Trends in incidence and risk markers of student emergency department visits with alcohol intoxication in a US public university - A longitudinal data linkage study
Trends in incidence and risk markers of student emergency department visits with alcohol intoxication in a US public university - A longitudinal data linkage study
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DOI：
10.1016/j.drugalcdep.2018.03.050
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发表时间：
2018-07-01
影响因子：
4.2
通讯作者：
Holstege, Christopher P.
中科院分区：
文献类型：
--
作者：
Duc Anh Ngo;Rege, Saumitra V.;Holstege, Christopher P.
背景：旨在检查与急诊科 (ED) 就诊相关的学生酒精中毒的发病率和社会人口统计、组织、学术和临床风险标志物的趋势。方法：将 2009 年至 2015 年的学生入院数据与初级医疗保健数据以及每年首次（索引）入组后一年内使用 ICD-9 代码识别的后续 ED 就诊数据相关联。计算每万人年的发病率。 Cox 比例风险回归提供了学生特征与随后因酒精中毒就诊的 177,128 名学生中的关联风险比 (HR) (95% CI)。结果：在 177,128 名 16-49 岁的学生中，889 人至少接受过一次酒精中毒就诊，导致发病率为 59/10,000 人年。发病率从2009-10学年的45/10,000人年线性增加到2014-15学年的71/10,000人年（p < 0.001）。与此结果相关的学生特征的 HR (95% CI) 为： 男性（相对于女性）：1.38 (1.21-1.58)； 20岁以下（相对于25-30岁）：3.36（1.99-5.65）；西班牙裔（相对于亚洲裔）学生：1.61（1.16-2.25）；父母税收依赖性：1.49（1.16-1.91）；希腊终身会员：1.96（1.69-2.26）；运动队成员：0.51 (0.36-0.72)；本科生（与研究生）学生：2.65 (1.88-3.74)。去年饮酒或被诊断患有抑郁症或焦虑症也是重要的预测因素。对校园 p 相关因素的调整极大地削弱了学生社会人口特征与这一结果之间的关联。结论：将学生入学数据与 ED 临床数据联系起来可以帮助监测与 ED 就诊相关的学生酒精中毒情况，并确定风险较高的学生群体，随后可以针对这些学生群体进行干预工作。
Background: To examine the trends in incidence and socio-demographic, organizational, academic, and clinical risk markers of student alcohol intoxication associated with emergency department (ED) visits.Methods: Student admission data from 2009 to 2015 were linked to primary healthcare data and subsequent ED visits with alcohol intoxication identified using ICD-9 codes within one year following the first (index) enrollment each year. Incidence rate per 10,000 person-years was calculated. Cox proportional hazard regression provided adjusted hazard ratios (HR) (95 % CIs) for the association between student characteristics and subsequent ED visits with alcohol intoxication.Results: Of 177,128 students aged 16-49 enrolled, 889 had at least one ED visit with alcohol intoxication, resulting in an incidence rate of 59/10,000 person-years. Incidence increased linearly from 45/10,000 person years in 2009-10 to 71/10,000 person-years in the 2014-15 academic year (p < 0.001). HRs (95%CIs) of student characteristics associated with this outcome were: males (versus females): 1.38 (1.21-1.58); below 20 years of age (versus 25-30 years): 3.36 (1.99-5.65); Hispanic (versus Asian) students: 1.61 (1.16-2.25); parental tax dependency: 1.49 (1.16-1.91); Greek life member: 1.96 (1.69-2.26); member of an athletic team: 0.51 (0.36-0.72); undergraduate (versus graduate) students: 2.65 (1.88-3.74). Past year alcohol use or having been diagnosed with depression or anxiety were also significant predictors. Adjustments for campus p-related factors strongly attenuated the associations between student socio-demographic characteristics with this outcome.Conclusions: Linking student admission data with ED clinical data can help monitor student alcohol intoxication associated with ED visits and identify student groups at higher risk who subsequently can be targeted for intervention efforts.