Risk Factors For Neonatal Mortality Research Articles

Risk factors associated with neonatal mortality among neonates admitted to neonatal intensive care unit of the University Teaching Hospital in Lusaka

Globally, several children die shortly after birth and many more of them within the first 28 days of life. Sub-Sharan Africa accounts for almost half (43%) of the global neonatal death with slow progress in reduction. These neonatal deaths are associated with lack of quality care at or immediately after birth and in the first 28 days of life. This study aimed to determine the trends and risk factors of facility-based neonatal mortality in a major referral hospital in Lusaka, Zambia. We conducted retrospective analysis involving all neonates admitted in the University Teaching Hospital Neonatal Intensive Care Unit (UTH-NICU) in Lusaka from January 2018 to December 2019 (N = 2340). We determined the trends and assessed the factors associated with facility-based neonatal mortality using Generalized Linear Models (GLM) with a Poisson distribution and log link function. Overall, the facility-based neonatal mortality was 40.2% (95% CI 38.0–42.0) per 1000 live births for the 2-year period with a slight decline in mortality rate from 42.9% (95% CI 40.0–46.0) in 2018 to 37.3% (95% CI 35.0–40.0) in 2019. In a final multivariable model, home delivery (ARR: 1.70, 95% CI 1.46–1.96), preterm birth (ARR: 1.59, 95% CI 1.36–1.85), congenital anomalies (ARR: 1.59, 95% CI 1.34–1.88), low birthweight (ARR: 1.57, 95% CI 1.37–1.79), and health centre delivery (ARR: 1.48, 95% CI 1.25–1.75) were independently associated with increase in facility-based neonatal mortality. Conversely, hypothermia (ARR: 0.36, 95% CI 0.22–0.60), antenatal attendance (ARR: 0.76, 95% CI 0.68–0.85), and 1-day increase in neonatal age (ARR: 0.96, 95% CI 0.95–0.97) were independently associated with reduction in facility-based neonatal mortality. In this hospital-based study, neonatal mortality was high compared to the national and global targets. The improvement in neonatal survival observed in this study may be due to interventions including Kangaroo mother care already being implemented. Early identification and interventions to reduce the impact of risks factors of neonatal mortality in Zambia are important.

Using Routine EMR Registration on a National Scale for Evaluating the Impact of HIV and ART on Childbirth in Burundi.

A number of international studies have reported that HIV+ mothers under ART on average deliver babies that have low birth weight (LBW), are smaller (LBH) and are more often premature [1,2,3,4,5,6,7,8,9]. These 3 elements are well known risk factors for neonatal mortality. In our study we wanted to assess the actual status of such supposed HIV and ART related neonatal mortality risks in Burundi by taking advantage of the country's large scale EMR implementation. A total of 64,682 birth records were extracted from EMRs in 17 hospitals for the period between January 1, 2018 and October 31, 2022. After quality control for missing or impossible data, 54,180 records were retained for the study. This study demonstrated that the use of ART during HIV+ pregnancies has no statistically significant impact on risk factors for neonatal mortality in Burundi. The study also indicates that the HIV prevalence among pregnant women in Burundi who give birth in a hospital is more than twice as high as expected based on the official figures. It was also demonstrated that an explanation for this finding cannot be found in a possible concentration of HIV+ deliveries in the hospital environment. The availability of large-scale implementation of structured electronic health records brings numerous new possibilities for population research based on routinely registered health data in a low-resource country like Burundi.

Risk Factors for Neonatal Mortality at the Institute of Nutrition and Child Health of the Donka/Guinea-Conakry National Hospital

Risk Factors for Neonatal Mortality at the Institute of Nutrition and Child Health of the Donka/Guinea-Conakry National Hospital

Risk Factors for Neonatal Mortality in Rural Iganga District, Eastern Uganda: A Case Control Study

Risk Factors for Neonatal Mortality in Rural Iganga District, Eastern Uganda: A Case Control Study

