Abstract
Background
Neonatal sepsis remains a significant cause of morbidity and mortality among newborns worldwide. Although the implementation of intrapartum antibiotic prophylaxis (IAP) has led to changes in the microbiological landscape of early-onset sepsis (EOS), the incidence among full-term neonates has not declined as expected. This underscores the ongoing need to identify and understand maternal and neonatal risk factors to inform more effective prevention strategies.
Methods
We conducted a nationwide, population-based matched case–control study using data from January 1, 2010, to December 31, 2019, encompassing all pregnant individuals and their term infants in Taiwan. The primary objective was to identify clinical risk factors associated with EOS by comparing neonates diagnosed with EOS to matched controls without EOS. Conditional logistic regression was used for statistical analysis, adjusting for relevant maternal and neonatal covariates.
Results
A total of 1,694,043 mother–term infant pairs were included in the analysis, representing one of the largest national cohorts to date. Despite the implementation of a universal antenatal screening program and IAP in 2012, the incidence of clinical EOS did not decline over the study period and showed a slight increase around 2018. Adjusted analyses identified several significant risk factors for EOS, including chorioamnionitis (OR 8.99; 95% CI, 3.07–26.33), maternal pneumonia (OR 17.35; 95% CI, 6.85–43.90), Cesarean section (OR 1.45; 95% CI, 1.28–1.64), maternal diabetes mellitus (OR 1.95; 95% CI, 1.52–2.51), maternal antibiotic use during pregnancy (OR 1.33; 95% CI, 1.17–1.52), premature rupture of membranes (PROM) (OR 1.69; 95% CI, 1.32–2.15), birth weight (OR 0.99; 95% CI, 0.99–0.99) (all p < 0.001), and maternal genitourinary tract infections (OR 1.85; 95% CI, 1.22–2.80; p = 0.004). Mortality was notably higher among neonates with EOS (0.667%) compared to those without EOS (0.0926%) (p < 0.001).
Conclusions
This study provides the most comprehensive analysis to date of EOS risk in term neonates using a nationwide dataset. Our findings indicate that cesarean delivery, maternal antibiotic use, specific maternal infections, maternal diabetes mellitus, premature rupture of membranes, and lower birth weight are associated with an increased risk of EOS. Further research is warranted to explore the potential causal relationships underlying these associations.
Keywords: Risk, Early-onset sepsis, Full-term neonates, Maternal infections, Antibiotic usage, Cesarean section
Introduction
Since 2012, Taiwan has implemented a universal antenatal screening program alongside intrapartum antibiotic prophylaxis (IAP) to reduce infections caused by Group B Streptococcus (GBS) [1], a strategy proven to lower the risk of neonatal sepsis in term infants born to GBS carriers in other countries [2]. Additionally, empirical antibiotic treatment has been routinely provided to neonates identified as being at risk for early-onset sepsis (EOS). However, despite these proactive measures, there has been a reported rise in EOS cases linked to Escherichia coli (E. coli) and non-Enterococcal Group D Streptococcus among term infants [1]. This trend raises concerns about the unintended consequences of extensive antibiotic use during the perinatal period. Research suggests that antibiotic exposure may impair immune cell function and further exacerbate the already immunocompromised state of neonates2, potentially leading to a higher incidence of non-GBS infections. These observations highlight the pressing need to re-evaluate current EOS risk factors and to innovate more effective and targeted antibiotic stewardship and preventive strategies for neonatal care.
EOS and other infectious diseases continue to represent substantial causes of neonatal morbidity and mortality globally [3, 4]. According to national surveillance data from the U.S. Centers for Disease Control and Prevention (CDC), collected between 2005 and 2014, the majority of EOS cases were reported in full-term newborns [5, 6]. More recently, global health statistics reveal that in 2021 alone, approximately 2.3 million infants died within the first month of life—equivalent to about 6,500 deaths per day [7]. Among these, sepsis remains one of the most prevalent causes of neonatal mortality [8, 9]. These figures reinforce that neonatal sepsis remains a persistent global health challenge, consistently ranking as a leading cause of neonatal illness and death across diverse healthcare systems [9, 10].
Neonatal sepsis (NS) is broadly defined as a systemic inflammatory response in neonates due to a suspected or confirmed infection [11]. It can present in a variety of forms, including bloodstream infections, pneumonia, meningitis, arthritis, and osteomyelitis, among others [12]. Unlike in older populations where sepsis is often diagnosed based on organ dysfunction, neonatal sepsis is typically identified through clinical symptoms, microbiological culture results, and laboratory markers [13]. EOS, specifically, refers to a bacterial infection occurring within the first 72 h after birth [4, 9, 14]. This study focuses exclusively on term neonates—defined as those born at or beyond 37 weeks’ gestation—to avoid confounding effects associated with prematurity.
This research is grounded in the hypothesis that recognizing and characterizing EOS risk factors can improve early diagnosis and timely treatment, ultimately leading to better health outcomes in neonates. Prompt recognition and the early initiation of appropriate antimicrobial therapy in at-risk newborns are critical strategies for lowering sepsis-related mortality and complications [15]. A number of studies have investigated both maternal and neonatal risk factors for sepsis. For example, India’s national clinical guidelines identify seven key perinatal risk factors to guide early antibiotic intervention in newborns. However, certain risk factors remain inconsistently supported across studies, and the lack of large-scale, nationally representative data has limited comprehensive insights due to relatively small sample sizes in existing research.
Clinical observations have pointed to a potential link between Cesarean section (CS), maternal infections, and antibiotic use during pregnancy and the occurrence of EOS in term neonates. To validate these associations, we conducted a nationwide case-control study focusing exclusively on term neonates with EOS. By excluding preterm infants, this study minimizes confounding variables related to prematurity and aims to provide a clearer understanding of EOS risk factors [16]. The findings are intended to inform future prevention strategies and optimize neonatal sepsis management.
