Background:

Many studies suggested that menstrual and reproductive factors affected the gender disparity in liver carcinogenesis, but the results were inconsistent. Moreover, there are few studies in Asian populations. Therefore, our study was to explore the association of menstrual and reproductive factors on liver cancer risk in Chinese women.

Methods:

72,807 women were recruited in 1996 to 2000 and followed until the end of 2016 in Shanghai, China. Cox regression models were used to estimate HRs and 95% confidence intervals (CIs) for the association of menstrual and reproductive factors with liver cancer.

Results:

258 liver cancer cases were identified during 1,269,531 person-years of follow-up. In premenopausal and postmenopausal women, hormone replacement therapy (HRT) and injective contraceptives were positively associated with liver cancer risk respectively (HR, 1.23, 95% CI, 1.15–1.30; HR, 1.23, 95% CI, 1.17–1.30; HR, 1.07, 95% CI, 1.05–1.10; HR, 1.08, 95% CI, 1.05–1.11), while older age at menopause, longer reproductive period and fewer live births were associated with reduced risk, especially among postmenopausal women (Ptrend < 0.05). In addition, liver cancer risk was elevated in postmenopausal women who received hysterectomy (HR, 1.07; 95% CI, 1.04–1.11), oophorectomy (HR, 1.05; 95% CI, 1.01–1.10) or oral contraceptives (HR, 1.06; 95% CI, 1.03–1.08). No association was found between age at menarche and liver cancer risk. Similar results were observed when excluding participants with less than 2 follow-up years.

Conclusions:

The findings suggested that female sex hormones could play significant roles in liver carcinogenesis.

Impact:

Our study was the first population-based cohort to provide epidemiology evidence of menstrual and reproductive factors on liver cancer risk in Chinese women.

This article is featured in Highlights of This Issue, p. 1993

Primary liver cancer ranks as the sixth common cancer and the third main cause of cancer-related death with 905,677 incident cases and 830,180 deaths all over the world in 2020 (1). There has been a striking gender disparity that the incidence and mortality rates of men were two to three folds higher than of women in most countries (2). Moreover, longer survival times (3) and lower recurrence rates were also observed commonly in women rather than men (4). But the exact explanation for differences between men and women is still not clear. Some researchers argued that men have higher rates to expose to high-risk factors like alcohol abuse, cigarette smoking, and hepatitis B virus (HBV) and/or hepatitis C virus (HCV) infection than women (5), while other studies suggested that menstrual and reproductive factors may be also associated with the risk of liver cancer in women.

Estrogen and progesterone are the two main female sex hormones in the process of reproduction. A rodent model reported that ovariectomy promoted development of liver cancer and indicated a suppressive effect of endogenous ovarian hormones on hepatocellular tumorigenesis (6). Kai Zhang and colleagues found that the growth of HepG2 cells was inhibited by megestrol acetate, both in vitro and in vivo, which suggested progesterone as an inhibitor of liver cancer (7). As for estrogen, early animal experiments examined that estrogens have stimulating roles on inducing liver tumors chemically (8, 9) while others presented inverse effects (10–12).

The results of observational studies were inconsistent in the relationship between menstrual and reproductive factors and liver cancer risk in women. For example, the International Agency for Research on Cancer (IARC) indicated that oral contraceptives could increase the risk of hepatocellular carcinoma (HCC) without viral infections in 1999, and many case–control studies also reported that oral contraceptives were positively associated with liver cancer risk, especially in long-term users (13–15), while some cohort studies showed no evidence between oral contraceptives and liver cancer incidence (16–18). Some studies found that higher parity was associated with an increased liver cancer risk (19, 20), while others suggested inversely (21). Other factors like age at menarche and hormone replacement therapy (HRT) were not related to the risk of liver cancer (18, 22). Moreover, most of these findings were conducted in developed countries with low liver cancer incidence, and this needs to be further considered in studies especially from other geographic regions and/or higher-risk areas, such as China.

In this study, we evaluated the relationship between menstrual and reproductive factors and incident liver cancer in a population-based cohort study of Chinese women. We used some significant information from the Shanghai Women's Health Study, in which comprehensive details on female menstrual and reproductive factors were available, such as age at menarche and menopause, reproductive period, menopausal status, type of menopause, HRT, oral contraceptive, injective contraceptive and number of live births. The aim is to find more evidence about the effects of estrogen and progesterone on liver cancer development.

Study population

The Shanghai Women's Health Study (SWHS) recruited 74,940 women who were 40 to 70 years old and lived in urban Shanghai from December 1996 to May 2000 (23). The study design and rationale had been published in previous studies (24). Our trained interviewers interviewed each participant and completed a questionnaire including baseline demographic information, lifestyle characteristics, menstrual and reproductive histories. In the study, we excluded participants who followed the criteria including: (i) cancer in situ was diagnosed during follow-up (n = 135); (ii) there was no cancer type or diagnosis date collected when died from cancer (n = 244); (iii) diagnosis of cancer at baseline (n = 1,598); (iv) lost to follow-up after enrollment (n = 3); (v) unconfirmed cancer diagnosis (n = 67); (vi) participants who had missing data for the interesting covariates of interest were also excluded (n = 86; ref. 25). Finally, we retained 72,807 participants in this study and we obtained written informed consent from all these participants. This study was conducted in accordance with Declaration of Helsinki, and has been approved by the Renji Hospital Ethics Committee of Shanghai Jiao Tong University School of Medicine (KY2019-197).

Exposures and covariates

The information on menstrual and reproductive factors was collected including age at menarche (years, 6 categories: <14, 14, 15, 16, 17, ≥18), age at menopause (years, 4 categories: <45, 45–49, 50–54, ≥55), reproductive period [duration between age at menarche and age at menopause (26), years, 4 categories: <30, 30–34, 35–39, ≥40], menopausal status (yes/no), hysterectomy (yes/no), oophorectomy (yes/no), HRT (yes/no), oral contraceptives (yes/no), injective contraceptives (yes/no), and number of live births (4 categories: ≤1, 2, 3–4 and ≥5).

The following variables were selected as covariates: age at entry (continuous), BMI (kg/m2, continuous), physical activity (hours/week, continuous), calorie intake (kcal/day, continuous), education (4 categories: elementary school and below, middle school, high school, and college and above), family income (yuan per year, 4 categories: <10,000, 10,000–19,999, 20,000–29,999 and ≥30,000), occupation (4 categories: housewife, professional, clerical, manual workers), marital status (5 categories: never married, married, widowed, separated, divorced), smoking (we defined them as “ever smoked at least 1 cigarette/day for more than 6 months continuously”, yes/no), alcohol drinking (we defined them as “ever drank alcohol at least 3 times/week for more than 6 months continuously”, yes/no), tea drinking (we defined them as “ever drank tea at least 3 times/week for more than 6 months continuously”, yes/no), family history of liver cancer (yes/no), medical history of hepatitis (yes/no), cholelithiasis (yes/no), type 2 diabetes (yes/no), and high blood pressure (yes/no; ref. 27).

