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Systematic Review

Association between Dietary Nitrate, Nitrite Intake, and Site-Specific Cancer Risk: A Systematic Review and Meta-Analysis

1
Faculté des Sciences de L’Administration FSA, Université Laval, Québec, QC G1V 0A6, Canada
2
Department of Epidemiology and Biostatistics, School of Public Health, Southeast University, Nanjing 210009, China
3
Riphah Institute of Pharmaceutical Sciences, Riphah International University, Islamabad 44000, Pakistan
4
Institute of Epidemiology, Disease Control & Research (IEDCR), Dhaka 1212, Bangladesh
*
Authors to whom correspondence should be addressed.
These authors contributed equally to this work.
Nutrients 2022, 14(3), 666; https://doi.org/10.3390/nu14030666
Received: 16 November 2021 / Revised: 25 January 2022 / Accepted: 28 January 2022 / Published: 4 February 2022
(This article belongs to the Section Micronutrients and Human Health)

Abstract

:
Background: People consume nitrates, nitrites, nitrosamines, and NOCs compounds primarily through processed food. Many studies have yielded inconclusive results regarding the association between cancer and dietary intakes of nitrates and nitrites. This study aimed to quantify these associations across the reported literature thus far. Methods: We performed a systematic review following PRISMA and MOOSE guidelines. A literature search was performed using Web of Science, Embase, PubMed, the Cochrane library, and google scholar up to January 2020. STATA version 12.0 was used to conduct meta-regression and a two-stage meta-analysis. Results: A total of 41 articles with 13 different cancer sites were used for analysis. Of these 13 cancer types/sites, meta-regression analysis showed that bladder and stomach cancer risk was greater, and that pancreatic cancer risk was lower with increasing nitrite intakes. Kidney and bladder cancer risk were both lower with increasing nitrate intakes. When comparing highest to lowest (reference) categories of intake, meta-analysis of studies showed that high nitrate intake was associated with an increased risk of thyroid cancer (OR = 1.40, 95% CI: 1.02, 1.77). When pooling all intake categories and comparing against the lowest (reference) category, higher nitrite intake was associated with an increased risk of glioma (OR = 1.12, 95% CI: 1.03, 1.22). No other associations between cancer risk and dietary intakes of nitrates or nitrites were observed. Conclusion: This study showed varied associations between site-specific cancer risks and dietary intakes of nitrate and nitrite. Glioma, bladder, and stomach cancer risks were higher and pancreatic cancer risk was lower with higher nitrite intakes, and thyroid cancer risk was higher and kidney cancer risk lower with higher nitrate intakes. These data suggest type- and site-specific effects of cancer risk, including protective effects, from dietary intakes of nitrate and nitrite.

1. Introduction

Cancer is a leading cause of death worldwide, accounting for nearly 10.0 million (approximately one in six) deaths, in 2020 [1]. The global cancer burden is expected to be 28.4 million cases in 2040, a 47% rise from 2020 [1]. With this growing global burden, more evidence-based practice is needed in the identification and management of risk factors for cancer development. Although the causes of cancer are not completely understood, numerous factors are known to increase risk, including non-modifiable factors (e.g., gender, age, genetic factors) and modifiable factors (e.g., dietary, lifestyle) [2]. For instance, one-third of deaths from cancer are due to behavioral and dietary risks [3].
Over the past few years, new evidence has led a paradigm change in our understanding of the role of both dietary nitrate and nitrite on human health, particularly in relation to cancer risk [4,5,6,7]. Historically, a high intake of nitrate and nitrite were considered harmful food additives and listed as probable human carcinogens under conditions where endogenous nitrosation could take place and lead to formation of N-nitroso compounds (NOC) [2,4,8]. Nowadays, nitrate, nitrite and nitrosamine occur naturally in fruits and vegetables, which are regarded as an important part of a healthy diet due to the powerful evidence of beneficial health effects against cancer [9,10]. Numerous studies concluded that fruits and vegetables contribute over 80% of the daily dietary intake of nitrate [11,12,13] and nitrite [14,15,16,17], which represent the primary sources of exposure to nitrate and nitrite by humans.
Nitrates and nitrites are also widely used in food processing, such as in processed meats (e.g., sausages, hot dogs, luncheon meats, ham, and bacon) where they are used to reduce microbial spoilage and preserve meat products [18,19]. High consumption of both processed and fresh meat is linked to increased cancer risk (e.g., gastric [20], pancreatic [21], bladder [5], and colorectal [19]). It is the presence of nitrite, amides, and amines [8,22,23,24] in processed meats and heme iron in fresh meat [25,26,27,28,29] that is considered to be responsible for these risk effects. Moreover, there are other biological and dietary factors that may contribute to the effects that nitrates, nitrites, and their related compounds have on the body. For example, certain strains of oral bacteria have been identified that reduce nitrate found in food to nitrite [30]. This ”endogenous nitrosation” is known to occur mostly in the digestive system’s organs, especially the stomach, rectum, colon, and urinary bladder [31,32], but it can take place in any part of the body. Some of the NOC’s forms have been identified in human urine [33].
Despite the carcinogenic potential of NOCs, some epidemiologic studies found no association between dietary nitrate, nitrite, and NOC intake and cancer in humans [34,35,36]. Case control studies in Iowa [35] and Spain [36] found no association between long-term, average nitrate levels in public water supplies and bladder cancer. This might be due to the fact that nitrate in drinking water and their related compounds are in low concentrations [35,36,37]. Overall, epidemiologic studies that have examined associations between nitrate, nitrite, and NOC compounds and various types of cancer in humans have returned mixed and, in some cases, complex results. Some studies show positive associations [5,6,20,38,39], many show no association [35,36,37], and others show inverse associations, which may be due to confounding factors [31,37,40,41,42,43,44]. In this study, this systematic review aims to evaluate the association and clarify the relationship between dietary consumption of nitrate and nitrite and selected, site-specific cancer risks in humans.

2. Methods

Meta-analyses are typically used to estimate the overall/mean of an outcome of interest. However, inference about between-study variability, which is typically modeled using a between-study variance parameter, is usually an additional aim [45]. Meta-regression is a sensitivity analysis. In primary studies, we use regression, or multiple regression, to assess the relationship between one or more covariates (moderators) and a dependent variable. The same approach can be used with meta-analysis, except that the covariates are at the level of the study rather than the level of the subject, and the dependent variable is the effect size in the studies rather than subject scores. We use the term meta-regression to refer to these procedures when used in a meta-analysis [46].

2.1. Search Methods for Identifications of Studies

We performed a systematic review following PRISMA and MOOSE guidelines. This study evaluated the association and clarified the relationship between dietary nitrate, nitrite, and selected, site-specific cancers. Two investigators independently searched literature on the Web of Science, Embase, PubMed, the Cochrane library, and google scholar up to January 2020.

2.2. The Keywords and Search Terms Used

A literature search was performed on all the databases by using the following keywords: (Nitrate OR nitrates NO3-N OR NO3- OR nitrite OR nitrites OR N-nitroso compounds OR NO2-N OR NO2- OR sodium nitrate OR NaNO3 OR sodium nitrite OR NaNO2 OR ammonium nitrate OR NH4NO3 OR nitrosamine OR Nitrite amine OR NH2NO2 OR DMNA OR NDMA OR NDBA OR NMEA OR NDEA OR NPIP OR NPYR OR NMOR OR NDPA) AND (Neoplasm OR Tumor OR Tumour OR Cancer OR Carcinoma OR Carcinogenesis OR Malignant OR Adenocarcinoma OR Non-Hodgkin lymphoma OR Glioma) AND (Dietary OR Diet OR food). The full search strategy is provided in the online Supplementary Table S1. The bibliographies of original studies, reviews and relevant conferences were manually searched.

2.3. Inclusion and Exclusion Criteria

Inclusion criteria: Only articles reporting associations or outcomes between dietary nitrate, nitrite, and cancer in humans were used (both qualitatively and quantitatively). Exclusion criteria: All articles with animal experiments, articles not published in English, articles with a short commentary, short notes, no data or no records, or incomplete results and letters were excluded. Search results were screened for inclusion and exclusion criteria by four authors.

2.4. Data Extraction and Quality Assessment

Data collection and quality assessment processes were performed by four authors (Essien, Weihua, Kassim, and Abbas), and any disagreement was settled by group discussion. Qualitative analysis: the data were extracted using a self-developed data extraction form. For selected studies, data included the study characteristics: first author, year published and country, study design, exposure categories (nitrate and nitrite intake mg/day), reported Risk ratios (RR), odds ratios (OR), and hazard ratios (HR) with their 95% CIs, cancer sites, and adjustment. Quantitative analysis: the data included: Nitrate dosages and nitrite dosages from dietary intake; OR/RR/HR, with their 95% CI for each category of exposure.
The Newcastle-Ottawa Quality Assessment Scale (NOS) was used to assess the quality of the included studies. Scores ranged from 0 to 9; studies with a score ≥7 were seen as high-quality studies [47].

2.5. Statistical Analysis

Software: STATA version 12.0 (StataCorp LP, College Station, TX, USA) was used to conduct meta-regression and meta-analysis (of both binary and continuous outcome variables, (Effect/CI)). (Statistical calculations and figures were produced with this software).
Analysis of data: All nitrate and nitrite dosage, and their related compounds, OR, RR, and HR, with 95% CIs were extracted (both crude and adjusted OR, RR, and HR,). The RRs and HRs were assumed to be the accurate estimates of ORs. The median intake of nitrate and nitrite dosage was calculated from the range given, (formula = lowest dosage (lower limit) + highest dosage (upper limit) divided by two in each given quartile). When the median intake was given, the data was used directly. When the interval of a quartile of any category of nitrate or nitrite dosage was not provided, the width of the class interval of quartile before this quartile was used to calculate and estimate the interval, (when the shortest or longest category was open-ended, it was assumed that the open-ended interval length had the same length as the adjacent interval). Logarithm of the ORs (LogOR) was calculated. Standard error was also calculated, (formula = (log 95% CI upper limit value—log 95% CI lower limit value) divided by 3.92) using Microsoft Office Excel.
Conversion of nitrate units and nitrite dosage: mg/day was the standard unit for nitrite and nitrate dosage from dietary intake used for analysis because most of the articles used these units in their analyses. The recommended daily calorie intake in the US is around 2500 kcal for men and 2000 kcal for women [48]; for this analysis, 2500 calories (also referred to as kcal) was used for the standard conversion of data. (a) mg/1000 kcal was converted to mg/day (formula = the dosage in mg/1000 kcal multiplied by 2.5 (2500 kcal = mg/day)). (b) Mcg (nanogram) was converted to mg/day; (formula = the dosage in mcg or micro/1000 kcals or microgram/1000 kcals or µg/1000 kcal/day is divided by 0.001 to be converted into mg/1000 kcals and then multiplied by 2.5. (c) Mcg/day was converted to mg/day; (formula = the dosage in mcg/day is divided by 0.001).
Meta-regression: The parameters for meta-regression calculation were the dependent variable (y) = LogOR; covariates = median (the median intake of nitrate and nitrite dosage); and within-study variability = standard error was used for analysis. Meta-regression analysis was conducted to determine the associations between nitrate and nitrite exposure and cancer risk. A meta-regression coefficient was considered statistically significant at p ≤ 0.05. A sensitivity analysis was performed whereby extreme dosages were removed, including their ORs. Any cancer site that had less than three studies was not included in the meta-regression (these included ovarian cancer and uterus corpus).
Meta-analysis: Meta-analysis was performed using two different approaches. The first approach compared the effect sizes (ORs (95% CI)) for site-specific cancer risk of the highest category of dietary nitrate and nitrite against the lowest (reference) category. were compared. The second approach pooled the effect sizes (ORs (95% CI)) for site-specific cancer risk in all intake categories and compared it against the lowest (reference) category. When I2 statistics do not present a notable heterogeneity (p  >  0.05 or I2 ≤  50%), we used a fixed-effects analysis described by Mantel-Haenszel [49]; otherwise, a random-effects analysis was conducted described by the DerSimonian and Laird method [50]. Any cancer site that had less than three studies was not included in the meta-analysis. Two types of cancers with similar sites or very close locations in the human body were merged for analysis (these included ovarian cancer and uterus corpus).

