Cause Of Infant Mortality Research Articles

Microbiome-producing SCFAs are associated with preterm birth via trophoblast function modulation.

Preterm birth (PTB) is a leading cause of infant mortality and long-term health issues, affecting millions of families worldwide. Despite its prevalence, the exact causes of PTB remain unclear. Our study reveals that certain bacteria and their metabolic byproducts in the cervicovaginal environment, specifically short-chain fatty acids (SCFAs), are linked to the risk of preterm birth. By analyzing samples from pregnant women, we found that an imbalance in the vaginal microbiota and increased levels of SCFAs are associated with changes in cells that can lead to early labor. This research provides new insights into how the microbiome influences pregnancy outcomes and highlights potential biomarkers for predicting preterm birth. Understanding these microbial influences could lead to innovative strategies for early diagnosis and prevention, ultimately improving maternal and infant health.

Educational outcomes of children with major congenital anomalies: Study protocol for a population-based cohort study using linked hospital and education data from England

Background Major congenital anomalies (CAs) affect around 2% of live births and are a primary cause of infant mortality, childhood morbidity and long-term disability, often requiring hospitalisation and/or surgery. Children with CAs are at greater risk of lower educational attainment compared with their peers, which could be due to learning disabilities, higher rates of ill-health and school absences, or lack of adequate educational support. Our study will compare the educational attainment of children with CAs to those of their peers up to age 11 in England, using linked administrative health and education data. Methods We will analyse data from the ECHILD (Education and Child Health Insights from Linked Data) database. Children born in NHS-funded hospitals from 1st September 2003 to 31st August 2008 whose hospital records were linked to their educational records at three Key Stages (ages 4/5, 6/7 and 10/11 years) will be included. Children with different CAs, indicated by recorded hospital diagnosis codes, will be compared to children without CAs. We will compare the proportions of enrolled children who take the assessment, the proportions who reached national expected levels of attainment, and the mean standardised attainment scores for Maths and English at each Key Stage. We will describe variations in outcome by sex, ethnic minority background, region, and neighbourhood deprivation, and perform regression modelling to compare the attainment trajectories of children with and without CAs, controlling for sociodemographic factors. Ethics and dissemination Ethics approval has been obtained for the analyses of the ECHILD database. Our findings will provide information for parents regarding their children’s expected academic potential, and also enable the development of interventions to support those at risk of not doing well. We will disseminate our findings to academics, policy makers, service users and providers through seminars, peer-reviewed publications, conference abstracts and other media (lay summaries and infographics).

Di-(2-ethylhexyl) Phthalate Exposure Induces Developmental Toxicity in the Mouse Fetal Heart via Mitochondrial Dysfunction.

Congenital heart disease (CHD) is a major cause of infant mortality and morbidity, with growing interest in the role of environmental factors in its etiology. Di-(2-ethylhexyl) phthalate (DEHP), an environmental endocrine disruptor, has been implicated in the development of CHD. This study aimed to investigate the effects of DEHP exposure on fetal heart development in mice. Pregnant mice exposed to DEHP exhibited increased fetal malformations, decreased fetal weight, and reduced crown-rump length.f Transcriptomic analysis revealed the downregulation of genes involved in aerobic respiration and mitochondrial ATP synthesis. Functional assays demonstrated reduced mitochondrial respiration, decreased ATP production, elevated reactive oxygen species levels, and lowered mitochondrial membrane potential in DEHP-exposed fetal cardiomyocytes. These findings underscore the detrimental effects of DEHP on fetal cardiac health and provide insights into the molecular mechanisms underlying DEHP-induced CHD. Understanding these mechanisms is crucial for developing preventive strategies against environmental toxicants that affect fetal cardiac development.

Distinct maternofetal immune signatures delineate preterm birth onset following urinary tract infection.

