Purpose: To examine the developmental relationship between adolescent substance use and risky sexual behavior in young adulthood. Methods: A gender-balanced, ethnically diverse urban sample of 808 children in Seattle was surveyed at age 10 years in 1985 and followed prospectively to age 21 years in 1996. Semiparametric group-based modeling was used to determine trajectory groups of binge-drinking, cigarette smoking, marijuana use, and the use of other illicit drugs. Negative binomial regressions and logistic regressions were used to examine whether these trajectory groups predicted the number of sex partners and condom use at age 21 years. Results: Specific forms of adolescent substance use significantly predicted risky sexual behavior at age 21 years, after other substance use and early measures of sexual behavior were controlled. Early binge-drinkers had significantly more sex partners than nonbinge-drinkers. Late onset binge-drinkers and marijuana users had significantly more sex partners and were less likely to use condoms consistently than those who did not binge drink or use marijuana. Experimenters in cigarette smoking, who did not escalate smoking, were more likely to use condoms consistently than nonsmokers. In contrast, the use of other illicit drugs in adolescence did not predict risky sexual behavior at age 21 years. Conclusions: The effects of adolescent substance use on risky sexual behavior at age 21 years differed for youths with developmentally different substance use trajectories in this urban sample disproportionately drawn from high crime neighborhoods. To prevent risky sexual behavior among young adults, attention should be paid to binge-drinking and marijuana use during adolescence.
Bibliographical noteFunding Information:
This research was supported by research grants #1R03DA13382-01 and #R01DA09679 from the National Institute on Drug Abuse, and a grant from the Robert Wood Johnson Foundation. Points of view are those of the authors and not the official positions of the funding agencies.
- Drug usage
- Psychosexual behavior
- Semiparametric group-based modeling