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Decomposition of Mean Sex Differences in Alcohol Use Within a Genetic Factor Model

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Abstract

A wealth of literature suggests that normative and heavy alcohol consumption continue to follow a historical pattern of greater prevalence among males as compared to females. Some prior research suggested that sex-specific factors might explain some of this gender gap. Generally speaking, though, more recent studies have indicated that the sources of differences for most complex traits, both genetic and environmental, are similar for males and females. To the best of our knowledge, however, no studies have tested whether genetic and environmental factors common to both sexes are more often expressed in males, on average, thereby accounting for some of the mean sex difference in alcohol use. The current study used nationally representative data from American twin respondents and a multiple group genetic factor model with a mean structure to address this gap in the literature. Results provide no evidence of sex differences in covariance structure and suggest that genetic and nonshared environmental influences common to both sexes largely explain why male alcohol use is more frequent and severe, on average, than is female use. In contrast, shared environmental influences seem to play a less important role. We discuss our findings in the context of the existing literature and chart out directions for future research.

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Notes

  1. Selection bias is one additional potential source of apparent sex differences in frequency and severity of alcohol use. More males than females, for instance, might select to treatment and receive an AUD diagnosis. Here we do not consider this possibility further because we are attending to differences detected in nationally representative data.

  2. Researchers can test still higher levels of invariance (e.g., invariance of factor variances and residuals) but typically only configural, metric, and scalar invariance are evaluated. This is partly because invariance at these levels ensures most inferences of interest are not compromised by bias, and partly because higher levels are often more difficult to achieve (for further discussion, see Wang et al. 2018).

  3. Mplus fixes the first loading on each factor to one by default. We freed these loadings so they could be estimated and constrained them equal across the groups. Mplus constrains intercepts to zero by default when the WLSMV estimator is used and information about them is captured by thresholds. Observed variable residuals are not estimated under delta parameterization.

References

  • Agrawal A, Freedman ND, Cheng Y-C et al (2012) Measuring alcohol consumption for genomic meta-analyses of alcohol intake: opportunities and challenges. Am J Clin Nutr 95:539–547

    Article  Google Scholar 

  • Barnes J, Boutwell BB (2013) A demonstration of the generalizability of twin-based research on antisocial behavior. Behav Genet 43:120–131

    Article  Google Scholar 

  • Browne MW, Cudeck R (1993) Alternative ways of assessing model fit. Sage focus editions 154:136–136

    Google Scholar 

  • Burt SA, Slawinski BL, Carsten EE et al (2019) How should we understand the absence of sex differences in the genetic and environmental origins of antisocial behavior? Psychol Med 49(10):1600–1607

    Article  Google Scholar 

  • Byrne B (2001) Multivariate applications book series. Structural equation modeling with AMOS: basic concepts, applications, and programming. Lawrence Erlbaum Associates Publishers, Mahwah

    Google Scholar 

  • Chabris CF, Lee JJ, Cesarini D et al (2015) The fourth law of behavior genetics. Curr Dir Psychol Sci 24:304–312

    Article  Google Scholar 

  • Cho SB, Wood PK, Heath AC (2009) Decomposing group differences of latent means of ordered categorical variables within a genetic factor model. Behav Genet 39:101–122

    Article  Google Scholar 

  • Cohen J (2013) Statistical power analysis for the behavioral sciences. Academic Press, Cambridge

    Book  Google Scholar 

  • Copping LT, Richardson GB (2019) Studying sex differences in psychosocial life history indicators. Evol Psychol Sci 6:47–59

    Article  Google Scholar 

  • Cross CP, Copping LT, Campbell A (2011) Sex differences in impulsivity: a meta-analysis. Psychol Bull 137:97

    Article  Google Scholar 

  • Dolan CV, Molenaar PC, Boomsma DI (1992) Decomposition of multivariate phenotypic means in multigroup genetic covariance structure analysis. Behav Genet 22:319–335

    Article  Google Scholar 

  • Dolan CV, Molenaar PC, Boomsma DI (1991) Simultaneous genetic analysis of longitudinal means and covariance structure in the simplex model using twin data. Behav Genet 21:49–65

    Article  Google Scholar 

  • Grant BF, Chou SP, Saha TD et al (2017) Prevalence of 12-month alcohol use, high-risk drinking, and DSM-IV alcohol use disorder in the United States, 2001–2002 to 2012–2013: results from the National Epidemiologic Survey on Alcohol and Related Conditions. JAMA Psychiatry 74:911–923

    Article  Google Scholar 

  • Heath AC, Bucholz K, Madden P et al (1997) Genetic and environmental contributions to alcohol dependence risk in a national twin sample: consistency of findings in women and men. Psychol Med 27:1381–1396

