Electronic Theses and Dissertation

Latar belakang: osteoporosis merupakan penyakit degeneratif yang meningkatkan risiko fraktur, terutama pada wanita pascamenopause akibat penurunan estrogen. data terkait distribusi risiko fraktur dan faktor determinan osteoporosis di aceh saat ini masih terbatas. fracture risk assessment tool (frax®) dapat digunakan untuk memprediksi risiko fraktur dalam 10 tahun berdasarkan faktor klinis. tujuan: menganalisis hubungan determinan sosiodemografi, klinis, dan gaya hidup terhadap skor risiko fraktur berdasarkan skor frax® pada wanita pascamenopause di kota banda aceh. metode: studi observasional analitik dengan desain cross sectional pada 441 wanita pascamenopause. penelitian ini dilakukan di 11 puskesmas di kota banda aceh. data dikumpulkan melalui wawancara dan kuesioner, kemudian dihitung skor frax tanpa bmd. analisis dilakukan secara univariat, bivariat menggunakan uji chi-square/fisher’s exact, dan multivariat menggunakan analisis regresi logistik biner dengan signifikansi p

Background: Osteoporosis is a degenerative disease that increases the risk of fractures, especially in postmenopausal women due to reduced estrogen levels. Data regarding the distribution of fracture risk and determinants of osteoporosis in Aceh remain limited. The Fracture Risk Assessment Tool (FRAX®) can be used to estimate the 10-year probability of fractures based on clinical risk factors. Objective: To analyze the association between sociodemographic, clinical, and lifestyle determinants and fracture risk scores based on FRAX® in postmenopausal women in Banda Aceh City. Methods: This study was an analytical observational study with a cross-sectional design involving 441 postmenopausal women. The study was conducted in 11 primary healthcare centers in Banda Aceh City. Data were collected through interviews and questionnaires, and FRAX® scores were calculated without bone mineral density (BMD). Data analysis was performed using univariate, bivariate methods with Chi-square/Fisher’s Exact tests, and multivariate methods with logistic regression tests with a significance level of p