Variations In Neonatal Mortality Research Articles

Variations in neonatal mortality of preterm infants with intraparenchymal haemorrhage in Europe: the EPICE cohort

ObjectiveThe aim of this study was to investigate variations in mortality before neonatal intensive care unit (NICU) discharge of infants born preterm with intraparenchymal haemorrhage (IPH) in Europe with a...

Is the quality of public health facilities always worse compared to private health facilities: Association between birthplace on neonatal deaths in the Indian states.

The role of place of delivery on the neonatal health outcomes are very crucial. Although the quality of care is being improved, there is no consensus about who is the better healthcare provider in low and middle-income countries (LMICs), public or private facilities. The aim of this study is to assess the differentials in neonatal mortality by the type of healthcare providers in India and its states. We used the data from the fourth wave of the National Family Health Survey 2015-16 (NFHS-4). Information on 259,627 live births to women within the five years preceding the survey was examined. Neonatal mortality rates for state and national levels were calculated using DHS methodology. Multi-variate logistics regression was performed to find the effect of birthplace on neonatal deaths. Propensity score matching (PSM) was used to evaluate the relationship between place of delivery and neonatal deaths to account for the bias attributable to observable covariates. The rise in parity of the women and purchasing power influences the choice of healthcare providers. Increased neonatal mortality was found in private hospital delivery compared to public hospitals in Punjab, Rajasthan, Chhattisgarh, Madhya Pradesh, Bihar, Jharkhand, Odisha, Goa, Maharashtra, Andhra Pradesh and Karnataka states using propensity score matching analysis. However, analysis on the standard of pre-natal and post-natal care indicates that private hospitals generally outperformed public hospitals. The study observed a significant variation in neonatal mortality among public and private health care systems in India. Findings of the study urges that more attention be paid to the improve care at the place of delivery to improve neonatal health. There is a need of strengthened national health policy and public-private partnerships in order to improve maternal and child health care in both private and public health facilities.

Multilevel modelling of neonatal mortality in Ghana: Does household and community levels matter?

BackgroundNeonatal mortality accounts for an increasing share of under-five deaths, and they are declining at a slower rate than postnatal deaths. Apparently, neonatal mortality is increasingly becoming a major public health problem in Ghana and the world over. The current study sought to analyze neonatal mortality as a function of predictor variables and to estimate and understand unobserved household and community-level residual effects on neonatal mortality to provide data driven evidence to shape informed policies and interventions aimed at reducing the neonatal mortality burden. MethodsThe current study extracted three-level complex data on 5884 children born in the five years preceding the 2014 Ghana Demographic and Health Survey. A two-level and three-level multilevel logistic models were applied to estimate unobserved household and community-level variations in neonatal mortality in the presence of set of predictor variables. Sampling weights were incorporated in both the descriptive and inferential analysis since the data used emanated from a complex survey. Model fit statistics such as AIC scores for a weighted two-level and three-level random intercept logistic models were compared. The model with the lowest AIC score was considered the most preferred model. ResultsThe household-level random intercept model suggested that the odds of neonatal mortality was higher among multiple births [OR = 3.15 (95% CI: 1.17, 8.50)], babies born to mothers who received prenatal care from non-skilled worker [OR = 5.88 (95% CI: 2.90, 11.91)], babies delivered through caesarian section [OR = 2.47 (95% CI: 1.06, 5.79)], a household with 1–4 members [OR = 10.23 (95% CI: 4.17, 25.50)], a short preceding birth interval (<24 months) [OR = 3.05 (95% CI: 1.18, 7.88)], and preceding birth interval between 24 and 47 months [OR = 2.88 (95% CI: 1.41, 5.91)]. Substantial unobserved household-level residual variations in neonatal mortality were observed. ConclusionThe findings of the current study provide an actionable information to be used by government and other stakeholders in the health sector to renew commitment to reduce neonatal mortality to an acceptable level. There is the need to intensify maternal health education by health providers to encourage pregnant women to visit antenatal clinics at least four times so they could benefit substantially from ANC services.

The survival rate of neonates in Pakistan: Problems in health care access, quality and recommendations.

