Researcher Spotlight: Kristen Litzelman
Kristin Litzelman is a doctorate in the Department of Population Health Sciences at the University of Wisconsin School of Medicine and Public Health and is one of many researchers who have utilized the Survey of the Health of Wisconsin (SHOW) to investigate research questions regarding health outcomes within the community.
She is especially interested in the physiology of stress and has utilized SHOW data to publish two papers on the topic. Kristin was interviewed to speak about her findings and about her work with SHOW.
Can you summarize what your study explores?
What we did for this particular study was look at caregivers and non-caregivers in the Survey of the Health of Wisconsin, or SHOW. A caregiver is anyone who provided unpaid care to a family member or friend having an aliment or disability. We looked at care recipients of any age, some people were caring for children while others were caring for parents or grandparents. We included caregivers of all types, hoping to obtain a population level understanding.
Levels of stress and characteristics of their care giving experience like how many hours per week, how long, and amount of strain they experienced were obtained for the caregiver sample population. Strain can be defined as the stress a caregiver experienced specifically from caregiving. We wanted to see how these characteristics impacted an individual on a cellular level.
Using SHOW’s biological sample bank, and their DNA donated from residents of Wisconsin, we looked specifically at telomere length which is a biological marker of cellular aging. It has been associated in several studies with older age and poor health outcomes. The goal was really to see if these caregiving factors impacting people not just in terms of mood, but at a cellular level.
What were the results of that study?
We ended up finding very interesting things. First, for both caregivers and non-care givers combined, we looked at how stress was associated with telomere length. We found that people who had moderate levels of stress had longer telomeres, meaning they had less cellular aging, compared to people who either had very low amounts of stress or very high amounts of stress. When we looked at caregivers verse non caregivers, we did not find any difference between their telomere lengths. This is not surprising because the caregiver group is so disparate, there are so many different types of people.
When we looked at caregivers specifically, we found that people providing more hours of care per week had shorter telomeres - and thus more evidence of cellular aging - than people who were providing less care. Additionally, people who had more strain because of caregiving had shorter telomeres. Lastly, we found that people caring for a child or young adult, less than 25 years old, had shorter telomeres than their counter parts.
Other work has shown that when you’re caring for someone who is younger there is more uncertainty involved and parents don’t anticipate this. Parents are forced to take on roles that they aren’t accustomed to and that a lot of their peers aren’t doing. We also found that it didn’t matter if the caregiver was the parent or someone else, caring for a child showed in accelerated cellular aging, for people across the board. We don’t know exactly why this is, but evidence seems to show that caring for a child is very different than caring for another adult.
You have used SHOW data to study caregiving dynamics before. What did you find?
The other study looked at quality of life. We were interested in looking into if there was a difference between caregivers and non-caregivers not just in general in terms of quality of life, but also in terms of level of strain. Specifically, we were interested in health related quality of life, which is the perception of quality life in the areas of mental and physical health. Caregivers were split up into high amounts of strain, middle amounts of strain and low amounts of strain.
We found that for mental health, caregivers with low amounts of strain had better mental health than non-caregivers and caregivers with high amounts of strains had worse mental health. For physical health we found that people who had the highest amounts of strain had worse physical quality of life than non-caregivers.
Something interesting about this study is that we also looked at global stress, meaning the amount of all other forms of stress experienced in the past year, in that relationship, and found that it is not only strain that causes the problem, but that stress also has an effect. The takeaway from these findings is that while clinicians should be asking about caregiver strain, they should also be asking about other stress in people’s lives because that can also influence their health outcomes and effect their physical and mental quality of life.
What instruments did you use in those studies?
We focused on the quality of life measure that SHOW has and utilized the caregiver strain index for measuring strain. For stress we used the global stress scale (STS) from the Jackson Heart Study.
Do you focus primarily on caregivers in our society and how we can support them?
Yes. In general I focus on how we can support them through policy and in clinical interactions. In the end, I would like to explore is if there are there things that we can do in the clinical world, as well as on a more community policy level, to help caregivers. When a physician has a cancer patient for example, they are focused on their patient, and for good reason because that is the person who needs their care, but it is also important that their caregiver is doing well because otherwise they cannot effectively take care of that person.
I am interested in testing out what we can do in a clinical setting to wrap caregivers into the care of patients. Focusing on the patient, necessarily, but also the caregiver as well.
How did SHOW’s data and work helped you to make this research possible?
It’s a great data set. It was very clean when I got it. Usually there is so much information in a dataset that it can be a lot of information to sift through, but the way SHOW delivered the data was clean and useable. In preparing for these studies I started to look at different data sets and found that SHOW already asked some caregiver questions. I liked that I could use SHOW’s dataset as opposed to trying to cobble together multiple datasets, and the fact that they are open to ancillary studies was helpful because it made additional data collection possible.
From a research perspective, the interaction with SHOW was fantastic. And from a data perspective the data were great. Because it is population based and relatively large, it was great for my needs.