Pre-pregnancy body mass index and gestational weight gain - impact on pregnancy and neonatal health in the Polish population

Pre-pregnancy body mass index and gestational weight gain - impact on pregnancy and neonatal health in the Polish population | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Pre-pregnancy body mass index and gestational weight gain - impact on pregnancy and neonatal health in the Polish population Justyna Marchewka-Długońska, Joanna Nieczuja-Dwojacka, Krystyna Krygowska, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5683886/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 04 Mar, 2025 Read the published version in Scientific Reports → Version 1 posted 10 You are reading this latest preprint version Abstract Overweight and obesity are significant public health concerns, affecting pregnant women and potentially leading to numerous complications for both maternal and neonatal health. The aim of this study is to estimate how pre-pregnancy overweight and obesity, as well as gestational weight gain, influence pregnancy outcomes and neonatal health in Poland. The study material consisted of data from 2,878 women aged 16–46 years from hospitals in Warsaw and Krosno. The analysis included data on the course of singleton pregnancies and the biological condition of the newborns, correlated with pre-pregnancy Body Mass Index (BMI) and gestational weight gain (GWG), which were compared to the standards set by the Institute of Medicine (IOM). Gestational diabetes, hypertension, cesarean section, perineal injuries, and retained placenta occurred significantly more often in women with overweight and obesity compared to women with normal body weight. Pre-pregnancy BMI had the greatest impact on the occurrence of gestational diabetes, hypertension, and perineal injuries. At the same time, diabetes was more frequently observed in women who gained weight by IOM standards. Newborns delivered by women who were overweight and obesity were significantly larger than those born to women with normal body weight. Gestational weight gain played substantial role in shaping mentioned parameters. The likelihood of macrosomia, perinatal injuries, and breastfeeding difficulties increased among women with overweight and obesity. Health sciences/Medical research Health sciences/Risk factors overweight obesity pregnancy neonatal newborn outcomes Introduction The World Health Organization (WHO) estimates that nearly 60% of the adult population and every third child are affected by overweight or obesity [ 1 ]. It indicates that the proportion of individuals struggling with these conditions has nearly tripled since 1975, allowing their prevalence to be classified as a pandemic [ 2 , 3 ]. This issue affects all nationalities, regardless of socioeconomic status [ 4 ], and importantly, both overweight and obesity are recognized as risk factors for numerous diseases [ 5 , 6 , 7 ]. Additionally, excessive body weight significantly impacts the overall quality of life of affected individuals [ 8 ] and increases their mortality rate [ 9 ]. The prevalence of overweight and obesity also concerns women of reproductive age. According to research presented by Stoś et al. [ 10 ], approximately 45% of women aged 18 to 49 in Poland struggle with excessive body weight. In the context of the increasingly advanced age at which women choose to have children—thereby increasing the age at which they have their first child—it is important to note that the proportion of women with overweight and obesity increases with age. Among women aged 18–29 years, the percentage of those with overweight and obesity is nearly 34%, while in the age group of 40–49 years, it rises to just over 63% [ 11 ]. Undoubtedly, this increase in the prevalence of overweight and obesity among women with age may result from a higher likelihood of postpartum weight retention from previous pregnancies. According to research, postpartum weight retention is a widespread issue and is often addressed in scientific studies and research [ 12 , 13 ]. Regardless of the underlying causes, overweight and obesity significantly impact reproductive capabilities in both women and men, substantially raising the risk of reduced or complete infertility [ 14 , 15 ]. Women with overweight and obesity experience earlier onset of menarche and nearly three times higher rates of menstrual irregularities [ 16 ] and anovulatory cycles [ 17 ]. Obesity may also diminish the fertilization potential of oocytes. As demonstrated by Machtinger et al. [ 18 ], oocytes from women with obesity are smaller and exhibit more spindle anomalies and chromosomal defects. Similarly, the effectiveness of in vitro fertilization is lower, which is attributed to the poorer quality of oocytes in women with normal body weight compared to those with obesity [ 19 ]. Pregnancies in women with overweight and obesity are more frequently accompanied by complications. Obese women experience a higher incidence of miscarriages [ 20 , 21 ] and are also more prone to gestational diabetes [ 22 , 23 ], preeclampsia, eclampsia, and hypertension [ 24 , 25 , 26 ]. Furthermore, labor in obese women is often more complicated, lasting longer, more frequently requiring induction (including the administration of oxytocin), and more often ending in cesarean delivery [ 27 ]. Postpartum hemorrhages are also more common in this group [ 28 ], and labor duration tends to be prolonged [ 29 ]. Maternal overweight and obesity, particularly obesity, also have a significant impact on the biological condition of newborns. Obese women are more likely to experience preterm births [ 30 ], although some studies suggest that a BMI above 50 predisposes to post-term deliveries [ 31 ]. Findings from several meta-analyses also indicate a relationship between maternal BMI and the occurrence of macrosomia in newborns, defined as a birth weight exceeding 4000 g, as well as large-for-gestational-age birth weight, characterized by a birth weight above the 90th percentile [ 32 ]. Similar associations concerning the risk of pregnancy complications, labor difficulties, and their impact on newborn outcomes have also been observed with excessive weight gain during pregnancy. Total GWG is calculated as the difference between the weight at the first prenatal visit and the weight at the last prenatal visit just prior to delivery. According to the recommendations of the Institute of Medicine (IOM) [ 33 ], the amount of weight women should gain during pregnancy is determined by specific ranges based on pre-pregnancy BMI. Similar to the pre-pregnancy BMI described above, excessive weight gain during pregnancy can adversely affect the occurrence of pregnancy complications and newborn outcomes [ 34 , 35 ]. Retention of excess weight after pregnancy is also significant, impacting the woman’s health and potentially influencing the course of subsequent pregnancies [ 36 , 37 ]. Given the aforementioned issues, the objectives of this study were to examine how pre-pregnancy overweight and obesity affect pregnancy outcomes and newborn outcomes. Similarly, the study investigated how weight gain during pregnancy exceeding the standards set by the IOM influenced pregnancy outcomes and newborn outcomes. Material and methods The research material consisted of data collected from medical records of women giving birth at St. Zofia’s Hospital in Warsaw (1554 women) and the John Paul II Province Hospital in Krosno (1324 women). The data collection was conducted with the authorization of the Ethics Committee of the John Paul II Podkarpackie Province Hospital in Krosno, approved by the Cardinal Stefan Wyszynski University Ethics and Bioethics Committee for studies involving humans, and in accordance with the Declaration of Helsinki. All participants and/or their legal guardians provided informed consent, and all studies were conducted in full compliance with established standards. The age of the women ranged from 16 to 46 years, with a mean of 30.6 years (+/- 4.84). The analysis included information on singleton pregnancies and pregnancies without recorded fetal genetic abnormalities. Table 1 presents the characteristics of the studied women regarding age, parity, pre-pregnancy body weight, and weight gain during pregnancy. The table also includes the results of significance testing comparing women giving birth in Warsaw and Krosno (using the Mann-Whitney test, p < 0.05, following the application of the Shapiro-Wilk test). Table 1 Characteristics of the studied women. Warsaw (n = 1554) Krosno (n = 1324) Mann-Whitney test Mean (SD) range Mean (SD) range Age [years] 31.58 (4.84) 17.0–44.0 29.37 (5.30) 16.0–46.0 p < 0.001 (Z=-12.03) Delivery 1.56 (0,74) 1.0–6.0 1.84 (0.98) 1.0–11.0 p < 0.001 (Z = 6.09) Pre-pregnancy body weight [kg] 62.24 (10.88) 42.0-136.0 63.73 (12.32) 40.0-140.0 p = 0,005 (Z = 2.79) Changes in body weight 14.57 (4.93) 1.0–43.0 13.47 (5.18) -3.0-35.0 p < 0.001 (Z=-5.48) Despite the significant differences observed between women from Krosno and Warsaw, further analyses were conducted collectively for the entire group to provide the most average representation of the studied issue within the Polish population. This approach was also dictated by the relatively small number of women whose BMI classified them as obese. BMI was calculated as weight divided by height squared (kg/m²). Height and weight were measured during the first prenatal visit and before delivery using standard measurement techniques [ 21 ]. The BMI categories were identified according to international standards [ 38 ]. Respondents were categorized into three BMI groups: normal-weight (≥ 18.5–24.9 kg/m²), overweight (≥ 25.0–29.9 kg/m²), and obese (≥ 30.0 kg/m²). Weight change was calculated as the difference between pre-delivery and pre-pregnancy weight. The relationship between overweight and obesity among the participants and their parity was examined. For this purpose, the participants were divided into three groups: first-time mothers, second-time mothers, and those having their third or subsequent child. The analysis examined the relationship between overweight and obesity and infertility treatments, miscarriages (estimated as the difference between the number of pregnancies and births), pregnancy and perinatal complications (gestational diabetes, eclampsia, pregnancy-induced hypertension), PROM (Prelabor Rupture of Membranes), oligohydramnios, mode of delivery (cesarean section or vaginal delivery), perineal injuries during delivery (perineal lacerations), and incomplete placenta expulsion. Subsequently, the relationship between overweight and obesity in women and newborn outcomes was analyzed, including birth weight, birth length, the occurrence of macrosomia, perinatal injuries, and breastfeeding difficulties. The gestational weight gain was also analyzed, which according to the 2009 IOM guidelines should not exceed 18 kg for underweight women, 16 kg for women with normal body weight, 11.5 kg for overweight women, and 9 kg for obese women. The women were divided into two groups based on GWG, about the 2009 IOM guidelines: those whose weight gain was below or within the norm, and those whose weight gain exceeded the IOM guidelines. Statistical analysis was performed using Statistica 13.0 software. To examine the relationships between variables, Spearman's rank correlation analysis, and linear and logistic regression were used, and to estimate the odds ratio, logistic regression analysis was applied. The significance of differences was analyzed using the Mann-Whitney tests (after applying the Shapiro-Wilk test) and ANOVA. For nominal variables, the χ 2 test was used for p < 0.05. Results The study investigated whether the described trend in the literature—regarding the increase in body weight and BMI with subsequent pregnancies—was observed in the examined group of women. It also analyzed how gestational weight gain varied among women giving birth for the first, second, third, and subsequent times. The results are presented in Table 2 . The applied Tukey post hoc test revealed that, in the case of pre-pregnancy weight, the mean values for women giving birth for the third and subsequent times were statistically significantly higher than for primiparas and those giving birth for the second time (first birth vs. third and subsequent: p < 0.001; second birth vs. third and subsequent: p < 0.001). No significant differences in mean pre-pregnancy weight were observed between women giving birth for the first and second times ( p = 0.1592). For the mean pre-pregnancy BMI, the Tukey post hoc test revealed that the mean BMI values of women in subsequent pregnancies were statistically significantly higher (primiparas vs. second pregnancy: p = 0.006; second pregnancy vs. third and subsequent pregnancies, as well as first vs. third and subsequent pregnancies: p < 0.001). Table 2 Pre-pregnancy body weight, pre-pregnancy BMI and weight change during pregnancy and delivery order. Weight Pre-pregnancy BMI Changes in body weight Mean (SD) range Mean (SD) range Mean (SD) range First birth (n = 1434) 62.05 (11.50) 42.0-140.0 22.39 (3.85) 14.54–49.60 14.51 (5.01) -1.0-34.0 Secon birth (n = 1060) 62.90 (11.24) 40.0-117.0 22.78 (3.87) 15.62–44.58 13.95 (5.13) -3.0-43.0 Third and subsequent births (n = 384) 66.22 (12.25) 42.0-126.0 24.04 (4.12) 16.73–41.52 12.71 (4.89) 1.0–29.0 ANOVA p < 0,001 (F = 19.86) p < 0,001 (F = 27.42) p < 0,001 (F = 19.60) Spearman correlation R = 0.1120; p < 0.001 (t(N-2) = 5.99) R = 0.1400; p < 0.001 (t(N-2) = 7.58) R = -0.1084; p < 0.001 (t(N-2) = -5.85) Regarding the mean GWG, an opposite trend was observed: the average weight gain during the first pregnancy was significantly higher than during the second, third, and subsequent pregnancies (primiparas vs. second pregnancy: p = 0.017; second pregnancy vs. third and subsequent pregnancies, as well as first vs. third and subsequent pregnancies: p < 0.001). The conducted Spearman's rank correlation analysis confirmed that the relationships described above were statistically significant. Next, the impact of overweight and obesity on women's reproductive abilities was examined. The analysis included infertility treatment among women and the occurrence of at least one miscarriage in their medical history. In the studied group, no statistically significant relationships were observed. However, in the case of infertility treatment, the percentage of women undergoing this procedure was highest in the obesity group. Regarding the history of miscarriage, no statistically significant relationship with pre-pregnancy BMI was found; however, it was noted that this percentage increased across successive BMI categories (Table 3 ). Table 3 Infertility treatment and miscarriage occurrence. Factors Per-pregnancy BMI No n[%] Yes n[%] Infertility treatment Normal weight (n = 2242) 2213 [98.71] 29 [1.29] Overweight (n = 478) 474 [99.16] 4 [0.84] Obesity (n = 158) 155 [98.10] 3 [1.90] χ 2 p = 0.5398 (χ = 1.2333; df = 2) Miscarriages Normal weight (n = 2242) 1859 [82.92] 383 [17.08] Overweight (n = 478) 396 [82.85] 82 [17.15] Obesity (n = 158) 130 [82.28] 28 [17.72] χ 2 p = 0.9789 (χ = 0.0426; df = 2) Complications of pregnancy and childbirth To evaluate the relationship between pre-pregnancy BMI, GWG, and the occurrence of selected pregnancy and childbirth complications, the first step was to estimate the proportion of women in each BMI category who gained weight by IOM recommendations (or less) versus those who exceeded these values. Based on the collected data, it was noted that for women with overweight and obesity, the proportion of individuals who gained more than the IOM-recommended values was more than twice as high compared to those who adhered to or stayed below the guidelines (Table 4 ). Table 4 Weight changes in accordance with IOM, depending on pre-pregnancy BMI. IOM standards Pre-pregnancy BMI Normal weight (n = 2242) Overweight (n = 478) Obesity (n = 158) At or below standard 1601 [71.41] 178 [37.24] 63 [39.87] Above standard 641 [28.59] 300 [62.76] 95 [60.13] χ 2 p < 0.0001 (χ = 241.93; df = 2) In the next step, the relationship between pregnancy and childbirth complications, pre-pregnancy BMI, and gestational weight gain was analyzed. GWG was assessed based on whether weight gain during pregnancy was below, within, or above the ranges recommended by IOM standards (Table 5 ). Regarding the occurrence of gestational diabetes mellitus, the likelihood of developing this condition increased among overweight women and was the highest among obese women. The correlation coefficient (r) values indicate that pre-pregnancy BMI had a greater influence on the occurrence of gestational diabetes mellitus (GDM) than GWG. Adherence to IOM-recommended weight gain ranges did not appear to mitigate this risk. Interestingly, in the studied group, GDM was more frequently observed among women who gained weight by the IOM standards. Table 5 Pre-pregnancy BMI and GWG in relation to pregnancy and perinatal complications. Pre-pregnancy BMI GWG according IOM Normal weight (n = 2242) Overweight (n = 478) Obesity (n = 158) At or below standard (n = 1842) Above standard (n = 1036) Gestational diabetes mellitus No n[%] 2092 [93.31] 432 [90.38] 134 [84.81] 1663 [90.28] 995 [96.04] Yes n[%] 150 [6.69] 46 [9.62] 24 [15.19] 179 [9.72] 41 [3.69] Odds ratio (95% CI) 1 1.48 (1.05–2.10) 2.43 (1.41–4.17) - χ 2 p = 0.0001 (χ = 18.28; df = 2) p = 0.0001 (χ = 31.16; df = 1) p, R, R 2 regression p < 0.0001 ; R = 0,112; R 2 = 0.012 p < 0.0001 ; R = 0.104; R 2 = 0.011 Gestational hypertension No n[%] 2159 [96.30] 422 [88.28] 129 [81.65] 1795 [95.49] 951 [91.80] Yes n[%] 83 [3.70] 56 [11.72] 29 [18.35] 86 [4.51] 85 [8.20] Odds ratio (95% CI) 1 3.45 (2.42–4.92) 2.42 (1.92–3.04) 1 2.112 (1.716–2.863) χ 2 p < 0.0001 (χ = 93.68; df = 2) p < 0.0001 (χ = 16.50; df = 1) p, R, R 2 regression p < 0.0001 ; R = 0.180; R 2 = 0.032 p < 0.0001 ; R = 0.076; R 2 = 0.006 Caesarean section No n[%] 1443 [64.42] 272 [57.14] 81 [51.27] 1190 [64.74] 606 [58.49] Yes n[%] 797 [35.58] 204 [42.86] 77 [48.73] 648 [35.26] 430 [41.51] Odds ratio (95% CI) 1 1.36 (1.11–1.66) 1.25 (1.08–1.43) 1 2.36 (1.88–2.97) χ 2 p = 0.0019 (χ = 10.63; df = 2) p = 0.0009 (χ = 11.04; df = 1) p, R, R 2 regression p = 0.0001 ; R = 0.075; R 2 = 0.006 p = 0.0012 ; R = 0.060 R 2 = 0.004 PROM No n[%] 2181 [97.28] 459 [96.03] 154 [97.47] 1789 [97.12] 1005 [97.01] Yes n[%] 61 [2.72] 19 [3.97] 4 [2.53] 53 [2.88] 91 [2.99] Odds ratio (95% CI) 1 1.48 (0.88–2.49) 0.91 (0.49–1.89) 1 1.04 (0.67–1.62) χ 2 p = 0.3206 (χ = 2.27; df = 2) p = 0.8604 (χ = 0.0309; df = 1) p, R, R 2 regression p = 0.3208; R = 0. 