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Evolutionary Psychological Science

, Volume 4, Issue 3, pp 272–284 | Cite as

What Caused over a Century of Decline in General Intelligence? Testing Predictions from the Genetic Selection and Neurotoxin Hypotheses

  • Michael A. Woodley of MenieEmail author
  • Matthew A. Sarraf
  • Mateo Peñaherrera-Aguirre
  • Heitor B. F. Fernandes
  • David Becker
Research Article
First Online:

Abstract

Several converging lines of evidence indicate that general intelligence (g) has declined in Western populations. The causes of these declines are debated. Here, two hypotheses are tested: (1) selection acting against genetic variants that promote g causes the decline and (2) the presence of neurotoxic pollution in the environment causes the decline. A linear mixed model was devised to test (1) and (2), in which the secular decline in a “heritable g” (g.h) chronometric factor (comprised of convergent indicators of simple reaction time, working memory, utilization frequencies of high difficulty and also social-intelligence-indicating vocabulary items and per capita macro-innovation rates) was predicted using a neurotoxin chronometric factor (comprised of convergent secular trends among measures of lead, mercury and dioxin + furan pollution, in addition to alcohol consumption) and a polygenic score chronometric factor (comprised of polygenic score means for genetic variants predictive of g, sourced from US and Icelandic age-stratified cohorts). Bivariate correlations revealed that (other than time) only the polygenic score factor was significantly associated with declining g.h (r = .393, p < .05 vs. .033, ns for the neurotoxin factor). Using a hierarchical linear mixed model approach incorporating 25 year lags between the predictors and g.h, time period, operationalized categorically as fifths of a century, accounted for the majority of the variance in the decline in g.h (partial η2 = .584, p < .05). Net of time period and neurotoxins, changing levels of polygenic scores also significantly predicted variance in the decline in g.h (partial η2 = .253, p < .05); however, changing levels of neurotoxins did not significantly predict variance in g.h net of time (partial η2 = .027 ns). Within-period analysis indicates that the independent significant positive effect of the polygenic score factor on g.h was restricted to the third fifth of a century period (β = .202, p < .05).

Keywords

Directional selection Dysgenics General intelligence Neurotoxins Polygenic scores 
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References

