Chinese Medical E-ournals Database
Adv Search
中华妇幼临床医学杂志(电子版)

Chinese Journal of Obstetrics & Gynecology and Pediatrics(Electronic Edition) ›› 2022, Vol. 18 ›› Issue (05): 591 -598. doi: 10.3877/cma.j.issn.1673-5250.2022.05.014

Original Article

Analysis of influencing factors of perinatal maternal depression during the COVID-19 pandemic

Ruixin Yong1, Hongxia Chai2,†(), Weiwei Tuo1, Dandan Chen1, Dongrong Zhao3   

  1. 1First School of Clinical Medical, Lanzhou University, Lanzhou 730099, Gansu Province, China
    2Department of Obstetrics, First Hospital of Lanzhou University, Lanzhou 730013, Gansu Province, China
    3Department of Obstetrics, Lanzhou Third People′s Hospital, Lanzhou 730050, Gansu Province, China
  • Received:2022-01-18 Revised:2022-08-17 Published:2022-10-01
  • Corresponding author: Hongxia Chai
  • Supported by:
    National Undergraduate Scientific Research and Innovation Project(202210730176); Undergraduate Scientific Research Innovation Project of Lanzhou University(20200060032); Undergraduate Scientific Research Innovation Project of Lanzhou University(20220060099); Lanzhou Health Science and Technology Development Project(2019-023); Lanzhou Talent Innovation and Entrepreneurship Project(2020-RC-75)
HTML ( ) PDF ( )
Objective

To investigate incidence and social factors of depression in perinatal pregnant women under corona virus disease 2019 (COVID-19) pandemic.

Methods

A total of 71 pregnant women were randomly selected according to their medical card number from April 1, 2020 to August 31, 2020 in the obstetric department outpatient and inpatient of a grade A class 3 hospital in Lanzhou during the COVID-19 outbreak. Then, a total of 71 pregnant women who were treated in the obstetrics department outpatient and inpatient of the same hospital during the normalized COVID-19 pandemic period from April 1 to August 31, 2021 were selected into this study. According to the Edinburgh Postnatal Depression Scale (EPDS), pregnant women were divided into depression group (n=64, EPDS score≥9) and non-depression group (n=78, EPDS score<9). The general information of the subjects was investigated by filling in the electronic questionnaire or manually filling in the paper version of the questionnaire, and then the EPDS and Social Support Rating Scale (SSRS) were used to investigate their social support information. Multivariate unconditional logistic regression analysis was used to analyze the influencing factors of depression in perinatal pregnant women. The procedures followed in this study were in accordance with the newly revised World Medical Association Declaration of Helsinki in 2013, and informed consent for clinical study was signed with all subjects.

Results

① Among 142 pregnant women, the detection rate of depression was 45.1% (64/142). There were significant differences in education level and growth environment between two groups (P<0.05). ② The scores of each dimension of SSRS in two groups showed that the score of support utilization of depression group was lower than that of the non-depression group [(6.6±1.2) scores vs (7.8±1.6) scores], and the difference was statistically significant (t=4.72, P<0.001). ③ Among the social related factors of pregnant women in two groups, there were statistically significant differences in the composition ratio of the total score of the SSRS and the support degree of community medical service center (χ2=12.26, 11.56; P=0.002, 0.009). ④ The results of multivariate unconditional logistic regression analysis showed that education level, growth environment and the total score of SSRS were the influencing factors of perinatal pregnant depression. Among them, growing up in rural areas (OR=2.397, 95%CI: 1.012-5.675, P=0.047) and lower education level (high school and technical secondary school) (OR=3.929, 95%CI: 1.046-14.762, P=0.043) were independent risk factors. In addition, the total score of SSRS was 30-39 (OR=0.106, 95%CI: 0.024-0.472, P=0.003) was an independent protective factor for perinatal pregnant women. ⑤ The most desired support and help for perinatal pregnant women in two groups was " economy" .

Conclusions

Under the circumstance of COVID-19 pandemic, it may be helpful to regulate the bad mood of pregnant women. For perinatal pregnant women, help and support from community health centers are still lacking. Timely screening and intervention are necessary to prevent the occurrence of depression in perinatal pregnant women. Due to the increasing cost of childbearing, there is an urgent need for economic support during perinatal period.