Risk Factors for Neonatal Death in Konawe Islands District

Background: The prevalence of neonatal mortality rate of Konawe Islands Regency in 2019 was 22 per 1000 live births, in 2020 it was 26.2 per 1000 live births and experienced a significant increase in 2021 to 34.9 per 1000 live births (Konawe Islands Regency Health Office 2019-2021). The purpose of the study was to analyze the risk factors of Mothers, Infants, Work and Postpartum care for Neonatal deaths in the Konawe Islands Regency.
 Methods: This study used a Case Control Study approach. The population numbered 48 people. The Study Sample totaled 24 case samples and 24 control samples. The sample technique in this study is Simple Random Sampling. The data is processed using the Odds Ratio Test. 
 Result: The results showed that the gestational age or 7,286 LL value 2,034 and UL 26,102, PARITY OR 3,215 LL value 0.902 and UL value 11,460, disease history OR 6,000 LL value 1,711 and UL value 21,038, BMI OR 4,200 LL value 1,228 and UL value 14,365, against Neonatal deaths in the Konawe Islands Regency Area.
 Conclusion: The conclusions in this study show that maternal factors, infant factors and postpartum care are risk factors while occupation is not a risk factor for neonatal mortality in the Konawe Islands Regency. It is expected for the Health Office and Puskesmas to always provide education in the form of counseling and counseling related to maternal and child health to reduce neonatal death cases.

Neonatal mortality and video assessment of resuscitation in four district hospitals in Pemba, Tanzania.

We aimed to assess risk factors for neonatal mortality, quality of neonatal resuscitation (NR) on videos and identify potential areas for improvement. This prospective cohort study included women in childbirth and their newborns at four district hospitals in Pemba, Tanzania. Videos were analysed for quality-of-care. Questionnaires on quality-of-care indicators were answered by health workers (HW) and women. Risk factors for neonatal mortality were analysed in a binomial logistic regression model. 1440 newborns were enrolled. 34 newborns died within the neonatal period (23.6 per 1000 live births). Ninety neonatal resuscitations were performed, 20 cases on video. Positive pressure ventilation (PPV) was inadequate in 15 cases (75%). Half (10/20) did not have PPV initiated within the first minute, and in one case (5.0%), no PPV was performed. PPV was not sustained in 16/20 (80%) newborns. Of the 20 videos analysed, death occurred in 10 newborns: 8 after resuscitation attempts and two within the first 24 h. Most of HW 49/56 (87.5%) had received training in NR. Video analysis of NR revealed significant deviations from guidelines despite 87.5% of HW being trained in NR. Videos provided direct evidence of gaps in the quality of care and areas for future education, particularly effective PPV. Neonatal mortality in Pemba is 23.6 per 1000 livebirths, with more than 90% occurring in the first 24 h of life. Video assessment of neonatal resuscitation revealed deviations from guidelines and can add to understanding challenges and aid intervention design. The present study using video assessment of neonatal resuscitation is the first one performed at secondary-level hospitals where many of the world's births are conducted. Almost 90% of the health workers had received training in neonatal resuscitation, and the paper can aid intervention design by understanding the actual challenges in neonatal resuscitation.

The Occurrence and Correlating Elements of Newborn Mortality in Jinja District, Uganda

In Uganda, the neonatal mortality rate remains high, standing at 27 deaths per 1000 live births. However, there's a lack of comprehensive data concerning the prevalence and factors associated with neonatal mortality in Jinja district, Uganda. This study aimed to fill this gap by assessing the prevalence and identifying associated risk factors for neonatal mortality in the area. Using a pretested survey questionnaire, data from the electronic database of Jinja district on maternal and newborn interventions were collected, focusing on 245 women who had given birth within the past year, irrespective of birth outcomes. The collected data underwent analysis using SPSS version 25, employing chi-squared analysis at a significance level of p=0.05 to discern factors linked with neonatal mortality. The study revealed a neonatal mortality rate of 12.2%. Factors contributing to increased neonatal mortality included mothers with an education level below secondary, residing in rural areas, male infants, neonates aged 2-7 days, preterm birth, and low birth weight. Notably, the neonatal mortality rate observed in this study was lower than the national average. The findings suggest that employing community-based initiatives to educate and raise awareness within households about appropriate maternal and newborn care practices could significantly contribute to reducing neonatal mortality rates. Keywords: Neonatal mortality, Newborn, Preterm birth, Mothers

Risk factors for neonatal mortality: an observational cohort study in Sarlahi district of rural southern Nepal

ObjectivesTo assess the association between maternal characteristics, adverse birth outcomes (small-for-gestational-age (SGA) and/or preterm) and neonatal mortality in rural Nepal.DesignThis is a secondary observational analysis to identify risk factors for...

