Prevalence of high blood pressure and its associated factors among students in Shenyang, China: A cross-sectional study.

There is growing evidence that the prevalence of high blood pressure is increasing, and it may have serious consequences. However, research on the prevalence and influencing factors of high blood pressure among primary and secondary school students is still relatively scarce. This study aims to investigate the prevalence and influencing factors of high blood pressure among primary and secondary school students in Shenyang, in order to provide scientific evidence for the prevention and management of this disease. From April to May 2020, 4892 students aged 7 to 17 years were selected as the survey subjects, and on-site physical measurements and questionnaire surveys were conducted. The prevalence of high blood pressure was described. Restricted cubic spline was used to analyze the dose-response relationship between sleep duration, BMI and the risk of high blood pressure. Logistic regression was used to analyze the risk factors. Multiplicative and additive models were used to analyze the interaction between sleep duration and BMI. The results showed that the overall prevalence of high blood pressure among students aged 7 to 17 years in Shenyang was 9.9%, with a higher prevalence in females than males (12.1% vs 7.9%) and in urban areas than suburban areas (11.8% vs 7.7%). The prevalence was lowest in students with normal weight (8.3%) and highest in those who were obese (12.5%). The prevalence fluctuated to some extent among different age groups, but overall, it increased with age, with the lowest prevalence in primary school students (7.0%), 11.4% in mild school students, and the highest prevalence of 14.3% in high school students. Multivariable analysis showed that the risk of high blood pressure in female students was 1.90 times higher than that in male students (95% CI: 1.54-2.35), and the risk in suburban areas was 0.65 times lower than that in urban areas (95% CI: 0.52-0.81). Students with a BMI ≥ 21 kg/m2 had a 1.58 times higher risk than those with a BMI < 21 kg/m2(95% CI: 1.28-1.96), while those with a sleep time ≥ 8 hours had a 0.80 times lower risk than those with a sleep time < 8 hours (95% CI: 0.65-0.99). Exercise can significantly reduce the risk of high blood pressure, while using electronic devices for more than 0.5 hours significantly increases the risk of high blood pressure. BMI and sleep duration have no interaction effect on the risk of high blood pressure. To reduce the prevalence of high blood pressure, students should reduce the use of electronic devices, ensure adequate exercise, maintain a reasonable weight, and ensure sufficient sleep.

Correlation between the migration scale index and the number of new confirmed coronavirus disease 2019 cases in China.

In late December 2019, patients of atypical pneumonia due to an unidentified microbial agent were reported in Wuhan, Hubei Province, China. Subsequently, a novel coronavirus was identified as the causative pathogen which was named SARS-CoV-2. As of 12 February 2020, more than 44 000 cases of SARS-CoV-2 infection have been confirmed in China and continue to expand. Provinces, municipalities and autonomous regions of China have launched first-level response to major public health emergencies one after another from 23 January 2020, which means restricting movement of people among provinces, municipalities and autonomous regions. The aim of this study was to explore the correlation between the migration scale index and the number of confirmed coronavirus disease 2019 (COVID-19) cases and to depict the effect of restricting population movement. In this study, Excel 2010 was used to demonstrate the temporal distribution at the day level and SPSS 23.0 was used to analyse the correlation between the migration scale index and the number of confirmed COVID-19 cases. We found that since 23 January 2020, Wuhan migration scale index has dropped significantly and since 26 January 2020, Hubei province migration scale index has dropped significantly. New confirmed COVID-19 cases per day in China except for Wuhan gradually increased since 24 January 2020, and showed a downward trend from 6 February 2020. New confirmed COVID-19 cases per day in China except for Hubei province gradually increased since 24 January 2020, and maintained at a high level from 24 January 2020 to 4 February 2020, then showed a downward trend. Wuhan migration scale index from 9 January to 22 January, 10 January to 23 January and 11 January to 24 January was correlated with the number of new confirmed COVID-19 cases per day in China except for Wuhan from 22 January to 4 February. Hubei province migration scale index from 10 January to 23 January and 11 January to 24 January was correlated with the number of new confirmed COVID-19 cases per day in China except for Hubei province from 22 January to 4 February. Our findings suggested that people who left Wuhan from 9 January to 22 January, and those who left Hubei province from 10 January to 24 January, led to the outbreak in the rest of China. The 'Wuhan lockdown' and the launching of the first-level response to this major public health emergency may have had a good effect on controlling the COVID-19 epidemic. Although new COVID-19 cases continued to be confirmed in China outside Wuhan and Hubei provinces, in our opinion, these are second-generation cases.