Identifying patterns of main causes of death in the young EU population

TL;DR

This paper introduces a novel clustering method using symbolic data analysis to identify and compare mortality cause patterns across EU countries' young populations, considering age, gender, and sociodemographic factors.

Contribution

It presents an alternative clustering approach that incorporates comprehensive cause-of-death distributions across age-gender groups in EU mortality data.

Findings

Identified clusters of EU countries with similar mortality patterns.

Revealed relationships between mortality patterns and sociodemographic indicators.

Provided insights into age-gender specific mortality causes in the young population.

Abstract

The study of mortality patterns is a popular research topic in many areas. We are particularly interested in mortality patterns among main causes of death associated with age-gender combinations. We use symbolic data analysis (SDA) and include three dimensions: age, gender, and patterns across main causes of death. In this study, we present an alternative method to identify clusters of EU countries with similar mortality patterns in the young population, while considering comprehensive information on the distribution of deaths among the main causes of death by different age-gender groups. We explore possible relationships between mortality patterns in the identified clusters and some other sociodemographic indicators. We use EU data of crude mortality rates from 2016, as the most recent complete data available.