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Childhood Predictors and Mid-Adolescent Correlates of Developmental Trajectories of Alcohol Use among Male and Female Youth

  • Empirical Research
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Abstract

The identification of salient risk factors for alcohol consumption among male and female adolescents is an important topic not only for etiology research but also for designing effective gender-specific alcohol prevention programs for young people. This study examined the extent to which problematic alcohol use trajectories from ages 14 to 18 among male and female youth were related to childhood predictors assessed at age 9 (i.e., impulsivity, academic self-confidence, social problems with peers), socio-demographic variables, and mid-adolescent correlates [i.e., parental use, body mass index (BMI), risky peer context, conduct problems at school, parent–child relationship, somatic complaints]. Data analysis was based on a representative German longitudinal study (1986–1995, n = 1,619, 55 % female). Using growth mixture modeling methodology, associations of childhood predictors and mid-adolescent correlates to distinctive trajectories of alcohol use were examined for males and females separately. For males, a problematic consumption trajectory was associated with poor relationships to parents in adolescence and small community size. For females, low impulsivity during childhood, high BMI, and contact with deviant peers during adolescence predicted problematic as compared to normative alcohol use trajectories. Additionally, high parental alcohol use, low parental educational background, and conduct problems at school during adolescence were common predictors of a problematic alcohol use trajectory in both genders. The results provide insights regarding differences in the gender-typical development of adolescent alcohol use as well as stress the need of gender-specific intervention components along with universal prevention strategies against problematic consumption trajectories.

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Notes

  1. Participant loss primarily occurred for two reasons (both a consequence of German unification). First, families moved away from the city of Leipzig from 1990 onward, usually to West Germany (see also Sahner 1996; Statistisches Landesamt des Freistaates Sachsen 2002). Second, the East German school system was restructured in 1990–1991 (Kuhnke 1997).

  2. As of July 1991, the equivalent amounts in USD currency were: the median per capita household income was $344.92 per month (ranging from $57.40 to $1069.54).

  3. According to Pulkkinen (1996), impulsivity is characterized by acting without appropriate reflection, distorted information processing, or inability to maintain attention. In the present study, both cognitive (i.e., cognitive test results) and behavioral (i.e., parent and teacher reports) aspects of impulsivity were assessed (White et al. 1994). All indicators sought to capture features of temperament that are related to problematic use of alcohol among adolescents (see Tarter 2002). Our measure of impulsivity was validated by concurrent parent reports which revealed meaningful associations between high impulsivity on the one hand and perinatal complications and problematic, harsh parenting practices on the other hand (see Weichold 2002, for more information).

  4. As shown in several studies (e.g., Lane et al. 2013; Stoolmiller et al. 2005), predictors may be related to trajectory class membership and/or developmental course over time within a given trajectory group. Both components of prediction have important implications for prevention and intervention efforts. Because the main focus of the current study was on the prediction of trajectory class membership, we applied the described stepwise testing strategy in order to empirically identify the most salient predictors of within-class developmental course and thus minimize model complexity.

  5. We also predicted trajectory group membership using groups with “normative” consumption trajectories (i.e., “late escalators” for males and “increases” for females) as baseline groups. Result tables for these analyses can be obtained from the first author upon request. Briefly summarizing, the key findings for these prediction models were as follows: for males, just one variable was significantly linked to membership in the early peaker group. Older males were more likely to belong to the early peaker group than to the baseline group of late escalators (p < .05). Three variables were significant predictors of membership in the regular user group. Males from larger communities (p < .05) and with highly educated parents (p < .05) were less likely to belong to the regular user group, and males with higher levels of parents’ alcohol use were more likely to belong to the regular user group (p < .01) relative to the baseline group of late escalators. Finally, two variables were significantly associated with membership in the rare user group. Older males were more likely to be in the rare user group (p < .05), and males with more highly educated parents were less likely to belong to the rare user group (p < .05) compared to the baseline group of late escalators. For females, two variables significantly predicted membership in the rare user group. Females with higher impulsivity (p < .05) and from larger communities (p < .05) were more likely to be in the rare user group than in the baseline group of increasers. Two variables were significantly linked to membership in the decreaser group. Females with higher body mass index (p < .05) and with a more risky peer context (p < .01) were more likely to belong to the decreasers compared to the baseline group of increasers. Finally, five variables were significant predictors of regular user group membership. Females with higher levels of impulsivity (p < .05) and higher paternal education (p < .05) were less likely to belong to the regular users than to the baseline group of increasers. Females with higher levels of parents’ alcohol use (p < .01), higher body mass index (p < .01), and a more risky peer context (p < .01) were more likely to be in the regular user group compared to the baseline group of increasers.

