Observations and Analysis
 
    The hypothesis that the degradation in PEF rate has a high and inverse correlation with both the PM10 and TVOC concentration levels is true.

 

    The lining of the bronchial tubes are hyper-sensitive to air particulates in asthmatic subjects. Exposure to respirable particulate matter results in a cascading allergic response that includes mast cell reaction, and leads to mucus secretion and bronchoconstriction.

 

    Total VOCs are a mixture of compounds, some of which cause irritation in the bronchial tubes depending on the reactivity of the subject.

 

    There is no material correlation between the PEF rate and both the CO and CO2 concentration levels.  Increasing levels of these gases lowers the oxygen level in the body. The PEF rate depends only on the level of constriction in the bronchial tubes, and not on the level of oxygen. The CO level must not be ignored however. Like O2, CO can travel into the lungs, blood stream, and tissues, and therefore could irreparably damage them. 


Novel Mathematical PEF Rate Prediction Model that Incorporates Air Pollutants (PM10 and TVOC)
 
The regression model indicated above in Equation 4 modifies the Nunn 1989 PEF (NPEF) regression model in order to quantify the effect of air pollutants (PM10 and TVOC) on the PEF rate (Equation 3). 



     To understand the implication of this, let us take a look at one of my test subjects. Please open this sample report which I generated from the interactive online program I developed using ASP coding. As summarized, the details of this subject are as follow:
 
    Subject Age, Gender, Height: 50 years, Male 182"
 
    Subject's environment:            PM10 = 20 µg/m3 , TVOC = 1000 µg/m3
 
    The subject has a total degradation in PEF rate of 31.6%. However, the model suggests that about 17% of this degradation is attributable to pathophysiological factors and about 14% is attributable to environmental factors. Targeted remediation is possible with this new information. 
 
 
 
 
 
 
 



Observations
Show an understanding of what you saw happening during your experiment. Describe the patterns and trends you saw emerge as you worked.  


 


Judges' Tip Excellent observations will describe patterns or trends supported by the data (500 words maximum).