DSpace Collection:

Parental misperception of their child's weight status and how weight underestimation is associated with childhood obesity

2020-02-21T21:30:15Z

Title: Parental misperception of their child's weight status and how weight underestimation is associated with childhood obesity Authors: Rodrigues, Daniela; Machado-Rodrigues, Aristides M; Padez, Cristina Abstract: Obesity is a major public health concern worldwide. This study aims to investigate the accuracy of parental perception of child's weight and related factors as well as how underestimation is associated with the prevalence of childhood obesity.

A particular heritage: The importance of identified osteological collections

2019-12-17T16:46:47Z

Title: A particular heritage: The importance of identified osteological collections Authors: Santos, Ana Luisa

Un patrimonio particular: la importancia de las colecciones osteológicas identificadas

2019-12-17T16:47:45Z

Title: Un patrimonio particular: la importancia de las colecciones osteológicas identificadas Authors: Santos, Ana Luisa Abstract: Uno de los pilares de los estudios bioantropológicos son las colecciones osteológicas identificadas. Este trabajo tiene como objetivo describir este patrimonio y mostrar su importancia. Desde el siglo xix, varios países han reunido conjuntos de cráneos y esqueletos de personas de las cuales se conocen algunos datos biográficos; entre otros, qué edad tenían al morir y su sexo. Actualmente existen cerca de cincuenta colecciones en países de América del Norte y del Sur, África, Europa y Asia. Las investigaciones realizadas sobre estas tienen aplicaciones en el estudio de la evolución humana, de las poblaciones del pasado, de la paleopatología y de la historia de la medicina, entre otros. La necesidad de aumentar el número de individuos y ampliar la distribución geográfica de las muestras conduce al continuo desarrollo de estas colecciones

SPINNE: An app for human vertebral height estimation based on artificial neural networks

2019-12-17T11:01:40Z

Title: SPINNE: An app for human vertebral height estimation based on artificial neural networks Authors: Vilas-Boas, D; Wasterlain, S N; d'Oliveira Coelho, J; Navega, D; Gonçalves, D Abstract: The absence or poor preservation of vertebrae often prevent the application of the anatomical method for stature estimation. The main objective of this paper was to develop a web app based on artificial neural network (ANN) models to estimate the vertebral height of absent or poorly preserved vertebrae from other vertebrae and thus enable the application of anatomical methods. Artificial neural models were developed based on the vertebral height of vertebrae C2 to S1 of a sample composed of 56 adult male and 69 adult female individuals. The skeletons belong to the Identified Skeletal Collection of the University of Coimbra and the ages at death of these individuals ranged from 22 to 58 years old. Statistical analysis and algorithmic development were performed with the R language, R Core Team (2018). Intra- and inter-observer errors regarding the vertebral height were small for all vertebrae (<0.45 mm). Significant models to estimate vertebral height were obtained for both sexes and for the sex-pooled group, although none with an R2 higher than 0.48 and 0.34 for the C2 and the S1, respectively. The root mean square error (RMSE) regarding the predicted vertebral height and the observed vertebral height was almost always smaller than 1.0 mm while most R2 values were higher than 0.6 although models with worse performances were obtained for some vertebrae located at the ends of the vertebral column (C3, L4, and L5). The ANN models have clear potential to predict vertebral height. This mathematical approach may be used to enable the application of the anatomical method for stature estimation when some vertebrae are absent or poorly preserved. The application of the ANN models can be carried out by using the new web based app SPINNE.