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

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.

Associations between Lifestyle Changes, Risk Perception and Anxiety during COVID-19 Lockdowns: A Case Study in Xi’an

“…Compared with the physical activity of Chinese individuals during the non-pandemic period (14.1%) reported by WHO, the prevalence of insufficient physical activity rose over three-fold (57.5%) during the pandemic [ 14 ]. Zheng et al (2022) discussed the impacts of the COVID-19 pandemic on diet among Chinese citizens [ 15 ]. Zhu et al (2021) found a significant increase in total food intake (9.8%) and a significant decrease in PA (31.5%) during lockdowns in Wuhan [ 16 ].…”

Social Disparities in Lifestyle and Body Weight Changes during COVID-19 Quarantine and Post-Quarantine Persistence of Changes among Lithuanian Adult Population

“…The highest increase in the Healthy Eating Index during the lockdown was shown among the less-educated participants in a Canadian study [28]. Favourable changes in food consumption induced by the COVID-19 pandemic were more prominent for Chinese residents who lived in rural areas than urban areas [29]. A Spanish study found that people who lived in rural areas during the quarantine were more physically active than those who lived in urban areas were [30].…”

Impact of COVID-19 on risks and deaths of non-communicable diseases in the Western Pacific region

“…A total of 13 studies that included national data were extracted for details ( Table 4 ). Of a total of 13 studies, 6 studies were performed in China, 37 , 38 , 39 , 40 , 41 , 42 2 in Vietnam, 43 , 44 2 in Japan, 45 , 46 1 in South Korea, 47 1 in Malaysia 48 and 1 in New Zealand. 49 …”

“…analysed provincial level food consumption data between 2015 and 2020 and found that rural residents and those living in the eastern region were more likely to adopt a healthier diet due to the COVID-19 pandemic. 37 In Japan, perceived threat of COVID-19 has been found to be positively associated with both healthier and unhealthier dietary changes with odds ratios (OR) of 1.06 (95% CI 1.04–1.07) and 1.02 (1.00–1.04), respectively. 46 Surprisingly, decrease in household income also affected dietary change in both directions with ORs of 1.42 (1.18–1.70) and 1.53 (1.20–1.95) for healthier change and unhealthy change.…”