Evidence map›Paper›PMID 41256918›Full record

ArticleFrontiers in nutrition2025

Patterns of meat and vegetable consumption among community-dwelling adults aged 18 years and older in China.

Xiaojing Deng, Hui Cheng, Wenjun Wang, Yalin Hong, Xin Yuan, Huiqing Xu, Yunting Xu, Guofeng Ao, Jian Xu, Yeping Bian and 1 more

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Article in Frontiers in nutrition, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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4 · The record

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5 · Who and what money

Authors and funding

11 authors.

Xiaojing Deng *Geriatric Hospital of Nanjing Medical University, Nanjing, China.
Hui Cheng *Geriatric Hospital of Nanjing Medical University, Nanjing, China.
Wenjun Wang *Geriatric Hospital of Nanjing Medical University, Nanjing, China.
Yalin HongGeriatric Hospital of Nanjing Medical University, Nanjing, China.
Xin YuanJiangsu University School of Medicine, Zhenjiang, China.
Huiqing XuNanjing Municipal Center for Disease Control and Prevention, Nanjing, China.
Yunting XuNanjing Municipal Center for Disease Control and Prevention, Nanjing, China.
Guofeng AoNanjing Municipal Center for Disease Control and Prevention, Nanjing, China.
Jian XuGeriatric Hospital of Nanjing Medical University, Nanjing, China.
Yeping BianGeriatric Hospital of Nanjing Medical University, Nanjing, China.
Qing YeNanjing Municipal Center for Disease Control and Prevention, Nanjing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Meat and vegetable consumption was each vital for maintaining human health condition. Periodic surveillance and assessment of population-level meat and vegetable consumption are critically important for tailored healthy eating intervention. The primary aim of this study was to investigate the consumption patterns of meat and vegetables among community-dwelling adults in regional China in 2023. Methods: A cross-sectional survey was conducted in the first year of the post-COVID-19 pandemic in Nanjing Municipality of China. Participants were those residents aged 18 years or above and randomly selected from the whole municipality. The recommendations recently released by the China Nutrition Society in 2022 were used to assess participants' meat and vegetable consumption level. Logistic regression models were used to identify potential influencing factors of meat and vegetable consumption. Results: Among the 60,945 participants analyzed, the medians of meat and vegetable consumption were 700.0 g/wk (interquartile range = 375.0, 1,100) and 200.0 g/d (interquartile range = 100.0, 300.0), respectively. Moreover, 13.7% (95%CI = 13.4, 13.9), 18.1% (95%CI = 17.8, 18.5), and 68.2% (95%CI = 67.8, 68.6) of participants consumed meat under, within, and beyond the recommended level, respectively, whereas 71.1% (95%CI = 70.7, 71.4) and 28.9% (95%CI = 28.6, 29.3) consumed vegetables under and reaching the recommended level, respectively. Selected socio-demographic characteristics, lifestyle and behaviors, and chronic conditions were associated with meat and vegetable consumption. Conclusion: A large proportion of community-dwelling adults consumed meat exceeding the recommended level, whereas a small proportion consumed vegetables reaching the recommended level in regional China in 2023. Moreover, disparities of meat and vegetable consumption existed in socio-demographic characteristics, lifestyle and behaviors, and selected chronic conditions. However, no causality could be inferred due to the nature of the cross-sectional study. For future tailored population-level interventions of healthy eating of meat and vegetables, particular attention should be paid to participants' socio-demographic characteristics, lifestyle and behaviors, and specific chronic conditions.

Indexed as

adultsChineseconsumption patternmeatvegetable

Identifiers

PMID41256918
PMCPMC12620413

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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.