Jackson Alexandra, Weaver Raven H, Weybright Elizabeth, Lanigan Jane, Parker Louise, Iniguez Anaderi, Decker Autumn
Washington State University, Vancouver, WA, USA.
Washington State University, Pullman, WA, USA.
J Prev Health Promot. 2022 Nov;3(4):539-562. doi: 10.1177/26320770221096839.
The COVID-19 pandemic led to unique, pervasive, and changing global impacts. It is imperative to characterize groups of individuals based on modifiable factors, and to describe how groups have been impacted by the continuing pandemic in the United States to promote health and well-being and to inform preventive interventions. We used latent transition analysis to identify subgroups of modifiable psychosocial, economic, and health risk factors; to explore subgroup shifts across time; and to assess the prevalence of non-modifiable factors associated with subgroup membership. We recruited 450 participants 18 years and older living in the United States to complete a longitudinal survey exploring health during the pandemic. Participants completed three waves of data collection from April to November 2020. We used latent transition analysis to identify statuses, shifts in prevalence over three waves, and the relationships of non-modifiable covariates with each status. Five statuses were identified: high risk together, low risk together, high risk alone, low risk alone, and financial risk together. Statuses were relatively stable over time; the majority (60%-66%) of participants were in statuses categorized by multiple indicators of high modifiable risk, and the largest transitions were to lower risk subgroups. Increasing age, being male, and living in an urban area were the only non-modifiable covariates associated with status membership. It is imperative to continue to scale up targeted interventions aimed at promoting resilience, well-being, financial well-being, delays in healthcare use, food insecurity, and depression among individuals in higher-risk subgroups to promote health and well-being.
新冠疫情带来了独特、普遍且不断变化的全球影响。根据可改变因素对个体群体进行特征描述，并阐述美国持续的疫情如何影响这些群体，对于促进健康和福祉以及为预防性干预措施提供信息而言至关重要。我们使用潜在转变分析来识别可改变的心理社会、经济和健康风险因素的亚组；探索亚组随时间的变化；并评估与亚组成员身份相关的不可改变因素的患病率。我们招募居住在美国的450名18岁及以上的参与者，以完成一项关于疫情期间健康状况的纵向调查。参与者在2020年4月至11月期间完成了三轮数据收集。我们使用潜在转变分析来识别状态、三轮调查中患病率的变化，以及不可改变的协变量与每种状态的关系。识别出了五种状态：高风险聚集、低风险聚集、单独高风险、单独低风险和财务风险聚集。随着时间推移，这些状态相对稳定；大多数（60%-66%）参与者处于由多个高可改变风险指标分类的状态，最大的转变是转向风险较低的亚组。年龄增长、男性身份以及居住在城市地区是与状态成员身份相关的仅有的不可改变的协变量。必须继续扩大有针对性的干预措施，旨在提高高风险亚组个体的恢复力（心理韧性）、福祉、财务状况、延迟医疗使用、粮食不安全和抑郁状况，以促进健康和福祉。
