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

步行的社区障碍和促进因素、膝骨关节炎的流行病学以及制定有效的运动处方

• 批准号: 10599960
• 负责人: Sarah Gebauer
• 金额: $ 15.74万
• 依托单位: SAINT LOUIS UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-04-01 至 2027-01-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10599960
• 关键词: Adult; Affect; American; Area; Award; Big Data; Caring; Characteristics; Chronic Disease; Computerized Medical Record; Country; Crime; Data; Data Set; Degenerative polyarthritis; Development Plans; Diagnosis; Epidemic; Epidemiology; Exercise; Fright; Geographic Information Systems; Geographic Locations; Glean; Goals; Growth; Guidelines; Health; High Prevalence; Individual; Inequality; Information Sciences; Infrastructure; Intervention; Interview; Knee Osteoarthritis; Knowledge; Lead; Life; Link; Measures; Medical; Medical Records; Mentored Patient-Oriented Research Career Development Award; Mentorship; Methodology; Methods; Modeling; Musculoskeletal; Neighborhoods; Obesity; Outcome; Pain; Pain management; Patient Care; Patients; Physical activity; Population; Prevalence; Provider; Public Health; Qualitative Methods; Reporting; Research; Resources; Retrospective cohort; Risk; Risk Factors; Sampling; Series; Social Characteristics; Social Environment; Socioeconomic Status; Symptoms; Time; Training; United States; United States Department of Veterans Affairs; Urban Developments; Veterans; Veterans Health Administration; Walking; big data management; built environment; career development; clinical care; cohort; cost; design; disability; effective therapy; end stage disease; evidence base; exercise prescription; exercise program; experience; follow-up; human old age (65+); improved; innovation; knee replacement arthroplasty; metropolitan; multilevel analysis; neighborhood disadvantage; novel; osteoarthritis pain; pain reduction; pain relief; pain score; pain symptom; patient engagement; primary care provider; public health intervention; sedentary lifestyle; shared decision making; skills; social; social capital; social health determinants; software systems; statistics; violent crime; walkability

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.

在美国，膝骨关节炎 (OA) 是一个代价高昂且日益恶化的问题，有近 1400 万人患有膝骨关节炎 (OA)。 患有疼痛和僵硬症状的成年人。尽管存在许多治疗方法，但它们往往缺乏证据 就功效而言，存在重大风险，或者是难以维持的锻炼计划。走在一个人的身边 Neighborhood 提供了一种低成本的解决方案，已被证明可以控制 OA 症状。然而，大多数 美国人以及大多数 OA 患者都没有进行足够的体力活动。行走的障碍是 社区的建筑和社会环境，例如步行性和对犯罪的恐惧。虽然适合步行 和社会环境与步行和身体活动有关，但尚未有研究将其联系起来 与普遍存在的膝关节骨关节炎的差距。调查和识别步行适宜性和社会环境组成部分 对膝关节骨关节炎的患病率影响最大的因素以及膝关节骨关节炎至终末期全膝关节置换术的轨迹 （TKA）可以提供干预目标。这个为期 5 年的 K23 奖项以及在“大数据”、地理空间方面的强有力指导 信息科学 (GISc) 和定性方法将帮助 Gebauer 博士成为整合领域的领导者 电子病历数据 (EMR) 和 GISc，并获得定性方法方面的技能，以促进混合 方法研究探讨邻里关系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，探索两者之间的关联 社区因素，例如步行适宜性、社会资本、暴力犯罪率和膝关节患病率 利用丰富的退伍军人事务部 (VA) EMR 数据集在美国各地进行 OA 和 TKA。创新的 将使用具有邻里步行适宜性和社会特征的时变测量的 GISc 建模 对全国各地的退伍军人进行 11 年来的动态回顾，提供急需的信息 纵向数据为公共卫生行动提供证据。定性方法和 通过对初级保健提供者 (PCP) 和 OA 进行定性访谈，三角测量将有助于实现目标 3 帮助患者了解患者或 PCP 对社区障碍和资源的了解如何 用于加强 PCP 和患者之间的共同决策，并围绕 步行治疗膝关节骨关节炎。 通过完成这些目标和纵向/多层次建模的额外培训 策略、资助以及与社区和体育活动专家的联系，格鲍尔博士 将提供膝关节 OA 的新危险因素和 TKA 时间，引入创新的空间生存模型 慢性病流行病学，以及对患者及其患者共同决策的新理解 PCP，为后续 R01 研究提供数据，研究邻里特征的整合 增加膝骨关节炎患者的步行次数，在平民和其他大都市地区重复这项研究， 并开始探索其他因在附近散步而受益的肌肉骨骼状况。