A Higher Dietary Inflammatory Index Score is Associated with a Higher Risk of Incidence and Mortality of Cancer: A Comprehensive Systematic Review and Meta-Analysis.

To evaluate the maximum level of sensitivity, we simultaneously searched main international electronic data sources; PubMed and NLM Gateway (for MEDLINE), Institute of Scientific Information (ISI), and SCOPUS for studies until January, 2017. Further, a hand-search of all references included in the identified articles. We did not limit our research by the publication date and language. Our strategy for searching relevant studies was using the following key words “Index-based dietary patterns,” “dietary inflammatory Index or DII,” and all related domains to neoplasm,” “cancer,” “Malignancy,” and “tumor”. Any observational epidemiologic study, either cross-sectional, case-control, or cohort, which had used DII, and the estimation of a adjusted effect size measure [odds ratio (OR), relative risk (RR), and hazard ratio (HR)] and 95% confidence interval (CI) comparing level and score of the DII with respect to the risk of incidence, mortality, and length of hospitalization of all cancer types were eligible to include in this systematic review. We excluded all papers with duplicate entries. In case of multiple publications on the same population, only the largest study or the main source of data was included. The quality of studies was assessed using the Newcastle-Ottawa scale designing for cohort and case-control studies. According to this scale, 9 points can be allocated to each study including four scores for selection, two scores for comparability, and three scores for assessment of outcomes. The process of quality assessment and data extraction was carried out independently by two research experts. Quality assessment agreement on quality assessment between raters was established using Cohen's kappa statistic. The Kappa statistic for agreement on quality assessment was 0.92, which shows perfect agreement. The discrepancy between the raters was resolved by an auditor. Data were extracted according to a checklist. The items on the checklist included (a) the number of citation; (b) demographic characteristics of population such as age, target population, and type of cancers; (c) methodological information of study such as study design, food assessment questionnaire, duration of follow-up, sample size, type of effect size measure (OR, RR, and HR), and adjusted covariates. We examined the association of DII and cancers in terms of morbidity (incidence), mortality, and length of hospitalization. For meta-analysis, we classified cancers into four main categories: (a) digestive tract cancers; (b) hormone-dependent cancers; (c) respiratory tract cancers; and (d) urothelial cancers. However, for those studies that reported several adjusted models, we included only the multivariate model. Although in this systematic review we included all studies with reported DII as continuous (score) or categorical variable (tertile/quartile/quintile), we performed meta-analysis only for DII as categorical variable. In meta-analysis, risk of incidence and mortality of cancer in the highest level of DII (last tertile/quartile/quintile) was compared with lowest level of DII (last tertile/quartile/quintile). Although a number of studies have reported cancer subsites, meta-analysis have not performed according to subsites of cancer.[ 9 10 11 12 13 14 ] The meta-analysis on the association between DII and risk of cancer mortality has been conducted only for all cancer mortality. Because there was only one study on the association between length of hospitalization and DII, we did perform mate-analysis for the association of DII and length of hospitalization of cancer. The results reported as adjusted effect size measure and 95% CI. The Chi-square based Q test and I square statistics used to assess the heterogeneity between studies. The results of Q test were statistically significant at P < 0.1. Because of severe heterogeneity among studies on the reported values, pooled estimate was estimated using random-effect meta-analysis model (using the Dersimonian and Laird method). The forest plot also was used to present the results of meta-analysis schematically. A random-effects meta-regression was performed using unrestricted maximum likelihood method to evaluate the association of estimated effect size measure and potential confounders such as design of study, type of cancer, food assessment questionnaire, and publication year. Potential publication bias was assessed using Egger's weighted regression tests, and the results of Egger's test were statistically significant at P < 0.1. The funnel plot also was used to present the results of publication bias schematically. “Trim and fill” method was used to adjust the analysis for the effects of publication bias. All statistical analysis was performed using STATA 11 software. The protocol of study was approved by the ethical committee of Alborz University of Medical Science. All reviewed studies were properly cited. For more information about a certain study, we contacted the corresponding authors.

