A network analysis of basic leisure-time activities

Social scientists like to compile information about what human beings do with their time, day and night. Some of that time is called "work time", where we often have little control, and the rest is "leisure time", during which we have at least some control over the time we spend on each activity. This blog post looks at how much time people in different countries allocate to some of their different leisure-time activities.

The data are taken from the American Association of Wine Economists' Facebook page: Leisure Time Spent in OECD Countries. The five leisure-time activities included in the dataset are:

• Eating & drinking
• TV & radio
• Sports
• Shopping
• Sleeping

The hours for these five activities turn out to account for about half of the 24-hour day (46-56%, depending on the country). The data cover 24 of the 36 OECD countries*, plus 3 others (China, India and South Africa). The interest here is to explore the similarities between the people of different countries, in terms of how they allocate their leisure time (on average).

Since these are multivariate data, one of the simplest ways to get an overview of the data patterns is to use a phylogenetic network, as a tool for exploratory data analysis. For this network analysis, I first normalized the data within each of the five activities, and then calculated the similarity of the countries using the Manhattan distance. A Neighbor-net analysis was then used to display the between-country similarities.

The resulting network is shown in the first figure. Countries that are closely connected in the network are similar to each other based on the relative times allocated to the leisure-time activities, and those countries that are further apart are progressively more different from each other.

Clearly, there is considerable diversity between the countries. Moreover, there is very little in the way of consistent patterns in the network — it is basically a single "starburst" pattern. So, we may first conclude that the people of the different countries basically all go their own way, when it comes to allocating their leisure time.

Some of the network associations may result from historical or cultural similarities, such as the closeness of Japan and South Korea in the network. However, this clearly does not apply in other cases — for example, Spain and Portugal are not near each other, and neither are Australia and New Zealand, nor are Denmark, Norway and Sweden. Cultural generalizations seem therefore not to be supported by the data.

India and South Africa both stand out from the rest of the network, indicating that their people behave differently to all of the other countries (on average). Notably, both countries have very short times allocated to Sports and to Shopping. India also has rather short TV/radio time and a long Sleeping time, while South Africa has the longest Sleeping time of all of the countries (45 min longer than the country average!).

The USA has relatively short Eating/drinking time, a long Sleeping time, and the longest TV/radio time of all. That is, Americans spend less time on eating & drinking than most other people, and use the time gained for watching TV and sleeping, instead.

Of the other countries, France has the longest time spent on Eating/drinking, followed by Denmark and Italy, and then Japan and South Korea. Canada and the United Kingdom, on the other hand, actually have the shortest Eating/drinking times of all of the countries. Spain has a relatively short Eating/drinking time and the longest time of all allocated to Sports (nearly double the country average!). This may be a more healthy way to behave than the American one.

A related topic that we could look at is gender differences in time allocation, and how this may differ between countries. The data for this are taken from another American Association of Wine Economists' Facebook page: Time per Day Spent Eating and Drinking, by Country and Gender.

So, the country data are for the averages for Eating/drinking only, with separate observations for males and females. These two averages are plotted against each other in the second figure, where each point represents a single country. I have labeled the three top countries and the five bottom countries.

Obviously, there is a close correlation between the males and females within any one country, so that most of the time variation is between countries (93%). If couples and families usually eat together, then this result is to be expected. It is the children who are likely to have more independent eating habits!

However, there are 14 countries where the average male time somewhat exceeds that for females, and only 7 where the female average time exceeds that for the males, with the remaining 6 being approximately equal (as represented by the pink line). Interestingly, the 2 biggest deviations from equality are where females spend more time on Eating/drinking than do the males (Japan and the Netherlands). You may make of this what you will.

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* The 12 missing OECD countries are:
Chile, Czechia, Greece, Hungary, Iceland, Israel, Latvia, Lithuania, Luxembourg, Slovakia, Switzerland and Turkey.