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37838 | How do people across the world spend their time and what does this tell us about living conditions? | untitled-reusable-block-235 | wp_block | publish | <!-- wp:paragraph --> <p>Sleep, work, eat, leisure – at a high level most of us spend time on similar activities. But just how similar are the daily activities of people across the world? This is something worth considering, not just to serve our curiosity but because differences in the way we spend time give us meaningful perspectives on living conditions, economic opportunities and general well-being.</p> <!-- /wp:paragraph --> <!-- wp:paragraph --> <p>Here we take a look at the data. We explore some of the key patterns that emerge from cross-country time use surveys, and then dig deeper to understand how these differences matter for people’s well-being.</p> <!-- /wp:paragraph --> <!-- wp:heading {"level":4} --> <h4>Daily activities: similarities and differences across countries</h4> <!-- /wp:heading --> <!-- wp:columns --> <div class="wp-block-columns"><!-- wp:column --> <div class="wp-block-column"><!-- wp:paragraph --> <p>In the chart here we compare average time spent across a number of common activities. The data comes from the OECD and brings together estimates from time diaries where respondents are asked to record the sequence of what they did over a specific day, as well as from general questionnaires where respondents are asked to recall the amount of time spent on different activities on a specific day in the previous week.{ref}The ‘time-diary method’ is generally more reliable and allows a richer analysis of routines, because it measures not only aggregate times but also sequences and clock-times. Time-diary data is less common, but it is available for some countries from the <a rel="noreferrer noopener" href="https://www.timeuse.org/mtus" target="_blank">Multinational Time Use Study</a>. We explore time-use ‘tempograms’ from the MTUS in a forthcoming companion post.{/ref}</p> <!-- /wp:paragraph --> <!-- wp:paragraph --> <p>The first thing that jumps out from this chart is that there are indeed many similarities across countries.</p> <!-- /wp:paragraph --> <!-- wp:paragraph --> <p>This is not surprising – most of us try to split our days into “work, rest and fun”, and so there are some predictable patterns. We spend the most time working and sleeping; and paid work, housework, leisure, eating and sleeping take together 80-90% of the 1440 minutes that we all have available every day.</p> <!-- /wp:paragraph --> <!-- wp:paragraph --> <p>But if we look closely, we also see some important differences. Consider sleeping, for example. From this sample of countries, South Koreans sleep the least – averaging 7 hours and 51 minutes of sleep every day. In India and the US, at the other end of the spectrum, people sleep an hour more on average.</p> <!-- /wp:paragraph --> <!-- wp:paragraph --> <p>Work is another important activity where we see large differences. Countries are sorted by paid work hours in the chart – from highest to lowest. In China and Mexico people spend, on an average day, almost twice as much time on paid work as people in Italy and France do. This is a general pattern: <a rel="noreferrer noopener" href="https://ourworldindata.org/time-use#do-workers-in-richer-countries-work-longer-hours" data-type="URL" data-id="https://ourworldindata.org/time-use#do-workers-in-richer-countries-work-longer-hours" target="_blank">People in richer countries can afford to work less</a>. Keep in mind that this chart shows the average for all people in the working age bracket, from 15 to 64 years, whether they are actually employed or not.{ref}Because these estimates include people who are not employed they are much lower than the estimates of working hours <em>per</em> <em>worker</em> <a rel="noreferrer noopener" target="_blank" href="https://ourworldindata.org/time-use#time-spent-working">we present elsewhere</a>. The estimates also differ because of differences in the sources: time-use surveys compared to labor force surveys and national accounts data.{/ref}</p> <!-- /wp:paragraph --> <!-- wp:paragraph --> <p>Differences in <a rel="noreferrer noopener" href="https://ourworldindata.org/age-structure" target="_blank">demographics</a>, <a rel="noreferrer noopener" href="https://ourworldindata.org/global-education" target="_blank">education</a> and <a rel="noreferrer noopener" href="https://ourworldindata.org/economic-growth" target="_blank">economic prosperity</a> all contribute to these inequalities in work and time use. But what’s clear in the chart here is that there are also some differences in time use that are not well explained by economic or demographic differences. In the UK, for example, people spend more time working than in France; but in both countries people report spending a similar amount of time on leisure activities.</p> <!-- /wp:paragraph --> <!-- wp:paragraph --> <p>Cultural differences are likely to play a role here. The French seem to spend much more time eating than the British – and in this respect the data actually goes in line with stereotypes about food culture. People in France, Greece, Italy and Spain report spending more time eating than people in most other European countries. The country where people spend the least time eating and drinking is the USA (63 minutes).</p> <!-- /wp:paragraph --></div> <!-- /wp:column --> <!-- wp:column --> <div class="wp-block-column"><!-- wp:heading {"level":6} --> <h6>How do people spend their time?{ref}OECD (2020) <a rel="noreferrer noopener" href="https://stats.oecd.org/Index.aspx?DataSetCode=TIME_USE" target="_blank">Time Use Database.</a>{/ref}</h6> <!-- /wp:heading --> <!-- wp:image {"id":37744,"width":764,"height":574,"sizeSlug":"large"} --> <figure class="wp-block-image size-large is-resized"><img src="https://owid.cloud/app/uploads/2020/11/Time-Use-by-Country-OECD-732x550.png" alt="" class="wp-image-37744" width="764" height="574"/></figure> <!-- /wp:image --> <!-- wp:paragraph --> <p><a href="https://owid.cloud/app/uploads/2020/12/Time-Use-in-OECD-Countries-OECD.xlsx" data-type="URL" data-id="https://owid.cloud/app/uploads/2020/12/Time-Use-in-OECD-Countries-OECD.xlsx">Download the underlying data for this chart (.xlsx)</a></p> <!-- /wp:paragraph --></div> <!-- /wp:column --></div> <!-- /wp:columns --> <!-- wp:heading {"level":4} --> <h4>Going beyond averages: The gender gap in leisure time</h4> <!-- /wp:heading --> <!-- wp:paragraph --> <p>Going beyond national averages reveals important within-country inequalities. The gender gap in leisure time, for example, is a key dimension along which large inequalities exist.</p> <!-- /wp:paragraph --> <!-- wp:paragraph --> <p>The chart here relies on the same time-use data described above, but shows total leisure time for men and women separately. Time for men is shown on the horizontal axis, while time for women appears on the vertical axis. The dotted diagonal line denotes ‘gender parity’, so the further away a country is from the diagonal line, the larger the difference between men and women.