{"title":"Preconception depression reduces fertility: a couple-based prospective preconception cohort","authors":"Tierong Liao, Yaya Gao, Xinliu Yang, Yanlan Tang, Baoling Wang, Qianhui Yang, Xin Gao, Ying Tang, Kunjing He, Jing Shen, Shuangshuang Bao, Guixia Pan, Peng Zhu, Fangbiao Tao, S. Shao","doi":"10.1093/hropen/hoae032","DOIUrl":null,"url":null,"abstract":"\n \n \n Is preconception depression associated with time to pregnancy (TTP) and infertility?\n \n \n \n Couples with preconception depression needed a longer time to become pregnant and exhibited an increased risk of infertility.\n \n \n \n Preconception depression in women contributes to impaired fertility in clinical populations. However, evidence from the general population—especially based on couples—is relatively scant.\n \n \n \n A couple-based prospective preconception cohort study was performed in 16 premarital examination centers between April 2019 and June 2021. The final analysis included 16,521 couples who tried to conceive for ≤6 months at enrollment. Patients with infertility were defined as those with a TTP ≥12 months and those who conceived through ART.\n \n \n \n Couples’ depression was assessed using the Patient Health Questionnaire-9 at baseline. Reproductive outcomes were obtained via telephone at 6 and 12 months after enrollment. Fertility odds ratios (FORs) and infertility risk ratios (RRs) in different preconception depression groups were analysed using the Cox proportional-hazard models and logistic regression, respectively.\n \n \n \n Of the 16,521 couples analyzed, 10,834 (65.6%) and 746 (4.5%) couples achieved pregnancy within the first 6 months and between the 6th and 12th months, respectively. The median (P25, P75) TTP was 3.0 (2.0, 6.0) months. The infertility rate was 13.01%. After adjusting for potential confounders, in the individual-specific analyses, we found that preconception depression in women was significantly related to reduced odds of fertility (FOR = 0.947, 95% CI: 0.908–0.988), and preconception depression in either men or women was associated with an increased risk of infertility (women: RR = 1.212, 95%CI: 1.076–1.366; men: RR = 1.214, 95%CI: 1.068–1.381); in the couple-based analyses, we found that—compared to couples where neither partner had depression—the couples where both partners had depression exhibited reduced fertility (adjusted FOR = 0.904, 95%CI: 0.838–0.975). The risk of infertility in the group where only the woman had depression and both partners had depression increased by 17.8% (RR = 1.178, 95%CI: 1.026–1.353) and 46.9% (RR = 1.469, 95%CI: 1.203–1.793), respectively.\n \n \n \n Reporting and recall bias were unavoidable in this large epidemiological study. Some residual confounding factors—such as the use of anti-depressants and other medications, sexual habits, and prior depressive and anxiety symptoms—remain unaddressed. We used a cut-off score of 5 to define depression, which is lower than prior studies. Finally, we assessed depression only at baseline, therefore we could not detect effects of temporal changes in depression on fertility.\n \n \n \n This couple-based study indicated that preconception depression in individuals and couples negatively impacts couples’ fertility. Early detection and intervention of depression to improve fertility should focus on both sexes.\n \n \n \n This work was supported by grants from the National Natural Science Foundation of China (No. 82273638) and the National Key Research and Development Program of China (No. 2018YFC1004201). All authors declare no conflicts of interest.\n \n \n \n N/A.\n","PeriodicalId":8,"journal":{"name":"ACS Biomaterials Science & Engineering","volume":"28 16","pages":""},"PeriodicalIF":5.4000,"publicationDate":"2024-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Biomaterials Science & Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1093/hropen/hoae032","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MATERIALS SCIENCE, BIOMATERIALS","Score":null,"Total":0}
引用次数: 0
Abstract
Is preconception depression associated with time to pregnancy (TTP) and infertility?
Couples with preconception depression needed a longer time to become pregnant and exhibited an increased risk of infertility.
Preconception depression in women contributes to impaired fertility in clinical populations. However, evidence from the general population—especially based on couples—is relatively scant.
