Longitudinal Teen Study: First Puff-->Daily Use. Factors Involved in Daily MJ Use

[Richard_smoker]

Ever wonder what makes people more likely to turn into big-time stoners?? Well of course you haven't. And certainly no one needs an official scientific social study to analyze these variables. But, here's one anyway. What factors tend to turn kids into burn-out stoners? surprise: male gender, cigarette smoking, alcohol use, peer pressure, surroundings, age of first use, and many more--read on to find out more!

Initiation and progression of cannabis use in a population-based Australian adolescent longitudinal study

Coffey C, Lynskey M, Wolfe R, Patton GC. Addiction. 2000 Nov;95(11):1679-90

Abstract:
AIMS: To examine predictors of cannabis use initiation, continuity and progression to daily use in adolescents.
DESIGN: Population-based cohort study over 3 years with 6 waves of data collection.
PARTICIPANTS: 2032 students, initially aged 14-15 years, from 44 secondary schools in the state of Victoria, Australia.
MEASUREMENTS: Self-report cannabis use was categorized on four levels (none, any, weekly, daily) and summarized as mid-school (waves 2/3) and late-school (waves 4/5/6) use. Background, school environment, mid-school peer use and individual characteristics were assessed.
FINDINGS: Peer cannabis use, daily smoking, alcohol use, antisocial behaviour and high rates of school-level cannabis use were associated with mid-school cannabis use and independently predicted late-school uptake. Cannabis use persisted into late-school use in 80% of all mid-school users. Persisting cannabis use from mid- to late-school was more likely in regular users (odds ratio (OR) 3.4), cigarette smokers (OR any smoking: 2.0, daily smoking: 3.3) and those reporting peer use (OR 2.1). Mid-school peer use independently predicted incident late-school daily use in males (OR 6.5) while high-dose alcohol use (OR 6.1) and antisocial behaviour (OR 6.6) predicted incident late-school daily use in females.
CONCLUSIONS: Most cannabis use remained occasional during adolescence but escalation to potentially harmful daily use in the late-school period occurred in 12% of early users. Transition was more likely in males, for whom availability and peer use were determinants. In contrast, females with multiple extreme behaviours were more likely to become daily users. Cigarette smoking was an important predictor of both initiation and persisting cannabis use.

THE ENTIRE STUDY REPORT (& bibliography):
Click here to access the full report from Addiction in PDF format. For your convenience, I copied and pasted the text below, but the original PDF is formatted and easier to read.... Enjoy! -Dick

Addiction (2000) 95(11), 1679–1690
RESEARCH REPORT
Initiation and progression of cannabis use in a population-based Australian adolescent longitudinal study
C. COFFEY,1 M. LYNSKEY,2 R. WOLFE3 & G. C. PATTON1
1Centre for Adolescent Health, Department of Paediatrics, University of Melbourne, 2National Drug and Alcohol Research Centre, University of New South Wales, Sydney & 3Clinical Epidemiology and Biostatistics Unit, Royal Children’s Hospital and Department of Paediatrics,
University of Melbourne, Australia

Abstract
Aims. To examine predictors of cannabis use initiation, continuity and progression to daily use in adolescents. Design. Population-based cohort study over 3 years with 6 waves of data collection. Participants. 2032 students, initially aged 14–15 years, from 44 secondary schools in the state of Victoria, Australia. Measurements. Self-report cannabis use was categorized on four levels (none, any, weekly, daily) and summarized as mid-school (waves 2/3) and late-school (waves 4/5/6) use. Background, school
environment, mid-school peer use and individual characteristics were assessed. Findings. Peer cannabis use, daily smoking, alcohol use, antisocial behaviour and high rates of school-level cannabis use were associated
with mid-school cannabis use and independently predicted late-school uptake. Cannabis use persisted into
late-school use in 80% of all mid-school users. Persisting cannabis use from mid- to late-school was more likely
in regular users (odds ratio (OR) 3.4), cigarette smokers (OR any smoking: 2.0, daily smoking: 3.3) and
those reporting peer use (OR 2.1). Mid-school peer use independently predicted incident late-school daily use
in males (OR 6.5) while high-dose alcohol use (OR 6.1) and antisocial behaviour (OR 6.6) predicted
incident late-school daily use in females. Conclusions. Most cannabis use remained occasional during
adolescence but escalation to potentially harmful daily use in the late-school period occurred in 12% of early
users. Transition was more likely in males, for whom availability and peer use were determinants. In contrast,
females with multiple extreme behaviours were more likely to become daily users. Cigarette smoking was an
important predictor of both initiation and persisting cannabis use.

Introduction
There is concern about cannabis use by young people in most developed countries (Adlaf & Smart, 1991; Fergusson, Lynskey & Horwood, 1993; Johnston, OMalley & Bachman 1998; Hall, Johnston & Donnelly, 1999; Lynskey & Hall, 1999). Cannabis use is typically initiated
during adolescence with patterns of heaviest use usually occurring during late adolescence and young adulthood (Chen & Kandel, 1995). Correspondence to: Ms Carolyn Coffey, Centre for Adolescent Health, 2 Gatehouse Street, Parkville 3052, Australia Submitted 31st January 2000; initial review completed 7th April 2000; Ž nal version accepted 9th June 2000. ISSN 0965–2140 print/ISSN 1360-0443 online/00/111679–12 Ó Society for the Study of Addiction to Alcohol and Other Drugs Carfax Publishing, Taylor & Francis Ltd DOI: 10.1080/01439680020000911
1st sample N1 =1037 Wave 1 n1 =898 (87%) late 1992 2nd sample N2 =995 Wave 2 n2 =1728 (85%) early 1993
Wave 3 n3 =1699 (84%) late 1993
Wave 4 n4 =1629 (80%) early 1994
Wave 5 n5 =1576 (78%) late 1994
Wave 6 n6 =1530 (75%) early 1995
Total intended sample = N1 + N2 = 2032
Total achieved sample = 1947 (96%) 1680 C. Coffey et al.
Figure 1. Participation rates of 2032 secondary school students in the adolescent health cohort study in Victoria, Australia.

