Temporal trends in pregnancy outcomes during a health system shock: A retrospective longitudinal study

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Dalrymple, Alice McGreevy, Lucilla Poston, and 14 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6886833/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract To better understand reported COVID-19 pandemic effects on pregnancy, we examined temporal trends in pregnancy outcomes in a diverse population from South London, United Kingdom. We included 31,411 singleton pregnancies with complete registration and birth outcomes across pre-pandemic (May 1/2019–March 22/2020, 24.5%), pandemic lockdowns (March 23/2020–July 17/2021, 32.3%), and pandemic without lockdown epochs (July 18/2021–April 22/2023, 43.2%). Multivariable regression was employed to evaluate outcomes by study epoch, adjusting for potential confounders (e.g., ethnicity, deprivation, site), followed by generalized additive modelling to visualise monthly trends. Of 17 outcomes: six had stable trends (e.g., preterm birth, stillbirth); eight showed linear trends, either decreasing (e.g., gestational age at birth, vaginal tears) or increasing (e.g., Caesareans, postpartum haemorrhage); and three showed quadratic (complex) trends (e.g., secondary mental health services, labour induction). Overall, most outcomes during the pandemic mirrored pre-pandemic trends, with observed fluctuations likely due to site-specific responses. Sexual & Reproductive Medicine Figures Figure 1 Figure 2 Figure 3 Figure 4 INTRODUCTION During the COVID-19 pandemic, pregnant women and birthing people were at risk from direct effects of SARS-CoV-2 infection and indirect effects of maternity service reconfigurations. Whilst a small proportion (≈ 9%) of pregnant or recently pregnant women attending hospital were diagnosed with suspected or confirmed COVID-19 infection( 1 ), all women accessing maternity care were affected by maternity care changes, alongside societal changes in social interaction, isolation, and activity( 2 ). Maternity service reconfigurations included a shift to provision of at least some care via telephone or videoconference; a reduction in the number of antenatal visits; and an increase in self-monitoring for pregnancy-related complications, such as hypertension( 3 ). Globally, the impact of the pandemic on pregnancy outcomes has been examined primarily in the first pandemic year or slightly beyond into the summer of 2021( 4 , 5 ). Many studies have found the pandemic was associated with a reduction in: preterm birth (particularly spontaneous preterm birth), and small-for-gestational age (SGA) babies; increases in mental health problems( 6 ) and intervention at birth, such as labour induction and Caesarean birth( 4 , 5 ); and no effect on stillbirth or neonatal death( 7 ). However, others have reported a lower incidence of labour induction for fetal growth restriction (FGR), in the absence of commonly-associated adverse outcomes( 8 ). Pandemic effects on outcomes have varied by ethnicity, but not social deprivation( 4 ). To inform post-pandemic maternity care planning, this study aimed to extend the period of observation in other studies, and evaluate trends across pre-pandemic, pandemic lockdowns, and pandemic without lockdown phases, in key indicators measured at birth in the UK, reflecting: organisational performance, clinical quality improvement, and national maternity outcomes. Pregnancy outcomes were recorded at monthly intervals, using maternity data from a population of ethnic diversity and high deprivation. METHODS The Early Life Cross Linkage in Research - Born in South London data linkage. Data for this retrospective longitudinal study were obtained from the ‘eLIXIR (Early Life Cross Linkage in Research)-Born in South London (BiSL)’ data linkage, the methods for which have been published previously( 9 ). In brief, these data are routinely-collected, linked maternity, neonatal, and maternal mental health records from two maternity hospitals (Guy’s and St. Thomas’ NHS Foundation Trust, and King’s College Hospital NHS Foundation Trust), in South London, United Kingdom (UK), and Maudsley NHS Foundation Trust (SLaM). Both maternity hospitals provide services that cover community-based, standard-risk, as well as high-risk specialist care to ethnically- and socioeconomically-diverse populations. In line with recommendations from the Royal College of Obstetricians and Gynaecologists and Royal College of Midwives, like most UK maternity units, GSTT and KCH: reduced antenatal contacts, some of which (particularly in early pregnancy) were converted to remote consultations, increased use of self-monitoring of blood pressure, modified screening for gestational diabetes, reduced the frequency of fetal growth surveillance by ultrasound, and reduced options for place of birth( 19 ). Of note, there were few changes to labour induction indications or the offer of Caesarean by request. Site-specific differences were that GSTT, which has a greater focus on maternal high-risk pregnancies, maintained OGTT testing for women at increased risk of GDM. KCH as a centre of excellence for fetal medicine and pre-eclampsia screening, maintained these services, from 11–13 weeks’ gestation; this centre is also co-located with perinatal mental health expertise. The eLIXIR-BiSL dataset includes comprehensive records from antenatal booking to postnatal follow-up, covering ~ 15,000 births annually in an ethnically and socio-demographically diverse population of South London, UK. Raw clinical data are extracted from BadgerNet Systems, securely linked with mental health data from SLaM on the Case Register Interactive Search tool( 10 ), and primary care records from Lambeth DataNet. The data are not coded. Inclusion is based on opt-out consent. For further details, see the Methods Appendix . Participants The target population was women and birthing people who: (i) did not opt-out nationally from research or locally from eLIXIR-BiSL data linkage (as the current course of action by ≈ 0.03% of women); (ii) registered for antenatal care at the relevant NHS hospital (site, as above), between 01/October/2018 (when data linkage began) and 30/April/2023 (the date up to which data were available for both sites) (N = 54,924); and (iii) had both antenatal registration and birth records and dates (N = 36,985) ( Figure S1 ). We included only one birth per woman and birthing people. Those with more than one birth during the study period had one pregnancy randomly included within the data, using the method of Langham et al.( 11 ), allowing simplification of the data structure. (See Table S3 for a comparison of patient characteristics between the full and reduced data, excluding multiple pregnancies per woman). We excluded multifetal pregnancies, as is commonly done due to their high-risk nature, and to support a simplified data structure for birth outcomes( 12 ). We truncated the data to exclude pregnancies outside the timeframe of 01 May 2019, to 22 April 2023 ( Figure S2 ), as linkage across antenatal bookings and delivery data showed tails when summarising the total number of deliveries and/or bookings per month. This was due to pregnancies with late antenatal registration in the antenatal booking data, and preterm births in the delivery data. We chose to truncate the data for a stable ‘number of deliveries’ denominator, to avoid biasing our data for records at the beginning and end of the study period. Data collection and outcomes Baseline maternal and pregnancy characteristics at antenatal registration were demographic factors, and current and past obstetric, medical, social (including socioeconomic status), and mental health history. All variable are listed fully in Table 1 , and include the following indicators of organisation performance measured at antenatal registration: maternal age, ethnicity, index of multiple deprivation (IMD)( 13 ), prior Caesarean, and gestational age at booking. Ethnicity was defined using the eight-category classification by the Office for National Statistics, UK: White, Black/African/Caribbean/Black British, Indian (Asian or Asian British), Pakistani (Asian or Asian British), Other Asian/Asian British, Mixed/multiple ethnic groups, Any other ethnic group, or Not stated/unknown( 14 ). The Index of Multiple Deprivation (IMD) was used as the standard measure in the UK; IMD uses postal code to give an overall measure of deprivation within an defined geographic area (roughly equivalent to a neighbourhood of 1000–3000 people), and incorporates the domains of: income, employment, educations skills and training, health deprivation and disability, crime, barriers to housing and services, and living environment( 13 ). Table 1 Baseline participant pregnancy characteristics, and pregnancy outcomes Overall Pre-pandemic Pandemic with lockdowns Pandemic without lockdowns Antenatal Booking N = 31,411 1 N = 7,706 1 N = 10,137 1 N = 13,568 1 Data Source Site A 18,728 (59.6%) 4,471 (58%) 5,949 (59%) 8,308 (61%) Site B 12,683 (40.4%) 3,235 (42%) 4,188 (41%) 5,260 (39%) Gestation at Booking (weeks) 9.00 (8.00, 12.00) 10.00 (8.00, 12.00) 9.00 (8.00, 12.00) 10.00 (8.00, 12.00) Ethnicity White 15,887 (51%) 3,812 (49%) 5,338 (53%) 6,737 (50%) Black/African/Caribbean/Black British 6,309 (20%) 1,442 (19%) 2,063 (20%) 2,804 (21%) Indian (Asian or Asian British) 765 (2.4%) 160 (2.1%) 241 (2.4%) 364 (2.7%) Mixed/multiple ethnic groups 1,636 (5.2%) 326 (4.2%) 529 (5.2%) 781 (5.8%) Other Asian/Asian British 1,930 (6.1%) 386 (5.0%) 627 (6.2%) 917 (6.8%) Pakistani (Asian or Asian British) 327 (1.0%) 72 (0.9%) 111 (1.1%) 144 (1.1%) Any Other ethnic group 2,186 (7.0%) 499 (6.5%) 795 (7.8%) 892 (6.6%) (Missing) 2,371 (7.5%) 1,009 (13%) 433 (4.3%) 929 (6.8%) IMD Quintile 1 (most deprived) 6,050 (19%) 1,460 (19%) 1,900 (19%) 2,690 (20%) 2 12,914 (41%) 3,230 (42%) 4,167 (41%) 5,517 (41%) 3 7,790 (25%) 1,979 (26%) 2,563 (25%) 3,248 (24%) 4 2,906 (9.3%) 685 (8.9%) 932 (9.2%) 1,289 (9.5%) 5 (least deprived) 1,210 (3.9%) 267 (3.5%) 400 (3.9%) 543 (4.0%) (Missing) 541 (1.7%) 85 (1.1%) 175 (1.7%) 281 (2.1%) Nulliparous 17,226 (55%) 3,922 (51%) 5,459 (54%) 7,845 (58%) Smoker at Booking 1,126 (3.6%) 301 (3.9%) 357 (3.5%) 468 (3.4%) Previous Caesarean 4,475 (14%) 1,139 (15%) 1,459 (14%) 1,877 (14%) Pregnancy outcomes Gestation At Birth (Wks) 39.00 (38.00, 40.00) 39.00 (38.00, 40.00) 39.00 (38.00, 40.00) 39.00 (38.00, 40.00) Smoker At Birth 825 (2.6%) 216 (2.8%) 278 (2.7%) 331 (2.4%) Mental Health Service accessed Any (includes inpatient) 2,286 (7.3%) 532 (6.9%) 651 (6.4%) 1,103 (8.1%) NHS ‘Talking Therapies’* 1,372 (4.4%) 297 (3.9%) 420 (4.1%) 655 (4.8%) ‘Community contacts’† 1,176 (3.7%) 285 (3.7%) 298 (2.9%) 593 (4.4%) Preterm birth 2,074 (6.6%) 535 (6.9%) 634 (6.3%) 905 (6.7%) Induction of labour 6,845 (22%) 1,430 (19%) 2,323 (23%) 3,092 (23%) Unassisted Vaginal Birth 14,368 (46%) 3,862 (50%) 4,772 (47%) 5,734 (42%) (Missing) 84 (0.3%) 8 (0.1%) 28 (0.3%) 48 (0.4%) Interventional Delivery Emergency Caesarean 7,062 (22%) 1,473 (19%) 2,123 (21%) 3,466 (26%) (Missing) 84 (0.3%) 8 (0.1%) 28 (0.3%) 48 (0.4%) Elective Caesarean 5,064 (16%) 1,115 (14%) 1,580 (16%) 2,369 (17%) (Missing) 84 (0.3%) 8 (0.1%) 28 (0.3%) 48 (0.4%) Assisted Vaginal birth 4,833 (15%) 1,248 (16%) 1,634 (16%) 1,951 (14%) (Missing) 84 (0.3%) 8 (0.1%) 28 (0.3%) 48 (0.4%) Vaginal tear (3rd / 4th ) 500 (1.6%) 146 (1.9%) 144 (1.4%) 210 (1.5%) PPH 3,186 (10%) 731 (9.5%) 976 (9.6%) 1,479 (11%) (Missing) 1 (< 0.1%) 0 (0%) 0 (0%) 1 (< 0.1%) Stillbirth 163 (0.5%) 35 (0.5%) 55 (0.5%) 73 (0.5%) 5-min Apgar < 7 502 (1.6%) 121 (1.6%) 157 (1.5%) 224 (1.7%) (Missing) 934 (3.0%) 202 (2.6%) 298 (2.9%) 434 (3.2%) SGA 2,242 (7.1%) 546 (7.1%) 681 (6.7%) 1,015 (7.5%) (Missing) 75 (0.2%) 19 (0.2%) 16 (0.2%) 40 (0.3%) LGA 3,841 (12%) 959 (12%) 1,270 (13%) 1,612 (12%) (Missing) 75 (0.2%) 19 (0.2%) 16 (0.2%) 40 (0.3%) Admitted to NICU 2,072 (6.6%) 576 (7.5%) 737 (7.3%) 759 (5.6%) ICU (intensive care unit), IMD (Index of multiple deprivation), IQR (interquartile range), LGA (large-for-gestational age), NHS (National Health Service), NICU (neonatal intensive care unit), PPH (postpartum haemorrhage), SGA (small-for-gestational age), Wk (weeks) * NHS ‘Talking Therapies’ are psychological therapies for anxiety and depression ( https://www.england.nhs.uk/mental-health/adults/nhs-talking-therapies/ ), † These are secondary mental health services community consultations. 1 n (%); Median (IQR) We evaluated trends in key pregnancy and delivery indicators across three epochs, according to delivery date: pre-pandemic (01 October 2018 to 22 March 2020), pandemic lockdowns (23 March 2020 to 17 July 2021), and pandemic without lockdown (18 July 2021 to 4 May 2023)( 15 ). Key indicators measured at birth reflected UK: (i) Organisational Performance Indicators (i.e., interventional birth, defined as Caesarean birth or operative vaginal delivery); (ii) Clinical Quality Improvement Metrics (i.e., smoker at delivery, gestational age at birth, preterm birth < 37 weeks, mode of birth, 3rd or 4th degree vaginal tears, and 5-minute Apgar < 7); and (iii) National Maternity Indicators (i.e., mode of birth, 3rd or 4th degree tears, postpartum haemorrhage [PPH], 5-minute Apgar < 7, birthweight 90th centile] infants, and neonatal care unit [NICU] admission), and mental health outcomes given particular interest in these related to the pandemic (i.e., maternal utilisation of mental health services, as NHS ‘Talking Therapies’ [psychological therapies for anxiety and depression, developed to improve access and delivery of relevant treatment and previously known as Improving Access to Psychological Therapies( 17 )], secondary mental health services ‘community contacts’, and mental health-related inpatient admissions). Statistical Methods Descriptive statistics allowed for presentation of data, overall and by pandemic period, as mean (SD), median (IQR), and counts (percentage), as appropriate by data type and normality assumptions. The primary analysis compared the incidence of each maternal outcome across pandemic phases (as above( 6 )), using multivariable regression. Ordinal factor trend testing was employed by treating pandemic phases as a three-stage ordinal predictor variable and tested for evidence of flat (no trend), linear, and/or quadratic relationships over time. Adjustment factors were site (A or B) and variables based on published literature: ethnicity, IMD quintile, gestational age at booking (weeks), smoking at booking, nulliparity, prior Caesarean and month. A dummy variable for month was included in all models, to account for seasonality. The overall contribution was assessed using an ANOVA F-test, and the global p-value was reported to evaluate seasonality. BMI was not included as an adjustment factor due to the significant increase in its missingness during pandemic lockdowns, related to less face-to-face care; inclusion of BMI could have introduced bias due to non-random missingness. Regression estimates, or odd ratios (ORs), with 95% confidence intervals (CIs) were reported for each delivery outcome for pandemic vs pandemic lockdowns, and pandemic lockdowns vs pandemic without lockdown, and additionally for each covariate. Interactions for each delivery outcome were tested between pandemic phase and: site, ethnicity, and IMD, to examine whether the pandemic exacerbated inequalities. A secondary analysis visualised temporal trends in maternity outcomes in more granularity, by month, using generalised additive models (GAMs). These allow modelling and visualisation of complex and non-linear relationships. Given the timing and intensity of pandemic-related interventions, GAMs provided an appropriately flexible framework to capture the potential effects on outcomes of gradual and variable changes in care patterns, particularly at an individual level. For each delivery outcome, GAMs were plotted to illustrate trends, using flexible thin-plate regression splines stratified by site, from 1 May 2019 to 22 April 2023. The data were interpreted in terms of predicted means or probabilities of delivery outcomes, contingent upon the outcome distribution, per month/year of the study period. All outcomes were adjusted for the same confounders, as above. A sensitivity analysis was conducted across all outcomes to assess the impact of time spent in pandemic epoch “pandemic with lockdowns”, per trimester. This was calculated by the proportion of days within each trimester within the defined “pandemic with lockdowns” period between March 2020 and July 2021. Multivariable regression analyses, adjusting for the same covariates as in the primary analysis was used to assess the relationship between maternal and birth outcome and the proportion of time spent in a lockdown period across three trimester variables, to provide an indication of the lockdown effect during the antenatal period, and not solely by delivery date. All analyses and data