570 Biowissenschaften; Biologie
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Modeling a secular trend by Monte Carlo simulation of height biased migration in a spatial network
(2017)
Background: In a recent Monte Carlo simulation, the clustering of body height of Swiss military conscripts within a spatial network with characteristic features of the natural Swiss geography was investigated. In this study I examined the effect of migration of tall individuals into network hubs on the dynamics of body height within the whole spatial network. The aim of this study was to simulate height trends. Material and methods: Three networks were used for modeling, a regular rectangular fishing net like network, a real world example based on the geographic map of Switzerland, and a random network. All networks contained between 144 and 148 districts and between 265-307 road connections. Around 100,000 agents were initially released with average height of 170 cm, and height standard deviation of 6.5 cm. The simulation was started with the a priori assumption that height variation within a district is limited and also depends on height of neighboring districts (community effect on height). In addition to a neighborhood influence factor, which simulates a community effect, body height dependent migration of conscripts between adjacent districts in each Monte Carlo simulation was used to re-calculate next generation body heights. In order to determine the direction of migration for taller individuals, various centrality measures for the evaluation of district importance within the spatial network were applied. Taller individuals were favored to migrate more into network hubs, backward migration using the same number of individuals was random, not biased towards body height. Network hubs were defined by the importance of a district within the spatial network. The importance of a district was evaluated by various centrality measures. In the null model there were no road connections, height information could not be delivered between the districts. Results: Due to the favored migration of tall individuals into network hubs, average body height of the hubs, and later, of the whole network increased by up to 0.1 cm per iteration depending on the network model. The general increase in height within the network depended on connectedness and on the amount of height information that was exchanged between neighboring districts. If higher amounts of neighborhood height information were exchanged, the general increase in height within the network was large (strong secular trend). The trend in the homogeneous fishnet like network was lowest, the trend in the random network was highest. Yet, some network properties, such as the heteroscedasticity and autocorrelations of the migration simulation models differed greatly from the natural features observed in Swiss military conscript networks. Autocorrelations of district heights for instance, were much higher in the migration models. Conclusion: This study confirmed that secular height trends can be modeled by preferred migration of tall individuals into network hubs. However, basic network properties of the migration simulation models differed greatly from the natural features observed in Swiss military conscripts. Similar network-based data from other countries should be explored to better investigate height trends with Monte Carlo migration approach.
Body height has traditionally been looked upon as a mirror of the condition of society, short height being an indicator of poor nutritional status, poor education, and low social status and income. This view has recently been questioned. We aimed to quantify the effects of nutrition, education, sibship size, and household income, factors that are conventionally considered to be related to child growth, on body height of children and adolescents raised under urban Indian conditions. Sample and methods: We re-analyzed several anthropometric measurements and questionnaires with questions on sibship size, fathers’ and mother’s education, and monthly family expenditure, from two cross-sectional growth studies performed in Kolkata, India. The first Kolkata Growth Study (KG1) took place in 1982-1983, with data on 825 Bengali boys aged 7 to 16 years; and the second Kolkata Growth Study (KG2) between 1999 and 2011 with data of 1999 boys aged 7 to 21 years from Bengali Hindu families, and data of 2195 girls obtained between 2005 and 2011. Results: Indian children showed positive insignificant secular trends in height and a significant secular trend in weight and BMI between between 1982 and 2011. Yet, multiple regression analysis failed to detect an association between nutritional status (expressed in terms of skinfold thickness), monthly family expenditure and sibship size with body height of these children. The analysis only revealed an influence of parental education on female, but not on male height. Conclusion: We failed to detect influences of nutrition, sibship size, and monthly family expenditure on body height in a large sample of children and adolescents raised in Kolkata, India, between 1982 and 2011. We found a mild positive association between parental education and girls’ height. The data question current concepts regarding the impact of nutrition, and household and economic factors on growth, but instead underscore the effect of parental education.
In nature, dominance is often shown by body size; even in humans many studies report that social status is associated with body height. In today's society, educational status is an important factor for social classification. Since growing children do not have their own educational or social status, they are often affected by the status of their parents. Therefore, the question appears, whether parental educational status measurably affects the growth of a child. If so, is this explainable by the nutritional factors? To test this hypothesis, seven different Indian data sets where reexamined using the St. Nicolas House Analysis. The results show a direct association between parental education and body height (hSDS) of the child, but there was no influence of parental education on the nutritional status. We conclude that education has a direct effect on height that is not mediated via nutrition.
Background: Child growth is a dynamic process. When measured at short intervals, children’s growth shows characteristic patterns that can be of great importance for clinical purposes.
Objective: To study whether measuring height on a daily basis using an APP is practicable and user-friendly.
Methods: Recruitment took place via Snowball Sampling. Thirteen out of 14 contacted families signed up for a study period of 12 weeks with altogether 22 healthy children aged 3 to 13 years (response rate 93%). The study started with a visit to the family home for the setup of the measurement site, conventional height measuring and initial training of the new measurement process. Follow-up appointments were made at four, eight and 12 weeks. The children’s height was measured at daily intervals at their family homes over a period of three months.
Results: The parents altogether recorded 1704 height measurements and meticulously documented practicability and problems when using the device.
A 93% response rate in recruitment was achieved by maintaining a high motivation within the families. Contact with the principal investigator was permanently available, including open communication, personal training and attendance during the appointments at the family homes.
Conclusion: Measuring height by photographic display is interesting for children and parents and can be used for height measurements at home. A positive response rate of 13 out of 14 families with altogether 22 children highlights feasible recruitment and the high convenience and user-friendliness of daily APP-supported height measurements. Daily APP measurements appear to be a promising new tool for longitudinal growth studies.
