3 research outputs found

    Prevalence and incidence of iron deficiency in European community-dwelling older adults: an observational analysis of the DO-HEALTH trial

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    Background and aim Iron deficiency is associated with increased morbidity and mortality in older adults. However, data on its prevalence and incidence among older adults is limited. The aim of this study was to investigate the prevalence and incidence of iron deficiency in European community-dwelling older adults aged ≥ 70 years. Methods Secondary analysis of the DO-HEALTH trial, a 3-year clinical trial including 2157 community-dwelling adults aged ≥ 70 years from Austria, France, Germany, Portugal and Switzerland. Iron deficiency was defined as soluble transferrin receptor (sTfR) > 28.1 nmol/L. Prevalence and incidence rate (IR) of iron deficiency per 100 person-years were examined overall and stratified by sex, age group, and country. Sensitivity analysis for three commonly used definitions of iron deficiency (ferritin  1.5) were also performed. Results Out of 2157 participants, 2141 had sTfR measured at baseline (mean age 74.9 years; 61.5% women). The prevalence of iron deficiency at baseline was 26.8%, and did not differ by sex, but by age (35.6% in age group ≥ 80, 29.3% in age group 75–79, 23.2% in age group 70–74); P  1.5. Occurrences of iron deficiency were observed with IR per 100 person-years of 9.2 (95% CI 8.3–10.1) and did not significantly differ by sex or age group. The highest IR per 100 person-years was observed in Austria (20.8, 95% CI 16.1–26.9), the lowest in Germany (6.1, 95% CI 4.7–8.0). Regarding the other definitions of iron deficiency, the IR per 100 person-years was 4.5 (95% CI 4.0–4.9) for ferritin  1.5. Conclusions Iron deficiency is frequent among relatively healthy European older adults, with people aged ≥ 80 years and residence in Austria and Portugal associated with the highest risk

    Pervasive gaps in Amazonian ecological research

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    Biodiversity loss is one of the main challenges of our time, and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space. While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes, vast areas of the tropics remain understudied. In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity, but it remains among the least known forests in America and is often underrepresented in biodiversity databases. To worsen this situation, human-induced modifications 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, 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
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