CRIS

Permanent URI for this communityhttps://cris-udd.scimago.es/handle/123456789/1

Browse

Search Results

Now showing 1 - 5 of 5

Some of the metrics are blocked by your
consent settings
Drug-Resistant Tuberculosis in Prisons of Latin America and the Caribbean: A Critical Reflection on Structural Challenges and Gaps
(2026)
Torres Rodriguez, Ariel Antonio
;
Sánchez Redrobán, José
;
Trujillo Lopez, Gisselle
Drug-resistant tuberculosis (DR-TB) represents a major public health threat, particularly in the prisons of Latin America and the Caribbean, where rates are up to 40 times higher than those observed in the general population. These facilities act as community amplifiers due to overcrowding, poor ventilation, diagnostic delays, and treatment discontinuity. This study offers a critical reflection on the magnitude, determinants, and implications of DR-TB in regional penitentiary contexts. A reflective analytical review was conducted in PubMed, Scopus, Web of Science, SciELO, and LILACS, complemented by WHO and PAHO reports, prioritising studies from 2019 to 2024. The findings reveal MDR-TB and pre-extensively drug-resistant (pre-XDR) outbreaks in Peru, Paraguay, and the Dominican Republic, as well as community transmission linked to prisons in Brazil and Colombia. Persistent gaps remain in systematic screening, drug susceptibility testing coverage, and post-release follow-up. Scientific production continues to be uneven and predominantly biomedical, with limited consideration of social and human rights determinants. DR-TB in prisons reflects the structural deficiencies of health and justice systems; its control requires intersectoral policies, genomic surveillance, and strategies that ensure early diagnosis, treatment continuity, and dignified detention conditions. © 2026 by the authors.
6
Some of the metrics are blocked by your
consent settings
Dietary Diversity, Dietary Patterns, and Cardiometabolic Health in University Students: A Cross-Sectional Study
(2026)
Diana Fonseca-Pérez
;
Ludwig Álvarez-Córdova
;
Cecilia Arteaga-Pazmiño
;
Víctor Sierra-Nieto
;
Cagua Ordoñez, Jaen
Cardiometabolic risk is increasingly observed in young adults, particularly during university years, and is not limited to individuals with elevated body mass index. Emerging evidence highlights the presence of normal weight obesity—characterized by excess adiposity and unfavorable body composition despite normal BMI—which may confer early metabolic vulnerability. Dietary diversity is often promoted as a marker of dietary adequacy; however, its relationship with adiposity, body composition, and muscular health remains inconsistent, particularly in Latin American populations. Moreover, few studies have directly contrasted dietary diversity indicators with empirically derived dietary patterns in relation to cardiometabolic and functional outcomes. Objective: To examine the associations between dietary diversity, dietary patterns, and indicators of adiposity, muscular strength, and relative muscle mass in Ecuadorian university students. Methods: A cross-sectional study was conducted among 349 undergraduate students aged 18–26 years enrolled in health sciences programs in Ecuador. Dietary intake was assessed using a validated food frequency questionnaire. Dietary diversity was quantified using the Food and Agriculture Organization’s Individual Dietary Diversity Score, while dietary patterns were identified through principal component analysis followed by k-means clustering. Outcomes included excess body weight, relative muscle mass assessed by bioelectrical impedance analysis, and handgrip strength. Multivariable Poisson and linear regression models were fitted, adjusting for age, sex, academic program, physical activity level, and pre-existing conditions. Results: Despite their young age and low prevalence of diagnosed disease, approximately one-third of the participants exhibited markers of early cardiometabolic risk, including excess body weight and central adiposity. Higher dietary diversity was independently associated with a higher prevalence of excess body weight (adjusted prevalence ratio per one-unit increase in IDDS: 1.17; 95% CI: 1.06–1.30) and with greater relative muscle mass (adjusted β = 0.13; 95% CI: 0.05–0.22), whereas no association was observed with handgrip strength. In contrast, dietary patterns derived from multivariate analysis showed no significant associations with adiposity, muscular strength, or relative muscle mass after adjustment. Conclusions: In this young adult population, dietary diversity captured aspects of overall dietary exposure associated with both increased adiposity and greater lean mass, but not with muscular strength. Empirically derived dietary patterns demonstrated limited discriminatory capacity, likely reflecting dietary homogeneity within the cohort. These findings indicate that dietary diversity alone does not necessarily reflect diet quality and underscore the importance of interpreting diversity metrics alongside indicators of food quality, energy density, and body composition when evaluating early cardiometabolic risk in contemporary food environments.
