STILLBIRTH RATE AND INFANT MORTALITY RATE: STUDY IN THE REGIONS OF UKRAINE MOST INTENSIVELY RADIOCONTAMINATED UPON THE CHORNOBYL NPP ACCIDENT

OBJECTIVE

to evaluate the time pattern peculiarities of stillbirth and infant mortality rates in the radiocontaminated territories of Ukraine in the post-accident period on the basis of the national State Statistics Service data.

OBJECT OF THE STUDY

stillbirth and infant mortality rates of population of the most intensively radiocontaminated territories of Ukraine (Lughinskyi, Narodytskyi, Ovrutskyi and Olevskyi districts of Zhytomyrska oblast, Vyshgorodskyi, Ivankivskyi and Poliskyi districts of Kyivska oblast, Rokytnivskyi and Sarnenskyi districts of Rivnenska oblast, and Kozeletskyi and Rypkinskyi districts of Chernihivska oblast).Research materials and methods. Information resources of the State Statistics Service of Ukraine for 1986-2020 regarding the infant mortality and stillbirth rates were used in the study. Demographic, mathematical-statistical, graphical, and software-technological research methods were applies.

RESULTS AND CONCLUSIONS

Parameters of infant mortality and stillbirth rates for the 1986-2020 period were studied retrospectively. Significant variations in values were revealed both between the territories and years of survey.

The Impact of Sociodemographic, Macroeconomic, and Health Status and Resources on Infant Mortality Rates in Oman: Evidence from 1980 to 2022

BACKGROUND

The infant mortality rate (IMR) is an important reflection of the well-being of infants and the overall health of the population. This study aims to examine the macroeconomic (ME), sociodemographic (SD), and health status and resources (HSR) effects on IMR, as well as how they may interact with each other.

METHODS

A retrospective time-series study using yearly data for Oman from 1980 to 2022. Partial Least Squares-Structural Equation Modelling (PLS-SEM) was utilized to develop the exploratory model of the determinants of IMR.

RESULTS

The model indicates that HSR determinants directly, but negatively, affect IMR (β = -0.617, p < 0.001). SD directly and positively affects IMR (β = 0.447, p < 0.001). ME only indirectly affects IMR (β = -0.854, p < 0.001). ME determinants also exert some direct influences on both HSR (β = 0.722, p < 0.001) and SD (β = -0.916, p < 0.001) determinants.

CONCLUSIONS

This study has indicated that IMR is a multi-faceted issue. It also highlighted the interplay of numerous variables and their influence on IMR, particularly the role that social status, the health sector, and the wealth of the country and its population play in reducing IMR. These findings indicate that an integrated policy that addresses socioeconomic and health-related factors and the overall ME environment is necessary for the health and well-being of the children and the population overall in Oman.

The Causes and Factors Associated with Infant Mortality Rate in Ethiopia: The Application of Structural Equation Modelling

Infant mortality rate is a proxy measure of population health. Previous studies on the infant mortality rate in Ethiopia did not consider measurement errors in the measured variables and had a one-directional effect; little emphasis was placed on testing multiple causal paths at the same time. We used structural equation modelling for a better understanding of the direct, indirect, and total effects among causal variables in a single model. A path analysis was part of an algorithm providing equations that were relating the variances and covariances of the indicators. From the results, the maternal mortality ratio (MMR) was significantly mediating the influence of out-of-pocket expenditure (OOP) on infant mortality rate (IMR), and the fertility rate (FR) was significantly mediating the influence of GDP to IMR (β = 1.168, p < 0.001). The GDP affects the IMR directly and indirectly while the OOP affects IMR indirectly. This study showed that there was a causal linkage between the World Bank Health and Population Variables for causing IMR in Ethiopia. The MMR and FR were found to be the intermediate indicators in this study. Through the indicators, FR had the highest standardised coefficients for increasing the IMR. We recommended that the existing interventions to reduce IMR be strengthened.

