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Human size changes over time with worldwide secular trends in height, weight, and body mass index (BMI). There is general agreement to relate the state of nutrition to height and weight, and to ratios of weight-to-height. The BMI is a ratio. It is commonly used to classify underweight, overweight and obesity in adults. Yet, the BMI is inappropriate to provide any immediate information on body composition.
It is accepted that the BMI is “a simple index to classify underweight, overweight and obesity in adults”. It is stated that “policies, programmes and investments need to be “nutrition-sensitive”, which means they must have positive impacts on nutrition”. It is also stated that “a need for policies that address all forms of malnutrition by making healthy foods accessible and affordable, while restricting unhealthy foods through fiscal and regulatory restrictions“. But these statements are neither warranted by arithmetic considerations, nor by historic evidence.
Measuring the BMI is an appropriate screening tool for detecting an unusual weight-to-height ratio, but the BMI is an inappropriate tool for estimating body composition, or suggesting medical and health policy decisions.
As tall as my peers
(2018)
Background: We define migrants as people who move from their place of birth to a new place of residence. Migration usually is directed by "Push-Pull" factors, for example to escape from poor living conditions or to find more prosperous socio-economic conditions. Migrant children tend to assimilate quickly, and soon perceive themselves as peers within their new social networks. Differences exist between growth of first generation and second generation migrants. Methods: We review body heights and height distributions of historic and modern migrant populations to test two hypotheses: 1) that migrant and adopted children coming from lower social status localities to higher status localities adjust their height growth toward the mean of the dominant recipient social network, and 2) social dominant colonial and military migrants display growth that significantly surpasses the median height of both the conquered population and the population of origin. Our analytical framework also considered social networks. Recent publications indicate that spatial connectedness (community effects) and social competitiveness can affect human growth. Results: Migrant children and adolescents of lower social status rapidly adjust in height towards average height of their hosts, but tend to mature earlier, and are prone to overweight. The mean height of colonial/military migrants does surpass that of the conquered and origin population. Conclusion: Observations on human social networks, non-human animal strategic growth adjustments, and competitive growth processes strengthen the concept of social connectedness being involved in the regulation of human migrant growth.
Background: Assessing short-term growth in humans is still fraught with difficulties. Especially when looking for small variations and increments, such as mini growth spurts, high precision instruments or frequent measurements are necessary. Daily measurements however require a lot of effort, both for anthropologists and for the subjects. Therefore, new sophisticated approaches are needed that reduce fluctuations and reveal underlying patterns.
Objectives: Changepoints are abrupt variations in the properties of time series data. In the context of growth, such variations could be variation in mean height. By adjusting the variance and using different growth models, we assessed the ability of changepoint analysis to analyse short-term growth and detect mini growth spurts.
Sample and Methods: We performed Bayesian changepoint analysis on simulated growth data using the bcp package in R. Simulated growth patterns included stasis, linear growth, catch-up growth, and mini growth spurts. Specificity and a normalised variant of the Matthews correlation coefficient (MCC) were used to assess the algorithm’s performance. Welch’s t-test was used to compare differences of the mean.
Results: First results show that changepoint analysis can detect mini growth spurts. However, the ability to detect mini growth spurts is highly dependent on measurement error. Data preparation, such as ranking and rotating time series data, showed negligible improvements. Missing data was an issue and may affect the prediction quality of the classification metrics.
Conclusion: Changepoint analysis is a promising tool to analyse short-term growth. However, further optimisation and analysis of real growth data is needed to make broader generalisations.
Carl Bergmann was an astute naturalist and physiologist. His ideas about animal size and shape were important advances in the pre-Darwinian nineteenth century. Bergmann's rule claims that that in cold climates, large body mass increases the ratio of volume-to-surface area and provides for maximum metabolic heat retention in mammals and birds. Conversely, in warmer temperatures, smaller body mass increases surface area relative to volume and allows for greater heat loss. For humans, we now know that body size and shape are regulated more by social-economic-political-emotional (SEPE) factors as well as nutrition-infection interactions. Temperature has virtually no effect. Bergmann's rule is a "just-so" story and should be relegated to teaching and scholarship about the history of science. That "rule" is no longer acceptable science and has nothing to tell us about physiological anthropology.
Background: Multiple linear correlations between parameters can be shown in correlation matrices. Correlations can be ranked, but can also be visualized in network graphs. Yet, translating a correlation matrix into a network graph is not trivial. In view of a popular child game, we propose to name this method St. Nicolas House Analysis. Material and methods: We present a new method (St. Nicolas House Analysis) that helps translating correlation matrices into network graphs. The performance of this and other network reconstruction methods was tested in randomly created virtual scale-free networks, networks consisting of bands or hubs, using balanced classification rate and the F1-Score for correctly predicting existing and non-existing edges. Thereafter we analyzed anthropometric data and information on parental education, obtained from an anthropometric survey in 908 Indonesian boys and 808 Indonesian girls. Seven parameters were analyzed: child height standard deviation score (hSDS), child BMI standard deviation scores (BMI_SDS), mid-upper-arm circumference (MUAC), mean thickness of subscapular and triceps skinfold (mean SF), and elbow breadth; as well as maternal and paternal education (years of schooling). The parameters were considered as the nodes of the network; the edges represent the correlations between the nodes. Results: Performance measures, balanced classification rate and the F1-score, showed that St. Nicolas’ House Analysis was superior to methods using sophisticated correlation value thresholds and methods based on partial correlations for analyzing bands and hubs. We applied this method also in an Indonesia data set. Ranking correlations showed the direct association between parental education and child growth. Conclusion: St. Nicolas House Analysis confirmed that growth of Indonesian school children directly depends on maternal education, with no evidence that this effect is mediated by the state of nutrition.
