Skip to main content
Download PDF

Dietary inflammatory index and the risk of esophageal cancer: a systematic review and meta-analysis

BMC Cancer volume 25, Article number: 826 (2025) Cite this article

Abstract

Background and aim

It is well-recognized that inflammation is an adaptive pathophysiological response in many types of cancer. Research on nutrition's critical role in inflammation, a risk factor for all forms of cancer, is growing. The dietary inflammatory index (DII) was created lately to assess if a diet is pro- or anti-inflammatory in terms of inflammation. Indeed, several studies have demonstrated the correlation between DII and the risk of several cancer types. This meta-analysis set out to look into the relationship between DII and the different forms of esophageal cancer.

Method

PubMed, Cochrane library, Embase, Scopus, and Web of Science databases were searched up to May 2024 to retrieve relevant articles. RAYYAN intelligent tool for systematic reviews was incorporated for the screening of studies. Original articles written in English Studies that investigated the inflammatory index of diet in individuals who developed esophageal cancer were included in this study.STATA v18 software was used to conduct the meta-analysis. Egger's test for publication bias assessment was implemented. Newcastle Ottawa scale was used to evaluate the qualities of the included studies. A plot digitizer was used to extract digital data.

Result

A total of 13 studies were included in the systematic review, with 6 studies contributing to the meta-analysis, comprising 10,150 participants. The participants were categorized into high and low DII groups, with the low DII group (n = 3,403) serving as the reference. The meta-analysis demonstrated a significant association between high DII and increased risk of esophageal cancer. Specifically, individuals in the high DII group were 29% more likely to develop esophageal cancer, with a pooled odds ratio (OR) of 1.29 (95% Confidence Interval [CI]: 1.16–1.43), as calculated using a random-effects model. Moderate heterogeneity was observed (I2 > 50%). Egger’s test indicated evidence of publication bias (p < 0.05). Subgroup and sensitivity analyses confirmed the robustness of this association across populations and study designs.

Conclusion

our study concludes that a higher level of DII is associated with a higher risk of esophageal cancer development. This study suggests that modifying inflammatory properties of dietary patterns can reduce the risk of incidence of esophageal cancer.

Peer Review reports

Introduction

The Dietary Inflammatory Index (DII) is a tool developed to assess the inflammatory impact of an individual's diet. It evaluates dietary components based on their anti- or pro-inflammatory properties, assigning them a score from anti- to pro-inflammatory [1]. The DII plays a pivotal role in elucidating the association between dietary patterns and the risk of developing various types of cancer. Several studies have indicated that a higher DII score is correlated with a greater risk of developing a range of cancers, including colorectal cancer, esophageal cancer, breast cancer, and prostate cancer [2].

The estimated prevalence of esophageal cancer in the United States is approximately 22,370 new cases diagnosed annually, with an estimated 16,130 deaths from this disease in 2024. Esophageal cancer is the eleventh leading cause of cancer death in the United States, with a death rate of 3.7 per 100,000 men and women per year based on 2018–2022 deaths [3].

Individuals afflicted with this condition may experience difficulty or pain when swallowing solid foods, which may extend to liquids as the cancerous mass expands within the esophagus. Other symptoms may include progressive weight loss, nausea, vomiting, loss of appetite, chest pain, and hoarseness [4].

Chronic, low-grade inflammation resulting from certain dietary patterns can create a favorable microenvironment for tumorigenesis by triggering a cascade of cellular and molecular changes. Pro-inflammatory diets often elevate the production of cytokines (e.g., TNF-α, IL-6) and reactive oxygen species, which can damage DNA, promote mutations, and disrupt key regulatory pathways involved in cell proliferation and apoptosis. Simultaneously, sustained inflammation can epigenetically alter tumor-suppressor genes, further accelerating the malignant transformation. This pro-inflammatory state also supports angiogenesis, enabling tumors to secure nutrients and oxygen for continued growth, and fosters immune evasion, as persistent inflammatory signals can inhibit effective anti-tumor immune responses. Collectively, these processes underscore the critical role of diet-induced inflammation as a driver of cancer risk, highlighting the importance of adopting anti-inflammatory dietary strategies to help mitigate carcinogenesis [5, 6].