Determinants of Neonatal Mortality in the United States.

Introduction Despite a notable reduction in infant mortality over recent decades, the United States, with a rate of 5.8 deaths per 1,000 live births, still ranks unfavorably compared to other developed countries. This improvement appears inadequate when contrasted with the country's healthcare spending, the highest among developed nations. A significant proportion of this infant mortality rate can be attributed to neonatal fatalities. Objective The present study aimed to determine the risk factors associated with neonatal deaths in the United States. Method Using the United States Vital Statistics records, we conducted a retrospective study on childbirths between 2015 and 2019 to identify risk factors for neonatal mortality. Our final multivariate analysis included maternal parameters like age, insurance type, education level, cesarean section rate, pregnancy inductions and augmentations, weight gain during pregnancy, birth weight, number of prenatal visits, pre-existing conditions like chronic hypertension and prediabetes, and pregnancy complications like gestational diabetes mellitus (GDM). These variables were incorporated to enhance our model's sensitivity and specificity. Result There were 51,174 neonatal mortalities. Mothers with augmentation of labor had a 25% reduction in neonatal mortalities (NM) (OR=0.75; 95% CI 0.72-0.79), while labor induction was associated with a 31% reduction in NM (OR=0.69; 95% CI 0.66-0.72). Women above 40 years had a 29% increase in NM rate (OR=1.29;95% CI 1.15-1.44). Women without prenatal care have a 22% increase in the risk of NM (OR=1.22; 95% CI 1.14-1.30). The present model has a 60.7% sensitivity and a 99.9% specificity. Conclusion In the present study, significant interventions such aslabor induction, augmentation, and prenatal care were associated with improved neonatal outcomes. These findingscould serve as an algorithm for improving neonatal outcomes in the United States.

Determinants of neonatal mortality in Margaret Kenyatta Mother Baby Wing at Nakuru level 5 hospital, Nakuru County, Kenya

Background: Nakuru county has 41.9 neonatal deaths per 1000 live births, more than double the national average of 19. This study examined Nakuru level 5 hospital neonatal mortality risk factors. Methods: A retrospective mismatched case-control study was used. The 429 neonates (143 cases and 286 controls) were estimated assuming a 1:2 case-to-control ratio and 18% prevalence of exposure among controls. Binary logistic regression measured dependent-independent variable correlation. Results: The study found that high parity, high number of stillbirths, positive HIV, HBsAg, syphilis, pregnancy-induced hypertension, antepartum hemorrhage, PROM 18hours, and maternal peri-partum increased the risk of neonatal. Similarly, mothers who had fewer ANC visits throughout their pregnancy had a higher risk of neonatal mortality compared to mothers who attended more than three ANC clinics, with mortality risk reducing by 69% and 59% for 1-2 visits and more than 3 visits, respectively, compared to non-attendance. Vaginal aided birth had an or of 2.188 and vaginal unassisted OR=4.533 compared to caesarian delivery. Antibiotics and prenatal dexamethasone decreased maternal mortality. Antibiotics lowered NMR or 0.381. Newborns admitted from referral facilities or labor wards had or 1.11 and or 6.220 death rates. Low birth weight, admission weight, gain weeks, and congenital defects increased mortality. In this study, birthweight decreased newborn mortality. Conclusions: The study concluded that maternal characteristics, neonatal complications are key to improving neonatal outcomes. The study recommends regular training of staff working in the maternity and newborn unit on emergency care and neonatal resuscitation.

Neonatal mortality of lambs in production systems in a semi-arid environment: main risk factors

