Waterborne diseases as an indicator of health disparities: A nationwide study of WaSH related morbidity and mortality in Ecuador from 2011-2020

Article Subjects > Biomedicine
Subjects > Social Sciences
Ibero-american International University > Research > Articles and books Abierto Inglés Background Despite worldwide progress in terms of clean water supply, sanitation, and hygiene knowledge, some middle and most of low-income countries are still experiencing many diseases transmitted using unsafe water and the lack of sanitation. Methods To understand the impact of all waterborne diseases (WBD) registered in Ecuador, we performed an analysis of all cases and deaths related to WBD to compute incidence and mortality rates. Results We found that in Ecuador, mestizo people had the greatest morbidity rate (141/100,000) patient followed by indigenous (63/100,000) and self-determined white patients (21/100,000). However, in terms of mortality, indigenous population have a 790% increase in mortality rate (2.6 /100,000) when compared to self-determined white populations (0.29/100,000) or 176% more when compared to mestizos (0.94/100,000). This trend remains the same among children and the elderly who have higher mortality rates when compared to other ethnic groups. Conclusions In Ecuador, water borne diseases (WBD) are still a major public health problem. We found that younger children and elderly are more likely to be get sick and die due to water borne diseases. In terms of morbidity, mestizos reported the highest rate, while in terms of mortality, indigenous populations are the most affected, having the highest mortality among different ethnic groups. We hypostatize that reduced health care access is linked to fewer reporting incidence rates among indigenous populations but higher mortality rates. metadata Ortiz-Prado, Esteban and Simbaña-Rivera, Katherine and Cevallos-Sierra, Gabriel and Cevallos, Domenica and Lister, Alex and Fernandez-Naranjo, Raul and Ríos-Touma, Blanca and Vasconez, Jorge and Izquierdo Condoy, Juan Sebastian and Gomez-Barreno, Lenin mail UNSPECIFIED (2022) Waterborne diseases as an indicator of health disparities: A nationwide study of WaSH related morbidity and mortality in Ecuador from 2011-2020. Research square. (Unpublished)

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Abstract

Background Despite worldwide progress in terms of clean water supply, sanitation, and hygiene knowledge, some middle and most of low-income countries are still experiencing many diseases transmitted using unsafe water and the lack of sanitation. Methods To understand the impact of all waterborne diseases (WBD) registered in Ecuador, we performed an analysis of all cases and deaths related to WBD to compute incidence and mortality rates. Results We found that in Ecuador, mestizo people had the greatest morbidity rate (141/100,000) patient followed by indigenous (63/100,000) and self-determined white patients (21/100,000). However, in terms of mortality, indigenous population have a 790% increase in mortality rate (2.6 /100,000) when compared to self-determined white populations (0.29/100,000) or 176% more when compared to mestizos (0.94/100,000). This trend remains the same among children and the elderly who have higher mortality rates when compared to other ethnic groups. Conclusions In Ecuador, water borne diseases (WBD) are still a major public health problem. We found that younger children and elderly are more likely to be get sick and die due to water borne diseases. In terms of morbidity, mestizos reported the highest rate, while in terms of mortality, indigenous populations are the most affected, having the highest mortality among different ethnic groups. We hypostatize that reduced health care access is linked to fewer reporting incidence rates among indigenous populations but higher mortality rates.

Item Type: Article
Uncontrolled Keywords: waterborne diseases, water, sanitation, hygiene, disparities, inequalities
Subjects: Subjects > Biomedicine
Subjects > Social Sciences
Divisions: Ibero-american International University > Research > Articles and books
Date Deposited: 11 Jan 2023 23:30
Last Modified: 11 Jan 2023 23:30
URI: https://repositorio.unib.org/id/eprint/5375

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Influence of E-learning training on the acquisition of competences in basketball coaches in Cantabria