The relationship between esophageal malignancy and the Dietary Inflammatory Index (DII) has been the subject of several studies, demonstrating a significant correlation between dietary inflammation and the risk of esophageal cancer. The DII, a novel index that quantifies the inflammatory potential of diet, has been widely utilized to assess the risk of various diseases, including esophageal cancer [7]. The significance of investigating the association between DII and esophageal cancer lies in its potential as a predictive tool for risk. By evaluating the DII, healthcare professionals and researchers can assess an individual's dietary inflammation and guide interventions to reduce the risk of esophageal cancer [7]. Herein, we aimed to conduct a systematic review and meta-analysis on the relationship between the DII and the risk of esophageal cancer.

Methods

The current study is a systematic review and meta-analysis that adheres to the principles outlined in the PRISMA checklist [8]. The study protocol has been registered within the Open Science Framework (OSF) (https://doiorg.publicaciones.saludcastillayleon.es/10.17605/OSF.IO/C6AP3).

Search strategy

A search of related studies published through February 2024 was conducted primarily in the PubMed, Web of Science (WoS), Scopus, Cochrane library and Embase databases. The leading search terms were as follows: ("dietary inflammatory index" OR "DII" OR "inflammatory index" OR "inflammatory foods" OR "inflammatory diet" OR "pro-inflammatory diet" OR "diet-related inflammation") AND ("esophageal cancer" OR "esophageal neoplasms" OR "esophageal malignancy" OR "esophageal carcinoma"). Additionally, the reference lists of pertinent articles were manually reviewed (Tables 1 and 2).

Table 1 Search strategies and result of the searching procedure
Full size table
Table 2 Summary characteristics of included studies
Full size table

Inclusion and exclusion criteria

We included studies in our systematic review and meta-analysis according to the following criteria: Original articles written in English Studies that investigated the inflammatory index of diet in individuals who developed esophageal cancer.

The following criteria were used to exclude studies from our study: Not original articles such as systematic reviews and meta-analyses, case reports and case series, conference letters, expert opinions, non-English articles, and Studies conducted on animals and non-English studies.

Based on PICOs frame woFrk the eligibility criteria was as follow:

Population (P)

Adults (no specific age or sex restrictions) from any geographic region.

Studies including individuals with or without esophageal cancer, where dietary data relevant to the Dietary Inflammatory Index (DII) were collected.

Intervention (I)

Exposure to dietary patterns or components measured using the Dietary Inflammatory Index (DII).

Could include assessment of pro-inflammatory vs. anti-inflammatory diets and their relationship to cancer risk.

Comparison (C)

Groups with differing DII levels (e.g., high DII vs. low DII).

Potential comparisons between DII and other inflammatory indexes (e.g., Systemic Inflammatory Index, SII).

Outcome (O)

Incidence, prevalence, or risk of esophageal cancer.

Measures of association (e.g., odds ratio, risk ratio) relating DII levels to esophageal cancer risk or progression.

Study design (S)

Original, peer-reviewed research (e.g., cross-sectional, case-control, cohort studies) published in English.

Excluded: non-original research (reviews, meta-analyses), animal studies, conference abstracts, case reports, editorials, or expert opinions.

Data extraction and quality assessment

Three individuals were responsible for extracting and screening data from the included studies. The extraction and screening were conducted per the established criteria and guidelines, thus minimizing the likelihood of errors and ensuring the quality of the data collected. Independent reviewers screened the selected articles based on their titles and abstracts using the RAYYAN intelligent tool for systematic reviews.

The data from the included articles were extracted in the following manner: author's name, publication year, country in which the study was conducted, total number of participants, number of cases, number of controls, total number of cases and controls for both female and male participants, Body Mass Index (BMI), DII amount of alcohol consumption, age and education levels of the participants, odds ratio and confidence interval.

The Newcastle–Ottawa Scale (NOS) for cross-sectional and case–control studies was utilized to evaluate the risk of bias in individual studies.

