PDF(Pubmed)
Abstract：
UNASSIGNED: The COVID-19 pandemic has resulted in treatment interruption for chronic diseases. The scale of COVID-19 in Japan has varied greatly in terms of the scale of infection and the speed of spread depending on the region. This study aimed to examine the relationship between local infection level and treatment interruption among Japanese workers.
UNASSIGNED: Cross-sectional internet survey was conducted from December 22 to 26, 2020. Of 33,302 participants, 9,510 (5,392 males and 4,118 females) who responded that they required regular treatment were included in the analysis. The infection level in each participant\'s prefecture of residence was assessed based on the incidence rate (per 1,000 population) and the number of people infected. Age-sex and multivariate adjusted odds ratios (ORs) of regional infection levels associated with treatment interruption were estimated by multilevel logistic models, nested by prefecture of residence. The multivariate model was adjusted for sex, age, marital status, equivalent household income, educational level, occupation, self-rated health status and anxiety.
UNASSIGNED: The ORs of treatment interruption for the lowest and highest levels of infection in the region were 1.32 [95 % confidence interval (CI) were 1.09-1.59] for the overall morbidity rate (per 1,000) and 1.34 (95 % CI 1.10-1.63) for the overall number of people infected. Higher local infection levels were linked to a greater number of workers experiencing treatment interruption.
UNASSIGNED: Higher local infection levels were linked to more workers experiencing treatment interruption. Our results suggest that apart from individual characteristics such as socioeconomic and health status, treatment interruption during the pandemic is also subject to contextual effects related to regional infection levels. Preventing community spread of COVID-19 may thus protect individuals from indirect effects of the pandemic, such as treatment interruption.
UNASSIGNED: Cross-sectional internet survey was conducted from December 22 to 26, 2020. Of 33,302 participants, 9,510 (5,392 males and 4,118 females) who responded that they required regular treatment were included in the analysis. The infection level in each participant\'s prefecture of residence was assessed based on the incidence rate (per 1,000 population) and the number of people infected. Age-sex and multivariate adjusted odds ratios (ORs) of regional infection levels associated with treatment interruption were estimated by multilevel logistic models, nested by prefecture of residence. The multivariate model was adjusted for sex, age, marital status, equivalent household income, educational level, occupation, self-rated health status and anxiety.
UNASSIGNED: The ORs of treatment interruption for the lowest and highest levels of infection in the region were 1.32 [95 % confidence interval (CI) were 1.09-1.59] for the overall morbidity rate (per 1,000) and 1.34 (95 % CI 1.10-1.63) for the overall number of people infected. Higher local infection levels were linked to a greater number of workers experiencing treatment interruption.
UNASSIGNED: Higher local infection levels were linked to more workers experiencing treatment interruption. Our results suggest that apart from individual characteristics such as socioeconomic and health status, treatment interruption during the pandemic is also subject to contextual effects related to regional infection levels. Preventing community spread of COVID-19 may thus protect individuals from indirect effects of the pandemic, such as treatment interruption.
摘要：
COVID-19大流行导致慢性病治疗中断。根据不同地区的不同，日本的COVID-19感染规模和传播速度差异很大。这项研究旨在研究日本工人中当地感染水平与治疗中断之间的关系。
横断面互联网调查于2020年12月22日至26日进行。在33,302名参与者中，9,510名(5,392名男性和4,118名女性)回答他们需要定期治疗的人被包括在分析中。根据发病率（每1000人）和感染人数评估每个参与者居住地区的感染水平。通过多水平逻辑模型估计与治疗中断相关的区域感染水平的年龄-性别和多变量调整后的比值比（OR）。由居住地嵌套。多变量模型根据性别进行了调整，年龄,婚姻状况,相当于家庭收入，教育水平,职业,自我评估的健康状况和焦虑。
该地区最低和最高感染水平的治疗中断OR为总发病率（每1000人）1.32[95％置信区间（CI）为1.09-1.59]，总感染人数为1.34（95％CI1.10-1.63）。较高的局部感染水平与更多的工人经历治疗中断有关。
更高的局部感染水平与更多的工人经历治疗中断有关。我们的结果表明，除了个人特征，如社会经济和健康状况，大流行期间的治疗中断还受到与区域感染水平相关的环境影响。因此，防止COVID-19的社区传播可能会保护个人免受大流行的间接影响，如治疗中断。
横断面互联网调查于2020年12月22日至26日进行。在33,302名参与者中，9,510名(5,392名男性和4,118名女性)回答他们需要定期治疗的人被包括在分析中。根据发病率（每1000人）和感染人数评估每个参与者居住地区的感染水平。通过多水平逻辑模型估计与治疗中断相关的区域感染水平的年龄-性别和多变量调整后的比值比（OR）。由居住地嵌套。多变量模型根据性别进行了调整，年龄,婚姻状况,相当于家庭收入，教育水平,职业,自我评估的健康状况和焦虑。
该地区最低和最高感染水平的治疗中断OR为总发病率（每1000人）1.32[95％置信区间（CI）为1.09-1.59]，总感染人数为1.34（95％CI1.10-1.63）。较高的局部感染水平与更多的工人经历治疗中断有关。
更高的局部感染水平与更多的工人经历治疗中断有关。我们的结果表明，除了个人特征，如社会经济和健康状况，大流行期间的治疗中断还受到与区域感染水平相关的环境影响。因此，防止COVID-19的社区传播可能会保护个人免受大流行的间接影响，如治疗中断。
