STUDY OBJECTIVE: To determine the distribution of opioid use prevalence in small areas and its relation with socioeconomic indicators. DESIGN: Capture-recapture was applied using data from the Barcelona Drug Information System for 1993 (treatment demands, hospital emergency room visits, deaths from heroin acute adverse reaction and pre-trial prison admissions). To avoid dependence between sources, a log-linear regression model with interactions was fitted. For small neighbourhoods, where capture-recapture estimates were not obtainable, the Heroin Problem Index (HPI) was used to predict prevalence rates from a regression model. The correlation between estimated opioid use prevalence by neighbourhoods and their socioeconomic level was computed. MAIN RESULTS: The city's estimated prevalence was 12.9 opioid addicts per 1000 inhabitants aged 15 to 44 years (95% CI: 10.1, 17.2), which represents 9176 persons. The highest rate was found in the inner city neighbourhood. Comparing rates obtained for each neighbourhood with their unemployment rates, a high correlation coefficient was obtained (r = 0.80, p < 0.001). CONCLUSION: The main contribution of this study is that of combining capture-recapture with the HPI to produce small area prevalence estimates, which would not have been possible using only one method. Areas with higher socioeconomic status showed proportionally low addiction prevalences, but in depressed areas, prevalences varied widely.
STUDY OBJECTIVE: To determine the distribution of opioid use prevalence in small areas and its relation with socioeconomic indicators. DESIGN: Capture-recapture was applied using data from the Barcelona Drug Information System for 1993 (treatment demands, hospital emergency room visits, deaths from heroin acute adverse reaction and pre-trial prison admissions). To avoid dependence between sources, a log-linear regression model with interactions was fitted. For small neighbourhoods, where capture-recapture estimates were not obtainable, the Heroin Problem Index (HPI) was used to predict prevalence rates from a regression model. The correlation between estimated opioid use prevalence by neighbourhoods and their socioeconomic level was computed. MAIN RESULTS: The city's estimated prevalence was 12.9 opioid addicts per 1000 inhabitants aged 15 to 44 years (95% CI: 10.1, 17.2), which represents 9176 persons. The highest rate was found in the inner city neighbourhood. Comparing rates obtained for each neighbourhood with their unemployment rates, a high correlation coefficient was obtained (r = 0.80, p < 0.001). CONCLUSION: The main contribution of this study is that of combining capture-recapture with the HPI to produce small area prevalence estimates, which would not have been possible using only one method. Areas with higher socioeconomic status showed proportionally low addiction prevalences, but in depressed areas, prevalences varied widely.
Authors: Ana M Novoa; Glòria Pérez; Albert Espelt; Cynthia Echave; Patricia G de Olalla; M Jesús Calvo; Maribel Pasarín; Èlia Diez; Carme Borrell; M Jesús Calvo; Berta Cormenzana; Imma Cortés; Èlia Diez; Cynthia Echave; Albert Espelt; Patrícia G de Olalla; Josep Gòmez; Ana M Novoa; Montserrat Pallarès; Glòria Pérez; Maica Rodríguez-Sanz Journal: J Urban Health Date: 2018-10 Impact factor: 3.671