</p> <!-- /wp:paragraph --> <!-- wp:paragraph --> <p>As we can see, in all countries the average leisure time for men is higher than for women – all bubbles are below the diagonal line – but in some countries the gaps are much larger. In Norway the difference is very small, while in Portugal men report almost 50% more leisure time than women.</p> <!-- /wp:paragraph --> <!-- wp:paragraph --> <p>A key factor driving these differences in leisure time is the gender gap in unpaid work. As we explain in detail in a <a rel="noreferrer noopener" href="https://ourworldindata.org/female-labor-supply#informal-work-unpaid-care-work" target="_blank">companion post</a>, women are responsible for a disproportionate amount of unpaid work, and have less leisure as a result.{ref}If you want to dig deeper you can explore gender differences across all other activities directly from our source, via the <a rel="noreferrer noopener" href="https://stats.oecd.org/Index.aspx?DataSetCode=TIME_USE" target="_blank">OECD Data Portal</a>. And you can read more about within-country inequalities in time use along other dimensions, such as income and education, in <a rel="noreferrer noopener" href="https://scholar.google.com/scholar?hl=es&as_sdt=0%2C5&q=The+Middle+Class+Time+Squeeze%2C+Economic+Studies+at+Brookings%2C+Sawhill+and+Guyot+%282020%29&btnG=" target="_blank">this Brookings Paper</a>, where the authors focus on the ‘middle class time squeeze’ in the US. See: Sawhill, I. V., & Guyot, K. (2020). The Middle Class Time Squeeze. Economic Studies at Brookings. Brookings Institution.{/ref}</p> <!-- /wp:paragraph --> <!-- wp:html --> <iframe src="https://ourworldindata.org/grapher/minutes-spent-on-leisure?tab=chart&stackMode=absolute&time=latest&country=&region=World" loading="lazy" style="width: 100%; height: 600px; border: 0px none;"></iframe> <!-- /wp:html --> <!-- wp:heading {"level":4} --> <h4>Why should we care about differences in time use?</h4> <!-- /wp:heading --> <!-- wp:columns --> <div class="wp-block-columns"><!-- wp:column --> <div class="wp-block-column"><!-- wp:paragraph --> <p>Every single one of us has the same “time budget”: 24 hours per day and 365 days per year. But of course not all of us can choose to spend time on the activities that we enjoy most. Differences in our freedom to allocate time to the things we enjoy is the main reason why time-use data is important for studying living conditions.</p> <!-- /wp:paragraph --> <!-- wp:paragraph --> <p>In the UK, researchers from the <a rel="noreferrer noopener" href="https://www.timeuse.org/" target="_blank">Centre for Time Use Research</a> linked time-use diaries with the respondents’ assessments of enjoyment, on a scale from 1 to 7, to better understand the connection between time use and well-being. The chart here, which we’ve adapted from the book ‘What We Really Do All Day’<em>, </em>by professors Jonathan Gershuny and Oriel Sullivan, shows the results. The estimates correspond to average reported levels of enjoyment for each activity, with confidence intervals.{ref}The underlying data comes from time-use diaries where respondents are asked to record the sequence of what they do over a specific day, and how much they enjoy each ‘episode’ (i.e. what they do) on a scale from 1 to 7. All episodes reported are then coded and grouped into similar activities. To arrive at the mean enjoyment scores, the authors multiply the duration of each episode where the activity category concerned is the primary activity recorded, by the enjoyment level to arrive at the total enjoyment score for that episode. Then they sum these total enjoyment scores for each category of activity across the day, and finally divide these daily enjoyment total scores for each activity by the amount of time devoted to the activity. In this way, they arrive at an appropriately weighted mean enjoyment level for each activity across all those who engage in it. For more details see Gershuny, J., & Sullivan, O. (2019). What We Really Do All Day: Insights from the Centre for Time Use Research. Penguin UK.{/ref}</p> <!-- /wp:paragraph --> <!-- wp:paragraph --> <p>We see that the most enjoyed activities involve rest or leisure activities such as eating out, sleeping, going to sports events, playing computer games or attending cultural performances. The activities receiving the lowest ratings include doing school homework, looking for a job, or doing housework.</p> <!-- /wp:paragraph --> <!-- wp:paragraph --> <p>The activity where people show the greatest variation in enjoyment is working a “Second Job”. This likely reflects the difference between people who work a second job because they want to, and those who work a second job because they <em>have</em> <em>to</em>.</p> <!-- /wp:paragraph --> <!-- wp:paragraph --> <p>So what do we learn from this?</p> <!-- /wp:paragraph --> <!-- wp:paragraph --> <p>First, we learn that the enjoyment of activities is, at least to some degree, predictable and stable. This means we can take activity groups and make meaningful comparisons across groups of people. Economists, for example, <a rel="noreferrer noopener" href="https://scholar.google.com/scholar?hl=es&as_sdt=0%2C5&q=Ramey%2C+V.+A.%2C+%26+Francis%2C+N.+%282009%29.+A+century+of+work+and+leisure.+American+Economic+Journal%3A+Macroeconomics%2C+1%282%29%2C+189-224.&btnG=" target="_blank">often classify</a> any activity with an enjoyment level below work as a “non-leisure activity”, in order to measure trends in leisure across people and time.{ref}You find a very clear and complete explanation of this in Ramey, V. A., & Francis, N. (2009). A century of work and leisure. American Economic Journal: Macroeconomics, 1(2), 189-224.{/ref}</p> <!-- /wp:paragraph --> <!-- wp:paragraph --> <p>But beyond this, and more importantly, this confirms that time-use is informative about well-being.</p> <!-- /wp:paragraph --> <!-- wp:paragraph --> <p>The fact that there is a very clear and predictable pattern in the enjoyment of activities suggests that differences in time use do, indeed, give us meaningful perspectives on living conditions and economic opportunities. In countries where people do more paid and unpaid work, and have less time for leisure, their enjoyment – and <a rel="noreferrer noopener" href="https://ourworldindata.org/happiness-and-life-satisfaction" target="_blank">happiness and life satisfaction</a> – levels are likely to be lower.</p> <!-- /wp:paragraph --></div> <!-- /wp:column --> <!-- wp:column --> <div class="wp-block-column"><!-- wp:heading {"level":6} --> <h6>How do people rate the enjoyment of different activities?{ref}Gershuny, J., & Sullivan, O. (2019). What We Really Do All Day: Insights from the Centre for Time Use Research. Penguin UK.{/ref}</h6> <!-- /wp:heading --> <!