Posters
Presenting Author Academic/Professional Position
Blake Martin
Academic Level (Author 1)
Medical Student
Academic Level (Author 2)
Faculty
Discipline/Specialty (Author 2)
Population Health
Discipline Track
Clinical Science
Abstract Type
Research/Clinical
Abstract
Background: The Rio Grande Valley (RGV) is a rural area with underserved, unique communities that may influence the health of the population. The primary objective of this study was to analyze factors associated with osteoporosis in individuals in the RGV to determine if the number of pre-existing medical conditions had an association with the frequency of osteoporosis. We hypothesized that individuals with more pre-existing medical conditions would be associated with an increased frequency of osteoporosis.
Methods: This study was a retrospective chart review from January 1, 2018, to January 1, 2025, using the University of Texas Rio Grande Valley (UTRGV) UTHealth electronic database. We collected and analyzed medical charts (via ICD-10 codes) of individuals who were diagnosed with various pre-existing medical conditions including immunodeficiency, type 1 diabetes mellitus (T1DM), type 2 diabetes mellitus (T2DM), hypertension, obesity/overweight, tobacco use, alcohol misuse, vascular disorders, and anemia. We also collected and analyzed the charts of individuals with and without osteoporosis. Descriptive statistics were used along with propensity score matching (PSM) followed by logistic analysis.
Results: Our results demonstrate a strong and progressive association between the number of comorbid conditions and the likelihood of having osteoporosis. After adjusting for age and sex, individuals with multiple chronic conditions had significantly higher odds of osteoporosis.
Conclusion: Our study demonstrates a strong and progressive association between the number of comorbid conditions and the likelihood of having osteoporosis. These findings support the importance of multimorbidity as a risk marker for osteoporosis in clinical evaluations, especially in underserved communities such as the RGV.
Presentation Type
Poster
Recommended Citation
Martin, Blake C. and Lopez Alvarenga, Juan, "Chronic Conditions and Osteoporosis Risk: Insights from Penalized Logistic Modeling" (2025). Research Colloquium. 25.
https://scholarworks.utrgv.edu/colloquium/2025/posters/25
Included in
Chronic Conditions and Osteoporosis Risk: Insights from Penalized Logistic Modeling
Background: The Rio Grande Valley (RGV) is a rural area with underserved, unique communities that may influence the health of the population. The primary objective of this study was to analyze factors associated with osteoporosis in individuals in the RGV to determine if the number of pre-existing medical conditions had an association with the frequency of osteoporosis. We hypothesized that individuals with more pre-existing medical conditions would be associated with an increased frequency of osteoporosis.
Methods: This study was a retrospective chart review from January 1, 2018, to January 1, 2025, using the University of Texas Rio Grande Valley (UTRGV) UTHealth electronic database. We collected and analyzed medical charts (via ICD-10 codes) of individuals who were diagnosed with various pre-existing medical conditions including immunodeficiency, type 1 diabetes mellitus (T1DM), type 2 diabetes mellitus (T2DM), hypertension, obesity/overweight, tobacco use, alcohol misuse, vascular disorders, and anemia. We also collected and analyzed the charts of individuals with and without osteoporosis. Descriptive statistics were used along with propensity score matching (PSM) followed by logistic analysis.
Results: Our results demonstrate a strong and progressive association between the number of comorbid conditions and the likelihood of having osteoporosis. After adjusting for age and sex, individuals with multiple chronic conditions had significantly higher odds of osteoporosis.
Conclusion: Our study demonstrates a strong and progressive association between the number of comorbid conditions and the likelihood of having osteoporosis. These findings support the importance of multimorbidity as a risk marker for osteoporosis in clinical evaluations, especially in underserved communities such as the RGV.
