Evidence mapPaperPMID 39138490Full record

ArticleNutrition journal2024

Association between dietary diversity changes and frailty among Chinese older adults: findings from a nationwide cohort study.

Xiao-Meng Wang, Wen-Fang Zhong, Yi-Tian Zhang, Jia-Xuan Xiang, Huan Chen, Zhi-Hao Li, Qiao-Qiao Shen, Dong Shen, Wei-Qi Song, Qi Fu and 8 more

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Article in Nutrition journal, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
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 synthesis or guideline pooled it.

  1. Pooled it
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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

18 authors.

Xiao-Meng Wang *Department of Epidemiology, School of Public Health, Southern Medical University, Guangzhou, Guangdong, 510515, China.
Wen-Fang Zhong *Department of Epidemiology, School of Public Health, Southern Medical University, Guangzhou, Guangdong, 510515, China.
Yi-Tian ZhangDepartment of Hygiene Inspection and Quarantine, School of Public Health, Southern Medical University, Guangzhou, Guangdong, China.
Jia-Xuan XiangDepartment of Epidemiology, School of Public Health, Southern Medical University, Guangzhou, Guangdong, 510515, China.
Huan ChenDepartment of Epidemiology, School of Public Health, Southern Medical University, Guangzhou, Guangdong, 510515, China.
Zhi-Hao LiDepartment of Epidemiology, School of Public Health, Southern Medical University, Guangzhou, Guangdong, 510515, China.
Qiao-Qiao ShenDepartment of Epidemiology, School of Public Health, Southern Medical University, Guangzhou, Guangdong, 510515, China.
Dong ShenDepartment of Epidemiology, School of Public Health, Southern Medical University, Guangzhou, Guangdong, 510515, China.
Wei-Qi SongDepartment of Epidemiology, School of Public Health, Southern Medical University, Guangzhou, Guangdong, 510515, China.
Qi FuDepartment of Epidemiology, School of Public Health, Southern Medical University, Guangzhou, Guangdong, 510515, China.
Jian GaoDepartment of Epidemiology, School of Public Health, Southern Medical University, Guangzhou, Guangdong, 510515, China.
Zi-Ting ChenDepartment of Epidemiology, School of Public Health, Southern Medical University, Guangzhou, Guangdong, 510515, China.
Chuan LiDepartment of Epidemiology, School of Public Health, Southern Medical University, Guangzhou, Guangdong, 510515, China.
Jia-Hao XieDepartment of Epidemiology, School of Public Health, Southern Medical University, Guangzhou, Guangdong, 510515, China.
Dan LiuDepartment of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, Guangdong, China.
Yue-Bin LvChina CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, #7 Panjiayuan Nanli, Chaoyang, Beijing, 100021, China.
Xiao-Ming ShiChina CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, #7 Panjiayuan Nanli, Chaoyang, Beijing, 100021, China. shixm@chinacdc.cn.
Chen MaoDepartment of Epidemiology, School of Public Health, Southern Medical University, Guangzhou, Guangdong, 510515, China. maochen9@smu.edu.cn.

Funding

the China Postdoctoral Science Foundation 2023M741552the Construction of High-level University of Guangdong G623330580the Guangdong Basic and Applied Basic Research Foundation 2023A1515110727the Guangdong Province Universities and Colleges Pearl River Scholar Funded Scheme 2019the Postdoctoral Fellowship Program of CPSF GZC20231054
6 · The paper itself

Abstract

backgroundDietary diversity has been suggested as a potential preventive measure against frailty in older adults, but the effect of changes in dietary diversity on frailty is unclear. This study was conducted to examine the association between the dietary diversity score (DDS) and frailty among older Chinese adults.

methodsA total of 12,457 adults aged 65 years or older were enrolled from three consecutive and nonoverlapping cohorts from the Chinese Longitudinal Healthy Longevity Survey (the 2002 cohort, the 2005 cohort, and the 2008 cohort). DDS was calculated based on nine predefined food groups, and DDS changes were assessed by comparing scores at baseline and the first follow-up survey. We used 39 self-reported health items to assess frailty. Cox proportional hazard models were performed to examine the association between DDS change patterns and frailty.

resultsParticipants with low-to-low DDS had the highest frailty incidence (111.1/1000 person-years), while high-to-high DDS had the lowest (41.1/1000 person-years). Compared to the high-to-high group of overall DDS pattern, participants in other DDS change patterns had a higher risk of frailty (HRs ranged from 1.25 to 2.15). Similar associations were observed for plant-based and animal-based DDS. Compared to stable DDS changes, participants with an extreme decline in DDS had an increased risk of frailty, with HRs of 1.38 (1.24, 1.53), 1.31 (1.19, 1.44), and 1.29 (1.16, 1.43) for overall, plant-based, and animal-based DDS, respectively.

conclusionsMaintaining a lower DDS or having a large reduction in DDS was associated with a higher risk of frailty among Chinese older adults. These findings highlight the importance of improving a diverse diet across old age for preventing frailty in later life.

Indexed as

DietFrailtyAgedAged, 80 and overChinaCohort StudiesEast Asian PeopleFemaleFrail ElderlyGeriatric AssessmentHumansLongitudinal StudiesMaleProportional Hazards ModelsCohort studyDietary diversity changesFrailtyOlder adults

Identifiers

PMID39138490
PMCPMC11320915

What Socratic holds

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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 Socratic graph.