The Association between Season and Hypertensive Disorders of Pregnancy: A Systematic Review and Meta-Analysis

The Association between Season and Hypertensive Disorders of Pregnancy: A Systematic Review and Meta-Analysis | 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 Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The Association between Season and Hypertensive Disorders of Pregnancy: A Systematic Review and Meta-Analysis Lingyun Liao, Xiaohong Wei, Min Liu, Yijie Gao, Yangxue Yin, Rong Zhou This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-1020061/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: There is increasing and inconsistent evidence of a relationship between hypertensive disorders of pregnancy (HDP) and season of delivery or conception. Methods: Four databases, the Cochrane Library, PubMed, EMBASE and Web of Science, were searched until September 29th, 2021. Two authors extracted data independently. A random effects model and the Mantel-Haenszel method were used to calculate pooled ORs and 95% CIs. Results: Twenty articles were included in the systematic review, and 11 articles were included in the meta-analysis. The quantitative analysis of the association between delivery season and HDP showed that the odds of HDP was higher in women who deliver in winter than in those who delivered in summer (OR=1.18, 95% CI 1.02-1.38, p < 0.001) and all other seasons (OR = 1.17, 95% CI 1.03-1.34, p <0.001). In the qualitative analysis of the association between conception season and HDP, 4 of 7 studies suggested that women who conceived in summer had a higher risk of HDP than those who conceived in other seasons. Conclusions: Based on the evidence to date, we found weakly positive relationships between HDP and summer conception and winter delivery. Maternal & Fetal Medicine Sexual & Reproductive Medicine Delivery season Conception season Hypertensive Disorders of Pregnancy Preeclampsia Meta-analysis Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Background Hypertensive disorders of pregnancy (HDP) is a common obstetric disease, occurring in 5%-10% of all pregnancies and accounting for 10%-16% of total pregnancy-related deaths; it is the leading cause of maternal death ( 1 , 2 ). HDP not only has short-term impacts during pregnancy but also long-term impacts on the health of mothers and their offspring, potentially causing maternal coronary heart disease, stroke and hypertension in offspring ( 3 – 5 ). At present, the precise etiology of HDP is unclear and is considered to be the result of the interaction between genes and the environment. However, a number of risk factors have been demonstrated, such as older age, low maternal educational status and multiple pregnancies ( 6 , 7 ). Seasonal changes affect the occurrence and development of many diseases, such as cardiovascular diseases and autoimmune diseases ( 8 , 9 ). Similarly, seasonal changes also increased the risk of maternal and neonatal mortality and the incidence of delivery complications ( 10 ). HDP deserves our attention because some studies have reported that HDP is associated with season, but the findings have been inconsistent. Some researchers reported that the prevalence rates of gestational hypertension and preeclampsia were higher in women who delivered in winter and conceived in summer ( 7 , 11 ). However, some studies found no association with season ( 6 ) or found an opposite result ( 12 ). It is important to synthesize such findings to determine which season or month of delivery or conception is related to HDP to facilitate HDP management and interventions targeting high-risk groups. Methods The Meta-Analysis of Observational Studies in Epidemiology (MOOSE) (13) and Preferred Reporting Items for Systematic review and Meta-Analyses (PRISMA) (14) guidelines were followed for this systematic review and meta-analysis. This study did not require ethical approval or patient consent. Search strategy Four databases, the Cochrane Library, PubMed, EMBASE and Web of Science, were searched until September 29th, 2021 by two independent authors (LL and XW). Medical Subject Headings (MeSH) terms combined with free text were used to identify studies on associations between seasons and HDP. The detailed search terms of PubMed can be found in Table 1 and appropriate adjustments were made in other databases. Furthermore, we manually searched the citations of the included articles to prevent omission. After retrieval, we used the Endnote X9 library (Clarivate Analytics, Philadelphia, PA, USA) to check for duplicates and manage references. Table 1 Search strategy for PubMed. Outcome: Hypertensive Disorders of Pregnancy #1 MeSH terms "hypertension, pregnancy induced"[MeSH Terms] OR "pre eclampsia"[MeSH Terms] OR "Eclampsia"[MeSH Terms] #2 Title/Abstract "hypertension pregnancy induced" OR "pregnancy induced hypertension" OR "gestational hypertension" OR "hypertension gestational" OR "transient hypertension pregnancy" OR "pregnancy transient hypertension" OR "pregnancy hypertension" OR "hypertension in pregnancy" OR "pre eclampsia" OR "Preeclampsia" OR "pregnancy toxemias" OR "pregnancy toxemia" OR "edema proteinuria hypertension gestosis" #3 #1 OR #2 Exposure: season #4 MeSH terms "seasons"[MeSH Terms] OR "climate"[MeSH Terms] OR "meteorology"[MeSH Terms] OR "weather"[MeSH Terms] OR "temperature"[MeSH Terms] #5 Title/Abstract "season*" OR "summer" OR "spring" OR "autumn" OR "winter" OR "climat*" OR "meteorology*" OR "weather*" OR "temperatur*" OR "Cold" OR "frigidity" OR "Hot" OR "Heat" #6 #4 OR #5 #7 #3 AND #6 Selection criteria Inclusion criteria 1) The exposure of interest was season or month. 2) The investigation outcome was HDP. 3) The study design was a case-control, cohort or cross-sectional design. 4) Odds ratios (ORs) and 95% confidence intervals (95% CIs) or relevant data that could be computed were provided Exclusion criteria 1) Studies on season or month of admission. 2) Studies for which the full text could not be downloaded. 3) Studies that were not published in English. Data extraction and quality assessment We designed a data extraction table during the full-text review stage. Two authors (LL and XW) extracted the data independently. The information recorded included first author, published year, study region, research type, sample size, study period, exposure definition, and outcome definition. We also recorded adjusted ORs and 95% CIs or crude ORs and 95% CIs from the original data if provided. If necessary, authors were contacted for additional details or figure data. Based on the UK’s official weather service definition, March is regarded as the beginning of spring, and spring, summer, autumn and winter are defined in three-months increments (15). When the study country or region was in the Southern Hemisphere, we adjusted the seasons accordingly. We used Google maps to estimate the average latitudes of countries and regions (16). If a disagreement arose, we consulted a third author (RZ) or discussed until consensus was reached. Only studies that had sufficient data for calculation were included in the meta-analysis. Study quality was evaluated by two author (LL and XW) with the Newcastle-Ottawa quality assessment scale (NOS) (17), which includes three categories and eight items, with a total score of nine. A NOS score of seven or higher indicated high quality. Statistical analysis Stata/SE 15.1 (StataCorp, College Station, TX, USA) was used for the quantitative analysis. In studying the relationship between season of delivery and preeclampsia, summer was chosen as the reference month because most previous studies suggested that the prevalence associated with summer delivery was low (7, 18-21). Similarly, winter was chosen as the reference season in the analysis of conception season (22-26). A random effects model and the Mantel-Haenszel method were used to calculated pooled ORs and 95% CIs. ORs were displayed using a forest plot. Heterogeneity was estimated by the Cochrane Q statistic ( p < 0.1 indicates the existence of heterogeneity) and inconsistency index (I 2 ) (low: 25-50%; moderate: 50-75%; high: 75-100%). To explore the source of heterogeneity, subgroup analyses and sensitivity analyses were performed. Subgroup analyses were performed according to sample size, latitude, income group and whether multiple pregnancies were included. In addition, we used a stepwise elimination method to perform the sensitivity analysis and verify the robustness of the results. Begg’s funnel plot and Egger’s test were used to check for the risk of publication bias. Results Study selection Figure 1 shows the literature selection process in detail. A total of 2759 studies were retrieved for further screening based on the established selection criteria. After removing duplicates, the titles and abstracts of 2140 studies were screened, and 2007 unqualified studies were excluded. Finally, we screened the full texts of the remaining and excluded 113 unqualified studies. Consequently, 20 studies were included in the systematic review ( 6 , 7 , 11 , 12 , 18 – 33 ), and 11 studies with sufficient quantitative data were included in the meta-analysis ( 6 , 7 , 18 – 21 , 27 – 31 ). Study characteristics and quality assessment Table 2 shows the detailed descriptions and quality assessments of all the studies included in the review. Studies were carried out in 7 countries, all from the Northern Hemisphere, with different latitudes. All disease-related data was extracted from medical records. Fourteen studies reported the relationship between delivery season or month and HDP ( 6 , 7 , 11 , 18 – 21 , 26 – 32 ), while seven studies reported the relationship between conception season or month and HDP ( 12 , 22 – 26 , 33 ). The outcome definition was not completely uniform. Some studies focused on comprehensive HDP, while other studies focused on only severe preeclampsia. Using the quality assessment guidelines ( 17 ), seventeen studies were considered to be high quality (score of 7 or more). Three articles scored six points because they lacked ample control of confounding factors, such as singleton pregnancy or maternal-related disease history. Table 2 Characteristics of the included studies. Author Publication year Study region Study design Period Total/case (n) Exposure definition Outcome definition Latitude Income group NOS Rohr Thomsen et al. 2020 Denmark cohort 1989-2010 50665/4285 Month of conception HDP Middle High 8 Farzaneh et al. 2019 Sistan and Baluchestan, Iran nested case-control 2017 540/270 Season of delivery Preeclampsia Low Middle 7 Shayan et al. 2019 Hamadan, Iran case-control 2005-2015 1458/729 Season of conception Preeclampsia Middle Middle 6 Weinberg et al. 2017 Norway cohort 1999-2009 356662/13959 Month of conception Preeclampsia and eclampsia High High 8 Li et al. 2016 Hunan, China cohort 2010-2011 6223/449 Season of delivery Preeclampsia Middle Middle 7 Ali et al. 2015 Sudan case-control 2008-2010 306/153 Month of delivery HDP Low Low 7 Tran et al. 2015 Paris, France cohort 2008-2011 63633/526 Season of conception Severe preeclampsia Middle High 8 Morikawa et al. 2014 Japan cohort 2005-2009 301501/13848 Month of delivery HDP Middle High 8 Luo et al. 2013 Sichuan, China case-control 2007-2010 1300/650 Season of delivery Preeclampsia Middle Middle 7 Wellington et al. 2012 Texas, USA cohort 2001 31207/12481 Season of delivery Preeclampsia and eclampsia Middle High 7 Rylander et al. 2011 Sweden cohort 1990-1994 482659/182 Season of delivery Eclampsia High High 8 Bullock et al. 2011 Oklahoma, USA cohort 2005-2007 3050/176 Month of delivery Preeclampsia Middle High 6 Tam et al. 2008 Hong Kong, China cohort 1995-2002 15402/245 Season of conception Preeclampsia and eclampsia Low Middle 8 Soroori et al. 2007 Gilan, Iran cross-sectional 1999-2001 12142/397 Season of delivery Preeclampsia Middle Middle 