Unveiling the Risks and Outcomes of Preeclampsia: A Case-Control Study in the UAE

Unveiling the Risks and Outcomes of Preeclampsia: A Case-Control Study in the UAE | 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 Research Article Unveiling the Risks and Outcomes of Preeclampsia: A Case-Control Study in the UAE Preethi Nandagopal, Afreen Abdul Rahim Sanaullah, Sathyapriya Nandagopal, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7106149/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 19 Nov, 2025 Read the published version in BMC Pregnancy and Childbirth → Version 1 posted 20 You are reading this latest preprint version Abstract Background Preeclampsia is a pregnancy-related disorder characterized by high blood pressure and often proteinuria, affecting 2–8% of pregnancies worldwide. Preeclampsia is linked to various factors, including diabetes, obesity, multiple pregnancies, primiparity, age over 30, family history, lifestyle habits, and chronic hypertension. This study aimed to identify the determinants of pre-eclampsia as well as the maternal-fetal outcomes associated with it. Methods An unmatched case-control study included adults over 18 in the United Arab Emirates diagnosed with preeclampsia, who provided consent. Controls included those without preeclampsia. A content-validated questionnaire gathered data on socio-demographics, medical history, reproductive/obstetric history, surgical history, family history, and lifestyle factors. Chi-square and logistic regression analyses were performed on Statistical Package for Social Sciences (SPSS) version 30. A p-value < 0.05 was considered statistically significant. Results Factors such as unhealthy BMI (cOR 1.803), multigravidity (cOR 1.770), history of abortion (cOR 1.559), age at first pregnancy at 17–20 (aOR = 4.909) and 21–29 years old (aOR = 3.209), history of menstrual disorders (cOR 3.151), PCOS (cOR 2.611), hyperlipidemia (cOR 27.237), thyroid disorders (aOR = 4.346), allergy (aOR = 6.899), and family history of hypertension (aOR = 3.323) were significantly associated with risk of developing preeclampsia. Similarly, maternal-fetal outcomes such as persistent hypertension, postpartum depression, preterm birth, placental abruption, and neonatal respiratory distress syndrome were significantly associated with preeclampsia among women who gave birth at least once. Conclusion The results of this study highlight the importance of early detection of preeclampsia in at-risk individuals and addressing modifiable risk factors like stress and nutrition to reduce unfavorable pregnancy outcomes and to mitigate risk. Targeted interventions, such as raising pregnant women's awareness, can help reduce the adverse consequences. These findings also highlight the necessity for improving the overall maternal and fetal health and minimizing the complications associated with preeclampsia. Preeclampsia pregnant women high blood pressure maternal-fetal outcomes multigravidity maternal health Background Preeclampsia is a complex pregnancy-related disorder characterized by high blood pressure and often proteinuria. It usually occurs after 20 weeks of gestation and commonly in the near term. Over 50,000 maternal deaths, more than 500,000 fetal deaths, and 2–8% of pregnancy-related complications are caused by this condition globally. [ 1 , 2 ]. In Asia and Africa, pre-eclampsia and eclampsia account for about 10% of maternal mortality, and in Latin America, they account for 25% [ 3 ]. A recent study reported that the prevalence of preeclampsia in the Middle East ranged from 0.17–5%; however, there is a lack of studies regarding this in the United Arab Emirates (UAE) [ 4 ]. Several factors can increase the risk of pre-eclampsia. These can include medical conditions such as diabetes, high blood pressure, kidney disease, autoimmune conditions, and a history of pre-eclampsia in a previous pregnancy [ 1 ]. Demographic factors such as advanced maternal age, which is usually defined as the age above 35 years, are a risk factor for the development of pre-eclampsia and a BMI of 35 or more [ 1 , 5 , 6 ]. Similarly, other factors such as a family history of preeclampsia [ 7 ], twin pregnancies [ 8 ], lifestyle factors such as physical inactivity [ 9 ] were associated with the risk of preeclampsia, while one study also reported that smoking was seen to have a protective effect on the risk of preeclampsia [ 10 ]. If left untreated, pre-eclampsia can cause major problems for both the mother and the unborn child. These may include HELLP (Hemolysis, Elevated Liver enzymes and Low Platelets) syndrome, fetal growth restriction, placental abruption, and maternal and fetal death [ 3 ]. Additionally, a study has shown that preeclampsia was significantly associated with increased odds of cesarean delivery, acute maternal morbidity, preterm birth, low birth weight, neonatal intensive care unit (NICU) admissions, and stillbirths [ 11 ]. Previous studies done so far emphasize the importance of early intervention, timely delivery, and appropriate care to mitigate the risks of severe maternal and neonatal outcomes associated with preeclampsia. Despite the burden of preeclampsia worldwide, there is a notable lack of existing literature regarding preeclampsia and its associated risk factors among pregnant women residing in the UAE. Thus, this study aims to address this gap by determining various risk factors associated with preeclampsia among women in the UAE. Understanding the multiple variables can support early detection, increase maternal healthcare, and decrease unfavorable pregnancy outcomes. Materials and methods Study aim, design, setting, and population This study aimed to identify the Determinants of Preeclampsia as well as the Maternal-Fetal Outcomes associated with it. The study is an unmatched case-control research conducted among 545 pregnant women aged 18 and above in the United Arab Emirates. The study was conducted from January 2025 to April 2025. The cases were pregnant women who were diagnosed with preeclampsia and who were in gestation week 20 and above, whereas controls included pregnant women who were not diagnosed with preeclampsia. Convenience sampling was adopted to recruit the participants; additionally, medical records of pregnant women were accessed. The sample size was calculated using OpenEpi [ 12 ], assuming gestational diabetes mellitus as a risk factor. An odds ratio of 1.9 was used [ 13 ], based on prior literature, and the prevalence of gestational diabetes mellitus among controls was 21.5% [ 14 ]. With a case-to-control ratio of 1:3, a statistical power of 80%, and a significance level of 0.05, the required sample size was calculated to be 136 cases and 408 controls. ⁠Data collection Data were gathered using a self-administered questionnaire developed after a thorough literature search (Supplementary file 1). The questionnaire was distributed via Google Forms after receiving approval from the medical university's Institutional Review Board in Ajman, United Arab Emirates. Participants were informed about the purpose of the study and assured that their participation was entirely voluntary, with an option to withdraw at any point. Informed consent was obtained from all participants, and strict measures were implemented to maintain their privacy, anonymity, and confidentiality throughout the study. Additionally, the same questionnaire was used to extract data from the medical records of the pregnant women. The questionnaire included domains such as sociodemographic characteristics, past medical and surgical history, obstetric history, family history, lifestyle factors, and previous maternal and fetal outcomes. ⁠Data analysis Following data collection, responses were exported to Excel and then imported into SPSS version 30 for analysis. Descriptive statistics were summarized using frequency tables. The Chi-square test was used to examine associations between categorical variables. Variables with statistically significant associations were subjected to binary logistic regression to estimate the strength of associations. Those that remained significant were included in a multivariate logistic regression model to identify the net effect of each variable. The p-values below 0.05 were considered statistically significant. ⁠Ethical considerations Ethical approval was obtained from the Institutional Review Board of a medical university in Ajman, UAE (Ref. no. IRB-COM-STD-79-Oct-2024). To finalize the questionnaire, 3 doctors validated it, and the participants' consent was obtained before participating in the study. Confidentiality, anonymity, and the privacy of the participants were conserved. The research was conducted in accordance with the Helsinki Declaration. Results The study was conducted among pregnant women over the age of 18. Those diagnosed with preeclampsia were cases, and those without were considered controls. Table 1 Sociodemographic Characteristics of the Study Participants Sociodemographic Characteristics Groups Controls Cases P-value No. % No. % Age groups (in years) 18–34 319 78.2 110 80.3 0.602** 35 and above 89 21.8 27 19.7 Nationality SEAR* 178 74.8 60 25.2 0.715** EMR* 178 73.9 63 26.1 Others-AFR, AMR, WPR, EUR* 52 78.8 14 21.2 Educational groups High school or below 150 36.8 19 13.9 < 0.001 Undergraduate 198 48.5 115 83.9 Postgraduate 60 14.7 3 2.2 Employment Status Unemployed 334 74.2 116 25.8 0.453** Employed 74 77.9 21 22.1 BMI groups Normal BMI level 83 20.3 17 12.4 0.038 Abnormal BMI level 325 79.7 120 87.6 *EMR - Eastern Mediterranean Region, SEAR - South-East Asia Region, AFR - African Region, AMR - Region of the Americas, WPR - Western Pacific Region, and EUR - European Region. **Not statistically significant Table 1 compares the sociodemographic characteristics of women with and without preeclampsia, highlighting key differences. Most cases of preeclampsia are found in younger women aged 18–34 (80.3%), although the age difference between cases and controls is small. Nationality analysis shows a slight increase in preeclampsia cases among women from the Eastern Mediterranean Region (EMR) compared to those from the Southeast Asia Region (SEAR). Education level is a notable factor, with a significant. A higher proportion of cases have only an undergraduate education (83.9%), while postgraduate-educated women are less affected. Employment status shows minimal impact, with similar distributions among employed and unemployed women in both groups. Body Mass Index (BMI), however, is strongly associated with preeclampsia, as 87.6% of cases involve women with unhealthy weight compared to 79.7% of controls, emphasizing the role of obesity as a potential risk factor. Table 2 Association between Obstetric History and Preeclampsia Obstetric History Groups Controls Cases P-value No. % No. % Gravida Primigravida 99 24.3 21 15.3 0.029 Multigravida 309 75.7 116 84.7 Para Nulliparous 57 14 11 8 0.186* Primiparous 118 28.9 41 29.9 Multiparous 233 57.1 85 62 Abortion No 313 76.7 93 67.9 0.040 Yes 95 23.3 44 32.1 Age at 1st Pregnancy 17–20 52 12.7 24 17.5 0.005 21–29 284 69.6 104 75.9 30 and above 72 17.6 9 6.6 *Not statistically significant Table 2 shows that preeclampsia was more common among multigravida (84.7%) and multiparous (62%) women, suggesting a higher risk with multiple pregnancies. A history of abortion was more frequent in cases (32.1%) than in controls (23.3%), indicating a possible link to pre-eclampsia. Women who had their first pregnancy at a younger age (17–20 years) were more likely to develop preeclampsia (17.5%) compared to those aged 30 or above (6.6%). Overall, multiple pregnancies, previous abortions, and younger maternal age at first pregnancy appear to be associated with a higher risk of preeclampsia. Table 3 Association between Medical History and Preeclampsia Medical History Groups Controls Cases P-value No. % No. % Menstrual disorders No 397 97.3 126 92 0.006 Yes 11 2.7 11 8 PCOS No 387 94.9 120 87.6 0.004 Yes 21 5.1 17 12.4 Hypertension before pregnancy No 400 98 132 96.4 0.262* Yes 8 2 5 3.6 Diabetes before pregnancy No 391 95.8 136 99.3 0.051* Yes 17 4.2 1 0.7 High cholesterol No 405 99.3 114 83.2 < 0.001 Yes 3 0.7 23 16.8 Thyroid Disorders No 375 91.9 99 72.3 < 0.001 Yes 33 8.1 38 27.7 Autoimmune Disorders No 407 99.8 133 97.1 0.004 Yes 1 0.2 4 2.9 Blood Transfusion No 407 99.8 131 95.6 < 0.001 Yes 1 0.2 6 4.4 Iron Deficiency Anemia No 385 94.4 30 21.9 < 0.001 Yes 23 5.6 107 78.1 Allergy No 392 96.1 110 80.3 < 0.001 Yes 16 3.9 27 19.7 Abdominal or Pelvic Surgeries No 298 73 135 98.5 < 0.001 Yes 110 27 2 1.5 *Not statistically significant Table 3 explores the association between medical history and preeclampsia among cases and controls. The findings reveal that menstrual disorders (8% vs. 2.7%), PCOS (12.4% vs. 5.1%), and hypertension before pregnancy (3.6% vs. 2%) are more common in preeclampsia cases. In contrast, diabetes before pregnancy is higher in controls (4.2%) than in cases (0.7%). High cholesterol shows a significant association, affecting 16.8% of cases compared to just 0.7% of controls. Thyroid disorders are also notably more prevalent in preeclampsia cases (22.7%) than in controls (8.1%), while autoimmune disorders affect 2.9% of cases. Additionally, 4.4% of the cases reported having a history of blood transfusion, whereas 78.1% and 19.7% of the cases have a history of iron deficiency anemia and allergy, respectively. These findings emphasize that underlying medical conditions, particularly high cholesterol, thyroid issues, menstrual disorders, and PCOS, may increase the risk of developing preeclampsia during pregnancy. Table 4 Association between Preeclampsia and Family History, Lifestyle, and Other Factors Variables Groups Controls Cases P-value No. % No. % Family history of Hypertension No 327 80.1 74 54 < 0.001 Yes 81 19.9 63 46 Stress Low 123 30.1 1 0.7 < 0.001 Moderate 248 60.8 32 23.4 High 37 9.1 104 75.9 Exercise Yes 213 52.2 56 40.9 0.022 No 195 47.8 81 59.1 Diet Nutritious Food 123 30.1 56 40.9 0.021 Mixed Food 285 69.9 81 59.1 Alcohol Yes 0 0 3 2.2 0.003 No 408 100 134 97.8 Twin or triplet Yes 403 98.8 135 98.5 0.833* No 5 1.2 2 1.5 Use of contraceptive methods Yes 397 97.3 127 92.7 0.015 No 11 2.7 10 7.3 Fertility treatments (ART, IVF) Yes 404 99 133 97.1 0.102* No 4 1 4 2.9 *Not statistically significant Table 4 examines the association between preeclampsia and various factors, including family history, lifestyle, and reproductive factors. Key findings reveal that a family history of hypertension is much more common in preeclampsia cases (46%) than in controls (19.9%), suggesting a strong link. Stress levels also show a significant association, with high stress reported by 75.9% of cases compared to only 9.1% of controls, while regular exercise (59.1% of controls vs. 47.8% of cases) and a nutritious diet (40.9% vs. 30.1%) appear to reduce risk. Twin or triplet pregnancies (1.5% vs. 1.2%) and prior contraceptive use (7.3% vs. 2.7%) were more frequent in cases, while fertility treatments (2.9% vs. 1%) showed a small difference. Overall, a family history of hypertension, high stress, and poor diet are key risk factors, while regular exercise and nutritious food may provide protective benefits against preeclampsia. [insert Table 5 ] Table 5 Logistic Regression Analysis for Factors Associated with Preeclampsia Variables Groups Crude OR (CI 95%) p-value Adjusted OR (CI 95%) p-value Education High school 2.533 (0.723–8.877) 0.146* ---- ---- Undergraduate 11.616 (3.562–37.882) < 0.001 ---- ---- Postgraduate 1 ---- 1 ---- BMI Healthy weight 1 ---- 1 ---- Unhealthy weight 1.803 (1.027–3.163) 0.040 1.780 (0.952–3.329) 0.071* Gravida Primigravida 1 ---- 1 ---- Multigravida 1.770 (1.055–2.968) 0.030 1.228 (0.662–2.277) 0.514* Abortion Yes 1.559 (1.018–2.386) 0.041 1.433 (0.854–2.405) 0.174* No 1 ---- 1 ---- Age at 1st pregnancy 17–20 3.692 (1.586–8.596) 0.002 4.909 (1.880-12.882) 0.001 21–29 2.930 (1.414–6.070) 0.004 3.209 (1.420–7.250) 0.005 30 and above 1 ---- 1 ---- Menstrual disorders Yes 3.151 (1.334–7.442) 0.009 0.890 (0.297–2.667) 0.836* No 1 ---- 1 ---- PCOS Yes 2.611 (1.334–5.109) 0.005 1.511 (0.635–3.598) 0.351* No 1 ---- 1 ---- High Cholesterol Yes 27.237 (8.034–92.343) < 0.001 ---- ---- No 1 ---- 1 ---- Thyroid Disorders Yes 4.362 (2.603–7.309) < 0.001 4.346 (2.421–7.799) < 0.001 No 1 ---- 1 ---- Autoimmune Disorders Yes 12.241 (1.356-110.475) 0.026 ---- ---- No 1 ---- 1 ---- Blood Transfusion Yes 18.641 (2.224-156.259) 0.007 ---- ---- No 1 ---- 1 ---- Iron deficiency anemia Yes 59.703 (33.297-107.049) < 0.001 ---- ---- No 1 1 Allergy Yes 6.014 (3.128–11.560) < 0.001 6.899 (3.200-14.872) < 0.001 No 1 1 Abdominal or Pelvic Surgeries Yes 24.916 (6.064-102.377) < 0.001 ---- ---- No 1 ---- 1 ---- Family history of hypertension Yes 3.437 (2.270–5.204) < 0.001 3.323 (2.068–5.340) < 0.001 No 1 ---- 1 ---- Stress Low 1 ---- 1 ---- Moderate 15.871 (2.143-117.513) 0.007 ---- ---- High 345.730 (46.632-2563.212) < 0.001 ---- ---- Exercise Yes 1.580 (1.067–2.338) 0.022 1.521 (0.959-2-412) 0.074* No 1 ---- 1 ---- Diet Nutritious food 1.602 (1.073–2.392) 0.021 1.288 (0.804–2.063) 0.293* Mixed food 1 ---- 1 ---- Alcohol Yes 4918759223.0 (0.000) 0.999* ---- ---- No 1 ---- 1 ---- Use of contraceptive methods Yes 2.842 (1.179–6.847) 0.020 1.639 (0.590–4.577) 0.343* No 1 ---- 1 ---- *Not statistically significant Table 5 shows multiple variables associated with