Does monetary wealth equal sleep health? – Part 2, GDP and Population Sleep

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In the previous blog, we discussed relationships between Gross Domestic Product or GDP per capita and population health. We discussed that while population health improvements (measured through life expectancy) and GDP per capita tend to rise concurrently over time, this is a trend with exceptions, and that while richer countries tend to have higher life expectancies, this relationship is minimal or non-existent beyond a GDP per capita of ~40,000$ USD. We also discussed how a dogged push to increase GDP can at times be at the expense of the population’s health. In this blog, we will discuss the relationship between GDP per capita and population sleep behaviours/ health specifically. Certainly, one may assume that just as life expectancy tends to increase with GDP per capita, the population’s sleep will tend to improve as well. However equally, one may think that a GDP-centric mindset of a country may lead to increases in stress, overwork, and the sacrifice of sleep (as one presumably cannot positively contribute to the economy while unconscious). So, what does the data say?

One study published last year in the peer-review journal Scientific Reports appears quite damning, at least on the surface. Park and colleagues [1] looked at over 30,000 nights of sleep wearable data from individuals in 11 different countries, and used this data to (among many other comparisons) look at relationships between ‘GDP’ and sleep outcomes. They showed what appear to be quite large and sobering correlations; people in countries with higher GDPs going to bed a lot later, waking up only a little later, and having much lower overall sleep durations. However without going into the rabbit hole too far, the relationships that the study shows seem overwhelmingly swayed by Japanese participants, and their measure of GDP seems unclear, appearing (our assumption only) to be the overall GDP of the cities in which the individuals are from, not at a country level and not per capita as one would assume (unless we are to believe that Switzerland is considerably poorer per capita than Spain!). In other words, all we could interpret from this is that people in Tokyo sleep pretty terribly, a trend also shown nicely elsewhere [2].

Other cross-sectional approaches have yielded some inconsistent findings. An analysis of over 10,000 Chinese university students found that that those with a higher home-province GDP per capita were less likely to experience short sleep [3]. In contrast, a study looking at over 2500 adults, again in different regions of China, found higher GDP per capita regions to be associated with poorer sleep quality, with the authors suggesting this may be due to those in higher-GDP regions leading a ‘faster pace of life’ [4]. A third study looked at over 20,000 respondents to an online survey across 60 countries, and found those in high GDP per capita countries were less likely to experience insomnia and daytime sleepiness; though this work is limited, given that the vast majority of respondents were from high GDP countries [5].

If we are to look longitudinally (i.e. across time), we can find evidence for average sleep durations decreasing, and proportions of ‘short sleepers’ (normally defined as those that sleep less than 6 hours a night) increasing: However, these trends are somewhat complicated. For example, researchers at the University of South Australia found that over the past century, the sleep durations of children and young adults have decreased worldwide by about 1hr, however when separated by country, they found that sleep durations had actually increased in Australia, the UK, and Scandinavia [6]. Meanwhile, Bin and colleagues found the prevalence of short sleeping adults to increase in Italy and Norway, but actually decrease in the UK and USA, from the 80s to the 2000s [7]. More clarity may be found in an analysis which included eight national studies conducted on adults in the United States between 1975 to 2006 [8]. This study found an overall increase in short sleep prevalence in the 31 years, but when the data was stratified, this increase was found only in full-time working adults. Furthermore, short sleepers spent more than two hours at work per day than their counterparts. This work presents a strong case that as the decades go by, the working-class sacrifice sleep for time at work more and more. How this explicitly related to GDP per capita increases, or whether the relationship holds in other countries with high or lower GDP per capita values, isn’t known.

In summary, while we tend to live longer and spend more years in good health when GDP per capita grows, the relationship between GDP per capita and our sleep may be less rosy. Longer work hours, a sure consequence of a country’s more GDP-centric mindset, could increase the changes of not getting enough sleep quite drastically. It is both curious and concerning that at least one report has shown increasing average time awake (or decreasing sleep duration) over the past few decades to follow a pretty similar pattern to increases in obesity rate and the prescription of antipsychotic medication [9]. When it comes to countries (or even regions within countries) with different GDPs and sleep, the results are pretty unclear currently; however we note that studied hunter-gatherer tribes in Africa and South America, who assumedly think or care little about their GDP, do have words for insomnia in their language, such is its infrequence [10]. Perhaps monetary wealth does not necessarily equal sleep health/wealth.

References

  1. Park, S., et al., Social dimensions impact individual sleep quantity and quality. Scientific Reports, 2023. 13(1): p. 9681.  https://doi.org/10.1038/s41598-023-36762-5.
  2. Willoughby, A.R., et al., Country differences in nocturnal sleep variability: Observations from a large-scale, long-term sleep wearable study. Sleep Medicine, 2023. 110: p. 155-165.  https://doi.org/10.1016/j.sleep.2023.08.010.
  3. Yang, T., et al., Regional contextual influences on short sleep duration: a 50 universities population-based multilevel study in China. Global Health Action, 2018. 11(1): p. 1442684.  https://doi.org/10.1080/16549716.2018.1442684.
  4. Qu, S., M. Wang, and Y. Peng, Associations between residential environmental health and sleep quality: Potential mechanisms. Sleep Medicine, 2023. 103: p. 16-23.  https://doi.org/10.1016/j.sleep.2023.01.010.
  5. Babicki, M., P. Piotrowski, and A. Mastalerz-Migas Insomnia, Daytime Sleepiness, and Quality of Life among 20,139 College Students in 60 Countries around the World-A 2016-2021 Study. Journal of Clinical Medicine, 2023. 12.  https://doi.org/10.3390/jcm12020692.
  6. Matricciani, L., T. Olds, and J. Petkov, In search of lost sleep: Secular trends in the sleep time of school-aged children and adolescents. Sleep Medicine Reviews, 2012. 16(3): p. 203-211.  https://doi.org/10.1016/j.smrv.2011.03.005.
  7. Bin, Y.S., N.S. Marshall, and N. Glozier, Sleeping at the Limits: The Changing Prevalence of Short and Long Sleep Durations in 10 Countries. American Journal of Epidemiology, 2013. 177(8): p. 826-833.  https://doi.org/10.1093/aje/kws308.
  8. Knutson, K.L., et al., Trends in the prevalence of short sleepers in the USA: 1975-2006. Sleep, 2010. 33(1): p. 37-45.  https://doi.org/10.1093/sleep/33.1.37.
  9. McAllister, E.J., et al., Ten Putative Contributors to the Obesity Epidemic. Critical Reviews in Food Science and Nutrition, 2009. 49(10): p. 868-913.  https://doi.org/10.1080/10408390903372599.
  10. Yetish, G., et al., Natural Sleep and Its Seasonal Variations in Three Pre-industrial Societies. Current Biology, 2015. 25(21): p. 2862-2868.  https://doi.org/10.1016/j.cub.2015.09.046.

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