Abstract
Background/objectives
Vitamin C intake has been inversely associated with breast cancer risk in case-control studies, but not in meta-analyses of cohort studies using Food Frequency Questionnaires, which can over-report fruit and vegetable intake, the main source of vitamin C. This is the first study to investigate associations between vitamin C intake and breast cancer risk using food diaries.
Subjects/Methods
Estimated dietary vitamin C intake was derived from four to seven day food diaries pooled from five prospective studies in the UK Dietary Cohort Consortium. This nested case-control study of 707 incident breast cancer cases and 2144 matched controls examined breast cancer risk in relation to dietary vitamin C intake using conditional logistic regression adjusting for relevant covariates. Additionally, total vitamin C intake from supplements and diet was analysed in three cohorts.
Results
No evidence of associations were observed between breast cancer risk and vitamin C intake analysed for dietary vitamin C intake (OR = 0.98 per 60mg/d, 95%CI: 0.88 to 1.09, Ptrend = 0.7), dietary vitamin C density (OR = 0.97 per 60mg/d, 95% CI: 0.87 to 1.07, Ptrend = 0.5) or total vitamin C intake (OR = 1.01 per 60mg/d, 95%CI: 0.99 to 1.03, Ptrend = 0.3). Additionally, there was no significant association for post-menopausal women (OR = 1.02 per 60mg/d, 95%CI: 0.99 to 1.05, Ptrend = 0.3).
Conclusions
This pooled analysis of individual UK women found no evidence of significant associations between breast cancer incidence and dietary or total vitamin C intake derived uniquely from detailed diary recordings.
Keywords: Breast cancer, Vitamin C, cohort studies, food diaries
Introduction
In the UK a woman’s cumulative risk of being diagnosed with breast cancer is 6% by the age of 65, and 11% over a lifetime (Office for National Statistics 2000). It has been hypothesised that antioxidant properties of vitamin C can reduce cancer risk by decreasing reactive oxygen species (ROS) that may cause DNA damage (Willcox et al 2004). ROS, nevertheless, are involved in apoptosis, the beneficial death of tumour cells (Valko et al 2006).
Initial findings from retrospective case-control studies showed that fruit and vegetable intake, the main source of vitamin C, and also vitamin C intake were inversely associated with breast cancer risk (Gandini et al 2000, WCRF/AICR 1997, WCRF/AICR 2007). However, no conclusive evidence of a protective effect from fruit and vegetables has been produced prospectively from cohort studies (Key 2010, Michels et al 2007, Smith-Warner et al 2001, van Gils et al 2005, WCRF/AICR 2007). Similarly, the meta-analyses of prospective cohorts using Food Frequency Questionnaires (FFQs) in the 2007 World Cancer Research Fund (WCRF) report showed no significant associations with dietary or supplement vitamin C intake, nor in subgroup analyses by menopausal status (WCRF/AICR 2007). Only four prospective studies in this report included vitamin C from supplements as well as diet (Cho et al 2003, Kushi et al 1996, Nissen et al 2003, Zhang et al 1999), one of which showed an increased risk with increased total vitamin C intake (Nissen et al 2003). Only two studies since the WCRF report was published have assessed total vitamin C intake and breast cancer risk, (Cui et al 2008, Roswall et al 2010), one of which found a weak positive association (Cui et al 2008).
FFQs tend to encourage the over-reporting of fruit and vegetable consumption (Bingham et al 1997, Cade et al 2002, Calvert et al 1997), leading to the over-estimation of vitamin C intake (Bingham et al 1997). Alternatively, diaries may more accurately record numbers of fruit and vegetable portions consumed individually or in mixed dishes, (Bingham et al 1997) over a period of days, though they are limited by their short-term nature.
Our pooled analysis of the UK Dietary Cohort Consortium is the first study to investigate the relationship between breast cancer risk and vitamin C intake using food diaries; an alternative tool to FFQs used in previous analyses. Additionally, the current analysis is one of a small number of prospective studies assessing the relationship of breast cancer risk with total vitamin C intake, which includes intake from supplements as well as from diet.
