COGNITIVE EPIDEMIOLOGY, INTELLIGENCE, HEALTH, AND DEATH

Cognitive epidemiology as a separate line of inquiry emerged in the early 2000s. Its purpose is to study how and why individual differences in intelligence (especially when measured in childhood or young adulthood) associate with later differences in health, illness, and death. An article published in the April 2020 issue of the journal Nature Human Behaviours examines how an understanding of the association between intelligence and health/mortality has been refined with the advent of new, population-scale data and genetic tools. The manuscript looks at the associations between intelligence and, in turn, all-cause mortality, specific causes of mortality, physical illnesses, and health-related biomarkers. Possible causes of the observed associations (education, health behaviors and literacy, and genetics), are not mutually exclusive.

Although the causes underlying the associations between intelligence and health/mortality remain an open question, research over the past decade has provided results and fingerposts for further progress. As a way of obtaining a clearer understanding, the authors discuss how intelligence relates to specific causes of death, diseases/diagnoses, and biomarkers of health through the adult life course. They examine the extent to which mortality and health associations with intelligence might be attributable to differences in education, other indicators of socioeconomic status, health literacy, and adult environments and behaviors. Finally, they discuss whether genetic data provide new tools to understand parts of the intelligence–health associations. Social epidemiologists, differential psychologists and behavioral and statistical geneticists, among others, contribute to cognitive epidemiology. Any advances that occur will do so by building on a common cross-disciplinary knowledge base.

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COGNITIVE EPIDEMIOLOGY, INTELLIGENCE, HEALTH, AND DEATH

pertains to how an understanding of the association between intelligence and health/mortality has been refined with the advent of new, population-scale data and genetic tools. Read More Read More