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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 an...

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Detalles Bibliográficos
Autores principales: Amundsen, Ellen J., Bretteville-Jensen, Anne Line, Rossow, Ingeborg
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9020072/
https://www.ncbi.nlm.nih.gov/pubmed/35443672
http://dx.doi.org/10.1186/s12889-022-13199-5
Descripción
Sumario: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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12889-022-13199-5.