Controversy remains about the extent of the harmful social and health consequences of occasional use of this drug. Debate has been polarized between those who argue that adolescent cannabis use is essentially a benign, transient
practice with few social and health consequences for the great majority of young people (Shedler & Block, 1990; Robins, 1995) and those who view cannabis as having the
potential to lead to escalating drug use and its attendant problems (Kandel et al., 1986; Newcomb & Bentler, 1988; Fergusson, Lynskey & Horwood, 1996; Hall, 1997). Its peak use also coincides with the time of greatest risk for
adverse effects of substance use such as accidental injury, educational and legal difŽ culties (Hall, 1995). Most information on the risk factors for cannabis use derive from cross-sectional and retrospective studies. These studies have generated useful hypotheses but the processes involved can only be explored longitudinally, that is, with prospective measurement at multiple time-points of drug use and putative risk factors (Kandel,
1980; Farrington, 1991; Cicchetti & Rogosch, 1999).

Longitudinal studies beginning early in life have identiŽ ed childhood and early adolescent risk factors for cannabis use, but infrequent observations during the adolescent years have limited the ability of these studies to clarify risk processes around mid- to late teens, a period of rapid change in drug use behaviour. Well documented risk factors for licit and illicit substance use include ready substance availability together with afŽ liation with drug-using peers (Dembo et al., 1979; Kandel & Andrews, 1987; Maddahian, Newcomb & Bentler, 1988), but predictors of more regular use have been less explored than those for initial uptake. Further, few investigators have distinguished between occasional/experimental use and more regular use, thereby being insensitive to the possibility that risk factors for the two levels may differ.
The aims of this report are to use data from a 3-year prospective study of a representative sample of Australian adolescents to quantify the correlates of early cannabis use and to quantify risk factors for incident use, continuation and progression in use.
Method
Procedure and sample
Data were collected from subjects in a 6-wave cohort study of adolescent health performed throughout the state of Victoria, Australia between August 1992 and July 1995. The cohort was deŽ ned using a two-stage sampling procedure. At stage 1, 45 schools were selected from a stratiŽ ed frame of government, catholic and independent schools (total number of students 60 905). One school from the initial cross-sectional survey was unavailable for the cohort study leaving a total of 44 schools. At the second stage, a single intact class was randomly selected
from each school and these students were measured in wave 1. At the second wave of data collection, 6 months later, when the cohort had moved into year 10, a second intact class from the same grade at each participating school was selected at random (Fig. 1). Thus half the participants had been interviewed once before wave 2. The entire sample was followed-up from wave 2 to completion of the study. The study was presented as dealing with important adolescent health issues and covered both adolescent mental health and life-style. Written parental permission was sought at entry into the study. Subjects completed the questionnaire at intervals of 6 months between year levels Natural history of adolescent cannabis use 1681 9 and 12 (6 waves). The mean age at wave 1 was 14.5 (SD 0.5) years and at wave 6, 17.4 years (SD 0.4). The survey was administered at school using 28 laptop computers which allowed the collection of detailed self-report data through the use of branched questionnaires (Paperny et al., 1990). Subjects who were unavailable for followup at school were interviewed by telephone. The proportion of interviews conducted by telephone increased from 2% in wave 2 to 14% in wave 6.
Measures
Cannabis use
Assessment of cannabis use was based on self-reported
frequency. Participants described their cannabis use during the past 6 months using the following rating scale: (1) never used, (2) not used in the past 6 months, (3) a few times, (4) monthly, (5) weekly and (6) daily.
Cannabis use was summarized over two periods of the study: the highest reported level of cannabis use in waves 2 and 3, and similarly in waves 4, 5 and 6. These intervals correspond to the third last year at school, and the last 2 years of school. For convenience, these intervals are referred to as “mid-school” and “late-school”, respectively, although the second interval contained data from 219 (11%) participants who had left school before their Ž nal year.
Background and putative risk factors
A wide range of social, demographic, peer and individual factors were examined as possible predictors of cannabis use. These were selected on the basis of prior review of the literature which identiŽ ed factors most likely to be related to cannabis use and subject to availability within
our data. The factors included were:
Demographic variables. These were assessed at study entry and included gender, place of birth, metropolitan or rural location of school and parental separation or divorce.
However, rural school location was not associated with any cannabis use variable and so was dropped from all outcome analyses.

Peer cannabis use. At each wave, participants reported whether (1) none, (2) some or (3) most of their friends used cannabis. This variable was summarized over the mid-school period so that those reporting in at least one wave that most of their friends used cannabis were characterized accordingly. School level of cannabis use
In order to examine early exposure to regular cannabis use at school, the proportion of students within each school using cannabis at least weekly was calculated at wave 2. The schools were then divided into tertiles on the basis of these proportions. In all analyses of late-school
cannabis use with the three-level variable describing school-level exposure, only the highest category held a univariate association (if at all) with the outcome variable. Therefore the binary variable, top tertile vs. middle or bottom tertile, was used in each analysis.

Cigarette smoking. Participants reporting that they had smoked on 6 or 7 days in the previous week were categorized as daily smokers. If daily smoking was recorded in either waves 2 or 3 then the individual was characterized as a daily smoker during the midschool period (291 of the 1890 participants). For more detailed analysis of the effects of smoking, occasional smoking was deŽ ned as reporting smoking in the last month, but less than 6 days in the past week. Non-smoking was deŽ ned as not having smoked in the past month.

Alcohol consumption
Subjects reporting that they had drunk alcohol in the week before the survey were asked to complete a 1-week retrospective alcohol diary (beverage-and quantity-speciŽ c). Two measures of alcohol consumption were derived from the diary in waves 2 and 3: (1) Those who reported drinking on three or more days in the previous week in either wave 2 or 3 were classiŽ ed as frequent drinkers in the mid-school period (123 of 1890 participants). (2) Subjects were characterized by their average consumption of ethanol per drinking day (one unit equivalent to one standard drink, 1682 C. Coffey et al. 9 g ethanol). Those with an average of Ž ve units or greater were classiŽ ed as high dose drinkers (312 of 1890 participants).

Antisocial behaviour. Antisocial behaviours were evaluated with 10 items from the MofŽ tt & Silva (1988) selfreport early delinquency scale. Items included antisocial behaviour relating to property damage (vandalism, car damage, making grafŽ ti), interpersonal con? ict (Ž ghting, carrying weapons, running away from home, expulsion from school) and theft (stealing property from parents, or other, stealing cars). Items concerning alcohol or other substance use were not included. The reference period was 6 months. Antisocial behaviours were categorized according to whether more than one behaviour was endorsed “more than once” in order to distinguish participants with more global antisocial
behaviours. If this occurred in either wave 2 or wave 3, individuals were characterized as displaying antisocial behaviour in the mid-school period (240 of 1890 participants).

