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Environmental exposures and gene-exposure interactions are the major causes of some diseases. Early-life exposome studies are needed to elucidate the role of environmental exposures and their complex interactions with biological mechanisms involved in childhood health. This study aimed to determine the contribution of early-life exposome to DNA damage and the modifying effect of genetic polymorphisms involved in air pollutants metabolism, antioxidant defense, and DNA repair. We conducted a cohort study in 416 Colombian children under five years. Blood samples at baseline were collected to measure DNA damage by the Comet assay and to determine GSTT1, GSTM1, CYP1A1, H2AX, OGG1, and SOD2 genetic polymorphisms. The exposome was estimated using geographic information systems, remote sensing, LUR models, and questionnaires. The association exposome-DNA damage was estimated using the Elastic Net linear regression with log link. Our results suggest that exposure to PM2.5 one year before the blood draw (BBD) (0.83, 95 %CI: 0.76; 0.91), soft drinks consumption (0.94, 0.89; 0.98), and GSTM1 null genotype (0.05, 0.01; 0.36) diminished the DNA damage, whereas exposure to PM2.5 one-week BBD (1.18, 1.06; 1.32), NO2 lag-5 days BBD (1.27, 1.18; 1.36), in-house cockroaches (1.10, 1.00; 1.21) at the recruitment, crowding at home (1.34, 1.08; 1.67) at the recruitment, cereal consumption (1.11, 1.04; 1.19) and H2AX (AG/GG vs. AA) (1.44, 1.11; 1.88) increased the DNA damage. The interactions between H2AX (AG/GG vs. AA) genotypes with crowding and PM2.5 one week BBD, GSTM1 (null vs. present) with humidity at the first year of life, and OGG1 (SC/CC vs. SS) with walkability at the first year of life were significant. The early-life exposome contributes to elucidating the effect of environmental exposures on DNA damage in Colombian children under five years old. The exposome-DNA damage effect appears to be modulated by genetic variants in DNA repair and antioxidant defense enzymes.

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Exposome studies are advancing in high-income countries to understand how multiple environmental exposures impact health. However, there is a significant research gap in low- and middle-income and tropical countries. We aimed to describe the spatiotemporal variation of the external exposome, its correlation structure between and within exposure groups, and its dimensionality. A one-year follow-up cohort study of 506 children under 5 in two cities in Colombia was conducted to evaluate asthma, acute respiratory infections, and DNA damage. We examined 48 environmental exposures during pregnancy and 168 during childhood in eight exposure groups, including atmospheric pollutants, natural spaces, meteorology, built environment, traffic, indoor exposure, and socioeconomic capital. The exposome was estimated using geographic information systems, remote sensing, spatiotemporal modeling, and questionnaires. The median age of children at study entry was 3.7 years (interquartile range: 2.9-4.3). Air pollution and natural spaces exposure decreased from pregnancy to childhood, while socioeconomic capital increased. The highest median correlations within exposure groups were observed in meteorology (r = 0.85), traffic (r = 0.83), and atmospheric pollutants (r = 0.64). Important correlations between variables from different exposure groups were found, such as atmospheric pollutants and meteorology (r = 0.76), natural spaces (r = -0.34), and the built environment (r = 0.53). Twenty principal components explained 70%, and 57 explained 95% of the total variance in the childhood exposome. Our findings show that there is an important spatiotemporal variation in the exposome of children under 5. This is the first characterization of the external exposome in urban areas of Latin America and highlights its complexity, but also the need to better characterize and understand the exposome in order to optimize its analysis and applications in local interventions aimed at improving the health conditions and well-being of the child population and contributing to environmental health decision-making.

