Evidence map›Paper›PMID 35205987›Full record

ArticleFoods (Basel, Switzerland)2022

The Impact of COVID-19 on Food Consumption and Dietary Quality of Rural Households in China.

Xu Tian, Ying Zhou, Hui Wang

Open access · goldAbstract read
In one paragraph

Article in Foods (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
7.7field-weighted citation impact, top 3% 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

9 citing papers in PubMed, 29 citations in OpenAlex.

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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

3 authors at 2 institutions in 1 country.

Xu TianCollege of Economics and Management, Academy of Global Food Economics and Policy, China Agricultural University, Beijing 100083, China.ORCID 0000-0002-1070-3581
Ying ZhouCollege of Economics and Management, Nanjing Agricultural University, Nanjing 210095, China.ORCID 0000-0002-7593-3919
Hui WangDepartment of Maternal and Child Health, School of Public Health, Peking University, Xueyuan Rd 38, Haidian District, Beijing 100191, China.ORCID 0000-0002-7639-5702
Nanjing Agricultural University · CNPeking University · CN

Funding

Chinese Universities Scientific Fund 2021TC013
6 · The paper itself

Abstract

The COVID-19 pandemic disrupted the food supply chain and thus threatened the food security of many people, while the impact of the pandemic on food consumption of people living in rural areas is still unknown. This study filled in the research gaps by employing a three-wave food consumption survey from 2019 to 2021 conducted in rural China. We adopted a random effect model and Poisson regression to quantify the short-run and long-run impacts of COVID-19 on rural households' food consumption and dietary quality. We found that rural households increased the consumption of vegetables, aquaculture products and legumes in the short-run, and these changes in consumption behavior even lasted 1 year after lockdown was lifted. However, the positive impact was much smaller in households not engaged in agricultural production. In addition, our results showed that COVID-19 decreased dietary diversity but increased dietary quality for households still engaged in food-related agriculture production. Our study indicated that COVID-19 did not threaten the food security status of rural families in China. On the contrary, rural families, particularly those still engaged in agricultural production, increased the consumption of several foods to strengthen their resistance against the virus.

Indexed as

agricultural productionCOVID-19dietary qualityfood consumption

Identifiers

PMID35205987
PMCPMC8870752
OpenAlexW4211042277

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.