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Arts engagement, mortality and dementia: what can the data say?
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  1. Liam Wright
  1. Department of Epidemiology and Public Health, University College London, London, UK
  1. Correspondence to Liam Wright, Epidemiology and Public Health, University College London, London WC1E 7HB, UK; liam.wright.17{at}ucl.ac.uk

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Does going to a museum make you taller? Unlikely. But taller people may be more likely to attend museums or to engage in receptive art consumption. Height is related to socio-economic background1 and to cognitive ability.2 Both of these could explain any link between art engagement and height, rather than a direct causal relation.

In two recent papers,3 4 Fancourt and colleagues find that participants in the English Longitudinal Study of Ageing who engage with the receptive arts have lower rates of mortality and of dementia. In their models, they control for multiple factors that predict mortality, dementia and arts engagement, such as cognitive ability and financial wealth. But is this enough to account for the heavy social patterning of arts consumption? To explore this, I repeat their main analysis3 using height as an outcome variable.I If their regression adjustments do account for social patterning, it seems reasonable to assume we should see no independent association between arts engagement and height. (This is known as an outcome negative control test.5)

The left panel of figure 1 shows the results of bivariate and multivariate regressions. We see that individuals who engage in the arts are taller on average, even controlling for the array of control variables Fancourt and colleagues use. We also see similar results when we use frequency of eating out at restaurants, internet use or owning a mobile phone as alternative ‘treatment’ variables. These variables are likely to be similarly socially patterned.

Figure 1

Association between height and frequency of receptive arts engagement.

Does going to a museum increase your life expectancy? Does it reduce your risk of dementia? Perhaps. Fancourt and colleagues give several theoretical arguments for such a link. But I am unconvinced their data give us any further evidence in support.

Full regression results and replication code are available at https://osf.io/kgqnr/.II

REFERENCES

Footnotes

  • I Model covariates differ slightly across their two papers. I obtain qualitatively similar results using either set of covariates, but report the results from Fancourt and Steptoe3 as the set of covariates is larger in this study.

  • II The cognitive variables have not yet been made publicly available. I thank Daisy Fancourt for sharing the data and checking my code for inconsistencies with her work.

  • Contributors I am the sole author of this work and the analysis it contains.

  • Funding My PhD is funded by the Economic and Social Research Council through the UCL, Bloomsbury, and East London Doctoral Training Partnership (ES/P000592/1). This work is separate from my PhD research and was not influenced in anyway by my funders.

  • Competing interests All authors have completed the Unified Competing Interest form (available on request from the corresponding author) and declare no support from any organisation for the submitted work; no financial relationships with any organisations that might have an interest in the submitted work in the previous three years, no other relationships or activities that could appear to have influenced the submitted work.

  • Ethics approval Not required.

  • Patient consent for publication This was a secondary data analysis exploring the results of an existing study. It was not appropriate or possible to involve patients or the public in the design, or conduct, or reporting, or dissemination plans of our research.

  • Data sharing statement I used data from the English Longitudinal Study of Ageing, available through the UK Data Service. Code to replicate the analysis is available at https://osf.io/kgqnr/.

  • Provenance and peer review Not commissioned; internally peer reviewed.

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