A greater nurse and midwife density protects against infant mortality globally.

PURPOSE: As the largest profession within the health care workforce, nurses and midwives play a critical role in the health and wellness of families especially children and infants. This study suggests those countries with higher nurse and midwife densities (NMD) had lower infant mortality rates (IMR). DESIGN AND METHODS: With affluence, low birthweight and urbanization incorporated as potential confounders, this ecological study analyzed the correlations between NMD and IMR with scatterplots, Pearson r correlation, partial correlation and multiple linear regression models. Countries were also grouped for analysing and comparing their Pearson's coefficients. RESULTS: NMD inversely and significantly correlated to IMR worldwide. This relationship remained significant independent of the confounders, economic affluence, low birthweight and urbanization. Explaining 57.19% of IMR variance, high NMD was implicated in significantly reducing the IMR. PRACTICE IMPLICATIONS: Countries with high NMD had lower IMRs both worldwide and with special regard to developing countries. This may interest healthcare policymakers, especially those from developing countries, to consider the impacts of global nursing and midwifery staffing shortages. Nurses and midwives are the group of healthcare professionals who spend most with infants and their carers. This may be another alert for the health authorities to extend nurses and midwives' practice scope for promoting infant health.

An Application of Social Vulnerability Index to Infant Mortality Rates in Ohio Using Geospatial Analysis- A Cross-Sectional Study.

BACKGROUND: Ohio ranks 43rd in the nation in infant mortality rates (IMR); with IMR among non-Hispanic black infants is three times higher than white infants. OBJECTIVE: To identify the social factors determining the vulnerability of Ohio counties to IMR and visualize the spatial association between relative social vulnerability and IMR at county and census tract levels. METHODS: The social vulnerability index (SVICDC) is a measure of the relative social vulnerability of a geographic unit. Five out of 15 social variables in the SVICDC were utilized to create a customized index for IMR (SVIIMR) in Ohio. The bivariate descriptive maps and spatial lag model were applied to visualize the quantitative relationship between SVIIMR and IMR, accounting for the spatial autocorrelation in the data. RESULTS: Southeastern counties in Ohio displayed highest IMRs and highest overall SVIIMR; specifically, highest vulnerability to poverty, no high school diploma, and mobile housing. In contrast, extreme northwestern counties exhibited high IMRs but lower overall SVIIMR. Spatial regression showed five clusters where vulnerability to low per capita income in one county significantly impacted IMR (p = 0.001) in the neighboring counties within each cluster. At the census tract-level within Lucas county, the Toledo city area (compared to the remaining county) had higher overlap between high IMR and SVIIMR. CONCLUSION: The application of SVI using geospatial techniques could identify priority areas, where social factors are increasing the vulnerability to infant mortality rates, for potential interventions that could reduce disparities through strategic and equitable policies.

STILLBIRTH RATE AND INFANT MORTALITY RATE: STUDY IN THE REGIONS OF UKRAINE MOST INTENSIVELY RADIOCONTAMINATED UPON THE CHORNOBYL NPP ACCIDENT. / МЕРТВОНАРОДЖУВАНІСТЬ ТА МАЛЮКОВА СМЕРТНОСТЬ: ДОСЛІДЖЕННЯ РАЙОНІВ УКРАЇНИ НАЙБІЛЬШ РАДІОАКТИВНО ЗАБРУДНЕНИХ ВНАСЛІДОК АВАРІЇ НА ЧОРНОБИЛЬСЬКІЙ АЕС.

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.

What is the role of institutional quality in health outcomes? A panel data analysis on 158 countries from 2001-2020.

