Hostname: page-component-cd9895bd7-dk4vv Total loading time: 0 Render date: 2024-12-29T03:58:43.884Z Has data issue: false hasContentIssue false
  • English
  • Français

The rearing environment and risk for drug abuse: a Swedish national high-risk adopted and not adopted co-sibling control study

Published online by Cambridge University Press:  12 January 2016

K. S. Kendler ,
H. Ohlsson ,
K. Sundquist  and
J. Sundquist
K. S. Kendler*
Affiliation:
Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, USA Department of Psychiatry, Virginia Commonwealth University, Richmond VA, USA Department of Human and Molecular Genetics, Virginia Commonwealth University, Richmond, VA, USA
H. Ohlsson
Affiliation:
Center for Primary Health Care Research, Lund University, Malmö, Sweden
K. Sundquist
Affiliation:
Center for Primary Health Care Research, Lund University, Malmö, Sweden Stanford Prevention Research Center, Stanford University School of Medicine, Stanford, CA, USA
J. Sundquist
Affiliation:
Center for Primary Health Care Research, Lund University, Malmö, Sweden Stanford Prevention Research Center, Stanford University School of Medicine, Stanford, CA, USA
*
* Address for correspondence: K. S. Kendler, MD, Virginia Institute for Psychiatric and Behavioral Genetics of VCU, Box 980126, Richmond, VA 23298-0126, USA. (Email: [email protected])
Get access Rights & Permissions [Opens in a new window]

Abstract

Background

Although drug abuse (DA) is strongly familial, with important genetic influences, we need to know more about the role of rearing environment in the risk for DA. To address this question, we utilized a high-risk adopted and non-adopted co-sibling control design.

Method

High-risk offspring had one or more biological parents registered for DA, alcohol use disorders or criminal behavior. Using Swedish registries, we identified 1161 high-risk full-sibships and 3085 high-risk half-sibships containing at least one member who was adopted-away and one member who was not. Registration for DA was via national criminal, medical and pharmacy registers. In Sweden, adoptive families are screened to provide high-quality rearing environment for adoptees.

Results

Controlling for parental age at birth and gender (and, in half-siblings, high-risk status of the other parent), risk for DA was substantially lower in the full- and half-siblings who were adopted v. not adopted [hazard ratios and 95% confidence intervals: 0.55 (0.45–0·69) and 0.55 (95% CI 0.48–0.63), respectively]. The protective effect of adoption on risk for DA was significantly stronger in the full- and half-sibling pairs with very high familial liability (two high-risk parents) and significantly weaker when the adoptive family was broken by death or divorce, or contained a high-risk parent.

Conclusions

In both full- and half-sibling pairs, we found replicated evidence that rearing environment strongly impacts on risk for DA. High-quality rearing environments can substantively reduce risk for DA in those at high genetic risk.

Keywords

Adoptioncross-generational transmissiondrug abuserearing
Type
Original Articles
Information
Psychological Medicine , Volume 46 , Issue 7 , May 2016 , pp. 1359 - 1366
Copyright
Copyright © Cambridge University Press 2016 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