7 Rudra et al. 2005 Washington, USA cross-sectional 1987-2001 83228/6680 Month of conception Preeclampsia Middle High 7 Phillips et al. 2004 Vermont, USA case-control 1995-2003 7904/142 Season of conception and delivery Preeclampsia Middle High 7 Magnus et al. 2001 Norway cohort 1967-1998 1869388/51801 Month of delivery Preeclampsia High High 7 Makhseed et al. 1999 Kuwait case-control 1992-1994 26805/692 Month of delivery Preeclampsia Low High 6 Ros et al. 1998 Sweden cohort 1987-1993 10193/557 Season of delivery Eclampsia High High 8 Jamelle et al. 1998 Pakistan case-control 1996 18878/395 Month of delivery Eclampsia Low Middle 6 Season of delivery and HDP Fourteen articles assessed the relationship between delivery season and HDP ( 6 , 7 , 11 , 18 – 21 , 26 – 32 ), and eleven articles with sufficient data were included in the meta-analysis ( 6 , 7 , 18 – 21 , 27 – 31 ). Because the heterogeneity between studies was high ( p 25%), we used a random effects model to pool the ORs and 95% CIs. With summer delivery as the reference, a significant association between HDP and winter delivery (OR = 1.18, 95% CI 1.02-1.38, p < 0.001) was found, but there was no association with spring delivery (OR = 1.09, 95% CI 0.97-1.22, p = 0.066) or fall delivery (OR = 1.01, 95% CI 0.92-1.11, p =0.189) (Figure 2 ). Subgroup analyses were carried out according to latitude, income group, sample size, and whether multiple pregnancies were excluded in the studies. The results of the associations of HDP with winter delivery and summer delivery were as follows. In the latitude subgroup analysis (Figure 3 ), the heterogeneity decreased slightly (high latitude: I 2 = 42.6%, p =0.187; middle latitude: I 2 = 67.2%, p =0.016; low latitude: I 2 = 0.0%, p = 0.931), and a stronger association was observed in high-latitude countries (OR = 1.62, 95% CI 1.20-2.20) and middle-latitude countries (OR = 1.24, 95% CI 1.00-1.55). However, at low latitudes, the result was nonsignificant (OR = 0.90, 95% CI 0.76-1.05). When stratified by income group and excluding studies with a sample size <10,000, the heterogeneity did not change considerably, and the correlation between HDP and winter delivery remained positive. In 2 studies excluding women with multiple pregnancies, the studies by Li (OR = 1.56, 95% CI 0.91-2.69) and Rylander (OR = 1.99, 95% CI 1.33-2.98) still showed significant associations between HDP and winter delivery ( 7 , 21 ). The results of the subgroup analyses for spring and fall delivery versus summer delivery were nonsignificant. The sensitivity analysis suggested that no single study altered the association (Figure 4 ). In the publication bias test, three Begg’s funnel plots were symmetric, and Egger’s test was nonpositive (winter p = 0.175; spring p = 0.454; fall p = 0.623) (Figure 5 ). Based on the above results, we further compared winter delivery with delivery in other seasons. The result yielded a statistically significant result (OR = 1.17, 95% CI 1.03-1.34, I 2 = 75.4%, p <0.001) (Figure 6 ). Subgroup analysis did not significantly reduce the interstudy heterogeneity. The results of the sensitivity analysis were stable. Symmetrical Begg’s funnel plots and Egger’s test ( p = 0.155) showed that there was no publication bias. Two of the remaining three studies that were not included in the quantitative analysis revealed that the risk of HDP was highest when women delivered in the winter months ( 11 , 32 ), which was consistent with our quantitative analysis. Morikawa reported that the relative risks of pregnancy-induced hypertension were 1.12 (95% CI 1.06–1.19) for delivery in January–February and 1.16 (95% CI 1.09–1.22) for delivery in March–April compared with delivery in July– August ( 11 ). Magnus reported that delivery in August was associated with the lowest risk of preeclampsia, while the risk was highest in the winter months (for December, adjusted OR = 1.26, 95% CI 1.20–1.31) ( 32 ). However, Phillips found that there were no significant differences in the rates of preeclampsia in women with winter and spring deliveries, but women with summer deliveries (OR = 0.63, 95% CI 0.39– 0.99 vs. spring) and fall deliveries (OR = 0.60, 95% CI 0.37–0.98 vs. spring) had reduced odds of developing preeclampsia ( 26 ). Season of conception and HDP Seven studies assessed the relationship between conception season or month and HDP. Four studies supported that conception in summer increased the risk of developing HDP ( 22 , 24 – 26 ). Rohr Thomsen showed that women who conceived in August (OR = 1.35, 95% CI 1.11-1.64) had the highest risk of gestational hypertension, and those who conceived in June (OR = 1.17, 95% CI 0.94-1.45) had the highest risk of preeclampsia, which occurred in both the summer months ( 22 ). Tran found that conception in summer was associated with the highest risk of severe preeclampsia (OR = 1.53, 95% CI 1.27-1.85, vs. winter) ( 24 ). Tam (OR = 1.7, 95% CI 1.2–2.5, vs. autumn) and Phillips (OR = 1.7, 95% CI 1.1-2.8 vs. spring) revealed that conception in summer was associated with an increased risk of preeclampsia ( 25 , 26 ). However, the results of 3 studies were not consistent with the above conclusion. Rudra reported that conception in February (OR = 1.17, 95% CI 1.03-1.33 vs. January) and April (OR = 1.18, 95% CI 1.03-1.34 vs. January) through August (OR = 1.14, 95% CI 1.01-1.30 vs. January) were associated with significantly higher risks of preeclampsia ( 33 ). However, Shayan found that conception in autumn increased the odds of preeclampsia (OR = 1.13, 95% CI 0.73-1.76, vs. winter) and that conception in summer was associated with the lowest odds of preeclampsia (OR = 0.26, 95% CI 0.17-0.38, vs. winter) ( 12 ). Weinberg revealed that women who conceived in spring had a higher risk of HDP, while those that conceived in autumn had a lower risk ( 23 ). Discussion Main findings This systematic review of 20 studies and meta-analysis of 11 studies explored the relationship between season and the development of hypertensive pregnancy disorders. The results showed increased odds of HDP in women who delivered in winter compared with those who delivered in summer (OR = 1.18, 95% CI 1.02-1.38, p < 0.001) and other seasons (OR = 1.17, 95% CI 1.03-1.34, p < 0.001). Furthermore, in the analysis of the relationships between HDP and seasons or months of conception, 4 of 7 studies reported that women who conceived in summer had a higher risk of HDP. Some studies have suggested that HDP may be more strongly associated with conception time than with delivery time (26, 34). Although the stages of pregnancy in the included studies were different, we combined them by gestation period. For example, in the studies on delivery and conception months, women who conceived in hot months generally delivered in cold months in the following year (11, 18, 22, 27, 32). Women who conceived in June and delivered in March had the highest risk of preeclampsia (22). The differences in these study results studies were possibly associated with premature delivery in women with HDP and the miscalculation of conception time. First, many studies have reported that women with HDP are prone to premature delivery (35-37), and low-dose aspirin could decrease the incidence of preterm birth, particularly if initiated before 16 weeks of gestation (36). Therefore, this could help explain the high incidence of HDP in women who conceived in summer and delivered in winter. Second, a lack of ultrasound examination to determine the date of conception or the presence of menstrual disorders may cause inaccurate estimates of the date of conception, resulting in less accurate conclusions about the relationship between HDP and month of conception (25, 33). Based on our analysis, it was not possible to explain how season factors could affect the onset of HDP. According to basic research and epidemiological investigations, a number of possible mechanisms influenced by factors such as nutritional status, sunlight exposure, temperature, humidity, and infection, may explain the correlation. Here, we discuss some relevant factors. Among the different seasons, there is wide variation in the nutrients consumed by people, resulting in different risks of pregnancy-related diseases (38). Lowensohn reported that calcium supplementation may reduce the risk of HDP, especially in low-calcium populations (38). In addition, Mirzakhani reported that vitamin D levels above 30 ng/ml at the start of the trial and in late pregnancy were associated with a lower risk of preeclampsia (39). Vitamin D levels are not only affected by seasonal variations in nutrient intake but are also closely related to sunlight exposure. Vitamin D is produced naturally in the skin when skin is exposed to sunlight, which varies greatly among seasons (18, 21, 22). In a recent study by Horton-French, young adults had a 3 times higher risk of vitamin D deficiency in the winter than in the summer, which was consistent with our findings of a higher risk in women who delivered in winter (40). Additionally, variations in temperature and humidity have also been hypothesized. Xiong reported that in the early stages of pregnancy, cold temperatures reduced the risk, whereas hot temperatures increased the risk (34). Moreover, the incidence of preeclampsia was significantly higher during the dry season than during the rainy season (41, 42). As a possible explanation, Krininger reported that heat shock was found to compromise embryo implantation in an animal model (43). Water loss resulting in reduced plasma volume in warm months may increase the risk of developing preeclampsia (44), which may indirectly explain the increased risk of HDP in women who conceive in summer. Exposure to cold temperatures could lead to vasospasms and subsequent ischemia (45), which is a possible reason for the increased risk of HDP in winter (20). All of these factors that affect cardiovascular conditions may together increase blood pressure, promoting the formation of HDP. Finally, seasonal fluctuations in infection rates may result in variability in the seasonal occurrence of preeclampsia (46), which could cause a maternal systemic inflammatory response. In this meta-analysis of studies on delivery season and conception season, the heterogeneity was high, possibly due to confounding factors such as sample size, latitude, income group, study design, and definitions of outcomes. To solve this problem, we performed subgroup analyses to find the source of the heterogeneity. The heterogeneity slightly decreased in only the latitude subgroup analysis. Although we failed to find the major source of heterogeneity, our sensitivity analysis indicated that our results were valid. In addition, because reference seasons or months were different and some original data could not be obtained, we failed to carry out a meta-analysis of studies on conception season and HDP. Therefore, more studies need to be analyzed to minimize heterogeneity and explore the relationship between conception season and HDP to obtain more accurate correlation results. In summary, additional large-scale multicenter studies analyzing specific seasonal factors, such as temperature, humidity and pollution, are needed to thoroughly study the relationship between season or month and HDP. Furthermore, the identification of risk factors for the onset of HDP is important because it could greatly improve pregnancy and fetal outcomes. Strengths and limitations Accurate and robust statistical results were reported in this meta-analysis on the positive association between season and HDP. In addition, this is the first quantitative analysis of this topic. However, this study has some limitations. First, we found heterogeneity in our meta-analysis. Many factors beyond our control, such as sample size, latitude, income group, study design, and definitions of outcomes, could