an increased risk of developing preeclampsia. Women with an undergraduate education had markedly higher odds (cOR: 11.616, p < 0.001) compared to postgraduates, suggesting that lower educational attainment may increase susceptibility. While unhealthy BMI initially showed an association with preeclampsia (cOR: 1.803, p = 0.040), this relationship lost significance after adjustment (p = 0.071). Similarly, multigravida women had increased odds in crude analysis (cOR: 1.770, p = 0.030), but this association disappeared after adjustment (p = 0.514). Prior abortion also demonstrated a crude odds ratio of 1.559 (p = 0.041), but its significance was not maintained after adjustment (p = 0.174). However, age at first pregnancy remained a robust predictor, with women who conceived at ages 17–20 having a significantly increased adjusted OR of 4.909 (p = 0.001), and those aged 21–29 also at higher risk (adjusted OR: 3.209, p = 0.005), indicating that early pregnancy is a key risk factor for preeclampsia. Menstrual disorders (cOR = 3.151, p = 0.009) and PCOS (cOR = 2.611, p = 0.005) initially show increased risk, but their significance diminishes after adjustment. High cholesterol (cOR = 27.237, p < 0.001), autoimmune disorders (cOR = 12.241, p = 0.026), blood transfusions (cOR = 18.641, p < 0.001), and iron deficiency anemia (cOR = 59.703, p < 0.001) exhibit strong crude associations. Thyroid disorders remain significantly associated even after adjustment (Adjusted OR = 4.346, p < 0.001), confirming them as an independent risk factor. Similarly, allergies (Adjusted OR = 6.014, p < 0.001) retain their significance post-adjustment. Abdominal or pelvic surgeries show a high (cOR = 24.916, p < 0.001), highlighting their potential role. These findings emphasize the importance of thyroid disorders and allergies as significant risk factors after controlling for confounders. A family history of hypertension shows a strong, independent association with increased risk (Adjusted OR = 3.323, p < 0.001). High stress levels are identified as a major risk factor with a very high (cOR = 345.730, p < 0.001), while moderate stress also shows increased risk (cOR = 15.871, p = 0.007). Exercise has an adjusted OR of 1.580 (p = 0.022), though it is not statistically significant. A nutritious diet shows a cOR of 1.602 (p = 0.021) but does not show a significant association after adjustment. The use of contraceptive methods shows a crude association with increased risk (cOR = 2.842, p = 0.020), but the adjusted OR (p = 0.343) is not significant. Overall, age at 1st pregnancy, thyroid disorders, allergies, and family history of hypertension emerge as key risk factors in the development of preeclampsia. Regarding education, high cholesterol, autoimmune diseases, history of blood transfusions, iron deficiency anemia, surgical history, and stress levels, adjusted OR was not done because CI was too large; thus, these variables did not meet the criteria for Adjustment. [insert Table 6 ] Table 6 Association between Preeclampsia and Maternal-Fetal Outcomes* Maternal-fetal Outcomes Groups Controls Cases p-value No. % No. % Persistent Hypertension No 286 99 91 89.2 0.000 Yes 3 1 11 10.8 Gestational Diabetes No 269 93.1 99 97.1 0.115** Yes 20 6.9 3 2.9 Postpartum Depression No 288 99.7 90 88.2 0.000 Yes 1 0.3 12 11.8 Preterm birth No 266 92 82 80.4 0.003 Yes 23 8 20 19.6 Amniotic fluid abnormalities No 286 99 99 97.1 0.209** Yes 3 1 3 2.9 Placental abnormalities No 283 97.9 99 97.1 0.681** Yes 6 2.1 3jg 2.9 Placental abruption No 289 100 99 97.1 0.005 Yes 0 0 3 2.9 Respiratory distress syndrome No 288 99.7 74 72.5 0.000 Yes 1 0.3 28 27.5 Stillbirth No 283 97.9 101 99 0.436** Yes 6 2.1 1 1 Intrauterine growth restrictions No 288 99.7 102 100 0.540** Yes 1 0.3 0 0 Chromosomal abnormalities No 298 100 102 100 - Yes 289 100 102 100 *Maternal-fetal outcomes were assessed only in multigravida and those who had at least delivered once. **Not statistically significant Table 6 explores the association between preeclampsia and the maternal-fetal outcomes associated with it. The findings show that persistent hypertension was observed in 10.8% of cases and 1% of controls (p = 0.000), gestational diabetes in 2.9% cases and 6.9% controls (p = 0.115), postpartum depression in 11.8% cases and 0.3 controls (p = 0.000), preterm birth in 19.6% cases and 8% controls (p = 0.003), amniotic fluid abnormalities occurred in 2.9% cases and 1% controls (p = 0.209), placental abnormalities in 2.9% cases and 2.1% controls (p = 0.681), placental abruption in 2.9% of cases (p = 0.005), neonatal respiratory distress was reported in 27.5% of cases and 0.3% of controls (p = 0.000), and stillbirth in 1% cases and 2.1% of controls (p = 0.436). These findings highlight the increased risk of complications associated with pre-eclampsia. Discussion Our study findings suggest that factors such as unhealthy BMI (cOR 1.803), multigravidity (cOR 1.770), history of abortion (cOR 1.559), age at first pregnancy at 17–20 (aOR = 4.909) and 21–29 years old (aOR = 3.209), history of menstrual disorders (cOR 3.151), PCOS (cOR 2.611), hyperlipidemia (cOR 27.237), thyroid disorders (aOR = 4.346), allergy (aOR = 6.899), and family history of hypertension (aOR = 3.323) were significantly associated with risk of developing preeclampsia. Similarly, maternal-fetal outcomes such as persistent hypertension, postpartum depression, preterm birth, placental abruption, and neonatal respiratory distress syndrome were complications associated with preeclampsia. The current study found that 83.9% of women with preeclampsia had an undergraduate education, while only 2.2% held a postgraduate degree, revealing a statistically significant association between educational level and the risk of developing preeclampsia. Further analysis indicated that women with an undergraduate education were approximately 11.6 times more likely to develop preeclampsia compared to those with a postgraduate education, suggesting that lower educational attainment may be a potential risk factor for the condition. Findings from other studies both support and contrast these results. For instance, a study by Tika Citra Ayu Lestari et al. also reported a significant association between lower education levels and increased risk of preeclampsia, consistent with the descriptive findings of the current study. However, their analysis did not demonstrate a statistically significant independent association, implying that education level may not be an independent risk factor once other variables are controlled for. This finding may be associated with limited access to prenatal care, poor nutrition, and increased psychosocial stress, which can impair placental development and immune tolerance, increasing the risk of preeclampsia. Additionally, women with lower educational attainment often come from lower socioeconomic backgrounds, which may limit their access to quality healthcare. This reduced access can contribute to an increased risk of developing preeclampsia [ 15 ]. BMI was identified as a key sociodemographic factor associated with preeclampsia in this study. Among women diagnosed with preeclampsia, 87.6% had an unhealthy BMI, compared to only 12.4% with a healthy BMI, a statistically significant difference. Analysis further revealed that an unhealthy BMI was associated with a higher crude risk of developing pre-eclampsia. However, this association lost statistical significance after adjusting for potential confounding factors, indicating that the link between BMI and preeclampsia may be influenced by other variables. Notably, similar findings were reported in studies by Tika Citra Ayu Lestari and Muhammad Alamsyah Aziz, which also found no significant association between BMI and the occurrence of preeclampsia. This may be because women with high BMI promote chronic low-grade inflammation, insulin resistance, and endothelial dysfunction, which impair placental perfusion and contribute to hypertensive disorders of pregnancy [ 15 , 16 ]. Several lifestyle and medical factors were found to be significantly associated with an increased risk of preeclampsia in the current study, including a family history of hypertension, high stress levels, regular physical activity, intake of a nutrient-dense diet, alcohol consumption, and non-use of contraceptive methods. However, after adjusting for potential confounders, only family history of hypertension emerged as an independent predictor. Women with a family history of hypertension were 3.32 times more likely to develop preeclampsia compared to those without such a history. In contrast, factors such as high stress, physical inactivity, poor diet, and non-use of contraception were not statistically significant in the adjusted model, suggesting that their effects may be mediated through or confounded by other variables. When examining the role of family history of hypertension, previous research has shown mixed results. For example, a study by Ananya Dutta Mou et al. found a 1.521-fold increased risk of preeclampsia among individuals with a family history of hypertension, supporting the current study's findings. In contrast, research by Abiyot Wolie Asres et al. also identified a positive association but reported that it was not statistically significant in the adjusted analysis, indicating that family history may not be an independent predictor and could be influenced by other confounding variables. This suggests a genetic predisposition to vascular dysregulation, impaired nitric oxide production, and altered renin-angiotensin signaling—all implicated in preeclampsia [ 17 , 18 ]. Existing literature has demonstrated a protective effect of healthy dietary patterns. For instance, increased fruit consumption during pregnancy has been associated with a 64% reduction in the risk of preeclampsia. However, in the present study, the consumption of nutritious food was found to increase the risk of preeclampsia by 1.288-fold. Nevertheless, this association was not statistically significant, suggesting that the observed relationship may be attributed to the influence of confounding variables. Diets high in sodium, trans fats, or low in antioxidants (e.g., vitamins C and E) can promote oxidative stress and inflammation, leading to endothelial dysfunction and abnormal placentation, increasing the risk of developing preeclampsia [ 18 ]. In terms of psychological factors, a separate study demonstrated that women experiencing mild stress were 4.7 times more likely to develop preeclampsia. However, the current study did not find stress to be an independent predictor after controlling for other variables, suggesting that its contribution may be indirect or operate through interactions with other risk factors. Previous studies suggest that chronic stress activates the HPA axis and sympathetic nervous system, increasing cortisol and catecholamines, which may contribute to vasoconstriction and placental hypoperfusion, leading to hypertensive disorders in pregnancy such as preeclampsia [ 19 ]. Physical activity showed a similar pattern to that of nutritious food intake. While previous research has indicated that women who engage in regular exercise have a 28% lower risk of developing preeclampsia after adjusting for confounders, the current study observed an increased risk associated with physical activity. However, this association was not statistically significant after adjustment, suggesting that the observed trend may be influenced by other confounding variables. This may be because physical inactivity worsens insulin resistance and endothelial function, both of which are involved in the pathogenesis of preeclampsia [ 20 ]. Finally, findings related to contraceptive use and alcohol consumption were somewhat contradictory when compared to existing literature. For instance, a study by Teta Puji Rahayu et al. reported that 66.7% of women with preeclampsia had used hormonal contraceptives, compared to 25% in the control group, with hormonal contraceptive use being associated with a sixfold increase in preeclampsia risk. Conversely, the present study found that women not using contraceptives had a 2.84-fold increased risk. However, this association did not remain statistically significant in the adjusted model, indicating that contraceptive use may not be an independent predictor of preeclampsia risk. It is known that alcohol disrupts angiogenesis and increases oxidative stress, potentially impairing placental development and increasing the risk of vascular complications during pregnancy. Similarly, studies show that, in some cases, lack of prior sperm exposure may impair maternal immune adaptation to paternal antigens, a proposed immunological contributor to preeclampsia [ 21 ]. When examining the association between obstetric history and preeclampsia, the current study observed that preeclampsia was more common among multigravida women compared to primigravida women. However, this association lost statistical significance after adjusting for potential confounding factors, suggesting that gravidity alone may not be an independent predictor of preeclampsia. These findings align with those of a study conducted by Pooja Kumari et al., which also reported a higher prevalence of preeclampsia among multigravida women; yet, the association was not statistically significant after controlling for other variables. Although preeclampsia is more common in primigravidas, multigravidas with a new partner, interpregnancy interval > 10 years, or underlying comorbidities may have renewed immune maladaptation and vascular stress, which could be a contributing factor to the development of preeclampsia [ 22 ]. Similarly, a greater proportion of women with preeclampsia in the current study reported a history of abortion compared to the control group. However, this association lost statistical significance after controlling for confounding factors, indicating that a previous abortion was not an independent risk factor for preeclampsia. In contrast, a study by Ahmed Mohammedian et al. in Sudan reported that only 22.2% of women with preeclampsia had experienced spontaneous abortion, whereas 37.8% of the control group had such a history. Their adjusted analysis showed that women with a history of spontaneous abortion had a 56% lower risk of developing preeclampsia, suggesting a possible independent protective effect. It is known that repeated abortions or curettage can affect endometrial receptivity and vascular remodeling, increasing the risk of defective placentation in subsequent pregnancies [ 23 ]. Age at first pregnancy emerged as the only obstetric history factor that served as a strong independent predictor of preeclampsia. Women who had their first pregnancy between the ages of 17 and 20 faced the highest risk, with a significantly increased likelihood, 3.209 times greater, of developing preeclampsia compared to those whose first pregnancy occurred after age 30. These findings align with those reported by Itamar Gilboa et al., who similarly found that women whose first pregnancy occurred at a younger age, particularly between 17 and 20 years, had a significantly higher risk of developing preeclampsia. In their study, the adjusted odds of preeclampsia were 4.909 times higher in this younger age group compared to women whose first pregnancy occurred at age ≥ 30. This may be because women > 35 have increased oxidative stress, vascular stiffness, and higher rates of comorbidities (e.g., hypertension, diabetes) that predispose to preeclampsia [ 24 ]. While assessing history of medical conditions, our study found that out of the preeclampsia cases, 8% had a history of menstrual disorders, 12.4% had PCOS, 16.8% have high cholesterol levels, 27.7% had a history of thyroid disorders, 2.9% have autoimmune conditions, 78.1% have iron deficiency anemia, 19.7% have a history of allergies. A study by Cheng et al. (2020) conducted a nationwide population-based Taiwan study analyzing primiparous women’s pre-pregnancy health. Compared to women without these conditions, those with pre-existing PCOS had an adjusted odds ratio (aOR) of 2.36 (95% CI 1.97–2.83), and women with systemic lupus erythematosus (SLE) had aOR of 1.95 (95% CI 1.37–2.78), both significantly raising the risk of gestational hypertension and preeclampsia [ 25 ]. Similarly, a 2024 Ethiopian multicenter case–control study (337 women; 113 cases with preeclampsia, 224 controls) found that iron deficiency anemia in pregnancy was significantly associated with preeclampsia (adjusted OR not specified, but statistically significant, p < 0.05) [ 26 ]. A large retrospective cohort analysis showed that women with untreated or refractory anemia had significantly higher odds of preeclampsia (aORs 1.44–1.54). Conversely, those whose anemia responded to oral iron had reduced odds (aOR 0.75; 95% CI 0.61–0.91) [ 27 ]. A study by Toloza et al. in 2022 found that among 39,826 pregnant women, subclinical hypothyroidism was associated with a 53% higher risk of preeclampsia compared to euthyroid individuals (OR 1.53; 95% CI 1.09–2.15). A U-shaped relationship was found between TSH and preeclampsia—both low and high TSH levels carried increased risk. No association with TPO-antibodies or isolated hypothyroxinemia [ 28 ]. A study by Hillary et al. in 2023 found that each 1‑SD increase in genetically elevated HDL-C was associated with a 16% reduction in preeclampsia risk (OR 