Background: We investigated height of Norwegian conscripts in view of the hypothesis of a "community effect on height" using autocorrelation analysis of district heights within a time-span of 20 years at the end of the 19th century and correlations between neighboring districts at this time. Material and methods: After digitalizing available body height data of Norwegian draftees in 1877-1878, 1880 (averaged as 1878), and 1895-1897 (averaged as 1896) we calculated the magnitude of autocorrelation of body height within the same municipality at different time points. Furthermore, we generated three different neighborhood networks, (1) based on Euclidean distances, (2) a minimum spanning tree build on those distances, (3) a network founded on real world road connections. The networks were used to determine the correlation between body height of neighboring districts depending on the number of edges required to connect two municipalities. Results: The autocorrelation value for body heights was around r = 0.5 (for all p < 0.001) in the years 1878 and 1896. The correlation between neighboring districts varied in the Euclidean distance based network between 0.47 and 0.27 approximately for both years in a sorted order, descending from nearest (0-50 km) to farthest (150-200 km, for all p < 0.001). First order neighbors in the minimum spanning tree network correlation was 0.36 in 1878 and 0.42 in 1896 (for all p < 0.001). The values of neighbor correlation in the road connection based network ranged in 1878 from 0.42 (first order neighbors) to 0.17 (forth order neighbors, for all p < 0.01) and in 1896 from 0.46 (first order neighbors) to 0.12 (forth order neighbors, for all p < 0.05). Conclusion: This initial study of Norwegian conscript height data from the 19th century showed significant medium sized effects for the within district autocorrelation between 1878 and 1896 as well as medium neighborhood correlation, slightly lower in comparison to a recent study regarding Swiss conscripts. Digitalizing more data from other years in this and later time spans as well as using older road and ship connections instead of the actual road data might stabilize and improve those findings.
The aim of the study was to investigate the correlation of heights of conscripts living in neighboring districts in Poland. The study used 10% of a nationally representative sample of 26,178 males 18.5-19.5 years old examined during the National survey of Polish conscripts conducted in 2001. The sample represented all regions and social strata of the country and included 354 different districts within 16 voivodships (provinces). Analyses were performed with the R statistical software. A small but significant correlation (0.24, p < 0.0001) was observed for height between 1st order neighboring districts. Correlations decreased with increased distances between neighboring districts, but remained significant for 7th node neighbors (0.18, p < 0.0001). Regarding voivodships (provinces), average height showed a geographical trend from the northwest (relatively tall) to the southeast (relatively short), and the correlation was stronger for first order neighboring provinces (0.796, p < 0.001). This study revealed clusters of tall people and short people, providing a support for hypothesis of the community effect in height. Small correlations between 1st order neighbors than in another country (Switzerland) may be associated with differences in geography, since in Poland there are no natural barriers (e.g., mountains) and road infrastructure is well-developed.
Background: We investigated average body height in the central provinces of the Russian empire in the middle of XIX century in view of the concept of "community effects on height". We analyzed body height correlations between neighboring districts at this time. We added information about secular changes in body height during the 19th century of this territory. Material and methods: The study used height data of conscripts, which were born in the years 1853-1863, and age 21 at the time of measurement. The territory of seven provinces was considered as a network with 105 nodes, each node representing one district with information on average male body height. In order to define neighboring districts three different approaches were used: based on the "common borders" method, based on Euclidean distances (from 60 to 120 km), based on real road connections. Results: Small but significant correlation coefficients were observed between 1st order districts in the network based on Euclidean distance of 100 km (r = 0.256, p-value = 0.006) and based on "the common borders" approach (r = 0.25, p-value = 0.02). Wherein no significant correlations were observed in the network based on road connections and between second order neighbors regardless of the method. Conclusion: Height correlation coefficients between 1st order neighboring districts observed in the Russian districts were very similar to values observed in the Polish study (r = 0.24). The considered Russian territory and the territory of Poland have a lot in common. They consist of both plains without mountains. In contradistinction to Poland the transport infrastructure in Russia was weakly developed in the middle of XIX century. In addition, the mobility of people was limited by serfdom. In this context the absent of significant correlation of second order neighbors can be explained by low population density and lack of migration and communication between the districts.
Introduction: Body height is influenced by biological factors such as genetics, nutrition and health, but also by the social network, and environmental and economical factors. During centuries, the Japanese society has developed on islands. This setting provides ideal natural conditions for studying the influence of social networks on human height. Material and methods: We investigated body height of male Japanese students aged 17.5 years obtained in 47 prefectures, from the Japanese school health survey of the years 1955, 1975, 1995, and 2015. Results: Japanese students increased in height from 163.23 cm in 1955 to 170.84 cm in 1995, with no further increase thereafter (170.63 cm in 2015). Students living in neighboring prefectures were similar in height. The correlation of height between neighboring prefectures ranged between r = 0.79 and r = 0.49 among first degree neighbors, between r = 0.49 and r = 0.21 among second degree neighbors and dropped to insignificance among third degree neighbors indicating psychosocial effects of the community on body height. Tall stature and short stature prefectures did not remain tall or short throughout history. Autocorrelations of height within the same prefectures decreased from the 20 years periods of 1955-1975, 1975-1995 and 1995-2015 (r = 0.52, r = 0.61, r = 0.63, respectively) to the 40 years periods of 1955-1995 and 1975-2015 (r = 0.49, r = 0.52), down to the 60 years period of 1955-2015 (r = 0.27), indicating significant volatility of height. Conclusion: Body height of 17.5 years old Japanese students increased since 1955. Body height depended on height of the neighboring prefecture, but was volatile with decreasing autocorrelation during a period of 60 years.