The role of drug use sequencing pattern in further problematic use of alcohol, tobacco, cannabis, and other drugs

Abstract

Background: There has been considerable debate regarding what typically occurs after experimentation with drugs throughout the life of young people who used various drugs.

Aims: To evaluate the clinical importance of the most common sequence for the first use of a drug by two models (the “gateway model” and the “alternative model”, which is the most popular sequence for Brazilian university students according to a previous study) regarding the problematic use of alcohol, tobacco, cannabis and other illegal drugs, assessed by ASSIST.

Method: People who had already experimented with three or more drugs across different stages of the two models were selected from a representative sample of university students from 27 Brazilian capitals (n = 12 711).

Findings: There were no differences regarding the problematic use of the most consumed drugs in Brazil (alcohol, tobacco and cannabis) between the models. Multiple drug seekers and violators had more problematic use of illegal drugs other than cannabis than individuals in the model sequence. However, in the case of violators, this was only evident in the alternative model.

Conclusions: Multiple drug seekers and violators deserve special attention due to their increased risk of problematic use of other illegal drugs.

• Abuse
• dependence
• problematic use
• sequence of drug experimentation
• university students

Declaration of interest

The authors acknowledge the support of National Secretariat for Drug Policies (SENAD), Brazil and São Paulo State Research Support Foundation FAPESP, Brazil. Dr. Martins received research support from the National Institute on Drug Abuse (NIDA) grant DA023434 and from the National Institute of Child and Human Development (NICHD) grant HD060072, USA, while working on this article. Dr. Oliveira received research support from FAPESP grant 2008/55550-7.

Notes

† In the last decade, there has been considerable debate about what typically occurs regarding experimentation with drugs sequencing pattern throughout the life of young people who used various drugs (Fergusson et al., 2006; Morral et al., 2002). This debate has been rekindled because of recent data from a study with laboratory animals that found the previous use of a legal substance (e.g. nicotine) increased the likelihood of becoming addicted to an illegal substance (e.g. cocaine) after its first use (Levine et al., 2011), but the reverse pattern was not found. Moreover, recent cross-national epidemiological data suggest that instead of finding a single universal sequence, the incorporation of the characteristics of each population will determine the most common sequence (Degenhardt et al., 2010) for that population.

‡ This model is consistent with the moderately high lifetime prevalence of inhalant use (24.6%), which is similar to that of cannabis use (35.4%) within this population (Wagner et al., 2007). The moderately high prevalence of inhalant lifetime use is a feature of the general population in Brazil, as inhalants are the fourth most widely used drug throughout lifespan (Fonseca et al., 2010).

§The sampling was conducted in two stages, such that a sample of HEIs was selected, and a sample of student classes was chosen from this selection. Given that the sizes of the HEIs and the classes (in terms of the number of universities) were not always the same, the conglomerates were of unequal sizes. The final response rate for this study was approximately 72.1% when the estimated size of the college student sample was taken into consideration (12, 721/17, 651). The analysis of the survey data complied with the following characteristics of the sampling plan: (i) a complex sample, (ii) the use of stratification, (iii) clustering and (iv) dissimilar selection probabilities. The dissimilar selection probability was one aspect of the sampling plan that was considered when analysing the data. Two weighting factors were obtained to deal with dissimilar selection.

¶ Figure 1 presents the number of people in each group. A logistic regression with an adjustment for socio-demographic variables was run to determine whether there were significant differences between the individuals who declared all of the ages (and were included in the study) compared with those who did not. Additionally, people who declared all of their ages of first use did not complete all of the questions on the ASSIST and were therefore excluded from the analysis (Figure 1). Only minor differences were found between individuals included in the study and those excluded because of missing data for both models (“Gateway” and “Alternative”).