The main aim of this study was to analyse the influence of e-learning training on the acquisition of competences in basketball coaches in Cantabria. The current landscape of basketball coach training shows an increasing demand for innovative training models and emerging pedagogies, including e-learning-based methodologies. The study sample consisted of fifty students from these courses, all above 16 years of age (36 males, 14 females). Among them, 16% resided outside the autonomous community of Cantabria, 10% resided more than 50 km from the city of Santander, 36% between 10 and 50 km, 14% less than 10 km, and 24% resided within Santander city. Data were collected through a Google Forms survey distributed by the Cantabrian Basketball Federation to training course students. Participation was voluntary and anonymous. The survey, consisting of 56 questions, was validated by two sports and health doctors and two senior basketball coaches. The collected data were processed and analysed using Microsoft® Excel version 16.74, and the results were expressed in percentages. The analysis revealed that 24.60% of the students trained through the e-learning methodology considered themselves fully qualified as basketball coaches, contrasting with 10.98% of those trained via traditional face-to-face methodology. The results of the study provide insights into important characteristics that can be adjusted and improved within the investigated educational process. Moreover, the study concludes that e-learning training effectively qualifies basketball coaches in Cantabria.

Producción Científica

Josep Alemany Iturriaga mail josep.alemany@uneatlantico.es, Álvaro Velarde-Sotres mail alvaro.velarde@uneatlantico.es, Javier Jorge mail , Kamil Giglio mail ,

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Carotenoids Intake and Cardiovascular Prevention: A Systematic Review

Background: Cardiovascular diseases (CVDs) encompass a variety of conditions that affect the heart and blood vessels. Carotenoids, a group of fat-soluble organic pigments synthesized by plants, fungi, algae, and some bacteria, may have a beneficial effect in reducing cardiovascular disease (CVD) risk. This study aims to examine and synthesize current research on the relationship between carotenoids and CVDs. Methods: A systematic review was conducted using MEDLINE and the Cochrane Library to identify relevant studies on the efficacy of carotenoid supplementation for CVD prevention. Interventional analytical studies (randomized and non-randomized clinical trials) published in English from January 2011 to February 2024 were included. Results: A total of 38 studies were included in the qualitative analysis. Of these, 17 epidemiological studies assessed the relationship between carotenoids and CVDs, 9 examined the effect of carotenoid supplementation, and 12 evaluated dietary interventions. Conclusions: Elevated serum carotenoid levels are associated with reduced CVD risk factors and inflammatory markers. Increasing the consumption of carotenoid-rich foods appears to be more effective than supplementation, though the specific effects of individual carotenoids on CVD risk remain uncertain.

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Sandra Sumalla Cano mail sandra.sumalla@uneatlantico.es, Imanol Eguren García mail imanol.eguren@uneatlantico.es, Álvaro Lasarte García mail , Thomas Prola mail thomas.prola@uneatlantico.es, Raquel Martínez Díaz mail raquel.martinez@uneatlantico.es, Iñaki Elío Pascual mail inaki.elio@uneatlantico.es,

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StackIL10: A stacking ensemble model for the improved prediction of IL-10 inducing peptides

Interleukin-10, a highly effective cytokine recognized for its anti-inflammatory properties, plays a critical role in the immune system. In addition to its well-documented capacity to mitigate inflammation, IL-10 can unexpectedly demonstrate pro-inflammatory characteristics under specific circumstances. The presence of both aspects emphasizes the vital need to identify the IL-10-induced peptide. To mitigate the drawbacks of manual identification, which include its high cost, this study introduces StackIL10, an ensemble learning model based on stacking, to identify IL-10-inducing peptides in a precise and efficient manner. Ten Amino-acid-composition-based Feature Extraction approaches are considered. The StackIL10, stacking ensemble, the model with five optimized Machine Learning Algorithm (specifically LGBM, RF, SVM, Decision Tree, KNN) as the base learners and a Logistic Regression as the meta learner was constructed, and the identification rate reached 91.7%, MCC of 0.833 with 0.9078 Specificity. Experiments were conducted to examine the impact of various enhancement techniques on the correctness of IL-10 Prediction. These experiments included comparisons between single models and various combinations of stacking-based ensemble models. It was demonstrated that the model proposed in this study was more effective than singular models and produced satisfactory results, thereby improving the identification of peptides that induce IL-10.