cleaning procedures were executed using RStudio version 4.3.0. A significance level of 1% was considered throughout. Missing data were reported in descriptive analyses and modelled as their own category throughout, providing insights into missingness. RESULTS Of 36,985 potentially eligible pregnancies, excluded were: 727 multifetal gestations, a random 3,298 pregnancies to mothers with more than one pregnancy, and 1,549 pregnancies during truncation ( Figure S1 ). As a result, there were 31,411 pregnancies included in our analysis, from sites A (59.6%) and Site B (40.4%), over pre-pandemic (N = 7,706; 24.5%), pandemic lockdowns (N = 10,137; 32.3%), and pandemic without lockdown epochs (N = 13,568; 43.2%) (Table 1 ). Throughout the study period, maternal and pregnancy characteristics remained similar (Table 1 ). The gestation at booking was 9–10 weeks. Approximately half of the cohort was from a minority ethnic group, primarily Black ethnicity. Just over half of pregnancies were from the two most socially-deprived IMD quintiles. Just over half of women were nulliparous, few reported smoking at antenatal booking, and about one-sixth had undergone prior Caesarean. Across study epochs, there were differences in many of the maternal outcomes evaluated (Table 1 ). Median gestational age at birth (39 weeks [IQR 38–40]) and smoking at birth (just under 3%) remained steady over time. However, there appeared to be a progressive rise in use of NHS Talking Therapies, and an initial decrease and then increase in secondary mental health services ‘community contacts’. Birth requiring intervention appeared to rise over time, particularly for elective and emergency Caesarean (3% and 7% across epochs). Unassisted vaginal birth decreased (by 2%). PPH appeared to have increased (by 1.5%) and NICU admission fell (by 2%). Table 2 presents adjusted outcome estimates from linear models (mean difference/OR, 95% CI and test for trend) across study epochs, and non-linear models by month (spline term p-values, sites A and B); unadjusted analyses are presented in Table S4 , which shows that unadjusted effects remained stable following adjustment for confounders across all outcomes, except with SGA. Figures 1 – 3 present visualisation of spline terms presented in Table 2 , stratified by site and adjusted for confounders, as in analyses presented in Table 2 (where site was also an adjustment variable). Estimated degrees of freedom (EDF) are presented in Table S5 , and largely support our linear trends (as reflected by EDF values close to 1.0), and non-linear trends (as reflected by EDF values > 2.0), without any low p-values from the k-index test that may reflect a poorly-fitted model. Table 2 Outcome event rates trends over time* Trend Test Spline term 3 Outcomes Pre-Pandemic vs Pandemic with lockdowns Pandemic without lockdowns vs. Pandemic with lockdowns Linear p-value Quadratic p-value Site A Site B Beta (95% CI) 1 Gestational age at birth (Wk) 1 -0.02 (-0.09, -0.04) -0.07 (-0.13, -0.01) 0.029 0.658 0.288 < 0.001 aORs (95% CI) 2 Smoker at birth 2 0.88 (0.68–1.13) 0.81 (0.65, 1.01) 0.476 0.106 0.229 0.322 Mental Health Services Accessed NHS ‘Talking Therapies’† 0.97 (0.83–1.13) 1.24 (1.09–1.40) < 0.001 0.154 0.081 < 0.001 Accessed ‘Community Contacts’ǂ 1.29 (1.09–1.53) 1.54 (1.33–1.78) 0.018 < 0.001 < 0.001 0.022 Preterm birth 0.92 (0.81–1.03) 1.02 (0.92–1.14) 0.250 0.276 0.837 0.662 Labour induction 1.27 (1.18–1.37) 0.98 (0.92–1.04) < 0.001 < 0.001 < 0.001 0.092 Unassisted Vaginal Birth 0.92 (0.85–0.98) 0.83 (0.78–0.88) < 0.001 0.091 < 0.001 < 0.001 Interventional Delivery Emergency Caesarean 1.08 (1.00–1.16) 1.25 (1.17–1.33) < 0.001 0.016 < 0.001 < 0.001 Elective Caesarean 1.12 (1.02–1.23) 1.20 (1.11–1.30) < 0.001 0.377 < 0.001 < 0.001 Assisted Vaginal 0.95 (0.88–1.03) 0.83 (0.77–0.89) < 0.001 0.051 < 0.001 < 0.001 Vaginal tear (3rd /4th degree) 0.73 (0.57–0.93) 1.03 (0.83–1.28) 0.009 0.087 0.001 0.188 PPH 0.99 (0.90–1.10) 1.12 (1.02–1.22) 0.031 0.154 0.387 0.003 Stillbirth 1.27 (0.83–2.00) 0.92 (0.64–1.33) 0.580 0.426 0.124 0.234 5-minute Apgar < 7 1.02 (0.81–1.30) 1.00 (0.81–1.23) 0.843 0.908 0.831 0.464 SGA infants 0.93 (0.83–1.04) 1.08 (0.98–1.20) 0.966 0.121 0.361 0.530 LGA infants 1.02 (0.93–1.12) 0.98 (0.91–1.06) 0.993 0.579 0.268 0.198 Admitted to NICU 1.01 (0.90–1.13) 0.70 (0.63–0.78) < 0.001 0.002 < 0.001 0.377 CI (confidence interval), LGA (large-for-gestational age), NHS (National Health Service), NICU (neonatal intensive care unit), OR (odds ratio), PPH (postpartum haemorrhage), SGA (small-for-gestational age), Wk (weeks) * 95% confidence intervals that do not cross 1.0 are shaded in grey, and p values < 0.01 are shaded in yellow. † NHS ‘Talking Therapies’ are psychological therapies for anxiety and depression ( https://www.england.nhs.uk/mental-health/adults/nhs-talking-therapies/ ), ǂ These are secondary mental health services community consultations. 1 Multivariable Linear Regression analysis for continuous outcomes presenting mean difference in estimates. All models were adjusted for the same minimal number of confounders: Data source (site A or B), Index of Multiple Deprivation Quintiles, Ethnicity, Gestation at booking (wks), Smoking at registration, Nulliparity, Month (for seasonality) and Previous Caesarean. 2 Multivariable Logistic Regression for binary outcomes presenting OR with 95% CI. Models were adjusted as above 1 . 3 Multivariable Generalised Additive Models’ p-value, corresponding to site A and B spline terms for each outcome to evaluate the probability of stable trends across different sites. Models adjusted as above 1 , except for site data, which were presented separately for sites A and B. Six outcomes showed stable probabilities over time: smoking at birth, preterm birth, stillbirth, 5-minute Apgar < 7, and SGA and LGA infants, as illustrated by trend test results, and by spline terms for sites A and B (Table 2 ). Further graphical illustrations are provided in Figs. 1 [a-f] , which display flat (zero slope) trends with overlapping 95% CIs across both sites over the months/years, for each outcome. Spline terms for these outcomes indicated no evidence of linear or non-linear trends, at either site. Linear trends were observed for several outcomes, with directions of overall effect shown by model estimates between epochs. Accessed ‘Talking Therapies’, emergency Caesareans, and elective Caesareans increased, while, unassisted vaginal birth, assisted vaginal birth, and 3rd or 4th-degree vaginal tears decreased (Table 2 ). Visualisation of spline terms by site revealed where linear trends were observed at only one site (but were stable at the other); gestational age at birth decreased only at site B (by approximately half a week, Fig. 2 a), accessed ‘Talking Therapies’ increased only at site B (by ~ 4–9% probability, Fig. 2 b), 3rd or 4th degree vaginal tears decreased only at site A (~ 2% change in probability, Fig. 2 c), and PPH increased only at site B (by ~ 4%, with a plateau during pandemic without lockdown, Fig. 2 d); changes in gestational age at birth (Fig. 2 a) and PPH (Fig. 2 d) were very small, and were undetected by trend testing at a 1% significance level (Table 2 ); however, they were noted in real-time by site B, which attributed them to rising Caesarean rates, and instituted more consultant supervision of trainees during emergency Caesareans (see below), greater awareness of PPH risk factors, more frequent use of prophylactic uterotonics, and early escalation of PPH. Strong linear trends were observed at both sites for emergency and elective Caesareans (increasing y-axis probability limits from 20–35% [Figure 3 a] and 10–16% [Figure 3 b]), and for unassisted and assisted vaginal births (decreasing y-axis probability limits from 45 to 30% [Figure 3 c] and 30–18% [Figure 3 d]). However, notable GAM features include: (i) for Fig. 3 a, some small fluctuations in emergency Caesareans at site A were undetected by the trend test analysis, but largely increased linearly; and (ii) for Fig. 3 a, a pre-pandemic decrease in unassisted vaginal births at site B also began at site A during the first pandemic lockdown, with ongoing linear decreases thereafter. Complex and non-linear trends were observed in secondary mental health services ‘community contacts’ (initially decreased by 2–3% during pandemic lockdowns [when reduced in availability], then increased), labour induction (sharp pre-pandemic increase from 15–28% probability and then plateaued at site B), and NICU admissions (some fluctuation at site A pre- and during pandemic lockdowns, then decreased from 8% mid-pandemic lockdowns to 2–3% probability). None of these patterns were consistent with seasonality. These trends were different at sites A and B (Table 2 ), except for accessed secondary mental health services ‘community contacts’, which, at both sites, decreased following the first pandemic lockdown, and then increased, surpassing pre-pandemic levels by the end of the pandemic (Fig. 4 a). In the sensitivity analysis, 13/17 outcomes displayed no association between the odds of any outcome at birth, and the proportion of time spent in “pandemic with lockdowns”, across all three trimesters (Table 3 ). Four outcomes showed some such association: (i) access to ‘Community Contacts’ mental health services displayed a decreased odds associated with more time spent in ‘pandemic with lockdowns’ during the third trimester; (ii) labour induction displayed an increased odds with more time spent in lockdown in the third trimester; (iii) unassisted vaginal birth was less likely with more time spent in lockdown in the first trimester; and (iv) admission to the neonatal unit was more likely with higher proportions of first and third trimesters spent in lockdown, and less likely with high proportions of second trimester spent in lockdown. These results were consistent with the complex, site-specific changes reflected in the GAMs. Table 3 Proportion of time spent in ‘pandemic with lockdowns’, by trimester Outcomes Proportion within Trimester 1 (days) Proportion with Trimester 2 (days) Proportion within Trimester 3 (days) Beta (95% CI) 1 Gestational age at birth (Wk) 1 -0.01 (-0.13, 0.10) -0.01 (-0.17, 0.16) 0.01 (-0.10, 0.13) aORs (95% CI) 2 Smoker at birth 2 1.04 (0.67, 1.611) 1.12 (0.58, 2.18) 1.18 (0.76, 1.82) Mental Health Services Accessed NHS ‘Talking Therapies’† 1.15 (0.89, 1.48) 0.93 (0.64, 1.37) 0.91 (0.70, 1.18) Accessed ‘Community Contacts’ǂ 1.16 (0.88, 1.52) 1.00 (0.66, 1.51) 0.67 (0.51, 0.88) Preterm birth 1.03 (0.84, 1.27) 0.93 (0.68, 1.28) 1.03 (0.83, 1.27) Labour induction 1.07 (0.94, 1.22) 0.92 (0.76, 1.12) 1.19 (1.05, 1.36) Unassisted Vaginal Birth 0.84 (0.74, 0.94) 1.14 (0.95, 1.36) 1.05 (0.94, 1.19) Interventional Delivery Emergency Caesarean 1.12 (0.99, 1.27) 0.91 (0.75, 1.11) 0.91 (0.80, 1.03) Elective Caesarean 1.15 (0.98, 1.34) 0.94 (0.74, 1.20) 0.91 (0.78, 1.07) Assisted Vaginal 1.02 (0.88, 1.18) 0.96 (0.77, 1.21) 1.13 (0.97, 1.31) Vaginal tear (3rd /4th degree) 1.17 (0.76, 1.78) 0.85 (0.45, 1.61) 0.86 (0.56, 1.31) PPH 0.99 (0.90–1.10) 1.12 (1.02, 1.22) 1.14 (0.96, 1.36) Stillbirth 1.27 (0.83–2.00) 0.92 (0.64, 1.33) 1.00 (0.77, 1.30) 5-minute Apgar < 7 1.02 (0.81–1.30) 1.00 (0.81, 1.23) 0.90 (0.76, 1.07) SGA infants 1.21 (0.99, 1.48) 0.85 (0.62, 1.15) 0.96 (0.78, 1.17) LGA infants 1.00 (0.85, 1.18) 1.08 (0.85, 1.37) 0.97 (0.83, 1.14) Admitted to NICU 1.28 (1.04, 1.57) 0.65 (0.47, 0.89) 1.68 (1.36, 2.07) CI (confidence interval), LGA (large-for-gestational age), NHS (National Health Service), NICU (neonatal intensive care unit), OR (odds ratio), PPH (postpartum haemorrhage), SGA (small-for-gestational age), Wk (weeks) * 95% confidence intervals that do not cross 1.0 are shaded in grey, and p values < 0.01 are shaded in yellow. † NHS ‘Talking Therapies’ are psychological therapies for anxiety and depression ( https://www.england.nhs.uk/mental-health/adults/nhs-talking-therapies/ ), ǂ These are secondary mental health services community consultations. 1 Multivariable Linear Regression analysis for continuous outcomes presenting mean difference in estimates. All models were adjusted for the same minimal number of confounders: Data source (site A or B), Index of Multiple Deprivation Quintiles, Ethnicity, Gestation at booking (wks), Smoking at registration, Nulliparity, Month (for seasonality) and Previous Caesarean. 2 Multivariable Logistic Regression for binary outcomes presenting OR with 95% CI. Models were adjusted as above 1 . Relationships between adjustment factors and outcomes are presented in Tables S6a and S6b. For all outcomes, significant associations were seen for minority ethnic groups (compared with White ethnicity) and nulliparity (vs. multiparity). For example, there was a 0.50–0.78 decreased odds of elective Caesarean across all ethnic minority groups (Black, Asian & Asian British, Mixed, and Multiple ethnic groups), compared with White ethnicity, and nulliparous (vs. multiparous) women showed a 4.58 increased odds of assisted vaginal birth. Other adjustment factors were associated with a number of adverse outcomes, such as a strong increased odds of elective Caesarean amongst those with the least (vs. most) deprived IMD, and for smokers (vs. non-smokers) at registration, a 0.41 decreased odds of LGA babies and 4.90 increased odds of accessing secondary mental health services ‘community contacts’. Eleven of 17 outcomes highlighted differences between the two sites (A vs. B). There was no evidence of seasonality in any maternal or birth outcomes. For each outcome, interactions between time (pandemic epoch) and site, ethnicity, and IMD are presented in Table S7; interactions with site were seen for induction, emergency Caesarean, PPH, and NICU admissions, as illustrated in Figs. 1 – 3 . Similarly, interactions between time and ethnicity were seen for some outcomes, although most interactions were attributable to ‘other’ or ‘missing’ ethnicity categories (as seen in 13% of pregnancies pre-pandemic, 4.3% during pandemic lockdowns, and 6.8% during pandemic without lockdown). Only for labour induction during pandemic lockdowns was there an interaction with a specific ethnicity category (Black ethnicity). No interaction was seen between time and IMD for any outcome. DISCUSSION Summary of findings In more than 30,000 pregnancies from ethnically and socio-economically diverse South London, UK, we found that most pregnancy outcomes followed pre-pandemic temporal trends, either stable (e.g., preterm birth), increasing (e.g., elective Caesarean), or decreasing (e.g., assisted vaginal birth). While there was a clear pandemic-related decrease in accessing secondary mental health services ‘community contacts’ during the first pandemic lockdown, when those services were decreased in availability, other temporal trends (including labour induction and NICU admissions) were related to fluctuations at only one site, potentially due to local adaptations. We saw no evidence of seasonality, and any associations between outcomes and the proportion of time spent in a given trimester reflected the few observed complex site-specific changes illustrated by the GAMs. Interaction tests between time and each site, ethnicity, and IMD quintiles supported the stratification of trends by data collection sites, highlighting their adaptations to pandemic impacts on maternal outcomes. While there was clear evidence of inequalities in outcomes for minority ethnic group (vs. White) women and those experiencing greater levels of deprivation, there was no compelling evidence that the pandemic exacerbated those inequalities. Comparison with the literature In contrast to our study which covered the entire pandemic and examined monthly trends, the global impact of the pandemic on pregnancy outcomes has been examined primarily in the first pandemic year with lockdowns, or slightly beyond that into the summer of 2021, in studies in South London, North West England( 7 ), England( 3 ), or globally( 5 ). While many studies found that the pandemic was associated with a decrease in preterm birth (overall and spontaneous)( 4 , 5 ), there was evidence of publication bias and heterogeneity( 18 ). In a population-based study in England, pandemic lockdown (vs. pre-pandemic) was associated with small changes in outcomes, albeit small: fewer preterm births, more interventions (such as Caesarean or labour induction), and fewer SGA babies( 4 ). Of note, if our approach had been to compare either pandemic lockdowns or the entire pandemic with pre-pandemic outcomes, we too would have described the pandemic to be associated with an increase in intervention (i.e., increase in emergency or elective Caesareans, and decrease in gestational age at birth and unassisted vaginal birth). Using interrupted time series analysis of data from North West England( 7 ) or Australia( 8 ), outcomes were largely unchanged, including stillbirth, preterm birth, and abnormal fetal growth ( 7 ), or