BackgroundExisting anthropometric studies for respirator designs are based on the head and facial dimensions of Americans and Chinese nationals, with no studies for multi-ethnic countries like Malaysia. This study aimed to create head and facial morphological database for Malaysia, specifically to identify morphological differences between genders, ethnicities, and birthplaces, as well as predictors of the dimensions.DesignA cross-sectional study.SettingMalaysia.ParticipantsA nation-wide cross-sectional study using a complex survey design with two stage-stratified random sampling was conducted among 3,324 participants, aged 18 years and above who were also participants of the National Health and Morbidity Survey 2020.Primary and secondary outcomesThe study collected data on sociodemographic, measurement of Body Mass Index (BMI) and 10 head and facial dimensions (3 dimensions were measured using direct measurement, and 7 others using Digimizer software for 2-dimension images). Linear regression was performed to determine the association between gender, ethnicity, birthplace, age and BMI and the dimensions.ResultsThere were significant differences in all the dimensions between sex, birthplace and ethnicity (p < 0.005). Further analysis using linear regression showed sex, ethnicity, birthplace, age and BMI were significant predictors of the dimensions. In comparison to studies from the United States and China, our study population had a wider interpupillary distance and nose breadth for both male and female participants, but smaller bigonial breadth and smaller minimal frontal breadth.ConclusionThese findings could assist in the design and sizing of respirators that will fit Malaysians and possibly other Southeast Asian population.

ObjectiveFacial anthropometric data is important for the design of respirators. Two-dimensional (2D) photogrammetry has replaced direct anthropometric method, but the reliability and accuracy of 2D photogrammetry has not been quantified. This study aimed to assess inter-rater reliability of 2D photogrammetry and to examine the reliability and accuracy of 2D photogrammetry with direct measurement.DesignA cross-sectional study.SettingMalaysia.ParticipantsA subset of 96 participants aged 18 and above.Primary and secondary outcomesTen facial dimensions were measured using direct measurement and 2D photogrammetry. An assessment of inter-rater reliability was performed using intra-class correlation (ICC) of the 2D images. In addition, ICC and Bland-Altman analyses were used to assess the reliability and agreement of 2D photogrammetry with direct measurement.ResultsExcept for head breadth and bigonial breadth, which were also found to have low inter-rater reliability, there was no significant difference in the inter-rater mean value of the 2D photogrammetry. The mean measurements derived from direct measurement and 2D photogrammetry were mostly similar. However, statistical differences were noted for two facial dimensions, i.e., bizygomatic breadth and bigonial breadth, and clinically the magnitude of difference was also significant. There were no statistical differences in respect to the remaining eight facial dimensions, where the smallest mean difference was 0.3 mm and biggest mean difference was 1.0 mm. The ICC showed head breadth had poor reliability, whilst Bland-Altman analyses showed seven out of 10 facial dimensions using 2D photogrammetry were accurate, as compared to direct measurement.ConclusionOnly certain facial measurements can be reliably and accurately measured using 2D photogrammetry, thus it is important to conduct a reliability and validation study before the use of any measurement methods in anthropometric studies. The results of this study also suggest that 2D photogrammetry can be used to supplement direct measurement for certain facial dimensions.

Particulate matter with an aerodynamic diameter of 10 μm or less (PM10) pollution poses a considerable threat to human health, and the first step in quantifying health impacts of human exposure to PM10 pollution is exposure assessment. Population-weighted exposure level (PWEL) estimation is one of the methods that provide a more refined exposure assessment as it includes the spatiotemporal distribution of the population into the pollution concentration estimation. This study assessed the population weighting effects on the estimated PM10 concentrations in Malaysia for years 2000, 2008, and 2013. Estimated PM10 annual mean concentrations with a spatial resolution of 5 kilometres retrieved from satellite data and population count obtained from the Gridded Population of the World version 4 (GPWv4) from the Centre for International Earth Science Information Network (CIESIN) were overlaid to generate the PWEL of PM10 for each state. The calculated PWEL of PM10 concentrations were then classified based on the World Health Organization (WHO) and the national Air Quality Guidelines (AQG) and interim targets (IT) for comparison. Results revealed that the annual mean PM10 concentrations in Malaysia ranged from 31 to 73 µg/m3 but became generally lower, ranging from 20 to 72 µg/m3 after population weighting, suggesting that the PM10 population exposure in Malaysia might have been overestimated. PWEL of PM10 distribution showed that the majority of the population lived in areas that complied with the national AQG, but were vulnerable to exposure level 3 according to the WHO AQG and IT, indicating that the population was nevertheless potentially exposed to significant health effects from long-term exposure to PM10 pollution.