008 R 2 = 0.001 p = 0.8604; R = 0.003 R 2 < 0.001 Eclampsia No n[%] 2227 [99.33] 475 [99.37] 157 [99.37] 1827 [99.19] 1032 [99.61] Yes n[%] 15 [0.67] 3 [0.63] 1 [0.63] 15 [0.81] 4 [0.39] Odds ratio (95% CI) - - χ 2 p = 0.5398 (χ = 1.23; df = 2) p = 0.1733 (χ = 1.85; df = 1) p, R, R 2 regression p = 0.9939; R = 0,002 R 2 < 0.001 p = 0.1734; R = 0.026 R 2 = 0.001 Oligohydramnios No n[%] 2220 [99.02] 473 [98.95] 154 [97.47] 1819 [98.75] 1028 [99.23] Yes n[%] 22 [0.98] 5 [1.05] 4 [2.53] 23 [1.25] 8 [0.77] Odds ratio (95% CI) 1 1.07 (0.39–2.91) 1.61 (0.94–2.78) - χ 2 p = 0.1887 (χ = 3.33; df = 2) p = 0.2346 (χ = 1.1413; df = 1) p, R, R 2 regression p = 0.1889; R = 0.034 R 2 = 0.001 p = 0.2348; R = 0.022 R 2 = 0.001 NATURAL BIRTH Normal weight (n = 1443) Overweight (n = 272) Obesity (n = 81) At or below standard (n = 1842) Above standard (n = 1036) Perineal lacerations No n[%] 784 [51.84] 126 [46.32] 39 [48.15] 623 [52.35] 290 [47.85] Yes n[%] 695 [48.16] 146 [53.68] 42 [51.85] 567 [47.65] 316 [52.15] Odds ratio (95% CI) 1 0.48 (0.387 − 0.06.1) 1.08 (0.86–1.35) 1 1.18 (0.98–1.46) χ 2 p = 0.2200 (χ = 3.03; df = 2) p = 0.0714 (χ = 3.2506; df = 1) p, R, R 2 regression p = 0.2203; R = 0.041 R 2 = 0.001 p = 0.0715; R = 0.042 R 2 = 0.002 Retained placenta No n[%] 1374 [95.28] 255 [93.59] 75 [92.59] 1129 [94.87] 575 [95.04] Yes n[%] 68 [4.72] 18 [6.25] 6 [7.41] 61 [5.13] 30 [4.96] Odds ratio (95% CI) 1 0.75 (0.43–1.28) 1.27 (0.82–1.96) - χ 2 p = 0.3530 (χ = 2.08; df = 2) p = 0.8786 (χ = 0.02; df = 1) p, R, R 2 regression p = 0.3533; R = 0.034 R 2 = 0.001 p = 0.8786; R = 0.004; R 2 < 0.001 The prevalence of gestational hypertension depended on both pre-pregnancy BMI and gestational weight gain within the IOM recommendations. However, correlation coefficient (r) values indicate that pre-pregnancy BMI had a greater impact on the development of this condition. A similar relationship was observed concerning the frequency of cesarean deliveries. Regarding PROM and oligohydramnios, these conditions were more frequently recorded among women with overweight and obesity; however, these differences were not statistically significant. Additionally, in the case of PROM, excessive GWG slightly increased its likelihood. Conversely, for oligohydramnios, no such association was observed. Interestingly, this condition was more frequently noted in women whose weight gain aligned with the IOM recommendations. Perinatal complications during vaginal deliveries, such as perineal injuries and retained placenta, were more frequently observed in women with overweight and obesity. For perineal injuries, it was also shown that they occurred slightly more often in women whose gestational weight gain exceeded the values recommended by the IOM. Pre-pregnancy BMI had a somewhat greater influence on the occurrence of perineal injuries. In contrast, no similar associations were recorded for eclampsia in the studied sample. This condition was slightly more common in the group of women with a BMI < 25 and those whose GWG was within the IOM recommendations. However, these results may be influenced by the overall low number of cases (a total of 19), which in turn could be attributed to the standards of care and early prevention. Table 6 presents the mean values for birth weight and length, APGAR scores in the first minute of life, and the occurrence of selected newborn parameters based on the pre-pregnancy BMI of the studied women and whether their GWG was within the ranges recommended by the IOM standards. Table 6 Relationship between neonatal birth parameters and women's pre-pregnancy BMI and GWG at or above IOM recommendations. Pre-pregnancy BMI GWG according IOM Normal weight Overweight Obesity At or below standard (n = 1842) Above standard (n = 1036) Body mass [g] Male Mean (+/-SD) 3453.2 (488.63) 3574.1 (474.3) 3551.3 (587.6) 3389.1 (486.9) 3630.6 (468.7) range 1320.0-4860.0 1800.0-4830.0 1100.0-5310.0 1100.0-4800.0 2240.0-5310.0 p, R and R 2 for regresion p = 0.0009 ; R = 0.098; R 2 = 0.010 p < 0.0001 ; R = 0.236; R 2 = 0.056 Female Mean (+/-SD) 3314.6 (480.23) 3462.3 (540.9) 2515.4 (509.8) 3257.3 (493.4) 3520.8 (453.5) range 3314.6 (480.28) 500.0-5270.0 2300.0-5000.0 500.0-470.0 2130–5270 p, R and R 2 for regresion p < 0.0001 ; R = 0.137; R 2 = 0.017 p < 0.0001 ; R = 0.256; R 2 = 0.066 Total Mean (+/-SD) 3383.9 (489.21) 3521.3 (509.8) 3532.9 (547.6) 3322.1 (494.5) 3579.8 (464.2) range 800.0-4860.0 500.0-5270.0 1100.0-5310.0 500.0-4800.0 2130.0-5130.0 p, R and R 2 for regresion p < 0.0001 ; R = 0.1116; R 2 = 0.014 p < 0.0001 ; R = 0.248; R 2 = 0.061 Body lenght [cm] Male Mean (+/-SD) 54.9 (2.81) 55.38 (2.73) 55.25 (3.50) 54.6 (2.87) 55.7 (2.60) range 44.0–62.0 45.0–62.0 37.0–62.0 37.0–62.0 48.0–62.0) p, R and R 2 for regresion p = 0.0407 ; R = 0.006; R 2 = 0.004 p < 0.0001 ; R = 0.186; R 2 = 0.034 Female Mean (+/-SD) 54.1 (2.92) 54.87 (3.42) 54.80 (2.912) 53.6 (3.05) 54.95 (2.82) range 35.0–63.0 25.0–63.0 46.0–65.0 25.0–63.0 35.0–65.0 p, R and R 2 for regresion p = 0.0003; R = 0.107; R 2 = 0.011 p < 0.0001 ; R = 0.171; R 2 = 0.029 Total Mean (+/-SD) 54.48 (2.88) 55.1 (3.09) 55.02 (3,21) 54.2 (2.99) 55.3 (2.73) range 35.0–63.0 25.0–63.0 37.0–65.0 25.0–63.0 35.0–65.0 p, R and R 2 for regresion p < 0.0001 ; R = 0.087; R 2 = 0.008 p < 0.0001 ; R = 0.180; R 2 = 0.032 APGAR 1 Male Mean (+/-SD) 9.78 (90.72) 9.75(0.92) 9.42 (1.52) 9.785 (0.77) 9.72 (0.90) range 3.0–10.0 0.0–10.0 3.0–10.0 0.00–10.0 3.0–10.0 p, R and R 2 for regresion p = 0.0006 ; R = 0.101; R 2 = 0.010 p < 0.1374; R = 0.039; R 2 = 0.001 Female Mean (+/-SD) 9.81 (0.76) 9.62 (1.27) 9.71 (0.66) 9.76 (0.86) 9.78 (0.84) range 1.0–10.0 1.0–10.0 7.0–10.0 1.0–10.0 1.0–10.0 p, R and R 2 for regresion p = 0.0186 ; R = 0.074; R 2 = 0.005 p < 0.6223; R = 0.013; R 2 < 0.001 Total Mean (+/-SD) 9.79 (0.74) 9.69 (1.11) 9.57 (1.16) 9.77 (0.82) 9.75 (0.88) range 1.0–10.0 0.0–10.0 3.0–10.0 0.0–10.0 1.0–10.0 p, R and R 2 for regresion p = 0.0006; R = 0.072; R 2 = 0.005 p = 0.487; R = 0.013; R 2 < 0.001 Other birth parameters Normal weight (n = 2239) Overweight (n = 478) Obesity (n = 158) At or below standard (n = 1836) Above standard (n = 1036) Makrosomia No n[%] 2032 [90,80] 409 [85.56] 130 [82.28] 1171 [93.19] 858 [82.82] Yes n[%] 207 [9.21] 69 [14.44] 28 [17.72] 125 [6.81] 178 [17.18] Odds ratio (95% CI) 1 1.67 (1.24–2.23) 1.32 (1.17–1.82) 1 2.83 (2.23–3.62) χ 2 p = 0.0003 (χ = 20.87; df = 2) p < 0.0001 (χ = 70.51; df = 1) p, R, R 2 regresion p < 0.0001 ; R = 0.085; R 2 = 0.007 p < 0.0001 ; R = 0.162; R 2 = 0.026 Perinatal injuries No n[%] 2181 [97.41] 456 [95.40] 150 [94.94] 1786 [97.28] 999 [96.43] Yes n[%] 58 [2.59] 22 [4.60] 8 [5.06] 50 [2.72] 37 [3.57] Odds ratio (95% CI) 1 1.82 (1.10–2.99) 1.32 (0.88–1.97) 1 1.32 (0.86–2.04) χ 2 p = 0.0371 (χ = 6.59; df = 2) p = 0.1974 (χ = 1.66; df = 1) p, R, R 2 regresion p = 0.0371 ; R = 0.048; R 2 = 0.002 p = 0.1975; R = 0.024; R 2 = 0.001 Breastfeeding difficulties No n[%] 1812 [80.92] 359 [75.10] 116 [73.42] 1469 [80.02] 815 [78.67] Yes n[%] 427 [19.08] 119 [24.90] 42 [26.58] 367 [19.98] 221 [21.33] Odds ratio (95% CI) 1 5.99 (4.45–8.05) 5.27 (4.16–6.68) 1 0.92 (0.76–1.11)) χ 2 p = 0.0023 (χ =12.18; df = 2) p = 0.3685 (χ = 0.81; df = 1) p, R, R 2 regresion p = 0.0003 (χ =20.87; df = 2) p = 0.3687; R = 0.011; R 2 < 0.001 For changes in measurable parameters, such as birth weight, length, and APGAR scores, the analysis accounted for the newborn's sex to explore potential differences between male and female infants. Newborns of both sexes born to women with overweight and obesity were heavier and longer than those born to women with a BMI < 25. For both birth weight and length, the r values indicate that GWG had a greater influence on these parameters than the mother’s pre-pregnancy BMI. In terms of GWG and pre-pregnancy BMI, both were found to slightly influence the birth weight of female newborns more strongly, but this difference was small and statistically insignificant. No similar associations were observed for APGAR scores. The probability of macrosomia, birth injuries, and feeding difficulties increased in newborns of women with overweight and obesity. While gestational weight gain had a statistically significant impact on the occurrence of macrosomia, with the r values indicating its greater importance, it was not a contributing factor in the cases of birth injuries or feeding difficulties. Discussion In this study, it was found that both pre-pregnancy weight and gestational weight gain, as well as BMI during pregnancy, significantly influenced selected parameters of maternal health and newborn outcomes. The literature contains numerous reports highlighting the increased pre-pregnancy weight of women having their second, third, or subsequent births compared to first-time mothers [ 39 , 40 , 41 ]. Some researchers suggest that the increasing weight of women with subsequent pregnancies is a result of postpartum weight retention. However, many authors believe that factors such as the age of menarche and the short interval between menarche and the first childbirth are equally important. The findings indicate that these factors may also contribute to the development of overweight status following pregnancy [ 18 , 42 ]. In the present study, the average GWG during the first pregnancy was significantly higher than in the second, third, and subsequent pregnancies. Heery et al. [ 43 ] observed a similar trend. Many women indulge in snacking and satisfying food cravings during pregnancy. At the same time, they give up physical activity out of concern for potential risks to the fetus. However, during subsequent pregnancies, women were more apprehensive about gaining excessive weight again, as they had faced challenges losing weight after previous deliveries. At the same time, most women did not consider that having previously delivered a macrosomic newborn could influence their lifestyle choices. In the studied group of women, no statistically significant relationship was found between undergoing infertility treatment and obesity. However, the highest percentage of women undergoing such procedures was observed in the overweight and obese groups. Similar findings have been reported by many authors. It is noted that individuals with obesity respond less effectively to ovulation induction and require higher doses of gonadotropins. Additionally, it is believed that overweight and obesity may affect oocyte activity, endometrial receptivity, fertilization rates, and the number of embryos obtained [ 44 , 45 , 46 ]. Some researchers also suggest that even significant weight loss in obese women before in vitro fertilization (IVF) procedures did not improve live birth rates [ 47 ]. George et al. [ 48 ] reported that IVF outcomes and newborn parameters in overweight and obese individuals were similar to those in women with normal body weight. However, the study emphasized the critical role of specialized obstetric and gynecological care in qualified hospitals. On the other hand, Zheng et al. [ 49 ] observed no association between BMI and the likelihood of achieving pregnancy or delivering a live baby, though the risk of miscarriage was higher. In the present study, no significant relationship was found between higher pre-pregnancy BMI and miscarriages. However, the percentage of miscarriages increased across successive BMI categories. It is widely believed that women with overweight or obesity face a significantly higher risk of miscarriage. This applies both to women who conceived naturally and those who underwent IVF [ 50 ]. Additionally, it is noted that individuals struggling with excessive body weight experience recurrent miscarriages more frequently compared to those with normal pre-pregnancy weight [ 51 ]. Some researchers also suggest that the increased risk of miscarriage is observed in obese women, but not in those who are merely overweight [ 52 ]. Researchers emphasize that maintaining a healthy pre-pregnancy BMI is crucial in preventing miscarriages [ 53 ]. The results of the conducted study suggest that in the case of women with overweight and obesity, more than twice as many participants increased their BMI beyond the levels recommended by IOM guidelines. A meta-analysis conducted in 2009 demonstrated that weight gain exceeding IOM recommendations occurred in 27.8% of cases, and this trend has continued to grow. In the United States, weight gain below, within, and above IOM guidelines has been observed in 5%, 13%, and 80% of overweight women, respectively, as well as in 17%, 13%, and 70% of obese women [ 34 , 54 ]. Interestingly, findings from Poland in 2019 suggest that mean pregnancy weight gain among overweight and obese women is lower than that of women with normal body weight [ 55 ]. The present study demonstrated that in women with overweight and obesity, the risk of developing gestational diabetes mellitus during pregnancy increased, with pre-pregnancy BMI having a greater impact on the occurrence of GDM. However, GDM was more frequently observed in women who gained weight by IOM guidelines. Najafi et al. [ 56 ] reported that the risk of developing GDM in the underweight/normal weight group was over 10%, while in the group of women with overweight and obesity, it was 23%. Other studies confirm that a higher risk of developing GDM is associated with higher pre-pregnancy BMI values and excessive weight gain during pregnancy [ 57 ]. Research findings also suggest that maintaining a stable body weight before pregnancy is extremely important, even in the five years before conception. Women who gained 2.3–10 kg per year before pregnancy had an increased risk of developing GDM compared to those with stable body weight [ 58 ]. The occurrence of gestational hypertension was also correlated with pre-pregnancy BMI values. Other researchers have estimated that women who were overweight or obese before pregnancy, as well as those whose GWG exceeded the recommendations set by the IOM, were more likely to experience hypertension during pregnancy compared to their normal-weight counterparts [ 59 , 60 ]. Slightly different results were obtained by Savitri et al. [ 61 ]. According to their findings, pre-pregnancy BMI values determined the blood pressure levels of pregnant women and were correlated with more frequent occurrences of gestational hypertension. However, gestational weight gain did not influence the increased