References

  • Baier, D., Pfeiffer, C., Simonson, J., & Rabold, S. (2009). Jugendliche in Deutschland als Opfer und Täter von Gewalt—Erster Forschungsbericht zum gemeinsamen Forschungsprojekt des Bundesinnenministeriums des Inneren und des KFN. [Adolescents in Germany as bullies and victims—First research report of the cooperation project of the Ministry of Inner Affairs and the KFN]. KFN: Research report No. 107 (unpublished research report).

  • Belsky, J., Steinberg, L., & Draper, P. (1991). Childhood experience, interpersonal development, and reproductive strategy: An evolutionary theory of socialization. Child Development, 62(4), 647–670.

    Article  PubMed  Google Scholar 

  • Biehl, M. C., Natsuaki, M. N., & Ge, X. (2007). The influence of pubertal timing on alcohol use and heavy drinking trajectories. Journal of Youth and Adolescence, 36(2), 153–167.

    Article  Google Scholar 

  • Bien, W., Bischoff, P., & Mattstedt, S. (1995). DFG-Projekt Politikorientierungen im Wandel. Teilbericht 1: Gesamtübersicht der im Projekt berücksichtigten Quer- und Längsschnittstudien des ehemaligen Zentralinstituts für Jugendforschung Leipzig aus den Jahren 1968 bis 1990 [DFG-project political orientations during times of change. Volume 1: Overview of cross-sectional and longitudinal studies at the Central Institute for Youth Research in Leipzig from 1968 to 1990 included in the project] (DJI-Arbeitspapier 3-116). DJI: Regionale Aussenstelle Leipzig.

  • Blake, S. M., Amaro, H., Schwartz, P. M., & Flinchbaugh, L. J. (2001). A review of substance abuse prevention intervention for young adolescent females. Journal of Early Adolescence, 1, 294–324.

    Article  Google Scholar 

  • Bühringer, G., et al. (2000). Alkoholkonsum und alkoholbezogene Störungen in Deutschland [Alcohol consumption and alcohol-related disorders in Germany] (Schriftenreihe des Bundesministeriums fuer Gesundheit, Vol. 128). Baden–Baden: Nomos.

  • Caspi, A., Moffitt, T. E., Newman, D. L., & Silva, P. A. (1996). Behavioural observations at age 3 predict adult psychiatric disorders: Longitudinal evidence from a birth cohort. Archives of General Psychiatry, 53, 1033–1039.

    Article  PubMed  Google Scholar 

  • Casswell, S., Pledger, M., & Pratap, S. (2002). Trajectories of drinking from 18 to 26 years: Identification and prediction. Addiction, 97, 1427–1437.

    Article  PubMed  Google Scholar 

  • Chaplin, T. M., Gillham, J. E., & Seligman, M. E. P. (2009). Gender, anxiety, and depressive symptoms: A longitudinal study of early adolescents. Journal of Early Adolescence, 29, 307–327.

    Article  PubMed Central  PubMed  Google Scholar 

  • Chassin, L., Flora, D. B., & King, K. M. (2004). Trajectories of alcohol and drug use and dependence from adolescence to adulthood: The effects of familial alcoholism and personality. Journal of Abnormal Psychology, 113, 483–498.

    Article  PubMed  Google Scholar 

  • Chassin, L., Pitts, S. C., & Prost, J. (2002). Binge drinking trajectories from adolescence to emerging adulthood in a high-risk sample: Predictors and substance abuse outcomes. Journal of Consulting and Clinical Psychology, 70, 67–78.

