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Abstract

Objectives

Though menstrual and reproductive factors have been associated with the risk of breast cancer in many populations, very few studies have been conducted among Vietnamese women. This study aimed to assess the association between menstrual and reproductive factors and the risk of breast cancer in Vietnamese women.

Methods

A retrospective case-control study of 490 breast cancer cases and 468 controls was conducted in Northern Vietnam. Unconditional logistic regression models adjusting for confounders were used to estimate odds ratios (ORs) and their 95% confidence intervals (CIs) for the associations of menstrual and reproductive factors with the risk of breast cancer; overall and by cancer subtype.

Results

Among breast cancer patients, the luminal B subtype was the most frequent (48.6%), followed by HER2-overexpressing (24.5%), luminal A (16.7%), and triple-negative breast cancer (TNBC; 10.2%). Among menopausal women, menopausal age at 50 years or older (OR = 1.71, 95% CI: 1.15-2.57 vs. <50 y) was associated with an increased risk of breast cancer. Earlier age at menarche (<13 y) was associated with a significantly increased risk of breast cancer (OR = 2.66, 95% CI: 1.08-7.51) among premenopausal women only and the luminal A subtype of breast cancer (OR = 3.06, 95% CI: 1.04-8.16). Having more than two children was associated with a reduced risk of premenopausal (OR = .42, 95%CI: .21-.83), luminal B (OR = .43, 95% CI: .24-.79), and TNBC (OR = .34, 95% CI: .14-.89). Later menopause was positively associated with the risk of breast cancer with HER2 overexpression (OR = 2.19, 95% CI: 1.14-4.23).

Conclusion

Associations of menstrual and reproductive factors with breast cancer among Vietnamese women, particularly for among premenopausal women and for the luminal A subtype, are generally consistent with those reported from other countries. These findings suggest that changes in menstrual and reproductive patterns among young Vietnamese women may contribute to the recent rising incidence of breast cancer in Vietnam.

Keywords

breast cancer tumor subtype menstrual factor reproductive behaviors case-control study

Introduction

Breast cancer is the most common cancer and the leading cause of death for women worldwide. The GLOBOCAN reported that there were 2.2 million new cases of breast cancer worldwide in 2020, accounting for a quarter of cancer cases among women.¹ In Vietnam, the incidence rate for breast cancer was 34.2 per 100 000 women, making it the most common cancer for women (25.8% of all cancers) and the fourth leading cause of cancer death overall, following lung cancer, liver cancer, and stomach cancer.¹

In the past few decades, breast cancer incidence rates have increased in developing countries, including Vietnam. Rising rates coincide with changes in lifestyle, population characteristics, and menstrual and reproductive patterns in these countries.¹ These changes include factors such as an increase of physical inactivity, obesity, dietary fat intake, alcohol consumption, early onset of menarche, late onset of menopause, nulliparity, late age at first birth, a decreased number of childbirths, and no or shortened duration of breastfeeding.^2,3

Prior studies have consistently shown that prolonged endogenous and exogenous estrogen exposure increases the risk of breast cancer.⁴ A meta-analysis of 117 studies in 2012 reported the associations between age at primiparity, parity, and at menopause with the risk of breast cancer.⁵ Fewer parities and advanced age at first birth both increased the risk of ER+/PR+ cancer, but they were not associated with the risk of ER-/PR-cancer in most prospective studies.⁶ A meta-analysis evaluated 15 studies, with 21 941 breast cancer patients and 864 177 controls, that investigated the impact of reproductive behaviors according to intrinsic subtype.⁷ Parity and breastfeeding were associated with a reduced risk of developing luminal subtype, while later age at first birth was related to an increased risk of developing luminal subtype.⁷ Breastfeeding was associated with a reduced risk of developing triple-negative breast cancer (TNBC) subtype.⁷ Research on other reproductive factors, such as spontaneous abortion (SA) or induced abortion (IA), with breast cancer risk has yielded inconsistent findings. A 2015 meta-analysis of 15 prospective studies revealed non-significant associations of breast cancer with SA and IA.⁸ These subtypes (luminal A, luminal B, HER2+, and TNBC) differ in age at diagnosis and prognosis. In addition, they may also differ etiologically and have different in risk factors.⁹

Vietnamese women are experiencing significant changes in lifestyle and reproductive patterns. However, little is known about how these changes affect breast cancer risk. To our knowledge, only two small-scale studies on breast cancer have been conducted in Vietnam and the results were inconsistent.^10,11 Herein, we report results from a large case-control study, the Vietnamese Breast Cancer Study (VBCS), focusing on the associations between menstrual and reproductive factors with breast cancer risk among Vietnamese women.

Methods

Study Population

We recruited newly diagnosed breast cancer patients (clinical diagnosis) aged 21 to 79 from inpatient surgical and chemotherapy units and outpatient units of the Vietnam National Cancer Hospital and the Hanoi Oncology Hospital. These are the two largest oncology hospitals in Northern Vietnam. Breast cancer patients with a prior history of cancer were not eligible for the study. Controls were selected from healthy relatives, neighbors, or friends of breast cancer patients (n = 64), or healthy women who were taking care of other cancer patients at these two hospitals (n = 402), and frequency was matched to cases on age (±3 years) and residence (urban/rural). Controls were recruited at approximately the same time as case recruiment. Women who had a history of cancer diagnosis were excluded from this study. Details of design and methods for the VBCS have been described previously.¹²

A total of 501 newly diagnosed breast cancer patients and 468 controls were included in this study from July 2017 to June 2018 in Hanoi, Vietnam (response rates of 93.1% and 97.7% for cases and controls, respectively).We excluded case participants who were subsequently confirmed to have a benign tumor based on a pathological review (n = 9) or who were diagnosed at stage 0 (n = 2). Finally, 490 cases and 468 controls remained in the current study. Our study initially applied an age frequency matched design. However, during data collection, it was adapted to the individual matching study, in which cases and controls were individually matched to cases on age (±3 years), city, and province of residency. Thus, out of 490 cases and 468 controls, there are 374 individually matched case-control pairs. All patient information was de-identified. The protocol of this study was approved by the Vietnam National Cancer Institute (No.160530 – IRB approval issued May 30, 2016) and Vanderbilt University Medical Center (No.161039 “Vietnam Center of Research Excellence (V-CORE) - IRB approval issued May 31, 2018”). All patients provided written informed consent prior to enrollment in the study.