Preterm birth is the leading cause of infant mortality resulting in over one million neonatal deaths annually. Maternal urinary tract infection (UTI) during pregnancy increases risk for preterm birth; however, biological processes mediating UTI-associated preterm birth are not well-described. We established a murine maternal UTI model in which challenge with uropathogenic E. coli resulted in preterm birth in about half of dams. Dams experiencing preterm birth displayed excessive bladder inflammation and altered uteroplacental T cell polarization compared to non-laboring infected dams, with no differences in bacterial burdens. Additional factors associated with preterm birth included higher proportions of male fetuses and lower maternal serum IL-10. Furthermore, exogenous maternal IL-10 treatment absolved UTI-associated preterm birth but contributed to fetal growth restriction in this model. Using urine samples from a cohort of human pregnancies with or without UTI, we correlated urinary cytokines with birth outcomes and urine culture status. These analyses yielded a non-invasive, highly predictive three-model system for evaluating preterm birth risk implicating cytokines IL-10, IL-15, IL-1β, and IL-1RA. Our unique bimodal murine model coupled with patient samples provides a platform to investigate immunological and microbial factors governing UTI-associated preterm birth, revealing novel therapeutic opportunities to predict or prevent preterm birth.

Congenital Heart Defects as One of the Causes of Perinatal Mortality

Congenital malformations are one of the most common causes of infant mortality and disability in children, and congenital heart defects (CHD) occupy a leading place in the structure of all developmental anomalies. The article presents data from a retrospective analysis of charts of children who died from complex congenital heart defects and congenital heart defects in combination with multiple developmental defects. An analysis of the pathological examination cards of 102 children from 0 to 2 years old who died in maternity hospitals and children's hospitals in Bishkek was carried out. The selection of autopsy cards of children was carried out on the basis of the Republican Pathological Bureau. As a result of pathological studies, changes in the heart and lungs were revealed. At the maternity hospital stage, out of 102 children with severe congenital heart defects, 70 newborns died, which averaged 68.6%. Among congenital heart defects, heart defects with aortopulmonary shunting with pulmonary hypertension predominated — in 45 children (44%), in particular, ventricular septal defect, atrial septal defect, then ductus-dependent heart defects were diagnosed in 25 children (24.5%), which included Tetralogy of Fallot, transposition of the great vessels. 23.5% of children had multiple congenital malformations: in all cases, congenital heart disease was recorded in combination with several malformations, such as an anomaly of the musculoskeletal system with craniofacial dimorphism, anomalies of the gastrointestinal tract and urinary system, and an anomaly of the lungs. The most common association of congenital heart disease with defects of other organs and systems was observed in cases of ventricular septal defect, atrial septal defect, patent ductus arteriosus.

Proinflammatory factors inhibition and fish oil treatment: A promising therapy for neonatal seizures

Brain injury is one of the most important causes of infant mortality and chronic neurological disabilities. Hypoxia is an acute brain injury which led to various cognitive, behavioral, and memory disorders throughout life. Previous studies reported neuroprotective possibilities for fish oil (FO) in brain-injured situations. In this study, we evaluated the effect of the FO diet during the lactation period on seizure activity, behavioral performance, histomorphometry, and inflammatory changes in the brains of hypoxia rats. Male Wistar rats were randomly divided in to 4 groups: Sham (intact rats), hypoxia, FO and FO+hypoxia groups. Hypoxia was induced by keeping neonate rats at PND12 in a hypoxic chamber (7 % oxygen and 93 % nitrogen intensity) for 15 minutes. In the FO groups, rats received oral FO (1 ml/day) for 12 days during the lactation period. Seizure activity was assessed by measuring the number of tonic-clonic seizures and seizure thresholds. Novel object recognition tests (NORT), rotarod, and open field tests were used to measure behavioral performances. A Histological study was performed to evaluate histomorphometric changes in the hippocampus and cerebellum. The gene expression of tumor necrosis factor-α (TNF-α) and interleukin-1β (IL-1β) was measured using RT-PCR. Findings showed that the number of tonic-clonic seizures, atrophy, and cell death in the hippocampus and cerebellum, the gene expression of TNF-α and IL-1β in the hippocampus, and behavioral disorders were significantly increased in the hypoxia rats compared to the sham group. Administration of FO in the hypoxia groups significantly decreased the gene expression of TNF-α and IL-1β, the number of tonic-clonic seizures, and neuronal cell death in the hippocampus and cerebellum compared to the hypoxia groups. Furthermore, it can improve behavioral tasks and cognitions.