0.84; 95% CI 0.74–0.94; p = 0.004). No consistent causal effect was found for LDL-C or triglycerides across ancestry groups. Suggests HDL-C elevation may be protective, whereas LDL-C/triglycerides showed no clear causality [ 29 ]. The current study also found a significant association between allergies and preeclampsia; this could be due to immune dysregulation, inflammation, endothelial dysfunction, medication effects, genetic predisposition, and shared risk factors such as immunity, obesity, hormonal and metabolic factors, and other comorbidities. However, there is limited direct evidence available. For these, the current literature remains sparse or confined to older cohorts. These findings could be due to the underlying hormonal imbalances (e.g., estrogen-progesterone axis) or metabolic disturbances that also affect placental development and endothelial health. PCOS is known to have a link to hyperandrogenism, insulin resistance, and chronic inflammation—all factors contributing to abnormal placental vasculature and hypertension. Elevated LDL and triglycerides promote endothelial dysfunction and oxidative stress, impairing placental perfusion and increasing susceptibility to preeclampsia. Thyroid dysfunction affects vascular tone, placental development, and immune function, increasing the risk of hypertensive disorders in pregnancy. Autoimmunity causes systemic inflammation and endothelial injury; antiphospholipid antibodies can promote thrombosis and placental infarction. Anemia reduces oxygen delivery to the placenta, potentially triggering hypoxia-induced oxidative stress and defective trophoblastic invasion. These could be the underlying mechanisms behind the cause of the development of preeclampsia, which are important risk factors for the disease. On assessing the maternal-fetal outcomes, the current study found that 10.8% of preeclampsia cases developed persistent hypertension postpartum, and 11.8% of the cases also developed postpartum depression. Our results also revealed that 2.9% of preeclamptic mothers developed placental abruption during pregnancy. We also found that 19.6% of cases had preterm births, and 27.5% of the babies developed respiratory distress syndrome post-delivery. A retrospective observational study by Qinqin et al. in 2023, in China, evaluated 188 women with preeclampsia: 30% developed recurrent postpartum hypertension (RecPPH) within one day, 13% by day 3, and 12% by day 5 after delivery. Women with severe or early-onset preeclampsia (before 34 weeks) had significantly higher odds of RecPPH and required longer hospital stays [ 30 ]. A comprehensive 2023 systematic review analyzed data from 21 cohort and 5 case–control studies (nearly 200,000 women): ~30% of women who had preeclampsia developed chronic hypertension within 10 years, which is 6 times higher than those with normotensive pregnancies. Early-onset preeclampsia (< 34 weeks) was associated with a higher risk of long-term hypertension compared to late-onset [ 31 ]. A retrospective study by Li Chen et al. in 2019 found that at 6 weeks postpartum, women with preeclampsia had 2.75-fold higher odds of PPD (Edinburgh scale ≥ 10) compared to controls (OR 2.75; 95% CI: 1.06–7.18). Severe preeclampsia carried even higher risk (OR 4.5; 95% CI: 1.94–17.26). Associations remained significant after adjusting for pre-delivery BMI [ 32 ]. A systematic review and meta-analysis by Dexin et al. in 2025 concluded that preeclampsia is an independent risk factor for placental abruption. The authors note that newer studies consistently indicate that pre-eclamptic pregnancies carry a significantly higher risk, even when adjusting for confounders [ 33 ]. Likewise, a retrospective Japanese cohort found that women with severe early-onset preeclampsia (< 34 weeks) had a notably higher rate of placental abruption compared to other hypertensive phenotypes [ 34 ]. A prospective cohort of 200,103 singleton pregnancies in China by Zhao et al. in 2022 found that the incidence of preterm birth was 5.44% in normotensive pregnancies vs. 7.33% with preeclampsia. Adjusted risk ratio (RR) for preterm birth in preeclampsia was 1.39 (95% CI: 1.25–1.55). Early-onset preeclampsia (< 28 weeks) conferred an 8.47-fold higher risk of preterm birth (95% CI: 5.59–12.80)—dramatically higher than late-onset (RR 1.30; 95% CI: 1.16–1.46) [ 35 ]. A retrospective cohort study by Yu-Hua et al. in 2019 studied 13,490 very-low-birth-weight (VLBW) infants (≥ 1500 g), born 1997–2014; 2,200 (16.3%) had maternal preeclampsia. Severe RDS, defined by surfactant therapy requirement: Crude analysis: Incidence lower in preeclampsia group (28.9% vs. 44%; OR 0.52, 95% CI 0.47–0.57). After adjustment (gestational age, birth weight, steroids, SGA, sex): Maternal preeclampsia slightly increased risk, adjusted OR 1.16 (95% CI 1.02–1.31). No significant increase in any-grade RDS (aOR 1.12; 95% CI 0.98–1.29). Protective factors included greater gestational age, higher birth weight, female sex, and ≥ 2 doses of antenatal steroids [ 36 ]. These findings may be due to endothelial dysfunction and vascular remodeling that persist postpartum, especially if chronic hypertension was unmasked during pregnancy. Preeclampsia may trigger systemic inflammation and stress-related neuroendocrine changes, increasing susceptibility to depressive symptoms. Preeclampsia causes vasospasm and endothelial injury in uteroplacental vessels, leading to hemorrhage and premature placental separation. Severe preeclampsia necessitates early delivery to prevent maternal and fetal complications, contributing to iatrogenic prematurity. Preterm birth due to preeclampsia often precedes full surfactant production, resulting in alveolar collapse and impaired gas exchange in neonates. Therefore, preeclampsia must be identified and treated during early pregnancy to avoid unfavorable outcomes as well as to mitigate risk. Limitations This single-center, retrospective case-control study conducted at Thumbay University Hospital in Ajman, UAE, has several limitations that may affect the generalizability and validity of its findings. The hospital-based sampling may not represent the broader population, and the reliance on self-reported data—such as stress, diet, sleep, and occupational exposures—introduces potential recall and information bias. The nature of data collection limits the ability to establish temporality between exposures and disease onset. Additionally, the study may be influenced by unmeasured confounders, and small subgroup sizes reduce the statistical power for certain analyses. Conclusion The findings of this study have important implications for maternal and fetal health, particularly in guiding early identification and prevention of preeclampsia. By highlighting key risk factors such as obesity, chronic hypertension, diabetes, and advanced maternal age, this research supports the need for targeted antenatal screening and risk stratification in clinical practice. Early recognition of high-risk individuals can enable timely interventions to reduce complications such as eclampsia, HELLP syndrome, preterm birth, and perinatal mortality. These results also underscore the importance of public health initiatives focused on educating women about healthy pregnancy practices, encouraging early and regular prenatal care, and promoting lifestyle modifications before and during pregnancy. Furthermore, the study provides valuable evidence for health policymakers to design context-specific strategies and allocate resources efficiently, ultimately improving maternal and neonatal outcomes in the UAE and similar settings. Abbreviations AFR African Region AMR Region of the Americas EMR Eastern Mediterranean Region EUR European Region HELLP Hemolysis, Elevated Liver enzymes, and Low Platelets syndrome IRB Institutional Review Board NICU Neonatal Intensive Care Unit SEAR South-East Asian Region SPSS Statistical Package for Social Sciences UAE United Arab Emirates WPR Western Pacific Region Declarations Ethics approval and consent to participate The Institutional Review Board of Gulf Medical University in Ajman, United Arab Emirates, granted ethical approval (Ref. no. IRB-COM-STD-79-Oct-2024). Informed consent was obtained from all the participants involved in the study. Consent for publication Not applicable Availability of data and materials The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request. Competing interests The authors declare that they have no competing interests. Funding Not applicable Authors' contributions PN, SN, AARS, and SMW all contributed to the study design, collection, and drafting of the manuscript. AAR analyzed the data using SPSS version 30. PN interpreted the data and created tables along with the table description. AARS wrote the background of the manuscript. PN and SMW wrote the discussion of the paper. AS contributed to the study by supervising the work. All authors read and approved the final manuscript. Acknowledgements We would like to thank all the participants for their willingness to participate in the study. References Website NHS. Pre-eclampsia. nhs.uk. 2024. Available from: https://www.nhs.uk/conditions/pre-eclampsia. Accessed on 6 May 2025. Karrar SA, Martingano DJ, Hong PL. Preeclampsia. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2025. Available from: https://www.ncbi.nlm.nih.gov/books/NBK570611/ Pre-eclampsia. Who.int. 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Association of maternal preeclampsia with neonatal respiratory distress syndrome in very-low-birth-weight infants. Sci Rep. 2019;9(1):13212. Available from: http://dx.doi.org/10.1038/s41598-019-49561-8 Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7106149","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":507048470,"identity":"5bb9369f-d49f-4a9b-979c-b4d67ca9c0af","order_by":0,"name":"Preethi Nandagopal","email":"","orcid":"","institution":"Gulf Medical University","correspondingAuthor":false,"prefix":"","firstName":"Preethi","middleName":"","lastName":"Nandagopal","suffix":""},{"id":507048471,"identity":"fa23b6ee-926a-48d8-b410-aafadfde4787","order_by":1,"name":"Afreen Abdul Rahim Sanaullah","email":"","orcid":"","institution":"Gulf Medical University","correspondingAuthor":false,"prefix":"","firstName":"Afreen","middleName":"Abdul Rahim","lastName":"Sanaullah","suffix":""},{"id":507048472,"identity":"e51e72a3-046b-444c-99ed-6a70f19f0e37","order_by":2,"name":"Sathyapriya Nandagopal","email":"","orcid":"","institution":"Gulf Medical University","correspondingAuthor":false,"prefix":"","firstName":"Sathyapriya","middleName":"","lastName":"Nandagopal","suffix":""},{"id":507048473,"identity":"dfb5df8e-1c54-4a81-b777-f5e623446e9c","order_by":3,"name":"Shahnaz Mohamed Wazil","email":"","orcid":"","institution":"Gulf Medical University","correspondingAuthor":false,"prefix":"","firstName":"Shahnaz","middleName":"Mohamed","lastName":"Wazil","suffix":""},{"id":507048476,"identity":"440034bb-03ca-4ba9-b815-92dc0309c86b","order_by":4,"name":"Shameema Asif Muhammed","email":"","orcid":"","institution":"Thumbay University Hospital","correspondingAuthor":false,"prefix":"","firstName":"Shameema","middleName":"Asif","lastName":"Muhammed","suffix":""},{"id":507048477,"identity":"b767494f-a9ef-476c-871b-8c4bc77f44ac","order_by":5,"name":"Anusha Sreejith","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAw0lEQVRIiWNgGAWjYJACZgYGG9K1pJGu5TAJyvln9xh/Lqg5b7d2RgLjhx8MdnIEtUjcOWMmPePY7eRtNxKYJXsYko0JW3Mjx4yZh+12stmNBAZpoCMTGwjpkL+RY/yZ5985kBbm3wwM9fUEtRjcyDGQ5m07YAfUwga05XACQXcZ3kgrk+btS04wO/OwzbLH4LghQVvkbiRv/szzzc7e7Hjy4Rs/KqrlCdoCA0BfMwLNNyBaAwODPQlqR8EoGAWjYKQBAGkbOPl6lt3FAAAAAElFTkSuQmCC","orcid":"","institution":"Gulf Medical University","correspondingAuthor":true,"prefix":"","firstName":"Anusha","middleName":"","lastName":"Sreejith","suffix":""}],"badges":[],"createdAt":"2025-07-12 06:38:10","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7106149/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7106149/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12884-025-08448-5","type":"published","date":"2025-11-19T15:57:51+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":96650126,"identity":"8f205c0a-a9f8-4454-8882-a120071c4980","added_by":"auto","created_at":"2025-11-24 16:08:24","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1533205,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7106149/v1/88569ef1-1e2b-4488-b940-911f2f5a4600.pdf"},{"id":90199329,"identity":"9455856b-318f-42bb-81ad-f7967c8d6559","added_by":"auto","created_at":"2025-08-29 18:08:17","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":33760,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFile1.docx","url":"https://assets-eu.researchsquare.com/files/rs-7106149/v1/673cff8b20bacaf500b874be.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Unveiling the Risks and Outcomes of Preeclampsia: A Case-Control Study in the UAE","fulltext":[{"header":"Background","content":"\u003cp\u003ePreeclampsia is a complex pregnancy-related disorder characterized by high blood pressure and often proteinuria. It usually occurs after 20 weeks of gestation and commonly in the near term. Over 50,000 maternal deaths, more than 500,000 fetal deaths, and 2\u0026ndash;8% of pregnancy-related complications are caused by this condition globally. [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. In Asia and Africa, pre-eclampsia and eclampsia account for about 10% of maternal mortality, and in Latin America, they account for 25% [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. A recent study reported that the prevalence of preeclampsia in the Middle East ranged from 0.17\u0026ndash;5%; however, there is a lack of studies regarding this in the United Arab Emirates (UAE) [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eSeveral factors can increase the risk of pre-eclampsia. These can include medical conditions such as diabetes, high blood pressure, kidney disease, autoimmune conditions, and a history of pre-eclampsia in a previous pregnancy [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Demographic factors such as advanced maternal age, which is usually defined as the age above 35 years, are a risk factor for the development of pre-eclampsia and a BMI of 35 or more [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Similarly, other factors such as a family history of preeclampsia [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e], twin pregnancies [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e], lifestyle factors such as physical inactivity [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e] were associated with the risk of preeclampsia, while one study also reported that smoking was seen to have a protective effect on the risk of preeclampsia [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eIf left untreated, pre-eclampsia can cause major problems for both the mother and the unborn child. These may include HELLP (Hemolysis, Elevated Liver enzymes and Low Platelets) syndrome, fetal growth restriction, placental abruption, and maternal and fetal death [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Additionally, a study has shown that preeclampsia was significantly associated with increased odds of cesarean delivery, acute maternal morbidity, preterm birth, low birth weight, neonatal intensive care unit (NICU) admissions, and stillbirths [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e\u003cp\u003ePrevious studies done so far emphasize the importance of early intervention, timely delivery, and appropriate care to mitigate the risks of severe maternal and neonatal outcomes associated with preeclampsia. Despite the burden of preeclampsia worldwide, there is a notable lack of existing literature regarding preeclampsia and its associated risk factors among pregnant women residing in the UAE. Thus, this study aims to address this gap by determining various risk factors associated with preeclampsia among women in the UAE. Understanding the multiple variables can support early detection, increase maternal healthcare, and decrease unfavorable pregnancy outcomes.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cp\u003e\u003cstrong\u003eStudy aim, design, setting, and population\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study aimed to identify the Determinants of Preeclampsia as well as the Maternal-Fetal Outcomes associated with it. The study is an unmatched case-control research conducted among 545 pregnant women aged 18 and above in the United Arab Emirates. The study was conducted from January 2025 to April 2025. The cases were pregnant women who were diagnosed with preeclampsia and who were in gestation week 20 and above, whereas controls included pregnant women who were not diagnosed with preeclampsia. Convenience sampling was adopted to recruit the participants; additionally, medical records of pregnant women were accessed. The sample size was calculated using OpenEpi [\u003cspan class=\"CitationRef\"\u003e12\u003c/span\u003e], assuming gestational diabetes mellitus as a risk factor. An odds ratio of 1.9 was used [\u003cspan class=\"CitationRef\"\u003e13\u003c/span\u003e], based on prior literature, and the prevalence of gestational diabetes mellitus among controls was 21.5% [\u003cspan class=\"CitationRef\"\u003e14\u003c/span\u003e]. With a case-to-control ratio of 1:3, a statistical power of 80%, and a significance level of 0.05, the required sample size was calculated to be 136 cases and 408 controls.