Bolduc Michele L F, Saberi Parya, Neilands Torsten B, Mercado Carla I, Johnson Shanice Battle, Freggens Zoe R F, Banks Desmond, Njai Rashid, Bullard Kai McKeever
Office of Minority Health, Office of Health Equity, Centers for Disease Control and Prevention (CDC), Atlanta, Georgia, United States of America.
Division of Prevention Science, Department of Medicine, University of California, San Francisco, California, United States of America.
PLoS One. 2025 Jun 4;20(6):e0300939. doi: 10.1371/journal.pone.0300939. eCollection 2025.
A better understanding of whether and how economic factors impact mental health can inform policy and program decisions to improve mental health. This study looked at the association between county-level economic factors and the prevalence of self-reported poor mental health among adults in United States counties in 2019, overall and disaggregated for urban and rural counties. General dominance analyses were completed to rank-order the relative influence of the selected variables in explaining county prevalence of adults reporting > 14 poor mental health days in the last 30 days ("poor mental health"). The highest weighted variables were assessed for the statistical significance of their relationships with county-level poor mental health through multiple linear regression. Across all models, the four highest-ranked economic factors were household income, receipt of Supplemental Security Income, population with a college degree, and receipt of Supplemental Nutrition Assistance Program benefits. The overall, rural, and urban models explained over 68% of the variation in poor mental health prevalence between counties. Urban and rural models showed notable differences in the top factors associated with poor mental health and opposite associations between poor mental health and population with public insurance. The findings from this study indicate a significant association between several economic factors and poor mental health, which may inform decision makers in addressing mental health in the United States.
更好地理解经济因素是否以及如何影响心理健康，可以为改善心理健康的政策和项目决策提供依据。本研究考察了2019年美国各县县级经济因素与成年人自我报告的心理健康状况不佳患病率之间的关联，总体情况以及按城乡县进行了分类分析。完成了一般优势分析，以对选定变量在解释各县报告在过去30天内有超过14天心理健康状况不佳（“心理健康状况不佳”）的成年人患病率方面的相对影响进行排序。通过多元线性回归评估了权重最高的变量与县级心理健康状况不佳之间关系的统计显著性。在所有模型中，排名前四的经济因素是家庭收入、领取补充保障收入、拥有大学学位的人口以及领取补充营养援助计划福利。总体、农村和城市模型解释了各县心理健康状况不佳患病率差异的68%以上。城市和农村模型在与心理健康状况不佳相关的首要因素方面存在显著差异，并且心理健康状况不佳与有公共保险的人口之间存在相反的关联。本研究的结果表明，几个经济因素与心理健康状况不佳之间存在显著关联，这可能为美国决策者解决心理健康问题提供参考。
