Modeling Associations between Principals’ Reported Indoor Environmental Quality and Students’ Self-Reported Respiratory Health Outcomes Using GLMM and ZIP Models
2016
Oluyemi Toyinbo | Markus Matilainen | Mari Turunen | Tuula Putus | Richard Shaughnessy | Ulla Haverinen-Shaughnessy
Background: The aim of this paper was to examine associations between school building characteristics, indoor environmental quality (IEQ), and health responses using questionnaire data from both school principals and students. Methods: From 334 randomly sampled schools, 4248 sixth grade students from 297 schools participated in a questionnaire. From these schools, 134 principals returned questionnaires concerning 51 IEQ related questions of their school. Generalized linear mixed models (GLMM) were used to study the associations between IEQ indicators and existence of self-reported upper respiratory symptoms, while hierarchical Zero Inflated Poisson (ZIP)—models were used to model the number of symptoms. Results: Significant associations were established between existence of upper respiratory symptoms and unsatisfactory classroom temperature during the heating season (ORs 1.45 for too hot and cold, and 1.27 for too cold as compared to satisfactory temperature) and dampness or moisture damage during the year 2006–2007 (OR: 1.80 as compared to no moisture damage), respectively. The number of upper respiratory symptoms was significantly associated with inadequate ventilation and dampness or moisture damage. A higher number of missed school days due to respiratory infections were reported in schools with inadequate ventilation (RR: 1.16). Conclusions: The school level IEQ indicator variables described in this paper could explain a relatively large part of the school level variation observed in the self-reported upper respiratory symptoms and missed school days due to respiratory infections among students.
Afficher plus [+] Moins [-]Mots clés AGROVOC
Informations bibliographiques
Cette notice bibliographique a été fournie par Multidisciplinary Digital Publishing Institute
Découvrez la collection de ce fournisseur de données dans AGRIS