Follow-up and case ascertainment

We followed all participants until cancer occurrence every 3–4 years through the whole follow-up surveys (28). The records had been annually linked with databases of the Shanghai Cancer Registry, Shanghai Vital Statistics Registry, and Shanghai Resident Registry (29). In total, five follow-up surveys on outcomes had been conducted during the following years with the response rates of 99.7% (2000–2002), 98.7% (2002–2004), 94.9% (2004–2006), 92.3% (2007–2010), and 91.1% (2012–2017), respectively (23). All the diagnoses of liver cancer in our study were verified by home visits, medical reports from hospitals that participants ever lived, and reviewed medical charts by a couple of clinical and pathological experts (25). And cancers were coded by the International Classification of Disease, Ninth Revision (ICD-9), and liver cancer was defined as a primary malignant tumor of number 155 (23). In our study, we censored the follow-up information on 31 December 2016.

Statistical analyses

We divided and compared the whole cohort by liver cancer cases and non-cases, and we further compared liver cancer cases and noncases among premenopausal and postmenopausal women. Baseline characteristics were described as medians with quantile ranges for continuous variables and counts with proportions for categorical ones. We used the t test or Wilcoxon–Mann–Whitney test to compare continuous variables, and the χ2 or Fisher test for comparing categorical variables, based on the data characteristics.

The Cox proportional hazard regression models were used to evaluate the association between menstrual and reproductive factors and liver cancer incidence in premenopausal and postmenopausal women (30). We determined the follow-up time (years) as the underlying time metric. Estimation of person-years (PY) to the event was calculated using the time at baseline to an event (i.e., liver cancer occurrence) or right-censoring (i.e., death, loss to follow-up, or December 31, 2016), whichever occurred first. And we used Schoenfeld residual method to check the proportional hazards assumptions for menstrual and reproductive factors, and no evidence of a violation of these assumptions had been detected. HRs and 95% confidence intervals (CI) were then obtained from two following models: the age-adjusted model (model 1) and the multivariable-adjusted model (model 2). Age at entry was adjusted in Model 1. Model 2 further adjusted for BMI, physical activity, calorie intake, education, family income, occupation, marital status, smoking, alcohol drinking, tea drinking, family history of liver cancer, medical history of hepatitis, cholelithiasis, type 2 diabetes, and high blood pressure.

In addition to the overall analyses, we also carried out sensitivity analyses which excluded participants with less than 2 follow-up years in order to avoid the bias due to reverse causation in the cohort studies.

When two-sided P values were less than 0.05, the results were considered statistically significant. R software was used to conduct all the analyses (version 4.0.5).

Data availability

The data will be available on request pending approval by the scientific committee of the relevant institutes.

A total of 258 female participants were newly identified with liver cancer during about 1.27 million person-years of follow up (average = 17.44 years) started from the baseline survey to the end of 2016. The incidence density rate of liver cancer is 20.33 cases per 100,000 PYs, and the cumulative incidence proportion of liver cancer is 0.35% during the follow-up time. Baseline demographic and lifestyle characteristics of the study population were described in Table 1. Participants with liver cancer are older, have higher BMI, and have a family history of liver cancer, medical history of hepatitis, cholelithiasis, type 2 diabetes, high blood pressure than noncases; less possibility of liver cancer can be observed in women who have ever drunk tea; imbalanced differentials of education, occupation and family income can be found in noncases and liver cancer cases. After categorizing all the participants by menopausal status, we also found similar results in the above interesting factors between noncases and liver cancer cases, especially among postmenopausal women.

Table 1.

Baseline demographic and lifestyle characteristics of the study population (SWHS, 1996–2016).

