents the baseline characteristics of the study population according to cancer status. Participants with a history of breastfeeding tended to be older, less educated, and more likely to be never-smokers and never-drinkers. They also had lower prevalence of family cancer history, but higher rates of hypertension and diabetes. Additionally, these participants exhibited later menarche age, were more frequently postmenopausal, had fewer reproductive system surgeries, and reported more physical activity. Table 1 Distributions of selected variables of the participants at baseline (2012–2021). Variables Person-years Non-breastfeeding (n = 15641) Breastfeeding (n = 141813) P value Age at enrollment (year, Mean ± SD) 760401.65 56.08 (9.05) 57.09 (9.76) < 0.001 Educational level (n, %) Low 161136.02 2683 (17.2) 33763 (23.8) < 0.001 Medium 509830.33 11238 (71.8) 93503 (65.9) High 89435.30 1720 (11.0) 14547 (10.3) Marital status (n, %) Married 734382.37 15124 (96.7) 136718 (96.4) 0.069 Others 26019.28 517 (3.3) 5095 (3.6) Smoking status (n, %) Never 722837.85 13845 (88.6) 135651 (95.7) < 0.001 Current 32440.26 1681 (10.8) 5421 (3.8) Ever 3874.36 107 (0.7) 604 (0.4) Alcohol drinking status (n, %) Never 706226.18 13314 (85.1) 132868 (93.7) < 0.001 Ever 54175.46 2327 (14.9) 8945 (6.3) BMI (kg/m 2 , Mean ± SD) 22.99 (2.65) 22.96 (2.65) 0.250 Underweight (< 18.5) 19472.72 383 (2.5) 3610 (2.5) 0.507 Normal (18.5–23.9) 502670.36 10473 (67.0) 94229 (66.5) Overweight (24.0-27.9) 207692.96 4161 (26.6) 38132 (26.9) Obese (≥ 28.0) 29834.26 607 (3.9) 5721 (4.0) Family history of cancer (n, %) No 578010.71 8200 (52.4) 109190 (77.0) < 0.001 Yes 182390.93 7441 (47.6) 32623 (23.0) Hypertension (n, %) No 695834.69 14477 (92.6) 129018 (91.0) < 0.001 Yes 64566.95 1164 (7.4) 12795 (9.0) Diabetes (n, %) No 741354.57 15358 (98.2) 138647 (97.8) 0.001 Yes 19047.07 283 (1.8) 3166 (2.2) Age at menarche (year, Mean ± SD) 13.70 (1.62) 13.90 (1.43) < 0.001 < 13 96891.13 3516 (22.5) 21085 (14.9) 14 235080.02 4365 (27.9) 41445 (29.2) Menopause status (n, %) No 267642.67 5511 (35.2) 44822 (31.6) < 0.001 Yes 492758.98 10130 (64.8) 96991 (68.4) Surgeries on the reproductive system * (n, %) No 655753.62 8758 (82.8) 100845 (91.7) < 0.001 Yes 71180.30 1823 (17.2) 9088 (8.3) Exercise No 477067.99 11190 (71.5) 87339 (61.6) < 0.001 Yes 283333.66 4451 (28.5) 54474 (38.4) Abbreviations: SD, standard deviation; BMI, body mass index. * The information on female reproductive system surgery was only collected between 2012 and 2019. Table 2 and eTable 2 show the associations of breastfeeding history with cancer incidence in three models (unadjusted model, age-adjusted model, and multivariate-adjusted model). The history of breastfeeding was statistically significantly associated with lower risk of breast cancer in the three models (all P < 0.05). No statistically significant associations were observed between history of breastfeeding and other site-specific cancers. Table 2 Risk of developing overall cancer and its main site-specific cancers in relationship to history of breastfeeding baseline total breastfeeding duration. History of breastfeeding Cases (n = 5542) Unadjusted model Age-adjusted model Multivariate-adjusted model HR (95%CI) HR (95%CI) HR (95%CI) Colon-rectum (C18-21) No 47 Ref. Ref. Ref. Yes 527 1.04 (0.77–1.41) 0.99 (0.73–1.34) 1.04 (0.77–1.40) Lung (C33-34) No 65 Ref. Ref. Ref. Yes 739 1.05 (0.81–1.35) 0.99 (0.77–1.28) 1.07 (0.83–1.39) Breast (C50) No 128 Ref. Ref. Ref. Yes 1000 0.73 (0.61–0.88) 0.73 (0.61–0.88) 0.78 (0.65–0.94) Cervix (C53) No 32 Ref. Ref. Ref. Yes 375 1.10 (0.77–1.58) 1.11 (0.77–1.59) 1.17 (0.81–1.69) Uterus (C54-55) No 18 Ref. Ref. Ref. Yes 222 1.14 (0.71–1.84) 1.14 (0.70–1.84) 1.14 (0.70–1.85) Brain (C70-72) No 20 Ref. Ref. Ref. Yes 251 1.15 (0.73–1.81) 1.10 (0.70–1.74) 1.14 (0.72–1.80) Thyroid (C73) No 47 Ref. Ref. Ref. Yes 425 0.81 (0.60–1.10) 0.83 (0.62–1.12) 0.92 (0.68–1.26) All others (NA) No 29 Ref. Ref. Ref. Yes 363 1.17 (0.80–1.71) 1.14 (0.78–1.66) 1.19 (0.81–1.76) All sites (C00-97, D32-33, D42-43, D45-47) No 487 Ref. Ref. Ref. Yes 5055 0.96 (0.87–1.05) 0.94 (0.85–1.03) 0.99 (0.90–1.09) Unadjusted model: no covariates were controlled for. Age-adjusted model: only age at enrollment (continuous) was controlled for. Multivariate-adjusted model: age-adjusted model + educational level (low, medium, high), marital status (married, others), smoking status (never, current, ever), alcohol drinking status (never, ever), regular exercise (no, yes), BMI (underweight, normal, overweight, obese), family history of cancer (no, yes), hypertension (no, yes), diabetes (no, yes), age at menarche ( 14 years), and menopause status (no, yes). Abbreviations: HR, hazard ratio; CI, confidence interval. Table 3 and eTable 3 present the associations of total breastfeeding duration (continuous and multi-categorical) with cancer incidence in three models. In the multivariate-adjusted model, the risk of gallbladder cancer increased with increasing months of total breastfeeding ( P -trend = 0.039), with a 51% increase in risk for each additional 12 months of breastfeeding (HR = 1.51, 95%CI: 1.12–2.02). The risk of breast cancer decreased with increasing months of total breastfeeding ( P -trend = 0.015), with a 15% reduction in risk for each additional 12 months of breastfeeding (HR = 0.85, 95%CI: 0.76–0.95). With respect to thyroid cancer, the risk decreased by 17% with each additional 12 months of breastfeeding (HR = 0.83, 95% CI: 0.69–0.99), although the trend was not statistically significant ( P -trend = 0.107) in the multivariate-adjusted model. Similarly, the risk of overall cancer incidence decreased by 5% with each additional 12 months of breastfeeding (HR = 0.95, 95% CI: 0.90–0.99), although the trend was not statistically significant ( P -trend = 0.225). Table 3 Risk of developing overall cancer and its main site-specific cancers in relationship to baseline total breastfeeding duration. Site-specific cancers Total breastfeeding duration Cases (n = 5542) Unadjusted model Age-adjusted model Multivariate-adjusted model HR (95%CI) HR (95%CI) HR (95%CI) Colon-rectum (C18-21) Continuous (per 12 months) 574 0.97 (0.84–1.12) 0.84 (0.73–0.98) 0.87 (0.75–1.01) Multi-categorical (month) 0 47 Ref. Ref. Ref. 1–6 79 1.22 (0.85–1.75) 1.25 (0.87–1.80) 1.25 (0.87–1.80) 7–12 335 1.01 (0.75–1.37) 0.99 (0.73–1.35) 1.03 (0.76–1.41) > 12 113 1.03 (0.73–1.45) 0.86 (0.61–1.21) 0.92 (0.65–1.30) P for trend 0.647 0.079 0.216 Lung (C33-34) Continuous (per 12 months) 804 1.07 (0.95–1.20) 0.93 (0.83–1.05) 0.97 (0.86–1.09) Multi-categorical (month) 0 65 Ref. Ref. Ref. 1–6 97 1.07 (0.78–1.47) 1.09 (0.80–1.50) 1.13 (0.82–1.54) 7–12 465 1.01 (0.78–1.31) 0.99 (0.76–1.28) 1.07 (0.82–1.39) > 12 177 1.15 (0.87–1.53) 0.96 (0.73–1.28) 1.06 (0.79–1.42) P for trend 0.381 0.517 0.915 Breast (C50) Continuous (per 12 months) 1128 0.83 (0.74–0.92) 0.82 (0.73–0.92) 0.85 (0.76–0.95) Multi-categorical (month) 0 128 Ref. Ref. Ref. 1–6 139 0.79 (0.62–1.01) 0.79 (0.62–1.01) 0.82 (0.64–1.04) 7–12 654 0.73 (0.60–0.88) 0.73 (0.60–0.88) 0.78 (0.64–0.94) > 12 207 0.70 (0.56–0.87) 0.69 (0.55–0.86) 0.75 (0.60–0.94) P for trend 0.002 0.001 0.015 Cervix (C53) Continuous (per 12 months) 407 1.05 (0.89–1.24) 1.07 (0.90–1.27) 1.09 (0.91–1.30) Multi-categorical (month) 0 32 Ref. Ref. Ref. 1–6 42 0.96 (0.61–1.52) 0.96 (0.60–1.52) 1.01 (0.64–1.60) 7–12 246 1.10 (0.76–1.59) 1.10 (0.76–1.59) 1.17 (0.81–1.71) > 12 87 1.19 (0.79–1.78) 1.22 (0.81–1.83) 1.30 (0.86–1.96) P for trend 0.253 0.197 0.130 Uterus (C54-55) Continuous (per 12 months) 240 1.11 (0.90–1.38) 1.11 (0.90–1.38) 1.13 (0.90–1.41) Multi-categorical (month) 0 18 Ref. Ref. Ref. 1–6 18 0.72 (0.37–1.38) 0.72 (0.37–1.38) 0.73 (0.38–1.40) 7–12 156 1.22 (0.75–1.99) 1.22 (0.75–1.99) 1.23 (0.75–2.01) > 12 48 1.14 (0.66–1.96) 1.14 (0.66–1.96) 1.16 (0.67–2.01) P for trend 0.218 0.222 0.215 Brain (C70-72) Continuous (per 12 months) 271 1.14 (0.93–1.39) 1.02 (0.84–1.25) 1.00 (0.82–1.23) Multi-categorical (month) 0 20 Ref. Ref. Ref. 1–6 29 1.03 (0.58–1.82) 1.05 (0.59–1.85) 1.08 (0.61–1.92) 7–12 163 1.14 (0.71–1.81) 1.12 (0.70–1.78) 1.16 (0.73–1.86) > 12 59 1.26 (0.76–2.09) 1.09 (0.66–1.81) 1.09 (0.65–1.84) P for trend 0.287 0.712 0.743 Thyroid (C73) Continuous (per 12 months) 472 0.72 (0.61–0.86) 0.77 (0.65–0.93) 0.83 (0.69–0.99) Multi-categorical (month) 0 47 Ref. Ref. Ref. 1–6 69 1.03 (0.71–1.49) 1.02 (0.70–1.47) 1.07 (0.73–1.55) 7–12 286 0.84 (0.61–1.14) 0.84 (0.62–1.14) 0.93 (0.68–1.28) > 12 70 0.62 (0.43–0.90) 0.68 (0.47–0.99) 0.78 (0.53–1.14) P for trend 0.002 0.014 0.107 All others (NA) Continuous (per 12 months) 392 1.15 (0.97–1.35) 1.04 (0.89–1.23) 1.05 (0.89–1.24) Multi-categorical (month) 0 29 Ref. Ref. Ref. 1–6 37 0.93 (0.57–1.52) 0.95 (0.58–1.55) 0.99 (0.60–1.62) 7–12 243 1.20 (0.82–1.76) 1.19 (0.81–1.74) 1.25 (0.84–1.86) > 12 83 1.24 (0.81–1.89) 1.10 (0.72–1.67) 1.15 (0.74–1.77) P for trend 0.146 0.462 0.371 All sites (C00-97, D32-33, D42-43, D45-47) Continuous (per 12 months) 5542 0.99 (0.95–1.04) 0.93 (0.88–0.97) 0.95 (0.90–0.99) Multi-categorical (month) 0 487 Ref. Ref. Ref. 1–6 666 0.98 (0.87–1.11) 0.99 (0.88–1.12) 1.02 (0.91–1.15) 7–12 3275 0.95 (0.86–1.04) 0.94 (0.85–1.03) 0.99 (0.90–1.10) > 12 1114 0.98 (0.88–1.09) 0.89 (0.80–0.99) 0.95 (0.85–1.06) P for trend 0.543 0.012 0.225 Unadjusted model: no covariates were controlled for. Age-adjusted model: only age at enrollment (continuous) was controlled for. Multivariate-adjusted model: Age-adjusted model + educational level (low, medium, high), marital status (married, others), smoking status (never, current, ever), alcohol drinking status (never, ever), regular exercise (no, yes), BMI (underweight, normal, overweight, obese), family history of cancer (no, yes), hypertension (no, yes), diabetes (no, yes), age at menarche ( 14 years), and menopause status (no, yes). Abbreviations: HR, hazard ratio; CI, confidence interval. Figure 1 and eTable 4 display the associations between breastfeeding behavior and cancer incidence stratified by menopausal status. The inverse associations of total breastfeeding duration with colon-rectum cancer (0.56 [0.35–0.91] vs. 0.92 [0.79–1.07], P -interaction = 0.028), and history of breastfeeding with uterus cancer (0.76 [0.38–1.49] vs. 1.62 [0.79–3.32]), P -interaction = 0.038), were more pronounced in premenopausal women compared with those in postmenopausal women. With respect to oesophagus cancer (6.01 [1.46–24.70] vs. 0.79 [0.38–1.65], P -interaction = 0.037) and larynx cancer (12.62 [2.69–59.25] vs. 0.37 [0.11–1.22], P -interaction = 0.002), stronger positive associations with total breastfeeding duration were observed in premenopausal women than those in postmenopausal women. Notably, the results on oesophagus cancer and larynx cancer should be treated cautiously because of the extremely low number of cancer cases. Figure 2 and eFigure 2 illustrates the dose-response associations between total breastfeeding duration and the risks of overall cancer and site-specific cancers. Significant linear associations were suggested concerning gallbladder cancer ( P -overall = 0.0302, P -nonlinear = 0.6558) and breast cancer ( P -overall = 0.0175, P -nonlinear = 0.5544). The results of a series of sensitivity analyses are presented in the Supplementary Material. First, the estimated effects of breastfeeding behavior on cancer incidence remained fairly robust after additionally adjusting for surgeries on the reproductive system. That was to say, the associations between total breastfeeding duration and gallbladder cancer (HR = 1.66, 95%CI: 1.22–2.25), breast cancer (HR = 0.88, 95%CI: 0.79–0.99), and thyroid cancer (HR = 0.82, 95%CI: 0.68–0.99) remained statistically significant (see eTable 5). In the sensitivity analyses for including nulliparous female participants into analysis, the breastfeeding behavior was still associated with higher risk of gallbladder cancer and lower risk of breast cancer and thyroid cancer (see eTable 6). Additionally, history of breastfeeding was associated with nasopharynx cancer (HR = 0.45, 95%CI: 0.23–0.87), and total breastfeeding duration was associated with overall cancer (HR = 0.94, 95%CI: 0.90–0.98). Discussion Main findings Evidence on the effect of breastfeeding on certain maternal cancers remains insufficient and controversial. To the best of our knowledge, this study is the first in China to systematically and comprehensively investigate the relationship between breastfeeding behaviors and all site-specific maternal cancers based on a large-scale population-based cohort, providing valuable evidence for the promotion of women’s health in China and Asia. In this prospective study that included 157,454 participants and 5,542 cancer cases, we discovered that the history of breastfeeding was statistically significantly associated with lower risk of breast cancer. In the multivariate-adjusted model, longer durations of total breastfeeding were associated with increased risk of gallbladder cancer and decreased risks of breast cancer, thyroid cancer, and overall cancer. The subgroup analyses according to menopausal status showed significant separations for colon-rectum cancer, uterus cancer, oesophagus cancer, and larynx cancer. In addition, significant linear associations were suggested concerning gallbladder cancer and breast cancer based on restricted cubic spline model. Our findings, derived from a relatively large population study, are highly pertinent to shaping public health policy and practices in China. Interpretation and comparison with previous studies The observed association between breastfeeding and decreased risk of breast cancer was in line with previous studies. 5 , 21 – 25 In fact, the protective effects of breastfeeding against breast cancer have been widely acknowledged by the academic researchers, whereas the precise mechanism remains uncertain. A recent review indicated that the mechanism may include the reduction of DNA methylation abnormalities, remodeling of breast tissue, lowering of estrogen levels, and inhibition of cancer cells within the microenvironment through breastfeeding. 5 In addition, the beneficial effect of breastfeeding varied for different types of breast cancer. 26 For example, findings from the Nurses’ Health Studies revealed that breastfeeding was solely associated with a reduced risk of estrogen receptor negative disease, but not estrogen receptor positive disease. 27 The varying associations between breastfeeding and breast cancer subtypes warrant further investigation, which will be addressed in our subsequent studies. This study found that the risk of gallbladder cancer increased with increasing months of total breastfeeding ( P -trend = 0.039), with a 51% increase in risk for each additional 12 months of breastfeeding (HR = 1.51, 95%CI: 1.12–2.02). Our results were inconsistent with the previous literature, which did not find an association between breastfeeding and gallbladder cancer. 28 – 31 For example, a case-control study in India discovered a positive but not statistically significant association of breastfeeding years with gallbladder cancer (OR = 1.01, 95%CI: 0.98–1.04). 30 According to a pooled analysis of the Asia Cohort Consortium across 4 countries (China, Japan, Korea, and Singapore), history of breastfeeding did not show a clear association with gallbladder cancer risk (pooled HR = 0.98, 95%CI: 0.72–1.34). 31 Despite the available literature, existing studies on the association between breastfeeding and gallbladder cancer remain limited, and further large-scale prospective studies are required to elucidate this relationship. The potential mechanism may involve breastfeeding-induced alterations in sex hormones, which are implicated in gallbladder carcinogenesis, as supported by in vitro data, animal models, and functional or physiological evidence. The abnormal expression of estrogen and progesterone receptors in gallbladder cancer tissues, vitro cell lines, and mouse models suggested a critical role for steroid hormones in the development of gallbladder carcinogenesis. 32 , 33 In this study, the risk of thyroid cancer decreased by 17% with each additional 12 months of breastfeeding (HR = 0.83, 95% CI: 0.69–0.99) in the multivariate-adjusted model, which was consistent with most previous studies. 34 – 37 A case-control study among Chinese women found that shorter lifetime breastfeeding (< 6 months) significantly increased the risk of papillary thyroid cancer. 34 A meta-analysis comprising nine reports revealed a significant inverse association between ever breastfeeding and thyroid cancer risk, as well as a significant linear relationship between breastfeeding duration and thyroid cancer risk. 35 Although most related studies have reported significant findings, a longitudinal study did not observe a statistically significant association regarding the months of breastfeeding and the risk of thyroid cancer. 