University Medical Center Hamburg-Eppendorf, Center for Psychosocial Medicine, Department of Psychiatry and Psychotherapy, Hamburg, Germany.
University Medical Center Hamburg-Eppendorf, Epidemiological Study Center, Hamburg, Germany.
Front Public Health. 2024 Aug 29;12:1430325. doi: 10.3389/fpubh.2024.1430325. eCollection 2024.
Socioeconomic status (SES) has consistently been associated with depressive symptoms, however, it remains unclear which subset of SES variables is most relevant to the development of depressive symptoms. This study determined a standardized SES-Index to test the relationship of its sub-dimensions with depressive symptoms.
HCHS data ( = 10,000; analysis sample = 8,400), comprising participants 45+ years of age, was used. A standardized approach to quantify SES was employed. Depressive symptoms were quantified using the Patient Health Questionnaire-9 (PHQ-9). Using multiple linear regression models, PHQ-9-scores were modeled as a function of age and sex, and (1a) total SES-Index score versus (1b) its three sub-dimension scores (education, occupational status, income). Models were compared on explained variance and goodness of fit. We determined risk ratios (RR, concerning a PHQ-9 sum score ≥ 10) based on (low, middle, high; 2a) SES-Index scores and (2b) the sub-dimension scores, with groups further differentiated by sex and age (45-64 versus 65+). We distinguished between the total SES-Index score and its three sub-dimension scores to identify relevant SES sub-dimensions in explaining PHQ-9-variability or risk of depression.
Among all regression models (total explained variance 4-6%), income explained most variance, but performance of the SES-Index was comparable. Low versus high income groups showed the strongest differences in depressive trends in middle-aged females and males (RRs 3.57 and 4.91). In older age, this result was restricted to females (RR ≈ 2). Middle-aged males (versus females) showed stronger discrepancies in depressive trends pertaining to low versus high SES groups. In older age, the effect of SES was absent. Education was related to depressive trends only in middle-aged females and males. In an exploratory analysis, marital status and housing slightly increased model fit and explained variance while including somatic symptoms lead to substantial increases (R = 0.485).
In line with previous research, the study provides evidence for SES playing a significant role in depressive symptoms in mid to old age, with income being robustly linked to depressive trends. Overall, the relationship between SES and depressive trends appears to be stronger in males than females and stronger in mid compared to old age.
社会经济地位(SES)与抑郁症状一直存在关联,但目前尚不清楚 SES 变量的哪个子集与抑郁症状的发展最相关。本研究旨在确定标准化 SES 指数,以检验其亚维度与抑郁症状的关系。
本研究使用 HCHS 数据( = 10000;分析样本 = 8400),纳入 45 岁及以上的参与者。采用标准化方法来量化 SES。抑郁症状采用患者健康问卷-9(PHQ-9)进行量化。使用多元线性回归模型,将 PHQ-9 评分作为年龄和性别的函数进行建模,(1a)SES 指数总分与(1b)其三个亚维度评分(教育、职业地位、收入)。比较模型的解释方差和拟合优度。我们基于(低、中、高;2a)SES 指数评分和(2b)亚维度评分,确定风险比(RR,涉及 PHQ-9 总分 ≥ 10),并根据性别和年龄(45-64 岁与 65 岁及以上)进一步对组进行区分。我们区分 SES 指数总分与其三个亚维度评分,以确定 SES 亚维度在解释 PHQ-9 变异性或抑郁风险方面的相关性。
在所有回归模型中(总解释方差为 4%-6%),收入解释了大部分方差,但 SES 指数的表现相当。在中年女性和男性中,低与高收入群体的抑郁趋势差异最大(RR 分别为 3.57 和 4.91)。在老年时,这种结果仅限于女性(RR ≈ 2)。中年男性(与女性相比)在低与高 SES 群体的抑郁趋势方面显示出更大的差异。在老年时,SES 的影响不存在。教育仅与中年女性和男性的抑郁趋势相关。在一项探索性分析中,婚姻状况和住房略微增加了模型拟合度和解释方差,而纳入躯体症状则会显著增加(R = 0.485)。
与先前的研究一致,本研究提供了 SES 在中年到老年期抑郁症状中起重要作用的证据,收入与抑郁趋势之间存在强有力的关联。总体而言,SES 与抑郁趋势之间的关系在男性中似乎比女性更强,在中年时比老年时更强。