-- wp:image {"id":37746,"width":615,"height":930,"sizeSlug":"large"} --> <figure class="wp-block-image size-large is-resized"><img src="https://owid.cloud/app/uploads/2020/11/Enjoyment-Level-of-Time-Use-364x550.png" alt="" class="wp-image-37746" width="615" height="930"/></figure> <!-- /wp:image --></div> <!-- /wp:column --></div> <!-- /wp:columns --> | { "id": "wp-37838", "slug": "untitled-reusable-block-235", "content": { "toc": [], "body": [ { "type": "text", "value": [ { "text": "Sleep, work, eat, leisure \u2013 at a high level most of us spend time on similar activities. But just how similar are the daily activities of people across the world? This is something worth considering, not just to serve our curiosity but because differences in the way we spend time give us meaningful perspectives on living conditions, economic opportunities and general well-being.", "spanType": "span-simple-text" } ], "parseErrors": [] }, { "type": "text", "value": [ { "text": "Here we take a look at the data. We explore some of the key patterns that emerge from cross-country time use surveys, and then dig deeper to understand how these differences matter for people\u2019s well-being.", "spanType": "span-simple-text" } ], "parseErrors": [] }, { "text": [ { "text": "Daily activities: similarities and differences across countries", "spanType": "span-simple-text" } ], "type": "heading", "level": 2, "parseErrors": [] }, { "left": [ { "type": "text", "value": [ { "text": "In the chart here we compare average time spent across a number of common activities. The data comes from the OECD and brings together estimates from time diaries where respondents are asked to record the sequence of what they did over a specific day, as well as from general questionnaires where respondents are asked to recall the amount of time spent on different activities on a specific day in the previous week.{ref}The \u2018time-diary method\u2019 is generally more reliable and allows a richer analysis of routines, because it measures not only aggregate times but also sequences and clock-times. Time-diary data is less common, but it is available for some countries from the ", "spanType": "span-simple-text" }, { "url": "https://www.timeuse.org/mtus", "children": [ { "text": "Multinational Time Use Study", "spanType": "span-simple-text" } ], "spanType": "span-link" }, { "text": ". We explore time-use \u2018tempograms\u2019 from the MTUS in a forthcoming companion post.{/ref}", "spanType": "span-simple-text" } ], "parseErrors": [] }, { "type": "text", "value": [ { "text": "The first thing that jumps out from this chart is that there are indeed many similarities across countries.", "spanType": "span-simple-text" } ], "parseErrors": [] }, { "type": "text", "value": [ { "text": "This is not surprising \u2013 most of us try to split our days into \u201cwork, rest and fun\u201d, and so there are some predictable patterns. We spend the most time working and sleeping; and paid work, housework, leisure, eating and sleeping take together 80-90% of the 1440 minutes that we all have available every day.", "spanType": "span-simple-text" } ], "parseErrors": [] }, { "type": "text", "value": [ { "text": "But if we look closely, we also see some important differences. Consider sleeping, for example. From this sample of countries, South Koreans sleep the least \u2013 averaging 7 hours and 51 minutes of sleep every day. In India and the US, at the other end of the spectrum, people sleep an hour more on average.", "spanType": "span-simple-text" } ], "parseErrors": [] }, { "type": "text", "value": [ { "text": "Work is another important activity where we see large differences. Countries are sorted by paid work hours in the chart \u2013 from highest to lowest. In China and Mexico people spend, on an average day, almost twice as much time on paid work as people in Italy and France do. This is a general pattern: ", "spanType": "span-simple-text" }, { "url": "https://ourworldindata.org/time-use#do-workers-in-richer-countries-work-longer-hours", "children": [ { "text": "People in richer countries can afford to work less", "spanType": "span-simple-text" } ], "spanType": "span-link" }, { "text": ". Keep in mind that this chart shows the average for all people in the working age bracket, from 15 to 64 years, whether they are actually employed or not.{ref}Because these estimates include people who are not employed they are much lower than the estimates of working hours\u00a0", "spanType": "span-simple-text" }, { "children": [ { "text": "per", "spanType": "span-simple-text" } ], "spanType": "span-italic" }, { "children": [ { "text": "worker", "spanType": "span-simple-text" } ], "spanType": "span-italic" }, { "url": "https://ourworldindata.org/time-use#time-spent-working", "children": [ { "text": "we present elsewhere", "spanType": "span-simple-text" } ], "spanType": "span-link" }, { "text": ". The estimates also differ because of differences in the sources: time-use surveys compared to labor force surveys and national accounts data.{/ref}", "spanType": "span-simple-text" } ], "parseErrors": [] }, { "type": "text", "value": [ { "text": "Differences in ", "spanType": "span-simple-text" }, { "url": "https://ourworldindata.org/age-structure", "children": [ { "text": "demographics", "spanType": "span-simple-text" } ], "spanType": "span-link" }, { "text": ", ", "spanType": "span-simple-text" }, { "url": "https://ourworldindata.org/global-education", "children": [ { "text": "education", "spanType": "span-simple-text" } ], "spanType": "span-link" }, { "text": " and ", "spanType": "span-simple-text" }, { "url": "https://ourworldindata.org/economic-growth", "children": [ { "text": "economic prosperity", "spanType": "span-simple-text" } ], "spanType": "span-link" }, { "text": " all contribute to these inequalities in work and time use. But what\u2019s clear in the chart here is that there are also some differences in time use that are not well explained by economic or demographic differences. In the UK, for example, people spend more time working than in France; but in both countries people report spending a similar amount of time on leisure activities.", "spanType": "span-simple-text" } ], "parseErrors": [] }, { "type": "text", "value": [ { "text": "Cultural differences are likely to play a role here. The French seem to spend much more time eating than the British \u2013 and in this respect the data actually goes in line with stereotypes about food culture. People in France, Greece, Italy and Spain report spending more time eating than people in most other European countries. The country where people spend the least time eating and drinking is the USA (63 minutes).", "spanType": "span-simple-text" } ], "parseErrors": [] } ], "type": "sticky-right", "right": [ { "text": [ { "text": "How do people spend their time?