38 The possible protective effect of breastfeeding against thyroid cancer deserves further exploration, with several potential biological mechanisms already having been suggested. Breastfeeding may inhibit ovulation, thereby reducing endogenous estrogen exposure, which in turn could decrease the proliferation, migration, invasion, and recurrence of malignant thyroid cells. 39 This study also found a reduced risk of overall cancer with each additional 12 months of breastfeeding (HR = 0.95, 95%CI: 0.90–0.99). This suggested that breastfeeding in general may be feasible for reducing the risk of cancer among parous women, despite its potential adverse effect on gallbladder cancer. Regarding site-specific cancers, we did not discover statistically significant associations between breastfeeding and cancers other than breast, gallbladder, and thyroid cancer. In fact, previous studies have reported rather mixed results related to other cancers. For example, numerous studies have evaluated the association between breastfeeding and ovarian cancer risk, with some indicating a significant reduction in risk while others reported no association. 7 , 40 , 41 Similarly, the inconsistent associations were observed between breastfeeding and endometrial cancer, 42 , 43 esophageal cancer, 44 , 45 gastric cancer, 46 , 47 colorectal cancer, 10 , 48 pancreatic cancer, 49 , 50 and lung cancer. 11 , 17 , 51 This may be attributable to variations in the study population (e.g., race, age, region), study methodology (e.g., statistical analysis methods, covariates adjusted), and cancer characteristics (e.g., anatomic subsite, histologic type, aggressiveness). In this study, the modifying effects of menopausal status were observed in the relationships between breastfeeding and colon-rectal cancer, uterine cancer, esophageal cancer, and laryngeal cancer. The potential protective effects of breastfeeding behavior against colon-rectal cancer and uterine cancer were more pronounced in premenopausal women compared to postmenopausal women, which was in line with reports from previous studies to some extent. For instance, a systematic review and meta-analysis found breastfeeding women had a lower risk of premenopausal breast cancer but not of postmenopausal breast cancer. 52 Siskind et al. found an association between breastfeeding and a reduced risk of ovarian cancer, but only before menopause. 53 A pooled analysis from the international lung cancer consortium demonstrated a statistically significant association between breastfeeding history and lung cancer risk, exclusively in premenopausal women, where the inverse relationship was also notably stronger ( P for interaction = 0.04). 54 The potential explanation is that breastfeeding influences cancer risk primarily through hormonal changes, with premenopausal women being more sensitive to these fluctuations and thus more likely to benefit from breastfeeding. 55 Notably, more pronounced inverse associations were observed among postmenopausal women for oesophagus cancer and larynx cancer. However, these findings should be interpreted with great caution due to the extremely limited number of cancer cases, necessitating a longer follow-up period to validate their robustness. Restricted cubic spline model in our study demonstrated significant linear associations between total breastfeeding duration and gallbladder cancer and breast cancer, which were comparable to previous studies. The existing evidence of dose-response relationship of breastfeeding and breast cancer was inconsistent. 56 – 58 Sumitra et al. found that there was a strong dose-response relationship for longer durations of breastfeeding and reduced risks of breast cancer ( P for trend = 0.02) among older postmenopausal women. 57 A case-control study conducted among Sri Lankan women indicated that the reduction of breast cancer risk continued to increase up to the lifetime breastfeeding duration of 36–47 months and decreased thereafter. 58 With respect to gallbladder cancer, there was limited evidence for the dose-response relationship regarding duration of breastfeeding. In addition, we observed a linear association between breastfeeding duration and thyroid cancer ( P for nonlinear > 0.05) although the overall association was borderline non-significant ( P for overall > 0.05). Our findings were consistent with a previous dose-response meta-analysis that revealed a significant linear relationship between breastfeeding duration and risk of thyroid cancer, especially in cohort studies. 35 Strengths and limitations of this study This study has several strengths. Firstly, to our knowledge, this study is the first in China to systematically examine the association of breastfeeding with all site-specific cancers, which could facilitate the exploration of less prevalent cancers and mitigate publication bias. Secondly, based on a large-scale prospective cohort derived from CanSPUC in Hunan Province, we were able to investigate the relationship between breastfeeding and maternal cancers within a representative provincial population, thereby contributing to the scientific evidence available from China and East Asia. Finally, we conducted a comprehensive statistical analysis, including a restricted cubic spline analysis to evaluate the dose-response relationship between breastfeeding and cancer, as well as subgroup and sensitivity analyses to ensure the robustness and reliability of the primary findings. This study also has limitations. Firstly, while this cohort provides robust socioeconomic and health data, it lacks detailed reproductive histories (including parity, age at first/last birth) and dietary measurements. Although we have adjusted for some available confounders like smoking and BMI, the absence of these variables may lead to residual confounding. Future studies incorporating reproductive calendars and nutritional assessments would help clarify these relationships. Secondly, the relatively short follow-up period resulted in a small number of cases for certain sub-specific cancers, which affected the statistical power and led to unstable results. Continued follow-up of the cohort will yield updated data, which we will analyze and present in future reports. Finally, despite the adequate sample size, the study’s confinement to a single province may limit the generalizability of the findings, which should therefore be interpreted with caution. Additional studies on diverse provinces and regions are necessary in the future. Implications and recommendations This study mainly assessed the association between breastfeeding behaviors and the subsequent risk of 24 types of maternal cancer among parous Chinese women. The observed complex findings provide a more comprehensive insights into the prevention and control of cancer. In this study, breastfeeding appears to be associated with a reduced risk of developing cancer in general, as well as the two most common female cancers (breast and thyroid), suggesting that breastfeeding has overall beneficial effects on women. The potential adverse effects on gallbladder cancer should be further elucidated and compared with other large prospective studies in the future. Based on the overall benefits of breastfeeding, there are several inspirations and recommendations for the prevention and control of cancer. Firstly, academic researchers and scientists could consider incorporating breastfeeding into broader cancer prevention recommendations, extending beyond just breast cancer. Guidelines for preventing specific cancers, such as thyroid cancer, may also benefit from including breastfeeding as a key recommendation. Secondly, as a critical role in enhancing women’s health, governments are able to improve policies and programs that advocate for breastfeeding support. Finally, individuals can prevent their cancer risks by actively engaging in self-management practices related to breastfeeding, such as seeking education on proper techniques, maintaining a balanced diet during lactation, and accessing social support networks to navigate challenges. Our study participants were drawn from the Urban Cancer Screening Program in China, a population profoundly shaped by the nation’s unique One-Child Policy (1979–2015), which resulted in over half of urban women having only one child. 59 , 60 This historical context creates a distinctive research setting where near-universal single-child status minimizes parity-related confounding—a persistent challenge in Western cohorts with wider parity variation. Although we lack individual parity data for stratified analysis, the policy-induced homogeneity in reproductive behavior ensures that breastfeeding effects are less likely to be distorted by multiparity interactions. These findings hold significant relevance for contemporary China, where delayed childbearing and low fertility persist, 61 and they provide unique insights into cancer prevention in populations with constrained parity variability. Conclusions In the large-scale population-based cohort study, we found that breastfeeding behaviors were associated with lower risk of breast cancer and thyroid cancer, and increased risk of gallbladder cancer. Besides, significant linear associations were suggested concerning breast cancer and gallbladder cancer. We also provided novel evidence of a more pronounced protective effect of breastfeeding behavior against two common cancers, including colorectal cancer and uterine cancer, in premenopausal women. These findings will benefit policy-making and intervention design in cancer prevention and suggest that the underlying biological mechanisms of breastfeeding related to cancer need to be revealed urgently. Declarations Funding declaration This study was supported by the Hunan Provincial Health High-Level Talent Scientific Research Project (grant number: R2023117), Natural Science Foundation of Hunan Province of China (grant number: 2024JJ9147; 2023JJ40408; 2022JJ40248), Hunan Provincial Health Scientific Research Project (grant number: 202102080033; 202212054721), Hunan Provincial Science and Technology Department (grant number: 2023ZJ1120 and 2022SK2050), Changsha Municipal Natural Science Foundation (grant number: kq2403127). Contributors WW and SY secured funding for this work. ZL and WW were joint first authors, and conceived, designed, and performed the work. XL, KX, YZ, ZS, YH, HX, CL, SC, SW, JG, SZ, and SY contributed to the data collection and extraction. ZL and SY revised the manuscript. All authors gave final approval and agree to be accountable for all aspects of work ensuring integrity and accuracy. Data Availability Statement The data will be available from the corresponding authors on request. Acknowledgment This research was supported by the Hunan Provincial Health High-Level Talent Scientific Research Project (grant number: R2023117), Natural Science Foundation of Hunan Province of China (grant number: 2024JJ9147; 2023JJ40408; 2022JJ40248), Hunan Provincial Health Scientific Research Project (grant number: 202102080033; 202212054721), Hunan Provincial Science and Technology Department (grant number: 2023ZJ1120 and 2022SK2050), Changsha Municipal Natural Science Foundation (grant number: kq2403127). We thank all the authors of the included studies. Declaration of interests We declare no competing interests. Ethics statement The study was approved by the Ethics Committee of National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College (number of IRB:CH-PRE-004). References Wu Z, Xia F, Lin R. Global burden of cancer and associated risk factors in 204 countries and territories, 1980-2021: a systematic analysis for the GBD 2021. Journal of Hematology & Oncology 2024;17(1):119. Bray F, Laversanne M, Sung H, Ferlay J, Siegel RL, Soerjomataram I, Jemal A. Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. Ca-a Cancer Journal for Clinicians 2024;74:229-63. Fan D, Xia Q, Lin D, Ma Y, Rao J, Liu L, Tang H, Xu T, Li P, Chen G, Zhou Z, Guo X, et al. Role of breastfeeding on maternal and childhood cancers: An umbrella review of meta-analyses. Journal of Global Health 2023;13. World Health Organization. Breastfeeding. 2024. https://www.who.int/health-topics/breastfeeding (accessed November 4 2024). Chen Y, Jiang P, Geng Y. The role of breastfeeding in breast cancer prevention: a literature review. Frontiers in Oncology 2023;13. Sangaramoorthy M, Hines LM, Torres-Mejia G, Phipps AI, Baumgartner KB, Wu AH, Koo J, Ingles SA, Slattery ML, John EM. A Pooled Analysis of Breastfeeding and Breast Cancer Risk by Hormone Receptor Status in Parous Hispanic Women. Epidemiology 2019;30:449-57. Babic A, Sasamoto N, Rosner BA, Tworoger SS, Jordan SJ, Risch HA, Harris HR, Rossing MA, Doherty JA, Fortner RT, Chang-Claude J, Goodman MT, et al. Association Between Breastfeeding and Ovarian Cancer Risk. Jama Oncology 2020;6. Zhan B, Liu X, Li F, Zhang D. Breastfeeding and the incidence of endometrial cancer: A meta-analysis. Oncotarget 2015;6:38398-409. Kotsopoulos J, Lubinski J, Salmena L, Lynch HT, Kim-Sing C, Foulkes WD, Ghadirian P, Neuhausen SL, Demsky R, Tung N, Ainsworth P, Senter L, et al. Breastfeeding and the risk of breast cancer in BRCA1 and BRCA2 mutation carriers. Breast Cancer Research 2012;14. Amitay EL, Niedermaier T, Alwers E, Chang-Claude J, Hoffmeister M, Brenner H. Reproductive Factors and Colorectal Cancer Risk: A Population-Based Case-Control Study. Jnci Cancer Spectrum 2022;6. Wilunda C, Sawada N, Yamaji T, Iwasaki M, Inoue M, Tsugane S. Reproductive Factors and Lung Cancer Risk among Never-Smoking Japanese Women with 21 Years of Follow-Up: A Cohort Study. Cancer Epidemiology Biomarkers & Prevention 2021;30:1185-92. Dong X, Du L, Luo Z, Xu Y, Wang C, Wang F, Cao W, Zhao L, Zheng Y, Zhu H, Xia C, Li J, et al. Combining fecal immunochemical testing and questionnaire-based risk assessment in selecting participants for colonoscopy screening in the Chinese National Colorectal Cancer Screening Programs: A population-based cohort study. PLoS medicine 2024;21. Zeng H, Chen W, Zheng R, Zhang S, Ji JS, Zou X, Xia C, Sun K, Yang Z, Li H, Wang N, Han R, et al. Changing cancer survival in China during 2003-15: a pooled analysis of 17 population-based cancer registries. Lancet Global Health 2018;6:E555-E67. Lin L, Hu Y, Lei F, Huang X, Zhang X, Sun T, Liu W, Li R, Zhang XJ, Cai J, She ZG, Wang G, et al. Cardiovascular health and cancer mortality: evidence from US NHANES and UK Biobank cohort studies. BMC Medicine 2024;22(1):368. Pan XF, He M, Yu C, Lv J, Guo Y, Bian Z, Yang L, Chen YP, Wu TC, Chen ZM, Pan A, Li LM, et al. Type 2 Diabetes and Risk of Incident Cancer in China: A Prospective Study Among 0.5 Million Chinese Adults. American Journal of Epidemiology 2018;187(7):1380-1391. Rask-Andersen M, Ivansson E, Höglund J, Ek WE, Karlsson T, Johansson Å. Adiposity and sex-specific cancer risk. Cancer Cell 2023;41(6):1186-1197. Yang Z, Wang F, Tan F, Cao W, Xu Y, Qin C, Yu Y, Zhao L, Wen Y, Wu Z, Zheng Y, Liu Y, et al. Menstrual factors, reproductive history, and risk of lung cancer: a multi-center population-based cohort study in Chinese females. Translational Lung Cancer Research 2021;10(10):3912-3928. Zheng Y, Dong X, Li J, Qin C, Xu Y, Wang F, Cao W, Xia C, Yu Y, Zhao L, Wu Z, Luo Z, et al. Use of Breast Cancer Risk Factors to Identify Risk-Adapted Starting Age of Screening in China. JAMA Network Open 2022;5(11):e2241441. Ye Z, An S, Gao Y, Xie E, Zhao X, Guo Z, Li Y, Shen N, Zheng J. Association between the triglyceride glucose index and in-hospital and 1-year mortality in patients with chronic kidney disease and coronary artery disease in the intensive care unit. Cardiovascular Diabetology 2023;22. Luo Z, Hou Y, Chen G, Wang F, Tu R, Dong X, Wang Y, Qiao D, Liu X, Liu X, Hou J, Mao Z, et al. Long-term effects of ambient air pollutants on suicidal ideation in China: The Henan Rural Cohort Study. Environmental Research 2020;188. Jin E, Kang H, Son M. Association between breastfeeding and breast, thyroid, and cervical cancer among Korean adult women based on the Korean Genome and Epidemiology Study: a cohort study. Korean Journal of Women Health Nursing 2021;27:368-78. Beral V, Bull D, Doll R, Peto R, Reeves G, La Vecchia C, Magnusson C, Miller T, Peterson B, Pike M, Thomas D, van Leeuwen F, et al. Breast cancer and breastfeeding: collaborative reanalysis of individual data from 47 epidemiological studies in 30 countries, including 50 302 women with breast cancer and 96 973 women without the disease. Lancet 2002;360:187-95. Tiruneh FN, Ntenda PAM. Duration of Breastfeeding and Risk Reduction of Breast Cancer among Mothers Who Have Ever Breastfed: A Case-Control Study Conducted in Bahir Dar, Ethiopia. Breast Journal 2024;2024:1987378. Yeo W, Yuen LW, Tsoi KK, Chan