Posters
Presenting Author Academic/Professional Position
Medical Student
Academic Level (Author 1)
Medical Student
Academic Level (Author 2)
Undergraduate
Academic Level (Author 3)
Faculty
Discipline/Specialty (Author 3)
Population Health and Biostatistics
Presentation Type
Poster
Discipline Track
Clinical Science
Abstract Type
Research/Clinical
Abstract
Background: The Rio Grande Valley (RGV) is a medically underserved, demographically unique population that warrants the exploration of various conditions, including joint conditions, such as osteoarthritis (OA), rheumatoid arthritis (RA), gout, ankylosing spondylitis (AS), psoriatic arthritis (PA), juvenile idiopathic arthritis (JIA), and septic arthritis (SA). We sought to determine the demographic disparities between the different types of common joint conditions in this community. We hypothesized that OA would follow national trends and be the most common joint condition in the Rio Grande Valley. We hypothesized that the demographics between the various joint conditions would vary depending on age, sex, BMI, and ethnicity.
Methods: This was a retrospective chart review, from January 1, 2018 to September 4, 2024, that analyzed medical charts for individuals diagnosed with OA, RA, gout, AS, PA, JIA, and SA. Patients’ charts with these diagnoses were obtained using the ICD-10 diagnosis codes M15-M19 for OA, M05-M06 for RA, M10 or M1A for gout, M45 for AS, L40.5 for PA, M08 for JIA, and M00.8 for SA. We analyzed the data via descriptive statistics and panel regression models.
Results: The average age of participants was 65.7 (SD 12.4) years. The mean BMI was 32.5 (SD 7), which falls into the obese classification. Osteoarthritis was by far the most common diagnosis, accounting for 87% of cases (7,418 patients) who have this diagnosis alone. In regard to ethnicity, Hispanics showed a strong positive association with BMI compared to non-Hispanics (p < 0.001). The largest difference of age was in septic arthritis, with non-Hispanic patients having an adjusted mean age of 71.3 years (95% CI: 57.9, 84.8) compared to 48.2 years (95% CI: 41.8, 54.7) for Hispanic patients, followed by AS, PA, Gout, RA, and OA in no particular order. However, Hispanic patients have a significantly higher adjusted mean age (59.9 years, 95% CI: 57.7, 62.1) than non-Hispanic patients (32.7 years, 95% CI: 16.2, 49.2) for JIA. The associations between BMI and Gout, Osteoarthritis, and Rheumatoid Arthritis are statistically significant, with p-values of 0.015, 0.014, and 0.030, respectively.
Conclusion: These findings underscore the importance of targeting obesity and age-related joint conditions in this population, especially in communities with high healthcare needs. Ethnicity being a significant predictor of BMI, especially Hispanic ethnicity, reinforces the importance of focusing on weight management in Hispanic populations with joint diseases and may suggest different patterns of disease onset, healthcare access, or lifestyle factors by ethnicity that could inform culturally tailored interventions such as prophylaxis in the form of lifestyle changes (diet, exercise) or medications.
Recommended Citation
Martin, Blake C.; Baez, Devian D.; and Lopez-Alvarenga, Juan C., "Association of Joint Disease with Demographic Factors in Clinical Populations of the Rio Grande Valley" (2025). Research Symposium. 36.
https://scholarworks.utrgv.edu/somrs/2025/posters/36
Included in
Association of Joint Disease with Demographic Factors in Clinical Populations of the Rio Grande Valley
Background: The Rio Grande Valley (RGV) is a medically underserved, demographically unique population that warrants the exploration of various conditions, including joint conditions, such as osteoarthritis (OA), rheumatoid arthritis (RA), gout, ankylosing spondylitis (AS), psoriatic arthritis (PA), juvenile idiopathic arthritis (JIA), and septic arthritis (SA). We sought to determine the demographic disparities between the different types of common joint conditions in this community. We hypothesized that OA would follow national trends and be the most common joint condition in the Rio Grande Valley. We hypothesized that the demographics between the various joint conditions would vary depending on age, sex, BMI, and ethnicity.
Methods: This was a retrospective chart review, from January 1, 2018 to September 4, 2024, that analyzed medical charts for individuals diagnosed with OA, RA, gout, AS, PA, JIA, and SA. Patients’ charts with these diagnoses were obtained using the ICD-10 diagnosis codes M15-M19 for OA, M05-M06 for RA, M10 or M1A for gout, M45 for AS, L40.5 for PA, M08 for JIA, and M00.8 for SA. We analyzed the data via descriptive statistics and panel regression models.
Results: The average age of participants was 65.7 (SD 12.4) years. The mean BMI was 32.5 (SD 7), which falls into the obese classification. Osteoarthritis was by far the most common diagnosis, accounting for 87% of cases (7,418 patients) who have this diagnosis alone. In regard to ethnicity, Hispanics showed a strong positive association with BMI compared to non-Hispanics (p < 0.001). The largest difference of age was in septic arthritis, with non-Hispanic patients having an adjusted mean age of 71.3 years (95% CI: 57.9, 84.8) compared to 48.2 years (95% CI: 41.8, 54.7) for Hispanic patients, followed by AS, PA, Gout, RA, and OA in no particular order. However, Hispanic patients have a significantly higher adjusted mean age (59.9 years, 95% CI: 57.7, 62.1) than non-Hispanic patients (32.7 years, 95% CI: 16.2, 49.2) for JIA. The associations between BMI and Gout, Osteoarthritis, and Rheumatoid Arthritis are statistically significant, with p-values of 0.015, 0.014, and 0.030, respectively.
Conclusion: These findings underscore the importance of targeting obesity and age-related joint conditions in this population, especially in communities with high healthcare needs. Ethnicity being a significant predictor of BMI, especially Hispanic ethnicity, reinforces the importance of focusing on weight management in Hispanic populations with joint diseases and may suggest different patterns of disease onset, healthcare access, or lifestyle factors by ethnicity that could inform culturally tailored interventions such as prophylaxis in the form of lifestyle changes (diet, exercise) or medications.