3. Results

3.1. Selection of the Studies

A total of 3348 records were identified through database searching. After screening titles and abstracts according to the inclusion and exclusion criteria, 98 records remained. The full texts of 74 articles were assessed for eligibility, upon which 31 articles were excluded. Therefore, 41 articles were eligible for meta-regression with 13 cancer sites. The process of selection of studies can be seen in Figure 1.

3.2. Results

3.2.1. Meta-Regression

Meta-regression analyses showed that the risk of both bladder (t = 1.99, p = 0.056, adjusted R2 = 33.77%) and stomach cancers (t = 4.09, p = 0.000, adjusted R2= 74.06%) were positively associated with the dosage of dietary nitrite (Figure 2b,c, but that the risk of pancreatic cancer was inversely associated (t = −2.89, p = 0.007, adjusted R2 = 33.37%) (Figure 2a. In relation to the dosage of dietary nitrate, the risk of both kidney (t = −4.02, p = 0.002, adjusted R2 = 100%) and bladder cancers (t = −2.78, p = 0.008, and R2 =58.38%) were inversely associated (Figure 2d,e). No other significant associations were observed by meta-regression analyses.

3.2.2. Meta-Analysis

When comparing highest to lowest (reference) categories of intake, meta-analysis of studies showed that high nitrate intake was associated with an increased risk of thyroid cancer (OR = 1.40, 95% CI: 1.02, 1.77) (Figure 3 and Table 1). Little heterogeneity was observed (I2 = 0.0%, p = 0.706). There was no evidence of association between the risk of cancers of the reproductive organs (ovary and uterine corpus), breast, non-Hodgkin’s lymphoma, stomach, pancreatic, esophageal, bladder, kidney, colon, or rectal cancer and dietary nitrate and nitrite (Table 1).
When pooling all intake categories and comparing against the lowest (reference) category, higher nitrite intake was associated with an increased risk of glioma (OR = 1.12, 95% CI: 1.03, 1.22) (Figure 4 and Table 1). Little heterogeneity was observed (I2 = 0.0%, p = 0.661). There was no evidence of association between the risk of cancers of the reproductive organs (ovary and uterine corpus), breast, non-Hodgkin’s lymphoma, stomach, pancreatic, esophageal, bladder, kidney, colon and rectal cancer, and dietary nitrate or nitrite consumption.
All results are shown in Table 1, and the remaining figures are shown in the Supplementary Figures S1 and S2.

3.2.3. Publication Bias

Both the Egger and Begg tests of bias indicated asymmetry (publication bias) for both cancer of the kidney (Egger, p = 0.019; Begg, p = 0.016; Figure 5b and Table 2), and stomach (Egger, p = 0.000; Begg, p = 0.006; Figure 5c and Table 2) with nitrates, and pancreatic cancer with nitrites (Egger, p = 0.000; Begg, p = 0.000; Figure 5e and Table 2). The Egger’s test showed statistical evidence of bias for colon cancer and nitrites (p = 0.027; Figure 5d and Table 2) but the Begg’s test did not (p = 0.141). The Begg’s test showed statistical evidence of bias for glioma and nitrates (p = 0.040; Figure 5a and Table 2) but the Egger’s test did not (p = 0.132). No other evidence of bias was indicated (Table 3). The remaining figures are shown in the Supplementary Figure S3.

4. Discussion

This systematic literature review and meta-analysis aimed to quantify the associations between cancer risk and dose of dietary nitrate and nitrite reported in the literature to date. Using 41 eligible articles, we conducted meta-analyses using two different approaches to compare the risk of 13 different site-specific cancers across different categories of dietary intake. Moreover, we conducted a meta-regression analysis to examine associations between site-specific cancer risk and dosage of dietary nitrates and nitrites.
Firstly, when comparing highest to lowest (reference) categories of intake, meta-analysis showed that high nitrate intake was associated with an increased risk of thyroid cancer (OR = 1.40, 95% CI: 1.02, 1.77). When pooling all intake categories and comparing against the lowest (reference) category, higher nitrite intake was associated with an increased risk of glioma (OR = 1.12, 95% CI: 1.03, 1.22).
Meta-regression analysis showed that bladder and stomach cancer risk was greater, and that pancreatic cancer risk was lower, with increasing nitrite intakes. Kidney and bladder cancer risk were both lower with increasing nitrate intakes. No other associations between cancer risk and dietary intakes of nitrates or nitrites were observed. These data suggest type- and site-specific effects on cancer risk, including protective effects, from dietary intakes of nitrate and nitrite.
These findings from a meta-analysis of the literature are an important contribution, as individual studies on their own have reported seemingly inconsistent findings. Some studies have shown positive, and others, negative associations with cancer risk at different intakes of dietary nitrate and nitrite. For example, Kilfoya et al. [51] reported an association between ovarian cancer and a daily nitrate intake of 175.4 mg/day, HR: 1.31 (95% CI: 1.01, 1.68) in a 10-year prospective cohort study of women (aged 50–71 years), with a total of 709 incident epithelial ovarian cancer cases. This same study did not show any association between ovarian cancer and total nitrate intake, yet there was a relationship between a nitrate intake of 0.33 mg/1000 kcal from animal sources HR: 1.34 (95% CI: 1.05, 1.69). In contrast, Inoue-Choi et al., [5] did not show any association with the same range of nitrate daily intake 165.48–209.2 mg/day, HR: 0.85 (95% CI: 0.56, 1.27) in a similar cohort study of women aged 55–69 years. This is a good comparison because these two studies have almost the same daily nitrate intake and the same demographic characteristics, which is sometimes difficult to find. Three studies on breast cancer did not show any associations [12,52,53]. More research is needed to study the association between nitrate and nitrite intake and breast cancer from both food and water, especially since it is the second leading cause of cancer death in 92% of women. Non-Hodgkin’s lymphoma studies showed an association between daily nitrite intake and the disease [25,56,60]. Most studies had daily intake ranges of 0–2 mg/day; one study did not report the daily intake [25]. There was no association between daily nitrate intake and this cancer. Stomach cancer was the most studied cancer among the articles retrieved for this systematic review, yet only three of these studies showed any relationship with dietary nitrite intake. This study’s meta-regression showed an association between dietary nitrite exposure and stomach cancer. Daily nitrate intake was not associated with stomach cancer in the meta-regression analysis. As for other cancers (cancer of the colon, rectum, esophagus, pancreas, kidney, thyroid, and glioma), one or two studies showed positive associations with dietary nitrate and nitrite intake.
Many studies have shown that a long period of exposure/daily dietary intake that contains nitrate, nitrite, and NOC compounds can lead to specific health issues, but these results are still contradictory. Keszei, et al. (2013) [69] conducted a cohort study with 16.3 years of follow-up in the Netherlands, from 1986 to 2002 for men and women aged 55–69 years. In this study, esophageal squamous cell carcinoma (ESCC) risk was associated with nitrite intake (HR for 0.1-mg/day increase: 1.19; 95% CI: 1.05, 1.36; p-trend = 0.06). Positive associations were observed between N-nitrosodimethylamine intake and esophageal squamous cell carcinoma (ESCC) risk (HR for 0.1 micro gram/day increase in intake: 1.15; 95% CI: 1.05, 1.25; p-trend = 0.01 based on tertiles of intake) and gastric non-cardia adenocarcinoma (GNCA) risk (1.06; 95% CI: 1.01, 1.10; p-trend = 0.09) in men. Meanwhile Cross et al., 2011, [53] conducted a cohort study with 10 years of follow-up in the USA, from 1995 to 2006 for men and women aged 50–71 years, which showed nitrate and nitrite were not associated with esophageal or gastric cancer. Some case-control studies and ecological studies have yielded inconclusive results about different types of cancers.
Individually, most of the research articles included in this systematic review did not find any association between nitrate and nitrite and any type of cancer in humans. However, when analyzed together, greater exposure to dietary nitrate and nitrite increased the risk of getting some cancers (glioma, bladder, stomach, and thyroid) and decreased the risk of getting others (pancreatic and kidney). Most of these cancers can be considered cancers of the digestive system. The risk of these types of cancers have been shown to be modified by other dietary and lifestyle factors. For example, some studies have shown an inverse association of vegetable and fruit intake with these cancers’ risk [78]. Other studies have shown that people who take in high vitamin C, high vitamin E, low red meat (or any type of meat), and folate while being exposed to nitrate or nitrite at the same time had a lower risk of having cancer, than those who did not [64,79]. However, not all studies showed these protective effects. Zeegers et al., 2006, [65] showed that vitamin C (p = 0.63) and vitamin E (p = 0.62), did not appear to be significant effect modifiers in the association between nitrate exposure from food and bladder cancer risk. Catsburg et al., (2014) [38] showed that among individuals with high nitrate intake, a positive association between high (i.e., above the median) heme intake and risk of bladder cancer was observed (highest category vs. lowest category OR = 1.76; 95% CI = 1.21–2.55; p trend = 0.007). Some studies showed no association at all [33,67,80].
Notwithstanding the null findings of some studies, it is widely accepted that it is important that people consume diets high in fresh fruits and vegetables that contain a lot of vitamins and essential minerals and reduce meat, fatty food, and processed food intake to improve their health. This may be important in modifying any harmful effects of dietary nitrates and nitrites on particularly susceptible tissues in the digestive system and elsewhere in the body. Cases of cancer are considered to be linked to nutritional factors. Scientific evidence suggests that food/diet is most convincingly linked to cancer of the lung, stomach, rectum, colon, pharynx, nasopharynx, esophagus, and mouth [81,82,83]. Filtration and purification of drinking water from both private and public sources before consumption is extremely important because several studies have shown that the consumption of nitrate and nitrite from drinking water, even in a very small amount, over a long period can lead to cancer (a chronic disease) and other health issues [31,84,85].
Most of the studies included in this systematic review were conducted in Europe and the U.S., and very few or no studies from South America, Africa, Australia, and Asia were retrieved. Many studies and awareness of early screening for different types of cancers are needed in South America, Africa, Australia, and Asia to better understand this issue on a larger scale with different demographics. A proper and comprehensive assessment of nitrate and nitrite from dietary intake, including inhibitors of endogenous nitrosation and intakes of antioxidants, are needed in future studies. Many studies lacked information about study participants’ water consumption and dietary intake that contain nitrate and nitrite simultaneously, which may be essential to better analyze the links between dietary intakes and cancers. Future studies should also pay close attention to the different duration or lengths (years) of food intake with nitrite and nitrate, especially to understand the effects of exposure. There is still no precise standard maximum contaminant level for nitrate and nitrite in food to protect people from non-communicable diseases like cancer. This might be because noncommunicable diseases, such as cancer, can take a long time to occur and the casualty has not yet been fully established.

