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Bisphosphonates are widely used as first-line therapy to slow bone loss and decrease fracture risk in postmenopausal women with osteoporosis. Nonadherence to oral bisphosphonates diminishes the benefit of reduced bone loss and fracture risk of these medications. Strategies to enhance osteoporosis monitoring and adherence to therapy are crucial to improve outcomes. Dual-energy x-ray absorptiometry (DXA) is the gold standard for monitoring bone mineral density but is slow to detect change after initiation of oral bisphosphonate therapy. Bone turnover markers (BTMs) are by-products released during bone remodeling and are measurable in blood and urine. We review how the rapid change in BTMs can be a useful short-term tool to monitor the effectiveness of oral bisphosphonate therapy, which may ultimately improve adherence to therapy and outcomes. KEY POINTSOral bisphosphonates slow bone loss and reduce the risk of fracture in postmenopausal women with osteoporosis.Nonadherence to bisphosphonate therapy diminishes the benefits of these medications.BTMs are a simple, low-risk, and convenient way to monitor effectiveness and adherence to oral bisphosphonate therapy in addition to DXA.Bisphosophonates induce a rapid dose-dependent decrease in bone resorption markers, making them an excellent tool to ascertain adherence to and efficacy of oral antiresorptive therapy. REVIEW CME MOC

Background: Given the significant health effects, we assessed geospatial patterns of adverse events (AEs), defined as physical or sexual abuse and accidents or poisonings at home, among children in a mixed rural–urban community. Methods: We conducted a population-based cohort study of children (<18 years) living in Olmsted County, Minnesota, to assess geographic patterns of AEs between April 2004 and March 2009 using International Classification of Diseases, Ninth Revision codes. We identified hotspots by calculating the relative difference between observed and expected case densities accounting for population characteristics ( $$Relative\;Difference = {\rm{ }}{{Observed\;Case\;Density - Expected\;Case\;Density} \over {Expected\;Case\;Density}}$$ ; hotspot ≥ 0.33) using kernel density methods. A Bayesian geospatial logistic regression model was used to test for association of subject characteristics (including residential features) with AEs, adjusting for age, sex, and socioeconomic status (SES). Results: Of the 30,227 eligible children (<18 years), 974 (3.2%) experienced at least one AE. Of the nine total hotspots identified, five were mobile home communities (MHCs). Among non-Hispanic White children (85% of total children), those living in MHCs had higher AE prevalence compared to those outside MHCs, independent of SES (mean posterior odds ratio: 1.80; 95% credible interval: 1.22–2.54). MHC residency in minority children was not associated with higher prevalence of AEs. Of addresses requiring manual correction, 85.5% belonged to mobile homes. Conclusions: MHC residence is a significant unrecognized risk factor for AEs among non-Hispanic, White children in a mixed rural–urban community. Given plausible outreach difficulty due to address discrepancies, MHC residents might be a geographically underserved population for clinical care and research.

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