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代表马来西亚人群的呼吸适配性测试面板。

Respiratory fit test panel representing population of Malaysia.

机构信息

Environmental Health Research Centre, Institute for Medical Research, National Institutes of Health, Ministry of Health, Setia Alam, Selangor, 40170, Malaysia.

Department of Social and Preventive Medicine, Faculty of Medicine, University of Malaya, Kuala Lumpur, 50603, Malaysia.

出版信息

BMC Pulm Med. 2024 Mar 7;24(1):122. doi: 10.1186/s12890-024-02919-9.

Abstract

BACKGROUND

The 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.

METHODOLOGY

A 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.

RESULTS

This 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%.

CONCLUSION

This 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.

摘要

背景

现有的呼吸适配性测试面板(RFTP)基于双变量和主成分分析(PCA),利用了美国和中国的头部和面部尺寸数据。由于马来西亚没有基于当地面部人体测量数据的 RFTP,因此进行了这项研究,旨在使用马来西亚的数据开发新的 RFTP。

方法

在马来西亚进行了一项横断面研究,研究对象为 2020 年全国健康和发病率调查中年龄在 18 岁及以上的 3324 名参与者。测量了 10 个头和面部尺寸。使用脸长和脸宽构建双变量面部面板,而使用前两个 PCA 的分数来开发 PCA 面板。

结果

本研究表明,马来西亚人拥有最宽的面部宽度上限。它还发现,从 PCA 分析中可以减少三个因素。然而,仅选择了两个因素,PCA1 代表头部和面部大小,PCA2 代表面部形状。我们的双变量面板可以容纳 95.0%的人群,而我们的 PCA 面板可以容纳 95.6%。

结论

这是第一项使用马来西亚头部和面部人体测量数据来创建双变量和 PCA 面板的研究。使用这些面板构建的呼吸器可能适合马来西亚≥95.0%的人口。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c23b/10921698/f9cf7c4b2aca/12890_2024_2919_Fig1_HTML.jpg

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