    Article  PubMed  Google Scholar 

  • Chuang, Y.-C., Ennett, S. T., Bauman, K. E., & Foshee, V. A. (2005). Neighborhood influences on adolescent cigarette and alcohol use: Mediating effects through parent and peer behaviors. Journal of Health and Social Behavior, 46(2), 187–204.

    Article  PubMed  Google Scholar 

  • Colder, C. R., Campbell, R. T., Ruel, E., Richardson, J. L., & Flay, B. R. (2002). A finite mixture model of growth trajectories of adolescent alcohol use: Predictors and consequences. Journal of Consulting and Clinical Psychology, 70, 976–985.

    Article  PubMed  Google Scholar 

  • Crockett, L. J., & Silbereisen, R. K. (Eds.). (2000). Negotiating adolescence in times of social change. Cambridge: University Press.

    Google Scholar 

  • Danielsson, A.-K., Romelsjö, A., & Tengström, A. (2011). Heavy episodic drinking in early adolescence: Gender-specific risk and protective factors. Substance Use and Misuse, 46(5), 633–643.

    Article  PubMed  Google Scholar 

  • Del Boca, F. K., & Darkes, J. (2003). The validity of self-reports of alcohol consumption: State of the science and challenges for research. Addiction, 98, 1–12.

    Article  PubMed  Google Scholar 

  • Duan, L., Chou, C.-P., Adreeva, V. A., & Pentz, M. A. (2009). Trajectories of peer social influences as long-term predictors of drug use from early through late adolescence. Journal of Youth and Adolescence, 38(3), 454–465.

    Article  PubMed  Google Scholar 

  • Flory, K., Lynam, D., Milich, R., Leukefeld, C., & Clayton, R. (2004). Early adolescent through young adult alcohol and marijuana use trajectories: Early predictors, young adult outcomes, and predictive utility. Development and Psychopathology, 16, 193–213.

    Article  PubMed  Google Scholar 

  • Friedrich, W. (1997). Zur inhaltlichen und methodischen Forschung am Zentralinstitut für Jugendforschung Leipzig [Contents and methods of research at the Central Institute for Youth Research in Leipzig]. In E. Brislinger, B. Hausstein, & E. Riedel (Eds.), Jugend im Osten: Sozialwissenschaftliche Daten und Kontextwissen aus der DDR sowie den neuen Bundesländern (1969 bis 1995) (pp. 85–101). Berlin: Trafo Verlag.

    Google Scholar 

  • Friedrich, W., Förster, P., & Starke, K. (Eds.). (1999). Das Zentralinstitut für Jugendforschung Leipzig 1966-1990 [The Central Institute for Youth Research in Leipzig 1966-1990]. Berlin: Edition Ost.

    Google Scholar 

  • Gmel, G., & Rehm, J. (2004). Measuring alcohol consumption. Contemporary Drug Problems, 31(3), 467–540.

    Google Scholar 

  • Graber, J. A., Brooks-Gunn, J., Paikoff, R. L., & Warren, M. P. (1994). Prediction of eating problems: An 8-year study of adolescent females. Developmental Psychology, 30(3), 823–834.

    Article  Google Scholar 

  • Graham, J. W., & Hofer, S. M. (2000). Multiple imputation in multivariate research. In T. D. Little, K. U. Schnabel, & J. Baumert (Eds.), Modeling longitudinal and multilevel data (pp. 201–218). Mahwah, NJ: Lawrence Erlbaum Associates.

    Google Scholar 

  • Graham, J. W., Olchowski, A. E., & Gilreath, T. D. (2007). How many imputations are really needed? Some practical clarifications of multiple imputation theory. Prevention Science, 8, 206–213.

    Article  PubMed  Google Scholar 

  • International Center for Alcohol Policies. (1998). What is a standard drink? ICAP Reports, 5, 1–6.

    Google Scholar 

  • Jackson, K. M., & Sher, K. J. (2005). Similarities and differences of longitudinal phenotypes across alternate indices of alcohol involvement: A methodologic comparison of trajectory approaches. Psychology of Addictive Behaviors, 19, 339–351.

