Human Papillomavirus Infections during Pregnancy and Adverse Pregnancy Outcomes: a Prospective Mother-Child Cohort Study

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VAERNESBRANDEN, Anne Cathrine STAFF, Johanna WIIK, and 16 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5108443/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 19 Nov, 2024 Read the published version in BMC Pregnancy and Childbirth → Version 1 posted 12 You are reading this latest preprint version Abstract BACKGROUND Human papillomaviruses are common in the urogenital tract amongst women of childbearing age. A few studies indicate a possible association between human papillomavirus infections in pregnancy and adverse pregnancy outcomes whilst other studies find no such association. We aimed to investigate the association between human papillomavirus infections during pregnancy and adverse pregnancy outcomes linked to placental dysfunction, including hypertensive disorders of pregnancy, gestational diabetes mellitus and newborns small for gestational age. MATERIAL AND METHODS Pregnant women from the general population in Norway and Sweden were enrolled at the time of routine mid-gestational ultrasound examination. Urine samples collected at mid-gestation in 950 and at delivery in 753 participants, were analyzed for 28 human papillomavirus genotypes, including 12 high-risk genotypes. Participants completed electronic questionnaires at enrollment and medical records were reviewed for background characteristics and for the following adverse pregnancy outcomes: hypertensive disorders of pregnancy including gestational hypertension, preeclampsia, superimposed preeclampsia, eclampsia and Hemolysis Elevated Liver enzymes and Low Platelets (HELLP) syndrome, gestational diabetes mellitus, and newborns small for gestational age. Associations between adverse pregnancy outcomes and a) any human papillomavirus, high-risk human papillomavirus and human papillomavirus genotype 16 infection at mid-gestation, b) multiple genotype infections at mid-gestation, and c) persisting infections during pregnancy were assessed with univariable and multivariable logistic regression models. Missing covariates were imputed using multiple imputation. RESULTS At mid-gestation, 40% (377/950) of women were positive for any of the 28 genotypes, 24% (231/950) for high-risk genotypes and human papillomavirus 16 was found in 6% (59/950) of the women. Hypertensive disorders of pregnancy was observed in 9% (83/950), gestational diabetes mellitus in 4% (40/950) and newborns small for gestational age in 7% (67/950). Human papillomavirus infection with any genotype, high-risk or human papillomavirus genotype 16 at mid-gestation was not associated with adverse pregnancy outcomes. No associations were found for multiple genotype infections at mid-gestation or persisting infections. CONCLUSION In a general population of pregnant women, we found no evidence of human papillomavirus infections during pregnancy being associated with hypertensive disorders of pregnancy, gestational diabetes mellitus, or newborns small for gestational age. TRIAL REGISTRATION The study is registered at ClincialTrials.gov; NCT02449850 on May 19 th , 2015. Human papillomavirus and pregnancy Placental dysfunction syndromes Hypertensive disorders of pregnancy Gestational diabetes mellitus Small for gestational age Figures Figure 1 Figure 2 Figure 3 Figure 4 INTRODUCTION The role of human papillomaviruses (HPVs) for human health has been extensively investigated. Its etiological role in cervical dysplasia is well established (1), while associations with adverse pregnancy outcomes are less clear (2–4). The prevalence of HPV infections peaks during the childbearing years of women, hence being the most common sexually transmitted infection. Several studies have demonstrated the presence of HPV in the placenta, specifically in trophoblast cells (5–7). Further, human papillomavirus has been shown to replicate in cultivated trophoblasts (5–9). In addition to this, HPV reduces adhesion and migratory properties as well as the number of trophoblast cells (8, 10). As extracellular trophoblast invasion is crucial for placentation and subsequent placental function, it is important to assess whether obstetric syndromes that are mediated by placental dysfunction are more prevalent in pregnancies affected by HPV infection. As HPV has been detected in first trimester placentae (5, 11, 12), HPV infection could potentially lead to placental dysfunction and thereby adverse pregnancy outcomes. Hypertensive disorders of pregnancy (HDP) include gestational hypertension (GH), preeclampsia, superimposed preeclampsia, eclampsia and Hemolysis Elevated Liver enzymes and Low Platelets (HELLP) syndrome. These disorders are closely linked to placental dysfunction and represent major causes of maternal and perinatal mortality and morbidity as well as increased risk of long-term cardiovascular disease in both mother and offspring (13–19). Gestational diabetes mellitus (GDM), also linked to placental dysfunction, increases the risk for additional adverse pregnancy outcomes, and neonatal adverse outcomes (20, 21). Women with GDM have an increased risk for developing postpartum diabetes mellitus type II, and long-term cardiovascular disease (17, 22). Small for gestational age (SGA) represents a proxy for fetal growth restriction, also representing a clinical feature of placental dysfunction (23). Newborns born SGA are at risk for both short- and long-term health complications (17). Research on adverse pregnancy outcomes and HPV infections has mainly focused on miscarriage or preterm delivery and to a lesser degree on adverse outcomes linked to placental dysfunction. An association between HPV and HDP, or SGA has been reported by some studies (4, 24–26), however, others find no association (27–29). Overall, studies are inconclusive and incomparable, due to differing methodologies, non-uniform definitions of adverse outcomes, and small sample sizes. Some studies are retrospective or data-linkage studies (25, 26, 28, 29), and some use abnormal Papanicolaou (PAP) smears as a proxy for HPV infections (25, 26, 29). A review and meta-analysis by Niyibizi et.al, concluded that many studies are of poor quality and further investigations are necessary (24). Using internationally recognized definitions for HDP, GDM and SGA in a prospective cohort of pregnant women from the mother-child PreventADALL (Preventing Atopic Dermatitis and Allergies in children) study (30), we aimed to investigate whether HPV infections during pregnancy were associated with adverse pregnancy outcomes linked to placental dysfunction. MATERIALS AND METHODS The present study is a multi-center prospective mother-child cohort study and a sub-study of the PreventADALL study, aiming to investigate early life interventions as a possible prevention for allergic diseases as well as to identify early life factors associated with non-communicable diseases (NCD) (30). Participants in the PreventADALL study were recruited from December 2014 to October 2016 and enrolled at Oslo University Hospital and Østfold Hospital Trust (Norway), as well as Karolinska Institute, Stockholm (Sweden) (30). Briefly, pregnant women from the general population were invited to participate in the study at the time of their second trimester routine ultrasound examination, excluding women who were not proficient in Norwegian or Swedish, were pregnant with more than two fetuses or had a severely diseased fetus. Women were asked to complete comprehensive electronic (e-) questionnaires at gestational weeks (GW) 18 and 34. Further study details are described elsewhere (3, 30). Of the 2701 pregnancies included, twin pregnancies (n=12) were excluded, and in the case of women participating with two separate pregnancies (n=4), the pregnancy with a urine sample with a valid HPV result at mid-gestation and delivery was included in the analyses. If both pregnancies had valid urine samples, the first pregnancy was selected. Women missing all adverse pregnancy outcome data were excluded, yielding 950 women that provided urine samples with a valid HPV result at the time of enrollment (GW16-22, mid-gestation), of whom 753 women had urine samples with valid HPV result at both mid-gestation and delivery (Figure 1). Pregnancy outcomes were recorded through medical chart revision in Norway and from birth registries in Sweden (31, 32). Women were asked to provide first-void urine samples at mid-gestation and delivery. Urine was collected and kept frozen at -80°C until analysis. Detection and genotyping of HPV DNA was performed using the Seegene Anyplex II HPV28 detection polymerase chain reaction (PCR) assay (Seegene Inc, Seoul, South Korea). Detailed description of urine handling and analysis has previously been described (3). Seegene Anyplex II HPV28 kit detects and genotypes 28 genital HPV genotypes, defined as Any-HPV group (HPV16, 18, 31, 33, 35, 39, 45, 51, 52, 56, 58, 59, 26, 53, 66, 68, 69, 70, 73, 82, 6, 11, 40, 42, 43, 44, 54, 61). Human papillomavirus genotypes were further subclassified according to their malignant potential, as high-risk (HR-) HPV (HR-HPV16, 18, 31, 33, 35, 39, 45, 51, 52, 56, 58, 59), according to the International Agency of Research on Cancer. Analyses were also performed with HPV16, which has the highest malignant potential (33, 34). Adverse pregnancy outcomes were defined as: 1) Hypertensive disorders of pregnancy including: a. Gestational hypertension: new-onset hypertension (systolic blood pressure ≥140mmHg and/or diastolic blood pressure ≥90mmHg) occurring from or after GW 20, without proteinuria. b. Preeclampsia: gestational hypertension with new-onset proteinuria c. Superimposed preeclampsia: chronic hypertension with new onset of proteinuria after GW 20. d. Eclampsia: General tonic clonic seizures occurring in women with preeclampsia. e. HELLP syndrome: defined according to clinical guidelines and based on blood analyses (32). Hypertensive disorders of pregnancy subgroups were defined according to the commonly used definitions at the time of study recruitment (2014-16) (32), and did in our study not include women with preexisting hypertension or hypertension diagnosed prior to GW 20 (chronic hypertension). 2) Gestational diabetes mellitus, defined as glucose intolerance diagnosed during pregnancy (22), was laboratory-wise defined according to clinical guidelines relevant at the time of study inclusion (2014-16). An oral glucose intolerance test with 75g oral glucose was administered and an overnight fasting glucose level <7.0mmol/L and 2 hours glucose level ≥7.8 (but <11.1mmol/L) confirmed a GDM diagnosis (35). 3) Newborns small for gestational age were defined as birthweight below the 10 th percentile for gestational age, stratified according to sex (36). Exposures were detection of Any-HPV, HR-HPV, HPV16 infection or multiple infections at mid-gestation, as well as genotype specific persistence of Any-HPV, HR-HPV or HPV16 from mid-gestation to delivery. We defined three groups of multiple HPV infections: 1) Multiple infections with Any-HPV defined as having ≥2 different HPV genotypes. 2) Multiple infections with HR-HPV defined as having ≥2 different HPVs, with at least one HR-HPV genotype. 3) Multiple HPV16 infections defined as having HPV16 with any other genotype. Persistence of Any-HPV, HR-HPV or HPV16 infection during pregnancy was defined as having the same genotype-specific HPV infection at mid-gestation and delivery. This definition was based on the long clearance time of HPV and the low probability of a woman engaging with a new sexual partner during her late pregnancy, thus contracting a new HPV infection of the same genotype as at mid-gestation. Possible confounding factors were collected from e-questionnaires including maternal age at enrollment, pre-pregnancy body mass index (ppBMI), duration of pre-conception relation with the child’s father (5 years), parity (0, 1 or ≥2), nicotine use during pregnancy (yes or no), alcohol consumption during pregnancy (yes or no), maternal chronic disease including chronic hypertension and pregestational diabetes mellitus (yes or no) and maternal educational level (preliminary/high school only, higher education ≤4 years or higher education/PhD >4 years). Statistical analyses Categorical variables are presented with numbers and percentages and continuous variables as means with standard deviations (SD) or medians with minimum and maximum values. Univariable and multivariable logistic regression models were used to investigate the association between Any-HPV, HR-HPV, HPV16 or multiple HPV infection at mid-gestation as well as persistent infection of Any-HPV, HR-HPV or HPV16 and adverse pregnancy outcomes. We ran separate models for each exposure variable and each of the three outcomes. Multivariable regression models were adjusted for potential confounders based on three directed acyclic graphs (37) (DAGs; Figures 2-4). In cases where cells contained < 5, univariable exact logistic regression models were done. The multivariable exact logistic regression models did not converge therefore multivariable logistic regression models were performed. Missing covariate values added up to 13-16% and were imputed using multiple imputation with chained equations and 40 data sets were imputed. Statistical analyses were performed using IBM© SPSS© statistics version 28 (Chicago, IL, U.S.A) or Stata version 16 (StataCorp LLC, College Station, Texas). A P-value <0.05 was considered statistically significant. RESULTS At the time of enrollment, the mean age of the baseline sample (N = 950) was 32.0 (SD = 4.6) years and median ppBMI 24.5 kg/m 2 (min-max: 17.8–48.2). Most women were married, 87% (825/950) with 52% (498/950) of the women in a relationship lasting 5 years or longer. Most women were expecting their first child, 55% (518/950). Mean gestational age at delivery was 40.1 weeks (SD = 1.5) and mean birthweight 3592 g (SD = 491.1; Table 1 ). No major differences were observed between the baseline sample (N = 950) and nonparticipants (N = 1748; Table 1 ). Table 1 Maternal characteristics for women in baseline sample (N = 950) and nonparticipants (N = 1748). Total n. 950 HR-HPV a positive n. 231 HR-HPV a negative n. 719 Any-HPV b positive n. 377 Any-HPV b negative n. 573 Nonparticipants from PreventADALL study n. 1748 Maternal Age, yr. Mean (SD) 32.0 (4.6) 31.3 (4.6) 32.3 (4.3) 31.7 (4.6) 32.2 (4.2) 32.5 (4.0) Maternal ppBMI. Median (min-max) 24.5 (17.8–48.2) 24.7 (18.7–38.9) 24.5 (17.8–48.2) 24.7 (18.4–39.3) 24.4 (17.8–48.2) 23.9 (17.2–44.2) Marital Status. n (%) Married/cohabitants 825 (87%) 199 (96%) 626 (99%) 322 (96%) 503 (99%) 1465 (84%) Single/Divorced/Other 17 (18%) 9 (4%) 8 (1%) 13 (4%) 4 (1%) 50 (3%) Missing 108 233 Maternal education. n (%) Preliminary/high school only 141 (15%) 47 (23%) 94 (15%) 72 (22%) 69 (14%) 118 (7%) Higher education ≤ 4 years 295 (31%) 69 (34%) 226 (36%) 112 (24%) 183 (36%) 462 (26%) Higher/PhD/> 4 years 400 (42%) 89 (43%) 311 (49%) 148 (45%) 252 (50%) 923 (53%) Missing 114 245 Duration of pre-conception relation with child’s father, yr. n (%) 5 498 (52%) 71 (38%) 427 (70%) 141 (45%) 357 (73%) 806 (46%) Missing 148 292 Nicotine use during pregnancy. n (%) No 740 (78%) 176 (85%) 564 (89%) 289 (86%) 451 (89%) 1327 (76%) Yes 100 (11%) 31 (15%) 69 (11%) 45 (14%) 55 (11%) 179 (10%) Missing 110 242 Alcohol consumption during pregnancy. n (%) No 591 (62%) 134 (65%) 457 (73%) 224 (67%) 367 (73%) 919 (53%) Yes 245 (26%) 72 (35%) 173 (27%) 109 (33%) 136 (27%) 582 (33%) Missing 114 247 Number of previous deliveries (Parity). n (%) 0 518 (55%) 161 (70%) 357 (50%) 234 (62%) 284 (50%) 1075 (62%) 1 321 (34%) 55 (24%) 266 (37%) 111 (30%) 210 (37%) 539 (31%) ≥2 109 (11%) 15 (6%) 94 (13%) 31 (8%) 78 (14%) 128 (7%) Missing 2 6 Gestational age at birth, weeks. Mean (SD) 40.1 (1.5) 40.1 (1.4) 40.1 (1.5) 40.1 (1.3) 40.0 (1.5) 39.9 (1.8) Fetal sex. n (%) Male 495 (52%) 115 (50%) 380 (53%) 185 (49%) 310 (54%) 916 (52%) Female 454 (48%) 116 (50%) 338 (47%) 191 (51%) 263 (46%) 811 (46%) Missing 1 21 Birthweight, g. Mean (SD) 3591.8 (491.1) 3588.2 (468.1) 3574.0 (507.5) 3576.8 (453.0) 3577.8 (525.5) 3517.5 (559.0) Blood pressure, mmHg. Mean (SD) Early pregnancy sBP (at inclusion) 110.3 (10.7) 110.6 (10.6) 110.4 (11.2) 110.3 (10.8) 110.5 (11.2) 107.9 (9.6) Early pregnancy dBP (at inclusion) 63.1 (7.8) 63.4 (8.4) 63.6 (8.2) 62.8 (8.2) 64.0 (8.2) 61.0 (6.4) Late pregnancy sBP (up to two weeks prior to delivery) 119.5 (12. 