The literature search strategy yielded a total of 575 publications. Further, 148 duplicated articles were excluded. After screening titles and abstracts, 345 irrelevant publications were excluded. Then, 82 remained articles and 6 retrieved articles through reference checking were carefully assessed and reviewed for eligibility; of which, 50 studies were excluded according to inclusion criteria. Finally, 38 studies met the inclusion criteria [ Figure 1 ]. The main results of the selected articles were discussed in terms of incidence ( n = 29), mortality ( n = 7), both of them ( n = 1), and length of hospitalization ( n = 1) in patients with different types of cancers. Papers search and review flowchart for selection of primary studies We found 30 articles (i.e. 20 case- controls and 10 cohorts) on the association of DII and incidence of different cancer types [ Table 1 ]. Twenty-eight articles used food frequency questionnaire (FFQ), and the rest used 24 hour dietary recall (24HR) and dietary history questionnaire as dietary assessment instruments. The highest and lowest effect size measures (95% CI) were observed for esophageal squamous cell carcinoma (OR: 8.24; 95% CI: 2.03-33.47) and breast cancer (HR: 0.85; 95% CI: 0.52-1.41), respectively. Association between DII and risk of cancer incidence Abbreviation: FFQ: food frequency questionnaire, 24HR: 24 hour recall, HR: hazard ratio, OR: odds ratio; DII: dietary inflammatory index; NA: not applicable Table 2 summarizes 8 cohort studies on the association of DII and mortality of different cancer types. Dietary intake was measured using FFQ and 24HR in the five and three articles, respectively. Association of DII and risk of cancer mortality FFQ: Food frequency questionnaire, 24HR: 24 hour recall, HR: Hazard ratio, DII: Dietary inflammatory index We found only one cohort study Table 3 on the association between DII and length of hospitalization. There was no significant association exists between DII and length of hospitalization in surgical patients treated for colorectal cancer. Association between DII and length of hospitalization FFQ: Food frequency questionnaire, OR: Odds ratio Table 4 presents the results of meta-analysis for the association of DII and incidence and mortality of different cancer types. There is a significant association between DII and incidence for all cancer types (OR: 1.32; 95% CI: 1.22-1.42; P < 0.001). A stratified meta-analysis by types of cancer shows that the highest and lowest effect size measures were observed for respiratory tract cancers and hormone-dependent cancers, respectively (OR: 1.64; 95% CI: 1.10-2.17 vs. OR: 1.14; 95% CI: 1.04-1.24). A stratified meta-analysis according to study design shows that the association of DII and incidence of all cancer types in case-control studies (OR: 1.53; 95% CI: 1.36-1.71) were more prominent than cohort studies (OR: 1.18; 95% CI: 1.07-1.30). Figures 2 and 3 report the forest plot of association between DII and cancer incidence according to the design of study and type of cancers, respectively. Moreover, there is a significant association between DII and mortality for all cancer types (HR: 1.16; 95% CI: 1.01-1.32) [ Figure 4 ]. Meta-analysis of association between DII and mortality/morbidity of cancer *The sum of number of studies for all cancers (34 studies) is more than the sum of digestive, hormone-dependent, respiratory and urothelial cancers because in one study, type of cancer was not reported Odds ratio and 95% CI of individual studies and pooled data for the association between DII and incidence of cancer according to the type of study using random-effect model. OR: Odds of ratios Odds ratio and 95% CI of individual studies and pooled data for the association between DII and incidence of cancer according to the type of cancer using random-effect model. OR: Odds of ratios Odds ratio and 95% CI of individual studies and pooled data for the association between DII and mortality of cancer according to the type of cancer using random-effect model. OR: Odds of ratios A meta-regression analysis suggests that design of study can have a significant effect on the association between DII and cancer incidence (slope: 0.54; P = 0.05), whereas meta-regression does not show any significant associations between DII and type of food assessment questionnaire (slope:-0.33;p = 0.21), type of cancer (slope:-0.22; P = 0.22), and publication year (slope: 0.24;p = 0.31). The result of meta-regression analysis for the association of DII and cancer mortality shows no significant association between DII and type of food assessment questionnaire (slope: 0.43; P = 0.47), type of cancer (slope:-0.54; P = 0.81), and publication year (slope: 0.21; P = 0.59). The results of Egger test for association of DII and all cancer incidence show that publication bias exists (coefficient: 2.87; P < 0.001) and funnel plot was asymmetric [ Figure 5 ]. “Trim and fill” correction suggested some potentially missing study on the right side of funnel plot [ Figure 5 ]. Imputation for this potentially missing study yielded an effect size of 1.23 (95% CI: 1.12-1.33). In addition, the results of Egger test for association between DII and all cancer mortality show that publication bias does not exist (coefficient: 1.06; P = 0.15) and funnel plot was symmetric [ Figure 6 ]. Funnel plot detailing publication bias in the studies reporting the association between DII and all cancer morbidity Funnel plot detailing publication bias in the studies reporting the association between DII and cancer mortality