Mental health. A computerized form of the Clinical Interview Schedule (CIS-R) was used to rate psychiatric
morbidity (Lewis & Williams, 1989; Lewis et al., 1992). This is a structured psychiatric interview designed for assessing symptoms of general psychiatric morbidity in non-clinical populations and includes indicators of depression and anxiety. The instrument generates 14 subscales which can then be added to form a scale indicating the degree of psychiatric morbidity. Mean scores for waves 2 and 3 were calculated and then dichotomized at the 11/12 cut-point, corresponding to the level at which a general practitioner might be concerned about a subject’s mental health (Lewis & Williams, 1989; Lewis et al., 1992). Thirty-two per cent of females and 15% of males scored above this threshold.

Data analysis. Data analysis was undertaken using Stata (StataCorp, 1999). Initially, cannabis use was assessed using a three-category ordinal scale1) not used in previous 6 months, (2) used in the last 6 months but less often than weekly and (3) weekly or more regular use. We considered two alternative ways of analysing this data. The Ž rst alternative was to dichotomize cannabis use as: (1) versus (2)–(3); or (1)–(2) versus (3), and then to examine separate logistic regression models Ž tted to these dichotomous outcomes. This approach would have resulted in two different odds ratio (OR) estimates of
the association of a factor with cannabis use. A marked difference between these OR would indicate that the association was different at different parts of the ordinal scale. If the underlying association with cannabis use that we were trying to estimate was, in fact, the same across
the ordinal scale (i.e. the underlying OR were equal) then this analysis method would be inefŽ cient and would ignore some of the information from the three-category scale. To optimize efŽ ciency we used the alternative
strategy of Ž tting ordinal logistic regression models. Within these models, it was possible to perform likelihood-ratio (LR) tests (Peterson & Harrell, 1990) of the assumption of a factor’s association with cannabis use being constant across the ordinal scale (the proportional odds (PO) assumption (McCullagh, 1980)). All variables
in the multivariable ordinal models included in this report complied with the proportional odds assumption at the 0.05 level of signiŽ cance. Exploratory univariate analyses were performed followed by multivariable ordinal logistic
regression modelling. First-order interactions with gender were tested in all models using the LR test comparing the more complex model with the simpler model. All reported conŽ dence intervals (CI) are based on a 95% conŽ dence
level. Other analyses performed were on the binary outcomes: poor survey completion, late-school daily use and persistence from early to lateschool use. These analyses used multivariate logistic regression. In the case of the predictive model for daily cannabis use, backwards stepwise selection was used to examine interaction terms with gender, keeping all main terms in the model. Items were dropped if p . 0.2 and reincluded if p , 0.1. A similar process was then used in the selected model in order to
examine the main terms, dropping terms if p . 0.1, and reincluding if p , 0.05.
Analysis Mid-school level of use Late-school level of use
(1) Mid-school cannabis use (cross-sectional) outcome no use < weekly weekly daily no use < weekly weekly daily (2) Cannabis use initiation no use < weekly weekly daily outcome no use < weekly weekly daily (3) Continuity of cannabis use no use < weekly weekly daily outcome no use < weekly weekly daily (4) Daily use initiation no use
< weekly weekly daily outcome no use < weekly weekly daily
Natural history of adolescent cannabis use 1683
Results
Sample characteristics
From the total sample of 2032 students on class registers, 1947 (95.8%) completed the questionnaire at least once in the course of the study. Based on the intended sample, response rates across waves were as follows: wave 1, 87%; wave 2, 85%; wave 3, 84%; wave 4, 80%; wave 5,
78%; and wave 6, 75%. The gender ratio of the cohort (males 47.0%) was similar to that in Victorian schools at the time of sampling (Australian Bureau of Statistics, 1993). A total of 1890 (93%) young people participated in waves 2–6. The mean age at wave 2 was 15.4 (SD 0.5) years and at completion of the follow-up was 17.4 years (SD 0.4). Two hundred and three subjects (11%) completed only one or two waves between waves 2 and 6. Characteristics of these low completers were examined in a logistic regression model. Males were over-represented (OR 1.8, 95% CI 1.3–2.5), as were non-Australian-born subjects (OR 2.0, CI 1.3–3.1), those who had experienced
parental divorce or separation (OR 2.6, CI 1.8–3.7) and those who reported using cannabis at least weekly at study inception (OR 1.9, CI 1.0–3.5). Four major outcome analyses were performed and are shown in Fig. 2. This Ž gure illustrates one cross-sectional analysis and three prospective analyses that are the subject of this report.
Table 1 shows the frequency of mid-school cannabis users by late-school users, and deŽ nes the observations included in the prospective analyses (2) to (4) illustrated in Fig. 2. (1) Mid-school cannabis use Twenty-one per cent of the 1864 participants in waves 2 and 3 (24% of males and 18% of females) reported using cannabis in the midschool period of follow-up (Fig. 2). As daily use was infrequent we combined this category with weekly use to generate a three-level variable describing cannabis use: (1) none, (2) less often than weekly ( , weekly), (3) weekly or more often (weekly 1 ). Male gender held a odest univariate association with mid-school cannabis use, but this association was not sustained after adjustment for covariates (Table 2). Reported peer use held the strongest independent association with cannabis use with a greater than 10-fold increase in odds. Antisocial behaviours, daily smoking and high-dose alcohol use were markedly associated with cannabis use, showing between three- and Ž ve-fold increases in odds, while alcohol use on three or more days was only modestly associated. Having divorced or separated parents showed a slightly elevated univariate
risk, which was still evident after adjustment for possible confounders. There was no evidence of an association with either psychiatric morbidity or Australian birth after adjustment for confounders.
Figure 2. Description of analyses. Shaded areas indicate data included in analysis, borders indicate boundaries between categories, gaps between categories indicate levels of outcome, and arrows indicate path of transition.
1684 C. Coffey et al.