    Article  PubMed Central  PubMed  Google Scholar 

  • Jackson, K. M., & Sher, K. J. (2006). Comparison of longitudinal phenotypes based on number and timing of assessments: A systematic comparison of trajectory approaches II. Psychology of Addictive Behaviors, 20, 373–384.

    Article  PubMed Central  PubMed  Google Scholar 

  • Jackson, K. M., & Sher, K. J. (2008). Comparison of longitudinal phenotypes based on alternate heavy drinking cut scores: A systematic comparison of trajectory approaches III. Psychology of Addictive Behaviors, 22, 198–209.

    Article  PubMed Central  PubMed  Google Scholar 

  • Jessor, R., Turbin, M. S., & Costa, F. M. (1998). Risk and protection in successful outcomes among disadvantaged adolescents. Applied Developmental Science, 2, 194–208.

    Article  Google Scholar 

  • Kuhnke, R. (1997). Anlage und Weiterführung der dritten Leipziger Längsschnittstudie [Design and continuation of the third Leipzig longitudinal study]. In E. Brislinger, B. Hausstein, & E. Riedel (Eds.), Jugend im Osten: Sozialwissenschaftliche Daten und Kontextwissen aus der DDR sowie den neuen Bundesländern (1969 bis 1995) (pp. 125–132). Berlin: Trafo Verlag.

    Google Scholar 

  • Kuntsche, E., Knibbe, R., Gmel, G., & Engels, R. (2006). Who drinks why? A review of socio-demographic, personality, and contextual issues behind the drinking motives in young people. Addictive Behaviors, 31, 1844–1857.

    Article  PubMed  Google Scholar 

  • Kurth, E. (1984). Testreihe zur Prüfung der Konzentrationsfähigkeit TPK [Test to assess concentration abilities TPK]. Berlin: Psychodiagnostisches Zentrum. Sektion Psychologie der Humboldt Universität.

    Google Scholar 

  • Lane, S. P., Bluestone, C., & Burke, C. T. (2013). Trajectories of BMI from early childhood through early adolescence: SES and psychosocial predictors. British Journal of Health Psychology, 18(1), 66–82.

    Article  PubMed  Google Scholar 

  • Lerner, R. M. (2000). Developing civil society through the promotion of positive youth development. Journal of Developmental and Behavioral Pediatrics, 21(1), 48–49.

    Article  PubMed  Google Scholar 

  • Li, L., & Hser, Y.-I. (2011). On inclusion of covariates for class enumeration of growth mixture models. Multivariate Behavioral Research, 46, 266–302.

    Article  PubMed Central  PubMed  Google Scholar 

  • Lintonen, T., Ahlström, S., & Metso, L. (2004). The reliability of self-reported drinking in adolescence. Alcohol and Alcoholism, 39, 362–368.

    Article  PubMed  Google Scholar 

  • Little, R. J. A., & Rubin, D. B. (1987). Statistical analysis with missing data. New York: Wiley.

    Google Scholar 

  • Martin, C. S., Lynch, K. G., Pollock, N. K., & Clark, D. B. (2000). Gender differences and similarities in the personality correlates of adolescent alcohol problems. Psychology of Addictive Behaviors, 14, 121–133.

    Article  PubMed  Google Scholar 

  • Masten, A. S., Faden, V. B., Zucker, R. A., & Spear, L. P. (2008). Underage drinking: A developmental framework. Pediatrics, 121, 235–251.

    Article  Google Scholar 

  • Miller, J. B. (1986). Toward a new psychology for women. Boston, MA: Bacon.

    Google Scholar 

  • Moffitt, T. E. (1993). Adolescence-limited and life-course-persistent antisocial behavior: A developmental taxonomy. Psychological Review, 100(4), 674–701.

    Article  PubMed  Google Scholar 

  • Muthén, L. K., & Muthén, B. O. (1998–2004). Mplus user’s guide. Los Angeles, CA: Muthén & Muthén.

