Adolescent IQ and Survival in the Wisconsin Longitudinal Study

RESEARCH on the association between early IQ and survival has led to the development of a nascent subdiscipline cognitive epidemiology (Deary & Batty, 2006, 2007; Deary, 2009, 2010; Deary, Whalley, & Starr, 2009; Lubinski, 2009). Much of this research has been integrated in a comprehensive account of follow-ups to the Scottish Mental Surveys (Deary et al., 2009). In addition to overall mortality (Batty, Wennerstad, et al., 2009; Hart, Deary, et al., 2003; Hart, Taylor, et al. 2003; Hart et al., 2005; Leon, Lawlor, Clark, Batty, & Macintyre, 2009; Osler et al., 2003; Whalley & Deary, 2001), IQ has been associated with accidental deaths (Batty, Deary, Schoon, & Gale, 2007; Batty, Gale, Tynelius, Deary, & Rasmussen, 2009; O’Toole, 1990; O’Toole & Stankov, 1992; Young, 2008), with homicide (Batty, Deary, Tengstrom, & Rasmussen, 2008), with hypertension, stroke, and cardiovascular disease (Batty, Mortensen, Andersen, & Osler, 2005; Batty, Modig Wennerstad, et al., 2007; Hart, Taylor, Davey, et al., 2003; Lindgarde, Furu, & Ljung, 1987; Starr et al., 2004), with quitting smoking (Taylor et al., 2003), and with time to menopause (Kuh et al., 2005; Richards, Kuh, Hardy, & Wadsworth, 1999; Shinberg, 1998; Whalley, Fox, Starr, & Deary 2004). These studies provide little evidence that differential survival by IQ is explained by the well-established correlation of IQ with social and economic origins. There is mixed evidence that the effects of IQ on mortality are mediated by one's own education and socioeconomic success (Batty, Wennerstad, et al., 2009; Link & Phelan, 2005; Link, Phelan, Miech, & Westin, 2008). In this article, we analyze the association between adolescent IQ and survival from ages 18 to 69 in a large American sample of high school graduates. The IQ–survival association is entirely explained by a cumulative measure of academic performance (rank in high school class) that is only moderately associated (r = .6) with IQ, leaving almost two thirds of its variance unexplained. Moreover, the effect of rank in high school class on survival is about three times larger than that of IQ. This finding suggests that higher cognitive functioning improves the chances of survival because it leads to behaviors that are responsible, well organized, timely, and appropriate to the situation and that such patterns of behavior are well established by late adolescence. Prior research suggests that conscientiousness, one of the “Big Five” personality characteristics, plays a key role in this relationship. It is a well-established antecedent of academic performance in high school (Poropat, 2009), and it is also related to health and survival at older ages (Roberts, Kuncel, Shiner, Caspi, & Goldberg 2007). Deary's (2008) essay in Nature noted that an association between “early life intelligence and mortality” has been established “across different populations, in different countries, and in different epochs.” He offered four potential explanations of this ubiquitous finding: higher education, healthy behaviors, early insults to the brain, and system integrity: “First, … intelligence is associated with more education and thereafter with more professional occupations that might place the person in healthier environments. … Second, people with higher intelligence might engage in more healthy behaviours. … Third, mental test scores from early life might act as a record of insults to the brain that have occurred before that date. … Fourth, mental test scores obtained in youth might be an indicator of a well-put-together system. It is hypothesized that a well-wired body is more able to respond effectively to environmental insults” (p. 176). The first two and the last two of these potential mechanisms differ in one important respect. Education and health behaviors are mediating mechanisms, although Deary's text suggests that IQ may be a proxy measure of “insults to the brain” and “a well-wired body.” The present analysis focuses on another mechanism that may mediate the life-long influence of intelligence. Importantly, Deary's essay also referred to a finding that “being more dependable or conscientious in childhood is also significantly protective to health” (Deary, Batty, Pattie, & Gale, 2008; Schwartz et al., 1995), yet this may be the key to explaining the association between IQ and survival. Some of the risk factors that account for health differentials, for example, smoking, drinking, overeating, and lack of exercise, are known by almost all adults. The important question is not whether these risks are known and understood, but why people continue to ignore them. Some researchers have emphasized strictly cognitive explanations for the association between survival and IQ early in life. In a prize-winning article, Gottfredson (2004) has suggested that IQ is “the epidemiologists’ elusive fundamental cause of social class differences in health,” thus implying that it may account for the influence of socioeconomic standing on survival. Deary has written “Whether you live to collect your old-age pension depends in part on your IQ at age 11. You just can’t keep a good predictor down” (Deary, 2005). Batty and Deary (2004) interpret the IQ differential as attributable to excessive cognitive demands in health care settings: “Given their inherently complex and sometimes conflicting nature, health care messages, treatment regimens, and preventative strategies perhaps surpass the cognitive abilities of some people. If this is the case—and bearing in mind that oversimplification of advice might reduce effectiveness substantially—proactive involvement of health care providers is warranted to reduce health inequalities attributable to differences in cognitive ability.” Although cognitive limits may well affect understanding and compliance in health care settings, there is no direct evidence that this accounts for the association between survival and IQ in early life. Moreover, the recent literature on IQ and survival may have overemphasized the implications of findings that identify variables(s) as statistically significant predictor(s) of mortality. Estimates of relative hazard or odds ratios and their standard errors may have very weak practical implications, despite their statistical reliability. For example, consider the recent article in which Batty, Wennerstad, and colleagues (2009) estimated the relationship between IQ (military induction test) and mortality among 1 million Swedish men for ∼20 years (from roughly age 18 to 38 years). Their main finding is a highly significant hazard ratio of 1.32 for the association between a 1 SD difference in IQ and the likelihood of death. Although this effect appears to be large, it has almost no impact on expected years of life within the age span covered by the survey (roughly 20 years). Of the 968,846 men in the Swedish cohort, just 14,498 men died. At the ages in question, the overall hazard is small and virtually constant, so it is fair to approximate the hazard as 14,498/(20 X [times au] 968,846) = .0007482. This implies about19.85 years of expected life, that is, just 0.15 years below the maximum of 20. If average IQ in the cohort was a full standard deviation higher—a most unlikely event—the hazard would fall to .0005668, and the expected number of years of life would rise to 19.89 years, just 0.04 years higher than before. To be sure, under this assumption, the number of deaths would fall by 24% but that merely underscores the extremity of assuming a 1 SD rise in average IQ. Existing research on IQ and survival leaves many important questions unanswered. Is the association between IQ and survival a consequence of purely cognitive processes? Or are there other intervening mechanisms? If IQ were immutable, which is increasingly doubtful (Nisbett, 2009), what avenues of intervention are available? What good would it do to intervene in the medical care setting if the influence of cognition is pervasive across the life course? Is cognition about health issues and medical procedures the real issue? And of what importance is the effect of IQ on survival, relative to other known correlates?