48 resultados para Multivalent associations


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Interpretation biases have been shown to play a role in adult depression and are a target in cognitive behavioural therapy. Adolescence is a key risk period for the development of depression and a period of rapid cognitive and emotional development but little research has investigated the relationship between interpretation biases and depression in adolescents. This study adapted a measure of interpretation bias, the Ambiguous Scenarios Test for Depression, for adolescents and evaluated its reliability and validity. A community sample of 206 young people aged 12 to 18 years completed a validated measure of depression symptoms (Mood and Feelings Questionnaires) and the adapted Ambiguous Scenarios Test. The Ambiguous Scenarios Test for Depression in Adolescents had good internal consistency and split half reliability. Depression symptoms were associated with participants’ ratings of the valence of ambiguous situations and with interpretation biases. Importantly, symptoms of depression and anxiety were independently associated with interpretation bias. This research suggests that interpretation biases can be measured in this age group, that negative interpretation biases exist in adolescents and that these are associated with depression symptoms.

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BACKGROUND: Although the peroxisome proliferator-activated receptor γ (PPARγ) pathway is central in adipogenesis, it remains unknown whether it influences change in body weight (BW) and whether dietary fat has a modifying effect on the association. OBJECTIVES: We examined whether 27 single nucleotide polymorphisms (SNPs) within 4 genes in the PPARγ pathway are associated with the OR of being a BW gainer or with annual changes in anthropometry and whether intake of total fat, monounsaturated fat, polyunsaturated fat, or saturated fat has a modifying effect on these associations. METHODS: A case-noncase study included 11,048 men and women from cohorts in the European Diet, Obesity and Genes study; 5552 were cases, defined as individuals with the greatest BW gain during follow-up, and 6548 were randomly selected, including 5496 noncases. We selected 4 genes [CCAAT/enhancer binding protein β (CEBPB), phosphoenolpyruvate carboxykinase 2, PPARγ gene (PPARG), and sterol regulatory element binding transcription factor 1] according to evidence about biologic plausibility for interactions with dietary fat in weight regulation. Diet was assessed at baseline, and anthropometry was followed for 7 y. RESULTS: The ORs for being a BW gainer for the 27 genetic variants ranged from 0.87 (95% CI: 0.79, 1.03) to 1.12 (95% CI: 0.96, 1.22) per additional minor allele. Uncorrected, CEBPB rs4253449 had a significant interaction with the intake of total fat and subgroups of fat. The OR for being a BW gainer for each additional rs4253449 minor allele per 100 kcal higher total fat intake was 1.07 (95% CI: 1.02, 1.12; P = 0.008), and similar associations were found for subgroups of fat. CONCLUSIONS: Among European men and women, the influence of dietary fat on associations between SNPs in the PPARγ pathway and anthropometry is likely to be absent or marginal. The observed interaction between rs4253449 and dietary fat needs confirmation.

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Accurate knowledge of species’ habitat associations is important for conservation planning and policy. Assessing habitat associations is a vital precursor to selecting appropriate indicator species for prioritising sites for conservation or assessing trends in habitat quality. However, much existing knowledge is based on qualitative expert opinion or local scale studies, and may not remain accurate across different spatial scales or geographic locations. Data from biological recording schemes have the potential to provide objective measures of habitat association, with the ability to account for spatial variation. We used data on 50 British butterfly species as a test case to investigate the correspondence of data-derived measures of habitat association with expert opinion, from two different butterfly recording schemes. One scheme collected large quantities of occurrence data (c. 3 million records) and the other, lower quantities of standardised monitoring data (c. 1400 sites). We used general linear mixed effects models to derive scores of association with broad-leaf woodland for both datasets and compared them with scores canvassed from experts. Scores derived from occurrence and abundance data both showed strongly positive correlations with expert opinion. However, only for occurrence data did these fell within the range of correlations between experts. Data-derived scores showed regional spatial variation in the strength of butterfly associations with broad-leaf woodland, with a significant latitudinal trend in 26% of species. Sub-sampling of the data suggested a mean sample size of 5000 occurrence records per species to gain an accurate estimation of habitat association, although habitat specialists are likely to be readily detected using several hundred records. Occurrence data from recording schemes can thus provide easily obtained, objective, quantitative measures of habitat association.