Population-based trends and risk factors of early- and late-onset preeclampsia in Taiwan 2001–2014

Population-based trends and risk factors of early- and late-onset preeclampsia in Taiwan 2001–2014 Background: Preeclampsia, a multisystem disorder in pregnancies complicates with maternal and fetal morbidity. Early- and late-onset preeclampsia, defined as preeclampsia developed before and after 34 weeks of gestation, respectively. The early-onset disease was less prevalent but associated with poorer outcomes. Moreover, the risk factors between early -and late- onset preeclampsia could be differed owing to the varied pathophysiology. In the study, we evaluated the incidences, trends, and risk factors of early- and late- onset preeclampsia in Taiwan. Methods: This retrospective population-based cohort study included all ≧20 weeks singleton pregnancies resulting in live-born babies or stillbirths in Taiwan between January 1, 2001 and December 31, 2014 (n = 2,884,347). The data was collected electronically in Taiwanese Birth Register and National Health Insurance Research Database. The incidences and trends of early- and late-onset preeclampsia were assessed through Joinpoint analysis. Multivariate logistic regression was used to analyze the risk factors of both diseases. Results: The age-adjusted overall preeclampsia rate was slightly increased from 1.1%(95%confidence interval [CI], 1. 1–1.2) in 2001 to 1.3% (95%CI, 1.2–1.3) in 2012 with average annual percentage change (AAPC) 0.1%/year (95%CI, 0–0.2%). However, the incidence was remarkably increased from 1.3% (95%CI, 1.3–1.4) in 2012 to 1.7% (95%CI, 1.6–1. 8) in 2014 with AAPC 1.3%/year (95%CI,0.3–2.5). Over the study period, the incidence trend in late-onset preeclampsia was steadily increasing from 0.7% (95%CI, 0.6–0.7) in 2001 to 0.9% (95%CI, 0.8–0.9) in 2014 with AAPC 0.2%/year (95%CI, 0.2–0.3) but in early-onset preeclampsia was predominantly increase from 0.5% (95%CI, 0.4–0.5) in 2012 to 0.8% (95%CI, 0.8–0.9) in 2014 with AAPC 2.3%/year (95%CI, 0.8–4.0). Advanced maternal age, primiparity, stroke, diabetes mellitus, chronic hypertension, and hyperthyroidism were risk factors of preeclampsia. Comparing early- and late-onset diseases, chronic hypertension (ratio of relative risk [RRR], 1.71; 95%CI, 1.55–1.88) and older age (RRR, 1.41; 95%CI 1.29–1.54) were more strongly associated with early-onset disease, whereas primiparity (RRR 0.71, 95%CI, 0.68–0.75) had stronger association with late-onset preeclampsia. Conclusions: The incidences of overall, and early- and late-onset preeclampsia were increasing in Taiwan from 2001 to 2014, predominantly for early-onset disease. Pregnant women with older age and chronic hypertension had significantly higher risk of early-onset preeclampsia. Keywords: Preeclampsia, Incidence, Risk factors, Early onset, Late onset, Hypertension * Correspondence: danielwu@cgmh.org.tw; taipei.chu@gmail.com Department of Obstetrics and Gynecology, Chang Gung Memorial Hospital, Linkou, Taiwan Department of Cardiology, Chang Gung Memorial Hospital, Linkou, Taiwan Full list of author information is available at the end of the article © The Author(s). 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. You et al. BMC Pregnancy and Childbirth (2018) 18:199 Page 2 of 11 Background early-onset disease, whereas women with nulliparity and Worldwide 2.0 to 8.0% pregnancies were complicated by diabetes mellitus had higher risk to develop late-onset preeclampsia [1–5] with variation across regions [2]. Pre- disease [14]. The other study conducted by Iacobelli et eclampsia, the progressive disorder during pregnancy is al. showed older age and higher prevalence of chronic strongly associated with maternal and fetal complications hypertension in the group of early-onset disease [16]. including eclampsia, acute renal failure, coagulopathy, pla- The incidence of preeclampsia in Taiwan was signifi- centa abruption, postpartum hemorrhage, intrauterine cantly increased from 0.87 to 1.21% between 1998 and growth restriction, medically indicated preterm birth, and 2010 [25]. However, there was limited data of early- and maternal and fetal death [1, 6, 7]. In a systemic analysis late-onset preeclampsia rate and the associated factors from World Health Organization (WHO), hypertensive in Taiwan has not been determined yet. The aim of the disorders including preeclampsia accounted for 14.0% ma- study was to investigate the population-based trends of ternal death between 2003 and 2009 [8]. Moreover, the early- and late-onset preeclampsia and examine the ma- risk of severe obstetric morbidities in women with ternal risk factors in Taiwanese population. eclampsia or severe preeclampsia was increasing [9]. Al- though most of the maternal dysfunctions resolved grad- Methods ually in postpartum, these women were at higher risk of Study design and data source developing chronic hypertension, recurrent preeclampsia The population-based cohort study retrospectively in- in the next pregnancy, and later-life cardiovascular dis- cluded all ≧20 weeks singleton deliveries, comprising live eases [10]. births and stillbirths in Taiwan from January 1, 2001 to Preeclampsia is recognized as a heterogenous syn- December 31, 2014. Two databases were used to obtain drome with different pathophysiology and be divided in data electronically in this study. One was Taiwanese two subtypes according to the disease onset [7, 11, 12]. birth registration system in Health Promotion Adminis- Early-onset preeclampsia, diagnosed less than 34 gesta- tration, Ministry of Health and Welfare (https:// tional weeks was less prevalent than late-onset pre- www.hpa.gov.tw/EngPages/Index.aspx), which included eclampsia, occurring at 34 or more weeks of gestation information of birth date, gestational age, and fetal [13]. The incidences of early- and late-onset preeclamp- weights of all neonates and stillbirths with gestational age sia were 0.3 and 2.7%, respectively [14, 15]; nevertheless, ≧20 weeks. Another was National Health Insurance Data- the early-onset disease contributed to more unfavorable base (NHIRD, https://nhird.nhri.org.tw/en/index.html), maternal and fetal outcomes [14, 16, 17]. Around which could be linked from Taiwanese birth registration ten-fold increased risk of perinatal death and maternal system for details of maternal general data and diagnosis. death in women with early-onset preeclampsia and two- Both databases have been encrypted to generate the fold higher risk of perinatal death and threefold in- unique identification to anonymous identification. creased risks of maternal death in women with In Taiwan, birth certificates of all neonates and still- late-onset disease were observed, comparing with normal births with gestational age ≧20 weeks or gestational age pregnancy [14, 15]. In addition, some studies showed bio- < 20 weeks but fetal birth weights ≧500 g are issued at logical variations and different spectrums of pathophysi- the hospital or medical institution and registered in the ology between early- and late-onset preeclampsia [18–20]. Ministry of Health and Welfare. The birth register can Clinical factors associated with risk of preeclampsia in- be linked to NHIRD, which was a database contained in- cluded primiparity, advanced maternal age, previous pre- formation of insured people, including demographic eclampsia, family history of preeclampsia, multiple data, dates of hospitalization and clinical visits, and diag- gestation, obesity, African-American race, diabetes melli- nostic codes as International Classification of Diseases, tus, chronic hypertension, chronic renal disease, and the 9th version (ICD-9) during the study period. presence of antiphospholipid antibodies were identified [21, 22]. Besides, there were evidences that stroke and Participants hyperthyroidism increased the risk of preeclampsia [23, There were 2,973,989 registered deliveries in Taiwan 24]. Further studies comparing predisposing factors of from January 1, 2001 to December 31, 2014. Women early- versus late-onset preeclampsia demonstrated simi- who were younger than 15-year-old or older than lar risk factors but the strengths of association were 55-year-old, with multiple gestation including twins, differed among the factors. There were only two triplets, or quadruplets, and with gestational age at deliv- population-based studies, to our knowledge to evaluate ery less than 20 weeks were excluded. To identify the in- each risk factor between early- and late-onset pre- cidences of early- and late-onset preeclampsia, all the eclampsia [14, 16]. One study, carried out by Lisonkova included delivers were categorized to ongoing pregnancy et al. revealed African-American race, chronic hyperten- at 20 weeks of gestation and 34 weeks of gestation ac- sion, and older age were more strongly associated with cording to the gestational age at delivery, and each of You et al. BMC Pregnancy and Childbirth (2018) 18:199 Page 3 of 11 which were the denominators of early- and late-onset (urban, suburban, rural), income (quintiles 1 to 5), and preeclampsia rate, respectively [14, 15, 26]. clinical factors associated with risk of preeclampsia were The diagnostic criteria of preeclampsia was two occa- examined for potential variables [14, 16, 22–24, 28, 29]. sions of hypertension at least 140/90 mmHg after The clinical factors were identified in NHIRD, including 20 weeks of gestation accompanied by proteinuria > acute coronary syndrome (ICD-9 codes, 410, 412 and 300 mg/day or ≧1+ on dipstick based on International 413), chronic ischemic heart disease (ICD-9 codes, 4140, Society for the Study of Hypertension in Pregnancy 4148 and 4149), stroke (ICD-9 codes, 43,301, 43,311, (ISSHP) by 2014 [10, 26, 27]. All included delivers asso- 43,321, 43,331, 43,381, 43,391, 43,401, 43,411, 43,491, ciated with diagnosis of preeclampsia were identified 435, 436, 4371, 4379 and 438), diabetes mellitus (ICD-9, from NHIRD ICD-9 diagnostic codes 642.4, 6424.5, 250), chronic hypertension (ICD-9 codes, 401–405) and 6424.6, and 6424.7 [14, 15]. To obtain the gestational hyperthyroidism (ICD-9 codes, 242). week of onset