The comparing of infant mortality rate in different World Health Organization regions during 1990–2017

Association of socioeconomic disadvantage and ethnicity with perinatal neonatal, and infant mortality in Slovakia

BACKGROUND

Infant mortality rates are reliable indices of the child and general population health status and health care delivery. The most critical factors affecting infant mortality are socioeconomic status and ethnicity. The aim of this study was to assess the association between socioeconomic disadvantage, ethnicity, and perinatal, neonatal, and infant mortality in Slovakia before and during the COVID-19 pandemic.

METHODS

The associations between socioeconomic disadvantage (educational level, long-term unemployment rate), ethnicity (the proportion of the Roma population) and mortality (perinatal, neonatal, and infant) in the period 2017-2022 were explored, using linear regression models.

RESULTS

The higher proportion of people with only elementary education and long-term unemployed, as well as the higher proportion of the Roma population, increases mortality rates. The proportion of the Roma population had the most significant impact on mortality in the selected period between 2017 and 2022, especially during the COVID-19 pandemic (2020-2022).

CONCLUSIONS

Life in segregated Roma settlements is connected with the accumulation of socioeconomic disadvantage. Persistent inequities between Roma and the majority population in Slovakia exposed by mortality rates in children point to the vulnerabilities and exposures which should be adequately addressed by health and social policies.

Countrywide analysis of heat- and cold-related mortality trends in the Czech Republic: growing inequalities under recent climate warming

BACKGROUND

Only little is known about trends in temperature-mortality associations among the most vulnerable subgroups, especially in the areas of central and eastern Europe, which are considered major climatic hotspots in terms of heatwave exposure. Thus, we aimed to assess trends in temperature-related mortality in the Czech Republic by sex, age and cause of death, and to quantify the temporal evolution of possible inequalities.

METHODS

We collected daily time series of all-cause (1987-2019) and cause-specific (1994-2019) mortality by sex and age category, and population-weighted daily mean 2-metre temperatures for each region of the Czech Republic. We applied a quasi-Poisson regression model to estimate the trends in region-specific temperature-mortality associations, with distributed lag non-linear models and multivariate random-effects meta-analysis to derive average associations across the country. We then calculated mortality attributable to non-optimal temperatures and implemented the indicator of sex- and age-dependent inequalities.

RESULTS

We observed a similar risk of mortality due to cold temperatures for men and women. Conversely, for warm temperatures, a higher risk was observed for women. Results by age showed a clear pattern of increasing risk due to non-optimum temperatures with increasing age category. The relative risk (RR) related to cold was considerably attenuated in most of the studied subgroups during the study period, whereas an increase in the RR associated with heat was seen in the overall population, in women, in the age category 90+ years and with respect to respiratory causes. Moreover, underlying sex- and age-dependent inequalities experienced substantial growth.

CONCLUSIONS

Our findings suggest ongoing adaptation to cold temperatures. Mal/adaptation to hot temperatures occurred unequally among population subgroups and resulted in growing inequalities between the sexes and among age categories.

Assessing risk factors for malnutrition among women in Bangladesh and forecasting malnutrition using machine learning approaches

BACKGROUND

This paper presents an in-depth examination of malnutrition in women in Bangladesh. Malnutrition in women is a major public health issue related to different diseases and has negative repercussions for children, such as premature birth, decreased infection resistance, and an increased risk of death. Moreover, malnutrition is a severe problem in Bangladesh. Data from the Bangladesh Demographic Health Survey (BDHS) conducted in 2017-18 was used to identify risk factors for malnourished women and to create a machine learning-based strategy to detect their nutritional status.

METHODS

A total of 17022 women participants are taken to conduct the research. All the participants are from different regions and different ages. A chi-square test with a five percent significance level is used to identify possible risk variables for malnutrition in women and six machine learning-based classifiers (Naïve Bayes, two types of Decision Tree, Logistic Regression, Random Forest, and Gradient Boosting Machine) were used to predict the malnutrition of women. The models are being evaluated using different parameters like accuracy, sensitivity, specificity, positive predictive value, negative predictive value, [Formula: see text] score, and area under the curve (AUC).

RESULTS

Descriptive data showed that 45% of the population studied were malnourished women, and the chi-square test illustrated that all fourteen variables are significantly associated with malnutrition in women and among them, age and wealth index had the most influence on their nutritional status, while water source had the least impact. Random Forest had an accuracy of 60% and 60.2% for training and test data sets, respectively. CART and Gradient Boosting Machine also had close accuracy like Random Forest but based on other performance metrics such as kappa and [Formula: see text] scores Random Forest got the highest rank among others. Also, it had the highest accuracy and [Formula: see text] scores in k-fold validation along with the highest AUC (0.604).

CONCLUSION

The Random Forest (RF) approach is a reasonably superior machine learning-based algorithm for forecasting women's nutritional status in Bangladesh in comparison to other ML algorithms investigated in this work. The suggested approach will aid in forecasting which women are at high susceptibility to malnutrition, hence decreasing the strain on the healthcare system.

2008 economic crisis impact on perinatal and infant mortality in Southern European countries

INTRODUCTION

The study of crisis events provides important lessons to prepare for upcoming events. The Great Recession's impact on perinatal health in Europe can provide relevant insights into the healthcare and social protection systems' response to the protection of the health of the most vulnerable groups.

