Literature DB >> 16736055

Modeling time-location patterns of inner-city high school students in New York and Los Angeles using a longitudinal approach with generalized estimating equations.

B Rey Decastro1, Sonja N Sax, Steven N Chillrud, Patrick L Kinney, John D Spengler.   

Abstract

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 having an after school job (1.29 [1.07:1.56]).

Mesh:

Year:  2006        PMID: 16736055     DOI: 10.1038/sj.jes.7500504

Source DB:  PubMed          Journal:  J Expo Sci Environ Epidemiol        ISSN: 1559-0631            Impact factor:   5.563


  4 in total

1.  Distributions and determinants of time spent outdoors among school-age children in China.

Authors:  Fei Gao; Qian Guo; Beibei Wang; Suzhen Cao; Ning Qin; Liyun Zhao; Chunrong Jia; Xiaoli Duan
Journal:  J Expo Sci Environ Epidemiol       Date:  2022-01-04       Impact factor: 5.563

2.  Longitudinal variability of time-location/activity patterns of population at different ages: a longitudinal study in California.

Authors:  Xiangmei Wu; Deborah H Bennett; Kiyoung Lee; Diana L Cassady; Beate Ritz; Irva Hertz-Picciotto
Journal:  Environ Health       Date:  2011-09-20       Impact factor: 5.984

3.  Ventilation and Air Quality in Student Dormitories in China: A Case Study during Summer in Nanjing.

Authors:  Zhe Yang; Jialei Shen; Zhi Gao
Journal:  Int J Environ Res Public Health       Date:  2018-06-25       Impact factor: 3.390

4.  A systematic approach to estimating the effectiveness of multi-scale IAQ strategies for reducing the risk of airborne infection of SARS-CoV-2.

Authors:  Jialei Shen; Meng Kong; Bing Dong; Michael J Birnkrant; Jianshun Zhang
Journal:  Build Environ       Date:  2021-04-30       Impact factor: 6.456

  4 in total

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