Abstract
Few epidemiological studies have evaluated the association of choline and betaine intake with breast cancer risk and the results remain inconsistent. This study aimed to assess the relationship between dietary intake of choline and betaine and the risk of breast cancer among Chinese women. A two‐stage case‐control study was conducted, with 807 cases and 807 age‐ (5‐year interval) and residence (rural/urban)‐matched controls. A validated food frequency questionnaire was used to assess dietary intake by face‐to‐face interview. An unconditional logistic regression model was used to calculate multivariate‐adjusted odds ratios (OR) and 95% confidence intervals (CI). A significant inverse association was found between dietary choline and betaine consumption and breast cancer risk. The adjusted OR for the highest quartile of intake compared with the lowest were 0.40 (95% CI = 0.28–0.57, P trend < 0.001) for total choline intake, 0.58 (95% CI = 0.42–0.80, P trend < 0.001) for betaine intake and 0.38 (0.27–0.53, P trend < 0.001) for choline plus betaine intake, respectively. Intakes of individual choline compouds, choline from glycerophosphocholine, phosphocholine, phosphatidylcholine, sphingomyelin and free choline were also negatively associated with breast cancer risk. The inverse association between choline intake and breast cancer risk was primarily confined to participants with low folate level (<242 g/day), with an OR (95% CI) of 0.46 (0.23–0.91) comparing the fourth quartile with the first quartile of choline intake (P trend = 0.005). The present study suggests that consumption of choline and betaine is inversely associated with the risk of breast cancer. The association of choline intake with breast cancer risk is probably modified by folate intake.
DNA methylation is an important epigenetic determinant of gene expression, maintenance of DNA integrity and stability, chromatin modifications and development of mutations – all events implicated in carcinogenesis.1 DNA methylation depends on the availability of methyl groups from S‐adenosylmethionine, the universal methyl donor. Folate can donate a methyl group to homocysteine to create methionine and ultimately to generate S‐adenosylmethionine. Choline and betaine are important human nutrients obtained from the diet from a variety of foods.2, 3 Like folate, choline is a necessary source of methyl groups for methyl group transfer. Choline can be oxidized to betaine and is the immediate precursor of betaine, which serves as a methyl group donor in a reaction converting homocysteine to methionine, and ensures the supply of S‐adenosylmethionine for many methylation reactions.1, 4
The relationship between dietary folate intake and breast cancer risk has been examined in several epidemiological studies and many studies have found that folate intake was inversely associated with breast cancer risk.5, 6, 7 Therefore, it is plausible that choline and betaine intake is also associated with breast cancer risk. So far, few epidemiological studies have examined the association of dietary intakes of choline and betaine with cancer risk,8, 9, 10 although choline and betaine are important methyl donors. Only three studies examining the relationship between choline and betaine intake and breast cancer risk have been published and the results are inconsistent.11, 12, 13 No association was observed in two of the three previous studies on this topic. Thus, more research is needed to clarify this issue.
The objective of the present study was to evaluate the associations between dietary choline and betaine intakes and breast cancer risk among Chinese women in Guangdong province. As homocysteine can be remethylated to methionine by accepting a methyl group from either betaine or folate, methylation of homocysteine by choline and betaine and by folate are highly interrelated.4, 14 We therefore evaluated whether the relationship between choline and betaine intake and breast cancer risk was modified by folate intake.
Materials and Methods
Study subjects
A two‐stage case‐control study was conducted to recruit breast cancer cases and controls. Detailed study methods of the first‐stage case‐control study design are reported elsewhere.15, 16 Briefly, a hospital‐based case‐control study was conducted in Guangdong province, China. Potential case subjects were recruited from patients admitted to the three teaching and general hospitals in the areas being studied. Eligible cases were 25–70‐year‐old natives of Guangdong province or those who have lived in Guangdong for at least 5 years, with incident, primary, histologically confirmed breast cancer diagnosed within 3 months prior to the interview. Women were excluded if they could not understand or speak Mandarin/Cantonese or had a prior history of breast cancer or other cancers. During June 2007 to August 2008, a total of 438 (96%) cases out of 455 eligible cases were successfully interviewed. Control subjects were patients with no history of cancer who were admitted to the same hospitals during the same time period as the case subjects. They were frequency matched by age (5‐year interval) and residence (rural/urban) to the case patients. The controls were also natives of Guangdong province or those who had lived in Guangdong for at least 5 years. They were selected from the departments of Ophthalmology, Plastic and Reconstructive Surgery, Vascular Surgery, Ear‐Nose‐Throat, and Orthopedics and Microsurgery. In total, 448 controls were identified; 10 (2%) controls invited to take part in the study during their hospital stay refused to be interviewed.
To improve the statistical power of the study, we recruited a second set of cases and controls. The second‐stage study is an ongoing case‐control study beginning in September 2011. Between September 2011 and August 2012, 369 cases and 369 controls were recruited. These two studies shared the same diagnostic standard and the same inclusion and exclusion criteria. The distribution of conditions among the control subjects is as follows: glaucoma/uveitis/keratitis/pterygium/dacryocystitis/optic neuritis (376; 46.6%); sudden deafness/acute bacterial/viral otitis media/sinusitis/deviation of nasal septum/tonsillitis (328; 40.7%); varicose veins (43; 5.3%); traumatic skeletal disorders/osteoarthritis/degenerate joint disease (27; 3.4%); orthopedics (22; 2.7%); trifacial neuralgia (9; 1.1%); and acute appendicitis (2; 0.2%).
The procedures and protocols of the present study were approved by The Ethical Committee of School of Public Health, Sun Yat‐sen University, and the Ethical Committee of the Chinese University of Hong Kong. Written informed consent was obtained from all participants.
Assessment of dietary intake
Dietary intake was assessed through an in‐person interview by using an 81‐item food frequency questionnaire (FFQ)17 covering the habitual diet of participants during the preceding 12 months. Participants also reported their recent dietary changes and use of nutritional supplements. Food photographs with usual portion size were used to help participants quantify the portions consumed. During the interview, each woman was asked to report their usual frequency of consumption as the number of times per day, per week, per month, per year or never during the previous year before the time of diagnosis for cases or interview for controls and the average amount of food eaten each time. Information on the frequency of intake and portion size was used to calculate the amount of each food item in grams consumed on average per day. Daily dietary nutrient intakes including choline and betaine and other nutrients were calculated based on the Chinese Food Composition Table18 and values published by Zeisel et al.19, 20 Total dietary intakes of energy, individual compound sources of choline (free choline, glycerophosphocholine, phosphocholine, phosphatidylcholine and sphingomyelin), betaine and folate were calculated by summing the product of the frequency of consumption, usual portion consumed and nutrient content of each food item. Total choline intake was calculated as the sum of choline intake from glycerophosphocholine, phosphocholine, phosphatidylcholine, sphingomyelin and free choline.