EY, Kwok CC, Soong I, Ng TY, Chiu J, Chan M, Chan SW, Wong TT, Chan YH, et al. Modifiable Risk Factors Including Self-Perceived Stress for Breast Cancer in Hong Kong: A Case-Control Study of 10 757 Subject. Clinical Medicine Insights-Oncology 2025;19:11795549251314434. Stordal B. Breastfeeding reduces the risk of breast cancer: A call for action in high-income countries with low rates of breastfeeding. Cancer Medicine 2023;12(4):4616-4625. Ambrosone CB, Higgins MJ. Relationships between Breast Feeding and Breast Cancer Subtypes: Lessons Learned from Studies in Humans and in Mice. Cancer Research 2020;80:4871-77. Fortner RT, Sisti J, Chai B, Collins LC, Rosner B, Hankinson SE, Tamimi RM, Eliassen AH. Parity, breastfeeding, and breast cancer risk by hormone receptor status and molecular phenotype: results from the Nurses' Health Studies. Breast Cancer Research 2019;21. Andreotti G, Hou L, Gao YT, Brinton LA, Rashid A, Chen J, Shen MC, Wang BS, Han TQ, Zhang BH, Sakoda LC, Fraumeni JF, Jr., et al. Reproductive factors and risks of biliary tract cancers and stones: a population-based study in Shanghai, China. British Journal of Cancer 2010;102:1185-89. Makiuchi T, Sobue T, Kitamura T, Sawada N, Iwasaki M, Sasazuki S, Yamaji T, Shimazu T, Tsugane S. Reproductive factors and gallbladder/bile duct cancer: a population-based cohort study in Japan. European Journal of Cancer Prevention 2017;26:292-300. Mhatre S, Ben L, Sherliker P, Chatterjee N, Rajaraman P, Goel M, Patkar S, Ostwal V, Patil P, Shrikhande SV, Chitkara G, Badwe R, et al. Reproductive factors and gall-bladder cancer, and the effect of common genetic variants on these associations: a case-control study in India. International journal of epidemiology 2022;51:789-98. Shin A, Cho S, Abe SK, Islam MR, Rahman MS, Saito E, Kazmi SZ, Katagiri R, Merritt M, Choi J-Y, Shu X-O, Sawada N, et al. Association of female reproductive and hormonal factors with gallbladder cancer risk in Asia: A pooled analysis of the Asia Cohort Consortium. International journal of cancer 2024;155:240-50. Saranga Bharathi R, Singh R, Gupta R, Verma GR, Kalra N, Kiran K, Joshi K. Female sex hormone receptors in gallbladder cancer. Journal of gastrointestinal cancer 2015;46:143-8. Wang L, Yang M, Guo X, Yang Z, Liu S, Ji Y, Jin H. Estrogen-related receptor-α promotes gallbladder cancer development by enhancing the transcription of Nectin-4. Cancer Science 2020;111:1514-27. He J-l, Zhang C, Hu M-j, Wu H-b, Lu X-l, Hao J-h, Huang F. Reproductive and menstrual factors for papillary thyroid cancer risk: A case-control study in Chinese women. Cancer Epidemiology 2021;73. Yi X, Zhu J, Zhu X, Liu GJ, Wu L. Breastfeeding and thyroid cancer risk in women: A dose-response meta-analysis of epidemiological studies. Clinical Nutrition 2016;35:1039-46. Kim H, Kim KY, Baek JH, Jung J. Are pregnancy, parity, menstruation and breastfeeding risk factors for thyroid cancer? Results from the Korea National Health and Nutrition Examination Survey, 2010-2015. Clinical Endocrinology 2018;89(2):233-239. Cordina-Duverger E, Leux C, Neri M, Tcheandjieu C, Guizard AV, Schvartz C, Truong T, Guénel P. Hormonal and reproductive risk factors of papillary thyroid cancer: A population-based case-control study in France. Cancer Epidemiology 2017;48:78-84. Schubart JR, Eliassen AH, Schilling A, Goldenberg D. Reproductive Factors and Risk of Thyroid Cancer in Women: An Analysis in the Nurses' Health Study II. Womens Health Issues 2021;31:494-502. Derwahl M, Nicula D. Estrogen and its role in thyroid cancer. Endocrine-Related Cancer 2014;21:T273-T83. Gaitskell K, Green J, Pirie K, Barnes I, Hermon C, Reeves GK, Beral V, Million Women Study C. Histological subtypes of ovarian cancer associated with parity and breastfeeding in the prospective Million Women Study. International journal of cancer 2018;142:281-89. Tsilidis KK, Allen NE, Key TJ, Dossus L, Lukanova A, Bakken K, Lund E, Fournier A, Overvad K, Hansen L, Tjonneland A, Fedirko V, et al. Oral contraceptive use and reproductive factors and risk of ovarian cancer in the European Prospective Investigation into Cancer and Nutrition. British Journal of Cancer 2011;105:1436-42. Ma X, Zhao L-G, Sun J-W, Yang Y, Zheng J-L, Gao J, Xiang Y-B. Association between breastfeeding and risk of endometrial cancer: a meta-analysis of epidemiological studies. European Journal of Cancer Prevention 2018;27:144-51. Katagiri R, Iwasaki M, Abe SK, Islam MR, Rahman MS, Saito E, Merritt MA, Choi J-Y, Shin A, Sawada N, Tamakoshi A, Koh W-P, et al. Reproductive Factors and Endometrial Cancer Risk Among Women. JAMA network open 2023;6. Zhu Y, Yue D, Yuan B, Zhu L, Lu M. Reproductive factors are associated with oesophageal cancer risk: results from a meta-analysis of observational studies. European Journal of Cancer Prevention 2017;26:1-9. Green J, Roddam A, Pirie K, Kirichek O, Reeves G, Beral V, Million Women Study C. Reproductive factors and risk of oesophageal and gastric cancer in the Million Women Study cohort. British Journal of Cancer 2012;106:210-16. Freedman ND, Chow W-H, Gao Y-T, Shu X-O, Ji B-T, Yang G, Lubin JH, Li H-L, Rothman N, Zheng W, Abnet CC. Menstrual and reproductive factors and gastric cancer risk in a large prospective study of women. Gut 2007;56:1671-77. Inoue M, Ito LS, Tajima K, Yamamura Y, Kodera Y, Takezaki T, Hamajima N, Hirose K, Kuroishi T, Tominaga S. Height, weight, menstrual and reproductive factors and risk of gastric cancer among Japanese postmenopausal women: Analysis by subsite and histologic subtype. International journal of cancer 2002;97:833-38. Tsilidis KK, Allen NE, Key TJ, Bakken K, Lund E, Berrino F, Fournier A, Olsen A, Tjonneland A, Overvad K, Boutron-Ruault MC, Clavel-Chapelon F, et al. Oral contraceptives, reproductive history and risk of colorectal cancer in the European Prospective Investigation into Cancer and Nutrition. British Journal of Cancer 2010;103:1755-59. Andersson G, Borgquist S, Jirstrom K. Hormonal factors and pancreatic cancer risk in women: The Malmo Diet and Cancer Study. International journal of cancer 2018;143:52-62. Alvarez A, Borch KB, Rylander C. Reproductive Factors, Use of Exogenous Hormones, and Pancreatic Cancer Incidence: The Norwegian Women and Cancer Study. Clinical Epidemiology 2021;13:67-80. Elbasheer MMA, Bohrmann B, Chen Y, Lv J, Sun D, Wu X, Yang X, Avery D, Li L, Chen Z, Kartsonaki C, Chan KH, et al. Reproductive factors and risk of lung cancer among 300,000 Chinese female never-smokers: evidence from the China Kadoorie Biobank study. Bmc Cancer 2024;24. Martin RM, Middleton N, Gunnell D, Owen CG, Smith GD. Breast-feeding and cancer: The Boyd Orr cohort and a systematic review with meta-analysis. Jnci-Journal of the National Cancer Institute 2005;97:1446-57. Siskind V, Green A, Bain C, Purdie D. Breastfeeding, menopause, and epithelial ovarian cancer. Epidemiology (Cambridge, Mass.) 1997;8:188-91. Ben Khedher S, Neri M, Papadopoulos A, Christiani DC, Diao N, Harris CC, Olivo-Marston S, Schwartz AG, Cote M, Koushik A, Siemiatycki J, Landi MT, et al. Menstrual and reproductive factors and lung cancer risk: A pooled analysis from the international lung cancer consortium. International journal of cancer 2017;141:309-23. World Health Organization. Menopause. 2024. https://www.who.int/news-room/fact-sheets/detail/menopause (accessed November 4 2024). Unar-Munguia M, Torres-Mejia G, Arantxa Colchero M, Gonzalez de Cosio T. Breastfeeding Mode and Risk of Breast Cancer: A Dose-Response Meta-Analysis. Journal of Human Lactation 2017;33:422-34. Shantakumar S, Terry MB, Teitelbaum SL, Britton JA, Neugut AI, Gammon MD. Reproductive factors and breast cancer risk among older women. American journal of epidemiology 2006;163:S97-S97. De Silva M, Senarath U, Gunatilake M, Lokuhetty D. Prolonged breastfeeding reduces risk of breast cancer in Sri Lankan women: A case-control study. Cancer Epidemiology 2010;34:267-73. Hesketh T, Zhou X, Wang Y. The End of the One-Child Policy: Lasting Implications for China. JAMA 2015;314(24):2619-2620. Wang J, Zhang W, Wang X, Li C, Li J, Zhao Y, Chen L, Qi X, Qiao L, Da W, Liu L, Xu C, et al. Urban-Rural Differences in Bone Mineral Density and its Association with Reproductive and Menstrual Factors Among Older Women. Calcified Tissue International 2020;106(6):637-645. Wang Y, Fan H, Guo C. Trend and Factors of Population Fertility Changes From the Perspective of Economics and Education - China, 1949-2020. China CDC Weekly 2021;3(28):599-603. Additional Declarations No competing interests reported. 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CAO","email":"","orcid":"","institution":"Hunan Cancer Hospital/the Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University","correspondingAuthor":false,"prefix":"","firstName":"Shiyu","middleName":"","lastName":"CAO","suffix":""},{"id":446517539,"identity":"f3ab6cd1-8f7b-4c80-b67c-a14792c0c6d4","order_by":10,"name":"Shiyu WANG","email":"","orcid":"","institution":"Hunan Cancer Hospital/the Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University","correspondingAuthor":false,"prefix":"","firstName":"Shiyu","middleName":"","lastName":"WANG","suffix":""},{"id":446517540,"identity":"f529085b-fae1-4e2a-90bc-a69e9218a0f4","order_by":11,"name":"Jia GUO","email":"","orcid":"","institution":"Hunan Cancer Hospital/the Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University","correspondingAuthor":false,"prefix":"","firstName":"Jia","middleName":"","lastName":"GUO","suffix":""},{"id":446517541,"identity":"9c7d10ff-b512-4c10-8c8e-c5d34341255d","order_by":12,"name":"Senmao ZHANG","email":"","orcid":"","institution":"Hunan Cancer Hospital/the Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University","correspondingAuthor":false,"prefix":"","firstName":"Senmao","middleName":"","lastName":"ZHANG","suffix":""},{"id":446517542,"identity":"408c13be-ba35-488a-a478-1e6f1c10dd18","order_by":13,"name":"Shipeng YAN","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA80lEQVRIie3PIQvCQBTA8SeDrZyuOg7Uj3AymFj8LBPBNGRdQZNJzfsQhiU1TgZbmcx4waAIS5oEQTD4GGjz0CZ4f457F+4HdwAy2Y+mAMtH9DVRu9+QPGJ9dp3Fm/DiurtKQ59fj+6gBTqNt3BbCUjS61KPZWbTOy9NL+qAMXPcwjQRkMCxFMLCts83C1oc4b8SYiuFsYCkJ/OCZOjzJEMy/IBwh1EkNksnKpIQiRYIicFPFpKs7nMVD1FMjAmB9VRASqmDD7vvqiwNM0oG/YpOtMP+JiC1IB+4l+38RHCx4D0AqI6eRH/d0/YiIZPJZP/XAxvSUQvq9GnLAAAAAElFTkSuQmCC","orcid":"","institution":"Hunan Cancer Hospital/the Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University","correspondingAuthor":true,"prefix":"","firstName":"Shipeng","middleName":"","lastName":"YAN","suffix":""}],"badges":[],"createdAt":"2024-11-17 16:38:18","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5470880/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5470880/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":81506427,"identity":"c1785d16-5c5b-41a0-9437-db8c69f45a96","added_by":"auto","created_at":"2025-04-28 05:30:33","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":16319687,"visible":true,"origin":"","legend":"\u003cp\u003eRisk of developing overall cancer and its main site-specific cancers in relationship to breastfeeding behavior stratified by menopausal status.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-5470880/v1/1bcc0fb1b3ade727b86d37fc.png"},{"id":81506420,"identity":"0bc7d729-1318-47df-98e0-111d8d42fb65","added_by":"auto","created_at":"2025-04-28 05:30:32","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":4262695,"visible":true,"origin":"","legend":"\u003cp\u003eThe dose-response relationship of total breastfeeding duration with the risk of overall cancer and its main site-specific cancers.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-5470880/v1/b7db509bb58155948798cab8.png"},{"id":81506308,"identity":"593c308e-c379-4fe5-82f4-5a9793fde2c9","added_by":"auto","created_at":"2025-04-28 05:30:26","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1656542,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5470880/v1/2adf2b78-40b6-41b0-bc30-ceb1845a8955.pdf"},{"id":81506408,"identity":"efadcbc2-49fd-43e6-8e8b-471b3a6f9eb5","added_by":"auto","created_at":"2025-04-28 05:30:32","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":7721483,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementary.docx","url":"https://assets-eu.researchsquare.com/files/rs-5470880/v1/8997325c9e73665089a060c4.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Breastfeeding and subsequent risk of 24 types of maternal cancer: a cohort study of Chinese women","fulltext":[{"header":"Introduction","content":"\u003cp\u003eCancer represents a major global health challenge, with estimated 14.57% of total deaths and 8.8% of total disability-adjusted life years according to the Global Burden of Disease Study 2021.\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e The burden continues to grow, with projections suggesting 35\u0026nbsp;million new cases by 2050.\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e Beyond its direct health impacts, cancer creates significant societal and economic consequences, highlighting the urgent need for preventive strategies. While established risk factors like tobacco use and obesity contribute substantially,\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e identifying additional modifiable factors remains crucial for targeted prevention.\u003c/p\u003e \u003cp\u003eBreastfeeding, as a major modifiable reproductive factor, plays a critical role in the health of both mother and infant.\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e Recognized worldwide as the best nutritional source for newborn infants, breastfeeding is extensively practiced, especially in low- and middle-income countries.\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e During motherhood, breastfeeding aids in the reduction of postpartum weight gain through increased caloric expenditure, promotes the release of the hormone oxytocin, facilitates the reduction of uterine size to pre-pregnancy levels, and decreases uterine bleeding. Additionally, the long-term benefits of breastfeeding may contribute to a decreased risk of certain cancers in mothers.\u003csup\u003e\u003cspan additionalcitationids=\"CR6 CR7\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e However, aside from breast cancer, the relationship between breastfeeding and the risk of other maternal cancers remains insufficient and controversial. These inconsistencies may stem from variations in populations, methodologies, tumor locations, histological types and invasiveness.\u003csup\u003e\u003cspan additionalcitationids=\"CR10\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e Furthermore, there is a paucity of comprehensive studies investigating the relationship between breastfeeding and all cancer subtypes within the same population, which could facilitate the exploration of less prevalent cancers and mitigate publication bias. Therefore, additional research is essential to explore the effect of breastfeeding on the risk of different site-specific cancers, particularly in sufficiently large cohorts.\u003c/p\u003e \u003cp\u003eIn this study, we concentrated on two breastfeeding behaviors including history of breastfeeding and total breastfeeding duration. Based on a large-scale prospective cohort study conducted in Hunan province, our main objective was to investigate the association of breastfeeding behavior with subsequent risk of 24 types of maternal cancer. Additionally, to examine the dose-response relationships of the above associations.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design and population\u003c/h2\u003e \u003cp\u003eWe conducted a large-scale prospective cohort study under the framework of the Cancer Screening Program in Urban China (CanSPUC). CanSPUC is a non-profit national cancer screening program co-funded by the Chinese Ministry of Finance and the National Health Commission, launched in October 2012. The details of the CanSPUC have been presented in previously published articles.\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e In brief, the targeted population was residents aged 40\u0026ndash;75 years living in the selected communities, and the targeted cancer types were the five most prevalent cancers in urban China, including lung cancer, liver cancer, female breast cancer, gastric cancer and colorectal cancer. All eligible participants who provided written informed consent were interviewed by trained staff to complete a questionnaire that included demographic characteristics, lifestyle factors, personal/family history of diseases, and menstrual and reproductive factors (for women only). Based on an established risk scoring system, participants at high risk for cancer were further invited to undergo clinical examinations for one or more cancer screenings. Finally, all participants who completed the questionnaire were followed up either passively or actively to collect information on their cancer incidence and mortality.