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Rapidly urbanizing cities in Latin America experience high levels of air pollution which are known risk factors for population health. However, the estimates of long-term exposure to air pollution are scarce in the region. We developed intraurban land use regression (LUR) models to map long-term exposure to fine particulate matter (PM2.5) and nitrogen dioxide (NO2) in the five largest cities in Colombia. We conducted air pollution measurement campaigns using gravimetric PM2.5 and passive NO2 sensors for 2 weeks during both the dry and rainy seasons in 2021 in the cities of Barranquilla, Bucaramanga, Bogotá, Cali, and Medellín, and combined these data with geospatial and meteorological variables. Annual models were developed using multivariable spatial regression models. The city annual PM2.5 mean concentrations measured ranged between 12.32 and 15.99 µg/m3 while NO2 concentrations ranged between 24.92 and 49.15 µg/m3. The PM2.5 annual models explained 82% of the variance (R2) in Medellín, 77% in Bucaramanga, 73% in Barranquilla, 70% in Cali, and 44% in Bogotá. The NO2 models explained 65% of the variance in Bucaramanga, 57% in Medellín, 44% in Cali, 40% in Bogotá, and 30% in Barranquilla. Most of the predictor variables included in the models were a combination of specific land use characteristics and roadway variables. Cross-validation suggests that PM2.5 outperformed NO2 models. The developed models can be used as exposure estimate in epidemiological studies, as input in hybrid models to improve personal exposure assessment, and for policy evaluation.

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Este trabajo tiene como objetivo presentar una mirada global de la aplicabilidad de los modelos de análisis multinivel en el ámbito de la investigación sanitaria. Ofrece información sobre los fundamentos teóricos, metodológicos y estadísticos y, además, menciona los pasos básicos para la construcción de estos modelos, y da ejemplos de su uso, según la estructura jerárquica de los datos. Cabe resaltar que, antes de utilizar estos modelos, se requiere contar con un soporte teórico sobre la necesidad de uso y una valoración estadística que dé cuenta del porcentaje de varianza explicada por el efecto de agrupación de las observaciones. Los requisitos para llevar a cabo este tipo de análisis dependen de condiciones especiales como el tipo de variables, la cantidad de unidades por nivel o el tipo de estructura jerárquica. Se concluye que los modelos de análisis multinivel son una herramienta útil para lograr la integración de información, dadas la complejidad de las relaciones y las interacciones que determinan la mayoría de las condiciones de salud, incluida la pérdida de independencia entre las unidades de observación.

This topic review aims to present a global vision of multilevel analysis models' applicability to health research, explaining its theoretical, methodological, and statistical foundations. We describe the basic steps to build these models and examples of their application according to the data hierarchical structure. It ir worth noticing that before using these models, researchers must have a rationale for needing them, and a statistical evaluation accounting for the variance percentage explained by the observations grouping effect. The requirements to conduct this type of analysis depends on special conditions such as the type of variables, the number of units per level, or the type of hierarchical structure. We conclude that multilevel analysis models are a useful tool to integrate information, considering the complexity of the relationships and interactions involved in most health conditions, including the loss of independence between observation units.

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Introducción: Colombia es uno de los países con mayor número de casos de COVID-19 en América Latina y el Caribe. Los gobiernos no pueden trabajar solos en una crisis de gran intensidad, por lo que las alianzas y la colaboración Gobierno-academia toman un valor preponderante. Objetivo: Sistematizar la experiencia del trabajo colaborativo que se realizó entre actores académicos de la región y las autoridades de salud del departamento de Santander, Colombia, en el marco de la emergencia sanitaria por COVID-19 durante 2020-2021. Metodología: A partir de la sistematización de experiencias y desde el enfoque crítico social se realizó un abordaje cualitativo con ocho actores clave del sector académico y de la autoridad en salud que participaron activamente en la alianza. Se hizo una revisión documental y se realizaron entrevistas semiestructuradas. Resultados: Una vez declarada la emergencia sanitaria, de manera rápida se conformaron dos grupos de trabajo colaborativo, uno entre academia y actores gubernamentales del municipio de Bucaramanga y otro entre academia y actores gubernamentales departamentales; ambos grupos se conformaron de manera voluntaria, pero se diferenciaron en su forma de organización. El trabajo colaborativo y voluntario brindó apoyo a las autoridades en salud, principalmente en la fase de preparación para afrontar la pandemia, traducción y difusión del conocimiento, vigilancia epidemiológica y actividades de fortalecimiento de la capacidad de respuesta. Conclusiones: El apoyo brindado por el equipo colaborativo fue muy proliferativo en actividades e intervenciones, no obstante, se presentaron dificultades y una de ellas fue que un número importante de sus recomendaciones no fueron atendidas por las autoridades sanitarias. Las dificultades presentadas no son diferentes a las ya reportadas en otras emergencias de salud pública, por lo que se requiere continuar fortaleciendo las relaciones Gobierno-academia para que se pueda trazar de manera proactiva una agenda que contribuya a superar las limitaciones que se reportan en este trabajo.