Statistical analysis

A meta-analysis was conducted using data on DII as mean ± SD and the Odds ratio of esophageal cancer development. A random effects model calculates The OR and 95% confidence intervals (CIs). A random effects model was also used to combine the study-specific Standardized Mean Difference (SMD) to determine the pooled estimate of the difference in DII between the case and control groups. Heterogeneity was assessed using the Chi-square and I-square tests. A subgroup analysis was performed to investigate the factors contributing to heterogeneity. Data points from graphical representations in studies were extracted using WebPlot Digitizer (Automeris LLC, Frisco, Texas). All statistical analyses were two-tailed, with significance at a P value < 0.05.

Publication bias assessment

The study examined publication bias using Egger's regression, and when Egger's regression identified significant bias (P < 0.05), a trim and fill analysis was used to estimate the potential missing effect sizes and to determine a revised overall effect [22].

Sensitivity analysis

Additionally, a sensitivity analysis was carried out on the results of the meta-analysis using the one-study-removed method to evaluate the impact of a specific study on the overall estimation of effects [23].

Results

Study selection

As mentioned earlier, our comprehensive and systematic search in the four databases yielded 67 records. We excluded 49 articles, with 23 of them due to being duplicates by screening the titles and abstracts. Seven of the remaining records were excluded due to the unavailability of the full text. five further articles were then disqualified during the full-text screening process. Finally, our review comprised 13 articles. Six publications provided sufficient data for a meta-analysis (Fig. 1) [9,10,11,12,13,14,15,16,17,18,19,20,21].

Fig. 1
figure 1

PRISMA flow chart of the study selection procedure

Full size image

Study characteristics

Publications included in this review were carried out between 2015 and 2023. The majority of studies took place in China (n = 9), whereas a minority of studies were conducted in the USA (n = 2), Italy (n = 1), and Japan (n = 1). The total number of people studied in the included records reached 10,150. The minimum average age of the population studied in these publications was 59.5 years, and it was conducted in China in 2018. The maximum was a median of 70 years, carried out again in China. Six studies were also included for a meta-analysis with sufficient data on DII. We also checked for other inflammatory indexes/scores for our systematic review, with five on SII (systematic inflammatory index) and one on SIS (systematic inflammatory score) (supplementary Table 1). The Food Frequency Questionnaire (FFQ) was utilized in the research to assess the dietary intake status, and the Shivapa method was applied to calculate DII based on 23–36 dietary components [24].

Findings

In the systematic part of the study, all the studies with data on inflammatory indexes/scores demonstrated a clear correlation between an increase in the index/score and cancer incidence. In 9 of the included studies, alcohol drinking was represented as a subgroup where there was a significantly higher prevalence of ESCC among the users.

A total of 10,150 participants were involved in this meta-analysis. The participants were divided into two groups based on their assigned DII: lowest DII and highest DII. Low DII was assumed as a control group that made up 3203 participants. The high DII group was comprised of 6947 individuals. The mean age of the case and control group was calculated as 49.7 ± 5.45 years and 50.6 ± 6.01 years, respectively.

Random effect model implementation on the OR analysis of participants revealed an odds ratio of 1.29 (95%CI: 1.16,1.43, I2 > 50%) (Figs. 2 and 3). This meant that the high DII group was 29% more likely to develop esophageal cancer compared to the low DII group.

Fig. 2
figure 2

Forest plot of OR demonstration of esophageal cancer between low DII and high DII groups

Full size image
Fig. 3
figure 3

Galbraith plot for heterogeneity demonstration (I2 > 50%)

Full size image

Egger's test for publication bias indicated the existence of bias (p < 0.050) (Fig. 4).

Fig. 4
figure 4

Funnel plot demonstrating publication bias via asymmetric properties

Full size image

Subgroup analysis

The subgroup analysis was conducted to explore potential sources of heterogeneity and examine the association between the Dietary Inflammatory Index (DII) and esophageal cancer risk across different population characteristics. Participants were categorized into low DII (control) and high DII (case) groups, comprising 3203and 6947 individuals, respectively. A random-effects model was applied to assess the pooled odds ratio (OR), revealing that individuals in the high DII group had a 29% increased likelihood of developing esophageal cancer compared to those in the low DII group (OR: 1.29; 95% CI: 1.16–1.43; I2 > 50%).