prevalence of this pregnancy complication. A similar relationship was observed in the current study regarding the performance of cesarean sections. Researchers investigating cesarean sections have noted that women with pre-pregnancy obesity, as well as those who experience excessive gestational weight gain during pregnancy, are more likely to undergo a cesarean delivery. It has also been observed that the risk of cesarean section increases in women who had a normal pre-pregnancy weight but gained more weight during pregnancy than recommended by the IOM guidelines [ 62 ]. Other studies conducted in Poland also indicate similar trends [ 63 ]. The occurrence of PROM and oligohydramnios was more frequently recorded in women with overweight and obesity; however, these differences were not statistically significant. Similarly, the observation of eclampsia was not associated with overweight or obesity. Spontaneous preterm births with PROM were more frequently observed in overweight women who experienced greater gestational weight gain than recommended by the IOM guidelines. It was also noted that lower GWG during pregnancy was a significant factor in reducing the likelihood of preterm delivery [ 64 ]. In the studies by Feng and Huang [ 65 ] and Blitz et al. [ 66 ], similar results were obtained for oligohydramnios - this condition was not significantly associated with overweight or obesity. However, the article by Yayla Abide et al. [ 67 ] reported that among women with excessive GWG, the rate of oligohydramnios was higher than in women who gained weight within the recommended range. Findings from other authors regarding eclampsia differed from those obtained in the present study. It was noted that women with pre-pregnancy overweight or obesity, as well as excessive GWG, were more likely to develop preeclampsia compared to their normal-weight counterparts [ 68 ]. Perineal lacerations and retained placenta were more frequently observed among overweight and obese women in Poland compared to women with normal body weight. A significant association was identified both in cases where GWG exceeded the values recommended by the IOM and among women with elevated pre-pregnancy BMI. Other authors have reached similar conclusions [ 69 ]; however, Gallagher et al. [ 70 ] did not observe such associations. It is noted that the majority of the cited research findings are consistent. Women with pre-pregnancy BMI values above the normal range were more likely to experience health issues during pregnancy as well as more frequent labor complications. "It is also important to address the condition of newborns. Newborns of both sexes born to women with overweight and obesity were heavier and longer compared to those born to women with a BMI < 25. These findings align with the data reported by other researchers [ 71 ]. This may also influence women's experiences during pregnancy and childbirth, for example, the occurrence of perineal lacerations [ 72 ]. The gestational weight gain had a greater impact on shaping the above-mentioned birth parameters of the newborns than the pre-pregnancy BMI of the mothers. Similar relationships have also been observed in data published by other researchers. This represents a significant public health issue, as children with macrosomia have a considerably increased likelihood of developing overweight and obesity later in life [ 73 , 74 ]. In the case of APGAR scores, no influence of either pre-pregnancy BMI or excessive gestational weight gain during pregnancy was observed. Different results were reported in studies from the US. In pregnant women with excessive GWG during pregnancy versus those without condition, APGAR was significantly lower compared to their normal-weight counterparts. This may be due to previously mentioned findings suggesting that women with excessive GWG during pregnancy experience more disturbances during both pregnancy and delivery [ 75 ]. Studies conducted in Poland suggest that the likelihood of experiencing breastfeeding difficulties increased among women with overweight and obesity. However, no problems with breastfeeding were noted in the case of excessive GWG. Similar results were observed among women in the US and China, where earlier-than-standard breastfeeding cessation occurred more frequently [ 76 , 77 ]. Many studies also suggest that increased pre-pregnancy BMI was associated with decreased breastfeeding initiation [ 78 , 79 , 80 ]. Although this is a common phenomenon, its mechanism remains unclear. It may result from the influence of increased body fat on prolactin and oxytocin, leading to delayed lactation. It is also believed that other health consequences of excessive body weight during pregnancy, such as gestational diabetes, gestational hypertension, and cesarean delivery, may contribute to the lack of breastfeeding initiation [ 81 , 82 , 83 ]. The increasingly common prevalence of overweight and obesity, combined with the observed steady rise in the age at which women have their first child, represents a global issue. This combination constitutes a growing problem, carrying not only financial consequences related to the care of pregnant women with excessive body weight and the health outcomes of their offspring but also serious demographic implications. The above studies have several limitations. The first is the relatively small study group, which resulted from restrictions in the medical record systems at hospitals. Pre-pregnancy body weight was not recorded for all patients, which prevented the collection of information on gestational weight gain. The second limitation is the combination of data from hospitals in Warsaw, the largest city in Poland, with data from a provincial hospital in Podkarpacie region. However, combining both datasets provided a more comprehensive view of pregnant women and newborn outcomes in Poland. The sample lacked women with morbid obesity (BMI above 40). Additionally, episiotomies and perineal lacerations were combined into a single factor -perineal injuries during delivery. This was due to the small sample size in individual groups when these factors were considered separately. Therefore, the authors of the study are concerned that the study group may not be fully representative. A low percentage of cases with eclampsia was also observed, which may, however, be attributable to good cardiac care and regular monthly visits by the patients. Declarations Author contributions Conceptualization: JMD, JND Design of the work: JMD, JND, MK Methodology: JMD Formal analysis: JMD Interpretation of the data: JMD Acquisition: KK, DS, BB Writing – draft version: JMD, JND Writing – review and editing: JMD, JND, KK, VB, MK, DS, BB All authors approved the submitted version. Data availability statement The data base of the mothers and the children information have not been made public to ensure the privacy of study participants, and are stored by the John Paul II Province Hospital in Krosno and in St. Zofia’s Hospital in Warsaw and are available from the corresponding author on reasonable request. Correspondence and requests for materials should be addressed to J.N.-D. Additional Information - Competing Interests Statement The author(s) declare no competing interests. References World Health Organization. Regional Office for Europe. WHO European Regional Obesity Report 2022. (2022). Chooi, Y. C., Ding, C. & Magkos, F. The epidemiology of obesity. Metabolism . 92 , 6-10. https://doi.org/10.1016/j.metabol.2018.09.005 (2019). Kumar, S. K. Y., Bhat, P. K. & Sorake, C. J. Double trouble: a pandemic of obesity and COVID-19. Lancet Gastroenterol Hepatol. 6 (8), 608. https://doi.org/10.1016/S2468-1253(21)00190-4 (2021). Blüher, M. 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Int J Environ Res Public Health . 18 (5), 2694. https://doi.org/10.3390/ijerph18052694 (2021). Hedderson, M. M., Williams, M. A., Holt, V. L., Weiss, N. S. & Ferrara, A. Body mass index and weight gain prior to pregnancy and risk of gestational diabetes mellitus. Am J Obstet Gynecol. 198 (4), 409.e1-7. https://doi.org/10.1016/j.ajog.2007.09.028 (2008). Zhou, A., Xiong, C., Hu, R., Zhang, Y., Bassig, B. A. & Triche, E. et al. Pre-Pregnancy BMI, Gestational Weight Gain, and the Risk of Hypertensive Disorders of Pregnancy: A Cohort Study in Wuhan, China. PLoS One . 10 (8), e0136291. https://doi.org/10.1371/journal.pone.0136291 (2015). Ito, M., Kyozuka, H., Yamaguchi, T., Sugeno, M., Murata, T. & Hiraiwa, T. et al. Association between Gestational Weight Gain and Risk of Hypertensive Disorders of Pregnancy among Women with Obesity: A Multicenter Retrospective Cohort Study in Japan. Nutrients . 15 (11), 2428. https://doi.org/10.3390/nu15112428 (2023). Savitri, A. I., Zuithoff, P., Browne, J. L., Amelia, D., Baharuddin, M. & Grobbee, D. E. et al. Does pre-pregnancy BMI determine blood pressure during pregnancy? A prospective cohort study. BMJ Open . 6 (8), e011626. https://doi.org/10.1136/bmjopen-2016-011626 (2016). Eloranta, A. M. , Gunnarsdottir, I., Thorisdottir, B., Gunnlaugsson, G., Birgisdottir, B. E. & Thorsdottir, I. et al. The combined effect of pre-pregnancy body mass index and gestational weight gain on the risk of pre-labour and intrapartum caesarean section-The ICE-MCH study. PLoS One . 18 (1), e0280060. https://doi.org/10.1371/journal.pone.0280060 (2023). Jaworowski, A., Micek, A., Kolak, M., Skibinska, K., Jurga, J. & Ptaszkiewicz, K. et al. Impact of body mass index and gestational weight gain on cesarean delivery rates: a comparative study of dinoprostone-induced vs spontaneous labor. Ginekol Pol . 17 . https://doi.org/10.5603/gpl.100230 (2024). Masho, S. W., Bishop, D. L. & Munn, M. Pre-pregnancy BMI and weight gain: where is the tipping point for preterm birth? BMC Pregnancy Childbirth . 13 , 120. https://doi.org/10.1186/1471-2393-13-120 (2013). Feng, N. & Huang, X., Effect of pre-pregnancy body mass index and gestational weight gain on perinatal outcomes, Int. J. Clin. Exp. Med . 14 (8), 2180-2188 (2021). Blitz, M. J., Rochelson, B., Stork, L. B., Augustine, S., Greenberg, M. & Sison, C. P. et al. Maternal Body Mass Index and Amniotic Fluid Index in Late Gestation. J. Ultrasound. Med . 37 (3), 561-568. https://doi.org/10.1002/jum.14362 (2018). Yayla Abide, C., Bostanci Ergen, E. & Kilicci, C., Association Between Gestational Weight Gain and Maternal and Neonatal Outcomes, East J. Med. 23 (2), 115-120. https://doi.org/10.5505/ejm.2018.49389 (2018). Shao, Y., Qiu, J., Huang, H., Mao, B., Dai, W. & He, X. et al. Pre-pregnancy BMI, gestational weight gain and risk of preeclampsia: a birth cohort study in Lanzhou, China. BMC Pregnancy Childbirth . 17 (1), 400. https://doi.org/10.1186/s12884-017-1567-2 (2017). Shao, F. X., He, P., Mao, Y. J., Liu, H. R., Wan, S. & Qin, S. et al. Association of pre-pregnancy body mass index and gestational weight gain on postpartum pelvic floor muscle morphology and function in Chinese primiparous women: A retrospective cohort study. Int. J. Gynaecol. Obstet . https://doi.org/10.1002/ijgo.15870 (2024). Gallagher, K., Migliaccio, L., Rogers, R. G., Leeman, L., Hervey, E. & Qualls, C. Impact of nulliparous women's body mass index or excessive weight gain in pregnancy on genital tract trauma at birth. J. Midwifery Women Health . 59 (1), 54-9. https://doi.org/10.1111/jmwh.12114 (2014). Liang, C. C., Chao, M., Chang, S. D. & Chiu, S. Y. Impact of prepregnancy body mass index on pregnancy outcomes, incidence of urinary incontinence and quality of life during pregnancy - An observational cohort study. Biomed J. 43 (6), 476-483. https://doi.org/10.1016/j.bj.2019.11.001 (2020). Turkmen, S., Johansson, S. & Dahmoun, M. Foetal Macrosomia and Foetal-Maternal Outcomes at Birth. J. Pregnancy . 2018 , 4790136. https://doi.org/10.1155/2018/4790136 (2018). Zhao, R., Xu, L., Wu, M. L., Huang, S. H. & Cao, X. J. Maternal pre-pregnancy body mass index, gestational weight gain influence birth weight. Women Birth . 31 (1), e20-e25. https://doi.org/10.1016/j.wombi.2017.06.003 (2018). Pongcharoen, T., Gowachirapant, S., Wecharak, P., Sangket, N. & Winichagoon, P. Pre-pregnancy body mass index and gestational weight gain in Thai pregnant women as risks for low birth weight and macrosomia. Asia Pac. J. Clin. Nutr. 25 (4), 810-817. https://doi.org/10.6133/apjcn.092015.41 (2016). Lackovic, M., Filimonovic, D., Mihajlovic, S., Milicic, B., Filipovic, I. & Rovcanin, M. et al. The Influence of Increased Prepregnancy Body Mass Index and Excessive Gestational Weight Gain on Pregnancy Course and Fetal and Maternal Perinatal Outcomes. Healthcare (Basel) . 8 (4), 362. https://doi.org/10.3390/healthcare8040362 (2020). Martin, H., Thevenet-Morrison, K. & Dozier, A. Maternal pre-pregnancy body mass index, gestational weight gain and breastfeeding outcomes: a cross-sectional analysis. BMC Pregnancy Childbirth . 20 (1), 471. https://doi.org/10.1186/s12884-020-03156-8 (2020). Tao, X. Y., Huang, K., Yan, S. Q., Zuo, A. Z., Tao, R. W. & Cao, H. et al. Pre-pregnancy BMI, gestational weight gain and breast-feeding: a cohort study in China. Public Health Nutr . 20 (6), 1001-1008. https://doi.org/10.1017/S1368980016003165 (2017). Hauff, L. E., Leonard, S. A. & Rasmussen, K. M. Associations of maternal obesity and psychosocial factors with breastfeeding intention, initiation, and duration. Am. J. Clin. Nutr . 99 , 524–534. https://doi.org/10.1093/ajcn/86.2.404 (2014). Winkvist, A., Brantsæter, A. L., Brandhagen, M., Haugen, M., Meltzer, H. M. & Lissner, L. Maternal prepregnant body mass index and gestational weight gain are associated with initiation and duration of breastfeeding among Norwegian mothers. J. Nutr. 145 , 1263–1270. https://doi.org/10.3945/jn.114.202507 (2015). Guelinckx, I., Devlieger, R., Bogaerts, A., Pauwels, S. & Vansant, G. The effect of pre-pregnancy BMI on intention, initiation and duration of breast-feeding. Public Health Nutr . 15 (5), 840-848. https://doi.org/10.1017/S1368980011002667 (2012). Otter, G., Davis, D., Kurz, E., Hooper, M. E., Shield, A. & Samarawickrema, I. et al. Promoting breastfeeding in women with gestational diabetes mellitus in high-income settings: an integrative review. Int. Breastfeed. J. 19 (1), 4. https://doi.org/10.1186/s13006-023-00603-y (2024). Strapasson, M. R., Ferreira, C. F. & Ramos, J. G. L. Feeding practices in the first 6 months after delivery: Effects of gestational hypertension. Pregnancy Hypertens . 13 , 254-259. https://doi.org/10.1016/j.preghy.2018.07.002 (2018). Hobbs, A. J., Mannion, C. A., McDonald, S. W., Brockway, M. & Tough, S. C. The impact of caesarean section on breastfeeding initiation, duration and difficulties in the first four months postpartum. BMC Pregnancy Childbirth . 16 , 90. https://doi.org/10.1186/s12884-016-0876-1 (2016). Additional Declarations No competing interests reported. 