Factors Associated with Osteoporosis Screening and Recommendations for Osteoporosis Screening in Older Adults
Osteoporosis screening rates are low, and it is unclear which patient factors are associated with screening and physician recommendations for screening.
To identify patient characteristics associated with osteoporosis screening recommendations and receipt of screening in older adults.
Cross-sectional mailed survey.
Women and men ≥60 years old living in or near western Pennsylvania.
Sociodemographic characteristics and osteoporosis-related data, including risk factors, physician recommendations for screening, and receipt of screening. Multivariable logistic regression analyses were performed to determine odds ratios for receipt of screening and screening recommendations for individuals with particular osteoporosis risk factors, adjusting for sociodemographic and other risk factors.
Surveys were completed by 1,268 of the 1,830 adults to whom surveys were mailed (69.3%). Most respondents were white (92.9%), female (58.7%), and believed they were in good to excellent health (88.2%). Only 47.6% said their physician recommended osteoporosis screening, and 62.6% of all respondents reported being screened. Screening recommendations were less likely for older respondents than younger ones (OR, 0.87 per 5-year increase in age; 95% CI, 0.77–0.97). Individuals with osteoporosis risk factors of a history of oral steroid use for >1 month, height loss >2.54 cm, or history of low-trauma fracture were no more likely to report screening recommendations than individuals without these characteristics. Receipt of screening was no more likely for more elderly respondents or respondents with a history of oral steroid use for >1 month than for respondents without these characteristics.
Individuals with several known osteoporosis risk factors are not being sufficiently targeted for screening.
- Factors Associated with Osteoporosis Screening and Recommendations for Osteoporosis Screening in Older Adults
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- Available under Open Access This content is freely available online to anyone, anywhere at any time.
Journal of General Internal Medicine
Volume 24, Issue 5 , pp 585-591
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- Author Affiliations
- 1. School of Medicine, Department of Medicine, Division of General Internal Medicine, Section of Decision Sciences and Clinical Systems Modeling, University of Pittsburgh, Pittsburgh, PA, USA
- 3. University of Pittsburgh, 200 Meyran Ave., Suite 200, Pittsburgh, PA, 15213, USA
- 2. School of Medicine, Department of Medicine, Division of Endocrinology and Metabolism and Division of Geriatric Medicine, University of Pittsburgh, Pittsburgh, PA, USA