{"paper_id":"048d9e49-6e65-4baf-bbbe-c141e3f691e5","body_text":"1 \n \nThe prevalence of mental ill-health in women during pregnancy and after childbirth 1 \nduring the Covid-19 pandemic: a Systematic review and Meta-analysis 2 \n 3 \n1Gayathri Delanerolle*, 12Mary McCauley*, Martin Hirsch 4,3*, 7Yutian Zheng*, 7Xu Cong **, 4 \n5,12Heitor Cavalini**, 1 2Ashish Shetty,  5 Shanaya Rathod, 7,8Jian Qing Shi***, 10 Dharani K 5 \nHapangama, 5,6Peter Phiri***, 6 \n 7 \nAffiliations 8 \n1University of Oxford, Nuffield Department of Primary Health Care Sciences  9 \n2University College London Hospitals NHS Foundation Trust  10 \n3University College London  11 \n4Oxford University Hospitals NHS Foundation Trust  12 \n5Southern Health NHS Foundation Trust, Research and Innovation Department 13 \n6University of Southampton, School of Primary Care, Population Sciences and Medical 14 \nEducation, Faculty of Medicine 15 \n7Southern University of Science and Technology 16 \n8 Alan Turing Institute 17 \n9University of Oxford, Department of Psychiatry  18 \n10University of Liverpool  19 \n11NHS England and NHS Improvement  20 \n12Liverpool Women’s NHS Foundation Trust, Liverpool 21 \nShared authorships 22 \n 23 \n 24 \n 25 \nShared first author* 26 \nShared second author** 27 \nShared last author*** 28 \n 29 \n 30 \n 31 \n 32 \n 33 \nCorresponding author: Dr Peter Phiri, BSc, PhD, RN,  34 \nDirector of Research & Innovation/ Visiting Fellow,  35 \nResearch & Innovation Department, Southern Health NHS Foundation Trust, Clinical Trials Facility, 36 \nTom Rudd Unit Moorgreen Hospital,  37 \nBotley Road, West End, Southampton SO30 3JB,  38 \nUnited Kingdom  39 \npeter.phiri@southernhealth.nhs.uk  40 \n 41 \n 42 \n 43 \n 44 \n 45 \n 46 \n 47 \n 48 \n 49 \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted June 14, 2022. ; https://doi.org/10.1101/2022.06.13.22276327doi: medRxiv preprint \nNOTE: This preprint reports new research that has not been certified by peer review and should not be used to guide clinical practice.\n\n \n2 \n \nAbstract 50 \nBackground  51 \nSevere Acute Respiratory Syndrome Coronavirus (SARS-CoV) is a respiratory disease 52 \ncausing coronavirus. SARS-CoV has caused the Middle East Respiratory Syndrome 53 \n(MERS), SARS-CoV in Hong King and SARS-CoV-2 (COVID-19). COVID-19, to date, have 54 \nhad the highest mortality and morbidity globally , thus reaching the pandemic status. In 55 \ncomparison to research conducted to explore the impact of pandemics on the general 56 \nwellbeing, there appears to be a paucity on its association with women’s mental health. 57 \nMany pregnant women have reported that the pandemic negatively impacted their mental 58 \nhealth.  59 \n 60 \nAim  61 \nThis study aimed is to explore the prevalenc e of the impact of the COVID-19, MERS and 62 \nSARS pandemics on the mental health of pregnant women.  63 \n 64 \nMethod 65 \nA study protocol was developed and published in PROSPERO ( CRD42021235356) to 66 \nexplore a number of key objectives. For the pur pose of this study PubMed, Science direct, 67 \nOvid PsycINFO and EMBASE databases were searched from December 2000 – July 2021. 68 \nThe search results were screened, first by title, and then by abstract. A meta-analysis was 69 \nconducted to report the findings.  70 \n 71 \nResults  72 \nThere were no studies reporting the mental health impact due to MERS and SARS. We 73 \nsystematically identified 316 studies that report ed on the mental health of women that were 74 \npregnant and soon after birth. The meta-analysis indicated 24.9% (21.37%-29.02%) of 75 \npregnant women reported symptoms of depressi on, 32.8% (29.05% to 37.21%) anxiety, 76 \n29.44% (18.21% - 47.61%) stress, 27.93% (9.05%-86.15 %) PTSD, and 24.38% (11.89%-77 \n49.96%) sleep disorders during the COVID-19 pandemic. Furthermore, the I 2 test showed a 78 \nhigh heterogeneity value. 79 \n 80 \nConclusion  81 \nThe importance of managing the mental health during pregnancy and after-delivery 82 \nimproves the quality of life and wellbeing of mothers. Developing an evidence based mental 83 \nhealth framework as part of pandemic preparedness to help pregnant women would improve 84 \nthe quality of care received during challenging times.   85 \n 86 \nKeywords: Covid-19, Mental ill-health, Depression, Anxiety, Stress, Pregnancy, Antenatal 87 \ncare, Postnatal care, Wellbeing 88 \n 89 \n 90 \n 91 \n 92 \n 93 \n 94 \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted June 14, 2022. ; https://doi.org/10.1101/2022.06.13.22276327doi: medRxiv preprint \n\n \n3 \n \nBackground:  95 \nSince December 2019, the coronavirus disease 2019 (COVID-19) pandemic caused by 96 \nsevere acute respiratory syndrome coronav irus 2 (SARS-Cov-2) has spread around the 97 \nworld unprecedentedly, overwhelming healthcare systems around the world. On March 11, 98 \n2020, the World Health Organization (WHO) declared COVID-19 a global pandemic. This 99 \nled to a rippling impact of the virus on healthcare systems and patients who needed to 100 \naccess care for both physical and mental health and wellbeing [1]. There was concern that 101 \nthe acute intensive care services would not be able to cope with the growing volume of 102 \naffected individuals requiring ventilatory supp ort. To reduce viral transmission and relieve 103 \npressure on healthcare systems, many countries, including the United Kingdom (UK), 104 \nentered lockdown.  105 \nPeople were ordered by law to stay at home. In many hospitals, staff were redeployed and 106 \ndepartments were adapted or converted to COVID-19 services. However, women who were 107 \npregnant and needed to give birth were identified as a vulnerable group and the ability to 108 \nprovide good quality maternity care during the Covid-19 pandemic was prioritised. 109 \n 110 \nIt is well documented that public health emergencies not only have a huge impact on the 111 \nphysical health of a population but also results in an increase in mental ill-health including: 112 \nconditions such as depression; post-traumatic stress disorder (PTSD); substance use 113 \ndisorder; behavioural disorders; noncomplianc e with public health directives, domestic 114 \nviolence; and child abuse[5]. These can arise from triggers directly related to the infection, 115 \nfor example, the neuroinvasive potential of SARS-CoV-2 may affect brain function and 116 \nmental health. The treatment for COVID-19 may also have adverse effects on mental health 117 \nand indirectly may contribute to anxiety. In addition, the imposition of unfamiliar and 118 \nundesired public health measures including social  isolation strongly correlates with the 119 \nlikelihood of clinically significant depression or anxiety [5,6]. These findings were echoed in 120 \nan evaluation of severe acute respiratory syndrome (SARS) epidemic with increases in 121 \nPTSD, stress, and psychological distress in both patients and clinicians. Affected individuals 122 \nand communities were motivated to comply with quarantine to reduce the risk of infecting 123 \nothers and to protect their community’s health. However emotional distress tempted some to 124 \nconsider violating the recommended public health measures[6].  