Assessment of Menstrual and Reproductive Characteristics

Information on menstrual and reproductive characteristics, demographics, lifestyle factors, medical history, and familial cancer history was collected through in-person interviews using a structured questionnaire built within the Research Electronic Data Capture (REDCap) mobile application.¹³ In addition, anthropometrics, weight, height, waist, and hip circumferences were taken by trained interviewers following a standard protocol, from which body mass index (BMI) was calculated as weight (kg)/[height (m)].² Data collected for the current study included age, marital status, residency (urban, rural), age at first menarche, age at menopause, menstrual cycle regularity and duration, parity, age at first live birth, age at last live birth, number of pregnancies and abortions, and total months of breastfeeding in a lifetime. Additionally, p postmenopausal status was defined as cease of menstruation naturally (i.e., excluding those brought on by pregnancy, surgery, or other treatments) for at least 12 months.

Menstrual and reproductive factors and covariates were categorized as follows in the study: age at menarche (<13 vs. ≥13 years, similar to publications from other Asian countries^14,15), menopausal status (premenopausal vs. postmenopausal), age at menopause (<50 vs. ≥50 years), regularity of menstrual cycle (i.e., regular, irregular, sometimes irregular), length of the menstrual cycle (<26 days, 26-30 days, >30 days), number of pregnancies (0, 1, 2, 3, ≥4), parity (ever vs. never), number of livebirth (1, 2, ≥3), age at first live birth (<25, 25-29, 30-34, ≥35 years), abortion (never, induced only, miscarriage only, both induced and miscarriage), breastfeeding (ever vs. never), breastfeeding duration (<12, 12-23, ≥24 months), and family history of breast cancer (no vs. yes). Body mass index (BMI) was categorized using the World Health Organization’s classification for Asian populations: underweight (BMI < 18.5 kg/m²), normal/healthy weight (BMI ranges from 18.5 to 22.9 kg/m²), overweight (BMI ranges from 23 to 27.5 kg/m²) and obese (BMI > 27.5 kg/m²). Economic status was defined by annual family income (i.e., ≤50 million, 50-100 million, 100-150 million, 150-200 million, >200 million).¹⁶

Data on ER/PR status and HER-2 expression was collected by reviewing medical charts from the Vietnam National Cancer Hospital and the Hanoi Oncology Hospital. ER and PR status, HER-2 expression, and Ki67 status were assessed by immunohistochemistry (IHC). Intrinsic tumor subtypes were classified as luminal A (ER-positive and/or PR-positive, HER-2 negative, and low Ki-67), luminal B (ER-positive and/or PR-positive, and HER-2 positive or HER-2 negative with high Ki-67), HER-2 overexpressing (ER-negative and PR negative, and HER-2 positive; HER 2+), and triple-negative (ER, PR, and HER-2 negative; TNBC).

Statistical Analysis

Differences in frequency distribution of categorical variables were evaluated by Pearson chi-square, while the Student t-test was performed to compare mean values of continuous variables between cases and controls. Unconditional logistic regression models were used to estimate odds ratios (ORs) and their respective 95% confidence intervals (CIs) for associations of breast cancer risk with menstrual and reproductive characteristics. The differences in ORs between the two groups, pre- and post-menopausal, was tested using Likelihood ratio tests. The multivariable logistic regression model was adjusted for potential confounders based on the literature. Tests for trends across categories were performed by assigning the median value for each category. Multivariable multinomial logistic regression was also performed to evaluate whether the observed risk estimates varied across molecular subtypes of breast cancer. We used likelihood ratio tests to evaluate heterogeneity across molecular subtypes. All analyses were performed using R version 4.1.0. A two-sided P-value of less than .05 was considered statistically significant.

The reporting of this study conforms to STROBE guidelines.¹⁷

Results

The distribution of participant characteristics is presented in Table 1. The age at diagnosis for cases ranged from 21 to 78 years, with a mean of 50.1 (standard deviation−SD = 9.8) years. The mean age for the control group was 49.9 (SD = 9.3) years. There were no significant differences between cases and controls in levels of education, marital status, residence, BMI, or family history of cancer among first-degree relatives. However, compared with controls, fewer cases had an annual family income >200 million Vietnamese Dong (VND). Our previous study described the characteristics of cases, in which 94 (19.2%) participants were diagnosed at stage I, 240 (49.2%) were diagnosed at stage II, and 119 (24.3%) were diagnosed at stage III and IV.¹⁸

Table 1.

Sociodemographic characteristics and familial cancer history of study participants.

