# Inflammation balance: a score for your week of food, and a blood test to check it

10 Nov 2026 · Csanad Novak · 18 min read

*There is no honest anti-inflammatory number for a single food. There is a validated score for a whole diet. Why we chose Emory's Dietary Inflammation Score, what it can and cannot tell you, and how to check it against your own CRP.*

![A week of food. A separate blood check: a week of days scored above and below a line, a diet pattern in fifths, and an hs-CRP blood tube (conceptual illustration)](https://vitalitytracker.app/_emdash/api/media/file/01M70PC39VSHKBKF8GQA5Z95MQ.webp)

For a long time our backlog had an item called "Anti-inflammatory Index for foods". I pictured a small number next to every food: blueberries good, bacon bad, a tidy ranking you could shop by. When I finally sat down to build it, the first thing I had to let go of was that picture.

A reliable anti-inflammatory index for a single food does not exist. Every validated measure I could find scores a whole diet, usually over weeks, against blood markers of inflammation. The per-food ratings some apps show are proprietary and, as far as I can tell, unvalidated. A number on each food would have been our own invention dressed up as science, and that is exactly the kind of thing Vitality Tracker exists to avoid.

What does exist, and what we have now built, is a validated score for your diet: the **Dietary Inflammation Score** from Emory University, which members see as **Inflammation balance**. This post is the long version of why we built it, why we chose that score over the better-known one, where it is strong, where it is weak, how we implemented it, and how I think you should read it.

## Why inflammation, and why food

Inflammation is how the body responds to injury and infection. Acute inflammation is meant to switch off when the job is done. The kind that matters here is different: low-grade, chronic, systemic inflammation that never quite switches off. A 2019 review in *Nature Medicine* gathered the evidence that this smouldering state runs through many of the chronic diseases of later life, including cardiovascular disease, type 2 diabetes, several cancers, kidney disease and neurodegeneration (Furman et al., 2019).

The marker most of us can actually get measured is **high-sensitivity C-reactive protein (hs-CRP)**. Twenty-five years ago it was already one of the strongest predictors of future cardiovascular events in women among the markers tested (Ridker et al., 2000). In 2017 the CANTOS trial went a step further: lowering inflammation with a drug, with cholesterol unchanged, reduced recurrent cardiovascular events in people who had already had a heart attack (Ridker et al., 2017). That trial did not make inflammation the whole story, but it moved it from "a marker that travels with risk" to "part of the mechanism".

So where does food come in? Diet is one of the few inputs to that system you change every day. In a two-year randomised trial in people with the metabolic syndrome, a Mediterranean-style diet lowered hs-CRP and IL-6 compared with a control diet (Esposito et al., 2004). That group also lost more weight, which is part of the effect, and I will come back to that. A meta-analysis of 17 trials and about 2,300 people found Mediterranean-style diets lowered hs-CRP by about 1 mg/L on average compared with control diets, although the trials differed a lot from each other (Schwingshackl and Hoffmann, 2014).

That is the case for paying attention to the inflammatory side of your diet: it is part of how food relates to long-term disease, it responds to what you eat, and you can measure it.

## Why it fits what Vitality Tracker is for

I keep coming back to three tests for anything we put in front of members. Is it **informative** about you, not about an average person? Is it **actionable**, meaning there is something concrete you can change? And can you **verify** it, so you are not taking our word for it? Most nutrition scores fail at least one of these. This one passes all three, which is why it went from a backlog item to a feature.

- **Informative.** It does not just say "your diet is inflammatory". It says which food groups pushed your week up or down, by how much, and compared with whom.
- **Actionable.** Every lever is a food group you can see in your own log: tomatoes, berries, processed meat, refined grains, added sugar. "Have more tomatoes and fewer sausages" is something you can do at the supermarket this week.
- **Verifiable.** The score was built against inflammation markers in blood, and the main one, hs-CRP, is a cheap, routine test. You can take one before you change anything and another after a few months, and see whether your own number moved.

That last point matters most to me. A score you cannot check against your own body is just an opinion with decimals.

## What we looked at

I went through the literature looking for something with a published method, validated against inflammation markers, and usable with the food data we actually have: generic foods from national tables, branded products, recipes, and photos turned into meals. These were the serious candidates.

