{"title":"Mortality trends and discrepancies among geographic and demographic factors in the USA: pre-, during and post-pandemic analysis","authors":"Siddharth Raj Gupta","doi":"10.1016/j.glohj.2024.12.001","DOIUrl":null,"url":null,"abstract":"<div><h3>Objective</h3><div>Human mortality is affected by a lot of different factors. Geographic and demographic variations are two such criteria that play significant importance in establishing the variation in mortality rate.</div></div><div><h3>Methods</h3><div>The current work uses data collected from the Centers for Disease Control and Prevention from 2018 to 2021 to study the dependence of mortality on several parameters such as gender, race, and age group. The analysis looks at all the different causes of death registered in the database and shows how they vary with not only the demographic variables mentioned above but also geographic variables such as states in the USA. The variation in trends pre-, during, and post-pandemic is also investigated. The study undertakes several multi-factorial relations such as location-age group, location-gender, age group-gender, and a blanket study across all the races for 2018‒2021.</div></div><div><h3>Results</h3><div>Texas, California, and Florida were analyzed to be the states with the most number of deaths for the majority of causes. The study shows that before the pandemic two of the most critical causes of death identified were Atherosclerotic heart disease and Alzheimer's disease which was outnumbered by coronavirus disease 2019 in years 2020 and 2021 for the age groups of 35‒84 years.</div></div><div><h3>Conclusion</h3><div>The outcome of the study clearly shows the irrational availability of data among different ages, states, and races. In addition, it helps to provide interesting insights into how the mortality trends relate to demographic and geographic factors and point out the discrepancies among them.</div></div>","PeriodicalId":73164,"journal":{"name":"Global health journal (Amsterdam, Netherlands)","volume":"9 2","pages":"Pages 159-180"},"PeriodicalIF":0.0000,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Global health journal (Amsterdam, Netherlands)","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2414644724000666","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Objective
Human mortality is affected by a lot of different factors. Geographic and demographic variations are two such criteria that play significant importance in establishing the variation in mortality rate.
Methods
The current work uses data collected from the Centers for Disease Control and Prevention from 2018 to 2021 to study the dependence of mortality on several parameters such as gender, race, and age group. The analysis looks at all the different causes of death registered in the database and shows how they vary with not only the demographic variables mentioned above but also geographic variables such as states in the USA. The variation in trends pre-, during, and post-pandemic is also investigated. The study undertakes several multi-factorial relations such as location-age group, location-gender, age group-gender, and a blanket study across all the races for 2018‒2021.
Results
Texas, California, and Florida were analyzed to be the states with the most number of deaths for the majority of causes. The study shows that before the pandemic two of the most critical causes of death identified were Atherosclerotic heart disease and Alzheimer's disease which was outnumbered by coronavirus disease 2019 in years 2020 and 2021 for the age groups of 35‒84 years.
Conclusion
The outcome of the study clearly shows the irrational availability of data among different ages, states, and races. In addition, it helps to provide interesting insights into how the mortality trends relate to demographic and geographic factors and point out the discrepancies among them.