Variables	Cases	Controls	P value
Variables	(N = 490)	(N = 468)
Age [mean ± SD (y)]	50.1 ± 9.8	49.9 ± 9.3	.74
Education level (n (%))
No formal education	7 (1.4)	7 (1.5)	.87
Elementary school	65 (13.3)	60 (12.8)
Middle school and high school	324 (66.3)	321 (68.5)
College and higher	93 (19.0)	80 (17.2)
Marital status (n (%))
Single	76 (15.5)	52 (11.1)	.06
Married or cohabiting	413 (84.5)	416 (88.9)
Annual family income (VND) (n (%))
≤50 million	144 (29.7)	145 (31.5)	.009
50-100 million	189 (39.0)	163 (35.4)
100-150 million	103 (21.1)	93 (20.2)
150-200 million	40 (8.2)	31 (6.7)
>200 million	9 (1.8)	29 (6.3)
Residence (n (%))
Urban	122 (24.9)	107 (23.1)	.75
Suburban	71 (14.5)	65 (14.0)
Rural	296 (60.5)	291 (62.9)
BMI (n (%))
mean ± SD (y)]	21.7 ± 2.5	21.5 ± 2.7	.37
<18.5 kg/m²	45 (9.2)	55 (11.8)	.42
18.5-22.9 kg/m²	303 (62.1)	288 (61.7)
23-27.5 kg/m²	131 (26.8)	112 (24.0)
>27.5 kg/m²	9 (1.9)	12 (3.5)
Familial cancer history (n (%))
No	384 (78.4)	359 (76.9)	.63
Yes	106 (21.6)	108 (23.1)

Table 2 shows the ORs and 95% CIs for breast cancer associated with menstrual and reproductive factors. The vast majority of study participants (95.2% of cases and 97.1% of controls) started menstruation at age 13 or later. Early age at menarche (<13 years) was associated with a non-significantly evaluated breast cancer risk (OR = 1.69, 95% CI: .85-3.49) compared to menarche age of 13 or older. A significantly increased risk of breast cancer was found among women with a later age at menopause (OR = 1.71, 95% CI: 1.15-2.57), compared to women with an earlier age at menopause. Compared with participants who had regular ovulatory menstrual cycles, women with irregular ovulatory menstrual cycles had a 48% (95% CI: .37-.71) lower risk of breast cancer, while participants with sometimes irregular menstrual cycles had a 3.49-fold (95% CI: 1.74-7.66) increased risk of breast cancer. Compared with controls, breast cancer cases were more likely to have fewer pregnancies and live births and were older at first live birth. Compared to women with one child, women with three or more children had a 47% (95% CI: .33-.85) reduced risk of breast cancer. In contrast, age at last birth was not associated with breast cancer risk (data not shown). History and number of spontaneous miscarriages, induced abortions, status, and duration of breastfeeding were not associated with breast cancer risk. Sensitivity analyses based on 374 individually matched pairs did not materially change the above-reported associations (Supplementary Tables S1).

Table 2.

Association between menstrual and reproductive factors and breast cancer risk.

Variables	Cases	Controls	OR (95% CI)^a
Variables	N (%)	N (%)	OR (95% CI)^a
Age at menarche
≥13	454 (95.2)	443 (97.1)	1.00 (ref)
<13	23 (4.8)	13 (2.9)	1.69 (.85-3.49)
Menopause
No	260 (53.5)	246 (53.0)	1.00 (ref)
Yes	226 (46.5)	218 (47.0)	.90 (.62-1.31)
Age at menopause
<50	112 (49.6)	137 (62.8)	1.00 (ref)
≥50	114 (50.4)	81 (37.2)	1.71 (1.15-2.57)
Regular menstrual cycle
Regular	370 (76.1)	324 (69.4)	1.00 (ref)
Irregular	80 (16.5)	133 (28.5)	.52 (.37-.71)
Sometimes	36 (7.4)	10 (2.1)	3.49 (1.74-7.66)
Length of menstrual cycle
<26 days	85 (23.2)	48 (14.8)	1.00 (ref)
26-30 days	221 (60.2)	205 (63.3)	.46 (.28-.76)
>30 days	61 (16.6)	71 (21.9)	.64 (.42-.96)
Trend test			P = .004
Number of pregnancies
0	28 (5.7)	27 (5.8)	1.00 (ref)
1	34 (7.0)	19 (4.1)	1.46 (.67-3.21)
2	66 (13.6)	71 (15.2)	.82 (.42-1.57)
3	117 (24.0)	110 (23.6)	.92 (.49-1.71)
≥4	242 (49.7)	240 (51.4)	.85 (.47-1.53)
Trend test			P = .30
Parity
Ever	451 (92.6)	433 (92.9)	1.00 (ref)
Never	36 (7.4)	33 (7.1)	1.19 (.71-2.01)
Number of live births
1	61 (13.3)	39 (9.0)	1.00 (ref)
2	254 (56.3)	229 (52.9)	.74 (.47-1.15)
≥3	137 (30.4)	165 (38.1)	.53 (.33-.85)
Trend test			P = .005
Age at first live birth^b
<25	246 (54.5)	279 (64.7)	1.00 (ref)
25-29	153 (33.9)	118 (27.4)	1.49 (1.10-2.02)
30-34	28 (6.2)	21 (4.9)	1.40 (.75-2.63)
≥35	24 (5.4)	13 (3.0)	1.66 (.76-3.71)
Trend test			P = .029
Abortion
Never	161 (33.1)	169 (36.2)	1.00 (ref)
Induced only	71 (14.6)	72 (15.4)	1.06 (.71-1.58)
Miscarriage only	197 (40.4)	170 (36.4)	1.19 (.87-1.61)
Both induced and miscarriage	58 (11.9)	56 (12.0)	1.02 (.66-1.58)
Breastfeeding^b
Ever	443 (91.0)	426 (91.4)	1.00 (ref)
Never	44 (9.0)	40 (8.6)	1.49 (.55-4.39)
Breastfeeding duration^b
<12	15 (3.4)	13 (3.1)	1.00 (ref)
12-23	115 (26.1)	103 (24.1)	1.01 (.45-2.28)
≥24	311 (70.5)	311 (72.8)	.95 (.42-2.10)
Trend test			P = .71

Adjusted for age, first-degree family cancer history, income.

additionally adjusted for number of live births among parous women.

