Socio-demographic risk factors for alcohol and drug dependence: The 10-year follow-up of the national comorbidity survey

National Scientific Research Center (CNRS 5231), Bordeaux, France.
Addiction (Impact Factor: 4.74). 07/2009; 104(8):1346-55. DOI: 10.1111/j.1360-0443.2009.02622.x
Source: PubMed


Continued progress in etiological research and prevention science requires more precise information concerning the specific stages at which socio-demographic variables are implicated most strongly in transition from initial substance use to dependence. The present study examines prospective associations between socio-demographic variables and the subsequent onset of alcohol and drug dependence using data from the National Comorbidity Survey (NCS) and the NCS Follow-up survey (NCS-2).
The NCS was a nationally representative survey of the prevalence and correlates of DSM-III-R mental and substance disorders in the United States carried out in 1990-2002. The NCS-2 re-interviewed a probability subsample of NCS respondents a decade after the baseline survey. Baseline NCS socio-demographic characteristics and substance use history were examined as predictors of the first onset of DSM-IV alcohol and drug dependence in the NCS-2.
A total of 5001 NCS respondents were re-interviewed in the NCS-2 (87.6% of baseline sample).
Aggregate analyses demonstrated significant associations between some baseline socio-demographic variables (young age, low education, non-white ethnicity, occupational status) but not others (sex, number of children, residential area) and the subsequent onset of DSM-IV alcohol or drug dependence. However, conditional models showed that these risk factors were limited to specific stages of baseline use. Moreover, many socio-demographic variables that were not significant in the aggregate analyses were significant predictors of dependence when examined by stage of use.
The findings underscore the potential for socio-demographic risk factors to have highly specific associations with different stages of the substance use trajectory.