  1. Bailey, D., Duncan, G. J., Odgers, C. L., & Yu, W. (2017). Persistence and fadeout in the impacts of child and adolescent interventions. Journal of Research on Educational Effectiveness, 10, 7–39.CrossRefPubMedGoogle Scholar
  2. Banks, G. C., Batchelor, J. H., & McDaniel, M. A. (2010). Smarter people are (a bit) more symmetrical: a meta-analysis of the relationship between intelligence and fluctuating asymmetry. Intelligence, 38, 393–401.CrossRefGoogle Scholar
  3. Bates, T., Hansell, N. K., Martin, N. G., & Wright, M. J. (2016). When does socioeconomic status (SES) moderate the heritability of IQ?: no evidence for g x SES interaction for IQ in a representative sample 1,176 Australian adolescent twin pairs. Intelligence, 56, 10–15.CrossRefGoogle Scholar
  4. Beauchamp, J. P. (2016). Genetic evidence for natural selection in humans in the contemporary United States. Proceedings of the National Academy of Sciences USA, 113, 7774–7779.CrossRefGoogle Scholar
  5. Bouchard Jr., T. J. (2004). Genetic influence on human psychological traits. Current Directions in Psychological Science, 13, 148–151.CrossRefGoogle Scholar
  6. Brand, C. (1999). IQ heritability—the emptiness of modern environmentalism. A review of: Robert J. Sternberg & Elena Grigorenko (eds.) (1997). Intelligence, Heredity and Environment. Cambridge, UK: Cambridge University press. Personality and Individual Differences, 26, 767–774.Google Scholar
  7. Brunswik, E. (1952). The conceptual framework of psychology (international encyclopedia of unified science, volume 1, number 10). Chicago, IL: The University of Chicago Press.Google Scholar
  8. Bunch, B., & Hellemans, A. (2004). The history of science and technology: a browser’s guide to the great discoveries, inventions, and the people who made them from the dawn of time to today. New York, NY: Houghton Mifflin Company.Google Scholar
  9. Calderón-Garcidueñs, L., Mora-Tiscareño, A., Onitveros, E., Gómez-Garza, G., Barragán-Mejía, G., Broadway, J., … Engle, R.W. (2008). Air pollution, cognitive deficits and brain abnormalities: a pilot study with children and dogs. Brain and Cognition, 68, 117–127.Google Scholar
  10. Cattell, R. B. (1950). The fate of national intelligence: test of a thirteen-year prediction. The Eugenics Review, 42, 136–148.PubMedPubMedCentralGoogle Scholar
  11. Cattell, R. B. (1937). The fight for our national intelligence. London, UK: P. S. King & Son, Ltd..Google Scholar
  12. Clarke, R. P. (2015). Rising-falling mercury pollution causing the rising-falling IQ of the Lynn-Flynn effect, as predicted by the antiinnatia theory of autism and IQ. Personality and Individual Differences, 82, 46–51.CrossRefGoogle Scholar
  13. Conley, D., Laidley, T., Belsky, D. W., Fletcher, J. M., Boardman, J. D., & Domingue, B. W. (2016). Assortative mating and differential fertility by phenotype and genotype across the 20th century. Proceedings of the National Academy of Sciences, USA, 113, 6647–6652.CrossRefGoogle Scholar
  14. Darwin, C. (1871). The descent of man, and selection in relation to sex. London, UK: D. Appleton & Co..CrossRefGoogle Scholar
  15. Debes, F., Ludvig, A., Budtz-Jørgensen, E., Weihe, P., & Grandjean, P. (2015). The effects of methylmercury on general intelligence in children and young adults. Oral presentation given at the 16th Annual Meeting of the International Society for Intelligence Research. Albuquerque, New Mexico, USA, September.Google Scholar
  16. Debes, F., Weihe, P., & Grandjean, P. (2016). Cognitive deficit at age 22 years associated with prenatal exposure to methylmercury. Cortex, 74, 358–369.CrossRefPubMedGoogle Scholar
  17. Demeneix, B. (2014). Losing our minds: how environmental pollution impairs human intelligence and mental health. Oxford, UK: Oxford University Press.CrossRefGoogle Scholar
  18. Demeneix, B. (2017). Toxic cocktail: how chemical pollution is poisoning our brains. New York, NY: Oxford University Press.Google Scholar
  19. Domingue, B., Belsky, D. W., Harrati, A., Conley, D., Weir, D., & Boardman, J. (2017). Mortality selection in a genetic sample and implications for association studies. International Journal of Epidemiology, 46, 1285–1294. (BioArxiv:  https://doi.org/10.1101/049635).
  20. Figlio, D. N., Freese, J., Karbownik, K., & Roth, J. (2017). Socioeconomic status and genetic influences on cognitive development. Proceedings of the National Academy of Sciences, USA, 114, 13441–13446.Google Scholar
  21. Flynn, J. R. (1987). Massive IQ gains in 14 nations: what IQ tests really measure. Psychological Bulletin, 101, 171–191.CrossRefGoogle Scholar