Further analyses stratified by menopausal status were conducted and the results are shown in Table 3. The association of breast cancer with age at menarche, parity, and age at first live birth were predominantly seen among premenopausal women. The associations for early age at menarche (OR = 2.66, 95% CI: 1.08-7.51, P_{heterogeneity} = .05) and number of live births with breast cancer (OR = .42, 95% CI: .21-.83) reached the statistical significance level. In addition, compared to women with a BMI of <18.5 kg/m², women with a BMI of 23-17.5 kg/m² experienced an increased risk of breast cancer among those who were postmenopausal (OR = 2.18, 95% CI: 1.08-4.49, P_{heterogeneity} = .04).

Table 3.

Association between menstrual and reproductive factors and breast cancer stratified by menopausal status.

Variables	Pre-menopause			Post-menopause
	Cases	Controls	OR (95% CI)^a	Cases	Controls	OR (95% CI)^a
	N (%)	N (%)	OR (95% CI)^a	N (%)	N (%)	OR (95% CI)^a
Age at menarche
≥13	241 (93.4)	239 (97.6)	1.00 (ref)	213 (97.7)	201 (96.6)	1.00 (ref)
<13	17 (6.6)	6 (2.4)	2.66 (1.08-7.51)	5 (2.3)	7 (3.4)	.75 (.22-2.43)
P_{heterogeneity} =.05*
Parity
Ever	246 (94.6)	236 (95.9)	1.00 (ref)	204 (90.7)	194 (89.4)	1.00 (ref)
Never	14 (5.4)	10 (4.1)	1.66 (.68-4.33)	21 (9.3)	23 (10.6)	.98 (.50-1.88)
P_{heterogeneity} = .41*
Number live births
1	33 (13.1)	19 (8.1)	1.00 (ref)	39 (14.2)	20 (10.3)	1.00 (ref)
2	166 (65.9)	140 (59.3)	.74 (.39-1.36)	91 (44.6)	87 (44.8)	.71 (.36-1.35)
≥3	53 (21.0)	77 (32.6)	.42 (.21-.83)	84 (41.2)	87 (44.8)	.62 (.32-1.20)
Trend test			P = .003			P = .23
P_{heterogeneity} = .15*
Age at first live birth^b
<25	140 (56.9)	162 (68.9)	1.00 (ref)	106 (52.0)	116 (60.1)	1.00 (ref)
25-29	85 (34.6)	59 (25.1)	1.67 (1.10-2.54)	67 (32.8)	57 (29.5)	1.29 (.82-2.04)
30-34	12 (4.9)	10 (4.3)	1.31 (.52-3.36)	16 (7.8)	11 (5.7)	1.54 (.67-3.69)
≥35	9 (3.7)	4 (1.7)	2.05 (.60-8.25)	15 (7.4)	9 (4.7)	1.53 (.55-4.43)
Trend test			P = .048			P = .21
P_{heterogeneity} = .49*
Breastfeeding^b
Ever	242 (93.1)	232 (94.7)	1.00 (ref)	200 (88.9)	191 (87.6)	1.00 (ref)
Never	18 (6.9)	13 (5.3)	2.66 (.62-18.25)	25 (11.1)	27 (12.4)	.81 (.18-3.52)
P_{heterogeneity} = .39
Breastfeeding duration^b
<12	9 (3.8)	5 (2.1)	1.00 (ref)	6 (3.0)	8 (4.2)	1.00 (ref)
12-23	63 (26.2)	55 (23.6)	.57 (.16-1.83)	52 (26.0)	48 (25.1)	1.88 (.59-6.31)
≥24	168 (70.0)	173 (74.2)	.51 (.15-1.62)	142 (71.0)	135 (70.7)	1.89 (.60-6.23)
Trend test			P = .44			P = .63
P_{heterogeneity} = .37*
BMI
<18.5 kg/m²	27 (11.0)	27 (10.4)	1.00 (ref)	18 (8.0)	28 (12.9)	1.00 (ref)
18.5-22.9 kg/m²	153 (62.2)	170 (65.6)	1.15 (.64-2.09)	130 (57.8)	132 (60.8)	1.66 (.87-3.25)
23-27.5 kg/m²	59 (24.0)	59 (22.8)	1.05 (.54-2.05)	72 (32.0)	52 (24.0)	2.18 (1.08-4.49)
>27.5 kg/m²	7 (2.8)	3 (1.2)	.45 (.09-1.83)	5 (2.2)	5 (2.3)	1.56 (.38-6.44)
Trend test			P = .40			P = .05

*P_{heterogeneity} = .04, Test for heterogeneity.

Adjusted for age, first-degree family cancer history, income.

additionally adjusted for number of live births among parous women.

Table 4 presents the associations between menstrual and reproductive characteristics and the risk of intrinsic breast cancer subtypes. Among breast cancer patients, luminal B subtype was most frequent (48.6%), followed by HER2-enriched (24.5%), luminal A (16.7%), and triple-negative breast cancer (TNBC; 10.2%). Menarche at an early age (<13 years) was associated with a significantly increased risk of luminal A (OR = 3.06, 95% CI: 1.04-8.16) and non-significantly increased HER2-enriched (OR = 1.93, 95% CI: .66-5.06) and TNBC (OR = 2.45, 95% CI: .54-8.25). Compared to women with one child, women with more than two children experienced a reduced risk of luminal B breast cancer (OR = .43, 95% CI: .24-.79) and TNBC (OR = .34, 95% CI: .14-.89), respectively. The risk of HER2-enriched breast cancer increased significantly (OR = 2.19, 95% CI: 1.14-4.23) with more advanced age at menopause. We observed no other significant associations for specific subtypes of breast cancer.

Table 4.

Association between menstrual and reproductive factors and breast cancer by intrinsic subtypes.

