Neighborhood Barriers and Facilitators to Walking, the Epidemiology of Knee Osteoarthritis and Developing Effective Exercise Prescriptions

膝关节骨关节炎（OA）是一个昂贵的和恶化的问题，在美国有近1400万 患有疼痛和僵硬症状的成年人。虽然有许多治疗方法，但往往缺乏证据。 有效性，风险很大，或者是难以维持的锻炼计划。走在一个 邻里提供了一个低成本的解决方案，已被证明可以控制OA症状。但大多数 此外，大多数OA患者没有进行足够的体力活动。步行障碍包括 建筑和社会环境在他们的邻居，如步行和犯罪的恐惧。虽然步行 和社会环境与步行和身体活动有关，但还没有研究表明 膝关节OA患病率的差距。调查和确定步行性和社会环境要素 最影响膝关节OA患病率和膝关节OA到终末期全膝关节置换术的轨迹 (TKA)可以提供干预的目标。这个为期5年的K23奖项和在“大数据”、地理空间 信息科学（GISc）和定性方法将帮助Gebauer博士成为整合的领导者。 电子病历数据（EMR）和地理信息系统c，并获得定性方法的技能，以促进混合 方法研究探讨邻里对步行和疼痛状况的影响。空间训练 统计和“大数据”管理将促进目标1和2，探索 邻里因素，如步行能力，社会资本，暴力犯罪率和膝关节炎的流行情况， 利用丰富的退伍军人事务部（VA）电子病历数据集，在美国各地进行OA和全膝关节置换术。创新 将使用GISc建模，其中包含随时间变化的街区步行能力和社会特征测量 在一个动态的回顾性队列中跟踪全国各地的退伍军人11年， 纵向数据，为公共卫生行动提供依据。质量方法培训， 三角测量将促进目标3，使用与初级保健提供者（PCP）和OA的定性访谈 帮助患者了解患者或PCP如何了解社区障碍和资源， 用于加强PCP和患者之间的共同决策，并建立 步行治疗膝关节OA。 通过完成这些目标和在纵向/多层次建模方面的额外培训， Gebauer博士说， 将为膝关节OA和TKA时间提供新的风险因素，引入创新的空间生存模型， 慢性病流行病学，以及对患者及其家属共同决策的新理解。 PCP，为后续R 01研究提供数据，研究邻里特征的整合， 增加膝关节骨性关节炎患者的行走，在平民和其他大都市地区复制这项研究， 并开始探索其他肌肉骨骼条件，受益于步行在附近。

Knee osteoarthritis (OA) is a costly and worsening problem in the United States with nearly 14 million adults suffering with symptoms of pain and stiffness. Although many treatments exist, they often lack evidence for efficacy, bare significant risk, or are exercise programs that are difficult to maintain. Walking in one’s neighborhood provides a low-cost solution that has been shown to control OA symptoms. However, most Americans, and further, most OA patients do not engage in enough physical activity. Barriers to walking are built and social environment in their neighborhood, such as walkability and fear of crime. Although walkability and social environment have been associated with walking and physical activity, no studies have yet bridged the gap to prevalent knee OA. Investigating and identifying walkability and social environmental components that most influence prevalence of knee OA and trajectory of knee OA to end stage total knee arthroplasty (TKA) can offer targets for intervention. This 5-year K23 award and strong mentorship in “Big Data”, Geospatial Information Science (GISc) and qualitative methods will help Dr. Gebauer become a leader in integrating Electronic Medical Record Data (EMR) and GISc and gain skills in qualitative methodology to facilitate mixed methods studies to explore the influence of neighborhood on walking and painful conditions. Training in spatial statistics and “Big Data” management will facilitate Aims 1 & 2, exploring the associations between neighborhood factors, such as walkability, social capital, and violent crime rates and prevalent cases of knee OA, as well as TKA across the United States utilizing the rich Veterans Affairs (VA) EMR Data set. Innovative GISc modeling with time-varying measures of neighborhood walkability and social characteristics will be used to follow veterans across the country in a dynamic retrospective cohort for 11 years, providing much needed longitudinal data to offer evidence to inform public health action. Training in qualitative methods and triangulation will facilitate Aim 3, using qualitative interviews with primary care providers (PCPs) and OA patients to help understand how patient or PCP knowledge of neighborhood barriers and resources can be leveraged to enhance shared decision making between PCPs and patients and establish concordance around walking for knee OA treatment. Through the completion of these aims and additional training in longitudinal/multilevel modeling strategies, grantsmanship, and networking with experts in neighborhoods and physical activity, Dr. Gebauer will provide novel risk factors for knee OA and time to TKA, introduce innovative spatial survival models to chronic disease epidemiology, as well as a new understanding of shared decision making for patients and their PCPs, providing data for follow up R01 studies examining integration of neighborhood characteristics to increase walking in knee OA patients, replicating this study in civilian populations and other metropolitan areas, and begin to explore other musculoskeletal conditions that benefit from walking in the neighborhood.