AbstractThe sheep farming has economic and sociocultural importance in semi-arid regions worldwide. Of the total of 1.2 billion sheep in the world, 0.4 are found in semi-arid regions. In this review, we have discussed the main risk factors for neonatal lamb mortality and its association with the prevailing environmental conditions of tropical semi-arid regions. Over the last decades, the average mortality rate of newborn lambs remained relatively constant (~15%) around the world. This rate is reported to be higher (Up to 30%) in small-scale sheep farming systems from developing countries. Overall, the main risk factors of neonatal mortality include low birth weight, dystocia, adverse weather conditions, inadequate milk, or colostrum supply, competition between siblings in multiple births, and poor expression of maternal behaviour. In tropical semi-arid regions, recent findings revealed that newborn lambs from hair coat sheep breeds are less vigorous to perform the first suckling when even exposed to moderate cold conditions (18–20°C). On the other hand, the high radiant heat load in these areas can also challenge the thermoregulation of ewes and newborn lambs, especially if they are kept in areas without protection against direct short-wave solar radiation. Under such circumstances, newborn lambs were reported to be hyperthermic. The heat stress as risk factor for neonatal lamb mortality is a topic that deserves more investigation, particularly in tropical semi-arid areas, where is expected to be drier and hotter as consequence of rapid advances in climate change.

Predictors of Neonatal Mortality: A Retrospective Cross-Sectional Study From the Special Newborn Care Unit of a Tertiary Care Hospital.

Background In India, a significant number of newborns die each year, with Madhya Pradesh having the highest neonatal mortality rate. However, there is a lack of information on factors that can predict neonatal mortality. Objective This study aimed to examine the factors influencing neonatal mortality among neonates admitted to a tertiary care centre's special newborn care unit (SNCU). Methods This retrospective record-based observational study was done at a tertiary care centre, where data from the special newborn care unit (SNCU) from 1st January 2021 to 31st December 2021 was used. We included data of all newborns who were treated in SNCU during the said period and excluded those who got referred or left against medical advice. We abstracted data on age at admission, gender, category, maturity status, birth weight, place of delivery, mode of transport, type of admission, indication of admission, duration of stay and outcome. Qualitative variables were described using frequency and percentage. The chi-square test was used to find out the association of different variables with the outcome, while multivariate logistic regression was conducted to identify risk factors of neonatal mortality. A p-value of <0.05 was considered significant. Results We finalized data of 1052 neonates for analysis. Among them, 846 neonates were successfully discharged while 206 neonates were deceased. The major cause of admission was perinatal asphyxia followed by prematurity. The major cause of mortality in this study was sepsis followed by respiratory distress syndrome, birth asphyxia, and prematurity. Mortality of neonates was significantly associated with maturity status, birth weight, place of delivery, age during admission and duration of stay. Prematurity (OR=3.762, 95% CI:1.93-7.33), birth weight 1000-1499g (OR=4.78, 95% CI:2.21-10.32), birth weight <1000g (OR=25.11, 95% CI:5.71-110.24), age at admission <1-day (OR=2.312, 95% CI:1.03-5.19), duration of stay 1-3-days (OR=12.98, 95% CI:7.48-22.52) and <1-day (OR=1271.88, 95% CI:121.39-13325.69) were significant predictors of mortality in our study. Conclusion Our study emphasizes monitoring and addressing risk factors like maturity status, birth weight, and age at admission to reduce neonatal mortality, with a focus on early management of preterm births and low birth weight.

Prediction of Preeclampsia Using Machine Learning and Deep Learning Models: A Review

Preeclampsia is one of the illnesses associated with placental dysfunction and pregnancy-induced hypertension, which appears after the first 20 weeks of pregnancy and is marked by proteinuria and hypertension. It can affect pregnant women and limit fetal growth, resulting in low birth weights, a risk factor for neonatal mortality. Approximately 10% of pregnancies worldwide are affected by hypertensive disorders during pregnancy. In this review, we discuss the machine learning and deep learning methods for preeclampsia prediction that were published between 2018 and 2022. Many models have been created using a variety of data types, including demographic and clinical data. We determined the techniques that successfully predicted preeclampsia. The methods that were used the most are random forest, support vector machine, and artificial neural network (ANN). In addition, the prospects and challenges in preeclampsia prediction are discussed to boost the research on artificial intelligence systems, allowing academics and practitioners to improve their methods and advance automated prediction.

Neonatal Mortality at Felege Hiwot Comprehensive Specialized Hospital in Ethiopia Over 5 years: Trends and Associated Factors.