Overall (n = 72,807)Premenopausal women (n = 37,252)Postmenopausal women (n = 35,555)
Liver cancer cases (n = 258)Non-cases (n = 72,549)PLiver cancer cases (n = 61)Non-cases (n = 37,191)PLiver cancer cases (n = 197)Non-cases (n = 35,358)P
Age at entry (years) 60.8 (14.7) 50.2 (16.4) <0.001 46.6 (5.2) 44.7 (5.3) <0.001 63.2 (8.1) 61.1 (10.6) <0.001 
BMI (kg/m224.6 (5.3) 23.7 (4.4) <0.001 23.1 (4.7) 23.1 (4.1) 0.394 25.2 (4.8) 24.4 (4.7) 0.007 
Physical activity (MET-hours/week) 102.7 (55.2) 100.5 (57.1) 0.937 103.0 (64.8) 99.3 (58.4) 0.829 102.2 (52.9) 101.7 (55.4) 0.986 
Calorie intake (kcal/day) 1,588.3 (474.4) 1,634.9 (495.4) 0.161 1,714.6 (566.1) 1,653.6 (491.6) 0.667 1,560.7 (460.1) 1,614.6 (498.8) 0.211 
Education (N, %)   <0.001   0.649   0.002 
 Elementary school and below 108 (41.9) 15,414 (21.2)  3 (4.9) 1,038 (2.8)  105 (53.3) 14,376 (40.7)  
 Middle school 65 (25.2) 27,046 (37.3)  27 (44.3) 18,693 (50.3)  38 (19.3) 8,353 (23.6)  
 High school 61 (23.6) 20,290 (28.0)  23 (37.7) 12,727 (34.2)  38 (19.3) 7,563 (21.4)  
 College and above 24 (9.3) 9,799 (13.5)  8 (13.1) 4,733 (12.7)  16 (8.1) 5,066 (14.3)  
Occupation (N, %)   0.033   0.731   0.011 
 Housewife 3 (1.2) 264 (0.4)  0 (0.0) 34 (0.1)  3 (1.5) 230 (0.7)  
 Professional 58 (22.5) 20,638 (28.4)  18 (29.5) 10,071 (27.1)  40 (20.3) 10,567 (29.9)  
 Clerical 59 (22.9) 15,057 (20.8)  16 (26.2) 8,879 (23.9)  43 (21.8) 6,178 (17.5)  
 Manual workers 138 (53.5) 36,590 (50.4)  27 (44.3) 18,207 (49.0)  111 (56.3) 18,383 (52.0)  
Family income (yuan/year)   0.002   0.029   0.104 
 <10,000 59 (22.9) 11,654 (16.1)  11 (18.0) 4,766 (12.8)  48 (24.4) 6,888 (19.5)  
 10,000- 95 (36.8) 27,742 (38.2)  20 (32.8) 14,434 (38.8)  75 (38.1) 13,308 (37.6)  
 20,000- 77 (29.8) 20,387 (28.1)  26 (42.6) 11,392 (30.6)  51 (25.9) 8,995 (25.4)  
 ≥30000 27 (10.5) 12,766 (17.6)  4 (6.6) 6,599 (17.7)  23 (11.7) 6,167 (17.4)  
Marital status (N, %)   0.138   0.972   0.878 
 Never married 1 (0.4) 620 (0.9)  0 (0.0) 415 (1.1)  1 (0.5) 205 (0.6)  
 Married 224 (86.8) 64,468 (88.9)  60 (98.4) 34,771 (93.5)  164 (83.2) 29,697 (84.0)  
 Widowed 29 (11.2) 5,330 (7.3)  0 (0.0) 622 (1.7)  29 (14.7) 4,708 (13.3)  
 Separated 2 (0.8) 791 (1.1)  0 (0.0) 479 (1.3)  2 (1.0) 312 (0.9)  
 Divorced 2 (0.8) 1,340 (1.8)  1 (1.6) 904 (2.4)  1 (0.5) 436 (1.2)  
Smoking status (yes) 11 (4.3) 2,006 (2.8) 0.203 1 (1.6) 534 (1.4) 0.587 10 (5.1) 1,472 (4.2) 0.645 
Alcohol drinking status (yes) 4 (1.6) 1,636 (2.3) 0.581 1 (1.6) 774 (2.1) 1.000 3 (1.5) 862 (2.4) 0.549 
Tea drinking status (yes) 58 (22.5) 21,725 (29.9) 0.011 14 (23.0) 12,857 (34.6) 0.076 44 (22.3) 8,868 (25.1) 0.421 
Family history of liver cancer (yes) 26 (10.1) 2,360 (3.3) <0.001 8 (13.1) 1,245 (3.3) <0.001 18 (9.1) 1,115 (3.2) <0.001 
History of hepatitis (yes) 37 (14.3) 1,835 (2.5) <0.001 15 (24.6) 825 (2.2) <0.001 22 (11.2) 1,010 (2.9) <0.001 
History of cholelithiasis (yes) 52 (20.2) 8,054 (11.1) <0.001 12 (19.7) 2,675 (7.2) <0.001 40 (20.3) 5,379 (15.2) 0.060 
History of diabetes (yes) 26 (10.1) 3,104 (4.3) <0.001 3 (4.9) 500 (1.3) 0.050 23 (11.7) 2,604 (7.4) 0.030 
History of high blood pressure (yes) 76 (29.5) 17,126 (23.6) 0.033 7 (11.5) 4,907 (13.2) 0.836 69 (35.0) 12,219 (34.6) 0.950 
Overall (n = 72,807)Premenopausal women (n = 37,252)Postmenopausal women (n = 35,555)
Liver cancer cases (n = 258)Non-cases (n = 72,549)PLiver cancer cases (n = 61)Non-cases (n = 37,191)PLiver cancer cases (n = 197)Non-cases (n = 35,358)P
Age at entry (years) 60.8 (14.7) 50.2 (16.4) <0.001 46.6 (5.2) 44.7 (5.3) <0.001 63.2 (8.1) 61.1 (10.6) <0.001 
BMI (kg/m224.6 (5.3) 23.7 (4.4) <0.001 23.1 (4.7) 23.1 (4.1) 0.394 25.2 (4.8) 24.4 (4.7) 0.007 
Physical activity (MET-hours/week) 102.7 (55.2) 100.5 (57.1) 0.937 103.0 (64.8) 99.3 (58.4) 0.829 102.2 (52.9) 101.7 (55.4) 0.986 
Calorie intake (kcal/day) 1,588.3 (474.4) 1,634.9 (495.4) 0.161 1,714.6 (566.1) 1,653.6 (491.6) 0.667 1,560.7 (460.1) 1,614.6 (498.8) 0.211 
Education (N, %)   <0.001   0.649   0.002 
 Elementary school and below 108 (41.9) 15,414 (21.2)  3 (4.9) 1,038 (2.8)  105 (53.3) 14,376 (40.7)  
 Middle school 65 (25.2) 27,046 (37.3)  27 (44.3) 18,693 (50.3)  38 (19.3) 8,353 (23.6)  
 High school 61 (23.6) 20,290 (28.0)  23 (37.7) 12,727 (34.2)  38 (19.3) 7,563 (21.4)  
 College and above 24 (9.3) 9,799 (13.5)  8 (13.1) 4,733 (12.7)  16 (8.1) 5,066 (14.3)  
Occupation (N, %)   0.033   0.731   0.011 
 Housewife 3 (1.2) 264 (0.4)  0 (0.0) 34 (0.1)  3 (1.5) 230 (0.7)  
 Professional 58 (22.5) 20,638 (28.4)  18 (29.5) 10,071 (27.1)  40 (20.3) 10,567 (29.9)  
 Clerical 59 (22.9) 15,057 (20.8)  16 (26.2) 8,879 (23.9)  43 (21.8) 6,178 (17.5)  
 Manual workers 138 (53.5) 36,590 (50.4)  27 (44.3) 18,207 (49.0)  111 (56.3) 18,383 (52.0)  
Family income (yuan/year)   0.002   0.029   0.104 
 <10,000 59 (22.9) 11,654 (16.1)  11 (18.0) 4,766 (12.8)  48 (24.4) 6,888 (19.5)  
 10,000- 95 (36.8) 27,742 (38.2)  20 (32.8) 14,434 (38.8)  75 (38.1) 13,308 (37.6)  
 20,000- 77 (29.8) 20,387 (28.1)  26 (42.6) 11,392 (30.6)  51 (25.9) 8,995 (25.4)  
 ≥30000 27 (10.5) 12,766 (17.6)  4 (6.6) 6,599 (17.7)  23 (11.7) 6,167 (17.4)  
Marital status (N, %)   0.138   0.972   0.878 
 Never married 1 (0.4) 620 (0.9)  0 (0.0) 415 (1.1)  1 (0.5) 205 (0.6)  
 Married 224 (86.8) 64,468 (88.9)  60 (98.4) 34,771 (93.5)  164 (83.2) 29,697 (84.0)  
 Widowed 29 (11.2) 5,330 (7.3)  0 (0.0) 622 (1.7)  29 (14.7) 4,708 (13.3)  
 Separated 2 (0.8) 791 (1.1)  0 (0.0) 479 (1.3)  2 (1.0) 312 (0.9)  
 Divorced 2 (0.8) 1,340 (1.8)  1 (1.6) 904 (2.4)  1 (0.5) 436 (1.2)  
Smoking status (yes) 11 (4.3) 2,006 (2.8) 0.203 1 (1.6) 534 (1.4) 0.587 10 (5.1) 1,472 (4.2) 0.645 
Alcohol drinking status (yes) 4 (1.6) 1,636 (2.3) 0.581 1 (1.6) 774 (2.1) 1.000 3 (1.5) 862 (2.4) 0.549 
Tea drinking status (yes) 58 (22.5) 21,725 (29.9) 0.011 14 (23.0) 12,857 (34.6) 0.076 44 (22.3) 8,868 (25.1) 0.421 
Family history of liver cancer (yes) 26 (10.1) 2,360 (3.3) <0.001 8 (13.1) 1,245 (3.3) <0.001 18 (9.1) 1,115 (3.2) <0.001 
History of hepatitis (yes) 37 (14.3) 1,835 (2.5) <0.001 15 (24.6) 825 (2.2) <0.001 22 (11.2) 1,010 (2.9) <0.001 
History of cholelithiasis (yes) 52 (20.2) 8,054 (11.1) <0.001 12 (19.7) 2,675 (7.2) <0.001 40 (20.3) 5,379 (15.2) 0.060 
History of diabetes (yes) 26 (10.1) 3,104 (4.3) <0.001 3 (4.9) 500 (1.3) 0.050 23 (11.7) 2,604 (7.4) 0.030 
History of high blood pressure (yes) 76 (29.5) 17,126 (23.6) 0.033 7 (11.5) 4,907 (13.2) 0.836 69 (35.0) 12,219 (34.6) 0.950 

