One data pattern, many interpretations

February 13, 2018
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(This article was originally published at Statistical Modeling, Causal Inference, and Social Science, and syndicated at StatsBlogs.)

David Pittelli points us to this paper: “When Is Higher Neuroticism Protective Against Death? Findings From UK Biobank,” and writes:

They come to a rather absurd conclusion, in my opinion, which is that neuroticism is protective if, and only if, you say you are in bad health, overlooking the probability that neuroticism instead makes you pessimistic when describing your health.

Here’s the abstract of the article, by Catharine Gale, Iva Cukic, G. David Batty, Andrew McIntosh, Alexander Weiss, and Ian Deary:

We examined the association between neuroticism and mortality in a sample of 321,456 people from UK Biobank and explored the influence of self-rated health on this relationship. After adjustment for age and sex, a 1-SD increment in neuroticism was associated with a 6% increase in all-cause mortality (hazard ratio = 1.06, 95% confidence interval = [1.03, 1.09]). After adjustment for other covariates, and, in particular, self-rated health, higher neuroticism was associated with an 8% reduction in all-cause mortality (hazard ratio = 0.92, 95% confidence interval = [0.89, 0.95]), as well as with reductions in mortality from cancer, cardiovascular disease, and respiratory disease, but not external causes. Further analyses revealed that higher neuroticism was associated with lower mortality only in those people with fair or poor self-rated health, and that higher scores on a facet of neuroticism related to worry and vulnerability were associated with lower mortality. Research into associations between personality facets and mortality may elucidate mechanisms underlying neuroticism’s covert protection against death.

The abstract is admirably modest in its claims; still, Pittelli’s criticism seems reasonable to me. I’m generally suspicious of reading too much into this sort of interaction in observational data. The trouble is that there are so many possible theories floating around, so many ways of explaining a pattern in data. I think it’s a good thing that the Gale et al. paper was published: they found a pattern in data and others can work to understand it.

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