Evaluation and Estimation of the Provincial Infant Mortality Rate in China's Sixth Census

Objective To assess the data quality and estimate the provincial infant mortality rate（1q0） from China＇s sixth census. Methods A log-quadratic model is applied to under-fifteen data. We analyze and compare the average relative errors（AREs） for 1q0 between the estimated and reported values using the leave-one-out cross-validation method. Results For the sixth census, the AREs are more than 100% for almost all provinces. The estimated average 1q0 level for 31 provinces is 12.3‰ for males and 10.7‰ for females. Conclusion The data for the provincial 1q0 from China＇s sixth census have a serious data quality problem. The actual levels of 1q0 for each province are significantly higher than the reported values.

A comparison of perinatal and infant mortality rates in British Columbia and Finland:Similarities and differences

Introduction: Despite similarities, perinatal and infant mortality rates between British Columbia, (BC) Canada and Finland differ. Key variables that may influence stillbirth, early neonatal, perinatal and infant mortality rates in BC and Finland were studied. Methods: After standardizing definitions, data for all births between 2001 and 2009 from provincial and national registries were used to compare perinatal outcomes between BC and Finland. Annual change was evaluated with regression analyses. Results: Births before 22 weeks gestation were excluded. All mortality rates per 1000 were lower in Finland vs BC (perinatal: 5.1 vs 6.2, stillbirth: 3.4 vs 3.9, early neonatal 1.7 vs 2.4, infant 2.9 vs 4.0;all p Higher multiple birth and preterm birth rates in BC are affecting mortality rates. Finland’s policy of single embryo transfer is a potential explanation. It is possible to have good perinatal outcomes and low caesarean section rates. Conclusions: The Finnish health care system may suggest possible solutions for improved perinatal outcomes. Lower per capita health care expenditures in Finland do not appear to have adversely affected perinatal outcomes.

SutteARIMA:A Novel Method for Forecasting the Infant Mortality Rate in Indonesia

This study focuses on the novel forecasting method(SutteARIMA)and its application in predicting Infant Mortality Rate data in Indonesia.It undertakes a comparison of the most popular andwidely used four forecasting methods:ARIMA,Neural Networks Time Series(NNAR),Holt-Winters,and SutteARIMA.The data used were obtained from the website of the World Bank.The data consisted of the annual infant mortality rate(per 1000 live births)from 1991 to 2019.To determine a suitable and best method for predicting InfantMortality rate,the forecasting results of these four methods were compared based on the mean absolute percentage error(MAPE)and mean squared error(MSE).The results of the study showed that the accuracy level of SutteARIMA method(MAPE:0.83%andMSE:0.046)in predicting InfantMortality rate in Indonesia was smaller than the other three forecasting methods,specifically the ARIMA(0.2.2)with a MAPE of 1.21%and a MSE of 0.146;the NNAR with a MAPE of 7.95%and a MSE of 3.90;and the Holt-Winters with aMAPE of 1.03%and aMSE:of 0.083.

An Assessment of Association between Neighborhood Socioeconomic Status and Infant Mortality in High Focus States in India

Neighbourhood characteristics influence infant mortality above and beyond individual/household factors. In India, there are very few studies discussing the effects of neighbourhood characteristics on infant mortality. This study examined the effect of neighbourhood socioeconomic characteristics on infant mortality using data from the India’s Third District Level Household Survey conducted in 2007-2008. Multilevel analyses applied on the representative sample of 168,625 nested within 14,193 communities using MCMC procedure. Results established that place of residence, neighbourhood socio-economic factors as important determinants of infant mortality. Overall, being born in affluent (OR: 0.79, p < 0.01), more educated (OR: 0.86, p < 0.01) and socially disadvantaged caste (OR: 0.83, p < 0.01) neighbourhood was associated with the significant reduction in hazards of infant death. The finding of this study suggests that effort should be made to reduce infant mortality in these high focus states by including policies which aim at improving infant survival in the neighbourhood that is economically and socially deprived.

“Breast is best”—Infant-feeding, infant mortality and infant welfare in Germany during the late nineteenth and twentieth centuries

Breastfeeding is considered to be the key variable for infant health. Consequently, UNICEF and the World Health Organization promote the beginning of breastfeeding within the first hour after birth and recommend to exclusively breastfeed the infant during the first six months. The origins of these modern breastfeeding campaigns can be traced back to the beginning of the twentieth century. Whereas high infant mortality rates traditionally were considered to be a matter of fate and the declining birth rates towards the end of the nineteenth century raised fears about the nation’s future and led to the emergence of an increasing infant welfare movement in imperial Germany. As low breastfeeding rates were identified as a key factor behind the high infant mortality rates, the main objective of the infant care movement was to increase breastfeeding. The paper examines how the context of infant care and infant mortality was constructed and how breastfeeding campaigns in the context of infant mortality, breastfeeding rates and socio-political changes developed during the twentieth century. Thus the paper covers the period from the beginnings of social paediatrics at the beginning of the 20th century, the breastfeeding campaigns embedded into Nazi ideology during the Third Reich, until the declining breastfeeding ratios and the “feeding on demand”-movement in the 1970s as well as the ideological differences between West and East Germany during the Cold War.