APA (1987). Diagnostic and Statistical Manual of Mental Disorders, revised 3rd edn. American Psychiatric Association: Washington, DC.Google Scholar
Andrews, JA, Tildesley, E, Hops, H, Li, F (2002). The influence of peers on young adult substance use. Health Psychology 21, 349–357.CrossRefGoogle ScholarPubMed
Bierut, LJ, Dinwiddie, SH, Begleiter, H, Crowe, RR, Hesselbrock, V, Nurnberger, JI Jr, Porjesz, B, Schuckit, MA, Reich, T (1998). Familial transmission of substance dependence: alcohol, marijuana, cocaine, and habitual smoking: a report from the Collaborative Study on the Genetics of Alcoholism. Archives of General Psychiatry 55, 982–988.Google Scholar
Bjorklund, A, Lindahl, M, Plug, E (2006). The origins of intergenerational associations: lessons from Swedish adoption data. Quarterly Journal of Economics 121, 999–1028.Google Scholar
Bohman, M (1970). Adopted Children and their Families: A Follow-up Study of Adopted Children, their Background, Environment and Adjustment. Seelig: Solna.Google Scholar
Cadoret, RJ, Troughton, E, O'Gorman, TW, Heywood, E (1986). An adoption study of genetic and environmental factors in drug abuse. Archives of General Psychiatry 43, 1131–1136.Google Scholar
Cadoret, RJ, Yates, WR, Troughton, E, Woodworth, G, Stewart, MA (1995). Adoption study demonstrating two genetic pathways to drug abuse. Archives of General Psychiatry 52, 42–52.Google Scholar
Cadoret, RJ, Yates, WR, Troughton, E, Woodworth, G, Stewart, MA (1996). An adoption study of drug abuse/dependency in females. Comprehensive Psychiatry 37, 88–94.Google Scholar
Capron, C, Duyme, M (1989). Assessment of effects of socio-economic status on IQ in a full cross-fostering study. Nature 340, 552–554.Google Scholar
Duyme, M, Dumaret, AC, Tomkiewicz, S (1999). How can we boost IQs of ‘dull children’?: a late adoption study. Proceedings of the National Academy of Sciences USA 96, 8790–8794.Google Scholar
Hawkins, JD, Catalano, RF, Miller, JY (1992). Risk and protective factors for alcohol and other drug problems in adolescence and early adulthood: implications for substance abuse prevention. Psychological Bulletin 112, 64–105.CrossRefGoogle ScholarPubMed
Hawkins, JD, Herrenkohl, T, Farrington, DP, Brewer, D, Catalano, RF, Harachi, TW (1998). A review of predictors of youth violence. In Serious & Violent Juvenile Offenders: Risk Factors and Successful Interventions (ed. Loeber, R. and Farrington, D.P.), pp. 106–146. Sage Publications, Inc.: London.Google Scholar
Hibell, B, Guttormsson, U, Ahlstrom, S, Balakireva, O, Bjarnason, T, Kokkevi, A, Kraus, L (2007). The 2007 ESPAD Report: Substance Use Among Students in 35 European Countries. The Swedish Council for Information on Alcohol and Other Drugs (CAN): Sweden.Google Scholar
Jockin, V, McGue, M, Lykken, DT (1996). Personality and divorce: a genetic analysis. Journal of Personality and Social Psychology 71, 288–299.Google Scholar
Kendler, KS, Karkowski, LM, Neale, MC, Prescott, CA (2000). Illicit psychoactive substance use, heavy use, abuse, and dependence in a US population-based sample of male twins. Archives of General Psychiatry 57, 261–269.Google Scholar
Kendler, KS, Maes, HH, Sundquist, K, Ohlsson, H, Sundquist, J (2013). Genetic and family and community environmental effects on drug abuse in adolescence: a Swedish national twin and sibling study. American Journal of Psychiatry 171, 209–217.Google Scholar
Kendler, KS, Ohlsson, H, Sundquist, K, Sundquist, J (2014). Peer deviance, parental divorce, and genetic risk in the prediction of drug abuse in a nationwide swedish sample: evidence of environment-environment and gene-environment interaction. JAMA Psychiatry 71, 439–445.Google Scholar
Kendler, KS, Ohlsson, H, Sundquist, J, Sundquist, K (2015 a). Triparental families: a new genetic-epidemiological design applied to drug abuse, alcohol use disorders, and criminal behavior in a Swedish national sample. American Journal of Psychiatry 172, 553–560.Google Scholar