Methods
Subjects
Individual participant data were pooled from five established cohort studies within the UK Dietary Cohort Consortium: EPIC-Norfolk (Bingham et al 2001); the UK Women’s Cohort Study (UKWCS) (Cade et al 2004); EPIC-Oxford (Davey et al 2003); Whitehall II (Marmot and Brunner 2005); and the MRC National Survey of Health and Development (NSHD) (Wadsworth et al 2006). Methods used were similar to those previously described for colorectal case-control analyses nested within this UK consortium(Dahm et al 2010).
Case ascertainment and matching
Incident cases of breast cancer were identified from data provided by UK cancer registries based on the International Classification of Diseases (ICD) version 9 (174) or 10 (C50). Diagnoses within six months of food diary completion were excluded to ensure that latent disease without formal diagnosis was not present, otherwise disease suspected by participants could have influenced their dietary habits. Across the cohorts 707 incident cases and 2144 controls were used in the dietary vitamin C analysis. Only three cohorts (EPIC-Oxford, EPIC-Cambridge and UKWCS) were used in the total vitamin C analysis which involved 601 incident cases and 1725 controls (85% of the consortium participants); the remaining two cohorts did not have adequate supplement use data to determine the vitamin C content of supplements consumed at diary date. Within each cohort, each case was matched to randomly selected controls based on age at recruitment (± 3 years) and date of diary completion (± 3 months or as close as possible). The number of controls matched to cases was four for EPIC-Norfolk, Whitehall and NSHD, and up to five for UKWCS. In EPIC-Oxford one control was matched to each case, to within six months of case diary completion. Controls had no registry-reported cancer diagnosis at recruitment (except non-melanoma skin cancer) and were free from breast cancer at the end of the follow-up period. The mean length of follow-up for cases in the cohorts ranged from 2.4 years to 10.8 years as detailed in Table 1; these were not adjusted for in the analyses.
Table 1.
Characteristics of the 5 cohorts participating in analyses of vitamin C and breast cancer risk in the UK Dietary Cohort Consortium
| Cohort | Participants | Diary days |
Years when food diary completed |
Last follow up date |
Mean time to diagnosis of cases |
Cases | Controls | Mean(sd) dietary vit c intake |
Mean(sd) total vit c intake |
|---|---|---|---|---|---|---|---|---|---|
| EPIC-Norfolk | General population in Norfolk |
7 days | 1993-1998 | 31.12.2006 | 6.0 yrs | 365 | 1329 | 91 (50) | 118 (167) |
| EPIC-Oxford | General population and vegetarians in the UK |
7 days | 1993-1998 | 31.12.2004 | 3.5 yrs | 194 | 194 | 111 (61) | 233 (436) |
| UK Women’s Cohort Study (UKWCS) |
Middle aged women in the UK |
4 days | 1999-2003 | 31.12.2006 | 2.4 yrs | 42 | 202 | 118 (60) | 251 (376) |
| Whitehall II | Civil servants in the UK | 7 days | 1991-1993 | 30.09.2005 | 7.8 yrs | 70 | 275 | 101 (51) | _a |
| National Survey of Health and Development (NSHD) |
Nationally reprehensive cohort of women who were born in one week in March 1946 in England, Wales and Scotland. |
5 days | 1989 | 31.12.2006 | 10.8 yrs | 36 | 144 | 66 (37) | _a |
Whitehall and NSHD did not have detailed diary data of vitamin C intake from supplements
Dietary methods
All cohorts collected dietary information using semi-weighed food diaries or included photographs to aid the estimation of portion size. The number of days intake recorded for each cohort is shown in table 1.
Food diary details were input by trained food diary analysts; the majority were entered into Data into Nutrients for Epidemiological Research (DINER), and a nutrient calculation program checked and derived the nutrient data (Welch et al 2001). Diaries from UKWCS were entered using the Diet and Nutrient Tool (DANTE), which had previously been validated against DINER on a subsample of 100 randomly selected diaries, with acceptable agreement (Dahm et al 2010). Diaries from the NSHD were entered into DIDO (Price et al 1995) which, after validation, proved to use portion sizes and recipes that were more concurrent with the time of NSHD diary completion. All estimated dietary vitamin C intake was based on standard tables of food composition and daily averages were calculated (Holland et al 1991).