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e⁠Data collection\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData were gathered using a self-administered questionnaire developed after a thorough literature search (Supplementary file 1). The questionnaire was distributed via Google Forms after receiving approval from the medical university\u0026apos;s Institutional Review Board in Ajman, United Arab Emirates. Participants were informed about the purpose of the study and assured that their participation was entirely voluntary, with an option to withdraw at any point. Informed consent was obtained from all participants, and strict measures were implemented to maintain their privacy, anonymity, and confidentiality throughout the study. Additionally, the same questionnaire was used to extract data from the medical records of the pregnant women. The questionnaire included domains such as sociodemographic characteristics, past medical and surgical history, obstetric history, family history, lifestyle factors, and previous maternal and fetal outcomes.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e⁠Data analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFollowing data collection, responses were exported to Excel and then imported into SPSS version 30 for analysis. Descriptive statistics were summarized using frequency tables. The Chi-square test was used to examine associations between categorical variables. Variables with statistically significant associations were subjected to binary logistic regression to estimate the strength of associations. Those that remained significant were included in a multivariate logistic regression model to identify the net effect of each variable. The p-values below 0.05 were considered statistically significant.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e⁠Ethical considerations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEthical approval was obtained from the Institutional Review Board of a medical university in Ajman, UAE (Ref. no. IRB-COM-STD-79-Oct-2024). To finalize the questionnaire, 3 doctors validated it, and the participants\u0026apos; consent was obtained before participating in the study. Confidentiality, anonymity, and the privacy of the participants were conserved. The research was conducted in accordance with the Helsinki Declaration.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eThe study was conducted among pregnant women over the age of 18. Those diagnosed with preeclampsia were cases, and those without were considered controls.\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\u003eSociodemographic Characteristics of the Study Participants\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\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eSociodemographic Characteristics\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eGroups\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003eControls\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003eCases\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eP-value\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNo.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eNo.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003eAge groups (in years)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e18\u0026ndash;34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e319\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e78.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e110\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e80.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.602**\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e35 and above\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e89\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e21.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e19.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e\u003cb\u003eNationality\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSEAR*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e178\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e74.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e25.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e0.715**\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEMR*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e178\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e73.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e63\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e26.1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOthers-AFR, AMR, WPR, EUR*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e52\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e78.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e21.2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e\u003cb\u003eEducational groups\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHigh school or below\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e150\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e36.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e13.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUndergraduate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e198\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e48.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e115\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e83.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePostgraduate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e14.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2.2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003eEmployment Status\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUnemployed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e334\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e74.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e116\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e25.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.453**\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEmployed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e74\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e77.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e22.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003eBMI groups\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNormal BMI level\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e83\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e20.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e12.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.038\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAbnormal BMI level\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e325\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e79.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e120\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e87.6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e*EMR - Eastern Mediterranean Region, SEAR - South-East Asia Region, AFR - African Region, AMR - Region of the Americas, WPR - Western Pacific Region, and EUR - European Region.\u003c/p\u003e\u003cp\u003e**Not statistically significant\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e compares the sociodemographic characteristics of women with and without preeclampsia, highlighting key differences. Most cases of preeclampsia are found in younger women aged 18\u0026ndash;34 (80.3%), although the age difference between cases and controls is small. Nationality analysis shows a slight increase in preeclampsia cases among women from the Eastern Mediterranean Region (EMR) compared to those from the Southeast Asia Region (SEAR). Education level is a notable factor, with a significant. A higher proportion of cases have only an undergraduate education (83.9%), while postgraduate-educated women are less affected. Employment status shows minimal impact, with similar distributions among employed and unemployed women in both groups. Body Mass Index (BMI), however, is strongly associated with preeclampsia, as 87.6% of cases involve women with unhealthy weight compared to 79.7% of controls, emphasizing the role of obesity as a potential risk factor.\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\u003eAssociation between Obstetric History and Preeclampsia\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\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eObstetric History\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eGroups\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003eControls\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003eCases\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eP-value\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNo.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eNo.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003eGravida\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePrimigravida\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e99\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e24.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e15.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.029\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMultigravida\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e309\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e75.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e116\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e84.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e\u003cb\u003ePara\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNulliparous\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e57\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e0.186*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePrimiparous\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e118\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e28.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e41\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e29.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMultiparous\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e233\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e57.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e85\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e62\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003eAbortion\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e313\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e76.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e93\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e67.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.040\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e95\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e23.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e44\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e32.1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e\u003cb\u003eAge at 1st Pregnancy\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e17\u0026ndash;20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e52\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e12.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e17.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e0.005\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e21\u0026ndash;29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e284\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e69.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e104\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e75.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e30 and above\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e72\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e17.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e6.6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"7\"\u003e*Not statistically significant\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows that preeclampsia was more common among multigravida (84.7%) and multiparous (62%) women, suggesting a higher risk with multiple pregnancies. A history of abortion was more frequent in cases (32.1%) than in controls (23.3%), indicating a possible link to pre-eclampsia. Women who had their first pregnancy at a younger age (17\u0026ndash;20 years) were more likely to develop preeclampsia (17.5%) compared to those aged 30 or above (6.6%). Overall, multiple pregnancies, previous abortions, and younger maternal age at first pregnancy appear to be associated with a higher risk of preeclampsia.\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\u003eAssociation between Medical History and Preeclampsia\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\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eMedical History\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eGroups\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003eControls\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003eCases\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eP-value\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNo.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eNo.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003eMenstrual disorders\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e397\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e97.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e126\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e92\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.006\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003ePCOS\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e387\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e94.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e120\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e87.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.004\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e12.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003eHypertension before pregnancy\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e400\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e98\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e132\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e96.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.262*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e3.6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003eDiabetes before pregnancy\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e391\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e95.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e136\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e99.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.051*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4.2\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\u003e0.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003eHigh cholesterol\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e405\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e99.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e114\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e83.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e16.8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003eThyroid Disorders\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e375\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e91.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e99\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e72.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e8.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e27.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003eAutoimmune Disorders\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e407\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e99.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e133\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e97.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.004\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\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\u003e0.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003eBlood Transfusion\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e407\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e99.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e131\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e95.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\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\u003e0.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e4.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003eIron Deficiency Anemia\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e385\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e94.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e21.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e107\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e78.1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003eAllergy\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e392\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e96.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e110\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e80.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e19.