Upper respiratory infection and seasonal variations in the occurrence of in South Korea

Upper respiratory infection and seasonal variations in the occurrence of in South Korea | 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 Upper respiratory infection and seasonal variations in the occurrence of in South Korea Yong Wook Jung, Eui-hyeok Kim, Sang Ah Lee, Seunggi Min This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-1181147/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 5 You are reading this latest preprint version Abstract The aim of this study was to examine the effect of seasonal changes on the incidence of preeclampsia in Asian regions and populations, and to evaluate the relationship between upper respiratory infection during pregnancy and the development of preeclampsia. This was a cohort study of women who delivered singletons between 2012 and 2018 in South Korea. A total of 548080 first singleton births were included for analysis. A total of 9,311 patients (1.70%) were diagnosed with preeclampsia. Multivariate analysis showed that older age (≥30 years old), low income, residing in the southern area of Korea, history of smoking, history of heavy drinking, higher body mass index, hypertension, or diabetes mellitus were risk factors for PE. Univariate analysis showed that upper respiratory infection was associated with the incidence of preeclampsia (P=0.0294). However, this association was not maintained in the multivariate analysis (aOR, 1.01; 95% CI, 0.95 - 1.07). After adjusting for confounding variables, the occurrence of PE was the highest in December (aOR, 1.21; 95%CI, 1.10-1.34) and lowest in July and August. This study demonstrated that there are seasonal variations in the occurrence of preeclampsia in Korea. Moreover, upper respiratory infection may be associated with the development of PE. Preeclampsia seasonal variation common cold risk factors Figures Figure 1 Figure 2 Figure 3 Figure 4 1. Introduction Preeclampsia (PE) is a disorder of pregnancy affecting 5–7% of all pregnant women and is characterized by new-onset hypertension (HTN) and proteinuria after 20 weeks of gestation. PE adversely affects various organs, such as the liver, kidney, brain, and lungs. In addition, severe PE can lead to multiple organ dysfunction, which is responsible for over 70,000 maternal deaths and 500,000 fetal deaths every year 1 . The definitive treatment for PE is delivery of the placenta and the baby. However, despite the serious adverse effects of PE on maternal and fetal health, its cause and pathogenesis have yet to be elucidated. Several researchers have indicated that environmental factors, such as the socioeconomic status of the mother, maternal obesity, and cigarette smoking during pregnancy, have potential roles in the development of PE 2 – 4 . In addition to various maternal demographic factors, seasonal changes are known risk factors for the development of PE. In Norway, the prevalence of PE is the highest in the winter months and the lowest in August 5 . Similarly, in Sweden, the prevalence of PE is lower in summer than in winter 6 . The prevalence of PE increases during the dry season and decreases during the rainy season in Zimbabwe 7 . In addition to seasonal variations, ethnic differences associated with the monthly variations of PE incidence have been reported 8 . However, although previous studies on PE have been conducted in various regions and populations, there is little data on the incidence of PE in Asian populations and regions. The cause of seasonal variations in the occurrence of PE remains unknown. In our previous study, we conducted transcriptome analysis using cell-free RNA in amniotic fluid extracted from patients predicted to develop PE 9 . KEGG pathway analysis showed that various immune pathways, such as those of asthma, antigen processing and presentation, and Staphylococcus aureus infection, were dysregulated in patients with PE. Generally, seasonal variations are observed for common cold or upper respiratory infection (URI). Considering the findings of our previous study and the seasonal variations in the occurrence of PE, we hypothesized that URI during pregnancy affects the development of PE. Therefore, we performed this study to examine the effect of seasonal changes on the development of PE in Asian regions and populations, and to evaluate the relationship between URI during pregnancy and the development of PE. 2. Results A total of 2,354,219 births were recorded in Korea between 2012 and 2018 (Fig. 1 ). Of these, 1,282,507 were the first deliveries of the mothers. We excluded twin pregnancies (N=16,988), women who did not undergo National Health Screening Examination (NHSE) within 2 years before their delivery (N=696,562), those with missing variables (N=20,813) in the NHSE, and those who were covered by medical aid (N=694). Therefore, a total of 548,080 singleton deliveries recorded between 2012 and 2018 were included in this study, and PE was diagnosed in 9,311 (1.70%) women. The maternal characteristics of the participants are described in Table 1 . In univariate the analysis, age, income, residential area, smoking, physical activity, body mass index (BMI), HTN, diabetes mellitus (DM), and URI were associated with the incidence of PE. In the multivariate logistic regression analysis, all demographic variables were adjusted as possible confounders. The results showed that older age (≥30 years old), low income, residing in the southern area of Korea, history of smoking, history of heavy drinking, higher BMI, HTN, and DM were risk factors for PE. In addition, physical activity was associated with the incidence of PE, whereas heavy drinking was not observed in the univariate analysis. However, heavy drinking was associated with the incidence of PE in the multivariate analysis, whereas physical activity was not. URI was associated with the development of PE in the univariate analysis ( P = 0.0294); however, multivariate analysis showed that there was no relationship between URI and the prevalence of PE (aOR, 1.01; 95% CI, 0.95-1.07; P = 0.7806). Women aged ≥40 years, who were obese, had a history of HTN, or had DM had substantially higher risks for PE ([age ≥40 years old: aOR, 1.56; 95% CI, 1.42-1.72] [obesity: aOR, 3.52; 95% CI, 3.35-3.69] [HTN: aOR, 5.67; 95% CI, 5.16-6.24] [DM: aOR, 2.56; 95% CI, 2.13-3.08]). Table 1 Demographic data of the participants Variables Total Preeclampsia N (%) No (N, %) Yes (N, %) P aOR (95% CI) P Age at the time of delivery <0.0001 Under 25 12,497 (2.3) 12,282 (98.3) 215 (1.7) 1.12 (0.97 – 1.29) 0.1221 25-29 138,807 (25.3) 136,839 (98.6) 1,968 (1.4) 1.0 30-34 290,598 (53.0) 286,117 (98.5) 4,481 (1.5) 1.07 (1.01 – 1.12) 0.023 35-39 85,663 (15.6) 83,653 (97.7) 2,010 (2.4) 1.45 (1.36 – 1.54) <0.0001 40 or older 20,515 (3.7) 19,878 (96.9) 67 (3.1) 1.56 (1.42 – 1.72) <0.0001 Income status <0.0001 1st quartile 65,671 (12.0) 64,394 (98.1) 1,277 (1.9) 1.0 2nd quartile 161,029 (29.4) 158,051 (98.2) 2978 (1.9) 1.01 (0.95 – 1.08) 0.7072 3rd quartile 226,536 (41.3) 222,926 (98.4) 3,610 (1.6) 0.93 (0.87 – 0.99) 0.0271 4th quartile 94,844 (17.3) 93,398 (98.5) 1,446 (1.5) 0.90 (0.83 – 0.97) 0.0065 Residential area 0.0002 Central 362,046 (66.1) 356,064(98.4) 5,982 (1.7) 1.00 Southern 186,034 (33.9) 182,705 (98.2) 3,329 (1.8) 1.08 (1.03 – 1.12) 0.0010 Smoker <0.0001 No 530,431 (96.8) 521,550 (98.3) 8,881 (1.7) 1.00 Yes 17,649 (3.2) 17,219 (97.6) 430 (2.4) 1.24 (1.12 – 1.38) <0.0001 Heavy drinker 0.1092 No 445,903 (81.4) 438,388 (98.3) 7,515 (1.7) 1.00 Yes 102,177 (18.6) 100,381 (98.2) 1,796 (1.8) 1.07 (1.01 – 1.13) 0.0134 Physically active 0.0445 No 344,318 (62.8) 338,562 (98.3) 5,756 (1.7) 1.00 (0.96 – 1.04) 0.9669 Yes 203,762 (37.2) 200,207 (98.3) 3,555 (1.7) 1.00 BMI <0.0001 Underweight 69,326 (12.7) 68,760 (99.2) 566 (0.8) 0.70 (0.64 – 0.76) <0.0001 Normal 337,373 (61.6) 333,331 (98.8) 4,042 (1.2) 1.00 Overweight 70,968 (13.0) 69,511 (98.0) 1,457 (2.1) 1.66 (1.56 – 1.76) <0.0001 Obese 70,413 (12.9) 67,167 (95.4) 3,246 (4.6) 3.52 (3.35 – 3.69) <0.0001 History of HTN <0.0001 No 543,382 (99.1) 534,656 (98.4) 8,726 (1.6) 1.00 Yes 4,698 (0.9) 4,113 (87.6) 585 (12.5) 5.67 (5.16 – 6.24) <0.0001 History of DM <0.0001 No 461,062 (84.1) 453,727 (98.4) 7,335 (1.6) 1.00 Yes 1,355 (0.3) 1,193 (88.0) 162 (12.0) 2.56 (2.13 – 3.08) <0.0001 GDM 85,663 (15.6) 83,849 (97.9) 1,814 (2.1) <0.0001 URI during pregnancy 0.0294 No 476,485 (86.9) 468,461 (98.3) 8,024 (1.7) 1.00 0.7806 Yes 71595 (13.1) 70,308 (98.2) 1,287 (1.8) 1.01 (0.95 - 1.07) BMI, body mass index; HTN, hypertension; GDM, gestational diabetes mellitus; URI, common cold. The prevalence of PE was the highest (1.88%) in December and lowest (1.56%) in July and August (Table 2 , Fig. 2 ). After adjusting for confounding variables, the occurrence of PE was still the highest in December (aOR, 1.21; 95% CI, 1.10-1.34) and lowest in July and August. Fig. 3 shows the monthly variations in the occurrence of PE. When stratified according to the season of delivery before adjusting for confounding variables, the prevalence of PE was the lowest in the summer, increased gradually in the fall, and was highest in the spring. Adjustment for demographic variables did not alter seasonal trends in the development of PE. The prevalence ratios of PE were as follows: winter, 1.10 (95% CI, 1.04-1.17); spring, 1.12 (95% CI, 1.06-1.19); and fall, 1.06 (95% CI, 1.00-1.13). The prevalence of PE in spring