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ORIGINAL ARTICLES |
From the Public Health and Health Policy, Division of Community Based Sciences, University of Glasgow (C.L.H., D.J.H.), Glasgow, Scotland; Psychology, School of Philosophy, Psychology and Language Sciences, University of Edinburgh (M.D.T., I.J.D), Edinburgh, Scotland; Department of Social Medicine, University of Bristol (G.D.S.), Bristol; Department of Mental Health, University of Aberdeen, Clinical Research Centre, Royal Cornhill Hospital (L.J.W), Aberdeen, Scotland; Royal Victoria Hospital (J.M.S.), Edinburgh, Scotland; and Scottish Council for Research in Education, University of Glasgow (V.W.), Edinburgh, Scotland.
For the Midspan studies, address reprint requests to: Carole Hart, MA, PhD, Public Health and Health Policy, Division of Community Based Sciences, University of Glasgow, 1, Lilybank Gardens, Glasgow G12 8RZ. E-mail c.l.hart{at}udcf.gla.ac.uk For the Scottish Mental Survey 1932, address reprint requests to: Ian J. Deary, PhD, FRCPE, Psychology, School of Philosophy, Psychology & Language Sciences, University of Edinburgh, 7, George Square, Edinburgh EH8 9JZ. E-mail i.deary@ed.ac.uk
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ABSTRACT |
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METHODS: Participants were from the Midspan studies conducted on adults in the 1970s; 938 Midspan participants were successfully matched with the Scottish Mental Survey 1932 in which children born in 1921 and attending Scottish schools on June 1, 1932, took a cognitive ability test.
Mortality, hospital admissions, and cancer incidence in the 25 years after the Midspan screening were investigated in relation to childhood IQ, social class, and deprivation.
RESULTS: The risk of dying in 25 years was 17% higher for each standard deviation disadvantage in childhood IQ. Adjustment for social class and deprivation category accounted for some, but not all, of this higher risk, reducing it to 12%. Analysis by IQ quartile showed a substantial increased risk of death for the lowest-scoring quarter only. Structural equation modeling indicated that the effect of childhood IQ on mortality was partly indirectly influenced by social factors. Cause-specific mortality or hospital admission showed that lower IQ was associated with higher risks for all cardiovascular disease and coronary heart disease. Cause-specific mortality or cancer incidence risk was higher with decreasing IQ for lung cancer.
CONCLUSIONS: Lower childhood IQ was related to higher mortality risk and some specific causes of death or morbidity. Childhood IQ may be considered as a marker for risk of death or illness in later life in similar and complementary ways to social class or deprivation category.
Key Words: cohort, • deprivation, • mental ability, • mortality, • Scotland, • social class.
Abbreviations: CHD = coronary heart disease; CVD = cardiovascular disease; SCRE = Scottish Council for Research in Education; SMS1932 = Scottish Mental Survey 1932
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INTRODUCTION |
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The application of personal-psychological variables, such as personality and cognitive traits, to the study of human mortality has occurred relatively recently and as yet there are few studies. Some such findings came from the Terman Life Cycle of Children with High Ability study, which extended over seven decades. Measured in childhood, the personality traits of conscientiousness, lack of cheerfulness, and permanence of mood (for men only on this trait) were associated with longer lives (7, 8). In the Nun Study the emotional content of the nuns’ hand-written autobiographies at age 22 was related to survival between 75 and 95 (9).
Many studies have reported significant associations between cognitive ability in old age and survival (eg, in the UK’s Medical Research Council Cognitive Function and Ageing Study (10) and in the Australian Longitudinal Study of Ageing) (11). The mechanisms postulated to account for these findings suggest that cognitive function in old age is a marker for both disease processes and biological ageing. However, does mental ability in childhood, before the effects of biological ageing and age-related disease processes, relate to mortality? One reason to suspect that it might is that higher mental ability in youth is associated with more favorable educational and occupational outcomes (12), factors that are associated with longevity.
In addition, there are some significant associations between cognitive ability in youth and mortality. Examples include the Nun Study, in which the idea density of their autobiographies written in the 1930s and 1940s related to the risk of dying between 1991 and 1998 (9), and the Australian Veterans Health Studies (13) in which intelligence test scores taken at army recruitment predicted death between age 22 and 40. In a previous study we reported that IQ at age 11, measured in the nationwide Scottish Mental Survey of 1932, related to survival up to age 76 (14). This was the first study to relate childhood IQ to survival in late life, and the first to examine both sexes in a representative population. We restricted our examination to Aberdeen city, which gave a manageable number of just under 2800 people tested at age 11 of whom we traced the vital status of about 80% at age 76.
