Maternal Risk Factors Associated with Neonatal Necrotizing Enterocolitis: a Meta-Analysis and Systematic Review

Maternal Risk Factors Associated with Neonatal Necrotizing Enterocolitis: a Meta-Analysis and Systematic Review | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Maternal Risk Factors Associated with Neonatal Necrotizing Enterocolitis: a Meta-Analysis and Systematic Review Lindsey Burnham, Will Lichstein, Alex Lyford This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7348561/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 25 You are reading this latest preprint version Abstract Background Neonatal Necrotizing Enterocolitis (NEC) is a multifactorial intestinal disorder that affects 2–5% of premature infants and has a mortality rate of 20–30%. 1 Researchers have identified the impact of maternal factors, such as a negative association of breastmilk feeding and antenatal corticosteroid therapy, on NEC development in infants. 2 – 5 However, other maternal risk factors have not been analyzed in detail. A better understanding of the role of specific maternal factors in developing NEC can help identify infants at risk and decrease the incidence of NEC. This meta-analysis aims to investigate the independent association between Cesarean section delivery, smoking, preeclampsia, chorioamnionitis, diabetes mellitus, and maternal education on the development of NEC. Methods We systematically searched for journal articles published before April 2025. 6 – 9 Studies were included if they contained data on incidence rates of NEC for any of the seven risk factors analyzed in this study. Two evaluators independently screened and extracted literature to be used for this meta-analysis. Disagreements were resolved through discussion, and interrater reliability was assessed using Cohen’s Kappa. Results We identified 74 manuscripts that met the inclusion criteria, of which 39 were suitable for our meta-analysis. The pooled risk calculation showed a statistically significant risk of NEC for mothers who smoked during pregnancy (OR: 1.75, 95% CI: 1.26–2.25, n = 10) and for mothers who had preeclampsia (OR: 2.03, 95% CI: 1.43–2.63, n = 8). All other pooled estimates for the maternal factors analyzed showed insignificant evidence of an association with NEC. In addition, the funnel plots and Egger’s regression tests indicated no evidence of publication bias for all maternal factors besides smoking during pregnancy (t = 2.61, p = 0.0313). Conclusions This study highlights a significant association between maternal smoking and preeclampsia during pregnancy and the development of NEC, suggesting a potential causal relationship. This study also identifies chorioamnionitis and Cesarean sections alone as nonsignificant risk factors, despite conflicting claims from other studies. Moreover, this meta-analysis also underscores the need for more research to be conducted to analyze the association between maternal smoking, preeclampsia, Cesarean sections, and chorioamnionitis on the development of NEC. Necrotizing Enterocolitis Meta-Analysis Forest Plot Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction and Background Neonatal Necrotizing Enterocolitis (NEC) is an intestinal inflammatory disease that affects primarily very low birth weight (VLBW, < 1500g birth weight) or premature infants. 10 Specifically, NEC is characterized by inflammation in parts of the intestine, often in the setting of tissue ischemia, usually affecting the distal ileum. 11 Because there is a lack of blood flow to parts of the intestine, intestinal tissue can die, and the intestinal mucosa can be damaged. 11 The intestinal mucosa is the innermost layer of the intestine, separating the gut lumen (the hollow part of the intestine) from the other layers of the intestine and the rest of the body. 12 The intestinal mucosa is an essential protective barrier, regulating what substances from the gut lumen get absorbed into the bloodstream and the lymphatic system while also preventing harmful pathogens from passing the mucosa and entering the rest of the body. 12 When the intestinal mucosa is damaged, bacterial translocation can occur where harmful bacteria from the lumen can invade deeper tissues, exacerbating inflammation and perpetuating a cycle of intestinal wall damage, death, and, in severe cases, perforation. 13 NEC progression can lead to sepsis, peritonitis, and death. While NEC only affects 2–5% of premature infants and 8% of neonatal intensive care unit (NICU)-admitted infants, its high mortality rate of 20–30%, as well as long-term effects on the intestines and neurodevelopment, make it a concern in neonatal care. 1 , 14 Although researchers have been studying NEC for decades, the approach to treating it has remained largely unchanged. 14 Milder cases of NEC are treated with various methods, including antibiotics, bowel rest, and close monitoring. For more severe cases of NEC, such as those with intestinal perforation, surgery is typically required. Surgery for NEC can involve resection of damaged and dead intestinal tissue, as well as creating a hole on the abdomen, known as an ostomy, to allow enteral contents to leave the body if the digestive system is not functioning properly. 15 Surgery can also involve draining the peritoneal cavity to allow the fluid and gas build-up caused by NEC to drain. If surgery is needed to treat NEC, the mortality rate increases to approximately 50%. One pertinent issue present is that even with decades of research, many factors that contribute to the development of NEC are not fully characterized. 16 Current literature has found that most NEC cases are among premature and VLBW infants. 14 One study by Singh et al. (2023) noted that 90% of NEC infants are born prematurely. 14 The reasons behind the increased risk of prematurity and VLBW infants developing NEC stem from the fact that they are more likely to have immature intestinal function. 17 If the intestinal tract is immature, the feedings the infants receive may move slower, which may lead to bacterial overgrowth, inflammation, and damage to the intestinal mucosa, contributing to NEC development. Fetal growth restriction (FGR) due to placental insufficiency has also been identified as a risk factor. 18 FGR is a condition in which a fetus is smaller than its expected gestational age in utero. In the setting of placental insufficiency, a fetus does not get the required oxygen and nutrients that are necessary to support growth. Researchers hypothesize that there could be in utero fetal hypoxia, which could result in blood flow redistribution away from the gastrointestinal tract. This condition could then result in an ischemic hit that disrupts intestinal formation and development, which could increase the risk of developing NEC. 19 Researchers have also investigated the effect of formula feeding on the development of NEC and found that premature infants may have a decreased risk of NEC if they are fed mostly breast milk instead of formula or a combination of breast milk and formula. 2 , 3 In addition, there is strong evidence indicating that antenatal corticosteroid (ACS) therapy decreases NEC risk in certain high-risk populations of infants. 20 – 23 NEC may also manifest in term infants, particularly in those with congenital heart disease (CHD), who are at an elevated risk. 24 This risk could be due to infants with CHD having poor diastolic pressure and mixed lesions where deoxygenated blood mixes into systemic circulation, leading to decreased oxygen delivery to the body’s tissues and organs. 25 Such conditions could lead to decreased oxygen delivery to the intestines before and after delivery, which could then result in mesenteric hypoperfusion and ischaemic bowel. 26 Infants with CHD who underwent surgery can also be vulnerable to developing NEC in the postoperative period. 25 These surgeries, such as systemic-to-pulmonary shunt procedures and cardiac lesion procedures, can compromise blood flow to the digestive system as well as alter blood flow patterns. These complications can result in hypoperfusion in the intestines, which can lead to gut necrosis and further put infants with CHD at risk for NEC. In the United States, studies have shown that both Hispanic neonates and non-Hispanic Black neonates have a higher risk of developing NEC. 27 – 29 ` Even when controlling for VLBW and prematurity, there is still an increased rate of Black and Hispanic infants developing NEC compared to white infants. 30 , 31 Infants born to Black and Hispanic mothers face a higher risk of conditions that are risk factors for NEC, such as limited access to prenatal care, lower rates of breastfeeding, increased risk of FGR, intrauterine growth restriction (IUGR), and prematurity. 31 – 33 Goldstein et al. (2020) show that white infants receive more human milk than Black and Hispanic infants. 32 In their univariate model examining the relationship between ethnicity and the development of NEC, Black and Hispanic infants have significantly higher odds of developing NEC compared to white infants. However, when using a multivariate model controlling for human milk, there was no longer a statistically significant increase in the odds of developing NEC. This study emphasized the possible role of human milk in preventing NEC and underscored the racial disparities in its delivery to infants. In a study conducted by Lind et al. (2014), researchers reported that hospitals in zip codes in the United States with a higher-than-average percentage of Black residents were significantly more likely to not meet the standards to support breastfeeding compared to hospitals in zip codes with a lower-than-average percentage of Black residents. 34 NEC is a multifactorial illness with a complex interplay between contributing risk factors. 35 While some researchers have singularly focused on factors such as VLBW, prematurity, breastfeeding, and corticosteroid therapy, others have taken the approach to broadly study multiple risk factors through meta-analysis and systematic reviews. 4 , 17 , 35 – 38 One meta-analysis reviewed literature that discusses methods of identifying medical vs. surgical NEC and the most effective methods. 37 Another meta-analysis investigated the global incidence of NEC, finding that from 1993 to 2018, there was a significant increase in the incidence of NEC. 35 Others broadly reviewed a plethora of risk factors for neonates, such as VLBW, prematurity, and congenital heart disease. 5 , 17 , 39 Others specifically investigate risk factors such as chorioamnionitis, human milk, antibiotic exposure, and administering antenatal corticosteroids. 3 , 4 , 38 , 40 , 41 In addition, systematic reviews, such as one done by Lin et al. (2014), have summarized some prevention strategies for NEC. 42 Lin et al. reinforce that probiotics and breastfeeding are plausible methods for preventing NEC. Even with a variety of literature regarding risk factors related to NEC and despite extensive efforts, we still haven’t fully determined the risk of maternal risk factors, such as smoking, on the development of NEC. This meta-analysis aims to investigate maternal factors present in the available literature and their association with NEC. Further, this meta-analysis will explore the potential risk of Cesarean section, smoking, preeclampsia, chorioamnionitis, diabetes mellitus, and education on the development of NEC. Methods Eligibility Criteria Studies deemed eligible for this meta-analysis were case-control, retrospective cohort, and population-based registry studies focusing on NEC in preterm infants. We did not limit studies to those with NEC as a primary outcome. Rather, only studies that assessed the incidence of NEC in infants based on the presence or absence of Cesarean section, preeclampsia, smoking, diabetes, chorioamnionitis, or maternal education were included. Studies were excluded if the NEC incidence rate associated with a specific maternal factor could not be extracted from the data provided. Studies that only included death records were excluded from our meta-analysis, as accounting only for deaths could underrepresent the true incidence of NEC, affecting the association between specific maternal factors and NEC. For inclusion, the sampling frame needed to be representative of the general population of mothers/infants. In addition, studies that only included full-term infants were excluded, as NEC is most prevalent in VLBW and premature infants, so this study group does not represent the general population of infants with NEC. Literature Search and Data Extraction Figure 1 illustrates the flowchart of study selection for our meta-analysis, adhering to the PRISMA guidelines. 43 Two authors independently searched Nature, Scopus, PubMed, and Google Scholar between September 2024 and April 2025 for cohort, population studies, systematic reviews, and meta-analyses. 6 – 9 The search terms “necrotizing enterocolitis,” “maternal risk,” “maternal factors,” “smoking,” “preeclampsia”, “chorioamnionitis,” and/or “diabetes” were used to narrow down results. Both authors reviewed journal article abstracts to see if they met the inclusion criteria. Afterward, the titles and abstracts of studies that met the initial criteria were evaluated, paying particular attention to the type of article, study goals, and the study population. In addition, studies were narrowed down based on whether they had “necrotizing enterocolitis” in their title. 74 studies were found among the two authors, tabulated with the corresponding maternal factors they included. Surgical and non-surgical cases of NEC were included, as we aimed to assess how maternal factors influenced the incidence of NEC rather than its severity. Additionally, there is a large overlap in risk factors for surgical and medical NEC, with the primary distinction being the severity of these factors. 