A couple-based prospective preconception cohort study was performed in 16 premarital examination centers between April 2019 and June 2021. The final analysis included 16,521 couples who tried to conceive for ≤6 months at enrollment. Patients with infertility were defined as those with a TTP ≥12 months and those who conceived through ART.
Couples’ depression was assessed using the Patient Health Questionnaire-9 at baseline. Reproductive outcomes were obtained via telephone at 6 and 12 months after enrollment. Fertility odds ratios (FORs) and infertility risk ratios (RRs) in different preconception depression groups were analysed using the Cox proportional-hazard models and logistic regression, respectively.
Of the 16,521 couples analyzed, 10,834 (65.6%) and 746 (4.5%) couples achieved pregnancy within the first 6 months and between the 6th and 12th months, respectively. The median (P25, P75) TTP was 3.0 (2.0, 6.0) months. The infertility rate was 13.01%. After adjusting for potential confounders, in the individual-specific analyses, we found that preconception depression in women was significantly related to reduced odds of fertility (FOR = 0.947, 95% CI: 0.908–0.988), and preconception depression in either men or women was associated with an increased risk of infertility (women: RR = 1.212, 95%CI: 1.076–1.366; men: RR = 1.214, 95%CI: 1.068–1.381); in the couple-based analyses, we found that—compared to couples where neither partner had depression—the couples where both partners had depression exhibited reduced fertility (adjusted FOR = 0.904, 95%CI: 0.838–0.975). The risk of infertility in the group where only the woman had depression and both partners had depression increased by 17.8% (RR = 1.178, 95%CI: 1.026–1.353) and 46.9% (RR = 1.469, 95%CI: 1.203–1.793), respectively.
Reporting and recall bias were unavoidable in this large epidemiological study. Some residual confounding factors—such as the use of anti-depressants and other medications, sexual habits, and prior depressive and anxiety symptoms—remain unaddressed. We used a cut-off score of 5 to define depression, which is lower than prior studies. Finally, we assessed depression only at baseline, therefore we could not detect effects of temporal changes in depression on fertility.
This couple-based study indicated that preconception depression in individuals and couples negatively impacts couples’ fertility. Early detection and intervention of depression to improve fertility should focus on both sexes.
This work was supported by grants from the National Natural Science Foundation of China (No. 82273638) and the National Key Research and Development Program of China (No. 2018YFC1004201). All authors declare no conflicts of interest.
N/A.
期刊介绍:
ACS Biomaterials Science & Engineering is the leading journal in the field of biomaterials, serving as an international forum for publishing cutting-edge research and innovative ideas on a broad range of topics:
Applications and Health – implantable tissues and devices, prosthesis, health risks, toxicology
Bio-interactions and Bio-compatibility – material-biology interactions, chemical/morphological/structural communication, mechanobiology, signaling and biological responses, immuno-engineering, calcification, coatings, corrosion and degradation of biomaterials and devices, biophysical regulation of cell functions
Characterization, Synthesis, and Modification – new biomaterials, bioinspired and biomimetic approaches to biomaterials, exploiting structural hierarchy and architectural control, combinatorial strategies for biomaterials discovery, genetic biomaterials design, synthetic biology, new composite systems, bionics, polymer synthesis
Controlled Release and Delivery Systems – biomaterial-based drug and gene delivery, bio-responsive delivery of regulatory molecules, pharmaceutical engineering
Healthcare Advances – clinical translation, regulatory issues, patient safety, emerging trends
Imaging and Diagnostics – imaging agents and probes, theranostics, biosensors, monitoring
Manufacturing and Technology – 3D printing, inks, organ-on-a-chip, bioreactor/perfusion systems, microdevices, BioMEMS, optics and electronics interfaces with biomaterials, systems integration
Modeling and Informatics Tools – scaling methods to guide biomaterial design, predictive algorithms for structure-function, biomechanics, integrating bioinformatics with biomaterials discovery, metabolomics in the context of biomaterials
Tissue Engineering and Regenerative Medicine – basic and applied studies, cell therapies, scaffolds, vascularization, bioartificial organs, transplantation and functionality, cellular agriculture