Evidence map›Paper›PMID 41589131›Full record

ArticleJournal of clinical biochemistry and nutrition2026

Development of a questionnaire-based Dietary Inflammatory Index assessment for clinical implementation.

Mamiko Yano, Nao Hasuzawa, Natsumi Maruyama, Lixiang Wang, Mizuki Gobaru, Ayako Nagayama, Kenji Ashida, Hitoshi Obara, Kenta Murotani, Yoshinori Moriyama and 1 more

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In one paragraph

Article in Journal of clinical biochemistry and nutrition, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Mamiko YanoDivision of Endocrinology and Metabolism, Department of Internal Medicine, Kurume University School of Medicine, 67 Asahi-machi, Kurume 830-0011, Japan.
Nao HasuzawaDivision of Endocrinology and Metabolism, Department of Internal Medicine, Kurume University School of Medicine, 67 Asahi-machi, Kurume 830-0011, Japan.
Natsumi MaruyamaDepartment of Clinical Nutrition, Kurume University Hospital, 67 Asahi-machi, Kurume 830-0011, Japan.
Lixiang WangDepartment of Medical Biochemistry, Kurume University School of Medicine, 67 Asahi-machi, Kurume 830-0011, Japan.
Mizuki GobaruDivision of Endocrinology and Metabolism, Department of Internal Medicine, Kurume University School of Medicine, 67 Asahi-machi, Kurume 830-0011, Japan.
Ayako NagayamaDivision of Endocrinology and Metabolism, Department of Internal Medicine, Kurume University School of Medicine, 67 Asahi-machi, Kurume 830-0011, Japan.
Kenji AshidaDivision of Endocrinology and Metabolism, Department of Internal Medicine, Kurume University School of Medicine, 67 Asahi-machi, Kurume 830-0011, Japan.
Hitoshi ObaraSchool of Medical Technology, Kurume University, 67 Asahi-machi, Kurume 830-0011, Japan.
Kenta MurotaniSchool of Medical Technology, Kurume University, 67 Asahi-machi, Kurume 830-0011, Japan.
Yoshinori MoriyamaDivision of Endocrinology and Metabolism, Department of Internal Medicine, Kurume University School of Medicine, 67 Asahi-machi, Kurume 830-0011, Japan.
Masatoshi NomuraDivision of Endocrinology and Metabolism, Department of Internal Medicine, Kurume University School of Medicine, 67 Asahi-machi, Kurume 830-0011, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The rising incidence of chronic metabolic diseases places a significant economic burden on healthcare systems. Although the efficacy of lifestyle interventions has been reported, clinical nutrition typically emphasizes total energy and macronutrient intake without consensus on ideal dietary patterns. The Dietary Inflammatory Index (DII) assesses the inflammatory potential of diets and has been linked to diseases like cardiovascular disease, cancer, and type 2 diabetes. However, DII use in clinical practice is limited by its complexity. In this study, we developed a method to calculate DII scores using a clinically available food frequency questionnaire (FFQ). Thirty healthy volunteers provided 3-day dietary records (DR) and completed the FFQ. Dietitians calculated the intake of 29 nutrients from the DR. A created table of nutrient content per FFQ item enabled nutrient intake and DII score calculation from the FFQ. Statistical analysis showed significant correlations between 27 of 29 nutrient intakes and DII scores from the DR and FFQ. Regression equations were developed to predict actual nutrient intakes from the FFQ. The estimated DII (eDII) calculated using the equations correlated strongly with the DR-derived DII (

Indexed as

chronic metabolic diseasesDietary Inflammatory Index (DII)food frequency questionnaire (FFQ)individualized dietary interventionnutrition

Identifiers

PMID41589131
PMCPMC12832144

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.