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On the Sources of the Height–Intelligence Correlation: New Insights from a Bivariate ACE Model with Assortative Mating

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On the Sources of the Height–Intelligence Correlation: New Insights from a Bivariate ACE Model with Assortative Mating Behav Genet (2011) 41:242–252 DOI 10.1007/s10519-010-9376-7 ORIGINAL RESEARCH On the sources of the height–intelligence correlation: New insights from a bivariate ACE model with assortative mating Jonathan P. Beauchamp • David Cesarini • Magnus Johannesson • Erik Lindqvist • Coren Apicella Received: 30 December 2009 / Accepted: 14 June 2010 / Published online: 6 July 2010 Ó The Author(s) 2010. This article is published with open access at Springerlink.com Abstract A robust positive correlation between height and For both traits, we find suggestive evidence of a shared genetic intelligence, as measured by IQ tests, has been established in architecture with height, but we demonstrate that point esti- the literature. This paper makes several contributions toward mates are very sensitive to assumed degrees of assortative establishing the causes of this association. First, we extend the mating. Third, we report a significant within-family correla- standard bivariate ACE model to account for assortative tion between height and intelligence q^ 0:10 ; suggesting ð ¼ Þ mating. The more general theoretical framework provides that pleiotropy might be at play. several key insights, including formulas to decompose a cross- trait genetic correlation into components attributable to Keywords Assortative mating Bivariate ACE model Á Á assortative mating and pleiotropy and to decompose a cross- Genetic correlation Height Intelligence IQ Á Á Á Á trait within-family correlation. Second, we use a large dataset Within-family correlation of male twins drawn from Swedish conscription records and examine how well genetic and environmental factors explain the association between (i) height and intelligence and (ii) Introduction height and military aptitude, a professional psychogologist’s assessment of a conscript’s ability to deal with wartime stress. A robust positive correlation between height and intelli- gence, as measured by IQ tests,1 has been established in the literature with little consensus regarding its cause (Humph- Edited by Stacey Cherny. reys et al. 1985; Johnson 1991; Kanazawa and Reyniers 2009; Tanner 1979; Teasdale et al. 1989; Wheeler et al. J. P. Beauchamp (&) 2004). Both environmental and genetic explanations have Department of Economics, Harvard University, Cambridge, been advanced. For instance, previous research has found MA 02138, USA e-mail: [email protected] that markers of prenatal quality and nutritional status during childhood are associated with height (Eide et al. 2005; D. Cesarini Steckel 1995) and cognition in adulthood (See Gomez- Department of Economics, New York University, New York, Pinilla 2008; Martyn et al. 1996; Seidman et al. 1992; NY 10012, USA Sørensen et al. 1997), suggesting that early environmental M. Johannesson factors may be responsible for the correlation between height Department of Economics, Stockholm School of Economics, and intelligence (Abbott et al. 1998). Other evidence in Box 6501, Stockholm 113 83, Sweden support of environmental channels is the decline in the cor- E. Lindqvist relation between height and intelligence over time observed Research Institute of Industrial Economics, P.O. Box 55665, in the Scandinavian countries (Teasdale et al. 1989; Sundet Stockholm 102 15, Sweden et al. 2005; Tuvemo et al. 1999). On the other hand, reported C. Apicella Department of Health Care Policy, Harvard Medical School, 1 We follow the literature and use the term ‘‘intelligence’’ to refer to Boston, MA 02115, USA what those IQ tests measure. 123 Behav Genet (2011) 41:242–252 243 heritability estimates in adults for measures of intelligence hypothesis that pleiotropy (or linkage) accounts for part of (e.g. 75%) (Neisser et al. 1996) and height (e.g. 87–93%) the genetic correlation. (Silventoinen et al. 2003) are high, suggesting that the relationship may instead be genetically mediated. For example, growth hormone deficiency, which is sometimes Method caused by genetic mutations, is characterized by both short stature and cognitive impairments (van Dam et al. 2005). Sample Evidence of a shared genetic architecture between brain volume, intracranial space, and height (Posthuma et al. Our data comes from two main sources: the Swedish Twin 2000) may also be interpreted as evidence of genetic medi- Registry (STR) and the Swedish National Service Adminis- ation of the height–intelligence correlation. tration (SNSA). The STR contains information on nearly all Two studies, using twin data, have attempted to estimate twin births in Sweden since 1886, and has been described in the components of the height–intelligence correlation that are further detail elsewhere (Lichtenstein et al. 2006). The due to genetic and environmental effects. The results were sample includes those individuals who have participated in at mixed. Silventoinen et al. (2006) found in several samples of least one of the Twin Registry’s surveys. The primary data- Dutch twins that the association between height and