Institute of Economic Research, Hitotsubashi University, 2-1 Naka, Kunitachi, Tokyo 186-8603, Japan.
Survey Research Center, 3-13-5 Nihonbashi, Chuoku, Tokyo 103-0027, Japan.
Int J Environ Res Public Health. 2022 Jul 22;19(15):8918. doi: 10.3390/ijerph19158918.
Several studies have reported the adverse impacts of the COVID-19 pandemic on health outcomes. However, little is known about which area of COVID-19 infection matters most for an individual's subjective health outcomes. We addressed this issue in the present study. We used the longitudinal data of 2260 individuals obtained from a two-wave internet-based nationwide survey conducted in Japan. We estimated the multilevel regression models, which controlled for fixed effects at the individual and prefecture levels, to explain an individual's self-rated health (SRH) based on the reported number of new COVID-19 infection cases at different area levels: prefecture, group of neighboring prefectures, and regional bloc. We found that SRH was highly associated with the average and maximum number of new infection cases among neighboring prefectures or in the regional bloc, but not with those at the prefecture level, if used jointly as explanatory variables. The results suggest that inter-prefectural coordination is needed not only to contain COVID-19 but also to reduce its adverse impact on the subjective health outcomes of residents.
多项研究报告了 COVID-19 大流行对健康结果的不利影响。然而，对于 COVID-19 感染的哪个领域对个人的主观健康结果最重要，知之甚少。我们在本研究中解决了这个问题。我们使用了从日本进行的两次基于互联网的全国性调查中获得的 2260 名个体的纵向数据。我们估计了多层次回归模型，该模型在个体和都道府县水平上控制了固定效应，根据不同地区水平（都道府县、邻近都道府县组和地区集团）报告的新 COVID-19 感染病例数，解释个体的自我报告健康状况（SRH）。我们发现，如果将相邻都道府县或地区集团的平均和最大新感染病例数联合作为解释变量，SRH 与这些数字高度相关，但与都道府县水平上的数字无关。结果表明，不仅需要在都道府县之间进行协调以控制 COVID-19，还需要减少其对居民主观健康结果的不利影响。