Socioeconomic and ethnic disparities in preterm births in an English maternity setting: a population-based study of 1.3 million births

BackgroundPreterm birth is a major cause of infant mortality and morbidity and accounts for 7–8% of births in the UK. It is more common in women from socially deprived areas and from minority ethnic groups, but the reasons for this disparity are poorly understood. To inform interventions to improve child survival and their quality of life, this study examined the socioeconomic and ethnic inequalities in preterm births (< 37 weeks of gestation at birth) within Health Trusts in England.MethodsThis study investigated socioeconomic and ethnic inequalities in preterm birth rates across the National Health Service (NHS) in England. The NHS in England can be split into different units known as Trusts. We visualised between-Trust differences in preterm birth rates. Health Trusts were classified into five groups based on their standard deviation (SD) variation from the average national preterm birth rate. We used modified Poisson regression to compute risk ratios (RR) and 95% confidence intervals (95% CI) with generalised estimating equations.ResultsThe preterm birth rate ranged from 6.8/100 births for women living in the least deprived areas to 8.8/100 births for those living in the most deprived areas. Similarly, the preterm birth rate ranged from 7.8/100 births for white women, up to 8.6/100 births for black women. Some Health Trusts had lower than average preterm birth rates in white women whilst concurrently having higher than average preterm birth rates in black and Asian women. The risk of preterm birth was higher for women living in the most deprived areas and ethnicity (Asian).ConclusionsThere was evidence of variation in rates of preterm birth by ethnic group, with some Trusts reporting below average rates in white ethnic groups whilst concurrently reporting well above average rates for women from Asian or black ethnic groups. The risk of preterm birth varied substantially at the intersectionality of maternal ethnicity and the level of socioeconomic deprivation of their residency. In the absence of other explanations, these findings suggest that even within the same Health Trust, maternity care may vary depending on the women’s ethnicity and/or whether she lives in an area of high socioeconomic deprivation. Thus, social factors are likely key determinants of inequality in preterm birth rather than provision of maternity care alone.

Bridging Prenatal Diagnostics and AI: A Systematic Review and Meta-Analysis of the Efficacy of Advanced Algorithms in Identifying Congenital Fetal Abnormalities

Congenital fetal abnormalities have emerged as a major cause of infant mortality globally. About 3% of pregnancies are reported as fetal structural anomaly through ultrasound, ranging from minor defect to severe organ system anomalies. Our study aimed to evaluate effectiveness of Artificial intelligence (AI) algorithms in prediction of fetal heart and brain abnormalities by using meta-analysis approach. In this study, the “Reporting Items for Systematic Review and Meta-Analysis (PRISMA)" guidelines were applied for screening and selection of research articles. We searched the research articles according to research aims from Google scholar, PubMed, and Ovid MEDLINE. The data search was limited to January 2015 to May 2024. Two researchers independently screened the studies to detect research aim oriented studies. After screening of titles, those researchers assessed all abstract for eligibility. The risk bias of included studies was assessed by two researchers who used Cochrane library tool (version 5.4.0). Using the DerSimonian-Laird technique, a bivariate random effect model that generated SROC plots, we pooled test estimates. This method is particularly helpful in visualizing variability in the sensitivity and specificity across studies, accounting for the heterogeneity. This improves the reliability of the SROC plot, offering a clear summary of diagnostic performance Using the software RevMan 5.4, we carried out every statistical analysis, particularly heterogeneity through the Q test. About 243,456 screened fetus or pregnant women of 11-32 gestational weeks through 10 studies based on AI algorithms (machine learning, deep learning and AI diagnostic tool). The imaging protocols including ultrasound and MRI were used to take visuals of fetal brain and heart abnormalities in all of including studies. DL and ML algorithms provided high-performance diagnostic predictions, mostly include CNN models that assist in providing accurate diagnostic results with high sensitivity and specificity. The AI algorithm model showed a generally good accuracy scores for detection of brain and heart abnormalities and reference machine learning findings, with sensitivity ranging from 82 to 99% and specificity from 78 to 99%. Fig. 5's area under the SROC curve was 0.960. In contrast to the general detection, ML and DL seems to be more sensitive in diagnosing fetal brain and heart abnormalities. Our study provided the scientific evidence that AI models including deep learning and Machine learning are effective in generating highly reliable detection or classification results for diagnosis of fetal brain and heart anomalies. These strategies can help in reducing infant mortalities, improving treatment outcomes, and postpartum outcomes among women.