8) 120.5 (12.1) 119.1 (13.0) 119.0 (12.5) 119.7 (13.0) 120.4 (13.7) Late pregnancy dBP (up to two weeks prior to delivery) 75.7 (9.8) 76.8 (9.7) 75.3 (9.8) 75.4 (9.8) 75.8 (9.8) 76.1 (9.6) Maternal chronic disease (including chronic hypertension and pregest. diabetes mellitus). n (%) No 652 (69%) 153 (66%) 499 (69%) 258 (68%) 394 (69%) 1197 (69%) Yes 298 (31%) 78 (34%) 220 (31%) 119 (32%) 179 (31%) 551 (31%) a HR-HPV: 16, 18, 31, 33, 35, 39, 45, 51, 52, 56, 58, 59 b Any-HPV: 16, 18, 31, 33, 35, 39, 45, 51, 52, 56, 58, 59, 26, 53, 66, 68, 69, 70, 73, 82, 6, 11, 40, 42, 43, 44, 54, 61 Abbreviations: yr- years, SD- standard deviation, ppBMI- pre-pregnancy Body Mass Index, min-minimum, max-maximum, sBP-systolic blood pressure, dBP-diastolic blood pressure, g-grams. Pregest-pregestational. In the baseline sample, 40% (377/950) were infected with Any-HPV whereas 24% (231/950) had an infection with HR-HPV. The most common single HPV genotype was HPV16 with 6% (59/950). Persistence of Any-HPV was 52% (152/290) and 52% (93/178) for HR-HPV whilst 64% (29/45) of HPV16 infections persisted until delivery. At the time of delivery, 9% (83/950) of the women were diagnosed with HDP (chronic hypertension not included). Gestational hypertension, diagnosed in 4% (42/950), was the most common HDP, followed by preeclampsia, 2% (19/950). None of the women developed eclampsia. Hypertensive disorders of pregnancy were observed in 7% (26/377) of women infected with Any-HPV and 8% (19/231) in women with HR-HPV at mid-gestation. In adjusted logistic regression analyses HDP was observed less often amongst women with Any-HPV infection at mid-gestation (adjusted odds ratio (aOR) 0.55, 95% confidence interval (CI) 0.32–0.93, p = 0.024), compared to women without infections; HR-HPV infections were not associated with HDP (aOR = 0.79, 95% CI 0.45–1.41, p = 0.427); Table 2 ). No associations were found in adjusted regression models for HPV16, multiple HPV infections at mid-gestation or persistent infections and HDP (Table 2 – 4 , Supplementary Table 1). Table 2 HPV infection at mid-gestation and adverse pregnancy outcomes. HYPERTENSIVE DISORDERS OF PREGNANCY Results from complete case analysis (N = 731) Results from imputed analysis (N = 942) N = 942 a HPV positive HDP b case (HPV pos/neg) N = 83 Crude OR (95% CI) p-value aOR c (95% CI) p-value Imputed aOR d (95% CI) p-value Any-HPV e 375 26/57 0.67 (0.41–1.08) 0.100 0.67 (0.35–1.31) 0.242 0.55 (0.32–0.93) 0.024 HR-HPV f 231 19/64 0.91 (0.53–1.55) 0.718 0.83 (0.40–1.72) 0.621 0.79 (0.45–1.41) 0.427 HPV16 59 5/78 0.97 (0.29–2.50) 1.000 0.81 (0.23–2.78) 0.732 0.85 (0.32–2.26) 0.747 GESTATIONAL DIABETES MELLITUS Results from complete case analysis (N = 883) Results from imputed analysis (N = 903) N = 903 a HPV positive GDM g case (HPV pos/neg) N = 40 Crude OR (95% CI) p-value aOR h (95% CI) p-value Imputed aOR i (95% CI) p-value Any-HPV e 355 12/28 0.65 (0.33–1.30) 0.221 0.57 (0.28–1.17) 0.127 0.56 (0.27–1.15) 0.114 HR-HPV f 218 8/32 0.78 (0.35–1.71) 0.532 0.76 (0.34–1.73) 0.517 0.77 (0.34–1.75) 0.528 HPV16 57 2/38 0.79 (0.09–3.19) 1.000 0.83 (0.19–3.65) 0.808 0.85 (0.20–3.74) 0.834 NEWBORNS SMALL FOR GESTATIONAL AGE Results from complete case analysis (N = 831) Results from imputed analysis (N = 949) N = 949 a HPV positive SGA j case (HPV pos/neg) N = 67 Crude OR (95% CI) p-value aOR k (95% CI) p-value Imputed aOR l (95% CI) p-value Any-HPV e 376 24/43 0.84 (0.50–1.41) 0.510 0.79 (0.44–1.42) 0.437 0.76 (0.45–1.29) 0.304 HR-HPV f 231 11/56 0.59 (0.30–1.15) 0.121 0.60 (0.29–1.24) 0.167 0.52 (0.26–1.02) 0.058 HPV16 59 2/65 0.45 (0.05–1.76) 0.392 0.45 (0.11–1.94) 0.287 0.36 (0.09–1.55) 0.171 a Eight women with missing HDP data, 47 women with missing GDM data and 1 woman with missing SGA data. b Hypertensive disorders of pregnancy, including gestational hypertension, superimposed preeclampsia, preeclampsia, eclampsia, Hemolysis, Elevated Liver enzymes, Low Platelets (HELLP). c Adjusted for: Duration of pre-pregnancy relation to child’s father, maternal age, pre-pregnancy Body Mass Index (ppBMI), parity, maternal chronic disease (including chronic hypertension and diabetes mellitus), maternal education. d Imputed variables: Maternal education, Duration of pre-pregnancy relation to child’s father, ppBMI. e HR-HPV: 16, 18, 31, 33, 35, 39, 45, 51, 52, 56, 58, 59 f Any-HPV: 16, 18, 31, 33, 35, 39, 45, 51, 52, 56, 58, 59, 26, 53, 66, 68, 69, 70, 73, 82, 6, 11, 40, 42, 43, 44, 54, 61 g GDM: Gestational Diabetes Mellitus. h Adjusted for: Maternal Age, ppBMI. i Imputed variables: ppBMI. j SGA-Newborns small for gestational age. k Adjusted for: Maternal chronic disease (including chronic hypertension and diabetes mellitus), nicotine use during pregnancy, alcohol consumption during pregnancy, maternal age. maternal education. l Imputed variables: Maternal education, nicotine use during pregnancy, alcohol consumption during pregnancy Abbreviations: HPV-Human papillomavirus, HR-HPV-High-Risk Human papillomavirus, OR-Odds Ratio, aOR-adjusted Odds Ratio, pos-positive, neg-negative. Table 3 Multiple HPV infection at mid-gestation and adverse pregnancy outcomes. HYPERTENSIVE DISORDERS OF PREGNANCY Results from complete case analysis (N = 731) Results from imputed analysis (N = 942) N = 942 a HPV positive HDP b case (HPV pos/neg) N = 83 Crude OR (95% CI) p-value aOR c (95% CI) p-value Imputed aOR d (95% CI) p-value Any-HPV e + Any-HPV 171 15/68 0.99 (0.55–1.79) 0.984 0.73 (0.32–1.68) 0.454 0.78 (0.41–1.50) 0.456 HR-HPV f + Any-HPV 139 14/69 1.19 (0.65–2.18) 0.570 0.84 (0.36-2.00) 0.696 0.96 (0.49–1.84) 0.892 HPV16 + Any-HPV 38 4/79 1.24 (0.31–3.61) 0.857 1.38 (0.380–4.98) 0.627 1.04 (0.34–3.16) 0.942 GESTATIONAL DIABETES MELLITUS Results from complete case analysis (N = 883) Results from imputed analysis (N = 903) N = 903 a HPV positive GDM g case (HPV pos/neg) N = 40 Crude OR (95% CI) p-value aOR h (95% CI) p-value Imputed aOR i (95% CI) p-value Any-HPV f + Any-HPV 162 6/34 0.80 (0.33–1.94) 0.621 0.68 (0.27–1.71) 0.409 0.68 (0.27–1.72) 0.417 HR-HPV g + Any-HPV 130 5/35 0.83 (0.25–2.17) 0.912 0.72 (0.26–1.94) 0.510 0.73 (0.27–1.97) 0.533 HPV16 + Any-HPV 36 2/38 1.28 (0.14–5.29) 0.966 1.39 (0.31–6.28) 0.670 1.42 (0.32–6.43) 0.647 NEWBORNS SMALL FOR GESTATIONAL AGE Results from complete case analysis (N = 831) Results from imputed analysis (N = 949) N = 949 a HPV positive SGA j case (HPV pos/neg) N = 67 Crude OR (95% CI) p-value aOR k (95% CI) p-value Imputed aOR l (95% CI) p-value Any-HPV f + Any-HPV 171 12/55 0.99 (0.52–1.90) 0.981 1.07 (0.52–2.15) 0.869 0.87 (0.45–1.69) 0.677 HR-HPV g + Any-HPV 139 8/59 0.78 (0.36–1.66) 0.517 0.77 (0.33–1.77) 0.531 0.67 (0.31–1.45) 0.308 HPV16 + Any-HPV 38 1/66 0.35 (0.01–2.13) 0.470 0.37 (0.05–2.78) 0.331 0.28 (0.04–2.08) 0.212 a Eight women with missing HDP data, 47 women with missing GDM data and 1 woman with missing SGA data. b Hypertensive disorders of pregnancy, including gestational hypertension, superimposed preeclampsia, preeclampsia, eclampsia, Hemolysis, Elevated Liver enzymes, Low Platelets (HELLP). c Adjusted for: Duration of pre-pregnancy relation to child’s father, maternal age, pre-pregnancy Body Mass Index (ppBMI), parity, maternal chronic disease (including chronic hypertension and diabetes mellitus), maternal education. d Imputed variables: Maternal education, Duration of pre-pregnancy relation to child’s father, ppBMI. e HR-HPV: 16, 18, 31, 33, 35, 39, 45, 51, 52, 56, 58, 59 f Any-HPV: 16, 18, 31, 33, 35, 39, 45, 51, 52, 56, 58, 59, 26, 53, 66, 68, 69, 70, 73, 82, 6, 11, 40, 42, 43, 44, 54, 61 g GDM: Gestational Diabetes Mellitus. h Adjusted for: Maternal Age, ppBMI. i Imputed variables: ppBMI. j SGA-Newborns small for gestational age. k Adjusted for: Maternal chronic disease (including chronic hypertension and diabetes mellitus), nicotine use during pregnancy, alcohol consumption during pregnancy, maternal age. maternal education. l Imputed variables: Maternal education, nicotine use during pregnancy, alcohol consumption during pregnancy Abbreviations: HPV-Human papillomavirus, HR-HPV-High-Risk Human papillomavirus, OR-Odds Ratio, aOR-adjusted Odds Ratio, pos-positive, neg-negative. Table 4 Persistent HPV infection from mid-gestation to delivery and adverse pregnancy outcomes. HYPERTENSIVE DISORDERS OF PREGNANCY a Results from complete case analysis Results from imputed analysis HPV pos. at mid-gestation HPV persistent HDP b case (HPV pos/neg) Crude OR (95% CI) p-value aOR c (95% CI) p-value Imputed aOR d (95% CI) p-value Any-HPV e N = 290 152 11/9 1.12 (0.45–2.79) 0.810 0.95 (0.27–3.32) 0.933 0.99 (0.36–2.73) 0.977 HR-HPV f N = 178 93 10/5 1.92 (0.63–5.89) 0.249 3.39 (0.58–19.79) 0.175 1.96 (0.54–7.12) 0.308 HPV16 N = 45 29 3/0 GESTATIONAL DIABETES MELLITUS Results from complete case analysis Results from imputed analysis HPV pos. at mid-gestation HPV persistent GDM g case (HPV pos/neg) Crude OR (95% CI) p-value aOR h (95% CI) p-value Imputed aOR i (95% CI) p-value Any-HPV e N = 271 143 3/3 0.91 (0.12–6.88) 1.000 0.81 (0.16–4.27) 0.801 0.81 (0.15–4.26) 0.799 HR-HPV f N = 166 88 2/3 1.38 (0.15–16.91) 1.000 1.18 (0.19–7.69) 0.866 1.19 (0.18–7.79) 0.853 HPV16 N = 45 29 0 - - - - NEWBORNS SMALL FOR GESTATIONAL AGE Results from complete case analysis Results from imputed analysis HPV pos. at mid-gestation HPV persistent SGA k case (HPV pos/neg) Crude OR (95% CI) p-value aOR l (95% CI) p-value Imputed aOR m (95% CI) p-value Any-HPV e N = 290 152 10/7 1.32 (0.48–3.56) 0.586 1.26 (0.42–3.73) 0.681 1.20 (0.44–3.34) 0.722 HR-HPV f N = 178 93 3/5 0.53 (0.12–2.30) 0.400 0.51 (0.10–2.59) 0.417 0.49 (0.11–2.24) 0.356 HPV16 N = 45 29 2/0 - - - - a Five women with missing HDP data and 42 women with missing GDM data. b Hypertensive disorders of pregnancy, including gestational hypertension, superimposed preeclampsia, preeclampsia, eclampsia, Hemolysis, Elevated Liver enzymes, Low Platelets (HELLP). c Adjusted for: Duration of pre-pregnancy relation to child’s father, maternal age, pre-pregnancy Body Mass Index (ppBMI), parity, maternal chronic disease (including chronic hypertension and diabetes mellitus), maternal education. d Imputed variables: Maternal education, Duration of pre-pregnancy relation to child’s father, ppBMI. e Any-HPV: 16, 18, 31, 33, 35, 39, 45, 51, 52, 56, 58, 59, 26, 53, 66, 68, 69, 70, 73, 82, 6, 11, 40, 42, 43, 44, 54, 61 f HR-HPV: 16, 18, 31, 33, 35, 39, 45, 51, 52, 56, 58, 59 g GDM: Gestational Diabetes Mellitus. h Adjusted for: Maternal Age, ppBMI. i Imputed variables: ppBMI. j ∞Infinite value k SGA-Newborns small for gestational age. l Adjusted for: Maternal chronic disease (including chronic hypertension and diabetes mellitus), nicotine use during pregnancy, alcohol consumption during pregnancy, maternal age. maternal education. m Imputed variables: Maternal education, nicotine use during pregnancy, alcohol consumption during pregnancy Abbreviations: HPV-Human papillomavirus, HR-HPV-High-Risk Human papillomavirus, OR-Odds Ratio, aOR-adjusted Odds Ratio, pos-positive, neg-negative. n Fisher’s Exact Test Four percent (40/950) of the women were diagnosed with GDM. The prevalence of GDM in women with Any-HPV was 3% (12/377) and 3% (8/231) in women with HR-HPV. We found no statistically significant association between Any-HPV infections or HR-HPV infections at mid-gestation and GDM in the adjusted regression models (aOR = 0.56, 95% CI 0.27–1.15, p = 0.114 and aOR = 0.77, 95% CI 0.34–1.75, p = 0.528, respectively; Table 2 ). No statistically significant associations were found for HPV16, multiple HPV infections at mid-gestation and persistent infections and GDM (Table 2 – 4 , Supplementary Table 1). Overall, 7% (67/950) of the newborns were SGA, while SGA was observed in 6% (24/377) in women with Any-HPV infection and in 5% (11/231) of women with HR-HPV infection. No statistically significant associations were found between Any-HPV infection or HR-HPV infection at mid-gestation and SGA in the adjusted regression analysis (aOR = 0.76, 95% CI 0.45–1.29, p = 0.304 and aOR = 0.52, 95% CI 0.26–1.02, p = 0.058, respectively; Table 2 ). No statistically significant associations were found for HPV16, multiple HPV infections at mid-gestation and persistent infections and SGA (Table 2 – 4 , Supplementary Table 1). DISCUSSION In this general population cohort of 950 pregnant women, the detection of Any-HPV, HR-HPV, HPV16 or multiple HPV infections at mid-gestation or persistent HPV infections during pregnancy was not associated with increased risk for hypertensive disorders of pregnancy, gestational diabetes mellitus, or newborns small for gestational age, in spite of a relatively high prevalence of HPV infections found during pregnancy. In our analyses we found no association between HPV infections and HDP, in line with several other studies (4, 8, 27–29). In contrast, McDonnold et al. who investigated 314 women with presumed HR-HPV infections at the time of entry to prenatal care, matched to 628 women with at least 2 negative consecutive PAP smears, found an association between HPV infections and preeclampsia. However, their study was retrospective, using abnormal PAP smear as a proxy for HR-HPV infections. Further HPV testing was performed on the same sample only if atypical squamous cells of undetermined significance (ASCUS) were found (25). The true HPV prevalence was not known as women with HPV infection and normal PAP smear were excluded in the exposure group. Our finding of no association between GDM and HPV infections is in line with other studies (25, 27, 28). Cho et al. surveyed 311 women in Korea six weeks postpartum and tested for 13 HR-HPV genotypes. However, as this was done six weeks after delivery, clearance of HPV infections might have occurred yielding fewer HPV positive women postpartum than during pregnancy (28). Pandey and colleagues however, used a prospective design, but in their sample size of 104 women, HPV was detected from condoms used on vaginal ultrasound probes during the first trimester, yielding uncertain results as all women with HPV may not have been identified and this method is yet to be validated (27). No association was seen between HPV infections and SGA, in line with several other studies (25, 27, 29). Ford et al. showed an association between HPV and SGA in a study using positive PAP smear 2 years prior to the index pregnancy as a proxy for HPV infection (26). Similar to the McDonnold study (25), the true HPV prevalence was not known for the current pregnancy. Comparability of our study to others is challenging, as Pandey et al. did not define SGA and McDonnold et al. did not record actual birthweight but rather ultrasound measurements (25, 27). A systematic review and meta-analysis from 2020 found an association between HPV infections during pregnancy and SGA (24). However, a true comparison to our present study is difficult as the definition of SGA in the included studies was either missing or varying, ranging from < 10% and < 5% in birthweight percentiles (24). This current study showed no evidence for increased risk of placental dysfunction disorders including hypertensive disorders of pregnancy, gestational diabetes mellitus or newborns small for gestational age in women with HPV infections compared to women without infections during pregnancy. These findings should be reassuring for pregnant women or women of childbearing age with a positive HPV-screening test result and normal cytology findings. In this study we have only investigated the association of HPV infections and adverse pregnancy outcomes, and not ongoing or previous abnormal cervical cytology due to HPV. This study utilized a prospective design and tested for the most common HPV genotypes at two time points during pregnancy enabling detection of longitudinal HPV infection throughout pregnancy. The effect estimates seem to show no associations, however due to the large uncertainty because of low numbers of HPV infections in women with adverse pregnancy outcomes and low prevalence of adverse pregnancy outcomes, results need to be interpreted carefully. There is a growing body of evidence showing that HPV infections during pregnancy do not affect pregnancy outcomes negatively (8, 27–29) including our present study. Girls who have received the HPV vaccine are now reaching childbearing age, and it will be of great interest to investigate whether the vaccine contributes to further lowering of adverse pregnancy outcomes. A strength of this study is the multi-center prospective and longitudinal cohort design. Pregnant women from the general population in Norway and Sweden were invited to participate and biological samples were collected at two time points during pregnancy, allowing a longitudinal HPV infection follow-up. Maternal characteristics were collected through detailed e-questionnaires and medical records. Urine samples were handled according to strict protocols, ensuring high quality samples. First-void urine samples have been shown to be adequate and reliable for detecting genital HPV infections (38, 39). A weakness of this study is the lack of data concerning HPV status prior to pregnancy and previous treatment for cervical dysplasia, as well as the HPV vaccine status of the women. However, due to their age, most women in the study were likely not vaccinated, as they were not eligible for the HPV vaccine through the childhood vaccine program starting 2009 in Norway and 2010 in Sweden. In addition to this, the first testing timepoint for HPV in this study was in the second trimester, thus HPV status during the first trimester is missing. In our study, we used SGA as a proxy for fetal growth restriction. The distinction between SGA and fetal growth restriction can only be made with ultrasound examinations during pregnancy (40). We may therefore have included constitutionally small infants amongst those with true placental pathology. Due to the design of this current study, women with miscarriages prior to enrollment at mid-gestation were excluded, preventing us from exploring the possible association between HPV infections and early miscarriage and leading to a potential selection bias when assessing adverse pregnancy outcomes (survival bias). CONCLUSION In a general population of pregnant women from Norway and Sweden, we found no evidence for an increased risk of adverse pregnancy outcomes linked to placental dysfunction in women with HPV infections during pregnancy, despite the high prevalence of HPV infections observed. Abbreviations HPV Human papillomavirus HR-HPV High-Risk Human papillomavirus HDP Hypertensive disorders of pregnancy GDM Gestational diabetes mellitus SGA Small for gestational age GW Gestational week CI Confidence interval aOR Adjusted odds ratio PreventADALL Preventing Atopic Dermatitis and ALLergies in children Declarations Ethical Approval Statement and consent to participate The PreventADALL study with the current sub-study was approved by the Regional Ethical Committee for Medical and Health Research in South-Eastern Norway (REC 2014/518 and REC 2017/1053) and in Sweden (2014/2242-31/4). All women