and winter did not differ. Table 2 Prevalence rates and ratios of preeclampsia according to the month of delivery, with August as the reference month Month of delivery Total N (%) Preeclampsia Prevalence P Unadjusted OR (95% CI) P Adjusted OR (95% CI) P No (N, %) Yes (N, %) January 46,397 (8.5) 45,616 (98.3) 781 (1.7) 1.68 0.0002 1.08 (0.98 – 1.20) 0.1257 1.03 (0.93 – 1.14) 0.5640 February 41,351 (7.5) 40,621 (98.2) 730 (1.8) 1.77 1.14 (1.02 – 1.26) 0.0149 1.10 (1.00 – 1.22) 0.0609 March 45,053(8.2) 44,235 (98.2) 818 (1.8) 1.82 1.17 (1.06 – 1.29) 0.0022 1.15 (1.04 – 1.27) 0.0064 April 42,954 (7.8) 42,172 (98.2) 782 (1.8) 1.82 1.17 (1.06 - 1.30) 0.0020 1.17 ( 1.06 – 1.30) 0.0020 May 42,194 (7.7) 41,489 (98.3) 705 (1.7) 1.67 1.07 (0.97 – 1.19) 0.1775 1.08 (0.97 – 1.19) 0.1656 June 41,859 (7.6) 41,162 (98.3) 697 (1.7) 1.67 1.07 (0.97 – 1.19) 0.2012 1.06 (0.96 – 1.18) 0.2405 July 45,716 (8.3) 45,004 (98.4) 712 (1.6) 1.56 1.00 (0.90 – 1.11) 0.9927 0.98 (0.88 – 1.09) 0.6766 August 49,160 (9.0) 48,394 (98.4) 766 (1.6) 1.56 1.00 1.00 September 51,203 (9.3) 50,402 (98.4) 801 (1.6) 1.56 1.00 (0.91 – 1.11) 0.9371 1.01 (0.91 – 1.12) 0.8553 October 49,505 (9.0) 48,664 (98.3) 841 (1.7) 1.70 1.09 (0.99 – 1.21) 0.0811 1.10 (0.99 – 1.21) 0.0670 November 46,683 (8.5) 45,869 (98.3) 814 (1.7) 1.74 1.12 (1.01 – 1.24) 0.0243 1.13 (1.02 – 1.25) 0.0185 December 46,005 (8.4) 45,141 (98.1) 864 (1.9) 1.88 1.21 (1.10 – 1.33) 0.0001 1.21 (1.10 – 1.34) 0.0001 Delivery season 0.0002 Spring 130,201 (23.8) 127,896 (98.2) 1.77 1.12 (1.05 – 1.18) 0.0003 1.12 (1.06 – 1.19) 0.0002 Summer 136,735 (25.0) 134,560 (98.4) 1.59 1.00 1.00 Fall 147,391 (26.9) 144,935 (98.3) 1.67 1.05 (0.99 – 1.11) 0.1116 1.06 (1.00 – 1.13) 0.0407 Winter 133,753 (24.4) 131,378 (98.2) 1.78 1.12 (1.06 – 1.19) 0.0002 1.10 (1.04 – 1.17) 0.0015 Adjusted for age at the time of delivery, income status, residential area, smoking status, drinking, physical activity, body mass index, history of hypertension before pregnancy, diabetes mellitus, and upper respiratory infection during pregnancy 3. Discussion In this study, we analyzed the effects of seasonal variations on the incidence of PE in South Korea, and evaluated the relationship between URI during pregnancy and the development of PE. The results showed that several patient demographic factors, including age, socioeconomic status, residential area, behavioral habits, BMI, HTN, and DM were associated with the risk for PE. We also observed seasonal variations in the occurrence of PE in Korea. In this study cohort, the incidence of PE was the lowest in August but increased steadily from August to December, thus reaching its nadir in spring. In addition, this seasonal trend was maintained after maternal characteristics were adjusted as potential confounders. Furthermore, the results indicated that URI was associated with the occurrence of PE. However, the association between the development of PE and URI was not maintained in the multivariate analysis. In the retrospective cohort study of Magnus et al., which included 1,869,388 recorded deliveries in Norway for over 30 years (1967 to 1998), the risk for PE was the lowest in August and highest in the winter months 5 . Since this study by Magnus et al. was published, several researchers have also noted seasonal trends in the occurrence of PE. Ros et al. reported that the risk for PE was the lowest in the summer and among women who delivered outside Nordic countries 6 . Phillips et al. reported that in Vermont, United States, the incidence of PE in the summer was decreased compared to that in spring 10 . In Texas, although minimal seasonal variation was reported, the prevalence of PE was the lowest in the fall and highest in the winter 11 . This observation was maintained after adjusting for several confounders. Korea is located in East Asia and has a temperate climate with four distinct seasons. The mean temperature of Seoul, which is the capital of Korea, is -4°C in January and 24.0℃ in August (Fig. 4 ). Although there were some differences depending on the region, the seasonal variations in PE occurrence in the present study are consistent with those of previous studies conducted in various regions. Differences between the monthly variations in the incidence of PE among white and black women has been reported. Bodnar et al. stated that the incidence of PE among white women in the United States decreased during summer 8 . However, this seasonal pattern was not noted in black women. The Republic of Korea is an ethnically homogenous country. Approximately 96% of the total population are of Korean ethnicity and Asian; even half of the immigrants in Korea are from China 12 . Therefore, our data, which represents the Asian population, demonstrates that the incidence of PE in Asian women varies according to seasons, as in white women. The prevalence of PE may vary according to seasons. Some researchers have proposed that cold temperatures may cause peripheral vasoconstriction, which increases placental vascular resistance, thus resulting in placental insufficiency and PE. However, there are several limitations to the hypothesis of the relationship between seasonal variation and PE. Seasonal variation in PE exists in regions where there is no winter season 7 . In addition, ethnic differences in the monthly variations of the incidence of PE have been reported 8 . These observations suggest that environmental exposures related to monthly changes in lifestyle patterns, such as acute infection, dietary intake, and sunlight exposure, may contribute to the pathogenesis of PE. Of these environmental factors, infection plays a crucial role in the initiation and aggravation of uteroplacental insufficiency 13 . Various infectious diseases activate systemic inflammatory responses and endothelial injury, which may lead to uteroplacental atherosclerosis and placental hypoxia. These responses to inflammation result in an increased risk of PE. Several studies have demonstrated that urinary tract infection and periodontal disease are also potential risk factors for PE 14 – 17 . Among other infections, those related to URI vary with seasons. We hypothesized that the immune response associated with URI during pregnancy affects the development of PE. Although multivariate analysis did not show a statistically significant association between the development of PE and URI, univariate analysis demonstrated that URI was associated with an increased prevalence of PE. Thus, the data of the present study show a potential association between URI and PE. In addition, a correlation between URI caused by viral infection and increased odds of PE was observed in a prospective study of pregnant women with asthma 18 . Furthermore, Romanyuk et al. observed a statistically significant association between pneumonia and severe PE in their population-based study 19 . However, the results of some studies do not suggest an association between URI and the development of PE. Minassian et al. conducted a population-based case-control study of 1,533 patients with PE and 14,236 randomly selected controls to assess the effect of URI on the risk of PE. The authors excluded any non-specific URI from the analysis, such as acute respiratory infection and respiratory tract infection, but did not observe any association between URI and PE 16 . The conflicting results of these studies might be a result of the varying definitions of URI and PE and the heterogeneity of the study populations. Therefore, further studies with larger populations and more stringent definitions of URI are required. The present study has several limitations. First, we could not determine exact pregnancy dates, which is important to distinguish the subtypes of PE and estimate the month of conception. PE is divided into two subtypes according to disease onset: early (<34 gestational weeks) and late (≥34 gestational weeks). The pathophysiology of these two subtypes differs. Therefore, as we could not determine the subtypes of PE in this study, the effect of seasonal changes on the development of PE according to its subtypes could not be elucidated. Second, we did not analyze PE in relation to the timing of conception. Phillips et al. suggested that the timing of conception is more strongly related to the seasonal variations in the incidence of PE than the season of delivery 10 . Lastly, the timing of infection during pregnancy may affect pregnancy outcomes related to PE. Placental development is complete by the end of the first trimester of pregnancy. Development of URI during this critical period may have a greater impact on the development of PE. However, we could not evaluate the association between the development of PE and the timing of URI during pregnancy because we had limited data on pregnancy dates. This study also has several strengths. To the best of our knowledge, there is little data on the association between seasonal variations and the incidence of PE in Asian populations and regions. Therefore, the present study makes a considerable contribution to the existing research. Another strength is the use of a national database. Considering that we examined all recorded births between 2012 and 2018 in Korea, the study data provides more reliable information. Moreover, we investigated the relationship between URI and PE development. Several studies have been conducted to evaluate the association between the development of PE and urinary tract