Key words: Pregnant women, Puerpera, Peripartum period, COVID-19, Depression, Social support, Psychosocial support systems
表1 2组围生期孕产妇一般资料比较[例数(%)]
组别 例数 填表时间 孕检卡标签颜色
2020年 2021年 绿色 黄色 红色 紫色 橙色 不清楚
抑郁组 64 34(53.1) 30(46.9) 24(37.5) 23(35.9) 2(3.1) 1(1.6) 6(9.4) 8(12.5)
非抑郁组 78 37(47.4) 41(52.6) 29(37.2) 26(33.3) 8(10.3) 6(7.7) 5(6.4) 4(5.1)
χ2值   0.46 7.92
P组   0.499 0.159
组别 例数 产次 家庭年收入
1次 2次 ≥3次 <5 000元 5 000~9 999元 10 000~19 999元 20 000~50 000元 >50 000元
抑郁组 64 33(51.6) 29(45.3) 2(3.1) 13(20.3) 14(21.9) 9(14.1) 2(3.1) 18(28.1)
非抑郁组 78 49(62.8) 24(30.8) 5(6.4) 16(20.5) 12(15.4) 9(11.5) 16(20.5) 25(32.1)
χ2值   3.53 1.62
P组   0.171 0.805
组别 例数 年龄 受教育程度 成长环境
<30岁 ≥30岁 初中及以下 高中及中专 大专 本科 研究生及以上 城镇 农村
抑郁组 64 24(37.5) 40(62.5) 7(10.9) 25(39.1) 11(17.2) 18(28.1) 3(4.7) 19(29.7) 45(70.3)
非抑郁组 78 33(42.3) 45(57.7) 13(16.7) 11(14.1) 18(23.1) 30(38.5) 6(7.7) 36(46.2) 42(53.9)
χ2值   0.34 11.67 4.02
P组   0.561 0.020 0.045
组别 例数 职业
IT/电子技术/化工 批发/零售/餐饮娱乐 财会/银行/证券 生物/医药 广告艺术/建筑装潢 物业/中介/交通/运输 农业/渔业/林业 教育/科研 其他
抑郁组 64 4(6.2) 6(9.4) 1(1.6) 3(4.7) 2(3.1) 1(1.6) 0(0) 4(6.2) 43(67.2)
非抑郁组 78 7(9.0) 6(7.7) 7(9.0) 8(10.3) 2(2.6) 5(6.4) 2(2.6) 7(9.0) 34(43.6)
χ2值   12.87
P组   0.116
表2 2组围生期孕产妇SSRS不同维度得分比较(分，±s)
组别 例数 主观支持 客观支持 支持利用度 总分
抑郁组 64 20.6±3.8 6.0±1.3 6.6±1.2 33.3±4.8
非抑郁组 78 21.2±4.0 6.5±1.8 7.8±1.6 35.5±5.5
t值   0.86 1.73 4.72 2.50
P值   0.393 0.086 <0.001 0.013
表3 2组围生期孕产妇相关因素比较[例数(%)]
组别 例数 SSRS总分 社区医疗服务中心支持程度
<30分 30~39分 ≥40分 无支持 较低 一般 全力以赴
抑郁组 64 21(32.8) 38(59.4) 5(7.8) 11(17.2) 7(10.9) 12(18.8) 34(53.1)
非抑郁组 78 9(11.5) 52(66.7) 17(21.8) 4(5.1) 4(5.1) 31(39.7) 39(50.0)
χ2值   12.26 11.56
P值   0.002 0.009
组别 例数 医保方式 经济条件满意度
全自费 城镇职工医保 城乡居民医保 商业保险 非常满意 满意 不满意 非常不满意