Table 1. Frequency ofmid-school cannabis use by late-school cannabis use. Figures in brackets are row percentages Late-school cannabis use Mid-school cannabis use None , Weekly Weekly Daily Total None 1153 163 26 5 1347 (85.6) (12.1) ( 1.9) ( 0.4) (100) , Weekly 63 123 61 10 257 (24.5) (47.9) (23.7) ( 3.9) (100) Weekly 3 22 28 22 75 ( 4.0) (29.3) (37.3) (29.3) (100) Daily 3 2 8 7 20 (10.0) (40.0) (35.0) (100) (15.0) Total 1222 310 123 44 1699 (71.9) (18.3) ( 7.2) ( 2.6) (100) There were 123 non-users, 25 , weekly, 10 weekly and seven daily cannabis users from the mid-school period who had no late-school observations. Table 2. Associations with mid-school cannabis use measured on three levels*: OR from ordinal logistic regression models (n 5 1864) Univariate Multivariate Explanatory variable OR 95% CI OR 95% CI Gender (male vs. female) 1.4 1.2–1.8 1.2 0.86–1.5 Australian birth 1.7 1.2–2.4 1.3 0.85–2.1 Divorced/separated parents 2.3 1.8–3.0 1.5 1.1–2.1 Peer cannabis use 26 19–35 12 8.6–17 Daily smoking 11 8.3–14 4.7 3.5–6.4 Alcohol . 2 days per week 6.0 4.2–8.7 1.6 1.0–2.5 High dose drinker 8.7 6.7–11 3.2 2.3–4.3 Antisocial behaviours 8.6 6.5–11 3.9 2.8–5.5 Psychiatric morbidity 2.1 1.7–2.7 1.0 0.76–1.4 * Levels of cannabis use: none (79%), less than weekly (15%), weekly or more often (6%). 1. Proportional odds (PO) assumed for all variables and interaction terms. 2. Overall likelihood-ratio test of PO assumption for multivariable model: v 2 (8) 5 7.8; p 5 0.45. (2) Prediction of Ž rst cannabis use Four hundred and forty-four of 1725 late-school participants (34% of males, 24% of females) reported cannabis use in the late-school period. Eighteen per cent reported using less than weekly, 7% weekly and 2.6% daily. Incident late-school cannabis use was examined in 1347 individuals who had not reported using cannabis in the mid-school period and had observations available in the late-school period (Fig. 2). In the multivariate ordinal model, peer use, daily smoking, frequent and high-dose alcohol use and antisocial behaviours all predicted cannabis uptake in the late-school period with between a twoand three-fold increase in odds (Table 3). Early exposure to a high level of school cannabis use was also predictive of subsequent cannabis initiation. Gender was not associated with late school initiation. There were no Ž rst order interactions with gender.
(3) Continuity between mid- and late-school any
cannabis use We deŽ ned participants who reported any level of use in both mid- and late-school as continuing users. Continuing users (N 5 283, 57% male) were compared with those reporting mid-school Natural history of adolescent cannabis use 1685 Table 3. Prediction of late-school cannabis use measured on three levels* for adolescents with no earlier reports of cannabis use (n 5 1347): OR from ordinal logistic regression models. Univariate Multivariate
Explanatory variable OR 95% CI OR 95% CI
Gender (male) 1.4 0.52–1.0 1.3 0.94–1.8
Australian birth 1.9 1.1–3.3 1.6 0.91–2.7 Divorced/separated parents 1.6 1.1–2.5 1.4 0.88–2.1
High level of weekly cannabis use in 1.8 1.3–2.4 1.7 1.2–2.4
school at study inception
Mid-school: most peers used cannabis 2.5 1.2–4.8 2.0 1.0–4.2
Mid-school: daily smoker 2.9 1.8–4.8 2.3 1.3–3.9
Mid-school: alcohol . 2 days/week 4.1 2.3–7.3 2.1 1.1–3.9
Mid-school: high dose drinker 3.9 2.6–5.8 2.6 1.7–4.1
Mid-school: antisocial behaviours 3.4 2.1–5.5 2.3 1.4–3.8
Mid-school: psychiatric morbidity 1.6 1.1–2.2 1.5 1.0–2.1
* Levels of cannabis use: no use (83%), less than weekly (13%), weekly or more often (4%). 1. Proportional odds (PO) assumed for all variables. 2. Overall likelihood-ratio test of PO assumption for Ž nal multivariable model: v 2
(10) 5 11.7; p 5 0.31 cannabis use but who reported no subsequent use (N5 69, 46% male) (Fig. 2). Seventy-Ž ve
per cent of the 257 , weekly mid-school users and 94% of 95 weekly 1 mid-school users continued (Table 4). In the initial analysis it was clear that daily smoking was an important predictor of continued use. In order to examine this effect further we included mid-school smoking in the model on three levels: non-smoker (60/83 continued), smoked in the last month (104/129 continued) and daily smoking (161/182 continued). Compared with non-smokers, occasional smokers were at double the risk of continuation and daily smokers were at over three times elevated risk, with evidence of a dose effect with increasing frequency of smoking. More frequent mid-school cannabis use and peer use were associated with a three-fold and two-fold elevation in risk, respectively. Although there was evidence of an interaction between parental divorce and gender
(likelihood ratio v 2 (1) 5 5.9, p 5 0.015), the effect of divorce within each gender was not substantial. The residual gender effect showed that males were at increased risk of continuing after allowing for this interaction (males to females adjusted OR 2.6, 1.3–5.6). Interaction between gender and mid-school level of cannabis use could not be tested due to the small number
of weekly 1 users who discontinued. There were no other signiŽ cant Ž rst order interactions with gender.
(4) Daily cannabis use
Young people reporting daily cannabis use were considered to be at high risk of harmful and dependent patterns of use so we were particularly interested in patterns of continuity and progression to daily use. Forty-four young people (3.7% of males and 1.7% of females) of the 1699 with observations in both periods reported using cannabis daily in late-school (another two had late-school but no mid-school observations) (Table 1). Only Ž ve of these had not reported some mid-school use. Twelve per cent of all mid-school users (25/192 males and 14/146 females) reported late-school daily use, constituting 4% of , weekly mid-school users and 31% of weekly 1 mid-school users. There was strong evidence of a dose–response relationship between late-school daily use and level of midschool use after adjustment for confounders (adjusted OR: less than weekly use mid-school 4.4, 1.3–15; weekly use mid-school 27, 7.0–1.5; daily use mid-school 25, 4.3–142). Prediction of initiation into late-school daily cannabis use The onset of daily cannabis use was examined in those participants not previously reporting daily cannabis use in the mid-school period (Fig. 2). There were 37 reports (24 males) of incident late-school daily cannabis use (male versus.
1686 C. Coffey et al. Table 4. Prediction of continuation of cannabis use frommid-school into late-school (n 5 283) for those adolescents reporting earlier cannabis use (n 5 352): OR from logistic regression models
Univariate Multivariate Explanatory variable OR 95% CI OR 95% CI
Australian birth 1.6 0.66–3.7 2.4 0.92–6.1
Parental divorce
females 2.1 0.87–5.3 2.1 0.82–5.6
males 0.63 0.26–1.6 0.47 0.14–1.6
High level of weekly cannabis use 1.1 0.66–1.9 0.87 0.49–1.6
in school at study inception
Mid-school: cannabis use weekly 1 4.8 2.0–12 3.4 1.3–9.0
Mid-school: most peers used cannabis 2.5 1.4–4.4 2.1 1.1–4.0
Mid-school:
Non-smoker 1 1
Smoked in the last month 1.7 0.86–3.2 2.0 1.0–4.2
Daily smoker 2.9 1.5–5.7 3.3 1.6–7.2
Mid-school: alcohol . 2 days/week 1.1 0.55–2.3 0.61 0.27–1.4
Mid-school: high dose drinker 1.3 0.75–2.2 0.62 0.33–1.2
Mid-school: antisocial behaviours 2.0 1.1–3.7 1.5 0.74–3.0
Mid-school: psychiatric morbidity 1.2 0.68–2.1 1.0 0.55–2.0
female OR 2.2, 1.1–4.3). All main effects and interactions between gender and the explanatory variables were examined using backwards stepwise regression. As all incident cases of daily cannabis use were participants born in Australia, this variable was not included in the analysis.
There was evidence of important interactions between gender and three mid-school predictors (Table 5). Males who reported that most of their peers used cannabis were at six-fold increased risk, in contrast to females for whom this effect was negligible. Conversely, females, unlike
males, were at around six-fold elevated risk if they reported earlier high dose drinking or antisocial behaviours. There was a trend for schoollevel exposure to cannabis use to predict incident daily cannabis use in late-school, independent of gender. The residual effect for gender was not signiŽ cantly predictive of daily use at p 5 0.05 (OR 3.8, 0.82–18). Parental divorce or separation
(univariate OR: 3.2, 1.6–6.3), mid-school daily smoking (univariate OR: 5.5, 2.4–13), midschool frequent alcohol use (univariate OR: 3.8, 1.6–8.9) and mid-school psychiatric morbidity (univariate OR: 2.0, 1.0–3.9) were removed from the model during the selection process as
they were not predictive of initiation into daily cannabis use in the multivariate model.