infection. However, few studies have been conducted to investigate the relationship between URI and PE. In summary, the present study demonstrated that there are seasonal variations in the occurrence of PE in Korea. In this study cohort, the incidence of PE was the lowest in August but gradually increased from August to December, thus reaching its nadir in spring. In addition, univariate analysis showed that URI was associated with the occurrence of PE. Further studies regarding the association between seasonal variations and the development of PE, with data on exact pregnancy dates, are required to evaluate the factors involved in the seasonal trends of PE development. Clarifying the biological mechanisms by which seasonal variations affect the development of PE is also necessary to elucidate the pathogenesis of PE. 4. Methods This was a retrospective cohort study conducted using National Health Insurance Service (NHIS) claims data, which were collected from January 2012 to December 2018. The government of South Korea provides universal healthcare coverage for 97% of the population residing in Korea through the NHIS. The remaining 3% are covered by medical aid to protect them from the financial burden of excessive medical expenditure. As part of the NHIS healthcare program, beneficiaries are invited to participate in a NHSE program biannually. The NHSE consists of health examinations and interviews, including questions regarding patients’ demographic, socioeconomic, and lifestyle characteristics. The results of the NHSE are stored in the NHIS database. To facilitate the evaluation of pre-pregnancy characteristics, only women who underwent an NHSE at least 2 years before their first delivery were included in the analysis. Those with missing data in the database were excluded. This study complies with the Declaration of Helsinki. The Institutional Review Board of the National Health Insurance Service (NHIS) Ilsan Hospital approved this study (NHIMC 2020). All methods were performed in accordance with the relevant guidelines and regulations. Written informed consent was waived by the Institutional Review Board of the National Health Insurance Service Ilsan Hospital because of the large number of participants in the cohort and the retrospective nature of the study. Given that the pathophysiology of HTN during pregnancy differs between parous and nulliparous women, only nulliparous women were included in the present study. The women included were identified using International Classification of Diseases, 10th revision (ICD-10) codes O11, O14, and O15 to identify cases of PE. The Korean Society of Obstetrics and Gynecology recommends that PE be diagnosed if gestational HTN and proteinuria are present. Gestational HTN was defined as ≥2 systolic blood pressure measurements ≥140 mmHg and/or a diastolic blood pressure ≥90 mmHg, which was observed for the first time in antenatal care. Proteinuria was defined as a 1+ result on two random urine dipstick tests or a 2 + result on one urine dipstick test. We examined known demographic risk factors for PE, including maternal age, income status, history of smoking, physical activity, heavy drinking, BMI, and medical history of HTN, DM, or URI during pregnancy. The women were stratified into four groups (quartiles) according to their economic status and according to BMI: underweight (BMI< 18.5 kg/m 2 ), normal (18.5-24.9 kg/m 2 ), overweight (25-29.9 kg/m 2 ), obese (≥30 kg/m 2 ). Regarding alcohol consumption habits, the included women were categorized as non-heavy or heavy drinkers. Heavy drinkers were defined as those with an alcohol consumption status that needed correction, those who consume alcohol more than four times per week, or those who have more than four drinks at a time. This definition is based on the criteria outlined by the National Institute on Alcohol Abuse and Alcoholism and revised by the Ministry of Health and Welfare (MOHW) in consideration of the alcohol consumption scenario in Korea. Regarding smoking status, the participants were categorized as current or non-smokers based on their NHSE results. For physical activity, the MOHW has presented a physical activity guide for Koreans based on the physical activity guidelines published by the US Department of Health and Human Services. According to the guidelines, physical activity is defined as more than three episodes of high-intensity workouts per week or more than five episodes of intermediate workouts per week. Korea has four distinct seasons: spring (March–May), summer (June–August), fall (September–November), and winter (December–February). Winter temperatures are higher along the southern coast (southern region) and considerably lower in the mountainous interior (central region). Therefore, we classified the participants’ areas of residence into southern or central regions. Regarding URI during pregnancy, the following ICD-10 codes were used to define/identify URI: R05, cough; R04, hemorrhage from respiratory passage; A37, whooping cough; J00-J06, acute upper respiratory infection; J10, influenza due to other identified influenza virus; and B34, viral infection of unspecified site. 4.1. Statistical analysis The demographic characteristics of the PE and control groups were compared using the chi-square test for categorical variables. The prevalence of births complicated by PE in each month and season was calculated. The relative risks for PE according to the month and season of delivery were estimated as adjusted prevalence odds ratios (aORs) using the month with the lowest risk as the reference. To adjust for possible confounding variables, multiple logistic regression was used to analyze the relative risk for PE using the other variables as ORs. The exact delivery date of each woman was identified using the NHIS claims data. The monthly prevalence of PE was calculated by dividing the number of women with PE in a month by the number of deliveries in that month. Statistical analyses were performed using SAS software (version 9.4; SAS Institute, Inc.; Cary, NC, USA). Declarations Acknowledgements This research was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) NRF-2019R1G1A1011557 Author contributions EK: Conceived and designed the study, collected data, SAL: Collected and analyzed the data, SM: Collected data YWJ: Conceived and designed the study, wrote the manuscript All authors contributed to data interpretation Conflicts of interest There are no conflicts of interest to declare. Funding This research was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) NRF-2019R1G1A1011557 Highlight There is a seasonality of preeclampsia incidence in South Korea References Kuklina, E. V., Ayala, C. & Callaghan, W. M. Hypertensive disorders and severe obstetric morbidity in the United States. Obstet Gynecol 113 , 1299–1306, doi: 10.1097/AOG.0b013e3181a45b25 (2009). Conde-Agudelo, A., Althabe, F., Belizan, J. M. & Kafury-Goeta, A. C. 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J Matern Fetal Neonatal Med 22 , 124–128, doi: 10.1080/14767050802488246 (2009). Murphy, V. E., Powell, H., Wark, P. A. B. & Gibson, P. G. A prospective study of respiratory viral infection in pregnant women with and without asthma. Chest 144 , 420–427, doi: 10.1378/chest.12-1956 (2013). Romanyuk, V., Raichel, L., Sergienko, R. & Sheiner, E. Pneumonia during pregnancy: radiological characteristics, predisposing factors and pregnancy outcomes. J Matern Fetal Neonatal Med 24 , 113–117, doi: 10.3109/14767051003678275 (2011). 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-1181147","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":79137040,"identity":"b5531893-cc3a-4483-b8ab-00a9836e4efa","order_by":0,"name":"Yong Wook Jung","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAyklEQVRIiWNgGAWjYDCCAwxsIEqOQQImwkOkFmPStSQ2EK2F70Z22mPeHbXp/bObn274wWAnx8Bz9gFeLZI3crcb8545njvjzjGzmz0MycYMvO0GeLUY3MjdJs3bdix3g0SC2W2gOxMb+NnwOwymJd1AIv0bSVpqEgwkcqC28Lbh1yJ55u12w7ltBwxn3Mgpu9ljkGzMxnMMvxa+47nbHrxtq5Pnn5G+7caPCjs5fp40/Fqg4DDMnQwMBHwCB3VEqhsFo2AUjIIRCQAjZUVXwd8XBQAAAABJRU5ErkJggg==","orcid":"","institution":"CHA Gangnam Medical Center, CHA University","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Yong","middleName":"Wook","lastName":"Jung","suffix":""},{"id":79137037,"identity":"e2ddb7ba-4589-4016-b949-caec2c0f81c4","order_by":1,"name":"Eui-hyeok Kim","email":"","orcid":"","institution":"National Health Insurance Service Ilsan Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Eui-hyeok","middleName":"","lastName":"Kim","suffix":""},{"id":79137038,"identity":"12b62e39-4c03-413b-a998-471d521a8aff","order_by":2,"name":"Sang Ah Lee","email":"","orcid":"","institution":"National Health Insurance Service Ilsan Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Sang","middleName":"Ah","lastName":"Lee","suffix":""},{"id":79137039,"identity":"716263cd-4679-433a-852c-91379b0a7aff","order_by":3,"name":"Seunggi Min","email":"","orcid":"","institution":"CHA Gangnam Medical Center, CHA University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Seunggi","middleName":"","lastName":"Min","suffix":""}],"badges":[],"createdAt":"2021-12-17 13:59:06","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-1181147/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-1181147/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":17716659,"identity":"dd396c46-524f-4556-ac8b-fbc0c710b638","added_by":"auto","created_at":"2022-01-27 21:34:40","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":26635,"visible":true,"origin":"","legend":"\u003cp\u003eFlowchart of the study\u003c/p\u003e","description":"","filename":"OnlineFig1.png","url":"https://assets-eu.researchsquare.com/files/rs-1181147/v1/9258c59785342bc6a721ba4e.png"},{"id":17716926,"identity":"82528332-472e-4026-a202-0e478943acf5","added_by":"auto","created_at":"2022-01-27 21:37:40","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":21082,"visible":true,"origin":"","legend":"\u003cp\u003ePrevalence of preeclampsia according to the month of delivery\u003c/p\u003e","description":"","filename":"OnlineFig2.png","url":"https://assets-eu.researchsquare.com/files/rs-1181147/v1/d7dc7f9fbff66c890b9166f2.png"},{"id":17716656,"identity":"08c208bd-9891-48ec-9ce0-88ec9db69e2c","added_by":"auto","created_at":"2022-01-27 21:34:40","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":13939,"visible":true,"origin":"","legend":"\u003cp\u003eAssociation between the month of delivery and preeclampsia\u003c/p\u003e\u003cp\u003e*Adjusted for age at the time of delivery, income status, residential area, smoking status, drinking status, physical activity, body mass index, history of hypertension before pregnancy, diabetes mellitus, and upper respiratory infection during pregnancy.