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It indicates that the proportion of individuals struggling with these conditions has nearly tripled since 1975, allowing their prevalence to be classified as a pandemic [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. This issue affects all nationalities, regardless of socioeconomic status [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e], and importantly, both overweight and obesity are recognized as risk factors for numerous diseases [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Additionally, excessive body weight significantly impacts the overall quality of life of affected individuals [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e] and increases their mortality rate [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe prevalence of overweight and obesity also concerns women of reproductive age. According to research presented by Stoś et al. [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e], approximately 45% of women aged 18 to 49 in Poland struggle with excessive body weight. In the context of the increasingly advanced age at which women choose to have children\u0026mdash;thereby increasing the age at which they have their first child\u0026mdash;it is important to note that the proportion of women with overweight and obesity increases with age. Among women aged 18\u0026ndash;29 years, the percentage of those with overweight and obesity is nearly 34%, while in the age group of 40\u0026ndash;49 years, it rises to just over 63% [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Undoubtedly, this increase in the prevalence of overweight and obesity among women with age may result from a higher likelihood of postpartum weight retention from previous pregnancies. According to research, postpartum weight retention is a widespread issue and is often addressed in scientific studies and research [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eRegardless of the underlying causes, overweight and obesity significantly impact reproductive capabilities in both women and men, substantially raising the risk of reduced or complete infertility [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Women with overweight and obesity experience earlier onset of menarche and nearly three times higher rates of menstrual irregularities [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e] and anovulatory cycles [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Obesity may also diminish the fertilization potential of oocytes. As demonstrated by Machtinger et al. [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e], oocytes from women with obesity are smaller and exhibit more spindle anomalies and chromosomal defects. Similarly, the effectiveness of \u003cem\u003ein vitro\u003c/em\u003e fertilization is lower, which is attributed to the poorer quality of oocytes in women with normal body weight compared to those with obesity [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e \u003cp\u003ePregnancies in women with overweight and obesity are more frequently accompanied by complications. Obese women experience a higher incidence of miscarriages [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e] and are also more prone to gestational diabetes [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e], preeclampsia, eclampsia, and hypertension [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Furthermore, labor in obese women is often more complicated, lasting longer, more frequently requiring induction (including the administration of oxytocin), and more often ending in cesarean delivery [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Postpartum hemorrhages are also more common in this group [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e], and labor duration tends to be prolonged [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eMaternal overweight and obesity, particularly obesity, also have a significant impact on the biological condition of newborns. Obese women are more likely to experience preterm births [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e], although some studies suggest that a BMI above 50 predisposes to post-term deliveries [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Findings from several meta-analyses also indicate a relationship between maternal BMI and the occurrence of macrosomia in newborns, defined as a birth weight exceeding 4000 g, as well as large-for-gestational-age birth weight, characterized by a birth weight above the 90th percentile [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSimilar associations concerning the risk of pregnancy complications, labor difficulties, and their impact on newborn outcomes have also been observed with excessive weight gain during pregnancy. Total GWG is calculated as the difference between the weight at the first prenatal visit and the weight at the last prenatal visit just prior to delivery. According to the recommendations of the Institute of Medicine (IOM) [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e], the amount of weight women should gain during pregnancy is determined by specific ranges based on pre-pregnancy BMI. Similar to the pre-pregnancy BMI described above, excessive weight gain during pregnancy can adversely affect the occurrence of pregnancy complications and newborn outcomes [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Retention of excess weight after pregnancy is also significant, impacting the woman\u0026rsquo;s health and potentially influencing the course of subsequent pregnancies [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eGiven the aforementioned issues, the objectives of this study were to examine how pre-pregnancy overweight and obesity affect pregnancy outcomes and newborn outcomes. Similarly, the study investigated how weight gain during pregnancy exceeding the standards set by the IOM influenced pregnancy outcomes and newborn outcomes.\u003c/p\u003e"},{"header":"Material and methods","content":"\u003cp\u003eThe research material consisted of data collected from medical records of women giving birth at St. Zofia\u0026rsquo;s Hospital in Warsaw (1554 women) and the John Paul II Province Hospital in Krosno (1324 women). The data collection was conducted with the authorization of the Ethics Committee of the John Paul II Podkarpackie Province Hospital in Krosno, approved by the Cardinal Stefan Wyszynski University Ethics and Bioethics Committee for studies involving humans, and in accordance with the Declaration of Helsinki. All participants and/or their legal guardians provided informed consent, and all studies were conducted in full compliance with established standards.\u003c/p\u003e \u003cp\u003eThe age of the women ranged from 16 to 46 years, with a mean of 30.6 years (+/- 4.84). The analysis included information on singleton pregnancies and pregnancies without recorded fetal genetic abnormalities. Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e presents the characteristics of the studied women regarding age, parity, pre-pregnancy body weight, and weight gain during pregnancy. The table also includes the results of significance testing comparing women giving birth in Warsaw and Krosno (using the Mann-Whitney test, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, following the application of the Shapiro-Wilk test).\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\u003eCharacteristics of the studied women.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eWarsaw (n\u0026thinsp;=\u0026thinsp;1554)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eKrosno (n\u0026thinsp;=\u0026thinsp;1324)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eMann-Whitney test\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean (SD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003erange\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMean (SD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003erange\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge [years]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e31.58 (4.84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e17.0\u0026ndash;44.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e29.37 (5.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e16.0\u0026ndash;46.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/b\u003e (Z=-12.03)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDelivery\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.56 (0,74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.0\u0026ndash;6.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.84 (0.98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.0\u0026ndash;11.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/b\u003e (Z\u0026thinsp;=\u0026thinsp;6.09)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePre-pregnancy body weight [kg]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e62.24 (10.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e42.0-136.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e63.73 (12.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e40.0-140.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003ep\u0026thinsp;=\u0026thinsp;0,005\u003c/b\u003e (Z\u0026thinsp;=\u0026thinsp;2.79)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChanges in body weight\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e14.57 (4.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.0\u0026ndash;43.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e13.47 (5.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-3.0-35.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/b\u003e (Z=-5.48)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eDespite the significant differences observed between women from Krosno and Warsaw, further analyses were conducted collectively for the entire group to provide the most average representation of the studied issue within the Polish population. This approach was also dictated by the relatively small number of women whose BMI classified them as obese.\u003c/p\u003e \u003cp\u003eBMI was calculated as weight divided by height squared (kg/m\u0026sup2;). Height and weight were measured during the first prenatal visit and before delivery using standard measurement techniques [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. The BMI categories were identified according to international standards [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. Respondents were categorized into three BMI groups: normal-weight (\u0026ge;\u0026thinsp;18.5\u0026ndash;24.9 kg/m\u0026sup2;), overweight (\u0026ge;\u0026thinsp;25.0\u0026ndash;29.9 kg/m\u0026sup2;), and obese (\u0026ge;\u0026thinsp;30.0 kg/m\u0026sup2;). Weight change was calculated as the difference between pre-delivery and pre-pregnancy weight. The relationship between overweight and obesity among the participants and their parity was examined. For this purpose, the participants were divided into three groups: first-time mothers, second-time mothers, and those having their third or subsequent child. The analysis examined the relationship between overweight and obesity and infertility treatments, miscarriages (estimated as the difference between the number of pregnancies and births), pregnancy and perinatal complications (gestational diabetes, eclampsia, pregnancy-induced hypertension), PROM (Prelabor Rupture of Membranes), oligohydramnios, mode of delivery (cesarean section or vaginal delivery), perineal injuries during delivery (perineal lacerations), and incomplete placenta expulsion. Subsequently, the relationship between overweight and obesity in women and newborn outcomes was analyzed, including birth weight, birth length, the occurrence of macrosomia, perinatal injuries, and breastfeeding difficulties.\u003c/p\u003e \u003cp\u003eThe gestational weight gain was also analyzed, which according to the 2009 IOM guidelines should not exceed 18 kg for underweight women, 16 kg for women with normal body weight, 11.5 kg for overweight women, and 9 kg for obese women. The women were divided into two groups based on GWG, about the 2009 IOM guidelines: those whose weight gain was below or within the norm, and those whose weight gain exceeded the IOM guidelines.\u003c/p\u003e \u003cp\u003eStatistical analysis was performed using Statistica 13.0 software. To examine the relationships between variables, Spearman's rank correlation analysis, and linear and logistic regression were used, and to estimate the odds ratio, logistic regression analysis was applied. The significance of differences was analyzed using the Mann-Whitney tests (after applying the Shapiro-Wilk test) and ANOVA. For nominal variables, the χ\u003csup\u003e2\u003c/sup\u003e test was used for p\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eThe study investigated whether the described trend in the literature\u0026mdash;regarding the increase in body weight and BMI with subsequent pregnancies\u0026mdash;was observed in the examined group of women. It also analyzed how gestational weight gain varied among women giving birth for the first, second, third, and subsequent times. The results are presented in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. The applied Tukey post hoc test revealed that, in the case of pre-pregnancy weight, the mean values for women giving birth for the third and subsequent times were statistically significantly higher than for primiparas and those giving birth for the second time (first birth vs. third and subsequent: \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001; second birth vs. third and subsequent: \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). No significant differences in mean pre-pregnancy weight were observed between women giving birth for the first and second times (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.1592). For the mean pre-pregnancy BMI, the Tukey post hoc test revealed that the mean BMI values of women in subsequent pregnancies were statistically significantly higher (primiparas vs. second pregnancy: \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.006; second pregnancy vs. third and subsequent pregnancies, as well as first vs. third and subsequent pregnancies: \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\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\u003ePre-pregnancy body weight, pre-pregnancy BMI and weight change during pregnancy and delivery order.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eWeight\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003ePre-pregnancy BMI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eChanges in body weight\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\" colname=\"c2\"\u003e \u003cp\u003eMean (SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003erange\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMean (SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003erange\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMean (SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003erange\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFirst birth (n\u0026thinsp;=\u0026thinsp;1434)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e62.05 (11.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e42.0-140.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22.39 (3.85)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e14.54\u0026ndash;49.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e14.51 (5.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-1.0-34.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSecon birth (n\u0026thinsp;=\u0026thinsp;1060)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e62.90 (11.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e40.0-117.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22.78 (3.87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15.62\u0026ndash;44.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e13.95 (5.13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-3.0-43.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThird and subsequent births (n\u0026thinsp;=\u0026thinsp;384)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e66.22 (12.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e42.0-126.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24.04 (4.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e16.73\u0026ndash;41.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e12.71 (4.89)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.0\u0026ndash;29.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eANOVA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;\u003cb\u003e0,001\u003c/b\u003e (F\u0026thinsp;=\u0026thinsp;19.86)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;\u003cb\u003e0,001\u003c/b\u003e (F\u0026thinsp;=\u0026thinsp;27.42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;\u003cb\u003e0,001\u003c/b\u003e (F\u0026thinsp;=\u0026thinsp;19.60)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSpearman correlation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eR\u0026thinsp;=\u0026thinsp;0.1120; \u003cb\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003cp\u003e(t(N-2)\u0026thinsp;=\u0026thinsp;5.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eR\u0026thinsp;=\u0026thinsp;0.1400; \u003cb\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003cp\u003e(t(N-2)\u0026thinsp;=\u0026thinsp;7.58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eR = -0.1084; \u003cb\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003cp\u003e(t(N-2) = -5.85)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eRegarding the mean GWG, an opposite trend was observed: the average weight gain during the first pregnancy was significantly higher than during the second, third, and subsequent pregnancies (primiparas vs. second pregnancy: \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.017; second pregnancy vs. third and subsequent pregnancies, as well as first vs. third and subsequent pregnancies: \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The conducted Spearman's rank correlation analysis confirmed that the relationships described above were statistically significant.