Combined Mineral Intakes and Risk of Colorectal Cancer in Postmenopausal Women

Colorectal cancer is the second most common cause of cancer-related deaths in the United States (1). Findings from epidemiologic studies indicate that environmental factors—especially diet and lifestyle—play an important role in colorectal cancer risk (2, 3). As summarized in Table 1, there is considerable biological plausibility for minerals (including calcium, magnesium, manganese, zinc, selenium, potassium, iodine, iron, copper, phosphorus, and sodium) affecting risk of colorectal carcinogenesis. Calcium has been consistently modestly inversely associated with colorectal neoplasms in multiple observational studies (4, 5, 33). However, relatively few studies reported associations of other mineral intakes with colorectal cancer, and the limited results are less consistent.

There are several possible reasons for the inconclusive epidemiologic results for minerals other than calcium, including biological interactions among minerals and that the contributions of individual minerals to colorectal cancer risk may be small. Examples of biological interactions include that calcium competes with magnesium for intestinal absorption and transport (7), and similar interactions were found between copper and iron (24), and copper and zinc (13). Hephaestus, a protein found in the colon, is a copper-dependent ferroxidase responsible for dietary iron transport (24). Balanced levels of copper and zinc are thought to contribute to proper functioning of copper–zinc superoxide dismutase, an antioxidation enzyme with tumor-suppressive properties (13). Although the contributions of individual minerals to risk may be small, it is possible that collectively they may be substantial. A method increasingly used to account for the possible combined effects of multiple, often correlated, interacting exposures is dietary scores (34).

Relatively few reported studies investigated associations of specific minerals, other than calcium, with colorectal cancer risk, and to our knowledge, none considered the possible aggregate effects of multiple minerals. Accordingly, we investigated associations of calcium, magnesium, manganese, zinc, selenium, potassium, iodine, iron, copper, phosphorus, and sodium intakes combined into a mineral intake score, with colorectal cancer incidence in a prospective cohort study.

The Iowa Women's Health Study, established in 1986, is a prospective cohort study of postmenopausal Iowa women (35, 36). Prospective participants were 55- to 69-year-old women on the Iowa Department of Transportation 1985 current drivers list, from whom 50% were randomly selected. Of these, 99,826 had a valid Iowa mailing address and were mailed a questionnaire, of whom 41,836 (42.7%) responded and were eligible for enrollment. Respondents, relative to nonrespondents, were, on average, 3 months older and had a slightly lower body mass index (BMI), income, and education and were more likely to reside in more rural counties (35). Cancer incidence did not substantially differ between respondents and nonrespondents.

The baseline questionnaire included questions on demographics, diet, family history, medical and reproductive history, smoking, physical activity, and body size characteristics. Written instructions and tape measures were provided so that the participant could have someone measure their waist circumference (1 inch above the umbilicus) and hip circumference (maximal protrusion) for waist–hip ratio calculations. BMI was calculated as self-reported weight over self-reported height squared (kg/m²). The dietary portion of the questionnaire was a Willett 127-item semiquantitative food frequency questionnaire (FFQ). Participants reported their usual food consumption over the previous year, referencing a commonly used serving size, according to nine frequency categories ranging from never or < 1 serving/month to ≥ 6 servings/day. The questionnaire also solicited intakes of multivitamin/mineral and specific vitamin and mineral supplements. Total energy and nutrient intakes were calculated by adding energy and nutrients from all food sources using the dietary database developed by Willett and colleagues (37). In addition to the original survey, follow-up surveys were sent to study participants in 1987, 1989, 1992, 1997, and 2004. Aspirin and other nonsteroidal anti-inflammatory drug use was not collected until 1992, and diet was only comprehensively reassessed in 2004 at which time only 68.3% of the participants remained alive.