Development and validation of the FFQ have previously been described.5, 17 Briefly, 61 female subjects recruited from the community in Guangzhou city completed 3‐day dietary records at intervals of 2 months during a 12‐month period, and two FFQ administered 1 year apart. The correlation coefficients comparing the second FFQ and 18‐day dietary records were 0.34 for choline, 0.26 for betaine, 0.35 for folate, 0.48 for glycerophosphocholine, 0.44 for phosphocholine, 0.23 for phosphatidylcholine and 0.36 for sphingomyelin and free choline, respectively. The correlation coefficients between the two FFQ of choline, betaine, folate, glycerophosphocholine, phosphocholine, phosphatidylcholine, sphingomyelin, free choline were 0.59, 0.44, 0.60, 0.67, 0.64, 0.56, 0.54 and 0.58, respectively.
Data collection
A structured questionnaire was used to collect information on socio‐demographic indicators such as age, educational level, household income, occupation and marital status, anthropometrics including current weight and height, menstrual and reproductive history, family history of breast cancer, physical activity over the past 12 months, smoking and alcohol consumption habits, and prior disease history. Relevant medical information, medical diagnosis and histological findings were abstracted from hospital medical records. Body mass index (BMI) was computed by dividing weight (kg) by height squared (m2). Regular smoking was defined as smoking at least one cigarette per day for more than six consecutive months. Regular drinking was defined as alcohol drinking at least once per week during the past year.
Statistical analyses
All data analyses were performed using spss 13.0 (SPSS Inc., Chicago, IL, USA). Chi‐squared or t tests were used to test differences in socio‐demographic and reproductive factors between the case and control subjects. Total and individual choline and betaine were grouped into quartiles based on their distributions in the control subjects for stage 1 and stage 2 separately, and combined, with the lowest quartile serving as the reference. Unconditional logistic regression models were used to estimate odds ratios (OR) and 95% confidence intervals (CI) of each quartile with the lowest quartile group serving as the reference after adjusting for the potential confounding variables. Potential confounders adjusted for in multivariate models included occupation (categorical, administrator/other white collar worker, blue collar worker and farmer/other), BMI (continuous), age at menarche, live births and age at first live birth (≤19, 20–24, 25–29, ≥30, nulliparous), family history of breast cancer in a first‐degree relative (yes/no), passive smoking from husband (yes/no), alcohol consumption (yes/no), physical activity (categorical, never, occasional and ≥1 time per week) and study stage (stage 1 or 2). Total energy intake was adjusted using the residual method. 21 Tests for trend were performed by entering the categorical variables as continuous variables in the models.
We previously observed that dietary folate intake was inversely associated with breast cancer risk.5 Because both folate and choline (through betaine) are involved in methyl‐group metabolism as methyl‐group donors, analysis stratified by folate intake values above and below the median (<242 vs ≥242 μg/day) was conducted to evaluate the potential modifying effect on choline and betaine intake and breast cancer risk. Because pre‐ and postmenopausal breast cancer probably has a separate disease etiology, we further investigated associations of choline and betaine consumption with breast cancer risk by menopausal status. Likelihood ratio tests comparing models with and without multiplicative interaction terms were used to assess the potential effect measure modification of the association between choline and betaine intakes and breast cancer risk by folate intakes and menopause status. Alcohol is a known folate antagonist.22, 23 It might also interfere with choline or betaine absorption. Analysis of non‐drinkers was performed to evaluate the association of choline or betaine intake with breast cancer risk. All statistical tests were based on two‐tailed probability values with P values of ≤0.05 interpreted as statistically significant.
Results
The socio‐demographic and established breast cancer risk factors of the two‐stage study subjects are shown in Table 1. Overall, the participant characteristics in two‐stage studies were highly comparable. In both the first‐ and second‐stage study, compared with controls, cases had an earlier age at menarche, older age at first live birth, higher BMI and consumed more alcohol. Cases were more likely to have a history of breast cancer in a first‐degree relative, a history of passive smoking from husband, and were less likely to be physically active than controls. No significant differences were found between the case and control subjects in educational level, marital status, household income or reproductive factors, including nulliparous, number of live births, age at menopause and use of oral contraceptive.
Table 1.
Comparison of breast cancer cases and controls on general characteristics among Chinese women
| Characteristics | Stage 1 | Stage 2 | Total | P | |||||
|---|---|---|---|---|---|---|---|---|---|