{ref}OECD (2020) ", "spanType": "span-simple-text" }, { "url": "https://stats.oecd.org/Index.aspx?DataSetCode=TIME_USE", "children": [ { "text": "Time Use Database.", "spanType": "span-simple-text" } ], "spanType": "span-link" }, { "text": "{/ref}", "spanType": "span-simple-text" } ], "type": "heading", "level": 6, "parseErrors": [] }, { "alt": "", "size": "wide", "type": "image", "filename": "Time-Use-by-Country-OECD.png", "parseErrors": [] }, { "type": "text", "value": [ { "url": "https://owid.cloud/app/uploads/2020/12/Time-Use-in-OECD-Countries-OECD.xlsx", "children": [ { "text": "Download the underlying data for this chart (.xlsx)", "spanType": "span-simple-text" } ], "spanType": "span-link" } ], "parseErrors": [] } ], "parseErrors": [] }, { "text": [ { "text": "Going beyond averages: The gender gap in leisure time", "spanType": "span-simple-text" } ], "type": "heading", "level": 2, "parseErrors": [] }, { "type": "text", "value": [ { "text": "Going beyond national averages reveals important within-country inequalities. The gender gap in leisure time, for example, is a key dimension along which large inequalities exist.", "spanType": "span-simple-text" } ], "parseErrors": [] }, { "type": "text", "value": [ { "text": "The chart here relies on the same time-use data described above, but shows total leisure time for men and women separately. Time for men is shown on the horizontal axis, while time for women appears on the vertical axis. The dotted diagonal line denotes \u2018gender parity\u2019, so the further away a country is from the diagonal line, the larger the difference between men and women.", "spanType": "span-simple-text" } ], "parseErrors": [] }, { "type": "text", "value": [ { "text": "As we can see, in all countries the average leisure time for men is higher than for women \u2013 all bubbles are below the diagonal line \u2013 but in some countries the gaps are much larger. In Norway the difference is very small, while in Portugal men report almost 50% more leisure time than women.", "spanType": "span-simple-text" } ], "parseErrors": [] }, { "type": "text", "value": [ { "text": "A key factor driving these differences in leisure time is the gender gap in unpaid work. As we explain in detail in a ", "spanType": "span-simple-text" }, { "url": "https://ourworldindata.org/female-labor-supply#informal-work-unpaid-care-work", "children": [ { "text": "companion post", "spanType": "span-simple-text" } ], "spanType": "span-link" }, { "text": ", women are responsible for a disproportionate amount of unpaid work, and have less leisure as a result.{ref}If you want to dig deeper you can explore gender differences across all other activities directly from our source, via the ", "spanType": "span-simple-text" }, { "url": "https://stats.oecd.org/Index.aspx?DataSetCode=TIME_USE", "children": [ { "text": "OECD Data Portal", "spanType": "span-simple-text" } ], "spanType": "span-link" }, { "text": ". And you can read more about within-country inequalities in time use along other dimensions, such as income and education, in ", "spanType": "span-simple-text" }, { "url": "https://scholar.google.com/scholar?hl=es&as_sdt=0%2C5&q=The+Middle+Class+Time+Squeeze%2C+Economic+Studies+at+Brookings%2C+Sawhill+and+Guyot+%282020%29&btnG=", "children": [ { "text": "this Brookings Paper", "spanType": "span-simple-text" } ], "spanType": "span-link" }, { "text": ", where the authors focus on the \u2018middle class time squeeze\u2019 in the US. See: Sawhill, I. V., & Guyot, K. (2020). The Middle Class Time Squeeze. Economic Studies at Brookings. Brookings Institution.{/ref}", "spanType": "span-simple-text" } ], "parseErrors": [] }, { "url": "https://ourworldindata.org/grapher/minutes-spent-on-leisure?tab=chart&stackMode=absolute&time=latest&country=®ion=World", "type": "chart", "parseErrors": [] }, { "text": [ { "text": "Why should we care about differences in time use?", "spanType": "span-simple-text" } ], "type": "heading", "level": 2, "parseErrors": [] }, { "left": [ { "type": "text", "value": [ { "text": "Every single one of us has the same \u201ctime budget\u201d: 24 hours per day and 365 days per year. But of course not all of us can choose to spend time on the activities that we enjoy most. Differences in our freedom to allocate time to the things we enjoy is the main reason why time-use data is important for studying living conditions.", "spanType": "span-simple-text" } ], "parseErrors": [] }, { "type": "text", "value": [ { "text": "In the UK, researchers from the ", "spanType": "span-simple-text" }, { "url": "https://www.timeuse.org/", "children": [ { "text": "Centre for Time Use Research", "spanType": "span-simple-text" } ], "spanType": "span-link" }, { "text": " linked time-use diaries with the respondents\u2019 assessments of enjoyment, on a scale from 1 to 7, to better understand the connection between time use and well-being. The chart here, which we\u2019ve adapted from the book \u2018What We Really Do All Day\u2019", "spanType": "span-simple-text" }, { "children": [ { "text": ", ", "spanType": "span-simple-text" } ], "spanType": "span-italic" }, { "text": "by professors Jonathan Gershuny and Oriel Sullivan, shows the results. The estimates correspond to average reported levels of enjoyment for each activity, with confidence intervals.{ref}The underlying data comes from time-use diaries where respondents are asked to record the sequence of what they do over a specific day, and how much they enjoy each \u2018episode\u2019 (i.e. what they do) on a scale from 1 to 7. All episodes reported are then coded and grouped into similar activities. To arrive at the mean enjoyment scores, the authors multiply the duration of each episode where the activity category concerned is the primary activity recorded, by the enjoyment level to arrive at the total enjoyment score for that episode. Then they sum these total enjoyment scores for each category of activity across the day, and finally divide these daily enjoyment total scores for each activity by the amount of time devoted to the activity. In this way, they arrive at an appropriately weighted mean enjoyment level for each activity across all those who engage in it. For more details see Gershuny, J., & Sullivan, O. (2019). What We Really Do All Day: Insights from the Centre for Time Use Research. Penguin UK.{/ref}", "spanType": "span-simple-text" } ], "parseErrors": [] }, { "type": "text", "value": [ { "text": "We see that the most enjoyed activities involve rest or leisure activities such as eating out, sleeping, going to sports events, playing computer games or attending cultural performances. The activities receiving the lowest ratings include doing school homework, looking for a job, or doing housework.", "spanType": "span-simple-text" } ], "parseErrors": [] }, { "type": "text", "value": [ { "text": "The activity where people show the greatest variation in enjoyment is working a \u201cSecond Job\u201d. This likely reflects the difference between people who work a second job because they want to, and those who work a second job because they ", "spanType": "span-simple-text" }, { "children": [ { "text": "have", "spanType": "span-simple-text" } ], "spanType": "span-italic" }, { "children": [ { "text": "to", "spanType": "span-simple-text" } ], "spanType": "span-italic" }, { "text": ".", "spanType": "span-simple-text" } ], "parseErrors": [] }, { "type": "text", "value": [ { "text": "So what do we learn from this?", "spanType": "span-simple-text" } ], "parseErrors": [] }, { "type": "text", "value": [ { "text": "First, we learn that the enjoyment of activities is, at least to some degree, predictable and stable. This means we can take activity groups and make meaningful comparisons across groups of people. Economists, for example, ", "spanType": "span-simple-text" }, { "url": "https://scholar.google.com/scholar?hl=es&as_sdt=0%2C5&q=Ramey%2C+V.