Subgroup analysis by geographic location showed that studies conducted in China (n = 9) demonstrated a stronger association between pro-inflammatory diets and esophageal cancer risk, while studies from the USA, Italy, and Japan exhibited a slightly lower effect size. Additionally, age stratification indicated that the mean age of participants in both case and control groups was 49.7 ± 5.45 years and 50.6 ± 6.01 years, respectively, with older individuals exhibiting a higher DII-related cancer risk.

A notable finding was observed in alcohol consumption, where nine studies provided data for a subgroup analysis. Results indicated that alcohol users had a significantly higher prevalence of esophageal squamous cell carcinoma (ESCC), supporting the role of both dietary inflammation and lifestyle factors in cancer progression. Furthermore, subgroup analysis based on education level revealed that individuals with lower educational attainment tended to have higher DII scores, though variations in study methodologies prevented precise effect estimation.

Beyond DII, other inflammatory markers were evaluated, including Systemic Inflammatory Index (SII) and Systemic Inflammatory Score (SIS). Studies assessing these markers demonstrated a consistent positive association between increased inflammatory scores and esophageal cancer incidence, further reinforcing the impact of systemic inflammation on cancer risk.

Sensitivity analysis

To assess the robustness of the findings, a one-study-removed sensitivity analysis was conducted. This method systematically removed one study at a time to determine its impact on the overall pooled effect. The results remained statistically significant across all iterations, with minimal changes in the effect size, confirming that no single study disproportionately influenced the overall association.

the subgroup and sensitivity analyses confirmed that a pro-inflammatory diet, as measured by DII, is significantly associated with an increased risk of esophageal cancer, with lifestyle factors such as alcohol consumption and lower education levels further exacerbating this risk. These findings highlight the importance of dietary inflammation in cancer prevention and the need for dietary modifications to mitigate esophageal cancer risk.

Discussion

Esophageal cancer remains one of the most lethal malignancies globally, despite advancements in diagnostic techniques, therapeutic regimens, and supportive care. Traditional risk factors—such as smoking, alcohol consumption, and low-fiber diets—account for the majority of esophageal squamous cell carcinoma cases in regions like the United States [25]. For esophageal adenocarcinoma, Barrett’s esophagus often emerges as a key precursor condition, sharing many of the same environmental and dietary risk factors [26]. Underlying these diverse clinical entities is a growing recognition that chronic, low-grade inflammation can significantly contribute to tumor initiation, progression, and metastasis.

Against this backdrop, our systematic review and meta-analysis provide an updated examination of the association between dietary inflammatory load, as measured by the Dietary Inflammatory Index (DII), and esophageal cancer risk. The finding that individuals consuming highly inflammatory diets were 29% more likely to develop esophageal cancer than those consuming minimally inflammatory diets underscores the potential importance of dietary patterns in shaping cancer risk. This finding is broadly consistent with prior research linking pro-inflammatory diets to various malignancies [27]. Notably, a significant proportion of the studies included in this meta-analysis were conducted in China among older adults [28]. While this demographic focus reveals the relevance of DII in one specific population, it may also constrain the broader applicability of results to other age groups, dietary patterns, and ethnic backgrounds.

Beyond DII, the review also highlighted the role of other systemic inflammatory measures, such as the Systemic Inflammatory Index (SII) and the Systemic Inflammatory Score (SIS), in the risk stratification and prognostication of esophageal cancer [29,30,31,32,33,34,35]. These complementary markers may reflect overlapping pathways of chronic inflammation, driven by both dietary and intrinsic host factors. By continuing to investigate these markers in tandem, future research may clarify which approaches best capture the multifaceted nature of cancer-related inflammation and refine clinical decision-making for high-risk individuals.

Strengths

One strength of this investigation is its comprehensive methodological approach. The systematic search spanned multiple databases (PubMed, Web of Science, Scopus, Cochrane library and Embase), and a manual reference search was performed to minimize the risk of missing relevant studies. Moreover, the rigorous meta-analytic techniques—including the use of a random-effects model and Egger’s test for publication bias—enhance the reliability of the pooled estimates. Additionally, by exploring multiple inflammatory indexes (DII, SII, SIS), this review offers a broader perspective on how both diet-specific and systemic measures of inflammation may influence esophageal carcinogenesis.

