One year follow-up of cannabis dependence among long-term users in Sydney, Australia

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Abstract

Eighty one percent of a sample of long-term cannabis users was followed up at 1 year (162/200). Half (51%) were daily smokers, while 20% had substantially decreased or ceased use. More than half received a dependence diagnosis on each of three measures in the last year, with 44% dependent on all three. Remission was much more common than incidence of dependence. Nevertheless, use and dependence patterns were strongly related over time. Longitudinal analyses revealed that quantity of use and severity of dependence at baseline were the primary predictors of those same variables at follow-up. These data suggest that cannabis use and dependence are fairly stable among long-term users.

Introduction

Cannabis use is typically initiated in late adolescence, used experimentally or intermittently, and often discontinued by the mid to late 20s (Chen and Kandel, 1995, Hall et al., 1999). A minority proceed to regular, long-term use. Approximately one tenth to one third of those who use on a monthly or more frequent basis at around 20 years of age report doing so in their early thirties (Bachman et al., 1997, Kandel and Davies, 1992). Compared to the rich longitudinal literature on the natural history of regular alcohol use, there is little research on the natural history of regular cannabis use.

Kandel and colleagues’ landmark prospective research on the consequences of adolescent drug use has contributed important information on the initiation, escalation and cessation of cannabis and other drug use in the general population. An early age of cannabis use onset, for example, was the major predictor of near-daily cannabis use at age 29 (Kandel and Davies, 1992). While the prevalence of daily use declined into the thirties, cannabis showed the highest persistence of the illicit drugs. Predictors of continued use included being male, frequent use, using to enhance positive and reduce negative feelings, early onset of use, and consumption of other illicit drugs (Chen and Kandel, 1998).

The Monitoring the Future Project (Bachman et al., 1997), studied successive, nationally representative cohorts comprising more than 33 000 young American adults over two decades. It found remarkable individual stability in cannabis use from late adolescence to early adulthood (correlations of approximately 0.9). As with alcohol, there was a modest age-related decline in use from the mid-twenties. Increases in cannabis and alcohol use after high school were attributed to the new freedoms associated with leaving home, while the subsequent decrease reflected new responsibilities such as marriage and parenthood. Because of the low overall prevalence and frequency of cannabis use in these studies, these findings were of little relevance to patterns of dependence.

Longitudinal research on cannabis dependence is rare. One of the few population studies to prospectively address dependence followed 1000 school children on five occasions over 12 years (Newcomb, 1992). Longitudinal analyses of a subset of this group investigated predictors of cannabis abuse, a term incorporating DSM-III-R dependence symptoms and items tapping other problem domains. Although cannabis consumption in late adolescence significantly predicted consumption in adulthood, it did not explain abuse, which was predicted by measures of psychosocial vulnerability, risk and protection (e.g. education, religiosity, availability, adult and peer use patterns). However, because this study was conducted on an adolescent population it does not necessarily relate to the experiences of older, more chronic users.

Consumption in adolescence (age 15) was also a strong predictor of consumption in early adulthood (age 21) in a recent prospective study (Poulton et al., 1997). Initiation and escalation of use was more common than remission or decrease in this age group. Almost half of those with a DSM-III-R cannabis dependence diagnosis at 18 were still dependent at 21. Finally, Kandel et al. (1997) calculated estimates of persistence of cannabis dependence from North American epidemiological research. They concluded that nicotine was the most addictive substance with the highest rate of persistence (0.45), followed by alcohol (0.32) and cannabis (0.25). Thus, one in four people with a lifetime diagnosis met criteria for cannabis dependence in the past year.

Unfortunately, the small body of prospective research on regular marijuana users (e.g. Weller and Halikas, 1982, Halikas et al., 1983, Halikas et al., 1984, Weller and Halikas, 1985, Haas, 1987, Hendin et al., 1987) has not addressed the issue of dependence, although it has provided valuable insight into the patterns and experiences of cannabis use over time.

For example, a group of 100 regular users and 50 non-using friends were followed over a 6–8 year period, and changes in cannabis and other drug use patterns, and psychological functioning, were examined (Weller and Halikas, 1982, Halikas et al., 1983, Weller and Halikas, 1985). Users displayed general stability in the reported effects of cannabis, although there was a small decrease in the frequency of desirable effects of use. Use patterns had polarised to either daily or occasional use, although they were significantly correlated with original frequency. There was a general decline in the use of other drugs with the exception of alcohol, and their use was also correlated with that reported initially.

In an attempt to supplement the sparse longitudinal literature on patterns of cannabis use and dependence this paper presents data collected from a 1-year follow-up interview of a sample of long-term cannabis users recruited in Sydney, Australia, as part of an exploratory study of the characteristics, correlates and measurement of cannabis dependence (Swift et al., 1998a, Swift et al., 1998b).

Section snippets

Aims

The aims of this study were to: (i) examine patterns and contexts of cannabis use and dependence in long-term users over a 1-year period, and (ii) investigate baseline factors that may be associated with these variables at follow-up.

Subjects

Eligible subjects were 200 long-term cannabis users who had participated in a comprehensive interview about their patterns and experiences of cannabis use and dependence in 1995–1996 and had provided permission to be contacted for a follow-up interview 12 months later. The recruitment and characteristics of this convenience sample are described elsewhere (Swift et al., 1998a, Swift et al., 1998b). Briefly, participants were recruited from advertisements or by word of mouth. Inclusion in the

Predictors of participation in follow-up

The baseline (n=200) and follow-up (n=162) samples were compared to investigate characteristics which predicted participation in the 1-year follow-up interview. Univariate analyses revealed a trend towards older participants remaining in the sample (χ2MH, 1 d.f.=3.4, P=0.07). Those who were re-interviewed were also more likely to be female (89 versus 75% of males; χ2, 1 d.f.=6.5, P=0.01), employed (86 versus 75% who were unemployed; χ2, 1 d.f.=3.4, P=0.06), in a relationship (86 versus 75% of

Discussion

A respectable 81% of the baseline sample was re-interviewed at 1 year. While younger, polydrug using males were significantly less likely to be interviewed at follow-up differential attrition had no effect on the predictors of the follow-up variables.

Consistent with other research (e.g. Halikas et al., 1984), cannabis use patterns remained fairly stable, with at least moderate correlations between frequency and quantity of use at the two interviews. Longitudinal multivariate analyses revealed

Acknowledgements

This research was funded by a National Drug Strategy Research Scholarship, Commonwealth Department of Health and Family Services. Professors Robin Room, of The Centre for Social Research on Alcohol and Drugs, Sweden, and Ronald Kessler, of the Harvard Medical School, USA, gave permission to use the ICD-10 measure of dependence and the short UM-CIDI, respectively. Dr Michael Lynskey provided valuable advice on the longitudinal analyses. We also thank the study participants who agreed to be

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