167 research outputs found

    Incidence and predictors of puerperal sepsis among postpartum women at Debre Markos comprehensive specialized hospital, northwest Ethiopia: A prospective cohort study

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    Background: Puerperal sepsis is one of the leading causes of maternal mortality, particularly in low and middle-income countries where most maternal deaths occur. Women with puerperal sepsis are prone to long-term disabilities, such as chronic pelvic pain, blocked fallopian tubes, and secondary infertility. Besides this, puerperal sepsis has received less attention. For this reason, this study aimed to determine the incidence of puerperal sepsis and its predictors among postpartum women at Debre Markos Comprehensive Specialized Hospital. Methods: A prospective cohort study was conducted among 330 postpartum women from September 2020 to 2021. A pre-tested interviewer-administered questionnaire with a data extraction checklist was used to collect the data. Data were entered into Epi data 4.2 and analyzed using STATA 14.0. The incidence rate of puerperal sepsis was calculated, and a Kaplan-Meier survival curve was used to estimate the survival probability of developing puerperal sepsis. The cox-proportional hazards regression model was fitted to identify predictors of puerperal sepsis. Results: The study participants were followed for a total of 1685.3 person-week observations. The incidence rate of puerperal sepsis was 14.24 per 1,000 person-weeks. However, the overall incidence of puerperal sepsis was 7.27%. Not attending formal education [AHR: 3.55, 95% CI: (1.09–11.58)], a cesarean delivery [AHR: 4.50; 95% CI: (1.79–11.30)], premature rupture of the membranes [AHR: 3.25; 95% CI: (1.08–9.79)], complicated pregnancy [AHR: 4.80; 95% CI: (1.85–12.43)], being referred [AHR: 2.90; 95% CI: (1.10–7.65)], and not having birth preparedness and complication readiness plan [AHR: 2.95; 95% CI: (1.08–10.50)] were statistically significant predictors of puerperal sepsis. Conclusion: The incidence of puerperal sepsis was 7.27%. Not attending formal education, cesarean delivery, premature rupture of membranes, complicated pregnancy, referral status, and absence of birth preparedness and complication readiness plan were predictors associated with the incidence of puerperal sepsis

    Electrocatalytic reduction of carbon dioxide on gold–copper bimetallic nanoparticles: Effects of surface composition on selectivity

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    In this work, bimetallic nanoparticles (NPs) of Au and Cu are synthesized for the electrochemical reduction reaction of CO2 (CO2RR). It is known that the binding strength between the reduction intermediates and the electrocatalyst affects the selectivity of products, but how to correlate the performance with the surface composition, structure, and properties of a bimetallic electrocatalyst, instead of stoichiometric or bulk composition remains less discussed. AuCu and AuCu3 NPs with the size around similar to 8 nm were prepared. By excluding the size effect, the work studies the effects of surface composition and heteroatomic interaction on the selectivity and faradaic efficiency of the reduction products. Based on X-ray absorption spectroscopy (XAS), one can quantify the alloying extent and surface compositions of electrocatalysts, which are supposed to have the pivotal effects on the reaction pathways and the corresponding reduction products. It is found that high activity and notably improved CO selectivity of Au-Cu bimetallic NPs can be attributed to the heterometallic coordination and their electronic interactions. The reduction products were analyzed by gas chromatography and nuclear magnetic resonance (NMR) spectroscopy. Nearly 60 mA cm(-2) of current density was recorded at -0.91 V vs. RHE, and selectivity of 78 +/- 4.3% CO was obtained using AuCu. (C) 2020 Published by Elsevier Ltd

    Socio-demographic correlates of unhealthy lifestyle in Ethiopia: a secondary analysis of a national survey

