Suchergebnisse

Abstract Background Nigeria continues to have one of the highest rates of neonatal deaths in Africa. This study aimed to identify risk factors associated with neonatal death in Nigeria using the 2008 Nigeria Demographic and Health Survey (NDHS). Methods Neonatal deaths of all singleton live-born infants between 2003 and 2008 were extracted from the 2008 NDHS. The 2008 NDHS was a multi-stage cluster sample survey of 36,298 households. Of these households, survival information of 27,147 singleton live-borns was obtained, including 996 cases of neonatal mortality. The risk of death was adjusted for confounders relating to individual, household, and community level factors using Cox regression. Results Multivariable analyses indicated that a higher birth order of newborns with a short birth interval ≤ 2 years (hazard ratio [HR] = 2.19, confidence interval [CI]: 1.68–2.84) and newborns with a higher birth order with a longer birth interval > 2 years (HR = 1.36, CI: 1.05–1.78) were significantly associated with neonatal mortality. Other significant factors that affected neonatal deaths included neonates born to mothers younger than 20 years (HR = 4.07, CI: 2.83–5.86), neonates born to mothers residing in rural areas compared with urban residents (HR = 1.26, CI: 1.03–1.55), male neonates (HR = 1.30, CI: 1.12–1.53), mothers who perceived their neonate's body size to be smaller than the average size (HR = 2.10, CI: 1.77–2.50), and mothers who delivered their neonates by caesarean section (HR = 2.80, CI: 1.84–4.25). Conclusions Our study suggests that the Nigerian government needs to invest more in the healthcare system to ensure quality care for women and newborns. Community-based intervention is also required and should focus on child spacing, childbearing at a younger age, and poverty eradication programs, particularly in rural areas, to reduce avoidable neonatal deaths in Nigeria.

AbstractEach year, 295,000 women die during and just after pregnancy, and 2.4 million babies die in the first month of their lives. In 2019, 2,160,000 neonatal deaths and 275,000 maternal deaths occurred in low-income and lower-middle-income countries alone, translating to a welfare loss equivalent to $426 billion and $36 billion for neonatal and maternal deaths, respectively. The total loss was $462 billion or almost 6 % of these countries' combined GDP. In the sustainable development goals pledge, the world promised to reduce maternal deaths to 0.07 % and neonatal mortality to below 1.2 %, saving about 200,000 women and 1.2 million children from dying annually. However, on the current trajectory, maternal mortality is expected to decline to only 0.16 % and neonatal deaths to only 1.5 % by 2030. This article analyses the most cost-effective way to reduce maternal and neonatal deaths – Increase coverage of basic emergency obstetric and newborn care from 68 to 90 % combined with increased family planning services in 55 low-income and lower-middle-income countries which account for around 90 % of the burden of maternal and neonatal mortality globally. The proposed package will require $3.2 billion per year more investment and will deliver benefits worth $278 billion per year in avoided deaths and higher economic growth. It will also yield a demographic dividend benefit equivalent to $25 billion annually. For every $1 invested, the social and economic benefits are estimated to be $87. The benefit-cost ratio is 87.

Background: Neonatal MortalityRate (NMR) reflects the quality of health services provided by the government. It is very important to disclose the health system capability of each country in managing mother and child health programs because it is an essential health policy that should be prioritized. The health system capability of a country will determine the welfare and social guarantee because most of NMR causes are preventable. Several components such as maternal factors, neonatal and health services were determined as predictors of NMR. The objective of this study is to compare neonatal mortality trends among eight South East Asia Countries (SEAC) from 2000 to 2017. Method: A cross-sectional design was used to analyze the data regarding the causes of neonatal death between 2000 and 2017. Data were taken from World Health Organization Maternal Child Epidemiology Estimation (WHO MCEE) database.The collected data were live birth; neonatal mortality rate; and the big five of neonatal mortality etiologies in the eight SEAC. Data were then analyzed descriptively with line chart to describe the trend of NMR. Result: This study found that Indonesia had the highest neonatal mortality rate, yet the trend decreased gradually from 102.700 in 2000 to 60.986 in 2017, followed by Philippines, Vietnam, Myanmar, Cambodia, Thailand, Laos, and Malaysia respectively. On the other hand, the trend of live birth was the lowest in Indonesia and the highest in Philippines . According to the data regarding the leading cause of NMR, preterm birth was the major cause of neonatal mortality followed by birth asphyxia and congenital defects. Conclusion: Indonesia has the highest mortality rate, yet the etiology such as as premature birth, asphyxia, and congenital disorder is similar to the other eight countries.