Our study investigated the impact of institutional quality on health system outcomes, utilizing worldwide governance indicators and analyzing data from 158 countries between 2001 and 2020. We employed Principal Component Analysis (PCA) to create a composite index of institutional quality and conducted various tests to select the appropriate econometric model. The role of institutional quality, along with other variables, in health outcomes was estimated using fixed effects and generalized method of moments (GMM) models. High-income and low-income countries were analyzed separately. The results of our study revealed that institutional quality, as measured by Control of Corruption, Voice and Accountability, Political Stability, Rule of Law, Regulatory Quality, and Government Effectiveness, had a negative impact on infant mortality rates and a positive impact on life expectancy. Similarly, variables such as GDP, mean years of schooling, total health expenditure, and urbanization rate showed a negative association with infant mortality rates and a positive association with life expectancy. Conversely, the logarithm of CO2 emissions exhibited a positive effect on infant mortality rates and a negative effect on life expectancy. These findings highlight the crucial role of institutional quality in determining health outcomes. Improving institutional quality contributes to the development of democratic and meritocratic systems, infrastructure enhancement, efficient tax and subsidy systems, optimal budget allocation, improved public education, and enhanced access to primary healthcare services. The influence of institutional quality is particularly significant in high-income countries compared to low-income countries. In conclusion, our study emphasizes the importance of institutional quality in shaping health system outcomes. Enhancing institutional quality is essential for the overall advancement of healthcare systems, encompassing governance, infrastructure, education, and access to healthcare services. It is crucial to prioritize efforts to improve institutional quality, especially in high-income countries, to achieve better health outcomes for populations worldwide.

The Relationship between Air Pollution and Infant Mortality Rate.

Background: We aimed to investigate the relationship between air pollution and the Infant mortality rate (IMR) during nearly ten years in Tehran, Iran. Methods: This study is a retrospective cohort case using time series analysis. Air pollution monitoring data during the study period (2009-2018) were collected from the information of 23 Air Quality Control Centers in different areas of Tehran. For this purpose, the daily measures of PM10, PM2.5, O3, CO, SO2, NO2 were obtained. Data on infant mortality was obtained from the National Statistics Office of Iran and mortality registered in Tehran's main cemetery during the study period. Distributed lag linear and non-linear models were used. Results: A total of 23,206 infant deaths were reported during the study period. Following an increase of 10 ug/m3 in PM10 in an early day of exposure, the risk of mortality increased significantly (RR=1.003, 95%CI:1.001-1.005). There is a pick on lag 5-10 that shows a very strong and immediate effect of cold temperature which means that cold temperatures increase the risk of mortality at an early time. At cold temperate, (var=0 and lag 0) risk of infant mortality was significantly higher than reference temperature (19°C) (RR=1.1295, %CI: 1.01-1.25). Conclusion: The results show the adverse effects of PM10 exposure on infant mortality in Tehran, Iran. Accordingly, a steady decline in PM10 levels in Tehran may have greater benefits in reducing the Infant mortality rate.

Neonatal, Infant, and Under Age Five Vaccine Doses Routinely Given in Developed Nations and Their Association With Mortality Rates.

Introduction In 2011, using 2009 data, we published a study demonstrating that among the most highly developed nations, those requiring the most vaccine doses for their infants tended to have the least favorable infant mortality rates (r = 0.70, p < .0001). Twelve years later, we replicated our original study using 2019 data. Linear regression analysis corroborated the positive trend reported in our initial paper (r = 0.45; p < .002). Herein, we broaden our analyses to consider the effect of vaccines on neonatal and under age five mortality rates.  Objective We performed several investigations to explore potential relationships between the number of early childhood vaccine doses required by nations and their neonatal, infant, and under age five mortality rates. Methods In this ecological study, we conducted linear regression analyses of neonatal, infant, and under age five vaccine doses required by nations and their neonatal, infant, and under age five mortality rates. All analyses were based on 2019 and 2021 data. We also stratified nations by the number of neonatal vaccine doses required and conducted a one-way ANOVA test and a post hoc Tukey-Kramer test to determine if there were statistically significant differences in the group mean neonatal, infant, and under age five mortality rates of nations that administered zero, one, or two neonatal vaccine doses. Results Linear regression analyses of neonatal vaccine doses required by nations in our 2021 dataset yielded statistically significant positive correlations to rates of neonatal mortality (r = 0.34, p = .017), infant mortality (r = 0.46, p = .0008), and under age five mortality (r = 0.48, p = .0004). Similar results were reported using 2019 data. Utilizing 2021 data, a post hoc Tukey-Kramer test indicated a statistically significant pairwise difference between the mean neonatal mortality rates, mean infant mortality rates, and mean under age five mortality rates of nations requiring zero vs. two neonatal vaccine doses. There was a statistically significant difference of 1.28 deaths per 1000 live births (p < .002) between the mean infant mortality rates among nations that did not give their neonates any vaccine doses and those that required two vaccine doses. Using 2019 and 2021 data, 17 of 18 analyses (12 bivariate linear regressions and six ANOVA and Tukey-Kramer tests) achieved statistical significance and corroborated the findings reported in our original study of a positive association between the number of vaccine doses required by developed nations and their infant mortality rates. Conclusions There are statistically significant positive correlations between mortality rates of developed nations and the number of early childhood vaccine doses that are routinely given. Further investigations of the hypotheses generated by this study are recommended to confirm that current vaccination schedules are achieving their intended objectives.