  • Muthén, B., & Muthén, L. (2000). Integrating person-centered and variable-centered analyses: Growth mixture modeling with latent trajectory classes. Alcoholism, Clinical and Experimental Research, 24, 882–891.

    Article  PubMed  Google Scholar 

  • Muthén, B., & Shedden, K. (1999). Finite mixture modeling with mixture outcomes using the EM algorithm. Biometrics, 55, 463–469.

    Article  PubMed  Google Scholar 

  • Nagin, D. S., & Tremblay, R. E. (1999). Trajectories of male’s physical aggression, opposition, and hyperactivity on the path to physically violent and nonviolent juvenile delinquency. Child Development, 70, 1181–1196.

    Article  PubMed  Google Scholar 

  • Noack, P., Hofer, M., Kracke, B., & Klein-Allermann, E. (1995). Adolescents and their parents facing social change in East and West Germany after unification. In P. Noack, M. Hofer, & J. Youniss (Eds.), Psychological responses to social change. Human development in changing environments (pp. 120–148). New York: Walter de Gruyter.

    Google Scholar 

  • Nolen-Hoeksema, S., & Hilt, L. (2006). Possible contributors to the gender differences in alcohol use and problems. The Journal of General Psychology, 133, 357–374.

    Article  PubMed  Google Scholar 

  • Nylund, K. L., Asparouhov, T., & Muthén, B. O. (2007). Deciding on the number of classes in latent class analysis and growth mixture modeling: A Monte Carlo simulation study. Structural Equation Modeling, 14, 535–569.

    Article  Google Scholar 

  • Oswald, W. D., & Roth, E. (1978). Der Zahlenverbindungstest ZVT. Ein sprachfreier Intelligenz-Schnell-Test [The number-connecting-test ZVT. A language-free short intelligence test]. Göttingen: Hogrefe.

  • Pasch, K. E., Velazquez, C. E., Cance, J. D., Moe, S. G., & Lytle, L. A. (2012). Youth substance use and body composition: Does risk in one area predict the other? Journal of Youth and Adolescence, 41(1), 14–26.

    Article  PubMed Central  PubMed  Google Scholar 

  • Petraitis, J., Flay, B. R., & Miller, T. Q. (1995). Reviewing theories of adolescent substance use: Organizing pieces in the puzzle. Psychological Bulletin, 117(1), 67–86.

    Article  PubMed  Google Scholar 

  • Peugh, J., & Fan, X. (2012). How well does growth mixture modeling identify heterogeneous growth trajectories? A simulation study examining GMM’s performance characteristics. Structural Equation Modeling, 19, 204–226.

    Article  Google Scholar 

  • Poulin, C., Hand, D., Boudreau, B., & Santor, D. (2005). Gender differences in the association between substance use and elevated depressive symptoms in a general adolescent population. Addiction, 100, 525–535.

    Article  PubMed  Google Scholar 

  • Pulkkinen, L. (1996). Impulse control in children. Journal of Forensic Psychiatry, 7(2), 228–233.

    Article  Google Scholar 

  • Sahner, H. (1996). Städte im Umbruch. In H. Bertram, H. M. Nickel, O. Niedermayer, & G. Trommsdorff (Eds.), Berichte der Kommission für die Erforschung des sozialen und politischen Wandels in den neuen Bundesländern e.V. (Bd. 5: Städte und Regionen – Räumliche Folgen des Transformationsprozesses) [Reports of the commission for the examination of social and political change in the former Eastern states, Volume 5: Cities and Regions – Spatial consequences of the transformation process] (pp. 447–480). Opladen: Leske & Budrich.

  • Schafer, J. L. (1997). Analysis of multivariate data. London: Chapman & Hall.

    Google Scholar 

  • Schafer, J. L. (1999). NORM. Software for Windows 95/98/NT. Available from http://www.stat.psu.edu/~jls/misoftwa.html.

  • Schafer, J. L., & Olsen, M. K. (1998). Multiple imputation for multivariate missing-data problems: A data analyst’s perspective. Multivariate Behavioral Research, 33, 545–571.