125 \n 126 \nOne such vulnerable group is women during their pregnancy and after childbirth. Maternal 127 \nmental ill-health has been an international public health concern for many years[ 1] with 128 \nmillions of women experiencing mental il l-health during pregnancy and after childbirth[ 1, 2]. 129 \nCommon mental disorders (depression, anxiety) rank third in the list of the burden of disease 130 \nglobally and maternal mental ill-health affects up to 10% of women during pregnancy and 131 \n13% of women after childbirth[6, 7]. It is well documented that compromised maternal mental 132 \nill-health is associated with adverse short and long-term consequences for the mother and 133 \nthe baby[12, 13] . However, limited data exists on the prevalence of mental ill-health in 134 \nwomen who were pregnant and gave birth during the COVID-19 pandemic. This systematic 135 \nreview and meta-analysis therefore assessed th e prevalence of mental ill-health in women 136 \nduring pregnancy and after childbirth during the Covid-19 pandemic. We then compared our 137 \nfindings in relation to other global pandemics including severe acute respiratory syndrome 138 \n(SARS) and Middle Eastern Respiratory Syndrome (MERS). 139 \n 140 \n 141 \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted June 14, 2022. ; https://doi.org/10.1101/2022.06.13.22276327doi: medRxiv preprint \n\n \n4 \n \n 142 \n 143 \nMethods: 144 \nA systematic methodology was developed along with a relevant protocol that was peer 145 \nreviewed and published in PROSPERO (CRD42021235356). The developed method 146 \nfocuses on the prevalence of mental ill-health in women during pregnancy and after 147 \nchildbirth during the Covid-19 pandemic.  148 \n 149 \nSearch criteria  150 \nThe search criteria was developed based upon the research question using PubMed, 151 \nScience direct, Ovid PsycINFO and EM BASE databases: PubMed, Science direct and 152 \nEMBASE. We developed a wide search criteri on to ensure the inclusion of any pregnant 153 \nwomen with existing gynaecological conditions. The MeSH terms used include (COVID) OR 154 \n(SARS-CoV-2) AND (SARS) AND (MERS) AND ((mental health) OR (depression) OR 155 \n(anxiety) OR (PTSD) OR (psychosis) OR (unipolar) OR (bipolar)) AND ((PCOS) OR (fibroid) 156 \nOR (endometriosis) OR (pre-eclampsia) OR (still  birth) OR (GDM) OR (preterm birth) OR 157 \n(women's health) OR (pregnant women) OR (pregnancy)). 158 \nScreening eligibility criteria 159 \nAll studies published in English were included from 20 th December 2019 to 31 st July 2021. 160 \nScreening and data extraction were performed by two authors independently. Initially, titles 161 \nand abstracts were reviewed to determine the relevance. A PRISMA diagram was 162 \ncompleted based on the eligibility steps completed.  163 \n 164 \nData extraction 165 \nFull texts of the included papers were reviewed carefully to extract data including time and 166 \nlocations of the study, participants and sample size, mean age, gestation, days since 167 \nchildbirth, prevalence of mental symptoms, data collection tools used, and cut-offs scores 168 \napplied. Any disagreement was discussed and resolved by consensus between two authors. 169 \nFor studies with both COVID-19 cohort and non-COVID-19 cohort, we only used data of the 170 \nCOVID-19 cohort and the p-value comparing them. Studies from SARS and MERS were 171 \nalso reviewed in full to ensure the eligibility criteria was met. For studies reporting mean 172 \n(SD) or median (IQR) of the scales measuring mental symptoms instead of prevalence rates 173 \nwere included and a simulation method assuming normal distribution was applied to 174 \ngenerate the corresponding prevalence rates. 175 \nRisk of bias assessment 176 \nA risk of bias assessment was completed with a RoB table.  177 \nData analysis 178 \nRandom effects model with restricted maximum-likelihood estimation method was applied 179 \nfor meta-analysis and I-square statistic was used to evaluate heterogeneity across studies. 180 \nThe pooled prevalence rates of anxiety, depressi on, PTSD, stress and sleep disorder with 181 \n95% confidence interval (CI) were computed. Subgroup analysis was conducted in terms of 182 \ntrimester. Sensitivity analysis was performed to assess the robustness of the results. 183 \nPotential publication bias was assessed with funnel plot and Egger’s test. Analyses were 184 \nconducted with the R studio (version 1.4.17.17) and STATA 16.1. 185 \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted June 14, 2022. ; https://doi.org/10.1101/2022.06.13.22276327doi: medRxiv preprint \n\n \n5 \n \n 186 \nResults: 187 \n 188 \nOur initial search identified a total of 1603 papers and 523 studies were excluded after 189 \nscreening by titles and abstracts. After full-text evaluation, 217 and 99 studies were included 190 \nin the systematic review and meta-analysis, respectively. The PRISMA (Preferred Reporting 191 \nItems for Systematic Reviews and Meta-analyses) flowchart was illustrated in Figure 1.  192 \nInclusion and exclusion criteria 193 \nAll COVID-19, SARS and MERS studies that evaluated the mental health of pregnant 194 \nwomen that may or may not have gynaecological conditions that were reported in English 195 \nbetween December 2000 – July 2021 were included. All other studies were excluded from 196 \nthis analysis.  197 \nCharacteristics of studies 198 \nA total of 217 COVID-19 studies were included and 99 studies were meta-analysed. These 199 \nstudies were reported from various parts of t he world, as indicated in the characteristics 200 \nTable 1.  We did not identify SARS and MERS studies that were suitably aligned to the 201 \neligibility criteria of our study.  202 \nStudy design, source of data, data collection method and sample size 203 \nAll 217 studies used different study designs; 107 cross-sectional, 7 cohort and 7 case 204 \ncontrolled. A total of 23 qualitative studies us ed self-reported methods of data collection. All 205 \nstudies reported a variety of mental health symptoms. Real-world data from hospital 206 \nadmissions were used in 5 studies whilst 2 extracted data from patient medical records. The 207 \n217 study pool comprised of a sample of 638,889 pregnant women whilst 6898 were within 208 \n90 days of delivery. The sample sizes used within the studies varied considerably; 129 209 \ncomprised of approximately 500, 40 with 500–999, 18 with 1000–1999 and 24 ≥ 2000 210 \nwomen.  211 \nStages of pregnancy assessed 212 \nA total of 99 studies reported pregnant women during their first, second and third trimester.   213 \nSite of data collection 214 \nMany studies reported that data collection took  place during routine antenatal or postnatal 215 \nvisits in outpatient departments, tertiary/provincial hospitals, secondary level or district 216 \nhospitals and primary healthcare facility level.  