Note: Values were median (quantile range) for continuous variables and count (proportion) for categorical item.

Abbreviations: BMI, body mass index; SWHS, Shanghai Women's Health Study.

Table 2 provided baseline information about menstrual and reproductive factors in the cohort. Women with liver cancer have younger menopause age, shorter reproductive period, higher rates of menopause and oophorectomy, lower rates of injective contraceptive use and larger number of live births than those without liver cancer; no significant difference in hysterectomy, HRT and oral contraceptive use. The same interesting factors had statistical significances when we observed liver cases and noncases among postmenopausal women, while only age at menarche is statistically significant among premenopausal women.

Table 2.

Menstrual and reproductive factors of the study population (SWHS, 1996–2016).

Overall (n = 72,807)Premenopausal women (n = 37,252)Postmenopausal women (n = 35,555)
Liver cancer cases (n = 258)Non-cases (n = 72,549)PLiver cancer cases (n = 61)Non-cases (n = 37,191)PLiver cancer cases (n = 197)Non-cases (n = 35,358)P
Premenopausal (n, %) 61 (23.6) 37,191 (51.3) <0.001 61 (100.0) 37,191 (100.0)     
Postmenopausal (n, %) 197 (76.4) 35,358 (48.7) <0.001    197 (100.0) 35,358 (100.0)  
Age at menarche (years) 15.0 (2.0) 15.0 (2.0) 0.001 15.0 (2.0) 15.0 (2.0) <0.001 15.0 (3.0) 15.0 (2.0) 0.016 
Age at menopause (years) 48.5 (4.4) 49.3 (4.7) 0.026    48.5 (4.4) 49.3 (4.7) 0.026 
Reproductive period (years) 33.2 (4.6) 33.9 (5.5) 0.004    33.2 (4.6) 33.9 (5.5) 0.004 
Hysterectomy (n, %)   0.068   1.000   1.000 
 Yes 20 (7.8) 3,670 (5.1)  0 (0.0) 8 (0.0)  20 (10.2) 3,662 (10.4)  
 No 238 (92.2) 68,879 (94.9)  61 (100.0) 37,183 (100.0)  177 (89.8) 31,696 (89.6)  
Oophorectomy (N, %)   0.017   0.657   0.324 
 Yes 18 (7.0) 2,821 (3.9)  2 (3.3) 639 (1.7)  16 (8.1) 2,182 (6.2)  
 No 240 (93.0) 69,728 (96.1)  59 (96.7) 36,552 (98.3)  181 (91.9) 33,176 (93.8)  
HRT (N, %)   0.583   1.000   0.312 
 Yes 7 (2.7) 2,568 (3.5)  2 (3.3) 1,066 (2.9)  5 (2.5) 1,502 (4.2)  
 No 251 (97.3) 69,981 (96.5)  59 (96.7) 36,125 (97.1)  192 (97.5) 33,856 (95.8)  
Oral contraceptives (N, %)   0.369   0.803   0.898 
 Yes 59 (22.9) 14,811 (20.4)  11 (18.0) 5,965 (16.0)  48 (24.4) 8,846 (25.0)  
 No 199 (77.1) 57,738 (79.6)  50 (82.0) 31,226 (84.0)  149 (75.6) 26,512 (75.0)  
Injective contraceptives (N, %)   <0.001   0.991   0.047 
 Yes 98 (38.0) 40,772 (56.2)  49 (80.3) 29,547 (79.4)  49 (24.9) 11,225 (31.7)  
 No 160 (62.0) 31,777 (43.8)  12 (19.7) 7,644 (20.6)  148 (75.1) 24,133 (68.3)  
Number of live births (N, %)   <0.001   0.311   0.001 
 0 7 (2.7) 2,367 (3.3)  3 (4.9) 1,163 (3.1)  4 (2.0) 1,204 (3.4)  
 1 84 (32.6) 39,919 (55.0)  49 (80.3) 32,179 (86.5)  35 (17.8) 7,740 (21.9)  
 2 57 (22.1) 15,301 (21.1)  9 (14.8) 3,584 (9.6)  48 (24.4) 11,717 (33.1)  
 3–4 91 (35.3) 11,912 (16.4)   264 (0.7)  91 (46.2) 11,648 (32.9)  
 5+ 19 (7.4) 3,050 (4.2)   1 (0.0)  19 (9.6) 3,049 (8.6)  
Overall (n = 72,807)Premenopausal women (n = 37,252)Postmenopausal women (n = 35,555)
Liver cancer cases (n = 258)Non-cases (n = 72,549)PLiver cancer cases (n = 61)Non-cases (n = 37,191)PLiver cancer cases (n = 197)Non-cases (n = 35,358)P
Premenopausal (n, %) 61 (23.6) 37,191 (51.3) <0.001 61 (100.0) 37,191 (100.0)     
Postmenopausal (n, %) 197 (76.4) 35,358 (48.7) <0.001    197 (100.0) 35,358 (100.0)  
Age at menarche (years) 15.0 (2.0) 15.0 (2.0) 0.001 15.0 (2.0) 15.0 (2.0) <0.001 15.0 (3.0) 15.0 (2.0) 0.016 
Age at menopause (years) 48.5 (4.4) 49.3 (4.7) 0.026    48.5 (4.4) 49.3 (4.7) 0.026 
Reproductive period (years) 33.2 (4.6) 33.9 (5.5) 0.004    33.2 (4.6) 33.9 (5.5) 0.004 
Hysterectomy (n, %)   0.068   1.000   1.000 
 Yes 20 (7.8) 3,670 (5.1)  0 (0.0) 8 (0.0)  20 (10.2) 3,662 (10.4)  
 No 238 (92.2) 68,879 (94.9)  61 (100.0) 37,183 (100.0)  177 (89.8) 31,696 (89.6)  
Oophorectomy (N, %)   0.017   0.657   0.324 
 Yes 18 (7.0) 2,821 (3.9)  2 (3.3) 639 (1.7)  16 (8.1) 2,182 (6.2)  
 No 240 (93.0) 69,728 (96.1)  59 (96.7) 36,552 (98.3)  181 (91.9) 33,176 (93.8)  
HRT (N, %)   0.583   1.000   0.312 
 Yes 7 (2.7) 2,568 (3.5)  2 (3.3) 1,066 (2.9)  5 (2.5) 1,502 (4.2)  
 No 251 (97.3) 69,981 (96.5)  59 (96.7) 36,125 (97.1)  192 (97.5) 33,856 (95.8)  
Oral contraceptives (N, %)   0.369   0.803   0.898 
 Yes 59 (22.9) 14,811 (20.4)  11 (18.0) 5,965 (16.0)  48 (24.4) 8,846 (25.0)  
 No 199 (77.1) 57,738 (79.6)  50 (82.0) 31,226 (84.0)  149 (75.6) 26,512 (75.0)  
Injective contraceptives (N, %)   <0.001   0.991   0.047 
 Yes 98 (38.0) 40,772 (56.2)  49 (80.3) 29,547 (79.4)  49 (24.9) 11,225 (31.7)  
 No 160 (62.0) 31,777 (43.8)  12 (19.7) 7,644 (20.6)  148 (75.1) 24,133 (68.3)  
Number of live births (N, %)   <0.001   0.311   0.001 
 0 7 (2.7) 2,367 (3.3)  3 (4.9) 1,163 (3.1)  4 (2.0) 1,204 (3.4)  
 1 84 (32.6) 39,919 (55.0)  49 (80.3) 32,179 (86.5)  35 (17.8) 7,740 (21.9)  
 2 57 (22.1) 15,301 (21.1)  9 (14.8) 3,584 (9.6)  48 (24.4) 11,717 (33.1)  
 3–4 91 (35.3) 11,912 (16.4)   264 (0.7)  91 (46.2) 11,648 (32.9)  
 5+ 19 (7.4) 3,050 (4.2)   1 (0.0)  19 (9.6) 3,049 (8.6)  