Methods
Data Sources
This nationwide case-control study utilized data from three major Taiwanese health databases: the National Health Insurance Research Database (NHIRD), the Birth Certificate Application Database (BCD), and the Maternal and Child Health Database (MCHD). These databases allowed identification of all pregnancies and their term newborns (gestational age ≥ 37 weeks) in Taiwan between 2010 and 2019. The data were accessed through the Health and Welfare Data Science Center (HWDSC), Ministry of Health and Welfare, Taiwan. The National Health Insurance system covers around 99.9% of Taiwan’s population—roughly 23 million people—and provides comprehensive records on diagnoses, prescriptions, and medical visits. The BCD contains essential birth data, including gestational age and infant birth weight, while the MCHD provides anonymized identifiers linking mothers and newborns. For this study, we integrated these three databases to extract de-identified information on maternal and neonatal health factors associated with early-onset sepsis (EOS).
Ethical considerations
This research was approved by the Institutional Review Board of China Medical University Hospital, Taiwan (Approval No. CMUH113-REC1-085). As the study was retrospective and used fully de-identified data, informed consent was not required. The study was conducted in accordance with the ethical principles of the Declaration of Helsinki.
Study population and case definition
The study identified term births and their mothers from 2010 to 2019, focusing on infants diagnosed with sepsis by physicians. Sepsis cases were determined using inpatient diagnostic codes—ICD-9-CM codes (038.xx, 785.52, 998.02, 995.91, 995.92, 003.1, 036.2, 098.89, 771.81) before 2015 and ICD-10-CM codes (A40.x, A41.xx, R65.20, R65.21, T81.12XA, T81.12XD, T81.12XS, A02.1, A39.4, A54.86, P36) afterward (see Table 1). Because blood culture results were not available in the databases, sepsis diagnoses were based solely on these coding systems. We analyzed sepsis incidence and associated mortality from birth to 90 days of life. To ensure clinical relevance, we excluded suspected cases lacking blood culture testing, antibiotic treatment, or hospital stays shorter than 10 days, aligning with American Academy of Pediatrics (that recommend a minimum of 10 days of antibiotics for neonatal bacteremia without a specific infection site [17]. Infants who developed late-onset sepsis (≥ 72 h after birth) without evidence of EOS were also excluded. For the control group, we selected live births matched at a 1:5 ratio based on fixed variables, including sex, birth year, and birth month, excluding any infants who had been previously diagnosed with sepsis or admitted to the neonatal intensive care unit (NICU) or special care nursery (see Fig. 1; Table 2). Matching on sex, birth year, and birth month was performed to control for potential confounding by immutable demographic factors that could influence both exposure and outcome. This approach allowed for more balanced comparison groups and helped minimize residual confounding that might not be fully addressed through covariate adjustment alone. To avoid inadvertently including EOS cases that were not formally coded in the control group, we excluded infants with any history of hospitalization, as such cases may occur in clinical practice due to the 3–7 day delay in obtaining blood culture results. The primary outcome was identification of risk factors for EOS, comparing characteristics between cases and matched controls.
Table 1.
Diagnoses of risk factors
| Risk factors | ICD-9-CM codes (2010–2015) | ICD-10-CM codes (2016–2019) |
|---|---|---|
| Maternal risk factors | ||
| Maternal fever | 659.20, 659.21, 659.23, 780.6 | O75.2, R50. 9 |
| Chorioamnionitis | 658.4x, 762.7 | O41.101x, O41.102x, O41.103x, O41.1090, O41.121x, O41.122x, O41.123x, O41.1290, P02.7 |
| Genitourinary tract infections | 599.0, 646.6x | N39.0, O23.xx |
| Group B streptococcus (GBS) colonization | V02.51 | Z22.330 |
| Pneumonia | 480.x-486 | J12.xx-J18.x |
| Premature rupture of membranes (PROM) | 658.1x | O42 |
| Delivery by Cesarean section | 669.70, 669.71, V30.01, V31.01, V32.01, V33.01, V34.01, V35.01, V36.01, V37.01, V39.01 | O82, Z38.01, Z38.31, Z38.62, Z38.64,, Z38.66, Z38.69, DRG 765, DRG 766 |
| Maternal systemic lupus erythematosus (SLE) | 710.0 | M32.xx |
| Maternal diabetes mellitus | 250.xx, 648.0x | E08.xxx-E13.xxx, O24.xxx |
| Neonatal risk factors | ||
| Birth injury | 767.x | P10.x-P15.x |
| Meconium aspiration syndrome (MAS) | 770.1 | P24.0x, P24.1x |
Fig. 1.
Flowchart illustrating the selection process for the clinically significant sepsis group and the non-sepsis control group, matched at a 1:5 ratio in this study
Table 2.
Baseline characteristics of participants by matching 1: 5 ratio in this case-control study. Data are shown as number (%)
| Variables | Sepsis group (N = 1449) |
Non-sepsis group (N = 7245) |
p value |
|---|---|---|---|
| Sex | 1.000 | ||
| Male | 877 (60.52) | 4385 (60.52) | |
| Female | 572 (39.48) | 2860 (39.48) | |
| Birth Year | 1.000 | ||
| 2010 | 93 (6.42) | 465 (6.42) | |
| 2011 | 86 (5.94) | 430 (5.94) | |
| 2012 | 92 (6.35) | 460 (6.35) | |
| 2013 | 123 (8.49) | 615 (8.49) | |
| 2014 | 126 (8.70) | 630 (8.70) | |
| 2015 | 194 (13.39) | 970 (13.39) | |
| 2016 | 24 (1.66) | 120 (1.66) | |
| 2017 | 246 (16.98) | 1,230 (16.98) | |
| 2018 | 260 (17.94) | 1,300 (17.94) | |
| 2019 | 205 (14.15) | 1,025 (14.15) | |
| Birth Month | 1.000 | ||
| January | 133 (9.18) | 665 (9.18) | |
| February | 111 (7.66) | 555 (7.66) | |
| March | 125 (8.63) | 625 (8.63) | |
| April | 107 (7.38) | 535 (7.38) | |
| May | 105 (7.25) | 525 (7.25) | |
| June | 122 (8.42) | 610 (8.42) | |
| July | 111 (7.66) | 555 (7.66) | |
| August | 136 (9.39) | 680 (9.39) | |
| September | 110 (7.59) | 550 (7.59) | |
| October | 140 (9.66) | 700 (9.66) | |
| November | 115 (7.94) | 575 (7.94) | |
| December | 134 (9.25) | 670 (9.25) | |
Covariates (Risk Factors)
Maternal risk factors—including fever, chorioamnionitis, genitourinary tract infections, GBS colonization, and pneumonia—were defined as any diagnosis recorded using ICD-9-CM or ICD-10-CM codes (Table 1) within 14 days before delivery. Diagnoses of maternal systemic lupus erythematosus (SLE) and diabetes mellitus (DM) were identified within 100 days before birth. Maternal antibiotic or steroid use was defined as having received at least one prescription for either drug class in the 14 days preceding labor. Antibiotics were classified using ATC code J01 (antibacterials for systemic use), while steroids, including antenatal corticosteroids, were identified using ATC codes H02AB01 (prednisolone) and H02AB02 (dexamethasone). Infant-related factors—such as birth trauma and meconium aspiration syndrome—were defined by relevant ICD-9-CM or ICD-10-CM codes recorded after birth (Table 1).
