Selecting a data set

This is part of my coursework for Data Management and Visualization.

I decided to use the codebook for Gapminder, I’ve decided to look at factors that affect the suicide rates of different countries.

I am particularly interested in the relationship between alcohol consumption and the suicide rate. My hypothesis is that alcohol consumption will be positively correlated to suicide rates. Alcohol can lower inhibitions and therefore increase the likelihood that someone will follow through on suicidal thoughts. Also, factors that increase the likelihood of alcoholism (for example, depression) might also be associated with suicide rates.

Some previous studies have found that alcohol dependence is an important risk factor for suicidal behaviour, for example, Sher 2005. However, the link has not been shown conclusively, for example, Isacsson 2000 found no correlation between alcohol consumption and suicide. Lester 1995, in a study of 13 nations, found that “suicide and homicide rates were usually, but not always, positively associated with the per capita consumption of alcohol”. However, Lester’s study uses old data, and I’m curious to know if this correlation holds up with 21st century data. 

It’s likely that other factors moderate the influence of alcoholism and suicide. These factors include income per person, employment rate, democracy score, and urban rate.

There may be other confounding factors, such as under-reporting of suicide or cultural factors around alcohol consumption. However, these are beyond the scope of this study.

I have created a personal codebook from the Gapminder data. My personal codebook includes variables for suicideper100TH (mortality due to self-inflicted injury, per 100 000 standard population, age adjusted) and alcconsumption (recorded and estimated average alcohol consumption, adult (15+) per capita consumption in litres pure alcohol). It also includes variables for income per person, polity (democracy) score, employment rate, and urbanization rate.



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