COVID-19 pandemic health expenditures and family economic behaviors: China health and retirement longitudinal study (CHARLS)
Since the onset of the coronavirus disease 2019 pandemic, there has been a total of 776 million confirmed infection cases worldwide with both countries, China and the US contributing a substantial number of cases. Aside from the grand number of cases, the pandemic has also demonstrated a worldwide financial toll. Specifically, as of May 20, 2020, China has been reported to obtain a cost of $373.20 million in overall patient hospitalizations. Yet, aside from these hospitalizations, the purchasing of personal protective equipment (PPE) to mitigate one’s risk for infection can also be expensive. In addition, the pandemic itself has resulted in a wealth of businesses shutting down worldwide, consequently resulting in job losses and attenuated income for workers worldwide. Thus, exploring the behavior of PPE purchasing by primary respondents of individual households as well as the degree in mediating their expenses following the pandemic was the focus of this study. Specifically, the present investigation sought to examine the association between medical and fitness expenditure toward PPE purchasing behavior for mainland residents of China aged 45+ due to the lack of existing literature examining this relationship from the best of our knowledge. The former relates to both direct and indirect medical expenses whilst the latter refers to the purchasing of exercise equipment and health supplements. Second, these expenditures were further utilized to explore its association with the level of ease in covering expenses following the pandemic as well. This was a secondary data analysis that used cross-sectional data from the China Health and Retirement Longitudinal Study database, wherein generalized linear mixed effects models were applied in examining the associations. Both medical and fitness expenditure were insignificant predictors of PPE purchasing behavior whilst they expressed a significant association toward predicting the degree of ease for the included participants in covering their daily expenses following the onset of the pandemic.
An, X., Xiao, L., Yang, X., Tang, X., Lai, F., & Liang, X.H. (2022). Economic burden of public health care and hospitalisation associated with COVID-19 in China. Public Health, 203:65-74. https://doi.org/10.1016/j.puhe.2021.12.001
Cohen, J., & van der Meulen Rodgers, Y. (2020). Contributing factors to personal protective equipment shortages during the COVID-19 pandemic. Preventative Medicine, 141:106263. https://doi.org/10.1016/j.ypmed.2020.106263
Coronavirus Resource Center by Johns Hopkins University of Medicine. (2023). China Overview. Available from: https://coronavirus.jhu.edu/region/china [Last accessed on 2024 Aug 23].
Elola-Somoza, F.J., Bas-Villalobos, M.C., Pérez-Villacastín, J., & Macaya-Miguel, C. (2021). Public healthcare expenditure and COVID-19 mortality in Spain and in Europe. Revista Clínica Española (Barc), 221(7):400-403. https://doi.org/10.1016/j.rceng.2020.11.006
Findling, M.G., Blendon, R.J., & Benson, J.M. (2021). Serious financial burdens facing U.S. households with employment loss during COVID-19. Challenge, 64(1):3-10. https://doi.org/10.1080/05775132.2020.1866905
Gong, J., Wang, G., Wang, Y., Chen, X., Chen, Y., Meng, Q., et al. (2022). Nowcasting and forecasting the care needs of the older population in China: Analysis of data from the china health and retirement longitudinal study (CHARLS). Lancet Public Health, 7(12):e1005-e1013. https://doi.org/10.1016/s2468-2667(22)00203-1
Hafidz, F., Adiwibowo, I.R., Kusila, G.R., Ruby, M., Saut, B., Jaya, C., et al. (2023). Out-of-pocket expenditure and catastrophic costs due to COVID-19 in Indonesia: A rapid online survey. Frontiers in Public Health, 11:1072250. https://doi.org/10.3389/fpubh.2023.1072250
Khan, J.R., Awan, N., Islam, M., & Muurlink, O. (2020). Healthcare capacity, health expenditure, and civil society as predictors of COVID-19 case fatalities: A global analysis. Frontiers in Public Health, 8:347. https://doi.org/10.3389/fpubh.2020.00347
Koumpias, A.M., Schwartzman, D., & Fleming, O. (2022). Long-haul COVID: Healthcare utilization and medical expenditures 6 months post-diagnosis. BMC Health Services Research, 22(1):1010. https://doi.org/10.1186/s12913-022-08387-3