of preeclampsia for determing early- and late-onset preeclampsia, which were occurring less than Statistical analysis and later than 34 weeks of gestation, the date of diagno- Thestandardizedpreeclampsiaincidence wasadjusted sis was subtracted from the date at delivery, and calcu- based on the age distribution in 2014 and 95% confi- lated the gestational age according to the information of dence intervals (CI) were derived from the Poisson gestational weeks at birth in birth registers. A flow chart distribution. The linear trends in proportion were illustrating patient inclusion is showed in Fig. 1. The assessed using Joinpoint Regression Program version study was approved by Institutional Review Board of the 4.2.0.2 (National Cancer Institute, Bethesda, MD, Chang Gung Memorial Hospital (IRB No.201600657B0). USA) to estimate temporal trends in standardized in- cidence of preeclampsia. Bayesian information criter- Definition of variables ion was used to generate ‘joinpoints’ over time Maternal characteristics including maternal age (15–24, according to the changes of trend and average annual 25–34, and 35–55 years old), parity (number of percentage change (AAPC) and 95%CI for each seg- prior≧20 weeks births, 0 vs. ≧1), place of residence ment were calculated. Fig. 1 Flow chart of the study You et al. BMC Pregnancy and Childbirth (2018) 18:199 Page 4 of 11 Multivariate logistic regression was used to obtain ad- chronic ischemic heart disease were not significantly justed relative risks (ARR) and 95% CIs adjusted for the associated with preeclampsia. The ARR of each clin- variables including maternal characteristics and clinical ical factor of overall preeclampsia are displayed in factors to examine the association with preeclampsia. Table 4. Of note, women with chronic hypertension The association between the clinical risk factors and had much higher risk of preeclampsia (ARR, 12.1; early- or late-onset preeclampsia was further compared 95%CI, 11.5–12.8). through the ratio of relative risks (RRR). Analyses were For subgroup analysis of early- and late-onset pre- carried out using SAS, version 9.4 (SAS Institute, Cary, eclampsia, the clinical factors associated with early- or NC, USA). A 2-tailed P < 0.05 was considered significant. late-onset diseases were identical to overall preeclamp- All tests of statistical hypothesis were done on the sia, detailed in Table 5. To compare the strength of the 2-sided 5% level of significance. association among the risk factors between early- and late-onset preeclampsia, RRR of each clinical factor was Results calculated according to the ARR of early- and late pre- Among 2,973,989 delivers over the 14 years period, eclampsia. Advanced maternal age (> 35 years) (RRR, 2,884,347 delivers were included and 32,742 preeclamp- 1.4; 95%CI, 1.3–1.5, p < 0.01) and chronic hypertension sia events were identified. The subgroups of early- and (RRR, 1.7; 95%CI, 1.6–1.9, p < 0.01) had higher risk to late- onset preeclampsia were 13,833 (42.3%) and 18,909 develop early-onset preeclampsia. In the contrary, primi- (57.6%) deliveries, respectively (Fig. 1). parity (RRR, 0.7; 95%CI, 0.7–0.8, p < 0.01) was more The overall preeclampsia incidence increased from strongly associated with late-onset disease. Other risk 1.1% (95%CI, 1.1–1.2) in 2001 to 1.7% (95%CI, 1.6–1.8) factors of preeclampsia including diabetes mellitus, in 2014. Table 1 reveals crude and age-adjusted overall stroke, and hyperthyroidism revealed no statistical differ- preeclampsia rates each year in the study period. The ence in the association of early- and late-onset pre- analysis of the overall, early-onset, and late-onset inci- eclampsia (Table 5). dence trends through average annual percentage change is presented in Table 2. The overall preeclampsia rate Discussion was slightly increased from 1.1% (95%CI, 1.1–1.2) in The incidences of overall, and early- and late-onset 2001 to 1.3% (95%CI, 1.2–1.3) in 2012 with average an- preeclampsia were increasing in Taiwan between nual percentage change (AAPC) 0.1%/year (95%CI, 0– 2001 and 2014, predominantly for early-onset disease. 0.2%). However, the incidence was remarkably increased Pregnant women with advanced maternal age, primi- from 1.3% (95%CI, 1.3–1.4) in 2012 to 1.7% (95%CI, parity, chronic hypertension, stroke, diabetes mellitus, 1.6–1.8) in 2014 with AAPC 1.3%/year (95%CI,0.3–2.5). and hyperthyroidism had significantly higher risk of Over the 14 years study period, the incidence trends in developing preeclampsia. Among the factors, older age late-onset preeclampsia was steadily increasing from and hypertension were more strongly associated with 0.7% (95%CI, 0.6–0.7) in 2001 to 0.9% (95%CI, 0.8–0.9) early-onset disease. in 2014 with AAPC 0.2%/year (95%CI, 0.2–0.3). How- Our study has certain limitations. First, overall pre- ever, in early-onset preeclampsia, similar to the trend of eclampsia was identified by diagnostic codes; thus, the overall preeclampsia, the incidence was relatively steady artificial coding error and misclassification bias could around 0.5% (95%CI, 0.4–0.5) in 2001 and 0.5% (95%CI, not be avoided. Second, NHIRD included 99% of Tai- 0.5–0.6) in 2012 but predominantly increase from 0.5% wanese residents, which led to around 1.2% deliveries in (95%CI, 0.4–0.5) in 2012 to 0.8% (95%CI, 0.8–0.9) in birth registration not be linked to hospital records. The 2014 with AAPC 2.3%/year (95%CI, 0.8–4.0). Figure 2 il- missing data could be susceptible to underascertain- lustrates the trends in overall preeclampsia, early-onset, ment, resulting in slightly underestimation of the inci- and late-onset disease. dence. Third, if a patient had neither antenatal exam nor Maternal characteristics (age, parity, place of resi- delivered in hospitals, or developed postpartum pre- dence, and income) and clinical factors (acute coronary eclampsia without hospitalization, the diagnostic code syndrome, chronic ischemic heart disease, stroke, dia- could not be obtained from the hospital record. The betes mellitus, chronic hypertension, and hyperthyroid- such undetermined were few and less severe but may ism) are described in Table 3. In multivariate logistic cause underestimation as well. Fourth, we did not clas- regression, all maternal characteristics and clinical fac- sify the severity of preeclampsia or determine the sub- tors listed in Table 3 were adjusted as possible con- group using aspirin for prevention, both of which may founders. Women with older age, nulliparity, chronic give more information to interpretate the trends of pre- hypertension, diabetes mellitus, stroke, and hyperthy- eclampsia. In addition, we failed to assess certain risk roidism were more likely to develop preeclampsia (all p factors including BMI, preeclampsia history in prior values< 0.01), while acute coronary syndrome and pregnancy, and family history of preeclampsia, as well as You et al. BMC Pregnancy and Childbirth (2018) 18:199 Page 5 of 11 Table 1 Preeclampsia incidence between January 1, 2001 and December 31, 2014 (n = 2,884,347) Total Early onset Late onset Year Total No of Crude IR, per Standardised Ongoing pregnancies at No of Crude IR, per Standardised Ongoing pregnancies at No of Crude IR, per Standardised Delivery (n) event 1000 births IR, per 1000 20 weeks (n) event 1000 births IR, per 1000 34 weeks (n) event 1000 births IR, per 1000 (95% CI) births (95% CI) births (95% CI) births (95%CI) (95%CI) (95%CI) 2001 243,357 2150 8.83 (8.46– 11.1 (10.5– 243,357 838 3.44 (3.21– 4.68 (4.31– 237,933 1312 5.51 (5.22– 6.56 (6.13– 9.21) 11.6) 3.68) 5.05) 5.81) 6.98) 2002 237,134 2186 9.22 (8.83– 11.6 (11.0– 237,134 950 4.01 (3.75– 5.37 (4.97– 231,862 1236 5.33 (5.03– 6.36 (5.93– 9.60) 12.1) 4.26) 5.76) 5.63) 6.78) 2003 221,232 2077 9.39 (8.98– 11.9 (11.3– 221,232 843 3.81 (3.55– 5.16 (4.76– 216,470 1234 5.70 (5.38– 6.88 (6.43– 9.79) 12.5) 4.07) 5.56) 6.02) 7.33) 2004 213,433 2014 9.44 (9.02– 11.7 (11.2– 213,433 839 3.93 (3.66– 5.10 (4.71– 208,461 1175 5.64 (5.31– 6.82 (6.37– 9.85) 12.3) 4.20) 5.49) 5.96) 7.27) 2005 203,137 1950 9.60 (9.17– 11.7 (11.1– 203,137 765 3.77 (3.50– 4.89 (4.51– 198,580 1185 5.97 (5.63– 6.98 (6.54– 10.0) 12.3) 4.03) 5.27) 6.31) 7.43) 2006 201,335 2306 11.5 (11.0– 13.3 (12.7– 201,335 968 4.81 (4.51– 5.76 (5.36– 196,617 1338 6.81 (6.44– 7.76 (7.30– 11.9) 13.9) 5.11) 6.16) 7.17) 8.23) 2007 199,389 2278 11.4 (11.0– 12.7 (12.1– 199,389 961 4.82 (4.51– 5.61 (5.22– 194,687 1317 6.76 (6.40– 7.27 (6.85– 11.9) 13.3) 5.12) 5.99) 7.13) 7.70) 2008 192,819 2086 10.8 (10.4– 11.9 (11.4– 192,819 891 4.62 (4.32– 5.22 (4.85– 188,125 1195 6.35 (5.99– 6.86 (6.45– 11.3) 12.4) 4.92) 5.58) 6.71) 7.28) 2009 188,735 2192 11.6 (11.1– 12.7 (12.2– 188,735 943 5.00 (4.68– 5.58 (5.21– 184,184 1249 6.78 (6.41– 7.32 (6.90– 12.1) 13.3) 5.32) 5.95) 7.16) 7.75) 2010 162,932 1927 11.8 (11.3– 12.4 (11.8– 162,932 801 4.92 (4.58– 5.23 (4.86– 158,724 1126 7.09 (6.68– 7.38 (6.94– 12.4) 13.0) 5.26) 5.60) 7.51) 7.82) 2011 194,095 2460 12.7 (12.2– 13.3 (12.7– 194,095 969 4.99 (4.68– 5.31 (4.97– 189,049 1491 7.89 (7.49– 8.18 (7.76– 13.2) 13.8) 5.31) 5.65) 8.29) 8.60) 2012 228,774 2885 12.6 (12.2– 13.0 (12.5– 228,774 1204 5.26 (4.97– 5.48 (5.17– 223,249 1681 7.53 (7.17– 7.73 (7.36– 13.1) 13.5) 5.56) 5.79) 7.89) 8.10) 2013 191,022 2775 14.5 (14.0– 14.6 (14.1– 191,022 1185 6.20 (5.85– 6.26 (5.91– 185,916 1590 8.55 (8.13– 8.59 (8.17– 15.1) 15.2) 6.56) 6.62) 8.97) 9.02) 2014 206,953 3506 16.9 (16.4– 16.9 (16.4– 206,953 1726 8.34 (7.95– 8.34 (7.95– 200,885 1780 8.86 (8.45– 8.86 (8.45– 17.5) 17.5) 8.73) 8.73) 9.27) 9.27) Abbreviation: IR incidence rate You et al. BMC Pregnancy and Childbirth (2018) 18:199 Page 6 of 11 Table 2 Joinpoint analysis of trend of preeclampsia incidence in Taiwan between 2001 and 2014 Standardised IR, per 1000 births AAPC Trend 1 Trend 2 2001 2014 Year AAPC (95%CI) Year AAPC (95%CI) Trend of entire cohort 11.1 (10.5–11.6) 16.9 (16.4–17.5) 3.01 (1.50 to 4.54)* 2001–2012 1.25 (0.36 to 2.14)* 2012–2014 13.3 (2.55 to 25.1) * by onset weeks < 34 weeks 4.68 (4.31–5.05) 8.34 (7.95–8.73) 3.67 (1.67 to 5.72)* 2001–2012 0.58 (− 0.63 to 1.80) 2012–2014 22.5 (7.50 to 39.6) * ≥ 34 weeks 6.56 (6.13–6.98) 8.86 (8.45–9.27) 2.21 (1.51 to 2.91)* AAPC average annual percent change *P < 0.05 the maternal and neonatal outcomes due to limited incidence of preeclampsia in the population-based study information. was thoroughly informative. The overall preeclampsia rate in Taiwan was relatively Our data suggested that the trend of preeclampsia was lower than the worldwide studies though, 42.3% pre- increasing between 2001 and 2014 after age ajustment, eclampsia events identified as early-onset disease was re- especially in early-onset disease from 2012 to 2014. We markable. The incidence of preeclampsia was 1.1 to 1.7% analyzed the subgroup trends of preeclampsia depend in Taiwan compared with 2 to 8% incidence of pre- on maternal age and women with or without hyperten- eclampsia worldwide with regional variations [2]. The sion, respectively [Additional file 1 and Additional file 2]. lower incidence could be owing to the majority of Asian Additional file 1 shows increased trend in all three age race in the population, which had lower risk of develop- groups (age 15–25, 25–35, and 35–55). However, Add- ing preeclampsia, 2.0–3.0%according to previous studies itional file 2 reveals no significant incidence change in [26, 30]. We did not collect data of races in this study women with our without hypertension during the study but over 95% of the population is Han Chinese, who are period. The subgroup analysis indicated that the increas- regarded as East Asian ethnic group based on the data ing trend of preeclampsia occurred in all age groups and in Ministry of Interior. Besides, there could possibly be possibly the growing number of women with hyperten- slight underestimation because of missing data in sion. Interestingly, the rise rate of preeclampsia was not NHIRD or the artificial bias of disease coding. Neverthe- universally consistent, for instance, studies for the entire less, NHIRD was one of the powerful tools in assessment USA from 1999 to 2004 showed plateaued rate [32] and of the epidemiology in Taiwan because of the high in Western New York from 1999 to 2003 [33] and Euro- coverage of National Health Insurance program, finan- pean countries during the past ten years [34] reported cing around 99% Taiwanese residents [31]. In the slight declines in preeclampsia. However, the increase in current study, the unidentified anonymous identification preeclampsia in our population could partially affected between birth register system and NHIRD was around by the revision of diagnostic criteria. American College 1.2%. In addition, compared with the study by Chan et al., of Obstetrician and Gynecologist (ACOG) in2013 and who revealed the increased incidence of preeclampsia in ISSHP in 2014 have excluded proteinuria as an necessary Taiwan was notable from 0.87 to 1.21% between 1998 and condition to establish diagnosis of preeclampsia in 2010 [25]. Therefore, the interpretation of exact pre- women presence of organ dysfunction of uteroplacental eclampsia rate could be somewhat underestimated owing dysfunction [35, 36]. Therefore, the observation of sig- to the unavoidable bias but the persisted increasing nificant rise in early-onset preeclampsia from 2012 to 2014 in this study was a conservative indication of in- creasing trend but the true percentage change should be followed since overall revision of the criteria in Taiwan. The proportion of early-onset preeclampsia was sig- nificantly higher (42.3% in early-onset and 57.6% in late onset disease) than previous studies conducted other than Taiwan [14–16], about twofold to nine-fold of late-onset disease than early-onset preeclampsia. The difference could attributed to increasing prevalence of chronic hypertension as a result of a surge of risk rates of prehypertension, obesity and metabolic syndrome in Taiwan [37]. Genetic variation or epigenetic regula- Fig. 2 Trends in overall, early-onset, and late-onset preeclampsia tion such as DNA methylation or microRNA expres- between 2001 and 2014 sion associated with preeclampsia in the population You et al. BMC Pregnancy and Childbirth (2018) 18:199 Page 7 of 11 Table 3 Maternal characteristics and clinical factors associated with early- and late-onset preeclampsia Characteristics Ongoing pregnancies at 20 weeks Early-onset preeclampsia Ongoing pregnancies at 34 weeks Late-onset preeclampsia n = 2,884,347 n = 13,883 Rate per 1000 n = 2,814,742 n = 18,909 Rate per 1000 (95% CI) (95% CI) Age at delivery 15–24 525,457 1305 2.48 (2.35–2.62) 513,581 2447 4.76 (4.58–4.95) 25–34 1,956,147 8688 4.44 (4.35–4.53) 1,914,210 12,155 6.35 (6.24–6.46) 35–55 402,743 3890 9.66 (9.36–9.96) 386,951 4307 11.13 (10.8–11.5) Number of prior ≧20 weeks births (parity) 0 1,938,341 9559 4.93 (4.83–5.03) 1,893,197 14,611 7.72 (7.59–7.84) ≥ 1 946,006 4324 4.57 (4.43–4.71) 921,545 4298 4.66 (4.52–4.80) Place of residence Urban 1681,534 7988 4.75 (4.65–4.85) 1,641,570 11,169 6.8 (6.68–6.93) Suburban 826,656 4368 5.28 (5.13–5.44) 806,062 5645 7 (6.82–7.19) Rural 192,141 1027 5.35 (5.02–5.67) 186,732 1403 7.51 (7.12–7.91) Unknown 184,016 500 2.72 (2.48–2.96) 180,378 692 3.84 (3.55–4.12) Income levels Quintile 1 558,314 2689 4.82 (4.63–5.00) 542,450 3825 7.05 (6.83–7.27) Quintile 2 516,131 2560 4.96 (4.77–5.15) 503,177 3441 6.84 (6.61–7.07) Quintile 3 566,360 3097 5.47 (5.28–5.66) 553,016 4140 7.49 (7.26–7.71) Quintile 4 527,626 2508 4.75 (4.57–4.94) 516,050 3499 6.78 (6.56–7.01) Quintile 5 540,007 2554 4.73 (4.55–4.91) 527,737 3351 6.35 (6.13–6.56) Unknown 175,909 475 2.7 (2.46–2.94) 172,312 653 3.79 (3.50–4.08) Acute Coronary syndrome No 2,878,429 13,809 4.8 (4.72–4.88) 2,809,040 18,854 6.71 (6.62–6.81) Yes 5918 74 12.5 (9.66–15.4) 5702 55 9.65 (7.10–12.2) Chronic ischemic heart disease No 2,877,398 13,767 4.78 (4.70–4.86) 2,808,117 18,801 6.7 (6.60–6.79) Yes 6949 116 16.69 (13.7–19.7) 6625 108 16.3 (13.2–19.4) Stroke No 2,877,911 13,792 4.79 (4.71–4.87) 2,808,569 18,824 6.7 (6.61–6.80) Yes 6436 91 14.14 (11.2–17.0) 6173 85 13.77 (10.8–16.7) Diabetes mellitus No 2,856,198 13,164 4.61 (4.53–4.69) 2,788,463 18,256 6.55 (6.45–6.64) Yes 28,149 719 25.54 (23.7–27.4) 26,279 653 24.85 (22.9–26.8) Chronic hypertension No 2,862,222 11,671 4.08 (4.00–4.15) 2,796,074 17,471 6.25 (6.16–6.34) Yes 22,125 2212 99.98 (95.8–104) 18,668 1438 77.03 (73.0–81.0) Hyperthyroidism No 2,813,030 13,316 4.73 (4.65–4.81) 2,745,618 18,231 6.64 (6.54–6.74) Yes 71,317 567 7.95 (7.30–8.60) 69,124 678 9.81 (9.07–10.5) [18, 38–40], and the theory of developmental origins However, none of the hypotheses has been verified. There- of health and disease (DOHaD) that the early life en- fore, higher proportion, almost half of early-onset pre- vironment impacting the risk of chronic disease from eclampsia women in the population warranted further childhood to adulthood [41] could possibly cause the investigation to provide addition insights into the variation population vulnerable to early- or late-onset preeclampsia. of early- and late-onset preeclampsia incidences. You et al. BMC Pregnancy and Childbirth (2018) 18:199 Page 8 of 11 Table 4 Maternal characteristics and clinical risk factors associated with preeclampsia Incidence rate per 1000 births (95%CI) Crude Relative risk P Value Adjusted Relative risk P Value (95%CI) (95%CI) Age at delivery 15–24 7.19 (6.96–7.42) Reference Reference 25–34 10.77 (10.6–10.9) 1.48 (1.43–1.54) < 0.01* 1.49 (1.44-1.55) < 0.01* 35–55 20.78 (20.3–21.2) 2.78 (2.67–2.89) < 0.01* 2.62 (2.51-2.73) < 0.01* Number of prior ≧20 weeks births (parity) 0 12.63 (12.5–12.8) 1.35 (1.32–1.38) < 0.01* 1.71 (1.67-1.76) < 0.01* ≥ 1 9.2 (9.00-9.39) Reference Reference Acute Coronary syndrome No 11.48 (11.4–11.6) Reference Reference Yes 22.28 (18.4–26.1) 1.93 (1.60–2.31) < 0.01* 0.9 (0.74-1.10) 0.32 Chronic ischemic heart disease No 11.45 (11.3–11.6) Reference Reference Yes 33.31 (28.9–37.7) 2.83 (2.46–3.27) < 0.01* 0.9 (0.77-1.06) 0.21 Stroke No 11.46 (11.3–11.6) Reference Reference Yes 28.12 (24.0–32.3) 2.44 (2.09–2.85) < 0.01* 1.33 (1.13-1.58) < 0.01* Diabetes mellitus No 11.12 (11.0–11.2) Reference Reference Yes 51.24 (48.5–53.9) 4.28 (4.02–4.55) < 0.01* 2.01 (1.86-2.16) < 0.01* Chronic hypertension No 10.29 (10.2–10.4) Reference Reference Yes 197.56 (191–204) 15.5 (14.8–16.2) < 0.01* 12.14 (11.5-12.8) < 0.01* Hyperthyroidism No 11.34 (11.2–11.5) Reference Reference Yes 17.77 (16.8–18.8) 1.56 (1.46–1.65) < 0.01* 1.21 (1.14-1.29) < 0.01* Adjusted Relative risk: adjusted with age at delivery, income, urbanization, parity, acute coronary syndrome, chronic ischemic heart disease, stroke, diabetes mellitus, chronic hypertension and hyperthyroidism Acute Coronary syndrome included myocardial infarction and unstable angina *P < 0.05 In the population between 2001 and 2014, our find- had highest ARR in all age groups and demonstrates old ings of the risk factors including advanced maternal age, age was an independent risk factor either in women with primiparity, stroke, diabetes mellitus, chronic hyperten- or without hypertension. The different strength of as- sion, or hyperthyroidism were consistent with commonly sociation among the specific risk factors between quoted clinical factors of preeclampsia [14, 16, 21, 22]. early- and late-onset preeclampsia could be associated The subgroups of women with early- and late-onset pre- with the different pathophysiologic mechanisms including eclampsia were similar in terms of maternal risk factors histology, hemodynamic change, or vascular adaption be- but different association in age, parity, and chronic tween early- and late-onset preeclampsia. Several evidences hypertension. Among the risk factors, advanced mater- supported more typical histological change of defective nal age and chronic hypertension revealed stronger asso- trophoblast invasion and higher percentage of altered uter- ciation with early-onset disease, while primiparity had ine artery Doppler in early-onset disease [18–20]. Cheng et higher risk of late-onset preeclampsia. The findings were al. revealed maternal serum markers associated with car- similar to previous studies [14, 16]. To assess the pos- diovascular inflammatory response such as