Statistical analysis
All analyses were performed using SAS software version 9.4 (SAS Institute, Cary, NC, USA). A P-value < 0.05 was considered statistically significant. Descriptive statistics summarized the distribution and incidence rates of maternal and neonatal risk factors. To identify factors independently associated with EOS, we employed conditional logistic regression with forward stepwise variable selection. Variables were entered into the model based on a p-value threshold of < 0.05, ensuring that only those with statistically significant associations were retained in the final model, thereby promoting model parsimony. Adjusted odds ratios (aORs) and 95% confidence intervals (CIs) were calculated to estimate the strength of associations between each risk factor and EOS. Model performance was assessed using the Hosmer-Lemeshow goodness-of-fit test and the area under the receiver operating characteristic curve (AUC) for the predicted probabilities.
Results
Epidemiology of sepsis diagnosed within 90 days of birth
Among 1,870,724 live births in Taiwan from 2010 to 2019, a total of 18,871 neonates (1.01%) were diagnosed with sepsis within the first 90 days of life (Fig. 1; Table 1). Of these, 1,694,043 were term newborns (90.56%), with 13,350 (0.778%) developing sepsis. The 176,681 preterm newborns (9.45% of all neonates) born during this period have been analyzed and reported previously [18]. Notably, 63.73% of sepsis cases in term infants occurred within the first three days after birth. Among 1,646 term neonates who died within 90 days of birth, 89 deaths (5.41%) were attributed to sepsis. The mortality rate for term neonates with sepsis (0.667%) was significantly higher than that for those without sepsis (0.0926%) (p < 0.001).
Selection of early-onset sepsis cases
Out of 8,540 sepsis cases identified among term neonates, 1,449 met the criteria for EOS. Exclusions included cases without blood culture data, lack of antibiotic treatment, or hospital stays shorter than 10 days (Fig. 1).
Incidence of EOS in term neonates
The incidence of EOS among term neonates was 0.0855% (1,449 out of 1,694,043), which closely aligns with the previously reported incidence rate of 0.079% at MacKay Children’s Hospital and MacKay Memorial Hospital, Tamsui Branch, between 2001 and 2018, where EOS was defined based on positive blood cultures.1. The incidence of clinical early-onset sepsis (EOS) in term neonates remained stable from 2010 to 2019, with a slight increase observed around 2018 (Table 2).
Baseline characteristics of study participants
In this case-control analysis of EOS risk factors in term neonates (n = 1,449), controls were matched at a 1:5 ratio. There were no significant differences between the EOS and control groups in sex, birth year, or birth month (all p = 1.0) (Table 2).
Risk factors for early-onset sepsis in term infants
Chi-square analysis revealed significant associations between EOS and several maternal factors, including chorioamnionitis, genitourinary tract infections, pneumonia, premature or prolonged rupture of membranes, Cesarean delivery, systemic lupus erythematosus (SLE), diabetes mellitus (DM), antibiotic use (all p < 0.001), maternal fever (p = 0.004), and steroid use (p = 0.007). Among neonatal factors, gestational age and birth weight were also significantly associated with EOS (Table 3).
Table 3.
Chi-square analysis on risk factors of neonates acquiring early-onset sepsis
| Risk factors | Sepsis group (N = 1449) |
Non-sepsis group (N = 7245) |
p value |
|---|---|---|---|
| Maternal factors | |||
| Maternal fever | 10 (0.69) | 17 (0.23) | 0.004 |
| Chorioamnionitis | 17 (1.17) | 5 (0.07) | < 0.001 |
| Maternal genitourinary tract infections | 47 (3.24) | 94 (1.30) | < 0.001 |
| Maternal group B streptococcus (GBS) colonization | 54 (3.73) | 241 (3.33) | 0.442 |
| Maternal pneumonia | 20 (1.38) | 6 (0.08) | < 0.001 |
| Premature rupture of membranes (PROM) | 98 (6.76) | 312 (4.31) | < 0.001 |
| Delivery by Cesarean section | 681 (47.00) | 2546 (35.14) | < 0.001 |
| Maternal systemic lupus erythematosus (SLE) | 9 (0.62) | 28 (0.39) | 0.2104 |
| Maternal diabetes mellitus | 95 (6.56) | 264 (3.64) | < 0.001 |
| Maternal antibiotics usage | 500 (34.51) | 1841 (25.40) | < 0.001 |
| Steroid (betamethasone or dexamethasone) usage | 23 (1.59) | 60 (0.83) | 0.007 |
| Neonatal factors | |||
| Gestational age (weeks)* | 38 ± 1 | 39 ± 1 | < 0.001 |
| Birth body weight (per 100 g)* | 29.87 ± 5.85 | 31.21 ± 3.79 | < 0.001 |
| Birth injury | 3 (0.21) | 20 (0.28) | 0.641 |
| Meconium aspiration syndrome (MAS) | 5 (0.35) | 23 (0.32) | 0.866 |
Data are presented as number (percentage among total positive cases for each risk factor), unless otherwise specified
*Continuous variables are shown as mean ± standard deviation
Forward stepwise logistic regression analysis confirmed independent associations between EOS and maternal chorioamnionitis, pneumonia, Cesarean section, diabetes mellitus, antibiotic use, lower birth weight (all p < 0.001), and genitourinary tract infections (p = 0.004) (Table 4). The stepwise model demonstrated good fit, as indicated by the Hosmer-Lemeshow test (p = 0.72), showing no evidence of lack of fit. The area under the curve (AUC) was 0.621, reflecting acceptable discriminatory ability for an epidemiological model [19].