There is a high prevalence of infant mortality in South Asia and other parts of Asia, but overall, the bulk of neonatal deaths occur in developing countries. Although Pakistan has made great strides in the past decade to reduce child mortality with the help of foreign donors and the government, very little progress has been made in reducing neonate and infant mortality. Several studies have demonstrated the potential for low-cost therapies to greatly reduce neonatal mortality by helping pregnant mothers and their newborns. We need to shed light on the efforts and problems surrounding this topic in order to find and implement solutions backed by research to lower newborn mortality. This brief overview was produced using international standards for conducting reviews. Researchers opted for an explanatory methodology. Our findings were based on research conducted through PubMed, Google's literature database, Journals Online, and the Internet Library. All of the works consulted primary sources, such as the World Health Organization (WHO) and the World Bank. The desired findings were obtained by using the term "neonatal mortality." The study's authors were interested in tracking variations in neonatal mortality over time. The increasing prevalence of neonatal death in Pakistan emphasizes the need for policies and programs that prioritized the health of children. Neonatal survival can be improved with the help of basic obstetric and newborn care in Pakistan.

Risk factor of neonatal mortality in Ethiopia: multilevel analysis of 2016 Demographic and Health Survey

BackgroundIn sub-Saharan African countries, neonatal mortality rates remain unacceptably high. Ethiopia is one of the countries in Sub-Saharan Africa with the highest death rates of newborn children. Therefore, this study aimed to identify the risk factors associated with neonatal mortality in Ethiopia at the individual and community level.MethodsThe 2016 Ethiopian Demographic and Health Survey data was accessed and used for the analysis. A total of 2449 newborn children were included in the analysis. The multilevel logistic regression model was used to identify the significant factor of neonatal mortality. Adjusted odds ratio with a 95% confidence interval and p-value < 0.05 in the multilevel model was reported.ResultsA total of 2449 newborn children were included in this study. Multiple birth type (AOR = 3.18; 95% CI 2.78, 3.63), birth order of ≥ 5 (AOR = 2.15; 95% CI 1.75, 2.64), pre-term birth (AOR = 5.97; 95% CI 4.96, 7.20), no antenatal care (ANC) visit during pregnancy (AOR = 2.33; 95% CI 2.09, 2.61), not received TT injection during pregnancy (AOR = 2.28; 95% CI 1.92, 2.71), delivered at home (AOR = 1.99; 95% CI 1.48, 2.69), less than 24 months of preceding birth interval (AOR = 1.51; 95% CI 1.35,1.68), smaller birth size (AOR = 1.58; 95% CI 1.46, 1.71), never breastfeeding (AOR = 2.43; 95% CI 2.17, 2.72), poor wealth index (AOR = 1.29; 95% CI 1.17,1.41), non-educated mothers (AOR = 1.58; 95% CI 1.46, 1.71), non-educated fathers (AOR = 1.32; 95% CI 1.12, 1.54), rural residence (AOR = 2.71; 95% CI 2.23, 3.29), unprotected water source (AOR = 1.35; 95% CI 1.16, 1.58), and have no latrine facility (AOR = 1.78; 95% CI 1.50, 2.12) were associated with a higher risk of neonatal mortality. Neonates living in Amhara, Oromia, Somali, Harari, and Dire Dawa had a higher risk of neonatal mortality compared to Tigray. Moreover, the random effects result showed that about 85.57% of the variation in neonatal mortality was explained by individual- and community-level factors.ConclusionsThe findings suggest that attention be paid to education-based programs for mothers that would highlight the benefits of delivery care services, such as ANC visits, TT injections, and facility births. Meanwhile, public health initiatives should focus on expanding access to quality sanitation facilities, especially for latrines and drinking water that could improve neonatal health at the community-level as a whole.

Variations in neonatal mortality, infant mortality, preterm birth and birth weight in England and Wales according to ethnicity and maternal country or region of birth: an analysis of linked national data from 2006 to 2012

BackgroundRisks of adverse birth outcomes in England and Wales are relatively low but vary across ethnic groups. We aimed to explore the role of mother’s country of birth on birth...

Variation in neonatal mortality and its relation to country characteristics in sub-Saharan Africa: an ecological study

BackgroundA substantial reduction in neonatal mortality is the main priority to reduce under-five mortality. A clear understanding of the variation in neonatal mortality and the underlying causes is important for...

VARIATION IN NEONATAL MORTALITY AND ITS RELATION TO COUNTRY CHARACTERISTICS IN SUB-SAHARAN AFRICA

BackgroundA substantial reduction in neonatal mortality is the main priority to reduce under-five mortality. A clear understanding of the variation in neonatal mortality and the underlying causes is important for...

Seasonal Variation in Solar Ultra Violet Radiation and Early Mortality in Extremely Preterm Infants.

