# Does a Pro-Inflammatory Diet Raise Cancer Risk? What a Major Review of 2.7 Million People Found

This systematic review and meta-analysis combined 24 large prospective cohort studies. The studies included 2,683,350 participants and 37,091 cancer cases. The review examined whether a diet with higher inflammatory potential is linked to cancer risk and cancer-specific death. Inflammatory potential was measured by the Empirical Dietary Inflammatory Pattern, or EDIP. The pooled results showed that people who most closely followed a pro-inflammatory diet had a 10% higher risk of total cancer. Those people had a 19% higher risk of colorectal cancer. Those people had a 48% higher risk of liver cancer. The comparison group was people who followed the pro-inflammatory diet least. Higher EDIP adherence was also linked to an 18% higher risk of dying from cancer, but no significant link was found for ovarian or endometrial cancer.

# Does a Pro-Inflammatory Diet Raise Cancer Risk? What a Major Review of 2.7 Million People Found

## Table of Contents

- Key Points
- Background: Why Diet and Inflammation Matter for Cancer
- What Is the Empirical Dietary Inflammatory Pattern (EDIP)?
- How the Researchers Conducted the Study
- The Studies Included in the Analysis
- Key Findings: Cancer Risk and Cancer-Specific Mortality
- Subgroup and Sensitivity Analyses
- What These Findings Mean for Patients
- Limitations of the Study
- Practical Recommendations
- Frequently Asked Questions
- Source Information

## Key Points

- A meta-analysis of 24 U.S. prospective cohort studies with over 2.6 million participants examined the link between the Empirical Dietary Inflammatory Pattern (EDIP) and cancer.
- People with the highest EDIP adherence had a 10% higher risk of total cancer, a 19% higher risk of colorectal cancer, and a 48% higher risk of liver cancer compared with those with the lowest adherence.
- Higher EDIP adherence was also linked to an 18% higher risk of dying from cancer, but no significant association was found for ovarian or endometrial cancer.
- The studies were observational, so they cannot prove that a pro-inflammatory diet causes cancer; they only show an association.
- Limitations include that all studies were conducted in the United States, diet was self-reported, and some cancer types were examined in only one study.

## Background: Why Diet and Inflammation Matter for Cancer

Cancer is becoming more common worldwide at a worrying rate. In 2015, cancer was the second most common cause of death globally, causing more than 8.7 million deaths. Cancer also causes high rates of disability and premature death. It places a heavy economic burden on healthcare systems.

Researchers have gathered strong evidence that long-term, low-grade inflammation plays a major role in cancer. This type of inflammation involves a persistent rise in inflammatory cells and pro-inflammatory mediators (substances that promote inflammation). Several of these mediators have been linked to cancer development. Examples include C-reactive protein (CRP) and cytokines (signaling molecules) such as interleukin-1 (IL-1), interleukin-6 (IL-6), and tumor necrosis factor-alpha (TNF-α).

These inflammatory mediators can promote cancer through the activation of downstream signaling pathways (a chain of molecular signals inside cells). Activating these pathways may help tumors grow new blood vessels (angiogenesis) and may suppress the body's anti-tumor immune response.

Diet plays an important role in regulating inflammation and the levels of inflammatory cytokines in the bloodstream. Because of this, researchers have developed ways to measure the inflammatory potential of a person's overall diet. These tools can help us understand how diet-related inflammation might be modified to manage health risks.

One widely used tool is the Dietary Inflammatory Index (DII). The DII was developed from a review of original articles published between 1950 and 2010. That review examined how 45 dietary components affect the six most established inflammatory markers: IL-1β, IL-4, IL-6, IL-10 (an anti-inflammatory component), TNF-α, and CRP.

However, the DII has several limitations. It is based on nutrients that cannot be accurately estimated because food compositions vary. It also focuses on single nutrients, but people actually consume nutrients together in the form of food groups.

Because of these limitations, researchers developed newer indices. These include the Inflammatory Score of the Diet, the Anti-Inflammatory Diet Index, the Dietary and Lifestyle Inflammation Scores, and the Empirical Dietary Inflammatory Pattern (EDIP). The EDIP has attracted increasing attention in recent years.

Several observational studies have examined whether following the EDIP is linked to cancer risk and cancer-specific mortality (death specifically from cancer). However, the results have been inconsistent. For example, in the Women's Health Initiative, greater adherence to the EDIP was significantly associated with a higher risk of total cancer. Greater adherence to the EDIP was also significantly associated with a higher risk of several specific cancers. These specific cancers included colorectal, endometrial, and breast cancer.