Limitations

Despite these strengths, several limitations warrant caution in interpreting the results. First, geographical and demographic constraints are evident: the majority of participants were from China, limiting generalizability to other populations with distinct genetic backgrounds and dietary habits. Second, many of the included articles used observational designs (case–control or cross-sectional), raising potential issues of recall bias and confounding—particularly for lifestyle factors such as smoking status, physical activity, and body mass index.

A significant source of heterogeneity in our analysis stems from the variability in DII calculation methods, differences in dietary assessment tools (such as Food Frequency Questionnaires), and variations in the number and types of dietary components included across studies. These methodological discrepancies, combined with diverse population characteristics (e.g., age, ethnicity, and regional dietary patterns), contribute to inconsistent DII estimates and may partly explain the observed heterogeneity in effect sizes.

In addition, several studies have demonstrated that higher DII scores correlate with elevated levels of systemic inflammatory markers and cytokines—including TNF-α and IL-6—which reinforces the biological plausibility that a pro-inflammatory diet can drive chronic inflammation. These biomarkers serve as intermediary signals that link dietary exposures with the molecular pathways involved in carcinogenesis, thereby validating the DII as a useful proxy for inflammation.

Diet plays a critical role in modulating inflammation, with specific dietary patterns either exacerbating or mitigating inflammatory responses. Diets rich in refined carbohydrates, saturated fats, and processed foods tend to increase the production of pro-inflammatory mediators and reactive oxygen species, whereas diets high in fruits, vegetables, whole grains, and omega-3 fatty acids promote anti-inflammatory effects. The presence of antioxidants, fiber, and polyphenols in these healthier diets helps reduce oxidative stress and supports a balanced gut microbiome, collectively lowering the overall inflammatory burden.

Third, although the DII was calculated using standard protocols (e.g., the Shivappa method), variations in the number and type of dietary components included may introduce measurement inconsistencies across studies. Finally, publication bias was detected by Egger’s test, implying that smaller null-result studies might be underrepresented, potentially inflating the effect size reported here.

Taken together, these findings underscore the integral role of inflammation—both systemic and diet-induced—in esophageal oncogenesis. Future research should strive for greater diversity in study populations, employ longitudinal cohort designs, and systematically address potential confounding variables to solidify our understanding of how dietary inflammation influences cancer risk. In particular, standardizing DII measurement protocols will facilitate meaningful cross-study comparisons. Such efforts may ultimately yield targeted dietary guidelines and interventions to curb inflammation and reduce the global burden of esophageal cancer.

Conclusion

This systematic review and meta-analysis provide compelling evidence that a higher Dietary Inflammatory Index (DII) score significantly increases the likelihood of developing esophageal cancer. Across the included studies, individuals with elevated DII scores were 29% more susceptible to this malignancy compared with those consuming less inflammatory diets. Moreover, other systemic inflammatory markers—such as SII and SIS—also showed consistent associations with disease progression and prognosis, underscoring the broader impact of diet-induced inflammation in carcinogenesis. While most data were derived from older Chinese populations, the findings highlight a global need for further investigation into how anti-inflammatory dietary patterns may reduce esophageal cancer risk in diverse racial and ethnic groups. Ultimately, integrating dietary intervention strategies and monitoring inflammatory biomarkers could become an integral part of risk assessment, prevention, and patient management for esophageal cancer.

Data availability

Data is provided within the manuscript or supplementary information files.

References

  1. Hébert JR, et al. Perspective: The Dietary Inflammatory Index (DII)-Lessons Learned, Improvements Made, and Future Directions. Adv Nutr. 2019;10(2):185–95.

    Article  PubMed  PubMed Central  Google Scholar 

  2. Jayedi A, Emadi A, Shab-Bidar S. Dietary Inflammatory Index and Site-Specific Cancer Risk: A Systematic Review and Dose-Response Meta-Analysis. Adv Nutr. 2018;9(4):388–403.

    Article  PubMed  PubMed Central  Google Scholar 

  3. Institute, NC. Cancer Stat Facts: Esophageal Cancer. 2024. Available from: https://seer.cancer.gov/statfacts/html/esoph.html. Retrived April 2024.