improvements in outcomes were reported, such as a reduction in labour induction for FGR which was not associated with a difference in FGR incidence or perinatal morbidity( 8 ). As in our study, Gurol-Urganci et al . reported that some clinical outcomes (i.e., preterm births, Caesareans, and unassisted vaginal births) varied in the pandemic by ethnicity (White vs. minority ethnic groups), but not social deprivation (IMD quintiles 1–3 vs. 4–5)( 4 ). Our data add to this work, by clarifying that while minority group ethnicity and social deprivation are each associated with adverse outcomes, there is no specific ethnicity category for which pandemic-related effects were different. Rather, any interactions between ethnicity and the pandemic were, with one exception, due to unspecified or missing ethnicity, which was slightly more common pre-pandemic. Also, we have confirmed that there is no interaction between time and IMD, when quintiles 1–2 are compared with 3–5. Our finding of ongoing increases in use of mental health treatment is consistent with published findings of a pandemic-related, negative legacy with regards to mental health. Pandemic-related social distancing restrictions had an adverse effect on women’s mental health before and after birth, related to restricted access to informal (family and friends) and formal (healthcare professional) support( 19 ). Antenatally, women described feeling trapped, anxious, and abandoned during initial lockdown and its lifting( 20 ), with prohibition of family from maternity wards particularly distressing whilst initial lockdown restrictions were being eased( 19 , 21 ). A similar, cumulative, negative effect was seen on postpartum mental health( 6 ), when pandemic social distancing restrictions could explain about one-third of the substantial increase in maternal depression (from 11–43%) and anxiety (from 18–61%), after accounting for current relevant diagnoses and other mental health risk factors( 22 ). Younger women and sexual minority women were more likely to have postnatal anxiety, with younger participants reporting anxieties about infant safety and welfare, whilst lesbian, gay, bisexual, and pansexual participants struggled more with psychosocial adjustment to motherhood( 23 ). Our finding that the vast majority of pregnancy outcomes followed pre-pandemic trends must be seen in light of the extensive, pandemic-related maternity service configurations in the UK. In line with recommendations from the Royal College of Obstetricians and Gynaecologists and Royal College of Midwives, a national survey documented that most UK maternity units reduced the number of antenatal contacts offered by any method, converted some antenatal appointments to remote consultations (particularly in the first and second trimesters, about which women reported mixed views( 2 ), increased use of self-monitoring of blood pressure, modified screening for gestational diabetes, reduced the frequency of fetal growth surveillance by ultrasound, and reduced options for place of birth( 24 ). Of note, there were few changes to labour induction indications or the offer of Caesarean by request. Clinical and research implications When considering the impact of system-wide influences on pregnancy outcomes, our findings highlight the importance of evaluating longer-term temporal trends to contextualise short-term pregnancy outcome rates, as well as benchmarking between hospitals. Examining temporal trends in outcomes, and not just comparing outcome event rates between two time periods, minimises the risk of drawing spurious conclusions and overestimating the impact of acute events on outcomes, particularly as the relationships are complex between factors influencing maternity care and pregnancy outcomes, and can arise from individuals (e.g., care-seeking behaviour), care providers (e.g., staffing), or guidance, local or national. Benchmarking between sites, particularly temporally, may identify variations in outcomes and their underlying processes of care, with the goal of identifying best practice, optimising outcomes and minimising costs, as has been done successfully by others using detailed, routinely-collected data( 25 ). All such activities are underpinned by a learning health system of data-driven learning, and rapid translation of learning into practice, to reduce the time to implementation; importantly, such an approach imbeds the engagement of key stakeholders, to co-design local solutions and influence policy. By virtue of its principle of continuous learning, a learning health system prepares the health system for shocks, such as a the COVID-19 pandemic. Strengths and limitations Strengths of our study include its large sample size and diversity of the study population in South London, UK, all based on routinely-collected data. We reported both physical and mental health outcomes. We covered the entire pandemic, facilitating our understanding of the impact of pandemic-related changes in care practices (and their withdrawal). Our multi-method analytic approach, which included multivariable regression, ordinal factor trend testing, and GAMs, allowed us to examine both linear and non-linear outcome patterns over time. The complementary results from each method led to comparable conclusions, further strengthening our findings. This methodological approach, not commonly employed to address trends in pregnancy outcomes, enabled us to make the distinction between ongoing trends and fluctuations due to pandemic-related changes. Additionally, our analyses were adjusted for site and individual-level characteristics, and we evaluated potential interactions between time and confounders. Also, we consulted clinicians from each hospital to deepen interpretation and verify trends. With respect to limitations of this study, our decision to classify the timing of pregnancies according to pandemic epoch of birth means that findings may reflect predominantly late pregnancy and intrapartum care, rather than that earlier in pregnancy. Whilst multiple outcomes were explored separately, and analyses adjusted for the same set of minimal confounders, we believe our results reflect a coherent pattern of the main processes at play across study epochs. However, given the complex nature of these outcomes, further work would be warranted to assess outcome-specific adjustments. There was a very low rate of SARS-CoV2 positivity, this may reflect underreporting (as seen in other routinely-collected data ( 21 )), however a similar prevalence of 0.1% has been reported by other cohorts in pregnant women during the pandemic ( 7 ); due to the low prevalence, this precluded an analysis of the impact of SARS-CoV2 positivity on pregnancy outcomes. Finally, we analysed raw, uncoded clinical data in eLIXIR-BiSL; while some data missingness was evident and the validity of all such data cannot be confirmed, this is the information on which clinical care was based in the index pregnancy, and will be based in future pregnancy. Conclusions In this large, diverse cohort of pregnancies from South London, UK, our findings reveal that, despite the significant health system shock of the pandemic and the decrement in experiences of maternity care, the direct impact on pregnancy outcomes was limited. Overall, outcomes during the pandemic largely reflected pre-pandemic trends and did not exacerbate inequalities, demonstrating the resilience of maternity services during this challenging period. ABBREVIATIONS CI Confidence interval eLIXIR-BiSL early-LIfe data cross-LInkage In Research, Born in South London FGR Fetal growth restriction GAM Generalised additive modelling IAPT Improved Access to Psychological Therapy IMD Index of multiple deprivation LGA Large-for-gestational age infant NHS National Health Service NICU Neonatal intensive care unit OR Odds ratio PPH Postpartum haemorrhage PTB Preterm birth SGA Small-for-gestational age infant UK United Kingdom Wks Weeks Declarations The authors have no relevant competing interests to declare. The views expressed are those of the author(s) and not necessarily those of NIHR, the NHS, or the Department of Health and Social Care, UK. ACKNOWLEDGEMENTS We wish to thank the women, their infants, and families from all participating sites for sharing their data and supporting the eLIXIR-BiSL programme. AUTHORS’ CONTRIBUTIONS The study was conceived by LAM, PvD, and FT. All authors contributed to the design and delivery of the study. The author FT assumes responsibility for the accuracy and completeness of data reporting. FT and LAM drafted the manuscript, which was revised and approved by all authors. FUNDING This project was funded by the National Institute for Health Research (NIHR) HSDR Programme [NIHR134293]. The Early Life Cross Linkage in Research, Born in South London (eLIXIR-BiSL) Partnership was developed by an MRC Partnership Grant [MR/P003060/1] and the MRC Longitudinal Population Study Grant [MR/X009742/1]. The eLIXIR-BiSL platform is also part-supported by the National Institute for Health Research (NIHR) Biomedical Research Centre at the South London and Maudsley NHS Foundation Trust and King’s College London. The funders played no role in study design, data acquisition or analyses, manuscript preparation, or the decision to submit for publication. ETHICAL APPROVAL The eLIXIR-BiSL Partnership received ethical approval from the Oxfordshire Research Ethics Committee C (Ref:18/SC/0086, 2018-23; renewal 23/SC/0116, 2023-8) as an anonymised dataset for medical research. DATA AVAILABILITY STATEMENT The data accessed by eLIXIR-BiSL remain within an NHS firewall and governance is provided by the eLIXIR Oversight Committee reporting to relevant information governance clinical leads. Subject to these conditions, data access is encouraged and those interested should contact the eLIXIR-BiSL Chief Investigator (Professor Lucilla Poston; [email protected] ) or the HDRUK Innovation Gateway (https://web.www.healthdatagateway.org/dataset/3c780d45-ed7b-4101-9c32-d50512cd9cfe). CODE AVAILABILITY STATEMENT The custom code used for data analysis in this study is available upon reasonable request to the corresponding author. Access will be provided in accordance with institutional and ethical guidelines. 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Magee","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA/ElEQVRIiWNgGAWjYBACPlRuRQJMJAGnFjZU7pkEmAixWhjbiNHCfsbsww8GOwbd9uMXH3yclybPxsD88ANjWxpuLTw5xjN7GJIZzM7kFBvO3JZj2MbAZizB2JaDx2E5xgw8DMwMZgdy0qR5t1UkAB1mBnRhBW4t/G+MGf8w1DOYnX+T/vvvHJAW9m/4tUjkGDPzMBxmMLuRfoyZsSEHqIUHZAseh0k8K2aWMTjOY3bjDbNkz7E0wzZmnmKJhHO4vc/Pn7yZ8U1FtZzZ+fSHH37UJMvzs7dv/PChLBmnFggwAIYAA48BhMPMgC9WUAD7A+LUjYJRMApGwYgDAHqFRS+m6kTZAAAAAElFTkSuQmCC","orcid":"","institution":"King's College London","correspondingAuthor":true,"prefix":"","firstName":"Laura","middleName":"A.","lastName":"Magee","suffix":""}],"badges":[],"createdAt":"2025-06-13 09:29:13","currentVersionCode":1,"declarations":{"humanSubjects":true,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":true,"humanSubjectConsent":true,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-6886833/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6886833/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":85714826,"identity":"452ce3a3-c78e-41c8-bf3a-5f641c74e1d6","added_by":"auto","created_at":"2025-07-01 03:42:46","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":128356,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003e[a-f]: \u003c/strong\u003eProbability of delivery outcomes with 95% CI, showing no change in trend over the pandemic period, for either site: smoking at delivery (p\u003csub\u003eA \u003c/sub\u003e= 0. 229and p\u003csub\u003eB \u003c/sub\u003e= 0.322)\u003cstrong\u003e [1A]\u003c/strong\u003e, pre-term birth (p\u003csub\u003eA \u003c/sub\u003e= 0·837 and p\u003csub\u003eB \u003c/sub\u003e= 0·662)\u003cstrong\u003e [1B]\u003c/strong\u003e, Stillbirth (p\u003csub\u003eA \u003c/sub\u003e= 0·124 and p\u003csub\u003eB \u003c/sub\u003e= 0·234)\u003cstrong\u003e [1C]\u003c/strong\u003e, low 5-minute Apgar (p\u003csub\u003eA \u003c/sub\u003e= 0·831 and p\u003csub\u003eB \u003c/sub\u003e= 0·464)\u003cstrong\u003e [1D]\u003c/strong\u003e, SGA (p\u003csub\u003eA \u003c/sub\u003e= 0·361 and p\u003csub\u003eB \u003c/sub\u003e= 0·530)\u003cstrong\u003e [1E]\u003c/strong\u003e and LGA (p\u003csub\u003eA \u003c/sub\u003e= 0·268 and p\u003csub\u003eB \u003c/sub\u003e= 0·198)\u003cstrong\u003e [1F]\u003c/strong\u003e. Blue represents trends over time for site A while, red represent\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6886833/v1/a1be02165af58a4cfc474d74.png"},{"id":85714068,"identity":"55d89cfc-6d9d-4b6f-8161-dc3f9ac6ab12","added_by":"auto","created_at":"2025-07-01 03:34:46","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":83821,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003e[A-D]:\u003c/strong\u003e Probability of delivery outcomes with 95% CI, showing outcomes with evidence of linear trend over the pandemic period at one site only: Gestational age at delivery (p\u003csub\u003eA \u003c/sub\u003e= 0·228 and p\u003csub\u003eB \u003c/sub\u003e\u0026lt;0·001)\u003cstrong\u003e [2A]\u003c/strong\u003e; NHS ‘Talking Therapies’ (p\u003csub\u003eA \u003c/sub\u003e=0·081 and p\u003csub\u003eB \u003c/sub\u003e\u0026lt;0·001)\u003cstrong\u003e [2B]\u003c/strong\u003e; vaginal tear (3\u003csup\u003erd\u003c/sup\u003e or 4\u003csup\u003eth\u003c/sup\u003e degree) (p\u003csub\u003eA \u003c/sub\u003e= 0·001 and p\u003csub\u003eB \u003c/sub\u003e= 0·1883)\u003cstrong\u003e [2C]\u003c/strong\u003e and PPH (p\u003csub\u003eA \u003c/sub\u003e= 0·387 and p\u003csub\u003eB \u003c/sub\u003e= 0·003)\u003cstrong\u003e [2D]\u003c/strong\u003e. Blue represents trends over time for site A while, red represent trends in site B.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6886833/v1/2bb528dc466bb2e854184829.png"},{"id":85714070,"identity":"e2c1b21c-fb98-4f0d-af17-04eedc0f74ec","added_by":"auto","created_at":"2025-07-01 03:34:46","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":90764,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003e[A-D]:\u003c/strong\u003e Probability of delivery outcomes with 95% CI, showing outcomes with evidence of linear trend over the pandemic period at both sites. Emergency Caesarean (p\u003csub\u003eA \u003c/sub\u003e\u0026lt;0·001 and p\u003csub\u003eB \u003c/sub\u003e\u0026lt;0·001)\u003cstrong\u003e [3A]\u003c/strong\u003e; Elective Caesarean (p\u003csub\u003eA \u003c/sub\u003e\u0026lt;0·001 and p\u003csub\u003eB \u003c/sub\u003e\u0026lt;0·001) \u003cstrong\u003e[3B]\u003c/strong\u003e; unassisted vaginal birth (p\u003csub\u003eA \u003c/sub\u003e\u0026lt;0·001 and p\u003csub\u003eB \u003c/sub\u003e\u0026lt;0·001) \u003cstrong\u003e[3C]\u003c/strong\u003e, and assisted vaginal birth specifically (p\u003csub\u003eA \u003c/sub\u003e\u0026lt;0·001 and p\u003csub\u003eB \u003c/sub\u003e\u0026lt;0·001) \u003cstrong\u003e[3D]. \u003c/strong\u003eBlue represents trends over time for site A while, red represent trends in site B.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-6886833/v1/1c132baf02e52095a609e857.png"},{"id":85714071,"identity":"ad836341-e350-42b7-918b-0839eabe7b34","added_by":"auto","created_at":"2025-07-01 03:34:46","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":69575,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003e[A-D] \u003c/strong\u003eProbability of outcomes with 95% CI, showing evidence of linear and non-linear trends over the pandemic periods but contrasting by Site: accessed secondary mental health services ‘Community contacts’ (p\u003csub\u003eA \u003c/sub\u003e= \u0026lt;0·001 and p\u003csub\u003eB \u003c/sub\u003e= 0·032) \u003cstrong\u003e[4A]\u003c/strong\u003e, labour induction (p\u003csub\u003eA \u003c/sub\u003e\u0026lt;0·001 and p\u003csub\u003eB \u003c/sub\u003e= 0·092) \u003cstrong\u003e[4B]\u003c/strong\u003e, and NICU admission (p\u003csub\u003eA \u003c/sub\u003e= \u0026lt;0·001 and p\u003csub\u003eB \u003c/sub\u003e= 0·3770) \u003cstrong\u003e[4C]\u003c/strong\u003e.\u0026nbsp; Blue represents trends over time for site A while, red represent trends in site B.