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A population-level comparison analysis of red meat, white meat and vegetable consumption among adults aged 60+ years before, during and after the coronavirus disease 2019 pandemic in regional China
Published online by Cambridge University Press: 22 August 2025
Abstract
This study compared red meat, white meat and vegetable consumption before, during and after COVID-19 pandemic among older adults in regional China. Data were collected from urban individuals aged 60+ years in Nanjing municipality in 2018, 2021 and 2023. Differences in food intake frequencies between participants and survey years were examined. Logistic regression models were employed to identify influencing factors of meat, and vegetable consumption. Totally, 13 792 participants were analysed, with 4355, 4622 and 4815 from 2018, 2021 and 2023 surveys, respectively. The mean weekly intake frequency (sd) in 2018, 2021 and 2023 was, separately, 3·85 (sd 2·83), 3·21 (sd 2·90) and 4·71 (sd 3·94) for red meat; 1·38 (sd 1·21), 2·08 (sd 1·90) and 2·73 (sd 2·55) for white meat; and 10·98 (sd 4·84), 10·00 (sd 5·04) and 10·34 (sd 5·04) for vegetable. Moreover, 23·2, 32·6 and 52·3 % of participants met the recommendation for meat intake, while 53·7, 46·8 and 49·6 % reached vegetable intake recommendation before, during and after COVID-19 pandemic, respectively. Meat intake was positively associated with education, marital status and drinking, but negatively associated with age. Additionally, education and marital status were in negative relation to vegetable consumption, while smoking and drinking were positively associated with vegetable intake. The older residents consumed less red meat and vegetable but more white meat during COVID-19 pandemic, and their consumption levels of meat and vegetable went up after the pandemic. These findings highlight the need for targeted interventions to support older adults’ dietary habits during emergency events.
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- © The Author(s), 2025. Published by Cambridge University Press on behalf of the Nutrition Society
Footnotes
Guilin Zhang and Haidi Wu contributed equally to this work.
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