44 After evaluating each study, the two authors met and resolved discrepancies, ultimately including 39 studies in this comprehensive search, which included the specific maternal factors we examined in their results. The study’s population size and number of infants with NEC whose mothers had or didn’t have the specific maternal risk factor were tabulated. The years the studies started and ended were also recorded, and the odds ratios (OR) with their corresponding 95% confidence intervals were calculated using Fisher’s exact test. 45 Quality Assessment We used the Hoy et al. (2012) risk of bias tool to assess the risk of bias in each study. The Hoy et al. (2012) tool presents eight yes-or-no questions, or “domains,” that encapsulate four main bias categories for non-randomized studies. The first category is external validity, which assesses whether the sampling frame accurately represents the target population of preterm infants. The question asked in this category is: “Was the study’s target population a close representation of the national population in relation to relevant variables?” In addition, this category assesses whether data were collected randomly or in the form of a census, specifically asking: “Was some form of random selection used to select the sample, OR was a census undertaken?” The second category is internal validity in participation selection, which asks, “Was the likelihood of nonresponse bias minimal?” This ensures that respondents and non-responders don’t differ significantly. For example, if more mothers who didn’t smoke during their pregnancy participated compared to mothers who did smoke, the results could be skewed. In addition, this category asks the specific question, “Were data collected directly from the subjects (as opposed to a proxy)?” to evaluate the potential for bias stemming from second-hand reported data. The third category assesses how the study collected and analyzed its data. For example, the risk of bias tool asks, “Was an acceptable case definition used in the study?” (e.g., Bell’s staging criteria and/or ICD9 and 10 codes). This category also contains the questions, “Was the study instrument that measured the parameter of interest shown to have validity and reliability?” and “Was the same mode of data collection used for all subjects?” to investigate whether data were assessed in the same way. For example, all data were extracted from the same dataset and evaluated using consistent diagnostic criteria across all subjects. Finally, the fourth category examines how studies analyze their data, specifically investigating the sample size and whether the proportion of infants with NEC was not underrepresented. This final category asks, “Were the numerator(s) and denominator(s) for the parameter of interest appropriate?” We evaluated whether the numerator and denominator were large enough in magnitude to make reasonable OR estimations. In addition, studies were deemed to have a high risk of bias if the proportion of infants with NEC was below 2%, which is in line with the rate of NEC development in premature infants. Two authors independently evaluated the risk of bias to determine whether studies introduced biases from sampling methodologies that could have led to misleading results. First, 10 of the 39 articles were evaluated using these parameters, and then the authors met to discuss their decisions and resolve any discrepancies in evaluation. After meeting, the other 29 studies were reviewed, and interrater reliability was assessed using Cohen’s Kappa. Statistical Analysis Forest Plots We performed all statistical analyses for this study in R (v4.4.3, R Core Team 2025) . 46 We made forest plots using the “meta” package (Baldudzzi et al, 2019) for each maternal factor. 47 Forest plots graphically present the results of multiple studies, showing individual risk estimates (e.g., the risk of developing NEC if the mother had a Cesarean section), along with their confidence intervals and a pooled overall estimate. They help determine whether, given the available studies, a maternal factor significantly increases or decreases the risk of NEC. Figure 2 illustrates a forest plot examining the relationship between Cesarean sections and NEC development. Forest plots display each study’s estimate of the OR (red square), the 95% confidence interval estimate for the OR (black line), and the overall estimate of the OR (blue diamond) given all of the studies included in the meta-analysis. An OR is a measurement to compare the odds of an event occurring in one group vs. another. By doing this, an OR can quantify the strength of association between an exposure and an outcome. An example of an OR is the ratio of the probability of the development of NEC if the mother smoked and the probability of the development of NEC if the mother did not smoke. An OR of 1 indicates no increased risk of NEC for mothers who smoke. In contrast, an OR greater than 1 suggests that mothers who smoked during pregnancy have elevated odds of their infants developing NEC. Conversely, an OR of less than 1 implies that the exposed group has reduced odds of the outcome. In addition, each study is weighted inversely to its variance so that studies with larger samples and more precise estimates are weighted more heavily. Weighting each study in this way has been shown to yield a more accurate and reliable overall effect estimate. 48 We used a random effects model to summarize the studies’ overall OR at the bottom of the forest plot. A random effects model considers variance within a study and between studies to produce an overall effect estimate. Heterogeneity For any meta-analysis, it is important to quantify whether the estimated effect size of a particular factor (e.g., maternal smoking status) on the outcome (e.g., the development of NEC) between individual studies is ‘similar enough’ to be plausible. To quantify this, we use Higgins and Thompson’s I 2 Statistic to assess the between-study heterogeneity. 49 Heterogeneity in a meta-analysis is the variation in the effect sizes—the strength of the relationship between variables—between the analyzed studies. We can evaluate effect sizes through the OR, which reports whether a mother having a certain maternal factor will increase or decrease the odds of the infant developing NEC. When quantifying observed effects between studies, two types of variation arise: sampling error and between-study heterogeneity. The I 2 statistic aims to quantify between-study heterogeneity: variation in study results beyond sampling error. This statistic is represented as a percentage, where an I 2 < 25% indicates low heterogeneity, 25% ≤ I 2 < 75% indicates moderate heterogeneity, and 75% ≤ I 2 ≤ 100% indicates substantial heterogeneity. Refer to Higgins and Thompson (2002) for the details of the rationale and proof of the validity of this statistic. 49 Publication Bias Publication bias is the phenomenon where studies with statistically significant results and larger sample sizes are more likely to be published than those without statistically significant findings/and or with smaller sample sizes. We therefore include a measurement to determine whether there is any publication bias included in this study. To do so, this study uses small-study effect methods. Sterne et al. (2000) define small study effects as: A tendency for treatment effect estimates in small studies to differ from those in larger studies [which] may have distorted the results of a meta-analysis. This could be due to publication bias, other reporting biases, low methodological quality of smaller studies or true heterogeneity in treatment effects. 50 The small-study effect methods used in this study are funnel plots and Egger’s regression test. A funnel plot is a graphical method for assessing the potential for publication bias. Figure 3 is an example of a funnel plot to assess for publication bias in the studies that investigate the relationship between Cesarean sections and the development of NEC in infants. The standard error of effect sizes for each study is plotted on the y-axis, and the logged OR (the logged odds of an NEC occurring given that the maternal factor measured is present) for each study is plotted on the x-axis. The OR was logged due to the inherent asymmetry of the raw OR scale. For example, an OR of 2 (indicating twice the odds) and an OR of 0.5 (indicating half the odds) are not equidistant from the null OR value of 1. Logging the OR creates symmetry about the null log(OR) of 0 (since log(1) = 0). This transformation allows us to test the assumption that the relationship between the log(OR) and the standard error is linear through Egger’s test. A funnel plot can test for asymmetry, meaning the distribution of study results is more likely to be distorted on a funnel plot. Asymmetry can be determined by plotting the standard error for each study on the y-axis vs. the estimated log(OR) of developing NEC given the mother has a specific maternal factor, such as having a Cesarean section, for each study on the x-axis. If the points plotted are asymmetrical across the overall aggregation of all studies' estimated log(OR) weighted by the inverse of their calculated variance (dotted vertical line), there is a possibility that there is publication bias in the meta-analysis. This is because the asymmetry in the funnel plot suggests that smaller studies with nonsignificant or negative results may be missing from the literature, potentially skewing the meta-analysis to an exaggerated or more favorable effect. In Fig. 3 , the studies are scattered relatively symmetrically about the vertical dotted line, leading us to suspect publication bias is unlikely. This study enhances the funnel plot by adding shades of gray (the shaded triangles) to indicate statistical significance thresholds (p values < 0.1, 0.05, and 0.01). These significance thresholds indicate whether the risk of developing NEC, given the mother has a specific maternal factor for each study, is due to more than random chance. The thresholds center around 0, as the null hypothesis is that log(OR) = 0. Log(OR)s that are farther away from 0 are increasingly unlikely to arise by chance Adding significance thresholds allows us to see trends in whether studies were published because of significance If most small studies (which are lower on the plot because they have a larger standard error) fall in the significant regions (p < 0.05), there could be potential publication bias because this result indicates that there are a lack small studies in literature with nonsignificant results. In Fig. 3 , we observe that the studies with a larger standard error fall within the non-significant regions (the white region where p > 0.1). While a funnel plot can suggest potential asymmetry, a formal test is necessary to confirm it. Egger’s Regression Test provides a quantitative method for measuring small study effects by examining funnel plot asymmetry using a linear regression approach. 50 Refer to the supplementary material for an in-depth explanation of Egger’s Regression Test. Results Systematic Search A total of 2760 studies were identified through our systematic search. After removing duplicates and studies deemed ineligible, 1011 records were initially screened to exclude studies that either did not include the correct study population, did not contain demographic information, excluded the maternal factors of interest, did not have a study design relevant to the meta-analysis question, did not directly pertain to NEC, or were systematic reviews themselves. After screening manuscripts, 74 were fully read; ultimately, 39 were deemed eligible for this meta-analysis. Study Characteristics Characteristics of each study are described in Table 1. Study periods ranged from 1983 to 2023. Of the 39 studies used for this meta-analysis, 14 were conducted in the United States, 32 , 51 – 63 3 in China and South Korea 20 , 64 – 68 . As well, 2 studies were conducted in Sweden, Turkey, Canada, the United Kingdom, Italy, and Israel. 69 – 80 Studies also came from Mexico, Kenya, France, Malaysia, Ethiopia, Australia, and Finland. 81 – 87 Newborns were diagnosed using ICD-9 and 10 codes, pathological and radiological findings to confirm the presence of NEC, or Bell’s criteria. Bell’s criteria is a staging system that stratifies infants into 3 stages (IA, IB, IIA, IIB, IIIA, IIIB) based on the presence or absence of clinical signs and radiographic findings. 88 Stages ≥ 2 are much more confident in NEC diagnosis, whereas stage 1 serves as a classification for suspected NEC. This system established a standardized method to classify infants with NEC, guiding their treatment. The studies varied in which stages of Bell’s criteria they used. Some studies only included Bell’s criteria stages ≥ 2, while others included all 3 stages. (See supplementary material for Table 1) Study designs included retrospective cohort studies, case-control studies, or population-based registry studies. The inclusion and exclusion criteria varied across studies. Maternal demographic data were extracted from medical records for each study, which served as the basis for the maternal characteristics analyzed in this meta-analysis. Assessment of Risk of Bias Risk of bias was evaluated across eight domains for each of the included studies, as shown in Fig. 4 . When assessing inter-rater reliability, a Cohen’s Kappa of 1 was found, indicating perfect agreement among the raters in their assessments of risk of bias. Overall, the risk of bias was generally low across the studies, with the primary concern being whether the ratio of NEC infants to control infants was appropriate. Additionally, some studies were deemed to be at high risk regarding the reliability and validity of the study instrument. In contrast, all studies utilized a consistent mode of data collection. Furthermore, all data were directly obtained from patients, rather than a proxy. Forest Plot Analysis Across all maternal factors, forest plots in Fig. 5 revealed varying levels of association with NEC. Table 2 shows the pooled ORs and 95% confidence intervals for each maternal factor. In summary, Cesarean Sections, Chorioamnionitis, maternal diabetes mellitus, over 12 years of education, and no education all had nonsignificant associations with the development of NEC. However, maternal smoking throughout pregnancy (summary OR: 1.75, 95% CI: 1.26–2.25, n = 10) and preeclampsia (summary OR: 2.03, 95% CI: 1.43–2.63, n = 8) had significant associations with NEC, found to be associated with 75% and 103% increased odds of NEC respectively. Table 2 Summary of the forest plot and Egger’s test results for each maternal factor. Maternal Factor n OR 95% CI I² (%) χ² Chi-square p t Egger's test p Cesarean Section 18 1.16 0.92–1.40 86.8 128.86 < 0.001 0.00 0.9992 Smoking during pregnancy 10 1.75 1.26–2.25 87.1 69.84 < 0.001 2.61 0.0313 Chorioamnionitis 19 2.41 0.59–4.23 99.3 2533.23 < 0.001 0.86 0.4029 Diabetes Mellitus 6 1.07 0.66–1.47 0 2.94 0.71 -0.32 0.7677 No Education 3 0.9 0.53–1.27 29 2.81 0.24 -4.41 0.1421 Over 12 Years of Education 4 1.6 0.54–2.66 85.2 20.27 < 0.001 0.80 0.5088 Preeclampsia 8 2.03 1.43–2.63 95.3 148.82 < 0.001 0.82 0.4437 Assessment of Heterogeneity The Chi-square and Higgins and Thompson I 2 statistics were used to quantify the extent of heterogeneity across studies. While the chi-square test determines whether the heterogeneity observed is due to random chance, the I 2 statistic quantifies the degree of heterogeneity. As summarized in Table 2 , the maternal factors Cesarean Section (χ²=128.86, p < 0.001, I 2 = 86.8), smoking during pregnancy (χ²=69.84, p < 0.001, I 2 = 87.1), chorioamnionitis (χ²=2533.23, p < 0.001, I 2 = 99.3), over 12 years of education (χ²=20.27, p < 0.001, I 2 = 95.3), and preeclampsia (χ²=148.82, p < 0.001, I 2 = 95.3) exhibited significant heterogeneity. Conversely, Diabetes Mellitus and no education did not show significant heterogeneity. Funnel Plot Analysis and Egger’s Test Funnel plots shown in Fig. 6 were used to assess publication bias, while Egger’s test was used to assess whether small-study effects or publication bias were present. We did not find evidence of publication bias for all maternal factors, except for smoking during pregnancy, which exhibited significant asymmetry. The maternal factor, smoking during pregnancy, displayed significant asymmetry (t = 2.61, p = 0.0313). This asymmetry was likely influenced by smaller studies with larger effect sizes that skewed to the right of the pooled OR. In particular, three small studies fell within significant regions (p < 0.05), indicating a potential influence of selective reporting or small-study effects. Discussion Key Findings With the high mortality rate of NEC and its prevalence in preterm infants, it is vital to understand how this disease manifests. This meta-analysis examined the risk of seven maternal factors on the development of NEC. Our review reveals that across studies, maternal smoking and preeclampsia have a statistically significant positive association with the development of NEC. The significant finding of the association between maternal smoking and NEC aligns with prior research investigating the effect of smoking on fetal development and neonatal outcomes. 