all affect the degree of heterogeneity. Thus, additional high-quality studies are needed to reduce heterogeneity in the future. Second, in the study of the relationship between conception season and HDP, the reference season or month differed, and original data were not reported. This caused difficulty in performing a meta-analysis, resulting in insufficient reliability of the results. Third, we excluded non-English articles, which led to the exclusion of studies not published in English, potentially influencing the representativeness of our results. Conclusion Based on the evidence to date, we found weakly positive relationships between HDP and summer conception and winter delivery. Additional large-scale multicenter studies analyzing detailed seasonal factors, such as temperature, humidity and pollution, are needed to thoroughly study the relationship between season or month and HPD. Abbreviations HDP : Hypertensive disorders of pregnancy MOOSE : The Meta-Analysis of Observational Studies in Epidemiology PRISMA : Preferred Reporting Items for Systematic review and Meta-Analyses MeSH : Medical Subject Headings ORs :Odds ratios 95% CIs: 95% confidence intervals NOS : the Newcastle-Ottawa quality assessment scale Declarations Availability of data and materials Data will be available from the corresponding author upon reasonable request. Acknowledgements Not applicable. Funding This work was supported by the National Natural Science Foundation of China (No. 81571465 and 81871175) and the Key Projects of Sichuan Science and Technology Department (No. 2021YFS0208). Author information Affiliations Department of Obstetrics and Gynecology, West China Second University Hospital, Sichuan University, Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University) of Ministry of Education, Chengdu, Sichuan, China Lingyun Liao, Xiaohong Wei, Min Liu, Yijie Gao, Yangxue Yin & Rong Zhou Contributions LL and XW performed experiments and analyzed the results. LL conceived the study and prepared the manuscript. ML modified the figure. YG, YY and RZ supervised the study. All authors contributed to the article and approved the submitted version. Corresponding author Rong Zhou Ethics declarations Ethics approval and consent to participate Not applicable. Consent for publication Not applicable. Competing interests The authors declare that they have no competing interests. References Hypertension in pregnancy. Report of the American College of Obstetricians and Gynecologists’ Task Force on Hypertension in Pregnancy. Obstet Gynecol. 2013;122(5):1122–31. Umesawa M, Kobashi G. Epidemiology of hypertensive disorders in pregnancy: prevalence, risk factors, predictors and prognosis. Hypertens Res. 2017;40(3):213–20. Malek AM, Wilson DA, Turan TN, Mateus J, Lackland DT, Hunt KJ. Maternal Coronary Heart Disease, Stroke, and Mortality Within 1, 3, and 5 Years of Delivery Among Women With Hypertensive Disorders of Pregnancy and Pre-Pregnancy Hypertension. J Am Heart Assoc. 2021:e018155. Countouris ME, Villanueva FS, Berlacher KL, Cavalcante JL, Parks WT, Catov JM. Association of Hypertensive Disorders of Pregnancy With Left Ventricular Remodeling Later in Life. J Am Coll Cardiol. 2021;77(8):1057–68. Kurbasic A, Fraser A, Mogren I, Hallmans G, Franks PW, Rich-Edwards JW, et al. Maternal Hypertensive Disorders of Pregnancy and Offspring Risk of Hypertension: A Population-Based Cohort and Sibling Study. Am J Hypertens. 2019;32(4):331–4. Farzaneh F, Tavakolikia Z, Soleimanzadeh Mousavi SH. Assessment of occurrence of preeclampsia and some clinical and demographic risk factors in Zahedan city in 2017. Clin Exp Hypertens. 2019;41(6):583–8. Li X, Tan H, Huang X, Zhou S, Hu S, Wang X, et al. Similarities and differences between the risk factors for gestational hypertension and preeclampsia: A population based cohort study in south China. Pregnancy Hypertens. 2016;6(1):66–71. Watad A, Azrielant S, Bragazzi NL, Sharif K, David P, Katz I, et al. Seasonality and autoimmune diseases: The contribution of the four seasons to the mosaic of autoimmunity. J Autoimmun. 2017;82:13–30. Stewart S, Keates AK, Redfern A, McMurray JJV. Seasonal variations in cardiovascular disease. Nat Rev Cardiol. 2017;14(11):654–64. Rylander C, Odland J, Sandanger TM. Climate change and the potential effects on maternal and pregnancy outcomes: an assessment of the most vulnerable--the mother, fetus, and newborn child. Glob Health Action. 2013;6:19538. Morikawa M, Yamada T, Yamada T, Cho K, Sato S, Minakami H. Seasonal variation in the prevalence of pregnancy-induced hypertension in Japanese women. J Obstet Gynaecol Res. 2014;40(4):926–31. Shayan A, Sourinejad H, Refaei M, Masoumi SZ, Tapak L, Soltani F. Predictors of Preeclampsia Based on a 10-Year Case-Control Study. J Family Reprod Health. 2019;13(1):14–20. Stroup DF, Berlin JA, Morton SC, Olkin I, Williamson GD, Rennie D, et al. Meta-analysis of observational studies in epidemiology: a proposal for reporting. Meta-analysis Of Observational Studies in Epidemiology (MOOSE) group. Jama. 2000;283(15):2008–12. Moher D, Shamseer L, Clarke M, Ghersi D, Liberati A, Petticrew M, et al. Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015 statement. Syst Rev. 2015;4(1):1. Met Office. https://www.metoffice.gov.uk/weather/learn-about/weather/seasons/spring/when-does-spring-start . Accessed 9 Sep 2021. Google map. https://www.maps.google.com . Accessed 9 Sep 2021. Stang A. Critical evaluation of the Newcastle-Ottawa scale for the assessment of the quality of nonrandomized studies in meta-analyses. Eur J Epidemiol. 2010;25(9):603–5. Ali AA, Adam GK, Abdallah TM. Seasonal variation and hypertensive disorders of pregnancy in eastern Sudan. J Obstet Gynaecol. 2015;35(2):153–4. Luo B, Ma X. Risk factors for preeclampsia: a case-control study. Hypertens Pregnancy. 2013;32(4):432–8. Wellington K, Mulla ZD. Seasonal trend in the occurrence of preeclampsia and eclampsia in Texas. Am J Hypertens. 2012;25(1):115–9. Rylander A, Lindqvist PG. Eclampsia is more prevalent during the winter season in Sweden. Acta Obstet Gynecol Scand. 2011;90(1):114–7. Rohr Thomsen C, Brink Henriksen T, Uldbjerg N, Milidou I. Seasonal variation in the hypertensive disorders of pregnancy in Denmark. Acta Obstet Gynecol Scand. 2020;99(5):623–30. Weinberg CR, Shi M, Basso O, DeRoo LA, Harmon Q, Wilcox AJ, et al. Season of Conception, Smoking, and Preeclampsia in Norway. Environ Health Perspect. 2017;125(6):067022. Tran TC, Boumendil A, Bussieres L, Lebreton E, Ropers J, Rozenberg P, et al. Are Meteorological Conditions within the First Trimester of Pregnancy Associated with the Risk of Severe Pre-Eclampsia? Paediatr Perinat Epidemiol. 2015;29(4):261–70. Tam WH, Sahota DS, Lau TK, Li CY, Fung TY. Seasonal variation in pre-eclamptic rate and its association with the ambient temperature and humidity in early pregnancy. Gynecol Obstet Invest. 2008;66(1):22–6. Phillips JK, Bernstein IM, Mongeon JA, Badger GJ. Seasonal variation in preeclampsia based on timing of conception. Obstet Gynecol. 2004;104(5 Pt 1):1015–20. Bullock N, Breese McCoy SJ, Payton ME. Role of race in the seasonality of deliveries with preeclampsia. Med Hypotheses. 2011;77(4):674–6. Soroori ZZ, Sharami SH, Faraji R. Seasonal variation of the onset of preeclampsia and eclampsia. J Res Med Sci. 2007;12(4):198–202. Makhseed M, Musini VM, Ahmed HA, Abdul Monem R. Influence of seasonal variation on pregnancy-induced hypertension and or preeclampsia. #N/A. 1999;39(2):196–9. Ros HS, Cnattingius S, Lipworth L. Comparison of risk factors for preeclampsia and gestational hypertension in a population-based cohort study. Am J Epidemiol. 1998;147(11):1062–70. Jamelle RN. Eclampsia: is there a seasonal variation in incidence? J Obstet Gynaecol Res. 1998;24(2):121–8. Magnus P, Eskild A. Seasonal variation in the occurrence of pre-eclampsia. Bjog. 2001;108(11):1116–9. Rudra CB, Williams MA. Monthly variation in preeclampsia prevalence: Washington State, 1987-2001. J Matern Fetal Neonatal Med. 2005;18(5):319–24. Xiong T, Chen P, Mu Y, Li X, Di B, Li J, et al. Association between ambient temperature and hypertensive disorders in pregnancy in China. Nat Commun. 2020;11(1):2925. Goldenberg RL, Culhane JF, Iams JD, Romero R. Epidemiology and causes of preterm birth. Lancet. 2008;371(9606):75–84. Hoffman MK, Goudar SS, Kodkany BS, Metgud M, Somannavar M, Okitawutshu J, et al. Low-dose aspirin for the prevention of preterm delivery in nulliparous women with a singleton pregnancy (ASPIRIN): a randomised, double-blind, placebo-controlled trial. Lancet. 2020;395(10220):285–93. Shulman JP, Weng C, Wilkes J, Greene T, Hartnett ME. Association of Maternal Preeclampsia With Infant Risk of Premature Birth and Retinopathy of Prematurity. JAMA Ophthalmol. 2017;135(9):947–53. Lowensohn RI, Stadler DD, Naze C. Current Concepts of Maternal Nutrition. #N/A. 2016;71(7):413–26. Mirzakhani H, Litonjua AA, McElrath TF, O'Connor G, Lee-Parritz A, Iverson R, et al. Early pregnancy vitamin D status and risk of preeclampsia. J Clin Invest. 2016;126(12):4702–15. Horton-French K, Dunlop E, Lucas RM, Pereira G, Black LJ. Prevalence and predictors of vitamin D deficiency in a nationally representative sample of Australian adolescents and young adults. Eur J Clin Nutr. 2021:1–10. Elongi JP, Tandu B, Spitz B, Verdonck F. [Influence of the seasonal variation on the prevalence of pre-eclampsia in Kinshasa]. Gynecol Obstet Fertil. 2011;39(3):132–5. Wacker J, Schulz M, Frühauf J, Chiwora FM, Solomayer E, Bastert G. Seasonal change in the incidence of preeclampsia in Zimbabwe. Acta Obstet Gynecol Scand. 1998;77(7):712–6. Krininger CE, 3rd, Stephens SH, Hansen PJ. Developmental changes in inhibitory effects of arsenic and heat shock on growth of pre-implantation bovine embryos. Mol Reprod Dev. 2002;63(3):335–40. Aardenburg R, Spaanderman ME, Ekhart TH, van Eijndhoven HW, van der Heijden OW, Peeters LL. Low plasma volume following pregnancy complicated by pre-eclampsia predisposes for hypertensive disease in a next pregnancy. Bjog. 2003;110(11):1001–6. Alba BK, Castellani JW, Charkoudian N. Cold-induced cutaneous vasoconstriction in humans: Function, dysfunction and the distinctly counterproductive. Exp Physiol. 2019;104(8):1202–14. Sibai B, Dekker G, Kupferminc M. Pre-eclampsia. Lancet. 2005;365(9461):785–99. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies 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-1020061","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":59945135,"identity":"a6b29b59-3f9a-4a61-b818-cedba3bb5695","order_by":0,"name":"Lingyun Liao","email":"","orcid":"","institution":"Department of Obstetrics and Gynecology, West China Second University Hospital, Sichuan University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Lingyun","middleName":"","lastName":"Liao","suffix":""},{"id":59945136,"identity":"5114627a-adda-44ab-8ab8-551164f951dd","order_by":1,"name":"Xiaohong Wei","email":"","orcid":"","institution":"Department of Obstetrics and Gynecology, West China Second University Hospital, Sichuan University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Xiaohong","middleName":"","lastName":"Wei","suffix":""},{"id":59945137,"identity":"5c641f3f-540a-4aa7-975b-586a44f5b35c","order_by":2,"name":"Min Liu","email":"","orcid":"","institution":"Department of Obstetrics and Gynecology, West China Second University Hospital, Sichuan University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Min","middleName":"","lastName":"Liu","suffix":""},{"id":59945138,"identity":"48d4363d-cd0b-45b7-afd6-8f05544e87ff","order_by":3,"name":"Yijie Gao","email":"","orcid":"","institution":"Department of Obstetrics and Gynecology, West China Second University Hospital, Sichuan University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Yijie","middleName":"","lastName":"Gao","suffix":""},{"id":59945139,"identity":"10576580-42c4-430c-bb61-63030b18aced","order_by":4,"name":"Yangxue Yin","email":"","orcid":"","institution":"Department of Obstetrics and Gynecology, West China Second University Hospital, Sichuan University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Yangxue","middleName":"","lastName":"Yin","suffix":""},{"id":59945140,"identity":"ba62ecf6-bce5-4747-97cf-6a4a5a87e5cd","order_by":5,"name":"Rong Zhou","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA4ElEQVRIiWNgGAWjYDACCQSD8QGElUC8FmYDkrWwSRClRX528zHpioo7dg3SPWaVP2oOM/Cz5xgw/NyBWwvjnGNpkmfOPEtukDmWdpvn2GEGyZ43Boy9Z3BrYZbIMZNsbDuczCCRfOw2Y8NhBoMbOQbMjG24tbAhtCS2Ff4EarEnpIUHqsUOZAsDL8gWCQJaJCTSki0bzhxOYAAypHmOpfNInHlWcLAXjxb5GckHbzZUHLZnkMgx/PijxlqOvz1544OfeLTAQOL+A1CXgogDhDUwMNgTo2gUjIJRMApGKAAA4QJK/FVgRG0AAAAASUVORK5CYII=","orcid":"","institution":"Department of Obstetrics and Gynecology, West China Second University Hospital, Sichuan University","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Rong","middleName":"","lastName":"Zhou","suffix":""}],"badges":[],"createdAt":"2021-10-26 11:44:11","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-1020061/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-1020061/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":15100741,"identity":"1eda12a6-f983-4832-9347-c0f641d53d48","added_by":"auto","created_at":"2021-11-01 16:42:49","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":87910,"visible":true,"origin":"","legend":"PRISMA flow diagram of study process.","description":"","filename":"OnlineFigure1.png","url":"https://assets-eu.researchsquare.com/files/rs-1020061/v1/cbe2fd872fcdde53a6f6d323.png"},{"id":15101198,"identity":"2917bf35-8146-4a0b-bfed-667b5686eabc","added_by":"auto","created_at":"2021-11-01 16:48:49","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":820787,"visible":true,"origin":"","legend":"The forest plots show the association between HDP and delivery season. Spring (A), Autumn (B), Winter (C) compared with summer as reference.","description":"","filename":"OnlineFigure2.png","url":"https://assets-eu.researchsquare.com/files/rs-1020061/v1/f98fef5c28b6c705a25ea8f5.png"},{"id":15100743,"identity":"2d25c54e-907e-4fb6-805c-1e2e1834de81","added_by":"auto","created_at":"2021-11-01 16:42:49","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":102489,"visible":true,"origin":"","legend":"Forest plot of subgroup analysis of HDP and winter delivery compared with summer on latitude.","description":"","filename":"OnlineFigure3.png","url":"https://assets-eu.researchsquare.com/files/rs-1020061/v1/b72bca7107c4b6868d587e56.png"},{"id":15100746,"identity":"cb8c763e-9109-439f-acb7-040c18348a4d","added_by":"auto","created_at":"2021-11-01 16:42:49","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":683259,"visible":true,"origin":"","legend":"Sensitivity analysis of HDP and winter delivery compared with summer.\n\n","description":"","filename":"OnlineFigure4.png","url":"https://assets-eu.researchsquare.com/files/rs-1020061/v1/c5496783477462cc550d5e68.png"},{"id":15101005,"identity":"0388103d-91e1-4339-924c-1eab1f3815e9","added_by":"auto","created_at":"2021-11-01 16:45:49","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":38178,"visible":true,"origin":"","legend":"Begg’s funnel plot of HDP and winter delivery compared with summer.","description":"","filename":"OnlineFigure5.png","url":"https://assets-eu.researchsquare.com/files/rs-1020061/v1/c3b57e07ba2174877fb2a7d5.png"},{"id":15100737,"identity":"6d1031d0-6759-4187-9abf-dce92b560c08","added_by":"auto","created_at":"2021-11-01 16:42:49","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":66647,"visible":true,"origin":"","legend":"The forest plots show the association between HDP and delivery season: winter delivery compared with other seasons.","description":"","filename":"OnlineFigure6.png","url":"https://assets-eu.researchsquare.com/files/rs-1020061/v1/5327bd6d05472cf01468ba94.png"},{"id":19276043,"identity":"d5468dd7-41b8-4774-80a7-7e5ef08a00a3","added_by":"auto","created_at":"2022-03-16 07:59:21","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1308378,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-1020061/v1/da9c7df0-8cbd-42cb-880c-1a89fa56e912.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"The Association between Season and Hypertensive Disorders of Pregnancy: A Systematic Review and Meta-Analysis","fulltext":[{"header":"Background","content":"\u003cp\u003eHypertensive disorders of pregnancy (HDP) is a common obstetric disease, occurring in 5%-10% of all pregnancies and accounting for 10%-16% of total pregnancy-related deaths; it is the leading cause of maternal death (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). HDP not only has short-term impacts during pregnancy but also long-term impacts on the health of mothers and their offspring, potentially causing maternal coronary heart disease, stroke and hypertension in offspring (\u003cspan additionalcitationids=\"CR4\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). At present, the precise etiology of HDP is unclear and is considered to be the result of the interaction between genes and the environment. However, a number of risk factors have been demonstrated, such as older age, low maternal educational status and multiple pregnancies (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSeasonal changes affect the occurrence and development of many diseases, such as cardiovascular diseases and autoimmune diseases (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). Similarly, seasonal changes also increased the risk of maternal and neonatal mortality and the incidence of delivery complications (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). HDP deserves our attention because some studies have reported that HDP is associated with season, but the findings have been inconsistent. Some researchers reported that the prevalence rates of gestational hypertension and preeclampsia were higher in women who delivered in winter and conceived in summer (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). However, some studies found no association with season (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e) or found an opposite result (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIt is important to synthesize such findings to determine which season or month of delivery or conception is related to HDP to facilitate HDP management and interventions targeting high-risk groups.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eThe Meta-Analysis of Observational Studies in Epidemiology (MOOSE)\u0026nbsp;(13)\u0026nbsp;and Preferred Reporting Items for Systematic review and Meta-Analyses (PRISMA)\u0026nbsp;(14)\u0026nbsp;guidelines were followed for this systematic review and meta-analysis. This study did not require ethical approval or patient consent.\u003c/p\u003e\n\u003ch2\u003eSearch strategy\u003c/h2\u003e\n\u003cp\u003eFour databases, the Cochrane Library, PubMed, EMBASE and Web of Science, were searched until\u0026nbsp;September 29th, 2021\u0026nbsp;by two independent authors (LL and XW). Medical Subject Headings (MeSH) terms combined with free text were used to identify studies on associations between seasons and HDP. The detailed search terms of PubMed can be found in Table 1\u0026nbsp;and\u0026nbsp;appropriate adjustments were made in other databases. Furthermore, we manually searched the citations of the included articles to prevent omission. After retrieval, we used the Endnote X9 library (Clarivate Analytics, Philadelphia, PA, USA) to check for duplicates and manage references.\u003c/p\u003e\n\u003cp id=\"isPasted\" style=\"text-align: center;\"\u003eTable 1\u003c/p\u003e\n\u003cp style=\"text-align: center;\"\u003e\u0026nbsp;Search strategy for PubMed.\u003c/p\u003e\n\u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003eOutcome: Hypertensive Disorders of Pregnancy\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e#1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMeSH terms\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026quot;hypertension, pregnancy induced\u0026quot;[MeSH Terms] OR \u0026quot;pre eclampsia\u0026quot;[MeSH Terms] OR \u0026quot;Eclampsia\u0026quot;[MeSH Terms]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e#2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eTitle/Abstract\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026quot;hypertension pregnancy induced\u0026quot; OR \u0026quot;pregnancy induced hypertension\u0026quot; OR \u0026quot;gestational hypertension\u0026quot; OR \u0026quot;hypertension gestational\u0026quot; OR \u0026quot;transient hypertension pregnancy\u0026quot; OR \u0026quot;pregnancy transient hypertension\u0026quot; OR \u0026quot;pregnancy hypertension\u0026quot; OR \u0026quot;hypertension in pregnancy\u0026quot; OR \u0026quot;pre eclampsia\u0026quot; OR \u0026quot;Preeclampsia\u0026quot; OR \u0026quot;pregnancy toxemias\u0026quot; OR \u0026quot;pregnancy toxemia\u0026quot; OR \u0026quot;edema proteinuria hypertension gestosis\u0026quot;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e#3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e#1 OR #2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003eExposure: season\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e#4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMeSH terms\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026quot;seasons\u0026quot;[MeSH Terms] OR \u0026quot;climate\u0026quot;[MeSH Terms] OR \u0026quot;meteorology\u0026quot;[MeSH Terms] OR \u0026quot;weather\u0026quot;[MeSH Terms] OR \u0026quot;temperature\u0026quot;[MeSH Terms]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e#5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eTitle/Abstract\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026quot;season*\u0026quot; OR \u0026quot;summer\u0026quot; OR \u0026quot;spring\u0026quot; OR \u0026quot;autumn\u0026quot; OR \u0026quot;winter\u0026quot; OR \u0026quot;climat*\u0026quot; OR \u0026quot;meteorology*\u0026quot; OR \u0026quot;weather*\u0026quot; OR \u0026quot;temperatur*\u0026quot; OR \u0026quot;Cold\u0026quot; OR \u0026quot;frigidity\u0026quot; OR \u0026quot;Hot\u0026quot; OR \u0026quot;Heat\u0026quot;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e#6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e#4 OR #5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e#7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e#3 AND #6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003eSelection criteria\u003c/h2\u003e\n\u003ch3\u003eInclusion criteria\u003c/h3\u003e\n\u003cp\u003e1) The exposure of interest was season or month.\u003c/p\u003e\n\u003cp\u003e2) The investigation outcome was HDP.\u003c/p\u003e\n\u003cp\u003e3) The study design was a case-control, cohort or cross-sectional design.\u003c/p\u003e\n\u003cp\u003e4) Odds ratios (ORs) and 95% confidence intervals (95% CIs) or relevant data that could be computed were provided\u003c/p\u003e\n\u003ch3\u003eExclusion criteria\u003c/h3\u003e\n\u003cp\u003e1) Studies on season or month of admission.\u003c/p\u003e\n\u003cp\u003e2) Studies for which the full text could not be downloaded.\u003c/p\u003e\n\u003cp\u003e3) Studies that were not published in English.\u003c/p\u003e\n\u003ch2\u003eData extraction and quality assessment\u003c/h2\u003e\n\u003cp\u003eWe designed a data extraction table during the full-text review stage. Two authors (LL and XW) extracted the data independently. The information recorded\u0026nbsp;included\u0026nbsp;first author, published year, study region, research type, sample size, study period, exposure definition, and outcome definition. We also recorded adjusted ORs and 95% CIs or crude ORs and 95% CIs from the original data if provided. If necessary, authors were contacted for additional details or figure data.