Limitations

Using two different statistical analyses for each cancer site is the strength of this research. It can help to better understand the robustness of the associations. However, the study’s limitations are as follows; first, very few articles were available for each type of cancer, some with three or fewer studies, and so the results for this analysis should be treated with caution. More detailed, well-designed studies with accurate and precise information about study participants’ food intake and other lifestyle factors may be essential to more accurately estimate associated risk. Secondly, this research was unable to adjust for potential confounders or examine effect modification (e.g., of dietary vitamin C intake) due to lack of available data in the included studies. Some studies included vitamin C, D, and E, and folate and red/processed meat intake; however, most did not. We recommend that such research should include dietary vitamin C, D, and E, intake, as well as folate intake, polyphenols, red/processed meat, heme iron intake, and other nutrients/minerals and compounds (especially the dosage) from food and drinking water that could affect nitrosation in the body, to enable more precise estimation of risks and more sophisticated analyses.
Third, there was a wide range of nitrate and nitrite intake values from different studies, which resulted in different ranges across the analyses performed in this meta-analysis. For example, dietary nitrite ranged from 0 to 2.4 mg/day in the analysis against bladder cancer risk and from 0 to 22 mg/day in the analysis against stomach cancer risk. This variation in range in the independent variable across different analyses could be partly responsible for the variation in association with the dependent variables (the different site-specific cancer risks) observed in this study. A lack of standardized units for reporting dietary intakes of nitrates and nitrites in the literature made it necessary to convert the data to a common unit for meta-regression. Whilst this is not a major limitation, it has the potential to introduce error. Moreover, a lack of standardized units might pose a problem to efforts to implement a limit or precise standard maximum contaminant level to protect people from health risks of having a type of cancer. Lastly, many cohort and case-control studies should be done in different parts of the world to understand this topic better, especially noting other confounding factors and nutrient intake.

5. Conclusions

This study showed varied associations between site-specific cancer risks and dietary intakes of nitrate and nitrite. Glioma, bladder, and stomach cancer risks were higher, but pancreatic cancer risk was lower with higher nitrite intakes. Thyroid cancer risk was higher, but kidney and bladder cancer risks were lower with higher nitrate intakes. These data suggest type- and site-specific effects of cancer risk, including protective effects, from dietary intakes of nitrate and nitrite.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/nu14030666/s1, Table S1: Search Strategy of this study; Figure S1: Pooled ORs (95 % CI) of the highest dosage versus lowest category of dosage of nitrate and nitrite consumption from dietary intake for the following cancer type: (1) Reproductive organs, (2) Breast, (3) Thyroid, (4) Glioma, (5) Non-hodgkin, (6) Pancreatic, (7) Bladder, (8) Kidney, (9) Esophageal, (10) Stomach, (11) Colon, and (12) Rectum; Figure S2: Pooled ORs (95 % CI) of all combined higher dosages versus the lowest category of nitrate and nitrite consumption from dietary intake for each type of cancer; Figure S3: Funnel plot of nitrates and nitrites and for each type of cancer risk for publication bias.

Author Contributions

Conceptualization: K.S.A., E.E.E. and M.A.; methodology: E.E.E., K.S.A. and M.A.; formal analysis: E.E.E., K.S.A., M.A. and X.Y.; data curation: E.E.E., L.A., J.S. and W.X.; writing—original draft preparation: K.S.A., E.E.E. and M.A.; writing—review and editing; supervision and project administration: M.A., X.Y. and A.C. All authors have read and agreed to the published version of the manuscript.

Funding

This research was supported by Centre de recherche en gestion des Services de Santé, University Laval and Riphah International University (Riphah-ORIC-21-22/FPS-51).

Informed Consent Statement

Not applicable.

Data Availability Statement

All data generated or analyzed during this study are included in this published article. The data set used/analyzed are available from the corresponding author on request.

Acknowledgments

The authors would like to thank Mattheu Haren for his collaboration in reviewing and commenting on our manuscript.

Conflicts of Interest

The authors declare that they have no competing interest.

