Evaluation of clinical risk factors for osteoporotic fractures using the FRAX calculator among women in Armenia aged 40 and older
摘要
This study assessed osteoporosis risk factors in Armenian women using the FRAX calculator. A BMI below 30, corticosteroid use, prior fractures, thyroid disorders, and diabetes significantly increased fracture risk. Findings highlight the need for national osteoporosis guidelines tailored to Armenia.
PurposeThe aim of the study was to assess the prevalence of clinical risk factors for osteoporotic fractures, as defined by the Armenian-specific FRAX model, among women aged 40 years and older in the Republic of Armenia, and to evaluate their contribution to fracture risk.
MethodsA cross-sectional pilot study was conducted among 265 women aged ≥ 40 years who visited the Osteoporosis Center in Yerevan, Armenia, between September and October 2024. FRAX scores were calculated using Armenia-calibrated data. Participants were randomly selected, and data on FRAX risk factors were collected. Based on fracture probabilities, participants were stratified into low-, moderate-, and high-risk groups. Due to limited numbers in the low-risk group, low and moderate categories were merged for regression analysis. Logistic regression models were used to assess associations between clinical risk factors and high fracture risk.
ResultsAmong participants, 21.1% were classified as high risk. Multivariate logistic regression identified a body mass index < 30 (OR = 4.3, 95% CI 1.6–11.5), history of prior fractures (OR = 52.5, 95% CI 17.2–160.3), corticosteroid use (OR = 5.0, 95% CI 1.6–15.1), thyroid disease (OR = 8.8, 95% CI 3.1–25.1), and type 2 diabetes (OR = 3.6, 95% CI 1.1–11.0) as independent predictors of high fracture risk. Although age ≥ 60 was associated with increased risk in univariate analysis, it did not retain significance in the multivariate model.
ConclusionThe study findings highlight the importance of developing national osteoporosis prevention and management guidelines that are tailored to the specific characteristics of the local population. Additionally, further research involving larger sample sizes is needed to enhance understanding of the prevalence of these risk factors and to inform targeted public health strategies.