included in the current study signed an informed consent form, with the opportunity to withdraw from the study at any time and without the need to disclose reason for withdrawal. Consent for publication Not applicable Availability of data The datasets used and/or analysed during the current study are available from the principal investigator in the PreventADALL study on reasonable request. Competing interest The authors report no conflict of interest. Funding The current substudy was funded by the South-Eastern Norway Regional Health Authority (2017023). The PreventADALL study was funded by the several funding bodies including: the South-Eastern Norway Regional Health Authority, the Norwegian Research Council, Oslo University Hospital, the University of Oslo, Health and Rehabilitation, Østfold Hospital Trust, the European Union (MeDALL project), by unrestricted grants from the Norwegian Association of Asthma and Allergy, the Kloster Foundation, Norwegian Society of Dermatology and Venerology, The Foundation for Healthcare and Allergy Research in Sweden -Vårdalstiftelsen, Swedish Asthma- and Allergy Association’s Research Foundation, The Swedish Research Council - the Initiative for Clinical Therapy Research, The Swedish Heart-Lung Foundation, SFO-V Karolinska University Hospital, Stockholm County Council (ALF-project), Forte, Swedish Order of Freemasons Foundation Barnhuset, The Sven Jerring Foundation, The Hesselman foundation, The Magnus Bergwall foundation, The Konsul Th C Bergh’s Foundation, The Swedish Society of Medicine, KI grants, The Cancer- and Allergy Foundation, The Pediatric Research Foundation at Astrid Lindgren Children's Hospital, The Samariten Foundation for Paediatric research. Author contributions MRV: Conceptualization, Methodology, Formal analysis, Investigation, Data Curation, Writing - Original Draft, Funding acquisition ACS: Conceptualization, Methodology, Writing - Review & Editing, Funding acquisition, Supervision, Project administration JW: Conceptualization, Methodology, Writing - Review & Editing, Investigation, Data Curation KS: Conceptualization, Methodology, Writing - Review & Editing, Funding acquisition, Supervision CSR: Methodology, Validation, Formal analysis, Writing - Review & Editing, Visualization MS: Writing - Review & Editing, Data Curation KCLC: Conceptualization, Methodology, Writing - Review & Editing, Funding acquisition, Supervision, Project administration BG: Writing - Review & Editing GH: Writing - Review & Editing, GH: Writing - Review & Editing KH: Writing - Review & Editing, Data Curation BN: Writing - Review & Editing, Project administration EMR: Conceptualization, Methodology, Writing - Review & Editing, Funding acquisition, Project administration KR, Professor: Writing - Review & Editing HOS: Conceptualization, Methodology, Writing - Review & Editing, Funding acquisition, Project administration BKS: Writing - Review & Editing, Data Curation CS: Writing - Review & Editing, RV: Formal analysis, Writing - Review & Editing CMJ: Conceptualization, Methodology, Writing - Review & Editing, Funding acquisition, Supervision, Project administration Acknowledgements We sincerely thank all study participants who have so kindly provided us with biological samples and background data for this study. We also want to thank all the healthcare workers that have contributed to facilitating the study by recruiting women, collecting biological samples, and meticulously collecting and cleaning the data. We especially want to thank our colleagues at Østfold Hospital Trust at the Centre of Laboratory Medicine and Department of Obstetrics and Gynecology. Camilla F NYSTRAND, Ms. PhD, Anbjørg RANGBERG, Ms. MSc, Yvonne SANDBERG, Ms. MSc, Sigrid SJELMO, Ms. MSc References Munoz N, Castellsague X, de Gonzalez AB, Gissmann L. Chapter 1: HPV in the etiology of human cancer. Vaccine. 2006;24 Suppl 3:S3/1-10. Wiik J, Nilsson S, Kärrberg C, Strander B, Jacobsson B, Sengpiel V. Associations of treated and untreated human papillomavirus infection with preterm delivery and neonatal mortality: A Swedish population-based study. PLoS Med. 2021;18(5):e1003641. Værnesbranden MR, Wiik J, Sjøborg K, Staff AC, Carlsen KCL, Haugen G, et al. 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Society for Maternal-Fetal Medicine Consult Series #52: Diagnosis and management of fetal growth restriction: (Replaces Clinical Guideline Number 3, April 2012). Am J Obstet Gynecol. 2020;223(4):B2-B17. Additional Declarations No competing interests reported. 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Oslo","correspondingAuthor":false,"prefix":"","firstName":"Anne","middleName":"Cathrine","lastName":"STAFF","suffix":""},{"id":366956994,"identity":"b2bb9477-9eca-4563-9cd3-94467d1008dc","order_by":2,"name":"Johanna WIIK","email":"","orcid":"","institution":"Gothenburg University","correspondingAuthor":false,"prefix":"","firstName":"Johanna","middleName":"","lastName":"WIIK","suffix":""},{"id":366956995,"identity":"9d5a5784-b840-499d-83f7-ffc626c9ca73","order_by":3,"name":"Katrine SJØBORG","email":"","orcid":"","institution":"Østfold Hospital Trust","correspondingAuthor":false,"prefix":"","firstName":"Katrine","middleName":"","lastName":"SJØBORG","suffix":""},{"id":366956996,"identity":"a4ec41b2-2e9d-4d69-8053-73c19896a53e","order_by":4,"name":"Corina S RUEEGG","email":"","orcid":"","institution":"Oslo University Hospital","correspondingAuthor":false,"prefix":"","firstName":"Corina","middleName":"S","lastName":"RUEEGG","suffix":""},{"id":366956997,"identity":"e81749d5-531e-4cca-9d09-f83319a86d4c","order_by":5,"name":"Meryam SUGULLE","email":"","orcid":"","institution":"Oslo University Hospital","correspondingAuthor":false,"prefix":"","firstName":"Meryam","middleName":"","lastName":"SUGULLE","suffix":""},{"id":366956999,"identity":"63b6e5dd-bfec-4e90-9a14-7677b1c790f5","order_by":6,"name":"Karin C LØDRUP CARLSEN","email":"","orcid":"","institution":"University of Oslo","correspondingAuthor":false,"prefix":"","firstName":"Karin","middleName":"C LØDRUP","lastName":"CARLSEN","suffix":""},{"id":366957000,"identity":"74c7699e-5ae6-4c39-b0f4-e76a7be20941","order_by":7,"name":"Berit GRANUM","email":"","orcid":"","institution":"Norwegian Institute of Public 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Sciences","correspondingAuthor":false,"prefix":"","firstName":"Knut","middleName":"","lastName":"RUDI","suffix":""},{"id":366957010,"identity":"de823dd3-b357-4f09-b8be-a16c71309283","order_by":14,"name":"Håvard O SKJERVEN","email":"","orcid":"","institution":"Oslo University Hospital","correspondingAuthor":false,"prefix":"","firstName":"Håvard","middleName":"O","lastName":"SKJERVEN","suffix":""},{"id":366957012,"identity":"585f4539-5c95-4710-ad58-2678125468fe","order_by":15,"name":"Birgitte K SUNDET","email":"","orcid":"","institution":"University of Oslo","correspondingAuthor":false,"prefix":"","firstName":"Birgitte","middleName":"K","lastName":"SUNDET","suffix":""},{"id":366957013,"identity":"ca4a240f-f1ec-40b4-8283-8d05cc519203","order_by":16,"name":"Cilla SÖDERHÄLL","email":"","orcid":"","institution":"Astrid Lindgren Children’s Hospital, Karolinska University Hospital","correspondingAuthor":false,"prefix":"","firstName":"Cilla","middleName":"","lastName":"SÖDERHÄLL","suffix":""},{"id":366957015,"identity":"6482be3d-c340-4a79-b532-f4b978ffcae9","order_by":17,"name":"Riyas VETTUKATTIL","email":"","orcid":"","institution":"University of Oslo","correspondingAuthor":false,"prefix":"","firstName":"Riyas","middleName":"","lastName":"VETTUKATTIL","suffix":""},{"id":366957018,"identity":"bf495992-0cee-4e30-af66-3485d4e52b30","order_by":18,"name":"Christine M JONASSEN","email":"","orcid":"","institution":"Østfold Hospital Trust","correspondingAuthor":false,"prefix":"","firstName":"Christine","middleName":"M","lastName":"JONASSEN","suffix":""}],"badges":[],"createdAt":"2024-09-18 08:48:34","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5108443/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5108443/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12884-024-06958-2","type":"published","date":"2024-11-19T15:57:31+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":68529919,"identity":"49a9c66f-0555-4b6c-8aea-5f3baee6fabc","added_by":"auto","created_at":"2024-11-08 09:04:48","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":29444,"visible":true,"origin":"","legend":"\u003cp\u003eFlow chart of enrolled women in the current study.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-5108443/v1/168518590293f5378b84d4e2.png"},{"id":68529924,"identity":"a2d64f93-8757-41b4-9985-f710e9f755ce","added_by":"auto","created_at":"2024-11-08 09:04:48","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":366200,"visible":true,"origin":"","legend":"\u003cp\u003eDirected acyclic graph of covariates of hypertensive disorders of pregnancy.\u003c/p\u003e\n\u003cp\u003eAbbreviations: HDP- hypertensive disorders of pregnancy, HPV-human papillomavirus, Mat.edu-maternal education, Mat.chornic dis.-maternal chronic disease, including chronic hypertension and pregestational diabetes mellitus, Mat.pre-preg.BMI- maternal pre-pregnancy Body Mass Index, Mat.age-maternal age, preg-pregnancy. Color explanation: green with arrow-exposure, blue with l- outcome of interest, green- ancestor (covariate) of exposure, blue- ancestor of outcome, pink-covariates needed for the adjustment analyses.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-5108443/v1/ca481eb10e3ccc10ef62b80c.png"},{"id":68529921,"identity":"1a5133e8-ddb7-4dc3-8a27-b21c2628daf2","added_by":"auto","created_at":"2024-11-08 09:04:48","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":114558,"visible":true,"origin":"","legend":"\u003cp\u003eDirected acyclic graph of covariates for gestational diabetes mellitus.\u003c/p\u003e\n\u003cp\u003eAbbreviations: GDM-gestational diabetes mellitus, HPV-human papillomavirus, Mat.pre-preg.BMI- maternal pre-pregnancy Body Mass Index, Mat.age-maternal age. Color explanation: green with arrow-exposure, blue with l- outcome of interest, pink-covariates needed for the adjustment analyses, grey- other variable.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-5108443/v1/7b9107790555a925e1352389.png"},{"id":68531487,"identity":"f307cb63-f838-47bb-8ae6-1ea1eafd1ec3","added_by":"auto","created_at":"2024-11-08 09:12:48","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":308621,"visible":true,"origin":"","legend":"\u003cp\u003eDirected acyclic graph of covariates of newborn small of gestational age.\u003c/p\u003e\n\u003cp\u003eAbbreviations: SGA- newborn of small gestational age, HPV-human papillomavirus, Mat.edu-maternal education, Mat.chornic dis.-maternal chronic disease, including chronic hypertension and pregestational diabetes mellitus, Mat.age-maternal age, preg-pregnancy, HDP- hypertensive disorders of pregnancy. Color explanation: green with arrow-exposure, blue with l- outcome of interest, blue- ancestor (covariate) of outcome, pink-covariates needed for the adjustment analyses.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-5108443/v1/20b2c02773be642c6a434f71.png"},{"id":69834874,"identity":"cc3fb0dd-8bbd-4a90-8444-45e9144fcf2a","added_by":"auto","created_at":"2024-11-25 16:09:50","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1725894,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5108443/v1/a4ad4194-b289-4fa5-b005-51b020b72b68.pdf"},{"id":68531486,"identity":"1efdde0f-5769-4be3-bf20-65c6d4f6eab5","added_by":"auto","created_at":"2024-11-08 09:12:48","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":25330,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementary.Table.Vrnesbranden.docx","url":"https://assets-eu.researchsquare.com/files/rs-5108443/v1/71d755e2655b37242e44a930.docx"},{"id":68529922,"identity":"7a770c45-6733-41e6-896c-fca9eda76bd1","added_by":"auto","created_at":"2024-11-08 09:04:48","extension":"png","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":120861,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eGraphical abstract\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"GraphicalAbstract.png","url":"https://assets-eu.researchsquare.com/files/rs-5108443/v1/61d623cab964d3bf94c27c08.png"}],"financialInterests":"No competing interests reported.","formattedTitle":"Human Papillomavirus Infections during Pregnancy and Adverse Pregnancy Outcomes: a Prospective Mother-Child Cohort Study","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eThe role of human papillomaviruses (HPVs) for human health has been extensively investigated. Its etiological role in cervical dysplasia is well established (1), while associations with adverse pregnancy outcomes are less clear (2\u0026ndash;4). The prevalence of HPV infections peaks during the childbearing years of women, hence being the most common sexually transmitted infection. Several studies have demonstrated the presence of HPV in the placenta, specifically in trophoblast cells (5\u0026ndash;7). Further, human papillomavirus has been shown to replicate in cultivated trophoblasts (5\u0026ndash;9). In addition to this, HPV reduces adhesion and migratory properties as well as the number of trophoblast cells (8, 10). As extracellular trophoblast invasion is crucial for placentation and subsequent placental function, it is important to assess whether obstetric syndromes that are mediated by placental dysfunction are more prevalent in pregnancies affected by HPV infection. As HPV has been detected in first trimester placentae (5, 11, 12), HPV infection could potentially lead to placental dysfunction and thereby adverse pregnancy outcomes.\u003c/p\u003e \u003cp\u003eHypertensive disorders of pregnancy (HDP) include gestational hypertension (GH), preeclampsia, superimposed preeclampsia, eclampsia and Hemolysis Elevated Liver enzymes and Low Platelets (HELLP) syndrome. These disorders are closely linked to placental dysfunction and represent major causes of maternal and perinatal mortality and morbidity as well as increased risk of long-term cardiovascular disease in both mother and offspring (13\u0026ndash;19). Gestational diabetes mellitus (GDM), also linked to placental dysfunction, increases the risk for additional adverse pregnancy outcomes, and neonatal adverse outcomes (20, 21). Women with GDM have an increased risk for developing postpartum diabetes mellitus type II, and long-term cardiovascular disease (17, 22). Small for gestational age (SGA) represents a proxy for fetal growth restriction, also representing a clinical feature of placental dysfunction (23). Newborns born SGA are at risk for both short- and long-term health complications (17).\u003c/p\u003e \u003cp\u003eResearch on adverse pregnancy outcomes and HPV infections has mainly focused on miscarriage or preterm delivery and to a lesser degree on adverse outcomes linked to placental dysfunction. An association between HPV and HDP, or SGA has been reported by some studies (4, 24\u0026ndash;26), however, others find no association (27\u0026ndash;29). Overall, studies are inconclusive and incomparable, due to differing methodologies, non-uniform definitions of adverse outcomes, and small sample sizes. Some studies are retrospective or data-linkage studies (25, 26, 28, 29), and some use abnormal Papanicolaou (PAP) smears as a proxy for HPV infections (25, 26, 29). A review and meta-analysis by Niyibizi et.al, concluded that many studies are of poor quality and further investigations are necessary (24).\u003c/p\u003e \u003cp\u003eUsing internationally recognized definitions for HDP, GDM and SGA in a prospective cohort of pregnant women from the mother-child PreventADALL (Preventing Atopic Dermatitis and Allergies in children) study (30), we aimed to investigate whether HPV infections during pregnancy were associated with adverse pregnancy outcomes linked to placental dysfunction.\u003c/p\u003e"},{"header":"MATERIALS AND METHODS","content":"\u003cp\u003eThe present study is a multi-center prospective mother-child cohort study and a sub-study of the PreventADALL study, aiming to investigate early life interventions as a possible prevention for allergic diseases as well as to identify early life factors associated with non-communicable diseases (NCD) (30). Participants in the PreventADALL study were recruited from December 2014 to October 2016 and enrolled at Oslo University Hospital and \u0026Oslash;stfold Hospital Trust (Norway), as well as Karolinska Institute, Stockholm (Sweden) (30). Briefly, pregnant women from the general population were invited to participate in the study at the time of their second trimester routine ultrasound examination, excluding women who were not proficient in Norwegian or Swedish, were pregnant with more than two fetuses or had a severely diseased fetus. Women were asked to complete comprehensive electronic\u003c/p\u003e\n\u003cp\u003e(e-) questionnaires at gestational weeks (GW) 18 and 34. Further study details are described elsewhere (3, 30).\u003c/p\u003e\n\u003cp\u003eOf the 2701 pregnancies included, twin pregnancies (n=12) were excluded, and in the case of women participating with two separate pregnancies (n=4), the pregnancy with a urine sample with a valid HPV result at mid-gestation and delivery was included in the analyses. If both pregnancies had valid urine samples, the first pregnancy was selected. Women missing all adverse pregnancy outcome data were excluded, yielding 950 women that provided urine samples with a valid HPV result at the time of enrollment (GW16-22, mid-gestation), of whom 753 women had urine samples with valid HPV result at both mid-gestation and delivery (Figure 1).\u003c/p\u003e\n\u003cp\u003ePregnancy outcomes were recorded through medical chart revision in Norway and from birth registries in Sweden (31, 32).