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Figure 1. Flow chart of study selection.
Figure 1. Flow chart of study selection.
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Figure 2. Meta-regression: the association between the risk of logarithm ORs and median dosage of dietary nitrite and nitrate for selected site-specific cancers; (a). Pancreatic cancer Median Nitrite dosage, (b). Bladder cancer: Median = Nitrite dosage, (c). Stomach cancer: Median = Nitrite dosage, (d). Kidney cancer: Median = Nitrate dosage, (e). Bladder cancer: Median = Nitrate dosage.
Figure 2. Meta-regression: the association between the risk of logarithm ORs and median dosage of dietary nitrite and nitrate for selected site-specific cancers; (a). Pancreatic cancer Median Nitrite dosage, (b). Bladder cancer: Median = Nitrite dosage, (c). Stomach cancer: Median = Nitrite dosage, (d). Kidney cancer: Median = Nitrate dosage, (e). Bladder cancer: Median = Nitrate dosage.
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Figure 3. ORs (95% CI) for thyroid cancer of the highest versus lowest category of dosage of dietary nitrate consumption for the following selected studies .
Figure 3. ORs (95% CI) for thyroid cancer of the highest versus lowest category of dosage of dietary nitrate consumption for the following selected studies .
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Figure 4. ORs (95% CI) for glioma of all combined higher dosages versus the lowest category of dietary nitrite consumption for the following selected studies.
Figure 4. ORs (95% CI) for glioma of all combined higher dosages versus the lowest category of dietary nitrite consumption for the following selected studies.
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Figure 5. Funnel plot of nitrates and (a) glioma, (b) kidney, and (c) stomach cancer risk; nitrites and (d) colon, (e) pancreatic and (f) bladder cancer risk for publication bias.
Figure 5. Funnel plot of nitrates and (a) glioma, (b) kidney, and (c) stomach cancer risk; nitrites and (d) colon, (e) pancreatic and (f) bladder cancer risk for publication bias.
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Table 1. Meta-analysis of pooled ORs (95% CI) of the highest versus lowest category and all combined higher versus the lowest category of dietary nitrate and nitrite consumption for selected, site-specific cancers.
Table 1. Meta-analysis of pooled ORs (95% CI) of the highest versus lowest category and all combined higher versus the lowest category of dietary nitrate and nitrite consumption for selected, site-specific cancers.
Type of CancerHighest versus the Lowest (Reference) CategoryAll Combined Highest versus the Lowest (Reference) CategoryPublication Bias
Pooled OR (95% CI)I-Squared (I2) and p-ValuePooled OR (95% CI)I-Squared (I2) and p-ValueEgger’s Test
p-Value
Begg’s Test
p-Value
(a) Ovarian and uterine corpus (nitrate)1.03, (0.84, 1.22)28.7%, p = 0.2400.97, (0.75, 1.19)80.6%, p = 0.0010.0670.090
(b) Breast (nitrate)0.91, (0.81, 1.00)0.0%, p = 0.5260.92, (0.87, 0.96)42.7%, p = 0.1750.3100.144
(c) Thyroid (nitrate)1.40, (1.02, 1.77)0.0%, p = 0.7061.27, (0.85, 1.69)62.0%, p = 0.0720.0640.325
(d) Glioma (nitrate)1.11, (0.91, 1.31)0.0%, p = 0.5461.11, (0.94, 1.29)66.9%, p = 0.0490.1320.040
(e) Glioma (nitrite)1.17, (0.98, 1.37)0.0%, p = 0.6461.12, (1.03, 1.22)0.0%, p = 0.6610.4420.060
(f) Non-Hodgkin’s Lymphoma (nitrate)0.82, (0.69, 0.94)27.1%, p = 0.1950.83, (0.75, 0.91)35.6%, p = 0.1240.1630.728
(g) Non-Hodgkin’s Lymphoma (nitrite)1.21, (0.78, 1.64)63%, p = 0.0191.11, (0.85, 1.38)71.4%, p = 0.0040.4960.702
(h) Pancreatic (nitrate)0.96, (0.84, 1.09)35.9%, p = 0.1670.95, (0.89, 1.00)48.0%, p = 0.0870.7220.399
(i) Pancreatic (nitrite)0.87, (0.76, 0.97)44.3%, p = 0.0951.04, (0.85, 1.24)76.1%, p = 0.0000.0000.000
(j) Bladder (nitrate)0.94, (0.84, 1.04)0.0%, p = 0.6150.94, (0.84, 1.03)70.7%, p = 0.0010.0890.322
(k) Bladder (nitrite)1.07, (0.94, 1.19)0.0%, p = 0.5741.05, (0.92, 1.18)79.2%, p = 0.0000.0450.338
(l) Kidney (nitrate)0.79, (0.17, 1.41)64.7%, p = 0.0590.84, (0.52, 1.16)73.1%, p = 0.0240.0190.016
(m) Kidney (nitrite)0.92, (0.62, 1.23)0.0%, p = 0.5861.10, (0.78, 1.48)76.7%, p = 0.0140.3220.245
(n) Colon (nitrate)0.99, (0.91, 1.08)40.1%, p = 0.1001.00, (0.96, 1.04)0.0%, p = 0.5930.3320.284
(o) Colon (nitrite)1.02, (0.92, 1.11)44.8%, p = 0.0931.02, (0.93, 1.11)67.2%, p = 0.0060.0270.141
(p) Rectal (nitrate)1.01, (0.88, 1.14)33.4%, p = 0.1611.10, (0.96, 1.24)68.8%, p = 0.0020.3670.930
(q) Rectal (nitrite)1.09, (0.79, 1.39)68.2%, p = 0.0081.06, (0.87, 1.26)82.3%, p = 0.0000.8410.952
(r) Esophageal (nitrate)0.75, (0.57, 0.94)46.1%, p = 0.0730.83, (0.72, 0.94)33.7%, p = 0.1590.9830.446
(s) Esophageal (nitrite)1.01, (0.78, 1.23)0.0%, p = 0.6890.93, (0.81, 1.05)0.0%, p = 0.8810.1970.714
(t) Stomach (nitrate)0.81, (0.70, 0.92)0.0%, p = 0.7760.81, (0.75, 0.87)22.0%, p = 0.2340.0000.006
(u) Stomach (nitrite)1.06, (0.92, 1.20)32.9%, p = 0.1271.04, (0.91, 1.11)54.7%, p = 0.0120.3080.382
I-squared (I2), a statistic representing the amount of total variation attributed to heterogeneity; p-value of Cochran’s Q test for heterogeneity.
Table 2. Characteristics of the included studies and reported associations between dietary nitrate (mg/day) and cancer risk.
Table 2. Characteristics of the included studies and reported associations between dietary nitrate (mg/day) and cancer risk.
First Author, Year, CountryStudy DesignCaseControl/Number of Person-YearsExposure Categories Nitrate Intake (mg/day)Reported OR/RR/HR 95 CICancer SitesAdjustmentNOS
Briseis Aschebrook-Kilfoya et al., 2012, USA [51]Cohort study, 1995–1996128
143
143
140
155
36.7
58.1
78.4
109.5
175.4
1 (Reference)
1.13 (0.89–1.44)
1.15 (0.9–1.44)
1.14 (0.89–1.46)
1.31 (1.01–1.68)
OvaryAge, race, total energy intake, family history of ovarian cancer, BMI, education, smoking status, menopausal status, parity, age at menarche, and total daily dietary vitamin C intake8
Peter J. Weyer et al., 2001, USA [52]Cohort study, 1986–199824
28
28
22
0–11.6
11.6–18
18.1–27.2
27.2–36.3
1 (Reference)
1.12 (0.65–1.94)
1.1 (0.63–1.92)
0.85 (0.47–1.55)
OvaryAge and total energy intake7
71
41
51
61
0–11.6
11.6–18
18.1–27.2
27.2–36.3
1 (Reference)
0.6 (0.41–0.88)
0.78 (0.54–1.12)
0.97 (0.68–1.39)
Uterine corpus
Maki Inoue-Choi et al., 2015, USA [12]Population-based cohort, 1986–201059
73
54
74
55
3.87–65.43
65.44–92.04
92.05–121.96
121.97–165.48
165.48–209.2
1 (Reference)
1.18 (0.83–1.68)
0.86 (0.58–1.26)
1.21 (0.84–1.74)
0.85 (0.56–1.27)
OvaryAge, BMI, family history of ovarian cancer, number of live births, age at menarche, age at menopause, age at first live birth, oral contraceptive use, estrogen use, and history of unilateral oophorectomy, and total energy intake8
Maki Inoue-Choi et al., 2012, USA [26]Prospective cohort study, 1986–2008604
541
575
601
554
3.9–65.2
65.2–91.8
91.8–121.8
121.8–165.6
165.6–209.9
1 (Reference)
0.86 (0.76–0.98)
0.9 (0.79–1.02)
0.96 (0.84–1.1)
0.86 (0.74–1.01)
BreastAge, total energy intake, BMI, WHR, education, smoking, physical activity level, alcohol intake, family history of breast cancer, education, smoking status, age at menopause, age at first live birth, estrogen use, total intake of folate, vitamin C and E intake and flavonoids, intake of cruciferae and red meat8
Nadia Espejo-Herrera et al., 2016, Spain [53]Multicase–Control Study, 2008–2013387
349
348
0–90
90–138
138–186
1 (Reference)
0.9 (0.74–1.1)
0.9 (0.73–1.1)
BreastStudy area, age, and education6
Peter J. Weyer et al., 2001, USA [52]Cohort study in Iowa, 1986–1998253
252
265
254
0–11.6
11.6–18
18.1–27.2
27.2–36.3
1 (Reference)
0.98 (0.83–1.17)
1.04 (0.87–1.24)
0.99 (0.83–1.19)
BreastAge and total energy intake7
Briseis Aschebrook-Kilfoy, et al., 2013, China [14]Cohort study, 1996–200934
56
41
33
165.8
257.8
350.6
506.8
1 (Reference)
1.81 (1.18–2.76)
1.44 (0.92–2.28)
1.32 (0.82–2.14)
ThyroidAge, total energy intake, education, and history of thyroid disease8
Mary H. Ward, et al., 2010, USA [54]Cohort study, 1986–20046
10
10
14
77,806
86,270
89,707
83,454
0–17.4
17.5–27.7
27.8–41.1
41.1–54.4
1 (Reference)
1.65 (0.59–4.61)
1.69 (0.58–4.84)
2.85 (1–8.11)
ThyroidAge, total calories, vitamin C intake, and residence location8
Briseis Aschebrook-Kilfoy et al., 2011, USA [55]Prospective cohort study, 1995–200363
67
60
74
106
29.6
49.8
70.2
100.9
166.8
1 (Reference)
1.01 (0.72–1.43)
0.87 (0.61–1.24)
1.04 (0.74–1.45)
1.41 (1.02–1.93)
ThyroidAge8
Dominique S. Michaud, et al. 2009, USA [32]3 prospective cohort studies, 1976–200567
74
60
59
75
Sub-cohort
(PY)
=815,155
833,168
811,541
822,304
818,945

69.3
94.7
127.7
180
1 (Reference)
1.06 (0.76–1.48)
0.84 (0.57–1.22)
0.95 (0.46–1.98)
1.02 (0.66–1.58)
GliomaAge and caloric intake6
*Robert Dubrow et al., 2010, USA [29]Prospective cohort study, 1995–200398
114
135
126
112
48.38
74.8
102.38
143.5
237.13
1 (Reference)
1.16 (0.89–1.52)
1.41 (1.09–1.84)
1.37 (1.05–1.79)
1.28 (0.97–1.7)
GliomaSex, age, race, energy intake, education, height, and history of cancer at baseline8
100
121
135
109
120
0.275 (nitrite plus nitrate)
0.725
1.225
1.925
3.575
1 (Reference)
1.15 (0.88–1.5)
1.24 (0.95–1.61)
0.97 (0.74–1.28)
1.04 (0.79–1.36)
Mary H. Ward et al., 2006, USA [56]Case-control study, 1998–2000156
116
111
80
98
98
98
97
0–76
76–113.9
114–169.9
170–225.9
1 (Reference)
0.75 (0.51–1.1)
0.71 (0.47–1.07)
0.54 (0.34–0.86)
Non-Hodgkin’s lymphomaAge, education, sex, study center, race, dietary vitamin C, and total energy7
Mary H. Ward, et al., 1996, USA [57]Case-control study, 1950–198735
38
20
11
82
106
86
64
0–13
13–19
19–26
26–33
1 (Reference)
1.1 (0.6–2.0)
0.8 (0.4–1.7)
0.7 (0.3–1.9)
Non-Hodgkin’s lymphomaAge, gender, family history of cancer, vitamin C, and carotenes7
Peter J. Weyer, et al., 2001, USA [52]Cohort study, 1986–199837
34
25
38
0–11.6
11.6–18
18.1–27.2
27.2–36.3
1 (Reference)
0.88 (0.55–1.4)
0.62 (0.37–1.04)
0.91 (0.56–1.46)
Non-Hodgkin’s lymphomaAge and total energy intake7
Briseis Aschebrook-Kilfoya et al., 2012, USA [58]Case-control, 1996–20080–62.8
62.8–95.9
95.9–141
141–186.1
1 (Reference)
1 (0.7–1.4)
1.1 (0.7–1.6)
1 (0.7–1.5)
Non-Hodgkin’s lymphomaCalories, age, family history, and vitamin C7
Briseis Aschebrook-Kilfoya et al., 2013, USA [59]Case-control, 1999–2002100
83
80
72
115
115
114
115
46.5
80.5
110.9
178.5
1 (Reference)
0.9 (0.6–1.3)
0.9 (0.6–1.3)
0.8 (0.5–1.3)
Non-Hodgkin’s lymphomaSex, age, body mass index, education, family history of cancer, vitamin C, and daily caloric intake6
Brian C.-H. Chiu et al., 2008, USA [60]Case-control study, 1983–198617
19
24
357
358
360
0–70
70–106
106–142
1 (Reference)
1 (0.5–1.9)
1.2 (0.6–2.4)
Non-Hodgkin’s lymphomaAge, sex, type of respondent, family history of cancer, and body mass index8
17
19
24
357
358
360
0–65
65–101
101–137
1 (Reference)
1 (0.5–1.9)
1.2 (0.6–2.4)
36
28
23
357
358
360
0–70
70–106
106–142
1 (Reference)
0.8 (0.5–1.3)
0.7 (0.4–1.2)
36
29
22
357
358
360
0–65
65–101
101–137
1 (Reference)
0.8 (0.5–1.3)
0.6 (0.3–1.1)
Briseis Aschebrook-Kilfoya et al., 2010, USA [25]Case-control study, 1995–2001274
317
352
355
Low
High
1 (Reference)
1.09 (0.86–1.39)
Non-Hodgkin’s lymphomaAge, family history of cancer, calories, vitamin C intake, vitamin E intake, and protein intake7
Arbor J.L. Quist et al., 2018, USA [61]Cohort study, 1986–201178
80
73
60
17
n = 8558
8552
8568
6849
1715
0–16.2
16.2–23.9
24–34.2
34.3–58.5
58.5–82.7
1 (Reference)
1.08 (0.78–1.48)
0.99 (0.7–1.39)
1.05 (0.72–1.52)
1.25 (0.71–2.21)
PancreasAge, smoking category, calories, and mutually adjusted for either natural log-transported nitrate or nitrite
Angela Coss, et al., 2004, USA [62]Case-control study, 1960–198726
33
39
43
298
311
311
327
0–58
58–82
83–117
117–151
1 (Reference)
1.1 (0.63–1.9)
1.2 (0.7–2)
1 (0.6–1.8)
PancreasAge, cigarette use, and caloric intake
39
33
24
26
164
157
158
160
0–63
63–90
91–126
126–161
1 (Reference)
0.99 (0.58–1.7)
0.64 (0.36–1.1)
0.53 (0.29–0.97)
Peter J. Weyer et al., 2001, USA [52]Cohort study, 1986–199819
15
16
19
0–11.6
11.6–18
18.1–27.2
27.2–36.3
1 (Reference)
0.79 (0.4–1.56)
0.86 (0.44–1.69)
1.02 (0.52–1.99)
PancreasAge and total energy intake7
*Jiali Zheng et al., 2019, USA [63]Case–control study, 2002–2009283
236
192
271
235
234
235
234
9.18–73.5
69.4–101.1
92.8–133.6
119.1–715.9
1 (Reference)
0.93 (0.72–1.2)
0.76 (0.59–0.99)
1.08 (0.84–1.39)
PancreasAge and energy intake
Briseis Aschebrook-Kilfoy et al., 2011, USA [64]Prospective cohort study, 1995–2006370
330
360
340
322
34.8
56.9
75.0
95.3
150.3
1 (Reference)
0.91 (0.78–1.06)
1.02 (0.88–1.18)
0.99 (0.85–1.16)
1.01 (0.85–1.2)
PancreasAge, race, total energy intake, smoking status, family history of cancer, family history of diabetes, body mass index, and intakes of saturated fat, folate, and vitamin C
Rena R. Jones, et al., 2016, USA [8]Cohort study, 1986–201067
68
64
59
n = 8467
8489
8, 506
8502
0–16.2
16.2–23.9
24–34.2
34.2–44.4
1 (Reference)
1 (0.72–1.41)
0.92 (0.66–1.3)
0.86 (0.6–1.22)
BladderAge and total in-transformed dietary nitrite from all sources
Maurice P. Zeegers et al., 2006, Netherlands [65]Cohort study, 1986–1995