Table 4.
Conditional logistic regression on risk factors of neonates acquiring early-onset sepsis
| Unadjusted model | Adjusted model (Full model) |
Adjusted model* (Forward stepwise model) |
|||||||
|---|---|---|---|---|---|---|---|---|---|
| OR | 95% CI | p value | OR | 95% CI | p value | OR | 95% CI | p value | |
| Maternal factors | |||||||||
| Maternal fever | 2.96 | 1.35 to 6.47 | 0.007 | 1.76 | 0.71 to 4.35 | 0.224 | |||
| Chorioamnionitis | 17.19 | 6.33 to 46.67 | < 0.001 | 8.74 | 2.97 to 25.71 | < 0.001 | 8.99 | 3.07 to 26.33 | < 0.001 |
| Maternal genitourinary tract infections | 2.55 | 1.79 to 3.64 | < 0.001 | 1.85 | 1.22 to 2.81 | 0.004 | 1.85 | 1.22 to 2.80 | 0.004 |
| Maternal group B streptococcus (GBS) colonization | 1.13 | 0.83 to 1.52 | 0.443 | 1.15 | 0.85 to 1.57 | 0.375 | |||
| Maternal pneumonia | 16.89 | 6.77 to 42.12 | < 0.001 | 16.75 | 6.57 to 42.69 | < 0.001 | 17.35 | 6.85 to 43.90 | < 0.001 |
| Premature rupture of membranes (PROM) | 1.61 | 1.28 to 2.04 | < 0.001 | 1.69 | 1.33 to 2.15 | < 0.001 | 1.69 | 1.32 to 2.15 | < 0.001 |
| Delivery by Cesarean section | 1.64 | 1.46 to 1.83 | < 0.001 | 1.47 | 1.29 to 1.67 | < 0.001 | 1.45 | 1.28 to 1.64 | < 0.001 |
| Maternal systemic lupus erythematosus (SLE) | 1.61 | 0.76 to 3.43 | 0.213 | 1.17 | 0.52 to 2.60 | 0.706 | |||
| Maternal diabetes mellitus | 1.86 | 1.46 to 2.36 | < 0.001 | 1.97 | 1.53 to 2.53 | < 0.001 | 1.95 | 1.52 to 2.51 | < 0.001 |
| Maternal antibiotics usage | 1.55 | 1.37 to 1.75 | < 0.001 | 1.32 | 1.16 to 1.50 | < 0.001 | 1.33 | 1.17 to 1.52 | < 0.001 |
| Steroid (betamethasone or dexamethasone) usage | 1.93 | 1.19 to 3.13 | 0.008 | 1.20 | 0.72 to 1.99 | 0.480 | |||
| Neonatal factors | |||||||||
| Gestational age (weeks) | 0.86 | 0.82 to 0.91 | < 0.001 | 1.02 | 0.96 to 1.08 | 0.558 | |||
| Birth weight (per 100 g) | 0.99 | 0.99 to 0.99 | < 0.001 | 0.99 | 0.99 to 0.99 | < 0.001 | 0.99 | 0.99 to 0.99 | < 0.001 |
| Birth injury | 0.75 | 0.22 to 2.53 | 0.642 | 0.70 | 0.17 to 2.90 | 0.622 | |||
| Meconium aspiration syndrome (MAS) | 1.09 | 0.41 to 2.87 | 0.862 | 0.38 | 0.08 to 1.75 | 0.214 | |||
*The Hosmer-Lemeshow test was 0.72, and the area under the curve was 0.621
Discussion
Our nationwide study found that the incidence of early-onset sepsis (EOS) in term neonates did not decline from 2010 to 2019 and even showed a slight increase around 2018, as seen in Table 2. This trend is consistent with previous findings that reported a rise in E. coli and non-Enterococcal Group D Streptococcus infections among full-term infants in Taiwan after 2012 [1]. These results underscore the urgent need for further research to identify specific risk factors and develop innovative prevention strategies for EOS. Among term neonates in our study, the incidence of clinical early-onset sepsis (EOS) was 0.0855% (1,449 out of 1,694,043), closely aligning with a previously reported rate of 0.079% for term neonates between 2001 and 2018 at MacKay Children’s Hospital and MacKay Memorial Hospital, Tamsui Branch, where EOS was diagnosed based on positive blood culture findings—representing only an 8.23% difference [1].
Using the largest dataset of EOS cases reported globally to date, our study identified eight significant risk factors that increase the likelihood of EOS in term neonates. These include cesarean section (CS), maternal antibiotic use, specific maternal infections, maternal diabetes mellitus, premature or prolonged rupture of membranes, and lower birth weight. In previous research, the relationship between CS and EOS was difficult to confirm due to limited case numbers [20]. A 2019 study from a NICU in Indonesia found that term infants delivered via CS were 3.25 times more likely to develop EOS compared to those delivered vaginally [21]. Similarly, our study also demonstrated an increased risk of EOS associated with CS. However, a multicenter study conducted in 36 NICUs in the United States from 2011 to 2016 reported an inverse association, suggesting that CS was linked to a reduced risk of EOS among term infants [22]. The authors of that study attributed the difference to the fact that EOS is primarily caused by vertical transmission.