Prediction model for composite adverse pregnancy outcomes: Indonesia demographic health survey analysis

Adverse Pregnancy Outcome (APO) is the leading cause of infant mortality, particularly in low and middle-income countries. Despite no significant change in neonatal mortality rates in Indonesia over the past fifteen years, identifying the risk factors for APO can help healthcare professionals provide personalized interventions and support. This study aims to determine the determinants of APO risk in Indonesia. The cross-sectional study utilized the 2017 Indonesian Health Demographic Survey (IDHS), which included 9,752 women of reproductive age. APO, including low birth weight, early birth, and stillbirth, was the outcome of the study. The demographic characteristics and other risk factors were evaluated. To identify APO-risk-associated factors, we performed multiple logistic regression analysis. The results showed that low economic status (Adj. OR= 1.407; 1.153-1.716; p= 0.001)), living in rural areas (Adj. OR= 0.804; 0.663-0.976; p= 0.027), having a history of pregnancy or childbirth complications (Adj. OR= 4.563; 3.617-5.756; p= 0.0001), premature rupture of the membrane during pregnancy or after giving birth (Adj. OR= 1.351; 1.069-1.708; p= 0.012), antenatal visits &lt;4 times (Adj. OR= 1.603; 1.123-2.288; p= 0.009), consumption of iron supplement tablets &lt;90 days (Adj. OR= 1.275; 1.063-1.529; p= 0.009), and twin pregnancy (Adj. OR= 33.715; 18.587-61.153; p= 0.0001) significantly influenced the APO prevalence. The study concluded that APO risk is significantly impacted by poor obstetric history features, multiple births, low health service utilization, and sociodemographic factors. Early detection of these risk factors is essential for reducing neonatal death caused by APO.

Risk and Protective Factors for Preterm Birth Among Racial, Ethnic, and Socioeconomic Groups in California

Preterm birth (PTB) (gestational age <37 weeks) is a major cause of infant mortality and morbidity in the US and is marked by racial and ethnic and socioeconomic inequities. Further research is needed to elucidate the association of risk and protective factors with trends in PTB rates and with related inequities. To describe the association of PTB rates with inequities as well as related risk and protective factors over the past decade in a US population-based cohort. This retrospective cohort study of singleton live births in California from January 1, 2011, to December 31, 2022, was conducted using vital statistics records and hospital records. The cohort included births with a gestational age of 22 to 44 weeks. Preterm birth rates by racial and ethnic group and by public and nonpublic insurance (considered as a proxy for socioeconomic status) were studied across years. Log-linear regression (relative risks with 95% CIs) was used to evaluate risk and protective factors within groups. Associations of PTB rates with risk and protective factors were assessed. This study included 5 431 018 singleton live births to individuals who identified as American Indian or Alaska Native (0.3%), Asian (14.2%), Black (4.9%), Hispanic (47.8%), or White (27.0%). A total of 43.1% of births were to individuals with public health insurance. From 2011 to 2022, the overall PTB rate increased from 6.8% to 7.5% (change [SE], 10.6% [0.6%]; z score of 18.5; P < .001). Differences in PTB rates and associated changes were observed for racial and ethnic groups and insurance groups. For example, 2022 PTB rates ranged from 5.8% among White individuals with nonpublic insurance to 11.3% among Black individuals with public health insurance. From 2011 to 2022, PTB rates decreased from 9.1% to 8.8% (change [SE], -3.5% [4.2]; z score of -0.8; P = .42) among Black individuals with nonpublic insurance, whereas they increased from 6.4% to 9.5% (change [SE], 49.8% [16.0%]; z score of 3.1; P = .002) among American Indian or Alaska Native individuals with nonpublic insurance. Increases in some risk factors (eg, preexisting diabetes, sexually transmitted infections, mental health conditions) were observed in most groups, and decreases in some protective factors (eg, participation in the California Women, Infants, and Children program) (P for trend < .001 from 2011 to 2021) were observed mostly in low-income groups. In this cohort study of singleton live births in California, PTB rates increased in many groups. Persistent racial and ethnic and socioeconomic inequities were also observed. Changes in risk and protective factors provided clues to patterns of PTB. These data point to an urgent need to address factors associated with PTB at both the individual and population levels.

