Epidemiological profile of patients hospitalized by COVID-19 in an Intensive Care Unit in the interior of Brazil

Objective: To describe the epidemiological profile of patients admitted by COVID-19 to the intensive care unit of a hospital in the interior of the northeastern countryside. Methods: Observational and retrospective study based on data from the electronic protocol of the service of patients admitted between April 24, 2020 and December 31, 2020. Data regarding gender, age, health insurance, need for orotracheal intubation and outcome were evaluated. Results: 118 patients were included in the study. Men were more affected than women. The mean age of patients was 65.35 years, with the mean age of women (70.53 years) being higher than the mean age of men (62.37 years). Regarding age group, the elderly accounted for 66.11% of patients. 48.31% of the patients required orotracheal intubation, of which 61.40% were male, with an outcome of death in 75.44% of the intubated patients. Of the total number of patients in the study, 40.68% died. Conclusion: Greater involvement and lethality were observed in men and in the elderly. The number of adult men admitted was triple the number of adult women admitted.Objetivo: Descrever o perfil epidemiológico de pacientes admitidos por COVID-19 em unidade de terapia intensiva em hospital de uma cidade do interior nordestino. Métodos: Estudo observacional e retrospectivo a partir de dados do protocolo eletrônico do serviço dos pacientes com admissão entre 24 de abril de 2020 e 31 de dezembro de 2020. Foram avaliados dados referentes a sexo, faixa etária, convênio, necessidade de intubação orotraqueal e desfecho. Resultados: Um total de 118 pacientes foram incluídos no estudo. Homens foram mais acometidos do que mulheres. A média de idade dos pacientes foi de 65,35 anos, sendo a média de idade das mulheres (70,53 anos) maior que a média de idade dos homens (62,37 anos). Em relação à faixa etária, os idosos corresponderam a 66,11% dos pacientes. 48,31% dos pacientes necessitaram de intubação orotraqueal, destes 61,40% eram do sexo masculino, com desfecho para óbito em 75,44% dos pacientes intubados. Do total de pacientes do estudo, 40,68% evoluíram para óbito. Conclusão: Observou-se maior acometimento e letalidade em homens e em idosos. A quantidade de homens adultos admitidos foi o triplo da quantidade de mulheres adultas admitidas

Sistemas silvipastoris com eucalipto: estocagem de carbono em diferentes espaçamentos e clones

This study aimed to compare the use of different eucalypt spacing and clones in carbon storage in six silvopastoral systems (SSP) located in Porto Firme - MG. Experiments containing six SSP were used in the field, with clones GG100, I144, and I224, hybrids of Eucalyptus grandis x Eucalyptus urophylla, in the spacing of 6m x 4m and 8m x 4m, at the ages of 60 and 96 months. The forest inventory carried out was of the census type, where all the trees had their circumference at 1,30 m in height (CAP) measured and separated into diametric classes. The volume was estimated based on the Spurr model. The wood density was calculated by the method of immersion in water and the carbon stock by the factor of 0,47. The genetic material I224, spaced 6m x 4m, had the highest potential for carbon storage. The basic density for the three clones, in 6m x 4m spacing, did not vary statistically, however, in 8m x 4m spacing, for the genetic materials GG100 and I224, there was a difference. It was possible to conclude that the genetic material I224, in 6m x 4m spacing (24 m² per plant), has the highest potential for carbon storage and that SSP with eucalypt contributes to low-carbon agriculture and mitigation of climate change.O objetivo do presente estudo foi comparar o uso de diferentes espaçamentos e clones de eucalipto na estocagem de carbono em 6 (seis) sistemas silvipastoris (SSP), localizados em Porto Firme - MG. Em campo foram utilizados experimentos contendo 6 (seis) SSP, com os clones GG100, I144, I224, híbridos de Eucalyptus grandis x Eucalyptus urophylla, nos espaçamentos de 6m x 4m e 8m x 4m, nas idades de 60 e 96 meses. O inventário florestal realizado foi do tipo censo, onde todas as árvores tiveram sua circunferência a 1,30 m de altura (CAP) mensuradas e foram separadas em classes diamétricas. O volume foi estimado baseado no modelo Spurr. A densidade da madeira foi calculada pelo método de imersão em água e o estoque de carbono pelo fator de 0,47. O material genético I224, no espaçamento de 6m x 4m, foi aquele com maior potencial de estocagem de carbono. A densidade básica para os três clones, no espaçamento de 6m x 4m, não variou estatisticamente. Porém, no espaçamento de 8m x 4m, para os materiais genéticos GG100 e I224, houve diferença. Foi possível concluir que o material genético I224, no espaçamento 6m x 4m (24 m² por planta) possui o maior potencial de estocagem de carbono e que os SSP com eucalipto contribuem para uma agricultura de baixa emissão de carbono e mitigação das mudanças climáticas.

