Econometric Analysis Between Harmful Air Conditions and Mortality of Respiratory Conditions
Session Number
Project ID: BHVSO 01
Advisor(s)
Patrick Kearney; Illinois Mathematics and Science Academy
Discipline
Behavioral and Social Sciences
Start Date
22-4-2020 9:45 AM
End Date
22-4-2020 10:00 AM
Abstract
It is important to be aware of how the environmental surroundings in cities, suburbs, and rural areas affect our physical health, no matter how subtle. One aspect that may have a huge effect is the air being inhaled. In our research, we draw data on particulate matter 2.5mm, as well as CO2 emissions from highway vehicles, off-highway, fuel combustion, industrial processes (including chemical and allied product manufacturing, metals processing, petroleum and related industries, and other industrial processes; solvent utilization; and storage and transportation), and waste disposal and recycling. Our other x-variables in the linear regression include household income and smoking rate. With this data, we use econometric modeling to test for correlation with data on mortality rates from numerous chronic respiratory diseases such as asthma, chronic obstructive pulmonary disease, and lung and bronchus cancer. Both variables include data across 3,000+ counties in the United States, encompassing all states with exception to Hawaii and Alaska. The results of the regression are inconclusive, but the various numbers may lead to qualitative context on whether any of the quantities of particulate matter have an effect on any of the chronic respiratory diseases.
Econometric Analysis Between Harmful Air Conditions and Mortality of Respiratory Conditions
It is important to be aware of how the environmental surroundings in cities, suburbs, and rural areas affect our physical health, no matter how subtle. One aspect that may have a huge effect is the air being inhaled. In our research, we draw data on particulate matter 2.5mm, as well as CO2 emissions from highway vehicles, off-highway, fuel combustion, industrial processes (including chemical and allied product manufacturing, metals processing, petroleum and related industries, and other industrial processes; solvent utilization; and storage and transportation), and waste disposal and recycling. Our other x-variables in the linear regression include household income and smoking rate. With this data, we use econometric modeling to test for correlation with data on mortality rates from numerous chronic respiratory diseases such as asthma, chronic obstructive pulmonary disease, and lung and bronchus cancer. Both variables include data across 3,000+ counties in the United States, encompassing all states with exception to Hawaii and Alaska. The results of the regression are inconclusive, but the various numbers may lead to qualitative context on whether any of the quantities of particulate matter have an effect on any of the chronic respiratory diseases.