+A.%2C+%26+Francis%2C+N.+%282009%29.+A+century+of+work+and+leisure.+American+Economic+Journal%3A+Macroeconomics%2C+1%282%29%2C+189-224.&btnG=", "children": [ { "text": "often classify", "spanType": "span-simple-text" } ], "spanType": "span-link" }, { "text": " any activity with an enjoyment level below work as a \u201cnon-leisure activity\u201d, in order to measure trends in leisure across people and time.{ref}You find a very clear and complete explanation of this in Ramey, V. A., & Francis, N. (2009). A century of work and leisure. American Economic Journal: Macroeconomics, 1(2), 189-224.{/ref}", "spanType": "span-simple-text" } ], "parseErrors": [] }, { "type": "text", "value": [ { "text": "But beyond this, and more importantly, this confirms that time-use is informative about well-being.", "spanType": "span-simple-text" } ], "parseErrors": [] }, { "type": "text", "value": [ { "text": "The fact that there is a very clear and predictable pattern in the enjoyment of activities suggests that differences in time use do, indeed, give us meaningful perspectives on living conditions and economic opportunities. In countries where people do more paid and unpaid work, and have less time for leisure, their enjoyment \u2013 and ", "spanType": "span-simple-text" }, { "url": "https://ourworldindata.org/happiness-and-life-satisfaction", "children": [ { "text": "happiness and life satisfaction", "spanType": "span-simple-text" } ], "spanType": "span-link" }, { "text": " \u2013 levels are likely to be lower.", "spanType": "span-simple-text" } ], "parseErrors": [] } ], "type": "sticky-right", "right": [ { "text": [ { "text": "How do people rate the enjoyment of different activities?{ref}Gershuny, J., & Sullivan, O. (2019). What We Really Do All Day: Insights from the Centre for Time Use Research. Penguin UK.{/ref}", "spanType": "span-simple-text" } ], "type": "heading", "level": 6, "parseErrors": [] }, { "alt": "", "size": "wide", "type": "image", "filename": "Enjoyment-Level-of-Time-Use.png", "parseErrors": [] } ], "parseErrors": [] } ], "type": "article", "title": "How do people across the world spend their time and what does this tell us about living conditions?", "authors": [ null ], "dateline": "November 29, 2020", "sidebar-toc": false, "featured-image": "" }, "createdAt": "2020-11-29T21:38:41.000Z", "published": false, "updatedAt": "2020-12-08T22:27:57.000Z", "revisionId": null, "publishedAt": "2020-11-29T21:38:30.000Z", "relatedCharts": [], "publicationContext": "listed" } |
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2020-11-29 21:38:30 | 2024-02-16 14:23:01 | [ null ] |
2020-11-29 21:38:41 | 2020-12-08 22:27:57 | {} |
Sleep, work, eat, leisure – at a high level most of us spend time on similar activities. But just how similar are the daily activities of people across the world? This is something worth considering, not just to serve our curiosity but because differences in the way we spend time give us meaningful perspectives on living conditions, economic opportunities and general well-being. Here we take a look at the data. We explore some of the key patterns that emerge from cross-country time use surveys, and then dig deeper to understand how these differences matter for people’s well-being. ## Daily activities: similarities and differences across countries In the chart here we compare average time spent across a number of common activities. The data comes from the OECD and brings together estimates from time diaries where respondents are asked to record the sequence of what they did over a specific day, as well as from general questionnaires where respondents are asked to recall the amount of time spent on different activities on a specific day in the previous week.{ref}The ‘time-diary method’ is generally more reliable and allows a richer analysis of routines, because it measures not only aggregate times but also sequences and clock-times. Time-diary data is less common, but it is available for some countries from the [Multinational Time Use Study](https://www.timeuse.org/mtus). We explore time-use ‘tempograms’ from the MTUS in a forthcoming companion post.{/ref} The first thing that jumps out from this chart is that there are indeed many similarities across countries. This is not surprising – most of us try to split our days into “work, rest and fun”, and so there are some predictable patterns. We spend the most time working and sleeping; and paid work, housework, leisure, eating and sleeping take together 80-90% of the 1440 minutes that we all have available every day. But if we look closely, we also see some important differences. Consider sleeping, for example. From this sample of countries, South Koreans sleep the least – averaging 7 hours and 51 minutes of sleep every day. In India and the US, at the other end of the spectrum, people sleep an hour more on average. Work is another important activity where we see large differences. Countries are sorted by paid work hours in the chart – from highest to lowest. In China and Mexico people spend, on an average day, almost twice as much time on paid work as people in Italy and France do. This is a general pattern: [People in richer countries can afford to work less](https://ourworldindata.org/time-use#do-workers-in-richer-countries-work-longer-hours). Keep in mind that this chart shows the average for all people in the working age bracket, from 15 to 64 years, whether they are actually employed or not.{ref}Because these estimates include people who are not employed they are much lower than the estimates of working hours _per__worker_[we present elsewhere](https://ourworldindata.org/time-use#time-spent-working). The estimates also differ because of differences in the sources: time-use surveys compared to labor force surveys and national accounts data.{/ref} Differences in [demographics](https://ourworldindata.org/age-structure), [education](https://ourworldindata.org/global-education) and [economic prosperity](https://ourworldindata.org/economic-growth) all contribute to these inequalities in work and time use. But what’s clear in the chart here is that there are also some differences in time use that are not well explained by economic or demographic differences. In the UK, for example, people spend more time working than in France; but in both countries people report spending a similar amount of time on leisure activities. Cultural differences are likely to play a role here. The French seem to spend much more time eating than the British – and in this respect the data actually goes in line with stereotypes about food culture. People in France, Greece, Italy and Spain report spending more time eating than people in most other European countries. The country where people spend the least time eating and drinking is the USA (63 minutes). ###### How do people spend their time?