Intelligence in early adulthood and mortality from natural and unnatural causes in middle-aged Danish men

J Epidemiol Community Health. 2014 Feb;68(2):130-6. doi: 10.1136/jech-2013-202637. Epub 2013 Sep 23.

Abstract

Background: High intelligence early in life has consistently been associated with decreased mortality, but the mechanisms are still not fully understood. In this cohort study, we examined the association between intelligence in early adulthood and later mortality from natural and unnatural causes taking birth weight, parental socioeconomic position, participants' own education and body mass index into account.

Methods: 13 536 Danish men born in 1953 and 1959-1961 with data from birth certificates and intelligence test scores from conscription were followed until 2009. Information on vital status was obtained from the Civil Registration System. Mortality risks were analysed by the multiple Cox proportional hazards model.

Results: The risk of mortality from natural as well as unnatural causes was more than twice as high among men in the lowest scoring intelligence tertile (HRnatural deaths=2.24; 1.90-2.65 and HRunnatural deaths=2.67; 2.03-3.53). Adjusting for all covariates attenuated the estimates, but the association remained (HRnatural deaths=1.82; 1.48-2.25 and HRunnatural deaths=2.30; 1.63-3.25).

Conclusions: In men, intelligence in early adulthood was inversely associated with midlife mortality from natural and unnatural causes. The associations remained after adjustments for a range of covariates.

Keywords: Adolescents CG; Cognition; Mortality.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Age Factors
  • Birth Certificates
  • Birth Weight
  • Body Mass Index*
  • Cause of Death*
  • Cohort Studies
  • Data Interpretation, Statistical
  • Denmark / epidemiology
  • Educational Status
  • Health Status Disparities
  • Humans
  • Intelligence Tests
  • Intelligence*
  • Male
  • Middle Aged
  • Mortality / trends*
  • Parent-Child Relations
  • Proportional Hazards Models
  • Registries
  • Risk Factors
  • Social Class*
  • Urban Population / statistics & numerical data