The functional state of the respiratory system of the patients with proximal spinal muscular atrophy 5q (SMA 5q): from the natural history of the disease to the era of pathogenetic therapy. Problems and expectations

Proximal spinal muscular atrophy 5q is an autosomal recessive neuromuscular disease. This disorder is characterized by progressive symptoms of flaccid paralysis and muscular atrophy due to degeneration of α-motor neurons in the anterior horns of the spinal cord. The disease is caused by the lack of a fully functional SMN protein due to homozygous deletion of exon 7 in the SMN1 gene. For a long time, spinal muscular atrophy was the leading genetic cause of infant mortality. With the introduction of modern pathogenetic treatment methods that modify the disease, the duration and quality of life of patients increases, and a “blurring of boundaries” between types of spinal muscular atrophy and the formation of new phenotypes happens. In this regard, approaches to patient management, including approaches to the assessment and correction of respiratory disorders, are changing. The review of the available medical literature was conducted. The clinical studies on spinal muscular atrophy in the natural course of the disease and with the use of pathogenetic drugs were analyzed, as well as the data on the state of the respiratory system of the patients.

Risk Stratification Of Signs Of Possible Serious Bacterial Infection For Prediction Of Mortality Among Young Infants

Objective: Possible serious bacterial infection (PSBI) is one of the leading causes of infant mortality. Based on WHO multi-centric study, signs of PSBI are categorized into: signs of clinical severe infection (CSI) and signs of critical illness (CI). Assessment of signs of PSBI helps to divide infants into risk groups for appropriate management and prognostication. This study aimed to assess risk stratification of signs of PSBI among young infants (0- 59 days of age) by correlating signs of PSBI with mortality. Methods: In this hospital-based prospective cohort study, 220 young infants with signs of PSBI were recruited. Infants were categorized into two: those with signs of CSI and those with signs of CI. Correlation of each sign of PSBI was done with mortality. Time to death was assessed by using the Kaplan Meier survival analysis. Results: 220 infants were analyzed for outcomes. Signs of CSI including fever, fast breathing, poor feeding, and movement only on stimulation had a low fatality rate; however low body temperature and severe chest pain was associated with high mortality of 20% and 9%, respectively. CI signs – convulsion, no movement at all, and no feeding at all were associated with high death rates of 14%, 63.7%, and 47.4% respectively. The majority of deaths were occurred within 48 hours of presentation. Conclusions: Mortality was high in infants with low body temperature, chest pain, or any sign of CI. Risk stratification based on clinical signs could help prioritize infants in need for urgent intervention and thus decrease infant mortality.

Secular Trends in Preterm Birth Rates: Uncovering the Primary Challenge for Perinatal Medicine in Greece.