Globally, neonatal mortality remains a serious catastrophic problem for newborns, particularly in a low-resource setting. There were no neonatal mortality trend studies in the study area. This study aimed to determine the trends and risk factors of neonatal mortality at the neonatal intensive care unit of Felege Hiwot Comprehensive Specialized Hospital, Northwest Ethiopia. An institution-based retrospective cross-sectional study was conducted among 870 admitted neonates from January 1, 2016 to December 31, 2020 in the neonatal intensive care unit by a stratified simple random sampling technique. Data were entered into EpiData and then exported to STATA 14.0 for analysis. A linear regression statistical model was used for trend analysis and binary logistic regression was carried out to identify explanatory variables of neonatal mortality. Overall, neonatal mortality averagely increased by 2.1% per year throughout the 5 consecutive years. In this study, rural residency [adjusted odds ratio (AOR): 1.96, 95% confidence interval (CI): (1.26, 3.06)], birth asphyxia (AOR: 7.73, 95% CI: 4.31, 13.84), congenital deformity (AOR: 3.61, 95% CI: 1.17, 11.18), low birth weight (AOR: 2.13, 95% CI: 1.23, 3.67), respiratory distress syndrome (AOR: 3.32, 95% CI: 1.97, 5.59), Ambu-bag resuscitation (AOR: 0.16, 95% CI: 0.07, 0.38), taking antibiotics (AOR: 0.50, 95% CI: 0.27, 0.90), glucose (AOR: 0.47, 95% CI: 0.30, 0.72), and oxygen (AOR: 0.26, 95% CI: 0.16, 0.41) were associated with neonatal mortality. This 5-year trend analysis revealed an increased trend of NMR, indicating more work is still needed to make progress toward meeting the SDG goal by 2030. Rural residency, birth asphyxia, congenital deformity, low birth weight, respiratory distress syndrome, Ambu-bag resuscitation, taking antibiotics, glucose, and oxygen were associated with neonatal mortality. Therefore, all stakeholders shall give due attention to reducing this timely-increasing trend of neonatal mortality.

Determining factors of neonatal mortality in Ethiopia: An investigation from the 2019 Ethiopia Mini Demographic and Health Survey.

Neonatal mortality is the probability of dying during the first 28 days of life. Of approximately 5 million children who die in the first year of life in the world, about 3 million are within their first 28 days of birth. In Ethiopia, the neonatal mortality rate is high about 37 per 1000 live births, and the factors are not well documented. Then, this study aimed to determine the key factors that have a significant influence on neonatal mortality. A total of 5753 neonatal mortality-related data were obtained from Ethiopia Mini Demographic and Health Survey (2019) data. A frequency distribution to summarize the overall data and Binary Logistic Regression to identify the subset of significant risk factors for neonatal mortality were applied to analyze the data. An estimated 36 per 1000 live children had died before the first 28 days, with the highest in the Benishangul Gumuz region (15.9%) and the lowest in Addis Ababa (2.4%). From the Binary logistic regression analysis, the odds ratio and 95% CI of age 25-34 (OR = 0.263, 95% CI: 0.106-0.653), Afar (OR = 0.384, 95% CI: 0.167-0.884), SNNPR (OR = 0.265, 95% CI: 0.098-0.720), Addis Ababa (OR = 5.741, 95% CI: 1.115-29.566), Urban (OR = 0.253, 95% CI: 0.090, 0.709), toilet facility (OR = 0.603, 95% CI: 0.404-0.900), single birth (OR = 0.261, 95% CI: 0.138-0.495), poorest (OR = 10.573, 95% CI: 2.166-51.615), poorer (OR = 19.573, 95% CI: 4.171-91.848), never breastfed (OR = 35.939, 95% CI: 25.193-51.268), public health delivery (OR = 0.302, 95% CI: 0.106-0.859), private health facility (OR = 0.269, 95% CI: 0.095-0.760). All regional states of Ethiopia, specially Benishangul Gumuz, and the Somali region must take remedial actions on public health policy, design strategies to improve facilities, and improve the capacities of stakeholders living in their region toward those major factors affecting neonatal mortality in the country.