\u003c/p\u003e\n\u003cp\u003eBased on the UK\u0026rsquo;s official weather service definition, March is regarded as the beginning of spring, and spring, summer, autumn and winter are defined in three-months increments\u0026nbsp;(15). When the study country or region was in the Southern Hemisphere, we adjusted the seasons accordingly. We used Google maps to estimate the average latitudes of countries and regions\u0026nbsp;(16).\u003c/p\u003e\n\u003cp\u003eIf a disagreement arose, we consulted a third author (RZ) or discussed until consensus was reached. Only studies that had sufficient data for calculation were included in the meta-analysis.\u003c/p\u003e\n\u003cp\u003eStudy quality was evaluated by two author (LL and XW) with\u0026nbsp;the\u0026nbsp;Newcastle-Ottawa quality assessment scale (NOS)\u0026nbsp;(17), which includes three categories and eight items,\u0026nbsp;with a total score of nine. A NOS score of seven or higher indicated high quality.\u003c/p\u003e\n\u003ch2\u003eStatistical analysis\u003c/h2\u003e\n\u003cp\u003eStata/SE 15.1 (StataCorp, College Station, TX, USA) was used for the quantitative analysis. In studying the relationship between season of delivery and preeclampsia, summer was chosen as\u0026nbsp;the\u0026nbsp;reference month because most previous studies suggested that the prevalence associated with summer delivery was low\u0026nbsp;(7, 18-21). Similarly, winter was chosen as\u0026nbsp;the\u0026nbsp;reference season in the analysis of\u0026nbsp;conception season\u0026nbsp;(22-26).\u003c/p\u003e\n\u003cp\u003eA random effects model and the Mantel-Haenszel method were used to calculated pooled\u0026nbsp;ORs\u0026nbsp;and 95%\u0026nbsp;CIs. ORs were displayed using a forest plot. Heterogeneity was estimated by\u0026nbsp;the\u0026nbsp;Cochrane Q\u0026nbsp;statistic\u0026nbsp;(\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.1 indicates the existence of heterogeneity) and inconsistency index (I\u003csup\u003e2\u003c/sup\u003e) (low: 25-50%; moderate: 50-75%; high: 75-100%). To explore the source of heterogeneity, subgroup analyses and sensitivity analyses were performed. Subgroup analyses were performed according to sample size, latitude, income group and whether multiple pregnancies were included. In addition, we used a stepwise elimination method to perform the sensitivity analysis and verify the robustness of the results. Begg\u0026rsquo;s funnel plot and Egger\u0026rsquo;s test were used to check for the risk of publication bias.\u003c/p\u003e"},{"header":"Results","content":"\u003ch2\u003eStudy selection\u003c/h2\u003e\n\u003cp\u003eFigure \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e shows the literature selection process in detail. A total of 2759 studies were retrieved for further screening based on the established selection criteria. After removing duplicates, the titles and abstracts of 2140 studies were screened, and 2007 unqualified studies were excluded. Finally, we screened the full texts of the remaining and excluded 113 unqualified studies. Consequently, 20 studies were included in the systematic review (\u003cspan class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e33\u003c/span\u003e), and 11 studies with sufficient quantitative data were included in the meta-analysis (\u003cspan class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e27\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e31\u003c/span\u003e).\u003c/p\u003e\n\u003ch2\u003eStudy characteristics and quality assessment\u003c/h2\u003e\n\u003cp\u003eTable \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e shows the detailed descriptions and quality assessments of all the studies included in the review. Studies were carried out in 7 countries, all from the Northern Hemisphere, with different latitudes. All disease-related data was extracted from medical records. Fourteen studies reported the relationship between delivery season or month and HDP (\u003cspan class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e26\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e32\u003c/span\u003e), while seven studies reported the relationship between conception season or month and HDP (\u003cspan class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e22\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e33\u003c/span\u003e). The outcome definition was not completely uniform. Some studies focused on comprehensive HDP, while other studies focused on only severe preeclampsia. Using the quality assessment guidelines (\u003cspan class=\"CitationRef\"\u003e17\u003c/span\u003e), seventeen studies were considered to be high quality (score of 7 or more). Three articles scored six points because they lacked ample control of confounding factors, such as singleton pregnancy or maternal-related disease history.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable border=\"1\" id=\"Tab2\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eCharacteristics of the included studies.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"11\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAuthor\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePublication\u003c/p\u003e\n \u003cp\u003eyear\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eStudy region\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eStudy design\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePeriod\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eTotal/case (n)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eExposure definition\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eOutcome definition\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eLatitude\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eIncome\u003c/p\u003e\n \u003cp\u003egroup\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNOS\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRohr Thomsen et al.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2020\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDenmark\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ecohort\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1989-2010\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e50665/4285\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMonth of conception\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHDP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMiddle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFarzaneh et al.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSistan and Baluchestan, Iran\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003enested case-control\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2017\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e540/270\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSeason of delivery\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePreeclampsia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMiddle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eShayan et al.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHamadan, Iran\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ecase-control\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2005-2015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1458/729\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSeason of conception\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePreeclampsia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMiddle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMiddle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWeinberg et al.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2017\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNorway\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ecohort\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1999-2009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e356662/13959\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMonth of conception\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePreeclampsia and eclampsia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLi et al.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2016\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHunan, China\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ecohort\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2010-2011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6223/449\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSeason of delivery\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePreeclampsia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMiddle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMiddle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAli et al.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSudan\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ecase-control\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2008-2010\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e306/153\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMonth of delivery\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHDP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTran et al.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eParis, France\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ecohort\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2008-2011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e63633/526\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSeason of conception\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSevere preeclampsia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMiddle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMorikawa et al.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2014\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eJapan\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ecohort\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2005-2009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e301501/13848\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMonth of delivery\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHDP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMiddle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLuo et al.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2013\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSichuan, China\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ecase-control\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2007-2010\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1300/650\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSeason of delivery\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePreeclampsia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMiddle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMiddle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWellington et al.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2012\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTexas, USA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ecohort\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e31207/12481\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSeason of delivery\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePreeclampsia and eclampsia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMiddle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRylander et al.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSweden\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ecohort\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1990-1994\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e482659/182\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSeason of delivery\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEclampsia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBullock et al.