Epidemiological studies have found that particulate matter less than 10 microns in diameter (PM10) is hazardous to human health. Population-weighted exposure level (PWEL) estimation is one of the methods in providing quantitative assessments of areas where population is vulnerable to the harmful pollutant. This study assessed the PWEL of PM10 concentrations in all 16 states of Malaysia for years 2000, 2008 and 2013 using remote sensing and geographic information system (GIS). PM10 concentration estimation method from a local study was applied to validate the estimated PM10 annual mean concentrations with a spatial resolution of 5 kilometers retrieved from satellite data. Population count was obtained from the Gridded Population of the World version 4 (GPWv4) from the Center for International Earth Science Information Network (CIESIN). Estimated PM10 concentrations and gridded population count were then overlaid to generate PWEL of PM10. PWEL of PM10 for each state in Malaysia for the three years were then calculated to study the trend of PWEL of PM10. Concentrations of the pollutant were then classified based on the World Health Organization interim target (WHO IT) guideline. Increasing PWEL of PM10 were seen in 9 states over the 13-year period. Over those years, Putrajaya and Penang had the most increasing trend of PWEL of PM10 with an increment of 119% and 95% respectively. Putrajaya also had the highest recorded PWEL of PM10 (72 µg/m3) in 2013, exceeding the WHO IT class 1 guideline (70 µg/m3). Results based on human exposure analysis showed higher risks were more towards urban and industrialized states. These results can be used as a decision-making tool and reference for health risk assessment on the population, areas, and sources that need more attention to curb air pollution. (283 words).

Epidemiological studies have found that particulate matter less than 10 microns in diameter (PM10) is hazardous to climate and human health. Population-weighted exposure level (PWEL) estimation is fundamental in providing quantitative assessments of areas where the population is vulnerable to the harmful pollutant. This study assesses PWEL of PM10 concentrations in all 16 states of Malaysia for years 2000, 2008 and 2013 using remote sensing and geographic information system (GIS). PM10 concentration estimation method from a local study was applied to validate the estimated PM10 annual mean concentrations with a spatial resolution of 5 kilometers retrieved from satellite data. Population count was obtained from the Gridded Population of the World version 4 (GPWv4) from the Center for International Earth Science Information Network (CIESIN). Estimated PM10 concentrations and gridded population count were then overlaid to generate PWEL of PM10. PWEL of PM10 for each state in Malaysia for the three years were then calculated to study the PWEL of PM10 trend. The concentrations of the pollutant were then classified based on the World Health Organization interim target (WHO IT) guideline. Increasing PWEL of PM10 were seen in 9 states over the 13-year period. Over those years, Putrajaya and Penang had the most increasing trend of PWEL of PM10 with an increment of 119% and 95% respectively. Putrajaya also had the highest recorded PWEL of PM10 (72 µg/m3) in 2013, exceeding the WHO IT class 1 guideline (70 µg/m3). Results based on human exposure analysis show the vulnerability was more towards urban and industrialized states. These results can be used as a decision-making tool and reference for health risk assessment on the population, areas, and sources that need more attention to curb air pollution.

Background: Existing 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. Design: A cross-sectional study. Setting: Malaysia. Participants: A 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 outcomes. The 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. Results: There 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. Conclusion: These findings could assist in the design and sizing of respirators that will fit Malaysians and possibly other Southeast Asian population.