217 \nOf the 217 systematically included studies, 64 reported data on depression, 82 on anxiety, 218 \n20 on stress, 7 on PTSD, and 8 on sleep disorder. Detailed characteristics of the 219 \nsystematically included studies and those meta-analysed are listed in Table 1 and 2 (table 2 220 \nsupplementary material).  221 \n 222 \n 223 \n 224 \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted June 14, 2022. ; https://doi.org/10.1101/2022.06.13.22276327doi: medRxiv preprint \n\n \n6 \n \n 225 \nTable 1. 217 studies in systematic review and meta-analysis 226 \n 227 \nID Authors Publication \nYear \nCountry Sample \nsize \np-value \n1 Wu Y 2020 China 1285 0.01 \n2 Duranku ş  F 2020 Turkey 260 N/A \n3 Moyer CA 2020 United States 2740 p<0.001 \n4 Zanardo V 2020 Italy 91 p<0.001 \n5 López-Morales H 2021 Argentina 43 N/A \n6 Salehi L 2020 Iran 220 N/A \n7 Pariente G 2020 Israel 223 0.002 \n8 Ostacoli L 2020 Italy 163 N/A \n9 Ravaldi C 2021 Italy 200 p<0.001 \n10 Zhou Y 2020 China 544 N/A \n11 Kahyaoglu Sut H 2021 Turkey 403 N/A \n12 Hui PW 2021 Hong Kong (China) 925 p<0.05 \n13 Oskovi-Kaplan ZA 2021 Turkey 223 N/A \n14 Sinaci S 2020 Turkey 246 N/A \n15 Dong H 2021 China 156 N/A \n16 Hocaoglu M 2020 Turkey 283 p=0.01 \n17 Liang P 2020 China 845 N/A \n18 Preis H 2020 US 4451 N/A \n19 Yue C 2021 China 308 N/A \n20 Maharlouei N 2020 Iran 540 N/A \n21 Medina-Jimenez V 2020 Mexico 503 N/A \n22 Ceulemans M 2020 Belgium 3445 N/A \n23 Milne SJ 2020 Ireland 70 N/A \n24 Matsushima M 2020 Japan 1777 N/A \n25 Ceulemans M 2021 Ireland, Norway, Switzerland, \nthe Netherlands, and the UK \n3545 N/A \n26 Gildner TE 2020 US 1856 N/A \n27 Shayganfard M 2020 Iran 103 N/A \n28 Yassa M 2020 Turkey 203 N/A \n29 Silverman ME 2020 US 516 p<0.001 \n30 Muhaidat N 2020 Jordan 944 N/A \n31 Thayer ZM 2021 US 2099 N/A \n32 Jiang H 2021 China 1873 N/A \n33 Zhang Y 2021 China 560 N/A \n34 Mayeur A 2020 France 88 N/A \n35 Lin W 2021 China 751 N/A \n36 Zhang CJP 2020 China 1901 N/A \n37 Yang X 2021 Chinese 19515 N/A \n38 Khamees RE 2021 Egypt 120 p<0.001 \n39 Lorentz MS 2021 Brazil 50 p=0.004 \n(comparing \nscores) \np=0.062 \n(comparing \nprevalence) \n40 Silverman ME 2020 US 485 N/A \n41 Akgor U 2021 Turkey 297 N/A \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted June 14, 2022. ; https://doi.org/10.1101/2022.06.13.22276327doi: medRxiv preprint \n\n \n7 \n \n42 Shahid A 2020 Pakistan 552 N/A \n43 Preis H 2020 US 788 N/A \n44 Dagklis T 2020 Greece 269 p<0.001 \n45 Ionio C 2021 Italy 40 N/A \n46 Esteban-Gonzalo S 2021 Spain 353 N/A \n47 Koyucu RG 2021 Turkey 729 N/A \n48 Overbeck G 2021 Denmark 330 0.2209 \n49 Kachi Y 2021 Japan 270 N/A \n50 Mariño-Narvaez C 2021 Spain 75 p=0.038 \n51 Liu J 2021 US 715 N/A \n52 Smith CL 2021 USA 83 N/A \n53 Cao Y 2021 China 298 N/A \n54 Mappa I 2021 Italy 161 p<0.0001 \n55 Mehdizadehkashi A 2021 Iran 300 N/A \n56 Yirmiya K 2021 Israel 1114 N/A \n57 Xie M 2021 China 689 p=0.03 \n58 Ge Y 2021 China 446 N/A \n59 López-Morales H 2021 Argentina 102 N/A \n60 Puertas-Gonzalez JA 2021 Spain 100 p=0.025 \n61 Çolak S 2021 Turkey  149 N/A \n62 Xu K 2021 China 274 N/A \n63 Zilver SJM 2021 Netherlands 1102 p=0.14(compa\nring \nprevalence)/p\n=0.03(compari\nng score) \n64 Maharlouei N 2021 Iran 540 N/A \n65 Harrison V 2021 UK 205 N/A \n66 Saadati N 2021 Iran 300 N/A \n67 Wang Q 2021 China 15428 N/A \n68 Behmard V 2021 Iran 801 N/A \n69 King LS 2021 US 725 p<0.001 \n70 Nurrizka RH 2021 Indonesia 120 N/A \n71 Jelly P 2021 India 333 N/A \n72 Wang Q 2021 China 19515 N/A \n73 Zhang Y 2021 China 1794 N/A \n74 Masjoudi M 2021 Iran 215 N/A \n75 Shangguan F 2021 China 2120 N/A \n76 T sakiridis I 2021 Greece 505 N/A \n77 Brik M 2021 Spain 164 N/A \n78 Effati-Daryani F 2021 Iran 437 N/A \n79 Boekhorst MGBM 2021 Netherlands 265 N/A \n80 An R 2021 China 209 N/A \n81 Lubián López DM 2021 Spain 514 N/A \n82 Maleki A 2021 Iran 2336 N/A \n83 Khoury JE 2021 Canada 304 N/A \n84 Suárez-Rico BV 2021 Mexico 293 N/A \n85 Korukcu O 2021 Turkey 497 p<0.0001 \n86 Obata S 2021 Japan 4798 N/A \n87 Sakalidis VS 2021 Australia and New Zealand 233 N/A \n88 Basu A 2021 64 countries 6894 N/A \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted June 14, 2022. ; https://doi.org/10.1101/2022.06.13.22276327doi: medRxiv preprint \n\n \n8 \n \n89 Kara P 2021 Turkey 445 N/A \n90 Fallon V 2021 UK 614 p<0.001 \n91 Mo PKH 2021 China 4087 N/A \n92 Wu F 2021 Shenzhen 3434 N/A \n93 Ding W 2021 Wuhan 817 N/A \n94 Chrzan-D ę tkoś  M 2021 Poland 78 p=0.025 \n95 Janevic T 2021 New York 228 N/A \n96 Thompson KA 2021 US 232 N/A \n97 Mirzaei N 2021 Iran 200 N/A \n98 Hiiragi K 2021 Japan 279 p=0.17 \n99 McFarland MJ 2021 US 2402 N/A \n100 Zhou Y 2021 China 1266 N/A \n101 Gluska H 2021 Israel 421 N/A \n102 Liu CH 2021 US 628 p<0.01 \n103 Ramirez Biermann C 2021 US 162 N/A \n104 Palalioglu RM 2021 Turkey 526 N/A \n105 Molgora S 2020 Italian 389 N/A \n106 Patabendige M 2020 Sri Lanka 257 N/A \n107 Mollard E 2021 US 885 N/A \n108 Wang J 2021 China 2235 N/A \n109 Zeng X 2020 China 625 N/A \n110 Miranda AR MD 2021 Argentina 305 N/A \n111 Nomura R 2021 Brazil 1662 N/A \n112 Davis JA 2021 US 31 N/A \n113 Provenzi L 2021 Italy 163 N/A \n114 Kotabagi P 2020 UK 11 N/A \n115 Berthelot N 2020 Canada 1258 0.001 \n116 Corbett GA 2020 NA 71 N/A \n117 Farrell T 2020 Qatar 288 N/A \n118 Stepowicz A 2020 Poland 210 N/A \n119 Mayopoulos GA 2021 United States 637 0.008 \n120 Liu CH 2021 United States 1123 N/A \n121 Farewell CV 2020 United States 27 N/A \n122 Haruna M 2020 Japan 2872 N/A \n123 Bender WR 2020 United States 318 N/A \n124 Aksoy Derya Y 2021 Turkey 48 N/A \n125 Nodoushan RJ 2020 Iran 560 N/A \n126 Mortazavi F 2021 Iran 484 N/A \n127 Chasson M 2021 Israel 233 N/A \n128 T aubman-Ben-Ari O 2020 Israel 233 N/A \n129 Moyer CA 2021 Ghana 71 N/A \n130 Dib S 2020 UK 1329 N/A \n131 Qi M 2020 China 298 N/A \n132 Kassaw C 2020 Ethiopia 178 N/A \n133 Zheng QX 2020 China 331 N/A \n134 0 2021 Brazil 1041 N/A \n135 Perzow SED 2021 US 135 p<0.001 \n136 Pope J 2021 US,Ireland,UK 573 N/A \n137 Kotabagi P 2020 UK 14 p=0.9 \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted June 14, 2022. ; https://doi.org/10.1101/2022.06.13.22276327doi: medRxiv preprint \n\n \n9 \n \n138 Naurin E 2021 Sweden 0 N/A \n139 Bo HX 2021 China 1309 N/A \n140 Barbosa-Leiker C 2021 US 162 N/A \n141 Stampini V 2021 Italy 600 N/A \n142 Li C 2021 China 2201 N/A \n143 Bradfield Z 2021 Australia 2840 N/A \n144 Kinser PA 2021 US 524 N/A \n145 Özkan Ş at S 2021 Turkey 376 N/A \n146 Kawamura H 2021 Japan 297 N/A \n147 Silverio SA 2021 UK 710 N/A \n148 Ahlers-Schmidt CR 2020 US 114 N/A \n149 de Arriba-García M 2021 Spain 754 N/A \n150 Chaves C 2021 Spain 724 N/A \n151 Wdowiak A 2021 Poland 50 N/A \n152 Ravaldi C 2020 Italy 2448 N/A \n153 Wyszynski DF 2021 64 countries 7185 N/A \n154 Sbrilli MD 2021 US 199 N/A \n155 Davenport MH 2020 Canada 900 p<0.01 \n156 Di Mascio D 2020 China,Saudia Arabia,South \nKorea,United \nArab,Jordan,Canada,USA \n19  \n157 Juan J 2020 USA,Iran,China,Italy,Spain,Pe\nru,Sweden,Turkey,Korea,Aust\nralia,Canada and France \n24  \n158 Amaral WND 2020 China,France,US,Iran,Italy,Sp\nain,EUA,Peru,UK, \nSwitzerland,Netherlands,Irela\nnd,Sweden,Canada,Korea \n1457  \n159 Di Mascio D 2020 Argentina,Australia,Belgium,B\nrazil,Colombia,Czech \nRepublic,Finland,Germany,Gr\neece,Israel,Italy, North \nMacedonia,Peru,Portugal,Re\npublic of \nKosovo,Romania,Russia,Ser\nbia,Slovenia,Spain,Turkey,US \n388  \n160 Sentilhes L 2020 Europe,Sub-Saharan \nAfrica,North Africa \n38  \n161 Sahin D 2021 Turkey 533  \n162 Kayem G 2020 France 617  \n163 Adhikari EH 2020 T exas,US 252  \n164 Garcia Rodriguez A 2020 N/A 1  \n165 Islam MM 2020 N/A 235  \n166 Hansen JN 2021 N/A 1  \n167 Oltean I 2021 N/A 315  \n168 Wei SQ 2021 N/A 438548  \n169 Singh V 2021 India 132  \n170 Della Gatta AN 2021 China 51  \n171 Di Toro F 2021 N/A 1104  \n172 Bellos I 2021 China 158  \n173 Abou Ghayda R 2020 China,Italy,Iran 104  \n174 Remaeus K 2020 Sweden 67  \n175 Mullins E 2020 N/A 1606  \n176 Zaigham M 2020 China,Sweden,US,Korea,Hon\nduras \n108  \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted June 14, 2022. ; https://doi.org/10.1101/2022.06.13.22276327doi: medRxiv preprint \n\n \n10 \n \n177 Yu N 2020 China 7  \n178 Galang RR 2020 N/A 12  \n179 Capobianco G 2020 N/A 44  \n180 Berthelot N 2020 Canada 1258  \n181 Mappa I 2020 Italy 178  \n182 Ayaz R 2020 N/A 63  \n183 Dubey P 2020 N/A 790  \n184 Pierce-Williams RAM 2020 USA 44  \n185 Gao YJ 2020 N/A 236  \n186 Yang R 2020 China 65  \n187 Yee J 2020 N/A 9032  \n188 Liu X 2020 China 1947  \n189 Novoa RH 2020 N/A 322  \n190 Matar R 2020 China,US,Republic of \nKorea,Honduras \n136  \n191 Gur RE 2020 America 787  \n192 Sakowicz A 2020 America 1317  \n193 T aubman-Ben-Ari O 2020 Israel 336  \n194 Ng QJ 2020 Singapore 324  \n195 Hamzehgardeshi Z 2020 Iran 318  \n196 Ozsurmeli M 2020 Turkey 24  \n197 Makvandi S 2020 N/A 68  \n198 Guo Y 2020 China 20  \n199 Karimi L 2020 N/A 571  \n200 Waratani M 2020 Japan 1  \n201 Savasi VM 2020 Italy 11  \n202 Effati-Daryani F 2020 Iran 205  \n203 Smith V 2020 N/A 92  \n204 Chen H 2020 China 9  \n205 Wang Y 2020 China 72  \n206 Janevic T 2021 USA 3731  \n207 Cao D 2020 China 10  \n208 Lebel C 2020 Canada 1764/175\n7 \n \n209 Marín Gabriel MA 2020 Spain 11  \n210 Lokken EM 2020 America 155  \n211 Ashraf MA 2020 N/A 90  \n212 de Vasconcelos \nGaspar A \n2021 Portugal 7  \n213 Huntley BJF 2020 N/A 538  \n214 Khoury R 2020 USA 241  \n215 Diriba K 2020 N/A 1316  \n216 Assiri A 2016 N/A 5  \n217 Malik A 2016 N/A 1  \n 228 \n 229 \n 230 \n 231 \n 232 \n 233 \n 234 \n 235 \n 236 \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted June 14, 2022. ; https://doi.org/10.1101/2022.06.13.22276327doi: medRxiv preprint \n\n \n11 \n \nTable 2. 99 studies selected for meta-analysis of depression, anxiety, stress, PTSD and sleep disorders 237 \n 238 \nAuthors Country Sample \nSize \nPublication \nYear \nSymptoms Measure Name \nLebel C Canada 1757/ \n1764 \n2020 Anxiety,Depression PROMIS,EPDS \nAyaz R Turkey 63 2020 Anxiety BAI \nDurankuş  F Turkey 260 2020 Anxiety,Depression BAI,EPDS \nLiu X China 1947 2020 Anxiety SAS \nMappa I Italy 178 2020 Anxiety STAI-T ,STAI-S \nLópez-Morales H Argentina 72 2021 Anxiety,Depression STAI-S,BDI-II \nSalehi L Iran 220 2020 Anxiety CDAS \nGur RE United States 787 2020 Anxiety,Depression GAD-7,PHQ-2 \nNg QJ Singapore 324 2020 Anxiety,Depression,Str\ness \nDASS21-A, \nDASS21-D, \nDASS21-S \nEffati-Daryani F Iran 205 2020 Anxiety,Depression,Str\ness \nDASS21-A, \nDASS21-D, \nDASS21-S \nRavaldi C Italy 200 2021 Anxiety COVID-ASSESS \nquestionnaire \nZhou Y China 544 2020 Anxiety,Depression,PT\nSD,Sleep orders \nGAD-7,PHQ-\n9,PCL-5,ISI \nKahyaoglu Sut H Turkey 403 2021 Anxiety,Depression HADS-A, \nHADS-D \nSinaci S Turkey 200 2020 Anxiety STAI-T ,STAI-S \nDong H China 156 2021 Anxiety,Depression SAS,SDS \nHocaoglu M Turkey 283 2020 Anxiety,PTSD STAI-T ,STAI-\nS/IES-R \nYue C China 308 2021 Anxiety SAS \nTaubman-Ben-Ari O Israel 336 2020 Anxiety self-designed \nquestionnaire \nMaharlouei N Iran 540 2020 Anxiety self-designed \nquestionnaire \nMilne SJ Ireland 70 2020 Anxiety N/A \nCeulemans M Ireland, Norway, \nSwitzerland, the \nNetherlands, and \nthe UK \n3545 2021 Anxiety,Depression,Str\ness \nGAD-7,EDS, \nPSS-10 \nYassa M Turkey 203 2020 Anxiety STAI-S,STAI-T \nJiang H China 1873 2021 Anxiety,Depression,Str\ness \nSAS,EDS, \nCPSS-14 \nMayeur A France 88 2020 Anxiety self-designed \nquestionnaire \nLin W China 751 2021 Anxiety,Depression SAS,PHQ-9 \nYang X Chinese 19515 2021 Anxiety,Depression GAD-7,PHQ-9 \nAkgor U Turkey 297 2021 Anxiety,Depression HADS-A, \nHADS-D \nPreis H US 788/4451 2020 Anxiety,Stress GAD-7,PREPS \nDagklis T Greece 269/215 2020 Anxiety,Depression STAI-S,STAI-\nT/EPDS \nEsteban-Gonzalo S Spain 353 2021 Anxiety STAI-S \nKoyucu RG Turkey 729 2021 Anxiety,Depression,Str\ness \nDASS21-A, \nDASS21-D, \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted June 14, 2022. ; https://doi.org/10.1101/2022.06.13.22276327doi: medRxiv preprint \n\n \n12 \n \nDASS21-S \nLiu J US 715 2021 Anxiety,Depression GAD-7,EPDS \nCao Y China 298 2021 Anxiety,Depression N/A \nMappa I Italy 161 2021 Anxiety STAI-T ,STAI-S \nMehdizadehkashi A Iran 300 2021 Anxiety self-designed \nquestionnaire \nYirmiya K Israel 1114 2021 Anxiety,Depression,Str\ness \nGAD-7,PHQ-\n2,PREPS \nXie M China 689 2021 Anxiety,Depression,Sl\neep disorders \nSCL90-R,PSQI \nGe Y China 446 2021 Anxiety SAS \nLópez-Morales H Argentina 102 2021 Anxiety,Depression STAI-S,BDI-II \nPuertas-Gonzalez \nJA \nSpain 100 2021 Anxiety,Depression,Str\ness \nSCL-90-R,PSS-14 \nÇolak S Turkey  149 2021 Anxiety,Depression,Str\ness \nBAI,BDI,PSQI \nXu K China 274 2021 Anxiety,Depression,Str\ness,Sleep disorders \nSAS,EPDS,CPSS,\nPSQI \nZilver SJM Netherlands 1102 2021 Anxiety,Depression,Str\ness \nHADS-A,HADS-\nD,PSS-10 \nMaharlouei N Iran 540 2021 Anxiety,Depression,Str\ness \nDASS21-A, \nDASS21-D, \nDASS21-S \nHarrison V UK 205 2021 Anxiety,Depression PASS,EPDS \nSaadati N Iran 300 2021 Anxiety HAQ \nWang Q China 15428 2021 Anxiety,Depression GAD-7,PHQ-9 \nBehmard V Iran 801 2021 Anxiety CDAS \nHamzehgardeshi Z Iran 318 2021 Anxiety,Depression PRAQ,EPDS \nJelly P India 333 2021 Anxiety GAD-7 \nWang Q China 19515 2021 Anxiety,Depression GAD-7,PHQ-9 \nZhang Y China 1794/560 2021 Anxiety,Stress SAS,IES \nMasjoudi M Iran 215 2021 Anxiety,Stress CDAS,PSS-14 \nShangguan F China 2120 2021 Anxiety,Stress GAD-7,PSS \nTsakiridis I Greece 505 2021 Anxiety,Depression STAI-S,STAI-\nT/EPDS \nBrik M Spain 109/164 2021 Anxiety STAI-S,STAI-\nT/EPDS \nEffati-Daryani F Iran 437 2021 Anxiety,Depression,Str\ness \nDASS21-A, \nDASS21-D, \nDASS21-S \nLubián López DM Spain 514 2021 Anxiety STAI-S,STAI-\nT/EPDS \nMaleki A Iran 2336 2021 Anxiety GAD-7 \nKhoury JE Canada 304 2021 Anxiety,Depression,Str\ness,Sleep disorders \nGAD-7,CES-\nD,PSS-10,ISI \nSuárez-Rico BV Mexico 293 2021 Anxiety STAI-T \nObata S Japan 4798 2021 Anxiety,Depression K6,EPDS \nMo PKH China 4087 2021 Anxiety,Depression GAD-7,PHQ-9 \nWu F Shenzhen 3434 2021 Anxiety,Depression GAD-7,PHQ-9 \nDing W Wuhan 817 2021 