Objective:
Stunting (height-for-age < −2 SD) is one of the forms of undernutrition and is frequent among children of low- and middle-income countries. But stunting perSe is not a synonym of undernutrition. We investigated association between body height and indicators of energetic undernutrition at three critical thresholds for thinness used in public health: (1) BMI SDS < −2; (2) mid-upper arm circumference divided by height (MUAC (mm) × 10/height (cm) < 1·36) and (3) mean skinfold thickness (SF) < 7 mm and to question the reliability of thresholds as indicators of undernutrition.
Design:
Cross-sectional study; breakpoint analysis.
Setting:
Rural and urban regions of Indonesia and Guatemala – different socio-economic status (SES).
Participants:
1716 Indonesian children (6·0–13·2 years) and 3838 Guatemalan children (4·0–18·9 years) with up to 50 % stunted children.
Results:
When separating the regression of BMI, MUAC or SF, on height into distinguishable segments (breakpoint analysis), we failed to detect relevant associations between height, and BMI, MUAC or SF, even in the thinnest and shortest children. For BMI and SF, the breakpoint analysis either failed to reach statistical significance or distinguished at breakpoints above critical thresholds. For MUAC, the breakpoint analysis yielded negative associations between MUAC/h and height in thin individuals. Only in high SES Guatemalan children, SF and height appeared mildly associated with R2 = 0·017.
Conclusions:
Currently used lower thresholds of height-for-age (stunting) do not show relevant associations with anthropometric indicators of energetic undernutrition. We recommend using the catch-up growth spurt during early re-feeding instead as immediate and sensitive indicator of past undernourishment. We discuss the primacy of education and social-economic-political-emotional circumstances as responsible factors for stunting.
Background: Biological age markers are a crucial indicator whether children are decelerated in growth tempo. Skeletal maturation is the standard measure. Yet, it relies on exposing children to x-radiation. Dental eruption is a potential, but highly debated, radiation free alternative.
Objectives: We assess the interrelationship between dental eruption and other maturational markers. We hypothesize that dental age correlates with body height and skeletal age. We further evaluate how the three different variables behave in cohorts from differing social backgrounds.
Sample and Method: Dental, skeletal and height data from the 1970s to 1990s from Guatemalan boys were converted into standard deviation scores, using external references for each measurement. The boys, aged between 7 and 12, derived from different social backgrounds (middle SES (N = 6529), low-middle SES (N = 736), low SES Ladino (N = 3653) and low SES Maya (N = 4587).
Results: Dental age shows only a weak correlation with skeletal age (0.18) and height (0.2). The distinction between cohorts differs according to each of the three measurements. All cohorts differ significantly in height. In skeletal maturation, the middle SES cohort is significantly advanced compared to all other cohorts. The periodically malnourished cohorts of low SES Mayas and Ladinos are significantly delayed in dental maturation compared to the well-nourished low-middle and middle class Ladino children.
Conclusion: Dental development is an independent system, that is regulated by different mechanisms than skeletal development and growth. Tooth eruption is sensitive to nutritional status, whereas skeletal age is more sensitive to socioeconomic background.
Aim Growth is both a matter of amplitude and tempo. We aimed to develop references for body height, body weight and body mass index (BMI) with respect to tempo of maturity. Methods Data obtained from the German KiGGS study (2003-2006) on body height, body weight and presence or absence of the menarche were re-analysed in 3776 girls, aged 10-17years. We developed smoothed centiles for BMI-, body-height- and body-weight-for-age using the LMS method for premenarcheal and postmenarcheal girls. Results Body height, body weight and BMI differed significantly between premenarcheal and postmenarcheal girls. On average, postmenarcheal girls aged 11-17years were 5.3cm taller and 9.7kg heavier, and their BMI was 2.9kg/m2 higher than in premenarcheal girls of the same calendar age. Conclusion Adolescent BMI rises with calendar age and biological age. New reference charts for adolescent girls aged 10-18years were generated to be inserted into the currently used references to avoid misclassifying underweight and overweight pubertal girls.
The aim of this methodological anthropometric study was to compare direct anthropometry and digital two- dimensional photogrammetry in 18 male and 27 female subjects, aged 24 to 65 years, from Potsdam, Germany. In view of the rising interest in reliable biometric kephalofacial data, we focussed on head and face measurements. Out of 34 classic facial anatomical landmarks, 27 landmarks were investigated both by direct anthropometry and 2D-photogrammetry; 7 landmarks could not be localized by 2D-photogrammetry. Twenty-six kephalofacial distances were analysed both by direct anthropometry and digital 2D-photogrammetry. Kephalofacial distances are on average 7.6% shorter when obtained by direct anthropometry. The difference between the two techniques is particularly evident in total head height (vertex-gnathion) due to the fact that vertex is usually covered by hair and escapes from photogrammetry. Also the distances photographic sellion-gnathion (1.3 cm, i. e. 11.6%) and nasal-gnathion (1.2 cm, i. e. 9.4%) differ by more than one centimetre. Differences below 0.5 cm between the two techniques were found when measuring mucosa-lip-height (2.2%), gonia (3.0%), glabella-stomion (3.9%), and nose height (glabella-subnasal) (4.0%). Only the estimates of forehead width were significantly narrower when obtained by 2D-photogrammetry (-1.4 cm, -13.1%). The methodological differences increased with increasing magnitude of the kephalometric distance. Apart from these limitations, both techniques are similarly valid and may replace each other.
Auxology has developed from mere describing child and adolescent growth into a vivid and interdisciplinary research area encompassing human biologists, physicians, social scientists, economists and biostatisticians. The meeting illustrated the diversity in auxology, with the various social, medical, biological and biostatistical aspects in studies on child growth and development.