**The Dietary Inflammatory Index (DII).** By far the best known, with hundreds of studies behind it. It scores up to 45 parameters, mostly nutrients (fibre, fats, vitamins, minerals) plus flavonoids and some specific foods and spices, against global mean intakes, with each parameter weighted by the published literature (Shivappa et al., 2014; Hébert et al., 2019). An umbrella review of 15 meta-analyses found the evidence "convincing" only for heart attack; for most other outcomes it was weaker (Marx et al., 2021). Two practical problems ruled it out for now. First, its name is a registered trademark of the University of South Carolina and it is licensed commercially; using the method under another name would still be taking someone else's work. Second, it needs nutrients that branded foods and photo estimates simply do not carry (flavonoids, for instance), so it would be thinnest exactly where members log most.

**The Empirical Dietary Inflammatory Pattern (EDIP).** From Harvard, built by regressing 39 food groups on CRP, IL-6 and a TNF receptor in US nurses, and kept to the 18 that predicted them best (Tabung et al., 2016; Tabung et al., 2017). It is food-based, which I liked, but the weights carry the fingerprints of one questionnaire in one population. Pizza and beer come out on the anti-inflammatory side; tomatoes on the pro-inflammatory side. Tested in a Brazilian population, it was not associated with inflammation markers at all (Norde et al., 2020). I could not put a score in front of members that tells them pizza is anti-inflammatory and expect them to trust anything else we say.

**The Anti-Inflammatory Diet Index (AIDI).** From Sweden: a points score of foods that related to hs-CRP in Swedish women, later linked with lower mortality in two Swedish cohorts (Kaluza et al., 2018; Kaluza et al., 2019). Simple and transparent, and a reasonable fallback, but built for a Nordic diet and a Nordic questionnaire.

**The Dietary Inflammation Score (DIS).** From Emory University (Byrd et al., 2019). This is the one we chose.

## Why we chose the Dietary Inflammation Score

The DIS takes 18 food groups plus a supplement score. Its developers fitted the weights against a panel of four inflammation markers measured together (hs-CRP, IL-6, IL-8 and IL-10), so each weight reflects how strongly that food group related to the overall inflammatory picture, not to one marker. Then they tested it.

In the REGARDS cohort, 14,210 US adults who were not part of the fitting, people in the highest fifth of the DIS had 1.66 times the odds of high CRP compared with the lowest fifth. In the same data the DII came in at 1.56 times and EDIP at 1.32 times (Byrd et al., 2019).

A few things made it the right choice for us:

- **It is food-based.** A branded muesli bar, a photo of a lasagne and your own recipe can all be described as food groups. That is not true of a 45-nutrient profile.
- **The method and the weights are published,** and I found no trademark, patent or licence on using them. We cite the paper and use our own name for the feature, so it does not read as Emory's product.
- **It has been used outside its developers' group:** in the US, Italy, the Netherlands, Iran and Australia. A 2025 review of 43 food-based inflammation indices named it among the "robust, empirically derived" ones (Reyneke, Lambert and Beck, 2025).
- **It relates to outcomes, not only to markers.** In REGARDS, people in the most pro-inflammatory fifth had a 41 % higher risk of developing type 2 diabetes than those in the least, the strongest association of the diet scores tested (Tison et al., 2022), and a 32 % higher risk of dying from any cause over follow-up (Troeschel et al., 2022). In the Iowa Women's Health Study, about 33,000 women followed for decades, the most pro-inflammatory fifth had an 11 % higher risk of death from any cause (Li et al., 2021). In Italy's Moli-sani study it has been linked with older biological age and poorer cognition (Martínez et al., 2023; Bracone et al., 2025).

The direction also agrees with everything else we know. Across 43 indices, fruit, vegetables, whole grains and legumes always come out on the favourable side, and red and processed meat and added sugar on the unfavourable side (Reyneke, Lambert and Beck, 2025). The DIS keeps that direction, except that it leaves whole grains out. More on that below.

## The limitations, upfront

I want to be as clear about the weaknesses as about the strengths, because some of them change how you should read your number.

**It is young.** The paper is from 2019. When I checked in November 2026, about 25 papers on PubMed named it, against more than 200 for the DII, and there was no meta-analysis of it yet.

