Introduction
Epidemiological studies have demonstrated a relationship between cognitive function in youth and the future risk of death [
1‐
3]. Such studies have shown that intelligence quotient (IQ) measured in childhood is positively associated with age of death and cardiovascular death in adulthood [
4‐
7]. Childhood IQ has also been shown to be associated with chronic conditions such as hypertension and coronary heart disease [
8‐
11]. In older adults, studies have reported a relationship between adult cognitive function and the risk of death [
12], as well as with the incidence of cardiovascular disease (CVD) [
13,
14] and diabetes [
15]. Less is known regarding the relationship between cognitive function in adolescence (as measured by tools that discriminate between cognitively intact individuals) and the subsequent risk for diabetes-related death.
An unusual opportunity exists in Israel to assess the potential link between cognitive function in adolescence and risk for diabetes and cardiovascular-related mortality, as all eligible citizens are required by law to undergo a pre-military examination that includes both medical and psycho-social assessments. Thus extensive neuropsychological evaluation data and sociodemographic information is routinely collected in addition to a detailed medical examination. Linkage of this information with the Israel Central Bureau of Statistics officially coded cause of death database enables assessment of the relationship between cognitive function in late adolescence and the risk for diabetes and CVD-related death in adulthood.
Discussion
This analysis of 2,277,188 adolescents followed for a median of 19.2 years demonstrates an inverse association between cognitive scores at the age of ~ 17 years and the risk for all-cause death, cardiovascular mortality, and CHD, stroke and diabetes-related death. The strongest relationship observed was for the cognitive function and diabetes mortality. For example, there was a ~ 1.8-fold greater multivariable-adjusted hazard for total cardiovascular disease mortality in those who were in the lowest vs. the highest GIT score category, while for diabetes-related death a ~ threefold greater hazard was observed. The associations, although substantially diminished after serial adjustments for variables that are known to be associated with both cognitive function and mortality (such as SES, education, origin and BMI), remained statistically significant.
This analysis is supported by data from previous studies conducted in children and in older individuals. An analysis of ~ 31,000 individuals with previous CVD reported a relationship between the Mini Mental State Examination Score (MMSE, a screening instrument for dementia) and incident cardiovascular events after adjustment for demographic and cardiovascular risk factors [
14]. In an analysis of 11,140 individuals with type 2 diabetes who were followed for a median of 5 years there was also an inverse relationship between the MMSE score at baseline and incident CVD events that persisted after multivariate adjustment for sociodemographic variables [
31]. In a study of 9204 individuals participating in the English Longitudinal study of Ageing, cognition was inversely associated with death from cancer, cardiovascular disease, respiratory illness and other causes [
32]. These association were attenuated after adjustment for demographic and SES variables but remained significant. There have been several studies in young adults. An inverse relationship between cognitive scores measured as part of military conscription in Denmark and risk for diabetes and for cardiovascular death was reported; the relationship was attenuated after adjustment for education but remained significant [
12]. We have previously reported an inverse relationship between cognitive scores determined in adolescence and the subsequent risk of diabetes and dysglycemia [
15,
33]. The findings of our study strengthen the results of these studies and further suggest that sensitive measures of cognitive function can discriminate between younger individuals with a higher/lower risk for diabetes and CVD related death.
There are several explanations for the relationship observed between cognitive function at age ~ 17 and the risk for diabetes and CVD-diabetes related death. First, as cognitive function is associated with education and SES, it may be that the relationship observed is a reflection of the already recognized relationship between these variables (and their possibly inadequate adjustment) and the subsequent risk for CVD death [
34‐
38]. A limited number of socio-demographic variables were available for adjustment in our study; thus it may well be that unmeasured or insufficiently discriminating socio-demographic factors, especially in the early years of the study, that affect the GIT account for the relationship. The strong reduction in the hazard ratios on multivariable adjustment, particularly for education, residential SES and origin (ie., model 4 adjustment), supports this explanation. Education is an increasingly non-discriminating variable in our data set as rapidly growing proportions over time have 12 years of education. Furthermore, we used an ecological measure of SES—based on locality of residence, which lacks refinement in cities. Therefore, residual confounding cannot be excluded as an explanation for the associations we report in multivariable-adjusted analyses. Alternatively, differences in GIT might be associated with different life-style behavioral patterns in childhood or specific intra-utero exposures (also referred to as fetal origin of adult disease [FOAD]) [
39]. For example it has been suggested that low birth weight, a surrogate marker of poor nutrition and fetal growth, is associated with stroke, coronary heart disease, stroke and diabetes [
40,
41]. Additionally, it could be that physical activity and diet in childhood could have affected intelligence scores and the subsequent risk for diabetes and CVD death in an independent manner. The observation of a shorter stature among adolescents with lower GIT may argue in favor of a common mechanism for these observation. For example, poor nutrition in early life and perhaps already in-utero may independently affect neurocognitive development (and thus lower GIT) [
42‐
44], growth velocity (thus shorter stature) [
45,
46] and may increase the risk for future development of the metabolic syndrome [
45,
47] and its associated cardio-metabolic risk. An additional possible explanation is that a higher GIT score leads to greater achievements, higher income, higher SES, a more healthy lifestyle, less exposure to a deleterious life-style, better access to healthcare and a better ability to prevent and manage disease [
48‐
50]. Finally, it could be that the relationship observed suggests a common origin(s) or pathway for both cognitive function and dyglycemia. These might include, among others, mitochondrial (dys)function [
51,
52], the sortilin pathway [
53], activation of the hypothalamic-pituitary-adrenal axis, inflammation, dysglycemia
perse or brain and systemic insulin sensitivity [
54‐
56]. Supporting the latter two explanations is the relatively strong relationship observed between cognitive function and diabetes-related mortality.
The study has several limitations. First, only a limited number of potential confounders were available for adjustment. Thus, information related to socio-demographic variables was restricted to country of origin, education and a residential-based index of SES in adolescence. Information related to individual measures of SES and to life-style factors such as diet, physical activity and smoking in adolescence (and adulthood) were not available, thus limiting our ability to assess an independent relationship (or an association mediated through these risk factors). Second, data regarding CVD mortality were not available from 1967 to 1981, however most cases of death during those years were attributable to service-based trauma, whereas the expected number of CVD or diabetes deaths was trivial [
16]. The study has several strengths including the large sample size and consequently substantial statistical power, the inclusion of data with respect to both women and men, the largely unselected population-based sampling and the ability to restrict the analysis to a healthy population.
Authors’ contributions
GT, TC-Y and JDK were responsible for study concept and design, statistical analysis and interpretation of the data, and drafting and redrafting of the manuscript. ED was responsible for statistical analysis. JDK, ED, NG and ZH were responsible for data acquisition. AT, HCG and AA contributed to critical revision of the manuscript. GT and JDK are the guarantors of this work and, as such, had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. All authors read and approved the final manuscript.