Note: Values were median (quantile range) for continuous variables and count (proportion) for categorical item.

Abbreviations: BMI, body mass index; SWHS, Shanghai Women's Health Study.

Table 3 showed the age-adjusted and multivariable-adjusted HRs and 95% CIs of liver cancer for age at menarche, oophorectomy, HRT, oral contraceptives, injective contraceptives and number of live births in premenopausal women. There was a linear trend (Ptrend < 0.001) for age at menarche to increase liver cancer risk in Model 1, which disappeared after multivariable adjustment. Model 1 and 2 both suggested that HRT (age-adjusted HR, 1.19; 95% CI, 1.12–1.26; multivariable-adjusted HR, 1.23; 95% CI, 1.15–1.30) and injective contraceptives (age-adjusted HR, 1.08; 95% CI, 1.05–1.10; multivariable-adjusted HR, 1.07; 95% CI, 1.05–1.10) were associated with an increased risk of liver cancer, and number of live births had a negative association with liver cancer risk in premenopausal women (age-adjusted HR, 0.85; 95% CI, 0.82–0.88; multivariable-adjusted HR, 0.81; 95% CI, 0.78–0.84). No significant results were found for oophorectomy, and oral contraceptives with liver cancer risk.

Table 3.

Adjusted HRs and 95% CIs of liver cancer for menstrual and reproductive factors among premenopausal women (SWHS, 1996–2016).

CasesPYsHR (95% CI)aHR (95% CI)b
Age at menarche 
 <14 11 164,305.3 1.00 [reference] 1.00 [reference] 
 14 18 151,864.9 1.03 (1.00–1.06) 1.01 (0.99–1.05) 
 15 15 147,956.1 1.06 (1.03–1.09) 1.03 (1.00–1.06) 
 16 115,926.1 1.04 (1.01–1.07) 1.02 (0.98–1.05) 
 17 56,482.9 1.06 (1.02–1.10) 1.02 (0.98–1.07) 
 ≥18 33,417.9 1.08 (1.03–1.14) 1.02 (0.97–1.08) 
Ptrend   <0.001 0.209 
Oophorectomy 
 No 59 658,438.6 1.00 [reference] 1.00 [reference] 
 Yes 11,514.6 1.01 (0.93–1.09) 1.05 (0.97–1.13) 
HRT 
 No 59 650,811.7 1.00 [reference] 1.00 [reference] 
 Yes 19,141.5 1.19 (1.12–1.26) 1.23 (1.15–1.30) 
Oral contraceptives 
 No 50 562,453.8 1.00 [reference] 1.00 [reference] 
 Yes 11 107,499.3 1.00 (0.97–1.02) 0.99 (0.97–1.02) 
Injective contraceptives 
 No 12 137,646.1 1.00 [reference] 1.00 [reference] 
 Yes 49 532,307.1 1.08 (1.05–1.10) 1.07 (1.05–1.10) 
Number of live births 
 ≤1 52 600,563.6 1.00 [reference] 1.00 [reference] 
 >1 693,89.5 0.85 (0.82–0.88) 0.81 (0.78–0.84) 
CasesPYsHR (95% CI)aHR (95% CI)b
Age at menarche 
 <14 11 164,305.3 1.00 [reference] 1.00 [reference] 
 14 18 151,864.9 1.03 (1.00–1.06) 1.01 (0.99–1.05) 
 15 15 147,956.1 1.06 (1.03–1.09) 1.03 (1.00–1.06) 
 16 115,926.1 1.04 (1.01–1.07) 1.02 (0.98–1.05) 
 17 56,482.9 1.06 (1.02–1.10) 1.02 (0.98–1.07) 
 ≥18 33,417.9 1.08 (1.03–1.14) 1.02 (0.97–1.08) 
Ptrend   <0.001 0.209 
Oophorectomy 
 No 59 658,438.6 1.00 [reference] 1.00 [reference] 
 Yes 11,514.6 1.01 (0.93–1.09) 1.05 (0.97–1.13) 
HRT 
 No 59 650,811.7 1.00 [reference] 1.00 [reference] 
 Yes 19,141.5 1.19 (1.12–1.26) 1.23 (1.15–1.30) 
Oral contraceptives 
 No 50 562,453.8 1.00 [reference] 1.00 [reference] 
 Yes 11 107,499.3 1.00 (0.97–1.02) 0.99 (0.97–1.02) 
Injective contraceptives 
 No 12 137,646.1 1.00 [reference] 1.00 [reference] 
 Yes 49 532,307.1 1.08 (1.05–1.10) 1.07 (1.05–1.10) 
Number of live births 
 ≤1 52 600,563.6 1.00 [reference] 1.00 [reference] 
 >1 693,89.5 0.85 (0.82–0.88) 0.81 (0.78–0.84) 