Variables	Controls		Luminal A		Luminal B		HER 2-enriched		TNBC
Variables	N	N	OR (95% CI)^a	N	OR (95% CI)^a	N	OR (95% CI)^a	N	OR (95% CI)^a
Age at menarche
≥13	443	66	1.00 (ref)	7	1.00 (ref)	102	1.00 (ref)	41	1.00 (ref)
<13	13	6	3.06 (1.04-8.16)	208	1.14 (.42-2.84)	6	1.93 (.66-5.06)	3	2.45 (.54-8.25)
Pheterogeneity = .09*
Menopause
No	246	42	1.00 (ref)	129	1.00 (ref)	51	1.00 (ref)	21	1.00 (ref)
Yes	218	32	.55 (.26-1.14)	88	.64 (.40-1.05)	58	1.37 (.74-2.54)	25	1.44 (.58-3.58)
Pheterogeneity = .09*
Age at menopause
<50	137	14	1.00 (ref)	50	1.00 (ref)	28	1.0 (ref)	14	1.00 (ref)
≥50	81	18	1.99 (.90-4.51)	38	1.17 (.69-1.98)	30	2.19 (1.14-4.23)	11	1.19 (.48-2.89)
Pheterogeneity = .04*
Regularity of menstrual cycle
Regular	324	58	1.00 (ref)	167	1.00 (ref)	84	1.00 (ref)	32	1.00 (ref)
Irregular	133	13	.54 (.27-1.00)	32	.44 (.28-.67)	16	.46 (.25-.80)	9	.68 (.30-1.43)
Sometimes	10	4	2.62 (.68-8.50)	17	3.51 (1.57-8.24)	9	4.32 (1.59-11.81)	5	6.30 (1.77-20.89)
Length of menstrual cycle
<26 days	48	11	1.00 (ref)	38	1.00 (ref)	24	1.00 (ref)	7	1.00 (ref)
26-30 days	205	32	.69 (.33-1.55)	99	.64 (.39-1.06)	49	.49 (.27-.90)	21	.71 (.30-1.92)
>30 days	71	14	.80 (.33-1.98)	28	.49 (.26-.90)	11	.28 (.12-.63)	4	.36 (.09-1.28)
Trend test			P = .82		P = .03		P = .003		P = .12
Pheterogeneity = .002*
Parity
Ever	433	72	1.00 (ref)	196	1.00 (ref)	104	1.00 (ref)	41	1.00 (ref)
Never	33	3	.62 (.14-1.89)	20	1.57 (.84-2.87)	6	.85 (.30-2.03)	5	1.79 (.56-4.85)
Pheterogeneity = .33*
Number live births
1	39	10	1.00 (ref)	28	1.00 (ref)	8	1.00 (ref)	9	1.00 (ref)
2	229	39	.70 (.33-1.58)	117	.73 (.42-1.26)	59	1.24 (.57-3.03)	18	.37 (.16-.94)
≥3	165	23	.52 (.23-1.23)	51	.43 (.24-.79)	37	1.08 (.48-2.67)	14	.34 (.14-.89)
Trend test			P = .14		P = .002		P = .77		P = .12
Pheterogeneity = .002*
Age at first live birth^b
<25	279	35	1.00 (ref)	109	1.00 (ref)	61	1.00 (ref)	24	1.00 (ref)
25-29	118	28	1.91 (1.09-3.34)	63	1.38 (.93-2.04)	33	1.31 (.79-2.15)	13	1.25 (.58-2.60)
30-34	21	4	1.43 (.38-4.34)	15	1.58 (.73-3.33)	5	1.24 (.39-3.34)	1	.34 (.02-2.00)
≥35	13	5	2.41 (.62-8.51)	9	1.37 (.51-3.58)	5	2.10 (.59-6.79)	3	1.36 (.25-5.88)
Trend test			P = .045		P = .13		P = .17		P = .91
Pheterogeneity = .01*
Abortion
Never	168	23	1.00 (ref)	80	1.00 (ref)	32	1.00 (ref)	14	1.00 (ref)
Induced only	72	15	1.58 (.76-3.23)	30	.90 (.53-1.48)	14	1.07 (.52-2.11)	4	.65 (.18-1.91)
Miscarriage only	171	30	1.26 (.70-2.30)	78	.93 (.63-1.36)	48	1.51 (.91-2.52)	24	1.70 (.85-3.53)
Both induced and miscarriage	56	7	.91 (.34-2.17)	28	.98 (.56-1.66)	16	1.45 (.71-2.88)	4	.85 (.23-2.53)
Breastfeeding^b
Ever	426	73	1.00 (ref)	192	1.00 (ref)	101	1.00 (ref)	39	1.00 (ref)
Never	40	2	-	24	1.48 (.41-5.05)	9	2.68 (.67-9.70)	7	3.10 (.43-14.91)
Pheterogeneity = .05*
Breastfeeding duration^b
<12	13	5	1.00 (ref)	5	1.00 (ref)	3	1.00 (ref)	2	1.00 (ref)
12-23	103	22	.66 (.21-2.29)	45	1.19 (.51-4.62)	25	1.02 (.29-4.79)	9	.63 (.13-4.66)
≥24	311	45	.41 (.13-1.39)	142	1.42 (.51-4.62)	72	.93 (.27-4.26)	28	.76 (.16-5.58)
Trend test			P = .06		P = .36		P = .73		P = .89

*P_{heterogeneity} = .30.

αTest for heterogeneity of trend; P value across four molecular subtypes.

Adjusted for age, first-degree family cancer history, income.

additionally adjusted for the number of live births among parous women.

Discussion

To our knowledge, this study is the largest case-control study of breast cancer and the first one to investigate breast cancer risk factors by tumor subtype in Vietnam. Most of our findings on menstrual/reproductive characteristic-breast cancer risk associations are consistent with those reported for Western and other Asian populations, while few previously established associations were not observed in our study.