| Cases (n = 438) | Controls (n = 438) | P | Cases (n = 369) | Controls (n = 369) | P | Cases (n = 807) | Controls (n = 807) | ||
| Age (mean ± SD) (years) | 47.04 ± 9.53 | 47.14 ± 9.58 | 0.875 | 48.18 ± 9.44 | 48.85 ± 9.40 | 0.334 | 47.56 ± 9.50 | 47.93 ± 9.53 | 0.445 |
| Marital status, n (%) | |||||||||
| Married | 409 (93.4) | 413 (94.3) | 0.574 | 342 (92.7) | 341 (92.4) | 0.889 | 751 (93.1) | 754 (93.4) | 0.766 |
| Educational level, n (%) | 0.401 | 0.014 | 0.158 | ||||||
| Primary school or below | 106 (24.2) | 127 (29.0) | 101 (27.4) | 77 (20.9) | 207 (25.7) | 204 (25.3) | |||
| Junior high school | 127 (29.0) | 116 (26.5) | 89 (24.1) | 83 (22.5) | 216 (26.8) | 199 (24.7) | |||
| Senior high school/secondary technical school | 109 (24.9) | 109 (24.9) | 94 (25.5) | 133 (36.0) | 203 (25.2) | 242 (30.0) | |||
| College or above | 96 (21.9) | 86 (19.6) | 85 (23.0) | 76 (20.6) | 181 (22.4) | 162 (20.1) | |||
| Occupation, n (%) | 0.157 | 0.022 | 0.005 | ||||||
| Administrator/other white collar worker | 190 (43.4) | 166 (37.9) | 151 (40.9) | 126 (34.1) | 341 (42.3) | 292 (36.2) | |||
| Blue collar worker | 97 (22.1) | 118 (26.9) | 98 (26.6) | 132 (35.8) | 195 (24.2) | 250 (31.0) | |||
| Farmer/other | 151 (34.5) | 154 (35.2) | 120 (32.5) | 111 (30.1) | 271 (33.6) | 265 (32.8) | |||
| Household income, n (%) | 0.751 | 0.224 | 0.623 | ||||||
| <2000 yuan/month | 157 (35.8) | 161 (36.8) | 114 (30.9) | 95 (25.7) | 271 (33.6) | 256 (31.7) | |||
| 2001–5000 yuan/month | 152 (34.7) | 149 (34.0) | 115 (31.2) | 140 (37.9) | 267 (33.1) | 289 (35.8) | |||
| 5001–8000 yuan/month | 68 (15.5) | 59 (13.5) | 90 (24.4) | 88 (23.8) | 158 (19.6) | 147 (18.2) | |||
| >8001 yuan/month | 61 (13.9) | 69 (15.8) | 50 (13.6) | 46 (12.5) | 111 (13.8) | 115 (14.3) | |||
| Body mass index (mean ± SD) | 22.92 ± 3.33 | 22.46 ± 3.05 | 0.038 | 22.99 ± 3.43 | 22.48 ± 2.97 | 0.034 | 22.95 ± 3.38 | 22.47 ± 3.02 | 0.003 |
| Regular smoker, n (%) | 7 (1.6) | 2 (0.4) | 0.094 | 4 (1.1) | 3 (0.8) | 0.704 | 11 (1.4) | 5 (0.6) | 0.132 |
| Passive smoker from husband, n (%) | 202 (46.1) | 170 (38.8) | 0.029 | 194 (52.6) | 118 (32.0) | <0.001 | 396 (49.1) | 288 (35.7) | <0.001 |
| Regular drinker, n (%) | 12 (2.7) | 10 (2.3) | 0.666 | 29 (7.9) | 11 (3.0) | 0.003 | 42 (5.2) | 21 (2.6) | 0.007 |
| Physical activity (exercise for health), n (%) | 0.016 | <0.001 | <0.001 | ||||||
| Never | 170 (38.8) | 139 (31.7) | 289 (78.3) | 103 (27.9) | 459 (56.9) | 242 (30.0) | |||
| Occasional | 46 (10.5) | 35 (8.0) | 19 (5.1) | 137 (37.1) | 65 (8.1) | 172 (21.3) | |||
| ≥1 times/week | 222 (50.7) | 264 (60.3) | 61 (16.5) | 129 (35.0) | 283 (35.1) | 393 (48.7) | |||
| Age at menarche (mean ± SD) (years) | 14.82 ± 1.88 | 15.11 ± 1.84 | 0.019 | 14.46 ± 1.81 | 14.79 ± 1.80 | 0.012 | 14.65 ± 1.86 | 14.96 ± 1.83 | 0.001 |
| Nulliparous, n (%) | 17 (3.9) | 19 (4.3) | 0.734 | 13 (3.5) | 15 (4.1) | 0.700 | 30 (3.7) | 34 (4.2) | 0.610 |
| No. live births (mean ± SD)a | 1.98 ± 1.12 | 2.03 ± 1.20 | 0.532 | 1.94 ± 1.09 | 1.77 ± 1.08 | 0.046 | 1.96 ± 1.10 | 1.91 ± 1.15 | 0.412 |
| Age at first live birth, n (%)a | 0.050 | 0.098 | 0.016 | ||||||
| ≤19 years | 11 (2.6) | 11 (2.6) | 13 (3.6) | 10 (2.8) | 24 (3.1) | 21 (2.7) | |||
| 20–24 years | 139 (33.0) | 170 (40.6) | 116 (32.6) | 139 (39.3) | 255 (32.8) | 309 (40.0) | |||
| 25–29 years | 227 (53.9) | 201 (48.0) | 170 (47.8) | 167 (47.2) | 397 (51.1) | 368 (47.6) | |||
| ≥30 years | 44 (10.5) | 37 (8.8) | 57 (16.0) | 38 (10.7) | 101 (13.0) | 75 (9.7) | |||
| Months of breast feeding, n (%)a | 0.034 | 0.077 | 0.375 | ||||||
| Never | 49 (11.6) | 26 (6.2) | 38 (10.3) | 46 (13.0) | 87 (11.2) | 72 (9.3) | |||
| 1–3 | 21 (5.0) | 22 (5.3) | 23 (6.2) | 22 (6.2) | 44 (5.7) | 44 (5.7) | |||
| 4–11 | 95 (22.6) | 108 (25.8) | 83 (22.5) | 103 (29.1) | 178 (22.9) | 211 (27.3) | |||
| 12–23 | 118 (285.0) | 102 (24.3) | 87 (23.6) | 92 (26.0) | 205 (26.4) | 194 (25.1) | |||
| ≥24 | 138 (32.8) | 161 (38.4) | 125 (33.9) | 91 (25.7) | 263 (33.8) | 252 (32.6) | |||
| Age at menopause (mean ± SD) (years)b | 49.33 ± 3.96 | 49.06 ± 3.93 | 0.579 | 50.12 ± 4.08 | 49.56 ± 3.84 | 0.251 | 49.71 ± 4.03 | 49.32 ± 3.89 | 0.253 |
| Menopausal status, n (%) | |||||||||
| Premenopausal | 306 (69.9) | 295 (67.4) | 0.423 | 243 (65.9) | 218 (59.1) | 0.057 | 549 (68.0) | 513 (63.6) | 0.059 |
| Postmenopausal | 132 (30.1) | 143 (32.6) | 126 (34.1) | 151 (40.9) | 258 (32.0) | 294 (36.4) | |||
| Mother/sister/daughter with breast cancer, n (%) | 17 (3.9) | 4 (0.9) | 0.004 | 15 (4.1) | 4 (1.1) | 0.011 | 32 (4.0) | 8 (1.0) | <0.001 |
| Ever used an oral contraceptive, n (%) | 27 (6.2) | 21 (4.8) | 0.373 | 30 (8.1) | 20 (5.4) | 0.143 | 57 (7.1) | 41 (5.1) | 0.095 |
| Total energy intake (mean ± SD) (kcal/day) | 1464 ± 430 | 1504 ± 429 | 0.160 | 1473 ± 403 | 1627 ± 461 | <0.001 | 1468 ± 418 | 1560 ± 448 | <0.001 |
| Total choline intake (mean ± SD) (mg/day) | 141.36 ± 63.46 | 164.97 ± 72.39 | <0.001 | 153.32 ± 76.68 | 182.93 ± 79.12 | <0.001 | 146.83 ± 70.02 | 173.18 ± 76.02 | <0.001 |
| Betaine intake (mean ± SD) (mg/day) | 275.93 ± 261.44 | 326.91 ± 279.04 | 0.005 | 219.62 ± 151.84 | 304.35 ± 222.43 | <0.001 | 250.18 ± 219.94 | 316.60 ± 254.81 | <0.001 |
| Folate intake (mean ± SD) (μg/day) | 207.41 ± 72.51 | 240.08 ± 85.04 | <0.001 | 214.06 ± 81.46 | 269.13 ± 98.99 | <0.001 | 210.45 ± 76.75 | 253.36 ± 92.76 | <0.001 |
Among parous women.
Among menopausal women.