抑郁组 64 11(17.2) 18(28.1) 38(59.4) 4(6.2) 5(7.8) 51(79.7) 8(12.5) 0(0)
非抑郁组 78 8(10.3) 37(47.4) 34(43.6) 6(7.7) 10(12.8) 57(73.1) 10(12.8) 1(1.3)
χ2值   6.47a —b
P值   0.087 0.672
组别 例数 参加各团体组织的宣传妇幼保健相关活动 医院支持程度
从不参加 偶尔参加 经常参加 主动参加并积极活动 无支持 较低 一般 全力支持
抑郁组 64 22(34.4) 40(62.5) 0(0) 2(3.1) 3(4.7) 0(0) 10(15.6) 51(79.7)
非抑郁组 78 19(24.4) 50(64.1) 3(3.9) 6(7.7) 1(1.3) 1(1.3) 11(14.1) 65(83.3)
χ2值   4.49a —b
P值   0.204 0.556
组别 例数 政府政策支持程度 工作单位或雇主支持程度
无支持 较低 一般 全力支持 无支持 较低 一般 全力支持
抑郁组 64 12(18.8) 5(7.8) 13(20.3) 43(67.2) 14(21.9) 7(10.9) 17(26.6) 26(40.6)
非抑郁组 78 7(9.0) 3(3.8) 26(33.3) 42(53.8) 6(7.7) 8(10.3) 20(25.6) 44(56.4)
χ2值   5.95a 6.82
P值   0.108 0.078
组别 例数 共同居住亲属
丈夫 孩子 男方父母 女方父母 男方亲属 女方亲属 其他
抑郁组 64 56(87.5) 23(35.9) 20(31.2) 8(12.5) 3(4.7) 2(3.1) 4(6.2)
非抑郁组 78 75(96.2) 27(34.6) 30(38.5) 9(11.5) 4(5.1) 1(1.3) 2(2.6)
χ2值   2.62a
P值   0.883
表4 导致围生期孕产妇抑郁情绪影响因素的多因素非条件logistic回归分析结果
条目 B SE Wald值 P值 OR值 OR值95%CI
成长环境(以城镇为对照) 0.874 0.440 3.948 0.047 2.397 1.012~5.675
受教育程度(以初中及以下为对照)            
  高中及中专 1.368 0.675 4.106 0.043 3.929 1.046~14.762
  大专 -0.069 0.684 0.010 0.920 0.933 0.244~6.111
  本科 0.525 0.656 0.640 0.424 1.690 0.467~11.599
  硕士及以上 0.460 1.016 0.206 0.650 1.585 0.217~11.599
SSRS总分(以<30分为对照)            
  30~39分 -1.392 0.532 6.861 0.009 0.249 0.088~0.704
  ≥40分 -2.244 0.762 8.677 0.003 0.106 0.024~0.472
社区医疗服务中心支持度(以无支持为对照)            
  较低 -0.196 0.947 0.043 0.836 0.822 0.128~5.261
  一般 -1.451 0.750 3.743 0.053 0.234 0.054~1.019
  全力支持 -0.219 0.722 0.092 0.762 0.804 0.195~3.306
常数项 0.487 0.925 0.277 0.598 1.628 —
图1 抑郁组64例围生期孕产妇(孕龄为28孕周至产后7 d)填写开放性问题的高频关键词分析结果
图2 非抑郁组78例围生期孕产妇(孕龄为28孕周至产后7 d)填写开放性问题的高频关键词分析结果
[1]
World Health Organization. Depression[DB/OL].(2022-03-10)[2022-05-17].