Vitamin D production during pregnancy promotes fetal lung development, a major determinant of infant survival after preterm birth. Because vitamin D synthesis in humans is regulated by solar ultraviolet B (UVB) radiation, we hypothesized that seasonal variation in solar UVB doses during fetal development would be associated with variation in neonatal mortality rates. This cohort study included infants born alive with gestational age (GA) between 23 and 28 weeks gestation admitted to a neonatal unit between 1996 and 2010. Three infant cohort groups were defined according to increasing intensities of solar UVB doses at 17 and 22 weeks gestation. The primary outcome was death during the first 28 days after birth. Outcome data of 2,319 infants were analyzed. Mean birth weight was 830 ± 230 g and median gestational age was 26 weeks. Mortality rates were significantly different across groups (p = 0.04). High-intensity solar UVB doses were associated with lower mortality when compared with normal intensity solar UVB doses (hazard ratio: 0.70; 95% confidence interval: 0.54-0.91; p = 0.01). High-intensity solar UVB doses during fetal development seem to be associated with risk reduction of early mortality in preterm infants. Prospective studies are needed to validate these preliminary findings.

Early life mortality and height in Indian states

Height is a marker for health, cognitive ability and economic productivity. Recent research on the determinants of height suggests that postneonatal mortality predicts height because it is a measure of the early life disease environment to which a cohort is exposed. This article advances the literature on the determinants of height by examining the role of early life mortality, including neonatal mortality, in India, a large developing country with a very short population. It uses state level variation in neonatal mortality, postneonatal mortality, and pre-adult mortality to predict the heights of adults born between 1970 and 1983, and neonatal and postneonatal mortality to predict the heights of children born between 1995 and 2005. In contrast to what is found in the literature on developed countries, I find that state level variation in neonatal mortality is a strong predictor of adult and child heights. This may be due to state level variation in, and overall poor levels of, pre-natal nutrition in India.

Neonatal mortality in Nepal: A multilevel analysis of a nationally representative

ObjectivesThis study investigated individual, community and district level factors associated with neonatal mortality among a national sample of Nepalese women. MethodsData were drawn from the 2006 Nepalese Demographic and Health Survey on women aged 15–49 who delivered within three years prior to the survey (N=4136). Multilevel logistic regression models with three levels were fitted to assess the influences of measured individual, community and district level variables on neonatal mortality. ResultsThe total neonatal mortality in three years preceding the survey was 4.5 deaths per 100 live births (N=190), with neonatal mortality rate (NMR)=46 per 1000 live births. Having a partner with no formal education, being in the middle on the wealth index and residing in less developed district were associated with neonatal death in bivariate analysis. Women who were assisted by skilled personnel during delivery were less likely to have neonatal death (adjusted OR for no assistance = 2.26, 95% CI=1.19–4.26). Having prenatal care with skilled attendant was associated with less likelihood of neonatal death (adjusted OR for no care = 1.75, 95% CI=1.17–2.62). Older women, mother’s education, parity and wealth index were associated with neonatal mortality. Considerable variations in neonatal mortality at community and district levels were found. ConclusionsThese findings emphasize the need for interventions at the individual level with regard to access and utilization of healthcare in order to reduce the neonatal mortality in Nepal.

Clustering of Neonatal Deaths inBangladesh: Results From theProjahnmo Studies

Neonatal mortality (NM) tends to be clustered within a small subset of mothers, households and/or geographical areas. Knowledge of the maternal and newborn factors associated with NM can help identify high-risk mothers and guide the targeting of intervention programmes. Data from pregnancy history surveys conducted as part of the Project for Advancing the Health of Newborns and Mothers (Projahnmo) in Sylhet and Mirzapur districts of Bangladesh were used to investigate risk factors for NM. We analysed data from babies born between 2001 and 2005 in the control clusters of the Projahnmo trials. Generalised linear mixed models were applied to quantify the heterogeneity among mothers and to investigate factors that contribute to this heterogeneity. There was an indication of correlation among siblings' outcomes. Neonates whose preceding sibling had died as a neonate in the mothers' lifetime pregnancy history were more likely (up to 1.9 times) to die than those with a living sibling. Factors that varied at the child and mother levels as well as the preceding siblings' outcome explained a large proportion (60% in Sylhet and 70% in Mirzapur) of the between-mother variation in NM. The preceding sibling's outcome may be a surrogate for genetic and other maternal health factors such as nutrition, infection or environmental factors that were not measured within Projahnmo. Further research into these factors is required in order to explain the variation in the risk for NM.