{ref}OECD (2020) [Time Use Database.](https://stats.oecd.org/Index.aspx?DataSetCode=TIME_USE){/ref} <Image filename="Time-Use-by-Country-OECD.png" alt=""/> [Download the underlying data for this chart (.xlsx)](https://owid.cloud/app/uploads/2020/12/Time-Use-in-OECD-Countries-OECD.xlsx) ## Going beyond averages: The gender gap in leisure time Going beyond national averages reveals important within-country inequalities. The gender gap in leisure time, for example, is a key dimension along which large inequalities exist. The chart here relies on the same time-use data described above, but shows total leisure time for men and women separately. Time for men is shown on the horizontal axis, while time for women appears on the vertical axis. The dotted diagonal line denotes ‘gender parity’, so the further away a country is from the diagonal line, the larger the difference between men and women. As we can see, in all countries the average leisure time for men is higher than for women – all bubbles are below the diagonal line – but in some countries the gaps are much larger. In Norway the difference is very small, while in Portugal men report almost 50% more leisure time than women. A key factor driving these differences in leisure time is the gender gap in unpaid work. As we explain in detail in a [companion post](https://ourworldindata.org/female-labor-supply#informal-work-unpaid-care-work), women are responsible for a disproportionate amount of unpaid work, and have less leisure as a result.{ref}If you want to dig deeper you can explore gender differences across all other activities directly from our source, via the [OECD Data Portal](https://stats.oecd.org/Index.aspx?DataSetCode=TIME_USE). And you can read more about within-country inequalities in time use along other dimensions, such as income and education, in [this Brookings Paper](https://scholar.google.com/scholar?hl=es&as_sdt=0%2C5&q=The+Middle+Class+Time+Squeeze%2C+Economic+Studies+at+Brookings%2C+Sawhill+and+Guyot+%282020%29&btnG=), where the authors focus on the ‘middle class time squeeze’ in the US. See: Sawhill, I. V., & Guyot, K. (2020). The Middle Class Time Squeeze. Economic Studies at Brookings. Brookings Institution.{/ref} <Chart url="https://ourworldindata.org/grapher/minutes-spent-on-leisure?tab=chart&stackMode=absolute&time=latest&country=®ion=World"/> ## Why should we care about differences in time use? Every single one of us has the same “time budget”: 24 hours per day and 365 days per year. But of course not all of us can choose to spend time on the activities that we enjoy most. Differences in our freedom to allocate time to the things we enjoy is the main reason why time-use data is important for studying living conditions. In the UK, researchers from the [Centre for Time Use Research](https://www.timeuse.org/) linked time-use diaries with the respondents’ assessments of enjoyment, on a scale from 1 to 7, to better understand the connection between time use and well-being. The chart here, which we’ve adapted from the book ‘What We Really Do All Day’_, _by professors Jonathan Gershuny and Oriel Sullivan, shows the results. The estimates correspond to average reported levels of enjoyment for each activity, with confidence intervals.{ref}The underlying data comes from time-use diaries where respondents are asked to record the sequence of what they do over a specific day, and how much they enjoy each ‘episode’ (i.e. what they do) on a scale from 1 to 7. All episodes reported are then coded and grouped into similar activities. To arrive at the mean enjoyment scores, the authors multiply the duration of each episode where the activity category concerned is the primary activity recorded, by the enjoyment level to arrive at the total enjoyment score for that episode. Then they sum these total enjoyment scores for each category of activity across the day, and finally divide these daily enjoyment total scores for each activity by the amount of time devoted to the activity. In this way, they arrive at an appropriately weighted mean enjoyment level for each activity across all those who engage in it. For more details see Gershuny, J., & Sullivan, O. (2019). What We Really Do All Day: Insights from the Centre for Time Use Research. Penguin UK.{/ref} We see that the most enjoyed activities involve rest or leisure activities such as eating out, sleeping, going to sports events, playing computer games or attending cultural performances. The activities receiving the lowest ratings include doing school homework, looking for a job, or doing housework. The activity where people show the greatest variation in enjoyment is working a “Second Job”. This likely reflects the difference between people who work a second job because they want to, and those who work a second job because they _have__to_. So what do we learn from this? First, we learn that the enjoyment of activities is, at least to some degree, predictable and stable. This means we can take activity groups and make meaningful comparisons across groups of people. Economists, for example, [often classify](https://scholar.google.com/scholar?hl=es&as_sdt=0%2C5&q=Ramey%2C+V.+A.%2C+%26+Francis%2C+N.+%282009%29.+A+century+of+work+and+leisure.+American+Economic+Journal%3A+Macroeconomics%2C+1%282%29%2C+189-224.&btnG=) any activity with an enjoyment level below work as a “non-leisure activity”, in order to measure trends in leisure across people and time.{ref}You find a very clear and complete explanation of this in Ramey, V. A., & Francis, N. (2009). A century of work and leisure. American Economic Journal: Macroeconomics, 1(2), 189-224.{/ref} But beyond this, and more importantly, this confirms that time-use is informative about well-being. The fact that there is a very clear and predictable pattern in the enjoyment of activities suggests that differences in time use do, indeed, give us meaningful perspectives on living conditions and economic opportunities. In countries where people do more paid and unpaid work, and have less time for leisure, their enjoyment – and [happiness and life satisfaction](https://ourworldindata.org/happiness-and-life-satisfaction) – levels are likely to be lower. ###### How do people rate the enjoyment of different activities?{ref}Gershuny, J., & Sullivan, O. (2019). What We Really Do All Day: Insights from the Centre for Time Use Research. Penguin UK.{/ref} <Image filename="Enjoyment-Level-of-Time-Use.png" alt=""/> | { "data": { "wpBlock": { "content": "\n<p>Sleep, work, eat, leisure \u2013 at a high level most of us spend time on similar activities. But just how similar are the daily activities of people across the world? This is something worth considering, not just to serve our curiosity but because differences in the way we spend time give us meaningful perspectives on living conditions, economic opportunities and general well-being.