89 Previous studies have identified that smoking during pregnancy is associated with preterm birth, FGR, and neonatal respiratory and gastrointestinal diseases, all of which predispose an infant to NEC. Fetal hypoxia has also been attributed to maternal smoking, damaging the intestinal barrier. 90 Damage to the intestinal barrier is known as one of the major pathological factors contributing to NEC development. 91 As well, maternal smoking can cause microvascular changes in the placenta that could cause placental insufficiency. This abnormal development of the placental vascularization in the case of maternal smoking can decrease nutrient and circulation exchange between the mother and the fetus. 92 This insufficiency can lead to complications such as gestational hypertension, FGR, and premature birth. Moreover, our results highlight the critical need for targeted smoking cessation interventions during pregnancy to mitigate the risk of NEC and improve neonatal outcomes. Additionally, previous literature supports preeclampsia as a risk factor for NEC. 63 Preeclampsia is a hypertensive disorder during pregnancy. 93 Preeclampsia is characterized by new-onset hypertension, sometimes accompanied with protein in the urine. This disorder usually manifests itself after 20 weeks of gestation and exists on a spectrum of severity. In severe cases, for the mother, there can be organ damage, particularly to the kidneys, liver, and blood. As well, fluid buildup is a complication associated with preeclampsia, which can lead to pulmonary edema. Preeclampsia is a leading cause of Cesarean sections and maternal and fetal mortality worldwide. 93 With preeclampsia, fetal blood flow is restricted due to placental hypoperfusion, which leads to FGR. 94 Infants born to mothers with preeclampsia have a birth weight 5% lower compared to those born to mothers with normal blood pressure. When the mother has preeclampsia, the fetus is often deprived of adequate placental blood flow, resulting in an abnormal intrauterine environment that can necessitate medically indicated preterm delivery. As preeclampsia is linked to low birth weight and early delivery, gut and intestinal maturation may be compromised, increasing the infant's susceptibility to necrotizing enterocolitis. Furthermore, our findings recapitulate the link between preeclampsia and NEC. In contrast, there were no other statistically significant associations between Cesarean section delivery, diabetes, chorioamnionitis, and maternal education on the development of NEC. However, there was significant heterogeneity between studies (I 2 = 68.0%), suggesting that inconsistencies in findings may be due to variation in study methodologies. Despite conflicting results in studies investigating Cesarean sections and NEC, our study amplifies that, across the literature, there is no definitive connection between the development of NEC and Cesarean section delivery. 14 Further, we believe there is no increased risk of NEC via Cesarean section delivery. Some argue that the route of delivery can affect the microbiome, where infants delivered by Cesarean section are not exposed to the mother’s vaginal and perineal microbiome, which has beneficial bacteria. 95 Instead, their microbiome is usually colonized by bacteria from the mother’s skin and the hospital environment, which could be pathogenic. 14 However, Cesarean sections are often performed when there are signs of fetal distress or to avoid a difficult vaginal birth, where there could be reduced oxygen flow to the infant. 96 So, it could be hypothesized that Cesarean sections could be protective of NEC by preventing oxygen deprivation and compromised circulation to the intestines. Further, the relationship between delivery methods and NEC development is likely complex and could be related to other factors such as gestational age, feeding practices, and the presence of underlying medical conditions in the infant or mother. Further work could be done by conducting a large multicenter cohort study with detailed maternal and perinatal records to adjust for associations such as gestational age, birth weight, CHD, FGR, and maternal characteristics and demographics, to validate that Cesarean section delivery is not associated with the development of NEC. Similarly, we did not detect evidence of a significant pooled risk of developing NEC if the mother had chorioamnionitis. Chorioamnionitis, a disease where the membranes surrounding the fetus are infected by bacteria, can disrupt the development of the infant’s intestines and trigger systemic inflammation in the womb. 97 While some studies and reviews have reported a positive association between chorioamnionitis and NEC, our analysis of the available literature found no overall significant risk. However, there was significant heterogeneity between the studies, indicating that the studies did not have consistent results. The wide range of effect sizes and heterogeneity could reflect variation in the study designs and imply that differences in the time and severity of chorioamnionitis influence fetal outcomes. In addition, while diabetes mellitus is linked to neonatal complications such as congenital anomalies, FGR, and various birth defects, our results indicated that across the studies analyzed, it did not emerge as a significant risk factor for NEC. One meta-analysis by Su et al. (2023) reported diabetes mellitus as a significant risk factor for NEC. 17 A reason for the discrepancy in findings could be due to differences in the studies used because of inclusion and exclusion criteria. Our meta-analysis also contains more recent studies, which may reflect shifts in clinical outcomes over time. While NEC has lagged, neonatology as a field has changed dramatically in the past half-century. In recent years, there have been advances in diagnostic tools and clinical practices, and changes in patient populations. Additionally, over time, there are shifting maternal demographics, evolving lifestyles, and environmental stressors. Further, using a large timeframe and including more recent studies can illuminate how diagnosis, patient demographics, and treatment have evolved, modifying the relationship between NEC and diabetes mellitus, as well as other possible maternal risk factors. Our meta-analysis, to our knowledge, is one of the few to test for an association between maternal education and NEC. Even though higher maternal education can be linked to better infant health outcomes, there was no overall association between the mother receiving over twelve years of education and NEC. 98 As well, the overall association between the mother receiving no education and the development of NEC was not significant. This aligns with current but limited research investigating maternal education and NEC. Moreover, our findings, as well as those of other studies, show that education does not appear to be a risk factor for NEC. Limitations First, the number of studies used for each maternal factor was relatively small, especially for preeclampsia, maternal education, and diabetes. While having a limited number of studies does not invalidate the findings, it may obscure or exaggerate the detection of a significant risk. A small number of studies included in the meta-analysis could also limit the statistical power of determining the presence of publication bias. When testing for publication bias with fewer than ten studies, using funnel plots and Egger’s regression test becomes less reliable due to limited data from too few studies being present. Testing for publication bias by funnel plot and Egger’s regression test when fewer than ten studies are included in the meta-analysis is typically less reliable, as it is hard to determine any asymmetry with too few studies present. 99 Further, even if funnel plots visually show symmetry and Egger’s regression test quantifies no significant asymmetry, there still could be publication bias. If published studies show significant results in different directions, there could still be selective reporting, but it is masked by the symmetry of the funnel plot. So, the visual symmetry may obscure true bias, and these methods should be cautiously interpreted and not used as definitive indicators of the presence or absence of publication bias. Second, our analysis only examined the univariate relationships between NEC and the given maternal factor, without considering multiple factors simultaneously. Considering only one variable at a time does not allow us to examine interactions between variables. For instance, risk factors for preeclampsia include hypertension, diabetes, and advanced maternal age. These factors are also shown to be independently associated with FGR and preterm delivery. 100 Given that FGR and preterm delivery are risk factors for NEC, one can question whether preeclampsia itself increases the risk of NEC or if it is just associated with other underlying risk factors. In the same vein, maternal hypertension, FGR, and preterm birth are associated with maternal smoking, making it difficult to deduce the effect of each individual factor on NEC risk. Considering NEC is a complex, multifactorial disease, this analysis may have missed important complexities that would have allowed us to understand more in-depth how and which maternal risk factors are associated with the development of NEC. Third, the studies that reported the incidence of NEC if the mother smoked throughout pregnancy did not quantify the extent of smoking. “Smoking throughout pregnancy” is a generalization that can vary greatly for each mother. This broad categorization does not allow us to examine the true effect of smoking on NEC, such as whether a higher level of smoking increases the risk or if any amount of smoking is sufficient to contribute to the development of NEC. Fourth, it is important to note that the significant heterogeneity between studies may be attributed to the inclusion of studies spanning over a large timeframe. Varying populations were included, and NEC was defined using different criteria. For instance, Bell’s stage 1 includes many infants with suspected NEC, and ICD-9 and 10 codes are NEC-stage unspecified. So, studies using Bell’s stage 1 and ICD-9 and 10 codes as NEC diagnosis criteria probably introduced a pool of infants that did not actually have NEC. Furthermore, this mixture of different populations and epochs introduced substantial heterogeneity that likely decreased the sensitivity of some maternal risk factors. Implications of Results and Future Research The significant overall estimated risk of developing NEC if the mother smokes during pregnancy warrants emphasis on prevention strategies for smoking during pregnancy. Kipling et al. found that in 2021, 5.4% of pregnant women reported that they smoked during pregnancy. 101 This statistic highlights the need to find ways to prevent smoking during pregnancy, especially given the adverse neonatal outcomes and the positive association between smoking and NEC found in this meta-analysis. Further research should be conducted to further confirm smoking as an NEC risk factor and to understand its relationship and interaction with other factors, such as maternal feeding, race, and socioeconomic status, to provide deeper insights into NEC development. A prospective multicenter cohort study with NEC as the primary outcome could be conducted to collect detailed data on smoking exposure and its relationship with NEC development. A multivariate analysis could be done to examine the effect of smoking on NEC development and whether that relationship is modified by any other factor. Researchers can also attempt to elucidate the mechanism underlying the relationship between smoking and NEC, specifically looking at how the nicotine, tobacco, and other toxins contained in cigarettes affect neonatal gastrointestinal development. Given the high maternal and fetal mortality rates associated with preeclampsia, strategies to reduce its incidence are critical. Prior research has explored preventative approaches, such as a study conducted by Esquivel (2022), which found that nutritional modifications, such as increasing calcium and vitamin D intake, can reduce the risk of preeclampsia. 102 Some also suggest that physical activity can decrease the risk of preeclampsia. 103 , 104 The 103% estimated increased risk of NEC when the mother has preeclampsia could be indirectly mitigated with these intervention strategies to reduce preeclampsia risk. It is also important to conduct further research to confirm preeclampsia’s significant relationship with NEC development, considering that preeclampsia is a common complication of pregnancy. 