Several factors may account for the variations in findings between countries. Firstly, the widespread application of advanced medical technologies and rigorous infection prevention protocols during cesarean sections (CS) in the U.S. may contribute to a lower incidence of EOS [18]. Secondly, intrauterine infections like sepsis can evolve into EOS and initiate fetal inflammatory response syndrome (FIRS), which frequently manifests as fetal distress—one of the primary reasons for performing emergency CS procedures [18, 23]. Unlike planned CS, emergency CS is often associated with a heightened risk of EOS. Research has demonstrated that fetal distress significantly elevates the likelihood of EOS (odds ratio = 3.00, p < 0.01) [24], and elective CS poses a substantially lower risk—approximately 0.15 times that of emergency CS (p < 0.001) [25]. The prevalence of elective CS in the U.S. (5.50%) is notably higher—9.82 times greater than that in Taiwan (0.56%, calculated as 12 out of 2,125 births) [26, 27], potentially explaining the lower EOS rates observed in U.S. populations. Thirdly, CS delivery may alter neonatal microbial colonization, particularly by reducing exposure to beneficial microbes such as Bifidobacterium and Bacteroides species [18, 28]. Newborns delivered by CS often exhibit disrupted gut microbiota, which may impair immune development and heighten vulnerability to EOS. Our results align with this theory and with previous studies linking CS birth to increased infection-related hospital admissions during early childhood, extending up to five years of age [29, 30]. These findings underscore the importance of maternal microbiota exposure during vaginal birth in establishing foundational immune defenses within the gastrointestinal and respiratory systems [31].
Maternal infections are among the leading causes of maternal mortality globally, contributing to approximately 10% of maternal deaths [32, 33], and they also increase the risk of neonatal sepsis [32–34]. Chorioamnionitis has been widely associated with both early- and late-onset neonatal sepsis [24, 25, 35], a correlation that our study also observed. We found that neonates born to mothers with a history of urinary tract or sexually transmitted infections (UTI/STI) had a higher risk of developing EOS, especially when these infections were untreated during the third trimester or labor, potentially resulting in birth canal colonization by pathogens [19]. GBS colonization at the genitourinary or gastrointestinal tract is a well-established risk factor for GBS-related EOS [36]. However, the administration of intrapartum antibiotic prophylaxis (IAP) to GBS-colonized women has significantly decreased the incidence of early-onset GBS infections. Therefore, according to AAP, GBS is not considered a risk factor if the mother received adequate IAP [17]. As prenatal screening and IAP are widely implemented in Taiwan, GBS colonization was not associated with neonatal sepsis in our study [1].
Pneumonia is the most common non-obstetrical infectious cause of maternal morbidity and mortality, with reported incidences of 0.5–1 per 1,000 pregnancies in the U.S. and 0.8 per 1,000 pregnancies in our study. Documented fetal outcomes associated with maternal pneumonia include preterm birth, small for gestational age, fetal distress, intrauterine infection, EOS, and fetal mortality [37]. Earlier research has indicated elevated incidences of neonatal infections among infants delivered by mothers with bacterial colonization or infections [38]. Our investigation is the first to identify an association between maternal pneumonia and a heightened risk of EOS in full-term newborns.
Approximately one in four pregnant individuals receives antibiotics during pregnancy or delivery [39], and this exposure disrupts maternal vaginal flora, affecting neonatal gut microbiota. This disruption can decrease the abundance of Lactobacillus species and may contribute to EOS [39, 40]. In our study, maternal bacterial infections—including chorioamnionitis, genitourinary infections, GBS colonization, and pneumonia occurring within 14 days before labor—were found in 9.25% of the sepsis group and 4.78% of the control group. However, 34.51% of mothers in the sepsis group and 25.40% in the control group received antibiotics. This indicates that antibiotic use exceeded the prevalence of confirmed infections. Although antibiotics may have been administered for perioperative prophylaxis (e.g., during cesarean section), for suspected but undocumented infections, or as part of standard obstetric protocols, some of this use may have been unnecessary and could potentially be reduced to lower the risk of early-onset sepsis (EOS).
Our evaluation of maternal health conditions demonstrated that gestational diabetes mellitus (GDM) is linked to a greater likelihood of EOS, a relationship not previously documented in term infants [41]. Although it is established that women with SLE face an elevated risk of peripartum infections and are more frequently administered antibiotics [42], our study did not find a meaningful association between SLE and EOS in term newborns.
Interestingly, our study is the first to show that higher birth weight may serve as a protective factor against EOS even among full-term infants. This observation is significant because previous studies did not specifically exclude preterm infants when evaluating this relationship [28]. Prolonged rupture of membranes is known to facilitate bacterial migration from the birth canal to the amniotic sac, increasing the risk of infection. These associations were confirmed both in our study and in prior research [19, 26, 37].
A previous nationwide cohort study reported that a single course of antenatal corticosteroids was associated with an increased risk of serious infections within the first year of life [43]. However, in our study focusing solely on term neonates, we did not observe a significant association between maternal steroid use and EOS.
Our study offers several strengths. It leveraged a nationwide dataset of over 1.68 million mother-child pairs collected over a decade, providing a comprehensive evaluation of EOS risk factors. The generalizability of our findings is enhanced by the study’s large sample size. The use of Taiwan’s universal single-payer health system allowed for complete and consistent tracking of diagnoses, prescriptions, and procedures, reducing selection and misclassification biases. Furthermore, the large sample provided robust statistical power for both cohort and matched analyses.
Nonetheless, this study has several limitations. The data were derived from a single country, and thus the findings should be validated in different geographic and healthcare settings. The absence of blood culture results and detailed clinical information—including antibiotic duration and maternal GBS colonization status— in the National Health Insurance Research Database limits the precision of EOS diagnosis, which relies on discharge codes and may be subject to bias. Case identification was based on administrative diagnoses and proxy indicators—such as blood culture testing, antibiotic administration, and hospital length of stay—which may result in misclassification or overestimation.
To avoid inadvertently including EOS cases that were not formally coded in the control group, we excluded infants with any history of hospitalization, as such cases may occur in clinical practice due to the 3–7 day delay in obtaining blood culture results. Although hospitalized neonates without any sepsis-related diagnosis accounted for only 3.69% of the control group, we acknowledge that factors associated with hospitalization may have introduced bias.