Introduction: Colombia is one of the countries with the highest number of COVID-19 cases in Latin America and the Caribbean. In a health crisis of high intensity, governments cannot work alone, so alliances and collaboration between Government and academia take on a preponderant value. Objective: Systematize the experience of the collaborative work carried out between academic actors in the region and the health authorities from the Department of Santander, Colombia in the framework of the health emergency due to COVID-19 during 2020-2021. Methods: Based on the systematization of experiences and from the critical social approach, a qualitative approach was carried out with eight key actors from the academic sector and the health authority that actively participated in the alliance. Documentary review and semi-structured interviews were conducted. Results: Once the health emergency was declared, two collaborative working groups were quickly formed, one between academia and government actors of the municipality of Bucaramanga and another between academia and departmental government actors; both groups were formed voluntarily but differed in their form of organization. The collaborative and voluntary work provided support to health authorities mainly in the preparation phase to face the pandemic, knowledge translation and dissemination, epidemiological surveillance, and response capacity-building activities. Conclusions: The support provided by the collaborative team was very proliferative in activities and interventions; however, difficulties occurred and one of them was that a significant number of their recommendations were not addressed by the health authorities. The difficulties presented are not different from those already reported in other public health emergencies, so it is necessary to continue strengthening the relations between Government-Academia, so that they can proactively draw up an agenda that contributes to overcoming the limitations that are reported in this work.

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This topic review aims to present a global vision of multilevel analysis models' applicability to health research, explaining its theoretical, methodological, and statistical foundations. We describe the basic steps to build these models and examples of their application according to the data hierarchical structure. It ir worth noticing that before using these models, researchers must have a rationale for needing them, and a statistical evaluation accounting for the variance percentage explained by the observations grouping effect. The requirements to conduct this type of analysis depends on special conditions such as the type of variables, the number of units per level, or the type of hierarchical structure. We conclude that multilevel analysis models are a useful tool to integrate information, considering the complexity of the relationships and interactions involved in most health conditions, including the loss of independence between observation units.

Este trabajo tiene como objetivo presentar una mirada global de la aplicabilidad de los modelos de análisis multinivel en el ámbito de la investigación sanitaria. Ofrece información sobre los fundamentos teóricos, metodológicos y estadísticos y, además, menciona los pasos básicos para la construcción de estos modelos, y da ejemplos de su uso, según la estructura jerárquica de los datos. Cabe resaltar que, antes de utilizar estos modelos, se requiere contar con un soporte teórico sobre la necesidad de uso y una valoración estadística que dé cuenta del porcentaje de varianza explicada por el efecto de agrupación de las observaciones. Los requisitos para llevar a cabo este tipo de análisis dependen de condiciones especiales como el tipo de variables, la cantidad de unidades por nivel o el tipo de estructura jerárquica. Se concluye que los modelos de análisis multinivel son una herramienta útil para lograr la integración de información, dadas la complejidad de las relaciones y las interacciones que determinan la mayoría de las condiciones de salud, incluida la pérdida de independencia entre las unidades de observación.

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The participation of civil society is essential for environmental health policies to be accepted. The objective of this study was to know the perceptions of government officials, members of civil society, and academics about environmental health problems and its governance in the Bucaramanga Metropolitan Area, Colombia. In the region, there is a strong citizens movement that defends the moorland ecosystem (páramo) as a source of drinking water for large-scale mining projects. A multi-method study was conducted, including the review of newspaper and scientific articles, a citizens survey, and interviews and focus groups with identified key stakeholders. The findings indicate that government officials prioritize their actions on issues related to air and water pollution and environmental education. In contrast, citizens prioritize water availability from the moorland ecosystem. There are some advances in the management of environmental health, mainly related to greater citizen awareness. Contrary perceptions among government officials, academics, and civil society prevent adequate prioritization of environmental health problems. Participation of civil society is absent in activities related to environmental governance. An ongoing citizens science experience engaging high school students and the academy can be the first meeting point with government officials in the pathway to improve the environmental governance in the territory. The participation of civil society in the environmental health governance must be enforced to broaden the issues of interest and prioritize the activities in short- and long-term policy planning.