Infant Death Clustering in the Quarter of a Century in India: A Decomposition Analysis

The study aims to examine the clustering of infant deaths in India and the relative contribution of infant death clustering after accounting for the socio-economic and biodemographic factors that explain the decline in infant deaths. The study utilized 10 years of birth history data from three rounds of the National Family Health Survey (NFHS). The random effects dynamic probit model was used to decompose the decline in infant deaths into the contributions by the socio-economic and demographic factors, including the lagged independent variable, the previous infant death measuring the clustering of infant deaths in families. The study found that there has been a decline in the clustering of infant deaths among families during the past two and half decades. The simulation result shows that if the clustering of infant deaths in families in India was completely removed, there would be a decline of nearly 30 percent in the infant mortality rate (IMR). A decomposition analysis based on the dynamic probit model shows that for NFHS-1 and NFHS-3, in the total change of the probability of infant deaths, the rate of change for a given population composition contributed around 45 percent, and about 44 percent was explained by a compositional shift. Between NFHS-3 and NFHS-4, the rate of change for a given population composition contributed 86%, and the population composition for a given rate contributed 10% to the total change in the probability of infant deaths. Within this rate, the contribution of a previous infant was 0.8% and the mother's age was 10%; nearly 31% was contributed by the region of residence, 69% by the mother's education, and around 20% was contributed by the wealth index and around 8.7% by the sex of the child. The mother's unobserved factors contributed more than 50 percent to the variability of infant deaths in all the survey rounds and was also statistically significant (p < 0.01). Bivariate analysis suggests that women with two or more infant losses were much less likely to have full immunization (10%) than women with no infant loss (62%), although institutional delivery was high among both groups of women.

Does the augmentation of monetary and non-monetary factors prerequisite for the improvement of health outcomes? Evidence from the Indian states

The present study was conducted in Indian states to examine the effect of monetary and non-monetary factors on Infant Mortality Rate (IMR) and Life Expectancy at Birth (LEB) by using the panel regression model. In addition, an attempt was also made to analysis the unequal pattern of health infrastructure and services across states over time with the help of a composite index on health infrastructure and services. It was found that the index value of the best performing state Chhattisgarh is more than fourth six times that of the worst performing state. The study also showed that, despite the higher level of average per capita public health expenditure and moderately better health infrastructure, the COVID 19 induced death rate was high in Punjab, Sikkim, Delhi and Goa. The panel regression results revealed that, an average increase of 1% in the monetary factor, public health expenditure to Gross State Domestic Product ratio (PHEGSDPR), would decrease the average of IMR by about 10%. Moreover, the elasticity of IMR with respect to non-monetary factor, health infrastructure and services per 0.1 million population (HISPLP), was negative and significant. Likewise, the explanatory variables, HISPLP and PHEGSDPR have a positive and significant effect on the LEB.

Revisiting the Neuropathology of Sudden Infant Death Syndrome (SIDS)

Background: Sudden infant death syndrome (SIDS) is one of the leading causes of infant mortality in the United States (US). The extent to which SIDS manifests with an underlying neuropathological mechanism is highly controversial. SIDS correlates with markers of poor prenatal and postnatal care, generally rooted in the lack of access and quality of healthcare endemic to select racial and ethnic groups, and thus can be viewed in the context of health disparities. However, some evidence suggests that at least a subset of SIDS cases may result from a neuropathological mechanism. To explain these issues, a triple-risk hypothesis has been proposed, whereby an underlying biological abnormality in an infant facing an extrinsic risk during a critical developmental period SIDS is hypothesized to occur. Each SIDS decedent is thus thought to have a unique combination of these risk factors leading to their death. This article reviews the neuropathological literature of SIDS and uses machine learning tools to identify distinct subtypes of SIDS decedents based on epidemiological data.

Methods: We analyzed US Period Linked Birth/Infant Mortality Files from 1990 to 2017 (excluding 1992–1994). Using t-SNE, an unsupervised machine learning dimensionality reduction algorithm, we identified clusters of SIDS decedents. Following identification of these groups, we identified changes in the rates of SIDS at the state level and across three countries.