\u003c/p\u003e\n\u003cp\u003eWomen were asked to provide first-void urine samples at mid-gestation and delivery. Urine was collected and kept frozen at -80\u0026deg;C until analysis. Detection and genotyping of HPV DNA was performed using the Seegene Anyplex II HPV28 detection polymerase chain reaction (PCR) assay (Seegene Inc, Seoul, South Korea). Detailed description of urine handling and analysis has previously been described (3). Seegene Anyplex II HPV28 kit detects and genotypes 28 genital HPV genotypes, defined as Any-HPV group (HPV16, 18, 31, 33, 35, 39, 45, 51, 52, 56, 58, 59, 26, 53, 66, 68, 69, 70, 73, 82, 6, 11, 40, 42, 43, 44, 54, 61). Human papillomavirus genotypes were further subclassified according to their malignant potential, as high-risk (HR-) HPV (HR-HPV16, 18, 31, 33, 35, 39, 45, 51, 52, 56, 58, 59), according to the International Agency of Research on Cancer. Analyses were also performed with HPV16, which has the highest malignant potential (33, 34).\u003c/p\u003e\n\u003cp\u003eAdverse pregnancy outcomes were defined as:\u003c/p\u003e\n\u003cp\u003e1)\u0026nbsp; \u0026nbsp;Hypertensive disorders of pregnancy including:\u003c/p\u003e\n\u003cp\u003ea.\u0026nbsp; \u0026nbsp;Gestational hypertension: new-onset hypertension (systolic blood pressure \u0026ge;140mmHg and/or diastolic blood pressure \u0026ge;90mmHg) occurring from or after GW 20, without proteinuria.\u003c/p\u003e\n\u003cp\u003eb.\u0026nbsp; \u0026nbsp;Preeclampsia: gestational hypertension with new-onset proteinuria\u003c/p\u003e\n\u003cp\u003ec.\u0026nbsp; \u0026nbsp;Superimposed preeclampsia: chronic hypertension with new onset of proteinuria after GW 20.\u003c/p\u003e\n\u003cp\u003ed.\u0026nbsp; \u0026nbsp;Eclampsia: General tonic clonic seizures occurring in women with preeclampsia.\u003c/p\u003e\n\u003cp\u003ee.\u0026nbsp; \u0026nbsp;HELLP syndrome: defined according to clinical guidelines and based on blood analyses (32).\u003c/p\u003e\n\u003cp\u003eHypertensive disorders of pregnancy subgroups were defined according to the commonly used definitions at the time of study recruitment (2014-16) (32), and did in our study not include women with preexisting hypertension or hypertension diagnosed prior to GW 20 (chronic hypertension).\u003c/p\u003e\n\u003cp\u003e2)\u0026nbsp; \u0026nbsp;Gestational diabetes mellitus, defined as glucose intolerance diagnosed during pregnancy (22), was laboratory-wise defined according to clinical guidelines relevant at the time of study inclusion (2014-16). An oral glucose intolerance test with 75g oral glucose was administered and an overnight fasting glucose level \u0026lt;7.0mmol/L and 2 hours glucose level \u0026ge;7.8 (but \u0026lt;11.1mmol/L) confirmed a GDM diagnosis (35).\u003c/p\u003e\n\u003cp\u003e3)\u0026nbsp; \u0026nbsp;Newborns small for gestational age were defined as birthweight below the 10\u003csup\u003eth\u003c/sup\u003e percentile for gestational age, stratified according to sex (36).\u003c/p\u003e\n\u003cp\u003eExposures were detection of Any-HPV, HR-HPV, HPV16 infection or multiple infections at mid-gestation, as well as genotype specific persistence of Any-HPV, HR-HPV or HPV16 from mid-gestation to delivery. We defined three groups of multiple HPV infections:\u003c/p\u003e\n\u003cp\u003e1)\u0026nbsp; \u0026nbsp;Multiple infections with Any-HPV defined as having \u0026ge;2 different HPV genotypes.\u003c/p\u003e\n\u003cp\u003e2)\u0026nbsp; \u0026nbsp;Multiple infections with HR-HPV defined as having \u0026ge;2 different HPVs, with at least one HR-HPV genotype.\u003c/p\u003e\n\u003cp\u003e3)\u0026nbsp; \u0026nbsp;Multiple HPV16 infections defined as having HPV16 with any other genotype.\u003c/p\u003e\n\u003cp\u003ePersistence of Any-HPV, HR-HPV or HPV16 infection during pregnancy was defined as having the same genotype-specific HPV infection at mid-gestation and delivery. This definition was based on the long clearance time of HPV and the low probability of a woman engaging with a new sexual partner during her late pregnancy, thus contracting a new HPV infection of the same genotype as at mid-gestation.\u003c/p\u003e\n\u003cp\u003ePossible confounding factors were collected from e-questionnaires including maternal age at enrollment, pre-pregnancy body mass index (ppBMI), duration of pre-conception relation with the child\u0026rsquo;s father (\u0026lt;1 year, 1-2 years, 3-4 years or \u0026gt;5 years), parity (0, 1 or \u0026ge;2), nicotine use during pregnancy (yes or no), alcohol consumption during pregnancy (yes or no), maternal chronic disease including chronic hypertension and pregestational diabetes mellitus (yes or no) and maternal educational level (preliminary/high school only, higher education \u0026le;4 years or higher education/PhD \u0026gt;4 years).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eStatistical analyses\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eCategorical variables are presented with numbers and percentages and continuous variables as means with standard deviations (SD) or medians with minimum and maximum values.\u003c/p\u003e\n\u003cp\u003eUnivariable and multivariable logistic regression models were used to investigate the association between Any-HPV, HR-HPV, HPV16 or multiple HPV infection at mid-gestation as well as persistent infection of Any-HPV, HR-HPV or HPV16 and adverse pregnancy outcomes. We ran separate models for each exposure variable and each of the three outcomes. Multivariable regression models were adjusted for potential confounders based on three directed acyclic graphs (37) (DAGs; Figures 2-4). In cases where cells contained \u0026lt; 5, univariable exact logistic regression models were done. The multivariable exact logistic regression models did not converge therefore multivariable logistic regression models were performed. Missing covariate values added up to 13-16% and were imputed using multiple imputation with chained equations and 40 data sets were imputed.\u003c/p\u003e\n\u003cp\u003eStatistical analyses were performed using IBM\u0026copy; SPSS\u0026copy; statistics version 28 (Chicago, IL, U.S.A) or Stata version 16 (StataCorp LLC, College Station, Texas). A P-value \u0026lt;0.05 was considered statistically significant.\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cp\u003eAt the time of enrollment, the mean age of the baseline sample (N\u0026thinsp;=\u0026thinsp;950) was 32.0 (SD\u0026thinsp;=\u0026thinsp;4.6) years and median ppBMI 24.5 kg/m\u003csup\u003e2\u003c/sup\u003e (min-max: 17.8\u0026ndash;48.2). Most women were married, 87% (825/950) with 52% (498/950) of the women in a relationship lasting 5 years or longer. Most women were expecting their first child, 55% (518/950). Mean gestational age at delivery was 40.1 weeks (SD\u0026thinsp;=\u0026thinsp;1.5) and mean birthweight 3592 g (SD\u0026thinsp;=\u0026thinsp;491.1; Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). No major differences were observed between the baseline sample (N\u0026thinsp;=\u0026thinsp;950) and nonparticipants (N\u0026thinsp;=\u0026thinsp;1748; Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\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\u003eMaternal characteristics for women in baseline sample (N\u0026thinsp;=\u0026thinsp;950) and nonparticipants (N\u0026thinsp;=\u0026thinsp;1748).\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\" colname=\"c2\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003cp\u003en. 950\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHR-HPV\u003csup\u003ea\u003c/sup\u003e positive\u003c/p\u003e \u003cp\u003en. 231\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHR-HPV\u003csup\u003ea\u003c/sup\u003e negative\u003c/p\u003e \u003cp\u003en. 719\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAny-HPV\u003csup\u003eb\u003c/sup\u003e positive\u003c/p\u003e \u003cp\u003en. 377\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eAny-HPV\u003csup\u003eb\u003c/sup\u003e negative\u003c/p\u003e \u003cp\u003en. 573\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNonparticipants from PreventADALL study\u003c/p\u003e \u003cp\u003en. 1748\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaternal Age, yr. Mean (SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e32.0 (4.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31.3 (4.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e32.3 (4.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e31.7 (4.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e32.2 (4.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e32.5 (4.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaternal ppBMI. Median\u003c/p\u003e \u003cp\u003e(min-max)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24.5 (17.8\u0026ndash;48.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24.7 (18.7\u0026ndash;38.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24.5 (17.8\u0026ndash;48.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e24.7 (18.4\u0026ndash;39.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e24.4 (17.8\u0026ndash;48.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e23.9 (17.2\u0026ndash;44.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarital Status. n (%)\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\u003eMarried/cohabitants\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e825 (87%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e199 (96%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e626 (99%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e322 (96%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e503 (99%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1465 (84%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSingle/Divorced/Other\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17 (18%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9 (4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8 (1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13 (4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4 (1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e50 (3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMissing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e108\u003c/p\u003e \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 \u003cp\u003e233\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaternal education. n (%)\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\u003ePreliminary/high school only\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e141 (15%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e47 (23%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e94 (15%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e72 (22%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e69 (14%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e118 (7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigher education\u0026thinsp;\u0026le;\u0026thinsp;4 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e295 (31%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e69 (34%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e226 (36%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e112 (24%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e183 (36%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e462 (26%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigher/PhD/\u0026gt; 4 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e400 (42%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e89 (43%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e311 (49%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e148 (45%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e252 (50%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e923 (53%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMissing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e114\u003c/p\u003e \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 \u003cp\u003e245\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDuration of pre-conception relation with child\u0026rsquo;s father, yr. n (%)\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\u003e\u0026lt;1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e27 (3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11 (6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16 (3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e14 (5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e13 (3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e69 (4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u0026ndash;2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e89 (9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e43 (23%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e46 (8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e64 (21%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e25 (5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e199 (11%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u0026ndash;5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e188 (20%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e64 (34%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e124 (20%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e92 (30%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e96 (20%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e382 (22%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e498 (52%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e71 (38%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e427 (70%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e141 (45%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e357 (73%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e806 (46%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMissing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e148\u003c/p\u003e \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 \u003cp\u003e292\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNicotine use during pregnancy.\u003c/p\u003e \u003cp\u003en (%)\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\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e740 (78%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e176 (85%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e564 (89%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e289 (86%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e451 (89%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1327 (76%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e100 (11%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31 (15%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e69 (11%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e45 (14%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e55 (11%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e179 (10%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMissing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e110\u003c/p\u003e \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 \u003cp\u003e242\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlcohol consumption during pregnancy. n (%)\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\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e591 (62%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e134 (65%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e457 (73%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e224 (67%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e367 (73%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e919 (53%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e245 (26%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e72 (35%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e173 (27%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e109 (33%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e136 (27%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e582 (33%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMissing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e114\u003c/p\u003e \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 \u003cp\u003e247\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of previous deliveries (Parity). n (%)\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\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e518 (55%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e161 (70%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e357 (50%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e234 (62%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e284 (50%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1075 (62%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e321 (34%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e55 (24%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e266 (37%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e111 (30%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e210 (37%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e539 (31%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e109 (11%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15 (6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e94 (13%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e31 (8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e78 (14%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e128 (7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMissing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \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 \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGestational age at birth, weeks. Mean (SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40.1 (1.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e40.1 (1.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e40.1 (1.