Additionally, the transition from ICD-9 to ICD-10 in 2016 may have introduced classification bias, potentially contributing to under- or over-identification of EOS cases. This may partly explain the unusually low number of cases recorded in 2016. The broader adoption of the Kaiser Permanente EOS calculator following its publication in 2017 may also have influenced clinical decision-making, contributing to the observed increase in EOS incidence in 2018 [44].
Emergency cesarean sections, which cannot be differentiated from elective procedures in the National Health Insurance Research Database, are likely confounded by factors such as fetal distress and chorioamnionitis. Additionally, important maternal variables—such as intrapartum fever—may be underreported and therefore not significantly associated with EOS in our analysis, despite being recognized predictors of neonatal sepsis. Finally, 41 neonates who died from sepsis within the first 10 days of life were excluded due to the study design. However, their exclusion is unlikely to affect the overall conclusions of our study.
Conclusions
This study represents the first large-scale investigation to systematically assess potential risk factors for early-onset sepsis in term neonates, utilizing the largest known cohort of newborns. Our findings suggest that cesarean delivery, maternal antibiotic use, specific maternal infections, gestational diabetes, premature rupture of membranes, and lower birth weight may be associated with an increased risk of early-onset sepsis. Further research is needed to clarify the causal pathways underlying these associations.
Acknowledgements
We thank Health and Welfare Data Science Center, Ministry of Health and Welfare Taiwan (HWDSC, MOHW) which provided National Health Insurance Research Database (NHIRD), Birth Reporting Database (BCD), and Maternal and Child Health Database (MCHD).
Authors’ contributions
Hao-Yuan Lee was responsible for the study concept and design, resource acquisition, project coordination, drafting of the original manuscript, critical revision, funding acquisition, and manuscript editing. Yu-Lung Hsu contributed to the study concept and design, as well as data visualization and validation. Wen-Yuan Lee oversaw project administration and funding acquisition and contributed to data visualization, manuscript review, and editing. Shu-Hua Ko supervised project administration and participated in funding acquisition. Yu-Ling Huang assisted with data visualization and funding acquisition. Hsin-Ju Lin supported data visualization and validation. Ming-Luen Tsai contributed to the development of the study methodology. Chyi-Liang Chen was responsible for figure editing. Yu-Chia Chang contributed to manuscript review and editing, resource provision, project coordination, data curation, formal analysis, conceptualization, software management, and study supervision. Hung-Chih Lin contributed to manuscript review and editing, project administration, methodology development, and investigation, and also participated in funding acquisition and overall supervision.
Funding
This work was supported in part by Wei Gong Memorial Hospital (Project Nos. WMH-113-005 and WMH-114-006) and China Medical University Hospital (DMR-106-048).
Data availability
The data analyzed in this study were provided from the Health and Welfare Data Science Center (HWDSC) affiliated to Ministry of Health and Welfare in Taiwan. Due to legal restrictions imposed by the Taiwan government related to the Personal Information Protection Act, the databases cannot be made publicly available. Requests for access to these data should be sent as a formal proposal to the HWDSC in Taiwan (https://dep. mohw. gov. tw/dos/cp- 5119- 59201- 113. html).
Declarations
Ethics approval and consent to participate
All data obtained from the National Health Insurance Research Database (NHIRD) were encrypted, deidentified, and subject to strict access control for on-site analysis by the Health and Welfare Data Science Center (HWDSC), under the Ministry of Health and Welfare, Taiwan. Given the retrospective nature of the study and the use of fully anonymized data, informed consent was waived. This waiver was approved by the Institutional Review Board of China Medical University Hospital, Taiwan, in accordance with national regulations (IRB No. CMUH113-REC1-085; Approval date: May 23, 2024). The study was conducted in accordance with the ethical principles outlined in the Declaration of Helsinki.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Contributor Information
Wen-Yuan Lee, Email: 005122@tool.caaumed.org.tw.
Yu-Chia Chang, ycchang@email.nqu.edu.tw.
Hung-Chih Lin, Email: d0373.cmuh@gmail.com.
References
- 1.Ko MH, Chang HY, Li ST, Jim WT, Chi H, Hsu CH, Peng CC, Lin CY, Chen CH, Chang JH. An 18-year retrospective study on the epidemiology of early-onset neonatal sepsis - emergence of uncommon pathogens. Pediatr Neonatol. 2021;62(5):491–8. 10.1016/j.pedneo.2021.02.005. [DOI] [PubMed] [Google Scholar]
- 2.Fung TY, Sahota DS. How can we reduce neonatal sepsis after universal group B Streptococcus screening? BMC Pregnancy Childbirth. 2024;24(1):586. 10.1186/s12884-024-06791-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Baheru FS, Shiferaw BZ, Toru T, GebreEyesus FA. Magnitude of neonatal sepsis and its associated factors among neonates admitted to the neonatal intensive care unit in Hawassa comprehensive specialized hospital, Sidama regional state, ethiopia, 2020. BMC Pregnancy Childbirth. 2024;24(1):383. 10.1186/s12884-024-06583-z. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Kariniotaki C, Thomou C, Gkentzi D, Panteris E, Dimitriou G, Hatzidaki E, Neonatal Sepsis. Compr Rev Antibiot. 2025;14(1):6. 10.3390/antibiotics14010006. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Stoll BJ, Puopolo KM, Hansen NI, Sánchez PJ, Bell EF, Carlo WA, Cotten CM, D’Angio CT, Kazzi SNJ, Poindexter BB, Van Meurs KP, Hale EC, Collins MV, Das A, Baker CJ, Wyckoff MH, Yoder BA, Watterberg KL, Walsh MC, Devaskar U, Laptook AR, Sokol GM, Schrag SJ, Higgins RD. Eunice Kennedy shriver National Institute of child health and human development neonatal research network Early-onset neonatal sepsis 2015 to 2017, the rise of Escherichia coli, and the need for novel prevention strategies. JAMA Pediatr. 2020;175(2):e200593. 10.1001/jamapediatrics.2020.0593. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Schrag SJ, Farley MM, Petit S, Reingold A, Weston EJ, Pondo T, Hudson Jain J. Lynfield R epidemiology of invasive early-onset neonatal sepsis, 2005 to 2014. Pediatrics. 2016;138(6):e20162013. 10.1542/peds.2016-2013. [DOI] [PubMed] [Google Scholar]
- 7.World Health Organization (WHO). Newborn mortality. https://www.who.int/news-room/fact-sheets/detail/newborn-mortality Accessed 9 March 2025.