Results: Through t-SNE and distance based statistical analysis, we identified three groups of SIDS decedents, each with a unique peak age of death. Within the US, SIDS is geographically heterogeneous. Following this, we found low birth weight and normal birth weight SIDS rates have not been equally impacted by implementation of clinical guidelines. We show that across countries with different levels of cultural heterogeneity, reduction in SIDS rates has also been distinct between decedents with low vs. normal birth weight.

Conclusions: Different epidemiological and extrinsic risk factors exist based on the three unique SIDS groups we identified with t-SNE and distance based statistical measurements. Clinical guidelines have not equally impacted the groups, and normal birth weight infants comprise more of the cases of SIDS even though low birth weight infants have a higher SIDS rate.

Indirect estimation of child mortality using 2011 census data in the Islamic Republic of Iran

Background

Child mortality rates are considered to be one of the key indicators of child health.

Aims

The main objective of this research was to calculate child mortality rates (CMRs) indirectly, using census data, and to investigate using spatial pattern analysis the presence of any clustering patterns among provincial regions.

Methods

The Trussell version of the Brass method and Coale-Demeny West model were used to estimate CMRs and life expectancy (LE) at birth. The analyses were performed using the QFive program of MORTPAK 4 software. For cluster analysis, local and global Moran's I indexes were measured.

Results

Infant mortality rate, under-5 mortality rate, 1-4 mortality rate and LE at birth were estimated as 21.9, 26, 4.1 (deaths per 1000 live births) and 72.1 years, respectively. Global Moran's I index was calculated as 0.09, 0.09, 0.08 and 0.12, respectively.

Conclusion

Special attention must be paid in provinces with high clusters regarding the evaluation of public health programmes, and the cause of failure of these programmes in reduction of childhood mortality indices.

Infant mortality in Sudan: Health equity, territorial disparity and social determinants of health

Recognition of, and acting on, Social Determinants of Health is crucial for reducing health inequalities and territorial disparities and hence improving health of the whole population. Although Sudan was among the first countries which adopted a roadmap for Health in All Policies, health inequity remains an important challenge for health makers in this country. This paper illustrates the urgent need to reduce health inequalities in Sudan by acting on Social Determinants of Health. Descriptive statistics and Principal Components Analysis were used to get summarized multidimensional data information. Statistical significance of differences was tested by Pearson's chi-squared. A large territorial disparity was found between the 18 states. Infant mortality rate is more than three times higher in East Darfur (88.5) than in River Nile (28.1). Ratios of 1.9 and 1.6 were indicated for income and mother education respectively. A lower gap was seen for milieu (1.2) and gender (1.34). The difference was statistically significant for states (p-value <0.0001), income (p-value <0.001) and education (p-value <0.005). Urgent strategies are needed by acting sufficiently on social determinants of health like milieu, gender, education, income and territoriality in order to reduce avoidable heath inequalities and unacceptable territorial disparities in Sudan.

An assessment of infant mortality rates in Colombia, 1980-2009

PURPOSE

The infant mortality rate is a key indicator of human welfare and development. However, in Colombia, the Departamento Administrativo Nacional de Estadística has set the registered rate for 2009 as 13.69 per 1,000 live births, while the estimated rate is 20.13, suggesting the presence of inconsistencies in the data, as in many other transitional economies. Objective: To set the record straight on Colombia's Infant mortality rate reporting since 1980 by using all available data that have recently become public.

METHODS

. The study analyzes 8,636,510 records of live births (1998-2009) and 443,338 records of deaths (1979-2009), and considers information from all available sources: births and death registries, census data, Departamento Administrativo Nacional de Estadística, and Profamilia surveys. First, following a descriptive analysis, an exponential function is used to estimate the Infant mortality rates in Colombia for 1980-2009 while resolving internal inconsistencies in the data from all sources. The objective is to evaluate the infant mortality rate in Colombia, 1980-2009.

