The first 2 goals of these analyses were to clarify in a fine-grained manner the developmental pattern of genetic and environmental influences on PSU and to determine whether these patterns differed across substance classes.
For nicotine, alcohol, and cannabis, our univariate analyses produced a qualitatively similar pattern. From the point in early adolescence at which we had statistically meaningful results, familial environmental influences on PSU were quite strong. As individuals aged, however, these effects generally declined in importance; they had disappeared by age 35 years for nicotine and cannabis and by age 40 years for alcohol. The reverse picture was seen for genetic factors. Genes were without influence on PSU in early adolescence but gradually grew in importance as individuals aged. Of interest, the magnitude and duration of the familial environmental influences differed across substances, being least prominent for alcohol, intermediate for nicotine, and most marked for cannabis.
These results for nicotine, alcohol, and cannabis can be usefully viewed from an alternative perspective. The influence of familial factors (a2 or c2) on these forms of PSU was relatively constant over age. However, over development, familial environmental influences on PSU were replaced by genetic influences.
The unique feature of the developmental pattern for caffeine was the very short interval in late childhood (ages 9-12 years) with strong familial environmental influences. This largely disappeared by age 13 years, and from then on, no systematic changes in genetic and environmental influences on caffeine use were seen.
These results are broadly comparable to those of prior studies7-12
that have examined the development of PSU or associated externalizing behaviors in genetically informative populations. For example, in twins from the Australian Twin Registry at ages 13 to 18 years, familial environmental and genetic factors were responsible for approximately 45% and 25%, respectively, of individual differences in smoking.8
When followed up over 2 subsequent waves, the role of familial environment declined and that of genetic factors increased.8
Familial environmental effects on PSU in our study persist long after most twins have left home and do not disappear until the early 30s for nicotine, cannabis, and perhaps alcohol. Familial environmental influences on PSU are therefore not solely attributable to the immediate effect of parental, community, school, or peer influences or to differing degrees of drug availability shared by adolescent twins. Rather, familial environmental effects on PSU are at least partially mediated by more enduring processes. One such mechanism might be attitudes toward substance use, including those related to religious beliefs,19
that are acquired in the home or community. Our results suggest that such attitudes have their most potent and enduring effects on cannabis, intermediate effects on alcohol and nicotine, and the least effects on caffeine.
What is responsible for the increasing genetic influences on PSU with age? Although our data provide no direct answer to this question, we would suggest for further consideration a biological hypothesis and a socially mediated hypothesis. The biological hypothesis posits that genes influencing PSU are expressed once exposed to sufficient quantities of drug over an adequate period. This hypothesis is consistent with the substantial body of research showing unique genetic effects on the transition from drug use to drug dependence—that is, genetic factors whose phenotypic effect only becomes manifest after initial exposure.20,21
The socially mediated hypothesis is based on increasing evidence that as we develop from childhood through adolescence to adulthood, our genes play an increasing role in shaping our own social environment.22
This hypothesis suggests that genes affect PSU indirectly by influencing the selection of environments that actively either discourage or encourage drug use. We would speculate that each of these mechanisms explains part of the expanding developmental role of genes in PSU.
The third goal of this study was to explore how genetic and environmental factors contribute to the correlations in use of different psychoactive substances. Our results suggested dynamic developmental changes in the sources of correlations in drug use that mirror those seen for individual substances. For the drug pairs we explored in detail (alcohol-cannabis, nicotine-cannabis, nicotine-alcohol, and nicotine-caffeine), a broadly similar picture emerged. In adolescence, the correlations in different forms of substance use are driven largely by shared environmental factors. However, as individuals age, the genetic contribution to the correlations in drug use becomes progressively stronger, whereas the effect of familial environmental factors becomes gradually weaker. These results are consistent with prior studies showing that in adolescence, both shared genetic and environmental factors contribute to the observed correlation for use of the common psychoactive substances,7,23
whereas in adulthood, shared environmental factors play little apparent role.24
These results suggest a substantial degree of nonspecificity in the shared environmental risk factors for PSU. Whether it be the immediate effects of parental substance use, substance availability, or learned attitudes about drug use that constitute the familial environmental influences on PSU, our results show that these influences often affect use of multiple psychoactive substances rather than just 1 substance alone. These analyses also illustrate that sources of covariation in PSU can be as developmentally dynamic as sources of variation.
