New Zealand Injury Report

Project Overview

For our final project, we decided to analyze different casues of injury in the country of New Zealand. Our data covers the years 2000 to 2020, and we took an extra close look at the years 2016 -2018. This analysis focuses not only on the different causes of injury observed in New Zealand, but how different ethnic populations, namely the indigenous Māori population, have been affected by these same causes of injury.

Population Overview Data
Population Comparison
Code and Data Sources

Challenges

We faced a few challenges during the process of completing this project, the most difficult of which was definitely cleaning our data. Our data was not the easiest to work with. There were many different combinations of qualitative variables between differnet populations, age groups, and injury causes. Although we thought at first that our biggest issue would be having enough data to work with, the far more challenging part proved to be organizing our data set in a way that allowed us to make meaningful comparisons between different people groups. We were interested in drawing comparisons across both age and ethnicity, but the scope of our data did not allow for meaningful comparisons between different age groups, which we did not discover until the later stages of our project.

Conclusions

A surface level view revealed that the Māori population has experienced an overall rate of injury similar to the whole population of New Zealand. However, an analysis of different injury causes revealed that the Māori ethnic population over the last 20 years has experienced some individual types of injuries at significantly differnet rates than the general population. Specifically, the Māori population experienced significantly higher rates of injury from motor vehicle crashes and assault while the general population experienced significantly higher rates of injury from Falls.

Ultimately, our data points to some general differneces in the experiences of the Māori ethnic group compared to the population as a whole. The data we worked with did not necessarily reveal why experiences differed among different ethnic groups, but we think this data is a good springboard for many, including researchers interested in what factors are influencing the differing experiences of indigenous people, policy makers interested in lowering the risks indigenous and/or non-indigenous people face in their daily lives, and organizations looking to improve overall population well-being.

An important factor that we kept in mind when analyzing our data is that we used census data to calculate population proportions, which can be somewhat limited in its accuracy.