\u003c/p\u003e \u003cp\u003eNext, the impact of overweight and obesity on women's reproductive abilities was examined. The analysis included infertility treatment among women and the occurrence of at least one miscarriage in their medical history. In the studied group, no statistically significant relationships were observed. However, in the case of infertility treatment, the percentage of women undergoing this procedure was highest in the obesity group. Regarding the history of miscarriage, no statistically significant relationship with pre-pregnancy BMI was found; however, it was noted that this percentage increased across successive BMI categories (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\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\u003eInfertility treatment and miscarriage occurrence.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFactors\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePer-pregnancy BMI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo n[%]\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eYes n[%]\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eInfertility treatment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNormal weight (n\u0026thinsp;=\u0026thinsp;2242)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2213 [98.71]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e29 [1.29]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOverweight (n\u0026thinsp;=\u0026thinsp;478)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e474 [99.16]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4 [0.84]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eObesity (n\u0026thinsp;=\u0026thinsp;158)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e155 [98.10]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 [1.90]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eχ\u0026thinsp;\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.5398 (χ\u0026thinsp;=\u0026thinsp;1.2333; df\u0026thinsp;=\u0026thinsp;2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eMiscarriages\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNormal weight (n\u0026thinsp;=\u0026thinsp;2242)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1859 [82.92]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e383 [17.08]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOverweight (n\u0026thinsp;=\u0026thinsp;478)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e396 [82.85]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e82 [17.15]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eObesity (n\u0026thinsp;=\u0026thinsp;158)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e130 [82.28]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e28 [17.72]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eχ\u0026thinsp;\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.9789 (χ\u0026thinsp;=\u0026thinsp;0.0426; df\u0026thinsp;=\u0026thinsp;2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003eComplications of pregnancy and childbirth\u003c/h3\u003e\n\u003cp\u003eTo evaluate the relationship between pre-pregnancy BMI, GWG, and the occurrence of selected pregnancy and childbirth complications, the first step was to estimate the proportion of women in each BMI category who gained weight by IOM recommendations (or less) versus those who exceeded these values. Based on the collected data, it was noted that for women with overweight and obesity, the proportion of individuals who gained more than the IOM-recommended values was more than twice as high compared to those who adhered to or stayed below the guidelines (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\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\u003eWeight changes in accordance with IOM, depending on pre-pregnancy BMI.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eIOM standards\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003ePre-pregnancy BMI\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNormal weight (n\u0026thinsp;=\u0026thinsp;2242)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOverweight (n\u0026thinsp;=\u0026thinsp;478)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eObesity \u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;158)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAt or below standard\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1601 [71.41]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e178 [37.24]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e63 [39.87]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAbove standard\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e641 [28.59]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e300 [62.76]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e95 [60.13]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eχ\u0026thinsp;\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;\u003cb\u003e0.0001\u003c/b\u003e (χ\u0026thinsp;=\u0026thinsp;241.93; df\u0026thinsp;=\u0026thinsp;2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eIn the next step, the relationship between pregnancy and childbirth complications, pre-pregnancy BMI, and gestational weight gain was analyzed. GWG was assessed based on whether weight gain during pregnancy was below, within, or above the ranges recommended by IOM standards (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). Regarding the occurrence of gestational diabetes mellitus, the likelihood of developing this condition increased among overweight women and was the highest among obese women. The correlation coefficient (r) values indicate that pre-pregnancy BMI had a greater influence on the occurrence of gestational diabetes mellitus (GDM) than GWG. Adherence to IOM-recommended weight gain ranges did not appear to mitigate this risk. Interestingly, in the studied group, GDM was more frequently observed among women who gained weight by the IOM standards.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePre-pregnancy BMI and GWG in relation to pregnancy and perinatal complications.\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\" colspan=\"2\" morerows=\"1\" nameend=\"c2\" namest=\"c1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003ePre-pregnancy BMI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eGWG according IOM\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNormal weight (n\u0026thinsp;=\u0026thinsp;2242)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eOverweight \u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;478)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eObesity \u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;158)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eAt or below standard\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;1842)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eAbove standard (n\u0026thinsp;=\u0026thinsp;1036)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eGestational diabetes mellitus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo n[%]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2092 [93.31]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e432 [90.38]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e134 [84.81]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1663 [90.28]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e995 [96.04]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes n[%]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e150 [6.69]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e46 [9.62]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e24 [15.19]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e179 [9.72]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e41 [3.69]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOdds ratio (95% CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.48 (1.05\u0026ndash;2.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.43 (1.41\u0026ndash;4.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eχ\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;\u003cb\u003e0.0001\u003c/b\u003e (χ\u0026thinsp;=\u0026thinsp;18.28; df\u0026thinsp;=\u0026thinsp;2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;\u003cb\u003e0.0001\u003c/b\u003e (χ\u0026thinsp;=\u0026thinsp;31.16; df\u0026thinsp;=\u0026thinsp;1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ep, R, R\u003csup\u003e2\u003c/sup\u003e regression\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;\u003cb\u003e0.0001\u003c/b\u003e; R\u0026thinsp;=\u0026thinsp;0,112; R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;\u003cb\u003e0.0001\u003c/b\u003e; R\u0026thinsp;=\u0026thinsp;0.104; R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.011\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eGestational hypertension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo n[%]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2159 [96.30]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e422 [88.28]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e129 [81.65]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1795 [95.49]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e951 [91.80]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes n[%]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e83 [3.70]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e56 [11.72]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e29 [18.35]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e86 [4.51]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e85 [8.20]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOdds ratio (95% CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.45 (2.42\u0026ndash;4.92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.42 (1.92\u0026ndash;3.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.112 (1.716\u0026ndash;2.863)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eχ\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;\u003cb\u003e0.0001\u003c/b\u003e (χ\u0026thinsp;=\u0026thinsp;93.68; df\u0026thinsp;=\u0026thinsp;2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;\u003cb\u003e0.0001\u003c/b\u003e (χ\u0026thinsp;= 16.50; df\u0026thinsp;=\u0026thinsp;1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ep, R, R\u003csup\u003e2\u003c/sup\u003e regression\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;\u003cb\u003e0.0001\u003c/b\u003e; R\u0026thinsp;=\u0026thinsp;0.180; R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.032\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;\u003cb\u003e0.0001\u003c/b\u003e; R\u0026thinsp;=\u0026thinsp;0.076; R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.006\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eCaesarean section\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo n[%]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1443 [64.42]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e272 [57.14]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e81 [51.27]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1190 [64.74]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e606 [58.49]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes n[%]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e797 [35.58]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e204 [42.86]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e77 [48.73]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e648 [35.26]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e430 [41.51]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOdds ratio (95% CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.36 (1.11\u0026ndash;1.66)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.25 (1.08\u0026ndash;1.43)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.36 (1.88\u0026ndash;2.97)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eχ\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;\u003cb\u003e0.0019\u003c/b\u003e (χ\u0026thinsp;=\u0026thinsp;10.63; df\u0026thinsp;=\u0026thinsp;2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;\u003cb\u003e0.0009\u003c/b\u003e (χ\u0026thinsp;=\u0026thinsp;11.04; df\u0026thinsp;=\u0026thinsp;1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ep, R, R\u003csup\u003e2\u003c/sup\u003e regression\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;\u003cb\u003e0.0001\u003c/b\u003e; R\u0026thinsp;=\u0026thinsp;0.075; R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e\u003cb\u003ep\u0026thinsp;=\u0026thinsp;0.0012\u003c/b\u003e; R\u0026thinsp;=\u0026thinsp;0.060 R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.004\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003ePROM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo n[%]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2181 [97.28]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e459 [96.03]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e154 [97.47]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1789 [97.12]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1005 [97.01]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes n[%]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e61 [2.72]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19 [3.97]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4 [2.53]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e53 [2.88]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e91 [2.99]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOdds ratio (95% CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.48 (0.88\u0026ndash;2.49)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.91 (0.49\u0026ndash;1.89)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.04 (0.67\u0026ndash;1.62)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eχ\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.3206 (χ\u0026thinsp;=\u0026thinsp;2.27; df\u0026thinsp;=\u0026thinsp;2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.8604 (χ\u0026thinsp;=\u0026thinsp;0.0309; df\u0026thinsp;=\u0026thinsp;1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ep, R, R\u003csup\u003e2\u003c/sup\u003e regression\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.3208; R\u0026thinsp;=\u0026thinsp;0. 