Contributors and associated risk factors of neonatal mortality in a tertiary care hospital in the sub-Himalayan region of West Bengal

Background: Lack of revision of knowledge on the magnitude of problem, cause and factors associated with neonatal mortality hampering early interventions and thus preventing reduction of neonatal mortality rate in India. Neonatal mortality statistics are sensitive indicators of the utility, convenience and effectiveness of maternal child health service in the community. This study was done to see the mortality pattern of neonates and contributing factors at the special newborn care unit (SNCU) and neonatal intensive care unit (NICU) of a rural tertiary care hospital so that special attention to those cause and factors can lead to favourable outcomes.Methods: This was a cross sectional retrospective study done in the SNCU and NICU of rural tertiary care centre of West Bengal for a period of three years with neonates admitted before 28 days of life. Data were collected in pre-designed proforma by analysing the case sheets from the records section of the hospital. Results were analysed by descriptive analytical method.Results: Total 13738 babies were admitted in the study period (7143 inborn and 6595 outborn). Majority of the inborns (86.8%) and outborns (68.4%) were discharged during that period while 9.4% inborns and 19.5% outborns were expired and only those expired cases were included in this study. HIE/moderate-severe birth asphyxia (41.2%) was the major contributor of death in inborns but in outborns the most common contributor of death was sepsis/pneumonia/meningitis (34.8%). Prematurity and low birth weight were the most common associated risk factors in both the groups.Conclusions: This study delineating the mortality patterns and associated risk factors of neonates in a rural tertiary care hospital of West Bengal which is unique in its kind. Outcome analysis showed that neonatal mortality rate for outborn babies was higher than in relevant recent studies.

Risk factors of mortality in neonates with neonatal encephalopathy in a tertiary newborn care unit in Zimbabwe over a 12-month period.

Neonatal encephalopathy (NE) accounts for ~23% of the 2.4 million annual global neonatal deaths. Approximately 99% of global neonatal deaths occur in low-resource settings, however, accurate data from these low-resource settings are scarce. We reviewed risk factors of neonatal mortality in neonates admitted with neonatal encephalopathy from a tertiary neonatal unit in Zimbabwe. A retrospective review of risk factors of short-term neonatal encephalopathy mortality was conducted at Sally Mugabe Central Hospital (SMCH) (November 2018 -October 2019). Data were gathered using a tablet-based data capture and quality improvement newborn care application (Neotree). Analyses were performed on data from all admitted neonates with a diagnosis of neonatal encephalopathy, incorporating maternal, intrapartum, and neonatal risk predictors of the primary outcome: mortality. 494/2894 neonates had neonatal encephalopathy on admission and were included. Of these, 94 died giving a neonatal encephalopathy-case fatality rate (CFR) of 190 per 1000 admitted neonates. Caesarean section (odds ratio (OR) 2.95(95% confidence interval (CI) 1.39-6.25), convulsions (OR 7.13 (1.41-36.1)), lethargy (OR 3.13 (1.24-7.91)), Thompson score "11-14" (OR 2.98 (1.08-8.22)) or "15-22" (OR 17.61 (1.74-178.0)) were significantly associated with neonatal death. No maternal risk factors were associated with mortality. Nearly 1 in 5 neonates diagnosed with neonatal encephalopathy died before discharge, similar to other low-resource settings but more than in typical high-resource centres. The Thompson score, a validated, sensitive and specific tool for diagnosing neonates with neonatal encephalopathy was an appropriate predictive clinical scoring system to identify at risk neonates in this setting. On univariable analysis time-period, specifically a period of staff shortages due to industrial action, had a significant impact on neonatal encephalopathy mortality. Emergency caesarean section was associated with increased mortality, suggesting perinatal care is likely to be a key moment for future interventions.

Definition of low birth weight in domestic mammals: a scoping review.

In people and animals, low birth weight (LBW) is recognized as highly predictive of health trajectory from the neonatal period to elderly ages. Regarding the neonatal period, although LBW is recognized as a major risk factor for neonatal mortality, there does not appear to be a clear definition of 'when a birth weight should be considered low' in all species. The aim of this work was to use the scientific literature available to map the various thresholds proposed to define LBW in domestic mammals. Using a standardized methodology, a scoping review was conducted through a literature search in three different bibliographic databases. After a two-step screening of 1729 abstracts and full-text publications by two independent reviewers, eleven studies met the inclusion criteria. Selected publications represented six mammalian species (rat, mouse, dog, pig, cow, and rabbit). Birth weight thresholds were identified through six different methods. In addition to the scarcity of scientific literature about the definition of LBW, this scoping review revealed the lack of standardization for the description, evaluation or the pertinence these definitions. Because the health consequences of LBW could be preventable, providing early identification of at-risk neonates, a consensus for the standardized definition of LBW is required.