Early age at menarche has been consistently associated with an increased risk of breast cancer in several Asian and Western populations.^19-24 In our study, early age at menarche was associated with a non-significantly elevated risk of breast cancer overall. This association became significant among premenopausal women and for luminal A breast cancer. These findings are consistent with previous studies that showed the association between menarche and breast cancer was stronger for the luminal A subtype.^15,25,26 Early-onset of menarche was related to early and greater cumulative exposure to estrogen, in which the presence of progesterone can increase the risk of breast cancer, particularly in the luminal A subtype in which estrogen exposure is most relevant. We found that the menarche-breast cancer association was mainly confined to premenopausal women is likely caused by a cohort effect as Vietnamese women traditionally have a late onset of menstruation (more than 97% of control participants began menstruation at ≥13 years of age). In addition, the age at menarche has decreased in younger generations. In our study, the average menarche age among controls was 15.7 years.

We found that women with irregular cycles had 48% and 56% reduced risks of breast cancer overall and for luminal B breast cancer, respectively. This finding is in line with reports from previous studies.^27,28 Irregular menstrual cycles may be related to anovulation, leading to reduced exposure to estrogen and progesterone, and thus, lower risk of breast cancer.²⁹ The more than 3-fold elevated odds ratio for overall breast cancer, and most subtypes of breast cancer, associated with sometimes irregular menstruation has not been previously reported and may be caused by recall bias. Of note, the confidence intervals for the OR associated with irregular menstruation are extremely wide due to how few women reported having the condition. Therefore, this result should be interpreted with caution.

Similarly, late age at menopause is a well-established risk factor for breast cancer. Our results show that women aged 50 or over at menopause had an increased risk for breast cancer overall and HER-2+ and a suggested elevated risk of luminal A breast cancer. Late menopause is associated with increased lifetime exposure to estrogen, which may account for the increased risk of breast cancer.³⁰ The lack of significance for luminal A breast cancer is likely due to the small sample size.

Our findings on reduced numbers of live births and late age at first live birth being associated with an increased risk of breast cancer were consistent with results of previous studies,^31-35 including those conducted in Vietnamese women.^36,37 Our study, for the first time, showed that these associations varied by tumor subtype among Vietnamese women. Specifically, women with more than two children had a decreased risk of both luminal B and TNBC subtypes, and a suggested decreased risk of luminal A breast cancer, compared to women with one child. However, the number of live births was unrelated to HER 2+ breast cancer. These results support a different etiology for breast cancer subtypes, which warrants further investigation.

Our finding of a null association for miscarriage and abortion with breast cancer risk was consistent with a 2015 meta-analysis that showed no evidence from prospective studies on an association between breast cancer risk and abortion, including both induced and spontaneous abortion.⁸

We did not find that the length of time breastfeeding was significantly associated with breast cancer overall and by subtypes in our study, which is inconsistent with some of the earlier findings.^38,39 It should be noted that 96.6% of cases and 96.9% of controls in our study have had breastfeeding experience, most for longer than 12 months. Thus, our study has low statistical power to investigate the influence of no or short-term breastfeeding on breast cancer risk.

The large sample size, high participation rate, standardized data collection, and availability of breast cancer subtype information are significant strengths of our study. However, our study also has several limitations. First, our study was hospital-based; therefore, selection bias cannot be excluded. Nevertheless, the Vietnam National Cancer Hospital and the Hanoi Oncology Hospital are the leading hospitals treating most breast cancer patients in Northern Vietnam. Because most Vietnamese have government-provided health insurance, systematic selection bias is minimized. In addition, we have adjusted for education and family income in our analysis to reduce selection bias further. Second, like almost all previous studies, information regarding menstrual and reproductive factors is self-reported. Misclassification is unavoidable and may introduce a biased estimation for the associations between menstrual/reproductive factors and breast cancer. Because our study is a retrospective by design, contrary to prospective studies, the bias may be differential. Third, most controls (95.9%) were recruited from female relatives or friends of cancer patients other than those treated for breast cancer at the Vietnam National Cancer Hospital. Therefore, they may not be a representative sample of Vietnam’s general population. This may be why the family history of cancer among controls was similar to that of cases in our study. This raises a potential concern that the association estimation derived from our research may be somewhat underestimated or overestimated.

Conclusion

In summary, in this first large case-control study investigating breast cancer risk factors by tumor subtype in Vietnam, we found that menstrual and reproductive factors played an important role in breast cancer etiology, particularly among premenopausal women and for hormonal positive breast cancer subtypes. Therefore, our findings are imperative for developing breast cancer prevention strategies in Vietnam, particularly given the recent changing trends in menstrual and reproductive patterns in the younger generation of Vietnamese women.

Supplemental Material

Supplemental Material - Menstrual and Reproductive Factors in Association With Breast Cancer Risk in Vietnamese Women: A Case-Control Study

Supplemental Material for Menstrual and Reproductive Factors in Association With Breast Cancer Risk in Vietnamese Women: A Case-Control Study by Oanh Thi Bui, Huong Thanh Tran1,2, Sang Minh Nguyen, Tu Van Dao, Quang Vinh Bui, Anh Tuan Pham, Martha J. Shrubsole, Qiuyin Cai, Fei Ye, Wei Zheng, Hung Nguyen Luu, Thuan Van Tran, and Xiao-Ou Shu in Cancer Control

Abbreviations

BMI

body mass index

confidence interval

estrogen receptor

induced abortion

HER-2

human epidermal growth factor receptor 2

odds ratio

PRprogesterone receptorSA

progesterone receptorSAspontaneous abortion

standard deviation

TNBC

triple-negative breast cancer

Footnotes

Acknowledgments

The authors would like to give special thanks to the participants and the research staff members of this project, without whom this study would not have been possible. We also thank Dr. Mary Shannon Byers and Ms Rachel Mullen for their assistance in editing this manuscript.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study was supported by NIH/NCI Grant # P20 CA210300 and OISE-19-66185-1 (PIs: Xiao-Ou Shu and Thuan V. Tran). Sang Nguyen was supported by a VECD Global Health Fellowship, funded by the National Cancer Institute (NCI) and the Fogarty International Center (FIC) of the NIH (D43 TW009337) and Ingram Cancer Professorship Fund (to Dr. Shu).

