Evidence map›Paper›PMID 40108541›Full record

ArticleBMC public health2025

Association between dietary patterns and anemia in older adults: the 2015 China adults chronic diseases and nutrition surveillance.

Pengfei Wang, Qiya Guo, Xue Cheng, Wen Zhao, Hongyun Fang, Lahong Ju, Xiaoli Xu, Xiaoqi Wei, Weiyi Gong, Lei Hua and 3 more

Abstract read
In one paragraph

Article in BMC public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
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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

13 authors.

Pengfei Wang *National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing100050, China.
Qiya Guo *National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing100050, China.
Xue ChengNational Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing100050, China.
Wen ZhaoPeking Union Medical College Hospital, Beijing100050, China.
Hongyun FangNational Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing100050, China.
Lahong JuNational Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing100050, China.
Xiaoli XuNational Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing100050, China.
Xiaoqi WeiNational Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing100050, China.
Weiyi GongNational Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing100050, China.
Lei HuaNational Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing100050, China.
Jiaxi LiNational Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing100050, China.
Xingxing WuNational Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing100050, China.
Li HeNational Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing100050, China. heli@ninh.chinacdc.cn.

Funding

This research funded by The National Key R&D Program project "Research on the Spectrum of Geriatric Diseases in China.(2022YFC3603002) and National Major Public Health Service Project "Chronic Disease and Nutrition Monitoring of Adults in China (2015) 2022YFC3603002
6 · The paper itself

Abstract

backgroundAnemia is a condition that has been affected 1.92 billion people worldwide in 2021, leading physical decline, functional limitation and cognitive impairment. However, there are currently fewer studies focusing on the relationship between anemia and dietary patterns in older adults. This study aimed to analysis the dietary patterns in older adults aged 60 and above in China and their association with anemia.

methodsThe data was obtained from the 2015 Chinese Adults Chronic Diseases and Nutrition Surveillance (2015 CACDNS), dietary information was collected using the food frequency method within the past year, exploratory factor analysis was used to extract dietary patterns, and logistic regression was used to analyze the relationship between dietary patterns and anemia.

resultsA total of 48,955 elderly people were included, and the number of anemia patients was 4,417 (9.02%). Four dietary patterns were categorized by the exploratory factor analysis, two dietary patterns have been found to have a statistically significant relationship with the prevalence of anemia. Compared to the first quintile, the fifth quintile of dietary pattern 2 (DP2), characterized by high intake of rice and flour, fresh vegetables, livestock and poultry meat, aquatic products, was associated with higher prevalence of anemia in older adults (OR = 1.412, 95%CI: 1.273-1.567, P < 0.0001), and the trend test results showed that score of this dietary pattern was associated with higher prevalence of anemia (p for trend < 0.0001). Compared to the first quintile, Dietary Pattern 4 (DP4), rich in fungi and algae, fried dough products, other grains, various beans, and rice and flour, was linked to lower prevalence of anemia of the fifth quintile (OR = 0.768, 95% CI: 0.674-0.874, P < 0.0001). And DP4 score was associated with lower prevalence of anemia (P for trend < 0.0001).

conclusionsThere were differences in dietary patterns among elderly people over 60 in China, and the prevalence of anemia in older adults was related to DP2, and DP4.

Indexed as

AnemiaDietAgedAged, 80 and overChinaChronic DiseaseFemaleHumansMaleMiddle AgedNutrition SurveysPrevalenceAnemiaDietary patternsElderly adults

Identifiers

PMID40108541
PMCPMC11924724

What Socratic holds

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LicenceCC BY
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Registered trials

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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.