high-sensitive sible interaction of old age and hypertension. We divided C-reactive protein and homocysteine were significantly women according to different age groups (age 15–25. higher in early-onset preeclampsia, which could be related age 25–35, age 35–55)and women with or without to direct injury to vascular endothelial cells or increased hypertension, respectively [Additional file 3]. In Add- oxidative stress and resulting in the sequence of placenta itional file 3: Table S6 reveals that chronic hypertension dysfunction and poorer outcomes [42]. Despite those You et al. BMC Pregnancy and Childbirth (2018) 18:199 Page 9 of 11 Table 5 Maternal characteristics and clinical risk factors associated with early- and late-onset preeclampsia Early onset preeclampsia Late onset preeclampsia Ratio of Relative P Value risk (95%CI) Crude Relative P Value Adjusted P Value Crude Relative P Value Adjusted P Value risk Relative risk risk Relative risk a a (95%CI) (95%CI) (95%CI) (95%CI) Age at delivery 15–24 Reference Reference Reference Reference Reference 25–34 1.79 (1.69–1.90) < 0.01* 1.73 (1.63-1.84) < 0.01* 1.33 (1.27-1.39) < 0.01* 1.36 (1.30-1.43) < 0.01* 1.27 (1.78-1.37) < 0.01* 35–55 3.84 (3.60–4.10) < 0.01* 3.21 (2.99-3.44) < 0.01* 2.31 (2.19-2.42) < 0.01* 2.28 (2.16-2.40) < 0.01* 1.41 (1.29-1.54) < 0.01* Number of prior ≧20 weeks births (parity) 0 1.06 (1.02–1.09) < 0.01* 1.39 (1.34-1.44) < 0.01* 1.65 (1.59-1.70) < 0.01* 1.95 (1.89-2.02) < 0.01* 0.71 (0.68-0.75) < 0.01* ≥ 1 Reference Reference Reference Reference Reference Acute Coronary syndrome No Reference Reference Reference Reference Reference Yes 2.59 (2.04–3.28) < 0.01* 1 (0.78-1.30) 0.98 1.45 (1.11–1.90) < 0.01* 0.77 (0.58-1.02) 0.07 1.3 (0.89–1.90) 0.09 Chronic ischemic heart disease No Reference Reference Reference Reference Reference Yes 3.44 (2.83–4.17) < 0.01* 0.84 (0.68-1.04) 0.11 2.45 (2.02–2.98) < 0.01* 0.92 (0.74-1.14) 0.45 0.91 (0.67–1.24) 0.28 Stroke No Reference Reference Reference Reference Reference Yes 2.96 (2.37–3.68) < 0.01* 1.33 (1.05-1.68) 0.02* 2.07 (1.67-2.58) < 0.01* 1.28 (1.02-1.61) 0.03* 1.04 (0.75-1.44) 0.4 Diabetes mellitus No Reference Reference Reference Reference Reference Yes 5.34 (4.91–5.81) < 0.01* 1.9 (1.71-2.10) < 0.01* 3.76 (3.46-4.08) < 0.01* 2.03 (1.85-2.23) < 0.01* 0.94 (0.82-1.08) 0.19 Chronic hypertension No Reference Reference Reference Reference Reference Yes 22.73 (21.5–24.0) < 0.01* 16.8 (15.7-18.0) < 0.01* 12.21 (11.5-13.0) < 0.01* 9.85 (9.19-10.6) < 0.01* 1.71 (1.55-1.88) < 0.01* Hyperthyroidism No Reference Reference Reference Reference Reference Yes 1.68 (1.53–1.83) < 0.01* 1.18 (1.07-1.29) < 0.01* 1.48 (1.36-1.60) < 0.01* 1.21 (1.12-1.32) < 0.01* 0.98 (0.86-1.10) 0.34 Adjusted Relative risk: adjusted for with age at delivery, income, urbanization, parity, acute coronary syndrome, chronic ischemic heart disease, stroke, diabetes mellitus, chronic hypertension and hyperthyroidism Acute Coronary syndrome included myocardial infarction and unstable angina *P < 0.05 evidences, there was yet no definite pathophysiology and appeared to be more frequent in patients with high mechanism to explain the development towards early- or body mass index (BMI) compared with early-onset late-onset preeclampsia. Thus, more investigations are disease [19]. However, we had no data of maternal needed to identify the specific correlation between old age BMI to assess and the mechanism between pre- or chronic hypertension and early-onset preeclampsia, and eclampsia and obesity was yet completely understood. clinicians should be aware of preeclampsia prediction in In general, maternal risk factors between early- and women with clinical risk factors, particularly chronic late- onset preeclampsia were similar but old age and hypertension, which had highest risk (ARR, 16.8, 95%CI, chronic hypertension appeared stronger association to 15.7–18.0) of early-onset preeclampsia in the current early-onset disease and primiparity had higher risk of study. Furthermore, early intervention such as aspirin late-onset preeclampsia. prophylaxis may be considered in patients with evidence of This study was the first documented the increasing higher risk, according to the ASPRE trial [43]toprevent trend of preeclampsia in Taiwan between 2001 and severe maternal morbidities and poorer birth outcomes of 2014, predominantly in early-onset disease. The strength early-onset preeclampsia [14, 16, 17]. On the other hand, of the study includes a large cohort sample from a spe- Valensise et al. have found late-onset preeclampsia cific geographic area which is very representative of the You et al. BMC Pregnancy and Childbirth (2018) 18:199 Page 10 of 11 regional population and the large study size provided re- Ethics approval and consent to participate The data collection and analysis of the study was approved by Institutional liability in statistics. Review Board of the Chang Gung Memorial Hospital (IRB No.201600657B0). The consent requirement has been waived according to IRB policy of retrospective chart review study. Conclusions In conclusion, the population-base study showed a rise in Competing interests the incidence of preeclampsia, particularly in early-onset The authors declare that they have no competing interests. disease in Taiwan from 2001 to 2014, suggesting the clin- ical early prediction, identification, and management of Publisher’sNote the diseases will increasingly challenge obstetricians. As Springer Nature remains neutral with regard to jurisdictional claims in increasing number of advanced maternal age and chronic published maps and institutional affiliations. hypertension in delivering population in Taiwan, precon- Author details ceptional counseling and surveillance is warranted in preg- Department of Obstetrics and Gynecology, Chang Gung Memorial Hospital, nant women with higher risk of early-onset preeclampsia. Linkou, Taiwan. Big data research office, Chang Gung Memorial Hospital, Linkou, Taiwan. Division of Rheumatology, Allergy and Immunology, Chang Further study of the predominance of early-onset pre- Gung Memorial Hospital, Linkou, Taiwan. Department of Cardiology, Chang eclampsia in the population and the stronger association Gung Memorial Hospital, Linkou, Taiwan. with old age and hypertension and early-onset preeclamp- Received: 21 November 2017 Accepted: 23 May 2018 sia is required. Additional files References 1. Khan KS, Wojdyla D, Say L, Gulmezoglu AM, Van Look PF. WHO analysis of causes of maternal death: a systematic review. Lancet. 2006;367(9516):1066–74. Additional file 1 Trends of preeclampsia incidence according to 2. Abalos E, Cuesta C, Grosso AL, Chou D, Say L. Global and regional estimates different ages between 2001 and 2014 (blue: 15–25-year-old; red: 25–35- of preeclampsia and eclampsia: a systematic review. Eur J Obstet Gynecol year-old; green:35–55-year-old). (TIF 1329 kb) Reprod Biol. 2013;170(1):1–7. Additional file 2 Trends of preeclampsia incidence according to 3. Duley L. The global impact of pre-eclampsia and eclampsia. Semin women with or without hypertension (orange: women with Perinatol. 2009;33(3):130–7. hypertension; blue: women without hypertension). (TIF 1131 kb) 4. Abalos E, Cuesta C, Carroli G, Qureshi Z, Widmer M, Vogel JP, Souza JP, W.H. Additional file 3 Table S6 Maternal characteristics and clinical risk O.M.S.o. Maternal, and N. Newborn Health Research. Pre-eclampsia, factors associated with preeclampsia by age group. Table S7 Maternal eclampsia and adverse maternal and perinatal outcomes: a secondary characteristics and clinical risk factors associated with preeclampsia by analysis of the World Health Organization Multicountry Survey on Maternal hypertension. (DOCX 22 kb) and Newborn Health. BJOG. 2014;121(Suppl 1):14–24. 5. Roberts CL, Algert CS, Morris JM, Ford JB, Henderson-Smart DJ. Hypertensive disorders in pregnancy: a population-based study. Med J Abbreviations Aust. 2005;182(7):332–5. AAPC: average annual percentage change; ACOG: American College of 6. Paruk F, Moodley J. Maternal and neonatal outcome in early- and late-onset Obstetrician and Gynecologist; ARR: adjusted relative risk; BMI: body mass pre-eclampsia. Semin Neonatol. 2000;5(3):197–207. index; CI: confidence interval; DOHaD: developmental origins of health and 7. Sibai B, Dekker G, Kupferminc M. Pre-eclampsia. Lancet. 2005;365(9461):785–99. disease; ICD-9: International Classification of Diseases, the 9th version; 8. Say L, Chou D, Gemmill A, Tuncalp O, Moller AB, Daniels J, Gulmezoglu AM, ISSHP: International Society for the Study of Hypertension in Pregnancy; Temmerman M, Alkema L. Global causes of maternal death: a WHO NHIRD: National Health Insurance Database; RRR: ratio of relative risk; systematic analysis. Lancet Glob Health. 2014;2(6):e323–33. WHO: World Health Organization 9. Kuklina EV, Ayala C, Callaghan WM. Hypertensive disorders and severe obstetric morbidity in the United States. Obstet Gynecol. 2009;113(6):1299–306. Funding 10. English FA, Kenny LC, McCarthy FP. Risk factors and effective management This work was funded by the National Science Council of Taiwan (project 104- of preeclampsia. Integr Blood Press Control. 2015;8:7–12. 2314-B-182A-047) and Chang Gung Memorial Hospital (project CMRPG3E1961) 11. Dekker G, Sibai B. Primary, secondary, and tertiary prevention of pre- and was supported by the University of Nottingham in methodology and eclampsia. Lancet. 2001;357(9251):209–15. infrastructure. 12. Ness RB, Roberts JM. Heterogeneous causes constituting the single Role of the sponsors: The sponsors of the study, the Chang Gung Memorial syndrome of preeclampsia: a hypothesis and its implications. Am J Obstet Hospital, the National Science Council, the University of Nottingham and the Gynecol. 1996;175(5):1365–70. Arthritis Research UK had no role in design and conduct of the study; 13. von Dadelszen P, Magee LA, Roberts JM. Subclassification of preeclampsia. collection, management, analysis, and interpretation of the data; and Hypertens Pregnancy. 2003;22(2):143–8. preparation, review, or approval of the manuscript and decision to submit 14. Lisonkova S, Joseph KS. Incidence of preeclampsia: risk factors and the manuscript for publication. outcomes associated with early- versus late-onset disease. Am J Obstet Gynecol. 