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOklahoma, USA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ecohort\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2005-2007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3050/176\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMonth of delivery\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePreeclampsia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMiddle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTam et al.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHong Kong, China\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ecohort\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1995-2002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15402/245\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSeason of conception\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePreeclampsia and eclampsia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMiddle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSoroori et al.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGilan, Iran\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ecross-sectional\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1999-2001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12142/397\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSeason of delivery\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePreeclampsia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMiddle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMiddle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRudra et al.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWashington, USA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ecross-sectional\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1987-2001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e83228/6680\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMonth of conception\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePreeclampsia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMiddle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePhillips et al.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eVermont, USA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ecase-control\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1995-2003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7904/142\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSeason of conception and delivery\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePreeclampsia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMiddle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMagnus et al.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNorway\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ecohort\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1967-1998\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1869388/51801\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMonth of delivery\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePreeclampsia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMakhseed et al.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1999\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eKuwait\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ecase-control\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1992-1994\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e26805/692\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMonth of delivery\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePreeclampsia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRos et al.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1998\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSweden\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ecohort\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1987-1993\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10193/557\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSeason of delivery\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEclampsia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eJamelle et al.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1998\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePakistan\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ecase-control\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1996\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18878/395\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMonth of delivery\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEclampsia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMiddle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003ch2\u003eSeason of delivery and HDP\u003c/h2\u003e\n\u003cp\u003eFourteen articles assessed the relationship between delivery season and HDP (\u003cspan class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e26\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e32\u003c/span\u003e), and eleven articles with sufficient data were included in the meta-analysis (\u003cspan class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e27\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e31\u003c/span\u003e). Because the heterogeneity between studies was high (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.1, I\u003csup\u003e2\u003c/sup\u003e \u0026gt; 25%), we used a random effects model to pool the ORs and 95% CIs.\u003c/p\u003e\n\u003cp\u003eWith summer delivery as the reference, a significant association between HDP and winter delivery (OR = 1.18, 95% CI 1.02-1.38, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001) was found, but there was no association with spring delivery (OR = 1.09, 95% CI 0.97-1.22, \u003cem\u003ep\u003c/em\u003e = 0.066) or fall delivery (OR = 1.01, 95% CI 0.92-1.11, \u003cem\u003ep\u003c/em\u003e =0.189) (Figure \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eSubgroup analyses were carried out according to latitude, income group, sample size, and whether multiple pregnancies were excluded in the studies. The results of the associations of HDP with winter delivery and summer delivery were as follows. In the latitude subgroup analysis (Figure \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e), the heterogeneity decreased slightly (high latitude: I\u003csup\u003e2\u003c/sup\u003e = 42.6%, \u003cem\u003ep\u003c/em\u003e =0.187; middle latitude: I\u003csup\u003e2\u003c/sup\u003e = 67.2%, \u003cem\u003ep\u003c/em\u003e =0.016; low latitude: I\u003csup\u003e2\u003c/sup\u003e = 0.0%, \u003cem\u003ep\u003c/em\u003e = 0.931), and a stronger association was observed in high-latitude countries (OR = 1.62, 95% CI 1.20-2.20) and middle-latitude countries (OR = 1.24, 95% CI 1.00-1.55). However, at low latitudes, the result was nonsignificant (OR = 0.90, 95% CI 0.76-1.05). When stratified by income group and excluding studies with a sample size \u0026lt;10,000, the heterogeneity did not change considerably, and the correlation between HDP and winter delivery remained positive. In 2 studies excluding women with multiple pregnancies, the studies by Li (OR = 1.56, 95% CI 0.91-2.69) and Rylander (OR = 1.99, 95% CI 1.33-2.98) still showed significant associations between HDP and winter delivery (\u003cspan class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e21\u003c/span\u003e). The results of the subgroup analyses for spring and fall delivery versus summer delivery were nonsignificant.\u003c/p\u003e\n\u003cp\u003eThe sensitivity analysis suggested that no single study altered the association (Figure \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e). In the publication bias test, three Begg\u0026rsquo;s funnel plots were symmetric, and Egger\u0026rsquo;s test was nonpositive (winter \u003cem\u003ep\u003c/em\u003e = 0.175; spring \u003cem\u003ep\u003c/em\u003e = 0.454; fall \u003cem\u003ep\u003c/em\u003e = 0.623) (Figure \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eBased on the above results, we further compared winter delivery with delivery in other seasons. The result yielded a statistically significant result (OR = 1.17, 95% CI 1.03-1.34, I\u003csup\u003e2\u003c/sup\u003e = 75.4%, \u003cem\u003ep\u003c/em\u003e \u0026lt;0.001) (Figure \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003e). Subgroup analysis did not significantly reduce the interstudy heterogeneity. The results of the sensitivity analysis were stable. Symmetrical Begg\u0026rsquo;s funnel plots and Egger\u0026rsquo;s test (\u003cem\u003ep\u003c/em\u003e = 0.155) showed that there was no publication bias.\u003c/p\u003e\n\u003cp\u003eTwo of the remaining three studies that were not included in the quantitative analysis revealed that the risk of HDP was highest when women delivered in the winter months (\u003cspan class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e32\u003c/span\u003e), which was consistent with our quantitative analysis. Morikawa reported that the relative risks of pregnancy-induced hypertension were 1.12 (95% CI 1.06\u0026ndash;1.19) for delivery in January\u0026ndash;February and 1.16 (95% CI 1.09\u0026ndash;1.22) for delivery in March\u0026ndash;April compared with delivery in July\u0026ndash; August (\u003cspan class=\"CitationRef\"\u003e11\u003c/span\u003e). Magnus reported that delivery in August was associated with the lowest risk of preeclampsia, while the risk was highest in the winter months (for December, adjusted OR = 1.26, 95% CI 1.20\u0026ndash;1.31) (\u003cspan class=\"CitationRef\"\u003e32\u003c/span\u003e). However, Phillips found that there were no significant differences in the rates of preeclampsia in women with winter and spring deliveries, but women with summer deliveries (OR = 0.63, 95% CI 0.39\u0026ndash; 0.99 vs. spring) and fall deliveries (OR = 0.60, 95% CI 0.37\u0026ndash;0.98 vs. spring) had reduced odds of developing preeclampsia (\u003cspan class=\"CitationRef\"\u003e26\u003c/span\u003e).\u003c/p\u003e\n\u003ch2\u003eSeason of conception and HDP\u003c/h2\u003e\n\u003cp\u003eSeven studies assessed the relationship between conception season or month and HDP. Four studies supported that conception in summer increased the risk of developing HDP (\u003cspan class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e24\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e26\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eRohr Thomsen showed that women who conceived in August (OR = 1.35, 95% CI 1.11-1.64) had the highest risk of gestational hypertension, and those who conceived in June (OR = 1.17, 95% CI 0.94-1.45) had the highest risk of preeclampsia, which occurred in both the summer months (\u003cspan class=\"CitationRef\"\u003e22\u003c/span\u003e). Tran found that conception in summer was associated with the highest risk of severe preeclampsia (OR = 1.53, 95% CI 1.27-1.85, vs. winter) (\u003cspan class=\"CitationRef\"\u003e24\u003c/span\u003e). Tam (OR = 1.7, 95% CI 1.2\u0026ndash;2.5, vs. autumn) and Phillips (OR = 1.7, 95% CI 1.1-2.8 vs. spring) revealed that conception in summer was associated with an increased risk of preeclampsia (\u003cspan class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e26\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eHowever, the results of 3 studies were not consistent with the above conclusion. Rudra reported that conception in February (OR = 1.17, 95% CI 1.03-1.33 vs. January) and April (OR = 1.18, 95% CI 1.03-1.34 vs. January) through August (OR = 1.14, 95% CI 1.01-1.30 vs. January) were associated with significantly higher risks of preeclampsia (\u003cspan class=\"CitationRef\"\u003e33\u003c/span\u003e). However, Shayan found that conception in autumn increased the odds of preeclampsia (OR = 1.13, 95% CI 0.73-1.76, vs. winter) and that conception in summer was associated with the lowest odds of preeclampsia (OR = 0.26, 95% CI 0.17-0.38, vs. winter) (\u003cspan class=\"CitationRef\"\u003e12\u003c/span\u003e). Weinberg revealed that women who conceived in spring had a higher risk of HDP, while those that conceived in autumn had a lower risk (\u003cspan class=\"CitationRef\"\u003e23\u003c/span\u003e).