In summary, cognitive ability as measured by IQ-type tests is one of the personal-psychological predictors of longevity in humans. Three tasks remain for researchers. First, the data establishing this association are relatively sparse. Therefore, replications would be valuable. Second, none of the studies to date have clearly separated the effects of IQ on mortality from the potentially confounding effects of social factors such as occupation and deprivation, to which IQ is related. Third, there has been only limited research on the possible mechanisms of the association between IQ and mortality. Various mechanisms have been suggested (14). For example, childhood IQ could act as a record of bodily insults in early life, including prenatal and postnatal effects of nutrition and chronic childhood illness, which could affect the developing brain. In this view childhood IQ captures pathology and the decline from some notional IQ that the person might have achieved in the absence of cerebral insults. Alternatively, childhood IQ might act as a predictor of system integrity within the body by indexing the efficiency of information processing in the nervous system. That is, IQ differences in the absence of any cerebral insults might be indicators of the general health of the body. Additionally, IQ might be related to the subsequent acquisition of behaviors conducive to good health, such as healthy eating and smoking avoidance. This idea that individual differences in psychological traits might act as a surrogate for later behaviors conducive to good health was argued in detail by Friedman et al. (15). Lastly, it could act as a predictor of entry to safer environments, such as less hazardous employment and reduced exposure to material privation. This would predict that adult social class would be an indirect pathway of the influence of childhood IQ on mortality. In a research area in which the association itself is being established and must still be separated from obvious confounders it is understandable that these mechanistic ideas remain relatively unexplored in empirical studies.
The present study aims to address all three tasks. We examine the relation between IQ at age 11 and mortality in a different area of Scotland, one with poorer socio-economic characteristics than Aberdeen. Thus we attempt to replicate our finding that childhood mental ability was positively related to survival up to age 76 in people born in 1921 and attending schools in Aberdeen in 1932 (14). The Aberdeen sample lacked satisfactory socioeconomic data. Therefore, it is not known whether mental ability is merely a surrogate for socioeconomic position, or an additional risk indicator with respect to mortality or morbidity risk. Here we investigate the relationships of childhood IQ, social class, and deprivation category of residence with mortality and morbidity risk in later life in a cohort of men and women who took part in health surveys in middle age and had mental ability data available from childhood. This addresses the second task by examining possible socioeconomic confounders of the IQ-mortality association. It also partially addresses the third task by testing one of the possible mechanisms of the association between IQ and mortality by exploring the role of socioeconomic factors.
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METHODS |
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The Midspan studies were large cardiorespiratory studies of adults carried out in Scotland in the 1960s and 1970s. Two studies are included in this analysis–the Collaborative study and the Renfrew/Paisley study. The Collaborative study was conducted between 1970 and 1973 in 27 workplaces in the west and central belt of Scotland (5). The full sample consisted of 6022 men and 1006 women of working age. The Renfrew/Paisley general population study was carried out between 1972 and 1976 and involved 7052 men and 8354 women aged 45 to 64 years who were residents in Renfrew and Paisley, two towns near Glasgow (17). The age ranges of the studies were such that some participants were born in 1921. Ethical permission was obtained from the Multi-Center Research Ethics Committee for Scotland to link the SMS1932 data set with the 1921-born participants of the Midspan data sets.
There were 1251 Midspan participants who were born in 1921; of these, 938 (75%) were matched to a mental ability score from the SMS1932. Full details of the matching procedures are reported elsewhere (18). Since the children’s ages varied between 10.5 and 11.5 years at the time of testing, the test scores were corrected for age and converted to usual IQ-type scores with mean 100 and standard deviation 15.
In both Midspan studies, participants completed a questionnaire and attended a physical examination (5, 17). The questionnaire included questions about age, home address, and occupation. The home address at the time of screening was retrospectively postcoded, enabling deprivation category as defined by Carstairs and Morris to be ascertained (4). This is an area-based measure of deprivation, obtained from four census variables–male unemployment, overcrowding, car ownership, and the proportion of heads of households in social classes IV and V (semi-skilled and unskilled respectively). A deprivation score for each postcode sector is obtained, which is converted to seven categories ranging from 1 (least deprived) to 7 (most deprived). Social class was coded according to the Registrar General’s Classification (19) for occupation at the time of screening. Social class is categorized in six groups: I (professional), II (intermediate), III NM (skilled nonmanual), III M (skilled manual), IV (semi-skilled), and V (unskilled). The social class of women was allocated according to their own occupation, except for those women in the Renfrew/Paisley study who gave their occupation as housewives. In these cases, the social class was that of their husband. Since deprivation category was missing for 3 participants and social class was missing for 13, the analyses were performed using the 922 participants with complete data.