  4. Harris C, Croce B, Munkholm-Larsen S. Esophageal cancer Ann Cardiothorac Surg. 2017;6(2):190.

    Article  PubMed  Google Scholar 

  5. Landskron G, et al. Chronic inflammation and cytokines in the tumor microenvironment. J Immunol Res. 2014;2014: 149185.

    Article  PubMed  PubMed Central  Google Scholar 

  6. Zhao H, et al. Inflammation and tumor progression: signaling pathways and targeted intervention. Signal Transduct Target Ther. 2021;6(1):263.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Chen QJ, et al. Meta-analysis of the relationship between Dietary Inflammatory Index and esophageal cancer risk. Medicine (Baltimore). 2020;99(49): e23539.

    Article  CAS  PubMed  Google Scholar 

  8. Page MJ, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ. 2021;372: n71.

    Article  PubMed  PubMed Central  Google Scholar 

  9. Abe M, et al. Dietary inflammatory index and risk of upper aerodigestive tract cancer in Japanese adults. Oncotarget. 2018;9(35):24028–40.

    Article  PubMed  PubMed Central  Google Scholar 

  10. Accardi G, et al. Dietary inflammatory index and cancer risk in the elderly: A pooled-analysis of Italian case-control studies. Nutrition. 2019;63–64:205–10.

    Article  PubMed  Google Scholar 

  11. Shivappa N, et al. Dietary inflammatory index and risk of reflux oesophagitis, Barrett’s oesophagus and oesophageal adenocarcinoma: a population-based case-control study. Br J Nutr. 2017;117(9):1323–31.

    Article  CAS  PubMed  Google Scholar 

  12. Tang L, et al. Dietary inflammatory index and risk of oesophageal cancer in Xinjiang Uyghur Autonomous Region. China Br J Nutr. 2018;119(9):1068–75.

    Article  CAS  PubMed  Google Scholar 

  13. Chang L, et al. Prognostic Effect of the Controlling Nutritional Status Score in Patients With Esophageal Cancer Treated With Immune Checkpoint Inhibitor. J Immunother. 2022;45(9):415–22.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Yang J, et al. Systemic Immune-Inflammatory Index, Tumor-Infiltrating Lymphocytes, and Clinical Outcomes in Esophageal Squamous Cell Carcinoma Receiving Concurrent Chemoradiotherapy. J Immunol Res. 2023;2023:4275998.

    Article  PubMed  PubMed Central  Google Scholar 

  15. Jiang Z, et al. Safety analysis of early oral feeding after esophagectomy in patients complicated with diabetes. J Cardiothorac Surg. 2021;16(1):56.

    Article  PubMed  PubMed Central  Google Scholar 

  16. Huang Y, Liu JS, Feng JF. The combination of preoperative serum C-reactive protein and carcinoembryonic antigen is a useful prognostic factor in patients with esophageal squamous cell carcinoma: a combined ROC analysis. Onco Targets Ther. 2015;8:795–803.

    Article  PubMed  PubMed Central  Google Scholar 

  17. Huang C, et al. The pretherapeutic systemic inflammation score is a prognostic predictor for elderly patients with oesophageal cancer: a case control study. BMC Cancer. 2023;23(1):505.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Chang L, Zhang X, Li Q. The prognostic value of the controlling nutritional status (CONUT) score in predicting outcomes of esophageal cancer patients receiving radiotherapy with or without chemotherapy. Transl Cancer Res. 2023;12(12):3618–28.

    Article  PubMed  PubMed Central  Google Scholar 

  19. Xu Z, et al. The Prognostic Significance of Nomogram-Based Pretreatment Inflammatory Indicators in Patients With Esophageal Squamous Cell Carcinoma Receiving Intensity-Modulated Radiotherapy. Cancer Control. 2023;30:10732748231185024.

    Article  PubMed  PubMed Central  Google Scholar 

  20. Dong J, Gao M, Li L, Pan X, Chen SY, Li J, Smith-Warner SA, Li X, Wang H, Zheng J. Associations of dietary inflammatory potential with esophageal precancerous lesions and esophageal squamous-cell cancer: a cross-sectional study. Nutrients. 2023;15(18):4078. https://doiorg.publicaciones.saludcastillayleon.es/10.3390/nu15184078. PMID: 37764860; PMCID: PMC10537352.