Discussion
One in Ž ve Australian adolescents used cannabis during the mid-teens. For the great majority the frequency of cannabis use remained at low levels with around two-thirds of all users in both midand late-school periods reporting less than weekly use. By examining progression to daily use we were able to delineate a group who were at unequivocal risk of harmful use. The mid- to late teens was an important period for progression in use with 13% of male and 9% of female mid-school users going on to daily cannabis use. This study differs from earlier work in that it is based on the repeated measurement of cannabis use at multiple points. It is therefore able to address questions of both initiation of use and progression to higher levels of use. As school retention rates were 98% in this state in the year of initial sampling, the sample frame provided an almost representative adolescent study population (Australian Bureau of Statistics, 1993). The age range is around the previously reported peak age for initiation of cannabis use (Chen & Kandel, 1995). One issue of importance is that of the validity of self-report of cannabis use. Self-report of cannabis use has been demonstrated to have good construct validity, to have
reasonable stability and to be no worse in this regard than other self-report measures (O’Malley, Bachman & Johnstone, 1983). Stability has been shown to be related to the recall period so we can expect that the daily and
weekly response categories were reasonably Natural history of adolescent cannabis use 1687 Table 5. Prediction of initiation into late-school daily cannabis use (n 5 37) by adolescents who reported none or less than daily mid-school cannabis use (n 5 1679): OR from logistic regression models