  22. Flynn, J. R., te Nijenhuis, J., & Metzen, D. (2014). The g beyond Spearman’s g: Flynn’s paradoxes resolved using four exploratory meta-analyses. Intelligence, 44, 1–10.CrossRefGoogle Scholar
  23. Fox, M. C., & Mitchum, A. L. (2013). A knowledge based theory of rising scores on “culture-free” tests. Journal of Experimental Psychology: General, 142, 979–1000.Google Scholar
  24. Galton, F. (1869). Hereditary genius. London, UK: MacMillan.CrossRefGoogle Scholar
  25. Gorsuch, R. L. (1983). Factor analysis. Hillside, NJ: L. Earlbaum Associates.Google Scholar
  26. Gottfredson, L. S. (2005). What if the hereditarian hypothesis is true? Psychology, Public Policy, and Law, 11, 311–319.CrossRefGoogle Scholar
  27. Hagenmeier, H., & Walczok, M. (1996). Time trends in levels, patterns and profiles for PCDD/PCDF in sediment cores of Lake Constance. Organohalogen Compounds, 28, 101–104.Google Scholar
  28. Herrnstein, R. J., & Murray, C. (1994). The bell curve: intelligence and class structure in American life. New York, NY: Free Press Paperbacks.Google Scholar
  29. Higgins, J. V., Reed, E. W., & Reed, S. C. (1962). Intelligence and family size: a paradox resolved. Eugenics Quarterly, 9, 84–90.CrossRefPubMedGoogle Scholar
  30. Huebner, J. (2005). A possible declining trend for worldwide innovation. Technological Forecasting and Social Change, 72, 980–986.CrossRefGoogle Scholar
  31. Jensen, A. R. (1998). The g factor: the science of mental ability. Westport, CT: Praeger.Google Scholar
  32. Kan, K. J., Wicherts, J. M., Dolan, C. V., & van der Maas, H. L. J. (2013). On the nature and nurture of intelligence and specific cognitive abilities: the more heritable, the more culture dependent. Psychological Science, 24, 2420–2428.CrossRefPubMedGoogle Scholar
  33. Kong, A., Banks, E., Poplin, R., Garimella, K. V., Maguire, J. R., et al. (2017). Selection against variants in the genome associated with educational attainment. Proceedings of the National Academy of Sciences, USA, 114, E727–E732.CrossRefGoogle Scholar
  34. Lakatos, I. (1970). Falsificationism and the methodology of scientific research programmes. In I. Lakatos & A. Musgrave (Eds.), Criticism and the growth of knowledge (pp. 91–196). Cambridge,UK: Cambridge University Press.Google Scholar
  35. Lievens, F., Reeve, C. L., & Heggestad, E. D. (2007). An examination of psychometric bias due to retesting in selection settings. Journal of Applied Psychology, 92, 1672–1682.CrossRefPubMedGoogle Scholar
  36. Lynn, R. (1996). Dysgenics: genetic deterioration in modern populations. Westport, CT: Praeger.Google Scholar
  37. Lynn, R., & van Court, M. (2004). New evidence of dysgenic fertility for intelligence in the United States. Intelligence, 32, 193–201.CrossRefGoogle Scholar
  38. Madison, G., Woodley of Menie, M. A., & Sänger, J. (2016). Possible secular slowing auditory simple reaction time in Sweden (1959-1985). Frontiers in Human Neuroscience, 10, 407.CrossRefPubMedPubMedCentralGoogle Scholar
  39. Marques, R. C., Bernardi, J. V. E., Cunha, M. P. L., & Dórea, J. G. (2016). Impact of organic mercury exposure and home delivery on neurodevelopment of Amazonian children. International Journal of Hygiene and Environmental Health, 219, 498–502.Google Scholar
  40. McKnight, P. E., McKnight, K. M., Sidani, S., & Figueredo, A. J. (2007). Missing data: a gentle introduction. New York, NY: Guildford Publications.Google Scholar
  41. Metzen, D. (2012). The causes of group differences in intelligence studied using the method of correlated vectors and psychometric meta-analysis. Unpublished Masters Thesis, University of Amsterdam.Google Scholar
  42. Millet, K., & Dewitte, S. (2007). Altruistic behaviour as a costly signal of general intelligence. Journal of Research in Personality, 41, 316–326.CrossRefGoogle Scholar
  43. Murray, C. (2003). Human accomplishment: the pursuit of excellence in the arts and sciences, 800 BC to 1950. New York, NY: Harper Collins.Google Scholar
  44. Nevin, R. (2000). How lead exposure relates to temporal changes in IQ, violent crime, and unwed pregnancy. Environmental Research Section A, 83, 1–22.CrossRefPubMedGoogle Scholar
  45. Okbay, A., Beauchamp, J.P., Fontana, M.A., Lee, J.J., Pers, T.H., Rietveld, C.A., et al. (2016). Genome-wide association study identifies 74 loci associated with educational attainment. Nature, 533, 539–542.Google Scholar
  46. Panizzon, M. S., Vuoksimaa, E., Spoon, K. M., Jacobson, K. C., Lyons, M. J., et al. (2014). Genetic and environmental influences on general cognitive ability: is g a valid latent construct? Intelligence, 43, 65–76.CrossRefPubMedPubMedCentralGoogle Scholar