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    Background: Multiple lifestyle risk factors exhibit a stronger association with non-communicable diseases (NCDs) compared to a single factor, emphasizing the necessity of considering them collectively. By integrating these major lifestyle risk factors, we can identify individuals with an overall unhealthy lifestyle, which facilitates the provision of targeted interventions for those at signifcant risk of NCDs. The aim of this study was to evaluate the socio-demographic correlates of unhealthy lifestyles among adolescents and adults in Ethiopia. Methods: A national cross-sectional survey, based on the World Health Organization’s NCD STEPS instruments, was conducted in Ethiopia. The survey, carried out in 2015, involved a total of 9,800 participants aged between 15 and 69 years. Lifestyle health scores, ranging from 0 (most healthy) to 5 (most unhealthy), were derived considering factors such as daily fruit and vegetable consumption, smoking status, prevalence of overweight/obesity, alcohol intake, and levels of physical activity. An unhealthy lifestyle was defned as the co-occurrence of three or more unhealthy behaviors. To determine the association of socio-demographic factors with unhealthy lifestyles, multivariable logistic regression models were utilized, adjusting for metabolic factors, specifcally diabetes and high blood pressure. Results: Approximately one in eight participants (16.7%) exhibited three or more unhealthy lifestyle behaviors, which included low fruit/vegetable consumption (98.2%), tobacco use (5.4%), excessive alcohol intake (15%), inadequate physical activity (66%), and obesity (2.3%). Factors such as male sex, urban residency, older age, being married or in a common-law relationship, and a higher income were associated with these unhealthy lifestyles. On the other hand, a higher educational status was associated with lower odds of these behaviors. Conclusion: In our analysis, we observed a higher prevalence of concurrent unhealthy lifestyles. Socio-demographic characteristics, such as sex, age, marital status, residence, income, and education, were found to correlate with individuals’ lifestyles. Consequently, tailored interventions are imperative to mitigate the burden of unhealthy lifestyles in Ethiopia.Yalemzewod Assefa Gelaw, Digsu N. Koye, Kefyalew Addis Alene, Kedir Y. Ahmed, Yibeltal Assefa, Daniel Asfaw Erku, Henok Getachew Tegegn, Azeb Gebresilassie Tesema, Berihun Megabiaw Zeleke, and Yohannes Adama Melak

    AMMI and GGE Biplot Analyses for Mega-Environment Identification and Selection of Some High-Yielding Oat (Avena sativa L.) Genotypes for Multiple Environments

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    This paper reports an evaluation of eleven oat genotypes in four environments for two consecutive years to identify high-biomass-yielding, stable, and broadly adapted genotypes in selected parts of Ethiopia. Genotypes were planted and evaluated with a randomized complete block design, which was repeated three times. The additive main effect and multiplicative interaction analysis of variances revealed that the environment, genotype, and genotype–environment interaction had a significant (p ≤ 0.001) influence on the biomass yield in the dry matter base (t ha−1). The interaction of the first and second principal component analysis accounted for 73.43% and 14.97% of the genotype according to the environment interaction sum of squares, respectively. G6 and G5 were the most stable and widely adapted genotypes and were selected as superior genotypes. The genotype-by-environment interaction showed a 49.46% contribution to the total treatment of sum-of-squares variation, while genotype and environment effects explained 34.94% and 15.60%, respectively. The highest mean yield was obtained from G6 (12.52 kg/ha), and the lowest mean yield was obtained from G7 (8.65 kg/ha). According to the additive main effect and multiplicative interaction biplot, G6 and G5 were high-yielding genotypes, whereas G7 was a low-yielding genotype. Furthermore, according to the genotype and genotype–environment interaction biplot, G6 was the winning genotype in all environments. However, G7 was a low-yielding genotype in all environments. Finally, G6 was an ideal genotype with a higher mean yield and relatively good stability. However, G7 was a poor-yielding and unstable genotype. The genotype, environment, and genotype x environment interaction had extremely important effects on the biomass yield of oats. The findings of the graphic stability methods (additive main effect and multiplicative interaction and the genotype and genotype–environment interaction) for identifying high-yielding and stable oat genotypes were very similar

    Epidemiology of Mycobacterium tuberculosis lineages and strain clustering within urban and peri-urban settings in Ethiopia