2013;209(6):544 e1–544 e12. Availability of data and materials 15. Lisonkova S, Sabr Y, Mayer C, Young C, Skoll A, Joseph KS. Maternal Chang-Fu Kuo had full access to all the data in the study and takes morbidity associated with early-onset and late-onset preeclampsia. Obstet responsibility for the integrity of the data and the accuracy of the data Gynecol. 2014;124(4):771–81. analysis. The datasets analyzed during the current study are available from 16. Iacobelli S, Bonsante F, Robillard PY. Comparison of risk factors and perinatal the Chang-Fu Kuo on reasonable request. outcomes in early onset and late onset preeclampsia: a cohort based study in Reunion Island. J Reprod Immunol. 2017;123:12–6. Authors’ contributions 17. Madazli R, Yuksel MA, Imamoglu M, Tuten A, Oncul M, Aydin B, Demirayak PHC initiated the concept and designed the study. TTC and CFK collected G. Comparison of clinical and perinatal outcomes in early- and late-onset the data and analyzed the data. SHY wrote the initial manuscript. HMW, PJC, preeclampsia. Arch Gynecol Obstet. 2014;290(1):53–7. and PHC gave critical comments to the study design, interpretation, and 18. Mifsud W, Sebire NJ. Placental pathology in early-onset and late-onset fetal revised the draft. All authors read and approved the final manuscript. growth restriction. Fetal Diagn Ther. 2014;36(2):117–28. You et al. BMC Pregnancy and Childbirth (2018) 18:199 Page 11 of 11 19. 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The association of the placental MTHFR 3'-UTR polymorphisms, promoter methylation and MTHFR expression with preeclampsia. J Cell Biochem. 2018;119(2):346–1354. 41. Bianco-Miotto T, Craig JM, Gasser YP, van Dijk SJ, Ozanne SE. Epigenetics and DOHaD: from basics to birth and beyond. J Dev Orig Health Dis. 2017;8(5):513–9. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png BMC Pregnancy and Childbirth Springer Journals

Population-based trends and risk factors of early- and late-onset preeclampsia in Taiwan 2001–2014

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Medicine & Public Health; Reproductive Medicine; Maternal and Child Health; Gynecology
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Abstract

Background: Preeclampsia, a multisystem disorder in pregnancies complicates with maternal and fetal morbidity. Early- and late-onset preeclampsia, defined as preeclampsia developed before and after 34 weeks of gestation, respectively. The early-onset disease was less prevalent but associated with poorer outcomes. Moreover, the risk factors between early -and late- onset preeclampsia could be differed owing to the varied pathophysiology. In the study, we evaluated the incidences, trends, and risk factors of early- and late- onset preeclampsia in Taiwan. Methods: This retrospective population-based cohort study included all ≧20 weeks singleton pregnancies resulting in live-born babies or stillbirths in Taiwan between January 1, 2001 and December 31, 2014 (n = 2,884,347). The data was collected electronically in Taiwanese Birth Register and National Health Insurance Research Database. The incidences and trends of early- and late-onset preeclampsia were assessed through Joinpoint analysis. Multivariate logistic regression was used to analyze the risk factors of both diseases. Results: The age-adjusted overall preeclampsia rate was slightly increased from 1.1%(95%confidence interval [CI], 1. 1–1.2) in 2001 to 1.3% (95%CI, 1.2–1.3) in 2012 with average annual percentage change (AAPC) 0.1%/year (95%CI, 0–0.2%). However, the incidence was remarkably increased from 1.3% (95%CI, 1.3–1.4) in 2012 to 1.7% (95%CI, 1.6–1. 8) in 2014 with AAPC 1.3%/year (95%CI,0.3–2.5). Over the study period, the incidence trend in late-onset preeclampsia was steadily increasing from 0.7% (95%CI, 0.6–0.7) in 2001 to 0.9% (95%CI, 0.8–0.9) in 2014 with AAPC 0.2%/year (95%CI, 0.2–0.3) but in early-onset preeclampsia was predominantly increase from 0.5% (95%CI, 0.4–0.5) in 2012 to 0.8% (95%CI, 0.8–0.9) in 2014 with AAPC 2.3%/year (95%CI, 0.8–4.0). Advanced maternal age, primiparity, stroke, diabetes mellitus, chronic hypertension, and hyperthyroidism were risk factors of preeclampsia. Comparing early- and late-onset diseases, chronic hypertension (ratio of relative risk [RRR], 1.71; 95%CI, 1.55–1.88) and older age (RRR, 1.41; 95%CI 1.29–1.54) were more strongly associated with early-onset disease, whereas primiparity (RRR 0.71, 95%CI, 0.68–0.75) had stronger association with late-onset preeclampsia. Conclusions: The incidences of overall, and early- and late-onset preeclampsia were increasing in Taiwan from 2001 to 2014, predominantly for early-onset disease. Pregnant women with older age and chronic hypertension had significantly higher risk of early-onset preeclampsia. Keywords: Preeclampsia, Incidence, Risk factors, Early onset, Late onset, Hypertension * Correspondence: danielwu@cgmh.org.tw; taipei.chu@gmail.com Department of Obstetrics and Gynecology, Chang Gung Memorial Hospital, Linkou, Taiwan Department of Cardiology, Chang Gung Memorial Hospital, Linkou, Taiwan Full list of author information is available at the end of the article © The Author(s). 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. You et al. BMC Pregnancy and Childbirth (2018) 18:199 Page 2 of 11 Background early-onset disease, whereas women with nulliparity and Worldwide 2.0 to 8.0% pregnancies were complicated by diabetes mellitus had higher risk to develop late-onset preeclampsia [1–5] with variation across regions [2]. Pre- disease [14]. The other study conducted by Iacobelli et eclampsia, the progressive disorder during pregnancy is al. showed older age and higher prevalence of chronic strongly associated with maternal and fetal complications hypertension in the group of early-onset disease [16]. including eclampsia, acute renal failure, coagulopathy, pla- The incidence of preeclampsia in Taiwan was signifi- centa abruption, postpartum hemorrhage, intrauterine cantly increased from 0.87 to 1.21% between 1998 and growth restriction, medically indicated preterm birth, and 2010 [25]. However, there was limited data of early- and maternal and fetal death [1, 6, 7]. In a systemic analysis late-onset preeclampsia rate and the associated factors from World Health Organization (WHO), hypertensive in Taiwan has not been determined yet. The aim of the disorders including preeclampsia accounted for 14.0% ma- study was to investigate the population-based trends of ternal death between 2003 and 2009 [8]. Moreover, the early- and late-onset preeclampsia and examine the ma- risk of severe obstetric morbidities in women with ternal risk factors in Taiwanese population. eclampsia or severe preeclampsia was increasing [9]. Al- though most of the maternal dysfunctions resolved grad- Methods ually in postpartum, these women were at higher risk of Study design and data source developing chronic hypertension, recurrent preeclampsia The population-based cohort study retrospectively in- in the next pregnancy, and later-life cardiovascular dis- cluded all ≧20 weeks singleton deliveries, comprising live eases [10]. births and stillbirths in Taiwan from January 1, 2001 to Preeclampsia is recognized as a heterogenous syn- December 31, 2014. Two databases were used to obtain drome with different pathophysiology and be divided in data electronically in this study. One was Taiwanese two subtypes according to the disease onset [7, 11, 12]. birth registration system in Health Promotion Adminis- Early-onset preeclampsia, diagnosed less than 34 gesta- tration, Ministry of Health and Welfare (https:// tional weeks was less prevalent than late-onset pre- www.hpa.gov.tw/EngPages/Index.aspx), which included eclampsia, occurring at 34 or more weeks of gestation information of birth date, gestational age, and fetal [13]. The incidences of early- and late-onset preeclamp- weights of all neonates and stillbirths with gestational age sia were 0.3 and 2.7%, respectively [14, 15]; nevertheless, ≧20 weeks. Another was National Health Insurance Data- the early-onset disease contributed to more unfavorable base (NHIRD, https://nhird.nhri.org.tw/en/index.html), maternal and fetal outcomes [14, 16, 17]. Around which could be linked from Taiwanese birth registration ten-fold increased risk of perinatal death and maternal system for details of maternal general data and diagnosis. death in women with early-onset preeclampsia and two- Both databases have been encrypted to generate the fold higher risk of perinatal death and threefold in- unique identification to anonymous identification. creased risks of maternal death in women with In Taiwan, birth certificates of all neonates and still- late-onset disease were observed, comparing with normal births with gestational age ≧20 weeks or gestational age pregnancy [14, 15]. In addition, some studies showed bio- < 20 weeks but fetal birth weights ≧500 g are issued at logical variations and different spectrums of pathophysi- the hospital or medical institution and registered in the ology between early- and late-onset preeclampsia [18–20]. Ministry of Health and Welfare. The birth register can Clinical factors associated with risk of preeclampsia in- be linked to NHIRD, which was a database contained in- cluded primiparity, advanced maternal age, previous pre- formation of insured people, including demographic eclampsia, family history of preeclampsia, multiple data, dates of hospitalization and clinical visits, and diag- gestation, obesity, African-American race, diabetes melli- nostic codes as International Classification of Diseases, tus, chronic hypertension, chronic renal disease, and the 9th version (ICD-9) during the study period. presence of antiphospholipid antibodies were identified [21, 22]. Besides, there were evidences that stroke and Participants hyperthyroidism increased the risk of preeclampsia [23, There were 2,973,989 registered deliveries in Taiwan 24]. Further studies comparing predisposing factors of from January 1, 2001 to