In contrast, two prospective studies — the Nurses' Health Study I and Nurses' Health Study II — found no significant association between greater EDIP adherence and endometrial cancer risk. For cancer-specific mortality, one study by Li et al. reported a significant association with greater EDIP adherence, but other studies found no significant association.

Because of these conflicting results, the researchers conducted this systematic review and meta-analysis. Their goal was to combine all available prospective studies to determine whether EDIP adherence is associated with an increased risk of cancer and cancer-specific mortality.

## What Is the Empirical Dietary Inflammatory Pattern (EDIP)?

The EDIP was developed by Tabung and colleagues and published in 2016. It is an empirically data-driven dietary pattern score. This means it was derived from a regression model fitted to a particular dataset, rather than being based on expert opinion alone.

The EDIP identifies a dietary pattern based on 18 food groups. These 18 food groups are the ones most predictive of pro-inflammatory markers, including IL-6, TNF-α, and CRP. The EDIP has been validated as highly effective at predicting inflammation biomarkers in three Harvard cohorts.

In simple terms, the EDIP score reflects how much a person's usual diet tends to promote inflammation in the body. A higher EDIP score indicates a diet with greater inflammatory potential.

## How the Researchers Conducted the Study

The study was officially registered on the PROSPERO database with registration ID CRD42024496912. PROSPERO is an international registry for systematic reviews. The researchers followed the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) guidelines and the MOOSE (Meta-analysis of Observational Studies in Epidemiology) guidelines.

The research team used the PECO framework to guide their methods. PECO stands for Population, Exposure, Comparator, and Outcome. The population was adults aged 18 years and older. The exposure was highest adherence to the EDIP. The comparator was lowest adherence to the EDIP. The primary outcome was total cancer or site-specific cancer, and the secondary outcome was cancer-specific mortality.

One researcher searched three electronic databases: Scopus, PubMed/MEDLINE, and ISI Web of Science. The search covered January 2016 to March 2024 and was limited to English-language publications. The researchers imposed a time restriction because the EDIP score was first developed and published in 2016. The same researcher also manually searched the reference lists of all included studies and relevant review articles to make sure no potentially relevant articles were missed.

Studies were included if they met five conditions:

1. Participants were 18 years of age or older.
1. The study design was prospective (participants were followed forward in time).
1. Adherence to the EDIP was assessed as the exposure of interest.
1. The outcomes included risk of total cancer, site-specific cancer, or cancer-specific mortality.
1. Studies reported adjusted estimates — including odds ratio (OR), hazard ratio (HR), or relative risk (RR) — with the corresponding 95% confidence interval (CI).

Studies were excluded if they were duplicate publications, systematic reviews or meta-analyses, clinical trials, case reports, case series, editorials, commentaries, notes, letters, or conference abstracts. Animal, in vivo, and in vitro studies were also excluded. Studies in newborns, children, adolescents, pregnant mothers, or breastfeeding women were excluded. Studies not available in full text, studies that examined the outcome in participants who already had the disease at the start, and studies with insufficient data were also excluded.

Two investigators independently performed a two-step selection process. First, they screened titles and abstracts. Second, they evaluated the full-length publications that seemed relevant. Any disagreements were resolved through discussion with a third investigator.

The quality of each included study was assessed using the Newcastle-Ottawa Scale (NOS). The NOS is a tool designed specifically for assessing the quality of non-randomized studies. It uses a star system based on three criteria: selection of study participants, comparability of the groups, and assessment of either the exposure or the outcome of interest. Each item can receive a maximum of one star, except for the comparability item, which can receive up to two stars. Publications scoring seven or higher were classified as high quality with low risk of bias. Those scoring below seven were classified as low quality with high risk of bias.

Two researchers independently extracted data from each eligible study. The extracted data included the author's name, publication year, and cohort identification (country and study name). The extracted data included sample characteristics (total and sex-stratified sample size), number of cases, baseline age, and body mass index (BMI). The extracted data included follow-up duration, person-years, dietary intake assessment method, and outcome assessment method. The extracted data included outcome type and variables adjusted in the multivariate analysis. The extracted data included the fully adjusted effect size with 95% CI.

For the statistical analysis, the researchers used the DerSimonian and Laird random-effects model. This model accounts for variation both within and between studies (heterogeneity). Hazard ratios reported in the original studies were considered equivalent to relative risks. Studies that reported odds ratios were converted to relative risks using a standard formula. The pooled effect sizes were calculated for the highest compared with the lowest EDIP adherence, as well as per-standard-deviation increases in EDIP adherence.

