Neighborhood Risk Factors for Falls in the Elderly

老年人跌倒的社区危险因素

• 批准号: 10342708
• 负责人: Wenjun Li
• 金额: $ 63.88万
• 依托单位: UNIVERSITY OF MASSACHUSETTS LOWELL
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-01 至 2025-04-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10342708
• 关键词: 3-Dimensional; Accelerometer; Address; Adult; Age; Aging; Area; Asians; Automobile Driving; Behavioral; Calendar; Communities; Data; Development; Devices; Elderly; Environment; Epidemiology; Ethnic group; Event; Exercise; Exposure to; Fall prevention; Fitness Centers; Formulation; Frequencies; Gender; Global Positioning System; Goals; Habits; Health; Health Status; Health behavior; Hispanics; Home visitation; Housing; Individual; Injury; Interview; Knowledge; Life Style; Living Arrangement; Location; Longitudinal cohort; Massachusetts; Measures; Medicaid; Medical Care Costs; Medicare; Methodology; Neighborhoods; Not Hispanic or Latino; Participant; Pattern; Perception; Personal Attribute; Persons; Physical Function; Physical activity; Population; Population Density; Predictive Factor; Prevention approach; Race; Randomized Clinical Trials; Reporting; Research; Resources; Risk; Risk Factors; Rural; Socioeconomic Status; Surveys; Telephone; Testing; Time; Walking; Woman; active lifestyle; base; cohort; community based research; density; design; disability; ethnic difference; ethnic diversity; ethnic minority population; fall injury; fall risk; falls; follow-up; gender disparity; hazard; high risk; human old age (65+); innovation; men; novel; older men; payment; personalized predictions; personalized risk prediction; personalized strategies; predictive modeling; programs; public health priorities; racial and ethnic; racial and ethnic disparities; racial disparity; racial diversity; risk prediction model; rural area; rural disparities; rural dwellers; socioeconomics; suburb; time use; urban area; urban disparity; urban setting

Project summary Falls are the leading cause of injuries in older adults. Prevention of fall injuries is a national public health priority. To date, most of the studies on falls in older adults were conducted in non-Hispanic White populations in urban areas. Little is known about the occurrence rates, circumstances and consequences of falls among older adults living in rural and suburban neighborhoods, and among racial/ethnic minorities. To our knowledge, no study on falls has examined how older adults’ space and time use differ in rural, suburban and urban neighborhoods, and how such differences are related to risk of falling. To fill in this knowledge gap, this project will investigate 1) the rural-urban, gender and racial/ethnic differences in time and space use and rates of location- and activity-specific falls; 2) how time and space use influence risks for indoor and outdoor falls among older adults living in urban, suburban and rural neighborhoods; and 3) what personal and neighborhood-level factors are predictive of space and time use and location- and activity-specific falls. Using the integrated data, 4) we will develop personalized prediction models for location- and activity-specific falls. We propose to establish a racially and ethnically diverse, gender-balanced longitudinal cohort of 1,252 adults age 65 years and older in Central Massachusetts, including 500 from urban, 500 from suburban and 252 from rural areas, and 600 (48%) non-Hispanic Whites and 652 (52%) racial/ethnic minorities (218 non-Hispanic Blacks, 218 Hispanics and 216 Asians/other races). Participants will be followed every 6 months for 3 years to track their falls, mobility, activity patterns, disability, health and health behaviors. Fall events will be tracked using monthly falls calendars and follow-up telephone surveys if a fall occurs. Participant mobility patterns with respect to space, frequency and duration will be measured using a global positioning system (GPS) unit, and participant timing, frequency, duration and intensity of indoor and outdoor activities will be concurrently measured using an accelerometer, at baseline, 6, 24 and 30 months. During the follow-up years 2 and 3, participants will be followed using in-home visits, mail or telephone surveys twice a year querying their health habits and health status. The GPS and accelerometer data will be integrated with the participant’s reported health, perception and behavioral data as well as neighborhood environment data. These data will be integrated and analyzed to achieve the above analytic goals. These study results will inform the design of community-based programs for promoting active living and preventing falls that will be effective in both genders, among all racial/ethnic groups and across the rural-urban continuum. Based on the personalized fall risk prediction models to be developed in this study, we will design and test personalized (precision) falls prevention approaches in a subsequent randomized clinical trial study.

项目概要 跌倒是老年人受伤的主要原因。预防跌倒伤害是全民健康 优先事项。迄今为止，大多数关于老年人跌倒的研究都是在非西班牙裔白人群体中进行的 在城市地区。人们对跌倒的发生率、情况和后果知之甚少 居住在农村和郊区以及少数种族/族裔的老年人。据我们所知， 尚无关于跌倒的研究探讨农村、郊区和城市老年人的空间和时间利用有何不同 社区，以及这些差异如何与跌倒风险相关。为了填补这一知识空白，该项目 将调查 1) 城乡、性别和种族/族裔在时间和空间使用以及使用率方面的差异 特定地点和活动的跌倒； 2) 时间和空间使用如何影响室内和室外跌倒风险 居住在城市、郊区和农村社区的老年人； 3) 个人和 邻里层面的因素可以预测空间和时间的使用以及特定位置和活动的跌倒。使用 综合数据，4）我们将为特定位置和特定活动的跌倒开发个性化预测模型。 我们建议建立一个种族和族裔多样化、性别平衡的纵向队列，共 1,252 名 马萨诸塞州中部 65 岁及以上的成年人，其中 500 名来自城市，500 名来自郊区，252 名来自郊区 来自农村地区的 600 名 (48%) 非西班牙裔白人和 652 名 (52%) 少数族裔/族裔（218 名非西班牙裔） 黑人、218 西班牙裔和 216 亚洲人/其他种族）。参与者将每 6 个月接受一次随访，持续 3 年，以便 跟踪他们的跌倒、行动能力、活动模式、残疾、健康和健康行为。将跟踪秋季事件 使用每月跌倒日历并在发生跌倒时进行后续电话调查。参与者的流动模式 空间、频率和持续时间将使用全球定位系统（GPS）单元进行测量，并且 参与者室内外活动的时间、频率、持续时间和强度将同时进行 使用加速度计在基线、6、24 和 30 个月时进行测量。在随后的第 2 年和第 3 年中， 每年两次通过家访、邮件或电话调查的方式对参与者进行跟踪，询问他们的健康状况 生活习惯和健康状况。 GPS 和加速度计数据将与参与者报告的数据集成 健康、感知和行为数据以及邻里环境数据。这些数据将 进行综合分析，以实现上述分析目标。 这些研究结果将为设计基于社区的项目提供信息，以促进积极的生活和 预防跌倒对男女、所有种族/族裔群体以及整个城乡都有效 连续体。基于本研究将开发的个性化跌倒风险预测模型，我们将设计 并在随后的随机临床试验研究中测试个性化（精确）跌倒预防方法。