Respiratory fit test panel representing population of Malaysia

BackgroundThe existing respiratory fit test panels (RFTPs) are based on Bivariate and Principal Component Analysis (PCA) which utilise American and Chinese head and facial dimensions. As RFTPs based on local facial anthropometric data for Malaysia are not available, this study was conducted with the...

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Main Authors: Lim, Yin Cheng, Soelar, Shahrul Aiman, Shakor, Ameerah Su'ad Abdul, Mohamad, Nadia, Pahrol, Muhammad Alfatih, Ismail, Rohaida, Danaee, Mahmoud, Shaharudin, Rafiza
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Published: BMC 2024
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Online Access:http://eprints.um.edu.my/45471/
https://doi.org/10.1186/s12890-024-02919-9
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spelling my.um.eprints.454712024-10-22T07:02:11Z http://eprints.um.edu.my/45471/ Respiratory fit test panel representing population of Malaysia Lim, Yin Cheng Soelar, Shahrul Aiman Shakor, Ameerah Su'ad Abdul Mohamad, Nadia Pahrol, Muhammad Alfatih Ismail, Rohaida Danaee, Mahmoud Shaharudin, Rafiza R Medicine (General) BackgroundThe existing respiratory fit test panels (RFTPs) are based on Bivariate and Principal Component Analysis (PCA) which utilise American and Chinese head and facial dimensions. As RFTPs based on local facial anthropometric data for Malaysia are not available, this study was conducted with the aim to develop new RFTPs using Malaysian data.MethodologyA cross-sectional study was conducted across Malaysia among 3,324 participants of the study of National Health and Morbidity Survey 2020 aged 18 and above. Ten head and facial dimensions were measured. Face length and face width were used to construct bivariate facial panel, whereas the scores from the first two PCA were used to develop the PCA panel.ResultsThis study showed that Malaysians have the widest upper limit for facial width. It also found that three factors could be reduced from the PCA analysis. However only 2 factors were selected with PCA 1 representing head and facial size and PCA 2 representing facial shape. Our bivariate panel could accommodate 95.0% of population, while our PCA panel accommodated 95.6%.ConclusionThis was the first study to use Malaysian head and facial anthropometry data to create bivariate and PCA panels. Respirators constructed using these panels are likely to fit >= 95.0% of Malaysia's population. BMC 2024-03 Article PeerReviewed Lim, Yin Cheng and Soelar, Shahrul Aiman and Shakor, Ameerah Su'ad Abdul and Mohamad, Nadia and Pahrol, Muhammad Alfatih and Ismail, Rohaida and Danaee, Mahmoud and Shaharudin, Rafiza (2024) Respiratory fit test panel representing population of Malaysia. BMC Pulmonary Medicine, 24 (1). p. 122. ISSN 1471-2466, DOI https://doi.org/10.1186/s12890-024-02919-9 <https://doi.org/10.1186/s12890-024-02919-9>. https://doi.org/10.1186/s12890-024-02919-9 10.1186/s12890-024-02919-9
institution Universiti Malaya
building UM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaya
content_source UM Research Repository
url_provider http://eprints.um.edu.my/
topic R Medicine (General)
spellingShingle R Medicine (General)
Lim, Yin Cheng
Soelar, Shahrul Aiman
Shakor, Ameerah Su'ad Abdul
Mohamad, Nadia
Pahrol, Muhammad Alfatih
Ismail, Rohaida
Danaee, Mahmoud
Shaharudin, Rafiza
Respiratory fit test panel representing population of Malaysia
description BackgroundThe existing respiratory fit test panels (RFTPs) are based on Bivariate and Principal Component Analysis (PCA) which utilise American and Chinese head and facial dimensions. As RFTPs based on local facial anthropometric data for Malaysia are not available, this study was conducted with the aim to develop new RFTPs using Malaysian data.MethodologyA cross-sectional study was conducted across Malaysia among 3,324 participants of the study of National Health and Morbidity Survey 2020 aged 18 and above. Ten head and facial dimensions were measured. Face length and face width were used to construct bivariate facial panel, whereas the scores from the first two PCA were used to develop the PCA panel.ResultsThis study showed that Malaysians have the widest upper limit for facial width. It also found that three factors could be reduced from the PCA analysis. However only 2 factors were selected with PCA 1 representing head and facial size and PCA 2 representing facial shape. Our bivariate panel could accommodate 95.0% of population, while our PCA panel accommodated 95.6%.ConclusionThis was the first study to use Malaysian head and facial anthropometry data to create bivariate and PCA panels. Respirators constructed using these panels are likely to fit >= 95.0% of Malaysia's population.
format Article
author Lim, Yin Cheng
Soelar, Shahrul Aiman
Shakor, Ameerah Su'ad Abdul
Mohamad, Nadia
Pahrol, Muhammad Alfatih
Ismail, Rohaida
Danaee, Mahmoud
Shaharudin, Rafiza
author_facet Lim, Yin Cheng
Soelar, Shahrul Aiman
Shakor, Ameerah Su'ad Abdul
Mohamad, Nadia
Pahrol, Muhammad Alfatih
Ismail, Rohaida
Danaee, Mahmoud
Shaharudin, Rafiza
author_sort Lim, Yin Cheng
title Respiratory fit test panel representing population of Malaysia
title_short Respiratory fit test panel representing population of Malaysia
title_full Respiratory fit test panel representing population of Malaysia
title_fullStr Respiratory fit test panel representing population of Malaysia
title_full_unstemmed Respiratory fit test panel representing population of Malaysia
title_sort respiratory fit test panel representing population of malaysia
publisher BMC
publishDate 2024
url http://eprints.um.edu.my/45471/
https://doi.org/10.1186/s12890-024-02919-9
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