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We assessed the relationship between the altitude of municipalities and the incidence, mortality, and fatality from COVID-19 and excess of mortality in Colombia between 2020 and 2022. We conducted an ecologic study including all 1122 municipalities in Colombia and used categories of altitude as main independent variable. We fit multivariable regression models for incidence, mortality, fatality rates, and excess of mortality controlling for several variables at municipality level. There was a higher incidence rate, similar mortality rate and lower case-fatality rate for COVID-19 during 2020-2022 in municipalities in the upper category of altitude (>=2500 masl) compared to the lower category (<1000 masl). The excess of mortality was lower but not statistically different in municipalities in the upper category of altitude, and significantly lower in the intermediate altitude category compared to the lowlands. Our findings provide evidence that municipalities with high altitude had similar mortality rate, and lower case-fatality rate and excess of mortality for COVID-19 compared to lowlands in Colombia.

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Anthropogenic and natural sources contribute to chemical mixtures in air, water, and soil, posing potential risks to the environment and human health. To understand the interplay between element profiles in the human body, geographical location, and associated economic activities, we carried out an observational analytic cross-sectional study. The study recruited 199 participants from three municipalities, two of which had gold-mining as their primary economic activity, while the other was dedicated to agricultural and other local activities not related to mining. The concentrations of a total of 30 elements in human hair samples and 21 elements in environmental soil samples were measured using various spectrometry techniques. Unsupervised clustering analysis using Self-Organizing Maps was applied to human hair samples to analyze element concentrations. Distinct clusters of individuals were identified based on their hair element profiles, which were mapped to geographical location and economic activities. While higher levels of heavy metals (Ag, As, Hg, and Pb) were observed in individuals engaged in mining activities in certain clusters, individuals in agricultural areas show higher concentrations of elements found in pesticides (Ba and Sr). However, the elemental composition of hair is influenced not only by the anthropogenic activities but also by the inherent geological context where people live. Our findings highlight the significance of accounting for environmental factors when evaluating human health risks, as the intricate mixture of elements can yield valuable insights for targeted health interventions.

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The COVID-19 pandemic highlighted the importance of strengthening collaborations between academia and government. The development and maintenance of these collaborative relationships is a complex and dynamic process, particularly during public health emergencies. This study was aimed at identifying and analysing factors that acted as barriers and facilitators in the collaboration process between academia and government during the COVID-19 pandemic in the five largest cities in Colombia. The study used a qualitative approach based on the systematization of experiences. A total of 25 semi-structured interviews were conducted with local actors from government and academia during 2021. Participants identified a variety of situations that involved individual, institutional and relational factors that acted as barriers and facilitators, and which have been previously reported in other countries and contexts not related to pandemics. Based on participant reports, two additional factors emerged, one corresponding to situations related to the pandemic management process itself and another related to structural or systemic conditions that involved government processes and the Colombian health system. Despite the challenges posed by the pandemic, the health emergency brought about shared feelings of local commitment and a willingness to work through interdisciplinary teams to address the pandemic with the least adverse effects on the community. Other facilitators of the collaborative process that were recognized were the importance of timely access to data and transparent analyses, as well as government decisions being informed by the perspectives of academics. The main barriers identified by both actors were excessive centralization of the pandemic's management and the need for rapid decision-making processes under high levels of uncertainty. In addition, the fragmentation of services in the health system posed a barrier to the interventions that were suggested by the collaborative work. Our results suggest that government-academia collaborations should be implemented as ongoing participatory processes integrating various sectors, actors and disciplines.