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Salman Sadullah Usmani mail , Izaz Ahmmed Tuhin mail , Md. Rajib Mia mail , Md. Monirul Islam mail , Imran Mahmud mail , Carlos Eduardo Uc Ríos mail carlos.uc@unini.edu.mx, Henry Fabian Gongora mail henry.gongora@uneatlantico.es, Imran Ashraf mail , Md. Abdus Samad mail ,

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Roman urdu hate speech detection using hybrid machine learning models and hyperparameter optimization

With the rapid increase of users over social media, cyberbullying, and hate speech problems have arisen over the past years. Automatic hate speech detection (HSD) from text is an emerging research problem in natural language processing (NLP). Researchers developed various approaches to solve the automatic hate speech detection problem using different corpora in various languages, however, research on the Urdu language is rather scarce. This study aims to address the HSD task on Twitter using Roman Urdu text. The contribution of this research is the development of a hybrid model for Roman Urdu HSD, which has not been previously explored. The novel hybrid model integrates deep learning (DL) and transformer models for automatic feature extraction, combined with machine learning algorithms (MLAs) for classification. To further enhance model performance, we employ several hyperparameter optimization (HPO) techniques, including Grid Search (GS), Randomized Search (RS), and Bayesian Optimization with Gaussian Processes (BOGP). Evaluation is carried out on two publicly available benchmarks Roman Urdu corpora comprising HS-RU-20 corpus and RUHSOLD hate speech corpus. Results demonstrate that the Multilingual BERT (MBERT) feature learner, paired with a Support Vector Machine (SVM) classifier and optimized using RS, achieves state-of-the-art performance. On the HS-RU-20 corpus, this model attained an accuracy of 0.93 and an F1 score of 0.95 for the Neutral-Hostile classification task, and an accuracy of 0.89 with an F1 score of 0.88 for the Hate Speech-Offensive task. On the RUHSOLD corpus, the same model achieved an accuracy of 0.95 and an F1 score of 0.94 for the Coarse-grained task, alongside an accuracy of 0.87 and an F1 score of 0.84 for the Fine-grained task. These results demonstrate the effectiveness of our hybrid approach for Roman Urdu hate speech detection.

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Performance of the 4C and SEIMC scoring systems in predicting mortality from onset to current COVID-19 pandemic in emergency departments

The evolution of the COVID-19 pandemic has been associated with variations in clinical presentation and severity. Similarly, prediction scores may suffer changes in their diagnostic accuracy. The aim of this study was to test the 30-day mortality predictive validity of the 4C and SEIMC scores during the sixth wave of the pandemic and to compare them with those of validation studies. This was a longitudinal retrospective observational study. COVID-19 patients who were admitted to the Emergency Department of a Spanish hospital from December 15, 2021, to January 31, 2022, were selected. A side-by-side comparison with the pivotal validation studies was subsequently performed. The main measures were 30-day mortality and the 4C and SEIMC scores. A total of 27,614 patients were considered in the study, including 22,361 from the 4C, 4,627 from the SEIMC and 626 from our hospital. The 30-day mortality rate was significantly lower than that reported in the validation studies. The AUCs were 0.931 (95% CI: 0.90–0.95) for 4C and 0.903 (95% CI: 086–0.93) for SEIMC, which were significantly greater than those obtained in the first wave. Despite the changes that have occurred during the coronavirus disease 2019 (COVID-19) pandemic, with a reduction in lethality, scorecard systems are currently still useful tools for detecting patients with poor disease risk, with better prognostic capacity.

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de Santos Castro