Using Latent class analysis (LCA) to analyze patterns of drug use in a population of illegal opioid users

The University of Calgary, Calgary, Alberta, Canada
Drug and Alcohol Dependence (Impact Factor: 3.42). 05/2007; 88(1):1-8. DOI: 10.1016/j.drugalcdep.2006.08.029
Source: PubMed


The objective of this paper is to empirically determine a categorization of illegal opioid users in Canada in order to describe and analyze drug use patterns within this population.
Drug use patterns of 679 eligible illegal opioid users outside treatment from the OPICAN study, a pan-Canadian cohort (recruited March to December, 2002) involving the cities of Toronto, Montreal, Vancouver, Edmonton and Quebec City, were empirically examined using latent class analysis. These latent classes were then further analyzed for associations using chi-square and t-test statistics.
The opioid and other drug user sample surveyed were categorized into three latent classes. Class 1 (N=256) was characterized by the use of Tylenol 3 and benzodiazepines along with high levels of depression and self-reported pain. Class 2 (N=68) was described by the non-injection use of both heroin and crack while having a high level of homelessness. Class 3 (N=344) was shown to consist of injection drug users of heroin and cocaine exhibiting the highest levels of HIV and Hepatitis C infections amongst the classes.
Using latent class analysis we found distinct patterns of drug use amongst illegal opioid users differing in terms of type of drugs co-used, social context, and co-morbid pathologies. These data may be useful as the empirical basis for the planning of specific prevention and treatment interventions.