December 31, 2014. Women early- versus late-onset preeclampsia demonstrated simi- who were younger than 15-year-old or older than lar risk factors but the strengths of association were 55-year-old, with multiple gestation including twins, differed among the factors. There were only two triplets, or quadruplets, and with gestational age at deliv- population-based studies, to our knowledge to evaluate ery less than 20 weeks were excluded. To identify the in- each risk factor between early- and late-onset pre- cidences of early- and late-onset preeclampsia, all the eclampsia [14, 16]. One study, carried out by Lisonkova included delivers were categorized to ongoing pregnancy et al. revealed African-American race, chronic hyperten- at 20 weeks of gestation and 34 weeks of gestation ac- sion, and older age were more strongly associated with cording to the gestational age at delivery, and each of You et al. BMC Pregnancy and Childbirth (2018) 18:199 Page 3 of 11 which were the denominators of early- and late-onset (urban, suburban, rural), income (quintiles 1 to 5), and preeclampsia rate, respectively [14, 15, 26]. clinical factors associated with risk of preeclampsia were The diagnostic criteria of preeclampsia was two occa- examined for potential variables [14, 16, 22–24, 28, 29]. sions of hypertension at least 140/90 mmHg after The clinical factors were identified in NHIRD, including 20 weeks of gestation accompanied by proteinuria > acute coronary syndrome (ICD-9 codes, 410, 412 and 300 mg/day or ≧1+ on dipstick based on International 413), chronic ischemic heart disease (ICD-9 codes, 4140, Society for the Study of Hypertension in Pregnancy 4148 and 4149), stroke (ICD-9 codes, 43,301, 43,311, (ISSHP) by 2014 [10, 26, 27]. All included delivers asso- 43,321, 43,331, 43,381, 43,391, 43,401, 43,411, 43,491, ciated with diagnosis of preeclampsia were identified 435, 436, 4371, 4379 and 438), diabetes mellitus (ICD-9, from NHIRD ICD-9 diagnostic codes 642.4, 6424.5, 250), chronic hypertension (ICD-9 codes, 401–405) and 6424.6, and 6424.7 [14, 15]. To obtain the gestational hyperthyroidism (ICD-9 codes, 242). week of onset of preeclampsia for determing early- and late-onset preeclampsia, which were occurring less than Statistical analysis and later than 34 weeks of gestation, the date of diagno- Thestandardizedpreeclampsiaincidence wasadjusted sis was subtracted from the date at delivery, and calcu- based on the age distribution in 2014 and 95% confi- lated the gestational age according to the information of dence intervals (CI) were derived from the Poisson gestational weeks at birth in birth registers. A flow chart distribution. The linear trends in proportion were illustrating patient inclusion is showed in Fig. 1. The assessed using Joinpoint Regression Program version study was approved by Institutional Review Board of the 4.2.0.2 (National Cancer Institute, Bethesda, MD, Chang Gung Memorial Hospital (IRB No.201600657B0). USA) to estimate temporal trends in standardized in- cidence of preeclampsia. Bayesian information criter- Definition of variables ion was used to generate ‘joinpoints’ over time Maternal characteristics including maternal age (15–24, according to the changes of trend and average annual 25–34, and 35–55 years old), parity (number of percentage change (AAPC) and 95%CI for each seg- prior≧20 weeks births, 0 vs. ≧1), place of residence ment were calculated. Fig. 1 Flow chart of the study You et al. BMC Pregnancy and Childbirth (2018) 18:199 Page 4 of 11 Multivariate logistic regression was used to obtain ad- chronic ischemic heart disease were not significantly justed relative risks (ARR) and 95% CIs adjusted for the associated with preeclampsia. The ARR of each clin- variables including maternal characteristics and clinical ical factor of overall preeclampsia are displayed in factors to examine the association with preeclampsia. Table 4. Of note, women with chronic hypertension The association between the clinical risk factors and had much higher risk of preeclampsia (ARR, 12.1; early- or late-onset preeclampsia was further compared 95%CI, 11.5–12.8). through the ratio of relative risks (RRR). Analyses were For subgroup analysis of early- and late-onset pre- carried out using SAS, version 9.4 (SAS Institute, Cary, eclampsia, the clinical factors associated with early- or NC, USA). A 2-tailed P < 0.05 was considered significant. late-onset diseases were identical to overall preeclamp- All tests of statistical hypothesis were done on the sia, detailed in Table 5. To compare the strength of the 2-sided 5% level of significance. association among the risk factors between early- and late-onset preeclampsia, RRR of each clinical factor was Results calculated according to the ARR of early- and late pre- Among 2,973,989 delivers over the 14 years period, eclampsia. Advanced maternal age (> 35 years) (RRR, 2,884,347 delivers were included and 32,742 preeclamp- 1.4; 95%CI, 1.3–1.5, p < 0.01) and chronic hypertension sia events were identified. The subgroups of early- and (RRR, 1.7; 95%CI, 1.6–1.9, p < 0.01) had higher risk to late- onset preeclampsia were 13,833 (42.3%) and 18,909 develop early-onset preeclampsia. In the contrary, primi- (57.6%) deliveries, respectively (Fig. 1). parity (RRR, 0.7; 95%CI, 0.7–0.8, p < 0.01) was more The overall preeclampsia incidence increased from strongly associated with late-onset disease. Other risk 1.1% (95%CI, 1.1–1.2) in 2001 to 1.7% (95%CI, 1.6–1.8) factors of preeclampsia including diabetes mellitus, in 2014. Table 1 reveals crude and age-adjusted overall stroke, and hyperthyroidism revealed no statistical differ- preeclampsia rates each year in the study period. The ence in the association of early- and late-onset pre- analysis of the overall, early-onset, and late-onset inci- eclampsia (Table 5). dence trends through average annual percentage change is presented in Table 2. The overall preeclampsia rate Discussion was slightly increased from 1.1% (95%CI, 1.1–1.2) in The incidences of overall, and early- and late-onset 2001 to 1.3% (95%CI, 1.2–1.3) in 2012 with average an- preeclampsia were increasing in Taiwan between nual percentage change (AAPC) 0.1%/year (95%CI, 0– 2001 and 2014, predominantly for early-onset disease. 0.2%). However, the incidence was remarkably increased Pregnant women with advanced maternal age, primi- from 1.3% (95%CI, 1.3–1.4) in 2012 to 1.7% (95%CI, parity, chronic hypertension, stroke, diabetes mellitus, 1.6–1.8) in 2014 with AAPC 1.3%/year (95%CI,0.3–2.5). and hyperthyroidism had significantly higher risk of Over the 14 years study period, the incidence trends in developing preeclampsia. Among the factors, older age late-onset preeclampsia was steadily increasing from and hypertension were more strongly associated with 0.7% (95%CI, 0.6–0.7) in 2001 to 0.9% (95%CI, 0.8–0.9) early-onset disease. in 2014 with AAPC 0.2%/year (95%CI, 0.2–0.3). How- Our study has certain limitations. First, overall pre- ever, in early-onset preeclampsia, similar to the trend of eclampsia was identified by diagnostic codes; thus, the overall preeclampsia, the incidence was relatively steady artificial coding error and misclassification bias could around 0.5% (95%CI, 0.4–0.5) in 2001 and 0.5% (95%CI, not be avoided. Second, NHIRD included 99% of Tai- 0.5–0.6) in 2012 but predominantly increase from 0.5% wanese residents, which led to around 1.2% deliveries in (95%CI, 0.4–0.5) in 2012 to 0.8% (95%CI, 0.8–0.9) in birth registration not be linked to hospital records. The 2014 with AAPC 2.3%/year (95%CI, 0.8–4.0). Figure 2 il- missing data could be susceptible to underascertain- lustrates the trends in overall preeclampsia, early-onset, ment, resulting in slightly underestimation of the inci- and late-onset disease. dence. Third, if a patient had neither antenatal exam nor Maternal characteristics (age, parity, place of resi- delivered in hospitals, or developed postpartum pre- dence, and income) and clinical factors (acute coronary eclampsia without hospitalization, the diagnostic code syndrome, chronic ischemic heart disease, stroke, dia- could not be obtained from the hospital record. The betes mellitus, chronic hypertension, and hyperthyroid- such undetermined were few and less severe but may ism) are described in Table 3. In multivariate logistic cause underestimation as well. Fourth, we did not clas- regression, all maternal characteristics and clinical fac- sify the severity of preeclampsia or determine the sub- tors listed in Table 3 were adjusted as possible con- group using aspirin for prevention, both of which may founders. Women with older age, nulliparity, chronic give more information to interpretate the trends of pre- hypertension, diabetes mellitus, stroke, and hyperthy- eclampsia. In addition, we failed to assess certain risk roidism were more likely to develop preeclampsia (all p factors including BMI, preeclampsia history in prior values< 0.01), while acute coronary syndrome and pregnancy, and family history of preeclampsia, as well as You et al. BMC Pregnancy and Childbirth (2018) 18:199 Page 5 of 11 Table 1 Preeclampsia incidence between January 1, 2001 and December 31, 2014 (n = 2,884,347) Total Early onset Late onset Year Total No of Crude IR, per Standardised Ongoing pregnancies at No of Crude IR, per Standardised Ongoing pregnancies at No of Crude IR, per Standardised Delivery (n) event 1000 births IR, per 1000 20 weeks (n) event 1000 births IR, per 1000 34 weeks (n) event 1000 births IR, per 1000 (95% CI) births (95% CI) births (95% CI) births (95%CI) (95%CI) (95%CI) 2001 243,357 2150 8.83 (8.46– 11.1 (10.5– 243,357 838 3.44 (3.21– 4.68 (4.31– 237,933 1312 5.51 (5.22– 6.56 (6.13– 9.21) 11.6) 3.68) 5.05) 5.81) 6.98) 2002 237,134 2186 9.22 (8.83– 11.6 (11.0– 237,134 950 4.01 (3.75– 5.37 (4.97– 231,862 1236 5.33 (5.03– 6.36 (5.93– 9.60) 12.1) 4.26) 5.76) 5.63) 6.78) 2003 221,232 2077 9.39 (8.98– 11.9 (11.3– 221,232 843 3.81 (3.55– 5.16 (4.76– 216,470 1234 5.70 (5.38– 6.88 (6.43– 9.79) 12.5) 4.07) 5.56) 6.02) 7.33) 2004 213,433 2014 9.44 (9.02– 11.7 (11.2– 213,433 839 3.93 (3.66– 5.10 (4.71– 208,461 1175 5.64 (5.31– 6.82 (6.37– 9.85) 12.3) 4.20) 5.49) 5.96) 7.27) 2005 203,137 1950 9.60 (9.17– 11.7 (11.1– 203,137 765 3.77 (3.50– 4.89 (4.51– 198,580 1185 5.97 (5.63– 6.98 (6.54– 10.0) 12.3) 4.03) 5.27) 6.31) 7.43) 2006 201,335 2306 11.5 (11.0– 13.3 (12.7– 201,335 968 4.81 (4.51– 5.76 (5.36– 196,617 1338 6.81 (6.44– 7.76 (7.30– 11.9) 13.9) 5.11) 6.16) 7.17) 8.23) 2007 199,389 2278 11.4 (11.0– 12.7 (12.1– 199,389 961 4.82 (4.51– 5.61 (5.22– 194,687 1317 6.76 (6.40– 7.27 (6.85– 11.9) 13.3) 5.12) 5.99) 7.13) 7.70) 2008 192,819 2086 10.8 (10.4– 11.9 (11.4– 192,819 891 4.62 (4.32– 5.22 (4.85– 188,125 1195 6.35 (5.99– 6.86 (6.45– 11.3) 12.4) 4.92) 5.58) 6.71) 7.28) 2009 188,735 2192 11.6 (11.1– 12.7 (12.2– 188,735 943 5.00 (4.68– 5.58 (5.21– 184,184 1249 6.78 (6.41– 7.32 (6.90– 12.1) 13.3) 5.32) 5.95) 7.16) 7.75) 2010 162,932 1927 11.8 (11.3– 12.4 (11.8– 162,932 801 4.92 (4.58– 5.23 (4.86– 158,724 1126 7.09 (6.68– 7.38 (6.94– 12.4) 13.0) 5.26) 5.60) 7.51) 7.82) 2011 194,095 2460 12.7 (12.2– 13.3 (12.7– 194,095 969 4.99 (4.68– 5.31 (4.97– 189,049 1491 7.89 (7.49– 8.18 (7.76– 13.2) 13.8) 5.31) 5.65) 8.29) 8.60) 2012 228,774 2885 12.6 (12.2– 13.0 (12.5– 228,774 1204 5.26 (4.97– 5.48 (5.17– 223,249 1681 7.53 (7.17– 7.73 (7.36– 13.1) 13.5) 5.56) 5.79) 7.89) 8.10) 2013 191,022 2775 14.5 (14.0– 14.6 (14.1– 191,022 1185 6.20 (5.85– 6.26 (5.91– 185,916 1590 8.55 (8.13– 8.59 (8.17– 15.1) 15.2) 6.56) 6.62) 8.97) 9.02) 2014 206,953 3506 16.9 (16.4– 16.9 (16.4– 206,953 1726 8.34 (7.95– 8.34 (7.95– 200,885 1780 8.86 (8.45– 8.86 (8.45– 17.5) 17.5) 8.73) 8.73) 9.27) 9.27) Abbreviation: IR incidence rate You et al. BMC Pregnancy and Childbirth (2018) 18:199 Page 6 of 11 Table 2 Joinpoint analysis of trend of preeclampsia incidence in Taiwan between 2001 and 2014 Standardised IR, per 1000 births AAPC Trend 1 Trend 2 2001 2014 Year AAPC (95%CI) Year AAPC (95%CI) Trend of entire cohort 11.1 (10.5–11.6) 16.9 (16.4–17.5) 3.01 (1.50 to 4.54)* 2001–2012 1.25 (0.36 to 2.14)* 2012–2014 13.3 (2.55 to 25.1) * by onset weeks < 34 weeks 4.68 (4.31–5.05) 8.34 (7.95–8.73) 3.67 (1.67 to 5.72)* 2001–2012 0.58 (− 0.63 to 1.80) 2012–2014 22.5 (7.50 to 39.6) * ≥ 34 weeks 6.56 (6.13–6.98) 8.86 (8.45–9.27) 2.21 (1.51 to 2.91)* AAPC average annual percent change *P < 0.05 the maternal and neonatal outcomes due to limited incidence of preeclampsia in the population-based study information. was thoroughly informative. The overall preeclampsia rate in Taiwan was relatively Our data suggested that the trend of preeclampsia was lower than the worldwide studies though, 42.3% pre- increasing between 2001 and 2014 after age ajustment, eclampsia events identified as early-onset disease was re- especially in early-onset disease from 2012 to 2014. We markable. The incidence of preeclampsia was 1.1 to 1.7% analyzed the subgroup trends of preeclampsia depend in Taiwan compared with 2 to 8% incidence of pre- on maternal age and women with or without hyperten- eclampsia worldwide with regional variations [2]. The sion, respectively [Additional file 1 and Additional file 2]. lower incidence could be owing to the majority of Asian Additional file 1 shows increased trend in all three age race in the population, which had lower risk of develop- groups (age 15–25, 25–35, and 35–55). However, Add- ing preeclampsia, 2.0–3.0%according to previous studies itional file 2 reveals no significant incidence change in [26, 30]. We did not collect data of races in this study women with our without hypertension during the study but over 95% of the population is Han Chinese, who are period. The subgroup analysis indicated that the increas- regarded as East Asian ethnic group based on the data ing trend of preeclampsia occurred in all age groups and in Ministry of Interior. Besides, there could possibly be possibly the growing number of women with hyperten- slight underestimation because of missing data in sion. Interestingly, the rise rate of preeclampsia was not NHIRD or the artificial bias of disease coding. Neverthe- universally consistent, for instance, studies for the entire less, NHIRD was one of the powerful tools in assessment USA from 1999 to 2004 showed plateaued rate [32] and of the epidemiology in Taiwan because of the high in Western New York from 1999 to 2003 [33] and Euro- coverage of National Health Insurance program, finan- pean countries during the past ten years [34] reported cing around 99% Taiwanese residents [31]. In the slight declines in preeclampsia. However, the increase in current study, the unidentified anonymous identification preeclampsia in our population could partially affected between birth register system and NHIRD was around by the revision of diagnostic criteria. American College 1.2%. In addition, compared with the study by Chan et al., of Obstetrician and Gynecologist (ACOG) in2013 and who revealed the increased incidence of preeclampsia in ISSHP in 2014 have excluded proteinuria as an necessary Taiwan was notable from 0.87 to 1.21% between 1998 and condition to establish diagnosis of preeclampsia in 2010 [25]. Therefore, the interpretation of exact pre- women presence of organ dysfunction of uteroplacental eclampsia rate could be somewhat underestimated owing dysfunction [35, 36]. Therefore, the observation of sig- to the unavoidable bias but the persisted increasing nificant rise in early-onset preeclampsia from 2012 to 2014 in this study was a conservative indication of in- creasing trend but the true percentage change should be followed since overall revision of the criteria in Taiwan. The proportion of early-onset preeclampsia was sig- nificantly higher (42.3% in early-onset and 57.6% in late onset disease) than previous studies conducted other than Taiwan [14–16], about twofold to nine-fold of late-onset disease than early-onset preeclampsia. The difference could attributed to increasing prevalence of chronic hypertension as a result of a surge of risk rates of prehypertension, obesity and metabolic syndrome in Taiwan [37]. Genetic variation or epigenetic regula- Fig. 2 Trends in overall, early-onset, and late-onset preeclampsia tion such as DNA methylation or microRNA expres- between 2001 and 2014 sion associated with preeclampsia in the population You et al. BMC Pregnancy and Childbirth (2018) 18:199 Page 7 of 11 Table 3 Maternal characteristics and clinical factors associated with early- and late-onset preeclampsia Characteristics Ongoing pregnancies at 20 weeks Early-onset preeclampsia Ongoing pregnancies at 34 weeks Late-onset preeclampsia n = 2,884,347 n = 13,883 Rate per 1000 n = 2,814,742 n = 18,909 Rate per 1000 (95% CI) (95% CI) Age at delivery 15–24 525,457 1305 2.48 (2.35–2.62) 513,581 2447 4.76 (4.58–4.95) 25–34 1,956,147 8688 4.44 (4.35–4.53) 1,914,210 12,155 6.35 (6.24–6.46) 35–55 402,743 3890 9.66 (9.36–9.96) 386,951 4307 11.13 (10.8–11.5) Number of prior ≧20 weeks births (parity) 0 1,938,341 9559 4.93 (4.83–5.03) 1,893,197 14,611 7.72 (7.59–7.84) ≥ 1 946,006 4324 4.57 (4.43–4.71) 921,545 4298 4.66 (4.52–4.80) Place of residence Urban 1681,534 7988 4.75 (4.65–4.85) 1,641,570 11,169 6.8 (6.68–6.93) Suburban 826,656 4368 5.28 (5.13–5.44) 806,062 5645 7 (6.82–7.19) Rural 192,141 1027 5.35 (5.02–5.67) 186,732 1403 7.51 (7.12–7.91) Unknown 184,016 500 2.72 (2.48–2.96) 180,378 692 3.84 (3.55–4.12) Income levels Quintile 1 558,314 2689 4.82 (4.63–5.00) 542,450 3825 7.05 (6.83–7.27) Quintile 2 516,131 2560 4.96 (4.77–5.15) 503,177 3441 6.84 (6.61–7.07) Quintile 3 566,360 3097 5.47 (5.28–5.66) 553,016 4140 7.49 (7.26–7.71) Quintile 4 527,626 2508 4.75 (4.57–4.94) 516,050 3499 6.78 (6.56–7.01) Quintile 5 540,007 2554 4.73 (4.55–4.91) 527,737 3351 6.35 (6.13–6.56) Unknown 175,909 475 2.7 (2.46–2.94) 172,312 653 3.79 (3.50–4.08) Acute Coronary syndrome No 2,878,429 13,809 4.8 (4.72–4.88) 2,809,040 18,854 6.71 (6.62–6.81) Yes 5918 74 12.5 (9.66–15.4) 5702 55 9.65 (7.10–12.2) Chronic ischemic heart disease No 2,877,398 13,767 4.78 (4.70–4.86) 2,808,117 18,801 6.7 (6.60–6.79) Yes 6949 116 16.69 (13.7–19.7) 6625 108 16.3 (13.2–19.4) Stroke No 2,877,911 13,792 4.79 (4.71–4.87) 2,808,569 18,824 6.7 (6.61–6.80) Yes 6436 91 14.14 (11.2–17.0) 6173 85 13.77 (10.8–16.7) Diabetes mellitus No 2,856,198 13,164 4.61 (4.53–4.69) 2,788,463 18,256 6.55 (6.45–6.64) Yes 28,149 719 25.54 (23.7–27.4) 26,279 653 24.85 (22.9–26.8) Chronic hypertension No 2,862,222 11,671 4.08 (4.00–4.15) 2,796,074 17,471 6.25 (6.16–6.34) Yes 22,125 2212 99.98 (95.8–104) 18,668 1438 77.03 (73.0–81.0) Hyperthyroidism No 2,813,030 13,316 4.73 (4.65–4.81) 2,745,618 18,231 6.64 (6.54–6.74) Yes 71,317 567 7.95 (7.30–8.60) 69,124 678 9.81 (9.07–10.5) [18, 38–40], and the theory of developmental origins However, none of the hypotheses has been verified. There- of health and disease (DOHaD) that the early life en- fore, higher proportion, almost half of early-onset pre- vironment impacting the risk of chronic disease from eclampsia women in the population warranted further childhood to adulthood [41] could possibly cause the investigation to provide addition insights into the variation population vulnerable to early- or late-onset preeclampsia. of early- and late-onset preeclampsia incidences. You et al. BMC Pregnancy and Childbirth (2018) 18:199 Page 8 of 11 Table 4 Maternal characteristics and clinical risk factors associated with preeclampsia Incidence rate per 1000 births (95%CI) Crude Relative risk P Value Adjusted Relative risk P Value (95%CI) (95%CI) Age at delivery 15–24 7.19 (6.96–7.42) Reference Reference 25–34 10.77 (10.6–10.9) 1.48 (1.43–1.54) < 0.01* 1.49 (1.44-1.55) < 0.01* 35–55 20.78 (20.3–21.2) 2.78 (2.67–2.89) < 0.01* 2.62 (2.51-2.73) < 0.01* Number of prior ≧20 weeks births (parity) 0 12.63 (12.5–12.8) 1.35 (1.32–1.38) < 0.01* 1.71 (1.67-1.76) < 0.01* ≥ 1 9.2 (9.00-9.39) Reference Reference Acute Coronary syndrome No 11.48 (11.4–11.6) Reference Reference Yes 22.28 (18.4–26.1) 1.93 (1.60–2.31) < 0.01* 0.9 (0.74-1.10) 0.32 Chronic ischemic heart disease No 11.45 (11.3–11.6) Reference Reference Yes 33.31 (28.9–37.7) 2.83 (2.46–3.27) < 0.01* 0.9 (0.77-1.06) 0.21 Stroke No 11.46 (11.3–11.6) Reference Reference Yes 28.12 (24.0–32.3) 2.44 (2.09–2.85) < 0.01* 1.33 (1.13-1.58) < 