Midspan study participants were flagged at the National Health Service Central Register in Edinburgh. Causes and dates of death in a 25-year follow-up period were provided. Causes of death were defined as all cardiovascular disease (CVD) (ICD9 codes 390–459), coronary heart disease (CHD) (ICD9 410–414), stroke (ICD9 430–438), hemorrhagic stroke (ICD8 430–431 and ICD9 430–432), respiratory disease (ICD9 460–519), all cancer (ICD9 140–208), lung cancer (ICD9 162), stomach cancer (ICD9 151), colorectal cancer (ICD9 153–154), and female breast cancer (ICD9 174). The few more recent deaths were coded in ICD10 and equivalent codes were used.
In addition, a computerized linkage with acute hospital discharges in Scotland provided records of acute hospital admissions and cancer incidence in 25 years of follow-up, although these were only provided to the end of 1995 for Renfrew/Paisley study participants (20). Causes of hospital admission and cancer incidence were coded in the same way as the deaths, except all cancer specifically excluded ICD9 173 (nonmelanoma skin cancer).
Cox’s models (21) were used to calculate proportional hazards regression coefficients for one standard deviation change in IQ, per social class, per deprivation category, and for IQ, social class, and deprivation category groupings. The exponentiated proportional hazards regression coefficients are referred to as relative rates. Adjustments were made by including other variables in the model. Adjustments were made for both social class and deprivation category as they have previously been found to make independent contributions to mortality risk (3). For mortality analyses, survival time was taken from the date of screening until the date of death or 25 years from the date of screening. For analyses of cause-specific mortality or events, survival time in 25 years was taken from the date of screening until either the date of hospital admission (or cancer incidence), or the date of death if no hospital admission (or cancer incidence) was found. One participant had embarked from the UK during the follow-up period and survival time was taken until the date of embarkation.
A model of association among IQ, social class, deprivation, and survival was examined with structural equation modeling using the EQS program (22). This technique examined the prior hypothesis that the effect of IQ on mortality was both direct and indirect via social class and deprivation (14). Sex, social class, deprivation category, and death were categorical variables. Robust methods were used for analysis. The method allows a number of interrelated variables to be configured as a hypothesized network of associations. Chi square, residual covariance, and fit indices were used to indicate goodness-of-fit of the model to the data. The procedure provides parameter weights that indicate the strength of association between variables in the model.
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RESULTS |
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2 for the model = 1.4 (df = 2, p = .50) (nonsignificant values indicate good fit). Both of these tests indicate that the residual covariance among the measured variables was low after the model’s paths were taken into account. The Bentler-Bonett (normed and nonnormed) and comparative fit indices were 0.99, 1.0, and 1.0, respectively (range from 0 to 1, values above 0.9 indicate good fit). These are goodness-of-fit indices, which reflect how well the model fits the variables’ covariance matrix. There were no constraints or covariances included in the model. There is a small direct effect of IQ on death, a second effect that is indirect, via deprivation, and a third that is indirect, via social class and deprivation. Sex influenced mortality and also IQ.
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2(robust method) for the model was 5.5 (df = 3, p = .14). The 2 difference between the two versions of the model was 4.1 (p < .05). Thus, the inclusion of the direct path between IQ and death significantly improves the model, and it may be concluded that the indirect paths—via social class and deprivation category—in the model do not fully mediate the influence of childhood IQ on death. Cause-specific mortality or hospital admission showed higher risks with lower childhood IQ for all cardiovascular disease, coronary heart disease, stroke, and respiratory disease (Table 4). These results were not statistically significant for stroke or respiratory disease. Hemorrhagic stroke had a particularly high (though not statistically significant) relative rate per standard deviation decrease in IQ. For cancers, cause-specific mortality or cancer incidence risk was higher with decreasing IQ for all cancer, lung cancer, and stomach cancer, and lower for colorectal and female breast cancer. The relationships were only statistically significant for lung cancer. Adjustment for social class and deprivation had a small effect on the cause-specific risks. After full adjustment, none of the causes were significantly related to childhood IQ.