\u0026nbsp;\u003c/p\u003e","description":"","filename":"OnlineFig3.png","url":"https://assets-eu.researchsquare.com/files/rs-1181147/v1/2f21e8629d9b9967145cb494.png"},{"id":17716657,"identity":"e39c1091-e8de-4d1f-9f14-41c084923139","added_by":"auto","created_at":"2022-01-27 21:34:40","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":21049,"visible":true,"origin":"","legend":"\u003cp\u003eClimate chart of South Korea\u003c/p\u003e","description":"","filename":"OnlineFig4.png","url":"https://assets-eu.researchsquare.com/files/rs-1181147/v1/7f49589974d10c0e498fc2bf.png"},{"id":17716927,"identity":"f16e1f5b-2ce9-4a45-af05-23bf11d2dae9","added_by":"auto","created_at":"2022-01-27 21:37:43","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":606988,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-1181147/v1/276567dc-89d6-46e0-86d5-7134e7727eb3.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Upper respiratory infection and seasonal variations in the occurrence of in South Korea","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003ePreeclampsia (PE) is a disorder of pregnancy affecting 5\u0026ndash;7% of all pregnant women and is characterized by new-onset hypertension (HTN) and proteinuria after 20 weeks of gestation. PE adversely affects various organs, such as the liver, kidney, brain, and lungs. In addition, severe PE can lead to multiple organ dysfunction, which is responsible for over 70,000 maternal deaths and 500,000 fetal deaths every year\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. The definitive treatment for PE is delivery of the placenta and the baby. However, despite the serious adverse effects of PE on maternal and fetal health, its cause and pathogenesis have yet to be elucidated.\u003c/p\u003e \u003cp\u003eSeveral researchers have indicated that environmental factors, such as the socioeconomic status of the mother, maternal obesity, and cigarette smoking during pregnancy, have potential roles in the development of PE\u003csup\u003e\u003cspan additionalcitationids=\"CR3\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. In addition to various maternal demographic factors, seasonal changes are known risk factors for the development of PE. In Norway, the prevalence of PE is the highest in the winter months and the lowest in August\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. Similarly, in Sweden, the prevalence of PE is lower in summer than in winter\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. The prevalence of PE increases during the dry season and decreases during the rainy season in Zimbabwe\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. In addition to seasonal variations, ethnic differences associated with the monthly variations of PE incidence have been reported\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. However, although previous studies on PE have been conducted in various regions and populations, there is little data on the incidence of PE in Asian populations and regions.\u003c/p\u003e \u003cp\u003eThe cause of seasonal variations in the occurrence of PE remains unknown. In our previous study, we conducted transcriptome analysis using cell-free RNA in amniotic fluid extracted from patients predicted to develop PE\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. KEGG pathway analysis showed that various immune pathways, such as those of asthma, antigen processing and presentation, and \u003cem\u003eStaphylococcus aureus\u003c/em\u003e infection, were dysregulated in patients with PE. Generally, seasonal variations are observed for common cold or upper respiratory infection (URI). Considering the findings of our previous study and the seasonal variations in the occurrence of PE, we hypothesized that URI during pregnancy affects the development of PE. Therefore, we performed this study to examine the effect of seasonal changes on the development of PE in Asian regions and populations, and to evaluate the relationship between URI during pregnancy and the development of PE.\u003c/p\u003e"},{"header":"2. Results","content":"\u003cp\u003eA total of 2,354,219 births were recorded in Korea between 2012 and 2018 (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Of these, 1,282,507 were the first deliveries of the mothers. We excluded twin pregnancies (N=16,988), women who did not undergo National Health Screening Examination (NHSE) within 2 years before their delivery (N=696,562), those with missing variables (N=20,813) in the NHSE, and those who were covered by medical aid (N=694). Therefore, a total of 548,080 singleton deliveries recorded between 2012 and 2018 were included in this study, and PE was diagnosed in 9,311 (1.70%) women.\u003c/p\u003e \u003cp\u003eThe maternal characteristics of the participants are described in Table \u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. In univariate the analysis, age, income, residential area, smoking, physical activity, body mass index (BMI), HTN, diabetes mellitus (DM), and URI were associated with the incidence of PE. In the multivariate logistic regression analysis, all demographic variables were adjusted as possible confounders. The results showed that older age (\u0026ge;30 years old), low income, residing in the southern area of Korea, history of smoking, history of heavy drinking, higher BMI, HTN, and DM were risk factors for PE. In addition, physical activity was associated with the incidence of PE, whereas heavy drinking was not observed in the univariate analysis. However, heavy drinking was associated with the incidence of PE in the multivariate analysis, whereas physical activity was not. URI was associated with the development of PE in the univariate analysis (\u003cem\u003eP\u003c/em\u003e = 0.0294); however, multivariate analysis showed that there was no relationship between URI and the prevalence of PE (aOR, 1.01; 95% CI, 0.95-1.07; \u003cem\u003eP\u003c/em\u003e = 0.7806). Women aged \u0026ge;40 years, who were obese, had a history of HTN, or had DM had substantially higher risks for PE ([age \u0026ge;40 years old: aOR, 1.56; 95% CI, 1.42-1.72] [obesity: aOR, 3.52; 95% CI, 3.35-3.69] [HTN: aOR, 5.67; 95% CI, 5.16-6.24] [DM: aOR, 2.56; 95% CI, 2.13-3.08]).\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\u003eDemographic data of the participants\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\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\u003eTotal\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003ePreeclampsia\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo (N, %)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eYes (N, %)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eaOR (95% CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge at the time of delivery\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;0.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnder 25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12,497 (2.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12,282 (98.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e215 (1.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.12 (0.97 \u0026ndash; 1.29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.1221\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e25-29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e138,807 (25.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e136,839 (98.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,968 (1.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.0\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\"\u003e \u003cp\u003e30-34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e290,598 (53.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e286,117 (98.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4,481 (1.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.07 (1.01 \u0026ndash; 1.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.023\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e35-39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e85,663 (15.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e83,653 (97.