Anxiety SAS \nMirzaei N Iran 200 2021 Anxiety,Depression HADS-A, \nHADS-D \nRamirez Biermann \nC \nUS 162 2021 Anxiety,Depression self-designed \nquestionnaire \nPalalioglu RM Turkey 526 2021 Anxiety self-designed \nquestionnaire \nMolgora S Italian 389 2020 Anxiety,Depression STAI-S,STAI-\nT/EPDS \nPatabendige M Sri Lanka 257 2020 Anxiety,Depression HADS-A, \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted June 14, 2022. ; https://doi.org/10.1101/2022.06.13.22276327doi: medRxiv preprint \n\n \n13 \n \nHADS-D \nZeng X China 516 2020 Anxiety,Depression,Sl\neep disorders \nGAD-7,EPDS, \nDSM-IV \nNurrizka RH Indonesia 36 2021 Anxiety DASS-21-A \nWu Y China 1285 2020 Depression EPDS \nWang Y China 72 2020 Depression,PTSD EPDS,PCL-C \nMedina-Jimenez V Mexico 503 2020 Depression,Stress EPDS,PSS \nMatsushima M Japan 1777 2020 Depression EPDS \nGildner TE US 1856 2020 Depression EPDS \nShayganfard M Iran 66 2020 Depression,Stress EPDS,PSS-14 \nSilverman ME US 516 2020 Depression EPDS \nMuhaidat N Jordan 944 2020 Depression self-designed \nquestionnaire \nThayer ZM US 2099 2021 Depression EPDS \nZhang CJP China 1901 2020 Depression,PTSD EPDS,PCL-S \nKhamees RE Egypt 120 2021 Depression EPDS \nSilverman ME US 485 2020 Depression EPDS \nShahid A Pakistan 552 2020 Depression,Sleep \ndisorders \nEPDS,self-\ndesigned \nquestionnaire \nIonio C Italy 75 2021 Depression EPDS \nOverbeck G Denmark 330 2021 Depression MDI \nKachi Y Japan 270 2021 Depression EPDS \nSmith CL USA 83 2021 Depression,Stress EPDS,PSS-10 \nKing LS US 725 2021 Depression EPDS \nKorukcu O Turkey 497 2021 Depression EDS \nZhou Y China 1266 2021 Depression PHQ-9 \nChaves C Spain 450 2021 Depression EPDS \nDavis JA US 31 2021 Stress PSS-10 \nIonio C Italy 75 2021 PTSD IES-R \nBasu A 64 countries 5712 2021 PTSD IES-6 \nKara P Turkey 445 2021 PTSD PCL-5 \nWang J China 2235 2021 Sleep disorders ISI \n 239 \n 240 \n 241 \n 242 \n 243 \n 244 \n 245 \n 246 \n 247 \n 248 \n 249 \n 250 \n 251 \n 252 \n 253 \n 254 \n 255 \n 256 \n 257 \n 258 \n 259 \n 260 \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted June 14, 2022. ; https://doi.org/10.1101/2022.06.13.22276327doi: medRxiv preprint \n\n \n14 \n \n 261 \nMeta-analysis 262 \nEdinburgh Postnatal Depression Scale (EPDS), the Patient Health Questionnaire 9-item 263 \n(PHQ-9), the depression subscale of the Hospital Anxiety and Depression Scale (HADS-D) 264 \nwere the commonly used data collection tools to assess symptoms of depression in women 265 \nduring pregnancy and after childbirth. The pooled prevalence of depression was 24.91% 266 \nwith a 95% CI of 21.37%- 29.02% (Figure 2).   267 \nFigure 2. Forest plot of depression 268 \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted June 14, 2022. ; https://doi.org/10.1101/2022.06.13.22276327doi: medRxiv preprint \n\n \n15 \n \n 269 \n 270 \n 271 \n 272 \n 273 \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted June 14, 2022. ; https://doi.org/10.1101/2022.06.13.22276327doi: medRxiv preprint \n\n \n16 \n \nAnxiety symptoms were commonly measured by the State-Trait Anxiety Inventory (STAI, 274 \nwith two subscales STAI-T and STAI-S), the General Anxiety Disorder 7-item (GAD-7) and 275 \nSelf-rating Anxiety Scale (SAS). Anxiety prevalence was 32.88% with a 95% CI of 29.05% to 276 \n37.21% (Figure 3).   277 \nFigure 3. Forest plot of anxiety 278 \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted June 14, 2022. ; https://doi.org/10.1101/2022.06.13.22276327doi: medRxiv preprint \n\n \n17 \n \n 279 \n 280 \n 281 \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted June 14, 2022. ; https://doi.org/10.1101/2022.06.13.22276327doi: medRxiv preprint \n\n \n18 \n \nTools like the Perceived Stress Scale (PSS, wi th 10-item and 14-item versions), the stress 282 \nsubscale of the 21-item Depression Anxiety and Stress Scale (DASS21-S) were frequently 283 \nused to evaluate stress symptoms. The pooled prevalence of stress among perinatal women 284 \nwas 29.44% (95% CI: 18.21% - 47.61%) as demonstrated in Figure 4.   285 \nFigure 4. Forest plot of stress 286 \n 287 \n 288 \n 289 \nPTSD symptoms were typically measured by the DSM-V Post-Traumatic Stress Disorder 290 \nChecklist (PCL-5) and the Impact of Events Scale (IES). The studies reporting PTSD 291 \nsymptoms were heterogeneous (Figure 5) resulting in a pooled prevalence of 27.93% with a 292 \n95%CI of 9.05%-86.15%.   293 \nFigure 5. Forest plot of PTSD 294 \n 295 \n 296 \n 297 \nThe Insomnia Severity Index (ISI) and the Pittsburgh Sleep Quality Index (PSQI) were to 298 \nassess and report symptoms associated with sleep disorders. The pooled prevalence was 299 \n24.38% with a 95% CI of 11.89%-49.96% (Figure 6 supplementary material).  300 \n 301 \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted June 14, 2022. ; https://doi.org/10.1101/2022.06.13.22276327doi: medRxiv preprint \n\n \n19 \n \nFigure 6. Forest plot of sleep disorders 302 \n 303 \n 304 \n 305 \n 306 \n 307 \nThe I 2 evaluated for depression, anxiety, PTSD, stress and sleep issues were over 98%, 308 \nwhich demonstrates a high heterogeneity among the studies. Therefore, a subgroup 309 \nanalysis was conducted to further evaluate the heterogeneity.  310 \nSubgroup analysis 311 \nWomen were assessed at different stages of their pregnancy. To determine the rates of 312 \ndepression, anxiety, PTSD, stress and sleep problems, the dataset was categorised based 313 \non the trimesters;1 st trimester (<12 weeks), 2 nd trimester (13-27 weeks), 3 rd trimester (28-41 314 \nweeks)] and the immediate post-partum period (immediately after childbirth and up to six 315 \nweeks) for studies that reported follow-up details.   316 \nThe heterogeneity of depression is lower in comparison to anxiety, PTSD, stress and sleep 317 \nproblems. Heterogeneity within the 1 st trimester was 89.47%. I 2 of the anxiety group during 318 \nthe 1st trimester and 2 nd trimester were 88.91% and 92.35%, respectively. These appear to 319 \nsimilar to the I 2 values of depression.  I 2 for stress associated with the 2 nd and 3rd trimesters 320 \nwere 78.57% and 64.65%, respectively, indicating mild heterogeneity. Intuitively, Maharlouei 321 \nand colleagues study reported a small prevalence, thus could be an influencing factor for the 322 \nheterogeneity reported.  I 2 for PTSD across three trimesters were 24.67%, 89.47% and 323 \n81.62%, respectively. I 2 was 0% during the 1 st trimester within the groups of participants 324 \nreporting sleep disturbance. 1 st trimester group showed relatively low heterogeneity across 325 \nmental health symptoms, thus strictly sti pulating the gestational weeks of the included 326 \npregnancy helped reduce the heterogeneity.  