Osteoporosis treatment disparities: a 6-year aggregate analysis from national survey data

• Published in: Osteoporosis international Vol. 25; no. 9; pp. 2199 - 2208
• Main Authors: Cunningham, T. D., Di Pace, B. S., Ullal, J.
• Format: Journal Article
• Language: English
• Published: London Springer London 01.09.2014; Springer Nature B.V
• Subjects: Absorptiometry, Photon - methods; Aged; Aged, 80 and over; Body Mass Index; Bone density; Bone Density - physiology; Bone Density Conservation Agents - therapeutic use; Drug Prescriptions - statistics & numerical data; Drug Utilization - statistics & numerical data; Endocrinology; Female; Health care; Healthcare Disparities - statistics & numerical data; Humans; Male; Medical treatment; Medicine; Medicine & Public Health; Middle Aged; Nutrition Surveys; Original Article; Orthopedics; Osteoporosis; Osteoporosis - drug therapy; Osteoporosis - epidemiology; Osteoporosis - physiopathology; Osteoporotic Fractures - epidemiology; Osteoporotic Fractures - prevention & control; Rheumatology; Socioeconomic Factors; United States - epidemiology; United States; Osteoporosis; Healthcare disparities; Treatment
• ISSN: 0937-941X; 1433-2965; 1433-2965
• DOI: 10.1007/s00198-014-2747-9

Summary We studied factors to determine the receipt of osteoporosis treatment in individuals with osteoporosis. Treatment was associated with age, gender, race, body mass index (BMI), family history, arthritis and thyroid problems, daily glucocorticoid use, number of prescriptions and healthcare visits, and insurance type. Introduction Osteoporosis is underrecognized and undertreated. Few studies have examined factors associated with osteoporosis treatment in a large, national sample of men and women. Methods We aggregated National Health and Nutrition Examination Survey (NHANES) data from 2005 to 2010 and created a subsample which included individuals 50 years or older who were identified to have osteoporosis either by self-report data or by bone density measurements. The primary outcome was the receipt of osteoporosis treatment either from self-report or from prescription records. Covariates included sociodemographics, clinical characteristics, and access to healthcare variables. Logistic regression analyses were performed to determine factors that associate with osteoporosis treatment. Results From a sample of 31,0134 participants, 1,133 subjects (3.65 %) met the study criteria. Treatment was associated with age (odds ratio (OR) = 1.14), gender (OR = 13.25), race (OR = 2.23, White vs. Black; OR = 1.76, other vs. Black), BMI (OR = 1.67, normal vs. obese; OR = 2.68, overweight vs. obese), family history of osteoporosis (OR = 1.94), arthritis (OR = 1.43), daily glucocorticoid use (OR = 1.43), number of prescriptions (OR = 1.01), and number of healthcare visits in the past year (OR = 1.44, 4–9 vs. 0–3 visits). All odds ratios were statistically significant. Conclusion A large number of individuals diagnosed with osteoporosis above the age of 50 remain untreated. It is important for healthcare providers to better assess older adults with osteoporosis, including individuals who frequently receive medical care.