008 R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.8604; R\u0026thinsp;=\u0026thinsp;0.003 R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eEclampsia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo n[%]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2227 [99.33]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e475 [99.37]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e157 [99.37]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1827 [99.19]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1032 [99.61]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes n[%]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15 [0.67]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 [0.63]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1 [0.63]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e15 [0.81]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4 [0.39]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOdds ratio (95% CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eχ\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.5398 (χ\u0026thinsp;=\u0026thinsp;1.23; df\u0026thinsp;=\u0026thinsp;2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.1733 (χ\u0026thinsp;=\u0026thinsp;1.85; df\u0026thinsp;=\u0026thinsp;1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ep, R, R\u003csup\u003e2\u003c/sup\u003e regression\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.9939; R\u0026thinsp;=\u0026thinsp;0,002 R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.1734; R\u0026thinsp;=\u0026thinsp;0.026 R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eOligohydramnios\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo n[%]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2220 [99.02]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e473 [98.95]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e154 [97.47]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1819 [98.75]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1028 [99.23]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes n[%]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22 [0.98]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5 [1.05]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4 [2.53]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e23 [1.25]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e8 [0.77]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOdds ratio (95% CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.07 (0.39\u0026ndash;2.91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.61 (0.94\u0026ndash;2.78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eχ\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.1887 (χ\u0026thinsp;=\u0026thinsp;3.33; df\u0026thinsp;=\u0026thinsp;2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.2346 (χ\u0026thinsp;=\u0026thinsp;1.1413; df\u0026thinsp;=\u0026thinsp;1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ep, R, R\u003csup\u003e2\u003c/sup\u003e regression\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.1889; R\u0026thinsp;=\u0026thinsp;0.034 R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.2348; R\u0026thinsp;=\u0026thinsp;0.022 R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003eNATURAL BIRTH\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNormal weight (n\u0026thinsp;=\u0026thinsp;1443)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eOverweight \u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;272)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eObesity \u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;81)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eAt or below standard\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;1842)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eAbove standard (n\u0026thinsp;=\u0026thinsp;1036)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003ePerineal lacerations\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo n[%]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e784 [51.84]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e126 [46.32]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e39 [48.15]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e623 [52.35]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e290 [47.85]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes n[%]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e695 [48.16]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e146 [53.68]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e42 [51.85]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e567 [47.65]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e316 [52.15]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOdds ratio (95% CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.48 (0.387\u0026thinsp;\u0026minus;\u0026thinsp;0.06.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.08 (0.86\u0026ndash;1.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.18 (0.98\u0026ndash;1.46)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eχ\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.2200 (χ\u0026thinsp;=\u0026thinsp;3.03; df\u0026thinsp;=\u0026thinsp;2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.0714 (χ\u0026thinsp;=\u0026thinsp;3.2506; df\u0026thinsp;=\u0026thinsp;1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ep, R, R\u003csup\u003e2\u003c/sup\u003e regression\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.2203; R\u0026thinsp;=\u0026thinsp;0.041 R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.0715; R\u0026thinsp;=\u0026thinsp;0.042 R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eRetained placenta\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo n[%]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1374 [95.28]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e255 [93.59]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e75 [92.59]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1129 [94.87]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e575 [95.04]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes n[%]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e68 [4.72]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18 [6.25]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6 [7.41]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e61 [5.13]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e30 [4.96]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOdds ratio (95% CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.75 (0.43\u0026ndash;1.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.27 (0.82\u0026ndash;1.96)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eχ\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.3530 (χ\u0026thinsp;=\u0026thinsp;2.08; df\u0026thinsp;=\u0026thinsp;2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.8786 (χ\u0026thinsp;=\u0026thinsp;0.02; df\u0026thinsp;=\u0026thinsp;1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ep, R, R\u003csup\u003e2\u003c/sup\u003e regression\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.3533; R\u0026thinsp;=\u0026thinsp;0.034 R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.8786; R\u0026thinsp;=\u0026thinsp;0.004; R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe prevalence of gestational hypertension depended on both pre-pregnancy BMI and gestational weight gain within the IOM recommendations. However, correlation coefficient (r) values indicate that pre-pregnancy BMI had a greater impact on the development of this condition.\u003c/p\u003e \u003cp\u003eA similar relationship was observed concerning the frequency of cesarean deliveries. Regarding PROM and oligohydramnios, these conditions were more frequently recorded among women with overweight and obesity; however, these differences were not statistically significant. Additionally, in the case of PROM, excessive GWG slightly increased its likelihood. Conversely, for oligohydramnios, no such association was observed. Interestingly, this condition was more frequently noted in women whose weight gain aligned with the IOM recommendations.\u003c/p\u003e \u003cp\u003ePerinatal complications during vaginal deliveries, such as perineal injuries and retained placenta, were more frequently observed in women with overweight and obesity. For perineal injuries, it was also shown that they occurred slightly more often in women whose gestational weight gain exceeded the values recommended by the IOM. Pre-pregnancy BMI had a somewhat greater influence on the occurrence of perineal injuries.\u003c/p\u003e \u003cp\u003eIn contrast, no similar associations were recorded for eclampsia in the studied sample. This condition was slightly more common in the group of women with a BMI\u0026thinsp;\u0026lt;\u0026thinsp;25 and those whose GWG was within the IOM recommendations. However, these results may be influenced by the overall low number of cases (a total of 19), which in turn could be attributed to the standards of care and early prevention.\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e presents the mean values for birth weight and length, APGAR scores in the first minute of life, and the occurrence of selected newborn parameters based on the pre-pregnancy BMI of the studied women and whether their GWG was within the ranges recommended by the IOM standards.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eRelationship between neonatal birth parameters and women's pre-pregnancy BMI and GWG at or above IOM recommendations.\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=\"4\" morerows=\"1\" nameend=\"c4\" namest=\"c1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003ePre-pregnancy BMI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003eGWG according IOM\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNormal weight\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eOverweight\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eObesity\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eAt or below standard\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;1842)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eAbove standard (n\u0026thinsp;=\u0026thinsp;1036)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"8\" rowspan=\"9\"\u003e \u003cp\u003eBody mass\u003c/p\u003e \u003cp\u003e[g]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c3\" namest=\"c2\" rowspan=\"2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMean (+/-SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3453.2 (488.63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3574.1 (474.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3551.3 (587.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3389.1 (486.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e3630.6 (468.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003erange\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1320.0-4860.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1800.0-4830.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1100.0-5310.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1100.0-4800.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2240.0-5310.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003ep, R and R\u003csup\u003e2\u003c/sup\u003e for regresion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003e\u003cb\u003ep\u0026thinsp;=\u0026thinsp;0.0009\u003c/b\u003e; R\u0026thinsp;=\u0026thinsp;0.098; R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e\u003cb\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.0001\u003c/b\u003e; R\u0026thinsp;=\u0026thinsp;0.236; R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.056\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c3\" namest=\"c2\" rowspan=\"2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMean (+/-SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3314.6 (480.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3462.3 (540.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2515.4 (509.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3257.3 (493.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e3520.8 (453.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003erange\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3314.6 (480.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e500.0-5270.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2300.0-5000.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e500.0-470.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2130\u0026ndash;5270\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003ep, R and R\u003csup\u003e2\u003c/sup\u003e for regresion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003e\u003cb\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.0001\u003c/b\u003e; R\u0026thinsp;=\u0026thinsp;0.137; R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e\u003cb\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.0001\u003c/b\u003e; R\u0026thinsp;=\u0026thinsp;0.256; R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.066\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c3\" namest=\"c2\" rowspan=\"2\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMean (+/-SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3383.9 (489.21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3521.3 (509.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3532.9 (547.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3322.1 (494.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e3579.8 (464.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003erange\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e800.0-4860.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e500.0-5270.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1100.0-5310.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e500.0-4800.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2130.0-5130.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003ep, R and R\u003csup\u003e2\u003c/sup\u003e for regresion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003e\u003cb\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.0001\u003c/b\u003e; R\u0026thinsp;=\u0026thinsp;0.1116; R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.014\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e\u003cb\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.0001\u003c/b\u003e; R\u0026thinsp;=\u0026thinsp;0.248; R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.061\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"8\" rowspan=\"9\"\u003e \u003cp\u003eBody lenght\u003c/p\u003e \u003cp\u003e[cm]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c3\" namest=\"c2\" rowspan=\"2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMean (+/-SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e54.9 (2.81)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e55.38 (2.73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e55.25 (3.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e54.6 (2.87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e55.7 (2.60)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003erange\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e44.0\u0026ndash;62.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e45.0\u0026ndash;62.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e37.0\u0026ndash;62.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e37.0\u0026ndash;62.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e48.0\u0026ndash;62.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003ep, R and R\u003csup\u003e2\u003c/sup\u003e for regresion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003e\u003cb\u003ep\u0026thinsp;=\u0026thinsp;0.0407\u003c/b\u003e; R\u0026thinsp;=\u0026thinsp;0.006; R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e\u003cb\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.0001\u003c/b\u003e; R\u0026thinsp;=\u0026thinsp;0.186; R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.034\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c3\" namest=\"c2\" rowspan=\"2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMean (+/-SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e54.1 (2.92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e54.87 (3.42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e54.80 (2.912)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e53.6 (3.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e54.95 (2.82)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003erange\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e35.0\u0026ndash;63.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e25.0\u0026ndash;63.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e46.0\u0026ndash;65.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e25.0\u0026ndash;63.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e35.0\u0026ndash;65.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003ep, R and R\u003csup\u003e2\u003c/sup\u003e for regresion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003e\u003cb\u003ep\u0026thinsp;=\u0026thinsp;0.0003;\u003c/b\u003e R\u0026thinsp;=\u0026thinsp;0.107; R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e\u003cb\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.0001\u003c/b\u003e; R\u0026thinsp;=\u0026thinsp;0.171; R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.029\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c3\" namest=\"c2\" rowspan=\"2\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMean (+/-SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e54.48 (2.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e55.1 (3.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e55.02 (3,21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e54.2 (2.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e55.3 (2.73)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003erange\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e35.0\u0026ndash;63.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e25.0\u0026ndash;63.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e37.0\u0026ndash;65.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e25.0\u0026ndash;63.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e35.0\u0026ndash;65.