These results should be interpreted in the context of 7 potential methodological limitations. First, this sample is restricted to white male twins born in Virginia. Although the patterns of PSU in our twin cohort are quite similar to those reported from comparable nationally representative samples of white individuals in the United States,25
these findings may not be generalizable to females or to other ethnic groups. We examined whether this sample was representative of the larger study from which it was derived by predicting cooperation from information collected in the previous wave of the last year's caffeine, nicotine, and alcohol use and lifetime maximal cannabis use. Controlling for age, education, and the twin structure of the data, completing this interview was significantly but very modestly predicted by higher levels of daily caffeine use (odds ratio=1.03; z
=.03), but it was not statistically associated with alcohol, nicotine, or cannabis use. Participation in this study appears to be largely unrelated to prior PSU.
Second, given the low rates of PSU at some ages and especially with cannabis, our results were somewhat statistically noisy. Presenting the results in , , and with standard errors helps to avoid overinterpretation of small “bumps” and “dips” in the curves that are unlikely to be reliable. While we could have smoothed our curves by lumping individual years into larger units, this might have obscured important developmental processes, especially those occurring in early adolescence.
Third, these models assume that excess similarity for PSU in MZ vs DZ twins did not result from greater similarity in MZ twins in their exposure to relevant environmental factors—particularly their peer group. We examined this assumption previously in this sample and found it to be supported.4,26
We asked the twins, only for the ages of 12 to 14 years, 15 to 17 years, 18 to 21 years, and 22 to 25 years, “how often did you and your twin have the same friends?” At each age, MZ pairs shared more of their peer group than did DZ pairs (). As they grew older, sharing of friends declined in both twin groups, with the difference between MZ and DZ pairs first increasing slightly and then declining as most of the twins left home. The also includes as an example the average correlation in nicotine use in these age groups in MZ and DZ pairs. Two trends are noteworthy, both of which are inconsistent with the hypothesis that our results arise from more similar social environments for MZ twins than DZ twins. In MZ pairs, similarity for smoking rises dramatically during this period while peer sharing declines. Furthermore, from the ages of 15 to 25 years, the difference in the degree of friend sharing in MZ vs DZ twins decreases while the difference in the degree of their similarity for smoking increases. Because rising heritabilities are seen for nicotine, alcohol, and cannabis use from ages 15 to 25 years (as well as stable or increasing MZ correlations for all substances except cannabis), it is unlikely that our results are substantially biased by differential peer group similarities in MZ vs DZ twins.
Similarity of the Peer Group and of Nicotine Use in Monozygotic and Dizygotic Twins Over Development
Fourth, because our information on PSU was collected retrospectively from adults, our findings could result from retrospective recall bias that systematically differed in MZ and DZ twins. However, it is difficult to imagine a pattern of biased recall that would artifactually produce the observed results. We tested the reliability of our assessments in 3 ways, all of which except for caffeine use demonstrated excellent reliability. (The lower reliability for caffeine use may explain the reduced MZ twin correlations observed for this form of PSU because unreliability attenuates such correlations and reduces estimates of genetic and shared environmental effects.) Furthermore, we used a life history calendar in our assessment of substance use. This method, which reflects the structure of autobiographical memory and promotes sequential retrieval within memory networks, has been shown to substantially improve the completeness and accuracy of retrospective reports.14,27-29
Fifth, our measures of PSU were not ideal. In assessing nicotine use, we did not include pipes, cigars, or smokeless tobacco. For caffeine, we did not account for differences in caffeine content between different caffeinated beverages.
Sixth, because our sample was born over a 34-year period, the pattern of our results could differ meaningfully across age cohorts (although we previously found no cohort differences in the genetic and environmental influences on PSU in this sample30
). To address this issue, we divided our sample at the median age at interview and then compared the fit of a model that constrained our ACE parameter estimates to equality in the older and younger cohorts vs allowed separate estimates for the 2 groups for PSU from ages 14 to 35 years. Of the 88 individual tests (4 substances×22 years), only 7 (8%) were statistically significant at the 5% level, a result not different from chance expectations.31
Lastly, the goal of these analyses was to provide a fine-grained looked at developmental trends in sources of individual differences in vulnerability to PSU. We have not been able to address other intriguing questions such as variation in individual drug use trajectories or the degree of cross-time continuity in genetic and environmental risk factors for PSU. We hope to address these and other interesting issues in future studies.