URL    
[2]
Dossett EC. Perinatal depression[J]. Obstet Gynecol Clin North Am, 2008, 35(3): 419-434, viii. DOI: 10.1016/j.ogc.2008.04.004.
[3]
Nisar A, Yin J, Waqas A, et al. Prevalence of perinatal depression and its determinants in mainland China: a systematic review and Meta-analysis[J]. J Affect Disord, 2020, 277: 1022-1037. DOI: 10.1016/j.jad.2020.07.046.
[4]
Stein A, Pearson RM, Goodman SH, et al. Effects of perinatal mental disorders on the fetus and child[J]. Lancet, 2014, 384(9956): 1800-1819. DOI: 10.1016/S0140-6736(14)61277-0.
[5]
Jacobson MH, Stein CR, Liu M, et al. Prenatal exposure to bisphenols and phthalates and postpartum depression: the role of neurosteroid hormone disruption[J]. J Clin Endocrinol Metab, 2021, 106(7): 1887-1899. DOI：10.1210/clinem/dgab199.
[6]
Mocking RJ, Steijn K, Roos C, et al. Omega-3 fatty acid supplementation for perinatal depression: a Meta-analysis[J]. J Clin Psychiatry, 2020, 81(5): 19r13106. DOI: 10.4088/JCP.19r13106.
[7]
许国敏，余慧．群组孕期保健干预对初产妇心理状态及分娩方式的影响[J]. 中国健康心理学杂志，2020, 28(7): 1000-1003. DOI: 10.13342/j.cnki.cjhp.2020.07.010.
[8]
欧妙贤，许秀定，文芳金. 孕期抑郁情绪的社工介入对产后抑郁的预防效果研究[J].中国社会工作，2019, 32(21): 40-42, 45. DOI: 10.3969/j.issn.1674-3857.2019.21.010.
[9]
于艳平，熊号峰. 新型冠状病毒肺炎合并急性胰腺炎研究进展[J].国际病毒学杂志，2021，28(4):346-349. DOI: 10.3760/cma.j.issn.1673-4092.2021.04.020.
[10]
Chorwe-Sungani G, Chipps J. A systematic review of screening instruments for depression for use inantenatal services in low resource settings[J]. BMC Psychiatry, 2017, 17(1): 112. DOI: 10.1186/s12888-017-1273-7.
[11]
肖水源． 《社会支持评定量表》的理论基础与研究应用[J].临床精神医学杂志，1994, 4(2): 98-100.
[12]
Racine N, Zumwalt K, McDonald S, et al. Perinatal depression: the role of maternal adverse childhood experiences and social support[J]. J Affect Disord, 2020, 263: 576-581. DOI: 10.1016/j.jad.2019.11.030.
[13]
Lövdén M, Fratiglioni L, Glymour MM, et al. Education and cognitive functioning across the life span[J]. Psychol Sci Public Interest, 2020, 21(1): 6-41. DOI：10.1177/152910062092057612.
[14]
Zemestani M, Fazeli Nikoo Z. Effectiveness of mindfulness-based cognitive therapy for comorbid depression and anxiety in pregnancy: a randomized controlled trial[J]. Arch Womens Ment Health, 2020, 23(2): 207-214. DOI：10.1007/s00737-019-00962-8.
[15]
Gelaye B, Rondon MB, Araya R, et al. Epidemiology of maternal depression, risk factors, and child outcomes in low-income and middle-income countries[J]. Lancet Psychiatry, 2016, 3(10): 973-982. DOI: 10.1016/S2215-0366(16)30284-X.
[16]
钟水映，汪世琦. 经济发展与生育率的"反J型"关系解读与启示[J].统计与决策，2022, 38(5): 43-49. DOI: 10.13546/j.cnki.tjyjc.2022.05.008.
[17]
COVID-19 Mental Disorders Collaborators. Global prevalence and burden of depressive and anxiety disorders in 204 countries and territories in 2020 due to the COVID-19 pandemic[J]. Lancet, 2021, 398(10312): 1700-1712. DOI: 10.1016/S0140-6736(21)02143-7.
[18]
Lee Y, Lui LMW, Chen LD, et al. Government response moderates the mental health impact of COVID-19: a systematic review and Meta-analysis of depression outcomes across countries[J]. J Affect Disord, 2021, 290: 364-377. DOI：10.1016/j.jad.2021.04.050.
[1] Can Zhou, Bohui Shi, Jin Yang, Juntao Li, Rui Xu, Yuanyuan Chen, Hongliang Wei, Zhen Liu, Zhiping Deng, Dong Fan, Yan Diao, Xiongxiong Li, Junwen Bai, Yu Ren. Clinical symptoms of female breast cancer patients with COVID-19: a multi-center cross-sectional study based on patient reported outcome[J]. Chinese Journal of Breast Disease(Electronic Edition), 2023, 17(03): 157-162.
[2] Tiantian Chen, Xiaodong Wang, Haiyan Yu. Pregnancy outcome of twin pregnancy with Gitelman syndrome: a case report and literature review[J]. Chinese Journal of Obstetrics & Gynecology and Pediatrics(Electronic Edition), 2023, 19(05): 559-568.
