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. 2001 Apr 7;322(7290):819.
doi: 10.1136/bmj.322.7290.819.

Longitudinal cohort study of childhood IQ and survival up to age 76

Affiliations

Longitudinal cohort study of childhood IQ and survival up to age 76

L J Whalley et al. BMJ. .

Abstract

Objectives: To test the association between childhood IQ and mortality over the normal human lifespan.

Design: Longitudinal cohort study.

Setting: Aberdeen.

Subjects: All 2792 children in Aberdeen born in 1921 and attending school on 1 June 1932 who sat a mental ability test as part of the Scottish mental survey 1932.

Main outcome measure: Survival at 1 January 1997.

Results: 79.9% (2230) of the sample was traced. Childhood mental ability was positively related to survival to age 76 years in women (P<0.0001) and men (P<0.0001). A 15 point disadvantage in mental ability at age 11 conferred a relative risk of 0.79 of being alive 65 years later (95% confidence interval 0.75 to 0.84); a 30 point disadvantage reduced this to 0.63 (0.56 to 0.71). However, men who died during active service in the second world war had a relatively high IQ. Overcrowding in the school catchment area was weakly related to death. Controlling for this factor did not alter the association between mental ability and mortality.

Conclusion: Childhood mental ability is a significant factor among the variables that predict age at death.

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Figures

Figure 1
Figure 1
Probability of survival at ages 12-76 years for women and men in highest and lowest quarters for IQ score at age 11
Figure 2
Figure 2
Best fitting structural equation model of associations among paternal occupation, overcrowding, IQ at age 11, and age at death up to 76 years. All parameter estimates are significantly greater than zero. Squaring the parameter weights gives the variance shared by adjacent variables; they are comparable to partial β weights in linear regression. Average off diagonal standardised residuals=0.013; χ2 (df=2)=3.29, P1=0.19; Bentler Bonett normed fit index=0.965, Bentler Bonett non-normed fit index=0.956; comparative fit index=0.985. All of these indices are indicative of a well fitting model

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