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2,010 (2.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.45 (1.36 \u0026ndash; 1.54)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e40 or older\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20,515 (3.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19,878 (96.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e67 (3.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.56 (1.42 \u0026ndash; 1.72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIncome status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;0.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1st quartile\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e65,671 (12.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e64,394 (98.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,277 (1.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.0\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\"\u003e \u003cp\u003e2nd quartile\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e161,029 (29.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e158,051 (98.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2978 (1.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.01 (0.95 \u0026ndash; 1.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.7072\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3rd quartile\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e226,536 (41.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e222,926 (98.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3,610 (1.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.93 (0.87 \u0026ndash; 0.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.0271\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4th quartile\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e94,844 (17.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e93,398 (98.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,446 (1.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.90 (0.83 \u0026ndash; 0.97)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.0065\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eResidential area\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCentral\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e362,046 (66.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e356,064(98.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5,982 (1.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.00\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\"\u003e \u003cp\u003eSouthern\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e186,034 (33.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e182,705 (98.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3,329 (1.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.08 (1.03 \u0026ndash; 1.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.0010\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmoker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;0.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e530,431 (96.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e521,550 (98.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8,881 (1.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.00\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\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17,649 (3.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17,219 (97.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e430 (2.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.24 (1.12 \u0026ndash; 1.38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeavy drinker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.1092\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e445,903 (81.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e438,388 (98.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7,515 (1.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.00\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\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e102,177 (18.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e100,381 (98.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,796 (1.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.07 (1.01 \u0026ndash; 1.13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.0134\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePhysically active\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0445\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e344,318 (62.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e338,562 (98.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5,756 (1.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.00 (0.96 \u0026ndash; 1.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.9669\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e203,762 (37.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e200,207 (98.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3,555 (1.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.00\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\"\u003e \u003cp\u003eBMI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;0.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnderweight\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e69,326 (12.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e68,760 (99.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e566 (0.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.70 (0.64 \u0026ndash; 0.76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e337,373 (61.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e333,331 (98.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4,042 (1.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.00\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\"\u003e \u003cp\u003eOverweight\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e70,968 (13.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e69,511 (98.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,457 (2.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.66 (1.56 \u0026ndash; 1.76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObese\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e70,413 (12.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e67,167 (95.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3,246 (4.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.52 (3.35 \u0026ndash; 3.69)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHistory of HTN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;0.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e543,382 (99.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e534,656 (98.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8,726 (1.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.00\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\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4,698 (0.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4,113 (87.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e585 (12.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.67 (5.16 \u0026ndash; 6.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHistory of DM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;0.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e461,062 (84.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e453,727 (98.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7,335 (1.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.00\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\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,355 (0.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,193 (88.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e162 (12.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.56 (2.13 \u0026ndash; 3.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGDM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e85,663 (15.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e83,849 (97.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,814 (2.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eURI during pregnancy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0294\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e476,485 (86.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e468,461 (98.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8,024 (1.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.7806\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e71595 (13.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e70,308 (98.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,287 (1.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.01 (0.95 - 1.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eBMI, body mass index; HTN, hypertension; GDM, gestational diabetes mellitus; URI, common cold.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe prevalence of PE was the highest (1.88%) in December and lowest (1.56%) in July and August (Table \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e2\u003c/span\u003e). After adjusting for confounding variables, the occurrence of PE was still the highest in December (aOR, 1.21; 95% CI, 1.10-1.34) and lowest in July and August. Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e3\u003c/span\u003e shows the monthly variations in the occurrence of PE. When stratified according to the season of delivery before adjusting for confounding variables, the prevalence of PE was the lowest in the summer, increased gradually in the fall, and was highest in the spring. Adjustment for demographic variables did not alter seasonal trends in the development of PE. The prevalence ratios of PE were as follows: winter, 1.10 (95% CI, 1.04-1.17); spring, 1.12 (95% CI, 1.06-1.19); and fall, 1.06 (95% CI, 1.00-1.13). The prevalence of PE in spring and winter did not differ.\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\u003ePrevalence rates and ratios of preeclampsia according to the month of delivery, with August as the reference month\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"10\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eMonth of delivery\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003cp\u003eN (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003ePreeclampsia\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ePrevalence\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eUnadjusted OR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAdjusted OR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo (N, %)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eYes (N, %)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eJanuary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e46,397 (8.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e45,616 (98.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e781 (1.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.0002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.08 (0.98 \u0026ndash; 1.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.1257\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1.03 (0.93 \u0026ndash; 1.14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.5640\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFebruary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e41,351 (7.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e40,621 (98.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e730 (1.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.14 (1.02 \u0026ndash; 1.26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.0149\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1.10 (1.00 \u0026ndash; 1.22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.0609\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarch\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e45,053(8.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e44,235 (98.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e818 (1.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.17 (1.06 \u0026ndash; 1.29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.0022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1.15 (1.04 \u0026ndash; 1.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.0064\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eApril\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e42,954 (7.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e42,172 (98.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e782 (1.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.17 (1.06 - 1.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.0020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1.17 ( 1.06 \u0026ndash; 1.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.0020\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMay\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e42,194 (7.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e41,489 (98.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e705 (1.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.07 (0.97 \u0026ndash; 1.19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.1775\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1.08 (0.97 \u0026ndash; 1.19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.1656\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eJune\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e41,859 (7.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e41,162 (98.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e697 (1.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.07 (0.97 \u0026ndash; 1.19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.2012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1.06 (0.96 \u0026ndash; 1.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.2405\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eJuly\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e45,716 (8.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e45,004 (98.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e712 (1.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.00 (0.90 \u0026ndash; 1.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.9927\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.98 (0.88 \u0026ndash; 1.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.6766\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAugust\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e49,160 (9.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e48,394 (98.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e766 (1.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSeptember\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e51,203 (9.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e50,402 (98.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e801 (1.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.00 (0.91 \u0026ndash; 1.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.9371\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1.01 (0.91 \u0026ndash; 1.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.8553\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOctober\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e49,505 (9.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e48,664 (98.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e841 (1.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.09 (0.99 \u0026ndash; 1.21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.0811\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1.10 (0.99 \u0026ndash; 1.21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.0670\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNovember\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e46,683 (8.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e45,869 (98.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e814 (1.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.12 (1.01 \u0026ndash; 1.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.0243\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1.13 (1.02 \u0026ndash; 1.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.0185\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDecember\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e46,005 (8.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e45,141 (98.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e864 (1.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.21 (1.10 \u0026ndash; 1.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1.21 (1.10 \u0026ndash; 1.34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDelivery season\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.0002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSpring\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e130,201 (23.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e127,896 (98.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.12 (1.05 \u0026ndash; 1.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.0003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1.12 (1.06 \u0026ndash; 1.19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.0002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSummer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e136,735 (25.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e134,560 (98.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFall\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e147,391 (26.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e144,935 (98.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.05 (0.99 \u0026ndash; 1.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.1116\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1.06 (1.00 \u0026ndash; 1.13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.0407\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWinter\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e133,753 (24.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e131,378 (98.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.12 (1.06 \u0026ndash; 1.19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.0002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1.10 (1.04 \u0026ndash; 1.