Preterm labour is a serious pregnancy complication that is the primary cause of infant mortality, with detrimental impacts on the offspring and the mother in the short as well as the long term. This study aims to comprehensively present the time trends of national preterm birth rates (PBRs) in Greece. Official national data regarding live births in Greece were acquired from the Hellenic Statistical Authority, and the annual total PBRand rates for gestational age groups were computed per 100 total live births spanning from 1980 to 2022. Time trends were analyzed through joinpoint regression analysis, and annual percent changes (APC) and average annual percent change (AAPC) were calculated with a 95% confidence interval (95% CI). Following a steady decline from 4.66% in 1980 to a historic low of 2.77% in 1991 with an APC of -5.1 (-6.2 to -4.2), the PBR exhibited a dramatic increase during 1991-2011 with an APC of 7.3 (6.9 to 7.8). Subsequently, between 2011 and 2022, the rise in PBR was attenuated, showing a slight statistically non-significant upward trend (APC = 0.5, 95% CI: -0.6 to 1.5). This led to a historical high of 12.07% in 2018, 4.4 times higher than that in 1991, and eventually, the PBR reached 11.90% in 2022. From 1991 to 2022, there were sharper increases in the rates of moderate (32-33 weeks) and late (34-36 weeks) preterm births, with AAPCs of 4.9 (3.5-6.4) and 5.8 (5.3-6.3), respectively. In contrast, the rates of extremely (<28 weeks) and very (28-31 weeks) preterm births saw slower growth, with AAPCs of 2.2 (1.7-2.7) and 0.7 (0.5-1.0), respectively. The PBR in Greece more than quadrupled during 1991-2022, mainly due to increases in moderate and late preterm births. Although its rise has markedly decelerated since 2011, amidst the country's economic recession, the PBR is alarmingly higher than those in all other European and developed nations. More than one in nine neonates is born prematurely in the Greek population, posing challenges in implementing evidence-based prevention strategies and perinatal care.

Association between ambient air pollution a week prior to delivery and preterm birth using a nationwide study in Sweden

BackgroundAir pollution exposure has been linked with increased risk of preterm birth, which is one of the leading causes of infant mortality. Limited studies have attempted to explore these associations in low-polluted areas. In this study, we aimed to assess the association between short-term exposure to ambient air pollution and preterm birth in Sweden. MethodIn this population-based study we included preterm births between 2014 and 2019 from the Swedish Pregnancy Register. We applied a spatiotemporal model to estimate daily levels of particulate matter <2.5 μm (PM2.5), PM < 10 μm (PM10), nitrogen dioxide (NO2), and ozone (O3) at the residential address of each participant. We applied a time-stratified case-crossover design with conditional logistic regression analysis to estimate odds ratios (OR) of preterm birth per 10 μg/m3 (PM10, NO2, O3) and 5 μg/m3 (PM2.5) increase in air pollution exposure at 0–6-day lag. Two-pollutant models were applied to evaluate the independent association of each exposure on preterm birth. We also stratified by maternal characteristics to identify potential effect modifiers. Results28,216 (4.5%) preterm births were included. An increase in O3 exposure was associated with increased odds of preterm birth [OR = 1.06 per 10 μg/m3 (95% CI, 1.02; 1.10]. PM2.5 and PM10 were not significantly associated with preterm birth, and NO2 displayed a negative nonlinear association with preterm birth. We did not observe any notable effect modification, but we found suggestive larger associations between O3 and preterm birth when stratifying by male sex, spontaneous delivery, and spring season. ConclusionsIncreased O3 exposure one week before delivery was associated with an increased risk of preterm birth in Sweden, a country with levels of air pollution below the current World Health Organization air quality guidelines. Increases in O3 levels with climate change make these findings especially concerning.

Spatiotemporal Trends of Birth Defects in North Carolina, 2003-2015.

Birth defects are a leading cause of infant mortality in the United States, but little is known about causes of many types of birth defects. Spatiotemporal disease mapping to identify high-prevalence areas, is a potential strategy to narrow the search for potential environmental and other causes that aggregate over space and time. We described the spatial and temporal trends of the prevalence of birth defects in North Carolina during 2003-2015, using data on live births obtained from the North Carolina Birth Defects Monitoring Program. By employing a Bayesian space-time Poisson model, we estimated spatial and temporal trends of non-chromosomal and chromosomal birth defects. During 2003-2015, 52,524 (3.3%) of 1,598,807 live births had at least one recorded birth defect. The prevalence of non-chromosomal birth defects decreased from 3.8% in 2003 to 2.9% in 2015. Spatial modeling suggested a large geographic variation in non-chromosomal birth defects at census-tract level, with the highest prevalence in southeastern North Carolina. The strong spatial heterogeneity revealed in this work allowed to identify geographic areas with higher prevalence of non-chromosomal birth defects in North Carolina. This variation will help inform future research focused on epidemiologic studies of birth defects to identify etiologic factors.

