Investigating Indoor Air Quality (IAQ) and Sick Building Syndrome Symptoms (SBSS) using generalized linear model

Authors

  • Amalina Abu Mansor
  • Samsuri Abdullah
  • Aimi Nursyahirah Ahmad
  • Nurul Ain Ismail
  • Marzuki Ismail

Abstract

Prediction of Indoor Air Quality and Sick Buildings Syndrome Symptoms (SBSS) was developed to predict the relative humidity (RH) inside the building. The developed generalized linear model (GLM) model consider relative humidity as dependent variables and independent variables consists of Indoor Air Quality Parameters (IAQ) such as ventilation performance indicator, physical and chemical parameters besides present SBSS. Primary data was collected, and distribution of questionnaires was conducted at the same time. Three models were developed which named Model A, Model B and Model C. A logarithmic link function was considered with a Poison probability distribution. Particular attention was dedicated to cases with Relative Humidity<mean (Model A), Relative Humidity mean range (Model B) and Relative Humidity >mean (Model C). Results indicate that best performance was Model A which outperformed Model B and Model C. It showed that there were a few contributions of SBS and IAQ towards RH inside the building such as dizziness, drowsiness, heavy headed, headache, temperature and PM10. This study showed that Model A (R2=96.8%) outstand Model B (86.9%) and Model C (93.5%) due to the data collected mostly distribute lower than mean value of RH.

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Published

2023-11-01

How to Cite

Mansor, A. A. ., Abdullah, S., Ahmad, A. N., Ismail, N. A., & Ismail, M. (2023). Investigating Indoor Air Quality (IAQ) and Sick Building Syndrome Symptoms (SBSS) using generalized linear model. Healthscope: The Official Research Book of Faculty of Health Sciences, UiTM, 6(1), 23-30. Retrieved from https://healthscopefsk.com/index.php/research/article/view/308

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Articles