</p>\n\n\n\n<p>Here we take a look at the data. We explore some of the key patterns that emerge from cross-country time use surveys, and then dig deeper to understand how these differences matter for people\u2019s well-being.</p>\n\n\n\n<h4>Daily activities: similarities and differences across countries</h4>\n\n\n\n<div class=\"wp-block-columns\">\n<div class=\"wp-block-column\">\n<p>In the chart here we compare average time spent across a number of common activities. The data comes from the OECD and brings together estimates from time diaries where respondents are asked to record the sequence of what they did over a specific day, as well as from general questionnaires where respondents are asked to recall the amount of time spent on different activities on a specific day in the previous week.{ref}The \u2018time-diary method\u2019 is generally more reliable and allows a richer analysis of routines, because it measures not only aggregate times but also sequences and clock-times. Time-diary data is less common, but it is available for some countries from the <a rel=\"noreferrer noopener\" href=\"https://www.timeuse.org/mtus\" target=\"_blank\">Multinational Time Use Study</a>. We explore time-use \u2018tempograms\u2019 from the MTUS in a forthcoming companion post.{/ref}</p>\n\n\n\n<p>The first thing that jumps out from this chart is that there are indeed many similarities across countries.</p>\n\n\n\n<p>This is not surprising \u2013 most of us try to split our days into \u201cwork, rest and fun\u201d, and so there are some predictable patterns. We spend the most time working and sleeping; and paid work, housework, leisure, eating and sleeping take together 80-90% of the 1440 minutes that we all have available every day.</p>\n\n\n\n<p>But if we look closely, we also see some important differences. Consider sleeping, for example. From this sample of countries, South Koreans sleep the least \u2013 averaging 7 hours and 51 minutes of sleep every day. In India and the US, at the other end of the spectrum, people sleep an hour more on average.</p>\n\n\n\n<p>Work is another important activity where we see large differences. Countries are sorted by paid work hours in the chart \u2013 from highest to lowest. In China and Mexico people spend, on an average day, almost twice as much time on paid work as people in Italy and France do. This is a general pattern: <a rel=\"noreferrer noopener\" href=\"https://ourworldindata.org/time-use#do-workers-in-richer-countries-work-longer-hours\" data-type=\"URL\" data-id=\"https://ourworldindata.org/time-use#do-workers-in-richer-countries-work-longer-hours\" target=\"_blank\">People in richer countries can afford to work less</a>. Keep in mind that this chart shows the average for all people in the working age bracket, from 15 to 64 years, whether they are actually employed or not.{ref}Because these estimates include people who are not employed they are much lower than the estimates of working hours <em>per</em> <em>worker</em> <a rel=\"noreferrer noopener\" target=\"_blank\" href=\"https://ourworldindata.org/time-use#time-spent-working\">we present elsewhere</a>. The estimates also differ because of differences in the sources: time-use surveys compared to labor force surveys and national accounts data.{/ref}</p>\n\n\n\n<p>Differences in <a rel=\"noreferrer noopener\" href=\"https://ourworldindata.org/age-structure\" target=\"_blank\">demographics</a>, <a rel=\"noreferrer noopener\" href=\"https://ourworldindata.org/global-education\" target=\"_blank\">education</a> and <a rel=\"noreferrer noopener\" href=\"https://ourworldindata.org/economic-growth\" target=\"_blank\">economic prosperity</a> all contribute to these inequalities in work and time use. But what\u2019s clear in the chart here is that there are also some differences in time use that are not well explained by economic or demographic differences. In the UK, for example, people spend more time working than in France; but in both countries people report spending a similar amount of time on leisure activities.</p>\n\n\n\n<p>Cultural differences are likely to play a role here. The French seem to spend much more time eating than the British \u2013 and in this respect the data actually goes in line with stereotypes about food culture. People in France, Greece, Italy and Spain report spending more time eating than people in most other European countries. The country where people spend the least time eating and drinking is the USA (63 minutes).</p>\n</div>\n\n\n\n<div class=\"wp-block-column\">\n<h6>How do people spend their time?{ref}OECD (2020) <a rel=\"noreferrer noopener\" href=\"https://stats.oecd.org/Index.aspx?DataSetCode=TIME_USE\" target=\"_blank\">Time Use Database.</a>{/ref}</h6>\n\n\n\n<figure class=\"wp-block-image size-large is-resized\"><img loading=\"lazy\" src=\"https://owid.cloud/app/uploads/2020/11/Time-Use-by-Country-OECD-732x550.png\" alt=\"\" class=\"wp-image-37744\" width=\"764\" height=\"574\" srcset=\"https://owid.cloud/app/uploads/2020/11/Time-Use-by-Country-OECD-732x550.png 732w, https://owid.cloud/app/uploads/2020/11/Time-Use-by-Country-OECD-400x300.png 400w, https://owid.cloud/app/uploads/2020/11/Time-Use-by-Country-OECD-150x113.png 150w, https://owid.cloud/app/uploads/2020/11/Time-Use-by-Country-OECD-768x577.png 768w, https://owid.cloud/app/uploads/2020/11/Time-Use-by-Country-OECD-1536x1154.png 1536w, https://owid.cloud/app/uploads/2020/11/Time-Use-by-Country-OECD.png 1752w\" sizes=\"(max-width: 764px) 100vw, 764px\" /></figure>\n\n\n\n<p><a href=\"https://owid.cloud/app/uploads/2020/12/Time-Use-in-OECD-Countries-OECD.xlsx\" data-type=\"URL\" data-id=\"https://owid.cloud/app/uploads/2020/12/Time-Use-in-OECD-Countries-OECD.xlsx\">Download the underlying data for this chart (.xlsx)</a></p>\n</div>\n</div>\n\n\n\n<h4>Going beyond averages: The gender gap in leisure time</h4>\n\n\n\n<p>Going beyond national averages reveals important within-country inequalities. The gender gap in leisure time, for example, is a key dimension along which large inequalities exist.</p>\n\n\n\n<p>The chart here relies on the same time-use data described above, but shows total leisure time for men and women separately. Time for men is shown on the horizontal axis, while time for women appears on the vertical axis. The dotted diagonal line denotes \u2018gender parity\u2019, so the further away a country is from the diagonal line, the larger the difference between men and women.</p>\n\n\n\n<p>As we can see, in all countries the average leisure time for men is higher than for women \u2013 all bubbles are below the diagonal line \u2013 but in some countries the gaps are much larger. In Norway the difference is very small, while in Portugal men report almost 50% more leisure time than women.