  47. Pietschnig, J., & Gittler, G. (2015). A reversal of the Flynn effect for spatial perception in German speaking countries: Evidence from a crosstemporal IRT-based meta-analysis (1977–2014). Intelligence, 53, 145–153.Google Scholar
  48. Pietschnig, J., & Voracek, M. (2015). One century of global IQ gains: a formal meta-analysis of the Flynn effect (1909–2013). Perspectives on Psychological Science, 10, 282–306.Google Scholar
  49. Pietschnig, J., & Gittler, G. (2017). Is ability-based emotional intelligence impervious to the Flynn effect? A cross-temporal meta-analysis (2001-2015). Intelligence, 61, 37-45.Google Scholar
  50. Plomin, R. (2002). Quantitative trait loci and general cognitive ability. In J. Benjamin, R. P. Ebstein, & R. H. Belmaker (Eds.), Molecular genetics and human personality (pp. 211–230). Washington, DC: American Psychiatric Publishing, Inc..Google Scholar
  51. Portman Group (n.d.). Retrieved September 16, 2017, from http://www.portmangroup.org.uk/
  52. Protzko, J. (2015). The environment in raising early intelligence: a meta-analysis of the fadeout effect. Intelligence, 53, 202–210.CrossRefGoogle Scholar
  53. Reeve, C. L., & Lam, H. (2007). The relation between practice effects, test-taker characteristics and degree of g-saturation. International Journal of Testing, 7, 225–242.CrossRefGoogle Scholar
  54. Rushton, J. P. (1998). The “Jensen effect” and the “Spearman–Jensen hypothesis” of black–white IQ differences. Intelligence, 26, 217–225.CrossRefGoogle Scholar
  55. Rushton, J. P. (1989). The generalizability of genetic estimates. Personality and Individual Differences, 10, 985–989.CrossRefGoogle Scholar
  56. Sarraf, M. (2017). Review of historical variability in heritable general intelligence: its evolutionary origins and sociocultural consequences. Personality and Individual Differences, 109, 238–241.CrossRefGoogle Scholar
  57. Schuster, P. F., Krabbenhoft, D. P., Nafz, D. L., Cecil, L. D., Olson, M. L., Dewild, J. F., et al. (2002). Atmospheric mercury deposition during the last 270 years: a glacial ice core record of natural and anthropogenic sources. Environmental Science and Technology, 36, 2303–2310.CrossRefPubMedGoogle Scholar
  58. Sesardic, N. (2005). Making sense of heritability. Cambridge, UK: Cambridge University Press.CrossRefGoogle Scholar
  59. Silverman, I. W. (2010). Simple reaction time: it is not what it used to be. American Journal of Psychology, 123, 39–50.CrossRefPubMedGoogle Scholar
  60. Skirbekk, V. (2008). Fertility trends by social status. Demographic Research, 18, 145–180.CrossRefGoogle Scholar
  61. Spearman, C. (1904). General intelligence, objectively determined and measured. American Journal of Psychology, 15, 201–293.CrossRefGoogle Scholar
  62. Sundet, J. M., Tambs, K., Magnus, P., & Berg, K. (1988). On the question of secular trends in the heritability of intelligence test scores: a study of Norwegian twins. Intelligence, 12, 47–59.CrossRefGoogle Scholar
  63. te Nijenhuis, J., & van der Flier, H. (2013). Is the Flynn effect on g?: a metaanalysis. Intelligence, 41, 802–807.CrossRefGoogle Scholar
  64. te Nijenhuis, J., Jongeneel-Grimen, B., & Kirkegaard, E. O. W. (2014). Are Headstart gains on the g factor? A meta-analysis. Intelligence, 46, 209–215.CrossRefGoogle Scholar
  65. te Nijenhuis, J., Jongeneel-Grimen, B., & Armstrong, E. L. (2015). Are adoption gains on the g factor? A meta-analysis. Personality and Individual Differences, 73, 56–60.CrossRefGoogle Scholar
  66. te Nijenhuis, J., van Vianen, A. E. M., & van der Flier, H. (2007). Sore gains on g-loaded tests: no g. Intelligence, 35, 283–300.CrossRefGoogle Scholar
  67. ten Tusscher, G.W., Leijs, M., Boer, L.D., Legler, J., Olie, K., Spekreijse, H., … Koppe, J. (2014). Neurodevelopmental retardation, as assessed clinically and with magnetoencephalography and electroencephalography, associated with perinatal dioxin exposure. Science of the Total Environment, 491-492, 235–239.Google Scholar
  68. Tucker-Drob, E. M., & Bates, T. C. (2016). Large cross-national differences in gene x socioeconomic status interaction on intelligence. Psychological Science, 27, 138–149.CrossRefPubMedGoogle Scholar
  69. VinePair. (n.d.). Retreived September 15, 2017, from https://www.vinepair.com.
  70. Voronin, I., te Nijenhuis, J., & Malykh, S. B. (2015). The correlation between g loadings and heritability in Russia. Journal of Biosocial Science, 28, 1–11.Google Scholar
  71. Wicherts, J. M., Dolan, C. V., Oosterveld, P., Hessen, D. J., van Baal, G. C. M., Boomsma, D. I., et al. (2004). Are intelligence tests measurement invariant over time? Investigating the nature of the Flynn effect. Intelligence, 32, 509–537.CrossRefGoogle Scholar