\u003c/p\u003e"},{"header":"Discussion","content":"\u003ch2\u003eMain findings\u003c/h2\u003e\n\u003cp\u003eThis systematic review of 20 studies and meta-analysis of 11 studies explored the relationship between season and\u0026nbsp;the\u0026nbsp;development of hypertensive\u0026nbsp;pregnancy\u0026nbsp;disorders. The results showed increased odds of HDP in women who\u0026nbsp;delivered\u0026nbsp;in winter compared with those who delivered in summer (OR = 1.18, 95% CI 1.02-1.38, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001) and other seasons (OR = 1.17, 95% CI 1.03-1.34, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001). Furthermore, in the analysis of the relationships between\u0026nbsp;HDP\u0026nbsp;and seasons or months of conception, 4 of 7 studies reported that women who conceived in summer had a higher risk of\u0026nbsp;HDP.\u003c/p\u003e\n\u003cp\u003eSome studies have suggested that HDP may be more strongly associated with conception time than with delivery time\u0026nbsp;(26, 34). Although the stages of pregnancy in the included studies were different, we combined them by gestation period. For example, in the studies on delivery and conception months, women who conceived in hot months generally delivered in cold months in the following year\u0026nbsp;(11, 18, 22, 27, 32). Women who conceived in June and delivered in March had the highest risk of preeclampsia\u0026nbsp;(22). The differences in these study results studies were possibly associated with premature delivery in women with HDP and the miscalculation of conception time. First, many studies have reported that women with HDP are prone to premature delivery\u0026nbsp;(35-37), and low-dose aspirin could decrease the incidence of preterm birth, particularly if initiated before 16 weeks of gestation\u0026nbsp;(36). Therefore, this could help explain the high incidence of HDP in women who conceived in summer and delivered in winter. Second, a lack of ultrasound examination to determine the date of conception or the presence of menstrual disorders may cause inaccurate estimates of the date of conception, resulting in less accurate conclusions about the relationship between HDP and month of conception\u0026nbsp;(25, 33).\u003c/p\u003e\n\u003cp\u003eBased on our analysis, it was not possible to explain how season factors could affect the onset of HDP. According to basic research and epidemiological investigations, a number of possible mechanisms\u0026nbsp;influenced by factors\u0026nbsp;such as nutritional status, sunlight exposure, temperature, humidity, and infection,\u0026nbsp;may explain the correlation. Here, we discuss some relevant factors. Among the different seasons, there is wide variation in the nutrients consumed by people, resulting in different risks of pregnancy-related diseases\u0026nbsp;(38). Lowensohn reported\u0026nbsp;that\u0026nbsp;calcium supplementation may reduce the risk of HDP, especially in low-calcium populations\u0026nbsp;(38). In addition, Mirzakhani reported that\u0026nbsp;vitamin\u0026nbsp;D levels above 30 ng/ml at the start of the trial and in late pregnancy were associated with a lower risk of preeclampsia\u0026nbsp;(39). Vitamin D\u0026nbsp;levels are\u0026nbsp;not only affected by seasonal variations in nutrient intake but\u0026nbsp;are\u0026nbsp;also closely related to sunlight exposure. Vitamin D is produced naturally in the skin when skin is exposed to sunlight, which\u0026nbsp;varies greatly among\u0026nbsp;seasons\u0026nbsp;(18, 21, 22). In a recent study by Horton-French, young adults had a 3 times higher risk of vitamin D deficiency in the winter than in the summer, which was consistent with our findings of a higher risk in women who delivered in winter\u0026nbsp;(40). Additionally, variations in temperature and humidity have also been hypothesized. Xiong reported\u0026nbsp;that\u0026nbsp;in the early stages of pregnancy, cold temperatures\u0026nbsp;reduced\u0026nbsp;the risk, whereas hot temperatures increased the risk\u0026nbsp;(34).\u0026nbsp;Moreover, the incidence of preeclampsia was significantly higher during the dry season\u0026nbsp;than during the\u0026nbsp;rainy season\u0026nbsp;(41, 42). As a possible explanation, Krininger reported\u0026nbsp;that\u0026nbsp;heat shock was found to compromise embryo implantation in an animal model\u0026nbsp;(43). Water loss resulting in reduced plasma volume in warm months may\u0026nbsp;increase\u0026nbsp;the risk of developing preeclampsia\u0026nbsp;(44), which may indirectly explain the increased risk of HDP in women who conceive in summer. Exposure to cold temperatures could lead to vasospasms and subsequent ischemia\u0026nbsp;(45), which\u0026nbsp;is a possible reason for\u0026nbsp;the\u0026nbsp;increased risk of HDP in winter\u0026nbsp;(20). All of these factors that affect cardiovascular conditions may together increase blood pressure, promoting the formation of HDP. Finally, seasonal fluctuations in infection rates may result in variability in the seasonal occurrence of preeclampsia\u0026nbsp;(46), which could cause a maternal systemic inflammatory response.\u003c/p\u003e\n\u003cp\u003eIn this meta-analysis of studies on delivery season and conception season, the heterogeneity was high, possibly due to confounding factors such as sample size, latitude, income group, study design, and definitions of outcomes. To solve this problem, we performed subgroup analyses to find the source of the heterogeneity. The heterogeneity slightly decreased in only the latitude subgroup analysis. Although we failed to find the major source of heterogeneity, our sensitivity analysis indicated that our results were valid. In addition, because reference seasons or months were different and some original data could not be obtained, we failed to carry out a meta-analysis of studies on conception season and HDP. Therefore, more studies need to be analyzed to minimize heterogeneity and explore the relationship between conception season and HDP to obtain more accurate correlation results.\u003c/p\u003e\n\u003cp\u003eIn summary, additional large-scale multicenter studies analyzing specific seasonal factors, such as temperature,\u0026nbsp;humidity\u0026nbsp;and\u0026nbsp;pollution, are needed to thoroughly study the relationship between season or month and HDP. Furthermore, the identification of risk factors for the onset of HDP is important because it could greatly improve pregnancy and fetal outcomes.\u003c/p\u003e\n\u003ch2\u003eStrengths and limitations\u003c/h2\u003e\n\u003cp\u003eAccurate and robust statistical results were reported in this meta-analysis on the positive association between season and HDP. In addition, this is the first quantitative analysis of this topic.\u003c/p\u003e\n\u003cp\u003eHowever, this study has some limitations. First, we found heterogeneity in our meta-analysis. Many factors beyond our control, such as sample size, latitude, income group, study design, and definitions of outcomes, could all affect the degree of heterogeneity. Thus, additional high-quality studies are needed to reduce heterogeneity in the future. Second, in the study of the relationship between conception season and HDP, the reference season or month differed, and original data were not reported. This caused difficulty in performing a meta-analysis, resulting in insufficient reliability of the results. Third, we excluded non-English articles, which led to the exclusion of studies not published in English, potentially influencing the representativeness of our results.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eBased on the evidence to date, we found weakly positive relationships between HDP and summer conception and winter delivery. Additional large-scale multicenter studies analyzing detailed seasonal factors, such as temperature, humidity and pollution, are needed to thoroughly study the relationship between season or month and HPD.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eHDP : Hypertensive disorders of pregnancy\u003c/p\u003e\n\u003cp\u003eMOOSE : The Meta-Analysis of Observational Studies in Epidemiology\u003c/p\u003e\n\u003cp\u003ePRISMA : Preferred Reporting Items for Systematic review and Meta-Analyses\u003c/p\u003e\n\u003cp\u003eMeSH : Medical Subject Headings\u003c/p\u003e\n\u003cp\u003eORs :Odds ratios\u003c/p\u003e\n\u003cp\u003e95% CIs: \u0026nbsp;95% confidence intervals\u003c/p\u003e\n\u003cp\u003eNOS : the Newcastle-Ottawa quality assessment scale\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAvailability of data and materials\u003c/h2\u003e\n\u003cp\u003eData will be available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003ch2 id=\"isPasted\"\u003eAcknowledgements\u003c/h2\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003ch2\u003eFunding\u003c/h2\u003e\n\u003cp\u003eThis work was supported by the\u0026nbsp;National Natural Science Foundation of China\u0026nbsp;(No. 81571465 and 81871175) and the Key Projects of Sichuan Science and Technology Department (No. 2021YFS0208).\u003c/p\u003e\n\u003ch2\u003eAuthor information\u003c/h2\u003e\n\u003ch2\u003eAffiliations\u003c/h2\u003e\n\u003cp\u003eDepartment of Obstetrics and Gynecology, West China Second University Hospital, Sichuan University, Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University) of Ministry of Education, Chengdu, Sichuan, China\u003c/p\u003e\n\u003cp\u003eLingyun Liao, Xiaohong Wei, Min Liu, Yijie Gao, Yangxue Yin \u0026amp; \u0026nbsp;Rong Zhou\u003c/p\u003e\n\u003ch2\u003eContributions\u003c/h2\u003e\n\u003cp\u003eLL and XW performed experiments and analyzed the results. LL conceived the study and prepared the manuscript. ML modified the figure. YG, YY and RZ supervised the study. All authors contributed to the article and approved the submitted version.\u003c/p\u003e\n\u003ch2\u003eCorresponding author\u003c/h2\u003e\n\u003cp\u003eRong Zhou\u003c/p\u003e\n\u003ch2\u003eEthics declarations\u003c/h2\u003e\n\u003ch2\u003eEthics approval and consent to participate\u003c/h2\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003ch2\u003eConsent for publication\u003c/h2\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003ch2\u003eCompeting interests\u003c/h2\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eHypertension in pregnancy. Report of the American College of Obstetricians and Gynecologists\u0026rsquo; Task Force on Hypertension in Pregnancy. Obstet Gynecol. 2013;122(5):1122\u0026ndash;31.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eUmesawa M, Kobashi G. Epidemiology of hypertensive disorders in pregnancy: prevalence, risk factors, predictors and prognosis. Hypertens Res. 2017;40(3):213\u0026ndash;20.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMalek AM, Wilson DA, Turan TN, Mateus J, Lackland DT, Hunt KJ. Maternal Coronary Heart Disease, Stroke, and Mortality Within 1, 3, and 5 Years of Delivery Among Women With Hypertensive Disorders of Pregnancy and Pre-Pregnancy Hypertension. J Am Heart Assoc. 2021:e018155.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCountouris ME, Villanueva FS, Berlacher KL, Cavalcante JL, Parks WT, Catov JM. Association of Hypertensive Disorders of Pregnancy With Left Ventricular Remodeling Later in Life. J Am Coll Cardiol. 2021;77(8):1057\u0026ndash;68.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKurbasic A, Fraser A, Mogren I, Hallmans G, Franks PW, Rich-Edwards JW, et al. Maternal Hypertensive Disorders of Pregnancy and Offspring Risk of Hypertension: A Population-Based Cohort and Sibling Study. Am J Hypertens. 2019;32(4):331\u0026ndash;4.