The Impact of Neonatal Care Resources on Regional Variation in Neonatal Mortality Among Very Low Birthweight Infants in Korea

Faced with extremely low fertility rates and increasing numbers of low-birthweight births in Korea, we examined the factors affecting the mortality of very-low-birthweight (VLBW) infants in Korea. A survey was conducted in 91 of 93 hospitals providing neonatal intensive care in Korea in 2009. Data included information on number of neonatal intensive care unit (NICU) beds, medical workforce, resources in the NICU, birth and death. There was approximately one NICU per 4888 births, one NICU bed per 355 births, one mechanical ventilator per 739 births, one incubator per 327 births and one board-certified neonatologist per 4683 births. Regional disparity existed in neonatal care resources and consequently in mortality rates. VLBW infants' mortality was related to the NICU facility level, volume of VLBW infants and geographic regions. The capital city, Seoul, has the best NICU facilities and workforce, and the least mortality. Overall mortality rates before hospital discharge for <750, 750-999 and 1000-1499 g were 44.8%, 20.4% and 6.5% respectively. There was a two to threefold difference in the mortality rates across the regions. However, following adjustments for NICU facility level and volume of VLBW infants admissions, regional difference in mortality rates was markedly reduced in the <750 g and disappeared in the larger VLBW groups. Regional disparity in mortality of VLBW infants in Korea is most marked in the lowest-birthweight group, <750 g. This disparity is primarily due to lack of resources for neonatal intensive care in most of provincial areas.

Quantifying spatial disparities in neonatal mortality using a structured additive regression model.

BackgroundNeonatal mortality contributes a large proportion towards early childhood mortality in developing countries, with considerable geographical variation at small areas within countries.MethodsA geo-additive logistic regression model is proposed for quantifying small-scale geographical variation in neonatal mortality, and to estimate risk factors of neonatal mortality. Random effects are introduced to capture spatial correlation and heterogeneity. The spatial correlation can be modelled using the Markov random fields (MRF) when data is aggregated, while the two dimensional P-splines apply when exact locations are available, whereas the unstructured spatial effects are assigned an independent Gaussian prior. Socio-economic and bio-demographic factors which may affect the risk of neonatal mortality are simultaneously estimated as fixed effects and as nonlinear effects for continuous covariates. The smooth effects of continuous covariates are modelled by second-order random walk priors. Modelling and inference use the empirical Bayesian approach via penalized likelihood technique. The methodology is applied to analyse the likelihood of neonatal deaths, using data from the 2000 Malawi demographic and health survey. The spatial effects are quantified through MRF and two dimensional P-splines priors.ResultsFindings indicate that both fixed and spatial effects are associated with neonatal mortality.ConclusionsOur study, therefore, suggests that the challenge to reduce neonatal mortality goes beyond addressing individual factors, but also require to understanding unmeasured covariates for potential effective interventions.

Bayesian Partitioning for Modeling and Mapping Spatial Case–Control Data

Methods for modeling and mapping spatial variation in disease risk continue to motivate much research. In particular, spatial analyses provide a useful tool for exploring geographical heterogeneity in health outcomes, and consequently can yield clues as to disease etiology, direct public health management, and generate research hypotheses. This article presents a Bayesian partitioning approach for the analysis of individual level geo-referenced health data. The model makes few assumptions about the underlying form of the risk surface, is data adaptive, and allows for the inclusion of known determinants of disease. The methodology is used to model spatial variation in neonatal mortality in Porto Alegre, Brazil.

NEONATAL MORTALITY IN THE EMPOWERED ACTION GROUP STATES OF INDIA: TRENDS AND DETERMINANTS

In India, the eight socioeconomically backward states of Bihar, Chhattisgarh, Jharkhand, Madhya Pradesh, Orissa, Rajasthan, Uttaranchal and Uttar Pradesh, referred to as the Empowered Action Group (EAG) states, lag behind in the demographic transition and have the highest infant mortality rates in the country. Neonatal mortality constitutes about 60% of the total infant mortality in India and is highest in the EAG states. This study assesses the levels and trends in neonatal mortality in the EAG states and examines the impact of bio-demographic compared with health care determinants on neonatal mortality. Data from India's Sample Registration System (SRS) and National Family and Health Survey (NFHS-2, 1998-99) are used. Cox proportional hazard models are applied to estimate adjusted neonatal mortality rates by health care, bio-demographic and socioeconomic determinants. Variations in neonatal mortality by these determinants suggest that universal coverage of all pregnant women with full antenatal care, providing assistance at delivery and postnatal care including emergency care are critical inputs for achieving a reduction in neonatal mortality. Health interventions are also required that focus on curtailing the high risk of neonatal deaths arising from the mothers' younger age at childbirth, low birth weight of children and higher order births with short birth intervals.

