Predicting Osteoporosis Risk Using Regression Model Based on Socio Demographic Factors among Indian Women

Osteoporosis is a major public health problem among Indian women, often being underdiagnosed until the occurrence of fractures. Socio-demographic factors associated with the risk of osteoporosis may be identified for early detection and prevention.

A total of 150 Indian women, aged 30-60 years, were selected for this study. Socio-demographic and lifestyle data were analyzed using a regression model to predict the risk of osteoporosis. Age, education, income, body mass index (BMI), physical activity, and dietary calcium intake were assessed as predictors of osteoporosis. Bone mineral density (BMD) was measured with dual-energy X-ray absorptiometry (DXA) as the outcome variable.

Advanced age (OR = 2.3, P < 0.01), low BMI (<18.5 kg/m²) (OR = 3.8, P < 0.01), and low dietary calcium intake (<500 mg/day) (OR = 2.7, P < 0.05) were significant predictors of osteoporosis. Socio-economic factors are also linked to education level and income, which contributed to risk stratification.

The regression model identifies a few important socio-demographic factors that determine risk factors for osteoporosis in Indian women. These findings thus emphasize targeted awareness programs and preventive interventions to reduce the risk of osteoporosis in at-risk groups.