**It was fitted on 639 people.** The weights come from a subsample of one US cohort of older adults, and most of the "validation" happened in the rest of that same cohort plus two smaller populations. That is normal for a new index, but it is not the same as years of independent replication.

**The head-to-head comparison flatters it.** The DIS predicts CRP better than the DII and EDIP partly because its weights were fitted to the same kind of biomarker panel it is then tested on. That is not an independent contest, and I am treating it accordingly.

**Diet is the weaker half of the story.** The same paper introduced a lifestyle score built from body weight, physical activity, alcohol and smoking. Again and again that score shows the stronger effects. In a Dutch bladder cancer cohort, each point of the lifestyle score went with 43 % higher hs-CRP, against 6 % for each point of the diet score (Kiebach et al., 2026). In the Iowa women, the most pro-inflammatory fifth for lifestyle had a 60 % higher risk of death from any cause, against 11 % for diet (Li et al., 2021). Food matters, but your weight, your activity, your drinking and whether you smoke matter more to your CRP.

**Some results are null.** I am including them because the positive ones are not the whole picture:

- In Iran, the DIS was not associated with chronic kidney disease, although two other inflammation scores were (Farhadnejad et al., 2023).
- In Australia, it was not associated with cardiovascular risk factors, apart from overweight in rural areas (Alston et al., 2023).
- In the Iowa women, it was not associated with colorectal cancer (Gao et al., 2022).
- It was not associated with colon cancer recurrence (Wesselink et al., 2025) or bladder cancer recurrence (Kiebach et al., 2026).
- In a large US cohort, results for diabetes, high blood pressure and kidney disease were mixed (Ramezankhani, Hadaegh and Asghari, 2026).

**It is observational.** These are associations in large groups of people. They do not prove that changing your diet will change your inflammation by any particular amount. The trials above show that diets in this direction can lower CRP, but the DIS itself has not, as far as I found, been tested in a trial.

**It has quirks, and we kept them.** The DIS was built from a food-frequency questionnaire, and some of its groupings reflect that questionnaire rather than biology:

- **Olive oil sits with butter and margarine** under "other fats", so adding oil raises the score. That is a feature of how the questionnaire grouped added fats, not a finding that olive oil is inflammatory.
- **Whole grains, soy and shellfish are left out entirely.** The authors dropped soy and shellfish because too few people in the cohort ate them weekly, and whole grains because the questionnaire measured them poorly. Eggs and alcohol are not in the food groups either. When I first saw oats, edamame and prawns count toward nothing, I was surprised too.
- **Potatoes count with refined grains.**
- **Red meat is almost neutral** (a weight of +0.02), while **processed meat** carries one of the largest weights (+0.68).

I seriously considered "fixing" some of these: putting whole grains back in, moving olive oil out. I decided not to. The weights were validated as a set. Change them and it is no longer the validated score; it is our opinion with the paper's name on it. So we use it **as published**, with one exception that I explain next, and we say plainly in the app which foods count toward nothing and why.

**We left out the supplement score.** The DIS has a 19th component for vitamin and mineral supplements, which carries the largest single weight. Our supplement log records one active ingredient per product, and a member who simply does not log supplements would look like a non-user. Rather than guess, we use the paper's own variant without supplements. If you take a multivitamin, the score does not see it.

**It is not a measure of inflammation in you.** It describes a diet pattern that studies have linked with higher or lower inflammation markers. The only way to know your own inflammation is a blood test.

## How we built it

This was more work than the formula suggests, because the formula assumes you already know how many servings of tomatoes are in a pizza.

### Every food, split into food groups

The DIS counts **servings a day** of each group. A tomato is easy. A pizza is refined grains (the base), tomatoes (the sauce), high-fat dairy (the cheese), processed meat (the ham) and other fats (the oil). The original study split mixed dishes like this with a US food-equivalents database. We had to do the same for every food in our tables.