Kendler, KS, Ohlsson, H, Sundquist, K, Sundquist, J (2015 b). The Causes of parent-offspring transmission of drug abuse: a Swedish population-based study. Psychological Medicine 45, 87–95.Google Scholar
Kendler, KS, Sundquist, K, Ohlsson, H, Palmer, K, Maes, H, Winkleby, MA, Sundquist, J (2012). Genetic and familial environmental influences on the risk for drug abuse: a national Swedish adoption study. Archives of General Psychiatry 69, 690–697.Google Scholar
Kendler, KS, Turkheimer, E, Ohlsson, H, Sundquist, J, Sundquist, K (2015 c). Family environment and the malleability of cognitive ability: a Swedish national home-reared and adopted-away cosibling control study. Proceedings of the National Academy of Science USA 112, 4612–4617.Google Scholar
Kraus, L, Augustin, R, Frischer, M, Kummler, P, Uhl, A, Wiessing, L (2003). Estimating prevalence of problem drug use at national level in countries of the European Union and Norway. Addiction 98, 471–485.Google Scholar
Kringlen, E, Torgersen, S, Cramer, V (2001). A Norwegian psychiatric epidemiological study. American Journal of Psychiatry 158, 1091–1098.CrossRefGoogle ScholarPubMed
Lynskey, MT, Heath, AC, Nelson, EC, Bucholz, KK, Madden, PA, Slutske, WS, Statham, DJ, Martin, NG (2002). Genetic and environmental contributions to cannabis dependence in a national young adult twin sample. Psychological Medicine 32, 195–207.Google Scholar
McGue, M, Lykken, D (1992). Genetic influence on risk of divorce. Psychological Science 3, 368–373.Google Scholar
Merikangas, KR, Stolar, M, Stevens, DE, Goulet, J, Preisig, MA, Fenton, B, Zhang, H, O'Malley, SS, Rounsaville, BJ (1998). Familial transmission of substance use disorders. Archives of General Psychiatry 55, 973–979.Google Scholar
Petraitis, J, Flay, BR, Miller, TQ, Torpy, EJ, Greiner, B (1998). Illicit substance use among adolescents: a matrix of prospective predictors. Substance Use and Misuse 33, 2561–2604.Google Scholar
SAS Institute I (2011). SAS/STAT User's Guide, Version 9.3. SAS Institute Inc.: Cary, NC.Google Scholar
Schiff, M, Duyme, M, Dumaret, A, Stewart, J, Tomkiewicz, S, Feingold, J (1978). Intellectual status of working-class children adopted early into upper-middle-class families. Science 200, 1503–1504.Google Scholar
Secretary of Health and Human Services (1997). Alcohol and Health: Ninth Special Report to the U.S. Congress from the Secretary of Health and Human Services. Washington: U.S. Department of Health and Human Services, Public Health Service, National Institutes of Health, NIAAA.Google Scholar
Steinberg, L, Fletcher, A, Darling, N (1994). Parental monitoring and peer influences on adolescent substance use. Pediatrics 93, 1060–1064.Google Scholar
Tsuang, MT, Lyons, MJ, Eisen, SA, Goldberg, J, True, W, Lin, N, Meyer, JM, Toomey, R, Faraone, SV, Eaves, L (1996). Genetic influences on DSM-III-R drug abuse and dependence: a study of 3372 twin pairs. American Journal of Medical Genetics 67, 473–477.Google Scholar
van den Bree, MB, Pickworth, WB (2005). Risk factors predicting changes in marijuana involvement in teenagers. Archives of General Psychiatry 62, 311–319.CrossRefGoogle ScholarPubMed
van Ijzendoorn, MH, Juffer, F, Poelhuis, CW (2005). Adoption and cognitive development: a meta-analytic comparison of adopted and nonadopted children's IQ and school performance. Psychological Bulletin 131, 301–316.Google Scholar
WHO (2010). Atlas on Substance use (2010) Resources for the Prevention and Treatment of Substance use Disorders [NLM classification: WM 270]. WHO Library Cataloguing-in-Publication Data, WHO Press: France.Google Scholar
Wickrama, KA, Conger, RD, Lorenz, FO, Martin, M (2012). Continuity and discontinuity of depressed mood from late adolescence to young adulthood: the mediating and stabilizing roles of young adults’ socioeconomic attainment. Journal of Adolescence 35, 648–658.CrossRefGoogle ScholarPubMed