327 \n 328 \n 329 \n 330 \n 331 \n 332 \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted June 14, 2022. ; https://doi.org/10.1101/2022.06.13.22276327doi: medRxiv preprint \n\n \n20 \n \n[Figure 7] 333 \nFigure 7 Subgroup analysis of depression 334 \n 335 \n 336 \n 337 \n 338 \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted June 14, 2022. ; https://doi.org/10.1101/2022.06.13.22276327doi: medRxiv preprint \n\n \n21 \n \n[Figure 8]  339 \nFigure 8 Subgroup analysis of anxiety 340 \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted June 14, 2022. ; https://doi.org/10.1101/2022.06.13.22276327doi: medRxiv preprint \n\n \n22 \n \n 341 \n 342 \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted June 14, 2022. ; https://doi.org/10.1101/2022.06.13.22276327doi: medRxiv preprint \n\n \n23 \n \n[Figure 9] 343 \nFigure 9 Subgroup analysis of stress 344 \n 345 \n 346 \n 347 \n 348 \n 349 \n[Figure 10] 350 \nFigure 10 Subgroup analysis of PTSD 351 \n 352 \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted June 14, 2022. ; https://doi.org/10.1101/2022.06.13.22276327doi: medRxiv preprint \n\n \n24 \n \n 353 \n 354 \n 355 \n 356 \n 357 \n[Figure 11] 358 \nFigure 11 Subgroup analysis of sleep disorders 359 \n 360 \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted June 14, 2022. ; https://doi.org/10.1101/2022.06.13.22276327doi: medRxiv preprint \n\n \n25 \n \n 361 \n 362 \n 363 \nFigure 12. Funnel plot of depression 364 \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted June 14, 2022. ; https://doi.org/10.1101/2022.06.13.22276327doi: medRxiv preprint \n\n \n26 \n \n 365 \n 366 \n 367 \n 368 \nFigure 13. Funnel plot of anxiety 369 \n 370 \n 371 \n 372 \n 373 \n 374 \n 375 \n 376 \n 377 \n 378 \n 379 \n 380 \n 381 \n 382 \nFigure 14. Funnel plot of stress 383 \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted June 14, 2022. ; https://doi.org/10.1101/2022.06.13.22276327doi: medRxiv preprint \n\n \n27 \n \n 384 \n 385 \nFigure 15. Funnel plot of PTSD 386 \n 387 \n 388 \n 389 \n 390 \n 391 \n 392 \n 393 \n 394 \n 395 \n 396 \n 397 \n 398 \n 399 \n 400 \n 401 \n 402 \n 403 \n 404 \nFigure 16. Funnel plot of sleep disorders 405 \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted June 14, 2022. ; https://doi.org/10.1101/2022.06.13.22276327doi: medRxiv preprint \n\n \n28 \n \n 406 \n 407 \n 408 \nPublication bias and sensitivity analysis 409 \nPublication bias and a sensitivity analysis was conducted to assess the reliability of the data 410 \nas some studies had large standard errors that would produce undesirable effects. Copas 411 \nselection model was used to select studies for the sensitivity analysis. The p-values of 412 \nresidual selection bias were evaluated as demonstrated in Figure 17-21. Studies with a p-413 \nvalue of >0.1 indicated that the residual selection had minimal bias and, the selected studies 414 \ncan be represented. The proportions ident ified were 67.84%, 100% and 59.49% for 415 \ndepression, anxiety and sleep disorders, respec tively. Studies reporting stress and PTSD, 416 \nthe copas selection model could not provide a decision indicating the previous conclusions 417 \nof high heterogeneity is accurate.  418 \n 419 \nFigure 17. P-value for residual selection bias of depression 420 \n 421 \nFigure 18. P-value for residual selection bias of anxiety 422 \n 423 \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted June 14, 2022. ; https://doi.org/10.1101/2022.06.13.22276327doi: medRxiv preprint \n\n \n29 \n 424 \n 425 \n 426 \nFigure 19. P-value for residual selection bias of stress 427 \n 428 \n 429 \n 430 \n 431 \nFigure 20. P-value for residual selection bias of PTSD 432 \n 433 \nFigure 21. P-value for residual selection bias of sleep disorders 434 \n 435 \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted June 14, 2022. ; https://doi.org/10.1101/2022.06.13.22276327doi: medRxiv preprint \n\n \n30 \n \n 436 \n 437 \nA summary of studies used within the Copas selection model and random effects model has 438 \nbeen demonstrated in Table 3, which indicates that the two models have no significant 439 \ndifference. P-value of the changes between these conclusions are 0.1108, 0.638 and 0.1042 440 \nfor depression, anxiety and sleep disorders, res pectively. The p-value of the Egger’s test 441 \nwas 0.0256 ( Table 4. supplementary material ) for studies of depression, revealing the 442 \nexistence of publication bias. The p-values of 0.256 and 0.998 (Table 4. supplementary 443 \nmaterial) indicates that it is challenging to detect publication bias for studies associated with 444 \nanxiety and sleep disturbances.  445 \n 446 \nTable 3. Summary of sensitivity analysis 447 \n 448 \nOutcome \nN of \nstud\ny \nModel \nProbability of \npublishing \nstudy with \nlargest \nstandard error \nProporti\non(%) lower(%) upper(%) \np-value for \ndifferences \nbetween two \nconclusions \nDepressio\nn 64 \ncopas selecion \nmodel 67.84% 27.1\n1 \n24.3\n2 30.22 \n0.1108 random effects \nmodel  \n24.9\n1 \n21.3\n7 \n \n29.02 \nanxiety 82 \ncopas selecion \nmodel 100.00% 32.8\n8 \n29.0\n8 37.18 \n0.638 random effects \nmodel  \n32.8\n8 \n29.0\n5 37.21 \nSleep \ndisorders 8 \ncopas selecion \nmodel 59.49% 27.1\n1 \n14.9\n4 49.21 \n0.1042 random effects \nmodel  \n24.3\n8 \n11.8\n9 49.95 \n  449 \nTable 4. P-value of Egger Test for the five mental health symptoms 450 \n 451 \nOutcome N of studies p-value of Egger test \ndepression 64 0.0256* \nanxiety 82 0.256 \nstress 20 0.069 \nPTSD 7 0.742 \nsleep disorders 8 0.998 \nNote:  ( *  ) : p<0.05 indicates significance 452 \n 453 \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted June 14, 2022. ; https://doi.org/10.1101/2022.06.13.22276327doi: medRxiv preprint \n\n \n31 \n \nDiscussion 454 \n 455 \nMain findings 456 \nOur study demonstrates that depression, anxiety, PTSD, stress and sleep problems were 457 \ncommon throughout the pregnancy period and after childbirth during the COVID-19 458 \npandemic with 24.9% of women reporting symptoms of depression, 32.8% anxiety, 29.44% 459 \nstress, 27.93% PTSD, and 24.38% sleep disorders. The lack of research conducted to 460 \nassess the mental health impact of SARS and MERS on pregnant women is a significant 461 \nlimitation as such data could have supported preparation for similar pandemics in the future. 462 \nOur meta-analyses indicated a clear-cut mental health impact of COVID on pregnant and 463 \npost-partum mothers with a pooled prevalence of  multiple symptomatologies of depression, 464 \nanxiety, PTSD, stress and insomnia. 465 \n 466 \nStrengths and weakness  467 \n 468 \nTo our knowledge, this is the first systematic review and meta-analysis to focus on mental 469 \nhealth outcomes in women during pregnancy and after childbirth during the Covid-19 470 \npandemic. The searches were not limited by geographical location or language, therefore, 471 \nfurther increasing the chances for all relevant literature to be identified. The MESH terms 472 \nused did not consider all types of obstetri c or gynaecology conditions but did include the 473 \ncommon conditions. The variety of screening tools used across the included studies must be 474 \nconsidered when interpreting the results of this review. Direct comparisons cannot be made 475 \nwhere the same screening tool was not used. Furthermore, most studies used self-reported 476 \nquestionnaires, with no clinical follow-up to c onfirm diagnoses. Therefore, the results cannot 477 \nbe interpreted as prevalence of mental illness, but rather prevalence of symptomatology. 