Gaydosh Lauren, Kelly Audrey, Gutin Iliya, Shanahan Lilly, Godwin Jennifer, Harris Kathleen Mullan, Copeland William
Department of Sociology and the Carolina Population Center, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599 USA.
Carolina Population Center, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599 USA.
Popul Res Policy Rev. 2025;44(3):33. doi: 10.1007/s11113-025-09952-4. Epub 2025 May 13.
Working age (25-64) mortality in the US has been increasing for decades, driven in part by rising deaths due to drug overdose, as well as increases in suicide and alcohol-related mortality. These deaths have been hypothesized by some to be due to despair, but this has rarely been empirically tested. For despair to explain mortality due to alcohol-related liver disease, suicide, and drug overdose, it must first predict the behaviors that lead to such causes of death. To that end, we aim to answer two research questions. First, does despair predict the behaviors that are antecedent to the "deaths of despair"? Second, what measures and domains of despair are most important? We use data from over 6000 individuals at five waves of the National Longitudinal Study of Adolescent to Adult Health and apply supervised machine learning to assess the role of despair in predicting self-destructive behaviors associated with these causes of death. Comparing predictive performance within each outcome using measures of despair to benchmark models of clinical and prior behavioral predictors, we evaluate the added predictive value of despair above and beyond established risk factors. We find that despair underperforms compared to clinical risk factors for suicidal ideation and heavy drinking, but over performs compared to clinical risk factors and prior behaviors for illegal drug use and prescription drug misuse. We also compare model performance and feature importance across outcomes; our ability to predict thoughts of suicide, drug abuse and misuse, and heavy drinking differs depending on the behavior, and the relative importance of different indicators of despair varies across outcomes as well. Our findings suggest that the self-destructive behaviors are distinct and the pathways from despair to self-destructive behavior varied. The results draw into question the relevance of despair as a unifying framework for understanding the current crisis in midlife health and mortality.
几十年来,美国劳动年龄(25至64岁)人口的死亡率一直在上升,部分原因是药物过量导致的死亡人数增加,以及自杀和酒精相关死亡率的上升。一些人推测这些死亡是由于绝望,但这很少得到实证检验。要使绝望能够解释与酒精相关的肝病、自杀和药物过量导致的死亡,它必须首先预测导致这些死亡原因的行为。为此,我们旨在回答两个研究问题。第一,绝望是否能预测“绝望死亡”之前的行为?第二,绝望的哪些测量指标和领域最为重要?我们使用来自全国青少年健康纵向研究(National Longitudinal Study of Adolescent to Adult Health)五轮调查中6000多名个体的数据,并应用监督机器学习来评估绝望在预测与这些死亡原因相关的自我毁灭行为中的作用。我们使用绝望的测量指标与临床和先前行为预测因素的基准模型进行比较,以评估每个结果中的预测性能,从而评估绝望在既定风险因素之上的额外预测价值。我们发现,与自杀意念和酗酒的临床风险因素相比,绝望的预测表现较差,但与非法药物使用和处方药滥用的临床风险因素及先前行为相比,绝望的预测表现较好。我们还比较了不同结果的模型性能和特征重要性;我们预测自杀念头、药物滥用和酗酒的能力因行为而异,绝望的不同指标的相对重要性在不同结果中也有所不同。我们的研究结果表明,自我毁灭行为各不相同,从绝望到自我毁灭行为的途径也多种多样。这些结果让人质疑绝望作为理解当前中年健康和死亡率危机的统一框架的相关性。