Individual differences in intelligence (cognitive ability, mental ability) test scores, as measured by standardized IQ-type tests in childhood, show an inverse association with risk of death from all causes throughout adulthood. That is, higher intelligence appears to confer protection. This finding is replicated in prospective cohorts from several Westernized countries,1
across different ranges of intelligence,2
and in follow-up periods from early through to late adulthood.2–4
Intelligence and somatic health may be inextricably linked throughout the life course. However, longitudinal studies help to establish causal pathway models of the effects of one upon the other. For example, morbidities such as diabetes, cancer, stroke and peripheral atherosclerosis, and/or their treatments, are reported to cause a decline in cognitive function after longitudinal follow-up.5–10
This illness-to-cognitive ability direction of association is a commonplace finding. The reverse direction of association is studied less often, and has only recently come to be recognized under the term ‘cognitive epidemiology’.11,12
That is, mental ability scores from early life associated with later adulthood morbidities, and before any somatic symptoms or risk factors of disease are manifest, provide evidence that cognitive abilities may be predictive of later health outcomes.
The association between premorbid intelligence and adult all-cause mortality was the subject of a systematic review,1
in which all nine studies that met the inclusion criteria demonstrated an inverse relationship between intelligence and risk of dying by the time of follow-up. The review did not quantify the association. Furthermore, there were insufficient studies to address comprehensively a number of pertinent questions from this research domain. One issue is whether or not the association between intelligence and mortality is the same in women as in men. For example, it is possible that sex differences in the incidence, age at onset of health behaviours, and the extent to which these act as risk factors for disease,13,14
could produce sex-specific intelligence–mortality gradients. Data from many more men than women have been included in intelligence–mortality cohort studies to date, mainly due to some studies using military conscript databases. Moreover, when mixed-sex cohorts report mortality risk as predicted by intelligence for men and women separately, they rarely test for statistical difference but, rather, report the observed trend. With more studies now reporting hazard ratios (HRs) for mortality by sex, there is an opportunity to quantify the predictive effects of intelligence on mortality separately for men and women.
A second issue yet to be evaluated systematically is the extent to which intelligence as a predictor of mortality is confounded by early-life environmental influences including socio-economic factors. Socio-economic status (SES) is established as an important determinant of public health inequalities,15–18
including risk of mortality, and it can carry influence in childhood, via factors such as family income and parental education, to predict individual differences in childhood intelligence.19,20
In this context, therefore, intelligence may be considered a mediating variable on the pathway between early-life influences and adult health outcomes. If early social factors substantially confound the link between intelligence and longevity, then adjusting for childhood SES would sizeably attenuate the effect size of the association between intelligence and mortality. In their systematic review, Batty et al
identified three out of nine studies that adjusted for childhood SES: one of these showed no change from an unadjusted model, and two had modest attenuating effects, suggesting that intelligence has independent effects on risk of mortality from those of early socio-economic influences. Due to this small number of studies, the role of childhood SES in the intelligence–mortality link requires further investigation.
One explanation why intelligence may exert an influence on life expectancy is its ability to predict educational outcomes21
and occupational class,22
which can both affect health outcomes via a number of mechanisms; for example, the knowledge and living conditions that contribute to better personal health risk assessment, behaviours and management.23
In population studies these adult SES factors are themselves inversely associated with risk of mortality.24–26
Some prospective cohorts take account of the attenuating effects of education and adult SES in estimating the risk of mortality according to intelligence; yet, to date, their influence has not been properly evaluated.
Investigators are giving increasing attention to the issues raised here, with a higher rate of publications reporting risk estimates for all-cause mortality according to differences in intelligence since the first systematic review.1
There is now an opportunity to re-evaluate this augmented literature, this time with a quantitative, meta-analytic approach. The systematic review by Batty et al.1
reported the overall quality of the nine studies as ‘moderate’, which was in part related to the weak validity of some measures of premorbid intelligence. Therefore, one important change to the systematic process reported here is the inclusion of studies in which only valid cognitive assessments were used. Kilgour et al.27
also raised a number of methodological considerations that should be addressed in intelligence–mortality studies, including taking account of ascertainment bias, age, sex and education. In this article we address the influence of these factors using subgroup analyses.
Accordingly, the aims of this report are to (i) quantify the association between premorbid intelligence and all-cause mortality, (ii) determine whether there are sex differences in the association and (iii) conduct subgroup analyses on studies that adjust for early-life SES, adult SES and education, to discover their magnitude of influence as potential confounders or mediators of the intelligence–mortality association.