- 8.Strunk T, Molloy EJ, Mishra A&, Bhutta Z. A neonatal bacterial sepsis. Lancet. 2024;404(10449):277–93. 10.1016/S0140-6736(24)00495-1. [DOI] [PubMed] [Google Scholar]
- 9.Shane AL, Sánchez PJ, Stoll BJ, Neonatal sepsis. Lancet. 2017;390(10104):1770–80. 10.1016/S0140-6736(17)31002-4. [DOI] [PubMed] [Google Scholar]
- 10.Yismaw AE, Abebil TY, Biweta MA, Araya BM. Proportion of neonatal sepsis and determinant factors among neonates admitted in university of Gondar comprehensive specialized hospital neonatal intensive care unit Northwest Ethiopia 2017. BMC Res Notes. 2019;12(1):542. 10.1186/s13104-019-4587-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Goldstein B, Giroir B, Randolph A. International Consensus Conference on Pediatric Sepsis International pediatric sepsis consensus conference: definitions for sepsis and organ dysfunction in pediatrics. Pediatr Crit Care Med. 2005;6(1): 2–8. 10.1097/01.PCC.0000149131.72248.E6 [DOI] [PubMed]
- 12.Stefanovic IM. Neonatal sepsis. Biochem Med (Zagreb). 2011;21(3):276–81. 10.11613/bm.2011.037. [DOI] [PubMed] [Google Scholar]
- 13.Hayes R, Hartnett J, Semova G, et al. Neonatal sepsis definitions from randomised clinical trials. Pediatr Res. 2023;93(5):1141–8. 10.1038/s41390-021-01749-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Puopolo KM, Mukhopadhay S, Frymoyer A, Benitz WE. The term newborn: early-onset sepsis. Clin Perinatol. 2021;48(3):471–84. 10.1016/j.clp.2021.05.003. [DOI] [PubMed] [Google Scholar]
- 15.Lee HY, Chen CL, Wu SR, Huang CW, Chiu CH. Risk factors and outcome analysis of acinetobacter baumannii complex bacteremia in critical patients. Crit Care Med. 2014;42(5):1081–8. 10.1097/CCM.0000000000000125. [DOI] [PubMed] [Google Scholar]
- 16.Niyoyita JC, Ndayisenga J, Omolo J, Niyompano H, Bimenyimana PC, Dzinamarira T, Nsekuye O, Chavez I, Hakizayezu F. Factors associated with neonatal sepsis among neonates admitted in Kibungo referral hospital. Rwanda Sci Rep. 2024;14(1):15961. 10.1038/s41598-024-66818-z. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Polin RA. Committee on fetus and newborn. Management of neonates with suspected or proven early-onset bacterial sepsis. Pediatrics. 2012;129(5):1006–15. 10.1542/peds.2012-0541. [DOI] [PubMed] [Google Scholar]
- 18.Lee HY, Hsu YL, Lee WY, Huang KH, Tsai ML, Chen CL, Chang YC, Lin HC. Maternal infections, antibiotics, steroid use, and diabetes mellitus increase risk of Early-Onset sepsis in preterm neonates: A nationwide Population-Based study. Pathogens (Basel Switzerland). 2025;14(1):89. 10.3390/pathogens14010089. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Hosmer DW, Lemeshow S, Sturdivant RX. Applied logistic regression: third edition. wiley; 2013. p. 510. 10.1002/9781118548387.
- 20.Gebremedhin D, Berhe H, Gebrekirstos K. Risk factors for neonatal sepsis in public hospitals of Mekelle city, North ethiopia, 2015: unmatched case control study. PLoS ONE. 2016;11(5):e0154798. 10.1371/journal.pone.0154798. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Utomo MT, Harum NA, Nurrosyida K, Sampurna MTA, Aden TY. The association between birth route and early/late-onset neonatal sepsis in term infants: a case-control study in the NICU of a tertiary hospital in East java, Indonesia. Iran J Neonatology. 2022;Oct(4). 10.22038/ijn.2022.63955.2237.