Differences in Neonatal Mortality Among Whites and Asian American Subgroups

To obtain information about health outcomes in neonates in 9 subgroups of the Asian population in the United States. Cross-sectional comparison of outcomes for births to mothers of Cambodian, Chinese, Filipino, Indian, Japanese, Korean, Laotian, Thai, and Vietnamese origin and for births to non-Hispanic white mothers. Regression models were used to compare neonatal mortality across groups before and after controlling for various risk factors. All California births between January 1,1991, and December 31, 2001. More than 2.3 million newborn infants. Racial and ethnic groups. Neonatal mortality (death within 28 days of birth). The unadjusted mortality rate for births to non-Hispanic white mothers was 2.0 per 1000. The unadjusted mortality rate for births to Chinese and Japanese mothers was significantly lower (Chinese: 1.2 per 1000, P<.001; Japanese: 1.2 per 1000, P=.004), and for births to Korean mothers the rate was significantly higher (2.7 per 1000, P=.003). For infants of Chinese mothers, observed risk factors explain the differences observed in unadjusted data. For infants of Cambodian, Japanese, Korean, and Thai mothers, differences persist or widen after risk factors are considered. After risk adjustment, infants of Cambodian, Japanese, and Korean mothers have significantly lower neonatal mortality rates compared with infants born to non-Hispanic white mothers (adjusted odds ratios, 0.58 for infants of Cambodian mothers, 0.67 for infants of Japanese mothers, and 0.69 for infants of Korean mothers; all P<.05); infants of Thai mothers have higher neonatal mortality rates (adjusted odds ratio, 1.89; P<.05). There are significant variations in neonatal mortality between subgroups of the Asian American population that are not entirely explained by differences in observable risk factors. Efforts to improve clinical care that treat Asian Americans as a homogeneous group may miss important opportunities for improving infant health in specific subgroups.

Birth Weight and Illness Severity

Richardson, Douglas K.; Phibbs, Ciaran S.; Gray, James E.; McCormick, Marie C.; Workman-Daniels, Kathryn; Goldmann, Donald A. Author Information

Birth Weight and Illness Severity: Independent Predictors of Neonatal Mortality

Low birth weight is a major determinant of neonatal mortality. Yet birth weight, even in conjunction with other demographic markers, is inadequate to explain the large variations in neonatal mortality between intensive care units. This variation probably reflects differences in admission severity. The authors have recently developed the Score for Neonatal Acute Physiology (SNAP), an illness severity index specific for neonatal intensive care, and demonstrated illness severity to be a major determinant of neonatal mortality. To define the relative contributions of birth weight and illness severity to the risk of neonatal mortality and to identify other significant independent risk factors. Logistic regression was used to analyze data from a cohort of 1621 consecutive admissions to three neonatal intensive care units (92 deaths), to test six alternative predictive models. The best logistic model was then used to develop a simple additive clinical score, the SNAP Perinatal Extension (SNAP-PE). These analyses demonstrated that birth weight and illness severity are powerful independent predictors across a broad range of birth weights and that their effects are additive. Below 750 g, there is an interaction between birth weight and SNAP. Other factors that showed independent predictive power were low Apgar score at 5 minutes and small size for gestational age. Separate derivation and test samples were used to demonstrate that the SNAP-PE is comparable to the best logistic model and has a sensitivity and specificity superior to either birth weight or SNAP alone (receiver-operator characteristic area .92 +/- .02) as well as excellent goodness of fit. This simplified clinical score provides accurate mortality risk estimates for application in a broad array of clinical and research settings.

Determinants of Regional Variations in Infant Mortality in Rural India

An analytical framework is specified for understanding the determinants of infant mortality. It distinguishes between factors at three levels – village, household and individual – and arranges them in ascending order with respect to their proximity to infant mortality. Village and household-level factors are assumed to influence infant mortality indirectly by influencing at least one of the six individual-level factors. The present analysis of the data aggregated at the state level clearly demonstrates the importance of both medical and non-medical factors for explaining the observed regional differences in infant mortality in rural India. The percentage of births attended by trained medical personnel and poverty, are the two important determinants of regional variations in neo-natal mortality; and the village-level availability of medical facilities and the extent of triple vaccination are the two important determinants of post-neo-natal mortality. The influence of adult women's literacy on infant mortality is explained by better medical care at birth, and preventive and curative medical care during the post-neo-natal period. Medical factors have been shown to be slightly more important than non-medical factors. This suggests that it might be possible to reduce the high level of infant mortality currently prevalent in many states in India by simple preventive medical interventions.