168
186
181
180
174
Subcohort
(PY)
=8512
8652
8706
8707
8564
2–69
69–88
88–107.5
107.5–135.3
135.3–451.1
1 (Reference)
1.14 (0.89–1.45)
1 (0.78–1.27)
1.02 (0.8–1.3)
1.01 (0.79–1.29)
BladderAge and sex
Chelsea E. Catsburg et al., 2014, USA [38]Case-control study, 1987–1996467
329
293
274
284
315
314
315
315
314
0–64.3
64.4–91.4
91.5–117.3
117.4–148.3
148.4–179.3
1 (Reference)
0.79 (0.63–1.01)
0.74 (0.57–0.97)
0.78 (0.58–1.06)
0.9 (0.6–1.35)
BladderSmoking duration, smoking intensity, and smoking status8
Mary H. Ward et al., 2003, USA [35]Case-control study, 1986–1989.0–59
59–84
84–119
119–154
1 (Reference)
0.8 (0.7–1.1)
0.9 (0.7–1.2)
0.9 (0.7–1.1)
BladderAge, education, and cigarette smoking, years chlorinated surface water, and study period
0–62
62–90
90–127
127–164
1 (Reference)
1.2 (0.8–1.9)
0.9 (0.5–1.4)
0.8 (0.5–1.3)
Peter J. Weyer, et al., 2001, USA [52]Cohort study, 1986–19989
17
13
14
0–11.6
11.6–18
18.1–27.2
27.2–36.3
1 (Reference)
1.88 (0.84–4.24)
1.46 (0.62–3.47)
1.57 (0.66–3.75)
BladderAge and total energy intake7
Kathryn Hughes Barry et al., 2020, New England [66]Case–control study, 1994–1996 and 2001–2004227
230
225
183
172
247
245
243
246
244
0–21.9
21.19–28.28
28.28–36.10
36.10–47.21
>47.21
1 (Reference)
1.2 (0.88–1.5)
1.2 (0.92–1.6)
1.0 (0.75–1.4)
0.95 (0.69–1.3)
BladderAdjusted for age, gender, smoking status, high-risk occupation, race, ethnicity, state, dietary vitamin C intake (per 1000 kcal—continuous), dietary vitamin B12 (per 1000 kcal—continuous), total energy intake (kcal—continuous), and total water intake (L/d—continuous); models for nitrate/nitrite from processed meat were additionally adjusted for total meat intake (per 1000 kcal—continuous)
*Leah M. Ferrucci et al., 2010, USA [5]Cohort study, 1995–2003236
185
150
145
138
49.25
76
103.75
145
238.5
1 (Reference)
0.86 (0.71–1.06)
0.76 (0.6–0.95)
0.77 (0.6–0.99)
0.8 (0.58–1.1)
BladderAge, gender, smoking, intakes of fruit, vegetables, beverages, and total energy
109
147
173
191
234
0.05
0.175
0.275
0.425
0.725
1 (Reference)
0.97 (0.76–1.24)
1.09 (0.87–1.38)
1.07 (0.85–1.36)
1.2 (0.95–1.51)
Mary H. Ward et al., 2007, USA [27]Case-control study, 1986–1989.109
83
84
57
471
472
471
472
0–59.32
59.32–86.62
86.63–122
122–157.77
1 (Reference)
0.71 (0.52–0.98)
0.69 (0.5–0.95)
0.41 (0.28–0.6)
KidneyAge, gender, sodium, and total calories
Rena R. Jones et al., 2017, USA [67]Cohort study, 1986–2010
67
65
66
43
15
n = 8467
8489
8, 506
6803
1699
0–16.2
16.2–23.9
23.91–34.27
34.28–58.64
58.6–82.96
1 (Reference)
0.96 (0.68–1.4)
0.95 (0.67–1.4)
0.78 (0.51–1.2)
1.1 (0.59–2)
KidneyAge, smoking status, pack-years of smoking, in-transformed total energy intake, body mass index, and total in-transformed total dietary nitrate or nitrite
Peter J. Weyer et al., 2001, USA [52]Cohort study from 1986–199812
15
14
14
0–11.6
11.6–18
18.1–27.2
27.2–36.3
1 (Reference)
1.32 (0.62–2.83)
1.32 (0.6–2.89)
1.37 (0.61–3.06)
KidneyAge and total energy intake
Mary H. Ward et al., 2008, USA [68]Case-control study
from 1988–1994
14
17
28
39
99
99
99
100
0–3.8
3.8–5.7
5.7–8.3
8.3–10.9
1 (Reference)
0.7 (0.3–1.6)
1.7 (0.7–4.1)
2.2 (0.9–5.7)
EsophagusYear of birth, gender, body mass index, smoking, alcohol, total calories, vitamin A, folate, riboflavin, zinc, protein, and carbohydrate
29
27
18
24
99
99
99
100
0–16.9
16.9–26.2
26.2–38.8
38.8–51.4
1 (Reference)
0.9 (0.5–1.8)
0.6 (0.3–1.3)
0.8 (0.3–1.8)
Andra’s P. Keszei et al., 2013, The Netherlands [69]Cohort study, 1986–2002