    Article  Google Scholar 

  • Hu L, Bentler PM (1999) Cutoff criteria for fit indexes in covariance structure analysis: conventional criteria versus new alternatives. Struct Equ Model 6:1–55

    Article  Google Scholar 

  • Little TD (1997) Mean and covariance structures (MACS) analyses of cross-cultural data: practical and theoretical issues. Multivar Behav Res 32:53–76

    Article  Google Scholar 

  • Millsap E (2011) Statistical methods for studying measurement invariance. Taylor & Fransis, Abingdon

    Google Scholar 

  • Muthén B, du Toit S, Spisic, D (1997) Robust inference using weighted least squares and quadratic estimating equations in latent variable modeling with categorical and continuous outcomes. Unpublished technical report

  • Naqvi S, Godfrey AK, Hughes JF et al (2019) Conservation, acquisition, and functional impact of sex-biased gene expression in mammals. Science 365:eaaw7317

    Article  Google Scholar 

  • Neale M, Cardon L (1992) Methodology for genetic studies of twins and families. Springer Science & Business Media, Berlin

    Book  Google Scholar 

  • Neale MC, Røysamb E, Jacobson K (2006) Multivariate genetic analysis of sex limitation and G× E interaction. Twin Res Hum Genet 9:481–489

    Article  Google Scholar 

  • Ngun TC, Ghahramani N, Sánchez FJ et al (2011) The genetics of sex differences in brain and behavior. Front Neuroendocrinol 32:227–246

    Article  Google Scholar 

  • Polderman TJ, Benyamin B, De Leeuw CA et al (2015) Meta-analysis of the heritability of human traits based on fifty years of twin studies. Nat Genet 47:702

    Article  Google Scholar 

  • Prescott CA, Aggen SH, Kendler KS (1999) Sex differences in the sources of genetic liability to alcohol abuse and dependence in a population-based sample of US twins. Alcoholism 23:1136–1144

    Article  Google Scholar 

  • Sanchis-Segura C, Becker JB (2016) Why we should consider sex (and study sex differences) in addiction research. Addict Biol 21:995–1006

    Article  Google Scholar 

  • Scholte RH, Poelen EA, Willemsen G et al (2008) Relative risks of adolescent and young adult alcohol use: the role of drinking fathers, mothers, siblings, and friends. Addict Behav 33:1–14

    Article  Google Scholar 

  • Schwabe I, Janss L, Van Den Berg SM (2017) Can we validate the results of twin studies? A census-based study on the heritability of educational achievement. Front Genet 8:160

    Article  Google Scholar 

  • Selzer ML (1971) The Michigan Alcoholism Screening Test: the quest for a new diagnostic instrument. Am J Psychiatry 127:1653–1658

    Article  Google Scholar 

  • Slutske WS (2005) Alcohol use disorders among US college students and their non–college-attending peers. Arch Gen Psychiatry 62:321–327

    Article  Google Scholar 

  • Thomasson HR (2002) Gender differences in alcohol metabolism. Recent developments in alcoholism. Springer, Berlin, pp 163–179

    Chapter  Google Scholar 

  • Verhulst B, Neale MC, Kendler KS (2015) The heritability of alcohol use disorders: a meta-analysis of twin and adoption studies. Psychol Med 45:1061–1072

    Article  Google Scholar 

  • Viding E, Spinath FM, Price TS et al (2004) Genetic and environmental influence on language impairment in 4-year-old same-sex and opposite-sex twins. J Child Psychol Psychiatry 45:315–325

    Article  Google Scholar 

  • Vink JM, Bartels M, Van Beijsterveldt TC et al (2012) Sex differences in genetic architecture of complex phenotypes? PLoS ONE 7:e47371

    Article  Google Scholar 

  • Wang S, Chen C-C, Dai C-L, Richardson GB (2018) A call for, and beginner’s guide to, measurement invariance testing in evolutionary psychology. Evol Psychol Sci 4:166–178

    Article  Google Scholar 

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Correspondence to George B. Richardson.

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George B. Richardson and Brian B. Boutwell declare that they have no conflict of interest.

Human and Animal Rights and Informed Consent

This study involved analysis of a publicly available and de-identified dataset, the Institutional Review Board at the University of Cincinnati determined that it did not meet the regulatory criteria for research involving human subjects.

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Richardson, G.B., Boutwell, B.B. Decomposition of Mean Sex Differences in Alcohol Use Within a Genetic Factor Model. Behav Genet 50, 320–331 (2020). https://doi.org/10.1007/s10519-020-10004-0

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