Risk and protective factors of SARS-CoV-2 infection - Meta-regression of data from worldwide nations

Although it has been reported that coexistent chronic diseases are strongly associated with COVID-19 severity, investigations of predictors for SARS-CoV-2 infection itself have been seldom performed. To screen potential risk and protective factors for SARS-CoV-2 infection, meta-regression of data from worldwide nations were herein conducted. We extracted total confirmed COVID-19 cases in worldwide 180 nations (May 31, 2020), nation total population, population ages 0-14/[≥]65, GDP/GNI per capita, PPP, life expectancy at birth, medical-doctor and nursing/midwifery-personnel density, hypertension/obesity/diabetes prevalence, annual PM2.5 concentrations, daily ultraviolet radiation, population using safely-managed drinking-water/sanitation services and hand-washing facility with soap/water, inbound tourism, and bachelors or equivalent (ISCED 6). Restricted maximum-likelihood meta-regression in the random-effects model was performed using Comprehensive Meta-Analysis version 3. To adjust for other covariates, we conducted the hierarchical multivariate models. A slope (coefficient) of the meta-regression line for the COVID-19 prevalence was significantly negative for population ages 0-14 (-0.0636; P = .0021) and positive for obesity prevalence (0.0411; P = .0099) and annual PM2.5 concentrations in urban areas (0.0158; P = .0454), which would indicate that the COVID-19 prevalence decreases significantly as children increase and that the COVID-19 prevalence increases significantly as the obese and PM2.5 increase. In conclusion, children (negatively) and obesity/PM2.5 (positively) may be independently associated with SARS-CoV-2 infection.