基于潜在剖面分析的 老年人抑郁分型及相关因素. (Chinese)

Objective: To evaluate the association between depressive subtypes(based on latent profile analysis) and related factors. Methods: Data from 8526 elderly persons who participated in the health study in Shanxi,China were used The depression symptoms, behaviors and social support of the elderly were investigated with the Self-rating Depression Scale(SDS), Health-Promoting Lifestyle Profile(HPLP-C) and Social Support Rating Scale(SSRS). Latent profile analysis was used to classified depression symptoms and regression mixture modeling(R3 STEP) was used to analyze their predictors of the elderly. Results: Classes of depression in the elderly were characterized using "low risk group"(C1,35.6%), "high depression-stable group"(C2,33.3%),and "low depression-unstable group"(C3,31.1 %).Self-actualization(OR=0.85,0.84),health responsibility(OR=1.25,1.12),nutrition(OR=0.79,0.90),SSRS score(OR=0.95,0.97), 80 years old and above(OR=1.36,1.33),and secondary education(OR=0.71,0.81) were common predictors of the C2 and C3. Conclusion: The depression of the elderly may be considered to 3 subtypes, according to the characteristics and related factors of different subtypes,targeted interventions should be carried out, and "low depression-unstable group" should be focused on. [ABSTRACT FROM AUTHOR]

目的：利用潜在剖面分析辨别老年人抑郁亚型，并分析抑郁亚型相关因素。方法：在社区选取8526名老年人，使用Zung抑郁自评量表（SDS）、健康促进生活方式量表（HPLP-C）、社会支持评定量表（SSRS）调查抑郁状况、行为方式和社会支持。利用潜在剖面分析对抑郁进行分型，采用回归混合模型（R3STEP）分析各类别的预测因子。结果：老年人抑郁可分为“抑郁低风险型”（C1,35.6%）、“高抑郁-稳定型”（C2,33.3%）及“低抑郁-不稳定型”（C3,31.1%）。以C1为参照，自我实现（OR=0.85、0.84）、健康责任（OR=1.25、1.12）、营养（OR=0.79、0.90）、SSRS得分（OR=0.95、0.97）、≥80岁（OR=1.36、1.33）、中等教育及以下（OR=0.71、0.81）是C2和C3的共性预测因子。结论：本研究提示，老年人抑郁存在不同的特征群体，应重点关注“低抑郁-不稳定型”老年人。 [ABSTRACT FROM AUTHOR]

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