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The exposure to chemical mixtures is a problem of concern in developing countries and it is well known that the kidney is the major target organ for toxic elements. This cross-sectional study aimed to estimate the individual and composite mixture effect of a large number of chemical elements on kidney function in gold-mining and surrounding non-mining populations in northeast Colombia. We measured concentrations of 36 chemical elements in hair as indicators of chronic exposure from 199 adult participants. We estimated the effect of exposure to mixtures of chemical elements on estimated glomerular filtration rate (eGFR) using weighted quantile sum regression (WQS). The WQS index of the mixture was associated with reduced eGFR (Coefficient -2.42; 95%CI: -4.69, -0.16) being Be, Cd, Pb, As, and Mn, the principal contributors of the toxic mixture. Mining activities and Hg concentration were not associated with decreased kidney function. Our results suggest that complex mixtures of chemical elements, mainly heavy metals, act as nephrotoxic in these populations and therefore the analysis of chemical element mixtures is a better approach to identify environmental and occupational chemical risks for kidney damage.

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BACKGROUND: Air pollution contains a mixture of different pollutants from multiple sources. However, the interaction of these pollutants with other environmental exposures, as well as their harmful effects on children under five in tropical countries, is not well known. OBJECTIVE: This study aims to characterize the external exposome (ambient and indoor exposures) and its contribution to clinical respiratory and early biological effects in children. MATERIALS AND METHODS: A cohort study will be conducted on children under five (n = 500) with a one-year follow-up. Enrolled children will be followed monthly (phone call) and at months 6 and 12 (in person) post-enrolment with upper and lower Acute Respiratory Infections (ARI) examinations, asthma development, asthma control, and genotoxic damage. The asthma diagnosis will be pediatric pulmonologist-based and a standardized protocol will be used. Exposure, effect, and susceptibility biomarkers will be measured on buccal cells samples. For environmental exposures PM2.5 will be sampled, and questionnaires, geographic information, dispersion models and Land Use Regression models for PM2.5 and NO2 will be used. Different statistical methods that include Bayesian and machine learning techniques will be used for the ambient and indoor exposures-and outcomes. This study was approved by the ethics committee at Universidad Pontificia Bolivariana. EXPECTED STUDY OUTCOMES/FINDINGS: To estimate i) The toxic effect of particulate matter transcending the approach based on pollutant concentration levels; ii) The risk of developing an upper and lower ARI, based on different exposure windows; iii) A baseline of early biological damage in children under five, and describe its progression after a one-year follow-up; and iv) How physical and chemical PM2.5 characteristics influence toxicity and children's health.

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Mortality inequalities have been described across Latin American countries, but less is known about inequalities within cities, where most populations live. We aimed to identify geographic and socioeconomic inequalities in mortality within the urban areas of four main cities in Colombia. We analyzed mortality due to non-violent causes of diseases in adults between 2015 and 2019 using census sectors as unit of analysis in Barranquilla, Bogotá, Cali, and Medellín. We calculated smoothed Bayesian mortality rates as main health outcomes and used concentration indexes (CInd) for assessing inequalities using the multidimensional poverty index (MPI) as the socioeconomic measure. Moran eigenvector spatial filters were calculated to capture the spatial patterns of mortality and then used in multivariable models of the association between mortality rates and quintiles of MPI. Social inequalities were evident but not consistent across cities. The most disadvantaged groups showed the highest mortality rates in Cali. Geographic inequalities in mortality rates, regardless of the adults and poverty distribution, were identified in each city, suggesting that other social, environmental, or individual conditions are impacting the spatial distribution of mortality rates within the four cities.

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Introducción. El cáncer de mama es el tipo de cáncer que genera más muertes en mujeres en el mundo. Aunque se reconoce el aporte de factores genéticos, hormonales y de estilos de vida como sus principales causas, las hipótesis que señalan que la contaminación del ambiente juega un papel importante en su desarrollo, han tomado mucha fuerza en los últimos años. Estas hipótesis surgen debido a que el aumento en la incidencia del cáncer de mama coincide con procesos de industrialización, además de mayor presencia en regiones urbanas y con altos niveles de contaminación. El objetivo de este artículo fue consolidar información sobre los mecanismos fisiopatológicos que puedan explicar la relación entre cáncer de mama y la contaminación por material particulado. Metodología. Se realizó una búsqueda de literatura en PubMed, Google Académico y Epistemonikos para documentos publicados sobre el tema desde enero de 2016 hasta el 3 de agosto de 2022. Resultados. Se encontró que algunos de los mecanismos que podrían explicar dicha relación incluyen: alteraciones endocrinas que favorecen cambios hormonales, induciendo el crecimiento mamario; cambios en las características histológicas del tejido normal, como involución reducida de unidades lobulares ductales terminales; formación de aductos de hidrocarburos aromáticos policíclicos-ácido desoxirribonucleico (HAP-ADN), con mutación específica del gen TP53; activación de la proliferación en la línea celular MCF-7; y, alteraciones en la metilación del ADN. Conclusión. Si bien órganos distales como la mama no son la primera entrada de los contaminantes ambientales al cuerpo, estos sí pueden verse afectados tras la exposición a largo plazo, a través de diferentes mecanismos de disrupción endocrina y daño al ADN principalmente