We took all 18,070 foods in New Zealand's FOODfiles, the Australian Food Composition Database and the USDA tables (SR Legacy, Foundation Foods and the survey foods), and split each one into servings per 100 g of each of the 18 groups. An AI model did the splitting, in one pass, working from each food's name and its nutrients as cross-checks: the fat content bounds the added fat, water and energy tell a dried food from a cooked one, and so on. We defined each serving explicitly: 75 g of vegetables (40 g of salad leaves), 150 g of fruit, 90 g of cooked legumes, 85 g of cooked meat or fish, 40 g of processed meat, a 4 g teaspoon of added sugar, 250 g of milk or 40 g of cheese, a cup of coffee or tea, 30 g of nuts, a 5 g teaspoon of added fat, and 30 g of bread or 75 g of cooked rice or pasta.

Added sugar comes from the tables' own figures wherever they have one. New Zealand's and Australia's tables do. For the US survey foods we took it from the USDA's Food Patterns Equivalents Database (FPED), which gives an added-sugar figure for every one of them.

Then we checked the model's splits against the USDA's own split of the same foods. FPED does for the 5,430 US survey foods what we did for all of ours. The two agreed on whether a food contains a group 91 to 99 % of the time, depending on the group, and the amounts correlated at 0.73 to 0.97. Where the levels differ, the reasons are known: FPED counts only the lean part of meat, puts cream and cream cheese with solid fats rather than dairy, and counts shellfish as fish.

Branded products and the foods members create take their groups from their food group and name: a branded apple counts as apples and berries, butter as other fats. A branded ready meal cannot be split that way, so only its added sugar counts, and its energy is reported as "not placed" rather than quietly counted as zero.

### Against whom?

A z-score needs a population: how many servings of tomatoes is a lot? The paper standardised to its own participants and does not publish those averages, and every later study did the same with its own. So the population was our choice. I chose **US adults from NHANES 2021–2023**, the US national nutrition survey.

The reason is rather practical. NHANES is a large, recent, public survey in which every food each participant ate is coded with the same USDA food codes we already hold. So we could score NHANES participants through exactly the same food splits as members, and the units match by construction. Every food the participants reported mapped to a food in our tables.

We used the 4,253 adults aged 20 and over with two complete days of dietary recall, excluding pregnant women: 1,873 men and 2,380 women, weighted to represent the US population. For scale, they average about 16 teaspoons of added sugar, 0.7 servings of processed meat and 1.8 cups of coffee or tea a day. You are compared with people of your own sex, or with all adults if you have not set it.

Two days of recall vary more than a usual week of eating, so the reference spreads a little wider than it would with more days. That pulls members' scores slightly towards the middle: the cautious direction.

### The calculation

For each food group: your servings a day, minus the reference average, divided by the reference spread, times the published weight. The score is the sum of the 18. Below zero is more anti-inflammatory than the average US diet, above zero more pro-inflammatory. On its own, the number means little to anyone, so we show where it falls in **fifths** of the reference.

## What you see

![From a week of food to a pattern you can check: log your week (18 food groups, at least 4 counted days), see the diet pattern in fifths of US adults (your sex, where set), then check your hs-CRP at a baseline and again after 12 or more weeks. The score describes your diet; it does not measure inflammation in your body.](https://vitalitytracker.app/_emdash/api/media/file/01M70PC3QACSWTS46NFAYKHDPS.webp)

**The week (the web's Report, and Analyse on the phone).** The headline is the week, because the score was built on usual intake, not single meals.

- **Where it sits:** in fifths of US adults' diets for your sex, on a scale from "More anti-inflammatory" to "More pro-inflammatory". For example: "More anti-inflammatory than most of US women's diets".
- **What moved it:** the three food groups that lowered your score most and the three that raised it most, each against the population, for example: "Processed meats: having more than the US men population: 1.4 servings a day, against their average of 0.7". A group can raise your score by being eaten more (processed meat) or less (apples and berries) than the population, so read the "more" or "less".
- **Each day's share of the week.** The week's score is the average of its days, so each day shows as what it added, not as a verdict on its own.
- **How much of the week's energy could be placed** in the food groups.

A day counts toward the week once it is done and at least half of its energy is in foods or recipes (a day logged only as totals from another app cannot be placed). Today counts once it is done: half a day would read as a day of eating very little. The week needs four counted days before it shows a score; until then it tells you how many count so far.