OBJECTIVE

To assess time trends and international disparities in perinatal mortality rates (PMR) and infant mortality rates (IMR), following the Great Recession, and their association with socioeconomic indicators in Portugal, Greece, Italy and Spain.

METHODS

Associations were assessed through generalised linear models for all four countries. A Poisson joinpoint regression model was applied to explore PMR and IMR trend changes between 2000 and 2018. Country disparities were analysed using mixed-effects multilevel models.

RESULTS

IMR and PMR have decreased overall in the four selected countries between 2000 and 2018. Still, whereas in Spain, Italy and Portugal the decreasing pace was attenuated after 2009, in Greece a positive trend was found after the 2008 crisis. IMR and PMR were significantly associated with socioeconomic indicators in all four countries. National disparities in the evolution of IMR and PMR were significantly associated with most socioeconomic indicators between 2000 and 2018.

CONCLUSION

Our results confirm the impact of the Great Recession on PMR and IMR trends in all four countries, taking recurring associations between macroeconomic cycles, variations in mortality trends, macroeconomic volatility and stagnation of IMR and PMR into account. The association with socioeconomic indicators stresses the need to strengthen social protection and healthcare systems to better protect the population's health from the earliest days.

Longitudinal trends in lipid profile in indian children and youth with type-1 diabetes: a 5-year follow up from a single centre

INTRODUCTION

High prevalence of dyslipidaemia in children and adolescents with type-1 diabetes (T1D) places them at increased risk of developing atherosclerosis leading to mortality caused by cardiovascular disease(CVD). Thus, screening for fasting blood lipids when diabetes is stabilized in children aged 11 years and above is routinely recommended with follow-up every 5 years.

OBJECTIVES

(1) To characterize the lipid profile of children and adolescents with respect to diabetes duration. (2) To describe longitudinal changes in lipid profile over a 5-year period in patients with T1D.

METHODS

This longitudinal 5-year follow-up study included 112 patients with T1D aged 3-18 years. Demographic data, anthropometry and laboratory measurements were performed using standard protocols at baseline and endline. P value < 0.05 was considered significant.

RESULTS

The prevalence of dyslipidaemia in our study was 49.5% with abnormal LDL as the most frequently deranged parameter. Duration of illness played a major role in deterioration of lipid profile mediated by triglyceride and VLDL. Duration of illness and fibre intake in diet significantly predicted the change in lipid profile which were driven by triglycerides and VLDL. Glycemic control, insulin sensitivity and serum TSH also significantly altered components of lipid profile with no impact on overall dyslipidaemia. A total of 6.5% subjects had LDL concentrations >130 mg/dl and the same proportion had non-HDL cholesterol concentrations >145 mg/dl at baseline while at endline, 11.9% subjects had LDL concentrations >130 mg/dl and 15.6% subjects had non-HDL cholesterol concentrations >145 mg/dl. 28.6% subjects with LDL > 130 mg/dl and non-HDL cholesterol >145 mg/dl at baseline had persistently elevated concentrations while 10.3% and 14.4% additional subjects developed elevated LDL and non-HDL cholesterol concentrations respectively during the study period.

CONCLUSIONS

The deterioration of lipid profile in T1D, due to increase in disease duration was chiefly mediated by increase in serum triglyceride and VLDL concentrations which may be prevented by improving glycaemic control, insulin sensitivity and fibre intake in diet.

Can Fetal Heart Lie? Intrapartum CTG Changes in COVID-19 Mothers

Background

COVID-19 infection has raised multiple concerns in pregnant mothers; many questioned the risk of vertical transmission and the implication on the feto-maternal outcome. Cardiotocogrm (CTG) is the principal method to observe intrapartum fetal well-being. This paper aims to verify intrapartum CTG changes seen in seropositive COVID-19 mothers versus healthy controls and looks into their relation to subsequent delivery mode and neonatal outcome.

Methods

A case-control study recruited 90 pregnant women at the labor word of AL Yarmouk Teaching Hospital. All were term pregnancy admitted for delivery. They were grouped into 2: seropositive COVID-19 confirmed by real-time RT-PCR test (30/90) and healthy controls (60/90). We recorded their demographic criteria, laboratory results, CTG changes, delivery mode, and indication.

Results

COVID-19 cases showed significantly higher pulse rate, temperature, and leukocyte counts. Cesarian deliveries (CS) were higher in cases versus healthy controls (70 % vs. 53.3 %) and P = 0.45. Analysis of the CS indications showed that abnormal fetal heart tracing accounts for 33.3 % versus 15.6 % (P-value = 0.015) for cases versus healthy controls. 60 % of COVID-19 cases exhibited abnormal CTG changes versus 19.4 % in healthy controls. These changes were primarily fetal tachycardia and reduced variabilities.

Conclusions

The higher incidence of abnormal CTG in COVID-19 cases, alongside infection signs and symptoms, underlies the exaggerated inflammatory reactions inside the pregnant mother. These inflammatory reactions are the main causes of CTG changes and higher CS rates. Therefore, obstetricians are advised to optimize the maternal condition to rectify reactive CTG changes rather than proceeding into urgent CS.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13224-022-01663-6.