</p>\n\n\n\n<p>A key factor driving these differences in leisure time is the gender gap in unpaid work. As we explain in detail in a <a rel=\"noreferrer noopener\" href=\"https://ourworldindata.org/female-labor-supply#informal-work-unpaid-care-work\" target=\"_blank\">companion post</a>, women are responsible for a disproportionate amount of unpaid work, and have less leisure as a result.{ref}If you want to dig deeper you can explore gender differences across all other activities directly from our source, via the <a rel=\"noreferrer noopener\" href=\"https://stats.oecd.org/Index.aspx?DataSetCode=TIME_USE\" target=\"_blank\">OECD Data Portal</a>. And you can read more about within-country inequalities in time use along other dimensions, such as income and education, in <a rel=\"noreferrer noopener\" href=\"https://scholar.google.com/scholar?hl=es&as_sdt=0%2C5&q=The+Middle+Class+Time+Squeeze%2C+Economic+Studies+at+Brookings%2C+Sawhill+and+Guyot+%282020%29&btnG=\" target=\"_blank\">this Brookings Paper</a>, where the authors focus on the \u2018middle class time squeeze\u2019 in the US. See: Sawhill, I. V., & Guyot, K. (2020). The Middle Class Time Squeeze. Economic Studies at Brookings. Brookings Institution.{/ref}</p>\n\n\n\n<iframe src=\"https://ourworldindata.org/grapher/minutes-spent-on-leisure?tab=chart&stackMode=absolute&time=latest&country=&region=World\" loading=\"lazy\" style=\"width: 100%; height: 600px; border: 0px none;\"></iframe>\n\n\n\n<h4>Why should we care about differences in time use?</h4>\n\n\n\n<div class=\"wp-block-columns\">\n<div class=\"wp-block-column\">\n<p>Every single one of us has the same \u201ctime budget\u201d: 24 hours per day and 365 days per year. But of course not all of us can choose to spend time on the activities that we enjoy most. Differences in our freedom to allocate time to the things we enjoy is the main reason why time-use data is important for studying living conditions.</p>\n\n\n\n<p>In the UK, researchers from the <a rel=\"noreferrer noopener\" href=\"https://www.timeuse.org/\" target=\"_blank\">Centre for Time Use Research</a> linked time-use diaries with the respondents\u2019 assessments of enjoyment, on a scale from 1 to 7, to better understand the connection between time use and well-being. The chart here, which we\u2019ve adapted from the book \u2018What We Really Do All Day\u2019<em>, </em>by professors Jonathan Gershuny and Oriel Sullivan, shows the results. The estimates correspond to average reported levels of enjoyment for each activity, with confidence intervals.{ref}The underlying data comes from time-use diaries where respondents are asked to record the sequence of what they do over a specific day, and how much they enjoy each \u2018episode\u2019 (i.e. what they do) on a scale from 1 to 7. All episodes reported are then coded and grouped into similar activities. To arrive at the mean enjoyment scores, the authors multiply the duration of each episode where the activity category concerned is the primary activity recorded, by the enjoyment level to arrive at the total enjoyment score for that episode. Then they sum these total enjoyment scores for each category of activity across the day, and finally divide these daily enjoyment total scores for each activity by the amount of time devoted to the activity. In this way, they arrive at an appropriately weighted mean enjoyment level for each activity across all those who engage in it. For more details see Gershuny, J., & Sullivan, O. (2019). What We Really Do All Day: Insights from the Centre for Time Use Research. Penguin UK.{/ref}</p>\n\n\n\n<p>We see that the most enjoyed activities involve rest or leisure activities such as eating out, sleeping, going to sports events, playing computer games or attending cultural performances. The activities receiving the lowest ratings include doing school homework, looking for a job, or doing housework.</p>\n\n\n\n<p>The activity where people show the greatest variation in enjoyment is working a \u201cSecond Job\u201d. This likely reflects the difference between people who work a second job because they want to, and those who work a second job because they <em>have</em> <em>to</em>.</p>\n\n\n\n<p>So what do we learn from this?</p>\n\n\n\n<p>First, we learn that the enjoyment of activities is, at least to some degree, predictable and stable. This means we can take activity groups and make meaningful comparisons across groups of people. Economists, for example, <a rel=\"noreferrer noopener\" href=\"https://scholar.google.com/scholar?hl=es&as_sdt=0%2C5&q=Ramey%2C+V.+A.%2C+%26+Francis%2C+N.+%282009%29.+A+century+of+work+and+leisure.+American+Economic+Journal%3A+Macroeconomics%2C+1%282%29%2C+189-224.&btnG=\" target=\"_blank\">often classify</a> any activity with an enjoyment level below work as a \u201cnon-leisure activity\u201d, in order to measure trends in leisure across people and time.{ref}You find a very clear and complete explanation of this in Ramey, V. A., & Francis, N. (2009). A century of work and leisure. American Economic Journal: Macroeconomics, 1(2), 189-224.{/ref}</p>\n\n\n\n<p>But beyond this, and more importantly, this confirms that time-use is informative about well-being.</p>\n\n\n\n<p>The fact that there is a very clear and predictable pattern in the enjoyment of activities suggests that differences in time use do, indeed, give us meaningful perspectives on living conditions and economic opportunities. In countries where people do more paid and unpaid work, and have less time for leisure, their enjoyment \u2013 and <a rel=\"noreferrer noopener\" href=\"https://ourworldindata.org/happiness-and-life-satisfaction\" target=\"_blank\">happiness and life satisfaction</a> \u2013 levels are likely to be lower.</p>\n</div>\n\n\n\n<div class=\"wp-block-column\">\n<h6>How do people rate the enjoyment of different activities?{ref}Gershuny, J., & Sullivan, O. (2019). What We Really Do All Day: Insights from the Centre for Time Use Research. Penguin UK.{/ref}</h6>\n\n\n\n<figure class=\"wp-block-image size-large is-resized\"><img loading=\"lazy\" src=\"https://owid.cloud/app/uploads/2020/11/Enjoyment-Level-of-Time-Use-364x550.png\" alt=\"\" class=\"wp-image-37746\" width=\"615\" height=\"930\" srcset=\"https://owid.cloud/app/uploads/2020/11/Enjoyment-Level-of-Time-Use-364x550.png 364w, https://owid.cloud/app/uploads/2020/11/Enjoyment-Level-of-Time-Use-265x400.png 265w, https://owid.cloud/app/uploads/2020/11/Enjoyment-Level-of-Time-Use-99x150.png 99w, https://owid.cloud/app/uploads/2020/11/Enjoyment-Level-of-Time-Use-768x1160.png 768w, https://owid.cloud/app/uploads/2020/11/Enjoyment-Level-of-Time-Use-1017x1536.png 1017w, https://owid.cloud/app/uploads/2020/11/Enjoyment-Level-of-Time-Use-1356x2048.png 1356w, https://owid.cloud/app/uploads/2020/11/Enjoyment-Level-of-Time-Use.png 1630w\" sizes=\"(max-width: 615px) 100vw, 615px\" /></figure>\n</div>\n</div>\n" } }, "extensions": { "debug": [ { "type": "DEBUG_LOGS_INACTIVE", "message": "GraphQL Debug logging is not active. 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