Univariate Multivariate
Explanatory variable OR 95% CI OR 95% CI
High level of weekly cannabis use in 3.6 1.9–7.1 2.0 0.97–4.3
school at study inception
Mid-school: cannabis use (weekly or 29 11–74 8.7 2.8–26.8
less often)
Mid-school: most peers used cannabis
Females 11 3.5–32 1.3 0.35–4.6
Males 23 9.3–58 6.5 2.3–18.3
Mid-school: high dose drinker
Females 29 7.8–107 6.1 1.4–25.4
Males 4.0 1.7–9.0 1.0 0.41–2.6
Mid-school: antisocial behaviours
Females 22 6.9–69 6.6 1.9–23.3
Males 3.9 1.7–9.0 0.91 0.36–2.4 reliable. Although the occasional category used a 6-month reference period, enhanced ability to remember unusual events could have countered a tendency to under-report (O’Malley et al., 1983). Another source of bias could have been the lower participation rates noted to be associated with weekly cannabis use at study entry. There was possibly the potential for misspeci Ž cation of cannabis use in individuals absent from waves within each study period. We have assumed that patterns of associations observed in the data were similar for individuals for whom data was missing. This could have resulted in slightly biased OR estimates. Different mechanisms have been suggested to
explain the uptake of illicit drugs in young people. The stage theory implies that use of one drug further down a sequence, for example alcohol and/or nicotine, in some way facilitates the use of drugs at higher levels, for example cannabis (Adler & Kandel, 1981; Yamaguchi &
Kandel, 1984; Welte & Barnes, 1985; Fleming et al., 1989; Graham et al., 1991; Ellickson, Hays & Bell, 1992; Kandel, Yamaguchi & Chen, 1992). Evidence from these studies is also consistent with the hypothesis that drug use is determined by a single underlying dimension of
vulnerability to drug use or “transition proneness” (Jessor & Jessor, 1977) and that the use of different drugs at different times is an opportunistic response to changing environmental conditions such as availability. The concept of vulnerability has been extended further to suggest
that drug use was one of a constellation of deviant behaviours described collectively as a syndrome of problem behaviours (Donovan & Jessor, 1985). The veracity of these theories can be informed by examining risk processes involved in the natural history of cannabis use. In this study, prior use of cannabis was found to be strongly and independently predictive of subsequent use. Overall, four-Ž fths of those who reported earlier cannabis use continued at some level. Only Ž ve of the 44 using cannabis daily in the later period had not reported earlier use, with strong evidence that more frequent early use
substantially increased the propensity to later, possibly harmful, daily use. SpeciŽ cally, both weekly and daily use carried around a six-fold elevated risk of later daily use relative to occasional use. However, it must be remembered that escalation was far from being an inevitable consequence of early occasional use in that only
4% of mid-school occasional users made this transition.
Quitting and persistence in cannabis use in adolescence has not been studied previously in non-clinical settings. Eighty-two per cent of those reporting cannabis in the mid-school period continued use in the late school period.
Continued use was more common among males, young people reporting more regular cannabis use, smokers and those with cannabis using friends. The co-occurrence of tobacco use and cannabis use is well documented (Hall, 1995). We 1688 C. Coffey et al. found that although both alcohol use and smoking were associated with cannabis uptake, only smoking was independently predictive of persistent use by early users. This Ž nding indicates that it is the co-occurrence of smoking rather than alcohol use that distinguishes between transient experimentation and entrenched behaviour, with the degree of entrenchment
apparently related to smoking frequency. It is interesting to speculate whether the mechanism is purely social, re? ecting the companionable experience in common with smoking cigarettes and smoking cannabis, or whether there may in part be an underlying physiological or psychological vulnerability to both nicotine and cannabis
dependency in these young people. This vulnerability may simply be that initiation of cannabis is unlikely in the absence of some prior history of smoking as a method of drug ingestion. That peer use was also an independent predictor of persistent use tends to support the possibility of a social determinant component. The lack of independent association with other norm-violating behaviours or with symptoms of depression and anxiety would seem to discount problem behaviour or psychological vulnerability as the mechanism. A number of previous studies have reported that tendencies in childhood to disruptive or norm-violating behaviours are important predictors of the development of cannabis use (Shedler & Block, 1990; Lynskey & Fergusson, 1995). In an extension of these Ž ndings and in contrast to persisting use, we found that antisocial behaviour in the mid-school period was predictive of cannabis uptake. As is already well-documented, we found that reported peer cannabis use held clear and robust associations with cannabis use and was strongly predictive of uptake. Further, to the best of our knowledge, this is the Ž rst study to speciŽ cally examine the in? uence of the level of cannabis use within the individual’s school environment measured at the school level. Elevated risk of cannabis initiation associated with environmental cannabis use is consistent with earlier reports that family, peer and
community levels of drug use are important determinants of substance use behaviours (Hawkins, Catalano & Miller, 1992). The analysis method we used to examine risk factors for cannabis initiation allowed us to infer that the in? uence of each risk factor was similar for incident occasional use and incident regular use. This Ž nding must be interpreted cautiously as the test of “proportional odds” had low power, but it may indicate that identiŽ ed factors
endowed a general blanket of risk, irrespective of the level of uptake. Initiation of daily cannabis use in the lateschool
period differed between males and females. Males were more than twice as likely to make the transition to daily use but earlier norm-violating behaviour, indicated by antisocial behaviour and high-dose drinking, was found to predict of daily use only in females. This observation lends credence to the existence of a syndrome of problem behaviours described by Donovan & Jessor (1985), but only for young women. Males, on the other hand, appeared to be responding more to social expectations and opportunities indicated by their greater responsiveness
to peer in? uences. This Ž nding has important implications for the prevention of harmful substance use and suggests that different strategies may be needed to address risks of
heavy cannabis use in young males and females. Prevention of early cannabis use is likely to affect rates of daily cannabis use in both sexes. For boys preventive and early treatment interventions might sensibly address the peer social context. In contrast, girls who become daily users appear to lead more chaotic lives and it is likely that intervention responses would sensibly extend beyond a focus on cannabis alone.

Acknowledgements
The authors acknowledge the support of the Victorian Health Promotion Foundation. We are particularly indebted to Associate Professor John Carlin from the Clinical Epidemiology and Biostatistics Unit, Royal Children’s Hospital for reviewing the paper.
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[oldfart]

Cigarette smoking was an important predictor of both initiation and persisting cannabis use.

Yes Niccotine is HIGHLY ADDICTIVE both physically and mentally, however some smart people realize this early and if they want the same effect as the first clean drag of a cig the will naturally seek it in a cheaper, more effective, and longer lasting alternative.

Smoking A MJ cig is much less addicitve as smoking a Nicotine cig. and the effects are similar but longer lasting with mj thats why peolpe who smoke cigs at an erly age will seek out the better high.

Also I do nto believe that any one under 18 should be allowed to smoke anything (medical reasons aside) one is still growing as a person and should develop as such until they are old enough to comprehend the uses and abuses of smoking ANYTHING.

[Paracelsus]

Are you saying that cannabis has effects similar to tobacco, only longer-lasting? Please.

[oldfart]

I am saying that when SWIY first start smoking ciggs (SWIM remembers this like it was yesterday although is was almost 30 years ago) you get a head rush, probably the receptors in the brain being created for the nicotine and the loss of oxygen to the brain (never had smoke in your lungs now there is instead of air) and this feeling is what initially starts the habbit (or rather the brain craving this feeling of euphoria more and more) do you dispute that when SWIY smoke cirtain strains of MJ that there is a full body euphoric effect usually the Indica strains vs the Mind high of the Sativa Strains. If SWIY does dispute this fact I suggest SWIY do their own research about strains thad the different effects. But I do love a debate, and I do admit when I am wrong, or cornered with logic. SWIM does however use weird words so please feel free to query if you are confused, SWIM is blonde

[OccularFantasm]

I recall smoking my first cigarette. SWIM could hardly stand up, the head rush was soo big. Then SWIM got addicted and no longer felt any euphoria. Soon after SWIM realized he couldnt do much physically so decided to quit 1 of the 2. Since 1 was no longer euphoric but the other was so naturally swi used the nice MJ smoke all day every day for 2 weeks, and thus had no more ciggarette addiction. Also it is no wonder why people would use the 2 together, as the cigarette poteniates the effects from the blunt smoked beforehand. SWIM als agrees strongly that there are effects, but the cigarette gives you and effect for maybe 1-3 minutes, whereas weed does for 1-12 hours, depending on dosage and weather or not you clam the smoke.

