首页> 外文期刊>Journal of exposure science & environmental epidemiology >Modeling time-location patterns of inner-city high school students in New York and Los Angeles using a longitudinal approach with generalized estimating equations.
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Modeling time-location patterns of inner-city high school students in New York and Los Angeles using a longitudinal approach with generalized estimating equations.

机译:使用具有广义估计方程的纵向方法,对纽约和洛杉矶的内城区高中学生的时间定位模式进行建模。

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The TEACH Project obtained subjects' time-location information as part of its assessment of personal exposures to air toxics for high school students in two major urban areas. This report uses a longitudinal modeling approach to characterize the association between demographic and temporal predictors and the subjects' time-location behavior for three microenvironments--indoor-home, indoor-school, and outdoors. Such a longitudinal approach has not, to the knowledge of the authors, been previously applied to time-location data. Subjects were 14- to 19-year-old, self reported non-smokers, and were recruited from high schools in New York, NY (31 subjects: nine male, 22 female) and Los Angeles, CA (31 subjects: eight male, 23 female). Subjects reported their time-location in structured 24-h diaries with 15-min intervals for three consecutive weekdays in each of winter and summer-fall seasons in New York and Los Angeles during 1999-2000. The data set contained 15,009 observations. A longitudinal logistic regression model was run for each microenvironment where the binary outcome indicated the subject's presence in a microenvironment during a 15-min period. The generalized estimating equation (GEE) technique with alternating logistic regressions was used to account for the correlation of observations within each subject. The multivariate models revealed complex time-location patterns, with subjects predominantly in the indoor-home microenvironment, but also with a clear influence of the school schedule. The models also found that a subject's presence in a particular microenvironment may be significantly positively correlated for as long as 45 min before the current observation. Demographic variables were also predictive of time-location behavior: for the indoor-home microenvironment, having an after school job (OR=0.67 [95% confidence interval: 0.54:0.85]); for indoor-school, living in New York (0.42 [0.29:0.59]); and for outdoor, being 16-year-old (0.80 [0.67:0.96]), 17-year-old (0.71 [0.54:0.92]), and havingan after school job (1.29 [1.07:1.56]).
机译:TEACH项目获得了受试者的时间信息,作为对两个主要城市地区的高中生个人接触空气中毒物评估的一部分。本报告使用纵向建模方法来表征人口统计和时间预测因素与受试者在三种微环境(室内,室内,学校和室外)的时间定位行为之间的关联。据作者所知,这种纵向方法以前并未应用于时间位置数据。受试者为14至19岁,自我报告为不吸烟者,是从纽约州纽约市(31名受试者:9名男性,22名女性)和加利福尼亚州洛杉矶市(31名受试者:8名男性, 23位女性)。在1999-2000年期间的纽约和洛杉矶,每个冬季和夏季的秋季,受试者连续三个工作日以15分钟为间隔,每隔15分钟记录一次结构化的24小时日记中的时间位置。数据集包含15,009个观测值。针对每个微环境运行纵向logistic回归模型,其中二元结果表明受试者在15分钟内存在于微环境中。具有交替逻辑回归的广义估计方程(GEE)技术用于说明每个主题内观察值的相关性。多元模型显示了复杂的时间-位置模式,对象主要位于室内微环境中,但也明显影响了学校的日程安排。这些模型还发现,在当前观察之前的45分钟之内,受试者在特定微环境中的存在可能会显着正相关。人口统计学变量也可预测时间行为:对于室内微环境,有放学后的工作(OR = 0.67 [95%置信区间:0.54:0.85]);对于住在纽约的室内学校(0.42 [0.29:0.59]);对于户外活动,年龄为16岁(0.80 [0.67:0.96]),17岁(0.71 [0.54:0.92])和课余工作(1.29 [1.07:1.56])。

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