478 \n 479 \nInterpretation  480 \n 481 \nSome studies have demonstrated that the extent and severity of mental health impact 482 \nincreased in women during pregnancy and after childbirth during humanitarian disasters and 483 \npandemics which is similar to our study [11]. 484 \n 485 \nThe subgroup analysis showed that the prevalenc e of depression is identical during the first 486 \ntrimester of pregnancy [24.61% (95% CI 17.12 – 35.37)] and after childbirth [24.96 (95% CI 487 \n20.26 – 30.76)] compared to the second and  third trimesters when the prevalence of 488 \ndepression is much lower at 16.52 (95% CI 9.31 – 29.33), and 22.49 (95% CI 18.91 – 489 \n26.74), respectively. This is suggestive of women who became pregnant and gave birth 490 \nduring the pandemic suffered from depression more frequently in the early stage and after 491 \nbirth, which appears to have been plateaued during the latter part of their pregnancy. It is 492 \nunclear as to the reason for this observation, and the impact of this in a real-time scenario. 493 \nThe prevalence of anxiety, on the other hand, is higher among women after childbirth [32.09 494 \n(95% CI 25.55 – 40.30)], compared to an identic al prevalence of anxiety during all the three 495 \ntrimesters of pregnancy [1st trimester 22.06 (95% CI 16.08 – 30.25), 2nd trimester 23.37 (95% 496 \nCI 17.36 – 31.45), 3 rd trimester 26.02 (95% CI 19.36 – 34.96)]. This finding suggests that 497 \nwomen after childbirth suffered more from anxiety during the Covid-19 pandemic. The stress 498 \nlevel was significantly higher in women during the 1 st trimester of pregnancy 70.58% (95% 499 \nCI 49.46 – 100.72), compared to 47.81% (95% CI 36.32 – 62.94).  500 \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted June 14, 2022. ; https://doi.org/10.1101/2022.06.13.22276327doi: medRxiv preprint \n\n \n32 \n \n 501 \nThis could be due to some of these women bei ng first-time mothers or, general stress and 502 \nhealth anxiety regarding how and when to access care from midwives and obstetricians as 503 \npart of routine and emergency maternity care  due to the Covid-19 pandemic. The findings of 504 \nhigh level of stress amongst pregnant women is in keeping with other studies carried out 505 \nduring the Covid-19 pandemic that reported up to 70% of pregnant women suffered from 506 \nstress during the pandemic[8]. Being pregnant and giving birth are known triggers for women 507 \nto develop anxiety, and depression and pregnancy is a known risk factor for exacerbations 508 \nor decline in pre-existing mental ill-health[9 ,10]. Other possible reasons for the increase in 509 \nmental ill-health in women during pregnancy or after childbirth may be because of the 510 \nmassive clinical changes that took place regar ding how women could access maternity care 511 \nduring the Covid-19 pandemic.  As pregnant women were at higher risk of severe illness if 512 \nthey become infected with severe acute respiratory syndrome (SARS)-CoV-2 and develop 513 \nCOVID-19, pregnant women were advised to be stringent with public health measures such 514 \nas social distancing and self-isolation to lower their risk of COVID-19 exposure. This led to 515 \nthe rapid implementation of virtual access to antenatal care to minimising the need for travel 516 \nto antenatal clinics and in-person contact with healthcare staff, and antenatal care changed 517 \nimmediately from face-to-face consultations to telephone or video consultations. Birth 518 \npartners were limited in number and visiting hour s for partners were restricted resulting in 519 \nless emotional and psychological support for women during labour in the delivery room, and 520 \nafter childbirth on the postnatal wards. Furthermore, as the Covid-19 vaccination was 521 \ndeveloped and the implementation programme initiated, there was uncertainty regarding the 522 \neffectiveness and safety of the Covid-19 vaccine in women who were pregnant, which may 523 \nhave contributed and exacerbated stress and anxiety.  524 \n 525 \nRecommendations 526 \n 527 \nAll women should be risk assessed for maternal mental health at their booking visit and 528 \nscreened at every contact during pregnancy and after childbirth. All healthcare systems 529 \nneed to invest in perinatal mental health services delivered from a multi-disciplinary team 530 \nincluding mental health nurses, specialist midwives, obstetricians with specialist interest in 531 \nmental health and perinatal psychologists and psychi atrist.  Maternity mental health services 532 \nshould be delivered in a way that meets the specific needs of the individual patient, including 533 \nface-to-face consultations, telephone calls and/or video consultations. Up to date information 534 \nregarding the impact of Covid-19 on maternity services needs to be available and easily 535 \naccessible for women during pregnancy and after childbirth, for example by using social 536 \nmedia campaigns and hospital websites. Learning from this data derived from COVID 537 \npandemic and consideration of the special n eeds of the pregnant and postnatal mothers 538 \nshould be imperative in strategies to implemen t early to improve preparedness of the health 539 \nservice in future pandemics. 540 \n 541 \nConclusion 542 \n 543 \nThis study highlights that maternity mental ill-health was common during the Covid-19 544 \npandemic and highlights the need to understand the complexity of factors associated with 545 \nmaternal mental health. Maternity mental health services need further investment and 546 \nprioritisation and clear effective referral pat hways and support for women who report mental 547 \nhealth concerns during and after pregnancy are needed and require further research as to 548 \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted June 14, 2022. ; https://doi.org/10.1101/2022.06.13.22276327doi: medRxiv preprint \n\n \n33 \n \nhow best provide this care in a way that meets the specific needs of each women, across 549 \ndifferent healthcare systems.  550 \n 551 \n 552 \n 553 \n 554 \n 555 \n 556 \nList of abbreviations: 557 \nMERS- Middle Eastern Respiratory Syndrome 558 \nSARS- Severe acute respiratory syndrome 559 \nEPDS- Edinburgh Postnatal Depression Scale 560 \nSAS- Self-rating Anxiety Scale 561 \nIES- Impact of Events Scale 562 \nISI - Insomnia Severity Index 563 \nPSQI- Pittsburgh Sleep Quality Index 564 \nIAPT- Improving Access to Psychological Therapy 565 \n 566 \nDeclarations: 567 \nEthics approval and consent to participate 568 \nNot applicable for this review? 569 \n 570 \nConsent for publication 571 \nNot applicable? 572 \n 573 \nAvailability of data and materials 574 \nData availability statement goes here. 575 \nCompeting interests 576 \nFinancial and non-financial competing interests should be mentioned here. 577 \n 578 \nFunding 579 \nSource(s) of funding should be mentioned here. Role of the funding source in the design of 580 \nthe study and data collection/analysis/interpretation should be declared. 