Although the neonatal mortality rate (NMR) in Bangladesh remained steady between 1995‐99 and 1999‐2003 (41‐42 deaths per 1,000 live births), evidence from the management information system (MIS) of a large nongovernmental organization (NGO) program indicates that the NMR declined by about 50 percent between 1996 and 2002 in the area served. This study aims to validate the recording of neonatal deaths among the cohort of children registered as born in 2003 and to assess the evidence of a decline in the NMR. It also measures the coverage of reproductive health outreach services, focusing on 12 of the 27 NGOs that have provided services in the same areas since 1996. Field‐workers' registers, verbal autopsy reports, and immunization records were checked to confirm infants' survival. Interviews were conducted with 142 mothers of children who died within 28 days postpartum and with a random sample of 109 women with registered stillbirths. Out of 11,253 registered live births in 2003, 210 neonatal deaths were found, compared with 194 deaths that were reported in the MIS for 2003. The corrected NMR was 19 deaths per 1,000 live births, and it was in the range of 15‐29 deaths per 1,000 live births in 11 of the NGO areas. Because underreporting of neonatal deaths was probably higher in 1996 when the MIS‐reported NMR was 39 deaths per 1,000 live births, the decline in the NMR is likely to have been genuine.

OBJECTIVE: The present study estimated the national and urban–rural levels and causes of neonatal deaths in China annually between 2014 and 2018 to provide data support for the further end of preventable neonatal deaths for China and other low-income and middle-income countries. METHODS: The study was based on data from the National Maternal and Child Health Surveillance System. All neonates of surveillance districts (gestational week: ≥28 weeks) who died after delivery have been involved in the study. The mortality rate and the leading causes of death for neonates were analysed. RESULTS: The neonatal mortality rate (NMR) of China has steadily decreased from 5.9 deaths per 1000 live births in 2014 to 3.9 deaths per 1000 live births in 2018. The NMR in 2018 of urban and rural areas was 2.2 deaths per 1000 live births and 4.7 deaths per 1000 live births, respectively. The leading preventable causes of neonatal deaths are the same in the urban and rural areas were same, which were preterm birth, intrapartum complications and pneumonia. Mortality rates of these three causes fell significantly between 2014 and 2018 but contributed to a higher proportion of deaths in rural areas than urban areas. The proportion of preventable deaths accounted for 74.6% in 2018. CONCLUSIONS: The NMR of China has decreased steadily from 2014 to 2018. However, the inequality between urban and rural areas still exists. The goal of government interventions should be to reduce the health inequality of neonates and further take targeted measures to eliminate preventable neonatal death.

Regionalization ofperinatal care is widely assumed to be an effective means of improving pregnancy outcomes. However, due to limitations of the research designs employed in previous studies aimed at empirically confirming this conventional wisdom, strong evidence concerning the impact of regionalization on pregnancy outcomes is still lacking. In this article an interrupted time-series design is used to assess the impact of regionalization of perinatal care on infant and early neonatal mortality in Central New York. The analysis indicates that regionalization has had a statistically significant, grad ual permanent impact on both infant and early neonatal mortality.