93 A multivariate analysis could be conducted to investigate whether preeclampsia is independently associated with NEC, or whether the observed increased risk can be attributed to preeclampsia’s established association with NEC risk factors, such as FGR and compromised intestinal maturation. The lack of significant findings for the five other maternal factors may reflect more nuanced interactions between risk factors. The insignificant findings may also indicate that these maternal factors are not actual risk factors for NEC. Rather than investigating each factor independently, further research should be conducted to examine how these factors interact and contribute to the development of NEC together. ​​Understanding these complex relationships could help identify prevention strategies for NEC. In addition, performing larger-scale studies to understand how these maternal factors relate, specifically in relation to race and socioeconomic status, could reveal how to effectively identify high-risk groups and attempt to reduce the incidence of NEC. Declarations Availability of Materials The data used to compute each of the forest and funnel plots, as well as the risk of bias plot in this study can be found in our data repository. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7348561","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":502025702,"identity":"7cf72c5d-5c00-4fe9-ac00-d514256b6650","order_by":0,"name":"Lindsey Burnham","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA7UlEQVRIiWNgGAWjYBACPgYeEHWAgYG9geEAD5sFgwFEghmnFja4Fp4DIC0SpGiRSABqI0qL2Nlj0pU77sjrznydeOBNmYScuUTuMwmGCuvEBlxapPPSJM+eeWa47XbuhoNzzkkYW85IN5NgOJOOR0uOmWRj22FGkJbDvG0SiRtupLFJMLYdJqjFftvNs2At9RAt/whrSdx2gxesJcEArKUBn5a8ZEugluRtZyB+MdzZ84zZIuFYujEuLfzSuQdvArXYbjt+dvOHN2U28ubsaYw3PtRYy+LSghWwgOKINMD8gVQdo2AUjIJRMKwBAK7HXgdNdVq7AAAAAElFTkSuQmCC","orcid":"","institution":"Middlebury College","correspondingAuthor":true,"prefix":"","firstName":"Lindsey","middleName":"","lastName":"Burnham","suffix":""},{"id":502025703,"identity":"1a8d7de3-8138-48ee-a38b-af8e203eae6c","order_by":1,"name":"Will Lichstein","email":"","orcid":"","institution":"Middlebury College","correspondingAuthor":false,"prefix":"","firstName":"Will","middleName":"","lastName":"Lichstein","suffix":""},{"id":502025704,"identity":"ebab0131-9677-4da6-b68b-5079a214d1a6","order_by":2,"name":"Alex Lyford","email":"","orcid":"","institution":"Middlebury College","correspondingAuthor":false,"prefix":"","firstName":"Alex","middleName":"","lastName":"Lyford","suffix":""}],"badges":[],"createdAt":"2025-08-11 17:08:16","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7348561/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7348561/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":89388265,"identity":"6d16970d-58d8-4ffd-bd3c-b44802e5b3f6","added_by":"auto","created_at":"2025-08-19 12:41:12","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":91517,"visible":true,"origin":"","legend":"\u003cp\u003ePRISMA flowchart of study selection\u003c/p\u003e","description":"","filename":"image1.png","url":"https://assets-eu.researchsquare.com/files/rs-7348561/v1/47a9b9cf9907e00ea0db3469.png"},{"id":89388270,"identity":"ef55d7ee-c00a-49ac-90ce-8b8c65c72f8b","added_by":"auto","created_at":"2025-08-19 12:41:13","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":814709,"visible":true,"origin":"","legend":"\u003cp\u003eForest plot using random effects model depicting the effect of giving birth through a Cesarean Section on the development of NEC.\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-7348561/v1/93dc44feb72eaa1913632904.png"},{"id":89388266,"identity":"9551a1b9-cc8b-4118-9d9c-e5ad6f622719","added_by":"auto","created_at":"2025-08-19 12:41:12","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":98984,"visible":true,"origin":"","legend":"\u003cp\u003eFunnel plot to assess for publication bias in studies that investigate the relationship between mothers having a Cesarean Section and the development of NEC in their infants.\u003c/p\u003e","description":"","filename":"image3.png","url":"https://assets-eu.researchsquare.com/files/rs-7348561/v1/c2463744174b288c2de28868.png"},{"id":89389608,"identity":"f3edaedf-0678-44b5-aaf3-2a2ad6d062c8","added_by":"auto","created_at":"2025-08-19 12:49:12","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":67067,"visible":true,"origin":"","legend":"\u003cp\u003eRisk of bias assessment using the Hoy et al. (2012) risk of bias tool for the 39 studies included in this meta-analysis.\u003c/p\u003e","description":"","filename":"image4.png","url":"https://assets-eu.researchsquare.com/files/rs-7348561/v1/f3616c207114bdb68d29384a.png"},{"id":89388269,"identity":"157ec7ac-48ee-46b1-abbe-9db8fce48b81","added_by":"auto","created_at":"2025-08-19 12:41:13","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":402689,"visible":true,"origin":"","legend":"\u003cp\u003eForest plots using a random effects model for the risk of NEC if the mother \u003cstrong\u003eA)\u003c/strong\u003e had a Cesarean-Section, \u003cstrong\u003eB)\u003c/strong\u003e smoked, \u003cstrong\u003eC)\u003c/strong\u003e had Chorioamnionitis, \u003cstrong\u003eD)\u003c/strong\u003ehad Diabetes Mellitus, \u003cstrong\u003eE) \u003c/strong\u003ehad no education, \u003cstrong\u003eF) \u003c/strong\u003ereceived over 12 years of education, or \u003cstrong\u003eG)\u003c/strong\u003e had Preeclampsia.\u003c/p\u003e","description":"","filename":"image5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7348561/v1/365a0c881811feb8aa5ba019.jpg"},{"id":89390630,"identity":"a0b9a85c-3cfb-4a09-92f8-e4eca47062ea","added_by":"auto","created_at":"2025-08-19 12:57:13","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":192796,"visible":true,"origin":"","legend":"\u003cp\u003eFunnel plots to assess for publication bias in studies investigating the relationship between the development of NEC and if the mother \u003cstrong\u003eA)\u003c/strong\u003e had a Cesarean-Section, \u003cstrong\u003eB)\u003c/strong\u003esmoked, \u003cstrong\u003eC)\u003c/strong\u003e had Chorioamnionitis, \u003cstrong\u003eD)\u003c/strong\u003e had Diabetes mellitus, \u003cstrong\u003eE) \u003c/strong\u003ehad no education, \u003cstrong\u003eF) \u003c/strong\u003ereceived over 12 years of education, or \u003cstrong\u003eG)\u003c/strong\u003e had Preeclampsia.\u003c/p\u003e","description":"","filename":"image6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7348561/v1/c60d2f6fd238dde16922fc56.jpg"},{"id":89392299,"identity":"29ade3c3-f7ee-40c2-bfe7-0485d8568e10","added_by":"auto","created_at":"2025-08-19 13:13:18","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2302304,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7348561/v1/d432cf7e-a38e-4b1a-b6f1-bd477b796238.pdf"},{"id":89389614,"identity":"3180d234-91d3-4f49-b213-671d2663dbed","added_by":"auto","created_at":"2025-08-19 12:49:13","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":92957,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTable 1. \u003c/strong\u003eCharacteristics of Included Studies\u003c/p\u003e","description":"","filename":"Burnhametal.includedstudycharacteristics.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7348561/v1/92d14f7703eceeefe493e06b.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Maternal Risk Factors Associated with Neonatal Necrotizing Enterocolitis: a Meta-Analysis and Systematic Review","fulltext":[{"header":"Introduction and Background","content":"\u003cp\u003eNeonatal Necrotizing Enterocolitis (NEC) is an intestinal inflammatory disease that affects primarily very low birth weight (VLBW, \u0026lt;\u0026thinsp;1500g birth weight) or premature infants.\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e Specifically, NEC is characterized by inflammation in parts of the intestine, often in the setting of tissue ischemia, usually affecting the distal ileum.\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e Because there is a lack of blood flow to parts of the intestine, intestinal tissue can die, and the intestinal mucosa can be damaged.\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e The intestinal mucosa is the innermost layer of the intestine, separating the gut lumen (the hollow part of the intestine) from the other layers of the intestine and the rest of the body.\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e The intestinal mucosa is an essential protective barrier, regulating what substances from the gut lumen get absorbed into the bloodstream and the lymphatic system while also preventing harmful pathogens from passing the mucosa and entering the rest of the body.\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e When the intestinal mucosa is damaged, bacterial translocation can occur where harmful bacteria from the lumen can invade deeper tissues, exacerbating inflammation and perpetuating a cycle of intestinal wall damage, death, and, in severe cases, perforation.\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e NEC progression can lead to sepsis, peritonitis, and death. While NEC only affects 2\u0026ndash;5% of premature infants and 8% of neonatal intensive care unit (NICU)-admitted infants, its high mortality rate of 20\u0026ndash;30%, as well as long-term effects on the intestines and neurodevelopment, make it a concern in neonatal care.\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eAlthough researchers have been studying NEC for decades, the approach to treating it has remained largely unchanged.\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e Milder cases of NEC are treated with various methods, including antibiotics, bowel rest, and close monitoring. For more severe cases of NEC, such as those with intestinal perforation, surgery is typically required. Surgery for NEC can involve resection of damaged and dead intestinal tissue, as well as creating a hole on the abdomen, known as an ostomy, to allow enteral contents to leave the body if the digestive system is not functioning properly.\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e Surgery can also involve draining the peritoneal cavity to allow the fluid and gas build-up caused by NEC to drain. If surgery is needed to treat NEC, the mortality rate increases to approximately 50%.\u003c/p\u003e\u003cp\u003eOne pertinent issue present is that even with decades of research, many factors that contribute to the development of NEC are not fully characterized.\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e Current literature has found that most NEC cases are among premature and VLBW infants.\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e One study by Singh et al. (2023) noted that 90% of NEC infants are born prematurely.\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e The reasons behind the increased risk of prematurity and VLBW infants developing NEC stem from the fact that they are more likely to have immature intestinal function.\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e If the intestinal tract is immature, the feedings the infants receive may move slower, which may lead to bacterial overgrowth, inflammation, and damage to the intestinal mucosa, contributing to NEC development.\u003c/p\u003e\u003cp\u003eFetal growth restriction (FGR) due to placental insufficiency has also been identified as a risk factor.\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e FGR is a condition in which a fetus is smaller than its expected gestational age in utero. In the setting of placental insufficiency, a fetus does not get the required oxygen and nutrients that are necessary to support growth. Researchers hypothesize that there could be in utero fetal hypoxia, which could result in blood flow redistribution away from the gastrointestinal tract. This condition could then result in an ischemic hit that disrupts intestinal formation and development, which could increase the risk of developing NEC.\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eResearchers have also investigated the effect of formula feeding on the development of NEC and found that premature infants may have a decreased risk of NEC if they are fed mostly breast milk instead of formula or a combination of breast milk and formula.\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e,\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e In addition, there is strong evidence indicating that antenatal corticosteroid (ACS) therapy decreases NEC risk in certain high-risk populations of infants.\u003csup\u003e\u003cspan additionalcitationids=\"CR21 CR22\" citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eNEC may also manifest in term infants, particularly in those with congenital heart disease (CHD), who are at an elevated risk.\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e This risk could be due to infants with CHD having poor diastolic pressure and mixed lesions where deoxygenated blood mixes into systemic circulation, leading to decreased oxygen delivery to the body\u0026rsquo;s tissues and organs.\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e Such conditions could lead to decreased oxygen delivery to the intestines before and after delivery, which could then result in mesenteric hypoperfusion and ischaemic bowel.\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e Infants with CHD who underwent surgery can also be vulnerable to developing NEC in the postoperative period.\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e These surgeries, such as systemic-to-pulmonary shunt procedures and cardiac lesion procedures, can compromise blood flow to the digestive system as well as alter blood flow patterns. These complications can result in hypoperfusion in the intestines, which can lead to gut necrosis and further put infants with CHD at risk for NEC.\u003c/p\u003e\u003cp\u003eIn the United States, studies have shown that both Hispanic neonates and non-Hispanic Black neonates have a higher risk of developing NEC.\u003csup\u003e\u003cspan additionalcitationids=\"CR28\" citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e` Even when controlling for VLBW and prematurity, there is still an increased rate of Black and Hispanic infants developing NEC compared to white infants.\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e,\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e Infants born to Black and Hispanic mothers face a higher risk of conditions that are risk factors for NEC, such as limited access to prenatal care, lower rates of breastfeeding, increased risk of FGR, intrauterine growth restriction (IUGR), and prematurity.\u003csup\u003e\u003cspan additionalcitationids=\"CR32\" citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e Goldstein et al. (2020) show that white infants receive more human milk than Black and Hispanic infants.