Population-based fracture risk assessment and osteoporosis treatment disparities by race and gender

Abstract

Background: Undertreatment of osteoporosis has been recognized as a common problem in selected patient subgroups. However, primary prevention has been hampered by limited risk assessment tools that can be applied to large populations.

Objectives: Using clinical risk factors with a new tool from the World Health Organization (FRAX) and recommendations from the National Osteoporosis Foundation (NOF), we evaluated fracture risk and osteoporosis treatment in a US cohort.

Participants: African Americans and Caucasians recruited from 2003-7 across the US as part of a longitudinal study.

Design: Cross-sectional.

Measures: The number of persons receiving prescription osteoporosis medications was assessed by race, sex, and fracture risk. Multivariable logistic regression evaluated the association between receipt of osteoporosis medications and fracture risk after controlling for potential confounders.

Results: Among 24,783 participants, estimated fracture risk was highest for Caucasian women. After multivariable adjustment for fracture-related risk factors, the likelihood of receipt of osteoporosis medications among African Americans was lower than among Caucasians [odds ratio (OR) = 0.44, 95% confidence interval (CI) 0.37, 0.53] and for men compared to women (OR = 0.08, 95% CI 0.06-0.10). Even for the highest risk group, Caucasian women with 10-year hip fracture risk > or = 3% (n = 3,025, 39.7%), only 26% were receiving treatment.

Conclusions: A substantial gap exists between 2008 NOF treatment guidelines based on fracture risk and the receipt of prescription osteoporosis medications. This gap was particularly notable for African Americans and men. FRAX is likely to be useful to assess risk at a population level and identify high-risk persons in need of additional evaluation.

Figure 1

Multivariable model showing the relationship between receipt of osteoporosis medications and race. Model 1 is the univariate model, with race only. Model 2 includes race, age, sex, and geographic region. Model 3 includes model 2 variables and socioeconomic factors (income, education, insurance). Model 4 includes model 3 variables and general health (MCS and PCS scores, perceived stress, depression, and overall health; see text for details). Model 5 includes model 4 variables, comorbidities (diabetes, heart disease, prior stroke and dyslipidemia, cognitive status), and number of unique medications. Model 6 includes model 5 variables and fracture risk factors (alcohol use, smoking, BMI, previous fracture, parental history of a hip fracture, use of glucocorticoids, and fall in the previous 6 months).