24
21
14
Sub-cohort
(PY)
8383
9015
9050
68.1
100.8
146.2
1 (Reference)
0.82 (0.45–1.48)
0.54 (0.28–1.05)
EsophagusAge
39
36
39
8383
9015
9050
68.1
100.8
146.2
1 (Reference)
0.86 (0.54–1.37)
0.92 (0.58–1.46)
15
18
15
9607
10,175
9996
66.4
98.5
142.7
1 (Reference)
1.17 (0.58–2.35)
1.02 (0.49–2.14)
14
13
4
9607
10,175
9996
66.4
98.5
142.7
1 (Reference)
0.89 (0.42–1.92)
0.29 (0.09–0.89)
*Amanda J. Cross, et al., 2011, USA [24]Cohort study, 1995–200622
25
15
25
41
0.605
0.1673
0.2818
0.4363
0.745
1 (Reference)
1.06 (0.59–1.91)
0.6 (0.3–1.18)
0.9 (0.49–1.67)
1.3 (0.72–2.35)
EsophagusAge, sex, BMI, education, ethnicity, tobacco smoking, alcohol drinking, usual physical activity at work, vigorous physical activity, daily intake of fruit, vegetables, saturated fat, and calories
47
61
68
89
112
0.605
0.1673
0.2818
0.4363
0.745
1 (Reference)
0.97 (0.66–1.43)
0.91 (0.62–1.35)
1.01 (0.7–1.47)
1.1 (0.75–1.6)
A. J. M. van Loon et al., 1998, The Netherlands [70]Cohort study, 1986–199269
61
45
49
58
Sub-cohort
(PY)
3784
3813
3814
3813
3796
55.8
79.4
98.7
120.7
172.2
1 (Reference)
0.93 (0.64–1.33)
0.65 (0.44–0.96)
0.71 (0.48–1.04)
0.83 (0.58–1.2)
StomachAge and sex
Raúl U. Hernández-Ramírez et al., 2009, Mexico [71]Case-control study, 2004–20050–90.4
90.4–141.7
141.7–193
1 (Reference)
0.93 (0.62–1.39)
0.61 (0.39–0.96)
StomachEnergy, age, gender, H. pylori CagA status, schooling, and consumptions of salt, chili, and alcohol.
Andra´s P. Keszei et al., 2013, The Netherlands [69]Cohort study, 1986–200249
47
43
Sub-cohort
(PY)
8383
9015
9050
68.1
100.8
146.2
1 (Reference)
0.89 (0.59–1.35)
0.81 (0.53–1.24)
StomachAge
111
125
93
8383
9015
9050
68.1
100.8
146.2
1 (Reference)
1.05 (0.79–1.39)
0.77 (0.57–1.04)
7
7
10
9607
10,175
9996
66.4
98.5
142.7
1 (Reference)
0.97 (0.34–2.81)
1.46 (0.54–3.93)
59
46
55
9607
10,175
9996
66.4
98.5
142.7
1 (Reference)
0.76 (0.51–1.13)
0.95 (0.64–1.4)
Carlo La Vecchia, et al., 1994, Italy [72]Case-control study, 1985–199262.95
80.7
96.33
116.88
1 (Reference)
0.71 (0.53–0.96)
0.66 (0.47–0.92)
0.78 (0.54–1.12)
StomachAge, sex, education, family history of gastric cancer, body mass index, total energy intake, plus all above variables5
* Amanda J. Cross et al., 2011, USA [24]Cohort study, 1995–200650
48
50
56
73
0.605
0.1673
0.2818
0.4363
0.745
1 (Reference)
0.9 (0.6–1.35)
0.89 (0.59–1.33)
0.91 (0.61–1.37)
1.04 (0.69–1.55)
StomachAge, sex, BMI, education, ethnicity, tobacco smoking, alcohol drinking, usual physical activity at work, vigorous physical activity, daily intake of fruit, vegetables, saturated fat, and calories.
39
57
36
61
62
0.605
0.1673
0.2818
0.4363
0.745
1 (Reference)
1.17 (0.77–1.77)
0.64 (0.4–1.02)
0.94 (0.61–1.45)
0.81 (0.52–1.25)
Mary H. Ward, et al., 2008, USA [68]Case-control study
from 1988–1994
19
31
25
29
99
99
99
100
0–3.8 (nitrite plus nitrate)
3.8–5.7
5.7–8.3
8.3–10.9
1 (Reference)
1.6 (0.8–3.2)
1.8 (0.8–3.8)
1.6 (0.7–3.7)
Stomach
Year of birth, gender, education, smoking, alcohol, total calories, vitamin C, fiber, and carbohydrate.
24
28
26
26
99
99
99
100
0–16.9
16.9–26.2
26.2–38.8
38.8–51.4
1 (Reference)
1.2 (0.6–2.5)
1.4 (0.7–2.9)
1.6 (0.7–3.6)
Curt T. Della Valle et al., 2014, China [44]Prospective cohort study, 1996 to 200783
70
65
87
78
98.7
144.1
182.4
229
313.2
1 (Reference)
0.9 (0.65–1.25)
0.84 (0.59–1.2)
1.13 (0.77–1.66)
0.98 (0.59–1.63)
ColonAge, energy intake, education, physical activity, dietary vitamin C intake, carotene, and folate
Nadia Espejo-Herrera et al., 2016, Spain [53]Case-control study, 2008–2013388
394
371
0–83
83–133
133–183
1 (Reference)
1.04 (0.87–1.24)
0.9 (0.74–1.1)
ColonSex, age, education, physical activity, non-steroidal anti-inflammatory drugs use, family history of colorectal cancer, body mass index, and intake energy
Rena R. Jones et al., 2019, USA [41]Cohort study, 1986–2010324
324
321
355
n = 8676
8674
8685
8673
0–9.8
9.81–13.8
13.81–19.29
19.29–24.77
1 (Reference)
0.98 (0.84–1.15)
0.97 (0.83–1.13)
1.11 (0.94–1.3)
ColonAge, heme iron, red meat, and total dietary nitrate or nitrite
Peter J. Weyer et al., 2001, USA [52]Cohort study, 1986–199898
78
90
97
0–11.6
11.6–18
18.1–27.2
27.2–36.3
1 (Reference)
0.79 (0.59–1.07)
0.93 (0.69–1.24)
1 (0.74–1.34)
ColonAge and total energy intake7
* Amanda J. Cross et al., 2010, USA [29]Prospective cohort study, 1994–2003341
344
386
439
485
0.0598
0.1633
0.274
0.423
0.723
1 (Reference)
0.93 (0.8–1.08)
0.99 (0.86–1.16)
1.08 (0.93–1.25)
1.13 (0.97–1.32)
ColonGender, education, BMI, smoking, and intake of total energy, fiber, and dietary calcium
* L. M. Ferrucci et al., 2012, USA [73]Multi-center, randomized controlled trial, 1993–2001.150
165
203
254
0.15 (nitrite plus nitrate)
0.425
0.9
2.1
1 (Reference)
0.98 (0.77–1.23)
1.07 (0.84–1.35)
1.16 (0.9–1.5)
ColonAge, study center, gender, ethnicity, education, family history of colorectal cancer, BMI, NSAIDs use, physical activity, smoking status, alcohol intake, dietary calcium, supplemental calcium, dietary fibre, and total energy intake
Anneclaire J. De Roos et al., 2003, USA [28]Case-control study, 1986–1990(n(%))
89 (32)
68 (24)
68 (24)
55 (20)
(n(%))
261 (27)
241 (25)
246 (25)
234 (24)
0–59.3
59.3–86.5
86.6–121.9
122–157
1 (Reference)
0.8 (0.6–1.2)
0.8 (0.5–1.1)
0.7 (0.4–1)
ColonAge, sex, and chlorinated surface water
Yun Zhu et al. 2014 [74]Case-control study, 1997–2006127
153
122
137
122
517
480
489
479
516
56.94
91.45
124.81
169.59
264.14
1 (Reference)
1.25 (0.93–1.66)
0.9 (0.66–1.23)
1.06 (0.78–1.48)
0.75 (0.54–1.05)
ColonAge, sex, energy intake, BMI, cigarette smoking status, education attainment, reported colon screening procedures, NSAID use, multivitamin supplement use, folate supplement use, vegetable intake, and province of residence
109
113
128
122
114
517
480
489
479
516
56.94
91.45
124.81
169.59
264.14
1 (Reference)
1.07 (0.78–1.48)
1.24 (0.9–1.71)
1.31 (0.94–1.83)
1.01 (0.71–1.45)
Curt T. Della Valle et al., 2014, China [44]Prospective cohort study, 1996–200746
39
41
51
59
98.7
144.1
182.4
229
313.2
1 (Reference)
0.9 (0.58–1.4)
0.95 (0.6–1.5)
1.17 (0.72–1.9)
1.26 (0.69–2.32)
RectumAge, energy intake, education, physical activity, dietary vitamin C intake, carotene, and folate
Nadia Espejo-Herrera et al., 2016, Spain [53]Case-control study, 2008–2013.195
161
151
0–83
83–133
133–183
1 (Reference)
0.85 (0.66–1.08)
0.76 (0.58–1)
RectumSex, age, education, physical activity, non-steroidal anti-inflammatory drugs use, family history of colorectal cancer, body mass index, and intake energy
Rena R. Jones et al., 2019, USA [41]Cohort study, 1986–201079
81
71
94
n = 8676
8674
8685
8673
0–9.8
9.81–13.8
13.81–19.29
19.29–24.77
1 (Reference)
1.03 (0.76–1.41)
0.91 (0.66–1.26)
1.27 (0.93–1.74)
RectumAge and total dietary nitrate or nitrite
Peter J. Weyer et al., 2001, USA [52]Cohort study, 1986–1998.28
39
27
28
0–11.6
11.6–18
18.1–27.2
27.2–36.3
1 (Reference)
1.42 (0.87–2.31)
1.01 (0.59–1.73)
1.06 (0.61–1.83)
RectumAge and total energy intake7
* Amanda J. Cross et al., 2010, USA [29]Prospective cohort study, 1994–2003110
126
144
170
174
0.0598
0.1633
0.274
0.423
0.723
1 (Reference)
1.08 (0.83–1.4)
1.18 (0.91–1.52)
1.31 (1.01–1.68)
1.26 (0.97–1.63)
RectumGender, education, BMI, smoking, and intake of total energy, fiber, and dietary calcium.
* L. M. Ferrucci et al., 2012, USA [73]Multi-center, randomized controlled trial, 1993–200144
64
75
80
0.15 (nitrite plus nitrate)
0.425
0.9
2.1
1 (Reference)
1.31 (0.88–1.95)
1.38 (0.92–2.07)
1.27 (0.8–1.99)
RectumAge, study center, gender, ethnicity, education, family history of colorectal cancer, BMI, NSAIDs use, physical activity, smoking status, alcohol intake, dietary calcium, supplemental calcium, dietary fiber, and total energy intake
Anneclaire J. De Roos et al., 2003, USA [28]Case-Control study, 1986–1990(n(%))
56 (22)
67 (27)
66 (27)
60 (24)
(n(%))
261 (27)
241 (25)
246 (25)
234 (24)
0–59.3
59.3–86.5
86.6–121.9
122–157
1 (Reference)
1.3 (0.9–1.9)
1.2 (0.8–1.8)
1.1 (0.8–1.7)
RectumAge, sex, and chlorinated surface water
Yun Zhu, et al. 2014 [74]Case-control study, 1997–2006118
126
130
133
118
517
480
489
479
516
56.94
91.45
124.81
169.59
264.14
1 (Reference)
1.12 (0.83–1.53)
1.23 (0.9–1.69)
1.34 (0.94–1.85)
1.03 (0.73–1.46)
RectumAge, sex, energy intake, BMI, cigarette smoking status, education attainment, reported colon screening procedures, NSAID use, multivitamin supplements use, folate supplement use, vegetable intakes and province of residence.
* Original exposure categories of nitrates from studies converted to mg/day for meta-regression calculation (explained under statistics analysis); ⁕ missing cases/controls/person-years in sub-cohort from the studies; ⁑ missing nitrate dosage.
Table 3. Characteristics of the included studies and reported associations between dietary nitrite (mg/day) and cancer risk.
Table 3. Characteristics of the included studies and reported associations between dietary nitrite (mg/day) and cancer risk.
First Author, Year, CountryStudy DesignCaseControlExposure Categories
Nitrite intake mg/day)
Reported OR/RR/HR 95 CICancer sitesAdjustmentNOS
* Robert Dubrow et al., 2010, USA [29]Prospective cohort study, 1995–2003100
121
135
109
120
0.275 (nitrite plus nitrate)
0.725
1.225
1.925
3.575
1 (Reference)
1.15 (0.88–1.5)
1.24 (0.95–1.61)
0.97 (0.74–1.28)
1.04 (0.79–1.36)
GliomaSex, age, race, energy intake, education, height, and history of cancer at baseline8
101
129
106
118
131
1.13
1.43
1.63
1.85
2.25
1 (Reference)
1.25 (0.96–1.63)
1.03 (0.79–1.36)
1.16 (0.89–1.52)
1.32 (1.01–1.71)
Mary H. Ward et al., 2005, USA [75]Case-control study, 1983–199438
27
23
33
67
74
71
73
0–0.7
0.7–0.94
0.94–1.19
1.19–1.44
1 (Reference)
0.8 (0.4–1.7)
1.0 (0.4–2.3)
1.2 (0.5–3.2)
GliomaAge, gender, respondent type, education, ever live/work on a farm, education, beta-carotene, fiber, and calories6
Dominique S Michaud et al., 2009, USA [32]3 prospective cohort studies, 1976–200555
65
71
69
75
Sub-cohort
(PY)
=812,763
812,974
844,064
810,417
820,895