- 22.Polcwiartek LB, Smith PB, Benjamin DK, Zimmerman K, Love A, Tiu L, Murray S, Kang P, Ebbesen F, Hagstrøm S, Clark RH, Greenberg RG. Early-onset sepsis in term infants admitted to neonatal intensive care units (2011–2016). J Perinatol. 2021;41(1):157–63. 10.1038/s41372-020-00860-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Giovannini E, Bonasoni MP, Pascali JP, Giorgetti A, Pelletti G, Gargano G, Pelotti S, Fais P. Infection induced fetal inflammatory response syndrome (FIRS): state-of- the-art and medico-legal implications—a narrative review. Microorganisms. 2023;11(4):1010. 10.3390/microorganisms11041010. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Guo L, Han W, Su Y, Wang N, Chen X, Ma J, Liang J, Hao L, Ren C. Perinatal risk factors for neonatal early-onset sepsis: a meta-analysis of observational studies. J Matern Fetal Neonatal Med. 2023;36(2):2259049. 10.1080/14767058.2023.2259049. [DOI] [PubMed] [Google Scholar]
- 25.Adatara P, Afaya A, Salia SM, Afaya RA, Kuug AK, Agbinku E, Agyabeng-Fandoh E. Risk factors for neonatal sepsis: a retrospective case-control study among neonates who were delivered by caesarean section at the trauma and specialist hospital, winneba, Ghana. Biomed Res Int. 2018;2018:6153501. 10.1155/2018/6153501. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Wu LC, Peng FS, Leung C, Lu HF, Lin HH, Hsiao SM. Comparison of Cesarean section rates between obstetricians preferring labor induction at early versus late gestational age. Taiwan J Obstet Gynecol. 2022;61:847–53. 10.1016/j.tjog.2022.05.016. [DOI] [PubMed] [Google Scholar]
- 27.Trahan MJ, Czuzoj-Shulman N, Abenhaim HA. Cesarean delivery on maternal request in the united States from 1999 to 2015. Am J Obstet Gynecol. 2022;226(3):411. 10.1016/j.ajog.2021.10.003. [DOI] [PubMed] [Google Scholar]
- 28.Moftian N, Samad Soltani T, Mirnia K, Esfandiari A, Tabib MS, Rezaei Hachesu P. Clinical risk factors for early-onset sepsis in neonates: an international Delphi study. Iran J Med Sci. 2023;48(1):57–69. 10.30476/IJMS.2022.92284.2352. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Miller JE, Goldacre R, Moore HC, Zeltzer J, Knight M, Morris C, Nowell S, Wood R, Carter KW, Fathima P, de Klerk N, Strunk T, Li J, Nassar N, Pedersen LH, Burgner DP. Mode of birth and risk of infection-related hospitalisation in childhood: A population cohort study of 7.17 million births from 4 high-income countries. PLoS Med. 2020;17(11):e1003429. 10.1371/journal.pmed.1003429. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Christensen N, Søndergaard J, Christesen HT, Fisker N, Husby S. Association between mode of delivery and risk of infection in early childhood: a cohort study. Pediatr Infect Dis J. 2018;37(4):316–23. 10.1097/INF.0000000000001778. [DOI] [PubMed] [Google Scholar]
- 31.Wampach L, Heintz-Buschart A, Fritz JV, et al. Birth mode is associated with earliest strain-conferred gut Microbiome functions and immunostimulatory potential. Nat Commun. 2018;9(1):5091. 10.1038/s41467-018-07631-x. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32.World Health Organization. WHO recommendations for prevention and treatment of maternal peripartum infections. 2015. (https://www.who.int/publications/i/item/9789241549363). [PubMed]
- 33.Tita ATN, Carlo WA, McClure EM, et al. A-PLUS trial group. Azithromycin to prevent sepsis or death in women planning a vaginal birth. N Engl J Med. 2023;388(13):1161–70. 10.1056/NEJMoa2212111. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34.Modell B, Berry RJ, Boyle CA, Christianson A, Darlison M, Dolk H, Howson CP, Mastroiacovo P, Mossey P, Rankin J. Global regional and National causes of child mortality. Lancet. 2012;380(9853):556. 10.1016/S0140-6736(12)61878-9. author reply 1556-7. [DOI] [PubMed] [Google Scholar]
- 35.Beck C, Gallagher K, Taylor LA, Goldstein JA, Mithal LB, Gernand AD. Chorioamnionitis and risk for maternal and neonatal sepsis: a systematic review and meta-analysis. Obstet Gynecol. 2021;137(6):1007–22. 10.1097/AOG.0000000000004377. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36.Stoll BJ, Hansen NI, Sánchez PJ, et al. Early onset neonatal sepsis: the burden of group B Streptococcal and E. coli disease continues. Pediatrics. 2011;127(5):817–26. 10.1542/peds.2010-2217. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 37.Ashby T, Staiano P, Najjar N, Louis M. Bacterial pneumonia infection in pregnancy. Best Pract Res Clin Obstet Gynaecol. 2022;85(Pt A):26–33. 10.1016/j.bpobgyn.2022.07.001. [DOI] [PubMed] [Google Scholar]
- 38.Chan GJ, Lee AC, Baqui AH, Tan J, Black RE. Risk of early-onset neonatal infection with maternal infection or colonization: a global systematic review and meta-analysis. PLoS Med. 2013;10(8):e1001502. 10.1371/journal.pmed.1001502. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 39.Haas DM, Marsh DJ, Dang DT, Parker CB, et al. Prescription and other medication use in pregnancy. Obstet Gynecol. 2018;131(5):789–98. 10.1097/AOG.0000000000002579. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 40.Zhou P, Zhou Y, Liu B, et al. Perinatal antibiotic exposure affects the transmission between maternal and neonatal microbiota and is associated with early-onset sepsis. mSphere. 2020;5(1):e00984–19. 10.1128/mSphere.00984-19. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 41.Wang J, Ji X, Liu T, Zhao N. Maternal and neonatal outcomes with the use of long acting, compared to intermediate acting basal insulin (NPH) for managing diabetes during pregnancy: a systematic review and meta-analysis. Diabetol Metab Syndr. 2022;14(1):154. 10.1186/s13098-022-00925-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 42.Bender Ignacio RA, Madison AT, Moshiri A, Weiss NS, Mueller BA. A population-based study of perinatal infection risk in women with and without systemic lupus erythematosus and their infants. Paediatr Perinat Epidemiol. 2018;32(1):81–9. 10.1111/ppe.12430. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 43.Yao TC, Chang SM, Wu CS, Tsai YF, Sheen KH, Hong X, Chen HY, Wu AC, Tsai HJ. Association between antenatal corticosteroids and risk of serious infection in children: nationwide cohort study. BMJ. 2023;382:e075835. 10.1136/bmj-2023-075835. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 44.Kuzniewicz MW, Puopolo KM, Fischer A, Walsh EM, Li S, Newman TB, Kipnis P, Escobar GJ. A quantitative, Risk-Based approach to the management of neonatal Early-Onset sepsis. JAMA Pediatr. 2017;171(4):365–71. 10.1001/jamapediatrics.2016.4678. [DOI] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The data analyzed in this study were provided from the Health and Welfare Data Science Center (HWDSC) affiliated to Ministry of Health and Welfare in Taiwan. Due to legal restrictions imposed by the Taiwan government related to the Personal Information Protection Act, the databases cannot be made publicly available. Requests for access to these data should be sent as a formal proposal to the HWDSC in Taiwan (https://dep. mohw. gov. tw/dos/cp- 5119- 59201- 113. html).