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-6886833/v1/d5401b0ef394922bc389af30.png"},{"id":85715170,"identity":"0bb72de4-9381-4aa8-83b7-bd9ea466637e","added_by":"auto","created_at":"2025-07-01 03:50:47","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1553524,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6886833/v1/423aaf58-7d3d-44bd-9553-d082001fa940.pdf"},{"id":85714073,"identity":"75fc1a98-c26b-4c5c-b721-85bf9072bae3","added_by":"auto","created_at":"2025-07-01 03:34:46","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":647040,"visible":true,"origin":"","legend":"","description":"","filename":"SUPPLEMENTARYMATERIALCleanforResearchSquare13June2025.docx","url":"https://assets-eu.researchsquare.com/files/rs-6886833/v1/7715fa78fc6e4fcc3a208e6a.docx"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eTemporal trends in pregnancy outcomes during a health system shock: A retrospective longitudinal study\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eDuring the COVID-19 pandemic, pregnant women and birthing people were at risk from direct effects of SARS-CoV-2 infection and indirect effects of maternity service reconfigurations. Whilst a small proportion (\u0026asymp;\u0026thinsp;9%) of pregnant or recently pregnant women attending hospital were diagnosed with suspected or confirmed COVID-19 infection(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e), all women accessing maternity care were affected by maternity care changes, alongside societal changes in social interaction, isolation, and activity(\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). Maternity service reconfigurations included a shift to provision of at least some care via telephone or videoconference; a reduction in the number of antenatal visits; and an increase in self-monitoring for pregnancy-related complications, such as hypertension(\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eGlobally, the impact of the pandemic on pregnancy outcomes has been examined primarily in the first pandemic year or slightly beyond into the summer of 2021(\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). Many studies have found the pandemic was associated with a reduction in: preterm birth (particularly spontaneous preterm birth), and small-for-gestational age (SGA) babies; increases in mental health problems(\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e) and intervention at birth, such as labour induction and Caesarean birth(\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e); and no effect on stillbirth or neonatal death(\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). However, others have reported a lower incidence of labour induction for fetal growth restriction (FGR), in the absence of commonly-associated adverse outcomes(\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). Pandemic effects on outcomes have varied by ethnicity, but not social deprivation(\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eTo inform post-pandemic maternity care planning, this study aimed to extend the period of observation in other studies, and evaluate trends across pre-pandemic, pandemic lockdowns, and pandemic without lockdown phases, in key indicators measured at birth in the UK, reflecting: organisational performance, clinical quality improvement, and national maternity outcomes. Pregnancy outcomes were recorded at monthly intervals, using maternity data from a population of ethnic diversity and high deprivation.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cp\u003e \u003cem\u003eThe Early Life Cross Linkage in Research - Born in South London data linkage.\u003c/em\u003e \u003c/p\u003e \u003cp\u003eData for this retrospective longitudinal study were obtained from the \u0026lsquo;eLIXIR (Early Life Cross Linkage in Research)-Born in South London (BiSL)\u0026rsquo; data linkage, the methods for which have been published previously(\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). In brief, these data are routinely-collected, linked maternity, neonatal, and maternal mental health records from two maternity hospitals (Guy\u0026rsquo;s and St. Thomas\u0026rsquo; NHS Foundation Trust, and King\u0026rsquo;s College Hospital NHS Foundation Trust), in South London, United Kingdom (UK), and Maudsley NHS Foundation Trust (SLaM). Both maternity hospitals provide services that cover community-based, standard-risk, as well as high-risk specialist care to ethnically- and socioeconomically-diverse populations. In line with recommendations from the Royal College of Obstetricians and Gynaecologists and Royal College of Midwives, like most UK maternity units, GSTT and KCH: reduced antenatal contacts, some of which (particularly in early pregnancy) were converted to remote consultations, increased use of self-monitoring of blood pressure, modified screening for gestational diabetes, reduced the frequency of fetal growth surveillance by ultrasound, and reduced options for place of birth(\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). Of note, there were few changes to labour induction indications or the offer of Caesarean by request. Site-specific differences were that GSTT, which has a greater focus on maternal high-risk pregnancies, maintained OGTT testing for women at increased risk of GDM. KCH as a centre of excellence for fetal medicine and pre-eclampsia screening, maintained these services, from 11\u0026ndash;13 weeks\u0026rsquo; gestation; this centre is also co-located with perinatal mental health expertise.\u003c/p\u003e \u003cp\u003eThe eLIXIR-BiSL dataset includes comprehensive records from antenatal booking to postnatal follow-up, covering\u0026thinsp;~\u0026thinsp;15,000 births annually in an ethnically and socio-demographically diverse population of South London, UK. Raw clinical data are extracted from BadgerNet Systems, securely linked with mental health data from SLaM on the Case Register Interactive Search tool(\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e), and primary care records from Lambeth DataNet. The data are not coded. Inclusion is based on opt-out consent. For further details, see the \u003cb\u003eMethods Appendix\u003c/b\u003e.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eParticipants\u003c/h2\u003e \u003cp\u003eThe target population was women and birthing people who: (i) did not opt-out nationally from research or locally from eLIXIR-BiSL data linkage (as the current course of action by \u0026asymp;\u0026thinsp;0.03% of women); (ii) registered for antenatal care at the relevant NHS hospital (site, as above), between 01/October/2018 (when data linkage began) and 30/April/2023 (the date up to which data were available for both sites) (N\u0026thinsp;=\u0026thinsp;54,924); and (iii) had both antenatal registration and birth records and dates (N\u0026thinsp;=\u0026thinsp;36,985) (\u003cb\u003eFigure S1\u003c/b\u003e).\u003c/p\u003e \u003cp\u003eWe included only one birth per woman and birthing people. Those with more than one birth during the study period had one pregnancy randomly included within the data, using the method of Langham et al.(\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e), allowing simplification of the data structure. (See \u003cb\u003eTable S3\u003c/b\u003e for a comparison of patient characteristics between the full and reduced data, excluding multiple pregnancies per woman).\u003c/p\u003e \u003cp\u003eWe excluded multifetal pregnancies, as is commonly done due to their high-risk nature, and to support a simplified data structure for birth outcomes(\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eWe truncated the data to exclude pregnancies outside the timeframe of 01 May 2019, to 22 April 2023 (\u003cb\u003eFigure S2\u003c/b\u003e), as linkage across antenatal bookings and delivery data showed tails when summarising the total number of deliveries and/or bookings per month. This was due to pregnancies with late antenatal registration in the antenatal booking data, and preterm births in the delivery data. We chose to truncate the data for a stable \u0026lsquo;number of deliveries\u0026rsquo; denominator, to avoid biasing our data for records at the beginning and end of the study period.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eData collection and outcomes\u003c/h3\u003e\n\u003cp\u003eBaseline maternal and pregnancy characteristics at antenatal registration were demographic factors, and current and past obstetric, medical, social (including socioeconomic status), and mental health history. All variable are listed fully in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, and include the following indicators of organisation performance measured at antenatal registration: maternal age, ethnicity, index of multiple deprivation (IMD)(\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e), prior Caesarean, and gestational age at booking. Ethnicity was defined using the eight-category classification by the Office for National Statistics, UK: White, Black/African/Caribbean/Black British, Indian (Asian or Asian British), Pakistani (Asian or Asian British), Other Asian/Asian British, Mixed/multiple ethnic groups, Any other ethnic group, or Not stated/unknown(\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). The Index of Multiple Deprivation (IMD) was used as the standard measure in the UK; IMD uses postal code to give an overall measure of deprivation within an defined geographic area (roughly equivalent to a neighbourhood of 1000\u0026ndash;3000 people), and incorporates the domains of: income, employment, educations skills and training, health deprivation and disability, crime, barriers to housing and services, and living environment(\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBaseline participant pregnancy characteristics, and pregnancy outcomes\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOverall\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePre-pandemic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePandemic\u003c/p\u003e \u003cp\u003ewith lockdowns\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePandemic\u003c/p\u003e \u003cp\u003ewithout lockdowns\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAntenatal Booking\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;31,411\u003csup\u003e\u003cem\u003e1\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;7,706\u003csup\u003e\u003cem\u003e1\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;10,137\u003csup\u003e\u003cem\u003e1\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;13,568\u003csup\u003e\u003cem\u003e1\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eData Source\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSite A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18,728 (59.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4,471 (58%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5,949 (59%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8,308 (61%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSite B\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12,683 (40.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3,235 (42%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4,188 (41%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5,260 (39%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGestation at Booking (weeks)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9.00 (8.00, 12.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.00 (8.00, 12.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.00 (8.00, 12.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10.00 (8.00, 12.00)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEthnicity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWhite\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15,887 (51%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3,812 (49%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5,338 (53%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6,737 (50%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBlack/African/Caribbean/Black British\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6,309 (20%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,442 (19%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2,063 (20%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2,804 (21%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndian (Asian or Asian British)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e765 (2.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e160 (2.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e241 (2.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e364 (2.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMixed/multiple ethnic groups\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,636 (5.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e326 (4.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e529 (5.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e781 (5.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther Asian/Asian British\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,930 (6.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e386 (5.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e627 (6.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e917 (6.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePakistani (Asian or Asian British)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e327 (1.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e72 (0.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e111 (1.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e144 (1.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAny Other ethnic group\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,186 (7.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e499 (6.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e795 (7.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e892 (6.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Missing)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,371 (7.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,009 (13%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e433 (4.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e929 (6.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIMD Quintile\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1 (most deprived)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6,050 (19%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,460 (19%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,900 (19%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2,690 (20%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12,914 (41%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3,230 (42%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4,167 (41%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5,517 (41%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7,790 (25%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,979 (26%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2,563 (25%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3,248 (24%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,906 (9.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e685 (8.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e932 (9.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1,289 (9.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5 (least deprived)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,210 (3.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e267 (3.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e400 (3.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e543 (4.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Missing)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e541 (1.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e85 (1.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e175 (1.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e281 (2.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNulliparous\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17,226 (55%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3,922 (51%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5,459 (54%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7,845 (58%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmoker at Booking\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,126 (3.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e301 (3.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e357 (3.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e468 (3.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrevious Caesarean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4,475 (14%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,139 (15%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,459 (14%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1,877 (14%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePregnancy outcomes\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGestation At Birth (Wks)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e39.00 (38.00, 40.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e39.00 (38.00, 40.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e39.00 (38.00, 40.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e39.00 (38.00, 40.00)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmoker At Birth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e825 (2.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e216 (2.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e278 (2.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e331 (2.