Demographic and socioeconomic determinants of cancer rates
Category
Business, Education and Humanities
Department
Finance and Economics
Student Status
Undergraduate
Research Advisor
Heather Eckstein
Document Type
Event
Location
Meadowlark
Start Date
10-4-2025 11:40 AM
End Date
10-4-2025 12:00 PM
Description
Cancer is one of the leading causes of death in the United States. The National Cancer Institute defines cancer as a disease in which some of the body's cells grow uncontrollably and spread to other parts of the body. Even with advancements in treatment methods there is no cure and even once in remission the cancer can come back. This study aims to answer how demographic and socioeconomic factors impact the cancer rate around the United States. A multivariate pooled regression analysis is conducted using linear panel data. To run the regression, we are using ordinary least squares. Cancer rate is the dependent variable. Population, gender, age, race, median household income, and marriage rate are the independent variables. Results from the regression show that male, female, median household income and marriage cause the cancer rate to increase, and they are all significant. Population, ages, and races all cause the cancer rate to decrease. They are all significant but the age group 0-24. AR (1) and AR (2) were used to help the regression model. The implication of these results shows that population, gender, ages 25 and above, ethnicity, median household income, and marriage rates play a significant role in shaping cancer rates in the United States.
Demographic and socioeconomic determinants of cancer rates
Meadowlark
Cancer is one of the leading causes of death in the United States. The National Cancer Institute defines cancer as a disease in which some of the body's cells grow uncontrollably and spread to other parts of the body. Even with advancements in treatment methods there is no cure and even once in remission the cancer can come back. This study aims to answer how demographic and socioeconomic factors impact the cancer rate around the United States. A multivariate pooled regression analysis is conducted using linear panel data. To run the regression, we are using ordinary least squares. Cancer rate is the dependent variable. Population, gender, age, race, median household income, and marriage rate are the independent variables. Results from the regression show that male, female, median household income and marriage cause the cancer rate to increase, and they are all significant. Population, ages, and races all cause the cancer rate to decrease. They are all significant but the age group 0-24. AR (1) and AR (2) were used to help the regression model. The implication of these results shows that population, gender, ages 25 and above, ethnicity, median household income, and marriage rates play a significant role in shaping cancer rates in the United States.