The mean (±SD) intakes were 173 ± 76 mg/day for total choline, 317 ± 255 mg/day for betaine and 490 ± 291 mg/day for choline plus betaine among the control subjects (Table 1). More than half (57.8%) the choline intake came from phosphatidylcholine, followed by free choline (22.1%), glycerophosphocholine (8.6%), phosphocholine (8.4%) and sphingomyelin (3.1%) (Table 2). Compared with controls, cases tended to have lower intakes of total choline, individual choline compounds and betaine.
Table 2.
Comparison of five main individual choline compound intakes between breast cancer cases and controls
| Choline compound | Cases (n = 807) | Controls (n = 807) | P a | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| Mean | SD | P25 | P50 | P75 | Mean | SD | P25 | P50 | P75 | ||
| Free choline (mg/day) | 32.5 | 15.1 | 21.8 | 29.3 | 40.0 | 39.0 | 16.9 | 27.1 | 36.2 | 47.7 | <0.001 |
| Choline from glycerophosphocholine (mg/day) | 12.6 | 9.2 | 6.8 | 9.5 | 15.1 | 16.0 | 10.8 | 8.3 | 12.6 | 20.9 | <0.001 |
| Choline from phosphocholine (mg/day) | 12.4 | 7.8 | 7.2 | 10.7 | 15.5 | 15.1 | 8.5 | 9.5 | 13.7 | 18.9 | <0.001 |
| Choline from phosphatidylcholine (mg/day) | 84.9 | 46.0 | 52.9 | 74.0 | 106.8 | 98.0 | 49.0 | 60.9 | 91.8 | 125.4 | <0.001 |
| Choline from sphingomyelin (mg/day) | 4.5 | 3.3 | 2.2 | 3.8 | 6.0 | 5.4 | 3.9 | 2.6 | 4.6 | 7.4 | <0.001 |
Wilcoxon rank‐sum test comparing median consumption levels between cases and controls.
P25, P50 and P75 represent the 25th, 50th and 75th percentile, respectively.
SD, standard deviation.
The main food sources of total choline, betaine and folate among control subjects are listed in Table 3. Spinach contributed 74.24% of the betaine intake, whereas the other main sources of betaine were grain products. Eggs, chicken and whole milk were the main food sources of total choline. Rice, Chinese cabbage and spinach were the main food sources of folate. The correlation coefficients were 0.487 between folate and choline, 0.730 between folate and betaine and 0.366 between choline and betaine.
Table 3.
Top five food sources of total choline, betaine and folate among control subjects
| Total choline | Betaine | Folate | |||
|---|---|---|---|---|---|
| Food | Percentage | Food | Percentage | Food | Percentage |
| Eggs | 24.57 | Spinach | 74.24 | Rice | 18.22 |
| Chicken | 20.53 | Pasta | 16.38 | Chinese cabbage | 10.04 |
| Broccoli | 7.61 | White bread | 3.93 | Spinach | 8.04 |
| Spinach | 4.82 | Wheat bread | 2.85 | Eggs | 7.71 |
| Whole milk | 3.82 | Potatoes | 1.05 | Soybean milk | 4.91 |
Associations between quartiles of intakes of dietary choline and betaine and breast cancer risk are presented in Table 4. Intakes of total choline and betaine were inversely related to breast cancer risk in a dose‐response manner in stage 1, stage 2 and the combined study (P trend < 0.001). In the combined subjects from the two‐stage study, the OR for the highest quartile of intake in comparison with the lowest were 0.37 (95% CI = 0.28–0.49, P trend < 0.001) for total choline intake and 0.46 (95% CI = 0.34–0.62, P trend < 0.001) for betaine intake, respectively. Further adjustment for potential confounding by the major risk factors for breast cancer did not materially change the results.
Table 4.
Odds ratios (OR) and 95% confidence intervals (CI) of breast cancer according to quartiles of choline and betaine intake in stage 1, stage 2 and the combined study
| Methyl donors | Stage 1 | Stage 2 | Total | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Intake | No. cases/controls | Crude OR (95% CI) | Adjusted OR (95% CI)a | Intake | No. cases/controls | Crude OR (95% CI) | Adjusted OR (95% CI)a | Intake | No. cases/controls | Crude OR (95% CI) | Adjusted OR (95% CI)a | |
| Total choline (mg/day) | <111.64 | 162/109 | 1 | 1 | <123.66 | 157/92 | 1 | 1 | <117.65 | 321/201 | 1 | 1 |
| 111.64–155.55 | 125/110 | 0.70 (0.50–0.99) | 0.71 (0.49–1.02) | 123.66–172.89 | 94/93 | 0.70 (0.47–1.04) | 0.83 (0.50–1.36) | 117.65–163.62 | 227/202 | 0.70 (0.54–0.91) | 0.70 (0.53–0.93) | |
| 155.55–207.86 | 86/110 | 0.42 (0.29–0.61) | 0.49 (0.33–0.72) | 172.89–232.24 | 67/92 | 0.45 (0.30–0.68) | 0.58 (0.31–1.10) | 163.62–217.47 | 141/203 | 0.44 (0.33–0.57) | 0.47 (0.34–0.64) | |
| >207.86 | 65/109 | 0.41 (0.28–0.62) | 0.35 (0.22–0.54) | >232.24 | 51/92 | 0.32 (0.21–0.49) | 0.51 (0.30–0.87) | >217.47 | 118/201 | 0.37 (0.28–0.49) | 0.40 (0.28–0.57) | |
| P trend | <0.001 | <0.001 | P trend | <0.001 | 0.022 | P trend | <0.001 | <0.001 | ||||
|
Betaine (mg/day) |
<132.41 | 123/109 | 1 | 1 | <154.75 | 146/92 | 1 | 1 | <140.14 | 260/200 | 1 | 1 |
| 132.41–239.18 | 126/110 | 1.00 (0.70–1.43) | 1.10 (0.75–1.60) | 154.75–257.51 | 115/93 | 0.85 (0.58–1.25) | 0.98 (0.61–1.58) | 140.14–246.87 | 248/204 | 0.94 (0.72–1.21) | 1.13 (0.84–1.50) | |
| 239.18–440.90 | 117/110 | 0.88 (0.61–1.29) | 0.97 (0.66–1.43) | 257.51–385.28 | 65/92 | 0.51 (0.34–0.76) | 0.56 (0.33–0.95) | 246.87–408.04 | 178/201 | 0.68 (0.52–0.90) | 0.83 (0.61–1.12) | |
| >440.90 | 72/109 | 0.63 (0.44–0.92) | 0.60 (0.39–0.92) | >385.28 | 43/92 | 0.28 (0.17–0.45) | 0.45 (0.25–0.80) | >408.04 | 121/202 | 0.46 (0.34–0.62) | 0.58 (0.42–0.80) | |
| P trend | 0.015 | 0.021 | P trend | <0.001 | 0.002 | P trend | <0.001 | <0.001 | ||||
|
Total choline + betaine (mg/day) |
<279.40 | 144/109 | 1 | 1 | <314.00 | 172/92 | 1 | 1 | <297.57 | 320/201 | 1 | 1 |
| 279.40–407.11 | 116/110 | 0.92 (0.64–1.33) | 0.83 (0.56–1.22) | 314.00–440.16 | 93/93 | 0.50 (0.34–0.74) | 0.70 (0.43–1.13) | 297.57–422.50 | 204/202 | 0.63 (0.49–0.82) | 0.74 (0.56–1.00) | |
| 407.11–627.38 | 115/110 | 0.76 (0.53–1.08) | 0.81 (0.55–1.18) | 440.16–600.19 | 59/92 | 0.30 (0.20–0.44) | 0.45 (0.26–0.78) | 422.50–615.63 | 176/203 | 0.54 (0.42–0.71) | 0.67 (0.50–0.92) | |
| >627.38 | 63/109 | 0.43 (0.29–0.63) | 0.43 (0.28–0.66) | >600.19 | 45/92 | 0.24 (0.15–0.38) | 0.40 (0.22–0.71) | >615.63 | 107/201 | 0.33 (0.25–0.45) | 0.38 (0.27–0.53) | |
| P trend | <0.001 | 0.001 | P trend | <0.001 | <0.001 | P trend | <0.001 | <0.001 | ||||
Odds ratios were adjusted for occupation, body mass index, age at menarche, live births and age at first live birth, mother/sister/daughter with breast cancer, passive smoking, alcohol consumption, physical activity, total energy intake and study stage.