[OccularFantasm]

The idea that when one starts to smoke cigarettes has any correlation to once marijuana habit is ludacris. all this study has done is find two drugs whose use tends to initiate around the same age. Both are also readily available to high school chums.
Maybe I'm wronghere but I think that this comparison is exactly the same as saying as any person approaches 100 they will die, and then blaming a specific numnber or group of numbers on the death. This would be sound organization, but not logical, as their age didnt kill them, some disease or possibly tragic accident did.

Swim really needs to organize his thoughts better so his ideas are in 1 post.

[Bajeda]

Originally Posted by OccularFantasm

The idea that when one starts to smoke cigarettes has any correlation to once marijuana habit is ludacris. all this study has done is find two drugs whose use tends to initiate around the same age. Both are also readily available to high school chums.

I wouldn't put too much trust in deriving causation from such correlations, but I wouldn't discount them entirely either. I think there is an evident relationship between developing a tobacco smoking habit and having problems controlling cannabis consumption, though smoking cigarettes alone shouldn't make you more likely to start smoking cannabis, besides that younger people probably find the two together early on.

I remember seeing another study on this, specific to the relationship between nicotine addiction and cannabis addiction however. Don't remember if I uploaded it to the archive, have to check on that. From swim's personal experience though I'd say that maintaining tobacco and cannabis habits simultaneously increases the likelihood of your having addiction problems with both substances.

[Bajeda]

Title: Cigarette smoking among marijuana users in the United Stats.
Author: Richter KP
Add.Author / Editor: Kaur H Resnicow K Nazir N Mosier MC Ahluwalia JS
Abstract: The vast majority of drug users smoke cigarettes. Most use marijuana and no other illicit drug. We analyzed adult responses to the 1997 NHSDA (n = 16,661) to explore relationships between marijuana use and cigarette smoking. Multivariate analyses controlled for other illicit drug use and other potential covariates. Nearly three-quarters of current marijuana users (74%) smoked cigarettes. Compared to nonusers, the adjusted odds of being a smoker were 5.43 for current marijuana users, 3.58 for past year marijuana users, and 2.02 for former marijuana users. Odds for cigarette smoking among current poly-drug users, compared to nonusers, were 2.3 to 1. Level of cigarette smoking was directly associated with frequency of marijuana use. Nationwide, an estimated 7 million adults smoke both substances and are at increased risk for respiratory illnesses and mortality. Cigarette smoking is a major co-morbidity of marijuana use and smoking cessation should be addressed among marijuana users in addition to their other illicit drug involvement.




Cannabis Use When It's Legal

Title: Cannabis use when it's legal.
Author: van Ours, Jan C
Citation: Addict Behav. Issue: Nov, Date: 2006 11 13, Year: 2006
Abstract: This paper addresses the question of whether alcohol and tobacco are "gateways" for cannabis use. To investigate this the relationships between the starting rates in the use of alcohol, tobacco, and cannabis are analyzed. The starting rate for cannabis use appears to be higher for smokers and lower for users of alcohol. Indeed, tobacco use seems to be a gateway for cannabis use. The main policy conclusion is that measures that reduce smoking will also reduce the incidence of cannabis use.




Progression from marijuana use to daily smoking and nicotine dependence in a national sample of U.S. adolescents

Title: Progression from marijuana use to daily smoking and nicotine dependence in a national sample of U.S. adolescents.
Author: Timberlake, David S
Add.Author / Editor: Bricker, Josh Hewitt, John K Hopfer, Christian J Sakai, Joseph T Haberstick, Brett C Lessem, Jeffrey M
Citation: Drug Alcohol Depend. Issue: Dec, Date: 2006 12 18, Year: 2006
Abstract: BACKGROUND: While it has been demonstrated that smoking cigarettes in adolescence increases the likelihood of progressing to marijuana use, few studies have considered the reverse scenario in which early use of cannabis leads to greater tobacco smoking. METHODS: Participants (n=5963), who had never smoked cigarettes daily by wave I of the National Longitudinal Study of Adolescent Health, were followed 6 years (waves I-III) from adolescence into young adulthood. Measures of marijuana use (lifetime use, monthly use, age at first use), as assessed at wave I within 12-16 (n=3712) and 17-21 (n=2251) year-olds, were separately modeled as predictors of three tobacco-related outcomes: (1) age at onset of daily cigarette smoking, (2) lifetime nicotine dependence, (3) current nicotine dependence. RESULTS: In the older cohort (17-21-year-olds at wave I), lifetime (>10 times) and past-month marijuana use at wave I were predictive of an earlier initiation into daily cigarette smoking and a greater likelihood of developing nicotine dependence by wave III. Furthermore, age at first use of cannabis was negatively associated with risk of nicotine dependence in the older, but not younger cohort. CONCLUSION: After controlling for baseline measures of tobacco smoking and other demographic risk factors, the use of marijuana in adolescence was modestly associated with daily cigarette smoking and nicotine dependence in young adulthood.





Reverse gateways? Frequent cannabis use as a predictor of tobacco initiation and nicotine dependence.
RESEARCH REPORT
Addiction. 100(10):1518-1525, October 2005.
Patton, George C. 1; Coffey, Carolyn 1; Carlin, John B. 2; Sawyer, Susan M. 1; Lynskey, Michael 3

Abstract:
Aims: To examine the risk posed by cannabis use in young people for tobacco use disorders. Specifically we examined whether cannabis use in non-smokers predicted later initiation of tobacco use and whether cannabis use predicted later nicotine dependence in tobacco users.
Design: A 10-year eight-wave cohort study.
Setting: State of Victoria, Australia.
Participants: A community sample of 1943 participants initially aged 14-15 years.
Measurements: Self-report of tobacco and cannabis use was assessed in the teens using a computerized interview assessment and in young adulthood with a CATI assessment. The Fagerstrom Test for Nicotine Dependence was used to define nicotine dependence.
Findings: For teen non-smokers, at least one report of weekly cannabis use in the teens predicted a more than eightfold increase in the odds of later initiation of tobacco use (OR 8.3; 95% CI 1.9-36). For 21-year-old smokers, not yet nicotine-dependent, daily cannabis use raised the odds of nicotine dependence at the age of 24 years more than threefold (OR 3.6, 1.2, 10) after controlling for possible confounders, including level of tobacco use and subsyndromal signs of nicotine dependence.
Conclusions: Weekly or more cannabis use during the teens and young adulthood is associated with an increased risk of late initiation of tobacco use and progression to nicotine dependence. If this effect is causal, it may be that a heightened risk of nicotine dependence is the most important health consequence of early frequent cannabis use.






