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Lifestyle Risk Factors for Urban and Rural Participants with Cancer

What I Did

The goal of my research project was to examine how lifestyle and other risk factors differed between urban and rural cancer patients in the California Teachers Study (CTS) cohort. Lifestyle risk factors are behaviors or habits that affect our health and can be modified or changed.


My project had three steps. First, I identified the ten most common cancers in the CTS. Next, I compared the lifestyle factors of participants who lived in urban areas at the time of their diagnosis with the lifestyle factors of participants who lived in rural areas at the time of their diagnosis. Finally, I analyzed each risk factor to determine if there was a statistical difference between urban and rural residents for any of the ten most common cancers. A statistically significant difference means it is unlikely that the differences we are seeing are due to chance.


My project looked at following risk factors:

  • age at cancer diagnosis

  • age at first pregnancy

  • alcohol consumption

  • body mass index (BMI)

  • diet (both with and without alcohol)

  • physical activity

  • parity at baseline (whether the participant had given birth to any children when they joined the study)

  • socioeconomic status (SES)

  • total number of pregnancies


What I Found

The chart below shows the ten most common cancers in the CTS. Breast cancer is the most common cancer: almost 40% of all cancers were breast cancer. The second most common cancer is melanoma.

When I compared the lifestyle factors for urban and rural participants for each of these cancers, I found that lifestyle factors did vary for certain cancer types.


The table below shows the cancer types and the risk factors I evaluated. If there is a check mark, that means there were statistically significant differences between urban and rural participants for that particular risk factor and cancer type. For example, age at diagnosis was statistically different between urban and rural participants with melanoma, but not for any of the other cancer types I examined.


There was only one factor that showed significance for every single cancer type: socioeconomic status (SES). We measured SES by creating a SES quartile variable. This variable consists of four groups (quartiles), where quartile 1 is the poorest and quartile 4 is the wealthiest. When I looked at these findings more closely, I found that most urban participants with cancer were from the higher SES quartiles and most rural participants with cancer were from the middle SES quartiles.


The graph below shows the SES quartiles for rural and urban participants with breast cancer. If we look at the top line of the graph, we can see how many participants were in the quartile 4, the highest SES group. Among rural participants with breast cancer, only 23% were in the highest SES quartile. In contrast, more than half (54%) of all urban participants with breast cancer were in the highest SES quartile.



Future Goals

Cancer is the second most common cause of death in the CTS. It is also a leading cause of death in the United States. Identifying modifiable risk factors—meaning risk factors that can be changed— can guide public health programs aimed at reducing disparities.


This project provides a basis for further exploring the differences in lifestyle factors between urban and rural participants who have had cancer. Future studies could compare the socioeconomic status of urban and rural cancer patients to the socioeconomic status of all study participants to see if urban-rural disparities exist generally in the CTS or if they are cancer specific.


In the literature I reviewed, rural and urban definitions varied by study. This makes it difficult to compare research on urban-rural cancer differences. It would be helpful to agree on consistent definitions of urban and rural, as well as to recognize that urban and rural areas exist on a continuum and do not necessarily fit into strict categories.


About the author

My name is Jean Rinkowski and I currently work as a Physical Therapist. After almost two decades working in healthcare, I’ve seen substantial disparities in people’s access to healthcare and their health outcomes. Seeing these disparities first-hand inspired me to pursue my Master of Public Health (MPH) at the University of Michigan, where I’m currently a graduate student. My academic focus areas are epidemiology, data analysis, and health policy. I’m passionate about using data to identify disparities, enhance health policies, and improve health outcomes for entire populations.


Completing my Applied Practicum Experience with the CTS team has allowed me to gain hands-on experience analyzing data from a large cohort study. This experience involved writing code, interpreting the findings, and identifying potential areas for further research. I’m incredibly thankful to the CTS team for sharing their expertise and guidance during this experience.



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