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.0015\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"10\"\u003eAdjusted for age at the time of delivery, income status, residential area, smoking status, drinking, physical activity, body mass index, history of hypertension before pregnancy, diabetes mellitus, and upper respiratory infection during pregnancy\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"3. Discussion","content":"\u003cp\u003eIn this study, we analyzed the effects of seasonal variations on the incidence of PE in South Korea, and evaluated the relationship between URI during pregnancy and the development of PE. The results showed that several patient demographic factors, including age, socioeconomic status, residential area, behavioral habits, BMI, HTN, and DM were associated with the risk for PE. We also observed seasonal variations in the occurrence of PE in Korea. In this study cohort, the incidence of PE was the lowest in August but increased steadily from August to December, thus reaching its nadir in spring. In addition, this seasonal trend was maintained after maternal characteristics were adjusted as potential confounders. Furthermore, the results indicated that URI was associated with the occurrence of PE. However, the association between the development of PE and URI was not maintained in the multivariate analysis.\u003c/p\u003e \u003cp\u003eIn the retrospective cohort study of Magnus et al., which included 1,869,388 recorded deliveries in Norway for over 30 years (1967 to 1998), the risk for PE was the lowest in August and highest in the winter months\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. Since this study by Magnus et al. was published, several researchers have also noted seasonal trends in the occurrence of PE. Ros et al. reported that the risk for PE was the lowest in the summer and among women who delivered outside Nordic countries\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. Phillips et al. reported that in Vermont, United States, the incidence of PE in the summer was decreased compared to that in spring\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. In Texas, although minimal seasonal variation was reported, the prevalence of PE was the lowest in the fall and highest in the winter\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. This observation was maintained after adjusting for several confounders. Korea is located in East Asia and has a temperate climate with four distinct seasons. The mean temperature of Seoul, which is the capital of Korea, is -4\u0026deg;C in January and 24.0℃ in August (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Although there were some differences depending on the region, the seasonal variations in PE occurrence in the present study are consistent with those of previous studies conducted in various regions.\u003c/p\u003e \u003cp\u003eDifferences between the monthly variations in the incidence of PE among white and black women has been reported. Bodnar et al. stated that the incidence of PE among white women in the United States decreased during summer\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. However, this seasonal pattern was not noted in black women. The Republic of Korea is an ethnically homogenous country. Approximately 96% of the total population are of Korean ethnicity and Asian; even half of the immigrants in Korea are from China\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. Therefore, our data, which represents the Asian population, demonstrates that the incidence of PE in Asian women varies according to seasons, as in white women.\u003c/p\u003e \u003cp\u003eThe prevalence of PE may vary according to seasons. Some researchers have proposed that cold temperatures may cause peripheral vasoconstriction, which increases placental vascular resistance, thus resulting in placental insufficiency and PE. However, there are several limitations to the hypothesis of the relationship between seasonal variation and PE. Seasonal variation in PE exists in regions where there is no winter season\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. In addition, ethnic differences in the monthly variations of the incidence of PE have been reported\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. These observations suggest that environmental exposures related to monthly changes in lifestyle patterns, such as acute infection, dietary intake, and sunlight exposure, may contribute to the pathogenesis of PE. Of these environmental factors, infection plays a crucial role in the initiation and aggravation of uteroplacental insufficiency\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. Various infectious diseases activate systemic inflammatory responses and endothelial injury, which may lead to uteroplacental atherosclerosis and placental hypoxia. These responses to inflammation result in an increased risk of PE. Several studies have demonstrated that urinary tract infection and periodontal disease are also potential risk factors for PE\u003csup\u003e\u003cspan additionalcitationids=\"CR15 CR16\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. Among other infections, those related to URI vary with seasons. We hypothesized that the immune response associated with URI during pregnancy affects the development of PE. Although multivariate analysis did not show a statistically significant association between the development of PE and URI, univariate analysis demonstrated that URI was associated with an increased prevalence of PE. Thus, the data of the present study show a potential association between URI and PE. In addition, a correlation between URI caused by viral infection and increased odds of PE was observed in a prospective study of pregnant women with asthma\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. Furthermore, Romanyuk et al. observed a statistically significant association between pneumonia and severe PE in their population-based study\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. However, the results of some studies do not suggest an association between URI and the development of PE. Minassian et al. conducted a population-based case-control study of 1,533 patients with PE and 14,236 randomly selected controls to assess the effect of URI on the risk of PE. The authors excluded any non-specific URI from the analysis, such as acute respiratory infection and respiratory tract infection, but did not observe any association between URI and PE\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. The conflicting results of these studies might be a result of the varying definitions of URI and PE and the heterogeneity of the study populations. Therefore, further studies with larger populations and more stringent definitions of URI are required.\u003c/p\u003e \u003cp\u003eThe present study has several limitations. First, we could not determine exact pregnancy dates, which is important to distinguish the subtypes of PE and estimate the month of conception. PE is divided into two subtypes according to disease onset: early (\u0026lt;34 gestational weeks) and late (\u0026ge;34 gestational weeks). The pathophysiology of these two subtypes differs. Therefore, as we could not determine the subtypes of PE in this study, the effect of seasonal changes on the development of PE according to its subtypes could not be elucidated. Second, we did not analyze PE in relation to the timing of conception. Phillips et al. suggested that the timing of conception is more strongly related to the seasonal variations in the incidence of PE than the season of delivery\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. Lastly, the timing of infection during pregnancy may affect pregnancy outcomes related to PE. Placental development is complete by the end of the first trimester of pregnancy. Development of URI during this critical period may have a greater impact on the development of PE. However, we could not evaluate the association between the development of PE and the timing of URI during pregnancy because we had limited data on pregnancy dates.\u003c/p\u003e \u003cp\u003eThis study also has several strengths. To the best of our knowledge, there is little data on the association between seasonal variations and the incidence of PE in Asian populations and regions. Therefore, the present study makes a considerable contribution to the existing research. Another strength is the use of a national database. Considering that we examined all recorded births between 2012 and 2018 in Korea, the study data provides more reliable information. Moreover, we investigated the relationship between URI and PE development. Several studies have been conducted to evaluate the association between the development of PE and urinary tract infection. However, few studies have been conducted to investigate the relationship between URI and PE.\u003c/p\u003e \u003cp\u003eIn summary, the present study demonstrated that there are seasonal variations in the occurrence of PE in Korea. In this study cohort, the incidence of PE was the lowest in August but gradually increased from August to December, thus reaching its nadir in spring. In addition, univariate analysis showed that URI was associated with the occurrence of PE. Further studies regarding the association between seasonal variations and the development of PE, with data on exact pregnancy dates, are required to evaluate the factors involved in the seasonal trends of PE development. Clarifying the biological mechanisms by which seasonal variations affect the development of PE is also necessary to elucidate the pathogenesis of PE.