\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e In their univariate model examining the relationship between ethnicity and the development of NEC, Black and Hispanic infants have significantly higher odds of developing NEC compared to white infants. However, when using a multivariate model controlling for human milk, there was no longer a statistically significant increase in the odds of developing NEC. This study emphasized the possible role of human milk in preventing NEC and underscored the racial disparities in its delivery to infants. In a study conducted by Lind et al. (2014), researchers reported that hospitals in zip codes in the United States with a higher-than-average percentage of Black residents were significantly more likely to not meet the standards to support breastfeeding compared to hospitals in zip codes with a lower-than-average percentage of Black residents.\u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eNEC is a multifactorial illness with a complex interplay between contributing risk factors.\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e While some researchers have singularly focused on factors such as VLBW, prematurity, breastfeeding, and corticosteroid therapy, others have taken the approach to broadly study multiple risk factors through meta-analysis and systematic reviews.\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e,\u003cspan additionalcitationids=\"CR36 CR37\" citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e One meta-analysis reviewed literature that discusses methods of identifying medical vs. surgical NEC and the most effective methods.\u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e Another meta-analysis investigated the global incidence of NEC, finding that from 1993 to 2018, there was a significant increase in the incidence of NEC.\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e Others broadly reviewed a plethora of risk factors for neonates, such as VLBW, prematurity, and congenital heart disease.\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e,\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e Others specifically investigate risk factors such as chorioamnionitis, human milk, antibiotic exposure, and administering antenatal corticosteroids.\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e,\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e,\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e In addition, systematic reviews, such as one done by Lin et al. (2014), have summarized some prevention strategies for NEC.\u003csup\u003e\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e Lin et al. reinforce that probiotics and breastfeeding are plausible methods for preventing NEC.\u003c/p\u003e\u003cp\u003eEven with a variety of literature regarding risk factors related to NEC and despite extensive efforts, we still haven\u0026rsquo;t fully determined the risk of maternal risk factors, such as smoking, on the development of NEC. This meta-analysis aims to investigate maternal factors present in the available literature and their association with NEC. Further, this meta-analysis will explore the potential risk of Cesarean section, smoking, preeclampsia, chorioamnionitis, diabetes mellitus, and education on the development of NEC.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eEligibility Criteria\u003c/h2\u003e\u003cp\u003eStudies deemed eligible for this meta-analysis were case-control, retrospective cohort, and population-based registry studies focusing on NEC in preterm infants. We did not limit studies to those with NEC as a primary outcome. Rather, only studies that assessed the incidence of NEC in infants based on the presence or absence of Cesarean section, preeclampsia, smoking, diabetes, chorioamnionitis, or maternal education were included. Studies were excluded if the NEC incidence rate associated with a specific maternal factor could not be extracted from the data provided. Studies that only included death records were excluded from our meta-analysis, as accounting only for deaths could underrepresent the true incidence of NEC, affecting the association between specific maternal factors and NEC. For inclusion, the sampling frame needed to be representative of the general population of mothers/infants. In addition, studies that only included full-term infants were excluded, as NEC is most prevalent in VLBW and premature infants, so this study group does not represent the general population of infants with NEC.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eLiterature Search and Data Extraction\u003c/h3\u003e\n\u003cp\u003eFigure \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e illustrates the flowchart of study selection for our meta-analysis, adhering to the PRISMA guidelines.\u003csup\u003e\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e Two authors independently searched Nature, Scopus, PubMed, and Google Scholar between September 2024 and April 2025 for cohort, population studies, systematic reviews, and meta-analyses.\u003csup\u003e\u003cspan additionalcitationids=\"CR7 CR8\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e The search terms \u0026ldquo;necrotizing enterocolitis,\u0026rdquo; \u0026ldquo;maternal risk,\u0026rdquo; \u0026ldquo;maternal factors,\u0026rdquo; \u0026ldquo;smoking,\u0026rdquo; \u0026ldquo;preeclampsia\u0026rdquo;, \u0026ldquo;chorioamnionitis,\u0026rdquo; and/or \u0026ldquo;diabetes\u0026rdquo; were used to narrow down results. Both authors reviewed journal article abstracts to see if they met the inclusion criteria. Afterward, the titles and abstracts of studies that met the initial criteria were evaluated, paying particular attention to the type of article, study goals, and the study population. In addition, studies were narrowed down based on whether they had \u0026ldquo;necrotizing enterocolitis\u0026rdquo; in their title. 74 studies were found among the two authors, tabulated with the corresponding maternal factors they included. Surgical and non-surgical cases of NEC were included, as we aimed to assess how maternal factors influenced the incidence of NEC rather than its severity. Additionally, there is a large overlap in risk factors for surgical and medical NEC, with the primary distinction being the severity of these factors.\u003csup\u003e\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e After evaluating each study, the two authors met and resolved discrepancies, ultimately including 39 studies in this comprehensive search, which included the specific maternal factors we examined in their results. The study\u0026rsquo;s population size and number of infants with NEC whose mothers had or didn\u0026rsquo;t have the specific maternal risk factor were tabulated. The years the studies started and ended were also recorded, and the odds ratios (OR) with their corresponding 95% confidence intervals were calculated using Fisher\u0026rsquo;s exact test.\u003csup\u003e\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\n\u003ch3\u003eQuality Assessment\u003c/h3\u003e\n\u003cp\u003eWe used the Hoy et al. (2012) risk of bias tool to assess the risk of bias in each study. The Hoy et al. (2012) tool presents eight yes-or-no questions, or \u0026ldquo;domains,\u0026rdquo; that encapsulate four main bias categories for non-randomized studies. The first category is external validity, which assesses whether the sampling frame accurately represents the target population of preterm infants. The question asked in this category is: \u0026ldquo;Was the study\u0026rsquo;s target population a close representation of the national population in relation to relevant variables?\u0026rdquo; In addition, this category assesses whether data were collected randomly or in the form of a census, specifically asking: \u0026ldquo;Was some form of random selection used to select the sample, OR was a census undertaken?\u0026rdquo; The second category is internal validity in participation selection, which asks, \u0026ldquo;Was the likelihood of nonresponse bias minimal?\u0026rdquo; This ensures that respondents and non-responders don\u0026rsquo;t differ significantly. For example, if more mothers who didn\u0026rsquo;t smoke during their pregnancy participated compared to mothers who did smoke, the results could be skewed. In addition, this category asks the specific question, \u0026ldquo;Were data collected directly from the subjects (as opposed to a proxy)?\u0026rdquo; to evaluate the potential for bias stemming from second-hand reported data. The third category assesses how the study collected and analyzed its data. For example, the risk of bias tool asks, \u0026ldquo;Was an acceptable case definition used in the study?\u0026rdquo; (e.g., Bell\u0026rsquo;s staging criteria and/or ICD9 and 10 codes). This category also contains the questions, \u0026ldquo;Was the study instrument that measured the parameter of interest shown to have validity and reliability?\u0026rdquo; and \u0026ldquo;Was the same mode of data collection used for all subjects?\u0026rdquo; to investigate whether data were assessed in the same way. For example, all data were extracted from the same dataset and evaluated using consistent diagnostic criteria across all subjects. Finally, the fourth category examines how studies analyze their data, specifically investigating the sample size and whether the proportion of infants with NEC was not underrepresented. This final category asks, \u0026ldquo;Were the numerator(s) and denominator(s) for the parameter of interest appropriate?\u0026rdquo; We evaluated whether the numerator and denominator were large enough in magnitude to make reasonable OR estimations. In addition, studies were deemed to have a high risk of bias if the proportion of infants with NEC was below 2%, which is in line with the rate of NEC development in premature infants. Two authors independently evaluated the risk of bias to determine whether studies introduced biases from sampling methodologies that could have led to misleading results. First, 10 of the 39 articles were evaluated using these parameters, and then the authors met to discuss their decisions and resolve any discrepancies in evaluation. After meeting, the other 29 studies were reviewed, and interrater reliability was assessed using Cohen\u0026rsquo;s Kappa.\u003c/p\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003eStatistical Analysis\u003c/h2\u003e\u003cdiv id=\"Sec7\" class=\"Section3\"\u003e\u003ch2\u003eForest Plots\u003c/h2\u003e\u003cp\u003eWe performed all statistical analyses for this study in R \u003cem\u003e(v4.4.3, R Core Team 2025)\u003c/em\u003e.\u003csup\u003e\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e We made forest plots using the \u0026ldquo;meta\u0026rdquo; package (Baldudzzi et al, 2019) for each maternal factor.\u003csup\u003e\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u003c/sup\u003e Forest plots graphically present the results of multiple studies, showing individual risk estimates (e.g., the risk of developing NEC if the mother had a Cesarean section), along with their confidence intervals and a pooled overall estimate. They help determine whether, given the available studies, a maternal factor significantly increases or decreases the risk of NEC. Figure\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e illustrates a forest plot examining the relationship between Cesarean sections and NEC development. Forest plots display each study\u0026rsquo;s estimate of the OR (red square), the 95% confidence interval estimate for the OR (black line), and the overall estimate of the OR (blue diamond) given all of the studies included in the meta-analysis. An OR is a measurement to compare the odds of an event occurring in one group vs. another. By doing this, an OR can quantify the strength of association between an exposure and an outcome. An example of an OR is the ratio of the probability of the development of NEC if the mother smoked and the probability of the development of NEC if the mother did not smoke. An OR of 1 indicates no increased risk of NEC for mothers who smoke. In contrast, an OR greater than 1 suggests that mothers who smoked during pregnancy have elevated odds of their infants developing NEC. Conversely, an OR of less than 1 implies that the exposed group has reduced odds of the outcome. In addition, each study is weighted inversely to its variance so that studies with larger samples and more precise estimates are weighted more heavily. Weighting each study in this way has been shown to yield a more accurate and reliable overall effect estimate.\u003csup\u003e\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e We used a random effects model to summarize the studies\u0026rsquo; overall OR at the bottom of the forest plot. A random effects model considers variance within a study and between studies to produce an overall effect estimate.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eHeterogeneity\u003c/h2\u003e\u003cp\u003eFor any meta-analysis, it is important to quantify whether the estimated effect size of a particular factor (e.g., maternal smoking status) on the outcome (e.g., the development of NEC) between individual studies is \u0026lsquo;similar enough\u0026rsquo; to be plausible. To quantify this, we use Higgins and Thompson\u0026rsquo;s I\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e Statistic to assess the between-study heterogeneity.\u003csup\u003e\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u003c/sup\u003e Heterogeneity in a meta-analysis is the variation in the effect sizes\u0026mdash;the strength of the relationship between variables\u0026mdash;between the analyzed studies. We can evaluate effect sizes through the OR, which reports whether a mother having a certain maternal factor will increase or decrease the odds of the infant developing NEC. When quantifying observed effects between studies, two types of variation arise: sampling error and between-study heterogeneity. The I\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e statistic aims to quantify between-study heterogeneity: variation in study results beyond sampling error. This statistic is represented as a percentage, where an I\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;\u0026lt;\u0026thinsp;25% indicates low heterogeneity, 25% \u0026le; I\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;\u0026lt;\u0026thinsp;75% indicates moderate heterogeneity, and 75% \u0026le; I\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;\u0026le;\u0026thinsp;100% indicates substantial heterogeneity. Refer to Higgins and Thompson (2002) for the details of the rationale and proof of the validity of this statistic.