Farewell Charlotte V, Thayer Zaneta, Paulson James, Nicklas Jacinda, Walker Caroline, Waldie Karen, Morton Susan, Leiferman Jenn A
Department of Community and Behavioral Health, School of Public Health, University of Colorado-Anschutz Medical Campus, Mail Stop B119, East 17Aurora, CO, 1300180045, USA.
Dartmouth College, Hanover, NH, USA.
Arch Womens Ment Health. 2022 Apr;25(2):451-461. doi: 10.1007/s00737-022-01211-1. Epub 2022 Feb 8.
The primary objective of this study was to delineate classes of individuals based on depression trajectories from the antenatal period through 54-month postpartum and internal and external resources that are associated with low depression risk. Participants came from the Growing Up in New Zealand (GUiNZ) study (n = 5664), which is a pregnancy cohort study and is nationally representative of the ethnic and socioeconomic diversity of contemporary New Zealand births. Growth curve mixture modeling was used to identify distinct subgroups based on depression scores from the antenatal period through 54-month postpartum. Logistic regression models were run to investigate socioeconomic factors and internal and external resources that were associated with depression class membership. A two-class model, "low risk" and "high risk," resulted in the best model fit. Most of the sample (n = 5110, 90%) fell into the "low-risk" class defined by no-to-mild depression symptoms during pregnancy and decreasing depressive symptoms over time (b = - .05, b = - .05). Approximately 10% of the sample fell into the "high-risk" class (n = 554, 10%) defined by mild-to-moderate depressive symptoms during pregnancy and increasing depressive symptomology over time (b = .39, b = .57). More positive parenting-related attitudes, better pre-pregnancy self-reported health, informal social supports, and community belonging were significantly associated with greater odds of being in the "low-risk" class, after controlling for socioeconomic factors. These findings suggest that targeting internal and external resources for individuals across the perinatal and early childhood periods is important to mitigating maternal depression.
本研究的主要目的是根据从孕期到产后54个月的抑郁轨迹以及与低抑郁风险相关的内部和外部资源来划分个体类别。参与者来自新西兰成长（GUiNZ）研究（n = 5664），这是一项妊娠队列研究，在族裔和社会经济多样性方面具有当代新西兰出生情况的全国代表性。使用生长曲线混合模型，根据从孕期到产后54个月的抑郁评分来识别不同的亚组。运行逻辑回归模型以研究与抑郁类别归属相关的社会经济因素以及内部和外部资源。一个两类模型，即“低风险”和“高风险”，产生了最佳的模型拟合。大多数样本（n = 5110，90%）属于“低风险”类别，其定义为孕期无至轻度抑郁症状且抑郁症状随时间减少（b = -0.05，b = -0.05）。大约10%的样本属于“高风险”类别（n = 554，10%），其定义为孕期有轻度至中度抑郁症状且抑郁症状随时间增加（b = 0.39，b = 0.57）。在控制了社会经济因素后，更积极的育儿相关态度、孕前自我报告的更好健康状况、非正式社会支持和社区归属感与处于“低风险”类别的更高几率显著相关。这些发现表明，针对围产期和幼儿期个体的内部和外部资源对于减轻母亲抑郁很重要。
