Hello, everyone. My name is Penli Kena-Oo, and I'm a second year osteopathic medical student at the University of New England in Maine. Today, I will be presenting my project on characteristics and experience of chronic pain across demographics and social determinants of health in Maine. Chronic pain is a significant and complex health problem in the U.S. Many factors can impact the experience of pain, including, but not limited to, demographics, physical activities, and mental health. The CDC reported that over 20% of U.S. adults experience chronic pain. Additionally, the prevalence appeared to be higher among older adults and females. Maine has the highest percentage of persons 65 years and older out of all the states. This population presents with a unique opportunity to further explore the burden of chronic pain. Current knowledge of chronic pain in Maine is limited to a single study from Dr. Mallon in 2018, which used the Maine All-Payers Insurance Claims Database back from 2006 to 2011. There is a clear gap in knowledge regarding chronic pain in Maine, so this led the Sal Lab to create an SDOH-focused pain survey for Mainers, which is still ongoing. My data analysis is on the preliminary data export from this survey. My two objectives are below, the first being to understand the SDOH characteristics and demographics of those with pain in the state via descriptive stats. Secondly, I wanted to explore the relationship between SDOH characteristics versus pain-related measures, including pain severity and associated comorbidities. So how did we go about doing this? Individuals living in Maine who are at least 18 years old with any type of recurrent or frequent pain are eligible to participate in the Pain Registry for Maine through an anonymous survey link via RedCap. There are 25 questions total divided into four sections, demographics, pain characteristics, pain management, and SDOH. For demographics, I was interested in age, biological sex, and county of residence. For social determinants of health, I focused on education level measured by highest degree earned. Pain characteristics were measured using an established scale referred to as PROPER, which measures pain comorbidities in eight domains. Each question is then measured on five levels on a Likert scale. Responses were added per domain to get our domain mean scores. I treated demographics and SDOH as the independent variables, and each of the proper domains were my dependent variables. This relationship was examined using a multivariate analysis of variants. 109 subjects were eligible for analysis. Note that all subjects met the chronic pain diagnosis as they all reported to have pain for at least three months. This table breaks down demographics by age. The graphs on the right shows the relationship between age and the domains that I found age to have significant effects on through MANOVA. Figure one shows proper anxiety scores across age. Here, as we increase in age, respondents reported better outcomes in anxiety. Figure two shows the proper depression scores. Similarly, with age increase, respondents tend to report better outcomes in the depression domain. Figure three displays the proper cognitive function scores across age groups. The two questions asked in this domain had to do with the subject's ability to concentrate and remember common tasks. With age increase, the respondents tend to report better outcomes in the cognitive domain as well. The next table breaks down social determinants of health categorized by the highest educational degree earned. More than half of the respondents earned a bachelor's degree or higher. This distribution is not a representation of Maine's education, but because the survey was established and distributed widely at the University of New England, it is likely that we have skewed data from graduate-level students as well as faculty members. Degrees earned were significantly associated with various pain outcomes. Figure four shows proper physical function scores across education levels. We saw worse physical function scores for those with higher degrees. Figure five shows that with increase in education, those with higher degrees tend to report less fatigue. Figure six shows the proper depression scores, while figure seven shows anxiety scores across education levels. These two graphs are very similar and show that with an increase in education, there were less anxiety and depression reported. Figure eight shows proper cognitive function scores increased across education level. Figure nine shows the proper ability to participate in activities and social role domain scores across education. Those with higher degrees earned reported worse outcomes in this domain. Now for the remaining two demographics, county and age, MANOVA did not detect statistically significant effects. Table three breaks down demographics by residing counties. The majority of respondents reported to be living in Cumberland and York, which are considered metro counties in Maine and home to UNE's two campuses. There were less respondents from rural counties. Table four breaks down demographics by biological sex, which shows that most respondents reported to be female. In conclusion, based on our data analysis, there was notable pain, comorbidity in younger Mainers and differential effects of education level on pain comorbidities. The analysis is consistent with previous reports on the high prevalence of pain among females in Maine, which is also consistent with national pain data. The pain registry for Maine is ongoing and remains open to the public. Hopefully more people, especially from a variety of educational backgrounds and more rural counties can contribute to the data collection. Only then can we truly understand the pain population in Maine and how specific demographics and SDOH characteristics could influence individuals' chronic pain experiences. The higher prevalence of pain and associate comorbidities reported by certain social groups can inform clinicians when assessing pain patients' risk for developing chronic pain and identifying appropriate preventative as well as treatment options. I would like to thank my PI for allowing me to use the data exported from her survey and thank you all for listening.

chronic pain

social determinants

Maine demographics

pain survey

multivariate analysis