Applying latent growth mixture modeling (GMM), this study delves into the examination of self-esteem trajectories in a sample of 5,597 older adults over a nine-year period. Four distinct patterns of self-esteem changes have emerged: low, decreasing, increasing, and high. Additionally, the study explores the relationships between each trajectory and various predictors encompassing demographic factors, socioeconomic status, health, and interpersonal relationships. The findings highlight the significance of these factors in predicting the likelihood of an individual following a specific self-esteem trajectory. Notably, maintaining employment, fostering satisfactory social relationships, and being free of frequent depressive feelings emerged as strong predictors for the stability and increase of high self-esteem. Intriguingly, an average or above-average income was unexpectedly associated with lower levels of self-esteem. The study emphasizes the contribution of GMM to advancing aging research.

中文翻译：

---

晚年自尊变化的多重轨迹和预测因素：潜在增长混合建模方法

这项研究应用潜在增长混合模型 (GMM)，深入研究了 9 年期间 5,597 名老年人样本的自尊轨迹。出现了四种不同的自尊变化模式：低、下降、增加和高。此外，该研究还探讨了每个轨迹与各种预测因素之间的关系，包括人口因素、社会经济地位、健康和人际关系。研究结果强调了这些因素在预测个人遵循特定自尊轨迹的可能性方面的重要性。值得注意的是，维持就业、培养令人满意的社会关系以及摆脱频繁的抑郁情绪是高自尊的稳定性和增强的有力预测因素。有趣的是，平均或高于平均水平的收入出乎意料地与较低的自尊水平相关。该研究强调了 GMM 对推进衰老研究的贡献。