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMental Health Service accessed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAny (includes inpatient)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,286 (7.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e532 (6.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e651 (6.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1,103 (8.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNHS \u0026lsquo;Talking Therapies\u0026rsquo;*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,372 (4.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e297 (3.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e420 (4.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e655 (4.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lsquo;Community contacts\u0026rsquo;\u0026dagger;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,176 (3.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e285 (3.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e298 (2.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e593 (4.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePreterm birth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,074 (6.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e535 (6.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e634 (6.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e905 (6.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInduction of labour\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6,845 (22%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,430 (19%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2,323 (23%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3,092 (23%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnassisted Vaginal Birth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14,368 (46%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3,862 (50%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4,772 (47%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5,734 (42%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Missing)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e84 (0.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (0.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e28 (0.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e48 (0.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInterventional Delivery\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEmergency Caesarean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7,062 (22%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,473 (19%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2,123 (21%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3,466 (26%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Missing)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e84 (0.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (0.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e28 (0.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e48 (0.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eElective Caesarean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5,064 (16%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,115 (14%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,580 (16%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2,369 (17%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Missing)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e84 (0.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (0.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e28 (0.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e48 (0.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAssisted Vaginal birth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4,833 (15%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,248 (16%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,634 (16%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1,951 (14%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Missing)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e84 (0.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (0.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e28 (0.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e48 (0.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVaginal tear (3rd / 4th )\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e500 (1.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e146 (1.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e144 (1.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e210 (1.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePPH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3,186 (10%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e731 (9.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e976 (9.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1,479 (11%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Missing)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (\u0026lt;\u0026thinsp;0.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1 (\u0026lt;\u0026thinsp;0.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStillbirth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e163 (0.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35 (0.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e55 (0.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e73 (0.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5-min Apgar\u0026thinsp;\u0026lt;\u0026thinsp;7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e502 (1.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e121 (1.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e157 (1.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e224 (1.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Missing)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e934 (3.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e202 (2.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e298 (2.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e434 (3.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSGA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,242 (7.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e546 (7.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e681 (6.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1,015 (7.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Missing)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e75 (0.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19 (0.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16 (0.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e40 (0.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLGA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3,841 (12%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e959 (12%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,270 (13%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1,612 (12%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Missing)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e75 (0.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19 (0.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16 (0.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e40 (0.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAdmitted to NICU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,072 (6.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e576 (7.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e737 (7.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e759 (5.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eICU (intensive care unit), IMD (Index of multiple deprivation), IQR (interquartile range), LGA (large-for-gestational age), NHS (National Health Service), NICU (neonatal intensive care unit), PPH (postpartum haemorrhage), SGA (small-for-gestational age), Wk (weeks)\u003c/p\u003e \u003cp\u003e* NHS \u0026lsquo;Talking Therapies\u0026rsquo; are psychological therapies for anxiety and depression (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.england.nhs.uk/mental-health/adults/nhs-talking-therapies/\u003c/span\u003e\u003cspan address=\"https://www.england.nhs.uk/mental-health/adults/nhs-talking-therapies/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e),\u003c/p\u003e \u003cp\u003e\u0026dagger; These are secondary mental health services community consultations.\u003c/p\u003e \u003cp\u003e\u003csup\u003e1\u003c/sup\u003e\u0026nbsp;n (%); Median (IQR)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eWe evaluated trends in key pregnancy and delivery indicators across three epochs, according to delivery date: pre-pandemic (01 October 2018 to 22 March 2020), pandemic lockdowns (23 March 2020 to 17 July 2021), and pandemic without lockdown (18 July 2021 to 4 May 2023)(\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). Key indicators measured at birth reflected UK: (i) \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eOrganisational Performance Indicators\u003c/span\u003e (i.e., interventional birth, defined as Caesarean birth or operative vaginal delivery); (ii) \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eClinical Quality Improvement Metrics\u003c/span\u003e (i.e., smoker at delivery, gestational age at birth, preterm birth\u0026thinsp;\u0026lt;\u0026thinsp;37 weeks, mode of birth, 3rd or 4th degree vaginal tears, and 5-minute Apgar\u0026thinsp;\u0026lt;\u0026thinsp;7); and (iii) \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eNational Maternity Indicators\u003c/span\u003e (i.e., mode of birth, 3rd or 4th degree tears, postpartum haemorrhage [PPH], 5-minute Apgar\u0026thinsp;\u0026lt;\u0026thinsp;7, birthweight\u0026thinsp;\u0026lt;\u0026thinsp;10th centile(\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). Additionally, we included other standard pregnancy outcomes (i.e., labour induction, stillbirth, large-for-gestational age [LGA, \u0026gt;\u0026thinsp;90th centile] infants, and neonatal care unit [NICU] admission), and mental health outcomes given particular interest in these related to the pandemic (i.e., maternal utilisation of mental health services, as NHS \u0026lsquo;Talking Therapies\u0026rsquo; [psychological therapies for anxiety and depression, developed to improve access and delivery of relevant treatment and previously known as Improving Access to Psychological Therapies(\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e)], secondary mental health services \u0026lsquo;community contacts\u0026rsquo;, and mental health-related inpatient admissions).\u003c/p\u003e\n\u003ch3\u003eStatistical Methods\u003c/h3\u003e\n\u003cp\u003eDescriptive statistics allowed for presentation of data, overall and by pandemic period, as mean (SD), median (IQR), and counts (percentage), as appropriate by data type and normality assumptions.\u003c/p\u003e \u003cp\u003eThe primary analysis compared the incidence of each maternal outcome across pandemic phases (as above(\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e)), using multivariable regression. Ordinal factor trend testing was employed by treating pandemic phases as a three-stage ordinal predictor variable and tested for evidence of flat (no trend), linear, and/or quadratic relationships over time. Adjustment factors were site (A or B) and variables based on published literature: ethnicity, IMD quintile, gestational age at booking (weeks), smoking at booking, nulliparity, prior Caesarean and month. A dummy variable for month was included in all models, to account for seasonality. The overall contribution was assessed using an ANOVA F-test, and the global p-value was reported to evaluate seasonality. BMI was not included as an adjustment factor due to the significant increase in its missingness during pandemic lockdowns, related to less face-to-face care; inclusion of BMI could have introduced bias due to non-random missingness.\u003c/p\u003e \u003cp\u003eRegression estimates, or odd ratios (ORs), with 95% confidence intervals (CIs) were reported for each delivery outcome for pandemic vs pandemic lockdowns, and pandemic lockdowns vs pandemic without lockdown, and additionally for each covariate. Interactions for each delivery outcome were tested between pandemic phase and: site, ethnicity, and IMD, to examine whether the pandemic exacerbated inequalities.\u003c/p\u003e \u003cp\u003eA secondary analysis visualised temporal trends in maternity outcomes in more granularity, by month, using generalised additive models (GAMs). These allow modelling and visualisation of complex and non-linear relationships. Given the timing and intensity of pandemic-related interventions, GAMs provided an appropriately flexible framework to capture the potential effects on outcomes of gradual and variable changes in care patterns, particularly at an individual level. For each delivery outcome, GAMs were plotted to illustrate trends, using flexible thin-plate regression splines stratified by site, from 1 May 2019 to 22 April 2023. The data were interpreted in terms of predicted means or probabilities of delivery outcomes, contingent upon the outcome distribution, per month/year of the study period. All outcomes were adjusted for the same confounders, as above.\u003c/p\u003e \u003cp\u003eA sensitivity analysis was conducted across all outcomes to assess the impact of time spent in pandemic epoch \u0026ldquo;pandemic with lockdowns\u0026rdquo;, per trimester. This was calculated by the proportion of days within each trimester within the defined \u0026ldquo;pandemic with lockdowns\u0026rdquo; period between March 2020 and July 2021. Multivariable regression analyses, adjusting for the same covariates as in the primary analysis was used to assess the relationship between maternal and birth outcome and the proportion of time spent in a lockdown period across three trimester variables, to provide an indication of the lockdown effect during the antenatal period, and not solely by delivery date.\u003c/p\u003e \u003cp\u003eAll analyses and data cleaning procedures were executed using RStudio version 4.3.0. A significance level of 1% was considered throughout. Missing data were reported in descriptive analyses and modelled as their own category throughout, providing insights into missingness.\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cp\u003eOf 36,985 potentially eligible pregnancies, excluded were: 727 multifetal gestations, a random 3,298 pregnancies to mothers with more than one pregnancy, and 1,549 pregnancies during truncation (\u003cb\u003eFigure S1\u003c/b\u003e). As a result, there were 31,411 pregnancies included in our analysis, from sites A (59.6%) and Site B (40.4%), over pre-pandemic (N\u0026thinsp;=\u0026thinsp;7,706; 24.5%), pandemic lockdowns (N\u0026thinsp;=\u0026thinsp;10,137; 32.3%), and pandemic without lockdown epochs (N\u0026thinsp;=\u0026thinsp;13,568; 43.2%) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThroughout the study period, maternal and pregnancy characteristics remained similar (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The gestation at booking was 9\u0026ndash;10 weeks. Approximately half of the cohort was from a minority ethnic group, primarily Black ethnicity. Just over half of pregnancies were from the two most socially-deprived IMD quintiles. Just over half of women were nulliparous, few reported smoking at antenatal booking, and about one-sixth had undergone prior Caesarean.\u003c/p\u003e \u003cp\u003eAcross study epochs, there were differences in many of the maternal outcomes evaluated (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Median gestational age at birth (39 weeks [IQR 38\u0026ndash;40]) and smoking at birth (just under 3%) remained steady over time. However, there appeared to be a progressive rise in use of NHS Talking Therapies, and an initial decrease and then increase in secondary mental health services \u0026lsquo;community contacts\u0026rsquo;. Birth requiring intervention appeared to rise over time, particularly for elective and emergency Caesarean (3% and 7% across epochs). Unassisted vaginal birth decreased (by 2%). PPH appeared to have increased (by 1.5%) and NICU admission fell (by 2%).\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e presents adjusted outcome estimates from linear models (mean difference/OR, 95% CI and test for trend) across study epochs, and non-linear models by month (spline term p-values, sites A and B); unadjusted analyses are presented in \u003cb\u003eTable S4\u003c/b\u003e, which shows that unadjusted effects remained stable following adjustment for confounders across all outcomes, except with SGA. Figures\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e3\u003c/span\u003e present visualisation of spline terms presented in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, stratified by site and adjusted for confounders, as in analyses presented in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e (where site was also an adjustment variable). Estimated degrees of freedom (EDF) are presented in \u003cb\u003eTable S5\u003c/b\u003e, and largely support our linear trends (as reflected by EDF values close to 1.0), and non-linear trends (as reflected by EDF values\u0026thinsp;\u0026gt;\u0026thinsp;2.0), without any low p-values from the k-index test that may reflect a poorly-fitted model.