Assessing Community Health Interventions in Reducing Infant and Child Mortality in the Southeastern Benin

Background: To reduce infant and child mortality in Benin, a package of high-impact interventions per healthcare level was implemented in 2009. This study aimed to assess the quality of community-based health interventions in reducing infant and child mortality within the municipality of Pobè in southeastern Benin. Methods: This was a cross-sectional evaluative study carried out in November 2021 focused on children aged 0 - 59 months, their mothers, health workers, community facilitators, community health workers and the Town Hall health focal point. Mothers and their children were targeted by cluster sampling, and exhaustive selection was used to recruit all other participants. Predetermined scores based on rating criteria were used to assess the quality of community health interventions using the “input, process and outcome” of Donabedian approach. Results: Over 300 mother-child couples, 46 community health workers, 7 health agents, 1 community facilitator and 1 health focal point from Pobè town hall were surveyed. Intervention quality was judged as “average”, with a score of 73.80%. The “inputs” and “outcomes” components were the weakest links. Conclusion: Improving access to the inputs needed by community health workers can enhance the quality of PIHI interventions.

Impact of nurse staffing on reducing infant, neonatal and perinatal mortality rates: Evidence from panel data analysis in 35 OECD countries

Objectives:To investigate the magnitude of effect nurse staffing had on decreasing the newborn mortality rates in member countries of Organisation for Economic Co-operation and Development(OECD).Methods:The statistical technique of panel data analysis was applied to explore the possibility of association between the number of nurses'density per 1,000 population and infant,neonatal and perinatal mortality rates(IMR,NMR and PMR)per 1000 births.The observations of 35 OECD countries were collected over the period of 2000 through 2016.Results:There were significant associations between nurse staffing and IMR,NMR and PMR i.e.a 1%increase in nurse-staffing level reduced IMR,NMR and PMR by 0.98%,0.97%and 0.96%,respectively.Furthermore,the role of nursing-related services in declining the average of newborn mortality rates were investigated at the highest level in Slovenia(-5.50),Sweden(-3.34),Iceland(-2.51),Czech Republic(-1.86),Japan(-1.64)and Finland(-1.64).Moreover,if the current relationship between nursestaffing level and newborn mortality rates are disturbed with nursing shortage(e.g.in Slovak Republic and Israel),then it takes about 17 years for the mortality rates to reduce and restore back to the previous equilibrium.Conclusions:A higher proportion of nurses'density per 1,000 population is associated with lower newborn mortality rates.In addition,the nursing-related services of Slovenia,Sweden,Iceland,Czech Republic,Japan and Finland with the highest impact on improving the health level of newborns would be good patterns for other developed countries in maternity and child health care.

Infant and Under-five Mortality in Bangladesh: Discriminant Analysis

Bangladesh is on target for achieving the Millennium Development Goal 4 relating to infant and under-five mortality because of very rapid reduction in mortality in recent years. But this rate of reduction may be difficult to sustain and may hamper the achievement of Millennium Development Goal 4. Therefore, the main objective of this paper is to discuss and compare the dif- ferent covariates of infant and under-five mortality in the context of overall country, urban and rural levels of Bangladesh using discriminant analysis. For this, the data are taken from Bangladesh Demographic and Health Survey, 2004. In discriminant analysis, the stepwise procedure has been picked up and only the significant variables are ranked according to the rank of Wilk's Lambda val- ues. The canonical discriminant function coefficients (unstandard- ized and standardized) for the predictor variables have also been calculated. Both the results show that breastfeeding is the most important variable in discriminating the two groups of mothers, i.e., mothers experiencing to infant mortality or not and mothers experiencing to under-five mortality or not. The related results of discriminant function also indicate that the discriminant func- tion is statistically significant and discriminates well. Therefore, improvements in the health system are essential for promoting the breastfeeding practices (both inclusive and exclusive), which may be the effective strategies to reach families and communities with targeted messages and information.

Post Millennium Development Goals Prospect on Child Mortality in India: An Analysis Using Autoregressive Integrated Moving Averages (ARIMA) Model

Background & Objectives: Sustainable Development Goals (SDGs) are set up as a part of the Post Millennium Development Goals (MDGs). Then it becomes essential to review the achievement of the MDGs in India and lessons learned to incorporate into the SDGs. The present study reviews and predicts different components of under-five mortality rate beyond 2015 to assess the present situation and to determine the future possibilities of achieving the new targets for SDGs in India. Data and Methods: It uses available time series data on different components of U5MR from the India’s Sample Registration System (SRS). Autoregressive Integrated Moving Averages (ARIMA) model has been taken as the method of time series analysis to forecast the mortality rates beyond 2015. Results: There is a consistent pattern of faster decline in the under-five mortality compared with the neonatal mortality rate across all major states in India although neonatal mortality contributes largest share in under-five mortality. Again, share of neonatal death among under-five death is increasing steadily over the future projected years. This indicates very slow progress of reduction in neonatal mortality. Stimulating efforts with new intervention programmes will be needed to focus more on lowering neonatal mortality particularly in rural India.

Validation of the China＇s maternal and child mortality surveillance in the diagnosis of infant deaths in two counties in Guizhou Province

The infant mortality rate in China declined from 50.2‰ to 13.8‰ between 1991 and 2009.1 Although China has made good progress,there were still about 190 thousand infants who died in 2009.Reliable birth and death registration and the causes of death in populations are essential for public health planning.The National Maternal and Child Mortality Surveillance System （MCMS） is the major system to register maternal and infant deaths.It samples 126 districts and 210 counties,totally 336 sites,covering 12% of counties and 9% of the population.Causes of deaths are determined by the attending clinician.For those who die out hospital or clinic,a community health provider will be asked to visit that family and make a decision as to the cause of death.