\u003csup\u003e\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003ePublication Bias\u003c/h3\u003e\n\u003cp\u003ePublication bias is the phenomenon where studies with statistically significant results and larger sample sizes are more likely to be published than those without statistically significant findings/and or with smaller sample sizes. We therefore include a measurement to determine whether there is any publication bias included in this study. To do so, this study uses small-study effect methods. Sterne et al. (2000) define small study effects as:\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eA tendency for treatment effect estimates in small studies to differ from those in larger studies [which] may have distorted the results of a meta-analysis. This could be due to publication bias, other reporting biases, low methodological quality of smaller studies or true heterogeneity in treatment effects.\u003csup\u003e\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThe small-study effect methods used in this study are funnel plots and Egger\u0026rsquo;s regression test. A funnel plot is a graphical method for assessing the potential for publication bias. Figure\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e is an example of a funnel plot to assess for publication bias in the studies that investigate the relationship between Cesarean sections and the development of NEC in infants. The standard error of effect sizes for each study is plotted on the y-axis, and the logged OR (the logged odds of an NEC occurring given that the maternal factor measured is present) for each study is plotted on the x-axis. The OR was logged due to the inherent asymmetry of the raw OR scale. For example, an OR of 2 (indicating twice the odds) and an OR of 0.5 (indicating half the odds) are not equidistant from the null OR value of 1. Logging the OR creates symmetry about the null log(OR) of 0 (since log(1)\u0026thinsp;=\u0026thinsp;0). This transformation allows us to test the assumption that the relationship between the log(OR) and the standard error is linear through Egger\u0026rsquo;s test.\u003c/p\u003e\u003cp\u003eA funnel plot can test for asymmetry, meaning the distribution of study results is more likely to be distorted on a funnel plot. Asymmetry can be determined by plotting the standard error for each study on the y-axis vs. the estimated log(OR) of developing NEC given the mother has a specific maternal factor, such as having a Cesarean section, for each study on the x-axis. If the points plotted are asymmetrical across the overall aggregation of all studies' estimated log(OR) weighted by the inverse of their calculated variance (dotted vertical line), there is a possibility that there is publication bias in the meta-analysis. This is because the asymmetry in the funnel plot suggests that smaller studies with nonsignificant or negative results may be missing from the literature, potentially skewing the meta-analysis to an exaggerated or more favorable effect. In Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, the studies are scattered relatively symmetrically about the vertical dotted line, leading us to suspect publication bias is unlikely. This study enhances the funnel plot by adding shades of gray (the shaded triangles) to indicate statistical significance thresholds (p values\u0026thinsp;\u0026lt;\u0026thinsp;0.1, 0.05, and 0.01). These significance thresholds indicate whether the risk of developing NEC, given the mother has a specific maternal factor for each study, is due to more than random chance. The thresholds center around 0, as the null hypothesis is that log(OR)\u0026thinsp;=\u0026thinsp;0. Log(OR)s that are farther away from 0 are increasingly unlikely to arise by chance Adding significance thresholds allows us to see trends in whether studies were published because of significance If most small studies (which are lower on the plot because they have a larger standard error) fall in the significant regions (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), there could be potential publication bias because this result indicates that there are a lack small studies in literature with nonsignificant results. In Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, we observe that the studies with a larger standard error fall within the non-significant regions (the white region where p\u0026thinsp;\u0026gt;\u0026thinsp;0.1).\u003c/p\u003e\u003cp\u003eWhile a funnel plot can suggest potential asymmetry, a formal test is necessary to confirm it. Egger\u0026rsquo;s Regression Test provides a quantitative method for measuring small study effects by examining funnel plot asymmetry using a linear regression approach.\u003csup\u003e\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u003c/sup\u003e Refer to the supplementary material for an in-depth explanation of Egger\u0026rsquo;s Regression Test.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eSystematic Search\u003c/h2\u003e\u003cp\u003eA total of 2760 studies were identified through our systematic search. After removing duplicates and studies deemed ineligible, 1011 records were initially screened to exclude studies that either did not include the correct study population, did not contain demographic information, excluded the maternal factors of interest, did not have a study design relevant to the meta-analysis question, did not directly pertain to NEC, or were systematic reviews themselves. After screening manuscripts, 74 were fully read; ultimately, 39 were deemed eligible for this meta-analysis.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003eStudy Characteristics\u003c/h2\u003e\u003cp\u003eCharacteristics of each study are described in Table\u0026nbsp;1. Study periods ranged from 1983 to 2023. Of the 39 studies used for this meta-analysis, 14 were conducted in the United States,\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e,\u003cspan additionalcitationids=\"CR52 CR53 CR54 CR55 CR56 CR57 CR58 CR59 CR60 CR61 CR62\" citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e\u003c/sup\u003e 3 in China and South Korea\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e,\u003cspan additionalcitationids=\"CR65 CR66 CR67\" citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e\u003c/sup\u003e. As well, 2 studies were conducted in Sweden, Turkey, Canada, the United Kingdom, Italy, and Israel.\u003csup\u003e\u003cspan additionalcitationids=\"CR70 CR71 CR72 CR73 CR74 CR75 CR76 CR77 CR78 CR79\" citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e\u003c/sup\u003e Studies also came from Mexico, Kenya, France, Malaysia, Ethiopia, Australia, and Finland.\u003csup\u003e\u003cspan additionalcitationids=\"CR82 CR83 CR84 CR85 CR86\" citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e87\u003c/span\u003e\u003c/sup\u003e Newborns were diagnosed using ICD-9 and 10 codes, pathological and radiological findings to confirm the presence of NEC, or Bell\u0026rsquo;s criteria. Bell\u0026rsquo;s criteria is a staging system that stratifies infants into 3 stages (IA, IB, IIA, IIB, IIIA, IIIB) based on the presence or absence of clinical signs and radiographic findings.\u003csup\u003e\u003cspan citationid=\"CR88\" class=\"CitationRef\"\u003e88\u003c/span\u003e\u003c/sup\u003e Stages\u0026thinsp;\u0026ge;\u0026thinsp;2 are much more confident in NEC diagnosis, whereas stage 1 serves as a classification for suspected NEC. This system established a standardized method to classify infants with NEC, guiding their treatment. The studies varied in which stages of Bell\u0026rsquo;s criteria they used. Some studies only included Bell\u0026rsquo;s criteria stages\u0026thinsp;\u0026ge;\u0026thinsp;2, while others included all 3 stages.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003cp\u003e(See supplementary material for Table\u0026nbsp;1)\u003c/p\u003e\u003cp\u003eStudy designs included retrospective cohort studies, case-control studies, or population-based registry studies. The inclusion and exclusion criteria varied across studies. Maternal demographic data were extracted from medical records for each study, which served as the basis for the maternal characteristics analyzed in this meta-analysis.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003eAssessment of Risk of Bias\u003c/h2\u003e\u003cp\u003eRisk of bias was evaluated across eight domains for each of the included studies, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. When assessing inter-rater reliability, a Cohen\u0026rsquo;s Kappa of 1 was found, indicating perfect agreement among the raters in their assessments of risk of bias. Overall, the risk of bias was generally low across the studies, with the primary concern being whether the ratio of NEC infants to control infants was appropriate. Additionally, some studies were deemed to be at high risk regarding the reliability and validity of the study instrument. In contrast, all studies utilized a consistent mode of data collection. Furthermore, all data were directly obtained from patients, rather than a proxy.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003eForest Plot Analysis\u003c/h2\u003e\u003cp\u003eAcross all maternal factors, forest plots in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e revealed varying levels of association with NEC. Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows the pooled ORs and 95% confidence intervals for each maternal factor. In summary, Cesarean Sections, Chorioamnionitis, maternal diabetes mellitus, over 12 years of education, and no education all had nonsignificant associations with the development of NEC. However, maternal smoking throughout pregnancy (summary OR: 1.75, 95% CI: 1.26\u0026ndash;2.25, n\u0026thinsp;=\u0026thinsp;10) and preeclampsia (summary OR: 2.03, 95% CI: 1.43\u0026ndash;2.63, n\u0026thinsp;=\u0026thinsp;8) had significant associations with NEC, found to be associated with 75% and 103% increased odds of NEC respectively.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eSummary of the forest plot and Egger\u0026rsquo;s test results for each maternal factor.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"9\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMaternal Factor\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003en\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eOR\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e95% CI\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eI\u0026sup2; (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eχ\u0026sup2;\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eChi-square p\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003et\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u003cp\u003eEgger's test p\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCesarean Section\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.92\u0026ndash;1.40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e86.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e128.86\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.9992\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSmoking during pregnancy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.75\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.26\u0026ndash;2.25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e87.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e69.84\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e2.61\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.0313\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eChorioamnionitis\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2.41\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.59\u0026ndash;4.23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e99.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e2533.23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.86\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.4029\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDiabetes Mellitus\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.66\u0026ndash;1.47\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e2.94\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.71\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e-0.32\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.7677\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo Education\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.53\u0026ndash;1.27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e2.81\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e-4.41\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.1421\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOver 12 Years of Education\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.54\u0026ndash;2.66\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e85.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e20.27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.80\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.5088\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePreeclampsia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.43\u0026ndash;2.63\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e95.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e148.82\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.82\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.4437\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\u003ch2\u003eAssessment of Heterogeneity\u003c/h2\u003e\u003cp\u003eThe Chi-square and Higgins and Thompson I\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e statistics were used to quantify the extent of heterogeneity across studies. While the chi-square test determines whether the heterogeneity observed is due to random chance, the I\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e statistic quantifies the degree of heterogeneity. As summarized in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e2\u003c/span\u003e, the maternal factors Cesarean Section (χ\u0026sup2;=128.86, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, I\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;86.8), smoking during pregnancy (χ\u0026sup2;=69.84, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, I\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;87.1), chorioamnionitis (χ\u0026sup2;=2533.23, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, I\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;99.3), over 12 years of education (χ\u0026sup2;=20.27, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, I\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;95.3), and preeclampsia (χ\u0026sup2;=148.82, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, I\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;95.3) exhibited significant heterogeneity. Conversely, Diabetes Mellitus and no education did not show significant heterogeneity.