In separate sections of the diaries, participants were asked to record supplement brand, name and amount per day for any supplement taken. In three cohorts databases were created to match this information against manufacturers’ information: EPIC-Norfolk (Lentjes et al 2011); EPIC-Oxford and UKWCS (Hutchinson et al 2011). The two databases used included supplement descriptions and ingredient composition from product labels directly obtained from manufacturers or the participants’ descriptions and/or labels. Where participants were unclear in their description, a weighted average of vitamin C from similar supplements was calculated from the database and applied (Lentjes et al 2011). For instance, separate generic averages were calculated for multivitamins, antioxidant ACE supplements and high dose vitamin C supplements. For each participant the average daily vitamin C amount consumed from all supplement types was calculated.
Statistical methods
Separate quintile cut points were determined for dietary intake (mg per day), dietary vitamin C intake density (mg per megajoule per day) and total vitamin C intake including supplements (mg per day). Dietary vitamin C intake density was analysed as a separate method of controlling for potential confounding by total energy intake. Conditional logistic regression was used to model the associations between fifths of vitamin C intake and breast cancer incidence. To test for linear trends we used continuous intake variables per increment of approximately one standard deviation of mean intake (being 60mg/day for dietary intake and 8mg/MJ/day for intake density). No supplement intakes were implausible. However, in sensitivity analyses women with extreme intakes, defined as more than 1.5 times the inter-quartile range above the 75th percentile, were excluded in tests for linear trends. These upper thresholds were 224.1 mg/d for dietary intake, 30.6 mg/MJ/day for intake density and 262.4 mg/d for total vitamin C intake, which excluded 77, 91 and 206 women respectively.
Owing to the process of matching cases and controls the conditional logistic regression model automatically adjusted for date of diary completion, age (in years) and cohort. The multivariate model adjusted for exact age, parity (0, 1, 2, 3, 4+, missing), hormone replacement therapy (HRT) use (current, non-current, missing), alcohol intake, total energy intake, weight (<60kg, 60-, 66-, >72kg, missing), height (<158cm, 158-, 163-, >168cm, missing), physical activity (low, low-medium, medium-high, high, missing), and menopausal status (pre, peri or post-menopausal, missing). The level of missing data ranged from 0% for alcohol and total energy intake, to 0.4% for parity to 3.6% for physical activity. Alcohol and total energy intake were ascertained from the diaries. All other covariates were collected by standard questionnaires, either self-administered or by trained researchers at or close to the time of diary completion. Sensitivity analysis was performed to adjust for variables which have weaker associations with breast cancer risk (smoking status and level of education) and also to adjust for important risk variables which had moderate levels of missing data (age at menarche (16%) and cumulative duration of breastfeeding (weeks) (18%)). This restricted the sensitivity analysis to 2150 participants. To investigate robustness of results to missing data, analyses were repeated using multiple imputation by chained equations (Royston 2009), with imputations based on exposure, covariates and outcome. Additional sensitivity analyses also controlled for dietary vitamin E and iron which affect vitamin C bioavailability. Finally, we formally tested our assumption of no heterogeneity across the different cohorts by including an exposure by centre interaction term in the models. Analyses were carried out using Stata version 10 (Timberlake Consultants UK, London, UK) and results were based on a significance level of p<0.05.
Results
Dietary vitamin C intake
On average the total women (2851) in the five cohorts were 56 years old and consumed 346g/d fruit and vegetables; 65% were post-menopausal, 58% had never smoked, 17% were educated to degree, HNC or HND level, and only 18% took HRT at the date of diary completion.
As observed in table 2 total cases (707) had similar characteristics to the 2144 controls and their mean (sd) dietary vitamin C intakes were 98mg/d (56) and 95mg/d (52) respectively. Women with a higher dietary vitamin C intake tended to have a higher energy intake, consume more alcohol, dietary vitamin E and iron as well as more fruit and vegetables. Additionally they had fewer children, were more active, had attained higher levels of education, or were more likely to be of higher socio-economic status or to have never smoked (table 2)
Table 2.