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    Background Previous work has shown differential predominance of certain Mycobacterium tuberculosis (M. tb) lineages and sub-lineages among different human populations in diverse geographic regions of Ethiopia. Nevertheless, how strain diversity is evolving under the ongoing rapid socio-economic and environmental changes is poorly understood. The present study investigated factors associated with M. tb lineage predominance and rate of strain clustering within urban and peri-urban settings in Ethiopia. Methods Pulmonary Tuberculosis (PTB) and Cervical tuberculous lymphadenitis (TBLN) patients who visited selected health facilities were recruited in the years of 2016 and 2017. A total of 258 M. tb isolates identified from 163 sputa and 95 fine-needle aspirates (FNA) were characterized by spoligotyping and compared with international M.tb spoligotyping patterns registered at the SITVIT2 databases. The molecular data were linked with clinical and demographic data of the patients for further statistical analysis. Results From a total of 258 M. tb isolates, 84 distinct spoligotype patterns that included 58 known Shared International Type (SIT) patterns and 26 new or orphan patterns were identified. The majority of strains belonged to two major M. tb lineages, L3 (35.7%) and L4 (61.6%). The observed high percentage of isolates with shared patterns (n = 200/258) suggested a substantial rate of overall clustering (77.5%). After adjusting for the effect of geographical variations, clustering rate was significantly lower among individuals co-infected with HIV and other concomitant chronic disease. Compared to L4, the adjusted odds ratio and 95% confidence interval (AOR; 95% CI) indicated that infections with L3 M. tb strains were more likely to be associated with TBLN [3.47 (1.45, 8.29)] and TB-HIV co-infection [2.84 (1.61, 5.55)]. Conclusion Despite the observed difference in strain diversity and geographical distribution of M. tb lineages, compared to earlier studies in Ethiopia, the overall rate of strain clustering suggests higher transmission and warrant more detailed investigations into the molecular epidemiology of TB and related factors

    Intimate partner violence and childhood health outcomes in 37 sub-Saharan African countries: an analysis of demographic health survey data from 2011 to 2022

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    Background Understanding the contribution of intimate partner violence (IPV) to childhood health outcomes (eg, morbidity and mortality) is crucial for improving child survival in sub-Saharan Africa. This comprehensive study aimed to explore the associations between maternal exposure to physical, sexual, or emotional violence and adverse childhood health outcomes in sub-Saharan Africa. Methods We analysed Demographic Health Survey datasets from 37 sub-Saharan African countries from 2011 to 2022. A generalised linear mixed model was used to examine the associations between maternal physical violence, sexual violence, or emotional violence, and early childhood health outcomes (eg, acute respiratory infection, diarrhoea, undernutrition, and child mortality). A random effects meta-analysis was used to calculate pooled odds ratios (ORs) for adverse childhood health outcomes. The odds of undernutrition and mortality were 55% and 58% higher among children younger than 5 years born to mothers who were exposed to physical and sexual violence, respectively. Findings 238 060 children younger than 5 years were included. Children whose mothers experienced physical violence (adjusted OR 1·33, 95% CI 1·29–1·42), sexual violence (1·47, 1·34–1·62), emotional violence (1·39, 1·32–1·47), or a combination of emotional and sexual violence (1·64, 1·20–2·22), or a combination of all the three forms of violence (1·88, 1·62–2·18) were associated with an increased odds of developing diarrhoeal disease. Similarly, children whose mothers experienced physical violence (1·43, 1·28–1·59), sexual violence (1·47, 1·34–1·62), emotional violence (1·39, 1·32–1·47), or a combination of emotional and sexual violence (1·48, 1·16–1·89), or a combination of all three forms of violence (1·66, 1·47–1·88) were positively associated with symptoms of acute respiratory infection. Interpretation We found a strong link between maternal exposure to IPV and health outcomes for children younger than 5 years in sub-Saharan Africa, with minor variations across countries. To address childhood morbidity and mortality attributed to IPV, interventions need to be tailored for specific countries. Burkina Faso, Burundi, Chad, Comoros, Gabon, Liberia, Nigeria, Sierra Leone, South Africa, and Uganda should be priority nations

    Global, regional, and national life expectancy, all-cause mortality, and cause-specific mortality for 249 causes of death, 1980–2015: a systematic analysis for the Global Burden of Disease Study 2015