1.4
1.6
1.8
2.03
1 (Reference)
1.11 (0.72–1.71)
1.2 (0.84–1.71)
1.14 (0.73–1.78)
1.26 (0.89–1.79)
GliomaSex, age, race, energy intake, education, height, and history of cancer at baseline8
Mary H. Ward et al., 2006, USA [56]Case-control study, 1998- 200082
108
110
166
98
98
98
97
0–0.71
0.71–0.909
0.91–1.209
1.21–1.509
1 (Reference)
1.5 (1–2.3)
1.7 (1.1–2.7)
3.1 (1.7–5.5)
Non-Hodgkin’s lymphomaAge, education, sex, study center, race, dietary vitamin C, and total energy
Briseis Aschebrook-Kilfoya et al., 2012, USA [58]Case-control study, 1996–20080–0.8
0.8–1.1
1.1–1.4
1.4–1.7
1 (Reference)
1.2(0.8–1.6)
0.8 (0.6–1.3)
1 (0.6–1.6)
Non-Hodgkin’s lymphomaCalories, age, family history, and vitamin C
Briseis Aschebrook-Kilfoya et al., 2013, USA [14]Case-control study, 1999–200282
90
68
95
114
115
116
114
0.9
1.2
1.5
1.7
1 (Reference)
1.2 (0.8–1.8)
0.8 (0.5–1.3)
1.3 (0.8–1.9)
Non-Hodgkin’s lymphomaSex, age, body mass index, education, family history of cancer, vitamin C, and daily caloric intake
Brian C.-H. Chiu et al., 2008, USA [60]Case-control study, 1983–198614
15
31
357
358
360
0–1
1–1
1–2
1 (Reference)
1.1 (0.5–2.4)
2.8 (1.3–6.1)
Non-Hodgkin’s lymphomaAge, sex, type of respondent, family history of cancer, and body mass index8
39
25
23
357
358
360
0–1
1–1
1–2
1 (Reference)
0.7 (0.4–1.1)
0.6 (0.3–1.2)
Briseis Aschebrook-Kilfoya et al., 2010, USA [25]Case-control study, 1995–2001248
345
349
355
Low
High
1 (Reference)
1.37 (1.04–1.79)
Non-Hodgkin’s lymphomaAge, family history of cancer, calories, vitamin C intake, vitamin E intake, and protein intake
Arbor J.L. Quist et al., 2018, USA [61]Cohort study, 1986–201188
67
70
68
15
n = 8501
8505
8753
6761
1722
0–0.86
0.86–1.11
1.12–1.43
1.44–2.05
2.05–2.66
1 (Reference)
0.85 (0.59–1.22)
0.94 (0.62–1.42)
1.3 (0.79–2.14)
1.28 (0.59–2.79)
PancreasAge, smoking category, calories, and mutually adjusted for either natural log-transported nitrate or nitrite
Angela Coss et al., 2004, USA [62]Case-control study, 1960–198715
22
40
64
233
307
333
374
0–0.75
0.75–0.98
0.99–1.3
1.3–1.61
1 (Reference)
1 (0.52–2)
1.5 (0.81–2.9)
1.5 (0.79–3)
PancreasAge, cigarette use, and caloric intake
9
22
60
50
264
282
359
342
0–0.22
0.22–0.31
0.32–0.53
0.53–0.74
1 (Reference)
2.1 (0.95–4.8)
3.8 (1.8–8)
2.3 (1.1–5.1)
18
32
32
40
144
146
168
181
0–0.56
0.56–0.71
0.72–0.93
0.93–1.13
1 (Reference)
1.8 (0.94–3.4)
1.4 (0.72–2.6)
1.3 (0.65–2.5)
13
32
26
51
148
164
147
180
0–0.13
0.13–0.18
0.19–0.26
0.26–0.33
1 (Reference)
2.4 (1.2–4.7)
1.9 (0.94–4)
3.2 (1.6–6.4)
* Jiali Zheng et al., 2019, USA [63]Case–control study, 2002–2009291
226
225
215
235
234
235
234
0.025–1.475
1.375–2.1
2.075–2.925
2.9–9.65
1 (Reference)
0.8 (0.62–1.03)
0.77 (0.6–1)
0.75 (0.59–0.91)
PancreasAge and energy intake
Briseis Aschebrook-Kilfoy et al., 2011, USA [64]Prospective cohort study, 1995- 2006361
361
331
348
321
0.8
1.0
1.2
1.2
1.6
1(Reference)
0.99 (0.86–1.16)
0.92 (0.79–1.08)
0.97 (0.83–1.14)
0.92 (0.78–1.08)
PancreasAge, race, total energy intake, smoking status, family history of cancer, family history of diabetes, body mass index, and intakes of saturated fat, folate, and vitamin C
Rena R. Jones et al., 2016, USA [8]Cohort study, 1986–201063
66
73
56
n = 8450
8514
8487
8513
0–0.86
0.86–1.12
1.13–1.43
1.44–1.74
1 (Reference)
1.15 (0.78–1.7)
1.38 (0.89–2.16)
1.15 (0.65–2.03)
BladderAge, smoking status, pack-years of smoking, in-transformed total energy intake, and total in-transformed dietary nitrate from all sources
Kathryn Hughes Barry et al., 2020, New England [76]Case–control study, 1994–1996, 2001–2004222
212
202
217
184
243
245
244
248
245
0–0.48
0.48–0.56
0.56–0.63
0.63–0.72
>0.72
1 (Reference)
1.0 (0.77–1.4)
1.0 (0.74–1.3)
1.1 (0.80–1.4)
0.97 (0.71–1.3)
BladderAdjusted for age, gender, smoking status, high-risk occupation, race, ethnicity, state, dietary vitamin C intake (per 1000 kcal—continuous), dietary vitamin B12 (per 1000 kcal—continuous), total energy intake (kcal—continuous), and total water intake (L/d—continuous); models for nitrate/nitrite from processed meat were additionally adjusted for total meat intake (per 1000 kcal—continuous)
Mary H. Ward et al., 2003, USA [35]Case-control study, 1986–19890–0.81
0.81–1.06
1.06–1.39
1.39–1.72
1 (Reference)
1.1 (0.9–1.4)
1.2 (0.9–1.5)
1.2 (0.9–1.6)
BladderAge, education, and cigarette smoking, years chlorinated surface water, and study period
0–0.58
0.58–0.75
0.75–0.98
0.98–1.21
1 (Reference)
1 (0.6–1.5)
0.8 (0.5–1.3)
1 (0.7–1.6)
* Leah M. Ferrucci et al., 2010, USA [5]Cohort study, 1995– 2003176
181
164
161
172
1.15
1.425
1.625
1.85
2.275
1 (Reference)
1.17 (0.9–1.45)
1.1 (0.89–1.37)
1.14 (0.91–1.44)
1.28 (1.02–1.61)
BladderAge, gender, smoking, intakes of fruit, vegetables, beverages, and total energy
109
147
173
191
234
0.025
0.075
0.15
0.25
0.475
1 (Reference)
1.15 (0.9–1.46)
1.08 (0.85–1.37)
1.39 (1.11–1.74)
1.07 (0.85–1.36)
* Chelsea E. Catsburg et al., 2014, USA [38]Case-control study, 1987– 1996400
287
302
314
344
314
316
313
315
315
0–0.234
0.235–0.311
0.312–0.4
0.401–0.532
0.532–0.664
1 (Reference)
0.75 (0.59–0.94)
0.81 (0.63–1.03)
0.82 (0.64–1.07)
0.89 (0.66–1.2)
BladderSmoking duration, smoking intensity, and smoking status8
Mary H. Ward et al., 2007, USA [27]Case-control study, 1986–198992
74
78
89
471
472
471
472
0–0.7
0.7–0.93
0.94–1.25
1.26–1.57
1 (Reference)
0.82 (0.58–1.17)
0.84 (0.57–1.22)
0.82 (0.5–1.33)
KidneyAge, gender, sodium, total fat, and total calories
64
90
88
91
471
472
471
472
0–0.18
0.18–0.28
0.29–0.47
0.48–0.66
1 (Reference)
1.37 (0.95–1.95)
1.24 (0.85–1.83)
1 (0.63–1.59)
Rena R. Jones et al., 2017, USA [67]Cohort study, 1986–201057
68
69
49
13
n = 8450
8514
8487
1704
6809
0–0.86
0.86–1.12
1.13–1.43
1.44–2.06
2.06–2.68
1 (Reference)
1.3 (0.87–1.9)
1.4 (0.89–2.3)
1.4 (0.77–2.5)
1.6 (0.7–3.8)
KidneyAge, smoking status, pack-years of smoking, in-transformed total energy intake, body mass index, and total in-transformed total dietary nitrate or nitrite
Mary H. Ward et al., 2008, USA [68]Case-control study,
1988–1994
23
28
17
30
94
102
101
100
0–0.36
0.36–0.52
0.52–0.67
0.67–0.82
1 (Reference)
1.1 (0.5–2.3)
0.6 (0.2–1.3)
1 (0.4–2.4)
EsophagusYear of birth, gender, body mass index, smoking, alcohol, total calories, vitamin A, folate, riboflavin, zinc, protein, and carbohydrate
19
31
25
29
99
99
99
100
0–3.8 (nitrite plus nitrate)
3.8–5.7
5.7–8.3
8.3–10.9
1 (Reference)
0.7 (0.3–1.6)
1.7 (0.7–4.1)
2.2 (0.9–5.7)
Andra´s P Keszei et al., 2013, The Netherlands [69]Cohort study, 1986–200217
19
23
Sub-cohort
(PY)
8665
8895
8890
0.03
0.12
0.28
1 (Reference)
1.18 (0.61–2.3)
1.49 (0.78–2.87)
EsophagusAge
42
38
34
8665
8895
8890
0.03
0.12
0.28
1(Reference)
0.9 (0.57–1.43)
0.81 (0.5–1.31)
16
18
14
10,009
10,016
9752
0.02
0.08
0.2
1 (Reference)
1.17 (0.59–2.32)
0.96 (0.46–2)
12
12
7
10,009
10,016
9752
0.02
0.08
0.2
1 (Reference)
1.05 (0.47–2.36)
0.64 (0.25–1.64)
* Amanda J. Cross et al., 2011, USA [24]Cohort study, 1995–200620
30
19
28
31
0.0303
0.0865
0.1535
0.2573
0.498
1 (Reference)
1.36 (0.76–2.43)
0.82 (0.43–1.57)
1.15 (0.63–2.11)
1.21 (0.67–2.2)
EsophagusAge, sex, BMI, education, ethnicity, tobacco smoking, alcohol drinking, usual physical activity at work, vigorous physical activity, daily intake of fruit, vegetables, saturated fat, and calories
50
60
66
81
120
0.0303
0.0865
0.1535
0.2573
0.498
1 (Reference)
0.89 (0.61–1.3)
0.82 (0.56–1.2)
0.88 (0.61–1.27)
1.19 (0.84–1.68)
Lawrence S. Engel et al., 2003, USA [77]Case–control study, 1993–19951.8–5.55
5.65–7.2
7.3–9.5
9.6–35.2
1 (Reference)
1.5 (1–2.4)
1.8 (1.1–3)
2.5(1.4–4.3)
StomachGeographic center, age, sex, race, income, respondent type, energy intake, and the other factors included in the table
