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

Area of Science:

• Public Health
• Endocrinology
• Gerontology

Background:

• Osteoporosis poses a significant public health challenge for Indian women.
• The condition is frequently underdiagnosed, with fractures often being the first indication.
• Identifying socio-demographic risk factors is crucial for early detection and prevention.

Purpose of the Study:

• To identify socio-demographic and lifestyle factors associated with osteoporosis risk in Indian women.
• To develop a predictive model for osteoporosis risk stratification.

Main Methods:

• A study involving 150 Indian women aged 30-60 years.
• Analysis of socio-demographic and lifestyle data using regression modeling.
• Bone mineral density (BMD) measured by dual-energy X-ray absorptiometry (DXA).

Main Results:

• Advanced age (OR=2.3), low body mass index (BMI <18.5 kg/m²) (OR=3.8), and low dietary calcium intake (<500 mg/day) (OR=2.7) were significant predictors.
• Education level and income also contributed to osteoporosis risk stratification.
• The regression model identified key socio-demographic determinants of osteoporosis.

Conclusions:

• The study highlights critical socio-demographic factors influencing osteoporosis risk in Indian women.
• Findings underscore the need for targeted awareness programs and preventive interventions.
• Early identification of at-risk groups can mitigate osteoporosis prevalence.