Greenfield A P, Banerjee S, Depasquale A, Weiss N, Sirey J
J Frailty Aging. 2016;5(3):149-157.
This study used the Evans model of public health determinants to identify factors associated with nutritional risk in older adults.
The Evans model domains (physical and mental well-being, social/environmental statuses, individual choice, and economic security) were measured in a sample of homebound older adults. Regularized logistic regression analysis with LASSO penalty function was used to determine the strongest domain of the Evans model. Using traditional logistic regression, individual variables across all domains were compared to identify the significant predictors.
Older adults receiving home meal services were referred to the study by community program staff.
Participants included 164 homebound older adults (age > 60) who endorsed at least one gateway symptom of depression.
Measurements: Nutritional risk was determined using the Mini Nutritional Assessment. Domains of the Evans model were measured using the MAI Medical Condition Checklist, items from the IADL scale, the Structured Clinical Interview for DSM-IV Axis I Disorders, the Duke Social Support Index, living arrangements, marital status, the Alcohol Use Disorders Identification Test, items from the SCID Screening Module, and a self-report of perceived financial security.
Poor mental well-being, defined by a diagnosis of major depressive disorder, was identified as the strongest Evans model domain in the prediction of nutritional risk. When each variable was independently evaluated across domains, instrumental support (Wald’s Z=-2.24, p=0.03) and a history of drug use (Wald’s Z=-2.40, p=0.02) were significant predictors.
The Evans model is a useful conceptual framework for understanding nutritional health, with the mental domain found to be the strongest domain predictor of nutritional risk. Among individual variables across domains, having someone to help with shopping and food preparation and a history of drug use were associated with lower nutritional risk. These analyses highlight potential targets of intervention for nutritional risk among older adults.
本研究采用埃文斯公共卫生决定因素模型来确定与老年人营养风险相关的因素。
在居家老年人样本中测量埃文斯模型的各个领域（身心健康、社会/环境状况、个人选择和经济安全）。使用带有LASSO惩罚函数的正则化逻辑回归分析来确定埃文斯模型中最强的领域。使用传统逻辑回归，比较所有领域的个体变量以识别显著的预测因素。
接受上门送餐服务的老年人由社区项目工作人员转介到本研究。
参与者包括164名居家老年人（年龄>60岁），他们认可至少一种抑郁症的入门症状。
使用微型营养评定法确定营养风险。使用MAI医疗状况检查表、IADL量表项目、DSM-IV轴I障碍结构化临床访谈、杜克社会支持指数、生活安排、婚姻状况、酒精使用障碍识别测试、SCID筛查模块项目以及感知财务安全的自我报告来测量埃文斯模型的各个领域。
在预测营养风险方面，以重度抑郁症诊断定义的心理健康不佳被确定为埃文斯模型中最强的领域。当对每个变量在各个领域进行独立评估时，工具性支持（Wald Z=-2.24，p=0.03）和药物使用史（Wald Z=-2.40，p=0.02）是显著的预测因素。
埃文斯模型是理解营养健康的有用概念框架，其中心理领域被发现是营养风险最强的领域预测因素。在各个领域的个体变量中，有人帮忙购物和准备食物以及药物使用史与较低的营养风险相关。这些分析突出了老年人营养风险干预的潜在目标。