581 \n 582 \nAuthors’ contributions 583 \nAuthors’ individual contributions should be mentioned here. 584 \n 585 \nAcknowledgements 586 \nAuthors should obtain permission from everyone to be acknowledged in this section. 587 \n 588 \n 589 \n 590 \n 591 \n  592 \n 593 \n 594 \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted June 14, 2022. ; https://doi.org/10.1101/2022.06.13.22276327doi: medRxiv preprint \n\n \n34 \n \n 595 \n 596 \n 597 \n 598 \n 599 \n 600 \nReferences 601 \n1. Odejinmi F, Egbase E, Clark TJ, Mallick R. COVID-19 in Women's health reducing the risk 602 \nof infection to patients and staff during acute and elective hospital admission for 603 \ngynaecological surgery. Best Pract Res Clin Obstet Gynaecol.  2021; 73 : 40-55 [PMID: 604 \n7970477 DOI: 10.1016/j.bpobgyn.2021.03.005]. 605 \n2. Royal College of Obstetricians and Gynaecologists Restoration and Recovery: Priorities 606 \nfor Obstetrics and Gynaecology. Royal College of Obstetricians and Gynaecologists . 2020. 607 \nhttps://www.rcog.org.uk/globalassets/documents/guidelines/2020-05-29-restoration-and-608 \nrecovery---priorities-for-obstetrics-and-gynaecology.pdf  609 \n3. The Lancet Rheumatology. Too long to wait: the impact of COVID-19 on elective surgery. 610 \nLancet Rheumatol . 2021 Feb.; 3: e83 [PMID: 33778775 DOI: 10.1016/s2665-611 \n9913(21)00001-1]  612 \n4. Soares-Júnior JM, Sorpreso ICE, Motta EV, Utiyama EM, Baracat EC. Gynecology and 613 \nwomen's health care during the COVID-19 pandemic: Patient safety in surgery and 614 \nprevention. Clinics (Sao Paulo). 2020 Jun 22; 75: e2063 [PMID: 32578830 DOI: 615 \n10.6061/clinics/2020/e2063]  616 \n5. Galea S, Merchant RM, Lurie N. The Mental Health Consequences of COVID-19 and 617 \nPhysical Distancing: The Need fo r Prevention and Early Intervention. JAMA Intern 618 \nMed. 2020 Jun 1;180: 817-818 [PMID: 32275292 DOI: 10.1001/jamainternmed.2020.1562] 619 \n6. Pfefferbaum B, North CS. Mental Health and the Covid-19 Pandemic. N Engl J Med. 2020 620 \nAug 6; 383: 510-512 [PMID: 32283003 DOI: 10.1056/nejmp2008017]  621 \n7. Loades ME, Chatburn E, Higson-Sweeney N, Reynolds S, Shafran R, Brigden A, et al. 622 \nRapid Systematic Review: The Impact of Social Isolation and Loneliness on the Mental 623 \nHealth of Children and Adolescents in the Context of COVID-19. J Am Acad Child Adolesc 624 \nPsychiatry. 2020; 59:1218-1239.e3 [PMID: 32504808 DOI:  10.1016/j.jaac.2020.05.009] 625 \n8. Yan H, Ding Y, Guo W. Mental Health of Pregnant and Postpartum Women During the 626 \nCoronavirus Disease 2019 Pandemic: A Systematic Review and Meta-Analysis. Front 627 \nPsychol. 2020; 11: 617001 [PMID: 33324308 DOI: 10.3389/fpsyg.2020.617001]  628 \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted June 14, 2022. ; https://doi.org/10.1101/2022.06.13.22276327doi: medRxiv preprint \n\n \n35 \n \n9. Woody CA, Ferrari AJ, Siskind DJ, Whiteford HA, Harris MG. A systematic review and 629 \nmeta-regression of the prevalence and incidence of perinatal depression. J affect disord . 630 \n2017; 219: 86-92 [PMID: 28531848 DOI: 10.1016/j.jad.2017.05.003]  631 \n10. Dennis C-L, Falah-Hassani K, Shiri R. Prevalence of antenatal and postnatal anxiety: 632 \nsystematic review and meta-analysis. Br J Psychiatry. 2017; 210: 315-323 [PMID: 28302701 633 \nDOI: 10.1192/bjp.bp.116.187179]  634 \n11. Harville E, Xiong X, Buekens P. Disasters and perinatal health:a systematic review. 635 \nObstet Gynecol Surv . 2010; 65: 713-28 [PMID: 21375788 DOI: 636 \n10.1097/ogx.0b013e31820eddbe]  637 \n 638 \n 639 \nFigure 1. PRISMA Flow Diagram 640 \nTable 1. 217 studies in systematic review and meta-analysis 641 \nTable 2. (Supplementary material) 99 studies selected for meta-analysis of 642 \ndepression, anxiety, stress, PTSD and sleep disorders 643 \nFigure 2. Forest plot of depression 644 \nFigure 3. Forest plot of anxiety 645 \nFigure 4. Forest plot of stress 646 \nFigure 5. Forest plot of PTSD 647 \nFigure 6 (supplementary material) 648 \nFigure 7 Subgroup analysis of depression (supplementary material) 649 \nFigure 8 Subgroup analysis of anxiety (supplementary material) 650 \nFigure 9 Subgroup analysis of stress (supplementary material) 651 \nFigure 10 Subgroup analysis of PTSD (supplementary material) 652 \nFigure 11 Subgroup analysis of sleep disorders (supplementary material) 653 \nFigure 12. Funnel plot of depression  654 \nFigure 13. Funnel plot of anxiety 655 \nFigure 14. Funnel plot of stress 656 \nFigure 15. Funnel plot of PTSD 657 \nFigure 16. Funnel plot of sleep disorders (supplementary material) 658 \nFigure 17. P-value for residual selection bias of depression 659 \nFigure 18. P-value for residual selection bias of anxiety 660 \nFigure 19. P-value for residual selection bias of stress 661 \nFigure 20. P-value for residual selection bias of PTSD 662 \nFigure 21. P-value for residual selection bias of sleep disorders (supplementary 663 \nmaterial) 664 \nTable 3. Summary of sensitivity analysis (supplementary material) 665 \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted June 14, 2022. ; https://doi.org/10.1101/2022.06.13.22276327doi: medRxiv preprint \n\n \n36 \n \nTable 4. P-value of Egger Test for the five mental health symptoms (supplementary 666 \nmaterial) 667 \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted June 14, 2022. ; https://doi.org/10.1101/2022.06.13.22276327doi: medRxiv preprint \n\nPRISMA Flow Diagram \n \n                                                                                                                 \n \n \n \n \n \n   \n \n \n \n \n \n                                                                                                                            \n \n \n \n \n \n \n \n \n                                                                                         \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \nRelevant records identified \nthrough database \n(n = 975 ) \nScreening Included Eligibility Identification \nAdditional records identified \nthrough other sources \n(n = 628)  \nRecords after duplicates removed \n(n =1376) \nRecords screened \n(n =523) \nRecords excluded \n(n =853) \nFull-text articles \nassessed for eligibility \n(n = 309) \nFull-text articles excluded, with reasons  \n(n = 95) \n-  Duplicated (n=4) \n-  Not relative objective (n=2) \n-  No mental health outcome (n = 55) \n-  No pregnancy group specified (n \n=15) \n-  Study unpublished or incomplete (n \n= ) \n-  With other interventions (n=1) \n-  wrong publication type (n=17) \n-  missed data (n=1) \nFinal sample size \n(n = 217) \nStudies included for the \nsystematic review \n(n =217) \nStudies included for the meta-\nanalysis \n(n =99) \nInitial review (n = 6750) \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted June 14, 2022. ; https://doi.org/10.1101/2022.06.13.22276327doi: medRxiv preprint","source_license":"CC-BY-4.0","license_restricted":false}