Participant characteristics by fifth of dietary vitamin C intake derived from food diaries in the UK Dietary Cohort Consortium
| Breast cancer | Dietary vitamin C intake (diary fifths) |
||||||||
|---|---|---|---|---|---|---|---|---|---|
| Covariates (at diary date) | Cases | Controls | 1 | 2 | 3 | 4 | 5 | P* | |
| Cases/controls | 707 | 2144 | 130/440 | 138/432 | 144/426 | 142/428 | 153/418 | ||
| Dietary vitamin C intake (mg/day) | mean (SD) | 98 (56) | 95 (52) | 36.9 (9.9) | 61.9 (6.4) | 85.1 (7.2) | 114.6 (10.0) | 178.4(45.5) | |
| Fruit Intake g/d | mean (SD) | 191 (138) | 185 (135) | 81 (74) | 136 (84) | 188 (105) | 223 (123) | 304 (159) | <0.001 |
| Vegetable intake g/d | mean (SD) | 165 (86) | 158 (82) | 101 (49) | 141 (59) | 161 (65) | 182 (79) | 214 (104) | <0.001 |
| Age at diary completion (yr) | mean (SD) | 55.7 (9.4) | 56.3 (9.6) | 55.5 (10.0) | 55.7 (9.8) | 56.9 (9.6) | 56.8 (9.6) | 56.0 (9.4) | 0.3 |
| Height (cm) | mean (SD) | 163 (7) | 162 (6) | 160.7 (6.5) | 161.5 (6.3) | 161.8 (6.8) | 162.3 (6.4) | 162.9 (6.2) | <0.001 |
| Weight (kg) | mean (SD) | 67.8 (11.8) | 67.2 (12.2) | 67.9 (12.0) | 67.5 (12.6) | 67.8 (12.7) | 66.6 (11.2) | 66.8 (12.0) | 0.1 |
| Energy intake (diary, MJ/day) | mean (SD) | 7.6 (1.7) | 7.4 (1.7) | 6.8 (1.8) | 7.4 (1.6) | 7.4 (1.6) | 7.7 (1.7) | 7.8 (1.7) | <0.001 |
| Alcohol intake (diary, g/day) | mean (SD) | 10.3 (13.6) | 8.7 (12.8) | 7.9 (12) | 8.5 (13) | 10.3 (14) | 9.0 (13) | 9.7 (13) | 0.02 |
| Total fat (g/d) | mean (SD) | 68.9 (21.8) | 67.2 (22.0) | 64.9 (21.3) | 69.5 (21.7) | 66.2 (21.5) | 70.3 (22.5) | 67.6 (21.4) | 0.07 |
| Dietary vitamin E (mg/d) | mean (SD) | 9.9 (4.1) | 9.3 (4.0) | 8.0 (3.8) | 9.2 (3.7) | 9.3 (3.7) | 10.2 (4.2) | 10.6 (4.1) | <0.001 |
| Dietary Iron (mg/d) | mean (SD) | 11.8 (3.5) | 11.3 (3.4) | 9.5 (3.1) | 10.9 (2.9) | 11.5 (3.4) | 12.0 (3.5) | 13.0 (3.5) | <0.001 |
| Parity (number of children) | mean (SD) | 1.8 (1.2) | 1.9 (1.3) | 2.1 (1.3) | 1.9 (1.3) | 1.9 (1.3) | 1.8 (1.3) | 1.6 (1.3) | <0.001 |
| Exercise ( medium - high) | n (%) | 242 (37) | 796 (38) | 162 (30) | 198 (36) | 208 (37) | 230 (42) | 240 (44) | <0.001 |
| HRT use (current user) | n (%) | 122 (18) | 373 (18) | 89 (16) | 94 (17) | 106 (19) | 110 (20) | 96 (17) | 0.4 |
| Menopausal status (post-menopausal) | n (%) | 436 (63) | 1424 (67) | 352 (63) | 368 (66) | 385 (68) | 387 (69) | 367 (65) | 0.2 |
| Never smoked | n (%) | 413 (60) | 1233 (58) | 272 (49) | 316 (56) | 333 (59) | 349 (62) | 376 (67) | <0.001 |
| Education level (degree, HNC, HND) | n (%) | 136 (21) | 313 (15) | 38 (7) | 68 (13 ) | 77 (15) | 113 (21) | 151 (28) | <0.001 |
| Social class (professional or intermediate) | n (%) | 238 (47) | 901 (47) | 187 (37) | 207 (42) | 232 (48) | 254 (53) | 259 (58) | <0.001 |
p is Ptrend over continuous variables, and p for χ2 tests for categorical variables
