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  1. NTU Theses and Dissertations Repository
  2. 公共衛生學院
  3. 流行病學與預防醫學研究所
請用此 Handle URI 來引用此文件: http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/37347
標題: 三年全國青少年調查的學區特性與飲酒相關性之多層次分析
Multilevel analyses on the relations of school district's characteristics to alcohol drinking in a 3-year national survey of adolescents
作者: I-Chin Lin
林宜瑾
指導教授: 陳為堅(Wei J. Chen)
關鍵字: 青少年,酒精使用,多層次分析,學區,
adolescent,alcohol use,multilevel analysis,school-district,
出版年 : 2008
學位: 碩士
摘要: 目的:在多層次的架構下,探討學區特性對於青少年酒精使用之影響;同時探究學區特性是否能夠解釋青少年飲酒的學區差異。
方法:在2004至2006年,利用多階段隨機群集抽樣的方式選取148個學區、53,597名全國代表性之學校青少年。青少年之酒精使用經驗、社會人口學特性、偏差行為的資訊皆以自我陳報問卷來蒐集。接著利用多層次羅吉斯迴歸分析的統計方式探討學區特性(察知同學酒精使用盛行率、便利商店密度、酒後駕車盛行率)與青少年酒精使用的相關性。
結果:察知同學酒精使用盛行率、便利商店密度、酒後駕車盛行率皆與青少年酒精使用顯著相關。高風險學區青少年相較於低風險學區青少年的酒精使用風險平均增加1.45倍。儘管個人變項可解釋將近70%的學區殘差異質性,此三種區域變項只能進一步地解釋10.20%至12.24%的學區變異。
結論:位在較高察知同學酒精使用盛行率、較高便利商店密度、較高酒後駕車盛行率之學區的青少年有較高的酒精使用勝算。然而,察知同學酒精使用盛行率、便利商店密度、酒後駕車盛行率可解釋的學區變異相對地較有限。
Objective: To examine the effects of school-districts' characteristics on adolescent alcohol use and whether the characteristics of school-districts can explain the school-district differences on adolescent alcohol use under the multilevel framework.
Methods: In 2004-2006, a nationally representative sample of 53,597 school-attending adolescents from 148 school-districts was selected using multistage, random, cluster sampling. Information on adolescents' alcohol use experiences, sociodemographic characteristics, and delinquent behaviors was collected through the self-administered questionnaire. Relations of three school-district characteristics (prevalence of perceived classmate' alcohol use, density of convenience stores, and prevalence of drinking and driving) to adolescent alcohol use were examined by means of multilevel logistic regression analysis.
Results: Prevalence of perceived classmates' alcohol use, density of convenience stores, and prevalence of drinking and driving were significantly associated with current alcohol use among adolescents. The odds on current alcohol use would increase 1.45 times on average for adolescents in school-districts of higher risks comparing to the ones in school-districts with lower risks. While nearly 70% of residual heterogeneity among school-districts could be explained by the individual-level variables, only 10.20% to 12.24% of school-district variances were further explained by the three area-level variables.
Conclusions: Adolescents whose schools located in townships with higher prevalence of perceived classmates' alcohol use, higher density of convenience stores, or higher prevalence of drinking and driving had higher odds of using alcohol. Yet, prevalence of perceived classmates' alcohol use, density of convenience stores, and prevalence of drinking and driving explained relatively limited school-district differences on adolescent alcohol use.
URI: http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/37347
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