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Available from: Louisa Degenhardt, Oct 05, 2015
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    • "ach individual ' s comorbid status . All ' Comorbid ' participants were found to have episodes of alcohol use disorder and mental health disorder occurring within 12 months of each other , indicating temporal overlap . Socio - economic measures : SES measures were investigated for association with comorbidity group according to previous findings ( Swendsen et al . , 2009 ; Najman et al . , 2010 ; Australian Institute of Health and Welfare , 2012 ; Pulkki - Raback et al . , 2012 ) . Family income , parental employment and parental education were assessed at baseline and coded binomially for disadvantage as below . Family income was recorded as less than $ 2600pa , < $ 5200pa , < $ 10 , 400pa , < $ 15 , 6"
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    ABSTRACT: Background: Alcohol and mental health disorders are highly prevalent in the general population, with co-occurrence recognised as a major public health issue. Socio-economic factors are frequently associated with both disorders but their temporal association is unclear. This paper examines the association between prenatal socio-economic disadvantage and comorbid alcohol and mental health disorders at young adulthood. Methods: An unselected cohort of women was enrolled during early pregnancy in the large longitudinal Mater-University of Queensland Study of Pregnancy (MUSP), at the Mater Misericordiae Public Hospital in Brisbane, Australia. The mothers and their offspring were followed over a 21 year period. Offspring from the MUSP birth cohort who provided full psychiatric information at age 21 and whose mothers provided socioeconomic information at baseline were included (n=2399). Participants were grouped into no-disorder, mental health disorder only, alcohol disorder only or comorbid alcohol and mental health disorders according to DSM-IV diagnoses at age 21 as assessed by the Composite International Diagnostic Interview. We used multivariate logistic regression analysis to compare associations of disorder group with single measures of prenatal socio-economic disadvantage including family income, parental education and employment, and then created a cumulative scale of socioeconomic disadvantage. Results: Greater socio-economic disadvantage was more strongly associated with comorbidity (OR 3.36; CI95 1.37, 8.24) than with single disorders. This relationship was not fully accounted for by maternal mental health, smoking and drinking during pregnancy. Conclusion: Multiple domains of socio-economic disadvantage in early life are associated with comorbid alcohol and mental health disorders.
    Drug and Alcohol Dependence 09/2014; 142. DOI:10.1016/j.drugalcdep.2014.06.011 · 3.42 Impact Factor
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    • "This shift is unlikely to happen as long as the present view of alcohol dependence as a very complicated disorder to manage prevails. Previous studies of the correlates of alcohol dependence in the United States have shown that socio-economic risk factors for dependence vary as a function of DSM-IV symptom severity, which suggests that our findings have relevance outside Sweden (Grant, 1997b; Swendsen et al., 2009). Previous investigations in the US and Australia have also confirmed that most alcohol dependent individuals do not seek treatment due to the stigma associated with specialist clinics, highlighting the importance of brief interventions in general health care settings (Kalaydjian et al., 2009; Teesson et al., 2010). "
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    ABSTRACT: The severity of alcohol dependence can be estimated by the number of DSM-IV criteria that are fulfilled for this disorder. This paper describes the proportions in a general population sample that meet different numbers of diagnostic criteria for alcohol dependence and their association with drinking and social background factors. Data came from a random, cross-sectional, self-report survey of adults from 12 Swedish communities. 28,800 persons, age 19-70, were surveyed through postal questionnaires. 14,706 questionnaires (51%) could be used for analysis. Alcohol dependence was assessed by questions relating to the seven DSM-IV criteria for alcohol dependence. Alcohol consumption and social background factors were examined in relation to alcohol dependence. A total of 73.8% of the general population fulfilled no criteria for alcohol dependence; 4.0% reported 3 or more criteria and qualified for the diagnosis of alcohol dependence. There were trends toward an increasing number of dependence criteria with increasing consumption levels and negative social background factors. The majority of people with alcohol dependence however did not drink at the highest consumption levels, did not live alone, and were not unemployed. Given the current definition of alcohol dependence the majority of people have few criteria fulfilled (3 or 4) and few social problems. This has important implications for treatment as dependence with low severity may require less treatment and less specialist involvement.
    Alcohol (Fayetteville, N.Y.) 10/2012; 47(1). DOI:10.1016/j.alcohol.2012.10.001 · 2.01 Impact Factor
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    • "It is a proxy indicator for risky behaviors (such as cigarette smoking, drug smuggling, and serious fights) in school ages, and shows a predisposing personality of the involved person to risky behaviors such as injecting drugs.[19] Two studies conducted in Canada and United States, showed that one of the factors associated with IDU was low education.[2021] "
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    ABSTRACT: This study aims to identify the differences between Injecting Drug Users (IDUs) and non-IDUs, with regard to some potential factors. This could be useful to design effective interventions for harm reduction, which is one of the priority areas in reducing the burden of addiction. Sixty cases and 60 controls participated in this pair-matched case-control study, which was conducted in Tehran. The cases were IDUs who were asked to introduce two friends; one IDU and the other non-IDU as the paired control. In addition to demographic variables, onset age of cigarette smoking, dropping out of school, imprisonment, history of being sexually abused for money, and family history of using illegal drugs were obtained from the cases and controls via an interview. Pair Odds Ratio (OR) was estimated through McNemar and conditional multivariable logistic regression analysis. Eighty-three % of the IDUs and 92% the controls were male. The mean for onset age of cigarette smoking was 16 in the cases and 20 in the controls, which was significantly different between cases and controls (P<0.001). In the multivariate analysis, dropping out from school was significantly different between cases and controls (OR=4.22 95% CI: 2.23 - 14.0). Imprisonment was more frequent in IDUs compared to non-IDUs (OR=3.70 95% CI: 1.09 - 11.08). The cases had more sexual relationship for earning money compared to the controls (OR=3.14 95% CI: 1.24 - 13.70). Onset age of cigarette smoking was significantly (P<0.001) sooner in the IDUs compared to the non-IDUs (15.9 and 20.1 years, respectively). IDUs reported 5.5 times more that non-IDUs of having an addict in their family (P value=0.04). The finding of this study can be useful in identifying the persons who are at risk of IDU. Therefore, people who involve with risk factors recognized in this study should be triggered for harm reduction prevention strategies.
    International journal of preventive medicine 06/2012; 3(6):414-9.
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