Those studies weren't exactly what I was looking for, but I couldn't find one comparing the two dependencies on a physiological basis. I'll post if I find that article I was thinking of.

[stoneinfocus]

What do you mean with physiologica basis? -marijuhana smoke contains nicotine as well, so no wonder they might be into cigarettes, not to mention the same route of drug-admistration.

there´s no dependence caused by a drug, despite of depletion of transmitters causing withdrawl, but before this ultimate withdrwal happens, ther must be a conscious step and a decision into taking a drug and doing this at a frequency that a habit will form and later on maybe a withdrawl, but that´s not it, it´s ignoring many facts of the behaviour by the drug-user and the scientists, about what´s the cuaser of this behaviour and the dependence-withdrawl cause isn´t initiated by a drug, in no way.

Swim could have been "addicted" to cigarettes, amphetamines, marihuana and alcohol for some times in swims life, as scheduled by a scientist or medic, but he stopped and uses all those for some years, doing all the drugs again, on a 1week to 3-year frequency, added even more medical and research drugs to his life, which swim thinks to benefit from, and calls himself immune to addiction, because it´s all in the mind, nowhere else!

Why don´t we talk about the cause of cannabis use in teens, relate it if it´s really that bad and the cause of subsequent tobacco abuse and if smoking 5 cigs´/day ´d be really so bad, concerening the measures taken to the teen, inlcluding brain washing, threatening with law-enforcement and juristiction, while some or most of those user´s obviously are just having a good time maybe overdoing their experiment a little... this might be something that´d help all and gave a deeper understanding, beside neuroscientists being total morons, there´s no excuse for searching in the darkness of neurons and bio-chemical mechanisms, when it´s obviously our fault and clearly visiblly a consequence of our lifestyle, if one only opened his eyes and ´d be honest to himself and some lifestyles might not be condemned or doomed, just for being different.

[Nature Boy]

Originally Posted by co-incidence

-marijuhana smoke contains nicotine as well, so no wonder they might be into cigarettes, not to mention the same route of drug-admistration.

Marijuana smoke contains nicotine? Forgive me for being so skeptical but you might want to back that statement up with some hard evidence.

[OccularFantasm]

SWIM has to agree with you views on addiction co-incidence. SWIM was surprised to hear that marijuana smoke had nicotine so SWIM looked it up. Erowid has a very helpful chart comparing all the chemicals released from a marijuana cigarette and a tobacco cigarette. It seems marijuana smoke does not contain this from the chart, however many blunt wraps are made from tobacco not to mention how many people light up a dutch or garcia y vega which have tobacco in it. (swim is talking bout the leaf not the innards)

Table 3 : Marijuana and Tobacco Reference Cigarette Analysis of Mainstream Smoke (pg 17)
Strange Abbr: mcg: microgram C? : known Carcinogen (X means yes)
A.Cigarettes
UnitsMarijuanaTobacco

(85mm)(85mm) Average Weight (mg)11151110 Mositure (%)10.311.1 Pressure Drop cm 14.7 7.2 Static Burning rate mg/s 0.88 0.80 Puff Number
10.7 11.1
B.Mainstream Smoke I. Gas PhaseUnitsMarijuanaTobacco Carbon Monoxide % 3.99 4.58
mg 17.6 20.2 Carbon Dioxide % 8.27 9.38
mg 57.3 65.0 Ammonia mcg 228 199 HCN mcg 532 498 Cyanogen (CN)2 mcg 19 20 Isoprene mcg 83 310 Acetaldehyde mcg 1200 980 Acetone mcg 443 578 Acrolein mcg 92 85 Acetonitrilebenzene mcg 132 123 Benzene mcg 76 67 Toluene mcg 112 108 Vinyl chloride ng5.4 12.4 Dimethylnitrosamine ng75 84 Methylethylnitrosamine ng27 30 pH, third puff
6.56 6.14 fifth puff
6.57 6.15 seventh puff
6.58 6.14 ninth puff
6.56 6.10 tenth puff
6.58 6.02
II. Particulate phaseUnitsMarijuanaTobacco Tl particulate - dry mg 22.7 39.0 Phenol mcg 76.8 138.5 o-Cresol mcg 17.9 24 m- and p-Cresol mcg 54.4 65 Dimethylphenol mcg 6.8 14.4 Catechol mcg 188 328 Cannbidiol mcg 190 D9 THC mcg 820 Cannabinol mcg 400 Nicotine mcg
2850 N-Nitrosonornicotine ng
390 Naphthalene mcg 3.0 1.2 1-Methylnaphthalene mcg 6.1 3.65 2-Methylnaphthalese mcg 3.6 1.4 Benz(a)anthracene ng 75 43 Benzo(a)pyrene ng 31 21.1
Sources cited by the Institute of Medicine:
Hofmann, D., Brunnemann, K.D.,Gori,G.B. and Wynder, E.L. On the carcinogenicity of marijuana smoke, pp 63-81. In Runeckles, V.C. (ed) Recent Advances in Phytochemistry New York: Plenum Publishing Corp., 1975.
Hoffmann, D., Patrianakos, C., Brunneman, K.D., et al. Chromatographic determination of vinyl chloride in tobacco smoke. Anal Chem 48:47-50, 1976.
Brunnemann,K.D., Lee, H.C., and Hoffmann, D. Chemical studies on tobacco smoke. XLVII. On the quantitative analysis of catechols and their reduction. Anal. Lett. 9:939-955, 1976.
Brunnemann, K.D., Yu, L., and Hoffmann, D. Chemical Studies on tobacco somke. XLIX. Gas chromotographic determination of hydrogen cyanide and cynogen in tobacco smoke. J Anal. Toxicol. 1:38-42, 1977.

[OccularFantasm]

that last post didnt post right at all. There was supposed to be a chart, not just mess. feel free to fix/delete or something. sorry bout that