The spatio-temporal characteristics and effects of PM10 associated with the cardio-respiratory morbidity of the selected population using biomarkers of exposure

Spatio-temporal of PM10 was proven to be associated with hospitalization of cardiorespiratory disease yet needs extensive investigation of molecular interaction to explain the disease pathway. There is a need to establish an association between PM10 exposure and health effects at a macro and micro level of exposure assessment. The first objective was to determine at the macro level the spatio-temporal cause-and-effect relationship between PM10 concentration level with traffic, land-use types, and meteorological parameters using spatial models. Secondly, to associate the effect of spatio-temporal PM10 exposure with cardio-respiratory-related hospitalization at the macro level using the Poisson model. Thirdly, to assess the micro exposure level of environmental risk factors and their interaction with urinary 1-OHP and IL-6 biomarkers using MANOVA. Multistage sampling comprising of secondary and primary data executed in the first and second phases, respectively. Results of Log-Log transformation of OLS and GWR spatial model showed 53% (R2 = 0.53) and 45% (R2 = 0.45) PM10 variation influenced by traffic (β = 0.04), industry land-use (β = 0.03), RH (β = -1.55) and time trend (β = 0.22), p-value < 0.05. Both models estimated a rise of one average traffic count and 1-hectare of industry development area would increase 0.33 mg/m3 and 0.0002 mg/m3 of PM10 concentration, respectively. Space-time analysis of spatio-temporal PM10 reveals Balok Baru and Seremban were highly polluted areas and new hot spots, respectively. Poisson model indicated an increment of one μg/m3 of PM10 exposure significantly increase by 0.3% (RR = 1.003) and 0.5% (RR = 1.005) cardiovascular and respiratory hospitalization, respectively. The RR for cardiovascular disease were 5.5 and 4.4 in Seremban and Balok Baru, respectively, times as high as the cardiovascular risk in other locations. Similarly, RR for respiratory disease was 4.4 and 3.7 in Seremban and Balok Baru, respectively. The mean value of total PAHs was 7.31 ng/m3 with high and low molecular weight dominated PAHs proportion in Balok Baru and Seremban, respectively. Urinary 1-OHP and IL-6 concentrations range from 0.001 to 2.53 μmol/mol-creatinine and 0.04 to 82.08 pg/mol, respectively. Interaction analysis using MANOVA revealed that the estimated marginal mean of Seremban recorded the highest mean concentration of urinary 1-OHP (p-value = 0.03). This thesis concludes that the macro-level exposure to spatio-temporal PM10 has a significant RR of cardio-respiratory hospitalization. Subsequently supported by the micro-level exposure assessment that showed molecular interaction between biomarkers of exposure (1-OHP and IL-6) differs by the environmental risk factors. This thesis contributes to an insight of modeling enhancement in health risk assessment of particulate pollution exposure. Future research needs to include other biomarkers because it is a promising way of associating PM10 exposure with the environmental-related cardiorespiratory etiology.