137 research outputs found

    Associations between eating speed, diet quality, adiposity, and cardiometabolic risk factors

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    Objective: To assess the associations between eating speed, adiposity, cardiometabolic risk factors, and diet quality in a cohort of Spanish preschool-children. Study design: A cross-sectional study in 1371 preschool age children (49% girls; mean age, 4.8 ± 1.0 years) from the Childhood Obesity Risk Assessment Longitudinal Study (CORALS) cohort was conducted. After exclusions, 956 participants were included in the analyses. The eating speed was estimated by summing the total minutes used in each of the 3 main meals and then categorized into slow, moderate, or fast. Multiple linear and logistic regression models were fitted to assess the ÎČ-coefficient, or OR and 95% CI, between eating speed and body mass index, waist circumference, fat mass index (FMI), blood pressure, fasting plasma glucose, and lipid profile. Results: Compared with participants in the slow-eating category, those in the fast-eating category had a higher prevalence risk of overweight/obesity (OR, 2.9; 95% CI, 1.8-4.4; P < .01); larger waist circumference (ÎČ, 2.6 cm; 95% CI, 1.5-3.8 cm); and greater FMI (ÎČ, 0.3 kg/m2; 95% CI, 0.1-0.5 kg/m2), systolic blood pressure (ÎČ, 2.8 mmHg; 95% CI, 0.6-4.9 mmHg), and fasting plasma glucose levels (ÎČ, 2.7 mg/dL, 95% CI, 1.2-4.2 mg/dL) but lower adherence to the Mediterranean diet (ÎČ, −0.5 points; 95% CI, −0.9 to −0.1 points). Conclusions: Eating fast is associated with higher adiposity, certain cardiometabolic risk factors, and lower adherence to a Mediterranean diet. Further long-term and interventional studies are warranted to confirm these associations

    Global data on earthworm abundance, biomass, diversity and corresponding environmental properties

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    14 p.Earthworms are an important soil taxon as ecosystem engineers, providing a variety of crucial ecosystem functions and services. Little is known about their diversity and distribution at large spatial scales, despite the availability of considerable amounts of local-scale data. Earthworm diversity data, obtained from the primary literature or provided directly by authors, were collated with information on site locations, including coordinates, habitat cover, and soil properties. Datasets were required, at a minimum, to include abundance or biomass of earthworms at a site. Where possible, site-level species lists were included, as well as the abundance and biomass of individual species and ecological groups. This global dataset contains 10,840 sites, with 184 species, from 60 countries and all continents except Antarctica. The data were obtained from 182 published articles, published between 1973 and 2017, and 17 unpublished datasets. Amalgamating data into a single global database will assist researchers in investigating and answering a wide variety of pressing questions, for example, jointly assessing aboveground and belowground biodiversity distributions and drivers of biodiversity change

    Global data on earthworm abundance, biomass, diversity and corresponding environmental properties

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    Publisher Copyright: © 2021, The Author(s).Earthworms are an important soil taxon as ecosystem engineers, providing a variety of crucial ecosystem functions and services. Little is known about their diversity and distribution at large spatial scales, despite the availability of considerable amounts of local-scale data. Earthworm diversity data, obtained from the primary literature or provided directly by authors, were collated with information on site locations, including coordinates, habitat cover, and soil properties. Datasets were required, at a minimum, to include abundance or biomass of earthworms at a site. Where possible, site-level species lists were included, as well as the abundance and biomass of individual species and ecological groups. This global dataset contains 10,840 sites, with 184 species, from 60 countries and all continents except Antarctica. The data were obtained from 182 published articles, published between 1973 and 2017, and 17 unpublished datasets. Amalgamating data into a single global database will assist researchers in investigating and answering a wide variety of pressing questions, for example, jointly assessing aboveground and belowground biodiversity distributions and drivers of biodiversity change.Peer reviewe
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