![Inflammation balance for a week in the phone's Meals Analyse: among the most anti-inflammatory fifth of US men's diets, 7 of 7 days counted. Apples and berries, other vegetables, and nuts and peanut butter lowered the week's score most; deep yellow or orange vegetables and fruit, and high-fat dairy, raised it most. Each day's share of the score is shown below.](https://vitalitytracker.app/_emdash/api/media/file/01M70PC440HNZ8NRP9HFW9XRTR.webp)

**A day (the Day summary and Analyse).** You see the same picture for a single day, as eaten or, in Analyse, as planned. A day is placed among single days of the reference, not among weeks, because one day varies much more than a week, and the same score would otherwise look more extreme than it is. Each day says so: one day varies a lot, and the week is the steadier read. The planned day is the one I find most useful. It lets you see before you shop that tomorrow's plan of pizza and bacon sits in the fourth fifth, mostly because of processed meat.

**A food.** Each food's detail now says which groups it counts as and which way each pushes the score: "Counts as refined grains and starchy vegetables (raises), processed meats (raises) and tomatoes (lowers)". There is deliberately no score per food. A food in no group says why: whole grains, eggs, soy, shellfish and alcohol are not part of the score.

## How I would read it

**Read the week, not the day.** A single day tells you about that day's choices. The week is what the score was built for.

**Read the lists, not just the fifth.** The fifth tells you where you are. The two lists tell you why, and what you could change. If "Tomatoes: having less than the US women population" sits at the top of "raised the week's score most", that is a concrete, cheap change: a piece of tomatoes, or a salad will do.

**Remember who you are compared with.** The middle fifth means "about as inflammatory as the typical US adult diet", which is not a high bar. Moving from the middle towards the anti-inflammatory end is the direction the evidence supports. There is nothing magic about the first fifth.

**Know the quirks.** If olive oil, oats or edamame are a big part of your diet, the score will not reward them, because the published score does not. That is a limit of the instrument, not advice to stop eating them.

**Check it against your blood.** This is the part I care about most:

- **Get a baseline hs-CRP** while you are well: not during or just after a cold, an injury or a very hard training block. The American Heart Association and the CDC describe below 1 mg/L as lower risk, 1 to 3 as average and above 3 as higher. They advise averaging two measurements about two weeks apart, and treating a result above 10 mg/L as a sign of something else (an infection or injury, for instance) to look into and retest, not as a diet signal (Pearson et al., 2003).
- **Change the pattern for at least three months.** The trials in the meta-analysis all lasted at least 12 weeks, and the Italian one two years (Schwingshackl and Hoffmann, 2014; Esposito et al., 2004).
- **Retest under the same conditions** and compare.
- **Remember the bigger levers.** Weight, activity, alcohol and smoking move CRP more than diet does (Kiebach et al., 2026; Li et al., 2021). If your CRP moves, the food may be only part of why; if your weight changed as well, it probably is. That is fine. You are measuring your inflammation, not the score's.

None of this is medical advice. A raised CRP can have many causes, and your doctor should be the one to interpret it.

## What comes next

Eir will explain your week from these figures, in the same register: patterns in the diet and what the studies found, never diagnosis or treatment. Further out, the same paper's lifestyle score (weight, activity, alcohol and smoking) is the stronger half of the story, and VT already has most of what it needs. I would like to bring the two together. In the paper, people in the top fifth of both scores had more than seven times the odds of high CRP. That probably belongs alongside Playbooks rather than in Meals, and it is not decided yet.

