Omidvar Sedigheh, Jafari Jozani Mohammad, Nematollahi Nader, Leslie Wiliam D
Department of Statistics, Allameh Tabataba'i University, Tehran, Iran.
Department of Statistics, University of Manitoba, Winnipeg, Canada.
J Appl Stat. 2023 Sep 24;51(11):2090-2115. doi: 10.1080/02664763.2023.2260572. eCollection 2024.
Osteoporosis is a metabolic bone disorder that is characterized by reduced bone mineral density (BMD) and deterioration of bone microarchitecture. Osteoporosis is highly prevalent among women over 50, leading to skeletal fragility and risk of fracture. Early diagnosis and treatment of those at high risk for fracture is very important in order to avoid morbidity, mortality and economic burden from preventable fractures. The province of Manitoba established a BMD testing program in 1997. The Manitoba BMD registry is now the largest population-based BMD registry in the world, and has detailed information on fracture outcomes and other covariates for over 160,000 BMD assessments. In this paper, we develop a number of methodologies based on ranked-set type sampling designs to estimate the prevalence of osteoporosis among women of age 50 and older in the province of Manitoba. We use a parametric approach based on finite mixture models, as well as the usual approaches using simple random and stratified sampling designs. Results are obtained under perfect and imperfect ranking scenarios while the sampling and ranking costs are incorporated into the study. We observe that rank-based methodologies can be used as cost-efficient methods to monitor the prevalence of osteoporosis.
骨质疏松症是一种代谢性骨病，其特征是骨矿物质密度（BMD）降低和骨微结构恶化。骨质疏松症在50岁以上的女性中非常普遍，会导致骨骼脆弱和骨折风险。为了避免可预防骨折带来的发病率、死亡率和经济负担，对骨折高危人群进行早期诊断和治疗非常重要。曼尼托巴省于1997年设立了骨密度检测项目。曼尼托巴骨密度登记处现在是世界上最大的基于人群的骨密度登记处，拥有超过160,000次骨密度评估的骨折结果和其他协变量的详细信息。在本文中，我们基于排序集抽样设计开发了一些方法，以估计曼尼托巴省50岁及以上女性骨质疏松症的患病率。我们使用基于有限混合模型的参数方法，以及使用简单随机和分层抽样设计的常用方法。在完美和不完美排序情况下获得结果，同时将抽样和排序成本纳入研究。我们观察到基于排序的方法可以用作监测骨质疏松症患病率的经济有效方法。