RESULTS

The analysis demonstrates that the registered and the estimated rates for 2009 are incompatible since they follow inconsistent long-term rates of decline in Infant mortality rate. While the registered rate underestimates the real situation, the estimated rate appears to grossly overestimate it. Analyses, based on other sources, put the Infant mortality rate between 15.81 and 17.58 in 2009, with rates of decline between 3.0 and 5.0 percent for the period 1980-2009.

CONCLUSIONS

The study concludes that during the period 1980-2009, the Infant mortality rate for Colombia on average fell from about 54 to about 17, suggesting a long-term annual rate of decline of about 4.0 percent.

Forecasting Indian infant mortality rate: An application of autoregressive integrated moving average model

BACKGROUND:

The Infant Mortality Rate (IMR) reflects the socioeconomic development of a nation. The IMR was reduced by 28% between 2015 and 2016 (National Family Health Survey-4 [NFHS-4]) as compared to 2005–2006 (NFHS-3), from 57/1000 to 41/1000 live births. The target fixed by the Government of India for IMR in 2019 is 28/1000 live births (National Health Policy, 2017). One of the most common methods of forecasting this is the autoregressive integrated moving average (ARIMA) model. A forecast of IMR can help implementation of interventions to reduce the burden of infant mortality within the target range.

MATERIALS AND METHODS:

The objective of the study was to give a detailed explanation of ARIMA model to forecast the IMR (2017–2025). Secondary data analysis and forecast were done for the available year and IMR data extracted from “open government data platform India” website.

RESULTS:

The forecast of the sample period (1971–2016) showed accuracy by the selected ARIMA (2, 1, 1) model. The postsample forecast with ARIMA (2, 1, 1) showed a decreasing trend of IMR (2017–2025). The forecast IMR for 2025 is 15/1000 live births.

CONCLUSION:

In the current study, long-time series IMR data were used to forecast the IMR for 9 years. The data showed that IMR would decline from 33/1000 live births in 2017 to 15/1000 live births in 2025. When the actual data for another year (2017) are available, the model can be checked for validity and a more accurate forecast can be performed.

From single-case analysis of neonatal deaths toward a further reduction of the neonatal mortality rate

Background The infant mortality rate (IMR), a key indicator of the quality of a healthcare system, has remained at approximately 3.5‰ for the past 10 years in Germany. Generic quality indicators (QIs), as used in Germany since 2010, greatly help in ensuring such a good value but do not seem to be able to further reduce the IMR. The neonatal mortality rate (NMR) contributes to 65-70% of the IMR. We therefore propose single-case analysis of neonatal deaths as an additional method and show an efficient way to implement this approach. Methods We used the Nordic-Baltic classification (NBC) to detect avoidable neonatal deaths. We applied this classification to a sample of 1968 neonatal death records, which represent over 90% of all neonatal deaths in East Berlin from 1973 to 1989. All cases were analyzed as to their preventability based on the complete perinatal and clinical data by a special commission of different experts. The NBC was automatically applied through natural language processing and an ontology-based terminology server. Results The NBC was used to select the group of cases that had a high potential of avoidance. The selected group represented 6.0% of all cases, and 60.4% of the cases within that group were judged avoidable or conditionally avoidable. The automatic detection of malformations showed an F1 score of 0.94. Conclusion The results show that our method can be applied automatically and is a powerful and highly specific tool for selecting potentially avoidable neonatal deaths and thus for supporting efficient single-case analysis.

