Department of Research, Cizik School of Nursing, University of Texas Health Science Center, Houston, Texas, United States of America.
School of Social Work, Temple University, Philadelphia, Pennsylvania, United States of America.
PLoS One. 2022 Aug 24;17(8):e0272614. doi: 10.1371/journal.pone.0272614. eCollection 2022.
The purpose of the current study was to use a social determinants of health (SDOH) framework and latent class analysis (LCA) to identify risk classes among mothers with young children. The risk classes were then used to predict food insecurity severity and stability/change of food insecurity over time.
The secondary data from the Fragile Families and Child Wellbeing Study (n = 2,368; oversampled for non-marital births) was used in this study. Household food insecurity was assessed using the 18-items USDA Food Security Survey. A seventeen-item inventory of educational, economic stability, incarceration (i.e. social context), neighborhood safety (i.e. neighborhood and built environment), health and health care, and substance use behaviors at baseline/Year-1 were included to identify SDOH risk indicators in the LCA. Covariate-adjusted multinomial logistic regression models were used to examine the relation between risk classes at Year-1 and the severity of food insecurity at Year-3 and stability/change of food insecurity between Year-3 and Year -5.
LCA identified five risk classes: High utility and medical hardship (Class 1), high housing and employment hardship, high substance use, and incarceration (Class 2), high housing and medical hardship, poor health, and health care (Class 3), high employment hardship and low-income (Class 4) and low-risk (Class 5). The Class 1, Class 2 and Class 3 had greater odds of low food security and very low food security at Year-3 compared to Class 4. In addition, compared to Class 4, Class 1, Class 2 and Class 3 had greater odds unstable food insecurity and persistent food insecurity over time.
LCA could be used to identify distinctive family system risk profiles predictive of food insecurity. The generated risk profiles could be used by health care providers as an additional tool to identify families in need for resources to ensure household food security.
本研究旨在使用社会决定因素健康(SDOH)框架和潜在类别分析(LCA)来识别有年幼子女的母亲的风险类别。然后,使用这些风险类别来预测食品不安全的严重程度以及食品不安全的稳定性/变化。
本研究使用了脆弱家庭和儿童福利研究(n = 2368;非婚生子女进行了过采样)的二次数据。家庭食品不安全状况使用美国农业部食品安全调查的 18 项进行评估。在基线/第 1 年时,包括了 17 项教育、经济稳定、监禁(即社会背景)、邻里安全(即邻里和建筑环境)、健康和医疗保健以及物质使用行为的清单,以确定 LCA 中的 SDOH 风险指标。调整协变量的多项逻辑回归模型用于检验第 1 年的风险类别与第 3 年食品不安全严重程度以及第 3 年至第 5 年食品不安全稳定性/变化之间的关系。
LCA 确定了五个风险类别:高效用和医疗困难(第 1 类)、高住房和就业困难、高物质使用和监禁(第 2 类)、高住房和医疗困难、健康状况不佳和医疗保健(第 3 类)、高就业困难和低收入(第 4 类)和低风险(第 5 类)。与第 4 类相比,第 1 类、第 2 类和第 3 类在第 3 年时低食品安全性和极低食品安全性的可能性更大。此外,与第 4 类相比,第 1 类、第 2 类和第 3 类在第 3 年时不稳定的食品不安全和持续的食品不安全的可能性更大。
LCA 可用于识别具有预测食品不安全的独特家庭系统风险特征。生成的风险特征可以由医疗保健提供者用作额外的工具,以识别需要资源以确保家庭食品安全的家庭。