Because the conversion of choline to betaine is irreversible when it donates a methyl group to homocysteine, we also examined the combined intakes of choline and betaine and an inverse association with breast cancer risk was also observed. The adjusted OR (95% CI) for the fourth versus the first quartile was 0.38 (0.27–0.53) (P trend < 0.001).
Intakes of individual compound sources of choline, choline from glycerophosphocholine, phosphocholine, phosphatidylcholine, sphingomyelin and free choline were similarly inversely associated with breast cancer risk in the separate analysis in the stage 1 and 2 study and the combined study. Compared with the lowest quartile, the adjusted OR (95% CI) of breast cancer for the highest quartile was 0.44 (0.31–0.63) for choline from glycerophosphocholine, 0.40 (0.29–0.56) for choline from phosphocholine, 0.61 (0.44–0.85) for choline from phosphatidylcholine, 0.56 (0.40–0.80) for choline from sphingomyelin and 0.38 (0.26–0.54) for free choline in the combined subjects from the two‐stage study, respectively (Table 5).
Table 5.
Odds ratios (OR) and 95% confidence intervals (CI) of breast cancer according to quartiles of five main choline‐containing compound intake in stage 1, stage 2 and the combined study
| Choline compound | Stage 1 | Stage 2 | Total | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Intake | No. cases/controls | Crude OR (95% CI) | Adjusted OR (95% CI)a | Intake | No. cases/controls | Crude OR (95% CI) | Adjusted OR (95% CI)a | Intake | No. cases/controls | Crude OR (95% CI) | Adjusted OR (95% CI)a | |
| Free choline (mg/day) | <25.74 | 167/109 | 1 | 1 | <28.42 | 169/92 | 1 | 1 | <27.12 | 342/201 | 1 | 1 |
| 25.74–35.29 | 128/110 | 0.76 (0.54–1.08) | 0.72 (0.49–1.04) | 28.42–37.34 | 86/93 | 0.50 (0.34–0.74) | 0.65 (0.40–1.05) | 27.12–36.20 | 209/203 | 0.60 (0.47–0.78) | 0.68 (0.51–0.90) | |
| 35.29–46.99 | 84/110 | 0.50 (0.34–0.72) | 0.46 (0.31–0.69) | 37.34–48.70 | 60/92 | 0.36 (0.24–0.54) | 0.47 (0.27–0.82) | 36.20–47.68 | 144/203 | 0.42 (0.32–0.55) | 0.46 (0.33–0.62) | |
| >46.99 | 59/109 | 0.35 (0.24–0.53) | 0.30 (0.19–0.49) | >48.70 | 54/92 | 0.32 (0.21–0.49) | 0.46 (0.25–0.84) | >47.68 | 112/200 | 0.33 (0.25–0.44) | 0.38 (0.26–0.54) | |
| P trend | <0.001 | <0.001 | P trend | <0.001 | 0.004 | P trend | <0.001 | <0.001 | ||||
| Choline from glycerophosphocholine (mg/day) | <8.18 | 159/109 | 1 | 1 | <8.35 | 153/92 | 1 | 1 | <8.29 | 314/202 | 1 | 1 |
| 8.18–12.05 | 112/110 | 0.70 (0.49–1.00) | 0.72 (0.49–1.06) | 8.35–13.22 | 114/92 | 0.74 (0.51–1.09) | 1.16 (0.70–1.92) | 8.29–12.58 | 216/202 | 0.69 (0.53–0.89) | 0.82 (0.61–1.10) | |
| 12.05–20.33 | 93/110 | 0.58 (0.40–0.84) | 0.60 (0.40–0.90) | 13.22–22.09 | 60/93 | 0.39 (0.26–0.59) | 0.46 (0.26–0.81) | 12.58–20.93 | 161/200 | 0.52 (0.39–0.68) | 0.64 (0.47–0.89) | |
| >20.33 | 74/109 | 0.46 (0.32–0.68) | 0.45 (0.29–0.70) | >22.09 | 42/92 | 0.28 (0.18–0.43) | 0.36 (0.19–0.70) | >20.93 | 116/203 | 0.37 (0.28–0.49) | 0.44 (0.31–0.63) | |
| P trend | <0.001 | <0.001 | P trend | <0.001 | <0.001 | P trend | <0.001 | <0.001 | ||||
| Choline from phosphocholine (mg/day) | <9.18 | 179/109 | 1 | 1 | <9.71 | 155/92 | 1 | 1 | <9.50 | 336/202 | 1 | 1 |
| 9.18–13.65 | 117/110 | 0.65 (0.46–0.92) | 0.63 (0.44–0.91) | 9.71–13.79 | 83/92 | 0.54 (0.36–0.79) | 0.65 (0.39–1.07) | 9.50–13.66 | 190/202 | 0.56 (0.43–0.74) | 0.61 (0.46–0.81) | |
| 13.65–18.72 | 78/110 | 0.43 (0.30–0.63) | 0.41 (0.27–0.60) | 13.79–19.06 | 75/93 | 0.48 (0.32–0.71) | 0.72 (0.44–1.20) | 13.66–18.87 | 162/204 | 0.48 (0.36–0.63) | 0.49 (0.36–0.66) | |
| >18.72 | 64/109 | 0.36 (0.24–0.53) | 0.34 (0.23–0.52) | >19.06 | 56/92 | 0.36 (0.24–0.55) | 0.59 (0.33–1.06) | >18.87 | 119/199 | 0.36 (0.27–0.48) | 0.40 (0.29–0.56) | |
| P trend | <0.001 | <0.001 | P trend | <0.001 | 0.051 | P trend | <0.001 | <0.001 | ||||
| Choline from phosphatidylcholine (mg/day) | <57.73 | 139/110 | 1 | 1 | <65.67 | 141/92 | 1 | 1 | <60.92 | 272/201 | 1 | 1 |
| 57.73–84.34 | 136/109 | 0.99 (0.69–1.41) | 0.91 (0.63–1.32) | 65.67–100.41 | 113/92 | 0.80 (0.55–1.17) | 0.96 (0.59–1.56) | 60.92–91.78 | 259/203 | 0.94 (0.73–1.22) | 0.95 (0.72–1.27) | |
