Jawaharlal Institute of Postgraduate Medical Education and Research, Pondicherry, India.
JMIR Public Health Surveill. 2020 Nov 27;6(4):e23083. doi: 10.2196/23083.
The impact of the COVID-19 pandemic has varied widely across nations and even in different regions of the same nation. Some of this variability may be due to the interplay of pre-existing demographic, socioeconomic, and health-related factors in a given population.
The aim of this study was to examine the statistical associations between the statewise prevalence, mortality rate, and case fatality rate of COVID-19 in 24 regions in India (23 states and Delhi), as well as key demographic, socioeconomic, and health-related indices.
Data on disease prevalence, crude mortality, and case fatality were obtained from statistics provided by the Government of India for 24 regions, as of June 30, 2020. The relationship between these parameters and the demographic, socioeconomic, and health-related indices of the regions under study was examined using both bivariate and multivariate analyses.
COVID-19 prevalence was negatively associated with male-to-female sex ratio (defined as the number of females per 1000 male population) and positively associated with the presence of an international airport in a particular state. The crude mortality rate for COVID-19 was negatively associated with sex ratio and the statewise burden of diarrheal disease, and positively associated with the statewise burden of ischemic heart disease. Multivariate analyses demonstrated that the COVID-19 crude mortality rate was significantly and negatively associated with sex ratio.
These results suggest that the transmission and impact of COVID-19 in a given population may be influenced by a number of variables, with demographic factors showing the most consistent association.
COVID-19 大流行在各国之间以及同一国家的不同地区造成的影响差异很大。这种变异性的部分原因可能是由于在特定人群中,预先存在的人口统计学、社会经济和与健康相关的因素相互作用所致。
本研究旨在检验印度 24 个地区(23 个邦和德里)COVID-19 的州级患病率、死亡率和病死率与关键人口统计学、社会经济和与健康相关的指标之间的统计关联。
截至 2020 年 6 月 30 日,从印度政府提供的统计数据中获取了疾病流行率、粗死亡率和病死率的数据。使用双变量和多变量分析方法,检验了这些参数与所研究地区的人口统计学、社会经济和与健康相关的指标之间的关系。
COVID-19 患病率与男女比例(定义为每 1000 名男性中的女性人数)呈负相关,与特定邦是否有国际机场呈正相关。COVID-19 的粗死亡率与性别比例和腹泻病的州级负担呈负相关,与缺血性心脏病的州级负担呈正相关。多变量分析表明,COVID-19 的粗死亡率与性别比例呈显著负相关。
这些结果表明,特定人群中 COVID-19 的传播和影响可能受到多种变量的影响,其中人口统计学因素表现出最一致的关联。