Infuência da actividade física, de factores somáticos e do envolvimento na coordenação e habilidades motoras: um estudo em crianças madeirenses

O presente estudo foi delineado com os seguintes objectivos: (I) analisar as diferenças entre sexos no desempenho da coordenação e habilidades motoras e (II) avaliar a influência da actividade física (ActF), das características somáticas e do envolvimento familiar na capacidade de coordenação motora CM e expressão das habilidades motoras. A amostra foi constituída por 1632 crianças (835 do sexo feminino e 797 do sexo masculino) que participaram no projecto “Crescer com Saúde na Região Autónoma da Madeira” (CRES). Para avaliar o desenvolvimento coordenativo foi utilizada a bateria KTK e para as habilidades motoras recorremos ao Teste de Desenvolvimento das Habilidades Motoras Fundamentais (TGMD 2). As variáveis somáticas avaliadas foram: altura, peso e soma de cinco pregas adiposas (S5PA). As variáveis do envolvimento avaliadas foram: estatuto sócio-económico (ESE), fratria e outras variáveis relacionadas com o espaço habitacional e práticas educativas. A ActF foi avaliada através do questionário de Godin e Shephard (1985). Foi realizada a estatística descritiva para todas as variáveis observadas: média, desviopadrão, mínimo e máximo para as variáveis medidas nas escalas intervalar e de razão, frequências e percentagens para as variáveis medidas na escala nominal. Foi usada a prova de Student para analisar a diferença entre os dois sexos nas diferentes provas motoras. Para identificar as variáveis determinantes do desempenho motor foi usada a análise de regressão múltipla com o método stepwise. Em todas as provas estatísticas os resultados foram considerados significativos quando p≤0,05. Os rapazes obtiveram resultados médios superiores às raparigas na CM e no desempenho das habilidades motoras, com excepção dos testes de avaliação locomotora nas crianças com idade superior aos 6 anos em que não existem diferenças entre os sexos. A generalidade das crianças apresenta valores de CM que se situam nos níveis de insuficiências e perturbações coordenativas. As variáveis somáticas foram as melhores preditoras na variação do desempenho nos testes de CM e habilidades motoras. Níveis mais elevados de ctF estão associados a resultados médios superiores no desempenho dos testes de CM e na avaliação de controlo de objectos, nos rapazes com idade superior a 6 anos. As variáveis do envolvimento que melhor explicaram os resultados obtidos nos testes motores foram o ESE, o tipo de habitação, a ordem da fratria e o limite geográfico concedido à criança para brincar.

Multivariate analysis for the classification and differentiation of Madeira wines according to main grape varieties

In order to differentiate and characterize Madeira wines according to main grape varieties, the volatile composition (higher alcohols, fatty acids, ethyl esters and carbonyl compounds) was determined for 36 monovarietal Madeira wine samples elaborated from Boal, Malvazia, Sercial and Verdelho white grape varieties. The study was carried out by headspace solid-phase microextraction technique (HS-SPME), in dynamic mode, coupled with gas chromatography–mass spectrometry (GC–MS). Corrected peak area data for 42 analytes from the above mentioned chemical groups was used for statistical purposes. Principal component analysis (PCA) was applied in order to determine the main sources of variability present in the data sets and to establish the relation between samples (objects) and volatile compounds (variables). The data obtained by GC–MS shows that the most important contributions to the differentiation of Boal wines are benzyl alcohol and (E)-hex-3-en-1-ol. Ethyl octadecanoate, (Z)-hex-3-en-1-ol and benzoic acid are the major contributions in Malvazia wines and 2-methylpropan-1-ol is associated to Sercial wines. Verdelho wines are most correlated with 5-(ethoxymethyl)-furfural, nonanone and cis-9-ethyldecenoate. A 96.4% of prediction ability was obtained by the application of stepwise linear discriminant analysis (SLDA) using the 19 variables that maximise the variance of the initial data set.

Content in metallic ions of wines from the Madeira and Azores archipelagos

This study determines for the first time Na, K, Ca, Mg, Fe, Cu, Zn, Mn, Sr, Li and Rb contents in wines from the archipelagos of Madeira and Azores (Portugal). The greater part of the mean content for the different parameters fell within the ranges described in the literature, except for sodium whose higher content may be due to the effect of marine spray. ANOVA was used to establish the metals with significant differences in mean content between the wines from both archipelagos, between table and liquor wines of Madeira, and between wines of Pico and Terceira Islands from the Azores archipelago. Principal component analysis shows differences in the wines according to the wine-making process and/or the equipment employed. Stepwise linear discriminant analysis achieves a good classification and validation of wines according to the archipelago of origin, and the island in the case of Azores wines.

Dynamic headspace solid-phase microextraction combined with one-dimensional gas chromatography–mass spectrometry as a powerful tool to differentiate banana cultivars based on their volatile metabolite profile

In this study the effect of the cultivar on the volatile profile of five different banana varieties was evaluated and determined by dynamic headspace solid-phase microextraction (dHS-SPME) combined with one-dimensional gas chromatography–mass spectrometry (1D-GC–qMS). This approach allowed the definition of a volatile metabolite profile to each banana variety and can be used as pertinent criteria of differentiation. The investigated banana varieties (Dwarf Cavendish, Prata, Maçã, Ouro and Platano) have certified botanical origin and belong to the Musaceae family, the most common genomic group cultivated in Madeira Island (Portugal). The influence of dHS-SPME experimental factors, namely, fibre coating, extraction time and extraction temperature, on the equilibrium headspace analysis was investigated and optimised using univariate optimisation design. A total of 68 volatile organic metabolites (VOMs) were tentatively identified and used to profile the volatile composition in different banana cultivars, thus emphasising the sensitivity and applicability of SPME for establishment of the volatile metabolomic pattern of plant secondary metabolites. Ethyl esters were found to comprise the largest chemical class accounting 80.9%, 86.5%, 51.2%, 90.1% and 6.1% of total peak area for Dwarf Cavendish, Prata, Ouro, Maçã and Platano volatile fraction, respectively. Gas chromatographic peak areas were submitted to multivariate statistical analysis (principal component and stepwise linear discriminant analysis) in order to visualise clusters within samples and to detect the volatile metabolites able to differentiate banana cultivars. The application of the multivariate analysis on the VOMs data set resulted in predictive abilities of 90% as evaluated by the cross-validation procedure.

Prediction of adult height in girls: the Beunen-MalinaFreitas method

The purpose of this study was to validate and cross-validate the Beunen-Malina-Freitas method for non-invasive prediction of adult height in girls. A sample of 420 girls aged 10–15 years from the Madeira Growth Study were measured at yearly intervals and then 8 years later. Anthropometric dimensions (lengths, breadths, circumferences, and skinfolds) were measured; skeletal age was assessed using the Tanner-Whitehouse 3 method and menarcheal status (present or absent) was recorded. Adult height was measured and predicted using stepwise, forward, and maximum R2 regression techniques. Multiple correlations, mean differences, standard errors of prediction, and error boundaries were calculated. A sample of the Leuven Longitudinal Twin Study was used to cross-validate the regressions. Age-specific coefficients of determination (R2) between predicted and measured adult height varied between 0.57 and 0.96, while standard errors of prediction varied between 1.1 and 3.9 cm. The cross-validation confirmed the validity of the Beunen-Malina-Freitas method in girls aged 12–15 years, but at lower ages the cross-validation was less consistent. We conclude that the Beunen-Malina-Freitas method is valid for the prediction of adult height in girls aged 12–15 years. It is applicable to European populations or populations of European ancestry.