aModel 1 was adjusted by age at entry.

bModel 2 was adjusted by age at entry, BMI, physical activity, calorie intake, education, family income, occupation, marital status, smoking, alcohol drinking, tea drinking, family history of liver cancer, medical history of hepatitis, cholelithiasis, diabetes, and high blood pressure.

The associations between age at menarche, age at menopause, reproductive period, hysterectomy, oophorectomy, HRT, oral contraceptives, injective contraceptives, number of live births and the risk of liver cancer in postmenopausal women were presented in Table 4. A linear trend (Ptrend < 0.001) was observed between age at menarche and an increased risk of liver cancer in Model 1, which disappeared in Model 2. Models 1 and 2 consistently suggested that hysterectomy (age-adjusted HR = 1.10; 95% CI, 1.06–1.14; multivariable adjusted HR, 1.07; 95% CI, 1.04–1.11), oophorectomy (age-adjusted HR, 1.05; 95% CI, 1.01–1.10; multivariable-adjusted HR, 1.05; 95% CI, 1.01–1.10), HRT (age-adjusted HR, 1.15; 95% CI, 1.09–1.21; multivariable-adjusted, HR, 1.23, 95% CI, 1.17–1.30), oral contraceptive (age-adjusted HR, 1.05; 95% CI, 1.02–1.07; multivariable-adjusted HR, 1.06; 95% CI, 1.03–1.08) and injective contraceptive (age-adjusted HR, 1.06; 95% CI, 1.04–1.09; multivariable-adjusted HR, 1.08; 95% CI, 1.05–1.11) were associated with increasing risk of liver cancer, and age at menopause (age-adjusted Ptrend < 0.001; multivariable-adjusted Ptrend = 0.009), reproductive period (age-adjusted Ptrend < 0.001; multivariable-adjusted Ptrend = 0.031) and number of live births had significant linear trends with decreasing risk of liver cancer (Ptrend < 0.001) in postmenopausal women.

Table 4.

Adjusted HRs and 95% CIs of liver cancer for menstrual and reproductive factors among postmenopausal women (SWHS, 1996–2016).

CasesPYsHR (95% CI)aHR (95% CI)b
Age at menarche 
 <14 29 119,559.6 1.00 [reference] 1.00 [reference] 
 14 31 112,413.1 0.99 (0.95–1.02) 0.97 (0.94–1.00) 
 15 45 124,579.7 1.01 (0.98–1.05) 0.98 (0.95–1.01) 
 16 36 112,635.5 0.99 (0.95–1.02) 0.94 (0.91–0.98) 
 17 33 71,478.9 1.04 (1.00–1.08) 0.98 (0.94–1.02) 
 ≥18 23 58,910.7 1.05 (1.01–1.09) 0.99 (0.95–1.03) 
Ptrend   0.015 0.322 
Age at menopause 
 <45 29 99,088.5 1.00 [reference] 1.00 [reference] 
 45–49 109 263,274.8 0.93 (0.90–0.96) 0.95 (0.92–0.98) 
 50–54 50 213,687.3 0.91 (0.88–0.94) 0.95 (0.92–0.98) 
 ≥55 23,526.8 0.93 (0.87–0.98) 0.95 (0.90–1.01) 
Ptrend   <0.001 0.009 
Reproductive period 
 <30 41 112,639.7 1.00 [reference] 1.00 [reference] 
 30–34 104 251,856.2 0.94 (0.91–0.96) 0.96 (0.93–0.99) 
 35–39 47 201,826.1 0.92 (0.89–0.95) 0.96 (0.93–0.99) 
 ≥40 33,255.4 0.89 (0.84–0.93) 0.95 (0.90–1.00) 
Ptrend   <0.001 0.031 
Hysterectomy 
 No 177 536,211.7 1.00 [reference] 1.00 [reference] 
 Yes 20 63,365.8 1.10 (1.06–1.14) 1.07 (1.04–1.11) 
Oophorectomy 
 No 181 561,579.8 1.00 [reference] 1.00 [reference] 
 Yes 16 37,997.6 1.05 (1.01–1.10) 1.05 (1.01–1.10) 
HRT 
 No 192 572,786.6 1.00 [reference] 1.00 [reference] 
 Yes 26,790.8 1.15 (1.09–1.21) 1.23 (1.17–1.30) 
Oral contraceptives 
 No 149 446,320.2 1.00 [reference] 1.00 [reference] 
 Yes 48 153,257.3 1.05 (1.02–1.07) 1.06 (1.03–1.08) 
Injective contraceptives 
 No 148 403,233.6 1.00 [reference] 1.00 [reference] 
 Yes 49 196,343.8 1.06 (1.04–1.09) 1.08 (1.05–1.11) 
Number of live births 
 ≤1 39 156,222.7 1.00 [reference] 1.00 [reference] 
 2 48 203,819.4 0.82 (0.80–0.84) 0.82 (0.79–0.84) 
 3–4 91 192,218.6 0.87 (0.84–0.89) 0.78 (0.76–0.81) 
 5+ 19 47,316.7 0.97 (0.92–1.01) 0.83 (0.79–0.87) 
Ptrend   <0.001 <0.001 
CasesPYsHR (95% CI)aHR (95% CI)b
Age at menarche 
 <14 29 119,559.6 1.00 [reference] 1.00 [reference] 
 14 31 112,413.1 0.99 (0.95–1.02) 0.97 (0.94–1.00) 
 15 45 124,579.7 1.01 (0.98–1.05) 0.98 (0.95–1.01) 
 16 36 112,635.5 0.99 (0.95–1.02) 0.94 (0.91–0.98) 
 17 33 71,478.9 1.04 (1.00–1.08) 0.98 (0.94–1.02) 
 ≥18 23 58,910.7 1.05 (1.01–1.09) 0.99 (0.95–1.03) 
Ptrend   0.015 0.322 
Age at menopause 
 <45 29 99,088.5 1.00 [reference] 1.00 [reference] 
 45–49 109 263,274.8 0.93 (0.90–0.96) 0.95 (0.92–0.98) 
 50–54 50 213,687.3 0.91 (0.88–0.94) 0.95 (0.92–0.98) 
 ≥55 23,526.8 0.93 (0.87–0.98) 0.95 (0.90–1.01) 
Ptrend   <0.001 0.009 
Reproductive period 
 <30 41 112,639.7 1.00 [reference] 1.00 [reference] 
 30–34 104 251,856.2 0.94 (0.91–0.96) 0.96 (0.93–0.99) 
 35–39 47 201,826.1 0.92 (0.89–0.95) 0.96 (0.93–0.99) 
 ≥40 33,255.4 0.89 (0.84–0.93) 0.95 (0.90–1.00) 
Ptrend   <0.001 0.031 
Hysterectomy 
 No 177 536,211.7 1.00 [reference] 1.00 [reference] 
 Yes 20 63,365.8 1.10 (1.06–1.14) 1.07 (1.04–1.11) 
Oophorectomy 
 No 181 561,579.8 1.00 [reference] 1.00 [reference] 
 Yes 16 37,997.6 1.05 (1.01–1.10) 1.05 (1.01–1.10) 
HRT 
 No 192 572,786.6 1.00 [reference] 1.00 [reference] 
 Yes 26,790.8 1.15 (1.09–1.21) 1.23 (1.17–1.30) 
Oral contraceptives 
 No 149 446,320.2 1.00 [reference] 1.00 [reference] 
 Yes 48 153,257.3 1.05 (1.02–1.07) 1.06 (1.03–1.08) 
Injective contraceptives 
 No 148 403,233.6 1.00 [reference] 1.00 [reference] 
 Yes 49 196,343.8 1.06 (1.04–1.09) 1.08 (1.05–1.11) 
Number of live births 
 ≤1 39 156,222.7 1.00 [reference] 1.00 [reference] 
 2 48 203,819.4 0.82 (0.80–0.84) 0.82 (0.79–0.84) 
 3–4 91 192,218.6 0.87 (0.84–0.89) 0.78 (0.76–0.81) 
 5+ 19 47,316.7 0.97 (0.92–1.01) 0.83 (0.79–0.87) 
Ptrend   <0.001 <0.001 

