Evidence map›Paper›PMID 38351960›Full record

ArticleFrontiers in public health2024

Nutritional knowledge, attitudes, and practices among residents in the Northeast areas of China during the COVID-19 epidemic.

Liyan Hou, Xueyan Xia, Ying Du, Yu Zhang, Shuangshuang Li, Wen Liu, Jie Zhao, Ke Wang, Lei Zhang, Qingshan Wang

Open access · goldAbstract read
In one paragraph

Article in Frontiers in public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.6field-weighted citation impact, top 35% of its field
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

2 citing papers in PubMed, 1 citations in OpenAlex.

  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

10 authors at 1 institution in 1 country.

Liyan Hou *Dalian Medical University Library, Dalian, China.
Xueyan Xia *Dalian Medical University Library, Dalian, China.
Ying Du *Dalian Municipal Center for Disease Control and Prevention, Dalian, China.
Yu ZhangNational-Local Joint Engineering Research Center for Drug-Research and Development (R&D) of Neurodegenerative Diseases, Dalian Medical University, Dalian, China.
Shuangshuang LiDalian Xinyulong Marine Organisms Seed Industry Technology Co., Ltd, Dalian, China.
Wen LiuDalian Xinyulong Marine Organisms Seed Industry Technology Co., Ltd, Dalian, China.
Jie ZhaoNational-Local Joint Engineering Research Center for Drug-Research and Development (R&D) of Neurodegenerative Diseases, Dalian Medical University, Dalian, China.
Ke WangDepartment of Clinical Nutrition, Second Affiliated Hospital of Dalian Medical University, Dalian, China.
Lei ZhangDalian Medical University Library, Dalian, China.
Qingshan WangNational-Local Joint Engineering Research Center for Drug-Research and Development (R&D) of Neurodegenerative Diseases, Dalian Medical University, Dalian, China.
Dalian Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The coronavirus disease 2019 (COVID-19) due to SARS-CoV-2 infection continues to affect the daily life of communities worldwide. Nutrition is a vital determinant of overall health. Given the lack of specific drugs for COVID-19 and incomplete vaccination coverage, optimizing nutrition appears to be one of the most cost-effective means of enhancing immunity. Therefore, this study was designed to evaluate nutrition-related knowledge, attitudes, and practices (KAP) to offer insights into the personal determinants of dietary behavior during COVID-19 pandemic in four major cities within the Northeast region. Methods: This cross-sectional study was conducted between January and December 2022 using a self-administered questionnaire. The data were entered in EpiData V-3.02 and analyzed using SPSS version 26. Binary logistic regression analysis was also employed to examine the association between dependent and independent variables. Results: A total of 4,092 respondents were included in the study. Most of the respondents demonstrated had inadequate nutrition knowledge, 26% of them provided ≥60% of correct answers. About one-third of the respondents were knowledgeable about the daily levels of oil, salt, milk, water, vegetables and fruits for adults. Furthermore, our results showed that 60.6% of participants held positive attitudes toward healthy eating. Additionally, only 54.6% of the participants have heathy dietary practices during COVID-19 pandemic. Binary logistic regression analysis showed that the following characteristics were associated with displaying unhealthy dietary behaviors: being men, having a lower education level, having a family income of 10,000-19,999 and more than 20,000, being resided in Harbin, Shenyang, and Changchun. Importantly, the strongest associations were observed between poor dietary knowledge and unhealthy eating behaviors. Similarly, dietary attitudes were strongly associated with healthy dietary behaviors when the effects of other factors were excluded; responders with negative attitudes were more likely to exhibit unhealthy eating behaviors. Conclusion: Our findings suggest that residents in the Northeast China possessed a relatively low level of nutritional knowledge, which directly influenced their dietary practices during the COVID-19 pandemic. This study provides valuable insights into the cross-sectional description and key factors related to nutrition-related KAP, serving as a basis for future policymaking to respond more effectively to health crises.

Indexed as

COVID-19AdultChinaCross-Sectional StudiesFemaleHealth Knowledge, Attitudes, PracticeHumansMalePandemicsSARS-CoV-2and practicesattitudesCOVID-19 pandemicdietary behaviorknowledgenutritionSARS-CoV-2

Identifiers

PMID38351960
PMCPMC10861797
OpenAlexW4391358993

What OpenQuestion 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 OpenQuestion graph.