| 84.34–120.21 | 91/110 | 0.66 (0.45–0.95) | 0.62 (0.41–0.92) | 100.41–137.34 | 48/93 | 0.34 (0.22–0.52) | 0.38 (0.21–0.67) | 91.78–125.39 | 127/202 | 0.46 (0.35–0.62) | 0.52 (0.38–0.72) | |
| >120.21 | 72/109 | 0.52 (0.35–0.77) | 0.48 (0.31–0.74) | >137.34 | 67/92 | 0.48 (0.32–0.72) | 0.78 (0.44–1.38) | >125.39 | 149/201 | 0.55 (0.41–0.72) | 0.61 (0.44–0.85) | |
| P trend | <0.001 | <0.001 | P trend | <0.001 | 0.069 | P trend | <0.001 | <0.001 | ||||
| Choline from sphingomyelin (mg/day) | <2.36 | 130/109 | 1 | 1 | <3.26 | 142/92 | 1 | 1 | <2.58 | 253/202 | 1 | 1 |
| 2.36–4.14 | 116/110 | 0.88 (0.61–1.27) | 0.84 (0.58–1.22) | 3.26–5.26 | 101/93 | 0.70 (0.48–1.03) | 1.09 (0.65–1.84) | 2.58–4.59 | 239/201 | 0.95 (0.73–1.24) | 0.94 (0.70–1.26) | |
| 4.14–6.45 | 102/112 | 0.76 (0.53–1.10) | 0.74 (0.50–1.10) | 5.26–8.33 | 94/92 | 0.66 (0.45–0.98) | 0.65 (0.39–1.08) | 4.59–7.39 | 193/203 | 0.76 (0.58–1.00) | 0.88 (0.64–1.19) | |
| >6.45 | 90/107 | 0.70 (0.48–1.03) | 0.71 (0.46–1.08) | >8.33 | 32/92 | 0.22 (0.14–0.36) | 0.27 (0.14–0.54) | >7.39 | 122/201 | 0.48 (0.36–0.65) | 0.56 (0.40–0.80) | |
| P trend | 0.049 | 0.081 | P trend | <0.001 | 0.014 | P trend | <0.001 | 0.003 | ||||
Odds ratios were adjusted for occupation, body mass index, age at menarche, live births and age at first live birth, mother/sister/daughter with breast cancer, passive smoking, alcohol consumption, physical activity, total energy intake and study stage.
Stratified analyses by levels of folate intake showed the inverse association between choline or choline plus betaine intake with breast cancer risk only among women with low folate level (OR for the highest vs lowest quartile 0.46 [95% CI = 0.23–0.91, P trend = 0.005] and 0.46 [95% CI = 0.26–0.81, P trend = 0.011]), but not among those with a high folate intake. However, the interaction effect between consumption of folate and choline was not statistically significant (P for interaction = 0.437). Betaine intake was inversely associated with breast cancer risk at the low level of folate intake but the association was not statistically significant (Table 6). We also examined menopausal status as a potential effect modifier but found similar inverse associations across the strata (Table 7). Sensitivity analyses excluding women with alcohol intake yielded similar results of the association of choline and betaine intake and breast cancer risk (data not shown).
Table 6.
Associations between quartiles of choline and betaine intake and breast cancer risk according to folate intake
| Methyl donors | Quartile 1 | Quartile 2 | Quartile 3 | Quartile 4 | P trend |
|---|---|---|---|---|---|
| Total choline | |||||
| Folate <242 μg/day | |||||
| No. cases/controls | 310/182 | 186/128 | 82/68 | 20/25 | 0.005 |
| Adjusted OR (95% CI)a | 1 | 0.76 (0.55–1.04) | 0.65 (0.43–0.99) | 0.46 (0.23–0.91) | |
| Folate ≥242 μg/day | |||||
| No. cases/controls | 11/19 | 41/74 | 59/135 | 98/176 | 0.970 |
| Adjusted OR (95% CI)a | 1 | 0.68 (0.27–1.72) | 0.56 (0.23–1.36) | 0.76 (0.32–1.84) | |
| P interaction | 0.437 | ||||
| Betaine | |||||
| Folate <242 μg/day | |||||
| No. cases/controls | 239/149 | 191/117 | 118/88 | 50/49 | 0.130 |
| Adjusted OR (95% CI)a | 1 | 1.11 (0.80–1.55) | 0.88 (0.60–1.28) | 0.68 (0.42–1.09) | |
| Folate ≥242 μg/day | |||||
| No. cases/controls | 21/51 | 57/87 | 60/113 | 71/153 | 0.756 |
| Adjusted OR (95% CI)a | 1 | 1.71 (0.86–3.38) | 1.38 (0.71–2.70) | 1.19 (0.62–2.29) | |
| P interaction | 0.670 | ||||
| Total choline + betaine | |||||
| Folate <242 μg/day | |||||
| No. cases/controls | 307/170 | 160/126 | 102/75 | 29/32 | |
| Adjusted OR (95% CI)a | 1 | 0.74 (0.53–1.02) | 0.80 (0.54–1.18) | 0.46 (0.26–0.81) | 0.011 |
| Folate ≥242 μg/day | |||||
| No. cases/controls | 13/31 | 44/76 | 74/128 | 78/169 | |
| Adjusted OR (95% CI)a | 1 | 1.50 (0.66–3.46) | 1.35 (0.61–2.98) | 1.06 (0.48–2.31) | 0.424 |
| P interaction | 0. 694 | ||||
Odds ratios were adjusted for occupation, body mass index, age at menarche, live births and age at first live birth, mother/sister/daughter with breast cancer, passive smoking, alcohol consumption, physical activity, total energy intake and study stage. CI, confidence interval; OR, odds ratio.
Table 7.