aModel 1 was adjusted by age at entry.

bModel 2 was adjusted by age at entry, BMI, physical activity, calorie intake, education, family income, occupation, marital status, smoking, alcohol drinking, tea drinking, family history of liver cancer, medical history of hepatitis, cholelithiasis, diabetes, and high blood pressure.

Supplementary Tables S1 and S2 performed the results of sensitivity analyses among premenopausal and postmenopausal women. We found that after we excluded participants with less than 2 follow-up years, similar results can be showed as the main analyses which included all follow-up time.

In this cohort study, we analyzed the associations between menstrual and reproductive factors and the risk of liver cancer in Chinese women. Postmenopausal women always have extremely less endogenous ovarian hormones, which are still high among premenopausal women (31). In our study, premenopausal and postmenopausal women at baseline were analyzed to find out whether the whole exposure times and intensities of menstrual and reproductive factors were associated with liver cancer risk. The results showed that HRT and injective contraceptives were positively associated with liver cancer risk, while age at menopause, reproductive period and the number of live births were associated with decreasing the risk with linear trends especially among postmenopausal women. In addition, hysterectomy, oophorectomy and oral contraceptives were associated with an increased risk of liver cancer among postmenopausal women. And we found no association between age at menarche and liver cancer risk. Similar results were also found in the sensitivity analyses.

Menarche is a major symbol of puberty in women, and the level of endogenous ovarian hormones started to increase at that time (31). Late age at menarche has been considered to decrease ovarian cancer risk and endometrial cancer (32, 33). Yu and colleagues conducted a study with 218 HCC and 729 controls and reported that age at menarche ≥16 was negatively associated with liver cancer risk (OR, 0.38; 95% CI, 0.18–0.80; ref. 34). The Liver Cancer Pooling Project among U.S. women also suggested that age at menarche ≥14 was negatively associated with liver cancer risk (HR, 0.64; 95% CI, 0.40–1.03; ref. 18). However, our study found no statistical association between age at menarche and liver cancer risk. The different results in the two cohorts might be due to the study types, different average age at menarche between the populations, which was 12–13 years old in the U.S. cohort and 15 years old in our study, and more evidence is needed to find out the association between age at menarche and the risk of liver cancer.

During the period of pregnancy, levels of female sex hormones were rising rapidly, and the increasing number of live births are positively associated with exposure of sex hormones (31). Recently, a meta-analysis found a J-shaped curve showing the association between number of live births and liver cancer risk (Pnonlinearity < 0.01), at which the risk decreased less than three and slightly increased over three (22). However, our study only found that the number of live births had a linear trend in decreasing the risk of liver cancer, which may be related to most Chinese women having number of kids less than three. So the researches need to be expanded in other countries.

The postmenopausal period was considered as a significant transition time for women's healthy lifetime, and good menopausal health could carry out considerable personal and societal benefits (35). Age at menopause and reproductive period are thought to reflect cumulative exposure to endogenous female sex hormones (36). A clinic-based retrospective study showed that earlier age at surgical menopause would increase the risk of nonalcoholic fatty liver disease significantly, especially among women who had endometrial cancer (37). Moreover, Yu and colleagues found that age at menopause had a significant linear trend with decreasing risk of liver cancer, especially among women who were 45 to 55 years old and didn't have surgical menopause (Ptrend = 0.025; ref. 34). Our study also indicated that women with earlier age at menopause and shorter reproductive period were at higher risk of liver cancer, which suggested endogenous female sex hormones had a negative relationship with liver cancer risk.