The odds ratios for breast cancer according to dietary intake of vitamin C in the five cohorts are shown in table 3 for the unadjusted and multivariate model. There was no evidence of any significant association between dietary vitamin C intake and incidence of breast cancer for total women in the five cohorts. In the adjusted analysis for total women the odds ratio of breast cancer per 60mg/day increments was 0.98 (95%CI: 0.88 to 1.09, Ptrend = 0.7) Similarly, there was no evidence of any linear trends or significant associations between dietary vitamin C intake groups and incidence of breast cancer in the sub-analysis by post-menopausal status (OR=0.98 per 60mg/day, 95%CI: 0.85 to 1.13, Ptrend = 0.8). The results remained non-significant in sensitivity analyses after further adjustment for smoking status, age at menarche, cumulative duration of breastfeeding (weeks), and level of education. Odds ratios did not alter substantially. There was no evidence of any linear trends or significant associations between the incidence of breast cancer and dietary vitamin C expressed as intake density (Table 4). In the sensitivity analyses, which excluded women with extreme dietary vitamin C intakes, the odds ratios for linear trends relating to absolute dietary intake and intake density were reduced to between 0.91 and 0.95, but none were statistically significant.
Table 3.
Dietary vitamin C intake recorded by diaries and risk of breast cancer in the UK Dietary Cohort Consortium
| Dietary vitamin C intake Fifths: mean mg/day (sd) |
Cases/ Controls |
Unadjusted * | Multivariate † |
|---|---|---|---|
|
| |||
| OR (95% CI) | OR (95% CI) | ||
| Total women | |||
| 1 (lowest): 36.9 (9.9) | 130/440 | 0.94 (0.71, 1.25) | 0.95 (0.71, 1.28) |
| 2 61.9 (6.4) | 138/432 | 1 | 1 |
| 3 85.1 (7.2) | 144/426 | 1.03 (0.78, 1.36) | 1.00 (0.75, 1.33) |
| 4 114.6 (10.0) | 142/428 | 0.98 (0.74, 1.29) | 0.92 (0.69, 1.22) |
| 5 (highest): 178.4 (45.5) | 153/418 | 1.02 (0.77, 1.35) | 0.96 (0.72, 1.27) |
| P trend per 60mg/d | 0.9 | 0.7 | |
| Continuous estimate/ 60mg/d | 1.01 (0.91, 1.11) | 0.98 (0.88, 1.09) | |
| Post menopausal | |||
| 1 (lowest) 36.9 (9.7) | 77/276 | 1.02 (0.70, 1.48) | 1.05 (0.71, 1.55) |
| 2 62.2 (6.5) | 79/289 | 1 | 1 |
| 3 85.0 (7.2) | 96/289 | 1.22 (0.85, 1.74) | 1.19 (0.82, 1.71) |
| 4 114.9 (10.0) | 91/296 | 1.06 (0.74, 1.52) | 0.99 (0.68, 1.44) |
| 5 (highest) 179.0 (47.7) | 93/274 | 1.12 (0.77, 1.61) | 1.01 (0.69, 1.48) |
| P trend per 60mg/d | 0.7 | 0.8 | |
| Continuous estimate/ 60mg/d | 1.03 (0.90, 1.17) | 0.98 (0.85,1.13) | |
Conditional logistic regression on cases and controls matched by cohort, age and date of diary completion
As for the unadjusted model * with additional adjustment for exact age, height (<158cm, 158−, 163−, 168+), weight (<60kg, 60−, 66−, 72+), physical activity, parity (0,1,2,3,4+), current HRT use, menopausal status, diary-derived alcohol consumption and total energy intake. Missing data added as a category.
Table 4.