Deaths were identified through the State Health Registry of Iowa and the National Death Index. Cancer diagnoses were collected through linkage with the State Health Registry of Iowa, a participant in the National Cancer Institute's Surveillance, Epidemiology, and End Results Program; ascertainment of cancer diagnoses was nearly 100% (35, 36). Colorectal cancer was defined as adenocarcinoma of the colon or rectum (ICD-O-3 codes: C18.0–18.9, C19.9, and C20.9). Follow-up time was calculated as the time between the date of completing the baseline questionnaire and age at first colorectal cancer diagnosis, date when they moved from Iowa, or date of death; if none of these events occurred, the subject was assumed to be alive, cancer-free, and living in Iowa, and censored at the end of follow-up (December 31, 2012; refs. 35, 36).

Women who reported a history of cancer other than nonmelanoma skin cancer at baseline (n = 3,830), left ≥ 30 FFQ items blank (n = 2,499), or reported implausible total daily energy intakes (<600 or >5,000 kcal/day; n = 286) were excluded from the analytic cohort, leaving 35,221 participants, including 1,731 who developed colorectal cancer during follow-up, for analysis.

The FFQ-derived food and supplement data were used to calculate mineral scores for all participants. The 11 components in the mineral score, the rationale behind their inclusion, and their predominant sources are listed in Table 1. For most mineral intakes, we summed values derived from foods and supplements. Measurements of dietary selenium and iodine are unreliable because their intakes depend on their abundance in soil, which varies substantially around the world (38, 39). Therefore, only supplemental selenium and iodine intakes were used. Nutrient density intakes were calculated as the intake of a mineral per 1,000 kilocalories of total energy intake per day, and then the intakes of each mineral were categorized into quintiles based on the distribution within the analytic cohort at baseline. For each mineral hypothesized to reduce colorectal cancer risk, each participant was assigned a value equal to their quintile rank (i.e., a value of 1–5, with lower ranks indicating lower mineral intakes and higher ranks indicating higher mineral intakes). For each mineral hypothesized to have predominantly procarcinogenic properties in the colon, the values assigned to the rankings were reversed (i.e., values of 5–1, with lower ranks indicating higher mineral intakes and higher ranks indicating lower mineral intakes). Finally, each woman's values for each mineral were summed to represent her mineral score; thus, the range of possible scores was 11 to 55.

All statistical analyses were performed using SAS version 9.2 (SAS Institute Inc.). All P values were two-sided, and a P value < 0.05 or a 95% confidence interval (CI) that excluded 1.0 was considered statistically significant. Selected participant characteristics at baseline across quintiles of the mineral score were summarized and compared using χ² tests for categorical variables and analysis of variance for continuous variables (the latter transformed by the natural logarithm when needed to improve normality). The association of the mineral score—as a continuous variable and categorized according to quintiles—with risk of incident colorectal cancer was estimated using multivariable Cox proportional hazards regression to calculate hazard ratios (HR) and their 95% CIs. The covariates, chosen a priori as previously having been found to be strong risk factors for colorectal cancer, included age, total energy intake, height, BMI, waist–hip ratio, smoking, physical activity, hormone replacement therapy (HRT) use, education, family history of colorectal cancer in a first-degree relative, and diabetes; total fat, dietary fiber, total fruits and vegetables, total red and processed meats, and alcohol intakes; and a dietary oxidative balance score (OBS). An equal-weight dietary OBS, as described by Dash and colleagues, included the dietary antioxidants α-carotene, β-carotene, β-crypotoxanthin, lutein, lycopene, vitamin C, vitamin E, omega-3 fatty acids, and flavonoids, and the dietary pro-oxidants omega-6 fatty acids and saturated fat (40, 41). A test for trend was calculated using the median value for each quintile of the mineral score.

The above models were also applied in stratified analyses, which were conducted to examine the association of the mineral score with colorectal cancer incidence according to categories of selected covariates. Strata for the following continuous variables were created based on values above and below the population median: age, height, waist–hip ratio, dietary OBS, and total energy, total fat, dietary fiber, total fruits and vegetables, and total red and processed meats intakes. Strata for other variables were as follows: smoking—current, former, never; alcohol intake—none, >0 g–<15 g/day, ≥15 g/day; physical activity—tertiles; HRT use—current, former, never; BMI (according to WHO criteria)—<25, 25–30, ≥30 kg/m²; family history of colorectal cancer in a first degree relative—yes/no; personal history of diabetes—yes/no; and education—≥college graduate/< college graduate. Effect-measure modification was assessed by comparing stratum-specific HRs.

The analyses were also repeated separately for different colorectal cancer sites. Incident colorectal cancer in the cecum, appendix, ascending colon, hepatic flexure, transverse colon, and overlapping colon lesions (ICD-O-3 codes C18.0-18.4 and C18.8-18.9) were categorized as proximal colorectal cancer (n = 971, 56% of total cases), and cancers in the splenic flexure, descending colon, sigmoid colon, rectosigmoid junction, and rectum (ICD-O-3 codes C18.5-C18.7, C19.9, C20.9) were categorized as distal colorectal cancer (n = 760, 44% of total cases). No cases had missing codes or unspecified subsites.

We also conducted several sensitivity analyses. The first set of sensitivity analyses was to investigate whether mineral sources (foods vs. supplements), mineral category (putatively anti- vs. procarcinogenic), or any individual score component was particularly influential in the observed associations. First, we investigated whether including in our models one or more variables to represent supplement-taking behaviors (multivitamin and/or other supplement use) materially affected our estimated associations. Second, we created separate supplement-only and diet-only mineral scores, categorized each of the two scores into five categories based on their distributions, and assessed their joint/combined association with colorectal cancer. For the latter analysis, the reference category was participants who jointly took no supplemental minerals and had a low diet-only mineral score. Third, similarly as for the latter analysis, we created separate anti- and procarcinogenic mineral scores, assessed their correlation with Pearson correlation coefficients, and then categorized the two scores into quintiles and assessed their joint/combined association with colorectal cancer. For the latter analysis, the reference category was participants who had a joint low anticarcinogenic mineral score/high procarcinogenic mineral score. A P_interaction was calculated in a multivariable model in which both scores were entered as continuous variables, along with an anticarcinogenic mineral score × procarcinogenic mineral score interaction term; the P value for the multiplicative interaction term was taken as the P_interaction. Fourth, we took individual mineral components in and out of the mineral score one at a time and assessed the associations of (i) the remaining 10-component scores with colorectal cancer, and (ii) each mineral score component individually with colorectal cancer, adjusted for its respective remaining 10-component mineral score.

In additional sensitivity analyses, we assessed whether adjustment for aspirin and other nonsteroidal anti-inflammatory drug use affected the mineral score–colorectal cancer association by including only subjects who replied to the 1992 follow-up questionnaire regarding the use of aspirin and other nonsteroidal anti-inflammatory drugs. To reduce ambiguity in the temporal relation between the mineral score and incident colorectal cancer, we excluded participants who were diagnosed with colorectal cancer or died during the first year of follow-up. We also assessed censoring participants when they reached the age of 75.

Selected characteristics of the participants at baseline by quintiles of the mineral score are summarized in Table 2. Study participants were, on average, 61 years of age, and 99% were white. Those in the higher mineral score quintiles tended to be less educated and more likely to have diabetes, a normal BMI, and a higher physical activity level than those in the lower quintiles. On average, participants in the upper relative to the lower quintiles had a smaller waist–hip ratio; higher total fat, dietary fiber, and total fruits and vegetables intakes; and lower total energy and red and processed meats intakes.

The associations of the mineral score with risk of incident colorectal cancer estimated using Cox proportional hazards regression models are summarized in Table 3. Adjustment for multiple known and suspected risk factors had a minimal effect on the risk estimates. In the multivariable-adjusted analyses, for each one-point increase in the mineral score, there was an estimated statistically significant 2% lower risk for incident colorectal cancer. When analyzed by quintiles, there was a statistically significant trend for decreasing colorectal cancer risk with an increasing score, and those in the upper relative to the lowest quintile were at a statistically significant approximately 25% lower risk. There were no substantial or consistent differences in our findings in relation to colon site (Supplementary Table S1) or according to levels of the other risk factors noted in the statistical section (Supplementary Table S2).

The results of the sensitivity analyses were as follows. Adjustment for multivitamin and/or other supplement use did not materially alter our results (Supplementary Table S3). In the joint/combined analysis of the diet-only and supplement-only mineral scores (Table 4), there was (i) decreasing risk with an increasing diet-only mineral score among those who did not take supplemental minerals, culminating in an HR of 0.84 (95% CI, 0.80–0.88) among those in the upper diet-only mineral score quantile; (ii) decreasing risk with an increasing supplement-only mineral score among those in the lowest diet-only mineral score quantile, culminating in an HR of 0.87 (0.82–0.90) among those in the upper supplement-only mineral score quantile; and (iii) the lowest risk (HR, 0.66; 95% CI, 0.63–0.68) was found among those who were in the joint high diet-only/high supplement-only mineral score category relative to those who were in the joint low diet-only/no supplemental minerals category.

In other sensitivity analyses, the correlation between the anti- and procarcinogenic mineral scores was r = 0.23 (P = 0.06). In the joint/combined analysis of the anti- and procarcinogenic mineral scores (Supplementary Table S4), the lowest risk (HR, 0.69; 95% CI, 0.61–0.87) was found among those who were in the joint high anticarcinogenic/low procarcinogenic mineral score category relative to those who were in the joint low anticarcinogenic/high procarcinogenic mineral score category (P_interaction = 0.04). The risk estimates after removal and replacement of each score component one at a time (Supplementary Table S5) differed only minimally from those with the full score. The associations of each individual score mineral—adjusted for its respective remaining 10-component mineral score—with colorectal cancer were all less than that for the overall mineral score (Supplementary Table S6). For those in the upper relative to the lowest intake quintiles of the putative anticarcinogenic minerals, the estimated HRs ranged from 0.84 for total calcium intake to 0.99 for total zinc intake, and for the putative procarcinogenic minerals they ranged from 1.01 for sodium to 1.21 for copper.

Finally, in additional sensitivity analyses, exclusion of those who died or were diagnosed with colorectal cancer during their first year of follow-up, or censoring participants when they reached age 75 had negligible impact on the risk estimates (Supplementary Table S7). When we used 1992 as the baseline for follow-up, additional adjustment for aspirin and other NSAID use did not materially alter the results (Supplementary Table S8).

Our findings suggest that higher calcium, magnesium, manganese, zinc, selenium, potassium, and iodine intakes, combined with lower iron, copper, phosphorus, and sodium intakes, may be associated with lower risk of incident colorectal cancer. As discussed below, our findings are consistent with much of the data available from previous studies on associations of calcium, magnesium, zinc, selenium, iodine, iron, copper, and phosphorus intakes individually with colorectal cancer risk. Our findings of decreasing risk of colorectal cancer with an increasing mineral score support the antioxidant-related and other anticolon carcinogenic effects of calcium, magnesium, manganese, zinc, selenium, potassium, and iodine, and the prooxidant and other pro-colon carcinogenic effects of iron, copper, phosphorus, and sodium. To our knowledge, there are no previous reports of associations of combined intakes of the aforementioned 11 minerals with colorectal cancer incidence.

Whereas study of calcium in relation to colorectal carcinogenesis has been considerable, study of other minerals in relation to the disease has been relatively limited. In a 2015 meta-analysis of 20 prospective cohort studies of a calcium–colorectal cancer association, the summary relative risk (RR) for those in the highest relative to those in the lowest calcium intake categories was 0.80 (95% CI, 0.70–0.92; refs. 33). In a 2016 meta-analysis of 4 randomized, controlled trials of the efficacy of supplemental calcium on reducing colorectal adenoma recurrence, the summary RR was 0.89 (95% CI, 0.82–0.96; ref. 42). In a 2014 meta-analysis of 4 prospective cohort studies of a magnesium–colorectal cancer association, the summary RR among those in the highest relative to the lowest category of magnesium intake was 0.78 (95% CI, 0.66–0.92; ref. 8). In a 2013 meta-analysis of 6 prospective cohort studies of a zinc–colorectal cancer association, the summary RR for those in the highest relative to the lowest category of zinc was 0.83 (95% CI, 0.72–0.94; ref. 43). In a 2016 meta-analysis of 10 cohort studies of associations of selenium exposure (measured as supplemental intake or serum or toenail concentrations) with colorectal cancer, the summary odds ratio (OR) for those in the highest relative to the lowest category of selenium exposure was 0.89 (95% CI, 0.67–1.17; ref. 16). In a 2016 meta-analysis of 8 case–control and 2 prospective cohort studies of an iron–colorectal adenoma association, the summary RRs for those in the highest relative to the lowest categories of intakes of total iron (dietary plus supplemental), dietary iron, supplemental iron, and heme iron were, respectively, 0.93 (95% CI, 0.62–1.42), 0.83 (95% CI, 0.71–0.98), 0.73 (95% CI, 0.54–0.97), and 1.23 (95% CI, 1.03–1.48; ref. 44). In a French-based case–control study (n = 171 cases, 309 controls), which to our knowledge is the only reported study of a copper–colorectal cancer association, the OR for those in the fourth relative to the first quartile of dietary copper intake was 2.4 (95% CI, 1.3–4.6; ref. 25). In a French-based prospective study (n = 67,312, of whom 172 developed colorectal adenoma or carcinoma), the RR for those in the fourth relative to the first quartile of phosphorus intake was 0.70 (95% CI, 0.54–0.90; ref. 27). To the best of our knowledge, there are no reported studies on associations of manganese, potassium, iodine, or sodium intakes with colorectal neoplasms.

In summary, calcium has been consistently, modestly associated with risk in a substantial number of studies; magnesium, zinc, and selenium have been modestly inversely associated with risk in a relatively small number of studies; copper was directly associated with risk in the one study to investigate it; the findings for iron have been unclear; and there are no data on associations of manganese, potassium, iodine, or sodium with colorectal neoplasms. Overall, these findings suggest that multiple minerals, which as noted in Table 1 may plausibly affect colorectal cancer risk, individually may be modestly associated with colorectal cancer risk in the hypothesized directions.

A few studies investigated associations of limited combinations of certain minerals with colorectal neoplasms. In a randomized, controlled trial of calcium supplementation (1,200 mg/day) over 4 years, the RRs for adenoma recurrence among those with dietary calcium:magnesium intake ratios above and below the median at baseline were 0.98 (95% CI, 0.75–1.28) and 0.68 (95% CI, 0.52–0.90), respectively (9). In a case–control study (n = 688 adenoma cases, 1,306 polyp-free controls), total magnesium consumption was statistically significantly inversely associated with colorectal adenoma, primarily among individuals with a low calcium:magnesium intake ratio (7). On the other hand, in a pooled case–control study of colorectal adenoma (n = 807 cases, 2,185 controls), associations of calcium with adenoma did not differ according to magnesium and phosphorus intakes, and associations of calcium:magnesium and calcium:phosphorus ratios with adenoma did not substantially differ from those involving calcium alone (45). In the above-noted French prospective cohort study (27), there was no association of a calcium:phosphorus ratio with risk for colorectal neoplasms. In the Iowa Women's Health Study cohort (n = 34,708), heme iron was directly associated with colon cancer incidence within each category of zinc; however, zinc was inversely associated with colon cancer incidence within each category of heme iron (14).

Although a combined mineral score has not been previously reported, other similarly constructed scores to account for multiple, interacting exposures that individually may modestly affect risk are increasingly reported. OBSs, comprised of anti- and prooxidant exposures, were inversely associated with colorectal adenoma and cancer (40, 41). A dietary inflammatory index, a score composed of multiple putative dietary pro- and anti-inflammatory exposures such that a higher score represents a more proinflammatory diet, was directly associated with colorectal cancer, other cancers, and other chronic diseases (46). In order to incorporate the synergistic effects of food items in the Mediterranean diet, the Mediterranean diet score was used to investigate associations of a Mediterranean diet pattern with colorectal cancer and cardiovascular disease, finding that higher Mediterranean diet scores are associated with lower colorectal cancer risk (47, 48). The Healthy Eating Index, a score based on recommendations from MyPyramid and the US Dietary Guidelines for Americans, was statistically significantly inversely associated with colorectal cancer risk (49).

A strength of our study is the novel composite mineral score used to summarize multiple mineral exposures. Whereas the contributions of individual minerals to risk for colorectal cancer may be small, collectively they may be substantial. Inconsistent results for individual minerals in prior epidemiologic studies may have been because the minerals individually are only weakly associated with risk, the weak associations are difficult to detect using current dietary assessment methods, and investigating individual minerals adjusted for all others does not account for the interactions (including synergisms and antagonisms) among them. Synergisms often occur on a metabolic level. For example, an adequate copper intake is necessary for iron metabolism. Antagonisms, on the other hand, usually occur on the absorption level. A high intake of calcium, for example, may suppress zinc absorption in the gastrointestinal tract. Calcium, an antagonist of magnesium, also competes with magnesium for intestinal absorption and transport. Also, in animal studies, calcium inhibited heme-induced cytotoxicity and prevented heme-induced colonic epithelial hyperproliferation (50). The mineral score method allowed us to summarize overall mineral exposure while accounting for the biological interactions among the minerals.

Other strengths of our study include the large sample size; the prospective design; accurate and complete data on colorectal cancer diagnosis; data on many potential confounding variables; the use of cancer incidence, rather than mortality, as the endpoint of interest; the use of a validated dietary assessment instrument; and our multiple sensitivity analyses.

Study limitations include the known limitations of FFQs (e.g., recall error, limited number of food choices) and measuring diet only once. Another limitation was the possible overestimation of fruit and vegetable intake (the reported average consumption of total fruits and vegetables in this cohort was 37.8 servings/week, or 5.4 servings/day). Also, the study population comprised only white women; thus, generalization to men, other populations, or races may be limited. Also, data on colorectal cancer screening were not collected until near the end of follow-up, after only 68.3% of the study participants remained alive; however, not being able to include colorectal cancer screening, a potential effect-modifying factor, in our analyses likely attenuated our estimated associations. This is because no matter how high risk someone's diet or lifestyle may be, if via colorectal cancer screening (which is actually mostly colorectal adenoma detection and subsequent removal) they have their adenomas removed, they are unlikely to get colorectal cancer. So, in a sense, these patients are “misclassified,” thus attenuating what the associations may have been had there been no screening. Finally, we cannot rule out the possibility that some supplements were taken in response to symptoms or clinical disease; however, in our sensitivity analyses, exclusion of participants who were diagnosed with colorectal cancer or died during the first year of follow-up did not materially affect our estimated associations.

In conclusion, our findings, taken in context with those from previous studies, suggest that higher calcium, magnesium, manganese, zinc, selenium, potassium, and iodine intakes, combined with lower iron, copper, phosphorus, and sodium intakes may be associated with lower risk of colorectal cancer.

No potential conflicts of interest were disclosed.

The findings and conclusions contained within are those of the authors and do not necessarily reflect positions or policies of the NCI. The NCI had no influence on the analysis and interpretation of the data, the decision to submit the manuscript for publication, or the writing of the manuscript.

Conception and design: S. Swaminath, R.M. Bostick

Development of methodology: S. Swaminath, R.M. Bostick

Acquisition of data (provided animals, acquired and managed patients, provided facilities, etc.): DA Lazovich

Analysis and interpretation of data (e.g., statistical analysis, biostatistics, computational analysis): S. Swaminath, A.E. Prizment, DA Lazovich, R.M. Bostick

Writing, review, and/or revision of the manuscript: S. Swaminath, C.Y. Um, A.E. Prizment, DA Lazovich, R.M. Bostick

Administrative, technical, or material support (i.e., reporting or organizing data, constructing databases): S. Swaminath

Study supervision: R.M. Bostick

This work was supported by the NCI of the NIH (grant R01 CA039742).

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.