An Overview of Infant Mortality Trends in Qatar from 2004 to 2014

Background Infant mortality is an important health indicator that estimates population well-being. Infant mortality has declined globally but is still a major public health challenge. This article provides the characteristics, causes, burden, and trends of infant mortality in Qatar. Methods Frequencies, percentages, and rates were calculated using data from birth-death registries over 2004-2014 to describe infant mortality by nationality, gender, and age group. We calculated the relative risks of the top causes of infant mortality among subgroups according to the 10^th Revision of the International Statistical Classification of Diseases and Related Health Problems (ICD-10, Version 2016). Results During 2004-2014, 204,224 live births and 1,505 infant deaths were recorded. The infant mortality rate (IMR) averaged 7.4/1000 live births (males 8.1, females 6.6, non-Qataris 7.7, and Qataris 6.8). IMR declined 20% from 2004 to 2014. The decline in IMR was significant for the overall population of infants (p=0.006), male infants (p=0.04), females (p=0.006), and for non-Qatari males (p=0.007) and non-Qatari females (p=0.007). The leading causes of infant mortality were congenital malformations (all types) (34.5%), low birth weight (LBW) (27%), and respiratory distress of newborns (2.8%). Male infants had a higher risk of mortality than female infants due to a congenital malformation of lungs (p=0.02), other congenital malformations, not elsewhere classified (p=0.01), and cardiovascular disorders (p=0.05). Conclusion The study shows that infant mortality among male infants is high due to the top infant mortality-related disorders, and male infants have a higher risk of mortality than female infants.

Geographic variation of reproductive health indicators and outcomes in the United States: place matters

The social determinants of health are the circumstances in which people are born, grow up, live, work, and age and the systems put in place to deal with illness. These circumstances, in turn, are shaped by a wider set of forces: economics, social policies, and politics. Reproductive health indicators and conditions that are germane to obstetricians and gynecologists vary across states and regions in the United States as well as within regions and states. The aim of this article is to illustrate this variation with the use of examples of gynecologic malignancies, sexually transmitted infections, teen birth rates, preterm birth rates, and infant mortality rates. Using the example of infant death, the difficulties in "unpacking" the construct of place will be discussed, and a special emphasis is placed on the interaction of race, place, and disparities in shaping perinatal outcomes. Finally, readily available and easy-to-use online data resources will be provided so that obstetricians and gynecologists will be able to assess geographic variation in health indicators and outcomes in their own localities.

Public health consequences of terrorism on maternal-child health in New York City and Madrid

Past research provides evidence for trajectories of health and wellness among individuals following disasters that follow specific pathways of resilience, resistance, recovery, or continued dysfunction. These individual responses are influenced by event type and pre-event capacities. This study was designed to utilize the trajectories of health model to determine if it translates to population health. We identified terrorist attacks that could potentially impact population health rather than only selected individuals within the areas of the attacks. We chose to examine a time series of population birth outcomes before and after the terrorist events of the New York City (NYC) World Trade Center (WTC) attacks of 2001 and the Madrid, Spain train bombings of 2004 to determine if the events affected maternal-child health of those cities and, if so, for how long. For percentages of low birth weight (LBW) and preterm births, we found no significant effects from the WTC attacks in NYC and transient but significant effects on rates of LBW and preterm births following the bombings in Madrid. We did find a significant positive and sustained effect on infant mortality rate in NYC following the WTC attacks but no similar effect in Madrid. There were no effects on any of the indicator variables in the comparison regions of New York state and the remainder of Spain. Thus, population maternal-health in New York and Madrid showed unique adverse effects after the terrorist attacks in those cities. Short-term effects on LBW and preterm birth rates in Madrid and long-term effects on infant mortality rates in NYC were found when quarterly data were analyzed from 1990 through 2008/2009. These findings raise questions about chronic changes in the population's quality of life following catastrophic terrorist attacks. Public health should be monitored and interventions designed to address chronic stress, environmental, and socioeconomic threats beyond the acute aftermath of events.

Health trends in Sub-Saharan Africa: conflicting evidence from infant mortality rates and adult heights

We investigate trends in cohort infant mortality rates and adult heights in 39 developing countries since 1961. In most regions of the world improved nutrition, and reduced childhood exposure to disease, have lead to improvements in both infant mortality and adult stature. In Sub-Saharan Africa, however, despite declining infant mortality rates, adult heights have not increased. We argue that in Sub-Saharan Africa the decline in infant mortality may have been due to interventions that prevent infant deaths rather than improved nutrition and childhood morbidity. Despite declining infant mortality, Sub-Saharan Africa may not be experiencing increases in health human capital.