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 (ß = -0.617, p < 0.001). SD directly and positively affects IMR (ß = 0.447, p < 0.001). ME only indirectly affects IMR (ß = -0.854, p < 0.001). ME determinants also exert some direct influences on both HSR (ß = 0.722, p < 0.001) and SD (ß = -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 (ß = 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.

Contextual, maternal, and infant factors in preventable infant deaths: a statewide ecological and cross-sectional study in Rio Grande do SUL, Brazil.

BACKGROUND: Ending preventable deaths of newborns and children under five by 2030 is among the United Nations Sustainable Development Goals. This study aimed to describe infant mortality rate due to preventable causes in Rio Grande do Sul (RS), the Southernmost state in Brazil. With 11,329,605 inhabitants and 141,568 live births in 2017, RS was the fifth most populous state in the country. METHOD: An ecological and cross-sectional statewide study, with data extracted from records of the Mortality Information System, Death Certificates, and Live Birth Certificates for the year 2017. Preventability was estimated by applying the List of Causes of Deaths Preventable through Intervention of SUS (acronym for Sistema Unico de Saude - Brazilian Unified Health System) Intervention. Rates of preventable infant mortality (PIMR), preventable early neonatal mortality (PENMR), preventable late neonatal mortality (PLNMR), and preventable post-neonatal mortality (PPNMR) per 1000 live births (LB) were quantified. Incidence ratios, according to contextual characteristics (human development index of the health region and of the municipality; Gini index of the municipality), maternal characteristics at the time of delivery (age, education, self-reported skin color, presence of a partner, number of antenatal care consultations, and type of delivery), and characteristics of the child at the time of birth (gestational age, weight, and pregnancy type) were calculated. RESULTS: In 2017, there were 141,568 live births and 1425 deaths of infants younger than 1 year old, of which 1119 were preventable (PIMR = 7.9:1000 LB). The PENMR, PLNMR, and PPNMR were 4.1:1000 LB; 1.5:1000 LB; and 2.3:1000 LB, respectively. More than 60% of deaths in the first week and 57.5% in the late neonatal period could be reduced through adequate care of the woman during pregnancy. The most frequent preventable neonatal causes were related to prematurity, mainly acute respiratory syndrome, and non-specified bacterial septicemia. In the post-neonatal period, 31.8% of deaths could be prevented through adequate diagnostic and treatment. CONCLUSIONS: The strategies needed to reduce preventable infant deaths should preferably focus on preventing prematurity, through adequate care of the woman during pregnancy.

Analyzing the impact of access to electricity and biomass energy consumption on infant mortality rate: a global perspective.

Conserving the lives of newborns has been a long-standing issue around the world, where 2.4 million babies die in the first month of the life. The literature indicates that the important challenges of social development goals around the globe include affordable and easy access to electricity, promotion of sustainable economic development, and provision of better social services and creation of job opportunities which help in reducing infant mortality rate. This calls for the need to probe into this matter minutely and brings up the ways for reducing the infant mortality rate. The present study is an attempt to analyze the impact of rural and urban electrification and biomass energy consumption on infant mortality rate for the period 1990-2020 using the Panel Quantile Regression (PQR) approach. The results of the study show that in both developed and developing countries, biomass energy consumption has positive impact on infant mortality rate, while rural and urban electrification has proposed the inverted U-shaped relationship with infant mortality in different quantile groups. It is also concluded that few developing countries are failed to achieve the maturity of the inverted U-shaped curve while all developed countries have achieved at the maturity stage. This study recommended that for reducing the infant mortality rate, the world should discourage the use of biomass energy and promote the affordable and easy access to electricity on priority basis.