Authors’ Contributions

Conception and design: O. T. Bui, H.TT. Tran, X. O. Shu, Development of methodology: O. T. Bui, X. O. Shu, Acquisition of data (provided animals, acquired and managed patients, provided facilities, etc.): O. T. Bui, H. TT. Tran, S. M. Nguyen, T.V. Dao, Q. V. Bui, A. T. Pham, M. J. Shrubsole, Q. Cai, F. Ye, W. Zheng, H. N. Luu, T. V. Tran, X. O. Shu, Analysis and interpretation of data (e.g., statistical analysis, biostatistics, computational analysis): O. T. Bui, S. M. Nguyen, X. O. Shu, Writing, review, and or revision of the manuscript: O. T. Bui, S. M. Nguyen, H.TT. Tran, X. O. Shu, Administrative, technical, or material support (i.e., reporting or organizing data, constructing databases): O. T. Bui, H. T. T. Tran, S. M. Nguyen, T. V. Dao, Q. V. Bui, A. T. Pham, M. J. Shrubsole, Q. Cai, F. Ye, W. Zheng, H. N. Luu, T. V. Tran, X. O. Shu, Study supervision: H. T. T. Tran, T. V. Tran, X. O. Shu

Ethical Approval

The protocol of this study was approved by the Vietnam National Cancer Institute and Vanderbilt University Medical Center.

Informed Consent

All patients provided written informed consent prior to enrollment in the study.

ORCID iDs

Oanh Thi Bui

Sang Minh Nguyen

Tu Van Dao

Anh Tuan Pham

Hung Nguyen Luu

Thuan Van Tran

Supplemental Material

Supplemental material for this article is available online.

References

Sung

Ferlay

Siegel

, et al. Global cancer statistics 2020: Globocan estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2021;71(3):209-249. doi:10.3322/caac.21660

Momenimovahed

Salehiniya

. Epidemiological characteristics of and risk factors for breast cancer in the worldBreast Cancer Dove Med Press. 11;2019:151-164. 10.2147/BCTT.S176070

Łukasiewicz

Czeczelewski

Forma

Baj

Sitarz

Stanisławek

. Breast Cancer—Epidemiology, risk factors, classification, prognostic markers, and current treatment strategies—an updated review. Cancers. 2021;13(17):4287. doi:10.3390/cancers13174287

Inumaru

Irineu Gomes Duarte Quintanilha

Da Silveira

ÉA

Veloso Naves

. Risk and protective factors for breast cancer in Midwest of Brazil. J Environ Public Health. 2012;2012:356851. doi:10.1155/2012/356851

Collaborative Group on Hormonal Factors in Breast Cancer . Menarche, menopause, and breast cancer risk: Individual participant meta-analysis, including 118 964 women with breast cancer from 117 epidemiological studies. Lancet Oncol. 2012;13(11):1141-1151. doi:10.1016/S1470-2045(12)70425-4

Bernstein

Pike

Ursin

. Reproductive factors and breast cancer risk according to joint estrogen and progesterone receptor status: A meta-analysis of epidemiological studies. Breast Cancer Res. 2006;8(4):R43. doi:10.1186/bcr1525

Lambertini

Santoro

Del Mastro

, et al. Reproductive behaviors and risk of developing breast cancer according to tumor subtype: A systematic review and meta-analysis of epidemiological studies. Cancer Treat Rev. 2016;49:65-76. doi:10.1016/j.ctrv.2016.07.006

Guo

Huang

Yang

, et al. Association between abortion and breast cancer: An updated systematic review and meta-analysis based on prospective studies. Cancer Causes Control. 2015;26(6):811-819. doi:10.1007/s10552-015-0536-1

Holm

Eriksson

Ploner

, et al. Assessment of breast cancer risk factors reveals subtype heterogeneity. Cancer Res. 2017;77(13):3708-3717. doi:10.1158/0008-5472.CAN-16-2574

10.

Nguyen

Duong

, et al. A matched case-control study of risk factors for breast cancer risk in vietnam. International Journal of Breast Cancer. 2016;2016:1-7. doi:10.1155/2016/7164623

11.

Trieu

PDY

Mello-Thoms

Peat

Brennan

. Risk factors of female breast cancer in vietnam: A case-control study. Cancer Res Treat. 2017;49(4):990-1000. doi:10.4143/crt.2016.488

12.

Nguyen

Tran

HTT

Nguyen

, et al. Association of fruit, vegetable, and animal food intakes with breast cancer risk overall and by molecular subtype among vietnamese women. Cancer Epidemiol Biomarkers Prev. 2022;31(5):1026-1035. doi:10.1158/1055-9965.EPI-21-1085

13.

Harris

Taylor

Minor

, et al. The REDCap consortium: Building an international community of software platform partners. J Biomed Inf. 2019;95:103208. doi:10.1016/j.jbi.2019.103208

14.

Devi

CRB

Tang

Corbex

. Incidence and risk factors for breast cancer subtypes in three distinct South-East Asian ethnic groups: Chinese, Malay and natives of Sarawak, Malaysia. Int J Cancer. 2012;131(12):2869-2877. doi:10.1002/ijc.27527

15.

