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


 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.


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 de nitive 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][3][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 uid 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 ndings 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.

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 rst 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

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. 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 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 rst 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.

Methods
This was a retrospective cohort study conducted using National Health Insurance Service (NHIS) claims data, which were collected from January 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 identi ed using International Classi cation 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 de ned as ≥2 systolic blood pressure measurements ≥140 mmHg and/or a diastolic blood pressure ≥90 mmHg, which was observed for the rst time in antenatal care. Proteinuria was de ned 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 strati ed 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 de ned 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 de nition 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 de ned as more than three episodes of high-intensity workouts per week or more than ve 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 classi ed the participants' areas of residence into southern or central regions. Regarding URI during pregnancy, the following ICD-10 codes were used to de ne/identify URI: R05, cough; R04, hemorrhage from respiratory passage; A37, whooping cough; J00-J06, acute upper respiratory infection; J10, in uenza due to other identi ed in uenza virus; and B34, viral infection of unspeci ed site.

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 identi ed 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 Figure 1 Flowchart of the study Figure 2