Journal article
Large-scale societal dynamics are reflected in human mood and brain
- Abstract:
- AbstractThe stock market is a bellwether of socio-economic changes that may directly affect individual well-being. Using large-scale UK-biobank data generated over 14 years, we applied specification curve analysis to rigorously identify significant associations between the local stock market index (FTSE100) and 479,791 UK residents’ mood, as well as their alcohol intake and blood pressure adjusting the results for a large number of potential confounders, including age, sex, linear and non-linear effects of time, research site, other stock market indexes. Furthermore, we found similar associations between FTSE100 and volumetric measures of affective brain regions in a subsample (n = 39,755; measurements performed over 5.5 years), which were particularly strong around phase transitions characterized by maximum volatility in the market. The main findings did not depend on applied effect-size estimation criteria (linear methods or mutual information criterion) and were replicated in two independent US-based studies (Parkinson’s Progression Markers Initiative; n = 424; performed over 2.5 years and MyConnectome; n = 1; 81 measurements over 1.5 years). Our results suggest that phase transitions in the society, indexed by stock market, exhibit close relationships with human mood, health and the affective brain from an individual to population level.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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(Preview, Version of record, pdf, 2.9MB, Terms of use)
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- Publisher copy:
- 10.1038/s41598-022-08569-3
Authors
+ Marianne and Marcus Wallenberg Foundation
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- Funder identifier:
- 10.13039/501100011898
- Grant:
- MMW2014.0065
+ Karolinska Institutet
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- Funder identifier:
- 10.13039/501100004047
- Grant:
- KID 019-00939
- Publisher:
- Nature Research
- Journal:
- Scientific Reports More from this journal
- Volume:
- 12
- Issue:
- 1
- Pages:
- 4646-4646
- Article number:
- 4646
- Publication date:
- 2022-03-17
- DOI:
- EISSN:
-
2045-2322
- ISSN:
-
2045-2322
- Language:
-
English
- Keywords:
- Pubs id:
-
1249825
- Local pid:
-
pubs:1249825
- Source identifiers:
-
W4221109885
- Deposit date:
-
2026-04-23
- ARK identifier:
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Terms of use
- Copyright date:
- 2022
- Licence:
- CC Attribution (CC BY)
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