Center for Primary Health Care Research, Lund University, Jan Waldenströmsgata 35, CRC, building 28, floor 11, entrance 72, Malmö University Hospital, Malmö, S-205 02, Sweden.
Center for Primary Health Care Research, Lund University, Jan Waldenströmsgata 35, CRC, building 28, floor 11, entrance 72, Malmö University Hospital, Malmö, S-205 02, Sweden.
Drug Alcohol Depend. 2014 Jan 1;134:355-361. doi: 10.1016/j.drugalcdep.2013.11.011. Epub 2013 Nov 19.
The societal consequences of drug abuse (DA) are severe and well documented, the World Health Organization recommending tracking of population trends for effective policy responses in treatment of DA and delivery of health care services. However, to correctly identify possible sources of DA change, one must first disentangle three different time-related influences on the need for treatment due to DA: age effects, period effects and cohort effects.
We constructed our main Swedish national DA database (spanning four decades) by linking healthcare data from the Swedish Hospital Discharge Register to individuals, which included hospitalisations in Sweden for 1975-2010. All hospitalized DA cases were identified by ICD codes. Our Swedish national sample consisted of 3078,129 men and 2921,816 women. We employed a cross-classified multilevel logistic regression model to disentangle any net age, period and cohort effects on DA hospitalization rates.
We found distinct net age, period and cohort effects, each influencing the predicted probability of hospitalisation for DA in men and women. Peak age for DA in both sexes was 33-35 years; net period effects showed an increase in hospitalisation for DA from 1996 to 2001; and in birth cohorts 1968-1974, we saw a considerable reduction (around 75%) in predicted probability of hospitalisation for DA.
The use of hospital admissions could be regarded as a proxy of the population's health service use for DA. Our results may thus constitute a basis for effective prevention planning, treatment and other appropriate policy responses.
药物滥用（DA）的社会后果严重且有据可查，世界卫生组织建议跟踪人口趋势，以便对 DA 进行有效的政策应对，并提供医疗保健服务。然而，要正确识别 DA 变化的可能来源，首先必须理清由于 DA 而导致的治疗需求的三种不同的与时间相关的影响：年龄效应、时期效应和队列效应。
我们通过将瑞典医院出院登记处的医疗数据与个人相关联，构建了我们的主要瑞典全国 DA 数据库（跨越四个十年），其中包括 1975 年至 2010 年在瑞典的住院治疗。所有因 DA 住院的病例均通过 ICD 代码识别。我们的瑞典全国样本包括 3078129 名男性和 2921816 名女性。我们采用交叉分类多水平逻辑回归模型来分离 DA 住院率的任何净年龄、时期和队列效应。
我们发现了明显的净年龄、时期和队列效应，这些效应都影响了男女 DA 住院率的预测概率。两性 DA 的高峰年龄均为 33-35 岁；净时期效应显示，1996 年至 2001 年 DA 住院人数增加；在 1968-1974 年出生的队列中，我们看到 DA 住院预测概率大幅下降（约 75%）。
医院入院率可被视为人群因 DA 而使用卫生服务的一个指标。因此，我们的研究结果可以为有效的预防规划、治疗和其他适当的政策应对提供依据。