intelli- source is SALT (Screening Across the Lifespan Twin study). gence is primarily genetic in origin. Sundet et al. (2005), using This was a survey administered to all Swedish twins born conscription data from a considerably larger and more rep- between 1926 and 1958 and attained a response rate of 74%. resentative sample of Norwegian twins, found that the asso- Fifty percent of the subjects in the dataset are from the SALT ciation between height and intelligence is primarily explained cohort. The secondary source is the web-based survey by common environmental factors. Both papers use a standard STAGE (The Study of Twin Adults: Genes and Environ- bivariate ACE model to arrive at these conclusions. ment). This was a web-based survey administered between The present study makes several contributions toward November 2005 and March 2006 to all twins born in Sweden elucidating the sources of covariation between height and between 1959 and 1985. It attained a response rate of 61%. intelligence. First, we extend the bivariate ACE model to Approximately 30% of our subjects are drawn from STAGE. allow for assortative mating and derive a general formula for Our final datasource comes from a survey sent out in 1973 to decomposing a cross-trait genetic correlation into compo- the same cohort as SALT (Lichtenstein et al. 2006). nents attributable to assortative mating and pleiotropy. This We matched the Swedish twins to the conscription data provides a clear theoretical framework for studying the provided by SNSA. All Swedish men are required by law to correlation between two traits and is particularly useful when participate in a nationwide military conscription at the age of examining phenotypes for which there is high assortative 18. Before 1990, exemptions were very rare. The actual mating, height and intelligence being prime examples. The drafting procedure can take several days during which model demonstrates how sensitive estimates from the recruits undergo medical and psychological examination. bivariate ACE model are to assumptions about assortative The basic structure of the administered intelligence test has mating. Second, we use a sample of male Swedish twins remained unchanged during our study period, though minor matched to conscription records to examine the relative changes took place in 1980 and 1994. Recruits take four importance of genetic and environmental factors in subtests (logical, verbal, spatial and technical) which, for explaining the association between height and intelligence. most of the study period, are graded on a scale from 0 to 40. The sample used is the largest to date for such a study. It These raw scores are converted to a ordinal variable ranging includes an additional measure of cognitive function other from 1 to 9. Carlstedt (2000) discusses the history of psy- than intelligence, measured during enlistment through chometric testing in the Swedish military and provides interviews by a military psychologist. This measure, which evidence that this test of intelligence is a good measure of we label military aptitude, has a strong predictive validity for general intelligence. Thus, this test differs from the AFQT, labor market outcomes independent of intelligence, such as which focuses more on ‘‘crystallized’’ intelligence. wages, earnings and unemployment (Lindqvist and Vestman All conscripts also see a psychologist for a structured forthcoming). We apply the standard bivariate ACE model to interview. The psychologist has access to background infor- decompose the height–intelligence and the height–military mation on the interviewee, such as school grades, medical aptitude correlations, but we caution that the resulting esti- background, cognitive ability and answers to a battery of mates are very sensitive to assumptions about assortative questions on friends, family, and life. In conducting the mating and illustrate the sensitivity of these estimates by interview, the psychologist is required to follow a manual and, reporting results for different assumed levels of assortative ultimately, to make an assessment of the prospective recruit’s mating. Lastly, we report a significant within-family height– capacity to handle stress in a war situation. In making the intelligence correlation q^ 0.10 ; consistent with the assessment, the psychologist considers an individual’s ability ðÞ¼ 123 244 Behav Genet (2011) 41:242–252 to function in a group, adapt to new environments, as well as Table 1 Background variables his persistance and emotional stability. Motivation for doing MZ DZ Population the military service is not among the set of characteristics that is considered beneficial for succeeding in the military. The Income (in SEK) 342,631 335,987 325,245 psychologist assigns each interviewee an ordinal score from 1 SD 241,060 340,271 258,867 to 9, but again these are constructed from four raw scores, this Education (years) 12.50 12.14 12.54 time ranging from 1 to 5. Like the intelligence test score, the SD 2.68 2.63 2.35 military aptitude score is subject to measurement error 1 if married 0.50 0.51 0.51 because of random influences on conscript performance and SD – – – because conscripts may differ in their motivation for the Age in 2005 48.85 51.69 45.43 2 military service.
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