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFarzaneh F, Tavakolikia Z, Soleimanzadeh Mousavi SH. Assessment of occurrence of preeclampsia and some clinical and demographic risk factors in Zahedan city in 2017. Clin Exp Hypertens. 2019;41(6):583\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLi X, Tan H, Huang X, Zhou S, Hu S, Wang X, et al. Similarities and differences between the risk factors for gestational hypertension and preeclampsia: A population based cohort study in south China. Pregnancy Hypertens. 2016;6(1):66\u0026ndash;71.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWatad A, Azrielant S, Bragazzi NL, Sharif K, David P, Katz I, et al. Seasonality and autoimmune diseases: The contribution of the four seasons to the mosaic of autoimmunity. J Autoimmun. 2017;82:13\u0026ndash;30.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eStewart S, Keates AK, Redfern A, McMurray JJV. Seasonal variations in cardiovascular disease. Nat Rev Cardiol. 2017;14(11):654\u0026ndash;64.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRylander C, Odland J, Sandanger TM. Climate change and the potential effects on maternal and pregnancy outcomes: an assessment of the most vulnerable--the mother, fetus, and newborn child. Glob Health Action. 2013;6:19538.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMorikawa M, Yamada T, Yamada T, Cho K, Sato S, Minakami H. Seasonal variation in the prevalence of pregnancy-induced hypertension in Japanese women. J Obstet Gynaecol Res. 2014;40(4):926\u0026ndash;31.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShayan A, Sourinejad H, Refaei M, Masoumi SZ, Tapak L, Soltani F. Predictors of Preeclampsia Based on a 10-Year Case-Control Study. J Family Reprod Health. 2019;13(1):14\u0026ndash;20.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eStroup DF, Berlin JA, Morton SC, Olkin I, Williamson GD, Rennie D, et al. Meta-analysis of observational studies in epidemiology: a proposal for reporting. Meta-analysis Of Observational Studies in Epidemiology (MOOSE) group. Jama. 2000;283(15):2008\u0026ndash;12.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMoher D, Shamseer L, Clarke M, Ghersi D, Liberati A, Petticrew M, et al. Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015 statement. Syst Rev. 2015;4(1):1.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMet Office. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.metoffice.gov.uk/weather/learn-about/weather/seasons/spring/when-does-spring-start\u003c/span\u003e\u003c/span\u003e. Accessed 9 Sep 2021.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGoogle map. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.maps.google.com\u003c/span\u003e\u003c/span\u003e. Accessed 9 Sep 2021.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eStang A. Critical evaluation of the Newcastle-Ottawa scale for the assessment of the quality of nonrandomized studies in meta-analyses. Eur J Epidemiol. 2010;25(9):603\u0026ndash;5.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAli AA, Adam GK, Abdallah TM. Seasonal variation and hypertensive disorders of pregnancy in eastern Sudan. J Obstet Gynaecol. 2015;35(2):153\u0026ndash;4.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLuo B, Ma X. Risk factors for preeclampsia: a case-control study. Hypertens Pregnancy. 2013;32(4):432\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWellington K, Mulla ZD. Seasonal trend in the occurrence of preeclampsia and eclampsia in Texas. Am J Hypertens. 2012;25(1):115\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRylander A, Lindqvist PG. Eclampsia is more prevalent during the winter season in Sweden. Acta Obstet Gynecol Scand. 2011;90(1):114\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRohr Thomsen C, Brink Henriksen T, Uldbjerg N, Milidou I. Seasonal variation in the hypertensive disorders of pregnancy in Denmark. Acta Obstet Gynecol Scand. 2020;99(5):623\u0026ndash;30.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWeinberg CR, Shi M, Basso O, DeRoo LA, Harmon Q, Wilcox AJ, et al. Season of Conception, Smoking, and Preeclampsia in Norway. Environ Health Perspect. 2017;125(6):067022.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTran TC, Boumendil A, Bussieres L, Lebreton E, Ropers J, Rozenberg P, et al. Are Meteorological Conditions within the First Trimester of Pregnancy Associated with the Risk of Severe Pre-Eclampsia? Paediatr Perinat Epidemiol. 2015;29(4):261\u0026ndash;70.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTam WH, Sahota DS, Lau TK, Li CY, Fung TY. Seasonal variation in pre-eclamptic rate and its association with the ambient temperature and humidity in early pregnancy. Gynecol Obstet Invest. 2008;66(1):22\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePhillips JK, Bernstein IM, Mongeon JA, Badger GJ. Seasonal variation in preeclampsia based on timing of conception. Obstet Gynecol. 2004;104(5 Pt 1):1015\u0026ndash;20.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBullock N, Breese McCoy SJ, Payton ME. Role of race in the seasonality of deliveries with preeclampsia. Med Hypotheses. 2011;77(4):674\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSoroori ZZ, Sharami SH, Faraji R. Seasonal variation of the onset of preeclampsia and eclampsia. J Res Med Sci. 2007;12(4):198\u0026ndash;202.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMakhseed M, Musini VM, Ahmed HA, Abdul Monem R. Influence of seasonal variation on pregnancy-induced hypertension and or preeclampsia. #N/A. 1999;39(2):196\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRos HS, Cnattingius S, Lipworth L. Comparison of risk factors for preeclampsia and gestational hypertension in a population-based cohort study. Am J Epidemiol. 1998;147(11):1062\u0026ndash;70.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJamelle RN. Eclampsia: is there a seasonal variation in incidence? J Obstet Gynaecol Res. 1998;24(2):121\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMagnus P, Eskild A. Seasonal variation in the occurrence of pre-eclampsia. Bjog. 2001;108(11):1116\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRudra CB, Williams MA. Monthly variation in preeclampsia prevalence: Washington State, 1987-2001. J Matern Fetal Neonatal Med. 2005;18(5):319\u0026ndash;24.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eXiong T, Chen P, Mu Y, Li X, Di B, Li J, et al. Association between ambient temperature and hypertensive disorders in pregnancy in China. Nat Commun. 2020;11(1):2925.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGoldenberg RL, Culhane JF, Iams JD, Romero R. Epidemiology and causes of preterm birth. Lancet. 2008;371(9606):75\u0026ndash;84.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHoffman MK, Goudar SS, Kodkany BS, Metgud M, Somannavar M, Okitawutshu J, et al. Low-dose aspirin for the prevention of preterm delivery in nulliparous women with a singleton pregnancy (ASPIRIN): a randomised, double-blind, placebo-controlled trial. Lancet. 2020;395(10220):285\u0026ndash;93.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShulman JP, Weng C, Wilkes J, Greene T, Hartnett ME. Association of Maternal Preeclampsia With Infant Risk of Premature Birth and Retinopathy of Prematurity. JAMA Ophthalmol. 2017;135(9):947\u0026ndash;53.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLowensohn RI, Stadler DD, Naze C. Current Concepts of Maternal Nutrition. #N/A. 2016;71(7):413\u0026ndash;26.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMirzakhani H, Litonjua AA, McElrath TF, O'Connor G, Lee-Parritz A, Iverson R, et al. Early pregnancy vitamin D status and risk of preeclampsia. J Clin Invest. 2016;126(12):4702\u0026ndash;15.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHorton-French K, Dunlop E, Lucas RM, Pereira G, Black LJ. Prevalence and predictors of vitamin D deficiency in a nationally representative sample of Australian adolescents and young adults. Eur J Clin Nutr. 2021:1\u0026ndash;10.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eElongi JP, Tandu B, Spitz B, Verdonck F. [Influence of the seasonal variation on the prevalence of pre-eclampsia in Kinshasa]. Gynecol Obstet Fertil. 2011;39(3):132\u0026ndash;5.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWacker J, Schulz M, Fr\u0026uuml;hauf J, Chiwora FM, Solomayer E, Bastert G. Seasonal change in the incidence of preeclampsia in Zimbabwe. Acta Obstet Gynecol Scand. 1998;77(7):712\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKrininger CE, 3rd, Stephens SH, Hansen PJ. Developmental changes in inhibitory effects of arsenic and heat shock on growth of pre-implantation bovine embryos. Mol Reprod Dev. 2002;63(3):335\u0026ndash;40.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAardenburg R, Spaanderman ME, Ekhart TH, van Eijndhoven HW, van der Heijden OW, Peeters LL. Low plasma volume following pregnancy complicated by pre-eclampsia predisposes for hypertensive disease in a next pregnancy. Bjog. 2003;110(11):1001\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAlba BK, Castellani JW, Charkoudian N. Cold-induced cutaneous vasoconstriction in humans: Function, dysfunction and the distinctly counterproductive. Exp Physiol. 2019;104(8):1202\u0026ndash;14.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSibai B, Dekker G, Kupferminc M. Pre-eclampsia. Lancet. 2005;365(9461):785\u0026ndash;99.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Delivery season, Conception season, Hypertensive Disorders of Pregnancy, Preeclampsia, Meta-analysis","lastPublishedDoi":"10.21203/rs.3.rs-1020061/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-1020061/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eBackground: There is increasing and inconsistent evidence of a relationship between hypertensive disorders of pregnancy (HDP) and season of delivery or conception.\u003c/p\u003e\u003cp\u003eMethods: Four databases, the Cochrane Library, PubMed, EMBASE and Web of Science, were searched until September 29th, 2021. Two authors extracted data independently. A random effects model and the Mantel-Haenszel method were used to calculate pooled ORs and 95% CIs.\u003c/p\u003e\u003cp\u003eResults: Twenty articles were included in the systematic review, and 11 articles were included in the meta-analysis. The quantitative analysis of the association between delivery season and HDP showed that the odds of HDP was higher in women who deliver in winter than in those who delivered in summer (OR=1.18, 95% CI 1.02-1.38, p \u0026lt; 0.001) and all other seasons (OR = 1.17, 95% CI 1.03-1.34, p \u0026lt;0.001). In the qualitative analysis of the association between conception season and HDP, 4 of 7 studies suggested that women who conceived in summer had a higher risk of HDP than those who conceived in other seasons.\u003c/p\u003e\u003cp\u003eConclusions: Based on the evidence to date, we found weakly positive relationships between HDP and summer conception and winter delivery.\u003c/p\u003e","manuscriptTitle":"The Association between Season and Hypertensive Disorders of Pregnancy: A Systematic Review and Meta-Analysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2021-11-01 16:42:46","doi":"10.21203/rs.3.rs-1020061/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"26a51080-f296-42cf-ac6b-eee06bfa560b","owner":[],"postedDate":"November 1st, 2021","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":8236636,"name":"Maternal \u0026 Fetal Medicine"},{"id":8236637,"name":"Sexual \u0026 Reproductive Medicine"}],"tags":[],"updatedAt":"2022-03-16T07:59:12+00:00","versionOfRecord":[],"versionCreatedAt":"2021-11-01 16:42:46","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-1020061","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-1020061","identity":"rs-1020061","version":["v1"]},"buildId":"GqpaHPwrfC8PjnIFayRh5","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}