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e40.1 (1.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e40.0 (1.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e39.9 (1.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFetal sex. n (%)\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\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e495 (52%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e115 (50%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e380 (53%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e185 (49%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e310 (54%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e916 (52%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e454 (48%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e116 (50%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e338 (47%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e191 (51%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e263 (46%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e811 (46%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMissing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \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 \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBirthweight, g. Mean (SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3591.8 (491.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3588.2 (468.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3574.0 (507.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3576.8 (453.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3577.8 (525.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3517.5 (559.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBlood pressure, mmHg. Mean (SD)\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\u003eEarly pregnancy sBP\u003c/p\u003e \u003cp\u003e(at inclusion)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e110.3 (10.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e110.6 (10.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e110.4 (11.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e110.3 (10.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e110.5 (11.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e107.9 (9.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEarly pregnancy dBP\u003c/p\u003e \u003cp\u003e(at inclusion)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e63.1 (7.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e63.4 (8.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e63.6 (8.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e62.8 (8.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e64.0 (8.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e61.0 (6.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLate pregnancy sBP\u003c/p\u003e \u003cp\u003e(up to two weeks prior to delivery)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e119.5 (12. 8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e120.5 (12.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e119.1 (13.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e119.0 (12.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e119.7 (13.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e120.4 (13.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLate pregnancy dBP\u003c/p\u003e \u003cp\u003e(up to two weeks prior to delivery)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e75.7 (9.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e76.8 (9.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e75.3 (9.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e75.4 (9.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e75.8 (9.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e76.1 (9.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaternal chronic disease\u003c/p\u003e \u003cp\u003e(including chronic hypertension and pregest. diabetes mellitus).\u003c/p\u003e \u003cp\u003en (%)\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\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e652 (69%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e153 (66%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e499 (69%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e258 (68%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e394 (69%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1197 (69%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e298 (31%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e78 (34%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e220 (31%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e119 (32%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e179 (31%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e551 (31%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003e\u003csup\u003ea\u003c/sup\u003eHR-HPV: 16, 18, 31, 33, 35, 39, 45, 51, 52, 56, 58, 59\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003e\u003csup\u003eb\u003c/sup\u003eAny-HPV: 16, 18, 31, 33, 35, 39, 45, 51, 52, 56, 58, 59, 26, 53, 66, 68, 69, 70, 73, 82, 6, 11, 40, 42, 43, 44, 54, 61\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eAbbreviations: yr- years, SD- standard deviation, ppBMI- pre-pregnancy Body Mass Index, min-minimum, max-maximum, sBP-systolic blood pressure, dBP-diastolic blood pressure, g-grams. Pregest-pregestational.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eIn the baseline sample, 40% (377/950) were infected with Any-HPV whereas 24% (231/950) had an infection with HR-HPV. The most common single HPV genotype was HPV16 with 6% (59/950). Persistence of Any-HPV was 52% (152/290) and 52% (93/178) for HR-HPV whilst 64% (29/45) of HPV16 infections persisted until delivery.\u003c/p\u003e \u003cp\u003eAt the time of delivery, 9% (83/950) of the women were diagnosed with HDP (chronic hypertension not included). Gestational hypertension, diagnosed in 4% (42/950), was the most common HDP, followed by preeclampsia, 2% (19/950). None of the women developed eclampsia. Hypertensive disorders of pregnancy were observed in 7% (26/377) of women infected with Any-HPV and 8% (19/231) in women with HR-HPV at mid-gestation. In adjusted logistic regression analyses HDP was observed less often amongst women with Any-HPV infection at mid-gestation (adjusted odds ratio (aOR) 0.55, 95% confidence interval (CI) 0.32\u0026ndash;0.93, p\u0026thinsp;=\u0026thinsp;0.024), compared to women without infections; HR-HPV infections were not associated with HDP (aOR\u0026thinsp;=\u0026thinsp;0.79, 95% CI 0.45\u0026ndash;1.41, p\u0026thinsp;=\u0026thinsp;0.427); Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). No associations were found in adjusted regression models for HPV16, multiple HPV infections at mid-gestation or persistent infections and HDP (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, Supplementary Table\u0026nbsp;1).\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\u003eHPV infection at mid-gestation and adverse pregnancy outcomes.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\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 \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"9\" nameend=\"c9\" namest=\"c1\"\u003e \u003cp\u003eHYPERTENSIVE DISORDERS OF PREGNANCY\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c7\" namest=\"c2\"\u003e \u003cp\u003eResults from complete case analysis\u003c/p\u003e \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;731)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003eResults from imputed analysis\u003c/p\u003e \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;942)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;942\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHPV positive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHDP\u003csup\u003eb\u003c/sup\u003e case\u003c/p\u003e \u003cp\u003e(HPV pos/neg)\u003c/p\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCrude OR\u003c/p\u003e \u003cp\u003e(95% CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eaOR\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(95% CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eImputed aOR\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(95% CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAny-HPV\u003csup\u003ee\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e375\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26/57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.67 (0.41\u0026ndash;1.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.67 (0.35\u0026ndash;1.31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.242\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.55 (0.32\u0026ndash;0.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e0.024\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHR-HPV\u003csup\u003ef\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e231\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19/64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.91 (0.53\u0026ndash;1.55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.718\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.83 (0.40\u0026ndash;1.72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.621\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.79 (0.45\u0026ndash;1.41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.427\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHPV16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5/78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.97 (0.29\u0026ndash;2.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.81 (0.23\u0026ndash;2.78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.732\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.85 (0.32\u0026ndash;2.26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.747\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"9\" nameend=\"c9\" namest=\"c1\"\u003e \u003cp\u003eGESTATIONAL DIABETES MELLITUS\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=\"6\" nameend=\"c7\" namest=\"c2\"\u003e \u003cp\u003eResults from complete case analysis\u003c/p\u003e \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;883)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003eResults from imputed analysis\u003c/p\u003e \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;903)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;903\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHPV positive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGDM\u003csup\u003eg\u003c/sup\u003e case\u003c/p\u003e \u003cp\u003e(HPV pos/neg)\u003c/p\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCrude OR\u003c/p\u003e \u003cp\u003e(95% CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eaOR\u003csup\u003eh\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(95% CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eImputed aOR\u003csup\u003ei\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(95% CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAny-HPV\u003csup\u003ee\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e355\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12/28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.65 (0.33\u0026ndash;1.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.221\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.57 (0.28\u0026ndash;1.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.127\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.56 (0.27\u0026ndash;1.15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.114\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHR-HPV\u003csup\u003ef\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e218\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8/32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.78 (0.35\u0026ndash;1.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.532\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.76 (0.34\u0026ndash;1.73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.517\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.77 (0.34\u0026ndash;1.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.528\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHPV16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2/38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.79 (0.09\u0026ndash;3.19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.83 (0.19\u0026ndash;3.65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.808\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.85 (0.20\u0026ndash;3.74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.834\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"9\" nameend=\"c9\" namest=\"c1\"\u003e \u003cp\u003eNEWBORNS SMALL FOR GESTATIONAL AGE\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=\"6\" nameend=\"c7\" namest=\"c2\"\u003e \u003cp\u003eResults from complete case analysis\u003c/p\u003e \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;831)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003eResults from imputed analysis\u003c/p\u003e \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;949)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;949\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHPV positive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSGA\u003csup\u003ej\u003c/sup\u003e case\u003c/p\u003e \u003cp\u003e(HPV pos/neg)\u003c/p\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCrude OR\u003c/p\u003e \u003cp\u003e(95% CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eaOR\u003csup\u003ek\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(95% CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eImputed aOR\u003csup\u003el\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(95% CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAny-HPV\u003csup\u003ee\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e376\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24/43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.84 (0.50\u0026ndash;1.41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.510\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.79 (0.44\u0026ndash;1.42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.437\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.76 (0.45\u0026ndash;1.29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.304\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHR-HPV\u003csup\u003ef\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e231\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11/56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.59 (0.30\u0026ndash;1.15)\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\u003e0.60 (0.29\u0026ndash;1.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.167\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.52 (0.26\u0026ndash;1.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.058\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHPV16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2/65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.45 (0.05\u0026ndash;1.76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.392\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.45 (0.11\u0026ndash;1.94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.287\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.36 (0.09\u0026ndash;1.55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.171\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003e\u003csup\u003ea\u003c/sup\u003eEight women with missing HDP data, 47 women with missing GDM data and 1 woman with missing SGA data.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003e\u003csup\u003eb\u003c/sup\u003eHypertensive disorders of pregnancy, including gestational hypertension, superimposed preeclampsia, preeclampsia, eclampsia, Hemolysis, Elevated Liver enzymes, Low Platelets (HELLP).\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003e\u003csup\u003ec\u003c/sup\u003eAdjusted for: Duration of pre-pregnancy relation to child\u0026rsquo;s father, maternal age, pre-pregnancy Body Mass Index (ppBMI), parity, maternal chronic disease (including chronic hypertension and diabetes mellitus), maternal education.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003e\u003csup\u003ed\u003c/sup\u003eImputed variables: Maternal education, Duration of pre-pregnancy relation to child\u0026rsquo;s father, ppBMI.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003e\u003csup\u003ee\u003c/sup\u003eHR-HPV: 16, 18, 31, 33, 35, 39, 45, 51, 52, 56, 58, 59\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003e\u003csup\u003ef\u003c/sup\u003eAny-HPV: 16, 18, 31, 33, 35, 39, 45, 51, 52, 56, 58, 59, 26, 53, 66, 68, 69, 70, 73, 82, 6, 11, 40, 42, 43, 44, 54, 61\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003e\u003csup\u003eg\u003c/sup\u003eGDM: Gestational Diabetes Mellitus.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003e\u003csup\u003eh\u003c/sup\u003eAdjusted for: Maternal Age, ppBMI.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003e\u003csup\u003ei\u003c/sup\u003eImputed variables: ppBMI.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003e\u003csup\u003ej\u003c/sup\u003eSGA-Newborns small for gestational age.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003e\u003csup\u003ek\u003c/sup\u003eAdjusted for: Maternal chronic disease (including chronic hypertension and diabetes mellitus), nicotine use during pregnancy, alcohol consumption during pregnancy, maternal age. maternal education.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003e\u003csup\u003el\u003c/sup\u003eImputed variables: Maternal education, nicotine use during pregnancy, alcohol consumption during pregnancy\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003eAbbreviations: HPV-Human papillomavirus, HR-HPV-High-Risk Human papillomavirus, OR-Odds Ratio, aOR-adjusted Odds Ratio, pos-positive, neg-negative.