Data Visualization and Analysis, Part 3/3 – Binge Drinking

By | March 28, 2016

Author: Qi Chen

1. Introduction

This is the final part of Data Visualization and Analysis with R and Tableau Series, for the previous parts, please refer to part 1/3 and part 2/3 for details.

There are roughly 2 billion people around the world consuming alcoholic drinks. Among them, a great number of people are considered as “binge drinking”, which means consuming 5 or more drinks per single occasion for male and 4 or more drinks for female. Drinking alcohol has caused many problems and there are about 88,000 people died from alcohol-related causes annually. Moreover, $223.5 billion has been spent for alcohol misuse problems and 75% of the cost are related to binge drinking. Therefore, the study of binge drinking is very important for the well-being of the society. In this article, we analyze the data from BRFSS (Behavior Risk Surveillance System) for disease control, trying to discover the relationship between binge drinking and other factors and assist in decreasing injuries, deaths, and costs related to binge drinking.

2. Analysis

2.1. Software used

In this article, we will demonstrate the use of Tableau and R to run data visualization and analysis.

2.2. Data Visualization with Tableau

Graph1 shows the proportion of people who drink alcohol and who are considered as binge drinking between 2002 and 2012. We can clearly see that the proportion increases a little in the 10 years and roughly 50% of people are alcohol consumers.

Graph 1: Binge vs. Any Drinking

We are also interested in the alcohol consumption for different counties in the United States, which is shown in Graph 2. Red means high alcohol consumption and green means vice versa. From this figure, we see that areas near northern Midwest (for example, Wisconsin) have relatively high alcohol consumption.

Graph 2: Alcohol Consumption in Counties in U.S.

Similarly, we plot the rate of alcohol related death for each state in Graph 3. Again a color closer to red means a higher rate. We see relatively high percentage of death toll in some states such as Wisconsin, North Dakota and Montana. Thus it might be a good idea to adopt more strict law against drunk driving and other dangerous behaviors related to binge drinking in those areas.

Graph 3: States of Alcohol Impairment

2.3. Data Analysis with R

In this part, we want to demonstrate the data analysis techniques using R. At first, we create a facet plot as shown in Graph 4 to show the correlation among different variables, including sleptim1 (sleep time), marital (marital status), avedrnk2 (average drink per day), x.age80 (age), x.rfsmok3 (smoker or not), and x.rfbing5 (binge drinking).

Graph 4: Facet Plot

In this graph, red is for male and blue is for female. An interesting phenomenon is that for single people, smokers and those who binge drink consist a large proportion compare to people who are married. We can also see that 50% of smokers binge drink, but less than 30% of nonsmokers binge drink, which indicates a high correlation between smoking and binge drinking.

With R package “party”, we create a conditional interface tree taking sex (gender), x.rfsmok3 (smoke condition), x.rfbmi5 (obesity) and marital (marital status) into consideration and trying to determine the conditional probability of binge drinking under each category. Readers who are interested in the conditional interface tree could refer to this link for details.

Graph 5: Conditional Interface Tree

For example, from this figure we could see that the probability for a single male smoker to binge drink is 52.9%.

2.4. Results and Summary

In this article, we demonstrate the use of Tableau and R to run data visualization and analysis regarding to binge drinking.

This article is based on a course project of Industrial Data Analytics offered by Prof. Kaibo Liu in the University of Wisconsin-Madison in Spring 2015. Thank Prof. Liu for his instruction and also thank Criss Ross, Corey Lester and Wyatt Suprise for their initial work.

3. Source

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15 thoughts on “Data Visualization and Analysis, Part 3/3 – Binge Drinking

  1. Bridget Schuessler

    The data backing Wisconsin and binge drinking is astounding. The state is known for a social culture of drinking, but these statistically backed visuals really show that something needs to be done to improve the health & safety of state residents.

  2. Michael Baer

    This is quite an interesting study. While I think the facet chart is hard to interpret, the conditional interference tree is very beneficial to help with understanding and helps draw interesting conclusions about binge drinking. I think it is also probably important to note that it is likely that the actual rates are higher than this as people may not think they are really binge drinking if they only do it occasionally, creating abnormally lower rates.