Breast cancer is the type of cancer that causes the most deaths in women worldwide. Although the contribution of genetic, hormonal and lifestyle factors are recognized as its main causes, the hypotheses that indicate that environmental pollution has an important role in its development have taken on great strength during the last years. These hypotheses are based on the increase in the incidence of breast cancer that coincides with industrialization processes, in addition to its greater presence in urban regions with high levels of pollution. The aim of this study was to consolidate information on the pathophysiological mechanisms that can explain the relationship between breast cancer and air pollution by particulate matter. Methodology. A literature search was carried out in PubMed, Google Scholar and Epistemonikos for documents published on this topic from January 2016 until August 3rd 2022. Results. Some of the mechanisms that could explain this association include endocrine alterations that favor hormonal changes, inducing breast growth; changes in the histological characteristics of normal tissue such as reduced involution of terminal duct lobular units; formation of polycyclic aromatic hydrocarbons-deoxyribonucleic acid (PAH-DNA) adducts, with specific mutation of the TP53 gene; an increase in cell proliferation in the MCF-7 cell line; and alterations in DNA methylation. Conclusion. Although distal organs such as the breast are not the entry site of environmental pollutants into the body, they can be affected after prolonged exposure, mainly through different mechanisms of endocrine disruption and DNA damage

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OBJECTIVE: To compare estimates of spatiotemporal variations of surface PM2.5 concentrations in Colombia from 2014 to 2019 derived from two global air quality models, as well as to quantify the avoidable deaths attributable to the long-term exposure to concentrations above the current and projected Colombian standard for PM2.5 annual mean at municipality level. METHODS: We retrieved PM2.5 concentrations at the surface level from the ACAG and CAMSRA global air quality models for all 1,122 municipalities, and compare 28 of them with available concentrations from monitor stations. Annual mortality data 2014-2019 by municipality of residence and pooled effect measures for total, natural and specific causes of mortality were used to calculate the number of annual avoidable deaths and years of potential life lost (YPLL) related to the excess of PM2.5 concentration over the current mean annual national standard of 25 µg/m3 and projected standard of 15 µg/m3. RESULTS: Compared to surface data from 28 municipalities with monitoring stations in 2019, ACAG and CAMSRA models under or overestimated annual mean PM2.5 concentrations. Estimations from ACAG model had a mean bias 1,7 µg/m3 compared to a mean bias of 4,7 µg/m3 from CAMSRA model. Using ACAG model, estimations of total nationally attributable deaths to PM2.5 exposure over 25 and 15 µg/m3 were 142 and 34,341, respectively. Cardiopulmonary diseases accounted for most of the attributable deaths due to PM2.5 excess of exposure (38%). Estimates of YPLL due to all-cause mortality for exceeding the national standard of 25 µg/m3 were 2,381 years. CONCLUSION: Comparison of two global air quality models for estimating surface PM2.5 concentrations during 2014-2019 at municipality scale in Colombia showed important differences. Avoidable deaths estimations represent the total number of deaths that could be avoided if the current and projected national standard for PM2.5 annual mean have been met, and show the health-benefit of the implementation of more restrictive air quality standards.