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003eAbdominal or Pelvic Surgeries\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e298\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e73\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e135\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e98.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e110\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"7\"\u003e*Not statistically significant\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e explores the association between medical history and preeclampsia among cases and controls. The findings reveal that menstrual disorders (8% vs. 2.7%), PCOS (12.4% vs. 5.1%), and hypertension before pregnancy (3.6% vs. 2%) are more common in preeclampsia cases. In contrast, diabetes before pregnancy is higher in controls (4.2%) than in cases (0.7%). High cholesterol shows a significant association, affecting 16.8% of cases compared to just 0.7% of controls. Thyroid disorders are also notably more prevalent in preeclampsia cases (22.7%) than in controls (8.1%), while autoimmune disorders affect 2.9% of cases. Additionally, 4.4% of the cases reported having a history of blood transfusion, whereas 78.1% and 19.7% of the cases have a history of iron deficiency anemia and allergy, respectively. These findings emphasize that underlying medical conditions, particularly high cholesterol, thyroid issues, menstrual disorders, and PCOS, may increase the risk of developing preeclampsia during pregnancy.\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\u003eAssociation between Preeclampsia and Family History, Lifestyle, and Other Factors\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\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eVariables\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eGroups\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003eControls\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003eCases\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eP-value\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNo.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eNo.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003eFamily history of Hypertension\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e327\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e80.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e74\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e54\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e81\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e19.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e63\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e46\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e\u003cb\u003eStress\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLow\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e123\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e30.1\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\u003e0.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eModerate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e248\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e60.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e32\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e23.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHigh\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e9.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e104\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e75.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003eExercise\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e213\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e52.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e56\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e40.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.022\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e195\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e47.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e81\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e59.1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003eDiet\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNutritious Food\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e123\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e30.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e56\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e40.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.021\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMixed Food\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e285\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e69.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e81\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e59.1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003eAlcohol\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.003\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e408\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e100\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e134\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e97.8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003eTwin or triplet\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e403\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e98.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e135\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e98.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.833*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003eUse of contraceptive methods\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e397\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e97.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e127\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e92.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.015\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e7.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003eFertility treatments (ART, IVF)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e404\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e99\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e133\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e97.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.102*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"7\"\u003e*Not statistically significant\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e examines the association between preeclampsia and various factors, including family history, lifestyle, and reproductive factors. Key findings reveal that a family history of hypertension is much more common in preeclampsia cases (46%) than in controls (19.9%), suggesting a strong link. Stress levels also show a significant association, with high stress reported by 75.9% of cases compared to only 9.1% of controls, while regular exercise (59.1% of controls vs. 47.8% of cases) and a nutritious diet (40.9% vs. 30.1%) appear to reduce risk. Twin or triplet pregnancies (1.5% vs. 1.2%) and prior contraceptive use (7.3% vs. 2.7%) were more frequent in cases, while fertility treatments (2.9% vs. 1%) showed a small difference. Overall, a family history of hypertension, high stress, and poor diet are key risk factors, while regular exercise and nutritious food may provide protective benefits against preeclampsia.\u003c/p\u003e\u003cp\u003e[insert Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e]\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\u003eLogistic Regression Analysis for Factors Associated with Preeclampsia\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=\"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\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariables\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGroups\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCrude OR (CI 95%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep-value\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAdjusted OR (CI 95%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003ep-value\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\u003e\u003cb\u003eEducation\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHigh school\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.533 (0.723\u0026ndash;8.877)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.146*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e----\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e----\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUndergraduate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e11.616 (3.562\u0026ndash;37.882)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e----\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e----\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePostgraduate\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\u003e----\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\u003e----\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003eBMI\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHealthy weight\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\u003e----\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\u003e----\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUnhealthy weight\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.803 (1.027\u0026ndash;3.163)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.040\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.780 (0.952\u0026ndash;3.329)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.071*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003eGravida\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePrimigravida\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\u003e----\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\u003e----\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMultigravida\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.770 (1.055\u0026ndash;2.968)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.030\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.228 (0.662\u0026ndash;2.277)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.514*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003eAbortion\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.559 (1.018\u0026ndash;2.386)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.041\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.433 (0.854\u0026ndash;2.405)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.174*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\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\u003e----\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\u003e----\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e\u003cb\u003eAge at 1st pregnancy\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e17\u0026ndash;20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.692 (1.586\u0026ndash;8.596)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.002\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e4.909 (1.880-12.882)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e21\u0026ndash;29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.930 (1.414\u0026ndash;6.070)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.004\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3.209 (1.420\u0026ndash;7.250)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.005\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e30 and above\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\u003e----\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\u003e----\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003eMenstrual disorders\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.151 (1.334\u0026ndash;7.442)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.009\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.890 (0.297\u0026ndash;2.667)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.836*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\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\u003e----\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\u003e----\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003ePCOS\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.611 (1.334\u0026ndash;5.109)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.005\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.511 (0.635\u0026ndash;3.598)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.351*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\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\u003e----\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\u003e----\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003eHigh Cholesterol\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e27.237 (8.034\u0026ndash;92.343)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e----\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e----\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\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\u003e----\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\u003e----\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003eThyroid Disorders\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.362 (2.603\u0026ndash;7.309)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e4.346 (2.421\u0026ndash;7.799)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\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\u003e----\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\u003e----\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003eAutoimmune Disorders\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e12.241 (1.356-110.475)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.026\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e----\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e----\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\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\u003e----\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\u003e----\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003eBlood Transfusion\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e18.641 (2.224-156.259)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.007\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e----\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e----\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\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\u003e----\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\u003e----\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003eIron deficiency anemia\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e59.703 (33.297-107.049)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e----\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e----\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\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\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003eAllergy\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6.014 (3.128\u0026ndash;11.560)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e6.899 (3.200-14.872)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\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\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003eAbdominal or Pelvic Surgeries\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e24.916 (6.064-102.377)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e----\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e----\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\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\u003e----\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\u003e----\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003eFamily history of hypertension\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.437 (2.270\u0026ndash;5.204)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3.323 (2.068\u0026ndash;5.340)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\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\u003e----\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\u003e----\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e\u003cb\u003eStress\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLow\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\u003e----\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\u003e----\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eModerate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e15.871 (2.143-117.513)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.007\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e----\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e----\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHigh\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e345.730 (46.632-2563.212)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e----\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e----\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003eExercise\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.580 (1.067\u0026ndash;2.338)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.022\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.521 (0.959-2-412)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.074*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\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\u003e----\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\u003e----\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003eDiet\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNutritious food\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.602 (1.073\u0026ndash;2.392)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.021\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.288 (0.804\u0026ndash;2.063)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.293*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMixed food\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\u003e----\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\u003e----\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003eAlcohol\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4918759223.0\u003c/p\u003e\u003cp\u003e(0.000)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.999*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e----\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e----\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\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\u003e----\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\u003e----\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003eUse of contraceptive methods\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.842 (1.179\u0026ndash;6.847)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.020\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.639 (0.590\u0026ndash;4.577)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.343*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\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\u003e----\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\u003e----\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"6\"\u003e*Not statistically significant\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e shows multiple variables associated with an increased risk of developing preeclampsia. Women with an undergraduate education had markedly higher odds (cOR: 11.616, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) compared to postgraduates, suggesting that lower educational attainment may increase susceptibility. While unhealthy BMI initially showed an association with preeclampsia (cOR: 1.803, p\u0026thinsp;=\u0026thinsp;0.040), this relationship lost significance after adjustment (p\u0026thinsp;=\u0026thinsp;0.071). Similarly, multigravida women had increased odds in crude analysis (cOR: 1.770, p\u0026thinsp;=\u0026thinsp;0.030), but this association disappeared after adjustment (p\u0026thinsp;=\u0026thinsp;0.514). Prior abortion also demonstrated a crude odds ratio of 1.559 (p\u0026thinsp;=\u0026thinsp;0.041), but its significance was not maintained after adjustment (p\u0026thinsp;=\u0026thinsp;0.174). However, age at first pregnancy remained a robust predictor, with women who conceived at ages 17\u0026ndash;20 having a significantly increased adjusted OR of 4.909 (p\u0026thinsp;=\u0026thinsp;0.001), and those aged 21\u0026ndash;29 also at higher risk (adjusted OR: 3.209, p\u0026thinsp;=\u0026thinsp;0.005), indicating that early pregnancy is a key risk factor for preeclampsia. Menstrual disorders (cOR\u0026thinsp;=\u0026thinsp;3.151, p\u0026thinsp;=\u0026thinsp;0.009) and PCOS (cOR\u0026thinsp;=\u0026thinsp;2.611, p\u0026thinsp;=\u0026thinsp;0.005) initially show increased risk, but their significance diminishes after adjustment. High cholesterol (cOR\u0026thinsp;=\u0026thinsp;27.237, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), autoimmune disorders (cOR\u0026thinsp;=\u0026thinsp;12.241, p\u0026thinsp;=\u0026thinsp;0.026), blood transfusions (cOR\u0026thinsp;=\u0026thinsp;18.641, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and iron deficiency anemia (cOR\u0026thinsp;=\u0026thinsp;59.703, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) exhibit strong crude associations. Thyroid disorders remain significantly associated even after adjustment (Adjusted OR\u0026thinsp;=\u0026thinsp;4.346, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), confirming them as an independent risk factor. Similarly, allergies (Adjusted OR\u0026thinsp;=\u0026thinsp;6.014, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) retain their significance post-adjustment. Abdominal or pelvic surgeries show a high (cOR\u0026thinsp;=\u0026thinsp;24.916, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), highlighting their potential role. These findings emphasize the importance of thyroid disorders and allergies as significant risk factors after controlling for confounders. A family history of hypertension shows a strong, independent association with increased risk (Adjusted OR\u0026thinsp;=\u0026thinsp;3.323, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). High stress levels are identified as a major risk factor with a very high (cOR\u0026thinsp;=\u0026thinsp;345.730, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), while moderate stress also shows increased risk (cOR\u0026thinsp;=\u0026thinsp;15.871, p\u0026thinsp;=\u0026thinsp;0.007). Exercise has an adjusted OR of 1.580 (p\u0026thinsp;=\u0026thinsp;0.022), though it is not statistically significant. A nutritious diet shows a cOR of 1.602 (p\u0026thinsp;=\u0026thinsp;0.021) but does not show a significant association after adjustment. The use of contraceptive methods shows a crude association with increased risk (cOR\u0026thinsp;=\u0026thinsp;2.842, p\u0026thinsp;=\u0026thinsp;0.020), but the adjusted OR (p\u0026thinsp;=\u0026thinsp;0.343) is not significant. Overall, age at 1st pregnancy, thyroid disorders, allergies, and family history of hypertension emerge as key risk factors in the development of preeclampsia. Regarding education, high cholesterol, autoimmune diseases, history of blood transfusions, iron deficiency anemia, surgical history, and stress levels, adjusted OR was not done because CI was too large; thus, these variables did not meet the criteria for Adjustment.\u003c/p\u003e\u003cp\u003e[insert Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e]\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\u003eAssociation between Preeclampsia and Maternal-Fetal Outcomes*\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\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eMaternal-fetal Outcomes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eGroups\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003eControls\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003eCases\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003ep-value\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNo.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eNo.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003ePersistent Hypertension\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e286\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e99\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e91\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e89.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.000\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e10.8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003eGestational Diabetes\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e269\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e93.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e99\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e97.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.115**\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003ePostpartum Depression\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e288\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e99.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e90\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e88.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.000\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\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\u003e0.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e11.8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003ePreterm birth\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e266\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e92\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e82\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e80.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.003\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e19.6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003eAmniotic fluid abnormalities\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e286\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e99\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e99\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e97.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.209**\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003ePlacental abnormalities\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e283\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e97.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e99\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e97.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.681**\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3jg\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003ePlacental abruption\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e289\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e100\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e99\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e97.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.005\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003eRespiratory distress syndrome\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e288\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e99.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e74\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e72.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.000\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\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\u003e0.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e27.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003eStillbirth\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e283\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e97.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e101\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e99\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.436**\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.1\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\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003eIntrauterine growth restrictions\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e288\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e99.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e102\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e100\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.540**\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\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\u003e0.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003eChromosomal abnormalities\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e298\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e100\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e102\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e100\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e289\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e100\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e102\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e100\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"7\"\u003e*Maternal-fetal outcomes were assessed only in multigravida and those who had at least delivered once.\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"7\"\u003e**Not statistically significant\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e explores the association between preeclampsia and the maternal-fetal outcomes associated with it. The findings show that persistent hypertension was observed in 10.8% of cases and 1% of controls (p\u0026thinsp;=\u0026thinsp;0.000), gestational diabetes in 2.9% cases and 6.9% controls (p\u0026thinsp;=\u0026thinsp;0.115), postpartum depression in 11.8% cases and 0.3 controls (p\u0026thinsp;=\u0026thinsp;0.000), preterm birth in 19.6% cases and 8% controls (p\u0026thinsp;=\u0026thinsp;0.003), amniotic fluid abnormalities occurred in 2.9% cases and 1% controls (p\u0026thinsp;=\u0026thinsp;0.209), placental abnormalities in 2.9% cases and 2.1% controls (p\u0026thinsp;=\u0026thinsp;0.681), placental abruption in 2.9% of cases (p\u0026thinsp;=\u0026thinsp;0.005), neonatal respiratory distress was reported in 27.5% of cases and 0.3% of controls (p\u0026thinsp;=\u0026thinsp;0.000), and stillbirth in 1% cases and 2.1% of controls (p\u0026thinsp;=\u0026thinsp;0.436). These findings highlight the increased risk of complications associated with pre-eclampsia.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eOur study findings suggest that factors such as unhealthy BMI (cOR 1.803), multigravidity (cOR 1.770), history of abortion (cOR 1.559), age at first pregnancy at 17\u0026ndash;20 (aOR\u0026thinsp;=\u0026thinsp;4.909) and 21\u0026ndash;29 years old (aOR\u0026thinsp;=\u0026thinsp;3.209), history of menstrual disorders (cOR 3.151), PCOS (cOR 2.611), hyperlipidemia (cOR 27.237), thyroid disorders (aOR\u0026thinsp;=\u0026thinsp;4.346), allergy (aOR\u0026thinsp;=\u0026thinsp;6.899), and family history of hypertension (aOR\u0026thinsp;=\u0026thinsp;3.323) were significantly associated with risk of developing preeclampsia. Similarly, maternal-fetal outcomes such as persistent hypertension, postpartum depression, preterm birth, placental abruption, and neonatal respiratory distress syndrome were complications associated with preeclampsia.\u003c/p\u003e\u003cp\u003eThe current study found that 83.9% of women with preeclampsia had an undergraduate education, while only 2.2% held a postgraduate degree, revealing a statistically significant association between educational level and the risk of developing preeclampsia. Further analysis indicated that women with an undergraduate education were approximately 11.6 times more likely to develop preeclampsia compared to those with a postgraduate education, suggesting that lower educational attainment may be a potential risk factor for the condition. Findings from other studies both support and contrast these results. For instance, a study by Tika Citra Ayu Lestari et al. also reported a significant association between lower education levels and increased risk of preeclampsia, consistent with the descriptive findings of the current study. However, their analysis did not demonstrate a statistically significant independent association, implying that education level may not be an independent risk factor once other variables are controlled for. This finding may be associated with limited access to prenatal care, poor nutrition, and increased psychosocial stress, which can impair placental development and immune tolerance, increasing the risk of preeclampsia. Additionally, women with lower educational attainment often come from lower socioeconomic backgrounds, which may limit their access to quality healthcare. This reduced access can contribute to an increased risk of developing preeclampsia [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eBMI was identified as a key sociodemographic factor associated with preeclampsia in this study. Among women diagnosed with preeclampsia, 87.6% had an unhealthy BMI, compared to only 12.4% with a healthy BMI, a statistically significant difference. Analysis further revealed that an unhealthy BMI was associated with a higher crude risk of developing pre-eclampsia. However, this association lost statistical significance after adjusting for potential confounding factors, indicating that the link between BMI and preeclampsia may be influenced by other variables. Notably, similar findings were reported in studies by Tika Citra Ayu Lestari and Muhammad Alamsyah Aziz, which also found no significant association between BMI and the occurrence of preeclampsia. This may be because women with high BMI promote chronic low-grade inflammation, insulin resistance, and endothelial dysfunction, which impair placental perfusion and contribute to hypertensive disorders of pregnancy [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eSeveral lifestyle and medical factors were found to be significantly associated with an increased risk of preeclampsia in the current study, including a family history of hypertension, high stress levels, regular physical activity, intake of a nutrient-dense diet, alcohol consumption, and non-use of contraceptive methods. However, after adjusting for potential confounders, only family history of hypertension emerged as an independent predictor. Women with a family history of hypertension were 3.32 times more likely to develop preeclampsia compared to those without such a history. In contrast, factors such as high stress, physical inactivity, poor diet, and non-use of contraception were not statistically significant in the adjusted model, suggesting that their effects may be mediated through or confounded by other variables. When examining the role of family history of hypertension, previous research has shown mixed results. For example, a