H. Takagi
Internal and Emergency Medicine, 2020
We read with great interest the article by Farsalinos et al. [1] recently published in Internal and Emergency Medicine. The review [1] of 13 studies enrolling a total of 5960 hospitalized coronavirus disease 2019 (COVID-19) patients in China revealed unusually lower (approximately one-fourth) smoking prevalence in COVID-19 cases than that in the general population. Recent meta-analyses [2, 3], however, demonstrated that smoking was associated with worse prognosis and mortality in patients with COVID-19. To determine whether COVID-19 prevalence is modulated by smoking prevalence, meta-regression of Japanese prefectural data was herein conducted. In each Japanese prefecture, the following was extracted: (1) number of confirmed COVID-19 cases on 15 June 2020 from the “Ministry of Health, Labour and Welfare” (https ://www.mhlw.go.jp/conte nt/10906 000/00064 0393.pdf); (2) smoking prevalence (%) in 2016 (latest survey) from the “National Cancer Center Japan” (https ://ganjo ho.jp/reg_stat/ stati stics /dl/index .html#smoki ng); and (3-1) population per 1-km2 inhabitable area (in 2018), (3-2) proportion (%) of males and < 15-year/≥ 65-year subjects (in 2018), (3-3) prevalence (/100 thousands) of neoplasm, type 2 diabetes mellitus, and essential hypertension (in 2017), (3-4) yearly average air temperature (°C), total sunshine hours (h), total precipitation (mm), and average relative humidity (%) (in 2018), (3-5) healthy life expectancy (years) (in 2016) and life expectancy at birth (years) (in 2015), (3-6) number (/100 thousands) of hospital beds (in 2017), doctors (in 2017), and nurses (in 2018), (3-7) monthly average households and persons assisted by livelihood protection (/1000 persons) (in 2017), and (3-8) monthly current income per household and living expenditure (≥ 2-person households–workers’ households) (yen) (in 2018) from the “e-Stat, Statistics of Japan” (https ://www.e-stat.go.jp) (Supplementary Table S1). To adjust for prefectural population density, COVID-19 prevalence was defined as the number of COVID-19 cases divided by the population per 100-km2 inhabitable area. Univariable (including smoking prevalence as only a covariate) and multivariable (including all the above-mentioned parameters as covariates) random-effects meta-regression was performed using OpenMetaAnalyst (https ://www.cebm.brown .edu/ openm eta/index .html). A meta-regression graph depicted COVID-19 prevalence (plotted as logarithm-transformed prevalence on the Y-axis) as a function of smoking prevalence (plotted on the X-axis). A slope of the univariable meta-regression line was significantly positive (coefficient, 0.319; 95% confidence interval [CI] 0.148–0.490; p < 0.001; Fig. 1), which indicated that COVID-19 prevalence increased significantly as smoking prevalence increased. The slope was also significantly positive (coefficient, 0.321; 95% CI 0.093–0.549; p = 0.006) even in multivariable meta-regression including all the 22 covariates together (Table 1). The present meta-regression suggests a positive association of smoking prevalence with COVID-19 prevalence independent of various examined covariates. Remarkably lower current-smoking prevalence in hospitalized COVID19 patients (6.5%; 95% CI 4.9–8.2%) than that in the general population (26.6%) in China (2018 Global Adult Tobacco Survey, https ://www.who.int/docs/defau lt-sourc e/wpro--docum ents/count ries/china /2018-gats-china -facts heetcn-en.pdf?sfvrs n=3f4e2 da9_2) has been reported in the article by Farsalinos et al. [1], which could be explained Electronic supplementary material The online version of this article (https ://doi.org/10.1007/s1173 9-020-02473 -2) contains supplementary material, which is available to authorized users.
Cited by 4 publications.
Field of study: Medicine