Associations between quartiles of choline and betaine intake and breast cancer risk according to menopausal status
| Methyl donors | Quartile 1 | Quartile 2 | Quartile 3 | Quartile 4 | p trend |
|---|---|---|---|---|---|
| Total choline | |||||
| Pre‐menopause | |||||
| No. cases/controls | 220/128 | 159/123 | 88/144 | 82/118 | |
| Adjusted OR (95% CI)a | 1 | 0.76 (0.54–1.08) | 0.40 (0.27–0.60) | 0.47 (0.30–0.72) | <0.001 |
| Postmenopause | |||||
| No. cases/controls | 101/73 | 68/79 | 53/59 | 36/83 | |
| Adjusted OR (95% CI)a | 1 | 0.60 (0.36–1.01) | 0.67 (0.38–1.19) | 0.32 (0.17–0.63) | 0.003 |
| P interaction | 0.945 | ||||
| Betaine | |||||
| Pre‐menopause | |||||
| No. cases/controls | 170/121 | 166/125 | 125/134 | 88/133 | |
| Adjusted OR (95% CI)a | 1 | 1.17 (0.82–1.69) | 0.83 (0.57–1.20) | 0.60 (0.40–0.89) | 0.004 |
| Postmenopause | |||||
| No. cases/controls | 90/79 | 82/79 | 53/67 | 33/69 | |
| Adjusted OR (95% CI)a | 1 | 1.03 (0.63–1.68) | 0.83 (0.48–1.44) | 0.50 (0.27–0.92) | 0.031 |
| P interaction | 0.830 | ||||
| Total choline + betaine | |||||
| Pre‐menopause | |||||
| No. cases/controls | 210/127 | 143/125 | 121/130 | 75/131 | |
| Adjusted OR (95% CI)a | 1 | 0.82 (0.57–1.18) | 0.73 (0.50–1.07) | 0.40 (0.27–0.61) | <0.001 |
| Postmenopause | |||||
| No. cases/controls | 110/74 | 61/77 | 55/73 | 32/70 | |
| Adjusted OR (95% CI)a | 1 | 0.63 (0.38–1.06) | 0.61 (0.35–1.05) | 0.32 (0.17–0.62) | 0.001 |
| P interaction | 0.711 | ||||
Odds ratios were adjusted for occupation, body mass index, age at menarche, live births and age at first live birth, mother/sister/daughter with breast cancer, passive smoking, alcohol consumption, physical activity, total energy intake, and study stage. CI, confidence interval; OR, odds ratio.
Discussion
This two‐stage case‐control study examined the association between choline and betaine intake and breast cancer risk among Chinese women. Our results found that higher intakes of choline and betaine were associated with a decreased risk of breast cancer. Choline intakes from individual sources were also inversely associated with breast cancer risk. The negative association between choline intake and breast cancer risk was modified by level of folate intake.
Studies examining the associations between choline and betaine intake and breast cancer risk have yielded inconsistent results. The Nurses' Health Study II, conducted in the USA, was the first study on choline and betaine intake and breast cancer risk.11 This study showed no evidence that higher intakes of choline and betaine reduce the risk of pre‐menopausal breast cancer, with an adjusted relative risk (RR) (95% CI) of 0.86 (0.57–1.30) for choline (P trend = 0.67) and 0.85 (0.54–1.33) for betaine (P trend = 0.55) comparing the top and bottom quintiles. Cho et al.12 also reported that no association was found between choline or betaine intake and the risk of postmenopausal breast cancer in the Nurses' Health Study; the RR (95% CI) were 1.10 (0.99–1.22, P trend = 0.14) for choline and 0.98 (0.89–1.09, P trend = 0.96) for betaine comparing the highest and lowest quintiles. However, one case‐control study of 1508 breast cancer cases and 1556 controls found an inverse association between choline intake and breast cancer risk; the OR was 0.76 (95% CI = 0.58–1.00) comparing the top quintile with the bottom quintile.13 Inconsistent results were also found on the relationships between choline and betaine intake and other cancers. No associations were found between intake of choline and betaine and the risk of ovarian cancer and colorectal cancer.9, 10 In contrast, a nested case‐control study reported that an elevated plasma concentration of choline was associated with an increased risk of prostate cancer,8 most likely because plasma choline levels can reflect dietary intake, genetic influences and other factors. Becasue of the limited studies, the protective effects of choline and betaine intake on breast cancer risk observed in both pre‐ and postmenopausal women in the present study need to be confirmed by further research in other populations.
Because phosphatidylcholine and sphingomyelin are lipid soluble, whereas free choline and other sources of choline including phosphocholine and glycerophosphocholine are water soluble, the bioavailability of different choline sources might differ. However, analyses of individual choline compounds revealed that intakes from different sources were all associated with a reduced risk of breast cancer.
In the present study, the inverse association between choline intake and breast cancer risk appeared to be particularly strong among those with a lower level of folate intake. Our data support the contention that individuals with a low folate intake might benefit from the intake of choline. This concurs with studies in animals and humans indicating the use of choline for methyl transfer reactions in the absence of folate. Animal studies reported a reduction in hepatic choline content in rats fed a folate‐deficient diet compared with controls.24 A folate‐depletion study conducted in men and women also showed that the need for choline is significantly increased during folate deficiency.25 A modifying effect of folate intake on choline was also found in the Framingham Offspring Study.26 This study showed that the inverse association between choline intake and homocysteine levels was limited to participants with low levels of folate intake (≤250 μg/day).26 However, the Nurses' Health Study found no association between choline intake and breast cancer risk when stratified by levels of folate intake.12 Half of the women in this cohort had adequate folate intake (≥400 μg/day), thus choline might not be as important in a population with low folate intake.
Dietary choline is obtained primarily from animal sources, whereas betaine is largely derived from plant sources, as is folate.19 As folate and betaine in human diets mainly come from plant foods and share the same food sources, participants with a lower intake level of folate might simultaneously have a lower betaine intake level. This might explain the less significant effect of dietaty folate on the association of betaine intake with breast cancer risk, as observed in the present study.
In China, the recommended intake for choline is 450 mg/day27 and no recommended daily intake is set for betaine. The mean dietary choline intake in the control group of the present study was 173 mg/day, which shows the potential deficiency of choline in the current study population.
The present study had some limitations. Selection bias is a potential limitation in hospital‐based case‐control studies. The socio‐demographic characteristics and dietary habits of cases and controls consecutively recruited from the studied hospitals might differ from that of the general population or patients admitted into other hospitals. However, a substantially high participation rate (96% and 98% for cases and controls, respectively) weighs against the selection bias in the present study. The use of hospital‐based controls with conditions potentially related to diet is also a major concern. To reduce this bias, an attempt was made to recruit controls from several disease conditions with no apparent association with a dietary cause. Recall bias is a particular problem inherent in case‐control studies. We tried to interview patients as soon as a diagnosis was made or before the operation to minimize this bias. We also provided photographs with usual intake portions of foods to help participants quantify the amount of food consumed. In addition, misclassification of choline and betaine intake is unavoidable due to measurement error in the food frequency questionnaire. However, any measurement error would most likely attenuate the true association between breast cancer risk and diet intake.