Kupcova, I., Danisovic, L., Klein, M., & Harsanyi, S. (2023). Effects of the COVID-19 pandemic on mental health, anxiety, and depression. BMC Psychololgy, 11(1):108. https://doi.org/10.1186/s40359-023-01130-5
Li, H., Liu, X., Zheng, Q., Zeng, S., & Luo, X. (2022). Gender differences and determinants of late-life depression in china: A cross-sectional study based on CHARLS. Journal of Affective Disorders, 309(15):178-185. https://doi.org/10.1016/j.jad.2022.04.059
Mukerji, S., MacIntyre, C.R., Seale, H., Wang, Q., Yang, P., Wang, X., et al. (2017). Cost-effectiveness analysis of N95 respirators and medical masks to protect healthcare workers in China from respiratory infections. BMC Infectious Diseases, 17(1):464. https://doi.org/10.1186/s12879-017-2564-9
Nia, H.S., Long, S., Kaur, H., Boyle, C., Fomani, F.K., Hoseinzadeh, E., et al. (2022). A predictive study between anxiety and fear of COVID-19 with psychological behaviour response: The mediation role of perceived stress. Frontiers in Psychology, 13:851212. https://doi.org/10.3389/fpsyt.2022.851212
Richards, F., Kodjamanova, P., Chen, X., Li, N., Atanasov, P., Bennetts, L., et al. (2022). Economic burden of COVID- 19: A systematic review. ClinicoEconomics and Outcomes Research, 14:293-307. https://doi.org/10.2147/ceor.s338225
Ruengorn, C., Awiphan, R., Wongpakaran, N., Wongpakaran, T., & Nochaiwong, S. (2021). Association of job loss, income loss, and financial burden with adverse mental health outcomes during coronavirus disease 2019 pandemic in Thailand: A nationwide cross-sectional study. Depression and Anxiety, 38(6):648-660. https://doi.org/10.1002/da.23155
World Health Organization. (2024). COVID-19 epidemilogical update. Available from: https://www.who.int/ publications/m/item/covid-19-epidemiological-update--- 24-december-2024 [Last accessed on 2025 Mar 25].
White & Case. (2020). COVID-19: Chinese Government Financial Assistance Measures. White & Case. Available from: https://www.whitecase.com/insight-alert/covid-19- chinese-government-financial-assistance-measures?utm_source [Last accessed on 2025 Jan 21].
Yin, W., Sifre-Acosta, N., Chamorro, D., Chowdhury, S., & Hu, N. (2025). Impact of physical activity on health behavior change and mental health during the COVID-19 epidemic among chinese adults: China health and retirement longitudinal study (CHARLS). International Journal of Environmental Research and Public Health, 22(2):201. https://doi.org/10.3390/ijerph22020201
Zhang, H. (2020). China’s employment stabilization policies in response to the impact of the COVID-19 pandemic. International Journal of Sociology and Social Policy, 42(3/4):201-209. https://doi.org/10.1108/ijssp-05-2020-0167
Zhang, J., & Mu, Q. (2018). Air pollution and defensive expenditures: Evidence from particulate-filtering facemasks. Journal of Environmental Economics and Management, 92(1):517-536. https://doi.org/10.1016/j.jeem.2017.07.006
Zhang, L., Sun, F., & Chu, X. (2022). China’s Policy Experience in Responding to COVID-19 Shock. United Nations Conference on Trade and Development. Available from: https://unctad.org/system/files/official-document/BRI-Project_RP24_en.pdf?utm_source [Last accessed on 2025 Jan 21].
Zhang, Y., Lu, S., Niu, Y., & Zhang, L. (2018). Medical expenditure clustering and determinants of the annual medical expenditures of residents: A population-based retrospective study from rural China. BMJ Open, 8(6):e022721. https://doi.org/10.1136/bmjopen-2018-022721
Zhao, Y., Chen, X., Wang, Y., Meng, Q., Bo, H., Chen, C., et al. (2023). China health and retirement longitudinal study wave 5 (2020) User guide. National School of Development, Peking University. Available from: https://charls.charlsdata. com/public/ashelf/public/uploads/document/2020-charls-wave5/application/charls_2020_questionnaire_english.pdf [Last accessed on 2024 Jul 15].
Zhao, Y., Hu, Y., Smith, J.P., Strauss, J., & Yang, G. (2014). Cohort profile: The china health and retirement longitudinal study (CHARLS). International Journal of Epidemiology, 43(1):61-68. https://doi.org/10.1093/ije/dys203
Zhou, M., Kuang, L., & Hu, N. (2023). The association between physical activity and intrinsic capacity in Chinese older adults and its connection to primary care: China health and retirement longitudinal study (CHARLS). International Journal of Environmental Research and Public Health, 20(7):5361. https://doi.org/10.3390/ijerph20075361