Estudo da mortalidade infantil nos estados brasileiros utilizando aplicação de dados em painel / Study of child mortality in brazilian states using panel data application / Estudio de mortalidad infantil en estados brasileños mediante aplicación de datos de panel

Este trabalho tem como objetivo determinar uma relação linear entre a Taxa de Mortalidade Infantil (TMI) e um conjunto de variáveis socioeconômicas observadas por unidades federativas no período de 2005 à 2010 utilizando o modelo de dados em painel de efeitos fixo e aleatório. Metodologia: trata-se de um estudo descritivo com abordagem quantitativa, com utilização dos Sistema de Informação sobre Mortalidade (SIM) e o Sistema de Informações sobre Nascidos Vivos (SINASC) e em seguida utilizou-se o software R para realizar esta análise de dados com a função plm. Resultados: os estudos mostram que o modelo mais adequado é o de efeito fixo com transformação logarítmica nas variáveis independentes e na variável dependente que foram as seguintes: TMI, taxa de analfabetismo, PIB per capita, proporção pessoas com baixa renda, percentual da população servida por rede de abastecimento de água e a proporção da população servida por coleta de lixo. Conclusão: As variáveis independentes que causam impacto significativo na TMI são taxa de analfabetismo, PIB per capita e proporção de pessoas com baixa renda.

This work aims to determine a linear relationship between the Infant Mortality Rate (IMR) and a set of socioeconomic variables observed by federative units in the period from 2005 to 2010 using the fixed and random effects panel data model. Methodology: this is a descriptive study with a quantitative approach, using the Mortality Information System (SIM) and the Live Birth Information System (SINASC) and then using the R software to perform this data analysis with the plm function. Results: studies show that the most appropriate model is the fixed effect model with logarithmic transformation in the independent variables and the dependent variable, which were as follows: IMR, illiteracy rate, GDP per capita, proportion of people with low income, percentage of the population served by water supply network and the proportion of the population served by garbage collection. Conclusion: The independent variables that have a significant impact on IMR are the illiteracy rate, GDP per capita and the proportion of people with low income.

Este trabajo tiene como objetivo determinar una relación lineal entre la Tasa de Mortalidad Infantil (TMI) y un conjunto de variables socioeconómicas observadas por las unidades federativas en el período 2005 a 2010 utilizando el modelo de datos de panel de efectos fijos y aleatorios. Metodología: se trata de un estudio descriptivo con enfoque cuantitativo, utilizando el Sistema de Información de Mortalidad (SIM) y el Sistema de Información de Nacidos Vivos (SINASC) y luego utilizando el software R para realizar este análisis de datos con la función plm. Resultados: los estudios muestran que el modelo más adecuado es el modelo de efectos fijos con transformación logarítmica en las variables independientes y la variable dependiente, las cuales fueron las siguientes: TMI, tasa de analfabetismo, PIB per cápita, proporción de personas con bajos ingresos, porcentaje de la población atendida por red de suministro de agua y la proporción de la población atendida por recolección de basura. Conclusión: Las variables independientes que tienen un impacto significativo en la TMI son la tasa de analfabetismo, el PIB per cápita y la proporción de personas con bajos ingresos.

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.

A Review on Umbilical Cord Milking and Its Implications in Neonatal Health.

In India, there is an extreme lack of advancement in techniques concerning the care of infants during labor and post-pregnancy, i.e., the postnatal period. India projected an Infant Mortality Rate of 28.771 deaths per 1000 live births for the year 2021. Such a high death rate in infants arises a dire need to discover and launch new techniques and increase the application of the existing lesser-known techniques. One less well-known technique is the milking of the infant's umbilical cord. Transfusion of placental blood has recently been considered definitive in the care of newborns with the boon to the infant of declined death rate in preterm neonates and the enhanced consequences of growth in term infants. The chief goal of this descriptive review article is to examine all the studies relating to umbilical cord milking (UCM) in late-preterm and term infants and to evaluate every achievable outcome and restriction of a given process in clinical application, mainly when compared to rapid and late umbilical cord clamping. Application of milking of the umbilical cord can be seen to improve the health of hypoxic neonates, weight parameters, blood volume, hematocrit, hemoglobin, iron levels in the blood, red blood cell count, blood pressure, right ventricular output, left ventricular functions, cerebral oxygenation, urine output regulation, cognitive abilities, antioxidant levels, better outcomes in the resuscitation of infant and above all helps in lowering Infant Mortality Rates.

The spatio-temporal dynamics of infant mortality in Ecuador from 2010 to 2019.