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Objetivo: Este estudio evaluó el efecto de la proximidad a fuentes industriales de contaminación del aire sobre la aparición de clústeres de casos de cáncer infantil en el Área Metropolitana del Valle de Aburrá, del departamento de Antioquia, durante el período 2000-2015. Metodología: La información de casos de cáncer infantil en menores de 15 años residentes del área metropolitana se obtuvo del Registro Poblacional de Cáncer de Antioquia, de dicho periodo. Se identificaron 32 conglomerados industriales, a partir del inventario de la autoridad ambiental local. Se realizaron pruebas de escaneo circular de Kulldorf locales y focalizadas, para detectar clústeres de cáncer infantil en los municipios y alrededor de los conglomerados industriales respectivamente. Se usó un modelo de regresión multivariable ajustado por estrato socioeconómico, para evaluar el efecto de las variables espaciales. Resultados: La tasa de incidencia específica en el Valle de Aburrá para el periodo evaluado fue de 117,13 casos por millón de niños menores de 15 años. Las tasas de incidencia más altas se presentaron en los municipios de Medellín y Sabaneta. La prueba de Kulldorf identificó 12 clústeres espaciales y 8 espacio-temporales con significación estadística en 7 de los municipios, particularmente en Bello y Medellín. Las pruebas focalizadas identificaron clústeres alrededor de 20 conglomerados industriales. En los modelos multivariables, un conglomerado en Bello evidenció asociación estadísticamente significativa e inversa entre la incidencia y la distancia al conglomerado con direccionalidad sureste. Conclusión: Algunos conglomerados espacio-temporales de cáncer infantil en el Área Metropolitana del Valle de Aburrá entre 2000 y 2015 están relacionados con proximidad a fuentes industriales de contaminación del aire.

Objective: This study evaluated the effect of proximity to industrial sources of air pollution on the occurrence of clusters of childhood cancer cases in the Aburrá Valley Metropolitan Area, Department of Antioquia, during the 2000-2015 period. Methodology: The information on childhood cancer cases in children under 15 years of age residing in the metropolitan area was obtained from the Registro Poblacional de Cáncer de Antioquia (Antioquia Cancer Population Registry) for that period. 32 industrial clusters were identified based on the local environmental authority's inventory. Local and targeted Kulldorff's circular scan tests were performed to detect childhood cancer clusters in the municipalities and surrounding the industrial clusters, respectively. We used a multivariate regression model adjusted for socioeconomic strata to assess the effect of spatial variables. Results: The specific incidence rate in the Aburrá Valley for the evaluated period was 117.13 cases per million children under 15 years of age. The highest incidence rates occurred in the municipalities of Medellín and Sabaneta. The Kulldorff test identified 12 spatial clusters and 8 space-time clusters that were statistically significant in 7 municipalities, particularly in Bello and Medellín. The targeted tests identified childhood cancer clusters surrounding 20 industrial clusters. In multivariate models, an industrial cluster in Bello showed a statistically significant inverse association between incidence and distance from the industrial cluster toward the southeast. Conclusion: Some space-time childhood cancer clusters in the Aburrá Valley Metropolitan Area between 2000 and 2015 are related to proximity to industrial sources of air pollution.

Objetivo: Este estudo avaliou o efeito da proximidade a fontes industriais de poluição do ar sobre a aparição de agrupações de casos de câncer infantil na Área Metropolitana do Valle de Aburrá, do departamento de Antioquia, durante o período 2000-2015. Metodología: A informação de casos de câncer infantil em menores de 15 anos residentes da área metropolitana foi obtida do Registro Populacional de Câncer de Antioquia, de tal período. Foram identificados 32 conglomerados industriais, a partir do inventário da autoridade ambiental local. Foram realizados testes de varredura circular de Kulldorf locais e focalizados, para detectar agrupações de casos de câncer infantil nos municípios e ao redor dos conglomerados industriais, respectivamente. Foi usado um modelo de regressão multivariável ajustado por nivel socioeconômico, para avaliar o efeito das variáveis espaciais. Resultados: A taxa de incidência específica no Valle de Aburrá para o período avaliado foi de 117,13 casos por milhão de crianças menores de 15 anos. As maiores taxas de incidencia apresentaram-se nos municípios de Medellín e Sabaneta. O teste de Kulldorf identificou 12 agrupações de casos espaciais e 8 espaço-temporais com significação estatística em 7 dos municípios, particularmente em Bello e Medellín. As provas focalizadas identificaram agrupações de casos ao redor de 20 conglomerados industriais. Nos modelos multivariáveis, um conglomerado em Bello evidenciou associação estatisticamente significativa e inversa entre a incidência e a distância com o conglomerado orientado ao sudeste. Conclusão: Algumas agrupações de casos espaço-temporais de câncer infantil na Área Metropolitana do Valle del Aburrá entre 2000 e 2015 estão relacionadas com a proximidade a fontes industriais de poluição do ar.