Dietary vitamin C intake densities recorded by diaries and risk of breast cancer in the UK Dietary Cohort Consortium
| Vitamin C nutrient density Fifths: mean mg/MJ/d (sd) |
Cases/ Controls |
Unadjusted* | Multivariate † |
|---|---|---|---|
|
| |||
| OR (95% CI) | OR (95% CI) | ||
| Total women | |||
| 1 (lowest): 5.2 (1.3) | 140/430 | 0.98 (0.75, 1.29) | 0.98 (0.74, 1.30) |
| 2 8.5 (0.8) | 143/427 | 1 | 1 |
| 3 11.6 (1.0) | 139/431 | 0.90 (0.68, 1.18) | 0.89 (0.67, 1.19) |
| 4 15.8 (1.4) | 152/418 | 1.05 (0.81, 1.39) | 1.05 (0.79, 1.39) |
| 5 (highest): 25.0 (7.1) | 133/438 | 0.80 (0.60, 1.06) | 0.80 (0.60, 1.08) |
| P trend per 8 mg/MJ/d | 0.4 | 0.5 | |
| Continuous estimate/ 8 units | 0.96 (0.87, 1.06) | 0.97 (0.87, 1.07) | |
| Post menopausal | |||
| 1 (lowest): 5.3 (1.3) | 76/261 | 0.90 (0.62, 1.30) | 0.89 (0.61, 1.31) |
| 2 8.5 (0.9) | 81/272 | 1 | 1 |
| 3 11.6 (1.0) | 89/293 | 0.95 (0.66, 1.35) | 0.95 (0.66, 1.37) |
| 4 15.7 (1.4) | 106/297 | 1.10 (0.77, 1.56) | 1.11 (0.77, 1.61) |
| 5 (highest): 25.4 (7.5) | 84/301 | 0.80 (0.55, 1.15) | 0.80 (0.54, 1.19) |
| P trend per 8 mg/MJ/d | 0.6 | 0.7 | |
| Continuous estimate/ 8 units | 0.97 (0.86, 1.09) | 0.97 (0.86,1.10) | |
Conditional logistic regression on cases and controls matched by cohort, age and date of diary completion
As for the unadjusted model * with additional adjustment for exact age, height (<158cm, 158−, 163−, 168+), weight (<60kg, 60−, 66−, 72+), physical activity, parity (0,1,2,3,4+), current HRT use, menopausal status, alcohol consumption and total energy intake. Missing data added as a category.
In tests for heterogeneity there was evidence of differences between the five study centres when a study centre by dietary vitamin C intake group interaction term was included (p=0.10 total women; p=0.05 post-menopausal).
The mean (sd) dietary intakes by cohort are shown in Table 1 The lower intake for the younger, nationally representative NSHD women (mean age 43 vs 50s in other cohorts) reflected previous findings from households with similar aged adults (Defra 2004).
Total vitamin C intake
In the analyses of total vitamin C, cases had a somewhat higher total vitamin C intake than controls: 174mg/d (sd 374) vs 143mg/d (sd 213). The average vitamin C intake from supplements for cases was 1.5 times higher than controls: 73mg/d (sd 364) vs 48mg/d (sd 201). Total intakes by cohort are shown in table 1. The mean vitamin C supplement intake per day for EPIC-Norfolk was significantly less than for UKWCS and EPIC-Oxford. Based on diary completion date, mean total intake in autumn and winter compared to spring and summer was not significantly different (151.7. (sd 312) vs 151.4 (sd 218) mg/d); comprising respectively of 46.4.1% and 53.6% of these women. The relationships between total vitamin C intake split by fifths and lifestyle characteristics were similar to those for dietary only intake shown in table 2. The highest intake group had the highest vitamin C intake from both diet and supplements (mean (sd) 159 (69) mg/d) and 256 (519) mg/d respectively); in this group 62% took supplements containing vitamin C and 84% of these women took them every day.
In pooling the three cohorts which recorded vitamin C intake from supplements there was also no evidence of any significant associations between total vitamin C intake and incidence of breast cancer for the continuous estimate for all women (OR = 1.01 per 60mg/d, 95%CI: 0.99 to 1.03, Ptrend = 0.3), or for post-menopausal women (OR = 1.02 per 60mg/d, 95%CI: 0.99 to 1.05, Ptrend = 0.3) or by fifths of total vitamin C intake (table 5). There was no evidence of significant differences between the three study centres when formally tested using a study centre by fifths of total vitamin C intake interaction term, for total and for post-menopausal women (p=0.7 and p=0.7 respectively).
Table 5.
