Publications (2)0.96 Total impact
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ABSTRACT: The aim of the present study was to examine the heritability of 11 traits in a mixed-longitudinal sample of Indian siblings, and to determine whether heritability estimates vary during the growth period and whether they are influenced by sex. The sample consisted of 245 brothers and 213 sisters from 138 nuclear families living in a semi-urban area in Kolkata, India. The age ranged between 5 and 19 years. The traits were standardised for age and sex using standard deviation scores (SDS) produced by the LMS method (Cole, T.J., 1988. Fitting smoothed centile curves to reference data. J. R. Stat. Soc. A 151, 385-418). The standard deviation scores were analysed by PCA. The two factors with eigenvalues above 1 explained 77.3% of the variance; they showed a high level of pleiotropism present among the studied traits and represented body lengths (PC1) and body weight and breadths (PC2). The heritability between all types of siblings (irrespective of sex) for the PC1 and PC2 was estimated. The heritability between various pairs of siblings showed variations along the whole ontogenetic period studied. During the childhood and pre-pubertal period, heritability between brothers, brother-sister pairs and any sibling pairs was mostly constant, with small and non-significant variations. All the pairs showed the lowest degree of heritability during puberty for PC1 but not for PC2, with significant changes of heritability estimates between adolescence and adulthood, in most of the analysed sibling pairs and in both PC factors. The highest heritability was generally observed at the end of the examined growth period in all pairs. A significant effect of sex on heritability was only detected for PC2 at 11 years of age.
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ABSTRACT: The methods of drawing references for height, using advanced statistical methodology based on fitting mathematical models of growth are useful to show both the pattern and timing of growth in individuals and populations (Ledford and Cole 1998). There is a set of growth models proposed to fit longitudinal and cross-sectional growth data of attained height by age which are not based on a set of parameters. They are often called non-structural models (Bock and Thissen 1980). The underlying assumption, in models depending on a set of parameters (Count 1943, Jenss and Bayley 1937, Preece and Baines 1978, Shohoji and Sasaki 1987, Jolicoeur et al 1988, Deming 1957, Marubini et al 1971, Thissen and Bock 1990), is that the growth pattern has a basic functional form to which a direct biological interpretation can be attributed (Berkey 1982, Hauspie, 1989). The disadvantage of these models is that they sometimes impose a too rigid shape upon the form of the growth cuive (Wember et al 1992, Zemel and Johnston 1994). This type of functions are normally used to model individual growth curves rather than to summarise a whole sample; however, they can be also applied to means (Tanner et al 1982) or to selected centiles and, in this way, a set of smooth centile curves can be generated. However, the independent fitting of the centile curves is not a good solution because some centile lines describe heterogeneous patterns of growth and the distribution of the centile curves often lacks homogeneity.
Universidad del País Vasco / Euskal Herriko Unibertsitatea
Leioa, Basque Country, Spain
- Departamento de Genética, Antropología Física y Fisiología Animal