Brookdale Department of Geriatrics and Palliative Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
Department of Population Health Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
J Am Geriatr Soc. 2023 Jul;71(7):2163-2171. doi: 10.1111/jgs.18295. Epub 2023 Mar 6.
Homebound status is a final common pathway for people with a variety of diseases and conditions. There are 7 million homebound older adults in the United States. Despite concerns regarding their high healthcare costs and utilization and limited access to care, the unique subsets within the homebound population are understudied. Better understanding of distinct homebound groups may enable more targeted and tailored approaches to care delivery. Therefore, in a nationally representative sample of homebound older adults we used latent class analysis (LCA) to examine distinct homebound subgroups based on clinical and sociodemographic characteristics.
Using data from the National Health and Aging Trends Study (NHATS) 2011-2019, we identified 901 newly homebound persons (defined as never/rarely leaving home or leaving home only with assistance and/or difficulty). Sociodemographic, caregiving context, health and function, and geographic covariates were derived from NHATS via self-report. LCA was used to identify the existence of distinct subgroups within the homebound population. Indices of model fit were compared for models testing 1-5 latent classes. Association between latent class membership and 1 year mortality was examined using a logistic regression.
We identified four classes of homebound individuals differentiated by their health, function, sociodemographic characteristics, and caregiving context: (i) Resource constrained (n = 264); (ii) Multimorbid/high symptom burden (n = 216); (iii) Dementia/functionally impaired (n = 307); (iv) Older/assisted living (n = 114). One year mortality was highest among the older/assisted living subgroup (32.4%) and lowest among the resource constrained (8.2%).
This study identifies subgroups of homebound older adults characterized by distinct sociodemographic and clinical characteristics. These findings will support policymakers, payers, and providers in targeting and tailoring care to the needs of this growing population.
居家状态是患有各种疾病和病症的人的最终共同途径。美国有 700 万居家的老年人。尽管人们对他们高昂的医疗保健费用和利用率以及有限的获得护理的机会表示关注，但居家人群中的独特亚组仍未得到充分研究。更好地了解不同的居家群体可能会为提供更有针对性和量身定制的护理方法提供支持。因此，我们在一项具有全国代表性的居家老年人样本中，使用潜在类别分析（LCA）根据临床和社会人口统计学特征来检查不同的居家亚组。
使用来自国家健康老龄化趋势研究（NHATS）2011-2019 年的数据，我们确定了 901 名新居家的人（定义为从未/很少离开家或仅在帮助和/或困难的情况下离开家）。社会人口统计学、护理背景、健康和功能以及地理协变量是通过 NHATS 中的自我报告得出的。LCA 用于识别居家人群中存在的不同亚组。比较了用于测试 1-5 个潜在类别的模型的拟合指数。使用逻辑回归检查潜在类别成员与 1 年死亡率之间的关联。
我们确定了四种居家个体的类别，这些类别通过他们的健康、功能、社会人口统计学特征和护理背景来区分：（i）资源受限（n=264）；（ii）多种疾病/高症状负担（n=216）；（iii）痴呆症/功能受损（n=307）；（iv）老年人/辅助生活（n=114）。老年人/辅助生活亚组的一年死亡率最高（32.4%），资源受限亚组的死亡率最低（8.2%）。
本研究确定了居家老年人的亚组，这些亚组具有不同的社会人口统计学和临床特征。这些发现将为政策制定者、支付者和提供者提供支持，以针对这一不断增长的人群的需求进行目标定位和定制护理。