  3. Erik Pechnick

    Interesting topic. It would be interesting to see if all of the highest drinking states have laws like wisconsin where you need to purchase alcohol before a certain time. I would also like to see the correlation between average temperature and % of binge drinkers in a particular state

  4. Eric Fleming

    This analysis helps validate the often quoted statistic that 7 of the 10 drunkest cities are in Wisconsin. I would love to see analysis and predictions about why binge drinking is so heavily concentrated in the north. I wonder if culture is enough to explain it. I’d love to see a map showing alcohol consumption rates of different countries since the social drinking culture brought by different immigrant groups is what people often use to explain the prevalence of drinking in Wisconsin and elsewhere.

  5. Dylan Weber

    Not surprising that the alcohol consumption is so high in the midwest. You hear about it all the time and this visualization seems to confirm those thoughts with data. Very interesting!

  6. Lauren Chiang

    Thank you for sharing your analysis. I found the results very eye-opening. I am curious to know why the northern Midwest areas have relatively high alcohol consumption. I wonder if there are less strict rules in these areas compared to the other states. It would have also been interesting to see the difference in binge drinking in the United States compared to other countries. In many other countries, there is not a drinking age or if there is, they are much more relaxed about it. An analysis on the amount of deaths due to alcohol consumption would be intriguing to examine. I liked the utilization of a conditional interface tree to illustrate the probability of binge drinking given certain attributes. Overall, I think that this analysis is useful information to gain support in reducing binge drinking across the U.S.

  7. Tom Dreher

    This is an excellent article: succinct yet very informative. It starts by establishing a very relevant reason for investigating binge drinking, a health problem that affects the US significantly every year, especially the Midwest. Its also clear that the author did a lot of work both in R and Tableau to find insights into who is more likely to binge drink. Creating a decision tree based on things like gender, marital status, and smoking was a great way of showing the stats on which populations are the heaviest drinkers. As a Midwest native, maybe we can look at laws and lifestyles of lower-drinking areas of the country and try to emulate these to become healthier as a region.

  8. MacKenzie Lundstrom

    I am not surprised that the midwest has higher alcohol consumption than most parts of the country, but I am surprised that California and some of the southern state aren’t higher considering wine country and the south being big football fans which typically correlates with drinking.

  9. Trevor

    I found this analysis interesting because of the heavy concentration of binge drinking in the Midwest and that I currently reside in Wisconsin as a student. Graph 2 illustrated that the most northern regions of the Midwest experienced the highest binge drinking rates. Southern Texas also stood out as a slight outlier to me and I would be interested in investigating what attributes these places have in common that correlate to a high binge drinking rate. Next, I predict the colder the weather in a Midwest region, the higher the binge drinking rate. I would want to test this hypothesis by comparing binge drinking rates to each Midwest region every month. Another good attribute to investigate would be the rank of states based on drinking law strictness. To decrease binge drinking rates in the future, lawmakers would likely want to know if high binge drinking rates correlate to weaker state drinking laws. Overall, I appreciate this analysis’ ability to communicate the need for reduced binge drinking, especially in certain places like the northern Midwest.

  10. Koryn Kessler

    I found it very interesting that most of the death rates due to alcoholism were congregated in a specific part of the United States. I also thought the components chosen on the decision tree were interesting to see.

  11. Saksham Garg

    I just wonder if the the population differences amongst the states would affect the data analysis of the on binge drinking by not giving the accurate per person consumption of alcohol.

  12. Joseph Dunleavy

    The data around the midwest was not surprising at all. The midwest is known for its drinking culture, and it is especially not surprising in Dane county. What’s funny is that a lot of the northernmost states have huge drinkers, but hey, what else would they be doing? Ha.

  13. Tejas Vedula

    An article that is providing good awareness overall. I’m very curious as to why the mid west region takes part in the highest rates of binge drinking. Is there any correlation between the midwest climate and alcohol consumption ? Or is there a correlation between the dense presence of universities and the ever increasing rise of alcohol consumption among the young people ? As mentioned in one of the previous comments, it would be interesting to observe the probability of a male in the US to be a binge drinker in comparison to an average male from other prominent countries in the world. Culture could play a massive influence in drinking habits among people.

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