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \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\u003eMultiple HPV infection at mid-gestation and adverse pregnancy outcomes.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\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 \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"9\" nameend=\"c9\" namest=\"c1\"\u003e \u003cp\u003eHYPERTENSIVE DISORDERS OF PREGNANCY\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c7\" namest=\"c2\"\u003e \u003cp\u003eResults from complete case analysis\u003c/p\u003e \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;731)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003eResults from imputed analysis\u003c/p\u003e \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;942)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;942\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHPV\u003c/p\u003e \u003cp\u003epositive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHDP\u003csup\u003eb\u003c/sup\u003e case\u003c/p\u003e \u003cp\u003e(HPV pos/neg)\u003c/p\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCrude\u003c/p\u003e \u003cp\u003eOR\u003c/p\u003e \u003cp\u003e(95% CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eaOR\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(95% CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eImputed aOR\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(95% CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAny-HPV\u003csup\u003ee\u003c/sup\u003e + Any-HPV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e171\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15/68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003cp\u003e(0.55\u0026ndash;1.79)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.984\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.73\u003c/p\u003e \u003cp\u003e(0.32\u0026ndash;1.68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.454\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.78\u003c/p\u003e \u003cp\u003e(0.41\u0026ndash;1.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.456\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHR-HPV\u003csup\u003ef\u003c/sup\u003e +\u003c/p\u003e \u003cp\u003eAny-HPV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e139\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14/69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.19\u003c/p\u003e \u003cp\u003e(0.65\u0026ndash;2.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.570\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.84\u003c/p\u003e \u003cp\u003e(0.36-2.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.696\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.96\u003c/p\u003e \u003cp\u003e(0.49\u0026ndash;1.84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.892\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHPV16 +\u003c/p\u003e \u003cp\u003eAny-HPV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4/79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.24\u003c/p\u003e \u003cp\u003e(0.31\u0026ndash;3.61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.857\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.38\u003c/p\u003e \u003cp\u003e(0.380\u0026ndash;4.98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.627\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.04\u003c/p\u003e \u003cp\u003e(0.34\u0026ndash;3.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.942\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"9\" nameend=\"c9\" namest=\"c1\"\u003e \u003cp\u003eGESTATIONAL DIABETES MELLITUS\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=\"6\" nameend=\"c7\" namest=\"c2\"\u003e \u003cp\u003eResults from complete case analysis\u003c/p\u003e \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;883)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003eResults from imputed analysis\u003c/p\u003e \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;903)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;903\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHPV\u003c/p\u003e \u003cp\u003epositive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGDM\u003csup\u003eg\u003c/sup\u003e case\u003c/p\u003e \u003cp\u003e(HPV pos/neg)\u003c/p\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCrude\u003c/p\u003e \u003cp\u003eOR\u003c/p\u003e \u003cp\u003e(95% CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eaOR\u003csup\u003eh\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(95% CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eImputed aOR\u003csup\u003ei\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(95% CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAny-HPV\u003csup\u003ef\u003c/sup\u003e + Any-HPV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e162\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6/34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.80\u003c/p\u003e \u003cp\u003e(0.33\u0026ndash;1.94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.621\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.68\u003c/p\u003e \u003cp\u003e(0.27\u0026ndash;1.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.409\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.68\u003c/p\u003e \u003cp\u003e(0.27\u0026ndash;1.72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.417\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHR-HPV\u003csup\u003eg\u003c/sup\u003e + Any-HPV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e130\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5/35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.83\u003c/p\u003e \u003cp\u003e(0.25\u0026ndash;2.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.912\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.72\u003c/p\u003e \u003cp\u003e(0.26\u0026ndash;1.94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.510\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.73\u003c/p\u003e \u003cp\u003e(0.27\u0026ndash;1.97)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.533\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHPV16 +\u003c/p\u003e \u003cp\u003eAny-HPV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2/38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.28\u003c/p\u003e \u003cp\u003e(0.14\u0026ndash;5.29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.966\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.39\u003c/p\u003e \u003cp\u003e(0.31\u0026ndash;6.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.670\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.42\u003c/p\u003e \u003cp\u003e(0.32\u0026ndash;6.43)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.647\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"9\" nameend=\"c9\" namest=\"c1\"\u003e \u003cp\u003eNEWBORNS SMALL FOR GESTATIONAL AGE\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=\"6\" nameend=\"c7\" namest=\"c2\"\u003e \u003cp\u003eResults from complete case analysis\u003c/p\u003e \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;831)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003eResults from imputed analysis\u003c/p\u003e \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;949)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;949\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHPV\u003c/p\u003e \u003cp\u003epositive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSGA\u003csup\u003ej\u003c/sup\u003e case\u003c/p\u003e \u003cp\u003e(HPV pos/neg)\u003c/p\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCrude\u003c/p\u003e \u003cp\u003eOR\u003c/p\u003e \u003cp\u003e(95% CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eaOR\u003csup\u003ek\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(95% CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eImputed aOR\u003csup\u003el\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(95% CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAny-HPV\u003csup\u003ef\u003c/sup\u003e + Any-HPV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e171\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12/55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003cp\u003e(0.52\u0026ndash;1.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.981\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.07\u003c/p\u003e \u003cp\u003e(0.52\u0026ndash;2.15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.869\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.87\u003c/p\u003e \u003cp\u003e(0.45\u0026ndash;1.69)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.677\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHR-HPV\u003csup\u003eg\u003c/sup\u003e + Any-HPV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e139\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8/59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.78\u003c/p\u003e \u003cp\u003e(0.36\u0026ndash;1.66)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.517\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.77\u003c/p\u003e \u003cp\u003e(0.33\u0026ndash;1.77)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.531\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.67\u003c/p\u003e \u003cp\u003e(0.31\u0026ndash;1.45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.308\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHPV16 +\u003c/p\u003e \u003cp\u003eAny-HPV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1/66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.35\u003c/p\u003e \u003cp\u003e(0.01\u0026ndash;2.13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.470\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.37\u003c/p\u003e \u003cp\u003e(0.05\u0026ndash;2.78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.331\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.28\u003c/p\u003e \u003cp\u003e(0.04\u0026ndash;2.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.212\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003e\u003csup\u003ea\u003c/sup\u003eEight women with missing HDP data, 47 women with missing GDM data and 1 woman with missing SGA data.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003e\u003csup\u003eb\u003c/sup\u003eHypertensive disorders of pregnancy, including gestational hypertension, superimposed preeclampsia, preeclampsia, eclampsia, Hemolysis, Elevated Liver enzymes, Low Platelets (HELLP).\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003e\u003csup\u003ec\u003c/sup\u003eAdjusted for: Duration of pre-pregnancy relation to child\u0026rsquo;s father, maternal age, pre-pregnancy Body Mass Index (ppBMI), parity, maternal chronic disease (including chronic hypertension and diabetes mellitus), maternal education.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003e\u003csup\u003ed\u003c/sup\u003eImputed variables: Maternal education, Duration of pre-pregnancy relation to child\u0026rsquo;s father, ppBMI.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003e\u003csup\u003ee\u003c/sup\u003eHR-HPV: 16, 18, 31, 33, 35, 39, 45, 51, 52, 56, 58, 59\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003e\u003csup\u003ef\u003c/sup\u003eAny-HPV: 16, 18, 31, 33, 35, 39, 45, 51, 52, 56, 58, 59, 26, 53, 66, 68, 69, 70, 73, 82, 6, 11, 40, 42, 43, 44, 54, 61\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003e\u003csup\u003eg\u003c/sup\u003eGDM: Gestational Diabetes Mellitus.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003e\u003csup\u003eh\u003c/sup\u003eAdjusted for: Maternal Age, ppBMI.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003e\u003csup\u003ei\u003c/sup\u003eImputed variables: ppBMI.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003e\u003csup\u003ej\u003c/sup\u003eSGA-Newborns small for gestational age.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003e\u003csup\u003ek\u003c/sup\u003eAdjusted for: Maternal chronic disease (including chronic hypertension and diabetes mellitus), nicotine use during pregnancy, alcohol consumption during pregnancy, maternal age. maternal education.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003e\u003csup\u003el\u003c/sup\u003eImputed variables: Maternal education, nicotine use during pregnancy, alcohol consumption during pregnancy\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003eAbbreviations: HPV-Human papillomavirus, HR-HPV-High-Risk Human papillomavirus, OR-Odds Ratio, aOR-adjusted Odds Ratio, pos-positive, neg-negative.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePersistent HPV infection from mid-gestation to delivery and adverse pregnancy outcomes.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\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 \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"9\" nameend=\"c9\" namest=\"c1\"\u003e \u003cp\u003eHYPERTENSIVE DISORDERS OF PREGNANCY\u003csup\u003ea\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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c7\" namest=\"c2\"\u003e \u003cp\u003eResults from complete case analysis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003eResults from imputed analysis\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHPV pos. at mid-gestation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHPV persistent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHDP\u003csup\u003eb\u003c/sup\u003e case\u003c/p\u003e \u003cp\u003e(HPV pos/neg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCrude\u003c/p\u003e \u003cp\u003eOR\u003c/p\u003e \u003cp\u003e(95% CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eaOR\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(95% CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eImputed\u003c/p\u003e \u003cp\u003eaOR\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(95% CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAny-HPV\u003csup\u003ee\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;290\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e152\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11/9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.12\u003c/p\u003e \u003cp\u003e(0.45\u0026ndash;2.79)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.810\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.95\u003c/p\u003e \u003cp\u003e(0.27\u0026ndash;3.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.933\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003cp\u003e(0.36\u0026ndash;2.73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.977\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHR-HPV\u003csup\u003ef\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;178\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10/5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.92\u003c/p\u003e \u003cp\u003e(0.63\u0026ndash;5.89)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.249\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.39\u003c/p\u003e \u003cp\u003e(0.58\u0026ndash;19.79)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.175\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.96\u003c/p\u003e \u003cp\u003e(0.54\u0026ndash;7.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.308\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHPV16\u003c/p\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3/0\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 \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"9\" nameend=\"c9\" namest=\"c1\"\u003e \u003cp\u003eGESTATIONAL DIABETES MELLITUS\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=\"6\" nameend=\"c7\" namest=\"c2\"\u003e \u003cp\u003eResults from complete case analysis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003eResults from imputed analysis\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHPV pos. at mid-gestation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHPV persistent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGDM\u003csup\u003eg\u003c/sup\u003e case\u003c/p\u003e \u003cp\u003e(HPV pos/neg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCrude\u003c/p\u003e \u003cp\u003eOR\u003c/p\u003e \u003cp\u003e(95% CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eaOR\u003csup\u003eh\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(95% CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eImputed\u003c/p\u003e \u003cp\u003eaOR\u003csup\u003ei\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(95% CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAny-HPV\u003csup\u003ee\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;271\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e143\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3/3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.91\u003c/p\u003e \u003cp\u003e(0.12\u0026ndash;6.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.81\u003c/p\u003e \u003cp\u003e(0.16\u0026ndash;4.