BACKGROUND: Low-income and middle-income countries have introduced different health insurance schemes over the past decades, but whether different schemes are associated with different neonatal outcomes is yet unknown. We examined the association between the health insurance coverage scheme and neonatal mortality in Colombia. METHODS: We used Colombian national vital registration data, including all live births (2 506 920) and neonatal deaths (17 712) between 2008 and 2011. We used Poisson regression models to examine the association between health insurance coverage and the neonatal mortality rate (NMR), distinguishing between women insured via the contributory scheme (40% of births, financed through payroll and employer's contributions), government subsidised insurance (47%) and the uninsured (11%). RESULTS: NMR was lower among babies born to mothers in the contributory scheme (6.13/1000) than in the subsidised scheme (7.69/1000) or the uninsured (8.38/1000). Controlling for socioeconomic and demographic factors, NMRs remained higher for those in the subsidised scheme (OR 1.09, 95% CI 1.05 to 1.14) and the uninsured (OR 1.16, 95% CI 1.10 to 1.23) compared to those in the contributory scheme. These differences increased in models that additionally controlled for caesarean section (C-section) delivery. This increase was due to the higher fraction of C-section deliveries among women in the contributory scheme (49%, compared to 34% for the subsidised scheme and 28% for the uninsured). CONCLUSIONS: Health insurance through the contributory system is associated with lower neonatal mortality than insurance through the subsidised system or lack of insurance. Universal health insurance may not be sufficient to close the gap in newborn mortality between socioeconomic groups.

In Bangladesh, like other developing countries, most births occur at home or in the community, so logistic problems and taboos prevent the weighing of every newborn child. This study was performed to see whether other simpler measurements could be substituted for weight to identify neonates of low birth weight. A total of 1676 live births at the Chittagong Medical College Hospital constituted the study sample, and this showed a high correlation between mid-arm circumference and birth weight (r=0.792, p<0·000). A mid-arm circumference of <9·0 cm had the best sensitivity and specificity for identifying newborns with a birth weight of less than 2500 g. These neonates were followed up to record neonatal deaths. Neonatal mortality showed an inverse relation with mid-arm circumference. A mid-arm circumference of <9·0 cm and a birth weight of <2500 g were equally useful in predicting neonatal outcome. Mid-arm circumference is a simple, quick and reliable indicator for predicting low birth weight and neonatal outcome, and can be easily measured by medical practitioners and traditional birth attendants (TBAs) in the community of developing countries like Bangladesh.

Background: Tribal peoples are among the most marginalised groups worldwide. Evidence on birth outcomes in these groups is scant. We describe inequalities in Stillbirth Rate (SBR), Neonatal Mortality Rate (NMR), and uptake of maternal and newborn health services between tribal and less disadvantaged groups in eastern India, and examine the contribution of poverty and education to these inequalities. Methods: We used data from a demographic surveillance system covering a 1 million population in Jharkhand State (March 2017 – August 2019) to describe SBR, NMR, and service uptake. We used logistic regression analysis combined with Stata's adjrr-command to estimate absolute and relative inequalities by caste/tribe (comparing Particularly Vulnerable Tribal Groups (PVTG) and other Scheduled Tribes (ST) with the less marginalised Other Backward Class (OBC)/none, using the Indian government classification), and by maternal education and household wealth. Results: PVTGs had a higher NMR (59/1000) than OBC/none (31/1000) (rate ratio (RR): 1.92, 95%CI: 1.55–2.38). This was partly explained by wealth and education, but inequalities remained large after adjustment (adjusted RR: 1.59, 95%CI: 1.28–1.98). NMR was also higher among other STs (44/1000), but disparities were smaller (RR: 1.47, 95%CI: 1.23–1.75). There was a systematic gradient in NMR by maternal education and household wealth. SBRs were only higher in poorer groups (RR poorest vs. least poor :1.56, 95%CI: 1.14–2.13). Uptake of facility-based services was low among PVTGs (e.g. institutional birth: 25% vs. 69% in OBC/none) and among poorer and less educated women. However, 65% of PVTG women with an institutional birth used a maternity vehicle vs. 34% among OBC/none. Visits from frontline workers (Accredited Social Health Activists [ASHAs]) were similar across groups, and ASHA accompaniment of institutional births was similar across caste/tribe groups, and higher among poorer and less educated women. Attendance in participatory women's groups was similar across ...