Department of Computer Science, University of Helsinki, Helsinki, Finland.
Department of Public Health, University of Helsinki, Helsinki, Finland.
BMC Geriatr. 2024 Oct 8;24(1):813. doi: 10.1186/s12877-024-05384-5.
Mental distress among retirees and older people is a severe public health challenge, and information on new risk groups is needed. This study aims to identify subgroups of old-age retirees with varying associations between low social support and mental distress by applying model-based recursive partitioning (MOB).
We used the Helsinki Health Study follow-up survey data of old-age retired former municipal sector employees of the City of Helsinki, Finland. Phase 1 data were collected in 2000-2002, when all participants were employed, Phase 2 in 2007, Phase 3 in 2012, Phase 4 in 2017, and Phase 5 in 2022 (n = 4,466, 81% women). Social support and covariates were measured at each Phase 1-5 and the outcome, mental distress (Depression Anxiety Stress Scales [DASS-21]) was measured at a single occasion, during Phase 5. The three subscales and the common factor of general distress were analysed separately. An approach rooted in computational statistics was used to investigate risk factor heterogeneity in the association of low social support and mental distress. MOB combines decision trees with regression analysis to identify subgroups with the most significant heterogeneity among risk factors.
Median (IQR) general distress score from DASS-21 was 5.7 (3.0, 9.0), while Social Support Questionnaire number-score (SSQN) was 1.5 (1.15, 2.05). The primary effect modifier for the association between social support and general distress was education (p < 0.001). Those with high education had a different association of low social support and general distress than those with low or medium education. Additionally, the subgroup with low and medium education had a significant effect modification for age (p = 0.01). For the association between low social support and depressive symptoms, the moderating effect of education was dependent on gender, as men with medium-high education had the weakest association, while for women with medium-high education the association was strongest.
Our results suggest that stratification by sociodemographic variables is justifiable when investigating risk factors of mental distress in old-age retirees. The incongruent association of low social support and depressive symptoms in men with medium-high education compared to women with medium-high education is a promising target for confirmatory research.
退休人员和老年人的精神困扰是一个严重的公共卫生挑战，需要了解新的风险群体。本研究旨在通过基于模型的递归划分（MOB）确定具有不同低社会支持与精神困扰关联的老年退休人员亚组。
我们使用芬兰赫尔辛基市前市政部门老年退休人员赫尔辛基健康研究随访调查数据。第一阶段数据于 2000-2002 年收集，当时所有参与者都在工作；第二阶段于 2007 年收集，第三阶段于 2012 年收集，第四阶段于 2017 年收集，第五阶段于 2022 年收集（n=4466，81%为女性）。在每个第一阶段至第五阶段都测量了社会支持和协变量，而精神困扰（抑郁焦虑压力量表[DASS-21]）则在第五阶段的一个单一时刻进行了测量。单独分析了三个分量表和一般困扰的共同因素。一种扎根于计算统计学的方法用于研究低社会支持与精神困扰关联中的风险因素异质性。MOB 将决策树与回归分析相结合，以识别风险因素中最显著异质性的亚组。
DASS-21 一般困扰评分的中位数（IQR）为 5.7（3.0，9.0），而社会支持问卷数字评分（SSQN）为 1.5（1.15，2.05）。社会支持与一般困扰之间关联的主要效应修饰符是教育（p<0.001）。那些受过高等教育的人与那些受过低或中等教育的人相比，他们的低社会支持与一般困扰之间的关联有所不同。此外，低教育和中等教育的亚组的年龄有显著的效应修饰（p=0.01）。对于低社会支持与抑郁症状之间的关联，教育的调节作用取决于性别，因为具有中高教育程度的男性的关联最弱，而具有中高教育程度的女性的关联最强。
我们的研究结果表明，在调查老年退休人员精神困扰的风险因素时，按社会人口统计学变量分层是合理的。与中高教育程度的女性相比，中高教育程度的男性低社会支持与抑郁症状之间关联的不一致性是一个有前途的确认性研究目标。