Heterogeneity between studies was assessed using the Cochran Q test and the I2 statistic. For the I2 metric, 25%, 50%, and 75% heterogeneity correspond to low, medium, and high degrees of heterogeneity, respectively. Subgroup and meta-regression analyses were performed to identify potential sources of heterogeneity. Sensitivity analysis using the one-study exclusion (leave-one-out) method was conducted to evaluate the robustness of the findings. Publication bias was tested by visually inspecting the funnel plot and using Egger's regression test. All statistical analyses were performed using STATA 17.0 software. A p-value less than 0.05 was considered statistically significant.

## The Studies Included in the Analysis

The initial electronic database search identified 229 relevant studies. Of these, 106 were from PubMed/MEDLINE, 63 from Scopus, and 60 from ISI Web of Science. After excluding 100 duplicate publications and screening titles and abstracts, 27 publications were identified as potentially relevant and underwent full-text evaluation.

After the full-text evaluation, three studies were excluded: one because it lacked the exposure of interest, one because it lacked the outcome, and one because of insufficient data. Finally, 24 studies were included in the analysis.

All 24 included studies were conducted in the United States and were published between 2017 and 2023. Together, they involved a total of 2,683,350 participants. The majority of the included studies were high quality.

Of the 24 included studies, 16 reported effect sizes for cancer risk, six reported effect sizes for cancer-specific mortality, and two reported effect sizes for both cancer risk and cancer-specific mortality.

**Cancer incidence studies:** Eighteen studies evaluated the EDIP–cancer risk relationship. These studies covered seven categories of cancer types:

- Gastrointestinal cancers: colorectal cancer (six studies), liver cancer (three studies), and pancreatic cancer (one study)
- Urological cancers: prostate cancer (two studies), bladder cancer (one study), and kidney cancer (one study)
- Ovarian cancer (three studies), endometrial cancer (two studies), breast cancer (one study), multiple myeloma (one study), and lung cancer (one study)

These 18 studies enrolled 2,662,531 participants, ranging from 1,048 to 485,931 participants per study. Over a 16- to 32-year follow-up period, a total of 37,091 cancer cases were documented. These cases included:

- 13,196 cases of colorectal cancer
- 953 cases of liver cancer
- 850 cases of pancreatic cancer
- 10,105 cases of prostate cancer
- 1,042 cases of bladder cancer
- 429 cases of kidney cancer
- 478 cases of multiple myeloma
- 4,393 cases of breast cancer
- 1,968 cases of endometrial cancer
- 1,561 cases of ovarian cancer
- 176 cases of lung cancer

All of these studies used a food frequency questionnaire (FFQ) to calculate the EDIP score. The mean age at baseline ranged from 38.43 to 63.85 years, and the mean BMI at baseline ranged from 24.5 to 27.59. Cancer incidence was obtained from medical reports in nine studies and from pathology reports in nine studies.

The majority of the included studies controlled for conventional risk factors. Specifically, 17 studies controlled for total energy intake, nine for supplement use, 11 for alcohol consumption, 15 for smoking, 13 for physical activity, and 13 for family history of cancer.

**Cancer-specific mortality studies:** Nine studies assessed the association between EDIP adherence and the risk of cancer-specific mortality. These studies covered seven categories of cancer-specific mortality. The categories were colorectal cancer (two studies), prostate cancer (two studies), and pancreatic cancer (one study). The categories also were multiple myeloma (one study), ovarian cancer (one study), and kidney cancer (one study).

These nine studies included a total of 20,819 participants, ranging from 423 to 117,870 participants per study. During a follow-up period spanning 16 to 40 years, a total of 5,006 cancer-specific mortality cases were recorded. These cases included:

- 570 cases of colorectal cancer mortality
- 740 cases of prostate cancer mortality
- 1,118 cases of pancreatic cancer mortality
- 295 cases of multiple myeloma mortality
- 1,102 cases of ovarian cancer mortality
- 113 cases of kidney cancer mortality

Of the nine studies that evaluated the EDIP–cancer-specific mortality relationship, eight used a food frequency questionnaire (FFQ) and one used a 24-hour recall questionnaire to calculate the EDIP. The mean age of participants at baseline ranged from 47.3 to 72.3 years.

## Key Findings: Cancer Risk and Cancer-Specific Mortality

The pooled results showed a significant association between higher adherence to the EDIP and an increased risk of total cancer. The effect size was 1.10 (95% CI: 1.05–1.15), with an I2 of 41.1. In plain language, this means that people with the highest EDIP adherence had a 10% higher risk of developing any cancer compared with people with the lowest EDIP adherence. The I2 value of 41.1 indicates moderate heterogeneity between the studies.