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eOutcome event rates trends over time*\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eTrend Test\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eSpline term\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOutcomes\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePre-Pandemic vs Pandemic with lockdowns\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePandemic without lockdowns vs. Pandemic with lockdowns\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLinear\u003c/p\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eQuadratic\u003c/p\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSite A\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSite B\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eBeta (95% CI)\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGestational age at birth (Wk)\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.02 (-0.09, -0.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.07 (-0.13, -0.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.029\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.658\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.288\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e\u003cb\u003eaORs (95% CI)\u003c/b\u003e \u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmoker at birth\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.88 (0.68\u0026ndash;1.13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.81 (0.65, 1.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.476\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.106\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.229\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.322\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMental Health Services\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAccessed NHS \u0026lsquo;Talking Therapies\u0026rsquo;\u0026dagger;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.97 (0.83\u0026ndash;1.13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.24 (1.09\u0026ndash;1.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.154\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.081\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAccessed \u0026lsquo;Community Contacts\u0026rsquo;ǂ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.29 (1.09\u0026ndash;1.53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.54 (1.33\u0026ndash;1.78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.022\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePreterm birth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.92 (0.81\u0026ndash;1.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.02 (0.92\u0026ndash;1.14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.250\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.276\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.837\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.662\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLabour induction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.27 (1.18\u0026ndash;1.37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.98 (0.92\u0026ndash;1.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.092\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnassisted Vaginal Birth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.92 (0.85\u0026ndash;0.98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.83 (0.78\u0026ndash;0.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.091\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInterventional Delivery\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEmergency Caesarean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.08 (1.00\u0026ndash;1.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.25 (1.17\u0026ndash;1.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.016\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eElective Caesarean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.12 (1.02\u0026ndash;1.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.20 (1.11\u0026ndash;1.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.377\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAssisted Vaginal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.95 (0.88\u0026ndash;1.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.83 (0.77\u0026ndash;0.89)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.051\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVaginal tear (3rd /4th degree)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.73 (0.57\u0026ndash;0.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.03 (0.83\u0026ndash;1.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.087\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.188\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePPH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.99 (0.90\u0026ndash;1.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.12 (1.02\u0026ndash;1.22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.031\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.154\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.387\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStillbirth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.27 (0.83\u0026ndash;2.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.92 (0.64\u0026ndash;1.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.580\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.426\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.124\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.234\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5-minute Apgar\u0026thinsp;\u0026lt;\u0026thinsp;7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.02 (0.81\u0026ndash;1.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.00 (0.81\u0026ndash;1.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.843\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.908\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.831\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.464\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSGA infants\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.93 (0.83\u0026ndash;1.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.08 (0.98\u0026ndash;1.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.966\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.121\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.361\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.530\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLGA infants\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.02 (0.93\u0026ndash;1.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.98 (0.91\u0026ndash;1.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.993\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.579\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.268\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.198\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAdmitted to NICU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.01 (0.90\u0026ndash;1.13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.70 (0.63\u0026ndash;0.78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.377\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003eCI (confidence interval), LGA (large-for-gestational age), NHS (National Health Service), NICU (neonatal intensive care unit), OR (odds ratio), PPH (postpartum haemorrhage), SGA (small-for-gestational age), Wk (weeks)\u003c/p\u003e \u003cp\u003e* 95% confidence intervals that do not cross 1.0 are shaded in grey, and p values\u0026thinsp;\u0026lt;\u0026thinsp;0.01 are shaded in yellow.\u003c/p\u003e \u003cp\u003e\u0026dagger; NHS \u0026lsquo;Talking Therapies\u0026rsquo; are psychological therapies for anxiety and depression (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.england.nhs.uk/mental-health/adults/nhs-talking-therapies/\u003c/span\u003e\u003cspan address=\"https://www.england.nhs.uk/mental-health/adults/nhs-talking-therapies/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e),\u003c/p\u003e \u003cp\u003eǂ These are secondary mental health services community consultations.\u003c/p\u003e \u003cp\u003e\u003csup\u003e1\u003c/sup\u003eMultivariable Linear Regression analysis for continuous outcomes presenting mean difference in estimates. All models were adjusted for the same minimal number of confounders: Data source (site A or B), Index of Multiple Deprivation Quintiles, Ethnicity, Gestation at booking (wks), Smoking at registration, Nulliparity, Month (for seasonality) and Previous Caesarean.\u003c/p\u003e \u003cp\u003e\u003csup\u003e2\u003c/sup\u003e Multivariable Logistic Regression for binary outcomes presenting OR with 95% CI. Models were adjusted as above\u003csup\u003e1\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003e\u003csup\u003e3\u003c/sup\u003e Multivariable Generalised Additive Models\u0026rsquo; p-value, corresponding to site A and B spline terms for each outcome to evaluate the probability of stable trends across different sites. Models adjusted as above\u003csup\u003e1\u003c/sup\u003e, except for site data, which were presented separately for sites A and B.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eSix outcomes showed \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003estable\u003c/span\u003e probabilities over time: smoking at birth, preterm birth, stillbirth, 5-minute Apgar\u0026thinsp;\u0026lt;\u0026thinsp;7, and SGA and LGA infants, as illustrated by trend test results, and by spline terms for sites A and B (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Further graphical illustrations are provided in Figs.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u003cb\u003e[a-f]\u003c/b\u003e, which display flat (zero slope) trends with overlapping 95% CIs across both sites over the months/years, for each outcome. Spline terms for these outcomes indicated no evidence of linear or non-linear trends, at either site.\u003c/p\u003e \u003cp\u003e \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eLinear trends\u003c/span\u003e were observed for several outcomes, with directions of overall effect shown by model estimates between epochs. Accessed \u0026lsquo;Talking Therapies\u0026rsquo;, emergency Caesareans, and elective Caesareans increased, while, unassisted vaginal birth, assisted vaginal birth, and 3rd or 4th-degree vaginal tears decreased (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Visualisation of spline terms by site revealed where linear trends were observed at only one site (but were stable at the other); gestational age at birth decreased only at site B (by approximately half a week, Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003ea), accessed \u0026lsquo;Talking Therapies\u0026rsquo; increased only at site B (by ~\u0026thinsp;4\u0026ndash;9% probability, Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003eb), 3rd or 4th degree vaginal tears decreased only at site A (~\u0026thinsp;2% change in probability, Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003ec), and PPH increased only at site B (by ~\u0026thinsp;4%, with a plateau during pandemic without lockdown, Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003ed); changes in gestational age at birth (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003ea) and PPH (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003ed) were very small, and were undetected by trend testing at a 1% significance level (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e); however, they were noted in real-time by site B, which attributed them to rising Caesarean rates, and instituted more consultant supervision of trainees during emergency Caesareans (see below), greater awareness of PPH risk factors, more frequent use of prophylactic uterotonics, and early escalation of PPH. Strong linear trends were observed at both sites for emergency and elective Caesareans (increasing y-axis probability limits from 20\u0026ndash;35% [Figure \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e3\u003c/span\u003ea] and 10\u0026ndash;16% [Figure \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e3\u003c/span\u003eb]), and for unassisted and assisted vaginal births (decreasing y-axis probability limits from 45 to 30% [Figure \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e3\u003c/span\u003ec] and 30\u0026ndash;18% [Figure \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e3\u003c/span\u003ed]). However, notable GAM features include: (i) for Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e3\u003c/span\u003ea, some small fluctuations in emergency Caesareans at site A were undetected by the trend test analysis, but largely increased linearly; and (ii) for Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e3\u003c/span\u003ea, a pre-pandemic decrease in unassisted vaginal births at site B also began at site A during the first pandemic lockdown, with ongoing linear decreases thereafter.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eComplex and non-linear trends\u003c/span\u003e were observed in secondary mental health services \u0026lsquo;community contacts\u0026rsquo; (initially decreased by 2\u0026ndash;3% during pandemic lockdowns [when reduced in availability], then increased), labour induction (sharp pre-pandemic increase from 15\u0026ndash;28% probability and then plateaued at site B), and NICU admissions (some fluctuation at site A pre- and during pandemic lockdowns, then decreased from 8% mid-pandemic lockdowns to 2\u0026ndash;3% probability). None of these patterns were consistent with seasonality. These trends were different at sites A and B (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), except for accessed secondary mental health services \u0026lsquo;community contacts\u0026rsquo;, which, at both sites, decreased following the first pandemic lockdown, and then increased, surpassing pre-pandemic levels by the end of the pandemic (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eIn the sensitivity analysis, 13/17 outcomes displayed no association between the odds of any outcome at birth, and the proportion of time spent in \u0026ldquo;pandemic with lockdowns\u0026rdquo;, across all three trimesters (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Four outcomes showed some such association: (i) access to \u0026lsquo;Community Contacts\u0026rsquo; mental health services displayed a decreased odds associated with more time spent in \u0026lsquo;pandemic with lockdowns\u0026rsquo; during the third trimester; (ii) labour induction displayed an increased odds with more time spent in lockdown in the third trimester; (iii) unassisted vaginal birth was less likely with more time spent in lockdown in the first trimester; and (iv) admission to the neonatal unit was more likely with higher proportions of first and third trimesters spent in lockdown, and less likely with high proportions of second trimester spent in lockdown. These results were consistent with the complex, site-specific changes reflected in the GAMs.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eProportion of time spent in \u0026lsquo;pandemic with lockdowns\u0026rsquo;, by trimester\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOutcomes\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eProportion within Trimester 1 (days)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eProportion with Trimester 2 (days)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eProportion within Trimester 3 (days)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eBeta (95% CI)\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGestational age at birth (Wk)\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.01 (-0.13, 0.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.01 (-0.17, 0.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.01 (-0.10, 0.13)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e\u003cb\u003eaORs (95% CI)\u003c/b\u003e \u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmoker at birth\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.04 (0.67, 1.611)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.12 (0.58, 2.