study by Ananya Dutta Mou et al. found a 1.521-fold increased risk of preeclampsia among individuals with a family history of hypertension, supporting the current study's findings. In contrast, research by Abiyot Wolie Asres et al. also identified a positive association but reported that it was not statistically significant in the adjusted analysis, indicating that family history may not be an independent predictor and could be influenced by other confounding variables. This suggests a genetic predisposition to vascular dysregulation, impaired nitric oxide production, and altered renin-angiotensin signaling\u0026mdash;all implicated in preeclampsia [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eExisting literature has demonstrated a protective effect of healthy dietary patterns. For instance, increased fruit consumption during pregnancy has been associated with a 64% reduction in the risk of preeclampsia. However, in the present study, the consumption of nutritious food was found to increase the risk of preeclampsia by 1.288-fold. Nevertheless, this association was not statistically significant, suggesting that the observed relationship may be attributed to the influence of confounding variables. Diets high in sodium, trans fats, or low in antioxidants (e.g., vitamins C and E) can promote oxidative stress and inflammation, leading to endothelial dysfunction and abnormal placentation, increasing the risk of developing preeclampsia [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eIn terms of psychological factors, a separate study demonstrated that women experiencing mild stress were 4.7 times more likely to develop preeclampsia. However, the current study did not find stress to be an independent predictor after controlling for other variables, suggesting that its contribution may be indirect or operate through interactions with other risk factors. Previous studies suggest that chronic stress activates the HPA axis and sympathetic nervous system, increasing cortisol and catecholamines, which may contribute to vasoconstriction and placental hypoperfusion, leading to hypertensive disorders in pregnancy such as preeclampsia [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e\u003cp\u003ePhysical activity showed a similar pattern to that of nutritious food intake. While previous research has indicated that women who engage in regular exercise have a 28% lower risk of developing preeclampsia after adjusting for confounders, the current study observed an increased risk associated with physical activity. However, this association was not statistically significant after adjustment, suggesting that the observed trend may be influenced by other confounding variables. This may be because physical inactivity worsens insulin resistance and endothelial function, both of which are involved in the pathogenesis of preeclampsia [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eFinally, findings related to contraceptive use and alcohol consumption were somewhat contradictory when compared to existing literature. For instance, a study by Teta Puji Rahayu et al. reported that 66.7% of women with preeclampsia had used hormonal contraceptives, compared to 25% in the control group, with hormonal contraceptive use being associated with a sixfold increase in preeclampsia risk. Conversely, the present study found that women not using contraceptives had a 2.84-fold increased risk. However, this association did not remain statistically significant in the adjusted model, indicating that contraceptive use may not be an independent predictor of preeclampsia risk. It is known that alcohol disrupts angiogenesis and increases oxidative stress, potentially impairing placental development and increasing the risk of vascular complications during pregnancy. Similarly, studies show that, in some cases, lack of prior sperm exposure may impair maternal immune adaptation to paternal antigens, a proposed immunological contributor to preeclampsia [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eWhen examining the association between obstetric history and preeclampsia, the current study observed that preeclampsia was more common among multigravida women compared to primigravida women. However, this association lost statistical significance after adjusting for potential confounding factors, suggesting that gravidity alone may not be an independent predictor of preeclampsia. These findings align with those of a study conducted by Pooja Kumari et al., which also reported a higher prevalence of preeclampsia among multigravida women; yet, the association was not statistically significant after controlling for other variables. Although preeclampsia is more common in primigravidas, multigravidas with a new partner, interpregnancy interval\u0026thinsp;\u0026gt;\u0026thinsp;10 years, or underlying comorbidities may have renewed immune maladaptation and vascular stress, which could be a contributing factor to the development of preeclampsia [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e].\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eSimilarly, a greater proportion of women with preeclampsia in the current study reported a history of abortion compared to the control group. However, this association lost statistical significance after controlling for confounding factors, indicating that a previous abortion was not an independent risk factor for preeclampsia. In contrast, a study by Ahmed Mohammedian et al. in Sudan reported that only 22.2% of women with preeclampsia had experienced spontaneous abortion, whereas 37.8% of the control group had such a history. Their adjusted analysis showed that women with a history of spontaneous abortion had a 56% lower risk of developing preeclampsia, suggesting a possible independent protective effect. It is known that repeated abortions or curettage can affect endometrial receptivity and vascular remodeling, increasing the risk of defective placentation in subsequent pregnancies [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eAge at first pregnancy emerged as the only obstetric history factor that served as a strong independent predictor of preeclampsia. Women who had their first pregnancy between the ages of 17 and 20 faced the highest risk, with a significantly increased likelihood, 3.209 times greater, of developing preeclampsia compared to those whose first pregnancy occurred after age 30. These findings align with those reported by Itamar Gilboa et al., who similarly found that women whose first pregnancy occurred at a younger age, particularly between 17 and 20 years, had a significantly higher risk of developing preeclampsia. In their study, the adjusted odds of preeclampsia were 4.909 times higher in this younger age group compared to women whose first pregnancy occurred at age\u0026thinsp;\u0026ge;\u0026thinsp;30. This may be because women\u0026thinsp;\u0026gt;\u0026thinsp;35 have increased oxidative stress, vascular stiffness, and higher rates of comorbidities (e.g., hypertension, diabetes) that predispose to preeclampsia [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eWhile assessing history of medical conditions, our study found that out of the preeclampsia cases, 8% had a history of menstrual disorders, 12.4% had PCOS, 16.8% have high cholesterol levels, 27.7% had a history of thyroid disorders, 2.9% have autoimmune conditions, 78.1% have iron deficiency anemia, 19.7% have a history of allergies. A study by Cheng et al. (2020) conducted a nationwide population-based Taiwan study analyzing primiparous women\u0026rsquo;s pre-pregnancy health. Compared to women without these conditions, those with pre-existing PCOS had an adjusted odds ratio (aOR) of 2.36 (95% CI 1.97\u0026ndash;2.83), and women with systemic lupus erythematosus (SLE) had aOR of 1.95 (95% CI 1.37\u0026ndash;2.78), both significantly raising the risk of gestational hypertension and preeclampsia [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Similarly, a 2024 Ethiopian multicenter case\u0026ndash;control study (337 women; 113 cases with preeclampsia, 224 controls) found that iron deficiency anemia in pregnancy was significantly associated with preeclampsia (adjusted OR not specified, but statistically significant, p \u0026lt; 0.05) [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. A large retrospective cohort analysis showed that women with untreated or refractory anemia had significantly higher odds of preeclampsia (aORs 1.44\u0026ndash;1.54). Conversely, those whose anemia responded to oral iron had reduced odds (aOR 0.75; 95% CI 0.61\u0026ndash;0.91) [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eA study by Toloza et al. in 2022 found that among 39,826 pregnant women, subclinical hypothyroidism was associated with a 53% higher risk of preeclampsia compared to euthyroid individuals (OR 1.53; 95% CI 1.09\u0026ndash;2.15). A U-shaped relationship was found between TSH and preeclampsia\u0026mdash;both low and high TSH levels carried increased risk. No association with TPO-antibodies or isolated hypothyroxinemia [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. A study by Hillary et al. in 2023 found that each 1‑SD increase in genetically elevated HDL-C was associated with a 16% reduction in preeclampsia risk (OR 0.84; 95% CI 0.74\u0026ndash;0.94; p\u0026thinsp;=\u0026thinsp;0.004). No consistent causal effect was found for LDL-C or triglycerides across ancestry groups. Suggests HDL-C elevation may be protective, whereas LDL-C/triglycerides showed no clear causality [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe current study also found a significant association between allergies and preeclampsia; this could be due to immune dysregulation, inflammation, endothelial dysfunction, medication effects, genetic predisposition, and shared risk factors such as immunity, obesity, hormonal and metabolic factors, and other comorbidities. However, there is limited direct evidence available. For these, the current literature remains sparse or confined to older cohorts. These findings could be due to the underlying hormonal imbalances (e.g., estrogen-progesterone axis) or metabolic disturbances that also affect placental development and endothelial health. PCOS is known to have a link to hyperandrogenism, insulin resistance, and chronic inflammation\u0026mdash;all factors contributing to abnormal placental vasculature and hypertension. Elevated LDL and triglycerides promote endothelial dysfunction and oxidative stress, impairing placental perfusion and increasing susceptibility to preeclampsia. Thyroid dysfunction affects vascular tone, placental development, and immune function, increasing the risk of hypertensive disorders in pregnancy. Autoimmunity causes systemic inflammation and endothelial injury; antiphospholipid antibodies can promote thrombosis and placental infarction. Anemia reduces oxygen delivery to the placenta, potentially triggering hypoxia-induced oxidative stress and defective trophoblastic invasion. These could be the underlying mechanisms behind the cause of the development of preeclampsia, which are important risk factors for the disease. On assessing the maternal-fetal outcomes, the current study found that 10.8% of preeclampsia cases developed persistent hypertension postpartum, and 11.8% of the cases also developed postpartum depression. Our results also revealed that 2.9% of preeclamptic mothers developed placental abruption during pregnancy. We also found that 19.6% of cases had preterm births, and 27.5% of the babies developed respiratory distress syndrome post-delivery.\u003c/p\u003e\u003cp\u003eA retrospective observational study by Qinqin et al. in 2023, in China, evaluated 188 women with preeclampsia: 30% developed recurrent postpartum hypertension (RecPPH) within one day, 13% by day 3, and 12% by day 5 after delivery. Women with severe or early-onset preeclampsia (before 34 weeks) had significantly higher odds of RecPPH and required longer hospital stays [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. A comprehensive 2023 systematic review analyzed data from 21 cohort and 5 case\u0026ndash;control studies (nearly 200,000 women): ~30% of women who had preeclampsia developed chronic hypertension within 10 years, which is 6 times higher than those with normotensive pregnancies. Early-onset preeclampsia (\u0026lt;\u0026thinsp;34 weeks) was associated with a higher risk of long-term hypertension compared to late-onset [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. A retrospective study by Li Chen et al. in 2019 found that at 6 weeks postpartum, women with preeclampsia had 2.75-fold higher odds of PPD (Edinburgh scale\u0026thinsp;\u0026ge;\u0026thinsp;10) compared to controls (OR 2.75; 95% CI: 1.06\u0026ndash;7.18). Severe preeclampsia carried even higher risk (OR 4.5; 95% CI: 1.94\u0026ndash;17.26). Associations remained significant after adjusting for pre-delivery BMI [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. A systematic review and meta-analysis by Dexin et al. in 2025 concluded that preeclampsia is an independent risk factor for placental abruption. The authors note that newer studies consistently indicate that pre-eclamptic pregnancies carry a significantly higher risk, even when adjusting for confounders [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. Likewise, a retrospective Japanese cohort found that women with severe early-onset preeclampsia (\u0026lt;\u0026thinsp;34 weeks) had a notably higher rate of placental abruption compared to other hypertensive phenotypes [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eA prospective cohort of 200,103 singleton pregnancies in China by Zhao et al. in 2022 found that the incidence of preterm birth was 5.44% in normotensive pregnancies vs. 7.33% with preeclampsia. Adjusted risk ratio (RR) for preterm birth in preeclampsia was 1.39 (95% CI: 1.25\u0026ndash;1.55). Early-onset preeclampsia (\u0026lt;\u0026thinsp;28 weeks) conferred an 8.47-fold higher risk of preterm birth (95% CI: 5.59\u0026ndash;12.80)\u0026mdash;dramatically higher than late-onset (RR 1.30; 95% CI: 1.16\u0026ndash;1.46) [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. A retrospective cohort study by Yu-Hua et al. in 2019 studied 13,490 very-low-birth-weight (VLBW) infants (\u0026ge;\u0026thinsp;1500 g), born 1997\u0026ndash;2014; 2,200 (16.3%) had maternal preeclampsia. Severe RDS, defined by surfactant therapy requirement: Crude analysis: Incidence lower in preeclampsia group (28.9% vs. 44%; OR 0.52, 95% CI 0.47\u0026ndash;0.57). After adjustment (gestational age, birth weight, steroids, SGA, sex): Maternal preeclampsia slightly increased risk, adjusted OR 1.16 (95% CI 1.02\u0026ndash;1.31). No significant increase in any-grade RDS (aOR 1.12; 95% CI 0.98\u0026ndash;1.29). Protective factors included greater gestational age, higher birth weight, female sex, and \u0026ge;\u0026thinsp;2 doses of antenatal steroids [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThese findings may be due to endothelial dysfunction and vascular remodeling that persist postpartum, especially if chronic hypertension was unmasked during pregnancy. Preeclampsia may trigger systemic inflammation and stress-related neuroendocrine changes, increasing susceptibility to depressive symptoms. Preeclampsia causes vasospasm and endothelial injury in uteroplacental vessels, leading to hemorrhage and premature placental separation. Severe preeclampsia necessitates early delivery to prevent maternal and fetal complications, contributing to iatrogenic prematurity. Preterm birth due to preeclampsia often precedes full surfactant production, resulting in alveolar collapse and impaired gas exchange in neonates. Therefore, preeclampsia must be identified and treated during early pregnancy to avoid unfavorable outcomes as well as to mitigate risk.\u003c/p\u003e\u003cp\u003e\u003cb\u003eLimitations\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThis single-center, retrospective case-control study conducted at Thumbay University Hospital in Ajman, UAE, has several limitations that may affect the generalizability and validity of its findings. The hospital-based sampling may not represent the broader population, and the reliance on self-reported data\u0026mdash;such as stress, diet, sleep, and occupational exposures\u0026mdash;introduces potential recall and information bias. The nature of data collection limits the ability to establish temporality between exposures and disease onset. Additionally, the study may be influenced by unmeasured confounders, and small subgroup sizes reduce the statistical power for certain analyses.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe findings of this study have important implications for maternal and fetal health, particularly in guiding early identification and prevention of preeclampsia. By highlighting key risk factors such as obesity, chronic hypertension, diabetes, and advanced maternal age, this research supports the need for targeted antenatal screening and risk stratification in clinical practice. Early recognition of high-risk individuals can enable timely interventions to reduce complications such as eclampsia, HELLP syndrome, preterm birth, and perinatal mortality. These results also underscore the importance of public health initiatives focused on educating women about healthy pregnancy practices, encouraging early and regular prenatal care, and promoting lifestyle modifications before and during pregnancy. Furthermore, the study provides valuable evidence for health policymakers to design context-specific strategies and allocate resources efficiently, ultimately improving maternal and neonatal outcomes in the UAE and similar settings.