A. J. M. van Loon et al., 1998, The Netherlands [70]Cohort study, 1986–199247
51
58
46
80
Sub-cohort
(PY)
3873
3706
3829
3844
3760
0.01
0.04
0.09
0.16
0.35
1 (Reference)
1.15 (0.76–1.74)
1.21 (0.81–1.83)
0.87 (0.57–1.33)
1.49 (1.01–2.2)
StomachAge and sex
Raúl U. Hernández-Ramírez et al., 2009, Mexico [71]Case–control study, 2004–20050–1
1–1.2
1.2–1.4
1 (Reference)
1.07 (0.69–1.65)
1.52 (0.99–2.34)
StomachEnergy, age, gender, H. pylori CagA status, schooling, and consumptions of salt, chili, and alcohol
Andra´s P Keszei et al., 2013, The Netherlands [69]Cohort study, 1986–200247
39
53
Sub-cohort
(PY)
8665
8895
8890
0.03
0.12
0.28
1 (Reference)
0.83 (0.53–1.29)
1.14 (0.75–1.72)
StomachAge
98
109
122
8665
8895
8890
0.03
0.12
0.28
1 (Reference)
1.17 (0.87–1.58)
1.36 (1.01–1.82)
9
9
6
10,009
10,016
9752
0.02
0.08
0.2
1 (Reference)
1.05 (0.41–2.67)
0.73 (0.26–2.07)
56
50
54
10,009
10,016
9752
0.02
0.08
0.2
1 (Reference)
0.94 (0.63–1.39)
1.06 (0.71–1.57)
Carlo La Vecchia et al., 1994, Italy [72]Case-control study, 1985–19921.91
2.41
2.94
3.64
1 (Reference)
0.96 (0.69–1.32)
0.97 (0.7–1.35)
1.02 (0.73–1.43)
StomachAge, sex, education, family history of gastric cancer, body mass index, total energy intake, plus all the above variables5
* Amanda J. Cross et al., 2011, USA [24]Cohort study, 1995–200644
40
55
61
55
0.0303
0.0865
0.1535
0.2573
0.498
1 (Reference)
0.72 (0.47–1.11)
0.88 (0.58–1.32)
0.87 (0.58–1.31)
0.71 (0.47–1.08)
StomachAge, sex, BMI, education, ethnicity, tobacco smoking, alcohol drinking, usual physical activity at work, vigorous physical activity, daily intake of fruits, vegetables, saturated fat, and calories
54
44
48
67
64
0.0303
0.0865
0.1535
0.2573
0.498
1 (Reference)
0.77 (0.51–1.15)
0.79 (0.53–1.18)
1.04 (0.71–1.52)
0.93 (0.63–1.37)
Mary H. Ward, et al., 2008, USA [68]Case-control study,
1988–1994
23
22
29
30
94
102
101
100
0–0.36
0.36–0.52
0.52–0.67
0.67–0.83
1 (Reference)
1.1 (0.4–2.7)
0.8 (0.3–2.2)
1.1 (0.3–3.4)
StomachYear of birth, gender, education, smoking, alcohol, total calories, vitamin C, fiber, and carbohydrate
19
31
25
29
99
99
99
100
0–3.8
3.8–5.7
5.7–8.3
8.3–10.9
1 (Reference)
1.6 (0.8–3.2)
1.8 (0.8–3.8)
1.6 (0.7–3.7)
Curt T. DellaValle et al., 2014, China [44]Prospective cohort study, 1996–200772
81
75
80
75
0.56
0.74
0.87
1.01
1.23
1 (Reference)
1.27 (0.92–1.76)
1.23 (0.88–1.73)
1.34 (0.94–1.9)
1.26 (0.85–1.86)
ColonAge, energy intake, education, physical activity, dietary vitamin C intake, carotene, and folate
Rena R. Jones et al., 2019, USA [41]Cohort study, 1986– 2010345
342
320
317
n = 8588
8655
8974
8491
0–0.57
0.58–0.65
0.66–0.74
0.74–0.82
1 (Reference)
0.93 (0.8–1.08)
0.83 (0.71–0.97)
0.87 (0.74–1.02)
ColonAge, heme iron, red meat, and total dietary nitrate or nitrite
* Amanda J. Cross et al., 2010, USA [29]Prospective cohort study, 1994–2003344
359
397
441
454
0.0298
0.0843
0.1493
0.2498
0.4853
1 (Reference)
0.96 (0.83–1.12)
1.01 (0.88–1.18)
1.09 (0.94–1.26)
1.09 (0.94–1.26)
ColonGender, education, BMI, smoking, and intake of total energy, fiber, and dietary calcium
* L. M. Ferrucci et al., 2012, USA [73]Multi-center, randomized controlled trial 1993–2001150
165
203
254
0.15 (nitrite plus nitrate)
0.425
0.9
2.1
1 (Reference)
0.98 (0.77–1.23)
1.07 (0.84–1.35)
1.16 (0.9–1.5)
ColonAge, study center, gender, ethnicity, education, family history of colorectal cancer, BMI, NSAIDs use, physical activity, smoking status, alcohol intake, dietary calcium, supplemental calcium, dietary fiber, and total energy intake
Anneclaire J. De Roos et al., 2003, USA [28]Case-Control study, 1986–1990(n(%))
90 (32)
73 (26)
48 (17)
69 (25)
(n(%))
311 (32)
251 (26)
220 (22)
200 (20)
0–0.704
0.705–0.93
0.94–1.25
1.26–1.57
1 (Reference)
1.1 (0.8–1.6)
0.9 (0.6–1.3)
1.5 (1–2.1)
ColonAge, sex, and chlorinated surface water
Yun Zhu et al. 2014 [74]Case-control study, 1997–2006131
145
126
120
139
536
496
520
474
455
0.65
0.89
1.12
1.4
1.92
1 (Reference)
1.15 (0.86–1.54)
0.91 (0.66–1.26)
0.81 (0.56–1.18)
0.95 (0.63–1.43)
ColonAge, sex, energy intake, BMI, cigarette smoking status, education attainment, reported colon screening procedures, NSAID use, multivitamin supplements use, folate supplement use, vegetable intakes, and province of residence
107
112
101
132
134
536
496
520
474
455
0.65
0.89
1.12
1.4
1.92
1 (Reference)
0.97 (0.7–1.34)
0.93 (0.65–1.32)
1.21 (0.82–1.78)
1.32 (0.85–2.04)
Curt T. Della Valle et al., 2014, China [44]Prospective cohort study, 1996–200757
45
48
42
44
0.56
0.74
0.87
1.01
1.23
1 (Reference)
0.87 (0.58–1.29)
0.94 (0.63–1.42)
0.81 (0.52–1.25)
0.8 (0.49–1.29)
RectumAge, energy intake, education, physical activity, dietary vitamin C intake, carotene, and folate
Rena R. Jones et al., 2019, USA [41]Cohort study, 1986– 201093
74
91
67
n = 8588
8655
8974
8491
0–0.57
0.58–0.65
0.66–0.74
0.74–0.82
1 (Reference)
0.75 (0.55–1.02)
0.88 (0.65–1.18)
0.68 (0.49–0.94)
RectumAge and total dietary nitrate or nitrite
* Amanda J. Cross et al., 2010, USA [29]Prospective cohort study, 1994–2003113
129
157
162
163
0.0298
0.0843
0.1493
0.2498
0.4853
1 (Reference)
1.07 (0.83–1.38)
1.23 (0.96–1.58)
1.21 (0.94–1.55)
1.16 (0.9–1.5)
RectumGender, education, BMI, smoking, and intake of total energy, fiber, and dietary calcium
* L. M. Ferrucci et al., 2012, USA [73]Multi-center, randomized controlled trial 1993–200144
64
75
80
0.15 (nitrite plus nitrate)
0.425
0.9
2.1
1 (Reference)
1.31 (0.88–1.95)
1.38 (0.92–2.07)
1.27 (0.8–1.99)
RectumAge, study center, gender, ethnicity, education, family history of colorectal cancer, BMI, NSAIDs use, physical activity, smoking status, alcohol intake, dietary calcium, supplemental calcium, dietary fiber, and total energy intake
Anneclaire J. De Roos et al., 2003, USA [28]Case-control study, 1986–1990(n(%))
74 (30)
62 (25)
43 (17)
70 (28)
(n(%))
311 (32)
251 (26)
220 (22)
200 (20)
0–0.705
0.705–0.93
0.94–1.25
1.26–1.57
1 (Reference)
1.1 (0.7–1.6)
0.9 (0.6–1.4)
1.7 (1.1–2.5)
RectumAge, sex, and chlorinated surface water
Yun Zhu et al. 2014 [74]Case-control study, 1997–200695
120
124
145
141
536
496
520
474
455
0.65
0.89
1.12
1.4
1.92
1 (Reference)
1.26 (0.91–1.73)
1.2 (0.84–1.71)
1.51 (1.02–2.22)
1.45 (0.94–2.24)
RectumAge, sex, energy intake, BMI, cigarette smoking status, education attainment, reported colon screening procedures, NSAID use, multivitamin supplements use, folate supplement use, vegetable intakes, and province of residence
* Original exposure categories of nitrite from studies converted to mg/day for meta-regression calculation (explained under statistics analysis); ⁕ missing cases/controls/person-years in sub-cohort from the studies; ⁑ missing nitrite dosage.
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Said Abasse, K.; Essien, E.E.; Abbas, M.; Yu, X.; Xie, W.; Sun, J.; Akter, L.; Cote, A. Association between Dietary Nitrate, Nitrite Intake, and Site-Specific Cancer Risk: A Systematic Review and Meta-Analysis. Nutrients 2022, 14, 666. https://doi.org/10.3390/nu14030666

AMA Style

Said Abasse K, Essien EE, Abbas M, Yu X, Xie W, Sun J, Akter L, Cote A. Association between Dietary Nitrate, Nitrite Intake, and Site-Specific Cancer Risk: A Systematic Review and Meta-Analysis. Nutrients. 2022; 14(3):666. https://doi.org/10.3390/nu14030666

Chicago/Turabian Style

Said Abasse, Kassim, Eno E. Essien, Muhammad Abbas, Xiaojin Yu, Weihua Xie, Jinfang Sun, Laboni Akter, and Andre Cote. 2022. "Association between Dietary Nitrate, Nitrite Intake, and Site-Specific Cancer Risk: A Systematic Review and Meta-Analysis" Nutrients 14, no. 3: 666. https://doi.org/10.3390/nu14030666

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