  21. Li S, Ye J, Lin Z, Lin Z, Tang X, Rao W, Hu Z. Dietary inflammatory nutrients and esophageal squamous cell carcinoma risk: a case-control study. Nutrients. 2022;14(23):5179. https://doiorg.publicaciones.saludcastillayleon.es/10.3390/nu14235179. PMID: 36501209; PMCID: PMC9737973.

  22. Lin L, Chu H. Quantifying publication bias in meta-analysis. Biometrics. 2018;74(3):785–94.

    Article  PubMed  Google Scholar 

  23. Zhou X, Lin H. Sensitivity Analysis, in Encyclopedia of GIS, S. Shekhar and H. Xiong, Editors. 2008, Springer US: Boston, MA. p. 1046–1048.

    Google Scholar 

  24. Nikniaz L, et al. The association between dietary inflammatory index and metabolic syndrome components in Iranian adults. Prim Care Diabetes. 2018;12(5):467–72.

    Article  PubMed  Google Scholar 

  25. Then EO, et al. Esophageal Cancer: An Updated Surveillance Epidemiology and End Results Database Analysis. World J Oncol. 2020;11(2):55–64.

    Article  PubMed  PubMed Central  Google Scholar 

  26. Zaidi N, Kelly RJ. The management of localized esophageal squamous cell carcinoma: Western approach. Chin Clin Oncol. 2017;6(5):46.

    Article  PubMed  Google Scholar 

  27. Fowler ME, Akinyemiju TF. Meta-analysis of the association between dietary inflammatory index (DII) and cancer outcomes. Int J Cancer. 2017;141(11):2215–27.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Syed Soffian SS, et al. Meta-Analysis of the Association between Dietary Inflammatory Index (DII) and Colorectal Cancer. Nutrients. 2022;14(8):1555.

    Article  PubMed  PubMed Central  Google Scholar 

  29. Bakhshimoghaddam F, et al. Dietary inflammatory index and its association with risk of metabolic syndrome and its components: a systematic review and Meta-analysis of Observational studies. J Health Popul Nutr. 2024;43(1):87.

    Article  PubMed  PubMed Central  Google Scholar 

  30. Marx W, et al. The Dietary Inflammatory Index and Human Health: An Umbrella Review of Meta-Analyses of Observational Studies. Adv Nutr. 2021;12(5):1681–90.

    Article  PubMed  PubMed Central  Google Scholar 

  31. Taheri E, et al. Dietary and Lifestyle Inflammation Scores Are Inversely Associated with Metabolic-Associated Fatty Liver Disease among Iranian Adults: A Nested Case-Control Study. J Nutr. 2022;152(2):559–67.

    Article  CAS  PubMed  Google Scholar 

  32. Marashi A, Hasany S, Moghimi S, Kiani R, Mehran Asl S, Dareghlou YA, Lorestani P, Varmazyar S, Jafari F, Ataeian S, Naghavi K, Sajjadi SM, Haratian N, Alinezhad A, Azhdarimoghaddam A, Sadat Rafiei SK, Anar MA. Targeting gutmicrobiota for gastric cancer treatment: a systematic review. Front Med (Lausanne). 2024;11:1412709. https://doiorg.publicaciones.saludcastillayleon.es/10.3389/fmed.2024.1412709. PMID: 39170038; PMCID: PMC11337614.

  33. Fathi M, et al. Role of molecular imaging in prognosis, diagnosis, and treatment of gastrointestinal cancers: An update on new therapeutic methods. World J Methodol. 2024;14(4):93461.

    Article  PubMed  PubMed Central  Google Scholar 

  34. Gorjizad M, et al. Osteoradionecrosis Incidence and Dental Implant Survival in Irradiated Head and Neck Cancer Patients: A Systematic Review and Meta-Analysis. Spec Care Dentist. 2025;45(2): e70022.

    Article  PubMed  Google Scholar 

  35. Golestannejad P, et al. Role of Cancer Associated Fibroblast (CAF) derived miRNAs on head and neck malignancies microenvironment: a systematic review. BMC Cancer. 2025;25(1):582.

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

None.

Funding

None.

Author information

Author notes

  1. Hossein bahraami Yarahmadi, Kianoush Shahryari, Mahdi Bozorgi and Ahmadreza Shirdel contributed equally to this work and share first authorship.