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Available from: Mark W Tyndall, Sep 30, 2015
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    • "To date, at least one study has used LCA to distinguish subtypes of drug users beyond pharmacological properties, based on the route and type of drugs. This study was conducted in Canada and found three classes: one class that consisted of high use of Tylenol 3 and benzodiazepine with a high rate of depression and pain, a second included non-injectors and crack smokers, and a third consisted of injection drug users (IDUs) with a high rate of HIV and Hepatitis C (Monga et al., 2007). An extension of this study using a more recent sample found eight classes (Patra et al., 2009). "
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    ABSTRACT: We empirically identified subtypes of inner-city users of heroin and cocaine based on type of drug used and route of administration. The sample was recruited from the communities in Baltimore, MD (SHIELD study) and consisted of 1061 participants who used heroin and or cocaine in the past 6 months on a weekly basis or more. Latent class analysis (LCA) was used to identify subtypes of drug users based on type of drug and route of administration. Logistic regression was used to compare the subtypes on depressive symptoms, injection risk and drug network compositions. Inner-city drug users were classified into five subtypes: three subtypes of injection drug users (IDUs) [heroin injecting (n=134; 13%), polydrug and polyroute (n=88, 8%), and heroin and cocaine injecting (n=404, 38%)], and two subtypes with low proportions of IDUs (LIDUs) [heroin snorting (n=275, 26%) and crack smoking (n=160; 14%)]. The polydrug and polyroute subtype had the highest depressive symptoms risk among all subtypes. Injection risk was lowest in the heroin injecting subtype and significantly differed from heroin and cocaine injecting subtype. The IDU subtypes also varied in the drug network compositions. The LIDU subtypes had similar depressive symptoms risk but vastly differed in the drug network compositions. Subgroups of inner-city cocaine and heroin users based on type and route of administration differed in their depressive symptoms, injection risk and drug network compositions. Future studies should longitudinally examine factors associated with transitioning across these subtypes to better inform prevention and treatment efforts.
    Drug and alcohol dependence 04/2011; 118(2-3):237-43. DOI:10.1016/j.drugalcdep.2011.03.030 · 3.42 Impact Factor
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    • "Those studies that have reported sex differences found that females were younger (Chen, Shu, Liang, Hung, & Lin, 1998; Chiang, et al., 2007; Williamson, Darke, Ross, & Teesson, 2007) and had more suicide attempts and fewer completed suicides (Darke & Ross, 2002; Darke, Ross, Lynskey, & Teesson, 2004; Darke, Williamson, Ross, & Teesson, 2005); different injecting behaviours (Hoda, Kerr, Li, Montaner, & Wood, 2008); less education and employment (Chen, et al., 1998; Chiang, et al., 2007); a younger onset of heroin use (Chen, et al., 1998); more dysfunctional families and exposure to more unfavourable social factors (Chatham, Hiller, Rowan-Szal, Joe, & Simpson, 1999; Chiang, et al., 2007); greater health service utilization (Darke, Ross, Teesson, & Lynskey, 2003; Fletcher, Broome, Delany, Shields, & Flynn, 2003); higher standardised mortality ratios (Rehm, et al., 2005); more psychological problems (Chatham, et al., 1999; Mills, Teesson, Darke, Ross, & Lynskey, 2004); and were more likely to sustain abstinence after treatment (Darke, et al., 2007a) than men. The evidence regarding sex differences in polysubstance use and dependence amongst heroin users is mixed, with one study finding no differences in the number of current or lifetime diagnoses (Darke & Ross, 1997), another found higher levels of polydrug use amongst male heroin users (Darke & Hall, 1995) and another finding no sex differences in class memberships based on polysubstance use (Monga, et al., 2007). "
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    ABSTRACT: To examine differences in the characteristics and histories of male and female dependent heroin users, and in the clinical characteristics associated with multiple substance dependence diagnoses. 1513 heroin dependent participants underwent an interview covering substance use and dependence, psychiatric history, child maltreatment, family background, adult violence and criminal history. Family background, demographic and clinical characteristics were analysed by sex. Ordinal regression was used to test for a relationship between number of substance dependence diagnoses and other clinical variables. Women were more likely to experience most forms of child maltreatment, to first use heroin with a boyfriend or partner, to experience ongoing adult violence at the hands of a partner, and to have a poorer psychiatric history than men. Males had more prevalent lifetime substance dependence diagnoses and criminal histories and were more likely to meet the criteria for ASPD. Predictors of multiple substance dependence diagnoses for both sexes were mental health variables, antisocial behaviour, childhood sexual abuse, victim of adult violence, younger age at first cannabis use and overdose. As the number of dependence diagnoses increased, clinical and behavioural problems increased. Childhood emotional neglect was related to increasing dependence diagnoses for females but not males, whereas PTSD was a significant predictor for males but not females. Mental health problems, other substance dependence, childhood and adult trauma were common in this sample, with sex differences indicating different treatment needs and possible different pathways to heroin dependence for men and women.
    Addictive behaviors 01/2011; 36(1-2):27-36. DOI:10.1016/j.addbeh.2010.08.008 · 2.76 Impact Factor
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    • "Recent national surveys also show that most (62%) new nonmedical opioid users are adults aged ≥ 18 years (SAMHSA, 2009). To date, adult studies have typically examined regional samples of drug users (Havens et al., 2009; Monga et al., 2007) and treatment-seeking patients (Banta-Green et al., 2009; Cicero et al., 2008; Green et al., 2009). While these studies have shown that drug use and psychiatric symptoms are relatively prevalent among nonmedical opioid users, information regarding specific DSM-IV substance use disorders (SUDs) and other mental disorders is often not available. "
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    ABSTRACT: To identify subtypes of nonmedical opioid users, gender variations in psychiatric disorders, and quality of life in a representative sample of adults. Analyses of data from the 2001-2002 National Epidemiologic Survey on Alcohol and Related Conditions (N=43,093). Latent class analysis (LCA) and multinomial logistic regression procedures examined subtypes of nonmedical opioid users. Approximately 5% (n=1815) of adults used nonmedical opioids. LCA identified four subtypes: opioid-marijuana users (33%), opioid-other prescription drug users (9%), opioid-marijuana-hallucinogen users (28%), and opioid-polydrug users (30%). Subtypes were distinguished by race/ethnicity, gender, familial substance abuse, personal history of substance abuse treatment, and patterns of psychiatric disorders. Whites and men had increased odds of being in the opioid-polydrug and opioid-marijuana-hallucinogen subtypes. The opioid-other prescription drug use subtype had disproportionately affected women who were characterized by high rates of mood/anxiety disorders and low quality of life. Across all subtypes, women and men had similarly problematic substance use disorders; however, women had more major depression and disability in the mental health domain. The generally high prevalence of psychiatric disorders among nonmedical opioid users, particularly women, underscores the need for comprehensive assessment and coordinated delivery of services to match needs with treatment, as well as continued monitoring of trends in opioid use and related problems.
    Drug and alcohol dependence 11/2010; 112(1-2):69-80. DOI:10.1016/j.drugalcdep.2010.05.013 · 3.42 Impact Factor
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