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Objective: To use publicly available secondary data to assess the impact of Brazil’s Family Health Program on state level infant mortality rates (IMR) during the 1990s. Design: Longitudinal ecological analysis using panel data from secondary sources. Analyses controlled for state level measures of access to clean water and sanitation, average income, women’s literacy and fertility, physicians and nurses per 10 000 population, and hospital beds per 1000 population. Additional analyses controlled for immunisation coverage and tested interactions between Family Health Program and proportionate mortality from diarrhoea and acute respiratory infections. Setting: 13 years (1990–2002) of data from 27 Brazilian states. Main results: From 1990 to 2002 IMR declined from 49.7 to 28.9 per 1000 live births. During the same period average Family Health Program coverage increased from 0% to 36%. A 10% increase in Family Health Program coverage was associated with a 4.5% decrease in IMR, controlling for all other health determinants (p<0.01). Access to clean water and hospital beds per 1000 were negatively associated with IMR, while female illiteracy, fertility rates, and mean income were positively associated with IMR. Examination of interactions between Family Health Program coverage and diarrhoea deaths suggests the programme may reduce IMR at least partly through reductions in diarrhoea deaths. Interactions with deaths from acute respiratory infections were ambiguous. Conclusions: The Family Health Program is associated with reduced IMR, suggesting it is an important, although not unique, contributor to declining infant mortality in Brazil. Existing secondary datasets provide an important tool for evaluation of the effectiveness of health services in Brazil.

Background: The infant mortality rate (IMR) has been criticised as a measure of population health because it is narrowly based and likely to focus the attention of health policy on a small part of the population to the exclusion of the rest. More comprehensive measures such as disability adjusted life expectancy (DALE) have come into favour as alternatives. These more comprehensive measures of population health, however, are more complex, and for resource poor countries, this added burden could mean diverting funds from much needed programmes. Unfortunately, the conjecture, that DALE is a better measure of population health than IMR, has not been empirically tested. Methods: IMR and DALE data for 1997 were obtained from the World Bank and the World Health Organisation, respectively, for 180 countries. Findings: There is a strong (generally) linear association between DALE and IMR (r=0.91). Countries with low DALE tend to have a high IMR. The countries with the lowest IMRs had DALEs above that predicted by the regression line. Interpretation: There is little evidence that the use of IMR as a measure of population health has a negative impact on older groups in the population. IMR remains an important indicator of health for whole populations, reflecting the intuition that structural factors affecting the health of entire populations have an impact on the mortality rate of infants. For countries with limited resources that require an easily calculated, pithy measure of population health, IMR may remain a suitable choice.

The Fetal–Infant mortality rate (FIMR) is the basic surveillance statistic in perinatal periods of risk (PPOR) analyses. This paper presents a model for the FIMR as the ratio of two Poisson random variables. From this model, expressions for estimators of variance, standard error, and relative standard error are developed. The coverage properties of interval estimators for the FIMR are investigated in a simulation study for both small and large populations and FIMR rates. Results from these studies are applied to a PPOR analysis of NC vital records. Results suggest that the sample size guidance provided in the literature to ensure statistical reliability is overly conservative and interval construction methodology should be selected based on population size.

This communication examines nutritional status and its impact on infant mortality rate (IMR) in Saiha district, Mizoram, India. 1650 mothers from 17 villages were surveyed using random sampling method. The district has very high IMR (219.6), significantly higher than Mizoram (35). Meanwhile, per day per capita calorie intake is 1703, which is less than the recommended dietary intake (2400 kcal). All food items which people consume daily were collected and nutritional status was assessed. Our result shows that high IMR in the district is due to food insecurity and malnutrition.

The long-term trends in maternal and child health (MCH) in China and the national-level factors that may be associated with these changes have been poorly explored. This study aimed to assess trends in MCH indicators nationally and separately in urban and rural areas and the impact of public policies over a 30‒year period. An ecological study was conducted using data on neonatal mortality rate (NMR), infant mortality rate (IMR), under-five mortality rate (U5MR), and maternal mortality ratio (MMR) nationally and separately in urban and rural areas in China from 1991 to 2020. Joinpoint regression models were used to estimate the annual percentage changes (APC), average annual percentage changes (AAPC) with 95% confidence intervals (CIs), and mortality differences between urban and rural areas. From 1991 to 2020, maternal and child mortalities in China gradually declined (national AAPC [95% CI]: NMRs − 7.7% [− 8.6%, − 6.8%], IMRs − 7.5% [− 8.4%, − 6.6%], U5MRs − 7.5% [− 8.5%, − 6.5%], MMRs − 5.0% [− 5.7%, − 4.4%]). However, the rate of decline nationally in child mortality slowed after 2005, and in maternal mortality after 2013. For all indicators, the decline in mortality was greater in rural areas than in urban areas. The AAPCs in rate differences between rural and urban areas were − 8.5% for NMRs, − 8.6% for IMRs, − 7.7% for U5MRs, and − 9.6% for MMRs. The AAPCs in rate ratios (rural vs. urban) were − 1.2 for NMRs, − 2.1 for IMRs, − 1.7 for U5MRs, and − 1.9 for MMRs. After 2010, urban‒rural disparity in MMR did not diminish and in NMR, IMR, and U5MR, it gradually narrowed but persisted. MCH indicators have declined at the national level as well as separately in urban and rural areas but may have reached a plateau. Urban‒rural disparities in MCH indicators have narrowed but still exist. Regular analyses of temporal trends in MCH are necessary to assess the effectiveness of measures for timely adjustments.