Total vitamin C intake from diet and supplements recorded by diaries and risk of breast cancer in EPIC-Oxford, EPIC-Norfolk and UKWCS cohorts
| Total vitamin C intake Fifths: mean mg/day (sd) |
Cases/ Controls |
Unadjusted* | Multivariate † |
|---|---|---|---|
|
| |||
| OR (95% CI) | OR (95% CI) | ||
| Total women | |||
| 1 (lowest): 39.3 (10.9) | 101/364 | 0.88 (0.64, 1.21) | 0.86 (0.62, 1.20) |
| 2 69.0 (8.0) | 112/353 | 1 | 1 |
| 3 97.7 (8.9) | 133/332 | 1.21 (0.90, 1.64) | 1.22 (0.89, 1.65) |
| 4 136.9 (14.6) | 130/335 | 1.08 (0.79, 1.48) | 1.02 (0.74, 1.40) |
| 5 (highest): 414.2 (507.3) | 125/341 | 0.98 (0.71, 1.34) | 0.93 (0.67, 1.28) |
| P for trend per 60mg/d | 0.3 | 0.3 | |
| Continuous estimate/ 60mg/d | 1.01 (0.99, 1.03) | 1.01 (0.99, 1.03) | |
| Post menopausal | |||
| 1 (lowest) 39.7 (10.7) | 72/275 | 0.97 (0.67, 1.41) | 0.99 (0.67, 1.47) |
| 2 68.9 (8.0) | 82/292 | 1 | 1 |
| 3 97.8 (8.9) | 91/257 | 1.29 (0.90, 1.84) | 1.38 (0.95, 1.99) |
| 4 136.2 (14.5) | 83/253 | 1.06 (0.72, 1.55) | 0.99 (0.66, 1.47) |
| 5 (highest) 395.3 (466.7) | 78/228 | 1.15 (0.78, 1.67) | 1.08 (0.72, 1.59) |
| P for trend per 60mg/d | 0.2 | 0.3 | |
| Continuous estimate/ 60mg/d | 1.02 (0.99, 1.05) | 1.02 (0.99,1.05) | |
Conditional logistic regression on cases and controls matched by cohort, age and date of diary completion
As for the unadjusted model * with additional adjustment for height (<158cm, 158−, 163−, 168+), weight (<60kg, 60−, 66−, 72+), physical activity, parity (0,1,2,3,4+), current HRT use, menopausal status, diary-derived alcohol consumption and total energy intake. Missing data added as a category.
For both dietary and total intake no substantial differences in the estimates were found in sensitivity analyses controlling for dietary vitamin E and iron.
Finally, a total of 73 matched case-control sets in the main analyses had some missing covariate information, mostly in HRT exposure, however the strength of associations were almost identical whether these matched sets were included by using a category for missing data, or included with additional information using multiple imputation.
Discussion
This pooled analysis of individual participant data from five UK cohorts found no evidence of an association between incidence of breast cancer and dietary vitamin C intake recorded by food diaries. Neither was there any evidence of an association with total vitamin C intake when vitamin C from supplements was included. Our non-significant results for post-menopausal women relating to dietary vitamin C intake support results of the 2007 WCRF meta-analyses of three cohort studies (HR=1.15 per 100mg/d, 95% CI: 0.92-1.43) (Graham et al 1992, Nissen et al 2003, Verhoeven et al 1997, WCRF/AICR 2007), also the high versus low intake results of two US studies (Kushi et al 1996, Zhang et al 1999), and the recent European Prospective Investigation into Cancer (EPIC) analysis involving the pooling of data from 10 European countries (highest vs. lowest quintile HR = 0.98, 95% CI: 0.87–1.11) (Nagel et al 2010); all of which used FFQs. Our results for dietary vitamin C are in conflict with significant evidence of a 12-14% reduced risk found in the meta-analysis of retrospective case-control studies (WCRF/AICR 2007) which, unlike our study, are prone to recall bias.
In contrast to our results and other studies (Cho et al 2003, Kushi et al 1996, Roswall et al 2010, Zhang et al 1999), the large Women’s Health Initiative study (Cui et al 2008) found significant but weak evidence of increased breast cancer risk for total intake. The advanced age of the participants in this cohort (average 64 years) might suggest that high vitamin C intake may promote the progression of cancer in older people or at later stages of the disease. Similarly positive associations with post-menopausal breast cancer for both dietary and total vitamin C intake (OR= 2.06 per 100mg/d, 95% CI: 1.45-2.91; and OR=1.08 per 100mg/d, 95% CI: 1.02-0.1.15 respectively) were found in a small Danish nested case-control study (Nissen et al 2003), but not in the recent full analysis of this Danish cohort (Roswall et al 2010); selection bias of controls may have possibly influenced the earlier results.