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Worldwide trends in underweight and obesity from 1990 to 2022: a pooled analysis of 3663 population-representative studies with 222 million children, adolescents, and adults

Background Underweight and obesity are associated with adverse health outcomes throughout the life course. We estimated the individual and combined prevalence of underweight or thinness and obesity, and their changes, from 1990 to 2022 for adults and school-aged children and adolescents in 200 countries and territories. Methods We used data from 3663 population-based studies with 222 million participants that measured height and weight in representative samples of the general population. We used a Bayesian hierarchical model to estimate trends in the prevalence of different BMI categories, separately for adults (age ≥20 years) and school-aged children and adolescents (age 5–19 years), from 1990 to 2022 for 200 countries and territories. For adults, we report the individual and combined prevalence of underweight (BMI <18·5 kg/m2) and obesity (BMI ≥30 kg/m2). For schoolaged children and adolescents, we report thinness (BMI <2 SD below the median of the WHO growth reference) and obesity (BMI >2 SD above the median). Findings From 1990 to 2022, the combined prevalence of underweight and obesity in adults decreased in 11 countries (6%) for women and 17 (9%) for men with a posterior probability of at least 0·80 that the observed changes were true decreases. The combined prevalence increased in 162 countries (81%) for women and 140 countries (70%) for men with a posterior probability of at least 0·80. In 2022, the combined prevalence of underweight and obesity was highest in island nations in the Caribbean and Polynesia and Micronesia, and countries in the Middle East and north Africa. Obesity prevalence was higher than underweight with posterior probability of at least 0·80 in 177 countries (89%) for women and 145 (73%) for men in 2022, whereas the converse was true in 16 countries (8%) for women, and 39 (20%) for men. From 1990 to 2022, the combined prevalence of thinness and obesity decreased among girls in five countries (3%) and among boys in 15 countries (8%) with a posterior probability of at least 0·80, and increased among girls in 140 countries (70%) and boys in 137 countries (69%) with a posterior probability of at least 0·80. The countries with highest combined prevalence of thinness and obesity in school-aged children and adolescents in 2022 were in Polynesia and Micronesia and the Caribbean for both sexes, and Chile and Qatar for boys. Combined prevalence was also high in some countries in south Asia, such as India and Pakistan, where thinness remained prevalent despite having declined. In 2022, obesity in school-aged children and adolescents was more prevalent than thinness with a posterior probability of at least 0·80 among girls in 133 countries (67%) and boys in 125 countries (63%), whereas the converse was true in 35 countries (18%) and 42 countries (21%), respectively. In almost all countries for both adults and school-aged children and adolescents, the increases in double burden were driven by increases in obesity, and decreases in double burden by declining underweight or thinness. Interpretation The combined burden of underweight and obesity has increased in most countries, driven by an increase in obesity, while underweight and thinness remain prevalent in south Asia and parts of Africa. A healthy nutrition transition that enhances access to nutritious foods is needed to address the remaining burden of underweight while curbing and reversing the increase in obesit

Height and body-mass index trajectories of school-aged children and adolescents from 1985 to 2019 in 200 countries and territories: a pooled analysis of 2181 population-based studies with 65 million participants

Summary Background Comparable global data on health and nutrition of school-aged children and adolescents are scarce. We aimed to estimate age trajectories and time trends in mean height and mean body-mass index (BMI), which measures weight gain beyond what is expected from height gain, for school-aged children and adolescents. Methods For this pooled analysis, we used a database of cardiometabolic risk factors collated by the Non-Communicable Disease Risk Factor Collaboration. We applied a Bayesian hierarchical model to estimate trends from 1985 to 2019 in mean height and mean BMI in 1-year age groups for ages 5–19 years. The model allowed for non-linear changes over time in mean height and mean BMI and for non-linear changes with age of children and adolescents, including periods of rapid growth during adolescence. Findings We pooled data from 2181 population-based studies, with measurements of height and weight in 65 million participants in 200 countries and territories. In 2019, we estimated a difference of 20 cm or higher in mean height of 19-year-old adolescents between countries with the tallest populations (the Netherlands, Montenegro, Estonia, and Bosnia and Herzegovina for boys; and the Netherlands, Montenegro, Denmark, and Iceland for girls) and those with the shortest populations (Timor-Leste, Laos, Solomon Islands, and Papua New Guinea for boys; and Guatemala, Bangladesh, Nepal, and Timor-Leste for girls). In the same year, the difference between the highest mean BMI (in Pacific island countries, Kuwait, Bahrain, The Bahamas, Chile, the USA, and New Zealand for both boys and girls and in South Africa for girls) and lowest mean BMI (in India, Bangladesh, Timor-Leste, Ethiopia, and Chad for boys and girls; and in Japan and Romania for girls) was approximately 9–10 kg/m2. In some countries, children aged 5 years started with healthier height or BMI than the global median and, in some cases, as healthy as the best performing countries, but they became progressively less healthy compared with their comparators as they grew older by not growing as tall (eg, boys in Austria and Barbados, and girls in Belgium and Puerto Rico) or gaining too much weight for their height (eg, girls and boys in Kuwait, Bahrain, Fiji, Jamaica, and Mexico; and girls in South Africa and New Zealand). In other countries, growing children overtook the height of their comparators (eg, Latvia, Czech Republic, Morocco, and Iran) or curbed their weight gain (eg, Italy, France, and Croatia) in late childhood and adolescence. When changes in both height and BMI were considered, girls in South Korea, Vietnam, Saudi Arabia, Turkey, and some central Asian countries (eg, Armenia and Azerbaijan), and boys in central and western Europe (eg, Portugal, Denmark, Poland, and Montenegro) had the healthiest changes in anthropometric status over the past 3·5 decades because, compared with children and adolescents in other countries, they had a much larger gain in height than they did in BMI. The unhealthiest changes—gaining too little height, too much weight for their height compared with children in other countries, or both—occurred in many countries in sub-Saharan Africa, New Zealand, and the USA for boys and girls; in Malaysia and some Pacific island nations for boys; and in Mexico for girls. Interpretation The height and BMI trajectories over age and time of school-aged children and adolescents are highly variable across countries, which indicates heterogeneous nutritional quality and lifelong health advantages and risks

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost