Introduction

Colorectal cancer (CRC) is the third most common cancer around the world. Dietary and lifestyle factors play an important role in the etiology of CRC; a healthy diet and lifestyle can prevent a large number of CRC incidences and morbidities [1,2,3]. Generally, the dietary food sources are quite different from various geographical areas; the intake of macro and trace elements from diet varies accordingly among humans [4]. With the progress of economics and the change of environment, excessive amounts of mineral elements are found in food or drinking water. Although elements are indispensable to the human body, excessive, inadequate, or unbalanced elements can lead to different levels of physical abnormality or disease [5, 6]. In the past 20 years, the importance of trace elements has been widely recognized, and it is of great significance for biological monitoring of trace element concentration in various media such as blood or urine [7]. In patients with CRC, the cancer tissues and non-cancerous tissues showed significant differences in the concentration of trace elements, suggesting that these elements might play a vital role in the development of cancer [8]. However, to the best of our knowledge, very few analyses have focused on the relationship between different element intake levels and risk of CRC, although several studies reached inconsistent results [9, 10].

All the macroelements such as calcium (Ca), magnesium (Mg), and potassium (K), as well as trace element iron (Fe) can be obtained through diet or supplements [11]. Ca is a vital element in health and maintenance of growth and mature bones, and dietary Ca intake from fruits and vegetables has been reported to inversely relate to the risk of CRC [12,13,14]. Fe is an essential dietary element. Fe deficiency and heme Fe deficiency anemia are global health problems. However, the ability of Fe to cycle between oxidized and reduced forms also renders it capable of contributing to free radical formation, which may have deleterious effects, including promutagenic effects that can potentate tumor formation [15]. Additionally, previous epidemiological data besides showed a suggestive association between dietary heme Fe and risk of colon cancer [16]. Mg is crucial for every cell, and low concentration of Mg increases the risk of various diseases [17]. Mg plays a key role in maintenance of gastrointestinal and hormonal functions; there is convincing evidence that intake of garlic and Mg may significantly protect against developing CRC [14]. K is a nutrient that easily deficient for human health because it is usually not present in foods or is commonly eaten as a dietary supplement [18]. A high intake of dietary K is a statistically significant protective factor in females and males for CRC [9]. Since the effect of element intakes from diet associated with CRC has been widely concerned in recent years, the controversy results have continued to confuse physicians and patients alike. Therefore, the purpose of this study was to explore the relationship between the high intake of these four elements (Ca, Fe, Mg, and K, respectively) and the incidence of CRC through a meta-analysis of cohort and case-control studies.

Materials and Methods

Search Strategy

This study was conducted according to Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines [19].PubMed, Web of Science, and Chinese National Knowledge Infrastructure (CNKI) databases were queried by using the following keywords, and all articles in both Chinese and English were collected from the inception date to December 17, 2017.

English retrieval strategy of PubMed and Web of Science databases are (1) colorectal cancer OR colon cancer OR rectal cancer OR rectum cancer OR colon and rectum cancer OR colorectal carcinoma OR colon carcinoma OR Colon rectum carcinoma OR carcinoma of colon and rectum OR CRC; (2) trace element OR microelement OR calcium OR Fe OR iron OR magnesium OR potassium OR kalium; and (3) (1) AND (2).

Chinese retrieval strategy of CNKI database are (1) trace element OR calcium OR Fe OR magnesium OR potassium; (2) colorectal cancer; and (3) (1) AND (2).

Study Selection

The initial selection of articles was based on titles and abstract to exclude studies unrelated to element intake and CRC. The collection of relevant data was extracted from the eligible studies according to the criteria listed below. (1) The study was a cohort or case-control; (2) results of the study included at least one dietary element in a person’s daily intake; (3) the outcome of interest was colorectal; (4) the hazard ratio (HR) estimates or odds ratio (OR) in case-control studies with corresponding 95% confidence interval (CI) were provided; and (5) potential confounders, including age, sex, BMI, and total energy intake and other factors should be adjusted.

Exclusion criteria included the following: (1) similar objective results in the same study or in the same institution at different times; (2) research has some problems, such as design defects and poor quality and smaller sample size (n < 200), and the data of the study is not complete; (3) the full text can neither be obtained from the database nor by contacting the author; (4) the statistical method had an error that cannot be modified and measurement data cannot provide the effect size; and (5) review articles.

Data Extraction and Quality Assessment

Data extraction from included studies was carefully performed by three independent authors to ensure the accuracy of the extracted information. The following data were extracted from each included eligible study using a standardized report form: the first author and the publishing time, follow years and time period, area, sex, age, the number of cases and participants, assessment method, the comparison of elemental intake, the HR or of CRC and the corresponding 95% CI, and covariate adjusted in each study. We extracted the value of the intake, and the corresponding 95% CI in the highest categories (tertile quartile or quintile) measured versus after HR or adjustment. HR is the ratio of the hazard rates corresponding with the conditions described by two levels of an explanatory variable. HR = P/(1 − P); P = HR/(1 + HR) [20]. OR refers to the number to the case group and the ratio with the exposure number divided by exposure to toll and the number of non exposed than in the control group, in epidemiological studies is a commonly used indicator of case-control study [21].

We employed Newcastle-Ottawa Scale (NOS) to assess the quality of all included studies [22]. The NOS used two different tools for the case–control and cohort studies, and consist of three parameters of quality: selection (0–4 points), comparability (0–2 points), and outcome (0–3 points) [23].NOS Scores ranged from 0 to 9, and we defined studies of high quality as those that scored 6–9 [24]. Discrepancy in quality assessment was discussed and resolved by the two reviewers. The literature with a score greater than 5 was included in our analysis [25].

Statistical Analysis

Subgroup analysis, heterogeneity testing, and publication bias assessment were performed according to the PRISMA checklist [19]. We used software Stata version 12.0 to analyze the data. All statistical tests were two-sided, and a P value < 0.05 was considered statistically significant.

The heterogeneity between studies was evaluated using the chi squared-based Q statistic and I2 statistic. If a P value for the Q statistic > 0.05 and I2 < 50%, there was a low heterogeneity in the included studies, and the results of fixed effect model were selected [26, 27]; if a P value for the Q statistic < 0.05 and I2 > 50%, there was evidence of substantial heterogeneity in the included studies, and then the random effect model would be chosen.

In addition, potential publication bias was investigated by the use of Begg’s funnel plots and Egger’s regression asymmetry test. When the measuring tool is the same, the effect size would further be used for analysis of data. On the contrary, if different measurement tools were used, we switched to standardized effect size. All analyses were performed with the 95% CI. When necessary, sensitivity analysis was performed to test the stability of the results.

Results

Study Characteristics

According to the retrieval strategy, there was a total of 29 eligible studies [28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56] selected in this meta-analysis, including a total of 14 cohort studies [28,29,30,31,32,33,34,35,36,37,38,39,40,41] and 15 case-control studies [42,43,44,45,46,47,48,49,50,51,52,53,54,55,56] (Fig. 1). We reported some characteristics of the included studies, such as the first author and the publishing time, follow years and time period, area, sex, age, the number of cases and participants, assessment method, and the comparison of elemental intake from each study between the highest categories (tertile, quartile, or quintile) and the lowest category. The characteristics of these studies were summarized in Tables 1 and 2.

Fig. 1
figure 1

Flowchart of the study selection process

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Table 1 The characteristics of 14 cohort studies
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Table 2 The characteristics of 15 case-control studies
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Of the 14 cohort studies, researches focused on Ca, heme Fe, and Mg intakes which had 8, 2, and 6 studies, respectively. Of the 15 case-control studies, researches with respect to Ca, Fe, Mg, and K intakes contained 11, 9, 3, and 2 studies, respectively. Among them, 26 of the 29 studies included were published after 2000. Confounding variables in these studies (age, sex, body mass index, total energy intake, and other factors) were adjusted. We also evaluated the quality of 29 studies, as shown in Tables 1 and 2, both greater than 5, indicating that all these studies were of high quality.

Meta-Analyses of Cohort Studies

When all cohort studies were pooled, the obtained HR represented the risk of CRC. The HR of dietary Ca intake was 0.76 (95% CI 0.72, 0.80), the HR of dietary Mg intake was 0.80 (95% CI 0.73, 0.87), and the HR of dietary heme Fe intake was 1.00 (95% CI 0.87, 1.14) (Fig. 2). All these results demonstrated that dietary Ca and Mg intakes were negatively correlated to the risk of colorectal, colon, and rectal cancer in the subgroup meta-analysis of the study designed. Similarly, the risk of colon cancer was negatively correlated (HR = 0.99, 95% CI 0.77, 1.21) with dietary heme Fe intake (Fig. 2). However, the risk of CRC and rectal cancer in the subgroup meta-analysis was positively correlated with dietary heme Fe, as the HR was 1.01 (95% CI 0.82, 1.19) and 1.04 (95% CI 0.67, 1.42), respectively (Fig. 2). Our meta-analysis showed that higher dietary Ca and Mg intakes seemed to have a protective effect for CRC. Higher heme Fe intake appeared to be a risk factor for colorectal and rectal cancer and might have a protective effect for colon cancer.

Fig. 2
figure 2

Pooled random-effects HR (95% CI) of CRC risk comparing with the highest category of element intake from diet

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Meta-Analyses of Case-Control Studies

Consistent with the cohort study, higher Ca and Mg intakes in case-control studies were still considered to be protective for CRC. The pooled OR for dietary Ca and Mg intakes were 0.36 (95% CI 0.32, 0.40) and 0.80 (95% CI 0.63, 0.98), respectively (Fig. 3). In addition, the OR of CRC of dietary K and Fe intakes were 0.97 (95% CI 0.74, 1.21) and 1.04 (95% CI 0.91, 1.18), respectively (Fig. 3). Analysis of case-control studies found that dietary high K intake might reduce the incidence of CRC, while high Fe intake from diet increased the risk of CRC.

Fig. 3
figure 3

Pooled random-effects OR (95% CI) of CRC risk comparing with the highest category of element intake from diet

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Heterogeneity and Publication Bias

By comparing the different element intakes and risk of CRC, the differences in dietary Ca intake in the case control showed that there were significant heterogeneity in 11 studies (P < 0.01, I2 = 87.9%). According to the quality assessment of the studies and the availability of the full text, heterogeneity may be affected by these factors: sample size and age. By using a dependent variable of subgroup analysis and meta-regression, it showed that single or multiple covariates could explain the heterogeneity.

Begg’s funnel plots suggested the absence of asymmetry, we did not find any statistically significant publication bias in other groups. The funnel plots are shown in Figs. 4 and 5. It was confirmed that rectal cancer, colon cancer, and CRC was associated with the intakes of four elements through Egger regression asymmetrical test, respectively (all P > 0.05). Results of the Begg’s test of the cohort study showed that the P values of Ca, heme Fe, and Mg were 0.428, 0.754, and 0.127, respectively. Results of the Begg’s test in the case-control study indicated that the P values of Ca, Fe, Mg, and K were 0.592, 0.913, 0.296, and 1.000, respectively.

Fig. 4
figure 4

Begg’s funnel plot (with pseudo 95% CI) of all cohort studies in the meta-analysis

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Fig. 5
figure 5

Begg’s funnel plot (with pseudo 95% CI) of all case-control studies in the meta-analysis

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Discussion

To investigate the relationship between the risk of CRC and dietary intakes of individual Ca, Fe, Mg, and K elements, we conducted a meta-analysis containing 29 studies. We extracted HR or OR and corresponding 95% CI of each element in the included cohort and case-control studies, and further conducted subgroup analyses.

Most of the studies in this meta-analysis used the food frequency questionnaire (FFQ) to assess the extent of exposure. The FFQ is a dietary assessment tool widely used for epidemiological studies to study the relationship between dietary intake and disease or risk factors since the early 1990s [57]. In our meta-analysis, all cohort studies on the relationship between high intakes of Fe and the risk of CRC were all calculated as dietary intake of heme Fe. Dietary total Fe is present in food, and the most important form is heme Fe [58]. Heme Fe is mainly found in animal liver, animal blood, and red meat, which can be absorbed directly. Previous research have claimed that red meat consumption can replenish the Fe; however, the high consumption of red meat or its products, is not good for health, which will increase the risk of noncommunicable diseases, including cancer, type 2 diabetes, and cardiovascular diseases [59]. The meta-analysis of included cohort studies showed that the high heme Fe intake form diet was positively correlated to the incidence of CRC and rectal cancer, suggesting that high intake of dietary heme Fe might increase the risk of CRC and rectal cancer. In the meta-analysis of case-control studies, daily high Fe intake form diet was positively correlated with CRC morbidity, suggesting that excessive intake of dietary Fe might increase the risk of CRC.

Healthy lifestyle recommendations may improve dietary Mg intake and play an independent role in improving certain metabolites [60]. Our meta-analysis indicates that dietary intakes of Ca, Mg, and K may be protective factors for CRC, and high intake of them from diet may reduce the risk of CRC. Fe and heme Fe may be risk factors, and increased dietary intake may increase the risk of CRC. Previous meta-analyses have shown that higher dietary Mg intake appears to exhibit protective effects on cancer, especially CRC and female cancer [61,62,63]. Based on the literature we included, we found the highest category intake values for these four elements, and the intakes of Ca, Fe, Mg, K in the highest categories (tertile, quartile, or quintile) were greater than 505.77 mg/day, 12.9 mg/day, 319 mg/day, and 3424 mg/day, respectively (Tables 1 and 2). The adequate intake of Ca for people ages between 31–50 is 1000 mg/day, and ages between 50–70 is 1200 mg/day [64]. The recommended dietary allowance (RDAs) for Fe is 8 mg/day for men ages between 31–70 and for women over 50, and 18 mg/day for women ages between 31–50 [65]. RDAs for Mg are 420 mg/day for men ages between 31–70, which is 320 mg/day for women [64]. An adequate intake of K is 4700 mg/day [66]. Promoting a healthy human diet based on RDAs at these ages may play a vital role in preventing CRC.

This meta-analysis also has several limitations. First, as a meta-analysis of epidemiological studies, it does not allow for uniform confusion in all studies. For example, differences in follow-up time may skew the results from included studies. Second, because of the inability to accurately assess dietary K intake, our study only conducted a meta-analysis of two case-control studies. More studies are needed to confirm the relationship between the risk of CRC and high intake of dietary K. Finally, since we only extracted the HR or, the corresponding 95% of the element intake and the corresponding risk of CRC in the study could also lead to the deviation from the meta-analysis results.

In summary, this meta-analysis suggests that higher or increased intakes of individual dietary Ca, Mg, and K may help to reduce the risk of CRC slightly, whereas higher or increased intakes of dietary heme Fe and Fe, respectively may increase the risk of CRC. Therefore, more prospective studies are needed in future meta-analyses to further demonstrate that four individual element (Ca, Fe, Mg, and K) intakes are risk factors of CRC, and more relevant health policy should be carried out to prevent that hazard effect.