\u003c/p\u003e \u003cp\u003eIn this study, we used data from CanSPUC conducted in Hunan Province between October 2012 and December 2021, covering a total of five cities (Changsha, Xiangtan, Yueyang, Zhuzhou, and Zhangjiajie). Altogether 319,592 eligible participants were enrolled, of whom 167,308 were females. According to the given exclusion criteria, 157,454 females with valid information were finally included in this study. The flow chart of the included participants in this study is shown in eFigure 1. The study was approved by the Ethics Committee of National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College (number of IRB:CH-PRE-004). The procedure of the study was conducted in accordance with the Declaration of Helsinki, and the informed consent was obtained from all participants.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eCohort follow-up and case identification\u003c/h3\u003e\n\u003cp\u003eFollow-up for each participant began at the end of the baseline questionnaire and ended with the first diagnosis of cancer, death, the last documented follow-up contact, or December 31, 2021, whichever came first. The system of our program was linked with Hunan Provincial cancer registration system and death surveillance system to access information on the incidence of cancer. The information was also cross-checked with the records of the provincial medical registration system from the Hunan Provincial Health Commission. All cancer cases were coded according to the International Classification standards (ICD-10) (see eTable 1) and further classified as 24 site-specific cancers.\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e In accordance with methodological recommendations from prior studies,\u003csup\u003e\u003cspan additionalcitationids=\"CR15\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e cancer subtypes with sufficient case numbers (\u0026ge;\u0026thinsp;200) were included in our primary analysis. Detailed results for rarer cancers (\u0026lt;\u0026thinsp;200 cases) have been moved to Supplementary Material to preserve full data accessibility and future meta-analyses.\u003c/p\u003e\n\u003ch3\u003eExposure assessment\u003c/h3\u003e\n\u003cp\u003eInformation on menstrual and reproductive factors was collected by self-reported questionnaire at baseline entry. Menstrual and reproductive factors include age at menarche (\u0026lt;\u0026thinsp;13, 13, 14, or \u0026gt;\u0026thinsp;14 years), menopause status (no, yes), surgeries on the reproductive system (no, yes), history of breastfeeding (no, yes), and total breastfeeding duration. Total breastfeeding duration was considered as both continuous and multi-categorical (0, 1\u0026ndash;6, 7\u0026ndash;12, or \u0026gt;\u0026thinsp;12 months).\u003c/p\u003e \u003cp\u003ePotential risk factors for cancer were selected based on experience and reports from previous studies. \u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e Marital status was classified as married or others (including unmarried, widowed, or divorced). Educational level was classified as low (elementary school or below), medium (junior or high school or equivalent), and high (college or above). Smoking status was defined as current (\u0026gt;\u0026thinsp;1 cigarette/day for at least 6 months), former (previously smoked and have quit for at least 6 months), and never smoking. Alcohol drinking status was classified as never and ever (current alcohol drinking and former alcohol drinking). Regular exercise (no, yes) was defined as an average of more than 3 times per week for more than 30 minutes per session. History of hypertension (no, yes) and diabetes (no, yes) referred to previous clinical diagnoses of hypertension and diabetes, respectively. Family history of cancer (no, yes) was defined as previous clinical diagnosis of cancer within participants\u0026rsquo; three generations. Body mass index (BMI) was calculated as weight in kilograms divided by the square of height in meters, and was further classified into four categories according to the Chinese standard: underweight (\u0026lt;\u0026thinsp;18.5 kg/m\u003csup\u003e2\u003c/sup\u003e), normal (18.5\u0026ndash;23.9 kg/m\u003csup\u003e2\u003c/sup\u003e), overweight (24.0-27.9 kg/m\u003csup\u003e2\u003c/sup\u003e) or obese (\u0026ge;\u0026thinsp;28.0 kg/m\u003csup\u003e2\u003c/sup\u003e).\u003c/p\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eDescriptive analyses were described as counts and proportions for categorical variables, and mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD) for continuous variables. Chi-square tests and t-tests were applied to compare the differences between groups. The hazard ratios (HRs) and 95% confidence intervals (CIs) of developing cancer in relationship to baseline breastfeeding behavior were evaluated using Cox proportional hazards models. Unadjusted model did not include any covariates; Age-adjusted model only adjusted for age at enrollment (continuous); Multivariate-adjusted model further adjusted for educational level (low, medium, high), marital status (married, others), smoking status (never, current, ever), alcohol drinking status (never, ever), regular exercise (no, yes), BMI (underweight, normal, overweight, obese), family history of cancer (no, yes), hypertension (no, yes), diabetes (no, yes), and age at menarche (\u0026lt;\u0026thinsp;13, 13, 14, \u0026gt;\u0026thinsp;14 years), and menopause status (no, yes).\u003c/p\u003e \u003cp\u003eFor the continuous variable (total breastfeeding duration), both the dose-response relationship and tests for non-linear associations were performed using restricted cubic spline models with three knots.\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e To examine effect modification, we conducted subgroup analyses for menopausal status. The associations were further investigated in multivariable models among premenopausal and postmenopausal females. Statistical differences between subgroups were investigated by including an interaction term of breastfeeding behaviors and menopausal status in the model.\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eA series of sensitivity analyses were additionally conducted. Considering the surgeries on the reproductive system, an important influencing factor of cancer incidence, was only collected in 2012\u0026ndash;2019, we further adjusted for surgeries on the reproductive system based on multivariate-adjusted model (2012\u0026ndash;2019). To evaluate the robustness of the main findings, we included nulliparous female participants into analysis, and took the history of breastfeeding and total breastfeeding duration as none/zero.\u003c/p\u003e \u003cp\u003eTests in this study were all two-sided and \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant. All statistical analyses were conducted using the R software, version 4.2.2.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eDuring a median follow-up of 4.81 years, 5,542 of 157,454 women were diagnosed with cancer in the cohort, with an incidence density of 82.67/10\u003csup\u003e5\u003c/sup\u003e person-years. Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e presents the baseline characteristics of the study population according to cancer status. Participants with a history of breastfeeding tended to be older, less educated, and more likely to be never-smokers and never-drinkers. They also had lower prevalence of family cancer history, but higher rates of hypertension and diabetes. Additionally, these participants exhibited later menarche age, were more frequently postmenopausal, had fewer reproductive system surgeries, and reported more physical activity.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDistributions of selected variables of the participants at baseline (2012\u0026ndash;2021).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePerson-years\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNon-breastfeeding\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;15641)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBreastfeeding\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;141813)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge at enrollment (year, Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e760401.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e56.08 (9.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e57.09 (9.76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducational level (n, %)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e161136.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2683 (17.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e33763 (23.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedium\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e509830.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11238 (71.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e93503 (65.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e89435.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1720 (11.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e14547 (10.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarital status (n, %)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e734382.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e15124 (96.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e136718 (96.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.069\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOthers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e26019.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e517 (3.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5095 (3.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmoking status (n, %)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNever\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e722837.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e13845 (88.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e135651 (95.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCurrent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e32440.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1681 (10.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5421 (3.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEver\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3874.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e107 (0.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e604 (0.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlcohol drinking status (n, %)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNever\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e706226.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e13314 (85.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e132868 (93.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEver\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e54175.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2327 (14.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8945 (6.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI (kg/m\u003csup\u003e2\u003c/sup\u003e, Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e22.99 (2.65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e22.96 (2.65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.250\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnderweight (\u0026lt;\u0026thinsp;18.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e19472.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e383 (2.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3610 (2.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.507\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNormal (18.5\u0026ndash;23.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e502670.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10473 (67.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e94229 (66.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOverweight (24.0-27.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e207692.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4161 (26.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e38132 (26.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObese (\u0026ge;\u0026thinsp;28.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e29834.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e607 (3.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5721 (4.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFamily history of cancer (n, %)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e578010.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8200 (52.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e109190 (77.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e182390.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7441 (47.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e32623 (23.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypertension (n, %)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e695834.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e14477 (92.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e129018 (91.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e64566.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1164 (7.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e12795 (9.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiabetes (n, %)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e741354.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e15358 (98.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e138647 (97.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e19047.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e283 (1.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3166 (2.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge at menarche (year, Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e13.70 (1.62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e13.90 (1.43)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e96891.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3516 (22.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e21085 (14.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e184815.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3373 (21.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e35188 (24.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e243614.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4387 (28.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e44095 (31.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e235080.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4365 (27.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e41445 (29.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMenopause status (n, %)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e267642.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5511 (35.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e44822 (31.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e492758.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10130 (64.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e96991 (68.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSurgeries on the reproductive system\u003csup\u003e*\u003c/sup\u003e (n, %)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e655753.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8758 (82.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e100845 (91.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e71180.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1823 (17.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9088 (8.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eExercise\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e477067.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11190 (71.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e87339 (61.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e283333.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4451 (28.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e54474 (38.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eAbbreviations: SD, standard deviation; BMI, body mass index.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003csup\u003e*\u003c/sup\u003e The information on female reproductive system surgery was only collected between 2012 and 2019.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and eTable 2 show the associations of breastfeeding history with cancer incidence in three models (unadjusted model, age-adjusted model, and multivariate-adjusted model). The history of breastfeeding was statistically significantly associated with lower risk of breast cancer in the three models (all \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). No statistically significant associations were observed between history of breastfeeding and other site-specific cancers.