Oophorectomy was considered to decrease the levels of endogenous ovarian hormones, which was positively associated with the risk of nonalcoholic fatty liver disease among women (38). A meta-analysis indicated an increased risk of liver cancer after oophorectomy (RR, 2.23; 95% CI, 1.46–3.41; I2 = 0.0%; Pheterogeneity = 0.50; ref. 22). Our study also reported that oophorectomy was related to increase liver cancer risk mainly among postmenopausal women, which suggested that endogenous female sex hormones were negatively associated with the risk of liver cancer, especially after menopause. In addition, results from our study and the cohort studies in the Liver Cancer Pooling Project and the UK Biobank suggested that hysterectomy was positively associated with the risk of intrahepatic cholangiocarcinoma (ICC) when compared with women who were 50 to 54 years old at natural menopause (HR, 1.98; 95% CI, 1.27–3.09; ref. 39), which was not observed in the meta-analysis (22). There was no direct evidence to interpret the association between hysterectomy and the risk of liver cancer, so this might be due to misclassified self-reported that some women maybe misreport hysterectomy instead of oophorectomy (40).

In addition, our study investigated other factors in relation to exogeneous female sex hormones in women, including HRT, oral contraceptives and injective contraceptives. We found that both HRT and injective contraceptives were associated with increasing the risk of liver cancer, while a positive association about oral contraceptives was only seen among postmenopausal women. However, we realized that HRT use was more common among women who underwent oophorectomy and/or hysterectomy (Supplementary Table S3), which could overestimate the role of HRT on liver cancer risk. In addition, a meta-analysis showed a negative relationship with liver cancer risk in menopausal hormone therapies (RR, 0.60; 95% CI, 0.37–0.96), while no association was seen in estrogen-only therapy (RR, 0.73; 95% CI, 0.46–1.17) and estrogen–progestin therapy (RR, 0.67; 95% CI, 0.45–1.02; ref. 22), which suggested that different composition (the proportions of estrogen and progestin) of hormone therapies might had different effects on liver cancer. The cohort studies in the Liver Cancer Pooling Project and the UK Biobank found that oral contraceptive use ≥9 years was positively associated with the risk of ICC (HR, 1.62; 95% CI, 1.03–2.55; ref. 39), while other studies observed no association between oral contraceptive and liver cancer risk (16, 17). Because the role of HRT, oral contraceptives and injective contraceptives were related to their duration, doses and type (the proportions of estrogen and progesterone), and many analyses including our study didn't collect integrally. More detailed designs were required for further analysis.

Given the above, the association between menstrual and reproductive factors and liver cancer risk may involve important roles of female sex hormones. But the mechanisms were still unclear. The biological role of natural progesterone on liver cancer had little study, while megestrol acetate was observed to be able to inhibit the growth of liver cancer cells both in vitro and in vivo, suggesting progesterone as a tumor inhibitor (7). Some animal studies suggested that estrogen could combine with estrogen receptor α and suppress the production of IL-6 to decrease liver carcinogenesis (11), while others found stimulating roles of estrogens on chemically induced liver tumors (8, 9). A review indicated that estradiol could activates polyclonal B cells, then altered the permeability of intestinal gut and causes gut microbiota migrating into the lamina propria, which may influence autoimmunity and even induce cell damage (41), Examination of the change in the levels and proportions of female sex hormones in blood samples would help to find out the mechanisms of estrogen and progesterone in liver carcinogenesis in women. A recent study analyzed the serum concentrations of seven sex steroid hormones from U.S. postmenopausal women and suggested that higher estrogen levels did not decrease liver cancer risk (42), and might be associated with increasing ICC risk. Measurements about concentration of progestin in blood samples with liver cancer risk were still rare and required for further population studies.

This is a cohort study firstly to evaluate the associations between menstrual and reproductive factors and the incidence of liver cancer in Chinese women. This study has a large-scale, and a population-based cohort study design. In addition, some established liver cancer risk factors in previous published and own studies, such as smoking, alcohol drinking, obesity, type 2 diabetes, cholelithiasis and family history of liver cancer, have been included in our data analysis, which could extremely eliminate the effects of potential confounders. However, some limitations should also be considered. First, we did not collect complete and detailed information about the duration, doses and types of HRT, oral contraceptive and injective contraceptive, which can be considered in further studies. Second, we only obtained menstrual and reproductive information from baseline surveys, and no alterations during follow-up have been taken into consideration. Third, we lacked the data of HBV or HCV infection assays. Although, related to HBV or HCV infection, medical history of hepatitis or chronic liver diseases was adjusted in the multivariate model, which would alleviate this kind of bias to some extent. And our previous nested case–control study estimated the prevalence was 4.98% from the density random-sampling controls who detected HBsAg (43), which was slightly lower than the prevalence of HBV (5.7%) in the general population in China (44). Moreover, the number of cases of several reproductive factors was small in our study, so the findings need to be interpreted with caution. Finally, we did not have relevant data about exact cases of hepatocellular carcinoma and other sites, and the proportion of unspecified sites of primary liver cancer was about 25% (28), so we used the combined cases in our analysis. The detailed histologic subtype of liver cancer would be required for further analysis.

In our study, the association between menstrual and reproductive factors and female liver cancer risk suggested the roles of female sex hormones on liver carcinogenesis. More epidemiologic evidence and evaluation of serum female sex hormone levels are still required for further studies.

Y.-B. Xiang reports grants from National Key Project of Research and Development Program of China (2021YFC2500404, 2016YFC1302503) and grants from US National Institutes of Health (UM1 CA182910) during the conduct of the study. No disclosures were reported by the other authors.

J.-Y. Tuo: Resources, data curation, formal analysis, writing–original draft, writing–review and editing. H.-L. Li: Resources, data curation, validation, investigation, project administration, writing–review and editing. J. Wang: Resources, project administration, writing–review and editing. J. Fang: Resources, project administration, writing–review and editing. Y.-T. Tan: Resources, data curation, project administration, writing–review and editing. Y.-B. Xiang: Conceptualization, resources, data curation, formal analysis, supervision, funding acquisition, investigation, writing–original draft, project administration, writing–review and editing.

We thank all participants and staff from the Shanghai Women's Health Studies for their contribution to this research. This work was supported by a grant from the National Key Project of Research and Development Program of China (2021YFC2500404 and 2016YFC1302503, to Y.B. Xiang); and the parent cohort was supported by a grant from the NIH (UM1 CA182910, to W. Zheng).

The publication costs of this article were defrayed in part by the payment of publication fees. Therefore, and solely to indicate this fact, this article is hereby marked “advertisement” in accordance with 18 USC section 1734.

Note: Supplementary data for this article are available at Cancer Epidemiology, Biomarkers & Prevention Online (http://cebp.aacrjournals.org/).

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Supplementary data