Researchers and policymakers often rely on the infant mortality rate as an indicator of a country's health. Despite arguments about its relevance, uniform measurement of infant mortality is necessary to guarantee its use as a valid measure of population health. Using important socioeconomic indicators, we develop a novel method to adjust country-specific reported infant mortality figures. We conclude that an augmented measure of mortality that includes both infant and late fetal deaths should be considered when assessing levels of social welfare in a country. In addition, mortality statistics that exhibit a substantially high ratio of late fetal to early neonatal deaths should be more closely scrutinized.

This paper investigates the effect of the socioeconomic development on life expectancy at birth as an indicator of mortality or longevity in five EU accession candidate countries (Macedonia, Serbia, Bosnia and Herzegovina, Montenegro, and Albania). Using aggregate time series pool data on an annual level from UN and World Bank databases for the period 1990–2017 and Full Information Maximum Likelihood model, it was found that this connection between the socioeconomic conditions and life expectancy at birth is a prerequisite for longer life in all these five countries. Our dependent variable was the life expectancy at birth, and the background exploratory variables for the socioeconomic development were GDP per capita and infant mortality rate. The main results are that higher values of GDP per capita and lower values of infant mortality levels lead to higher life expectancy at birth suggesting that longevity of people in these five countries is increasing. These results are supported by our theoretical background and research framework hypotheses.

Background Infant mortality is an important predictor of a government’s commitment to its people. Global infant deaths have declined since past decades but at a pace that leaves much to be desired. India’s declining pattern of trends is encouraging but the low performance of individual states like Madhya Pradesh (MP) indicates an urgent need for policy revision and implementation. Methods This paper forecasts the Infant mortality rate (IMR) of India and MP by the year 2030 through autoregressive integrated moving average (ARIMA) model after obtaining stationarity by differencing the series of IMR once. The Akaike’s information criterion and Bayesian information criterion have been used for the selection of best ARIMA model amongst other existing choices. The model diagnostics through Ljung and Box test shows absence of autocorrelation in the residuals ( p  > 0.05). Results The findings through ARIMA(3, 1, 0) foretell a declining IMR from 27 to 20 per thousand live births (from 2021 to 2030) in India. Similarly, MP is expected to experience reduction in infant deaths from 44 to 39 per thousand live births (from 2021 to 2030). The deployed model is well fitted as mean absolute percentage error lies below 5%. During 2010–20, India and MP witnessed a decadal reduction of 40% and 31% in IMR, respectively. From the year 2010 onwards, India experienced the highest annual reduction of 8.1% in IMR during 2015–16. Similarly, MP encountered a decrease of 6.5% in IMR recently (2019–20), which is the highest declining annual IMR in the state during past ten years. Conclusions The projected figures on IMR are satisfactory for policy makers at national level, but MP is still miles away to achieve acceptable IMR as compared to the country’s IMR. The state requires more attention and focus on exploring reasons and identifying underlying factors responsible for higher IMR across its demographic structure including socio-economic characteristics.

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.

Air pollution poses a persuasive threat to global health, demonstrating widespread detrimental effects on populations worldwide. Exposure to pollutants, notably particulate matter with a diameter of 2.5 µm (PM 2.5 ), has been unequivocally linked to a spectrum of adverse health outcomes. A nuanced understanding of the relationship between them is crucial for implementing effective policies. This study employs a comprehensive investigation, utilizing the extended health production function framework alongside the system generalized method of moments (SGMM) technique, to scrutinize the interplay between air pollution and health outcomes. Focusing on a panel of the top twenty polluted nations from 2000 to 2021, the findings yield substantial insights. Notably, PM 2.5 concentration emerges as a significant factor, correlating with a reduction in life expectancy by 3.69 years and an increase in infant mortality rates by 0.294%. Urbanization is found to increase life expectancy by 0.083 years while concurrently decreasing infant mortality rates by 0.00022%. An increase in real per capita gross domestic product corresponds with an improvement in life expectancy by 0.21 years and a decrease in infant mortality rates by 0.00065%. Similarly, an elevated school enrollment rate is associated with a rise in life expectancy by 0.17 years and a decline in infant mortality rates by 0.00032%. However, a higher population growth rate is found to modestly decrease life expectancy by 0.019 years and slightly elevate infant mortality rates by 0.000016%. The analysis reveals that per capita greenhouse gas emissions exert a negative impact, diminishing life expectancy by 0.486 years and elevating infant mortality rates by 0.00061%, while per capita energy consumption marginally reduces life expectancy by 0.026 years and increases infant mortality rates by 0.00004%. Additionally, economic volatility shock presents a notable decrement in life expectancy by 0.041 years and an increase in infant mortality rates by 0.000045%, with inflationary shock further exacerbating adverse health outcomes by lowering life expectancy by 0.70 years and elevating infant mortality rates by 0.00025%. Moreover, the study scrutinizes the role of institutional quality, revealing a constructive impact on health outcomes. Specifically, the institutional quality index is associated with an increase in life expectancy by 0.66% and a decrease in infant mortality rates by 0.0006%. Extending the analysis to examine the nuanced dimensions of institutional quality, the findings discern that economic institutions wield a notably stronger positive influence on health outcomes compared to political and institutional governance indices. Finally, the results underscore the pivotal moderating role of institutional quality in mitigating the deleterious impact of PM 2.5 concentration on health outcomes, counterbalancing the influence of external shocks, and improving the relationships between explanatory variables and health outcome indicators. These findings offer critical insights for guiding evidence-based policy implications, with a focus on fostering resilient, sustainable, and health-conscious societies.