ABSTRACT
Objective: Nepal has been participating in the May Measurement Month (MMM) aiming to raise hypertension awareness and improve health seeking behavior to control high blood pressure in communities and present data for policymakers. This study compares the results from 2017 to 2021. Design and Methods: Opportunistic cross-sectional surveys to measure the proportion of hypertension, its awareness, treatment, control, and risk factors among> = 18 years of age annually from 2017 to 2021 in Nepal. Although MMM was not executed globally due to the COVID-19 pandemic in 2020, it was conducted in Nepal by following safety measures. We administered the structured questionnaire and took three BP readings while sitting at 1-minutes intervals. Measures of association were calculated using the logistic regression model adjusting for age and sex. The same definition of hypertension (a mean of 2nd and 3rd BP reading> = 140/90 mmHg, or participants were treated with medicines for known hypertension) was applied for all years. Results: The summary characteristics from 2017 to 2021 are presented in Table 1. Baseline characteristics were similar for all five studies except for low tobacco use in 2017. The proportion of hypertension ranges from 20.6% to 31.3% (24.4% in 2017, 27.8% in 2018, 27.5% in 2019, 31.3% in 2020, and 20.6% in 2021). Awareness, treatment, and control were also similar across five years, ranging from 39.5% to 49.9%, 29.5% to 39.1%, and 46.0% to 56.0% respectively. Smoking, alcohol use, body mass index> = 25, diabetes, and history of myocardial infarction (MI) or stroke were associated with hypertension after adjusting for age and sex across multiple studies. Conclusions: A five-year comparison of the MMM study in Nepal showed that hypertension awareness, treatment, and control have been suboptimal, suggesting an urgent need to implement a nationwide prevention and control program together with a national screening program. (Table Presented).
ABSTRACT
In the current scenario, the pandemic COVID-19 spread globally starting from the end of 2019, in Wuhan, a city of China. As per the current data taken up to 26th of May 2020, globally there are a huge number of people are affected (Approximately 3 billions) by the pandemic. Though the entire data varies depending upon the several parameters like, population size, congestion of area, climate condition, awareness of peoples etc. we have only analyzes on the data of the country USA. The entire data is partitioned into various categories such as: infected rate, mortality rate. A statistical analysis is prepared to analyze or predict the future strategies of the infected rate as well as the removal (Death/cured) rate. The growth of both the infected and the removed can be predicted with the same observed data taken on daily basis from 15th February 2020. We retrieved these data from an authenticate source provided by Worldometer (http://www.worldometers.info). However, Prophet Forecasting Model (PMF) is used to simulate and discussed for the prediction of the mortality rate, active rate due to pandemic COVID-19. The proposed method is also tested for accuracy of model via cross validation method. © 2021 IEEE.