    Article  Google Scholar 

  • Schulenberg, J. E., O′Malley, P. M., Bachman, J. G., Wadsworth, K. N., & Johnston, L. D. (1996). Getting drunk and growing up: Trajectories of frequent binge drinking during the transition to young adulthood. Journal of Studies on Alcohol, 57, 289–304.

    PubMed  Google Scholar 

  • Schulte, M. T., Ramo, D., & Brown, S. A. (2009). Gender differences in factors influencing alcohol use and drinking progression among adolescents. Clinical Psychology Review, 29, 535–547.

    Article  PubMed Central  PubMed  Google Scholar 

  • Sher, K. J., Jackson, K. M., & Steinley, D. (2011). Alcohol use trajectories and the ubiquitous cat’s cradle: Cause for concern? Journal of Abnormal Psychology. doi:10.1037/a0021813.

  • Silverthorn, P., & Frick, P. J. (1999). Developmental pathways to antisocial behavior: The delayed-onset pathway in females. Development and Psychopathology, 11, 101–126.

    Article  PubMed  Google Scholar 

  • Simon, R., Tauscher, M., & Pfeiffer, T. (1999). Suchtbericht Deutschland 1999 [Report on addictions in Germany 1999]. Hohengehren: Schneider Verlag.

    Google Scholar 

  • Spoth, R., Trudeau, L. S., Guyll, M., & Shin, C. (2012). Benefits of universal intervention efforts on a youth protective shield 10 years after baseline. Journal of Adolescent Health, 50(4), 414–417.

    Article  PubMed Central  PubMed  Google Scholar 

  • Statistisches Landesamt des Freistaates Sachsen. (2002). 10 Jahre Statistisches Landesamt: 1992 bis 2001 [10 years of the Statistical Office: 1992 to 2001]. Kamenz: Statistisches Landesamt des Freistaates Sachsen.

    Google Scholar 

  • Stoolmiller, M., Kim, H. K., & Capaldi, D. M. (2005). The course of depressive symptoms in men from early adolescence to young adulthood: Identifying latent trajectories and early predictors. Journal of Abnormal Psychology, 114(3), 331–345.

    Article  PubMed Central  PubMed  Google Scholar 

  • Tarter, R. E. (2002). Etiology of adolescent substance abuse: A developmental perspective. American Journal on Addictions, 11, 171–191.

    Article  PubMed  Google Scholar 

  • Tarter, R. E., Kirisci, L., & Mezzich, A. (1997). Multivariate typology of adolescents with alcohol use disorder. American Journal on Addictions, 6(2), 150–158.

    Article  PubMed  Google Scholar 

  • Tarter, R. E., Kirisci, L., Mezzich, A., & Patton, D. (2011). Multivariate comparison of male and female adolescent substance abusers with accompanying legal problems. Journal of Criminal Justice, 39(3), 207–211.

    Article  PubMed Central  PubMed  Google Scholar 

  • Tarter, R., et al. (1999). Etiology of early age onset substance use disorder: A maturational perspective. Development and Psychopathology, 11, 657–683.

    Article  PubMed  Google Scholar 

  • Tofighi, D., & Enders, C. K. (2008). Identifying the correct number of classes in growth mixture models. In G. R. Hancock & K. M. Samuelsen (Eds.), Advances in latent variable mixture models (pp. 317–341). Charlotte, NC: Information Age Publishing.

    Google Scholar 

  • Tremblay, L., & Frigon, J. Y. (2005). The interaction role of obesity and pubertal timing on the psychosocial adjustment of adolescent females. International Journal of Obesity, 29(1), 1204–1211.

    Article  PubMed  Google Scholar 

  • Walden, B., Iacono, W. G., & McGue, M. (2007). Trajectories of change in adolescent substance use and symptomatology: Impact of paternal and maternal substance use disorders. Psychology of Addictive Behaviors, 21(1), 35–43.

    Article  PubMed  Google Scholar 

  • Weichold, K. (2002). Entwicklungspfade zu jugendlichem Alkoholkonsum in Zeiten sozialen Wandels in Ostdeutschland [Developmental pathways of adolescent alcohol consumption in times of social change]. University of Jena: Unpublished Dissertation Thesis.