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eRisk of developing overall cancer and its main site-specific cancers in relationship to history of breastfeeding baseline total breastfeeding duration.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eHistory of breastfeeding\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCases (n\u0026thinsp;=\u0026thinsp;5542)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUnadjusted model\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAge-adjusted model\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eMultivariate-adjusted model\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHR (95%CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHR (95%CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eHR (95%CI)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eColon-rectum (C18-21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e527\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.04 (0.77\u0026ndash;1.41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.99 (0.73\u0026ndash;1.34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.04 (0.77\u0026ndash;1.40)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLung (C33-34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e739\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.05 (0.81\u0026ndash;1.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.99 (0.77\u0026ndash;1.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.07 (0.83\u0026ndash;1.39)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBreast (C50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e128\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.73 (0.61\u0026ndash;0.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.73 (0.61\u0026ndash;0.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.78 (0.65\u0026ndash;0.94)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCervix (C53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e375\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.10 (0.77\u0026ndash;1.58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.11 (0.77\u0026ndash;1.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.17 (0.81\u0026ndash;1.69)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUterus (C54-55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e222\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.14 (0.71\u0026ndash;1.84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.14 (0.70\u0026ndash;1.84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.14 (0.70\u0026ndash;1.85)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBrain (C70-72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e251\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.15 (0.73\u0026ndash;1.81)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.10 (0.70\u0026ndash;1.74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.14 (0.72\u0026ndash;1.80)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThyroid (C73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e425\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.81 (0.60\u0026ndash;1.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.83 (0.62\u0026ndash;1.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.92 (0.68\u0026ndash;1.26)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAll others (NA)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e363\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.17 (0.80\u0026ndash;1.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.14 (0.78\u0026ndash;1.66)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.19 (0.81\u0026ndash;1.76)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAll sites (C00-97, D32-33, D42-43, D45-47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e487\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5055\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.96 (0.87\u0026ndash;1.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.94 (0.85\u0026ndash;1.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.99 (0.90\u0026ndash;1.09)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eUnadjusted model: no covariates were controlled for.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eAge-adjusted model: only age at enrollment (continuous) was controlled for.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eMultivariate-adjusted model: age-adjusted model\u0026thinsp;+\u0026thinsp;educational level (low, medium, high), marital status (married, others), smoking status (never, current, ever), alcohol drinking status (never, ever), regular exercise (no, yes), BMI (underweight, normal, overweight, obese), family history of cancer (no, yes), hypertension (no, yes), diabetes (no, yes), age at menarche (\u0026lt;\u0026thinsp;13, 13, 14, \u0026gt;\u0026thinsp;14 years), and menopause status (no, yes).\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\u003cp\u003eAbbreviations: HR, hazard ratio; CI, confidence interval.\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e and eTable 3 present the associations of total breastfeeding duration (continuous and multi-categorical) with cancer incidence in three models. In the multivariate-adjusted model, the risk of gallbladder cancer increased with increasing months of total breastfeeding (\u003cem\u003eP\u003c/em\u003e-trend\u0026thinsp;=\u0026thinsp;0.039), with a 51% increase in risk for each additional 12 months of breastfeeding (HR\u0026thinsp;=\u0026thinsp;1.51, 95%CI: 1.12\u0026ndash;2.02). The risk of breast cancer decreased with increasing months of total breastfeeding (\u003cem\u003eP\u003c/em\u003e-trend\u0026thinsp;=\u0026thinsp;0.015), with a 15% reduction in risk for each additional 12 months of breastfeeding (HR\u0026thinsp;=\u0026thinsp;0.85, 95%CI: 0.76\u0026ndash;0.95). With respect to thyroid cancer, the risk decreased by 17% with each additional 12 months of breastfeeding (HR\u0026thinsp;=\u0026thinsp;0.83, 95% CI: 0.69\u0026ndash;0.99), although the trend was not statistically significant (\u003cem\u003eP\u003c/em\u003e-trend\u0026thinsp;=\u0026thinsp;0.107) in the multivariate-adjusted model. Similarly, the risk of overall cancer incidence decreased by 5% with each additional 12 months of breastfeeding (HR\u0026thinsp;=\u0026thinsp;0.95, 95% CI: 0.90\u0026ndash;0.99), although the trend was not statistically significant (\u003cem\u003eP\u003c/em\u003e-trend\u0026thinsp;=\u0026thinsp;0.225).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eRisk of developing overall cancer and its main site-specific cancers in relationship to baseline total breastfeeding duration.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSite-specific cancers\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTotal breastfeeding duration\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCases\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;5542)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eUnadjusted model\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAge-adjusted model\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMultivariate-adjusted model\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHR (95%CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHR (95%CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eHR (95%CI)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eColon-rectum (C18-21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eContinuous (per 12 months)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e574\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.97 (0.84\u0026ndash;1.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.84 (0.73\u0026ndash;0.98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.87 (0.75\u0026ndash;1.01)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMulti-categorical (month)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u0026ndash;6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.22 (0.85\u0026ndash;1.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.25 (0.87\u0026ndash;1.80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.25 (0.87\u0026ndash;1.80)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7\u0026ndash;12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e335\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.01 (0.75\u0026ndash;1.37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.99 (0.73\u0026ndash;1.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.03 (0.76\u0026ndash;1.41)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e113\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.03 (0.73\u0026ndash;1.45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.86 (0.61\u0026ndash;1.21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.92 (0.65\u0026ndash;1.30)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e for trend\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.647\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.079\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.216\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLung (C33-34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eContinuous (per 12 months)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e804\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.07 (0.95\u0026ndash;1.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.93 (0.83\u0026ndash;1.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.97 (0.86\u0026ndash;1.09)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMulti-categorical (month)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u0026ndash;6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.07 (0.78\u0026ndash;1.47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.09 (0.80\u0026ndash;1.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.13 (0.82\u0026ndash;1.54)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7\u0026ndash;12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e465\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.01 (0.78\u0026ndash;1.31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.99 (0.76\u0026ndash;1.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.07 (0.82\u0026ndash;1.39)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e177\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.15 (0.87\u0026ndash;1.53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.96 (0.73\u0026ndash;1.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.06 (0.79\u0026ndash;1.42)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e for trend\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.381\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.517\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.915\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBreast (C50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eContinuous (per 12 months)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1128\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.83 (0.74\u0026ndash;0.92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.82 (0.73\u0026ndash;0.92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.85 (0.76\u0026ndash;0.95)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMulti-categorical (month)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e128\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u0026ndash;6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e139\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.79 (0.62\u0026ndash;1.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.79 (0.62\u0026ndash;1.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.82 (0.64\u0026ndash;1.04)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7\u0026ndash;12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e654\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.73 (0.60\u0026ndash;0.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.73 (0.60\u0026ndash;0.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.78 (0.64\u0026ndash;0.94)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e207\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.70 (0.56\u0026ndash;0.87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.69 (0.55\u0026ndash;0.86)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.75 (0.60\u0026ndash;0.94)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e for trend\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.015\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCervix (C53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eContinuous (per 12 months)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e407\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.05 (0.89\u0026ndash;1.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.07 (0.90\u0026ndash;1.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.09 (0.91\u0026ndash;1.30)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMulti-categorical (month)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u0026ndash;6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.96 (0.61\u0026ndash;1.52)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.96 (0.60\u0026ndash;1.52)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.01 (0.64\u0026ndash;1.60)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7\u0026ndash;12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e246\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.10 (0.76\u0026ndash;1.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.10 (0.76\u0026ndash;1.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.17 (0.81\u0026ndash;1.71)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.19 (0.79\u0026ndash;1.78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.22 (0.81\u0026ndash;1.83)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.30 (0.86\u0026ndash;1.96)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e for trend\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.253\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.197\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.130\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUterus (C54-55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eContinuous (per 12 months)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e240\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.11 (0.90\u0026ndash;1.38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.11 (0.90\u0026ndash;1.38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.13 (0.90\u0026ndash;1.41)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMulti-categorical (month)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u0026ndash;6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.72 (0.37\u0026ndash;1.38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.72 (0.37\u0026ndash;1.38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.73 (0.38\u0026ndash;1.40)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7\u0026ndash;12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e156\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.22 (0.75\u0026ndash;1.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.22 (0.75\u0026ndash;1.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.23 (0.75\u0026ndash;2.01)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.14 (0.66\u0026ndash;1.96)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.14 (0.66\u0026ndash;1.96)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.16 (0.67\u0026ndash;2.01)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e for trend\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.218\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.222\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.215\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBrain (C70-72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eContinuous (per 12 months)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e271\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.14 (0.93\u0026ndash;1.39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.02 (0.84\u0026ndash;1.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.00 (0.82\u0026ndash;1.23)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMulti-categorical (month)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u0026ndash;6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.03 (0.58\u0026ndash;1.82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.05 (0.59\u0026ndash;1.85)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.08 (0.61\u0026ndash;1.92)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7\u0026ndash;12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e163\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.14 (0.71\u0026ndash;1.81)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.12 (0.70\u0026ndash;1.78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.16 (0.73\u0026ndash;1.86)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.26 (0.76\u0026ndash;2.