The results also showed a significant association between higher EDIP adherence and colorectal cancer risk. The effect size was 1.19 (95% CI: 1.11–1.27), with an I2 of 41.1. This means that people with the highest EDIP adherence had a 19% higher risk of colorectal cancer compared with those with the lowest adherence.

The strongest association was found for liver cancer. The effect size was 1.48 (95% CI: 1.14–1.94), with an I2 of 36.9. This means that people with the highest EDIP adherence had a 48% higher risk of liver cancer compared with those with the lowest adherence. The I2 value of 36.9 indicates low-to-moderate heterogeneity.

However, the researchers found no significant association between increased EDIP adherence and increased risk of ovarian cancer or endometrial cancer.

For cancer-specific mortality, greater adherence to the EDIP was significantly associated with an increased risk. The effect size was 1.18 (95% CI: 1.05–1.33), with an I2 of 45.4. This means that people with the highest EDIP adherence had an 18% higher risk of dying from cancer compared with those with the lowest adherence. The I2 value of 45.4 indicates moderate heterogeneity.

## Subgroup and Sensitivity Analyses

The researchers performed subgroup analyses to identify potential sources of heterogeneity between studies. These analyses were based on several factors:

- Age (under 55 years versus over 55 years)
- Gender (men versus women)
- Number of participants (under 100,000 versus over 100,000)
- Outcome assessment method (medical record versus pathology report)
- Body mass index (normal weight versus overweight or obese)
- Baseline type 2 diabetes mellitus (T2DM) status (yes versus no)
- Adjustment for major confounders (total energy intake, supplement use, alcohol consumption, smoking status, physical activity, and family history of cancer)

The researchers also conducted a sensitivity analysis using the one-study exclusion (leave-one-out) method. This analysis evaluated whether the final pooled effect sizes were influenced by any single publication. The purpose was to test the robustness of the findings.

Publication bias was tested by visually inspecting the funnel plot and by using Egger's regression test.

## What These Findings Mean for Patients

This study provides strong evidence that a diet with higher inflammatory potential is associated with an increased risk of cancer and cancer-specific mortality. The findings are based on 24 large prospective cohort studies with more than 2.6 million participants, which makes the results robust and generalizable to adults in the United States.

The link was strongest for liver cancer, where the highest EDIP adherence was associated with a 48% higher risk. Colorectal cancer showed a 19% higher risk, and total cancer showed a 10% higher risk. These are meaningful differences at the population level.

Importantly, the study found no significant association between EDIP adherence and ovarian or endometrial cancer. This suggests that the effect of diet-related inflammation may differ by cancer type. Not all cancers respond to inflammation in the same way.

The finding that higher EDIP adherence was associated with an 18% higher risk of cancer-specific mortality is also significant. This means that diet-related inflammation may not only influence whether cancer develops but also how likely a person is to die from it.

These results support the idea that reducing the inflammatory potential of your diet could be a useful strategy for lowering cancer risk. However, because this is an observational study, it cannot prove that a pro-inflammatory diet directly causes cancer. It can only show an association.

## Limitations of the Study

This study has several limitations that patients should understand. First, all included studies were conducted in the United States. This means the findings may not apply to populations in other countries with different dietary patterns and lifestyles.

Second, all studies used food frequency questionnaires (FFQs) or 24-hour recall questionnaires to assess diet. These methods rely on participants' memory and self-reporting, which can introduce measurement error.

Third, the studies showed moderate heterogeneity (I2 values ranging from 36.9 to 45.4). This means that the studies were not entirely consistent with each other. The researchers attempted to address this through subgroup and meta-regression analyses, but some unexplained variation remains.

Fourth, as with all observational studies, residual confounding is possible. Even though most studies adjusted for major risk factors such as smoking, physical activity, and family history of cancer, other unmeasured factors could influence the results.

Fifth, the number of studies for some cancer types was small. For example, only one study each examined pancreatic cancer, bladder cancer, kidney cancer, breast cancer, multiple myeloma, and lung cancer risk. This limits the strength of conclusions for those specific cancers.

Finally, the study only included English-language publications, which could introduce language bias.