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\u003ch2\u003eFunnel Plot Analysis and Egger\u0026rsquo;s Test\u003c/h2\u003e\u003cp\u003eFunnel plots shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e were used to assess publication bias, while Egger\u0026rsquo;s test was used to assess whether small-study effects or publication bias were present. We did not find evidence of publication bias for all maternal factors, except for smoking during pregnancy, which exhibited significant asymmetry. The maternal factor, smoking during pregnancy, displayed significant asymmetry (t\u0026thinsp;=\u0026thinsp;2.61, p\u0026thinsp;=\u0026thinsp;0.0313). This asymmetry was likely influenced by smaller studies with larger effect sizes that skewed to the right of the pooled OR. In particular, three small studies fell within significant regions (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), indicating a potential influence of selective reporting or small-study effects.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"Discussion","content":"\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e\u003ch2\u003eKey Findings\u003c/h2\u003e\u003cp\u003eWith the high mortality rate of NEC and its prevalence in preterm infants, it is vital to understand how this disease manifests. This meta-analysis examined the risk of seven maternal factors on the development of NEC. Our review reveals that across studies, maternal smoking and preeclampsia have a statistically significant positive association with the development of NEC.\u003c/p\u003e\u003cp\u003eThe significant finding of the association between maternal smoking and NEC aligns with prior research investigating the effect of smoking on fetal development and neonatal outcomes.\u003csup\u003e\u003cspan citationid=\"CR89\" class=\"CitationRef\"\u003e89\u003c/span\u003e\u003c/sup\u003e Previous studies have identified that smoking during pregnancy is associated with preterm birth, FGR, and neonatal respiratory and gastrointestinal diseases, all of which predispose an infant to NEC. Fetal hypoxia has also been attributed to maternal smoking, damaging the intestinal barrier.\u003csup\u003e\u003cspan citationid=\"CR90\" class=\"CitationRef\"\u003e90\u003c/span\u003e\u003c/sup\u003e Damage to the intestinal barrier is known as one of the major pathological factors contributing to NEC development.\u003csup\u003e\u003cspan citationid=\"CR91\" class=\"CitationRef\"\u003e91\u003c/span\u003e\u003c/sup\u003e As well, maternal smoking can cause microvascular changes in the placenta that could cause placental insufficiency. This abnormal development of the placental vascularization in the case of maternal smoking can decrease nutrient and circulation exchange between the mother and the fetus.\u003csup\u003e\u003cspan citationid=\"CR92\" class=\"CitationRef\"\u003e92\u003c/span\u003e\u003c/sup\u003e This insufficiency can lead to complications such as gestational hypertension, FGR, and premature birth. Moreover, our results highlight the critical need for targeted smoking cessation interventions during pregnancy to mitigate the risk of NEC and improve neonatal outcomes.\u003c/p\u003e\u003cp\u003eAdditionally, previous literature supports preeclampsia as a risk factor for NEC.\u003csup\u003e\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e\u003c/sup\u003e Preeclampsia is a hypertensive disorder during pregnancy.\u003csup\u003e\u003cspan citationid=\"CR93\" class=\"CitationRef\"\u003e93\u003c/span\u003e\u003c/sup\u003e Preeclampsia is characterized by new-onset hypertension, sometimes accompanied with protein in the urine. This disorder usually manifests itself after 20 weeks of gestation and exists on a spectrum of severity. In severe cases, for the mother, there can be organ damage, particularly to the kidneys, liver, and blood. As well, fluid buildup is a complication associated with preeclampsia, which can lead to pulmonary edema. Preeclampsia is a leading cause of Cesarean sections and maternal and fetal mortality worldwide.\u003csup\u003e\u003cspan citationid=\"CR93\" class=\"CitationRef\"\u003e93\u003c/span\u003e\u003c/sup\u003e With preeclampsia, fetal blood flow is restricted due to placental hypoperfusion, which leads to FGR.\u003csup\u003e\u003cspan citationid=\"CR94\" class=\"CitationRef\"\u003e94\u003c/span\u003e\u003c/sup\u003e Infants born to mothers with preeclampsia have a birth weight 5% lower compared to those born to mothers with normal blood pressure. When the mother has preeclampsia, the fetus is often deprived of adequate placental blood flow, resulting in an abnormal intrauterine environment that can necessitate medically indicated preterm delivery. As preeclampsia is linked to low birth weight and early delivery, gut and intestinal maturation may be compromised, increasing the infant's susceptibility to necrotizing enterocolitis. Furthermore, our findings recapitulate the link between preeclampsia and NEC.\u003c/p\u003e\u003cp\u003eIn contrast, there were no other statistically significant associations between Cesarean section delivery, diabetes, chorioamnionitis, and maternal education on the development of NEC. However, there was significant heterogeneity between studies (I\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;68.0%), suggesting that inconsistencies in findings may be due to variation in study methodologies. Despite conflicting results in studies investigating Cesarean sections and NEC, our study amplifies that, across the literature, there is no definitive connection between the development of NEC and Cesarean section delivery.\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e Further, we believe there is no increased risk of NEC via Cesarean section delivery. Some argue that the route of delivery can affect the microbiome, where infants delivered by Cesarean section are not exposed to the mother\u0026rsquo;s vaginal and perineal microbiome, which has beneficial bacteria.\u003csup\u003e\u003cspan citationid=\"CR95\" class=\"CitationRef\"\u003e95\u003c/span\u003e\u003c/sup\u003e Instead, their microbiome is usually colonized by bacteria from the mother\u0026rsquo;s skin and the hospital environment, which could be pathogenic.\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e However, Cesarean sections are often performed when there are signs of fetal distress or to avoid a difficult vaginal birth, where there could be reduced oxygen flow to the infant.\u003csup\u003e\u003cspan citationid=\"CR96\" class=\"CitationRef\"\u003e96\u003c/span\u003e\u003c/sup\u003e So, it could be hypothesized that Cesarean sections could be protective of NEC by preventing oxygen deprivation and compromised circulation to the intestines. Further, the relationship between delivery methods and NEC development is likely complex and could be related to other factors such as gestational age, feeding practices, and the presence of underlying medical conditions in the infant or mother. Further work could be done by conducting a large multicenter cohort study with detailed maternal and perinatal records to adjust for associations such as gestational age, birth weight, CHD, FGR, and maternal characteristics and demographics, to validate that Cesarean section delivery is not associated with the development of NEC.\u003c/p\u003e\u003cp\u003eSimilarly, we did not detect evidence of a significant pooled risk of developing NEC if the mother had chorioamnionitis. Chorioamnionitis, a disease where the membranes surrounding the fetus are infected by bacteria, can disrupt the development of the infant\u0026rsquo;s intestines and trigger systemic inflammation in the womb.\u003csup\u003e\u003cspan citationid=\"CR97\" class=\"CitationRef\"\u003e97\u003c/span\u003e\u003c/sup\u003e While some studies and reviews have reported a positive association between chorioamnionitis and NEC, our analysis of the available literature found no overall significant risk. However, there was significant heterogeneity between the studies, indicating that the studies did not have consistent results. The wide range of effect sizes and heterogeneity could reflect variation in the study designs and imply that differences in the time and severity of chorioamnionitis influence fetal outcomes.\u003c/p\u003e\u003cp\u003eIn addition, while diabetes mellitus is linked to neonatal complications such as congenital anomalies, FGR, and various birth defects, our results indicated that across the studies analyzed, it did not emerge as a significant risk factor for NEC. One meta-analysis by Su et al. (2023) reported diabetes mellitus as a significant risk factor for NEC.\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e A reason for the discrepancy in findings could be due to differences in the studies used because of inclusion and exclusion criteria. Our meta-analysis also contains more recent studies, which may reflect shifts in clinical outcomes over time. While NEC has lagged, neonatology as a field has changed dramatically in the past half-century. In recent years, there have been advances in diagnostic tools and clinical practices, and changes in patient populations. Additionally, over time, there are shifting maternal demographics, evolving lifestyles, and environmental stressors. Further, using a large timeframe and including more recent studies can illuminate how diagnosis, patient demographics, and treatment have evolved, modifying the relationship between NEC and diabetes mellitus, as well as other possible maternal risk factors.\u003c/p\u003e\u003cp\u003eOur meta-analysis, to our knowledge, is one of the few to test for an association between maternal education and NEC. Even though higher maternal education can be linked to better infant health outcomes, there was no overall association between the mother receiving over twelve years of education and NEC.\u003csup\u003e\u003cspan citationid=\"CR98\" class=\"CitationRef\"\u003e98\u003c/span\u003e\u003c/sup\u003e As well, the overall association between the mother receiving no education and the development of NEC was not significant. This aligns with current but limited research investigating maternal education and NEC. Moreover, our findings, as well as those of other studies, show that education does not appear to be a risk factor for NEC.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec20\" class=\"Section2\"\u003e\u003ch2\u003eLimitations\u003c/h2\u003e\u003cp\u003eFirst, the number of studies used for each maternal factor was relatively small, especially for preeclampsia, maternal education, and diabetes. While having a limited number of studies does not invalidate the findings, it may obscure or exaggerate the detection of a significant risk. A small number of studies included in the meta-analysis could also limit the statistical power of determining the presence of publication bias. When testing for publication bias with fewer than ten studies, using funnel plots and Egger\u0026rsquo;s regression test becomes less reliable due to limited data from too few studies being present. Testing for publication bias by funnel plot and Egger\u0026rsquo;s regression test when fewer than ten studies are included in the meta-analysis is typically less reliable, as it is hard to determine any asymmetry with too few studies present.\u003csup\u003e\u003cspan citationid=\"CR99\" class=\"CitationRef\"\u003e99\u003c/span\u003e\u003c/sup\u003e Further, even if funnel plots visually show symmetry and Egger\u0026rsquo;s regression test quantifies no significant asymmetry, there still could be publication bias. If published studies show significant results in different directions, there could still be selective reporting, but it is masked by the symmetry of the funnel plot. So, the visual symmetry may obscure true bias, and these methods should be cautiously interpreted and not used as definitive indicators of the presence or absence of publication bias.\u003c/p\u003e\u003cp\u003eSecond, our analysis only examined the univariate relationships between NEC and the given maternal factor, without considering multiple factors simultaneously. Considering only one variable at a time does not allow us to examine interactions between variables. For instance, risk factors for preeclampsia include hypertension, diabetes, and advanced maternal age. These factors are also shown to be independently associated with FGR and preterm delivery.\u003csup\u003e\u003cspan citationid=\"CR100\" class=\"CitationRef\"\u003e100\u003c/span\u003e\u003c/sup\u003e Given that FGR and preterm delivery are risk factors for NEC, one can question whether preeclampsia itself increases the risk of NEC or if it is just associated with other underlying risk factors. In the same vein, maternal hypertension, FGR, and preterm birth are associated with maternal smoking, making it difficult to deduce the effect of each individual factor on NEC risk. Considering NEC is a complex, multifactorial disease, this analysis may have missed important complexities that would have allowed us to understand more in-depth how and which maternal risk factors are associated with the development of NEC.\u003c/p\u003e\u003cp\u003eThird, the studies that reported the incidence of NEC if the mother smoked throughout pregnancy did not quantify the extent of smoking. \u0026ldquo;Smoking throughout pregnancy\u0026rdquo; is a generalization that can vary greatly for each mother. This broad categorization does not allow us to examine the true effect of smoking on NEC, such as whether a higher level of smoking increases the risk or if any amount of smoking is sufficient to contribute to the development of NEC.\u003c/p\u003e\u003cp\u003eFourth, it is important to note that the significant heterogeneity between studies may be attributed to the inclusion of studies spanning over a large timeframe. Varying populations were included, and NEC was defined using different criteria. For instance, Bell\u0026rsquo;s stage 1 includes many infants with suspected NEC, and ICD-9 and 10 codes are NEC-stage unspecified. So, studies using Bell\u0026rsquo;s stage 1 and ICD-9 and 10 codes as NEC diagnosis criteria probably introduced a pool of infants that did not actually have NEC. Furthermore, this mixture of different populations and epochs introduced substantial heterogeneity that likely decreased the sensitivity of some maternal risk factors.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec21\" class=\"Section2\"\u003e\u003ch2\u003eImplications of Results and Future Research\u003c/h2\u003e\u003cp\u003eThe significant overall estimated risk of developing NEC if the mother smokes during pregnancy warrants emphasis on prevention strategies for smoking during pregnancy. Kipling et al. found that in 2021, 5.4% of pregnant women reported that they smoked during pregnancy.