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003ep, R and R\u003csup\u003e2\u003c/sup\u003e for regresion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003e\u003cb\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.0001\u003c/b\u003e; R\u0026thinsp;=\u0026thinsp;0.087; R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e\u003cb\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.0001\u003c/b\u003e; R\u0026thinsp;=\u0026thinsp;0.180; R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.032\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"8\" rowspan=\"9\"\u003e \u003cp\u003eAPGAR 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c3\" namest=\"c2\" rowspan=\"2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMean (+/-SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.78 (90.72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9.75(0.92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e9.42 (1.52)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e9.785 (0.77)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e9.72 (0.90)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003erange\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.0\u0026ndash;10.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.0\u0026ndash;10.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.0\u0026ndash;10.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.00\u0026ndash;10.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e3.0\u0026ndash;10.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003ep, R and R\u003csup\u003e2\u003c/sup\u003e for regresion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003e\u003cb\u003ep\u0026thinsp;=\u0026thinsp;0.0006\u003c/b\u003e; R\u0026thinsp;=\u0026thinsp;0.101; R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.1374; R\u0026thinsp;=\u0026thinsp;0.039; R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c3\" namest=\"c2\" rowspan=\"2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMean (+/-SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.81 (0.76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9.62 (1.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e9.71 (0.66)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e9.76 (0.86)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e9.78 (0.84)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003erange\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.0\u0026ndash;10.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.0\u0026ndash;10.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e7.0\u0026ndash;10.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.0\u0026ndash;10.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.0\u0026ndash;10.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003ep, R and R\u003csup\u003e2\u003c/sup\u003e for regresion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003e\u003cb\u003ep\u0026thinsp;=\u0026thinsp;0.0186\u003c/b\u003e; R\u0026thinsp;=\u0026thinsp;0.074; R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.6223; R\u0026thinsp;=\u0026thinsp;0.013; R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c3\" namest=\"c2\" rowspan=\"2\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMean (+/-SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.79 (0.74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9.69 (1.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e9.57 (1.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e9.77 (0.82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e9.75 (0.88)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003erange\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.0\u0026ndash;10.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.0\u0026ndash;10.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.0\u0026ndash;10.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.0\u0026ndash;10.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.0\u0026ndash;10.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003ep, R and R\u003csup\u003e2\u003c/sup\u003e for regresion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003e\u003cb\u003ep\u0026thinsp;=\u0026thinsp;0.0006;\u003c/b\u003e R\u0026thinsp;=\u0026thinsp;0.072; R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.487; R\u0026thinsp;=\u0026thinsp;0.013; R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"9\" nameend=\"c9\" namest=\"c1\"\u003e \u003cp\u003eOther birth parameters\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNormal weight (n\u0026thinsp;=\u0026thinsp;2239)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eOverweight \u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;478)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eObesity \u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;158)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eAt or below standard\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;1836)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eAbove standard (n\u0026thinsp;=\u0026thinsp;1036)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" morerows=\"4\" nameend=\"c2\" namest=\"c1\" rowspan=\"5\"\u003e \u003cp\u003eMakrosomia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eNo n[%]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2032 [90,80]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e409 [85.56]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e130 [82.28]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1171 [93.19]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e858 [82.82]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eYes n[%]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e207 [9.21]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e69 [14.44]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e28 [17.72]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e125 [6.81]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e178 [17.18]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eOdds ratio (95% CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.67 (1.24\u0026ndash;2.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.32 (1.17\u0026ndash;1.82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2.83 (2.23\u0026ndash;3.62)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eχ\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003e\u003cb\u003ep\u0026thinsp;=\u0026thinsp;0.0003\u003c/b\u003e (χ\u0026thinsp;= 20.87; df\u0026thinsp;=\u0026thinsp;2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e\u003cb\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.0001\u003c/b\u003e (χ\u0026thinsp;= 70.51; df\u0026thinsp;=\u0026thinsp;1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003ep, R, R\u003csup\u003e2\u003c/sup\u003e regresion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003e\u003cb\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.0001\u003c/b\u003e; R\u0026thinsp;=\u0026thinsp;0.085; R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e\u003cb\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.0001\u003c/b\u003e; R\u0026thinsp;=\u0026thinsp;0.162; R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.026\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" morerows=\"4\" nameend=\"c2\" namest=\"c1\" rowspan=\"5\"\u003e \u003cp\u003ePerinatal injuries\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eNo n[%]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2181 [97.41]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e456 [95.40]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e150 [94.94]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1786 [97.28]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e999 [96.43]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eYes n[%]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e58 [2.59]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e22 [4.60]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e8 [5.06]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e50 [2.72]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e37 [3.57]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eOdds ratio (95% CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.82 (1.10\u0026ndash;2.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.32 (0.88\u0026ndash;1.97)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.32 (0.86\u0026ndash;2.04)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eχ\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003e\u003cb\u003ep\u0026thinsp;=\u0026thinsp;0.0371\u003c/b\u003e (χ\u0026thinsp;= 6.59; df\u0026thinsp;=\u0026thinsp;2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.1974 (χ\u0026thinsp;= 1.66; df\u0026thinsp;=\u0026thinsp;1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003ep, R, R\u003csup\u003e2\u003c/sup\u003e regresion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003e\u003cb\u003ep\u0026thinsp;=\u0026thinsp;0.0371\u003c/b\u003e; R\u0026thinsp;=\u0026thinsp;0.048; R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.1975; R\u0026thinsp;=\u0026thinsp;0.024; R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" morerows=\"4\" nameend=\"c2\" namest=\"c1\" rowspan=\"5\"\u003e \u003cp\u003eBreastfeeding difficulties\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eNo n[%]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1812 [80.92]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e359 [75.10]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e116 [73.42]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1469 [80.02]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e815 [78.67]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eYes n[%]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e427 [19.08]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e119 [24.90]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e42 [26.58]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e367 [19.98]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e221 [21.33]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eOdds ratio (95% CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.99 (4.45\u0026ndash;8.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5.27 (4.16\u0026ndash;6.68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.92 (0.76\u0026ndash;1.11))\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eχ\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003e\u003cb\u003ep\u0026thinsp;=\u0026thinsp;0.0023\u003c/b\u003e (χ\u0026thinsp;=12.18; df\u0026thinsp;=\u0026thinsp;2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.3685 (χ\u0026thinsp;= 0.81; df\u0026thinsp;=\u0026thinsp;1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003ep, R, R\u003csup\u003e2\u003c/sup\u003e regresion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003e\u003cb\u003ep\u0026thinsp;=\u0026thinsp;0.0003\u003c/b\u003e (χ\u0026thinsp;=20.87; df\u0026thinsp;=\u0026thinsp;2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.3687; R\u0026thinsp;=\u0026thinsp;0.011; R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eFor changes in measurable parameters, such as birth weight, length, and APGAR scores, the analysis accounted for the newborn's sex to explore potential differences between male and female infants. Newborns of both sexes born to women with overweight and obesity were heavier and longer than those born to women with a BMI\u0026thinsp;\u0026lt;\u0026thinsp;25. For both birth weight and length, the r values indicate that GWG had a greater influence on these parameters than the mother\u0026rsquo;s pre-pregnancy BMI.\u003c/p\u003e \u003cp\u003eIn terms of GWG and pre-pregnancy BMI, both were found to slightly influence the birth weight of female newborns more strongly, but this difference was small and statistically insignificant. No similar associations were observed for APGAR scores.\u003c/p\u003e \u003cp\u003eThe probability of macrosomia, birth injuries, and feeding difficulties increased in newborns of women with overweight and obesity. While gestational weight gain had a statistically significant impact on the occurrence of macrosomia, with the r values indicating its greater importance, it was not a contributing factor in the cases of birth injuries or feeding difficulties.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this study, it was found that both pre-pregnancy weight and gestational weight gain, as well as BMI during pregnancy, significantly influenced selected parameters of maternal health and newborn outcomes.\u003c/p\u003e \u003cp\u003eThe literature contains numerous reports highlighting the increased pre-pregnancy weight of women having their second, third, or subsequent births compared to first-time mothers [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. Some researchers suggest that the increasing weight of women with subsequent pregnancies is a result of postpartum weight retention. However, many authors believe that factors such as the age of menarche and the short interval between menarche and the first childbirth are equally important. The findings indicate that these factors may also contribute to the development of overweight status following pregnancy [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn the present study, the average GWG during the first pregnancy was significantly higher than in the second, third, and subsequent pregnancies. Heery et al. [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e] observed a similar trend. Many women indulge in snacking and satisfying food cravings during pregnancy. At the same time, they give up physical activity out of concern for potential risks to the fetus. However, during subsequent pregnancies, women were more apprehensive about gaining excessive weight again, as they had faced challenges losing weight after previous deliveries. At the same time, most women did not consider that having previously delivered a macrosomic newborn could influence their lifestyle choices.\u003c/p\u003e \u003cp\u003eIn the studied group of women, no statistically significant relationship was found between undergoing infertility treatment and obesity. However, the highest percentage of women undergoing such procedures was observed in the overweight and obese groups. Similar findings have been reported by many authors. It is noted that individuals with obesity respond less effectively to ovulation induction and require higher doses of gonadotropins. Additionally, it is believed that overweight and obesity may affect oocyte activity, endometrial receptivity, fertilization rates, and the number of embryos obtained [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. Some researchers also suggest that even significant weight loss in obese women before in vitro fertilization (IVF) procedures did not improve live birth rates [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. George et al. [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e] reported that IVF outcomes and newborn parameters in overweight and obese individuals were similar to those in women with normal body weight. However, the study emphasized the critical role of specialized obstetric and gynecological care in qualified hospitals. On the other hand, Zheng et al. [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e] observed no association between BMI and the likelihood of achieving pregnancy or delivering a live baby, though the risk of miscarriage was higher.