## Practical Recommendations

Based on the findings of this study, here are some practical steps patients can consider:

1.
**Be aware of the inflammatory potential of your diet.** The EDIP is based on 18 food groups that are most predictive of inflammatory markers in the body. While the specific food groups are not listed in this article, the general principle is that some foods promote inflammation and others reduce it.
1.
**Focus on overall dietary patterns, not single nutrients.** The EDIP was designed to capture how foods are consumed together, which is more realistic than looking at single nutrients in isolation.
1.
**Discuss your cancer risk with your healthcare provider.** If you have a family history of cancer or other risk factors, talk to your doctor about how diet might affect your risk.
1.
**Consider a diet with lower inflammatory potential.** While this study cannot prove cause and effect, the consistent association across 24 studies suggests that reducing dietary inflammation may be beneficial.
1.
**Stay informed about ongoing research.** The EDIP is a relatively new tool, and more studies are needed to confirm these findings and to determine whether changing your diet can actually lower cancer risk.

It is important to remember that cancer is a complex disease with many causes. Diet is just one factor. Other important factors include genetics, smoking, physical activity, alcohol consumption, and environmental exposures.

## Frequently Asked Questions

### What is the Empirical Dietary Inflammatory Pattern (EDIP)?

The EDIP is a dietary pattern score developed by Tabung and colleagues in 2016. It is based on 18 food groups that most predict pro-inflammatory markers such as IL-6, TNF-α, and CRP. A higher EDIP score means a diet with greater potential to promote inflammation in the body. It has been validated in three Harvard cohorts.

### How much does a pro-inflammatory diet raise cancer risk?

In a meta-analysis of 24 prospective cohort studies with over 2.6 million participants, people with the highest EDIP adherence had a 10% higher risk of total cancer compared with those with the lowest adherence. They also had a 19% higher risk of colorectal cancer and a 48% higher risk of liver cancer.

### Does a pro-inflammatory diet affect the risk of dying from cancer?

Yes. The same meta-analysis found that people with the highest EDIP adherence had an 18% higher risk of dying from cancer compared with those with the lowest adherence. This suggests that diet-related inflammation may influence not only whether cancer develops but also survival after diagnosis.

### Were all cancer types affected by a pro-inflammatory diet?

No. The meta-analysis found no significant link between higher EDIP adherence and ovarian or endometrial cancer risk. The strongest association was for liver cancer, followed by colorectal cancer. This suggests that the effect of diet-related inflammation may differ by cancer type.

### What are the limitations of this research?

All included studies were conducted in the United States, so findings may not apply elsewhere. Diet was assessed by food frequency questionnaires or 24-hour recalls, which rely on memory and can introduce error. The studies showed moderate heterogeneity, and residual confounding is possible. Some cancer types were examined in only one study.

### Can reducing dietary inflammation lower my cancer risk?

The meta-analysis cannot prove cause and effect because it is observational. However, the consistent association across 24 studies suggests that reducing the inflammatory potential of your diet may be beneficial. Discuss your individual cancer risk and diet with your healthcare provider before making changes.

### What should I do with this information?

Be aware that some foods promote inflammation and others reduce it. Focus on overall dietary patterns rather than single nutrients. If you have a family history of cancer or other risk factors, talk to your doctor about how diet might affect your risk. Stay informed as more research on the EDIP becomes available.

### If a pro-inflammatory diet is linked to higher cancer risk, when should someone with cancer or a strong family history seek a second opinion?

A second opinion can be useful when you want your individual risk and situation reviewed against this evidence. A pro-inflammatory dietary pattern is associated with a 10% higher risk of total cancer, a 19% higher risk of colorectal cancer, a 48% higher risk of liver cancer, and an 18% higher risk of dying from cancer, with no significant link for ovarian or endometrial cancer. Because these are population-level associations from observational studies, they cannot predict any one person's outcome. Diagnostic Detectives Network provides independent expert second opinions.

## Source Information

**Original article title:** The association between empirical dietary inflammatory pattern and risk of cancer and cancer-specific mortality: a systematic review and meta-analysis of prospective cohort studies.

**Authors:** Fatemeh S. Hosseini, Ali Nikparast, Elahe Etesami, Fatemeh Javaheri-Tafti, and Golaleh Asghari.

**Affiliations:** Department of Nutrition, Science and Research Branch, Islamic Azad University, Tehran, Iran; Department of Clinical Nutrition & Dietetics, Faculty of Nutrition Science and Food Technology, Shahid Beheshti University of Medical Sciences, Tehran, Iran; Cancer Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran.

**Journal:** Frontiers in Nutrition, volume 11, article 1462931.

**Publication date:** 18 October 2024.

**DOI:** 10.3389/fnut.2024.1462931

**Systematic review registration:** PROSPERO registration no. CRD42024496912.

**Funding and conflicts of interest:** The original article is published as open access under the Creative Commons Attribution License (CC BY).

*This patient-friendly article is based on peer-reviewed research. It is intended for educational purposes only and should not replace professional medical advice. Always consult your healthcare provider about your individual health concerns.*


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