In summary, the present study found that intakes of dietary choline and betaine were inversely associated with breast cancer risk. The inverse association of dietary choline intake with breast cancer risk was manifested primarily in participants with low folate intakes.
Disclosure Statement
The authors have no conflict of interest.
Acknowledgments
The present study was supported by the National Natural Science Foundation of China (81102188), and the Center of Research and Promotion of Women's Health of the School of Public Health and Primary Care of the Chinese University of Hong Kong. The authors greatly appreciate the participation of the study subjects and the contributions of Xiao Zhong, Min‐Shan Lu and other students in the data collection.
(Cancer Sci, doi: 10.1111/cas.12064, 2012)
References
- 1. Kim YI. Folate and carcinogenesis: evidence, mechanisms, and implications. J Nutr Biochem 1999; 10: 66–88. [DOI] [PubMed] [Google Scholar]
- 2. Craig SA. Betaine in human nutrition. Am J Clin Nutr 2004; 80: 539–49. [DOI] [PubMed] [Google Scholar]
- 3. Zeisel SH. Choline: critical role during fetal development and dietary requirements in adults. Annu Rev Nutr 2006; 26: 229–50. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4. Zeisel SH, Blusztajn JK. Choline and human nutrition. Annu Rev Nutr 1994; 14: 269–96. [DOI] [PubMed] [Google Scholar]
- 5. Zhang CX, Ho SC, Chen YM, Lin FY, Fu JH, Cheng SZ. Dietary folate, vitamin B6, vitamin B12 and methionine intake and risk of breast cancer by estrogen and progesterone receptor status. Br J Nutr 2011; 106: 936–43. [DOI] [PubMed] [Google Scholar]
- 6. Ericson U, Sonestedt E, Gullberg B, Olsson H, Wirfält E. High folate intake is associated with lower breast cancer incidence in postmenopausal women in the Malmö Diet and Cancer cohort. Am J Clin Nutr 2007; 86: 434–43. [DOI] [PubMed] [Google Scholar]
- 7. Larsson SC, Giovannucci E, Wolk A. Folate and risk of breast cancer: a meta‐analysis. J Natl Cancer Inst 2007; 99: 64–76. [DOI] [PubMed] [Google Scholar]
- 8. Johansson M, Van Guelpen B, Vollset SE et al One‐carbon metabolism and prostate cancer risk: prospective investigation of seven circulating B vitamins and metabolites. Cancer Epidemiol Biomarkers Prev 2009; 18: 1538–43. [DOI] [PubMed] [Google Scholar]
- 9. Kotsopoulos J, Hankinson SE, Tworoger SS. Dietary betaine and choline intake are not associated with risk of epithelial ovarian cancer. Eur J Clin Nutr 2010; 64: 111–4. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10. Lee JE, Giovannucci E, Fuchs CS, Willett WC, Zeisel SH, Cho E. Choline and betaine intake and the risk of colorectal cancer in men. Cancer Epidemiol Biomarkers Prev 2010; 19: 884–7. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11. Cho E, Holmes M, Hankinson SE, Willett WC. Nutrients involved in one‐carbon metabolism and risk of breast cancer among premenopausal women. Cancer Epidemiol Biomarkers Prev 2007; 16: 2787–90. [DOI] [PubMed] [Google Scholar]
- 12. Cho E, Holmes MD, Hankinson SE, Willett WC. Choline and betaine intake and risk of breast cancer among post‐menopausal women. Br J Cancer 2010; 102: 489–94. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13. Xu X, Gammon MD, Zeisel SH et al Choline metabolism and risk of breast cancer in a population‐based study. FASEB J 2008; 22: 2045–52. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14. Niculescu MD, Zeisel SH. Diet, methyl donors and DNA methylation: interactions between dietary folate, methionine and choline. J Nutr 2002; 132: 2333S–5S. [DOI] [PubMed] [Google Scholar]
- 15. Zhang CX, Ho SC, Chen YM, Fu JH, Cheng SZ, Lin FY. Greater vegetable and fruit intake is associated with a lower risk of breast cancer among Chinese women. Int J Cancer 2009; 125: 181–8. [DOI] [PubMed] [Google Scholar]
- 16. Zhang CX, Ho SC, Lin FY, Cheng SZ, Fu JH, Chen YM. Soy product and isoflavone intake and breast cancer risk defined by hormone receptor status. Cancer Sci 2010; 101: 501–7. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17. Zhang CX, Ho SC. Validity and reproducibility of a food frequency questionnaire among Chinese women in Guangdong province. Asia Pac J Clin Nutr 2009; 18: 240–50. [PubMed] [Google Scholar]
- 18. Yang YX, Wang GY, Pan XC. China Food Composition. Beijing: Peking University Medical Press, 2002. [Google Scholar]
- 19. Zeisel SH, Mar MH, Howe JC, Holden JM. Concentrations of choline‐containing compounds and betaine in common foods. J Nutr 2003; 133: 1302–7. [DOI] [PubMed] [Google Scholar]
- 20. Zeisel SH, Mar MH, Howe JC, Holden JM. Erratum: concentrations of choline‐containing compounds and betaine in common foods. J Nutr 2003; 133: 2918–9. [DOI] [PubMed] [Google Scholar]
- 21. Willett WC, Howe GR, Kushi LH. Adjustment for total energy intake in epidemiologic studies. Am J Clin Nutr 1997; 65: 1220S–8S; discussion 9S–31S. [DOI] [PubMed] [Google Scholar]
- 22. Hillman RS, Steinberg SE. The effects of alcohol on folate metabolism. Annu Rev Med 1982; 33: 345–54. [DOI] [PubMed] [Google Scholar]
- 23. Weir DG, McGing PG, Scott JM. Folate metabolism, the enterohepatic circulation and alcohol. Biochem Pharmacol 1985; 34: 1–7. [DOI] [PubMed] [Google Scholar]
- 24. Kim YI, Miller JW, da Costa KA et al Severe folate deficiency causes secondary depletion of choline and phosphocholine in rat liver. J Nutr 1994; 124: 2197–203. [DOI] [PubMed] [Google Scholar]
- 25. Jacob RA, Jenden DJ, Allman‐Farinelli MA, Swendseid ME. Folate nutriture alters choline status of women and men fed low choline diets. J Nutr 1999; 129: 712–7. [DOI] [PubMed] [Google Scholar]
- 26. Cho E, Zeisel SH, Jacques P et al Dietary choline and betaine assessed by food‐frequency questionnaire in relation to plasma total homocysteine concentration in the Framingham Offspring Study. Am J Clin Nutr 2006; 83: 905–11. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27. Chinese Nutrition Society . Chinese Dietary Reference Intake, 1st edn Beijing: China Light Industry Press, 2000. [Google Scholar]