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.18 (0.76, 1.82)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMental Health Services\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAccessed NHS \u0026lsquo;Talking Therapies\u0026rsquo;\u0026dagger;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.15 (0.89, 1.48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.93 (0.64, 1.37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.91 (0.70, 1.18)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAccessed \u0026lsquo;Community Contacts\u0026rsquo;ǂ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.16 (0.88, 1.52)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.00 (0.66, 1.51)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.67 (0.51, 0.88)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePreterm birth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.03 (0.84, 1.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.93 (0.68, 1.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.03 (0.83, 1.27)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLabour induction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.07 (0.94, 1.22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.92 (0.76, 1.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.19 (1.05, 1.36)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnassisted Vaginal Birth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.84 (0.74, 0.94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.14 (0.95, 1.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.05 (0.94, 1.19)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInterventional Delivery\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEmergency Caesarean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.12 (0.99, 1.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.91 (0.75, 1.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.91 (0.80, 1.03)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eElective Caesarean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.15 (0.98, 1.34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.94 (0.74, 1.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.91 (0.78, 1.07)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAssisted Vaginal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.02 (0.88, 1.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.96 (0.77, 1.21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.13 (0.97, 1.31)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVaginal tear (3rd /4th degree)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.17 (0.76, 1.78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.85 (0.45, 1.61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.86 (0.56, 1.31)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePPH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.99 (0.90\u0026ndash;1.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.12 (1.02, 1.22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.14 (0.96, 1.36)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStillbirth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.27 (0.83\u0026ndash;2.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.92 (0.64, 1.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.00 (0.77, 1.30)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5-minute Apgar\u0026thinsp;\u0026lt;\u0026thinsp;7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.02 (0.81\u0026ndash;1.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.00 (0.81, 1.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.90 (0.76, 1.07)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSGA infants\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.21 (0.99, 1.48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.85 (0.62, 1.15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.96 (0.78, 1.17)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLGA infants\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.00 (0.85, 1.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.08 (0.85, 1.37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.97 (0.83, 1.14)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAdmitted to NICU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.28 (1.04, 1.57)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.65 (0.47, 0.89)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.68 (1.36, 2.07)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eCI (confidence interval), LGA (large-for-gestational age), NHS (National Health Service), NICU (neonatal intensive care unit), OR (odds ratio), PPH (postpartum haemorrhage), SGA (small-for-gestational age), Wk (weeks)\u003c/p\u003e \u003cp\u003e* 95% confidence intervals that do not cross 1.0 are shaded in grey, and p values\u0026thinsp;\u0026lt;\u0026thinsp;0.01 are shaded in yellow.\u003c/p\u003e \u003cp\u003e\u0026dagger; NHS \u0026lsquo;Talking Therapies\u0026rsquo; are psychological therapies for anxiety and depression (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.england.nhs.uk/mental-health/adults/nhs-talking-therapies/\u003c/span\u003e\u003cspan address=\"https://www.england.nhs.uk/mental-health/adults/nhs-talking-therapies/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e),\u003c/p\u003e \u003cp\u003eǂ These are secondary mental health services community consultations.\u003c/p\u003e \u003cp\u003e\u003csup\u003e1\u003c/sup\u003eMultivariable Linear Regression analysis for continuous outcomes presenting mean difference in estimates. All models were adjusted for the same minimal number of confounders: Data source (site A or B), Index of Multiple Deprivation Quintiles, Ethnicity, Gestation at booking (wks), Smoking at registration, Nulliparity, Month (for seasonality) and Previous Caesarean.\u003c/p\u003e \u003cp\u003e\u003csup\u003e2\u003c/sup\u003e Multivariable Logistic Regression for binary outcomes presenting OR with 95% CI. Models were adjusted as above\u003csup\u003e1\u003c/sup\u003e.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eRelationships between adjustment factors and outcomes are presented in \u003cb\u003eTables S6a\u003c/b\u003e and \u003cb\u003eS6b.\u003c/b\u003e For all outcomes, significant associations were seen for minority ethnic groups (compared with White ethnicity) and nulliparity (vs. multiparity). For example, there was a 0.50\u0026ndash;0.78 decreased odds of elective Caesarean across all ethnic minority groups (Black, Asian \u0026amp; Asian British, Mixed, and Multiple ethnic groups), compared with White ethnicity, and nulliparous (vs. multiparous) women showed a 4.58 increased odds of assisted vaginal birth. Other adjustment factors were associated with a number of adverse outcomes, such as a strong increased odds of elective Caesarean amongst those with the least (vs. most) deprived IMD, and for smokers (vs. non-smokers) at registration, a 0.41 decreased odds of LGA babies and 4.90 increased odds of accessing secondary mental health services \u0026lsquo;community contacts\u0026rsquo;. Eleven of 17 outcomes highlighted differences between the two sites (A vs. B). There was no evidence of seasonality in any maternal or birth outcomes.\u003c/p\u003e \u003cp\u003eFor each outcome, interactions between time (pandemic epoch) and site, ethnicity, and IMD are presented in \u003cb\u003eTable S7;\u003c/b\u003e interactions with site were seen for induction, emergency Caesarean, PPH, and NICU admissions, as illustrated in Figs.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e3\u003c/span\u003e. Similarly, interactions between time and ethnicity were seen for some outcomes, although most interactions were attributable to \u0026lsquo;other\u0026rsquo; or \u0026lsquo;missing\u0026rsquo; ethnicity categories (as seen in 13% of pregnancies pre-pandemic, 4.3% during pandemic lockdowns, and 6.8% during pandemic without lockdown). Only for labour induction during pandemic lockdowns was there an interaction with a specific ethnicity category (Black ethnicity). No interaction was seen between time and IMD for any outcome.\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eSummary of findings\u003c/h2\u003e \u003cp\u003eIn more than 30,000 pregnancies from ethnically and socio-economically diverse South London, UK, we found that most pregnancy outcomes followed pre-pandemic temporal trends, either stable (e.g., preterm birth), increasing (e.g., elective Caesarean), or decreasing (e.g., assisted vaginal birth). While there was a clear pandemic-related decrease in accessing secondary mental health services \u0026lsquo;community contacts\u0026rsquo; during the first pandemic lockdown, when those services were decreased in availability, other temporal trends (including labour induction and NICU admissions) were related to fluctuations at only one site, potentially due to local adaptations. We saw no evidence of seasonality, and any associations between outcomes and the proportion of time spent in a given trimester reflected the few observed complex site-specific changes illustrated by the GAMs.\u003c/p\u003e \u003cp\u003eInteraction tests between time and each site, ethnicity, and IMD quintiles supported the stratification of trends by data collection sites, highlighting their adaptations to pandemic impacts on maternal outcomes. While there was clear evidence of inequalities in outcomes for minority ethnic group (vs. White) women and those experiencing greater levels of deprivation, there was no compelling evidence that the pandemic exacerbated those inequalities.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eComparison with the literature\u003c/h3\u003e\n\u003cp\u003eIn contrast to our study which covered the entire pandemic and examined monthly trends, the global impact of the pandemic on pregnancy outcomes has been examined primarily in the first pandemic year with lockdowns, or slightly beyond that into the summer of 2021, in studies in South London, North West England(\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e), England(\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e), or globally(\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). While many studies found that the pandemic was associated with a decrease in preterm birth (overall and spontaneous)(\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e), there was evidence of publication bias and heterogeneity(\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). In a population-based study in England, pandemic lockdown (vs. pre-pandemic) was associated with small changes in outcomes, albeit small: fewer preterm births, more interventions (such as Caesarean or labour induction), and fewer SGA babies(\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). Of note, if our approach had been to compare either pandemic lockdowns or the entire pandemic with pre-pandemic outcomes, we too would have described the pandemic to be associated with an increase in intervention (i.e., increase in emergency or elective Caesareans, and decrease in gestational age at birth and unassisted vaginal birth). Using interrupted time series analysis of data from North West England(\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e) or Australia(\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e), outcomes were largely unchanged, including stillbirth, preterm birth, and abnormal fetal growth (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e), or improvements in outcomes were reported, such as a reduction in labour induction for FGR which was not associated with a difference in FGR incidence or perinatal morbidity(\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAs in our study, Gurol-Urganci \u003cem\u003eet al\u003c/em\u003e. reported that some clinical outcomes (i.e., preterm births, Caesareans, and unassisted vaginal births) varied in the pandemic by ethnicity (White vs. minority ethnic groups), but not social deprivation (IMD quintiles 1\u0026ndash;3 vs. 4\u0026ndash;5)(\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). Our data add to this work, by clarifying that while minority group ethnicity and social deprivation are each associated with adverse outcomes, there is no specific ethnicity category for which pandemic-related effects were different. Rather, any interactions between ethnicity and the pandemic were, with one exception, due to unspecified or missing ethnicity, which was slightly more common pre-pandemic. Also, we have confirmed that there is no interaction between time and IMD, when quintiles 1\u0026ndash;2 are compared with 3\u0026ndash;5.\u003c/p\u003e \u003cp\u003eOur finding of ongoing increases in use of mental health treatment is consistent with published findings of a pandemic-related, negative legacy with regards to mental health. Pandemic-related social distancing restrictions had an adverse effect on women\u0026rsquo;s mental health before and after birth, related to restricted access to informal (family and friends) and formal (healthcare professional) support(\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). Antenatally, women described feeling trapped, anxious, and abandoned during initial lockdown and its lifting(\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e), with prohibition of family from maternity wards particularly distressing whilst initial lockdown restrictions were being eased(\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e21\u003c/span\u003e). A similar, cumulative, negative effect was seen on postpartum mental health(\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e), when pandemic social distancing restrictions could explain about one-third of the substantial increase in maternal depression (from 11\u0026ndash;43%) and anxiety (from 18\u0026ndash;61%), after accounting for current relevant diagnoses and other mental health risk factors(\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). Younger women and sexual minority women were more likely to have postnatal anxiety, with younger participants reporting anxieties about infant safety and welfare, whilst lesbian, gay, bisexual, and pansexual participants struggled more with psychosocial adjustment to motherhood(\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eOur finding that the vast majority of pregnancy outcomes followed pre-pandemic trends must be seen in light of the extensive, pandemic-related maternity service configurations in the UK. In line with recommendations from the Royal College of Obstetricians and Gynaecologists and Royal College of Midwives, a national survey documented that most UK maternity units reduced the number of antenatal contacts offered by any method, converted some antenatal appointments to remote consultations (particularly in the first and second trimesters, about which women reported mixed views(\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e), increased use of self-monitoring of blood pressure, modified screening for gestational diabetes, reduced the frequency of fetal growth surveillance by ultrasound, and reduced options for place of birth(\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e). Of note, there were few changes to labour induction indications or the offer of Caesarean by request.\u003c/p\u003e\n\u003ch3\u003eClinical and research implications\u003c/h3\u003e\n\u003cp\u003eWhen considering the impact of system-wide influences on pregnancy outcomes, our findings highlight the importance of evaluating longer-term temporal trends to contextualise short-term pregnancy outcome rates, as well as benchmarking between hospitals. Examining temporal trends in outcomes, and not just comparing outcome event rates between two time periods, minimises the risk of drawing spurious conclusions and overestimating the impact of acute events on outcomes, particularly as the relationships are complex between factors influencing maternity care and pregnancy outcomes, and can arise from individuals (e.g., care-seeking behaviour), care providers (e.g., staffing), or guidance, local or national. Benchmarking between sites, particularly temporally, may identify variations in outcomes and their underlying processes of care, with the goal of identifying best practice, optimising outcomes and minimising costs, as has been done successfully by others using detailed, routinely-collected data(\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). All such activities are underpinned by a learning health system of data-driven learning, and rapid translation of learning into practice, to reduce the time to implementation; importantly, such an approach imbeds the engagement of key stakeholders, to co-design local solutions and influence\u0026thinsp;\u0026lt;\u0026thinsp;learning health system\u0026thinsp;\u0026gt;\u0026thinsp;policy. By virtue of its principle of continuous learning, a learning health system prepares the health system for shocks, such as a the COVID-19 pandemic.