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.09 (0.66\u0026ndash;1.81)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.09 (0.65\u0026ndash;1.84)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e for trend\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.287\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.712\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.743\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThyroid (C73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eContinuous (per 12 months)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e472\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.72 (0.61\u0026ndash;0.86)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.77 (0.65\u0026ndash;0.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.83 (0.69\u0026ndash;0.99)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMulti-categorical (month)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u0026ndash;6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.03 (0.71\u0026ndash;1.49)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.02 (0.70\u0026ndash;1.47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.07 (0.73\u0026ndash;1.55)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7\u0026ndash;12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e286\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.84 (0.61\u0026ndash;1.14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.84 (0.62\u0026ndash;1.14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.93 (0.68\u0026ndash;1.28)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.62 (0.43\u0026ndash;0.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.68 (0.47\u0026ndash;0.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.78 (0.53\u0026ndash;1.14)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e for trend\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.014\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.107\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAll others (NA)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eContinuous (per 12 months)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e392\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.15 (0.97\u0026ndash;1.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.04 (0.89\u0026ndash;1.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.05 (0.89\u0026ndash;1.24)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMulti-categorical (month)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u0026ndash;6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.93 (0.57\u0026ndash;1.52)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.95 (0.58\u0026ndash;1.55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.99 (0.60\u0026ndash;1.62)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7\u0026ndash;12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e243\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.20 (0.82\u0026ndash;1.76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.19 (0.81\u0026ndash;1.74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.25 (0.84\u0026ndash;1.86)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.24 (0.81\u0026ndash;1.89)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.10 (0.72\u0026ndash;1.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.15 (0.74\u0026ndash;1.77)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e for trend\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.146\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.462\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.371\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAll sites (C00-97, D32-33, D42-43, D45-47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eContinuous (per 12 months)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5542\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.99 (0.95\u0026ndash;1.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.93 (0.88\u0026ndash;0.97)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.95 (0.90\u0026ndash;0.99)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMulti-categorical (month)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e487\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u0026ndash;6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e666\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.98 (0.87\u0026ndash;1.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.99 (0.88\u0026ndash;1.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.02 (0.91\u0026ndash;1.15)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7\u0026ndash;12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3275\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.95 (0.86\u0026ndash;1.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.94 (0.85\u0026ndash;1.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.99 (0.90\u0026ndash;1.10)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1114\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.98 (0.88\u0026ndash;1.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.89 (0.80\u0026ndash;0.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.95 (0.85\u0026ndash;1.06)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e for trend\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.543\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.225\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eUnadjusted model: no covariates were controlled for.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eAge-adjusted model: only age at enrollment (continuous) was controlled for.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eMultivariate-adjusted model: Age-adjusted model\u0026thinsp;+\u0026thinsp;educational level (low, medium, high), marital status (married, others), smoking status (never, current, ever), alcohol drinking status (never, ever), regular exercise (no, yes), BMI (underweight, normal, overweight, obese), family history of cancer (no, yes), hypertension (no, yes), diabetes (no, yes), age at menarche (\u0026lt;\u0026thinsp;13, 13, 14, \u0026gt;\u0026thinsp;14 years), and menopause status (no, yes).\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eAbbreviations: HR, hazard ratio; CI, confidence interval.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and eTable 4 display the associations between breastfeeding behavior and cancer incidence stratified by menopausal status. The inverse associations of total breastfeeding duration with colon-rectum cancer (0.56 [0.35\u0026ndash;0.91] vs. 0.92 [0.79\u0026ndash;1.07], \u003cem\u003eP\u003c/em\u003e-interaction\u0026thinsp;=\u0026thinsp;0.028), and history of breastfeeding with uterus cancer (0.76 [0.38\u0026ndash;1.49] vs. 1.62 [0.79\u0026ndash;3.32]), \u003cem\u003eP\u003c/em\u003e-interaction\u0026thinsp;=\u0026thinsp;0.038), were more pronounced in premenopausal women compared with those in postmenopausal women. With respect to oesophagus cancer (6.01 [1.46\u0026ndash;24.70] vs. 0.79 [0.38\u0026ndash;1.65], \u003cem\u003eP\u003c/em\u003e-interaction\u0026thinsp;=\u0026thinsp;0.037) and larynx cancer (12.62 [2.69\u0026ndash;59.25] vs. 0.37 [0.11\u0026ndash;1.22], \u003cem\u003eP\u003c/em\u003e-interaction\u0026thinsp;=\u0026thinsp;0.002), stronger positive associations with total breastfeeding duration were observed in premenopausal women than those in postmenopausal women. Notably, the results on oesophagus cancer and larynx cancer should be treated cautiously because of the extremely low number of cancer cases.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and eFigure \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e illustrates the dose-response associations between total breastfeeding duration and the risks of overall cancer and site-specific cancers. Significant linear associations were suggested concerning gallbladder cancer (\u003cem\u003eP\u003c/em\u003e-overall\u0026thinsp;=\u0026thinsp;0.0302, \u003cem\u003eP\u003c/em\u003e-nonlinear\u0026thinsp;=\u0026thinsp;0.6558) and breast cancer (\u003cem\u003eP\u003c/em\u003e-overall\u0026thinsp;=\u0026thinsp;0.0175, \u003cem\u003eP\u003c/em\u003e-nonlinear\u0026thinsp;=\u0026thinsp;0.5544).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe results of a series of sensitivity analyses are presented in the Supplementary Material. First, the estimated effects of breastfeeding behavior on cancer incidence remained fairly robust after additionally adjusting for surgeries on the reproductive system. That was to say, the associations between total breastfeeding duration and gallbladder cancer (HR\u0026thinsp;=\u0026thinsp;1.66, 95%CI: 1.22\u0026ndash;2.25), breast cancer (HR\u0026thinsp;=\u0026thinsp;0.88, 95%CI: 0.79\u0026ndash;0.99), and thyroid cancer (HR\u0026thinsp;=\u0026thinsp;0.82, 95%CI: 0.68\u0026ndash;0.99) remained statistically significant (see eTable 5). In the sensitivity analyses for including nulliparous female participants into analysis, the breastfeeding behavior was still associated with higher risk of gallbladder cancer and lower risk of breast cancer and thyroid cancer (see eTable 6). Additionally, history of breastfeeding was associated with nasopharynx cancer (HR\u0026thinsp;=\u0026thinsp;0.45, 95%CI: 0.23\u0026ndash;0.87), and total breastfeeding duration was associated with overall cancer (HR\u0026thinsp;=\u0026thinsp;0.94, 95%CI: 0.90\u0026ndash;0.98).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eMain findings\u003c/h2\u003e \u003cp\u003eEvidence on the effect of breastfeeding on certain maternal cancers remains insufficient and controversial. To the best of our knowledge, this study is the first in China to systematically and comprehensively investigate the relationship between breastfeeding behaviors and all site-specific maternal cancers based on a large-scale population-based cohort, providing valuable evidence for the promotion of women\u0026rsquo;s health in China and Asia. In this prospective study that included 157,454 participants and 5,542 cancer cases, we discovered that the history of breastfeeding was statistically significantly associated with lower risk of breast cancer. In the multivariate-adjusted model, longer durations of total breastfeeding were associated with increased risk of gallbladder cancer and decreased risks of breast cancer, thyroid cancer, and overall cancer. The subgroup analyses according to menopausal status showed significant separations for colon-rectum cancer, uterus cancer, oesophagus cancer, and larynx cancer. In addition, significant linear associations were suggested concerning gallbladder cancer and breast cancer based on restricted cubic spline model. Our findings, derived from a relatively large population study, are highly pertinent to shaping public health policy and practices in China.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eInterpretation and comparison with previous studies\u003c/h3\u003e\n\u003cp\u003eThe observed association between breastfeeding and decreased risk of breast cancer was in line with previous studies.\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan additionalcitationids=\"CR22 CR23 CR24\" citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e In fact, the protective effects of breastfeeding against breast cancer have been widely acknowledged by the academic researchers, whereas the precise mechanism remains uncertain. A recent review indicated that the mechanism may include the reduction of DNA methylation abnormalities, remodeling of breast tissue, lowering of estrogen levels, and inhibition of cancer cells within the microenvironment through breastfeeding.\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e In addition, the beneficial effect of breastfeeding varied for different types of breast cancer.\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e For example, findings from the Nurses\u0026rsquo; Health Studies revealed that breastfeeding was solely associated with a reduced risk of estrogen receptor negative disease, but not estrogen receptor positive disease.\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e The varying associations between breastfeeding and breast cancer subtypes warrant further investigation, which will be addressed in our subsequent studies.\u003c/p\u003e \u003cp\u003eThis study found that the risk of gallbladder cancer increased with increasing months of total breastfeeding (\u003cem\u003eP\u003c/em\u003e-trend\u0026thinsp;=\u0026thinsp;0.039), with a 51% increase in risk for each additional 12 months of breastfeeding (HR\u0026thinsp;=\u0026thinsp;1.51, 95%CI: 1.12\u0026ndash;2.02). Our results were inconsistent with the previous literature, which did not find an association between breastfeeding and gallbladder cancer.\u003csup\u003e\u003cspan additionalcitationids=\"CR29 CR30\" citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e For example, a case-control study in India discovered a positive but not statistically significant association of breastfeeding years with gallbladder cancer (OR\u0026thinsp;=\u0026thinsp;1.01, 95%CI: 0.98\u0026ndash;1.04).\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e According to a pooled analysis of the Asia Cohort Consortium across 4 countries (China, Japan, Korea, and Singapore), history of breastfeeding did not show a clear association with gallbladder cancer risk (pooled HR\u0026thinsp;=\u0026thinsp;0.98, 95%CI: 0.72\u0026ndash;1.34).\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e Despite the available literature, existing studies on the association between breastfeeding and gallbladder cancer remain limited, and further large-scale prospective studies are required to elucidate this relationship. The potential mechanism may involve breastfeeding-induced alterations in sex hormones, which are implicated in gallbladder carcinogenesis, as supported by in vitro data, animal models, and functional or physiological evidence. The abnormal expression of estrogen and progesterone receptors in gallbladder cancer tissues, vitro cell lines, and mouse models suggested a critical role for steroid hormones in the development of gallbladder carcinogenesis.\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eIn this study, the risk of thyroid cancer decreased by 17% with each additional 12 months of breastfeeding (HR\u0026thinsp;=\u0026thinsp;0.83, 95% CI: 0.69\u0026ndash;0.99) in the multivariate-adjusted model, which was consistent with most previous studies. \u003csup\u003e\u003cspan additionalcitationids=\"CR35 CR36\" citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e A case-control study among Chinese women found that shorter lifetime breastfeeding (\u0026lt;\u0026thinsp;6 months) significantly increased the risk of papillary thyroid cancer.\u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e A meta-analysis comprising nine reports revealed a significant inverse association between ever breastfeeding and thyroid cancer risk, as well as a significant linear relationship between breastfeeding duration and thyroid cancer risk.\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e Although most related studies have reported significant findings, a longitudinal study did not observe a statistically significant association regarding the months of breastfeeding and the risk of thyroid cancer.\u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e The possible protective effect of breastfeeding against thyroid cancer deserves further exploration, with several potential biological mechanisms already having been suggested. Breastfeeding may inhibit ovulation, thereby reducing endogenous estrogen exposure, which in turn could decrease the proliferation, migration, invasion, and recurrence of malignant thyroid cells.\u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eThis study also found a reduced risk of overall cancer with each additional 12 months of breastfeeding (HR\u0026thinsp;=\u0026thinsp;0.95, 95%CI: 0.90\u0026ndash;0.99). This suggested that breastfeeding in general may be feasible for reducing the risk of cancer among parous women, despite its potential adverse effect on gallbladder cancer. Regarding site-specific cancers, we did not discover statistically significant associations between breastfeeding and cancers other than breast, gallbladder, and thyroid cancer. In fact, previous studies have reported rather mixed results related to other cancers. For example, numerous studies have evaluated the association between breastfeeding and ovarian cancer risk, with some indicating a significant reduction in risk while others reported no association.