Xing

Jin

. A case–control study of reproductive factors associated with subtypes of breast cancer in Northeast China. Med Oncol. 2010;27(3):926-931. doi:10.1007/s12032-009-9308-7

16.

Liabsuetrakul

. Southern soil-transmitted helminths and maternal health working group. is international or asian criteria-based body mass index associated with maternal anaemia, low birthweight, and preterm births among thai population? an observational study. J health popul Nutr. 2011;29(3):218-228. doi:10.3329/jhpn.v29i3.7869

17.

von Elm

Altman

Egger

, et al. Strengthening the reporting of observational studies in epidemiology (strobe) statement: Guidelines for reporting observational studies. BMJ. 2007;335(7624):806-808. doi:10.1136/bmj.39335.541782

18.

Nguyen

, et al. Delay in the diagnosis and treatment of breast cancer in Vietnam. Cancer Med. 2021;10(21):7683-7691. doi:10.1002/cam4.4244

19.

Gao

Shu

Dai

, et al. Association of menstrual and reproductive factors with breast cancer risk: Results from the shanghai breast cancer study. Int J Cancer. 2000;87(2):295-300.

20.

Liu

Gao

Ding

, et al. Physiological, reproductive factors and breast cancer risk in Jiangsu province of China. Asian Pac J Cancer Prev. 2011;12(3):787-790.

21.

de Almeida

Almeida

LAL

Araujo

GMR

Weller

. Reproductive risk factors differ among breast cancer patients and controls in a public hospital of paraiba, Northeast Brazil. Asian Pac J Cancer Prev APJCP. 2015;16(7):2959-2965. doi:10.7314/APJCP.2015.16.7.2959

22.

Winters

Martin

Murphy

Shokar

. Breast cancer epidemiology, prevention, and screening. In Progress in molecular biology and translational science, Vol 151. Elsevier; 2017:1-32. doi:10.1016/bs.pmbts.2017.07.002

23.

Msolly

Gharbi

Ben Ahmed

. Impact of menstrual and reproductive factors on breast cancer risk in Tunisia: A case–control study. Med Oncol. 2013;30(1). doi:10.1007/s12032-013-0480-4

24.

Sun

Shan

, et al. A case-control study on risk factors of breast cancer in China. Arch Med Sci. 2012;8(2):303-309. doi:10.5114/aoms.2012.28558

25.

Sun

Miller

, et al. BMI, reproductive factors, and breast cancer molecular subtypes: A case-control study and meta-analysis. J Epidemiol. 2017;27(4):143-151. doi:10.1016/j.je.2016.05.002

26.

Sisti

Collins

Beck

Tamimi

Rosner

Eliassen

. Reproductive risk factors in relation to molecular subtypes of breast cancer: Results from the nurses’ health studies: Reproductive factors and molecular subtypes of breast cancer. Int J Cancer. 2016;138(10):2346-2356. doi:10.1002/ijc.29968

27.

Henderson

Ross

Judd

Krailo

Pike

. Do regular ovulatory cycles increase breast cancer risk? Cancer. 1985;56(5):1206-1208.

28.

Pike

Henderson

Casagrande

Rosario

Gray

. Oral contraceptive use and early abortion as risk factors for breast cancer in young women. Br J Cancer. 1981;43(1):72-76. doi:10.1038/bjc.1981.10

29.

Henderson

Ross

Judd

Krailo

Pike

. Do regular ovulatory cycles increase breast cancer risk? Cancer. 1985;56(5):1206-1208.

30.

Travis

Key

. Oestrogen exposure and breast cancer risk. Breast Cancer Res. 2003;5(5):239. doi:10.1186/bcr628

31.

Sun

Miller

, et al. BMI, reproductive factors, and breast cancer molecular subtypes: A case-control study and meta-analysis. J Epidemiol. 2017;27(4):143-151. doi:10.1016/j.je.2016.05.002

32.

Akbari

Razzaghi

Homaee

Khayamzadeh

Movahedi

Akbari

. Parity and breastfeeding are preventive measures against breast cancer in Iranian women. Breast Cancer. 2011;18(1):51-55. doi:10.1007/s12282-010-0203-z

33.

Pizot

Boniol

Mullie

, et al. Physical activity, hormone replacement therapy and breast cancer risk: A meta-analysis of prospective studies. Eur J Cancer. 2016;52:138-154. doi:10.1016/j.ejca.2015.10.063

34.

Ren

Zhao

Zhou

Gao

. Induced abortion and breast cancer: results from a population-based case control study in China. Asian Pac J Cancer Prev APJCP. 2014;15(8):3635-3640. doi:10.7314/APJCP.2014.15.8.3635

35.

Galukande

Wabinga

Mirembe

Karamagi

Asea

. Breast cancer risk factors among ugandan women at a tertiary hospital: A case-control study. Oncology. 2016;90(6):356-362. doi:10.1159/000445379

36.

Nguyen

Duong

, et al. A matched case-control study of risk factors for breast cancer risk in vietnam. International Journal of Breast Cancer. 2016;2016:1-7. doi:10.1155/2016/7164623

37.

Trieu

PDY

Mello-Thoms

Peat

Brennan

. Risk factors of female breast cancer in vietnam: A case-control study. Cancer Res Treat. 2017;49(4):990-1000. doi:10.4143/crt.2016.488

38.

Gao

Shu

Dai

, et al. Association of menstrual and reproductive factors with breast cancer risk: Results from the shanghai breast cancer study. Int J Cancer. 2000;87(2):295-300.

39.

Lodha

Nandeshwar

Pal

, et al. Risk factors for breast cancer among women in Bhopal urban agglomerate: A case-control study. Asian Pac J Cancer Prev. 2011;12(8):2111-2115.

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