Department of Psychology, University of British Columbia, Vancouver, British Columbia, Canada.
Human Flourishing Program, Institute for Quantitative Social Science, Harvard University, Cambridge, Massachusetts, United States of America.
PLoS One. 2022 Nov 10;17(11):e0277222. doi: 10.1371/journal.pone.0277222. eCollection 2022.
As our society ages and healthcare costs escalate, researchers and policymakers urgently seek potentially modifiable predictors of reduced healthcare utilization. We aimed to determine whether changes in 62 candidate predictors were associated with reduced frequency, and duration, of overnight hospitalizations. We used data from 11,374 participants in the Health and Retirement Study-a national sample of adults aged >50 in the United States. Using generalized linear regression models with a lagged exposure-wide approach, we evaluated if changes in 62 predictors over four years (between t0;2006/2008 and t1;2010/2012) were associated with subsequent hospitalizations during the two years prior to t2 (2012-2014 (Cohort A) or 2014-2016 (Cohort B)). After robust covariate-adjustment, we observed that changes in some health behaviors (e.g., those engaging in frequent physical activity had 0.80 the rate of overnight hospital stays (95% CI [0.74, 0.87])), physical health conditions (e.g., those with cancer had 1.57 the rate of overnight hospital stays (95% CI [1.35, 1.82])), and psychosocial factors (e.g., those who helped friends/neighbors/relatives 100-199 hours/year had 0.73 the rate of overnight hospital stays (95% CI [0.63, 0.85])) were associated with subsequent hospitalizations. Findings for both the frequency, and duration, of hospitalizations were mostly similar. Changes in a number of diverse factors were associated with decreased frequency, and duration, of overnight hospitalizations. Notably, some psychosocial factors (e.g., informal helping) had effect sizes equivalent to or larger than some physical health conditions (e.g., diabetes) and health behaviors (e.g., smoking). These psychosocial factors are mostly modifiable and with further research could be novel intervention targets for reducing hospitalizations.
随着社会老龄化和医疗保健成本的不断攀升，研究人员和政策制定者迫切需要寻找可能改变的、降低医疗保健利用的预测指标。我们旨在确定 62 个候选预测指标的变化是否与减少夜间住院的频率和持续时间有关。我们使用了来自美国超过 50 岁成年人的全国样本——健康与退休研究（Health and Retirement Study）的 11374 名参与者的数据。我们使用具有滞后暴露广泛方法的广义线性回归模型，评估了在四年内（在 t0；2006/2008 年和 t1；2010/2012 年之间）62 个预测指标的变化是否与随后在 t2（2012-2014 年（队列 A）或 2014-2016 年（队列 B））之前的两年内的住院有关。在经过稳健的协变量调整后，我们观察到一些健康行为（例如，经常进行身体活动的人，夜间住院率为 0.80（95%CI[0.74,0.87]））、身体健康状况（例如，患有癌症的人，夜间住院率为 1.57（95%CI[1.35,1.82]））和心理社会因素（例如，每年帮助朋友/邻居/亲戚 100-199 小时的人，夜间住院率为 0.73（95%CI[0.63,0.85]））与随后的住院有关。住院的频率和持续时间的发现基本相似。许多不同因素的变化与夜间住院的频率和持续时间减少有关。值得注意的是，一些心理社会因素（例如，非正式帮助）的效应大小与一些身体健康状况（例如，糖尿病）和健康行为（例如，吸烟）相当或更大。这些心理社会因素大多是可改变的，通过进一步研究，它们可能成为减少住院的新的干预目标。