\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e Similarly, the inconsistent associations were observed between breastfeeding and endometrial cancer,\u003csup\u003e\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e esophageal cancer,\u003csup\u003e\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e gastric cancer,\u003csup\u003e\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u003c/sup\u003e colorectal cancer,\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e pancreatic cancer,\u003csup\u003e\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u003c/sup\u003e and lung cancer.\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e\u003c/sup\u003e This may be attributable to variations in the study population (e.g., race, age, region), study methodology (e.g., statistical analysis methods, covariates adjusted), and cancer characteristics (e.g., anatomic subsite, histologic type, aggressiveness).\u003c/p\u003e \u003cp\u003eIn this study, the modifying effects of menopausal status were observed in the relationships between breastfeeding and colon-rectal cancer, uterine cancer, esophageal cancer, and laryngeal cancer. The potential protective effects of breastfeeding behavior against colon-rectal cancer and uterine cancer were more pronounced in premenopausal women compared to postmenopausal women, which was in line with reports from previous studies to some extent. For instance, a systematic review and meta-analysis found breastfeeding women had a lower risk of premenopausal breast cancer but not of postmenopausal breast cancer.\u003csup\u003e\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e\u003c/sup\u003e Siskind et al. found an association between breastfeeding and a reduced risk of ovarian cancer, but only before menopause.\u003csup\u003e\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e\u003c/sup\u003e A pooled analysis from the international lung cancer consortium demonstrated a statistically significant association between breastfeeding history and lung cancer risk, exclusively in premenopausal women, where the inverse relationship was also notably stronger (\u003cem\u003eP\u003c/em\u003e for interaction\u0026thinsp;=\u0026thinsp;0.04).\u003csup\u003e54\u003c/sup\u003e The potential explanation is that breastfeeding influences cancer risk primarily through hormonal changes, with premenopausal women being more sensitive to these fluctuations and thus more likely to benefit from breastfeeding.\u003csup\u003e\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e\u003c/sup\u003e Notably, more pronounced inverse associations were observed among postmenopausal women for oesophagus cancer and larynx cancer. However, these findings should be interpreted with great caution due to the extremely limited number of cancer cases, necessitating a longer follow-up period to validate their robustness.\u003c/p\u003e \u003cp\u003eRestricted cubic spline model in our study demonstrated significant linear associations between total breastfeeding duration and gallbladder cancer and breast cancer, which were comparable to previous studies. The existing evidence of dose-response relationship of breastfeeding and breast cancer was inconsistent.\u003csup\u003e\u003cspan additionalcitationids=\"CR57\" citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e\u003c/sup\u003e Sumitra et al. found that there was a strong dose-response relationship for longer durations of breastfeeding and reduced risks of breast cancer (\u003cem\u003eP\u003c/em\u003e for trend\u0026thinsp;=\u0026thinsp;0.02) among older postmenopausal women.\u003csup\u003e\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e\u003c/sup\u003e A case-control study conducted among Sri Lankan women indicated that the reduction of breast cancer risk continued to increase up to the lifetime breastfeeding duration of 36\u0026ndash;47 months and decreased thereafter.\u003csup\u003e\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e\u003c/sup\u003e With respect to gallbladder cancer, there was limited evidence for the dose-response relationship regarding duration of breastfeeding. In addition, we observed a linear association between breastfeeding duration and thyroid cancer (\u003cem\u003eP\u003c/em\u003e for nonlinear\u0026thinsp;\u0026gt;\u0026thinsp;0.05) although the overall association was borderline non-significant (\u003cem\u003eP\u003c/em\u003e for overall\u0026thinsp;\u0026gt;\u0026thinsp;0.05). Our findings were consistent with a previous dose-response meta-analysis that revealed a significant linear relationship between breastfeeding duration and risk of thyroid cancer, especially in cohort studies.\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eStrengths and limitations of this study\u003c/h2\u003e \u003cp\u003eThis study has several strengths. Firstly, to our knowledge, this study is the first in China to systematically examine the association of breastfeeding with all site-specific cancers, which could facilitate the exploration of less prevalent cancers and mitigate publication bias. Secondly, based on a large-scale prospective cohort derived from CanSPUC in Hunan Province, we were able to investigate the relationship between breastfeeding and maternal cancers within a representative provincial population, thereby contributing to the scientific evidence available from China and East Asia. Finally, we conducted a comprehensive statistical analysis, including a restricted cubic spline analysis to evaluate the dose-response relationship between breastfeeding and cancer, as well as subgroup and sensitivity analyses to ensure the robustness and reliability of the primary findings.\u003c/p\u003e \u003cp\u003eThis study also has limitations. Firstly, while this cohort provides robust socioeconomic and health data, it lacks detailed reproductive histories (including parity, age at first/last birth) and dietary measurements. Although we have adjusted for some available confounders like smoking and BMI, the absence of these variables may lead to residual confounding. Future studies incorporating reproductive calendars and nutritional assessments would help clarify these relationships. Secondly, the relatively short follow-up period resulted in a small number of cases for certain sub-specific cancers, which affected the statistical power and led to unstable results. Continued follow-up of the cohort will yield updated data, which we will analyze and present in future reports. Finally, despite the adequate sample size, the study\u0026rsquo;s confinement to a single province may limit the generalizability of the findings, which should therefore be interpreted with caution. Additional studies on diverse provinces and regions are necessary in the future.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eImplications and recommendations\u003c/h2\u003e \u003cp\u003eThis study mainly assessed the association between breastfeeding behaviors and the subsequent risk of 24 types of maternal cancer among parous Chinese women. The observed complex findings provide a more comprehensive insights into the prevention and control of cancer. In this study, breastfeeding appears to be associated with a reduced risk of developing cancer in general, as well as the two most common female cancers (breast and thyroid), suggesting that breastfeeding has overall beneficial effects on women. The potential adverse effects on gallbladder cancer should be further elucidated and compared with other large prospective studies in the future.\u003c/p\u003e \u003cp\u003eBased on the overall benefits of breastfeeding, there are several inspirations and recommendations for the prevention and control of cancer. Firstly, academic researchers and scientists could consider incorporating breastfeeding into broader cancer prevention recommendations, extending beyond just breast cancer. Guidelines for preventing specific cancers, such as thyroid cancer, may also benefit from including breastfeeding as a key recommendation. Secondly, as a critical role in enhancing women\u0026rsquo;s health, governments are able to improve policies and programs that advocate for breastfeeding support. Finally, individuals can prevent their cancer risks by actively engaging in self-management practices related to breastfeeding, such as seeking education on proper techniques, maintaining a balanced diet during lactation, and accessing social support networks to navigate challenges.\u003c/p\u003e \u003cp\u003eOur study participants were drawn from the Urban Cancer Screening Program in China, a population profoundly shaped by the nation\u0026rsquo;s unique One-Child Policy (1979\u0026ndash;2015), which resulted in over half of urban women having only one child.\u003csup\u003e\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e, \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e\u003c/sup\u003e This historical context creates a distinctive research setting where near-universal single-child status minimizes parity-related confounding\u0026mdash;a persistent challenge in Western cohorts with wider parity variation. Although we lack individual parity data for stratified analysis, the policy-induced homogeneity in reproductive behavior ensures that breastfeeding effects are less likely to be distorted by multiparity interactions. These findings hold significant relevance for contemporary China, where delayed childbearing and low fertility persist,\u003csup\u003e\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e\u003c/sup\u003e and they provide unique insights into cancer prevention in populations with constrained parity variability.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusions","content":"\u003cp\u003eIn the large-scale population-based cohort study, we found that breastfeeding behaviors were associated with lower risk of breast cancer and thyroid cancer, and increased risk of gallbladder cancer. Besides, significant linear associations were suggested concerning breast cancer and gallbladder cancer. We also provided novel evidence of a more pronounced protective effect of breastfeeding behavior against two common cancers, including colorectal cancer and uterine cancer, in premenopausal women. These findings will benefit policy-making and intervention design in cancer prevention and suggest that the underlying biological mechanisms of breastfeeding related to cancer need to be revealed urgently.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding declaration\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported by the Hunan Provincial Health High-Level Talent Scientific Research Project (grant number: R2023117), Natural Science Foundation of Hunan Province of China (grant number: 2024JJ9147; 2023JJ40408; 2022JJ40248), Hunan Provincial Health Scientific Research Project (grant number: 202102080033; 202212054721), Hunan Provincial Science and Technology Department (grant number: 2023ZJ1120 and 2022SK2050), Changsha Municipal Natural Science Foundation (grant number: kq2403127).\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eContributors\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWW and SY secured funding for this work. ZL and WW were joint first authors, and conceived, designed, and performed the work. XL, KX, YZ, ZS, YH, HX, CL, SC, SW, JG, SZ, and SY contributed to the data collection and extraction. ZL and SY revised the manuscript. All authors gave final approval and agree to be accountable for all aspects of work ensuring integrity and accuracy.\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eData Availability Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data will be available from the corresponding authors on request.\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eAcknowledgment\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was supported by the Hunan Provincial Health High-Level Talent Scientific Research Project (grant number: R2023117), Natural Science Foundation of Hunan Province of China (grant number: 2024JJ9147; 2023JJ40408; 2022JJ40248), Hunan Provincial Health Scientific Research Project (grant number: 202102080033; 202212054721), Hunan Provincial Science and Technology Department (grant number: 2023ZJ1120 and 2022SK2050), Changsha Municipal Natural Science Foundation (grant number: kq2403127). We thank all the authors of the included studies.\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eDeclaration of interests\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe declare no competing interests.\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eEthics statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was approved by the Ethics Committee of National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College (number of IRB:CH-PRE-004).\u003cbr\u003e\u0026nbsp;\u003c/p\u003e\n"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eWu Z, Xia F, Lin R. Global burden of cancer and associated risk factors in 204 countries and territories, 1980-2021: a systematic analysis for the GBD 2021. Journal of Hematology \u0026amp; Oncology 2024;17(1):119.\u003c/li\u003e\n\u003cli\u003eBray F, Laversanne M, Sung H, Ferlay J, Siegel RL, Soerjomataram I, Jemal A. Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. Ca-a Cancer Journal for Clinicians 2024;74:229-63.\u003c/li\u003e\n\u003cli\u003eFan D, Xia Q, Lin D, Ma Y, Rao J, Liu L, Tang H, Xu T, Li P, Chen G, Zhou Z, Guo X, et al. Role of breastfeeding on maternal and childhood cancers: An umbrella review of meta-analyses. Journal of Global Health 2023;13.\u003c/li\u003e\n\u003cli\u003eWorld Health Organization. Breastfeeding. 2024. https://www.who.int/health-topics/breastfeeding (accessed November 4 2024).\u003c/li\u003e\n\u003cli\u003eChen Y, Jiang P, Geng Y. The role of breastfeeding in breast cancer prevention: a literature review. Frontiers in Oncology 2023;13.\u003c/li\u003e\n\u003cli\u003eSangaramoorthy M, Hines LM, Torres-Mejia G, Phipps AI, Baumgartner KB, Wu AH, Koo J, Ingles SA, Slattery ML, John EM. A Pooled Analysis of Breastfeeding and Breast Cancer Risk by Hormone Receptor Status in Parous Hispanic Women. Epidemiology 2019;30:449-57.\u003c/li\u003e\n\u003cli\u003eBabic A, Sasamoto N, Rosner BA, Tworoger SS, Jordan SJ, Risch HA, Harris HR, Rossing MA, Doherty JA, Fortner RT, Chang-Claude J, Goodman MT, et al. Association Between Breastfeeding and Ovarian Cancer Risk. Jama Oncology 2020;6.\u003c/li\u003e\n\u003cli\u003eZhan B, Liu X, Li F, Zhang D. Breastfeeding and the incidence of endometrial cancer: A meta-analysis. Oncotarget 2015;6:38398-409.\u003c/li\u003e\n\u003cli\u003eKotsopoulos J, Lubinski J, Salmena L, Lynch HT, Kim-Sing C, Foulkes WD, Ghadirian P, Neuhausen SL, Demsky R, Tung N, Ainsworth P, Senter L, et al. Breastfeeding and the risk of breast cancer in \u003cem\u003eBRCA1\u003c/em\u003e and \u003cem\u003eBRCA2\u003c/em\u003e mutation carriers. Breast Cancer Research 2012;14.\u003c/li\u003e\n\u003cli\u003eAmitay EL, Niedermaier T, Alwers E, Chang-Claude J, Hoffmeister M, Brenner H. Reproductive Factors and Colorectal Cancer Risk: A Population-Based Case-Control Study. Jnci Cancer Spectrum 2022;6.\u003c/li\u003e\n\u003cli\u003eWilunda C, Sawada N, Yamaji T, Iwasaki M, Inoue M, Tsugane S. Reproductive Factors and Lung Cancer Risk among Never-Smoking Japanese Women with 21 Years of Follow-Up: A Cohort Study. Cancer Epidemiology Biomarkers \u0026amp; Prevention 2021;30:1185-92.\u003c/li\u003e\n\u003cli\u003eDong X, Du L, Luo Z, Xu Y, Wang C, Wang F, Cao W, Zhao L, Zheng Y, Zhu H, Xia C, Li J, et al. Combining fecal immunochemical testing and questionnaire-based risk assessment in selecting participants for colonoscopy screening in the Chinese National Colorectal Cancer Screening Programs: A population-based cohort study. PLoS medicine 2024;21.\u003c/li\u003e\n\u003cli\u003eZeng H, Chen W, Zheng R, Zhang S, Ji JS, Zou X, Xia C, Sun K, Yang Z, Li H, Wang N, Han R, et al. Changing cancer survival in China during 2003-15: a pooled analysis of 17 population-based cancer registries. Lancet Global Health 2018;6:E555-E67.\u003c/li\u003e\n\u003cli\u003eLin L, Hu Y, Lei F, Huang X, Zhang X, Sun T, Liu W, Li R, Zhang XJ, Cai J, She ZG, Wang G, et al. Cardiovascular health and cancer mortality: evidence from US NHANES and UK Biobank cohort studies. BMC Medicine 2024;22(1):368.\u003c/li\u003e\n\u003cli\u003ePan XF, He M, Yu C, Lv J, Guo Y, Bian Z, Yang L, Chen YP, Wu TC, Chen ZM, Pan A, Li LM, et al. Type 2 Diabetes and Risk of Incident Cancer in China: A Prospective Study Among 0.5 Million Chinese Adults. American Journal of Epidemiology 2018;187(7):1380-1391. \u003c/li\u003e\n\u003cli\u003eRask-Andersen M, Ivansson E, H\u0026ouml;glund J, Ek WE, Karlsson T, Johansson \u0026Aring;. Adiposity and sex-specific cancer risk. Cancer Cell 2023;41(6):1186-1197.