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7. Bracone F, Gialluisi A, Bonaccio M, Costanzo S, Persichillo M, De Curtis A, et al. Exploring the correlation between pro-inflammatory dietary and lifestyle patterns and cognitive function: cross-sectional results from the Moli-sani study. *Journal of Affective Disorders*. 2025;393(Pt A):120216. [doi:10.1016/j.jad.2025.120216](https://doi.org/10.1016/j.jad.2025.120216)
8. Farhadnejad H, Teymoori F, Jahromi MK, Mokhtari E, Asghari G, Mirmiran P, et al. High dietary and lifestyle inflammatory scores are associated with increased risk of chronic kidney disease in Iranian adults. *Nutrition Journal*. 2023;22(1):1. [doi:10.1186/s12937-023-00835-y](https://doi.org/10.1186/s12937-023-00835-y)
9. Alston L, Nichols M, Allender S, Versace V, Brown LJ, Schumacher T, et al. Dietary patterns in rural and metropolitan Australia: a cross-sectional study exploring dietary patterns, inflammation and association with cardiovascular disease risk factors. *BMJ Open*. 2023;13(6):e069475. [doi:10.1136/bmjopen-2022-069475](https://doi.org/10.1136/bmjopen-2022-069475)
10. Wesselink E, Kok DE, Smit KC, van Lanen AS, Derksen JWG, Koopman M, et al. Dietary and lifestyle inflammation scores in relation to colon cancer recurrence in subgroups of patients based on common molecular tumour characteristics. *ESMO Gastrointestinal Oncology*. 2025;9:100202. [doi:10.1016/j.esmogo.2025.100202](https://doi.org/10.1016/j.esmogo.2025.100202)
11. Kiebach J, Kamps CSAD, Wesselink E, Aben KKH, van der Heijden AG, van Duijnhoven FJB, et al. Lifestyle and dietary inflammation scores and risks of recurrence and progression among patients with non-muscle invasive bladder cancer. *Nutrition*. 2026;151:113354. [doi:10.1016/j.nut.2026.113354](https://doi.org/10.1016/j.nut.2026.113354)
12. Ramezankhani A, Hadaegh F, Asghari G. Association of novel dietary and lifestyle inflammation scores with the incidence of diabetes, hypertension and chronic kidney disease among adults: results from a large US cohort with 12-year follow-up. *BMJ Open*. 2026;16(1):e105923. [doi:10.1136/bmjopen-2025-105923](https://doi.org/10.1136/bmjopen-2025-105923)

### Data we used to build it

1. Centers for Disease Control and Prevention, National Center for Health Statistics. National Health and Nutrition Examination Survey, August 2021–August 2023: Dietary Interview, Individual Foods, first and second day (DR1IFF_L, DR2IFF_L); Demographic Variables and Sample Weights (DEMO_L). [wwwn.cdc.gov/nchs/nhanes](https://wwwn.cdc.gov/nchs/nhanes/continuousnhanes/default.aspx?Cycle=2021-2023)
2. U.S. Department of Agriculture, Agricultural Research Service. Food and Nutrient Database for Dietary Studies 2021–2023, via FoodData Central survey foods (release of 31 October 2024). [fdc.nal.usda.gov](https://fdc.nal.usda.gov/download-datasets/)
3. U.S. Department of Agriculture, Agricultural Research Service. Food Patterns Equivalents Database 2021–2023 (FPED). [ars.usda.gov](https://www.ars.usda.gov/northeast-area/beltsville-md-bhnrc/beltsville-human-nutrition-research-center/food-surveys-research-group/docs/fped-databases/)
4. U.S. Department of Agriculture, Agricultural Research Service. FoodData Central: SR Legacy and Foundation Foods. [fdc.nal.usda.gov](https://fdc.nal.usda.gov)
5. The New Zealand Institute for Plant & Food Research Limited and the Ministry of Health (New Zealand). New Zealand FOODfiles 2024. [foodcomposition.co.nz](https://www.foodcomposition.co.nz)
6. Food Standards Australia New Zealand. Australian Food Composition Database, Release 3. Canberra: FSANZ; 2025. [foodstandards.gov.au](https://www.foodstandards.gov.au/science-data/food-nutrient-databases/afcd)

### On the Dietary Inflammatory Index's trademark and licence

1. University of South Carolina, Arnold School of Public Health. News release on Connecting Health Innovations, 2015. [sc.edu](https://www.sc.edu/study/colleges_schools/public_health/about/news/2015/chi_grant.php)
2. Dietary inflammatory index. *Wikipedia*. [en.wikipedia.org](https://en.wikipedia.org/wiki/Dietary_inflammatory_index)
3. Conflict-of-interest disclosure on the DII's licensing, *Nutrients*. 2019;11(7):1639. [mdpi.com](https://www.mdpi.com/2072-6643/11/7/1639)

Vitality Tracker describes patterns in what you log. It does not diagnose or treat anything; talk to your doctor about your results.

Source: https://vitalitytracker.app/blog/inflammation-balance