Non-national clients in Belgian drug treatment: different profile characteristics compared to Belgian clients

Thursday, 24 October, 2019 - 12:00 to 12:10
Networking zone 3 (N3)


Background: There is little insight in the social position of problem users with a migration background in European and Belgian treatment. The social gradient does however influence (mental) health status, problem use and help-seeking (Whitehead & Dalghren, 2006). Preliminary research in Belgium (Derluyn et al., 2008) found that MEM were significantly more often male, unemployed, less educated and more often referred to ambulant services compared to non-MEM counterparts. In addition, the study demonstrated that MEM in treatment were older, more often burdened by a judicial history and more often in treatment for problems with heroin, cocaine and methadone. The main aim of our study is to analyse whether these differential profile characteristics persisted in 2012-2014.

Methods: Based on a published preliminary treatment demand indicator (TDI) analysis – that documented the underrepresentation of specified MEM populations – presented at Lisbon Addiction 2017 (Blomme et al., 2017), we conducted an analysis of profile characteristics in the same 2012-2014 aggregated datasets. The analysis is based on a dataset including all 54.148 treatment episodes registered in Belgian drug treatment between 2012-2014, collected and processed for TDI-registration by the Belgian Reitox National Focal Point. Craemer’s V and indicative odds ratios (OR) (95% confidence intervals, P < 0.05) were calculated to examine associations between specified profile characteristics (gender, primary substance, education, labour, age, living situation) and nationality (Belgian, European and third country non-nationals).

Results: There was only a significant relation between nationality (Belgian, non-Belgian) and gender (Cramer’s V: 0.74). The primary substance also differed but was not significantly different: the odds of non-Belgian clients being admitted for opioid use were greater than the odds for Belgian clients (OR:6.90-95%CI:6.34-7.50). In turn, the odds for Belgian clients presenting to treatment with stimulants (OR:7.41-95%CI: 4.91-11.20) and alcohol (0R:7.48-95%CI: 6.55-8.53) as a primary substance were higher compared to non-Belgian clients. The following odds for non-national clients were also significant: being categorised at intake as a housemaker (OR:1.6-95%CI:1.47-1.77), unemployed (OR:1.12-95%CI: 1.09-1.30) and ‘never attended school’ (OR:6.14-95%CI:4.99-7.54) compared to Belgian clients. Concerning age, the odds of Belgian clients being aged less than 20 years old were higher compared to non-national clients (OR:2.60-95%CI:2.08-3.24). The odds of non-national clients to be aged over 35 years old were higher compared to Belgian clients (OR:1.44-95%CI:1.34-1.54). Lastly, the odds of non-nationals having an unstable living situation was greater than the odds for Belgian clients (OR:2.66-95%CI:2.32-3.06).

Conclusion: These results could preliminary confirm differential profile characteristics of non-national compared to Belgian clients but do not uncover directionality nor confounding variables. During the presentation we present all odds, absolute numbers and contextualise by means of the national drug reports and population statistics. These results should be dealt with cautiously because of limitations linked to dataset and variable quality that will be highlighted during the presentation. These results do however demonstrate that more research into the social gradient of MEM clients is indispensable and could inform more effective treatment practice.




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