Analytics on the Causal Factors Associated with Age, Injuries, and Fatalities in the USA (2001 – 2020)

Deaths and injuries are significant concerns of public health globally. For developing preventive and intervention programs, intricate relationships between the various factors predicting deaths and injuries have to be understood across all age segments of the population. In this research, the dataset created by the Centers for Disease Control and Prevention, USA, from 2001 – 2020 was used to analyze such relationships. It is the yearly cause of death or injury from fire or burn, poison, fall, and so forth, classified by various age groups. Descriptive statistics followed up and complemented with various analytical tools, like regression analysis tools; Chi-square analysis tools; and "ANOVA hypothesis testing" were brought into play to dig out intricate patterns that lie hidden. The Pearson chi-square shows that age group significantly relates to causes of injuries/deaths, and that the regression model holds good for the data. It also shows that various cause categories of injuries and deaths, age groups, coupled with their outcomes, correlate significantly with each other. Most noteworthy perhaps is the fact that "falls" represent the highest percentage of injuries/deaths-48.3%. There is, therefore, the need for targeted interventions and policies that are aimed at reducing, effectively,-assured casualties.