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eStrengths and limitations\u003c/h2\u003e \u003cp\u003eStrengths of our study include its large sample size and diversity of the study population in South London, UK, all based on routinely-collected data. We reported both physical and mental health outcomes. We covered the entire pandemic, facilitating our understanding of the impact of pandemic-related changes in care practices (and their withdrawal). Our multi-method analytic approach, which included multivariable regression, ordinal factor trend testing, and GAMs, allowed us to examine both linear and non-linear outcome patterns over time. The complementary results from each method led to comparable conclusions, further strengthening our findings. This methodological approach, not commonly employed to address trends in pregnancy outcomes, enabled us to make the distinction between ongoing trends and fluctuations due to pandemic-related changes. Additionally, our analyses were adjusted for site and individual-level characteristics, and we evaluated potential interactions between time and confounders. Also, we consulted clinicians from each hospital to deepen interpretation and verify trends.\u003c/p\u003e \u003cp\u003eWith respect to limitations of this study, our decision to classify the timing of pregnancies according to pandemic epoch of birth means that findings may reflect predominantly late pregnancy and intrapartum care, rather than that earlier in pregnancy. Whilst multiple outcomes were explored separately, and analyses adjusted for the same set of minimal confounders, we believe our results reflect a coherent pattern of the main processes at play across study epochs. However, given the complex nature of these outcomes, further work would be warranted to assess outcome-specific adjustments. There was a very low rate of SARS-CoV2 positivity, this may reflect underreporting (as seen in other routinely-collected data (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e21\u003c/span\u003e)), however a similar prevalence of 0.1% has been reported by other cohorts in pregnant women during the pandemic (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e); due to the low prevalence, this precluded an analysis of the impact of SARS-CoV2 positivity on pregnancy outcomes. Finally, we analysed raw, uncoded clinical data in eLIXIR-BiSL; while some data missingness was evident and the validity of all such data cannot be confirmed, this is the information on which clinical care was based in the index pregnancy, and will be based in future pregnancy.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusions","content":"\u003cp\u003eIn this large, diverse cohort of pregnancies from South London, UK, our findings reveal that, despite the significant health system shock of the pandemic and the decrement in experiences of maternity care, the direct impact on pregnancy outcomes was limited. Overall, outcomes during the pandemic largely reflected pre-pandemic trends and did not exacerbate inequalities, demonstrating the resilience of maternity services during this challenging period.\u003c/p\u003e"},{"header":"ABBREVIATIONS","content":"\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eCI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eConfidence interval\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eeLIXIR-BiSL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eearly-LIfe data cross-LInkage In Research, Born in South London\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eFGR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eFetal growth restriction\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eGAM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eGeneralised additive modelling\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eIAPT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eImproved Access to Psychological Therapy\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eIMD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eIndex of multiple deprivation\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLGA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLarge-for-gestational age infant\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNHS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNational Health Service\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNICU\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNeonatal intensive care unit\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eOR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eOdds ratio\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePPH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePostpartum haemorrhage\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePTB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePreterm birth\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSGA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSmall-for-gestational age infant\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eUK\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eUnited Kingdom\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eWks\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eWeeks\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"},{"header":"Declarations","content":"\u003cp\u003eThe authors have no relevant competing interests to declare. The views expressed are those of the author(s) and not necessarily those of NIHR, the NHS, or the Department of Health and Social Care, UK.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eACKNOWLEDGEMENTS\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe wish to thank the women, their infants, and families from all participating sites for sharing their data and supporting the eLIXIR-BiSL programme.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAUTHORS\u0026rsquo; CONTRIBUTIONS\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was conceived by LAM, PvD, and FT. All authors contributed to the design and delivery of the study. The author FT assumes responsibility for the accuracy and completeness of data reporting. FT and LAM drafted the manuscript, which was revised and approved by all authors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFUNDING\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis project was funded by the National Institute for Health Research (NIHR) HSDR Programme [NIHR134293]. The Early Life Cross Linkage in Research, Born in South London (eLIXIR-BiSL) Partnership was developed by an MRC Partnership Grant [MR/P003060/1] and the MRC Longitudinal Population Study Grant [MR/X009742/1]. The eLIXIR-BiSL platform is also part-supported by the National Institute for Health Research (NIHR) Biomedical Research Centre at the South London and Maudsley NHS Foundation Trust and King\u0026rsquo;s College London. The funders played no role in study design, data acquisition or analyses, manuscript preparation, or the decision to submit for publication. \u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eETHICAL APPROVAL\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe eLIXIR-BiSL Partnership received ethical approval from the Oxfordshire Research Ethics Committee C (Ref:18/SC/0086, 2018-23; renewal 23/SC/0116, 2023-8) as an anonymised dataset for medical research.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDATA AVAILABILITY STATEMENT\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data accessed by eLIXIR-BiSL remain within an NHS firewall and governance is provided by the eLIXIR Oversight Committee reporting to relevant information governance clinical leads. Subject to these conditions, data access is encouraged and those interested should contact the eLIXIR-BiSL Chief Investigator (Professor Lucilla Poston; [email protected]) or the HDRUK Innovation Gateway (https://web.www.healthdatagateway.org/dataset/3c780d45-ed7b-4101-9c32-d50512cd9cfe). \u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCODE AVAILABILITY STATEMENT\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe custom code used for data analysis in this study is available upon reasonable request to the corresponding author. Access will be provided in accordance with institutional and ethical guidelines.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAllotey J, Stallings E, Bonet M, Yap M, Chatterjee S, Kew T, et al. Clinical manifestations, risk factors, and maternal and perinatal outcomes of coronavirus disease 2019 in pregnancy: living systematic review and meta-analysis. BMJ. 2020;370:m3320.\u003c/li\u003e\n\u003cli\u003eSilverio SA, De Backer K, Easter A, von Dadelszen P, Magee LA, Sandall J. Women\u0026apos;s experiences of maternity service reconfiguration during the COVID-19 pandemic: A qualitative investigation. Midwifery. 2021;102:103116.\u003c/li\u003e\n\u003cli\u003eTownsend R, Chmielewska B, Barratt I, Kalafat E, van der Meulen J, Gurol-Urganci I, et al. Global changes in maternity care provision during the COVID-19 pandemic: A systematic review and meta-analysis. EClinicalMedicine. 2021;37:100947.\u003c/li\u003e\n\u003cli\u003eGurol-Urganci I, Jardine J, Carroll F, Fremeaux A, Muller P, Relph S, et al. Use of induction of labour and emergency caesarean section and perinatal outcomes in English maternity services: a national hospital-level study. BJOG. 2022;129(11):1899-906.\u003c/li\u003e\n\u003cli\u003eYang J, D\u0026apos;Souza R, Kharrat A, Fell DB, Snelgrove JW, Shah PS. COVID-19 pandemic and population-level pregnancy and neonatal outcomes in general population: A living systematic review and meta-analysis (Update#2: November 20, 2021). Acta Obstet Gynecol Scand. 2022;101(3):273-92.\u003c/li\u003e\n\u003cli\u003eJackson L, De Pascalis L, Harrold JA, Fallon V, Silverio SA. Postpartum women\u0026apos;s psychological experiences during the COVID-19 pandemic: a modified recurrent cross-sectional thematic analysis. BMC Pregnancy Childbirth. 2021;21(1):625.\u003c/li\u003e\n\u003cli\u003eWilkinson M, Johnstone ED, Simcox LE, Myers JE. The impact of COVID-19 on pregnancy outcomes in a diverse cohort in England. Sci Rep. 2022;12(1):942.\u003c/li\u003e\n\u003cli\u003eThirugnanasundralingam K, Davies-Tuck M, Rolnik DL, Reddy M, Mol BW, Hodges R, et al. Effect of telehealth-integrated antenatal care on pregnancy outcomes in Australia: an interrupted time-series analysis. Lancet Digit Health. 2023;5(11):e798-e811.\u003c/li\u003e\n\u003cli\u003eCarson LE, Azmi B, Jewell A, Taylor CL, Flynn A, Gill C, et al. Cohort profile: the eLIXIR Partnership-a maternity-child data linkage for life course research in South London, UK. BMJ Open. 2020;10(10):e039583.\u003c/li\u003e\n\u003cli\u003eStewart R, Soremekun M, Perera G, Broadbent M, Callard F, Denis M, et al. The South London and Maudsley NHS Foundation Trust Biomedical Research Centre (SLAM BRC) case register: development and descriptive data. BMC Psychiatry. 2009;9:51.\u003c/li\u003e\n\u003cli\u003eLangham J, Gurol-Urganci I, Muller P, Webster K, Tassie E, Heslin M, et al. Obstetric and neonatal outcomes in pregnant women with and without a history of specialist mental health care: a national population-based cohort study using linked routinely collected data in England. Lancet Psychiatry. 2023;10(10):748-59.\u003c/li\u003e\n\u003cli\u003eWastnedge EAN, Fretwell J, Johns EC, Denison FC, Reynolds RM. First and second pregnancy outcomes in women with class III obesity: An observational cohort study. Obes Res Clin Pract. 2021;15(4):357-61.\u003c/li\u003e\n\u003cli\u003eThe English Indices of Deprivation 2019 (IoD2019) Ministries of Housing, Communities and Local Government. https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/835115/IoD2019_Statistical_Release.pdf (2019).\u003c/li\u003e\n\u003cli\u003ehttps://www.ons.gov.uk/peoplepopulationandcommunity/culturalidentity/ethnicity.\u003c/li\u003e\n\u003cli\u003eBaker C, Kirk-Wade E, Brown J, Barber S. Coronavirus: A history of English lockdown laws https://commonslibraryparliamentuk/research-briefings/cbp-9068/ (cited 21 Jun 2024). 2021.\u003c/li\u003e\n\u003cli\u003eStandards and Tools. INTERGROWTH-21st. https://intergrowth21tghnorg/standards-tools/ (cited 21 Jun 2024).\u003c/li\u003e\n\u003cli\u003eNHS England. NHS Talking Therapies, for anxiety and depression. https://wwwenglandnhsuk/mental-health/adults/nhs-talking-therapies/ (cited 21 Jun 2024).\u003c/li\u003e\n\u003cli\u003eYao XD, Zhu LJ, Yin J, Wen J. Impacts of COVID-19 pandemic on preterm birth: a systematic review and meta-analysis. Public Health. 2022;213:127-34.\u003c/li\u003e\n\u003cli\u003eJackson L, De Pascalis L, Harrold JA, Fallon V, Silverio SA. Postpartum women\u0026apos;s experiences of social and healthcare professional support during the COVID-19 pandemic: A recurrent cross-sectional thematic analysis. Women Birth. 2022;35(5):511-20.\u003c/li\u003e\n\u003cli\u003eJackson L, Davies SM, Podkujko A, Gaspar M, De Pascalis LLD, Harrold JA, et al. The antenatal psychological experiences of women during two phases of the COVID-19 pandemic: A recurrent, cross-sectional, thematic analysis. PLoS One. 2023;18(6):e0285270.\u003c/li\u003e\n\u003cli\u003eJackson L, Davies SM, Gaspar M, Podkujko A, Harrold JA, Pascalis L, et al. The social and healthcare professional support drawn upon by women antenatally during the COVID-19 pandemic: A recurrent, cross-sectional, thematic analysis. Midwifery. 2024;133:103995.\u003c/li\u003e\n\u003cli\u003eFallon V, Davies SM, Silverio SA, Jackson L, De Pascalis L, Harrold JA. Psychosocial experiences of postnatal women during the COVID-19 pandemic. A UK-wide study of prevalence rates and risk factors for clinically relevant depression and anxiety. J Psychiatr Res. 2021;136:157-66.\u003c/li\u003e\n\u003cli\u003eMamrath S, Greenfield M, Fernandez Turienzo C, Fallon V, Silverio SA. Experiences of postpartum anxiety during the COVID-19 pandemic: A mixed methods study and demographic analysis. PLoS One. 2024;19(3):e0297454.\u003c/li\u003e\n\u003cli\u003eJardine J, Relph S, Magee LA, von Dadelszen P, Morris E, Ross-Davie M, et al. Maternity services in the UK during the coronavirus disease 2019 pandemic: a national survey of modifications to standard care. BJOG. 2021;128(5):880-9.\u003c/li\u003e\n\u003cli\u003eThe Canadian Neonatal Network. https://wwwcanadianneonatalnetworkorg/portal/ (accessed 21 Jun 2024).\u003c/li\u003e\n\u003cli\u003eGurol-Urganci, I. et al. Obstetric interventions and pregnancy outcomes during the COVID-19 pandemic in England: A nationwide cohort study. \u003cem\u003ePLoS Med\u003c/em\u003e. 2022;\u003cstrong\u003e19\u003c/strong\u003e(1):e1003884.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[{"identity":"2b61529e-6956-41e1-b817-a8dfa339a060","identifier":"10.13039/501100000272","name":"National Institute for Health Research","awardNumber":"NIHR134293","order_by":0},{"identity":"0cd4ae3f-eaf6-4d1f-844c-1605f449c4a6","identifier":"10.13039/501100000265","name":"Medical Research Council","awardNumber":"MR/P003060/1 \u0026 MR/X009742/1","order_by":1}],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"King's College London","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-6886833/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6886833/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eTo better understand reported COVID-19 pandemic effects on pregnancy, we examined temporal trends in pregnancy outcomes in a diverse population from South London, United Kingdom. We included 31,411 singleton pregnancies with complete registration and birth outcomes across pre-pandemic (May 1/2019\u0026ndash;March 22/2020, 24.5%), pandemic lockdowns (March 23/2020\u0026ndash;July 17/2021, 32.3%), and pandemic without lockdown epochs (July 18/2021\u0026ndash;April 22/2023, 43.2%). Multivariable regression was employed to evaluate outcomes by study epoch, adjusting for potential confounders (e.g., ethnicity, deprivation, site), followed by generalized additive modelling to visualise monthly trends. Of 17 outcomes: six had stable trends (e.g., preterm birth, stillbirth); eight showed linear trends, either decreasing (e.g., gestational age at birth, vaginal tears) or increasing (e.g., Caesareans, postpartum haemorrhage); and three showed quadratic (complex) trends (e.g., secondary mental health services, labour induction). Overall, most outcomes during the pandemic mirrored pre-pandemic trends, with observed fluctuations likely due to site-specific responses.\u003c/p\u003e","manuscriptTitle":"Temporal trends in pregnancy outcomes during a health system shock: A retrospective longitudinal study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-01 03:34:41","doi":"10.21203/rs.3.rs-6886833/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"ea081791-7377-47f9-8276-27c48ecf7c79","owner":[],"postedDate":"July 1st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":50608910,"name":"Sexual \u0026 Reproductive Medicine"}],"tags":[],"updatedAt":"2025-07-01T03:34:41+00:00","versionOfRecord":[],"versionCreatedAt":"2025-07-01 03:34:41","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6886833","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6886833","identity":"rs-6886833","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}