Evidence map›Paper›PMID 36771475›Full record

ArticleNutrients2023

Protein-Balanced Dietary Habits Benefit Cognitive Function in Japanese Older Adults.

Keisuke Sakurai, Erika Okada, Saya Anzai, Risako Tamura, Izumi Shiraishi, Noriko Inamura, Satoru Kobayashi, Mikako Sato, Takashi Matsumoto, Kazuyuki Kudo and 2 more

Abstract read
In one paragraph

Article in Nutrients, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
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

12 authors.

Keisuke SakuraiDepartment of Integrated Biosciences, Graduate School of Frontier Sciences, The University of Tokyo, Kashiwa 277-8562, Japan.
Erika OkadaDepartment of Integrated Biosciences, Graduate School of Frontier Sciences, The University of Tokyo, Kashiwa 277-8562, Japan.
Saya AnzaiDepartment of Integrated Biosciences, Graduate School of Frontier Sciences, The University of Tokyo, Kashiwa 277-8562, Japan.
Risako TamuraDepartment of Integrated Biosciences, Graduate School of Frontier Sciences, The University of Tokyo, Kashiwa 277-8562, Japan.
Izumi ShiraishiDepartment of Integrated Biosciences, Graduate School of Frontier Sciences, The University of Tokyo, Kashiwa 277-8562, Japan.
Noriko InamuraUrban Design Center Kashiwanoha (UDCK), Kashiwa 277-0871, Japan.
Satoru KobayashiCommunity Health Promotion Laboratory, Mitsui Fudosan, Co., Ltd., Kashiwa 277-8519, Japan.
Mikako SatoResearch & Development Center, NH Foods Ltd., Tsukuba 300-2646, Japan.
Takashi MatsumotoResearch & Development Center, NH Foods Ltd., Tsukuba 300-2646, Japan.
Kazuyuki KudoLifestyle Research Office, NH Foods Ltd., Shinagawa, Tokyo 141-6014, Japan.
Yukihiro SugawaraResearch & Development Center, NH Foods Ltd., Tsukuba 300-2646, Japan.
Tatsuhiro HisatsuneDepartment of Integrated Biosciences, Graduate School of Frontier Sciences, The University of Tokyo, Kashiwa 277-8562, Japan.ORCID 0000-0002-8580-9874

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Since daily dietary habits can affect cognitive function, dietary patterns such as the Mediterranean-DASH Intervention for Neurodegenerative Delay diet have been proposed as interventions to slow cognitive decline. However, because dietary habits vary widely among different food cultures, it is necessary to establish dietary pattern intervention methods that are appropriate for each population. Therefore, in this study, the dietary patterns of elderly Japanese individuals were classified using cluster analysis, and their relationship with cognitive function was investigated. We then modeled the dietary patterns and applied them to another cohort of elderly Japanese individuals to determine whether differences in dietary patterns could predict cognitive decline. One hundred and fifty older adults ≥ 65 years of age in the community were recruited. Their daily food intake and cognitive function were measured using the brief-type self-administered diet history questionnaire and Montreal Cognitive Assessment, respectively. K-means cluster analysis identified a high-carbohydrate (HC) dietary pattern with high cereal intake and a protein-balanced (PB) dietary pattern with high intake of legumes, vegetables, seafood, meat, and eggs. Cognitive function was significantly higher in the PB group than in the HC group. Furthermore, to classify the new data into HC and PB patterns, a classification model was created by discriminant analysis using food groups with significantly different intakes among dietary patterns. Next, we recruited 267 new older adults ≥ 65 years of age and measured food intake and cognitive function assessed using the memory performance index score. Individuals with cognitive decline were identified and their detailed cognitive functions were assessed using the neurocognitive index score. Cognitive function was significantly impaired in the HC pattern in both the general elderly and cognitively impaired cohorts. These findings suggest that a dietary pattern of low carbohydrate and high protein intake is associated with good cognitive function in elderly Japanese individuals. Classification by these dietary patterns can predict cognitive reservation in community-dwelling older adults.

Indexed as

Cognitive DysfunctionEast Asian PeopleAgedCarbohydratesCognitionDietFeeding BehaviorHumansVegetablesCarbohydratesagingcluster analysisdaily dietary habitsdietary patterndiscriminant analysismild cognitive impairmentmodeling

Identifiers

PMID36771475
PMCPMC9920661

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.