Patients admitted to treatment for substance use disorder in Norway: a population-based case-control study of socio-demographic correlates and comparative analyses across substance use disorders.

BACKGROUND: Improved knowledge regarding socio-demographic correlates of people with substance use disorders (SUDs) is essential to better plan and provide adequate services for SUD patients and their families, and to improve our understanding of the complex mechanisms underlying progression into and development of various SUDs. This study aimed to: i) describe demographic, economic, and social correlates of people with SUDs in comparison with those of the general population and ii) compare these correlates across SUDs from licit versus illicit substances, as well as across specific SUDs. METHODS: A national population-based case-control study included all SUD patients enrolled in specialized drug treatment in Norway in 2009-2010 (N = 31 245) and a population control sample, frequency-matched on age and gender (N = 31 275). Data on education level, labour market participation, income level and sources, and family/living arrangement were obtained by linkages to national registers. RESULTS: Demographic, economic, and social correlates of SUD patients differed substantially from those of the general population, and across specific SUDs. Among SUD patients, those with illicit - as compared to licit - SUDs were younger (mean quotient = 0.72 [0.71-0.72]), more often had low education level (RR = 1.68 [1.63-1.73]), were less often in paid work (RR = 0.74 [0.72-0.76]) and had lower income (mean quotient = 0.61 [0.60-0.62]). Comparison of patients with different SUD diagnoses revealed substantial demographic differences, including the relatively low mean age among cannabis patients and the high share of females among sedatives/hypnotics patients. Opioid patients stood out by being older, and more often out of work, receiving social security benefits, and living alone. Cocaine and alcohol patients were more often better educated, included in the work force, and had a better financial situation. CONCLUSION: Findings revealed substantial and important differences in socio-demographic correlates between SUD patients and the general population, between SUD patients with illicit and with licit substance use, and across specific SUD patient groups.

Who seeks treatment for cannabis use? Registered characteristics and physical, psychological and psychosocial problem indicators among cannabis patients and matched controls.

BACKGROUND: There has been an absolute and relative increase in the number of patients with cannabis-related disorders as the principal diagnosis in many countries in recent years. Cannabis is now the most frequently mentioned problem drug reported by new patients in Europe, and cannabis patients constituted one third of all drug treatment patients in 2015. There is limited knowledge with regard to patient characteristics, the extent and types of health and psychosocial problems, as well as their association with long-term outcomes. METHODS: We analysed indicators of physical, psychological and psychosocial problems of all patients admitted to treatment for cannabis use in Norway in 2009 and 2010 using register data and observed them to the end of 2013. Patient characteristics and outcomes were compared to a randomly drawn control group with corresponding age and gender distribution. Using logistic regression of prospective data, we studied associations between baseline characteristics and work and study status in 2013. RESULTS: Cannabis patients tended to be relatively young and the large majority were male. They had parents who were less highly educated compared to controls, while there was no difference in migration background. In addition to an increased risk of premature death, nearly half of the patients received a secondary psychological diagnosis and a similar proportion received an additional substance use diagnosis during the 4-5 years of study follow-up. The cannabis patients were less educated than the control group and also less likely to be studying or working at the end of the study period. Entering treatment at a young age, having completed more than secondary education, having a highly-educated mother and not having a secondary diagnosis were factors that were positively associated with being in education or employment at the end of follow-up. CONCLUSIONS: Data covering the entire Norwegian population of patients admitted primarily for cannabis-related problems showed comprehensive and complex patterns of physical, psychological and psychosocial problems. The prevalence and extent of these problems varied markedly from those of the general population. Work and study outcomes following treatment depended on the seriousness of the condition including co-morbidity as well as social capital.