\u003csup\u003e\u003cspan citationid=\"CR101\" class=\"CitationRef\"\u003e101\u003c/span\u003e\u003c/sup\u003e This statistic highlights the need to find ways to prevent smoking during pregnancy, especially given the adverse neonatal outcomes and the positive association between smoking and NEC found in this meta-analysis. Further research should be conducted to further confirm smoking as an NEC risk factor and to understand its relationship and interaction with other factors, such as maternal feeding, race, and socioeconomic status, to provide deeper insights into NEC development. A prospective multicenter cohort study with NEC as the primary outcome could be conducted to collect detailed data on smoking exposure and its relationship with NEC development. A multivariate analysis could be done to examine the effect of smoking on NEC development and whether that relationship is modified by any other factor. Researchers can also attempt to elucidate the mechanism underlying the relationship between smoking and NEC, specifically looking at how the nicotine, tobacco, and other toxins contained in cigarettes affect neonatal gastrointestinal development.\u003c/p\u003e\u003cp\u003eGiven the high maternal and fetal mortality rates associated with preeclampsia, strategies to reduce its incidence are critical. Prior research has explored preventative approaches, such as a study conducted by Esquivel (2022), which found that nutritional modifications, such as increasing calcium and vitamin D intake, can reduce the risk of preeclampsia.\u003csup\u003e\u003cspan citationid=\"CR102\" class=\"CitationRef\"\u003e102\u003c/span\u003e\u003c/sup\u003e Some also suggest that physical activity can decrease the risk of preeclampsia.\u003csup\u003e\u003cspan citationid=\"CR103\" class=\"CitationRef\"\u003e103\u003c/span\u003e,\u003cspan citationid=\"CR104\" class=\"CitationRef\"\u003e104\u003c/span\u003e\u003c/sup\u003e The 103% estimated increased risk of NEC when the mother has preeclampsia could be indirectly mitigated with these intervention strategies to reduce preeclampsia risk. It is also important to conduct further research to confirm preeclampsia\u0026rsquo;s significant relationship with NEC development, considering that preeclampsia is a common complication of pregnancy.\u003csup\u003e\u003cspan citationid=\"CR93\" class=\"CitationRef\"\u003e93\u003c/span\u003e\u003c/sup\u003e A multivariate analysis could be conducted to investigate whether preeclampsia is independently associated with NEC, or whether the observed increased risk can be attributed to preeclampsia\u0026rsquo;s established association with NEC risk factors, such as FGR and compromised intestinal maturation.\u003c/p\u003e\u003cp\u003eThe lack of significant findings for the five other maternal factors may reflect more nuanced interactions between risk factors. The insignificant findings may also indicate that these maternal factors are not actual risk factors for NEC. Rather than investigating each factor independently, further research should be conducted to examine how these factors interact and contribute to the development of NEC together. ​​Understanding these complex relationships could help identify prevention strategies for NEC. In addition, performing larger-scale studies to understand how these maternal factors relate, specifically in relation to race and socioeconomic status, could reveal how to effectively identify high-risk groups and attempt to reduce the incidence of NEC.\u003c/p\u003e\u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAvailability of Materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data used to compute each of the forest and funnel plots, as well as the risk of bias plot in this study can be found in our data repository. Additionally, all papers identified in our literature search can be found here.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; Contributions\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eLB and AL analyzed the data and performed all statistical analyses. LB and WL conducted the literature review and performed the literature search for all analyses included in this meta analysis. LB, AL, and WL were all involved in the process of preparing and editing the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe extend our most sincere thanks to Thomas Hays, whose comments and suggestions were invaluable in writing this manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eGinglen JG, Butki N. Necrotizing Enterocolitis. in \u003cem\u003eStatPearls\u003c/em\u003e. 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J Matern Fetal Neonatal Med. 2023;36:2253351.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAbebe M, Ayehu M, Tebeje TM, Melaku G. Risk factors of necrotizing enterocolitis among neonates admitted to the neonatal intensive care unit at the selected public hospitals in southern Ethiopia, 2023. Front Pediatr 12, (2024).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eH\u0026auml;llstr\u0026ouml;m M, Koivisto A-M, Janas M, Tammela O. Frequency of and risk factors for necrotizing enterocolitis in infants born before 33 weeks of gestation. Acta Paediatr. 2003;92:111\u0026ndash;3.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBoo N-Y, Cheah IGS. Risk factors associated with necrotising enterocolitis in very low birth weight infants in Malaysian neonatal intensive care units.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLuig M, Lui K, Group N. A. N. 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Early Hum Dev. 2016;102:47\u0026ndash;50.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSiggers RH, et al. Elective cesarean delivery affects gut maturation and delays microbial colonization but does not increase necrotizing enterocolitis in preterm pigs. Am J Physiology-Regulatory Integr Comp Physiol. 2008;294:R929\u0026ndash;38.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLeung TY, Lao TT. Timing of caesarean section according to urgency. Best Pract Res Clin Obstet Gynecol. 2013;27:251\u0026ndash;67.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFarghaly MAA, et al. Maternal chorioamnionitis and the risk for necrotizing enterocolitis in the United States: A national cohort study. Early Hum Dev. 2024;197:106108.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNoghanibehambari H, Salari M, Tavassoli N. Maternal human capital and infants\u0026rsquo; health outcomes: Evidence from minimum dropout age policies in the US. SSM - Popul Health. 2022;19:101163.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSterne JAC, et al. Recommendations for examining and interpreting funnel plot asymmetry in meta-analyses of randomised controlled trials. BMJ. 2011;343:d4002.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFox R, Kitt J, Leeson P, Aye CYL, Lewandowski AJ, Preeclampsia. Risk Factors, Diagnosis, Management, and the Cardiovascular Impact on the Offspring. J Clin Med. 2019;8:1625.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKipling L. Cigarette Smoking Among Pregnant Women During the Perinatal Period: Prevalence and Health Care Provider Inquiries \u0026mdash; Pregnancy Risk Assessment Monitoring System, United States, 2021. MMWR Morb Mortal Wkly Rep 73, (2024).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eEsquivel MK. Nutritional Status and Nutrients Related to Pre-Eclampsia Risk. Am J Lifestyle Med. 2022;17:41\u0026ndash;5.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSorensen TK, et al. Recreational physical activity during pregnancy and risk of preeclampsia. Hypertension. 2003;41:1273\u0026ndash;80.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMagnus P, Trogstad L, Owe KM, Olsen SF, Nystad W. Recreational Physical Activity and the Risk of Preeclampsia: A Prospective Cohort of Norwegian Women. Am J Epidemiol. 2008;168:952\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Table 1","content":"\u003cp\u003eTable 1 is available in the Supplementary Files section.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-pediatrics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bped","sideBox":"Learn more about [BMC Pediatrics](http://bmcpediatr.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bped/default.aspx","title":"BMC Pediatrics","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Necrotizing Enterocolitis, Meta-Analysis, Forest Plot","lastPublishedDoi":"10.21203/rs.3.rs-7348561/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7348561/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eNeonatal Necrotizing Enterocolitis (NEC) is a multifactorial intestinal disorder that affects 2\u0026ndash;5% of premature infants and has a mortality rate of 20\u0026ndash;30%.\u003csup\u003e1\u003c/sup\u003e Researchers have identified the impact of maternal factors, such as a negative association of breastmilk feeding and antenatal corticosteroid therapy, on NEC development in infants.\u003csup\u003e\u003cspan additionalcitationids=\"CR3 CR4\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e However, other maternal risk factors have not been analyzed in detail. A better understanding of the role of specific maternal factors in developing NEC can help identify infants at risk and decrease the incidence of NEC. This meta-analysis aims to investigate the independent association between Cesarean section delivery, smoking, preeclampsia, chorioamnionitis, diabetes mellitus, and maternal education on the development of NEC.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eWe systematically searched for journal articles published before April 2025.\u003csup\u003e\u003cspan additionalcitationids=\"CR7 CR8\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e Studies were included if they contained data on incidence rates of NEC for any of the seven risk factors analyzed in this study. Two evaluators independently screened and extracted literature to be used for this meta-analysis. Disagreements were resolved through discussion, and interrater reliability was assessed using Cohen\u0026rsquo;s Kappa.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eWe identified 74 manuscripts that met the inclusion criteria, of which 39 were suitable for our meta-analysis. The pooled risk calculation showed a statistically significant risk of NEC for mothers who smoked during pregnancy (OR: 1.75, 95% CI: 1.26\u0026ndash;2.25, n\u0026thinsp;=\u0026thinsp;10) and for mothers who had preeclampsia (OR: 2.03, 95% CI: 1.43\u0026ndash;2.63, n\u0026thinsp;=\u0026thinsp;8). All other pooled estimates for the maternal factors analyzed showed insignificant evidence of an association with NEC. In addition, the funnel plots and Egger\u0026rsquo;s regression tests indicated no evidence of publication bias for all maternal factors besides smoking during pregnancy (t\u0026thinsp;=\u0026thinsp;2.61, p\u0026thinsp;=\u0026thinsp;0.0313).\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e\u003cp\u003eThis study highlights a significant association between maternal smoking and preeclampsia during pregnancy and the development of NEC, suggesting a potential causal relationship. This study also identifies chorioamnionitis and Cesarean sections alone as nonsignificant risk factors, despite conflicting claims from other studies. Moreover, this meta-analysis also underscores the need for more research to be conducted to analyze the association between maternal smoking, preeclampsia, Cesarean sections, and chorioamnionitis on the development of NEC.\u003c/p\u003e","manuscriptTitle":"Maternal Risk Factors Associated with Neonatal Necrotizing Enterocolitis: a Meta-Analysis and Systematic Review","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-19 12:41:08","doi":"10.21203/rs.3.rs-7348561/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-11-10T09:17:57+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-09T15:05:19+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-07T11:44:52+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-07T08:58:29+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-05T11:31:27+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"337856327829068118043118238923843124619","date":"2025-11-05T11:11:06+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"157984413755088104801174220738191574010","date":"2025-11-05T10:57:12+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-05T09:02:08+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-05T07:45:40+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"138330543675640682411345040244514927489","date":"2025-11-04T10:47:49+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"200172707510003584166800020237536902342","date":"2025-11-04T06:26:41+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"316694415700529624737472446854475836676","date":"2025-11-04T06:04:50+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"254294877569245623996261536271680734722","date":"2025-11-04T04:13:16+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"50954621127349524243189131197722004939","date":"2025-11-04T02:10:06+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"287424602896762213513184834871685042762","date":"2025-11-03T21:22:05+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-03T21:00:13+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"175862545186536707507055094544835963098","date":"2025-11-03T20:59:50+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"159453094304281748907209384866419777425","date":"2025-11-03T20:33:21+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"79973964431901512616119034527228120019","date":"2025-11-03T20:20:35+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"293380014096532165322396373146283004544","date":"2025-11-03T20:11:23+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-08-21T14:54:08+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-08-21T12:06:00+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-08-21T07:13:58+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-08-21T07:12:48+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Pediatrics","date":"2025-08-11T17:03:49+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-pediatrics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bped","sideBox":"Learn more about [BMC Pediatrics](http://bmcpediatr.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bped/default.aspx","title":"BMC Pediatrics","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"195d94c6-7c02-4aa4-be1a-13a288cc3bcf","owner":[],"postedDate":"August 19th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-08T14:10:18+00:00","versionOfRecord":[],"versionCreatedAt":"2025-08-19 12:41:08","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7348561","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7348561","identity":"rs-7348561","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}