  72. Wongupparaj, P., Wongupparaj, R., Kumari, & Morris, R. G. (2017). The Flynn effect for verbal and visuospatial short-term and working memory: a cross-temporal meta-analysis. Intelligence, 64, 71–80.CrossRefGoogle Scholar
  73. Woodley, M. A. (2012). The social and scientific temporal correlates of genotypic intelligence and the Flynn effect. Intelligence, 40, 189–204.CrossRefGoogle Scholar
  74. Woodley, M. A., & Figueredo, A. J. (2013). Historical variability in heritable general intelligence: its evolutionary origins and socio-cultural consequences. Buckingham, UK: Buckingham University Press.Google Scholar
  75. Woodley, M. A., & Madison, G. (2013). Establishing an association between the Flynn effect and ability differentiation. Personality and Individual Differences, 55, 387–390.CrossRefGoogle Scholar
  76. Woodley, M. A., te Nijenhuis, J., & Murphy, R. (2013). Were the Victorians cleverer than us? The decline in general intelligence estimated from a meta-analysis of the slowing of simple reaction time. Intelligence, 41, 843–850.CrossRefGoogle Scholar
  77. Woodley, M. A., te Nijenhuis, J., & Murphy, R. (2014). Is there a dysgenic secular trend towards slowing simple reaction time? Responding to a quartet of critical commentaries. Intelligence, 46, 131–147.CrossRefGoogle Scholar
  78. Woodley of Menie, M. A. (2016). Consideration of cognitive variance components potentially solves Beauchamp’s paradox. Proceedings of the National Academy of Sciences, USA, 113, E5780–E5781.CrossRefGoogle Scholar
  79. Woodley of Menie, M. A., & Fernandes, H. B. F. (2015). Do opposing secular trends on backwards and forwards digit span evidence the co-occurrence model? A comment on Gignac (2015). Intelligence, 50, 125–130.CrossRefGoogle Scholar
  80. Woodley of Menie, M. A., & Fernandes, H. B. F. (2016a). Showing their true colours: possible secular declines and a Jensen effect on color acuity—more evidence for the weaker variant of Spearman’s other hypothesis. Personality and Individual Differences, 88, 280–284.CrossRefGoogle Scholar
  81. Woodley of Menie, M. A., & Fernandes, H. B. F. (2016b). The secular decline in general intelligence from decreasing developmental stability: theoretical and empirical considerations. Personality and Individual Differences, 92, 194–199.CrossRefGoogle Scholar
  82. Woodley of Menie, M. A., Fernandes, H. B. F., Figueredo, A. J., & Meisenberg, G. (2015a). By their words ye shall know them: evidence of genetic selection against general intelligence and concurrent environmental enrichment in vocabulary usage since the mid 19th century. Frontiers in Psychology, 6, 361.CrossRefGoogle Scholar
  83. Woodley of Menie, M. A., Figueredo, A. J., Sarraf, M. A., Hertler, S., Fernandes, H. B. F., & Peñaherrera Aguirre, M. (2017a). The rhythm of the west: a biohistory of the modern era, AD 1600 to the present. Journal of Social Political and Economic Studies, monograph series, no. 37. Washington, DC: Scott Townsend Press.Google Scholar
  84. Woodley of Menie, M. A., Peñaherrera-Aguirre, M., Fernandes, H. B. F., & Figueredo, A. J. (2017b). What causes the anti-Flynn effect? A data synthesis and analysis of predictors. Evolutionary Behavioral Sciences.  https://doi.org/10.1037/ebs0000106.
  85. Woodley of Menie, M. A., Schwartz, J. A., & Beaver, K. M. (2016). How cognitive genetic factors influence fertility outcomes: a meditational SEM analysis. Twins Research and Human Genetics, 19, 628–637.CrossRefGoogle Scholar
  86. Woodley of Menie, M. A., te Nijenhuis, J., & Murphy, R. (2015b). The Victorians were still faster than us. Commentary: Factors influencing the latency of simple reaction times. Frontiers in Human Neuroscience, 9, 452.CrossRefPubMedPubMedCentralGoogle Scholar
  87. Woodley of Menie, M.A., te Nijenhuis, J.,Shibaev, V., Li,M., & Smit, J. (2018). Are the effects of lead exposure linked to the g factor? A meta-analysis. Working Paper.Google Scholar

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© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Michael A. Woodley of Menie
    • 1
    • 2
    Email author
  • Matthew A. Sarraf
    • 3
  • Mateo Peñaherrera-Aguirre
    • 4
  • Heitor B. F. Fernandes
    • 4
  • David Becker
    • 5
  1. 1.Center Leo Apostel for Interdisciplinary StudiesVrije Universiteit BrusselBrusselsBelgium
  2. 2.Unz FoundationPalo AltoUSA
  3. 3.University of RochesterRochesterUSA
  4. 4.Department of PsychologyUniversity of ArizonaTucsonUSA
  5. 5.Department of PsychologyTechnische Universität ChemnitzChemnitzGermany

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