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Impacts of COVID-19 Pandemic on Dietary Consumption among Chinese Residents: Evidence from Provincial-Level Panel Data

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  • Xiaodong Zheng

    (School of Economics, Zhejiang Gongshang University, Hangzhou 310018, China)

  • Yinglin Wang

    (School of Economics, Zhejiang Gongshang University, Hangzhou 310018, China)

  • Yue Zhang

    (School of Economics, Zhejiang Gongshang University, Hangzhou 310018, China)

  • Tinghe Deng

    (Chinese Center for Health Education, Beijing 100011, China)

  • Yuanzheng Yang

    (Rural Development Institute, Chinese Academy of Social Science, Beijing 100732, China)

Abstract

The COVID-19 pandemic has profoundly affected people’s daily lives, including their dietary behaviors. Using a panel data set of 31 provinces from 2015 to 2020, this study employed two-way fixed effects (FE) models to examine the impacts of the COVID-19 pandemic on dietary consumption among Chinese residents. The results showed that the COVID-19 pandemic positively affected residents’ consumption of grain, eggs, dairy, and white meat (poultry and aquatic products), while it had a negative effect on individuals’ red meat consumption in both urban and rural areas. These results were robust to different measures of the COVID-19 pandemic, including the number of confirmed cases, suspect cases, and dead cases. Comparatively, the changes in food consumption induced by the COVID-19 pandemic were more prominent for Chinese residents who lived in rural areas than urban areas. In addition, compared to their counterparts, the dietary consequences of the pandemic were more pronounced for residents living in the eastern region and regions with a high old-age dependency ratio and low illiteracy rate. Furthermore, the estimation results of the quantile regression model for panel data suggested that the COVID-19 pandemic had relatively larger impacts on the dietary consumption of Chinese residents at lower quantiles of food consumption compared with those at higher quantiles. Overall, the results of this study suggested that Chinese residents had a healthier diet after the outbreak of the COVID-19 pandemic. We discussed possible mechanisms, including health awareness, income, food supply and prices, and other behavioral changes during COVID-19 (e.g., physical activity and cooking). To further improve residents’ dietary behaviors and health, our study proposed relevant measures, such as increasing residents’ dietary knowledge, ensuring employment and income, and strengthening the food supply chain resilience during the pandemic.

Suggested Citation

  • Xiaodong Zheng & Yinglin Wang & Yue Zhang & Tinghe Deng & Yuanzheng Yang, 2022. "Impacts of COVID-19 Pandemic on Dietary Consumption among Chinese Residents: Evidence from Provincial-Level Panel Data," IJERPH, MDPI, vol. 19(13), pages 1-16, June.
  • Handle: RePEc:gam:jijerp:v:19:y:2022:i:13:p:7612-:d:844584
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    References listed on IDEAS

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    1. repec:cup:judgdm:v:7:y:2012:i:6:p:716-727 is not listed on IDEAS
    2. Ivan A. Canay, 2011. "A simple approach to quantile regression for panel data," Econometrics Journal, Royal Economic Society, vol. 14(3), pages 368-386, October.
    3. Hélène Rossinot & Romain Fantin & Julien Venne, 2020. "Behavioral Changes During COVID-19 Confinement in France: A Web-Based Study," IJERPH, MDPI, vol. 17(22), pages 1-15, November.
    4. Dan Pan & Jiaqing Yang & Guzhen Zhou & Fanbin Kong, 2020. "The influence of COVID-19 on agricultural economy and emergency mitigation measures in China: A text mining analysis," PLOS ONE, Public Library of Science, vol. 15(10), pages 1-20, October.
    5. Xiaohua Yu, 2018. "Engel curve, farmer welfare and food consumption in 40 years of rural China," China Agricultural Economic Review, Emerald Group Publishing Limited, vol. 10(1), pages 65-77, February.
    6. Wei Liu & Xiao-Guang Yue & Paul B. Tchounwou, 2020. "Response to the COVID-19 Epidemic: The Chinese Experience and Implications for Other Countries," IJERPH, MDPI, vol. 17(7), pages 1-6, March.
    7. Jill E. Hobbs, 2020. "Food supply chains during the COVID‐19 pandemic," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 68(2), pages 171-176, June.
    8. Hooi Lean, Hooi & Huang, Wei & Hong, Junjie, 2014. "Logistics and economic development: Experience from China," Transport Policy, Elsevier, vol. 32(C), pages 96-104.
    9. Shimin Zhu & Yanqiong Zhuang & Patrick Ip, 2021. "Impacts on Children and Adolescents’ Lifestyle, Social Support and Their Association with Negative Impacts of the COVID-19 Pandemic," IJERPH, MDPI, vol. 18(9), pages 1-17, April.
    10. Koch, Alexander & Nafziger, Julia & Nielsen, Helena Skyt, 2015. "Behavioral economics of education," Journal of Economic Behavior & Organization, Elsevier, vol. 115(C), pages 3-17.
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    Cited by:

    1. Huan Yang & Qingyun Zhao & Zhengkai Zhang & Wenxiao Jia, 2022. "Associations between Lifestyle Changes, Risk Perception and Anxiety during COVID-19 Lockdowns: A Case Study in Xi’an," IJERPH, MDPI, vol. 19(20), pages 1-13, October.

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