[3] Xiaoqing Ju, Yunjie Jin, Xiaoyan Wang. Influencing factors of uterine rupture during vaginal delivery in patients with scarred uterus after cesarean section[J]. Chinese Journal of Obstetrics & Gynecology and Pediatrics(Electronic Edition), 2023, 19(05): 575-581.
[4] Beibei Wang, Qixiu Dong, Hongyan Xi, Qingyun Yu, Lijun Zhang, Guang Shi. Analysis of influencing factors of medical abortion failure of pregnant women in early pregnancy and construction of related prediction model and its predictive value for medical abortion success[J]. Chinese Journal of Obstetrics & Gynecology and Pediatrics(Electronic Edition), 2023, 19(05): 588-594.
[5] Xiaoyan Dong, Qi Zhao, Jun Tang, Li Zhang, Xiaoyan Yang, Jiao Li. Clinical characteristics of neonates infected with the Omicron variant of severe acute respiratory syndrome coronavirus 2[J]. Chinese Journal of Obstetrics & Gynecology and Pediatrics(Electronic Edition), 2023, 19(05): 595-603.
[6] Xu Chen, Yuru Zhan, Chunhua Wang. Clinical value of ABO blood group combined with thyroid function in prediction of gestational diabetes mellitus[J]. Chinese Journal of Obstetrics & Gynecology and Pediatrics(Electronic Edition), 2023, 19(05): 604-610.
[7] Mengling Zhou, Zhiwei Xue, Shu Zhou. Changes in size of uterine myoma during pregnancy and its association with adverse pregnancy outcomes[J]. Chinese Journal of Obstetrics & Gynecology and Pediatrics(Electronic Edition), 2023, 19(05): 611-615.
[8] Chenxi Ran, Rufei Shen, Mingyu Liao, Qian Liao, Ling Zhou, Yuling Zhang, Min Long. Treatment and management of pituitary tumor during pregnancy[J]. Chinese Journal of Obstetrics & Gynecology and Pediatrics(Electronic Edition), 2023, 19(04): 487-491.
[9] Ruochen Qi, Shuaijun Ma, Shichao Han, Guohui Wang, Kepu Liu, Xiaoyan Zhang, Xiaojian Yang, Weijun Qin. Diagnosis and treatment of COVID-19 in kidney transplant recipients: experience from a single center[J]. Chinese Journal of Transplantation(Electronic Edition), 2023, 17(04): 232-239.
[10] Jinpu Li, Xiangrong Rao. Antiviral drugs and acute kidney injury[J]. Chinese Journal of Kidney Disease Investigation(Electronic Edition), 2023, 12(05): 287-290.
[11] Xuezhu Li, Jianfeng Xie, Xiaoqing Li, Zeyan Xia, Ling Lu, Xiaoxia Gu, Shaolei Ma, Yingzi Huang. Application of circulating screening and classified admission in Fangcang shelter hospital for COVID-19 patient[J]. Chinese Journal of Critical Care & Intensive Care Medicine(Electronic Edition), 2023, 09(03): 316-320.
[12] Qiang Fu, Liyuan Qin, Quanbo Li. Analysis of serum miR-15a level and significance in patients with neuropathic pain[J]. Chinese Journal of Brain Diseases and Rehabilitation(Electronic Edition), 2023, 13(05): 293-298.
[13] Hui Pan, Ming Wang, Zhong Yang, Xiangdong Du. Low-frequency repetitive transcranial magnetic stimulation for adjuvant treatment of depression with different characteristics: a controlled study[J]. Chinese Journal of Clinicians(Electronic Edition), 2023, 17(05): 562-568.
[14] Xueyun Liu, Ying Fan, Aijun Yao, Shengmiao Zhang, Yani Lv, Bingqing Zhang, Xiaoyu Zhang, Heng. Liu. Effects of individualized whole-course nursing intervention based on WeChat mini program on pregnancy weight and delivery outcome[J]. Chinese Journal of Clinicians(Electronic Edition), 2023, 17(04): 455-460.
[15] Yang Yu, Xiaojie Liu, LiJuan Wang, Yuchen Gao, Yao Ding, Hushan Ao. Training model for cardiopulmonary resuscitation under the background of regular control of COVID-19[J]. Chinese Journal of Clinicians(Electronic Edition), 2023, 17(04): 483-486.
Viewed
Full text


Abstract

Copyright © Chinese Medical Association, Chinese Medical Multimedia Press  京ICP备14006079号-1  网络出版服务许可证：(署)网出证(京)字第075号