Maternal factors associated with the occurrence of Low Birth Weight (LBW) Infants at the Haji Hospital, East Java Province

Introduction: Low birth weight infants are an indicator of public health problems. They are also included in the 100 core health conditions the World Health Organization (WHO) compiled. LBW Infants are still the cause of infant mortality in Indonesia. The infant mortality rate in Indonesia is still not reaching the SDGS target. Objective: This study aims to examine maternal factors associated with the occurrence of LBW Infants at the Haji Hospital, East Java Province Method: This study used a retrospective method with a case-control study design. This study took a sample of 258 infants with inclusion and exclusion criteria. Data collection uses secondary data in the form of collection carried out in the delivery and medical records room. Result: Bivariate analysis obtained the results of gestational age (p &lt; 0.001), history of LBW infants (p = 0.03), anemia (p = 0.641), hypertension in pregnancy (p &lt; 0.001), maternal illness (p &lt; 0.001) with the occurrence of LBW infants. Based on multivariate analysis, mothers with gestational age &lt;37 weeks had OR 8.667 (95%CI 4.509-16.659), a history of LBW infant had OR 10.736 (95%CI 1.895-60.809), hypertension in pregnancy OR 2.468 (95%CI 1.250-4.869), and maternal illness OR 3.212 (95%CI 1.301-7.932) times to experience LBW infants. Conclusion: This study highlights the burden of caring for LBW infants in the Haji Hospital in East Java province. Maternal factors need to be given special attention during pregnancy. Health promotion measures, early detection screening, and intervention of related factors need to be done so that the occurrence of LBW infants can be prevented.

Factors associated with severe pneumonia among children

BackgroundPneumonia is one of the leading causes of infant mortality globally, particularly in sub-Saharan Africa. In Uganda, pneumonia was the fourth leading cause of death in children <5 years in 2018. Analysis of 2013–2022 data for children <5 years from the District Health Information System indicated a high incidence of severe pneumonia in Kasese District, Uganda. We investigated to identify factors associated with severe pneumonia among children <5 years in Kasese District to inform prevention and control strategies.MethodsWe conducted a 1:1 hospital-based case-control study among children aged 2–59 months presenting with pneumonia at five high-volume facilities in Kasese District from January to April 2023. A case was defined as pneumonia with ≥1 of the following danger signs: low oxygen saturation, central cyanosis, severe respiratory distress, feeding difficulties, altered consciousness, and convulsions. Controls were outpatient children aged 2–59 months with a diagnosis of non-severe pneumonia. We reviewed medical records at facilities and used an interviewer-administered questionnaire with caregivers to obtain information on socio-demographic and clinical characteristics. Logistic regression was used to identify factors associated with severe pneumonia.ResultsWe enrolled 199 cases and 174 controls. The odds of severe pneumonia were higher among children with diarrhoea only (adjusted odds ratio [aOR] = 2.9, 95%CI: 1.7–4.9), or malaria and diarrhoea (aOR = 3.4, 95%CI: 2.0-5.9), than those without a co-existing illness at the time of pneumonia diagnosis. Not being exclusively breastfed for ≥ 6 months (aOR = 2.0, 95%CI: 1.1–3.3) and exposure to indoor air pollution from cooking combustion sources (aOR = 2.9, 95%CI: 1.8–4.7) increased odds of severe pneumonia.ConclusionThe findings highlight the significance of comorbidities, lack of exclusive breastfeeding, and exposure to indoor air pollution in the development of severe pneumonia. Promoting exclusive breastfeeding for ≥ 6 months and advocating for the use of clean energy sources, could mitigate morbidity attributable to severe pneumonia in the region.