\u003c/p\u003e \u003cp\u003eIn the present study, no significant relationship was found between higher pre-pregnancy BMI and miscarriages. However, the percentage of miscarriages increased across successive BMI categories. It is widely believed that women with overweight or obesity face a significantly higher risk of miscarriage. This applies both to women who conceived naturally and those who underwent IVF [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. Additionally, it is noted that individuals struggling with excessive body weight experience recurrent miscarriages more frequently compared to those with normal pre-pregnancy weight [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. Some researchers also suggest that the increased risk of miscarriage is observed in obese women, but not in those who are merely overweight [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]. Researchers emphasize that maintaining a healthy pre-pregnancy BMI is crucial in preventing miscarriages [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe results of the conducted study suggest that in the case of women with overweight and obesity, more than twice as many participants increased their BMI beyond the levels recommended by IOM guidelines. A meta-analysis conducted in 2009 demonstrated that weight gain exceeding IOM recommendations occurred in 27.8% of cases, and this trend has continued to grow. In the United States, weight gain below, within, and above IOM guidelines has been observed in 5%, 13%, and 80% of overweight women, respectively, as well as in 17%, 13%, and 70% of obese women [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]. Interestingly, findings from Poland in 2019 suggest that mean pregnancy weight gain among overweight and obese women is lower than that of women with normal body weight [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe present study demonstrated that in women with overweight and obesity, the risk of developing gestational diabetes mellitus during pregnancy increased, with pre-pregnancy BMI having a greater impact on the occurrence of GDM. However, GDM was more frequently observed in women who gained weight by IOM guidelines. Najafi et al. [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e] reported that the risk of developing GDM in the underweight/normal weight group was over 10%, while in the group of women with overweight and obesity, it was 23%. Other studies confirm that a higher risk of developing GDM is associated with higher pre-pregnancy BMI values and excessive weight gain during pregnancy [\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e]. Research findings also suggest that maintaining a stable body weight before pregnancy is extremely important, even in the five years before conception. Women who gained 2.3\u0026ndash;10 kg per year before pregnancy had an increased risk of developing GDM compared to those with stable body weight [\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe occurrence of gestational hypertension was also correlated with pre-pregnancy BMI values. Other researchers have estimated that women who were overweight or obese before pregnancy, as well as those whose GWG exceeded the recommendations set by the IOM, were more likely to experience hypertension during pregnancy compared to their normal-weight counterparts [\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e, \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e]. Slightly different results were obtained by Savitri et al. [\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e]. According to their findings, pre-pregnancy BMI values determined the blood pressure levels of pregnant women and were correlated with more frequent occurrences of gestational hypertension. However, gestational weight gain did not influence the increased prevalence of this pregnancy complication.\u003c/p\u003e \u003cp\u003eA similar relationship was observed in the current study regarding the performance of cesarean sections. Researchers investigating cesarean sections have noted that women with pre-pregnancy obesity, as well as those who experience excessive gestational weight gain during pregnancy, are more likely to undergo a cesarean delivery. It has also been observed that the risk of cesarean section increases in women who had a normal pre-pregnancy weight but gained more weight during pregnancy than recommended by the IOM guidelines [\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e]. Other studies conducted in Poland also indicate similar trends [\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe occurrence of PROM and oligohydramnios was more frequently recorded in women with overweight and obesity; however, these differences were not statistically significant. Similarly, the observation of eclampsia was not associated with overweight or obesity. Spontaneous preterm births with PROM were more frequently observed in overweight women who experienced greater gestational weight gain than recommended by the IOM guidelines. It was also noted that lower GWG during pregnancy was a significant factor in reducing the likelihood of preterm delivery [\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e]. In the studies by Feng and Huang [\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e] and Blitz et al. [\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e], similar results were obtained for oligohydramnios - this condition was not significantly associated with overweight or obesity. However, the article by Yayla Abide et al. [\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e] reported that among women with excessive GWG, the rate of oligohydramnios was higher than in women who gained weight within the recommended range. Findings from other authors regarding eclampsia differed from those obtained in the present study. It was noted that women with pre-pregnancy overweight or obesity, as well as excessive GWG, were more likely to develop preeclampsia compared to their normal-weight counterparts [\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e].\u003c/p\u003e \u003cp\u003ePerineal lacerations and retained placenta were more frequently observed among overweight and obese women in Poland compared to women with normal body weight. A significant association was identified both in cases where GWG exceeded the values recommended by the IOM and among women with elevated pre-pregnancy BMI. Other authors have reached similar conclusions [\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e]; however, Gallagher et al. [\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e] did not observe such associations.\u003c/p\u003e \u003cp\u003eIt is noted that the majority of the cited research findings are consistent. Women with pre-pregnancy BMI values above the normal range were more likely to experience health issues during pregnancy as well as more frequent labor complications.\u003c/p\u003e \u003cp\u003e\"It is also important to address the condition of newborns. Newborns of both sexes born to women with overweight and obesity were heavier and longer compared to those born to women with a BMI\u0026thinsp;\u0026lt;\u0026thinsp;25. These findings align with the data reported by other researchers [\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e]. This may also influence women's experiences during pregnancy and childbirth, for example, the occurrence of perineal lacerations [\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e]. The gestational weight gain had a greater impact on shaping the above-mentioned birth parameters of the newborns than the pre-pregnancy BMI of the mothers. Similar relationships have also been observed in data published by other researchers. This represents a significant public health issue, as children with macrosomia have a considerably increased likelihood of developing overweight and obesity later in life [\u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e, \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn the case of APGAR scores, no influence of either pre-pregnancy BMI or excessive gestational weight gain during pregnancy was observed. Different results were reported in studies from the US. In pregnant women with excessive GWG during pregnancy versus those without condition, APGAR was significantly lower compared to their normal-weight counterparts. This may be due to previously mentioned findings suggesting that women with excessive GWG during pregnancy experience more disturbances during both pregnancy and delivery [\u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eStudies conducted in Poland suggest that the likelihood of experiencing breastfeeding difficulties increased among women with overweight and obesity. However, no problems with breastfeeding were noted in the case of excessive GWG. Similar results were observed among women in the US and China, where earlier-than-standard breastfeeding cessation occurred more frequently [\u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e, \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e]. Many studies also suggest that increased pre-pregnancy BMI was associated with decreased breastfeeding initiation [\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e, \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e, \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e]. Although this is a common phenomenon, its mechanism remains unclear. It may result from the influence of increased body fat on prolactin and oxytocin, leading to delayed lactation. It is also believed that other health consequences of excessive body weight during pregnancy, such as gestational diabetes, gestational hypertension, and cesarean delivery, may contribute to the lack of breastfeeding initiation [\u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e, \u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e82\u003c/span\u003e, \u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e83\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe increasingly common prevalence of overweight and obesity, combined with the observed steady rise in the age at which women have their first child, represents a global issue. This combination constitutes a growing problem, carrying not only financial consequences related to the care of pregnant women with excessive body weight and the health outcomes of their offspring but also serious demographic implications.\u003c/p\u003e \u003cp\u003eThe above studies have several limitations. The first is the relatively small study group, which resulted from restrictions in the medical record systems at hospitals. Pre-pregnancy body weight was not recorded for all patients, which prevented the collection of information on gestational weight gain. The second limitation is the combination of data from hospitals in Warsaw, the largest city in Poland, with data from a provincial hospital in Podkarpacie region. However, combining both datasets provided a more comprehensive view of pregnant women and newborn outcomes in Poland. The sample lacked women with morbid obesity (BMI above 40). Additionally, episiotomies and perineal lacerations were combined into a single factor -perineal injuries during delivery. This was due to the small sample size in individual groups when these factors were considered separately. Therefore, the authors of the study are concerned that the study group may not be fully representative. A low percentage of cases with eclampsia was also observed, which may, however, be attributable to good cardiac care and regular monthly visits by the patients.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConceptualization: JMD, JND\u003c/p\u003e\n\u003cp\u003eDesign of the work: JMD, JND, MK\u003c/p\u003e\n\u003cp\u003eMethodology: JMD\u003c/p\u003e\n\u003cp\u003eFormal analysis: JMD\u003c/p\u003e\n\u003cp\u003eInterpretation of the data: JMD\u003c/p\u003e\n\u003cp\u003eAcquisition: KK, DS, BB\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWriting – draft version: JMD, JND\u003c/p\u003e\n\u003cp\u003eWriting – review and editing: JMD, JND, KK, VB, MK, DS, BB\u003c/p\u003e\n\u003cp\u003eAll authors approved the submitted version.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data base of the mothers and the children information have not been made public to ensure the privacy of study participants, and are stored by the John Paul II Province Hospital in Krosno and in St. Zofia’s Hospital in Warsaw and are available from the corresponding author on reasonable request. Correspondence and requests for materials should be addressed to J.N.-D.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAdditional Information - Competing Interests Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe author(s) declare no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eWorld Health Organization. Regional Office for Europe. \u003cem\u003eWHO European Regional Obesity Report 2022.\u003c/em\u003e (2022).\u003c/li\u003e\n \u003cli\u003eChooi, Y. C., Ding, C. \u0026amp; Magkos, F. The epidemiology of obesity.\u003cem\u003e\u0026nbsp;Metabolism\u003c/em\u003e. \u003cstrong\u003e92\u003c/strong\u003e, 6-10. https://doi.org/10.1016/j.metabol.2018.09.005 (2019).\u003c/li\u003e\n \u003cli\u003eKumar, S. K. Y., Bhat, P. K. \u0026amp; Sorake, C. J. 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Feeding practices in the first 6 months after delivery: Effects of gestational hypertension. \u003cem\u003ePregnancy Hypertens\u003c/em\u003e. \u003cstrong\u003e13\u003c/strong\u003e, 254-259. https://doi.org/10.1016/j.preghy.2018.07.002 (2018).\u003c/li\u003e\n \u003cli\u003eHobbs, A. J., Mannion, C. A., McDonald, S. W., Brockway, M. \u0026amp; Tough, S. C. The impact of caesarean section on breastfeeding initiation, duration and difficulties in the first four months postpartum. \u003cem\u003eBMC Pregnancy Childbirth\u003c/em\u003e. \u003cstrong\u003e16\u003c/strong\u003e, 90. https://doi.org/10.1186/s12884-016-0876-1 (2016).\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":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"overweight, obesity, pregnancy, neonatal, newborn outcomes","lastPublishedDoi":"10.21203/rs.3.rs-5683886/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5683886/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eOverweight and obesity are significant public health concerns, affecting pregnant women and potentially leading to numerous complications for both maternal and neonatal health. The aim of this study is to estimate how pre-pregnancy overweight and obesity, as well as gestational weight gain, influence pregnancy outcomes and neonatal health in Poland. The study material consisted of data from 2,878 women aged 16\u0026ndash;46 years from hospitals in Warsaw and Krosno. The analysis included data on the course of singleton pregnancies and the biological condition of the newborns, correlated with pre-pregnancy Body Mass Index (BMI) and gestational weight gain (GWG), which were compared to the standards set by the Institute of Medicine (IOM). Gestational diabetes, hypertension, cesarean section, perineal injuries, and retained placenta occurred significantly more often in women with overweight and obesity compared to women with normal body weight. Pre-pregnancy BMI had the greatest impact on the occurrence of gestational diabetes, hypertension, and perineal injuries. At the same time, diabetes was more frequently observed in women who gained weight by IOM standards. Newborns delivered by women who were overweight and obesity were significantly larger than those born to women with normal body weight. Gestational weight gain played substantial role in shaping mentioned parameters. The likelihood of macrosomia, perinatal injuries, and breastfeeding difficulties increased among women with overweight and obesity.\u003c/p\u003e","manuscriptTitle":"Pre-pregnancy body mass index and gestational weight gain - impact on pregnancy and neonatal health in the Polish population","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-01-02 04:34:32","doi":"10.21203/rs.3.rs-5683886/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-01-24T05:13:57+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-01-23T11:08:22+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-01-18T00:51:44+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"76369512238945328265356698405927373108","date":"2025-01-18T00:50:28+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"172441046533853485419024394803362011670","date":"2025-01-17T08:16:05+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-01-17T01:01:46+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-01-17T00:59:41+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-01-02T14:47:19+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-12-31T10:55:57+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2024-12-20T12:11:28+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"f3480654-70cc-4df5-92bc-3399f64628ad","owner":[],"postedDate":"January 2nd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":42206001,"name":"Health sciences/Medical research"},{"id":42206002,"name":"Health sciences/Risk factors"}],"tags":[],"updatedAt":"2025-03-10T15:59:03+00:00","versionOfRecord":{"articleIdentity":"rs-5683886","link":"https://doi.org/10.1038/s41598-025-91879-z","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2025-03-04 15:56:50","publishedOnDateReadable":"March 4th, 2025"},"versionCreatedAt":"2025-01-02 04:34:32","video":"","vorDoi":"10.1038/s41598-025-91879-z","vorDoiUrl":"https://doi.org/10.1038/s41598-025-91879-z","workflowStages":[]},"version":"v1","identity":"rs-5683886","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5683886","identity":"rs-5683886","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}