Prenatal exposure to nitrate from drinking water and the risk of preterm birth: A Danish nationwide cohort study.

Background:Evidence is emerging that preterm birth (PTB, birth before 37 completed weeks of gestation), a risk factor for neonatal mortality and future morbidity, may be induced by maternal nitrate () exposure from drinking water. The objective of this study is to assess the association between maternal exposure to nitrate and the risk of PTB in a nationwide study of liveborn singletons.Methods:We estimated maternal nitrate exposure from household tap water for 1,055,584 births in Denmark to Danish-born parents during 1991–2015 by linkage of individual home address(es) with nitrate concentrations from a national monitoring database. Nitrate exposure during pregnancy was modeled using four categories and continuously. Logistic models adjusted for sex, birth year, birth order, urbanicity, and maternal age, smoking, education, income, and employment, with generalized estimating equations were used to account for sibling clusters.Results:A total of 1,009,189 births were included, comprising 51,747 PTB. An increase in the risk of PTB was seen across categories of exposure (P < 0.001) with an odds ratio (OR) in the uppermost category (>25 mg/L nitrate) of 1.05 (95% confidence interval [CI] = 1.00, 1.10). Evidence of an exposure–response relationship was observed in models using continuous nitrate (OR = 1.01 [95% CI = 1.00, 1.03] per 10 mg/L nitrate). In sensitivity analyses, results were robust to the addition of variables for short inter-pregnancy interval (<1 year between births), maternal pre-pregnancy body mass index, paternal socioeconomic status and age, season of birth, and inclusion of post-term births. Results were virtually unchanged when the analysis was restricted to women exposed to less than the current European Union standard of 50 mg/L.Conclusion:We observed an increasing risk of PTB with increases in nitrate in household tap water. These findings add to a growing body of evidence of adverse effects from nitrate in drinking water at levels below current regulatory levels.

Determinants of neonatal mortality in the neonatal intensive care unit of Dilla University Referral Hospital, Southern Ethiopia; 2019–2020; A matched, case–control study

BackgroundNeonatal mortality rate (NMR) refers to the number of deaths occurring from birth to 28 days of life per-1000 Live Births (LB). The global NMR declined from 37 deaths per- 1,000 LB in 1990 to 18 in 2017, whereas it was 27 deaths per 1000 LB in the Sub-Saharan region. Ethiopia plans to reduce the NMR from 28 deaths to 11 deaths per 1,000 LB by 2020 and to end all preventable child deaths by 2035. The aim of this study was to identify the determinants of neonatal mortality in the neonatal intensive care unit (NICU) of Dilla University Referral Hospital (DURH). MethodsAn age-matched case control study was conducted at DURH's NICU. Two controls having age 2 days before or after the case were used for matching. One hundred eighteen cases (died) and 236 controls (survived) neonates admitted to the NICU from January 11, 2018, to February 25, 2020, were studied. Missed data were filled by multiple imputations. Multicollinearity was checked by the variance inflation factor. For variables with a P-value <0.2 on bivariable conditional logistic regression, multivariable conditional logistic regression analysis was performed to control for confounders using clogit command in a survival package to identify the risk factors for neonatal mortality using R version 3.6.3. ResultGestational age <37 weeks (Adjusted matched odds ratio (AmOR): 14.02; 95% confidence interval (CI): 3.68–53.46), first-minute APGAR score <7 (AmOR: 5.68; 95% CI: 1.76–18.31), perinatal asphyxia (PNA) (AmOR: 4.62; 95% CI: 1.15–18.53) and being twins (AmOR: 6.84; 95% CI: 1.34–34.96) were significantly associated with neonatal deaths in our study. Furthermore, antenatal care and follow-up during pregnancy (AmOR: 0.15; 95% CI: 0.04–0.53) and having a normal random blood sugar level at admission (AmOR: 0.1; 95% CI: (0.02–0.66) were found to be determinant of neonatal mortalities in our study. ConclusionGestational age less than 37 weeks, first-minute APGAR scores <7, being twins, diagnosis of PNA, antenatal care and follow-up of mothers during pregnancy and normoglycemia in neonates at admission were significant determinant of neonatal death in the NICU of DURH.