\u003c/li\u003e\n\u003cli\u003eYang Z, Wang F, Tan F, Cao W, Xu Y, Qin C, Yu Y, Zhao L, Wen Y, Wu Z, Zheng Y, Liu Y, et al. Menstrual factors, reproductive history, and risk of lung cancer: a multi-center population-based cohort study in Chinese females. Translational Lung Cancer Research 2021;10(10):3912-3928.\u003c/li\u003e\n\u003cli\u003eZheng Y, Dong X, Li J, Qin C, Xu Y, Wang F, Cao W, Xia C, Yu Y, Zhao L, Wu Z, Luo Z, et al. Use of Breast Cancer Risk Factors to Identify Risk-Adapted Starting Age of Screening in China. JAMA Network Open 2022;5(11):e2241441.\u003c/li\u003e\n\u003cli\u003eYe Z, An S, Gao Y, Xie E, Zhao X, Guo Z, Li Y, Shen N, Zheng J. Association between the triglyceride glucose index and in-hospital and 1-year mortality in patients with chronic kidney disease and coronary artery disease in the intensive care unit. Cardiovascular Diabetology 2023;22.\u003c/li\u003e\n\u003cli\u003eLuo Z, Hou Y, Chen G, Wang F, Tu R, Dong X, Wang Y, Qiao D, Liu X, Liu X, Hou J, Mao Z, et al. Long-term effects of ambient air pollutants on suicidal ideation in China: The Henan Rural Cohort Study. Environmental Research 2020;188.\u003c/li\u003e\n\u003cli\u003eJin E, Kang H, Son M. Association between breastfeeding and breast, thyroid, and cervical cancer among Korean adult women based on the Korean Genome and Epidemiology Study: a cohort study. Korean Journal of Women Health Nursing 2021;27:368-78.\u003c/li\u003e\n\u003cli\u003eBeral V, Bull D, Doll R, Peto R, Reeves G, La Vecchia C, Magnusson C, Miller T, Peterson B, Pike M, Thomas D, van Leeuwen F, et al. Breast cancer and breastfeeding: collaborative reanalysis of individual data from 47 epidemiological studies in 30 countries, including 50 302 women with breast cancer and 96 973 women without the disease. Lancet 2002;360:187-95.\u003c/li\u003e\n\u003cli\u003eTiruneh FN, Ntenda PAM. Duration of Breastfeeding and Risk Reduction of Breast Cancer among Mothers Who Have Ever Breastfed: A Case-Control Study Conducted in Bahir Dar, Ethiopia. Breast Journal 2024;2024:1987378.\u003c/li\u003e\n\u003cli\u003eYeo W, Yuen LW, Tsoi KK, Chan EY, Kwok CC, Soong I, Ng TY, Chiu J, Chan M, Chan SW, Wong TT, Chan YH, et al. Modifiable Risk Factors Including Self-Perceived Stress for Breast Cancer in Hong Kong: A Case-Control Study of 10 757 Subject. Clinical Medicine Insights-Oncology 2025;19:11795549251314434.\u003c/li\u003e\n\u003cli\u003eStordal B. Breastfeeding reduces the risk of breast cancer: A call for action in high-income countries with low rates of breastfeeding. Cancer Medicine 2023;12(4):4616-4625.\u003c/li\u003e\n\u003cli\u003eAmbrosone CB, Higgins MJ. Relationships between Breast Feeding and Breast Cancer Subtypes: Lessons Learned from Studies in Humans and in Mice. Cancer Research 2020;80:4871-77.\u003c/li\u003e\n\u003cli\u003eFortner RT, Sisti J, Chai B, Collins LC, Rosner B, Hankinson SE, Tamimi RM, Eliassen AH. Parity, breastfeeding, and breast cancer risk by hormone receptor status and molecular phenotype: results from the Nurses\u0026apos; Health Studies. Breast Cancer Research 2019;21.\u003c/li\u003e\n\u003cli\u003eAndreotti G, Hou L, Gao YT, Brinton LA, Rashid A, Chen J, Shen MC, Wang BS, Han TQ, Zhang BH, Sakoda LC, Fraumeni JF, Jr., et al. Reproductive factors and risks of biliary tract cancers and stones: a population-based study in Shanghai, China. British Journal of Cancer 2010;102:1185-89.\u003c/li\u003e\n\u003cli\u003eMakiuchi T, Sobue T, Kitamura T, Sawada N, Iwasaki M, Sasazuki S, Yamaji T, Shimazu T, Tsugane S. Reproductive factors and gallbladder/bile duct cancer: a population-based cohort study in Japan. European Journal of Cancer Prevention 2017;26:292-300.\u003c/li\u003e\n\u003cli\u003eMhatre S, Ben L, Sherliker P, Chatterjee N, Rajaraman P, Goel M, Patkar S, Ostwal V, Patil P, Shrikhande SV, Chitkara G, Badwe R, et al. Reproductive factors and gall-bladder cancer, and the effect of common genetic variants on these associations: a case-control study in India. International journal of epidemiology 2022;51:789-98.\u003c/li\u003e\n\u003cli\u003eShin A, Cho S, Abe SK, Islam MR, Rahman MS, Saito E, Kazmi SZ, Katagiri R, Merritt M, Choi J-Y, Shu X-O, Sawada N, et al. Association of female reproductive and hormonal factors with gallbladder cancer risk in Asia: A pooled analysis of the Asia Cohort Consortium. International journal of cancer 2024;155:240-50.\u003c/li\u003e\n\u003cli\u003eSaranga Bharathi R, Singh R, Gupta R, Verma GR, Kalra N, Kiran K, Joshi K. Female sex hormone receptors in gallbladder cancer. Journal of gastrointestinal cancer 2015;46:143-8.\u003c/li\u003e\n\u003cli\u003eWang L, Yang M, Guo X, Yang Z, Liu S, Ji Y, Jin H. Estrogen-related receptor-\u0026alpha; promotes gallbladder cancer development by enhancing the transcription of Nectin-4. Cancer Science 2020;111:1514-27.\u003c/li\u003e\n\u003cli\u003eHe J-l, Zhang C, Hu M-j, Wu H-b, Lu X-l, Hao J-h, Huang F. Reproductive and menstrual factors for papillary thyroid cancer risk: A case-control study in Chinese women. Cancer Epidemiology 2021;73.\u003c/li\u003e\n\u003cli\u003eYi X, Zhu J, Zhu X, Liu GJ, Wu L. Breastfeeding and thyroid cancer risk in women: A dose-response meta-analysis of epidemiological studies. Clinical Nutrition 2016;35:1039-46.\u003c/li\u003e\n\u003cli\u003eKim H, Kim KY, Baek JH, Jung J. Are pregnancy, parity, menstruation and breastfeeding risk factors for thyroid cancer? Results from the Korea National Health and Nutrition Examination Survey, 2010-2015. Clinical Endocrinology 2018;89(2):233-239.\u003c/li\u003e\n\u003cli\u003eCordina-Duverger E, Leux C, Neri M, Tcheandjieu C, Guizard AV, Schvartz C, Truong T, Gu\u0026eacute;nel P. Hormonal and reproductive risk factors of papillary thyroid cancer: A population-based case-control study in France. Cancer Epidemiology 2017;48:78-84.\u003c/li\u003e\n\u003cli\u003eSchubart JR, Eliassen AH, Schilling A, Goldenberg D. Reproductive Factors and Risk of Thyroid Cancer in Women: An Analysis in the Nurses\u0026apos; Health Study II. Womens Health Issues 2021;31:494-502.\u003c/li\u003e\n\u003cli\u003eDerwahl M, Nicula D. Estrogen and its role in thyroid cancer. Endocrine-Related Cancer 2014;21:T273-T83.\u003c/li\u003e\n\u003cli\u003eGaitskell K, Green J, Pirie K, Barnes I, Hermon C, Reeves GK, Beral V, Million Women Study C. Histological subtypes of ovarian cancer associated with parity and breastfeeding in the prospective Million Women Study. International journal of cancer 2018;142:281-89.\u003c/li\u003e\n\u003cli\u003eTsilidis KK, Allen NE, Key TJ, Dossus L, Lukanova A, Bakken K, Lund E, Fournier A, Overvad K, Hansen L, Tjonneland A, Fedirko V, et al. Oral contraceptive use and reproductive factors and risk of ovarian cancer in the European Prospective Investigation into Cancer and Nutrition. British Journal of Cancer 2011;105:1436-42.\u003c/li\u003e\n\u003cli\u003eMa X, Zhao L-G, Sun J-W, Yang Y, Zheng J-L, Gao J, Xiang Y-B. Association between breastfeeding and risk of endometrial cancer: a meta-analysis of epidemiological studies. European Journal of Cancer Prevention 2018;27:144-51.\u003c/li\u003e\n\u003cli\u003eKatagiri R, Iwasaki M, Abe SK, Islam MR, Rahman MS, Saito E, Merritt MA, Choi J-Y, Shin A, Sawada N, Tamakoshi A, Koh W-P, et al. Reproductive Factors and Endometrial Cancer Risk Among Women. JAMA network open 2023;6.\u003c/li\u003e\n\u003cli\u003eZhu Y, Yue D, Yuan B, Zhu L, Lu M. Reproductive factors are associated with oesophageal cancer risk: results from a meta-analysis of observational studies. European Journal of Cancer Prevention 2017;26:1-9.\u003c/li\u003e\n\u003cli\u003eGreen J, Roddam A, Pirie K, Kirichek O, Reeves G, Beral V, Million Women Study C. Reproductive factors and risk of oesophageal and gastric cancer in the Million Women Study cohort. British Journal of Cancer 2012;106:210-16.\u003c/li\u003e\n\u003cli\u003eFreedman ND, Chow W-H, Gao Y-T, Shu X-O, Ji B-T, Yang G, Lubin JH, Li H-L, Rothman N, Zheng W, Abnet CC. Menstrual and reproductive factors and gastric cancer risk in a large prospective study of women. Gut 2007;56:1671-77.\u003c/li\u003e\n\u003cli\u003eInoue M, Ito LS, Tajima K, Yamamura Y, Kodera Y, Takezaki T, Hamajima N, Hirose K, Kuroishi T, Tominaga S. Height, weight, menstrual and reproductive factors and risk of gastric cancer among Japanese postmenopausal women: Analysis by subsite and histologic subtype. International journal of cancer 2002;97:833-38.\u003c/li\u003e\n\u003cli\u003eTsilidis KK, Allen NE, Key TJ, Bakken K, Lund E, Berrino F, Fournier A, Olsen A, Tjonneland A, Overvad K, Boutron-Ruault MC, Clavel-Chapelon F, et al. Oral contraceptives, reproductive history and risk of colorectal cancer in the European Prospective Investigation into Cancer and Nutrition. British Journal of Cancer 2010;103:1755-59.\u003c/li\u003e\n\u003cli\u003eAndersson G, Borgquist S, Jirstrom K. Hormonal factors and pancreatic cancer risk in women: The Malmo Diet and Cancer Study. International journal of cancer 2018;143:52-62.\u003c/li\u003e\n\u003cli\u003eAlvarez A, Borch KB, Rylander C. Reproductive Factors, Use of Exogenous Hormones, and Pancreatic Cancer Incidence: The Norwegian Women and Cancer Study. Clinical Epidemiology 2021;13:67-80.\u003c/li\u003e\n\u003cli\u003eElbasheer MMA, Bohrmann B, Chen Y, Lv J, Sun D, Wu X, Yang X, Avery D, Li L, Chen Z, Kartsonaki C, Chan KH, et al. Reproductive factors and risk of lung cancer among 300,000 Chinese female never-smokers: evidence from the China Kadoorie Biobank study. Bmc Cancer 2024;24.\u003c/li\u003e\n\u003cli\u003eMartin RM, Middleton N, Gunnell D, Owen CG, Smith GD. Breast-feeding and cancer: The Boyd Orr cohort and a systematic review with meta-analysis. Jnci-Journal of the National Cancer Institute 2005;97:1446-57.\u003c/li\u003e\n\u003cli\u003eSiskind V, Green A, Bain C, Purdie D. Breastfeeding, menopause, and epithelial ovarian cancer. Epidemiology (Cambridge, Mass.) 1997;8:188-91.\u003c/li\u003e\n\u003cli\u003eBen Khedher S, Neri M, Papadopoulos A, Christiani DC, Diao N, Harris CC, Olivo-Marston S, Schwartz AG, Cote M, Koushik A, Siemiatycki J, Landi MT, et al. Menstrual and reproductive factors and lung cancer risk: A pooled analysis from the international lung cancer consortium. International journal of cancer 2017;141:309-23.\u003c/li\u003e\n\u003cli\u003eWorld Health Organization. Menopause. 2024. https://www.who.int/news-room/fact-sheets/detail/menopause (accessed November 4 2024).\u003c/li\u003e\n\u003cli\u003eUnar-Munguia M, Torres-Mejia G, Arantxa Colchero M, Gonzalez de Cosio T. Breastfeeding Mode and Risk of Breast Cancer: A Dose-Response Meta-Analysis. Journal of Human Lactation 2017;33:422-34.\u003c/li\u003e\n\u003cli\u003eShantakumar S, Terry MB, Teitelbaum SL, Britton JA, Neugut AI, Gammon MD. Reproductive factors and breast cancer risk among older women. American journal of epidemiology 2006;163:S97-S97.\u003c/li\u003e\n\u003cli\u003eDe Silva M, Senarath U, Gunatilake M, Lokuhetty D. Prolonged breastfeeding reduces risk of breast cancer in Sri Lankan women: A case-control study. Cancer Epidemiology 2010;34:267-73.\u003c/li\u003e\n\u003cli\u003eHesketh T, Zhou X, Wang Y. The End of the One-Child Policy: Lasting Implications for China. JAMA 2015;314(24):2619-2620.\u003c/li\u003e\n\u003cli\u003eWang J, Zhang W, Wang X, Li C, Li J, Zhao Y, Chen L, Qi X, Qiao L, Da W, Liu L, Xu C, et al. Urban-Rural Differences in Bone Mineral Density and its Association with Reproductive and Menstrual Factors Among Older Women. Calcified Tissue International 2020;106(6):637-645.\u003c/li\u003e\n\u003cli\u003eWang Y, Fan H, Guo C. Trend and Factors of Population Fertility Changes From the Perspective of Economics and Education - China, 1949-2020. China CDC Weekly 2021;3(28):599-603.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"nutrition-journal","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"nutj","sideBox":"Learn more about [Nutrition Journal](http://nutritionj.biomedcentral.com/)","snPcode":"12937","submissionUrl":"https://submission.nature.com/new-submission/12937/3","title":"Nutrition Journal","twitterHandle":"@NutrJournal","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Breastfeeding, maternal cancer, Chinese women, cohort study, preventive","lastPublishedDoi":"10.21203/rs.3.rs-5470880/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5470880/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eExisting epidemiological evidence on breastfeeding and cancer risks is inconsistent, and no studies have thoroughly examined the relationship between breastfeeding and each site-specific cancer in China. We aimed to investigate these associations among parous Chinese women.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eA total of 157,454 participants aged 40\u0026ndash;75 years from 2012 to 2021 were recruited. Cox proportional hazards model was applied to explore the association between breastfeeding behaviors and cancer risks by hazard ratios (HRs) and corresponding 95% confidence intervals (CIs).\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003e5,542 incident cancer cases were identified with a median follow-up of 4.81 years. The history of breastfeeding was statistically significantly associated with lower risk of breast cancer in the multivariate-adjusted model (HR\u0026thinsp;=\u0026thinsp;0.78, 95%CI: 0.65\u0026ndash;0.94). In addition, the risk of gallbladder cancer increased with increasing months of total breastfeeding (\u003cem\u003eP\u003c/em\u003e-trend\u0026thinsp;=\u0026thinsp;0.039), with a 51% increase in risk for each additional 12 months of breastfeeding (HR\u0026thinsp;=\u0026thinsp;1.51, 95%CI: 1.12\u0026ndash;2.02). The risk of breast cancer decreased with increasing months of total breastfeeding (\u003cem\u003eP\u003c/em\u003e-trend\u0026thinsp;=\u0026thinsp;0.015), with a 15% reduction in risk for each additional 12 months of breastfeeding (HR\u0026thinsp;=\u0026thinsp;0.85, 95%CI: 0.76\u0026ndash;0.95). The subgroup analyses according to menopausal status shows significant separations for colon-rectum cancer, uterus cancer, oesophagus cancer, and larynx cancer (all \u003cem\u003eP\u003c/em\u003e-interaction\u0026thinsp;\u0026lt;\u0026thinsp;0.05). In addition, significant linear associations were suggested concerning gallbladder cancer (\u003cem\u003eP\u003c/em\u003e-overall\u0026thinsp;=\u0026thinsp;0.0302, \u003cem\u003eP\u003c/em\u003e-nonlinear\u0026thinsp;=\u0026thinsp;0.6558) and breast cancer (\u003cem\u003eP\u003c/em\u003e-overall\u0026thinsp;=\u0026thinsp;0.0175, \u003cem\u003eP\u003c/em\u003e-nonlinear\u0026thinsp;=\u0026thinsp;0.5544).\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eThis study provides further support for the role of breastfeeding behavior in overall cancer and its 24 site-specific cancers.\u003c/p\u003e","manuscriptTitle":"Breastfeeding and subsequent risk of 24 types of maternal cancer: a cohort study of Chinese women","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-04-28 05:30:11","doi":"10.21203/rs.3.rs-5470880/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-06-04T16:05:42+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-05-13T03:19:33+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-05-12T23:22:36+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-04-28T08:46:04+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"188853486211275330163133076136331674215","date":"2025-04-27T23:36:10+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"165591431425469144442248806566358056595","date":"2025-04-24T20:21:55+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"65461793001019480509871125008613950736","date":"2025-04-22T18:16:31+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-04-22T17:19:28+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-04-21T15:47:23+00:00","index":"","fulltext":""},{"type":"submitted","content":"Nutrition Journal","date":"2025-04-14T15:10:51+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"nutrition-journal","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"nutj","sideBox":"Learn more about [Nutrition Journal](http://nutritionj.biomedcentral.com/)","snPcode":"12937","submissionUrl":"https://submission.nature.com/new-submission/12937/3","title":"Nutrition Journal","twitterHandle":"@NutrJournal","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"63a6a592-7716-4a78-ba5d-74ecdd09444c","owner":[],"postedDate":"April 28th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-13T14:54:27+00:00","versionOfRecord":[],"versionCreatedAt":"2025-04-28 05:30:11","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5470880","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5470880","identity":"rs-5470880","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}