0.01* Diabetes mellitus No 11.12 (11.0–11.2) Reference Reference Yes 51.24 (48.5–53.9) 4.28 (4.02–4.55) < 0.01* 2.01 (1.86-2.16) < 0.01* Chronic hypertension No 10.29 (10.2–10.4) Reference Reference Yes 197.56 (191–204) 15.5 (14.8–16.2) < 0.01* 12.14 (11.5-12.8) < 0.01* Hyperthyroidism No 11.34 (11.2–11.5) Reference Reference Yes 17.77 (16.8–18.8) 1.56 (1.46–1.65) < 0.01* 1.21 (1.14-1.29) < 0.01* Adjusted Relative risk: adjusted with age at delivery, income, urbanization, parity, acute coronary syndrome, chronic ischemic heart disease, stroke, diabetes mellitus, chronic hypertension and hyperthyroidism Acute Coronary syndrome included myocardial infarction and unstable angina *P < 0.05 In the population between 2001 and 2014, our find- had highest ARR in all age groups and demonstrates old ings of the risk factors including advanced maternal age, age was an independent risk factor either in women with primiparity, stroke, diabetes mellitus, chronic hyperten- or without hypertension. The different strength of as- sion, or hyperthyroidism were consistent with commonly sociation among the specific risk factors between quoted clinical factors of preeclampsia [14, 16, 21, 22]. early- and late-onset preeclampsia could be associated The subgroups of women with early- and late-onset pre- with the different pathophysiologic mechanisms including eclampsia were similar in terms of maternal risk factors histology, hemodynamic change, or vascular adaption be- but different association in age, parity, and chronic tween early- and late-onset preeclampsia. Several evidences hypertension. Among the risk factors, advanced mater- supported more typical histological change of defective nal age and chronic hypertension revealed stronger asso- trophoblast invasion and higher percentage of altered uter- ciation with early-onset disease, while primiparity had ine artery Doppler in early-onset disease [18–20]. Cheng et higher risk of late-onset preeclampsia. The findings were al. revealed maternal serum markers associated with car- similar to previous studies [14, 16]. To assess the pos- diovascular inflammatory response such as high-sensitive sible interaction of old age and hypertension. We divided C-reactive protein and homocysteine were significantly women according to different age groups (age 15–25. higher in early-onset preeclampsia, which could be related age 25–35, age 35–55)and women with or without to direct injury to vascular endothelial cells or increased hypertension, respectively [Additional file 3]. In Add- oxidative stress and resulting in the sequence of placenta itional file 3: Table S6 reveals that chronic hypertension dysfunction and poorer outcomes [42]. Despite those You et al. BMC Pregnancy and Childbirth (2018) 18:199 Page 9 of 11 Table 5 Maternal characteristics and clinical risk factors associated with early- and late-onset preeclampsia Early onset preeclampsia Late onset preeclampsia Ratio of Relative P Value risk (95%CI) Crude Relative P Value Adjusted P Value Crude Relative P Value Adjusted P Value risk Relative risk risk Relative risk a a (95%CI) (95%CI) (95%CI) (95%CI) Age at delivery 15–24 Reference Reference Reference Reference Reference 25–34 1.79 (1.69–1.90) < 0.01* 1.73 (1.63-1.84) < 0.01* 1.33 (1.27-1.39) < 0.01* 1.36 (1.30-1.43) < 0.01* 1.27 (1.78-1.37) < 0.01* 35–55 3.84 (3.60–4.10) < 0.01* 3.21 (2.99-3.44) < 0.01* 2.31 (2.19-2.42) < 0.01* 2.28 (2.16-2.40) < 0.01* 1.41 (1.29-1.54) < 0.01* Number of prior ≧20 weeks births (parity) 0 1.06 (1.02–1.09) < 0.01* 1.39 (1.34-1.44) < 0.01* 1.65 (1.59-1.70) < 0.01* 1.95 (1.89-2.02) < 0.01* 0.71 (0.68-0.75) < 0.01* ≥ 1 Reference Reference Reference Reference Reference Acute Coronary syndrome No Reference Reference Reference Reference Reference Yes 2.59 (2.04–3.28) < 0.01* 1 (0.78-1.30) 0.98 1.45 (1.11–1.90) < 0.01* 0.77 (0.58-1.02) 0.07 1.3 (0.89–1.90) 0.09 Chronic ischemic heart disease No Reference Reference Reference Reference Reference Yes 3.44 (2.83–4.17) < 0.01* 0.84 (0.68-1.04) 0.11 2.45 (2.02–2.98) < 0.01* 0.92 (0.74-1.14) 0.45 0.91 (0.67–1.24) 0.28 Stroke No Reference Reference Reference Reference Reference Yes 2.96 (2.37–3.68) < 0.01* 1.33 (1.05-1.68) 0.02* 2.07 (1.67-2.58) < 0.01* 1.28 (1.02-1.61) 0.03* 1.04 (0.75-1.44) 0.4 Diabetes mellitus No Reference Reference Reference Reference Reference Yes 5.34 (4.91–5.81) < 0.01* 1.9 (1.71-2.10) < 0.01* 3.76 (3.46-4.08) < 0.01* 2.03 (1.85-2.23) < 0.01* 0.94 (0.82-1.08) 0.19 Chronic hypertension No Reference Reference Reference Reference Reference Yes 22.73 (21.5–24.0) < 0.01* 16.8 (15.7-18.0) < 0.01* 12.21 (11.5-13.0) < 0.01* 9.85 (9.19-10.6) < 0.01* 1.71 (1.55-1.88) < 0.01* Hyperthyroidism No Reference Reference Reference Reference Reference Yes 1.68 (1.53–1.83) < 0.01* 1.18 (1.07-1.29) < 0.01* 1.48 (1.36-1.60) < 0.01* 1.21 (1.12-1.32) < 0.01* 0.98 (0.86-1.10) 0.34 Adjusted Relative risk: adjusted for with age at delivery, income, urbanization, parity, acute coronary syndrome, chronic ischemic heart disease, stroke, diabetes mellitus, chronic hypertension and hyperthyroidism Acute Coronary syndrome included myocardial infarction and unstable angina *P < 0.05 evidences, there was yet no definite pathophysiology and appeared to be more frequent in patients with high mechanism to explain the development towards early- or body mass index (BMI) compared with early-onset late-onset preeclampsia. Thus, more investigations are disease [19]. However, we had no data of maternal needed to identify the specific correlation between old age BMI to assess and the mechanism between pre- or chronic hypertension and early-onset preeclampsia, and eclampsia and obesity was yet completely understood. clinicians should be aware of preeclampsia prediction in In general, maternal risk factors between early- and women with clinical risk factors, particularly chronic late- onset preeclampsia were similar but old age and hypertension, which had highest risk (ARR, 16.8, 95%CI, chronic hypertension appeared stronger association to 15.7–18.0) of early-onset preeclampsia in the current early-onset disease and primiparity had higher risk of study. Furthermore, early intervention such as aspirin late-onset preeclampsia. prophylaxis may be considered in patients with evidence of This study was the first documented the increasing higher risk, according to the ASPRE trial [43]toprevent trend of preeclampsia in Taiwan between 2001 and severe maternal morbidities and poorer birth outcomes of 2014, predominantly in early-onset disease. The strength early-onset preeclampsia [14, 16, 17]. On the other hand, of the study includes a large cohort sample from a spe- Valensise et al. have found late-onset preeclampsia cific geographic area which is very representative of the You et al. BMC Pregnancy and Childbirth (2018) 18:199 Page 10 of 11 regional population and the large study size provided re- Ethics approval and consent to participate The data collection and analysis of the study was approved by Institutional liability in statistics. Review Board of the Chang Gung Memorial Hospital (IRB No.201600657B0). The consent requirement has been waived according to IRB policy of retrospective chart review study. Conclusions In conclusion, the population-base study showed a rise in Competing interests the incidence of preeclampsia, particularly in early-onset The authors declare that they have no competing interests. disease in Taiwan from 2001 to 2014, suggesting the clin- ical early prediction, identification, and management of Publisher’sNote the diseases will increasingly challenge obstetricians. As Springer Nature remains neutral with regard to jurisdictional claims in increasing number of advanced maternal age and chronic published maps and institutional affiliations. hypertension in delivering population in Taiwan, precon- Author details ceptional counseling and surveillance is warranted in preg- Department of Obstetrics and Gynecology, Chang Gung Memorial Hospital, nant women with higher risk of early-onset preeclampsia. Linkou, Taiwan. Big data research office, Chang Gung Memorial Hospital, Linkou, Taiwan. Division of Rheumatology, Allergy and Immunology, Chang Further study of the predominance of early-onset pre- Gung Memorial Hospital, Linkou, Taiwan. Department of Cardiology, Chang eclampsia in the population and the stronger association Gung Memorial Hospital, Linkou, Taiwan. with old age and hypertension and early-onset preeclamp- Received: 21 November 2017 Accepted: 23 May 2018 sia is required. Additional files References 1. Khan KS, Wojdyla D, Say L, Gulmezoglu AM, Van Look PF. WHO analysis of causes of maternal death: a systematic review. Lancet. 2006;367(9516):1066–74. Additional file 1 Trends of preeclampsia incidence according to 2. Abalos E, Cuesta C, Grosso AL, Chou D, Say L. Global and regional estimates different ages between 2001 and 2014 (blue: 15–25-year-old; red: 25–35- of preeclampsia and eclampsia: a systematic review. Eur J Obstet Gynecol year-old; green:35–55-year-old). (TIF 1329 kb) Reprod Biol. 2013;170(1):1–7. Additional file 2 Trends of preeclampsia incidence according to 3. Duley L. The global impact of pre-eclampsia and eclampsia. Semin women with or without hypertension (orange: women with Perinatol. 2009;33(3):130–7. hypertension; blue: women without hypertension). (TIF 1131 kb) 4. Abalos E, Cuesta C, Carroli G, Qureshi Z, Widmer M, Vogel JP, Souza JP, W.H. Additional file 3 Table S6 Maternal characteristics and clinical risk O.M.S.o. Maternal, and N. Newborn Health Research. Pre-eclampsia, factors associated with preeclampsia by age group. Table S7 Maternal eclampsia and adverse maternal and perinatal outcomes: a secondary characteristics and clinical risk factors associated with preeclampsia by analysis of the World Health Organization Multicountry Survey on Maternal hypertension. (DOCX 22 kb) and Newborn Health. BJOG. 2014;121(Suppl 1):14–24. 5. Roberts CL, Algert CS, Morris JM, Ford JB, Henderson-Smart DJ. 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BMC Pregnancy and ChildbirthSpringer Journals

Published: May 31, 2018

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