Lower intellectual abilities in the lower socio-economic status groups took into account more than one third of the reported socio-economic differences in the decline in important components of quality of life and successful aging, i.e physical, affective, and cognitive functioning. None of the socioeconomic differences in functional decline remained statistically significant, when intellectual abilities were included in the model. The contribution of intellectual abilities was independent of the potentially confounding influence of early life socioeconomic conditions, including childhood deprivation, and early life developmental factors, including low birth weight. This was particularly due to only small effects of these early conditions on later functional decline.

A major drawback of our study is that the intellectual abilities were measured at baseline, when the respondents were 25 years old or older. We cannot exclude the possibility that intellectual abilities have changed as a result of socioeconomic circumstances and related work characteristics (rather than vice versa). The vocabulary sub-test of the GIT contributed most strongly to the association between socio-economic status and longitudinal decline in functioning. This is relevant here, as such crystallized abilities are thought to be particularly sensitive to educational experiences [29]. But, also if intellectual abilities can be stimulated by socioeconomic circumstances, such as being in an active job [30] or having a high education, our findings emphasize the importance of intellectual abilities for socioeconomic differences in health and functioning. The study of Batty and colleagues also reported substantial "explanation" by differences in intelligence [16]. Recent Whitehall II findings, on the contrary, indicated that intellectual abilities are probably not the driving force behind socioeconomic differences in health [15]. It is unclear how to explain this contrast among findings, but differences in the study population's composition, research design, age range, and measures of socioeconomic grading, health status, and intellectual abilities may be important. Foremost, our findings indicate that low socio-economic status cannot be established as a risk factor or indicator for functional decline, poor quality of life, and unsuccessful aging, until the possibility of confounding by intellectual abilities is fully excluded [11, 13].

Our findings thus show that intelligence is also informative for future deterioration of experienced quality of life. The personal functional experience and its "objective" counterparts, such as physical, performance-based tests or cognitive, neuropsychological tests are not necessarily perfectly related [31]. Equally well, there is no perfect relation between the reported functional decline and disease [31]. As mentioned previously, however, such quality of life measures are important for their patient-centeredness and their relevance for use of health care services [17, 18]. Moreover, the findings may shed some further light on the complexity of the mechanisms linking intelligence and premature mortality (as reported by others, e.g. [16]). As we will discuss below, personal perceptions of coping and mastery – related to functional outcomes – may be important here (see also [32]). As there were only few incident cases of coronary heart disease and all-cause mortality, these outcomes must await examination after longer follow-up intervals. In our data, prevalent disease appeared not to contribute to socioeconomic differences in functioning (see below) [33]. In previous studies, however, findings were about similar across health measures, including (coronary heart disease) mortality and self-reports of physical and mental functioning [15, 16]. However, the IQ contribution was somewhat stronger for the mortality outcomes in Batty and colleagues' study [16].

Lower intellectual abilities might affect rates of decline in functioning through adverse health behaviours [9, 34–37]. Unawareness of the consequences of unhealthy behaviours, such as smoking or a sedentary lifestyle, may be a mediating pathway. A related mediating pathway in the association between intellectual abilities and functioning might be via somatic diseases [4, 6, 8]. Perhaps persons with lower abilities have higher prevalences of disease (via their unhealthy behaviours might be one route). However, we have shown that prevalent adult diseases and health behaviours (and life-events) hardly contributed to the socioeconomic differences in physical, affective, and cognitive functioning and thus that intellectual abilities were probably not related to declines in functioning through behavioural or disease-related pathways [33]. Although the present study is not about mechanisms underlying the association between intellectual abilities and declines in functioning in varying domains, it is striking to find in our data a positive association between intellectual abilities and a measure of control beliefs (mastery) (these beliefs were measured at the follow-up phase only). The Pearson correlation was 0.26 (p = 0.05) (not tabulated). This suggests that higher intellectual abilities may help people to cope more easily with daily hassles, life events, and chronic stressful circumstances. Batty and Deary also postulated the possibility of a route via stress management skills as one of the mechanisms through which intelligence affects health [34]. Intelligence is about effectively dealing with complexity. Effective experiences, particularly in adverse and complex circumstances, are likely to increase levels of mastery and self-efficacy. Having to adhere to complex treatment regimens may be one such stressful circumstance with which the higher classes – because of their higher intellectual abilities – cope more effectively [6, 11, 34].

Further methodological considerations

Some further methodological issues should be discussed. Firstly, the psychometric quality of the outcome measures could be questioned. The physical functioning items showed a moderate to high internal consistency (Cronbach's α = 0.72) and strongly resemble items in well-known scales of instrumental activities of daily living [38]. The affective functioning items, though restricted to depression, come from a depression scale that has a high reliability and validity (Cronbach's α in our study = 0.89) [23]. The cognitive function item asks for bother due to forgetfulness. Such complaint is not necessarily strongly related to test performance. A recent study, however, found that persons with cognitive complaints (but normal test performance) showed brain atrophy similar to that of amnestic mild cognitive impairment [39]. Another recent study found that perceived memory function was a predictor of subsequent memory performance [40]. Other research confirms the importance of self-reports [24–26, 41]. Important here is also that intelligence is related to changes in the reported functioning (controlling for the baseline score) which indicates that reporting bias (e.g. negative affectivity) is less likely; negative affectivity would similarly bias reports of both baseline and follow-up reports of functioning and its bias is avoided when analyzing change.

Secondly, not many experienced major declines in functioning and most started from high levels of functioning. Residuals in the linear regression were, however, normally distributed, and findings were similar in old persons where there is more poor function and longitudinal decline. The high mean level of intellectual abilities (mean = 115.4; SD = 13.1) may also be indicative of the initially well-functioning MAAS cohort. Thirdly, persons with a low socioeconomic status, as well as persons with poor functioning and persons with low intellectual abilities more often dropped out during the study (particularly due to refusal rather than death or any other cause of attrition) [42]. This pattern of attrition may underlie the small six-year functional decline (from a high level of functioning) and the small socio-economic status and intelligence-related differences therein. It cannot, however, be determined how this pattern might have affected our finding of a substantial contribution of intellectual abilities. Fourthly, persons with a mental retardation were excluded from MAAS at baseline. Furthermore, excluding outliers and influential cases did not result in different findings. Hence, findings are probably not based on few persons with extreme low scores on the intellectual abilities measure.

Fifthly, birth weight and complications during birth and other developmental factors were based on self-reports and may therefore have been subject to recall bias, especially in older persons [43, 44]. However, the analysis of functional decline rather than momentary function excluded the possibility that overreports of adversities in childhood by those with poor functional outcomes could cause overestimated associations between childhood factors and our functional outcome. The extent of non-differential reporting bias is still unclear, as is the extent to which this might underlie the absence of effects of these factors on decline in adulthood.

Sixthly, if our measure of intellectual abilities also picks up characteristics, such as verbal abilities and differences in being used to test-taking, higher occupational level groups might have (artificially) higher scores on the particular measure. More research is needed to examine this issue in more detail [45]. Seventhly, the educational level of the parents might be a surrogate measure of the parents' intellectual ability levels, through which any effect of the parents' education might actually be confounded. In the absence of a consistent effect of the parents' education, such confounding has not likely played a major role. Finally, findings should be interpreted cautiously, because it is unclear why education and income, but not occupation, were related to affective and cognitive function at baseline.