6
Some of the metrics are blocked by your
consent settings
Using explainable artificial intelligence for mapping health vulnerability: Interaction-based analysis of multiple sources of data in Latin America
(2025)
Susana Alexandra Arias Tapia
;
Andrea Suárez López
;
Jadán Guerrero, Janio
Even as there are extensive genetic linkages across Latin America, local health risk is influenced by a host of interdependent factors that include (a) ethnic heterogeneity, (b) geographical isolation, and (c) disproportionate access to healthcare. The article presents a new explainable artificial intelligence (XAI) model for mapping and interpreting health vulnerability, combining several open-access datasets, such as disease prevalence, medical supply, and genetic ancestry profiles. We introduce a compound Interaction Index, as the product of ethnic diversity (E), inverted medical access (1 − M), and altitude (A), to quantify compounded structural and biological risk factors. Applying supervised learning models (F1 = 0.596 for SVM, F1 = 0.571 for gradient boosting, and logistic regression), in combination with unsupervised clustering and interpretable classification trees, we detect the high-risk regions with high diversity, low access, and mid-to-high altitude. This transparent and scalable methodology for equitable public health planning illuminates such ‘clusters of vulnerability’ which might remain hidden amid aggregate data.
10
Some of the metrics are blocked by your
consent settings
Evaluating Web Accessibility in Countries Included in the Latin American Artificial Intelligence Index
(2025)
Patricia Acosta-Vargas
;
Belén Salvador-Acosta
;
Mauricio Loachamín-Valencia
;
Marcos Chacón-Castro
;
Jadán Guerrero, Janio
This study examines the relationship between the Latin American Artificial Intelligence Index (ILIA) and the Web Accessibility Index (WAIN) in 19 Latin American countries to evaluate how technological innovation aligns with digital inclusivity. Results reveal notable disparities: Uruguay, Chile, and Brazil excel in both indices, whereas Jamaica and Venezuela face critical challenges. Significantly, high scores in artificial intelligence adoption do not always correlate with improved web accessibility, underscoring the need for integrated strategies that prioritize compliance with the Web Content Accessibility Guidelines (WCAG) 2.2 and inclusive design. The research highlights accessibility as a fundamental pillar for sustainable digital ecosystems and equitable access to technology. Limitations include the regional focus on Latin America, the reliance on automated tools, and the dynamic nature of technology. Future research should incorporate longitudinal analyses, user-centered evaluations, and comparative studies across diverse regions to develop comprehensive frameworks that are grounded in empirical evidence. By aligning technological progress with inclusivity, this study emphasizes the importance of fostering sustainable and accessible digital environments. Recommendations include adopting accessibility standards in early development stages, enhancing public policy, and prioritizing universal design. These steps are essential to achieving the Sustainable Development Goals (SDGs) related to reducing inequalities and promoting inclusive institutions. This work is a foundation for advancing equitable digital ecosystems in Latin America.
13 2
Some of the metrics are blocked by your
consent settings
Drivers for the Intention to Buy Wearables in a Latin American Country
(2025)
Cruz Cárdenas, Jorge
;
Andrés Palacio-Fierro
;
Ramos Galarza, Carlos
;
Guacyra Nascimento-Queiroz
The daily conduct of millions of people worldwide demonstrates the profound impact of technology on contemporary civilization. Wearables are a prominent example of this transformation. Due to their significance, companies in this sector are considering nearly tripling their sales of these devices by 2028. However, understanding the factors that influence user adoption has become crucial. Most studies have been conducted in developed countries, so this research aims to explore these factors in a developing country to determine if there are differences compared to developed nations. The study uses a personal survey with a sample of 360 individuals and employs a multiple approach for the prediction model. Results show that an innovative attitude and hedonic motivation are key drivers in predicting the intention to buy wearable technology devices. The main conclusion of this study is that certain factors do not contribute to explaining the intention to purchase wearables in developing countries, as they do in higher-income nations. This finding suggests a need to adjust marketing strategies to better target Latin American markets
17

CRIS

Browse

Filters

Settings

Sort By

Results per page

Search Results