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.801\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.81\u003c/p\u003e \u003cp\u003e(0.15\u0026ndash;4.26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.799\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHR-HPV\u003csup\u003ef\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;166\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2/3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.38\u003c/p\u003e \u003cp\u003e(0.15\u0026ndash;16.91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.18\u003c/p\u003e \u003cp\u003e(0.19\u0026ndash;7.69)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.866\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.19\u003c/p\u003e \u003cp\u003e(0.18\u0026ndash;7.79)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.853\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHPV16\u003c/p\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\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 \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"9\" nameend=\"c9\" namest=\"c1\"\u003e \u003cp\u003eNEWBORNS SMALL FOR GESTATIONAL AGE\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=\"6\" nameend=\"c7\" namest=\"c2\"\u003e \u003cp\u003eResults from complete case analysis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003eResults from imputed analysis\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHPV pos. at mid-gestation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHPV persistent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSGA\u003csup\u003ek\u003c/sup\u003e case\u003c/p\u003e \u003cp\u003e(HPV pos/neg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCrude\u003c/p\u003e \u003cp\u003eOR\u003c/p\u003e \u003cp\u003e(95% CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eaOR\u003csup\u003el\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(95% CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eImputed\u003c/p\u003e \u003cp\u003eaOR\u003csup\u003em\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(95% CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAny-HPV\u003csup\u003ee\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;290\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e152\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10/7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.32\u003c/p\u003e \u003cp\u003e(0.48\u0026ndash;3.56)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.586\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.26\u003c/p\u003e \u003cp\u003e(0.42\u0026ndash;3.73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.681\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.20\u003c/p\u003e \u003cp\u003e(0.44\u0026ndash;3.34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.722\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHR-HPV\u003csup\u003ef\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;178\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3/5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.53\u003c/p\u003e \u003cp\u003e(0.12\u0026ndash;2.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.400\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.51\u003c/p\u003e \u003cp\u003e(0.10\u0026ndash;2.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.417\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.49\u003c/p\u003e \u003cp\u003e(0.11\u0026ndash;2.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.356\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHPV16\u003c/p\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2/0\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 \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003e\u003csup\u003ea\u003c/sup\u003eFive women with missing HDP data and 42 women with missing GDM data.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003e\u003csup\u003eb\u003c/sup\u003eHypertensive disorders of pregnancy, including gestational hypertension, superimposed preeclampsia, preeclampsia, eclampsia, Hemolysis, Elevated Liver enzymes, Low Platelets (HELLP).\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003e\u003csup\u003ec\u003c/sup\u003eAdjusted for: Duration of pre-pregnancy relation to child\u0026rsquo;s father, maternal age, pre-pregnancy Body Mass Index (ppBMI), parity, maternal chronic disease (including chronic hypertension and diabetes mellitus), maternal education.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003e\u003csup\u003ed\u003c/sup\u003eImputed variables: Maternal education, Duration of pre-pregnancy relation to child\u0026rsquo;s father, ppBMI.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003e\u003csup\u003ee\u003c/sup\u003eAny-HPV: 16, 18, 31, 33, 35, 39, 45, 51, 52, 56, 58, 59, 26, 53, 66, 68, 69, 70, 73, 82, 6, 11, 40, 42, 43, 44, 54, 61\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003e\u003csup\u003ef\u003c/sup\u003eHR-HPV: 16, 18, 31, 33, 35, 39, 45, 51, 52, 56, 58, 59\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003e\u003csup\u003eg\u003c/sup\u003eGDM: Gestational Diabetes Mellitus.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003e\u003csup\u003eh\u003c/sup\u003eAdjusted for: Maternal Age, ppBMI.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003e\u003csup\u003ei\u003c/sup\u003eImputed variables: ppBMI.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003e\u003csup\u003ej\u003c/sup\u003e\u0026infin;Infinite value\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003e\u003csup\u003ek\u003c/sup\u003eSGA-Newborns small for gestational age.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003e\u003csup\u003el\u003c/sup\u003eAdjusted for: Maternal chronic disease (including chronic hypertension and diabetes mellitus), nicotine use during pregnancy, alcohol consumption during pregnancy, maternal age. maternal education.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003e\u003csup\u003em\u003c/sup\u003eImputed variables: Maternal education, nicotine use during pregnancy, alcohol consumption during pregnancy\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003eAbbreviations: HPV-Human papillomavirus, HR-HPV-High-Risk Human papillomavirus, OR-Odds Ratio, aOR-adjusted Odds Ratio, pos-positive, neg-negative.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003e\u003csup\u003en\u003c/sup\u003eFisher\u0026rsquo;s Exact Test\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eFour percent (40/950) of the women were diagnosed with GDM. The prevalence of GDM in women with Any-HPV was 3% (12/377) and 3% (8/231) in women with HR-HPV. We found no statistically significant association between Any-HPV infections or HR-HPV infections at mid-gestation and GDM in the adjusted regression models (aOR\u0026thinsp;=\u0026thinsp;0.56, 95% CI 0.27\u0026ndash;1.15, p\u0026thinsp;=\u0026thinsp;0.114 and aOR\u0026thinsp;=\u0026thinsp;0.77, 95% CI 0.34\u0026ndash;1.75, p\u0026thinsp;=\u0026thinsp;0.528, respectively; Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). No statistically significant associations were found for HPV16, multiple HPV infections at mid-gestation and persistent infections and GDM (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, Supplementary Table\u0026nbsp;1).\u003c/p\u003e \u003cp\u003eOverall, 7% (67/950) of the newborns were SGA, while SGA was observed in 6% (24/377) in women with Any-HPV infection and in 5% (11/231) of women with HR-HPV infection. No statistically significant associations were found between Any-HPV infection or HR-HPV infection at mid-gestation and SGA in the adjusted regression analysis (aOR\u0026thinsp;=\u0026thinsp;0.76, 95% CI 0.45\u0026ndash;1.29, p\u0026thinsp;=\u0026thinsp;0.304 and aOR\u0026thinsp;=\u0026thinsp;0.52, 95% CI 0.26\u0026ndash;1.02, p\u0026thinsp;=\u0026thinsp;0.058, respectively; Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). No statistically significant associations were found for HPV16, multiple HPV infections at mid-gestation and persistent infections and SGA (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, Supplementary Table\u0026nbsp;1).\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eIn this general population cohort of 950 pregnant women, the detection of Any-HPV, HR-HPV, HPV16 or multiple HPV infections at mid-gestation or persistent HPV infections during pregnancy was not associated with increased risk for hypertensive disorders of pregnancy, gestational diabetes mellitus, or newborns small for gestational age, in spite of a relatively high prevalence of HPV infections found during pregnancy.\u003c/p\u003e \u003cp\u003eIn our analyses we found no association between HPV infections and HDP, in line with several other studies (4, 8, 27\u0026ndash;29). In contrast, McDonnold et al. who investigated 314 women with presumed HR-HPV infections at the time of entry to prenatal care, matched to 628 women with at least 2 negative consecutive PAP smears, found an association between HPV infections and preeclampsia. However, their study was retrospective, using abnormal PAP smear as a proxy for HR-HPV infections. Further HPV testing was performed on the same sample only if atypical squamous cells of undetermined significance (ASCUS) were found (25). The true HPV prevalence was not known as women with HPV infection and normal PAP smear were excluded in the exposure group.\u003c/p\u003e \u003cp\u003eOur finding of no association between GDM and HPV infections is in line with other studies (25, 27, 28). Cho et al. surveyed 311 women in Korea six weeks postpartum and tested for 13 HR-HPV genotypes. However, as this was done six weeks after delivery, clearance of HPV infections might have occurred yielding fewer HPV positive women postpartum than during pregnancy (28). Pandey and colleagues however, used a prospective design, but in their sample size of 104 women, HPV was detected from condoms used on vaginal ultrasound probes during the first trimester, yielding uncertain results as all women with HPV may not have been identified and this method is yet to be validated (27).\u003c/p\u003e \u003cp\u003eNo association was seen between HPV infections and SGA, in line with several other studies (25, 27, 29). Ford et al. showed an association between HPV and SGA in a study using positive PAP smear 2 years prior to the index pregnancy as a proxy for HPV infection (26). Similar to the McDonnold study (25), the true HPV prevalence was not known for the current pregnancy. Comparability of our study to others is challenging, as Pandey et al. did not define SGA and McDonnold et al. did not record actual birthweight but rather ultrasound measurements (25, 27). A systematic review and meta-analysis from 2020 found an association between HPV infections during pregnancy and SGA (24). However, a true comparison to our present study is difficult as the definition of SGA in the included studies was either missing or varying, ranging from \u0026lt;\u0026thinsp;10% and \u0026lt;\u0026thinsp;5% in birthweight percentiles (24).\u003c/p\u003e \u003cp\u003eThis current study showed no evidence for increased risk of placental dysfunction disorders including hypertensive disorders of pregnancy, gestational diabetes mellitus or newborns small for gestational age in women with HPV infections compared to women without infections during pregnancy. These findings should be reassuring for pregnant women or women of childbearing age with a positive HPV-screening test result and normal cytology findings. In this study we have only investigated the association of HPV infections and adverse pregnancy outcomes, and not ongoing or previous abnormal cervical cytology due to HPV.\u003c/p\u003e \u003cp\u003eThis study utilized a prospective design and tested for the most common HPV genotypes at two time points during pregnancy enabling detection of longitudinal HPV infection throughout pregnancy. The effect estimates seem to show no associations, however due to the large uncertainty because of low numbers of HPV infections in women with adverse pregnancy outcomes and low prevalence of adverse pregnancy outcomes, results need to be interpreted carefully. There is a growing body of evidence showing that HPV infections during pregnancy do not affect pregnancy outcomes negatively (8, 27\u0026ndash;29) including our present study. Girls who have received the HPV vaccine are now reaching childbearing age, and it will be of great interest to investigate whether the vaccine contributes to further lowering of adverse pregnancy outcomes.\u003c/p\u003e \u003cp\u003eA strength of this study is the multi-center prospective and longitudinal cohort design. Pregnant women from the general population in Norway and Sweden were invited to participate and biological samples were collected at two time points during pregnancy, allowing a longitudinal HPV infection follow-up. Maternal characteristics were collected through detailed e-questionnaires and medical records. Urine samples were handled according to strict protocols, ensuring high quality samples. First-void urine samples have been shown to be adequate and reliable for detecting genital HPV infections (38, 39). A weakness of this study is the lack of data concerning HPV status prior to pregnancy and previous treatment for cervical dysplasia, as well as the HPV vaccine status of the women. However, due to their age, most women in the study were likely not vaccinated, as they were not eligible for the HPV vaccine through the childhood vaccine program starting 2009 in Norway and 2010 in Sweden. In addition to this, the first testing timepoint for HPV in this study was in the second trimester, thus HPV status during the first trimester is missing. In our study, we used SGA as a proxy for fetal growth restriction. The distinction between SGA and fetal growth restriction can only be made with ultrasound examinations during pregnancy (40). We may therefore have included constitutionally small infants amongst those with true placental pathology. Due to the design of this current study, women with miscarriages prior to enrollment at mid-gestation were excluded, preventing us from exploring the possible association between HPV infections and early miscarriage and leading to a potential selection bias when assessing adverse pregnancy outcomes (survival bias).\u003c/p\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eIn a general population of pregnant women from Norway and Sweden, we found no evidence for an increased risk of adverse pregnancy outcomes linked to placental dysfunction in women with HPV infections during pregnancy, despite the high prevalence of HPV infections observed.\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\u003eHPV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eHuman papillomavirus\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eHR-HPV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eHigh-Risk Human papillomavirus\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eHDP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eHypertensive disorders of pregnancy\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eGDM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eGestational diabetes mellitus\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\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eGW\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eGestational week\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\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\u003eaOR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAdjusted odds ratio\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePreventADALL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePreventing Atopic Dermatitis and ALLergies in children\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cem\u003eEthical Approval Statement and consent to participate\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe PreventADALL study with the current sub-study was approved by the Regional Ethical Committee for Medical and Health Research in South-Eastern Norway (REC 2014/518 and REC 2017/1053) and in Sweden (2014/2242-31/4).\u003c/p\u003e\n\u003cp\u003eAll women included in the current study signed an informed consent form, with the opportunity to withdraw from the study at any time and without the need to disclose reason for withdrawal.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eConsent for publication\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAvailability of data\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analysed during the current study are available from the principal investigator in the PreventADALL study on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eCompeting interest\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe authors report no conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eFunding\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe current substudy was funded by the South-Eastern Norway Regional Health Authority (2017023). The PreventADALL study was funded by the several funding bodies including: the South-Eastern Norway Regional Health Authority, the Norwegian Research Council, Oslo University Hospital, the University of Oslo, Health and Rehabilitation, Østfold Hospital Trust, the European Union (MeDALL project), by unrestricted grants from the Norwegian Association of Asthma and Allergy, the Kloster Foundation, Norwegian Society of Dermatology and Venerology, The Foundation for Healthcare and Allergy Research in Sweden -Vårdalstiftelsen, Swedish Asthma- and Allergy Association’s Research Foundation, The Swedish Research Council - the Initiative for Clinical Therapy Research, The Swedish Heart-Lung Foundation, SFO-V Karolinska University Hospital,\u0026nbsp;Stockholm County Council (ALF-project), Forte, Swedish Order of Freemasons\u0026nbsp;Foundation Barnhuset, The Sven Jerring Foundation, The Hesselman foundation, \u003cstrong\u003eThe Magnus Bergwall foundation,\u0026nbsp;\u003c/strong\u003eThe\u0026nbsp;Konsul\u0026nbsp;Th C\u0026nbsp;Bergh’s\u0026nbsp;Foundation, The Swedish Society of Medicine, KI grants, The Cancer- and Allergy Foundation, The Pediatric Research Foundation at Astrid Lindgren Children's Hospital, The Samariten Foundation for Paediatric research.