Pooling individual participant data in this consortium had three advantages. Firstly, it ensured that vitamin C intake over the whole consortium could be categorised into fifths; secondly, the variations in intake across the cohorts increase the power to detect smaller effect sizes (Schatzkin et al 2001), i.e. many women in EPIC-Oxford and UKWCS were vegetarians and/ or consumed supplements containing vitamin C compared to the other cohorts; thirdly, analysis and adjustment by covariates could be done in a uniform way.
Our study had a few caveats. Whilst the use of missing covariate categories may have grouped dissimilar individuals and introduced some bias, its effect on the adjusted results may be considered acceptable since the level of missing data was small, confounding was judged to be weak and multiple imputation results were almost identical. To account for the possible modulation of vitamin C on cancer development due to its the role in the regeneration of vitamin E, in the absorption of iron and in the Fenton reaction, (Valko et al 2006) sensitivity analysis adjustments were made for these dietary nutrients. Supplement intake data for these nutrients, however, was not available. The Danish studies, one of which found a positive association, controlled for both dietary and supplement intake of vitamin A and E (Nissen et al 2003, Roswall et al 2010). In the current study data were unavailable to adjust for family history of breast cancer which has been associated with high-dose vitamin C supplement use in the UK (Hutchinson et al 2011). Data were not available from all cohorts to exclude general supplement users from the dietary analysis; the different health behaviours of users may have influenced the results (Kirk et al 1999). There was inadequate power to sub-analyse by HRT users, oestrogen receptor-negative or pre-menopausal breast cancers.
This is the first time the relationship between breast cancer risk and vitamin C intake has been analysed using prospective data from food diaries. Diaries can capture detailed and accurate intake over a narrow period of days due to their open format, whereas FFQs aim to reflect intake over a much longer period, normally an estimated average of the previous 12 months. Repeated diary data collections may reduce their short-term limitations but were not undertaken for the whole consortium due to expense and time taken to administer, complete and analyse. The required commitment and awareness of intake may have also influenced participants’ consumption during diary recording. When compared to FFQs, food diaries have shown stronger correlations with plasma vitamin C biomarkers in validity tests when collected in close temporal proximity. However this may reflect the short-term nature of both plasma vitamin C and diary data, particularly since correlations with biomarker levels re-measured several years later were similar for diaries and FFQs (Bingham et al 2008, Bingham et al 1997, Willett 2008) Furthermore, other UK validation studies have shown similar associations between biomarkers and vitamin C estimated from FFQs and diaries (Brunner et al 2001, Michels et al 2005). Overall correlations between biomarkers and FFQs or diaries are generally weak to moderate (Cade et al 2002, Henríquez-Sánchez et al 2009). Since the absorption and storage of vitamin C is limited, particularly above 400mg/d (Levine et al 2001), biomarkers are unlikely to reflect dietary vitamin C intake well. Therefore it is difficult to assess objectively whether diaries or FFQs can rank individual intake sufficiently well in order to find associations between vitamin C and cancer risk. Given the limitations, results of vitamin C analyses from both FFQs and diaries need to be treated with some caution.
To conclude, the evidence to date from this and other prospective studies does not indicate either a beneficial or a detrimental effect of vitamin C intake on breast cancer risk, whether this intake is from diet only or also from supplements.
Acknowledgements
The UK Dietary Cohort Consortium is part of the MRC Centre for Nutritional Epidemiology in Cancer Prevention and Survival which is funded by the Medical Research Council. The cohorts forming the consortium have received funding from the World Cancer Research Fund, Cancer Research UK, British Heart Foundation and the Medical Research Council. Professor Sheila Rodwell (also known professionally as Sheila Bingham), who died in 2009, established the UK Dietary Cohort Consortium as part of the MRC Centre for Nutritional Epidemiology of which she was director.
Footnotes
Conflict of interest The authors declare no conflict of interest
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