Medical Genetics in Brazil in the 21st Century: A Thriving Specialty and Its Incorporation in Public Health Policies.

Brazil is a continent-size country with 203 million inhabitants, classified as a developing upper-middle-income country, although inequities remain significant. Most of the population is assisted by the public Unified Health System (SUS), along with a thriving private health sector. Congenital malformations are the second leading cause of infant mortality and chronic/genetic disorders and a significant burden in hospital admissions. The past two decades have been crucial for formalizing medical genetics as a recognized medical specialty in the SUS, as well as for implementing a new health policy by the Ministry of Health for comprehensive care for rare diseases. These public health policies had the broad support of the Brazilian Society of Medical Genetics and Genomics and patient organizations. Most comprehensive genetic services are concentrated in large urban centers in the South and Southeast regions of Brazil; with this new policy, new services throughout the country are progressively being integrated. The number of medical geneticists increased by 103% in a decade. Details on the policy and an overview of the availability of services, testing, human resources, newborn screening, research projects, patient organizations, and relevant issues regarding medical genetics in this vast and diverse country are presented.

What was Killing Babies in Rostock? An Investigation of Infant Mortality Using Individual-Level Cause-of-Death Data, 1800–1904

This paper examines the causes of infant mortality for the Hanseatic city of Rostock, Germany, between 1800 and 1904. Based on unique individual-level church records from Rostock's largest inner-city parish, St. Jakobi, we apply the novel ICD10h coding system for the first time to the German context. Using this coding system, we analyse cause-specific patterns of infant, neonatal and post-neonatal mortality in an internationally comparable way and bring new insights into the determinants of 19th-century infant mortality, which was shaped by increase and stagnation in wide parts of Germany. Our results show that Rostock experienced a stagnating infant mortality rate at a low level in international comparison during the first 40 years of the 19th century, followed by severe increases during the next 20 years and a stage of slight decline and stagnation towards the end of the study period. This suboptimal development from 1840 was strongly related to post-neonatal mortality and causes of death that are related to unfavourable sanitary conditions and/or poor nutrition, which possibly hints at worsening housing and living conditions following accelerated population growth. Our analyses also reveal that water-food borne diseases were underestimated in Rostock, even though symptomatic disease terms such as convulsions and teething, that were frequently recorded over much of the 19th century, had deviating seasonality patterns and thus cannot entirely refer to this disease group but rather to a wide field of different diseases. The applied coding scheme is a significant step forward to foster comparative international research on historical cause-specific mortality.

A Coarse-Fine Collaborative Learning Model for Three Vessel Segmentation in Fetal Cardiac Ultrasound Images.

Congenital heart disease (CHD) is the most frequent birth defect and a leading cause of infant mortality, emphasizing the crucial need for its early diagnosis. Ultrasound is the primary imaging modality for prenatal CHD screening. As a complement to the four-chamber view, the three-vessel view (3VV) plays a vital role in detecting anomalies in the great vessels. However, the interpretation of fetal cardiac ultrasound images is subjective and relies heavily on operator experience, leading to variability in CHD detection rates, particularly in resource-constrained regions. In this study, we propose an automated method for segmenting the pulmonary artery, ascending aorta, and superior vena cava in the 3VV using a novel deep learning network named CoFi-Net. Our network incorporates a coarse-fine collaborative strategy with two parallel branches dedicated to simultaneous global localization and fine segmentation of the vessels. The coarse branch employs a partial decoder to leverage high-level semantic features, enabling global localization of objects and suppression of irrelevant structures. The fine branch utilizes attention-parameterized skip connections to improve feature representations and improve boundary information. The outputs of the two branches are fused to generate accurate vessel segmentations. Extensive experiments conducted on a collected dataset demonstrate the superiority of CoFi-Net compared to state-of-the-art segmentation models for 3VV segmentation, indicating its great potential for enhancing CHD diagnostic efficiency in clinical practice. Furthermore, CoFi-Net outperforms other deep learning models in breast lesion segmentation on a public breast ultrasound dataset, despite not being specifically designed for this task, demonstrating its potential and robustness for various segmentation tasks.