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CONCLUSIONS |
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The present study examined whether the effects of childhood IQ on survival were accounted for by social factors in adulthood. Being in a higher social class or in a more affluent deprivation category was associated with higher IQ scores and the scores reduced with increasing deprivation in this dataset (18). In the current analyses, all-cause mortality was inversely associated with IQ and, following adjustment for social class and deprivation category, the inverse relationship remained. The adjustments could explain some, but not all, of the relative rate associated with one standard deviation lower IQ, reducing the relative rate from 1.17 to 1.12. This addressed our second task, to separate the effects of IQ on mortality from the socioeconomic effects. The analysis by IQ divided into four groups showed that it was the lowest group that had an increased relative rate of all-cause mortality, which was suggested previously by a more detailed analysis of the Aberdeen SMS1932 sample (24) and also seen in the Nun Study (9). Other risk factors, such as smoking, raised cholesterol, obesity, or raised blood pressure may help to explain the remainder of the relationship between childhood IQ and mortality and, although some are socially patterned, they may act in addition to social class and deprivation in the IQ-mortality relationship. These risk factors are likely to have larger associations with mortality than the relatively small IQ-mortality relationship.
Graded effects of all-cause mortality were seen with deprivation category, whereas in the analysis of all-cause mortality by social class, the highest risk was seen in social class III manual. To investigate this anomaly, the analyses were repeated for men and women separately (results not shown). A larger proportion of men than women were in social class III manual (38% vs. 17%). For men, there were increasing relative rates across the four social class groupings, with men in manual social classes having over 70% higher risk of mortality in 25 years than men in social classes I and II. For women, there were higher relative rates for women in social classes III nonmanual and III manual. Women in social classes IV and V had similar relative rates to women in social classes I and II. This could reflect the inadequacy of the social class categorization for women compared with men, which could be further affected by using husband’s occupation for women described as housewives. Social class would therefore seem to be the weakest of the three measures and in the structural equation model, it was the factor that did not directly link with death. Deprivation category is an area-based, rather than an individual-based variable, which could make its effects weaker. However both social class and deprivation attenuated the childhood IQ-mortality relationship.
The significant interaction found between IQ and deprivation category suggests that IQ in childhood is less important in terms of mortality for people who live in more affluent areas in adulthood than for people who live in deprived areas. This supports the effect on mortality risk of the accumulation of insults over the lifecourse (25). The interaction may also relate to the importance of mental ability in learning how to cope with adverse situations. This would be similar to the association between higher childhood IQ and maintenance of functional independence in old age (26), and would emphasize health behaviors learnt early in life as an important causal pathway in the effect of mental ability on mortality.
Limitations of the study include the exclusion of 25% of the Midspan 1921-born participants who were unable to be matched or were absent from school on the day of the test and had no IQ score recorded (18). However, they were generally similar, in terms of variables in middle age, to the matched participants, although the unmatched were likely to include migrants to the Midspan areas (18). Another limitation is that social class and deprivation category were measured at one time point only and these are factors that can change throughout the lifecourse. However, participants were likely to have been in a stable occupation and place of residence at the time of screening when they were in their early 50s because job changes are more likely to occur at younger ages (27). Measurement limitations, especially for social factors, should lead to caution in interpreting results. It is necessary to consider possible chains of causation. It is possible that low childhood IQ leads to adult deprivation, which in turn leads to earlier death. The structural equation model showed that IQ had a direct effect on risk of death, and also an indirect effect via deprivation. The subsequent influence of social class on deprivation formed the link between IQ, social class, and death. The structural equation model was in agreement with our epidemiological results and again addressed our second task, to separate the effects of IQ on mortality from the socioeconomic effects.
Although few of the cause-specific relationships were statistically significant, many were in the expected direction. Colorectal and breast cancer are more likely to be seen in the affluent, whereas lung and stomach cancer are more likely to be seen in the deprived (28). Relationships with IQ were similar to previously found relationships with childhood social class for stomach cancer (29) and stroke (30). Adverse socioeconomic circumstances in childhood had a specific influence on mortality from these disorders, which was not due to the continuity of social disadvantage throughout the lifecourse. Hemorrhagic stroke shows a particularly large (though nonsignificant) relative risk, which confirms other findings regarding higher hemorrhagic stroke risk with larger number of siblings (31) and lower adult height (32), both markers of adverse circumstances in childhood.
The mechanisms of the relationship between lower childhood mental ability and earlier death, our third task, must be understood further before they are practically useful for health policy formation. Exploring further specific IQ-illness relationships must take account of other causes. For example, birth weight is associated with both IQ at age 11 (33) and with heart disease in later life (34). The association with lung cancer affords a hypothesis that involves the effects of smoking and other factors, which will be investigated subsequently. Combining the SMS1932 and Midspan databases, and using complementary contributions of epidemiological and psychometric approaches to data analysis, has produced novel findings into the personal and social factors that contribute to health inequalities in later life.
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ACKNOWLEDGMENTS |
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Received for publication August 22, 2002.
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