\u003c/p\u003e"},{"header":"4. Methods","content":"\u003cp\u003eThis was a retrospective cohort study conducted using National Health Insurance Service (NHIS) claims data, which were collected from January 2012 to December 2018. The government of South Korea provides universal healthcare coverage for 97% of the population residing in Korea through the NHIS. The remaining 3% are covered by medical aid to protect them from the financial burden of excessive medical expenditure. As part of the NHIS healthcare program, beneficiaries are invited to participate in a NHSE program biannually. The NHSE consists of health examinations and interviews, including questions regarding patients\u0026rsquo; demographic, socioeconomic, and lifestyle characteristics. The results of the NHSE are stored in the NHIS database. To facilitate the evaluation of pre-pregnancy characteristics, only women who underwent an NHSE at least 2 years before their first delivery were included in the analysis. Those with missing data in the database were excluded. This study complies with the Declaration of Helsinki. The Institutional Review Board of the National Health Insurance Service (NHIS) Ilsan Hospital approved this study (NHIMC 2020). All methods were performed in accordance with the relevant guidelines and regulations. Written informed consent was waived by the Institutional Review Board of the National Health Insurance Service Ilsan Hospital because of the large number of participants in the cohort and the retrospective nature of the study.\u003c/p\u003e \u003cp\u003eGiven that the pathophysiology of HTN during pregnancy differs between parous and nulliparous women, only nulliparous women were included in the present study. The women included were identified using International Classification of Diseases, 10th revision (ICD-10) codes O11, O14, and O15 to identify cases of PE. The Korean Society of Obstetrics and Gynecology recommends that PE be diagnosed if gestational HTN and proteinuria are present. Gestational HTN was defined as \u0026ge;2 systolic blood pressure measurements \u0026ge;140 mmHg and/or a diastolic blood pressure \u0026ge;90 mmHg, which was observed for the first time in antenatal care. Proteinuria was defined as a 1+ result on two random urine dipstick tests or a 2 + result on one urine dipstick test.\u003c/p\u003e \u003cp\u003eWe examined known demographic risk factors for PE, including maternal age, income status, history of smoking, physical activity, heavy drinking, BMI, and medical history of HTN, DM, or URI during pregnancy. The women were stratified into four groups (quartiles) according to their economic status and according to BMI: underweight (BMI\u0026lt; 18.5 kg/m\u003csup\u003e2\u003c/sup\u003e), normal (18.5-24.9 kg/m\u003csup\u003e2\u003c/sup\u003e), overweight (25-29.9 kg/m\u003csup\u003e2\u003c/sup\u003e), obese (\u0026ge;30 kg/m\u003csup\u003e2\u003c/sup\u003e). Regarding alcohol consumption habits, the included women were categorized as non-heavy or heavy drinkers. Heavy drinkers were defined as those with an alcohol consumption status that needed correction, those who consume alcohol more than four times per week, or those who have more than four drinks at a time. This definition is based on the criteria outlined by the National Institute on Alcohol Abuse and Alcoholism and revised by the Ministry of Health and Welfare (MOHW) in consideration of the alcohol consumption scenario in Korea. Regarding smoking status, the participants were categorized as current or non-smokers based on their NHSE results. For physical activity, the MOHW has presented a physical activity guide for Koreans based on the physical activity guidelines published by the US Department of Health and Human Services. According to the guidelines, physical activity is defined as more than three episodes of high-intensity workouts per week or more than five episodes of intermediate workouts per week.\u003c/p\u003e \u003cp\u003eKorea has four distinct seasons: spring (March\u0026ndash;May), summer (June\u0026ndash;August), fall (September\u0026ndash;November), and winter (December\u0026ndash;February). Winter temperatures are higher along the southern coast (southern region) and considerably lower in the mountainous interior (central region). Therefore, we classified the participants\u0026rsquo; areas of residence into southern or central regions. Regarding URI during pregnancy, the following ICD-10 codes were used to define/identify URI: R05, cough; R04, hemorrhage from respiratory passage; A37, whooping cough; J00-J06, acute upper respiratory infection; J10, influenza due to other identified influenza virus; and B34, viral infection of unspecified site.\u003c/p\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e4.1. Statistical analysis\u003c/h2\u003e \u003cp\u003eThe demographic characteristics of the PE and control groups were compared using the chi-square test for categorical variables. The prevalence of births complicated by PE in each month and season was calculated. The relative risks for PE according to the month and season of delivery were estimated as adjusted prevalence odds ratios (aORs) using the month with the lowest risk as the reference. To adjust for possible confounding variables, multiple logistic regression was used to analyze the relative risk for PE using the other variables as ORs. The exact delivery date of each woman was identified using the NHIS claims data. The monthly prevalence of PE was calculated by dividing the number of women with PE in a month by the number of deliveries in that month. Statistical analyses were performed using SAS software (version 9.4; SAS Institute, Inc.; Cary, NC, USA).\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAcknowledgements\u003c/h2\u003e\n\u003cp\u003eThis research was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) NRF-2019R1G1A1011557\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003eAuthor contributions\u003c/h2\u003e\n\u003cp\u003eEK: Conceived and designed the study, collected data,\u003c/p\u003e\n\u003cp\u003eSAL: Collected and analyzed the data,\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSM: Collected data\u003c/p\u003e\n\u003cp\u003eYWJ: Conceived and designed the study, wrote the manuscript\u003c/p\u003e\n\u003cp\u003eAll authors contributed to data interpretation\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003eConflicts of interest\u003c/h2\u003e\n\u003cp\u003eThere are no conflicts of interest to declare.\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003eFunding\u003c/h2\u003e\n\u003cp\u003eThis research was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) NRF-2019R1G1A1011557\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003eHighlight\u003c/h2\u003e\n\u003cp\u003eThere is a seasonality of preeclampsia incidence in South Korea\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eKuklina, E. 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J Matern Fetal Neonatal Med \u003cb\u003e24\u003c/b\u003e, 113\u0026ndash;117, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3109/14767051003678275\u003c/span\u003e\u003c/span\u003e (2011).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Preeclampsia, seasonal variation, common cold, risk factors","lastPublishedDoi":"10.21203/rs.3.rs-1181147/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-1181147/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe aim of this study was to examine the effect of seasonal changes on the incidence of preeclampsia in Asian regions and populations, and to evaluate the relationship between upper respiratory infection during pregnancy and the development of preeclampsia. This was a cohort study of women who delivered singletons between 2012 and 2018 in South Korea. A total of 548080 first singleton births were included for analysis. A total of 9,311 patients (1.70%) were diagnosed with preeclampsia. Multivariate analysis showed that older age (\u0026ge;30 years old), low income, residing in the southern area of Korea, history of smoking, history of heavy drinking, higher body mass index, hypertension, or diabetes mellitus were risk factors for PE. Univariate analysis showed that upper respiratory infection was associated with the incidence of preeclampsia (P=0.0294). However, this association was not maintained in the multivariate analysis (aOR, 1.01; 95% CI, 0.95 - 1.07). After adjusting for confounding variables, the occurrence of PE was the highest in December (aOR, 1.21; 95%CI, 1.10-1.34) and lowest in July and August. This study demonstrated that there are seasonal variations in the occurrence of preeclampsia in Korea. Moreover, upper respiratory infection may be associated with the development of PE.\u003c/p\u003e","manuscriptTitle":"Upper respiratory infection and seasonal variations in the occurrence of in South Korea","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2022-01-27 21:34:38","doi":"10.21203/rs.3.rs-1181147/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Major revision","date":"2022-02-17T07:09:17+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2022-02-14T00:44:08+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2022-01-25T15:42:57+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2022-01-25T14:44:47+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2021-12-17T13:51:41+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"6b6465a0-ebb2-4103-bc45-8dda3a59a2fa","owner":[],"postedDate":"January 27th, 2022","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2022-05-18T06:44:17+00:00","versionOfRecord":[],"versionCreatedAt":"2022-01-27 21:34:38","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-1181147","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-1181147","identity":"rs-1181147","version":["v1"]},"buildId":"rHA-KDH7Qsr4HCuvH75dn","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}