Inflammation is now widely known as an adaptive pathophysiological response underlying various chronic diseases including type 2 diabetes mellitus, cardiovascular disease, obesity, metabolic diseases, and specific types of cancer.[ 1 2 3 ] Several factors are associated with inflammation such as sex, age, and lifestyle. Lifestyle such as diet, physical activity, and smoking as malleable factors can reduce inflammation and thereby contributing to health. Diet plays a contributing role in the regulation of inflammatory process. Various biomarkers have used to evaluate the association of nutrition and low-grade inflammatory status.[ 4 ] Consequently, it may be beneficial to identify dietary patterns related to their inflammatory properties.[ 5 ] Dietary inflammatory index (DII) is a new approach used to evaluate the inflammatory potential of a diet as either anti-inflammatory or pro-inflammatory.[ 6 ] In fact, some of the dietary patterns such as western pattern diet rich in red meat and refined grains is associated with a higher level of CRP, TNF- α, IL-1β, IL-2, and IL-6, which is often referred to as pro-inflammatory biomarkers. In contrast, there is an inverse association between Mediterranean diet including high amounts of fruits, whole grains, extra-virgin olive oil, and pro-inflammatory status.[ 7 8 ] Nowadays, the inflammatory properties of diet and its role in preventing chronic diseases have attracted much attention from health sciences researchers. Although in recent years several studies have shown the association of DII and risk of different cancer types, the findings of these studies are heterogeneous according to the type of study and cancer. However, according to our knowledge, pooled estimate of association of DII and all cancers is unclear and have not been investigated yet by systematic review. The aim of this meta-analysis was to investigate the association of DII with risk of incidence and mortality of any cancer types.

To the best of our knowledge, the present study is the first comprehensive systematic review and meta-analysis on the association of DII and cancer incidence and mortality. This meta-analysis shows a significant association between DII and risk of incidence and mortality of all cancer types. The results of the present study shows that a higher level of DII increases the risk of cancers incidence by 32% (95% CI: 1.22-1.42) including digestive tract cancers (OR: 1.55; 95% CI: 1.33-1.78), hormone-dependent cancers (OR = 1.14; 95% CI: 1.04-1.24), respiratory tract cancers (OR: 1.64; 95% CI: 1.11-2.17), and urothelial cancers (OR: 1.36; 95% CI: 1.00-1.73). Moreover, a higher level of DII in association with a higher risk of mortality caused by all type of cancer by 16% (95% CI: 1.01-1.32). Our findings were consistent with previous studies showing that a higher DII was associated with mortality. Moreover, some studies have documented a direct association between DII and a higher risk for metabolic syndrome and cardiovascular diseases (CVD).[ 4 ] One of the study reported different mechanisms by which inflammatory markers used for DII calculation can predict most prevalent diseases including cancers, CVD, and diabetes.[ 6 ] Results of present study show that the association of DII and incidence of all cancer types in case-control studies were more prominent than cohort studies, which was consistent with previous studies.[ 15 16 ] It has been suggested that dietary recall bias may justify the discrepant results between case-control and cohort studies on diet and the risk of cancers. Dietary patterns analysis is one of the most appropriate approaches to understand the relationship between diet and risk for various diseases including diabetes, cancers, and CVD.[ 17 ] All of the healthy dietary patterns (e.g. Dietary Approaches to Stop Hypertension and Mediterranean diet) can play a key role in preventing major chronic diseases, especially cancers.[ 18 19 20 ] In contrast, there was an inverse relationship between DII and dietary quality indices (e.g. Healthy Eating Index).[ 21 ] This was in line with the number of studies showing an inverse correlation between C-reactive protein, one of the inflammatory biomarkers used to calculate the DII, and higher consumption of vegetables, fruits,[ 22 ] legumes,[ 23 ] and nuts.[ 24 ] To define the inflammatory capacity of diet as a main determining factor for vast majority of chronic diseases, we developed DII from peer-reviewed literature by investigating the association between dietary components and inflammation. However, in contrast to the other dietary patterns, DII focuses on specific biological pathways modulating the impact of dietary factors on inflammation.[ 21 ] In fact, in comparison to other dietary pattern, DII can provide more comprehensive information on additional variables affecting inflammation.[ 25 26 27 28 29 ] The present meta-analysis has some strengths and limitations. The main strength is that the study includes all indices of incidence, mortality, and length of hospitalization of cancers in relation with a categorical and continuous score of DII. In addition, we carried out the meta-analysis on all types of cancer. The limitations of the study were as follows: (a) reviewed studies were heterogeneous in terms of population characteristics, design, and duration of follow-up periods; and (b) the questionnaires used for food assessment were different. However, we tried to reduce the effect of heterogeneity on estimated effect sizes by using a random-effect model of analysis.

In conclusion, the present meta-analysis suggested a significant association between DII and incidence, mortality, and hospitalization in patients with different types of cancers. DII, which is used for evaluating inflammatory properties of diets, can be used as an appropriate tool to predict the incidence and mortality of all cancer types. According to the results of the study, we recommend that changing dietary patterns as malleable factors can substantially reduce both incidence and mortality risks in cancer patients. The study was funded by Alborz University of Medical Sciences. There are no conflicts of interest.