The infant mortality rate (IMR) is still a key indicator in a middle-income country such as Ecuador where a slightly increase up to 11.75 deaths per thousand life births has been observed in 2019. The purpose of this study is to propose and apply a prioritization method that combines clusters detection (Local Indicators of Spatial Association, LISA) and a monotonic statistic depicting time trend over 10 years (Mann-Kendall) at municipal level. Annual national databases (2010 to 2019) of live births and general deaths are downloaded from National Institute of Statistics and Censuses (INEC). The results allow identifying a slight increase in the IMR at the national level from 9.85‰ in 2014 to 11.75‰ in 2019, neonatal mortality accounted for 60% of the IMR in the last year. The LISA analysis allowed observing that the high-high clusters are mainly concentrated in the central highlands. At the local level, Piñas, Cuenca, Ibarra and Babahoyo registered the highest growth trends (0.7,1). The combination of techniques made it possible to identify eight priority counties, half of them pertaining to the highlands region, two to the coastal region and two to the Amazon region. To keep infant mortality at a low level is necessary to prioritize critical areas where public allocation of funds should be concentrated and formulation of policies.

Infant mortality and risk factors in Nigeria in 2013-2017: A population-level study.

Background: Globally, over the past two decades, many countries have significantly reduced the rate of infant mortality. Yet, in Africa, Nigeria remains one of the countries with the highest infant mortality rate (IMR). Methods: We conducted a population-level study using the 2018 Nigeria Demographic Health Survey (NDHS). A total of 41,668 household data were analyzed retrospectively. The association between each exposure and infant mortality was analyzed in logistic regression models (independently adjusted by demographic and socioeconomic status variables) and confirmed by the multiple comparisons analysis. Findings: The overall IMR of 2013-2017 was 61.5 (95% CI 58.0, 65.3) per 1000 live births. In general, the North-West and North-East regions had the highest IMR, whereas the South-West, South-East and South-South regions had the lowest IMR. The regression analysis found women who delivered their babies at the age <=18 years old (odds ratio (OR): 1.37 [1.17, 1.62]), had religion of Islam (OR: 1.35 [1.10, 1.65]), no ANC visit (OR: 1.69 [1.21, 2.35]), >4 ANC visits (OR: 1.70 [1.23, 2.34]), ANC not at home or skilled provider (0.40 [0.35, 0.46]) and the babies as the first child (OR: 1.23 [1.07, 1.42]) to be associated with higher IMR. Interpretation: Our findings imply that Nigeria is not on track to achieving the SDG target of reducing child mortality by 2030. Sustainable interventions are urgently needed to address the challenges for women of reproductive age, particularly those that are living in the rural areas and Northern regions, having limited/no access to health care/skilled providers, and delivered their first child. Funding: None.

Socio-economic factors affecting high infant and child mortality rates in selected African countries: does globalisation play any role?

BACKGROUND: Despite the declining trends worldwide, infant and child mortality rates are still high in many African countries. These high rates are problematic; therefore, this study attempts to explore the contributing factors that cause high infant and child mortality rates in 14 African countries using panel data for the period of 2000-2018. In particular, the role globalisation is explored. METHODS: The panel corrected standard error (PCSE), the Feasible generalized least square (FGLS) models, and the pair-wise Granger causality test have been applied as methodological approaches. RESULTS: The public health expenditure, numbers of physicians, globalization, economic development, education, good governance, and HIV prevalence rate have been revealed as the determinants of infant and child mortality in these countries. All these variables except the HIV prevalence rate negatively affect the infant and child mortality rates, while the HIV prevalence rate is found to be positive. Bidirectional and unidirectional causal relationships between the variables are also attained. CONCLUSIONS: Effective socio-economic policy priority with due consideration of globalization should be emphasized to reduce infant and child mortality rates in these countries.

Geographical disparities in infant mortality in the rural areas of China: a descriptive study, 2010-2018.

