{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,24]],"date-time":"2025-08-24T01:27:26Z","timestamp":1755998846513},"reference-count":53,"publisher":"Oxford University Press (OUP)","issue":"1","license":[{"start":{"date-parts":[[2008,1,1]],"date-time":"2008-01-01T00:00:00Z","timestamp":1199145600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/journals\/pages\/open_access\/funder_policies\/chorus\/standard_publication_model"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2008,1,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Osteoporosis public health measures are hindered by the inability to easily identify subclinical disease. We have now estimated state-specific osteoporosis prevalences using a simple formula (OST Index) to analyze age and weight of 62,882 older women; the prevalences determined are similar to those based on BMD. This new method has potential use for guiding implementation of osteoporosis prevention\/treatment programs.<\/jats:p>\n               <jats:p>Introduction: Although osteoporosis-related fractures are a major U.S. public health issue, population-based prevention programs have not yet been developed. One contributing factor has been lack of a suitable screening test to detect asymptomatic high-risk individuals.<\/jats:p>\n               <jats:p>Materials and Methods: We estimated state-specific prevalences of postmenopausal osteoporosis using the Osteoporosis Self-Assessment Tool Index (OST Index; [self-reported weight in kg - age] \u00d7 0.2) to analyze data from 62,882 women \u226550 yr of age who participated in the 2002 Behavioral Risk Factor Surveillance System (BRFSS). The OST Index, designed to assess an individual's risk of disease, has previously been shown to have modest positive and high negative predictive value for osteoporosis defined by BMD criteria. Based on this index, women from each state were distributed among high-, moderate-, and low-risk OST categories. Calculated percentages for each category were weighted to U.S. Census Bureau population projections for 2002. By adjusting results to reflect previously validated percentages of women with osteoporosis in each risk category, we estimated the prevalence of postmenopausal osteoporosis in each state.<\/jats:p>\n               <jats:p>Results: Our calculated weighted prevalence estimates agreed closely with those of the National Osteoporosis Foundation derived from actual femoral neck BMD measurements obtained in the third National Health and Nutrition Examination Survey (1988-1994) and projected to U.S. census state population predictions for 2002. Comparison of unweighted BRFSS-OST results and NHANES BMD data revealed similar percentages of osteoporosis among all women \u226550 yr of age (BRFSS, 18.5%; NHANES, 18.0%; p = 0.47) and also among white women (BRFSS, 19.0%; NHANES, 20.0%; p = 0.28). However, the percentages of osteoporosis among blacks and Hispanics did not correspond, at least partly because of the lack of race-specific reference standards for BMD measurements and OST index ranges.<\/jats:p>\n               <jats:p>Conclusions: Analysis of readily available BRFSS data with the OST index formula is a simple, no-cost technique that provides state prevalence estimates of postmenopausal osteoporosis that could be used to guide allocation of resources to statewide osteoporosis prevention programs.<\/jats:p>","DOI":"10.1359\/jbmr.071005","type":"journal-article","created":{"date-parts":[[2007,10,1]],"date-time":"2007-10-01T13:55:54Z","timestamp":1191246954000},"page":"151-158","source":"Crossref","is-referenced-by-count":6,"title":["Assessing Population Risk for Postmenopausal Osteoporosis: A New Strategy Using Data From the Behavioral Risk Factor Surveillance System (BRFSS)"],"prefix":"10.1093","volume":"23","author":[{"given":"Christine R","family":"Schneyer","sequence":"first","affiliation":[{"name":"Division of Endocrinology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Helio","family":"Lopez","sequence":"additional","affiliation":[{"name":"Maryland Department of Health and Mental Hygiene, Baltimore, Maryland, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mary","family":"Concannon","sequence":"additional","affiliation":[{"name":"University of Maryland Cooperative Extension, Timonium, Maryland, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Marc C","family":"Hochberg","sequence":"additional","affiliation":[{"name":"Departments of Medicine and Epidemiology and Preventive Medicine, University of Maryland School of Medicine, Baltimore, Maryland, 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