Patterns in the within-population variability of stature and weight

Abstract

An analysis has been undertaken of the comparative magnitudes of the within-population variability in stature and body weight as reported in the recent literature. The distributions of the variability have been investigated for patterns related to latitude, altitude, 'affluence' and the mean value of the measurements. It is shown that differences in stature variability are substantially explained by differences in mean stature only. This however, is not the case with weight variability where, in addition to the mean, there is evidence of independent effects of affluence, altitude, and especially latitude. In most populations the weight of females is more variable than that of males. This is considered to be due to their greater amounts of fat, and differing levels of fat may also explain much of the geographical patterns in weight variability.

Effect of Economic Reforms on Child Growth in Urban and Rural Areas of China

“…Our results contradict other findings, 38 including those in a recent report by the WHO, which indicated that the variation in height for age is constant across populations regardless of the mean. 18 Our data were highly standardized, and we investigated the variation in distributions using the distance between percentile values rather than the standard deviation.…”

Associations of Physique with the Socioeconomic Factors of Family and Regional Origin in Chinese University Students

“…Schmitt L. H. et al also indicated there is a negative correlation between physique and altitude (18). This study has also reflected those results.…”

“…Ohsawa S. et al reported that there was a positive correlation between physique and latitude and a negative correlation between physique and temperature, precipitation or altitude (13). Schmitt L. H. et al expounded the negative correlation between physique and altitude (18).…”

“…Although they indicated that rich people's physique was larger than poor people's, differences in the racial and economic indices were not mentioned in their report (18). Takahashi E. discussed the difference between physique and socioeconomic levels of families in the central district of Sendai, Japan, in 1960, which were divided into 3 class upper (A), middle (B) and lower class (C).…”

Estimating male and female height inequality

“…The CV takes this effect into account and is therefore a more consistent and robust estimate of inequality (Blum and Baten, 2011;Schmitt and Harrison, 1988). The standard deviation  is expressed as a percentage of the mean .…”