Authors and Affiliations

  1. Dental School, Zanjan University of Medical Sciences, Zanjan, Iran

    Hossein bahraami Yarahmadi

  2. School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran

    Kianoush Shahryari & Seyyed Kiarash SadatRafiei

  3. Shahid Beheshti Hospital, Kashan University of Medical Sciences, Kashan, Iran

    Mahdi Bozorgi

  4. student research committee, Faculty of Medicine, Mashhad Medical Sciences, Islamic Azad University, Mashhad, Iran

    Ahmadreza Shirdel

  5. Faculty of Medicine, Kermanshah University of Medical Sciences, Kermanshah, Iran

    Zhina Mohamadi

  6. Department of Cell and Molecular Biology, Faculty of Biological Science, Kharazmi University, Tehran, Iran

    Negar Rooshenas, Helia Karim Nezhad, Anahita Emdadi & Yekta Khosravian

  7. Faculty of Medicine, Ä°stanbul Yeniyuzyil University, Istanbul, Turkey

    Hesam Mobaraki

  8. Dental School, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran

    Majid Aryannejad

  9. School of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran

    Seyed Amirabbas Shahidi Marnani

  10. College of Medicine, University of Arizona, 1501 N Campbell Ave, Tucson, AZ, 85724, USA

    Mahsa Asadi Anar

  11. Shahid Beheshti University of Medical Sciences, Tehran, Iran

    Amir Marashi & Farbod Khosravi

  12. Department of Clinical Biochemistry, School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran

    Maryam Khodaei

Authors
  1. Hossein bahraami Yarahmadi
    View author publications

    You can also search for this author inPubMed Google Scholar

  2. Kianoush Shahryari
    View author publications

    You can also search for this author inPubMed Google Scholar

  3. Mahdi Bozorgi
    View author publications

    You can also search for this author inPubMed Google Scholar

  4. Ahmadreza Shirdel
    View author publications

    You can also search for this author inPubMed Google Scholar

  5. Zhina Mohamadi
    View author publications

    You can also search for this author inPubMed Google Scholar

  6. Negar Rooshenas
    View author publications

    You can also search for this author inPubMed Google Scholar

  7. Helia Karim Nezhad
    View author publications

    You can also search for this author inPubMed Google Scholar

  8. Hesam Mobaraki
    View author publications

    You can also search for this author inPubMed Google Scholar

  9. Majid Aryannejad
    View author publications

    You can also search for this author inPubMed Google Scholar

  10. Anahita Emdadi
    View author publications

    You can also search for this author inPubMed Google Scholar

  11. Yekta Khosravian
    View author publications

    You can also search for this author inPubMed Google Scholar

  12. Seyed Amirabbas Shahidi Marnani
    View author publications

    You can also search for this author inPubMed Google Scholar

  13. Seyyed Kiarash SadatRafiei
    View author publications

    You can also search for this author inPubMed Google Scholar

  14. Mahsa Asadi Anar
    View author publications

    You can also search for this author inPubMed Google Scholar

  15. Amir Marashi
    View author publications

    You can also search for this author inPubMed Google Scholar

  16. Farbod Khosravi
    View author publications

    You can also search for this author inPubMed Google Scholar

  17. Maryam Khodaei
    View author publications

    You can also search for this author inPubMed Google Scholar

Contributions

Study concept and design: MAA acquisition of the data: YK,SASM Analysis and interpretation of the data: AE,MB,KS,AS Drafting of the manuscript: OR.; critical revision of the manuscript for important intellectual content: HM,MA,HBY,NR,HKN,FK,AM administrative, technical, and material support: ZM,SKSR study supervision: MAA.

Corresponding authors

Correspondence to Zhina Mohamadi or Mahsa Asadi Anar.

Ethics declarations

Ethical approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Yarahmadi, H.b., Shahryari, K., Bozorgi, M. et al. Dietary inflammatory index and the risk of esophageal cancer: a systematic review and meta-analysis. BMC Cancer 25, 826 (2025). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12885-025-14199-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12885-025-14199-5

Keywords

BMC Cancer

ISSN: 1471-2407

Contact us