BACKGROUND: The infant mortality rate (IMR) is considered a basic measure of public health for countries around the world. The specific aim of our study was to provide an updated description of infant mortality rate among different regions in rural China, and assess the trends and causes of the IMR geographical disparities. METHODS: Data were collected from China's Under-5 Child Mortality Surveillance System(U5CMSS). The annual number of deaths and causes of death were adjusted using a 3-year moving average underreporting rate based on annual national data quality control results. The average annual decline rate (AADR) and the relative risk (RR) of the IMR and cause-specific infant mortality were calculated by Poisson regression and the Cochran-Mantel-Haenszel method. Data analysis was completed by SAS software. RESULTS: There was an apparent decrease in infant mortality in rural China from 2010 to 2018, at the AADR of 11.0% (95%CI 9.6-12.4), 11.2% (95%CI 10.3-12.1) and 6.6% (95%CI 6.0-7.3) in the eastern, central and western rural areas, respectively. The IMR was highest in the western rural area, followed by the central and eastern rural areas. Compared with the eastern rural area, the RR of infant mortality in the central rural area remained at 1.4-1.6 and increased from 2.4 (95%CI 2.3-2.6) in 2010-2012 to 3.1 (95% CI 2.9-3.4) in 2016-2018 in the western rural area. Pneumonia, preterm birth /LBW and birth asphyxia were the leading causes of infant deaths in the western rural area. Mortality rates of these three causes fell significantly in 2010-2018 but contributed to a higher proportion of deaths in the western rural area than in the central and western rural ares. CONCLUSIONS: Our study indicated that the infant mortality rate dropped significantly from 2010 to 2018, however, geographical disparities of IMR in rural China are still persist. Therefore, there is an urgent need for public health programmes and policy interventions for infants in western rural China.

Perinatal Risks of Neonatal and Infant Mortalities in a Sub-provincial Region of China: A Livebirth Population-based Cohort Study.

BACKGROUND: Current vital statistics of birth population and neonatal outcome in China lacked information and definition of deaths at delivery and during hospitalization, especially for extreme preterm (EPT) birth. This study aims to delineate the prevalence of neonatal hospitalization, neonatal and infant mortality rates (NMR, IMR) and associated perinatal risks based on all livebirths in Huai'an, an evolving sub-provincial region in eastern China. METHODS: This retrospective cohort study established a comprehensive database linking information of whole regional livebirths and neonatal hospitalization in 2015, including deaths at delivery and EPT livebirths. The primary outcomes were NMR and IMR stratified by gestational age (GA) and birthweight (BW) with 95% confidence intervals. Causes of the neonatal and infant deaths were categorized according to the International Statistical Classification of Diseases 10th version, and population attributable fractions of GA and BW strata were analyzed. Perinatal risks of infant mortalities in continuum periods were estimated by Cox regression models. RESULTS: Among the whole livebirth population (59056), 7960 were hospitalized (prevalence 13.5%), with 168 (2.8‰) in-hospital deaths. The NMR was 3.6 (3.2, 4.1)‰ and IMR 4.9 (1.4, 4.5)‰, with additionally 35 (0.6‰) deaths at delivery. The major causes of infant deaths were perinatal conditions (2.6‰, mainly preterm-related), congenital anomalies (1.5‰), sudden unexpected death in infancy (0.6‰) and other causes (0.2‰). The deaths caused by preterm and low BW (LBW) accounted for 50% and 40% of NMR and IMR, with 20-30% contributed by EPT or extremely LBW, respectively. Multivariable Cox regression analysis revealed that peripartum factors and LBW strata had strong association with early- and late-neonatal deaths, whereas those of GA < 28 weeks were highly associated with postneonatal deaths. Congenital anomalies and neonatal hospitalization remained high death risks over the entire infancy, whereas maternal co-morbidities/complications were modestly associated with neonatal but not postneonatal infant mortality. CONCLUSIONS: The NMR, IMR, major causes of deaths and associated perinatal risks in continuum periods of infancy, denote the status and quality improvement of the regional perinatal-neonatal care associated with socioeconomic development. The study concept, applicability and representativeness may be validated in other evolving regions or countries for genuine comparison and better maternal-infant healthcare.

Carbon dioxide emission and health outcomes: is there really a nexus for the Nigerian case?

Health outcomes in sub-Saharan Africa are characteristically poor and Nigeria is no exception. Despite the recorded decline in infant and under five mortality rates in Nigeria, they still remain relatively high showing a poor status of the population's health. Carbon dioxide emission continues to fluctuate at high levels probably due to the increasing use of non renewable energy forms for economic activities mostly requiring energy consumption. This study examines the health consequences of environmental quality due to carbon dioxide emission in Nigeria for the period 1980 to 2016. Using two health outcome measures and decomposing carbon dioxide emission by sector and type of fuel consumed, a bound cointegration approach and an autoregressive distributed lag model were also employed. The results and a sensitivity analysis revealed that aggregate carbon dioxide emission significantly explained both infant mortality and under five mortality rates. However, when disaggregated, carbon dioxide emission from solid fuel had the greatest contribution to poor health outcomes.

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.