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Resumen Introducción: La pandemia por COVID-19 ha requerido de la respuesta institucional de las diferentes organizaciones para mitigar sus efectos. Objetivo: Describir el proceso de respuesta institucional dirigida a la comunidad universitaria de la Universidad Industrial de Santander (UIS) frente la epidemia por COVID-19 y analizar los resultados de los procesos implementados durante 2020 y 2021. Metodología: Estudio descriptivo de tipo mixto con un componente cualitativo descriptivo de la organización y desarrollo de la respuesta institucional y un componente cuantitativo descriptivo del análisis de los casos sospechosos y confirmados de COVID-19 en la comunidad universitaria UIS. Resultados: La respuesta institucional UIS comenzó desde marzo de 2020 y comprendió lineamientos y adaptaciones de tipo académico y laboral y un plan de respuesta que incluyó 6 componentes de acción y un retorno gradual a la presencialidad. Durante 2021 se confirmaron 272 casos en funcionarios y docentes y 208 casos en estudiantes, con una tendencia que reflejó la dinámica de transmisión local, pero con menor letalidad. Conclusiones: La respuesta institucional UIS frente a la epidemia por COVID-19 inició tempranamente e incluyó diferentes componentes que permitieron un retorno progresivo con baja transmisión en las sedes. Los aspectos por mejorar estuvieron relacionados con la cobertura, calidad y continuidad del diagnóstico y atención oportunos, conexas a las competencias y fragmentación propias del sistema de salud, y con la visibilidad del plan y sus resultados dentro de la comunidad universitaria.

Abstract Introduction: The COVID-19 pandemic has required the institutional response of different organizations to mitigate its effects. Objective: To describe the institutional response process for the COVID-19 pandemic at the Universidad Industrial de Santander (UIS) and analyze the results of the processes implemented during 2020 and 2021. Methodology: Descriptive mixed study with a qualitative component of the organization and development of the institutional response, and a descriptive quantitative component of the analysis of suspected and confirmed cases of COVID-19. Results: The UIS institutional response began in March 2020. The plan included academic and employment guidelines and adaptations, a response plan that included 6 action components and a gradual return to attendance. During 2021, 272 cases were confirmed in employees and professors, and 208 cases in students with a trend that reflected the dynamics of local transmission, but with lower lethality. Conclusions: The UIS institutional response to the COVID-19 epidemic began early and included different components that allowed for a progressive return with low transmission. The aspects to improve were related to the coverage, quality and continuity of timely diagnosis and care related to competencies and fragmentation of the health system, and the visibility of the plan and its results within the university community.

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Background: Childhood cancer is considered one the most important causes of death in children and adolescents, despite having a low incidence in this population. Spatial analysis has been previously used for the study of childhood cancer to study the geographical distribution of leukemias. This study aimed to identify the presence of space-time clusters of childhood of cancer excluding leukemia in Colombia between 2014 and 2017. Methods: All incident cancer cases (excluding leukemia) in children under the age of 15 years that had been confirmed by the National Surveillance System of Childhood Cancer between 2014 and 2017 were included. Kulldorf's circular scan test was used to identify clusters using the municipality of residence as the spatial unit of analysis and the year of diagnosis as the temporal unit of analysis. A sensitivity analysis was conducted with different upper limit parameters for the at-risk population. Results: A total of 2006 cases of non-leukemia childhood cancer were analyzed, distributed in 432 municipalities with a mean annual incidence rate of 44 cases per million children under the age of 15. Central nervous system (CNS) tumors were the most frequent type. Four spatial clusters and two space-time clusters were identified in the central and southwest regions of the country. In the analysis for CNS tumors, a spatial cluster was identified in the central region of the country.  Conclusions: The distribution of non-leukemia childhood cancer seems to have a clustered distribution in some Colombian regions that may suggest infectious or environmental factors associated with its incidence.

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