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eAFR\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eAfrican Region\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eAMR\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eRegion of the Americas\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eEMR\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eEastern Mediterranean Region\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eEUR\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eEuropean Region\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eHELLP\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eHemolysis, Elevated Liver enzymes, and Low Platelets syndrome\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eIRB\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eInstitutional Review Board\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eNICU\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eNeonatal Intensive Care Unit\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eSEAR\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eSouth-East Asian Region\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eSPSS\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eStatistical Package for Social Sciences\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eUAE\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eUnited Arab Emirates\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eWPR\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eWestern Pacific Region\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe Institutional Review Board of Gulf Medical University in Ajman, United Arab Emirates, granted ethical approval (Ref. no. IRB-COM-STD-79-Oct-2024). Informed consent was obtained from all the participants involved in the study.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors' contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePN, SN, AARS, and SMW all contributed to the study design, collection, and drafting of the manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAAR analyzed the data using SPSS version 30.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePN interpreted the data and created tables along with the table description.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAARS wrote the background of the manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePN and SMW wrote the discussion of the paper. AS contributed to the study by supervising the work.\u003c/p\u003e\n\u003cp\u003eAll authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe would like to thank all the participants for their willingness to participate in the study.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eWebsite NHS. Pre-eclampsia. nhs.uk. 2024. Available from: https://www.nhs.uk/conditions/pre-eclampsia. Accessed on 6 May 2025. \u003c/li\u003e\n\u003cli\u003eKarrar SA, Martingano DJ, Hong PL. Preeclampsia. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2025. Available from: https://www.ncbi.nlm.nih.gov/books/NBK570611/ \u003c/li\u003e\n\u003cli\u003ePre-eclampsia. Who.int. Available from: https://www.who.int/news-room/fact-sheets/detail/pre-eclampsia. Accessed on 6 May 2025. \u003c/li\u003e\n\u003cli\u003eHegazy A, Eid FA, Ennab F, Sverrisd\u0026oacute;ttir YB, Atiomo W, Azar AJ. Prevalence of pre-eclampsia in women in the Middle East: a scoping review. Front Public Health. 2024;12:1384964. Available from: http://dx.doi.org/10.3389/fpubh.2024.1384964 \u003c/li\u003e\n\u003cli\u003eGilboa I, Kupferminc M, Schwartz A, Landsberg Ashereh Y, Yogev Y, Rappaport Skornik A, et al. The association between advanced maternal age and the manifestations of preeclampsia with severe features. J Clin Med. 2023;12(20):6545. Available from: https://www.mdpi.com/2077-0383/12/20/6545 \u003c/li\u003e\n\u003cli\u003eSun M, Luo M, Wang T, Wei J, Zhang S, Shu J, et al. Effect of the interaction between advanced maternal age and pre-pregnancy BMI on pre-eclampsia and GDM in Central China. BMJ Open Diabetes Res Care. 2023;11(2):e003324. 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Available from: http://dx.doi.org/10.1016/j.preghy.2020.05.005\u003c/li\u003e\n\u003cli\u003eRodriguez-Lopez M, Escobar MF, Merlo J, Kaufman JS. Reevaluating the protective effect of smoking on preeclampsia risk through the lens of bias. J Hum Hypertens. 2023;37(5):338\u0026ndash;44. Available from: https://www.nature.com/articles/s41371-023-00827-9 \u003c/li\u003e\n\u003cli\u003eMaducolil MK, Al-Obaidly S, Olukade T, Salama H, AlQubaisi M, Al Rifai H. Pre-eclampsia: incidence, determinants, and pregnancy outcomes from maternity hospitals in Qatar: a population-based case-control study. J Matern Fetal Neonatal Med. 2024;35(25):7831\u0026ndash;9. Available from: https://pubmed.ncbi.nlm.nih.gov/34112060/\u003c/li\u003e\n\u003cli\u003eSullivan KM, Mir RA, Dean AG. OpenEpi - Sample Size for Unmatched Case-Control Studies. Openepi.com. Available from: https://www.openepi.com/SampleSize/SSCC.htm. Accessed on 24 June 2025. \u003c/li\u003e\n\u003cli\u003eAgarwal MM. 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Relationship of age, body mass index, gravida, and parity in pregnant women with the incidence of preeclampsia. Obgynia. 2022 [cited 2025 Jun 25];5(2):208. Available from: https://www.obgynia.com/obgyn/index.php/obgynia/article/view/389/0 \u003c/li\u003e\n\u003cli\u003eMou AD, Barman Z, Hasan M, Miah R, Hafsa JM, Das Trisha A, et al. Prevalence of preeclampsia and the associated risk factors among pregnant women in Bangladesh. Sci Rep. 2021;11(1):21339. Available from: https://www.nature.com/articles/s41598-021-00839-w \u003c/li\u003e\n\u003cli\u003eWolie Asres A, Tilahun AW, Addissie A. Factors associated with preeclampsia among pregnant women in Gojjam zones, Amhara region, Ethiopia: a case-control study. Blood Press. 2023;32(1):2255687. Available from: http://dx.doi.org/10.1080/08037051.2023.2255687\u003c/li\u003e\n\u003cli\u003eNovelia S, Rukmaini, Puspita Sari E. Stress Levels and Pre-Eclampsia in Pregnancy. HTechJ. 2024;2(1):83\u0026ndash;8. Available from: http://dx.doi.org/10.53713/htechj.v2i1.135 \u003c/li\u003e\n\u003cli\u003eHeljezović \u0026Scaron;, Lučovnik M, Verdenik I, \u0026Scaron;ćepanović D. Association between regular physical activity during pregnancy and perinatal outcomes: A population-based cohort study. Eur J Obstet Gynecol Reprod Biol X. 2025;26(100380):100380. Available from: http://dx.doi.org/10.1016/j.eurox.2025.100380 \u003c/li\u003e\n\u003cli\u003eTeta Puji Rahayu, Aning Rezki Murtanti, Sunarto. The Influence of Hormonal Contraceptive Risk Factors on the Incidence of Preeclampsia. Malaysian Journal of Medicine and Health Sciences. Available from: https://medic.upm.edu.my/upload/dokumen/202411110823407_MJMHS_0484.pdf \u003c/li\u003e\n\u003cli\u003eKumari P, Chouhan M, Jakhar B, Sharma G. A comparative study of serum lipid profile in preeclampsia and normotensive pregnancy in the third trimester and their fetomaternal outcome. Int J Reprod Contracept Obstet Gynecol. 2023;12(7):2177\u0026ndash;84. Available from: http://dx.doi.org/10.18203/2320-1770.ijrcog20231790 \u003c/li\u003e\n\u003cli\u003eMohamedain A, Rayis DA, AlHabardi N, Adam I. Association between previous spontaneous abortion and preeclampsia: a case-control study. BMC Pregnancy Childbirth. 2022;22(1):715. Available from: http://dx.doi.org/10.1186/s12884-022-05053-8 \u003c/li\u003e\n\u003cli\u003eGilboa I, Kupferminc M, Schwartz A, Landsberg Ashereh Y, Yogev Y, Rappaport Skornik A, et al. The association between advanced maternal age and the manifestations of preeclampsia with severe features. J Clin Med. 2023;12(20). Available from: http://dx.doi.org/10.3390/jcm12206545 \u003c/li\u003e\n\u003cli\u003ePan M-L, Chen L-R, Tsao H-M, Chen K-H. Prepregnancy endocrine, autoimmune disorders and the risks of gestational hypertension-preeclampsia in primiparas: A nationwide population-based study in Taiwan. Int J Environ Res Public Health. 2020;17(10):3657. Available from: http://dx.doi.org/10.3390/ijerph17103657\u003c/li\u003e\n\u003cli\u003eAweke MN, Almaw H, Alemu GG, Mengistu B, Mengistu W, Mulugeta Y. Relationship between maternal anemia during pregnancy and the risk of preeclampsia: A multicenter case-control study. Nutr Health. 2024;2601060241287002. Available from: http://dx.doi.org/10.1177/02601060241287002 \u003c/li\u003e\n\u003cli\u003eDetlefs SE, Jochum MD, Salmanian B, McKinney JR, Aagaard KM. The impact of response to iron therapy on maternal and neonatal outcomes among pregnant women with anemia. Am J Obstet Gynecol MFM. 2022;4(2):100569. Available from: http://dx.doi.org/10.1016/j.ajogmf.2022.100569 \u003c/li\u003e\n\u003cli\u003eToloza FJK, Derakhshan A, M\u0026auml;nnist\u0026ouml; T, Bliddal S, Popova PV, Carty DM, et al. Association between maternal thyroid function and risk of gestational hypertension and pre-eclampsia: a systematic review and individual-participant data meta-analysis. Lancet Diabetes Endocrinol. 2022;10(4):243\u0026ndash;52. Available from: http://dx.doi.org/10.1016/S2213-8587(22)00007-9 \u003c/li\u003e\n\u003cli\u003eHosier H, Lipkind HS, Rasheed H, DeWan AT, Rogne T. Dyslipidemia and risk of preeclampsia: A multiancestry Mendelian randomization study. Hypertension. 2023;80(5):1067\u0026ndash;76. Available from: http://dx.doi.org/10.1161/HYPERTENSIONAHA.122.20426 \u003c/li\u003e\n\u003cli\u003eXue Q, Li G, Gao Y, Deng Y, Xu B, Chen Y, et al. Analysis of postpartum hypertension in women with preeclampsia. J Hum Hypertens. 2023;37(12):1063\u0026ndash;9. Available from: http://dx.doi.org/10.1038/s41371-023-00849-3 \u003c/li\u003e\n\u003cli\u003eVoskamp LW, Rousian M, Koerts JJ, Steegers-Theunissen RPM, Danser AHJ, Verdonk K. Risk factors for chronic hypertension 5 years after a pregnancy complicated by preeclampsia: a systematic review and meta-analysis. J Hypertens. 2025;43(6):939\u0026ndash;48. 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Impact of gestational hypertension and pre-eclampsia on preterm birth in China: a large prospective cohort study. BMJ Open. 2022;12(9):e058068. Available from: http://dx.doi.org/10.1136/bmjopen-2021-058068 \u003c/li\u003e\n\u003cli\u003eWen Y-H, Yang H-I, Chou H-C, Chen C-Y, Hsieh W-S, Tsou K-I, et al. Association of maternal preeclampsia with neonatal respiratory distress syndrome in very-low-birth-weight infants. Sci Rep. 2019;9(1):13212. Available from: http://dx.doi.org/10.1038/s41598-019-49561-8\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-pregnancy-and-childbirth","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"prch","sideBox":"Learn more about [BMC Pregnancy and Childbirth](http://bmcpregnancychildbirth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/prch/default.aspx","title":"BMC Pregnancy and Childbirth","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Preeclampsia, pregnant women, high blood pressure, maternal-fetal outcomes, multigravidity, maternal health","lastPublishedDoi":"10.21203/rs.3.rs-7106149/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7106149/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cb\u003eBackground\u003c/b\u003e\u003c/p\u003e\u003cp\u003ePreeclampsia is a pregnancy-related disorder characterized by high blood pressure and often proteinuria, affecting 2\u0026ndash;8% of pregnancies worldwide. Preeclampsia is linked to various factors, including diabetes, obesity, multiple pregnancies, primiparity, age over 30, family history, lifestyle habits, and chronic hypertension. This study aimed to identify the determinants of pre-eclampsia as well as the maternal-fetal outcomes associated with it.\u003c/p\u003e\u003cp\u003e\u003cb\u003eMethods\u003c/b\u003e\u003c/p\u003e\u003cp\u003e An unmatched case-control study included adults over 18 in the United Arab Emirates diagnosed with preeclampsia, who provided consent. Controls included those without preeclampsia. A content-validated questionnaire gathered data on socio-demographics, medical history, reproductive/obstetric history, surgical history, family history, and lifestyle factors. Chi-square and logistic regression analyses were performed on Statistical Package for Social Sciences (SPSS) version 30. A p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e\u003cp\u003e\u003cb\u003eResults\u003c/b\u003e\u003c/p\u003e\u003cp\u003eFactors such as unhealthy BMI (cOR 1.803), multigravidity (cOR 1.770), history of abortion (cOR 1.559), age at first pregnancy at 17\u0026ndash;20 (aOR\u0026thinsp;=\u0026thinsp;4.909) and 21\u0026ndash;29 years old (aOR\u0026thinsp;=\u0026thinsp;3.209), history of menstrual disorders (cOR 3.151), PCOS (cOR 2.611), hyperlipidemia (cOR 27.237), thyroid disorders (aOR\u0026thinsp;=\u0026thinsp;4.346), allergy (aOR\u0026thinsp;=\u0026thinsp;6.899), and family history of hypertension (aOR\u0026thinsp;=\u0026thinsp;3.323) were significantly associated with risk of developing preeclampsia. Similarly, maternal-fetal outcomes such as persistent hypertension, postpartum depression, preterm birth, placental abruption, and neonatal respiratory distress syndrome were significantly associated with preeclampsia among women who gave birth at least once.\u003c/p\u003e\u003cp\u003e\u003cb\u003eConclusion\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe results of this study highlight the importance of early detection of preeclampsia in at-risk individuals and addressing modifiable risk factors like stress and nutrition to reduce unfavorable pregnancy outcomes and to mitigate risk. Targeted interventions, such as raising pregnant women's awareness, can help reduce the adverse consequences. These findings also highlight the necessity for improving the overall maternal and fetal health and minimizing the complications associated with preeclampsia.\u003c/p\u003e","manuscriptTitle":"Unveiling the Risks and Outcomes of Preeclampsia: A Case-Control Study in the UAE","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-29 18:00:13","doi":"10.21203/rs.3.rs-7106149/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-09-30T17:17:16+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-30T06:33:58+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"93348263599811255740211491998963673613","date":"2025-09-26T07:32:11+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-25T19:44:23+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"36822862325057395528858028929952252324","date":"2025-09-25T08:49:38+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"70876204155682867474936353875616562870","date":"2025-09-22T06:04:57+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-21T19:54:19+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"31386581772252631016436837882548298131","date":"2025-09-19T14:57:16+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"206442811108572762109628386170957355151","date":"2025-09-19T11:51:30+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"138286179442385323647174839157651051822","date":"2025-09-19T06:00:15+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"194684816900726058829673327408532399160","date":"2025-09-19T04:56:55+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-04T09:43:59+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-28T14:09:07+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"51470502604948002994886520766492360315","date":"2025-08-28T09:57:33+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"72308003934834510300887331544235266460","date":"2025-08-21T00:33:34+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-08-20T10:49:37+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-08-11T16:44:06+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-07-21T18:33:41+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-07-19T14:10:52+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Pregnancy and Childbirth","date":"2025-07-19T14:06:53+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-pregnancy-and-childbirth","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"prch","sideBox":"Learn more about [BMC Pregnancy and Childbirth](http://bmcpregnancychildbirth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/prch/default.aspx","title":"BMC Pregnancy and Childbirth","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"c34069d5-126e-40f6-91b1-b2e0385f66c1","owner":[],"postedDate":"August 29th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-11-24T16:01:39+00:00","versionOfRecord":{"articleIdentity":"rs-7106149","link":"https://doi.org/10.1186/s12884-025-08448-5","journal":{"identity":"bmc-pregnancy-and-childbirth","isVorOnly":false,"title":"BMC Pregnancy and Childbirth"},"publishedOn":"2025-11-19 15:57:51","publishedOnDateReadable":"November 19th, 2025"},"versionCreatedAt":"2025-08-29 18:00:13","video":"","vorDoi":"10.1186/s12884-025-08448-5","vorDoiUrl":"https://doi.org/10.1186/s12884-025-08448-5","workflowStages":[]},"version":"v1","identity":"rs-7106149","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7106149","identity":"rs-7106149","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}