  • Weichold, K., Brambosch, A., & Silbereisen, R. K. (2012). Do females profit more? Gender-specific effectiveness of a Life Skills Program against substance misuse in early adolescence. Journal of Early Adolescence, 32(2), 200–225.

    Article  Google Scholar 

  • Wenzel, V., Weichold, K., & Silbereisen, R. K. (2009). The Life Skills Program IPSY: Positive influences on school bonding and prevention of substance misuse. Journal of Adolescence, 32, 1391–1401.

    Article  PubMed  Google Scholar 

  • White, H. R., Johnson, V., & Buyske, S. (2000). Parental modelling and parenting behaviour effects on offspring alcohol and cigarette use: A growth curve analysis. Journal of Substance Abuse, 12, 287–310.

    Article  PubMed  Google Scholar 

  • White, J. L., Moffitt, T. E., Caspi, A., Bartusch, D. J., Needles, D. J., & Stouthamer-Loeber, M. (1994). Measuring impulsivity and examining its relationship to delinquency. Journal of Abnormal Psychology, 103(2), 192–205.

    Article  PubMed  Google Scholar 

  • Wichstrom, L. (2001). The impact of pubertal timing on adolescents’ alcohol use. Journal of Research on Adolescence, 11(2), 131–150.

    Article  Google Scholar 

  • Wiesner, M., Weichold, K., & Silbereisen, R. K. (2007). Trajectories of alcohol use among adolescent males and females: Identification, validation, and sociodemographic characteristics. Psychology of Addictive Behaviors, 21, 62–75.

    Article  PubMed  Google Scholar 

  • Windle, M., Mun, E.-Y., & Windle, R. C. (2005). Adolescent-to-young adulthood heavy drinking trajectories and their prospective predictors. Journal of Studies on Alcohol Use, 66, 313–322.

    Google Scholar 

  • Winters, K. C., Stinchfield, R. D., Henly, G. A., & Schwartz, R. H. (1991). Validity of adolescent self-report of alcohol use and other drug involvement. International Journal of Addictions, 25, 1379–1395.

    Google Scholar 

  • Zucker, R. A. (1994). Pathways to alcohol problems and alcoholism: A developmental account of the evidence for multiple alcoholisms and for contextual contributions to risk. In R. A. Zucker, G. M. Maled, & J. Howard (Eds.), The development of alcohol problems: Exploring the biopsychosocial matrix of risk (NIAAA Research Monograph 26, pp. 255–289). Rockville, MD: Department of Health and Human Services.

  • Zucker, R. A., Donovan, J. E., Masten, A. S., Mattson, M. E., & Moss, H. B. (2008). Early developmental processes and the continuity of risk for underage drinking and problem drinking. Pediatrics, 121, 252–272.

    Article  Google Scholar 

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Acknowledgments

This research was supported by German National Science Foundation Grant No. Si 296/32-1 awarded to Rainer K. Silbereisen and Karina Weichold.

Author Contributions

KW conceived the study, participated in its design, contributed to data analysis and interpretation of findings, and drafted the manuscript. MFW participated in conceiving the study and its design, conducted most of the statistical analyses, contributed to interpretation of findings, and helped in drafting the manuscript. RKS participated in conceiving the study, in its design, and interpretation of findings. All authors read and approved the final manuscript.

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  1. Center for Applied Developmental Science, Friedrich Schiller University of Jena, Semmelweisstr. 12, 07743, Jena, Germany

    Karina Weichold & Rainer K. Silbereisen

  2. Department of Educational Psychology, University of Houston, 491 Farish Hall, Houston, TX, 77204-5029, USA

    Margit F. Wiesner

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  1. Karina Weichold
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Correspondence to Karina Weichold.

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Weichold, K., Wiesner, M.F. & Silbereisen, R.K. Childhood Predictors and Mid-Adolescent Correlates of Developmental Trajectories of Alcohol Use among Male and Female Youth. J Youth Adolescence 43, 698–716 (2014). https://doi.org/10.1007/s10964-013-0014-6

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