Neighborhood Risk Factors for Falls in the Elderly

老年人跌倒的社区危险因素

• 批准号: 10396681
• 负责人: Wenjun Li
• 金额: $ 62.71万
• 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/10396681
• 关键词: 3-Dimensional; Accelerometer; Address; Adult; Age; Aging; Area; Asian population; Automobile Driving; Behavioral; Black Populations; 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; Hispanic Populations; 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; 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.

项目摘要 跌倒是老年人受伤的主要原因。预防秋季伤害是国家公共卫生 优先事项。迄今为止，大多数关于老年人跌倒的研究是在非西班牙裔白人种群中进行的 在城市地区。关于跌倒之间的发生率，情况和后果知之甚少 居住在粗糙和郊区社区以及种族/族裔少数民族中的老年人。据我们所知， 没有对瀑布的研究研究老年人的空间和时间在粗糙，郊区和城市 社区，以及这种差异与跌倒风险有何关系。为了填补这个知识差距，这个项目 将调查1）在时间和空间使用的崎and，性别和种族/种族差异以及 位置和活动特定的跌倒； 2）时间和空间使用如何影响室内和室外瀑布的风险 在城市，郊区和粗糙社区的老年人中； 3）什么个人和 邻居级别的因素可以预测时空的时间和时间使用以及特定于位置和活动特定的下降。使用 综合数据，4）我们将开发针对位置和活动特异性下降的个性化预测模型。 我们建议建立一个大致和种族多样化的，性别平衡的纵向人群为1,252 马萨诸塞州中部65岁及以上的成年人，包括500名来自Urban的成年人，郊区的500名和252 来自粗糙的地区，600名（48％）非西班牙裔白人和652（52％）种族/族裔少数民族（218个非西班牙裔 黑人，218个西班牙裔和216个亚洲人/其他比赛）。参与者将每6个月每6个月遵循3年 跟踪他们的跌倒，流动性，活动模式，残疾，健康和健康行为。秋季事件将被跟踪 如果发生秋季，请使用每月跌倒日历和后续电话调查。参与者的流动模式与 尊重空间，频率和持续时间将使用全球定位系统（GPS）单元进行衡量，并且 参与室内和室外活动的时间，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个月时测量。在2年和第3年的随访中， 参与者将使用家庭访问，邮件或电话调查每年两次查询健康状况 习惯和健康状况。 GPS和加速度计数据将与参与者报告的 健康，感知和行为数据以及邻里环境数据。这些数据将是 集成和分析以实现上述分析目标。 这些研究结果将为基于社区的计划设计，以促进积极的生活和 防止在所有种族/种族中以及整个农村地区的性别中有效的跌倒 连续。基于本研究中要开发的个性化秋季风险预测模型，我们将设计 并在随后的随后临床试验研究中测试个性化（精度）预防方法。