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAuthor contributions\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eMRV: Conceptualization, Methodology, Formal analysis, Investigation, Data Curation, Writing - Original Draft, Funding acquisition\u003c/p\u003e\n\u003cp\u003eACS: Conceptualization, Methodology, Writing - Review \u0026amp; Editing, Funding acquisition, Supervision, Project administration\u003c/p\u003e\n\u003cp\u003eJW: Conceptualization, Methodology, Writing - Review \u0026amp; Editing, Investigation, Data Curation\u003c/p\u003e\n\u003cp\u003eKS: Conceptualization, Methodology, Writing - Review \u0026amp; Editing, Funding acquisition, Supervision\u003c/p\u003e\n\u003cp\u003eCSR: Methodology, Validation, Formal analysis, Writing - Review \u0026amp; Editing, Visualization\u003c/p\u003e\n\u003cp\u003eMS: Writing - Review \u0026amp; Editing, Data Curation\u003c/p\u003e\n\u003cp\u003eKCLC: Conceptualization, Methodology, Writing - Review \u0026amp; Editing, Funding acquisition, Supervision, Project administration\u003c/p\u003e\n\u003cp\u003eBG: Writing - Review \u0026amp; Editing\u003c/p\u003e\n\u003cp\u003eGH: Writing - Review \u0026amp; Editing,\u003c/p\u003e\n\u003cp\u003eGH: Writing - Review \u0026amp; Editing\u003c/p\u003e\n\u003cp\u003eKH: Writing - Review \u0026amp; Editing, Data Curation\u003c/p\u003e\n\u003cp\u003eBN: Writing - Review \u0026amp; Editing, Project administration\u003c/p\u003e\n\u003cp\u003eEMR: Conceptualization, Methodology, Writing - Review \u0026amp; Editing, Funding acquisition, Project administration\u003c/p\u003e\n\u003cp\u003eKR, Professor: Writing - Review \u0026amp; Editing\u003c/p\u003e\n\u003cp\u003eHOS: Conceptualization, Methodology, Writing - Review \u0026amp; Editing, Funding acquisition, Project administration\u003c/p\u003e\n\u003cp\u003eBKS: Writing - Review \u0026amp; Editing, Data Curation\u003c/p\u003e\n\u003cp\u003eCS: Writing - Review \u0026amp; Editing,\u003c/p\u003e\n\u003cp\u003eRV: Formal analysis, Writing - Review \u0026amp; Editing\u003c/p\u003e\n\u003cp\u003eCMJ: Conceptualization, Methodology, Writing - Review \u0026amp; Editing, Funding acquisition, Supervision, Project administration\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAcknowledgements\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eWe sincerely thank all study participants who have so kindly provided us with biological samples and background data for this study.\u003c/p\u003e\n\u003cp\u003eWe also want to thank all the healthcare workers that have contributed to facilitating the study by recruiting women, collecting biological samples, and meticulously collecting and cleaning the data. We especially want to thank our colleagues at Østfold Hospital Trust at the Centre of Laboratory Medicine and Department of Obstetrics and Gynecology.\u003c/p\u003e\n\u003cp\u003eCamilla F NYSTRAND, Ms. PhD, Anbjørg RANGBERG, Ms. MSc, Yvonne SANDBERG, Ms. MSc, Sigrid SJELMO, Ms. MSc\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eMunoz N, Castellsague X, de Gonzalez AB, Gissmann L. Chapter 1: HPV in the etiology of human cancer. Vaccine. 2006;24 Suppl 3:S3/1-10.\u003c/li\u003e\n \u003cli\u003eWiik J, Nilsson S, K\u0026auml;rrberg C, Strander B, Jacobsson B, Sengpiel V. Associations of treated and untreated human papillomavirus infection with preterm delivery and neonatal mortality: A Swedish population-based study. PLoS Med. 2021;18(5):e1003641.\u003c/li\u003e\n \u003cli\u003eV\u0026aelig;rnesbranden MR, Wiik J, Sj\u0026oslash;borg K, Staff AC, Carlsen KCL, Haugen G, et al. Maternal human papillomavirus infections at mid-pregnancy and delivery in a Scandinavian mother-child cohort study. Int J Infect Dis. 2021;108:574-81.\u003c/li\u003e\n \u003cli\u003eNiyibizi J, Mayrand MH, Audibert F, Monnier P, Brassard P, Laporte L, et al. Association Between Human Papillomavirus Infection Among Pregnant Women and Preterm Birth. JAMA Netw Open. 2021;4(9):e2125308.\u003c/li\u003e\n \u003cli\u003eAmbuhl LMM, Leonhard AK, Widen Zakhary C, Jorgensen A, Blaakaer J, Dybkaer K, et al. Human papillomavirus infects placental trophoblast and Hofbauer cells, but appears not to play a causal role in miscarriage and preterm labor. Acta Obstet Gynecol Scand. 2017;96(10):1188-96.\u003c/li\u003e\n \u003cli\u003eSlatter TL, Hung NG, Clow WM, Royds JA, Devenish CJ, Hung NA. A clinicopathological study of episomal papillomavirus infection of the human placenta and pregnancy complications. Mod Pathol. 2015;28(10):1369-82.\u003c/li\u003e\n \u003cli\u003eReily-Bell AL, Fisher A, Harrison B, Bowie S, Ray S, Hawkes M, et al. Human Papillomavirus. Pathogens. 2020;9(3).\u003c/li\u003e\n \u003cli\u003eGomez LM, Ma Y, Ho C, McGrath CM, Nelson DB, Parry S. Placental infection with human papillomavirus is associated with spontaneous preterm delivery. Hum Reprod. 2008;23(3):709-15.\u003c/li\u003e\n \u003cli\u003eLiu Y, You H, Chiriva-Internati M, Korourian S, Lowery CL, Carey MJ, et al. Display of complete life cycle of human papillomavirus type 16 in cultured placental trophoblasts. Virology. 2001;290(1):99-105.\u003c/li\u003e\n \u003cli\u003eYou H, Liu Y, Agrawal N, Prasad CK, Chiriva-Internati M, Lowery CL, et al. Infection, replication, and cytopathology of human papillomavirus type 31 in trophoblasts. Virology. 2003;316(2):281-9.\u003c/li\u003e\n \u003cli\u003eWeyn C, Thomas D, Jani J, Guizani M, Donner C, Van Rysselberge M, et al. Evidence of human papillomavirus in the placenta. J Infect Dis. 2011;203(3):341-3.\u003c/li\u003e\n \u003cli\u003eSkoczyński M, Goździcka-J\u0026oacute;zefiak A, Kwaśniewska A. Prevalence of human papillomavirus in spontaneously aborted products of conception. Acta Obstet Gynecol Scand. 2011;90(12):1402-5.\u003c/li\u003e\n \u003cli\u003eSteegers EA, von Dadelszen P, Duvekot JJ, Pijnenborg R. Pre-eclampsia. Lancet. 2010;376(9741):631-44.\u003c/li\u003e\n \u003cli\u003eGestational Hypertension and Preeclampsia: ACOG Practice Bulletin, Number 222. Obstet Gynecol. 2020;135(6):e237-e60.\u003c/li\u003e\n \u003cli\u003eKhosla K, Heimberger S, Nieman KM, Tung A, Shahul S, Staff AC, et al. Long-Term Cardiovascular Disease Risk in Women After Hypertensive Disorders of Pregnancy: Recent Advances in Hypertension. Hypertension. 2021;78(4):927-35.\u003c/li\u003e\n \u003cli\u003eStaff AC, Benton SJ, von Dadelszen P, Roberts JM, Taylor RN, Powers RW, et al. Redefining preeclampsia using placenta-derived biomarkers. Hypertension. 2013;61(5):932-42.\u003c/li\u003e\n \u003cli\u003eStaff AC, Redman CW, Williams D, Leeson P, Moe K, Thilaganathan B, et al. Pregnancy and Long-Term Maternal Cardiovascular Health: Progress Through Harmonization of Research Cohorts and Biobanks. Hypertension. 2016;67(2):251-60.\u003c/li\u003e\n \u003cli\u003eRedman CWG, Staff AC, Roberts JM. Syncytiotrophoblast stress in preeclampsia: the convergence point for multiple pathways. Am J Obstet Gynecol. 2022;226(2S):S907-S27.\u003c/li\u003e\n \u003cli\u003eStaff AC. The two-stage placental model of preeclampsia: An update. J Reprod Immunol. 2019;134-135:1-10.\u003c/li\u003e\n \u003cli\u003eJacobsen DP, R\u0026oslash;ysland R, Strand H, Moe K, Sugulle M, Omland T, et al. Cardiovascular biomarkers in pregnancy with diabetes and associations to glucose control. Acta Diabetol. 2022;59(9):1229-36.\u003c/li\u003e\n \u003cli\u003eal-Okail MS, al-Attas OS. Histological changes in placental syncytiotrophoblasts of poorly controlled gestational diabetic patients. Endocr J. 1994;41(4):355-60.\u003c/li\u003e\n \u003cli\u003eACOG Practice Bulletin No. 190: Gestational Diabetes Mellitus. Obstet Gynecol. 2018;131(2):e49-e64.\u003c/li\u003e\n \u003cli\u003eAplin JD, Myers JE, Timms K, Westwood M. Tracking placental development in health and disease. Nat Rev Endocrinol. 2020;16(9):479-94.\u003c/li\u003e\n \u003cli\u003eNiyibizi J, Zanr\u0026eacute; N, Mayrand MH, Trottier H. Association Between Maternal Human Papillomavirus Infection and Adverse Pregnancy Outcomes: Systematic Review and Meta-Analysis. J Infect Dis. 2020;221(12):1925-37.\u003c/li\u003e\n \u003cli\u003eMcDonnold M, Dunn H, Hester A, Pacheco LD, Hankins GD, Saade GR, et al. High risk human papillomavirus at entry to prenatal care and risk of preeclampsia. Am J Obstet Gynecol. 2014;210(2):138 e1-5.\u003c/li\u003e\n \u003cli\u003eFord JH, Li M, Scheil W, Roder D. Human papillomavirus infection and intrauterine growth restriction: a data-linkage study. J Matern Fetal Neonatal Med. 2017:1-7.\u003c/li\u003e\n \u003cli\u003ePandey D, Solleti V, Jain G, Das A, Shama Prasada K, Acharya S, et al. Human Papillomavirus (HPV) Infection in Early Pregnancy: Prevalence and Implications. Infect Dis Obstet Gynecol. 2019;2019:4376902.\u003c/li\u003e\n \u003cli\u003eCho G, Min KJ, Hong HR, Kim S, Hong JH, Lee JK, et al. High-risk human papillomavirus infection is associated with premature rupture of membranes. BMC Pregnancy Childbirth. 2013;13:173.\u003c/li\u003e\n \u003cli\u003eNimrodi M, Kleitman V, Wainstock T, Gemer O, Meirovitz M, Maymon E, et al. The association between cervical inflammation and histologic evidence of HPV in PAP smears and adverse pregnancy outcome in low risk population. Eur J Obstet Gynecol Reprod Biol. 2018;225:160-5.\u003c/li\u003e\n \u003cli\u003eLodrup Carlsen KC, Rehbinder EM, Skjerven HO, Carlsen MH, Fatnes TA, Fugelli P, et al. Preventing Atopic Dermatitis and ALLergies in Children-the PreventADALL study. Allergy. 2018;73(10):2063-70.\u003c/li\u003e\n \u003cli\u003eStephansson O, Petersson K, Bj\u0026ouml;rk C, Conner P, Wikstr\u0026ouml;m AK. The Swedish Pregnancy Register - for quality of care improvement and research. Acta Obstet Gynecol Scand. 2018;97(4):466-76.\u003c/li\u003e\n \u003cli\u003eTranquilli AL, Dekker G, Magee L, Roberts J, Sibai BM, Steyn W, et al. The classification, diagnosis and management of the hypertensive disorders of pregnancy: A revised statement from the ISSHP. Pregnancy Hypertens. 2014;4(2):97-104.\u003c/li\u003e\n \u003cli\u003eBouvard V, Baan R, Straif K, Grosse Y, Secretan B, El Ghissassi F, et al. A review of human carcinogens--Part B: biological agents. Lancet Oncol. 2009;10(4):321-2.\u003c/li\u003e\n \u003cli\u003eHumans IWGotEoCRt. Biological agents. Volume 100 B. A review of human carcinogens. IARC Monogr Eval Carcinog Risks Hum. 2012;100(Pt B):1-441.\u003c/li\u003e\n \u003cli\u003eAlberti KG, Zimmet PZ. Definition, diagnosis and classification of diabetes mellitus and its complications. Part 1: diagnosis and classification of diabetes mellitus provisional report of a WHO consultation. Diabet Med. 1998;15(7):539-53.\u003c/li\u003e\n \u003cli\u003eSkjaerven R, Gjessing HK, Bakketeig LS. Birthweight by gestational age in Norway. Acta Obstet Gynecol Scand. 2000;79(6):440-9.\u003c/li\u003e\n \u003cli\u003eTextor J, van der Zander B, Gilthorpe MS, Liskiewicz M, Ellison GT. Robust causal inference using directed acyclic graphs: the R package \u0026apos;dagitty\u0026apos;. Int J Epidemiol. 2016;45(6):1887-94.\u003c/li\u003e\n \u003cli\u003ePathak N, Dodds J, Zamora J, Khan K. Accuracy of urinary human papillomavirus testing for presence of cervical HPV: systematic review and meta-analysis. BMJ. 2014;349:g5264.\u003c/li\u003e\n \u003cli\u003eJong E, Mulder JW, van Gorp EC, Wagenaar JK, Derksen J, Westerga J, et al. The prevalence of human papillomavirus (HPV) infection in paired urine and cervical smear samples of HIV-infected women. J Clin Virol. 2008;41(2):111-5.\u003c/li\u003e\n \u003cli\u003eMartins JG, Biggio JR, Abuhamad A, [email protected] SfM-FMSEa. Society for Maternal-Fetal Medicine Consult Series #52: Diagnosis and management of fetal growth restriction: (Replaces Clinical Guideline Number 3, April 2012). Am J Obstet Gynecol. 2020;223(4):B2-B17.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-pregnancy-and-childbirth","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"prch","sideBox":"Learn more about [BMC Pregnancy and Childbirth](http://bmcpregnancychildbirth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/prch/default.aspx","title":"BMC Pregnancy and Childbirth","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Human papillomavirus and pregnancy, Placental dysfunction syndromes, Hypertensive disorders of pregnancy, Gestational, diabetes mellitus, Small for gestational age","lastPublishedDoi":"10.21203/rs.3.rs-5108443/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5108443/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBACKGROUND\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eHuman papillomaviruses are common in the urogenital tract amongst women of childbearing age. A few studies indicate a possible association between human papillomavirus infections in pregnancy and adverse pregnancy outcomes whilst other studies find no such association. We aimed to investigate the association between human papillomavirus infections during pregnancy and adverse pregnancy outcomes linked to placental dysfunction, including hypertensive disorders of pregnancy, gestational diabetes mellitus and newborns small for gestational age.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMATERIAL AND METHODS\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePregnant women from the general population in Norway and Sweden were enrolled at the time of routine mid-gestational ultrasound examination. Urine samples collected at mid-gestation in 950 and at delivery in 753 participants, were analyzed for 28 human papillomavirus genotypes, including 12 high-risk genotypes. Participants completed electronic questionnaires at enrollment and medical records were reviewed for background characteristics and for the following adverse pregnancy outcomes: hypertensive disorders of pregnancy including gestational hypertension, preeclampsia, superimposed preeclampsia, eclampsia and Hemolysis Elevated Liver enzymes and Low Platelets (HELLP) syndrome, gestational diabetes mellitus, and newborns small for gestational age.\u0026nbsp; Associations between adverse pregnancy outcomes and a) any human papillomavirus, high-risk human papillomavirus and human papillomavirus genotype 16 infection at mid-gestation, b) multiple genotype infections at mid-gestation, and c) persisting infections during pregnancy were assessed with univariable and multivariable logistic regression models. Missing covariates were imputed using multiple imputation.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRESULTS\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAt mid-gestation, 40% (377/950) of women were positive for any of the 28 genotypes, 24% (231/950) for high-risk genotypes and human papillomavirus 16 was found in 6% (59/950) of the women. Hypertensive disorders of pregnancy was observed in 9% (83/950), gestational diabetes mellitus in 4% (40/950) and newborns small for gestational age in 7% (67/950). Human papillomavirus infection with any genotype, high-risk or human papillomavirus genotype 16 at mid-gestation was not associated with adverse pregnancy outcomes. No associations were found for multiple genotype infections at mid-gestation or persisting infections.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCONCLUSION\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn a general population of pregnant women, we found no evidence of human papillomavirus infections during pregnancy being associated with hypertensive disorders of pregnancy, gestational diabetes mellitus, or newborns small for gestational age.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTRIAL REGISTRATION\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study is registered at ClincialTrials.gov; NCT02449850 on May 19\u003csup\u003eth\u003c/sup\u003e, 2015.\u003c/p\u003e","manuscriptTitle":"Human Papillomavirus Infections during Pregnancy and Adverse Pregnancy Outcomes: a Prospective Mother-Child Cohort Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-11-08 09:04:43","doi":"10.21203/rs.3.rs-5108443/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-10-16T21:56:50+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-10-11T07:39:37+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-10-01T11:36:18+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"82540394161136852356248390647734400743","date":"2024-10-01T06:12:10+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-09-27T15:45:14+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"120445135036588552294544611721103417319","date":"2024-09-27T08:01:29+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"265545741187200140431481251545854966563","date":"2024-09-25T14:09:58+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-09-25T13:17:49+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2024-09-23T12:28:39+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-09-19T12:18:30+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-09-19T12:18:26+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Pregnancy and Childbirth","date":"2024-09-18T08:47:13+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-pregnancy-and-childbirth","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"prch","sideBox":"Learn more about [BMC Pregnancy and Childbirth](http://bmcpregnancychildbirth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/prch/default.aspx","title":"BMC Pregnancy and Childbirth","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"5e7313bb-8fe7-4396-8980-67f4f83d68b3","owner":[],"postedDate":"November 8th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-11-25T16:01:44+00:00","versionOfRecord":{"articleIdentity":"rs-5108443","link":"https://doi.org/10.1186/s12884-024-06958-2","journal":{"identity":"bmc-pregnancy-and-childbirth","isVorOnly":false,"title":"BMC Pregnancy and Childbirth"},"publishedOn":"2024-11-19 15:57:31","publishedOnDateReadable":"November 19th, 2024"},"versionCreatedAt":"2024-11-08 09:04:43","video":"","vorDoi":"10.1186/s12884-024-06958-2","vorDoiUrl":"https://doi.org/10.1186/s12884-024-06958-2","workflowStages":[]},"version":"v1","identity":"rs-5108443","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5108443","identity":"rs-5108443","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}