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    Background Improving survival and extending the longevity of life for all populations requires timely, robust evidence on local mortality levels and trends. The Global Burden of Disease 2015 Study (GBD 2015) provides a comprehensive assessment of all-cause and cause-specific mortality for 249 causes in 195 countries and territories from 1980 to 2015. These results informed an in-depth investigation of observed and expected mortality patterns based on sociodemographic measures. Methods We estimated all-cause mortality by age, sex, geography, and year using an improved analytical approach originally developed for GBD 2013 and GBD 2010. Improvements included refinements to the estimation of child and adult mortality and corresponding uncertainty, parameter selection for under-5 mortality synthesis by spatiotemporal Gaussian process regression, and sibling history data processing. We also expanded the database of vital registration, survey, and census data to 14 294 geography–year datapoints. For GBD 2015, eight causes, including Ebola virus disease, were added to the previous GBD cause list for mortality. We used six modelling approaches to assess cause-specific mortality, with the Cause of Death Ensemble Model (CODEm) generating estimates for most causes. We used a series of novel analyses to systematically quantify the drivers of trends in mortality across geographies. First, we assessed observed and expected levels and trends of cause-specific mortality as they relate to the Socio-demographic Index (SDI), a summary indicator derived from measures of income per capita, educational attainment, and fertility. Second, we examined factors affecting total mortality patterns through a series of counterfactual scenarios, testing the magnitude by which population growth, population age structures, and epidemiological changes contributed to shifts in mortality. Finally, we attributed changes in life expectancy to changes in cause of death. We documented each step of the GBD 2015 estimation processes, as well as data sources, in accordance with Guidelines for Accurate and Transparent Health Estimates Reporting (GATHER). Findings Globally, life expectancy from birth increased from 61·7 years (95% uncertainty interval 61·4–61·9) in 1980 to 71·8 years (71·5–72·2) in 2015. Several countries in sub-Saharan Africa had very large gains in life expectancy from 2005 to 2015, rebounding from an era of exceedingly high loss of life due to HIV/AIDS. At the same time, many geographies saw life expectancy stagnate or decline, particularly for men and in countries with rising mortality from war or interpersonal violence. From 2005 to 2015, male life expectancy in Syria dropped by 11·3 years (3·7–17·4), to 62·6 years (56·5–70·2). Total deaths increased by 4·1% (2·6–5·6) from 2005 to 2015, rising to 55·8 million (54·9 million to 56·6 million) in 2015, but age-standardised death rates fell by 17·0% (15·8–18·1) during this time, underscoring changes in population growth and shifts in global age structures. The result was similar for non-communicable diseases (NCDs), with total deaths from these causes increasing by 14·1% (12·6–16·0) to 39·8 million (39·2 million to 40·5 million) in 2015, whereas age-standardised rates decreased by 13·1% (11·9–14·3). Globally, this mortality pattern emerged for several NCDs, including several types of cancer, ischaemic heart disease, cirrhosis, and Alzheimer's disease and other dementias. By contrast, both total deaths and age-standardised death rates due to communicable, maternal, neonatal, and nutritional conditions significantly declined from 2005 to 2015, gains largely attributable to decreases in mortality rates due to HIV/AIDS (42·1%, 39·1–44·6), malaria (43·1%, 34·7–51·8), neonatal preterm birth complications (29·8%, 24·8–34·9), and maternal disorders (29·1%, 19·3–37·1). Progress was slower for several causes, such as lower respiratory infections and nutritional deficiencies, whereas deaths increased for others, including dengue and drug use disorders. Age-standardised death rates due to injuries significantly declined from 2005 to 2015, yet interpersonal violence and war claimed increasingly more lives in some regions, particularly in the Middle East. In 2015, rotaviral enteritis (rotavirus) was the leading cause of under-5 deaths due to diarrhoea (146 000 deaths, 118 000–183 000) and pneumococcal pneumonia was the leading cause of under-5 deaths due to lower respiratory infections (393 000 deaths, 228 000–532 000), although pathogen-specific mortality varied by region. Globally, the effects of population growth, ageing, and changes in age-standardised death rates substantially differed by cause. Our analyses on the expected associations between cause-specific mortality and SDI show the regular shifts in cause of death composition and population age structure with rising SDI. Country patterns of premature mortality (measured as years of life lost [YLLs]) and how they differ from the level expected on the basis of SDI alone revealed distinct but highly heterogeneous patterns by region and country or territory. Ischaemic heart disease, stroke, and diabetes were among the leading causes of YLLs in most regions, but in many cases, intraregional results sharply diverged for ratios of observed and expected YLLs based on SDI. Communicable, maternal, neonatal, and nutritional diseases caused the most YLLs throughout sub-Saharan Africa, with observed YLLs far exceeding expected YLLs for countries in which malaria or HIV/AIDS remained the leading causes of early death. Interpretation At the global scale, age-specific mortality has steadily improved over the past 35 years; this pattern of general progress continued in the past decade. Progress has been faster in most countries than expected on the basis of development measured by the SDI. Against this background of progress, some countries have seen falls in life expectancy, and age-standardised death rates for some causes are increasing. Despite progress in reducing age-standardised death rates, population growth and ageing mean that the number of deaths from most non-communicable causes are increasing in most countries, putting increased demands on health systems. Funding Bill & Melinda Gates Foundation
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