@article{MummSchefflerHermanussen2022,
  author    = {Mumm, Rebekka and Scheffler, Christiane and Hermanussen, Michael},
  title     = {Locally structured correlation (LSC) plots describe inhomogeneity in normally distributed correlated bivariate variables},
  series = {Archives of Public Health},
  volume    = {80},
  journal   = {Archives of Public Health},
  publisher = {Springer Nature BMC},
  address   = {Bruxelles},
  issn      = {0778-7367},
  doi       = {10.1186/s13690-021-00748-4},
  pages     = {6},
  year      = {2022},
  abstract  = {Background The association between bivariate variables may not necessarily be homogeneous throughout the whole range of the variables. We present a new technique to describe inhomogeneity in the association of bivariate variables. Methods We consider the correlation of two normally distributed random variables. The 45° diagonal through the origin of coordinates represents the line on which all points would lie if the two variables completely agreed. If the two variables do not completely agree, the points will scatter on both sides of the diagonal and form a cloud. In case of a high association between the variables, the band width of this cloud will be narrow, in case of a low association, the band width will be wide. The band width directly relates to the magnitude of the correlation coefficient. We then determine the Euclidean distances between the diagonal and each point of the bivariate correlation, and rotate the coordinate system clockwise by 45°. The standard deviation of all Euclidean distances, named "global standard deviation", reflects the band width of all points along the former diagonal. Calculating moving averages of the standard deviation along the former diagonal results in "locally structured standard deviations" and reflect patterns of "locally structured correlations (LSC)". LSC highlight inhomogeneity of bivariate correlations. We exemplify this technique by analyzing the association between body mass index (BMI) and hip circumference (HC) in 6313 healthy East German adults aged 18 to 70 years. Results The correlation between BMI and HC in healthy adults is not homogeneous. LSC is able to identify regions where the predictive power of the bivariate correlation between BMI and HC increases or decreases, and highlights in our example that slim people have a higher association between BMI and HC than obese people. Conclusion Locally structured correlations (LSC) identify regions of higher or lower than average correlation between two normally distributed variables.},
  language  = {en}
}
@article{SchefflerRogolIancuetal.2021,
  author    = {Scheffler, Christiane and Rogol, Alan D. and Iancu, Mirela and Hanc, Tomasz and Moelyo, Annang Giri and Suchomlinov, Andrej and Lebedeva, Lidia and Limony, Yehuda and Musalek, Martin and Veldre, Gudrun and Godina, Elena Z. and Kirchengast, Sylvia and Mumm, Rebekka and Groth, Detlef and Tutkuviene, Janina and B{\"o}ker, Sonja and Ozer, Basak Koca and Navazo, Barbara and Spake, Laure and Koziel, Slawomir and Hermanussen, Michael},
  title     = {Growth during times of fear and emotional stress},
  series = {Human biology and public health},
  journal   = {Human biology and public health},
  number    = {2},
  publisher = {Universit{\"a}tsverlag Potsdam},
  address   = {Potsdam},
  issn      = {2748-9957},
  doi       = {10.52905/hbph.v2.15},
  year      = {2021},
  abstract  = {Twenty-one scientists met for this year's virtual conference on Auxology held at the University Potsdam, Germany, to discuss child and adolescent growth during times of fear and emotional stress. Growth within the broad range of normal for age and sex is considered a sign of good general health whereas fear and emotional stress can lead to growth faltering. Stunting is a sign of social disadvantage and poor parental education. Adverse childhood experiences affect child development, particularly in families with low parental education and low socioeconomic status. Negative effects were also shown in Indian children exposed prenatally and in early postnatal life to the cyclone Aila in 2009. Distrust, fears and fake news regarding the current Corona pandemic received particular attention though the effects generally appeared weak. Mean birth weight was higher; rates of low, very and extremely low birth weight were lower. Other topics discussed by the participants, were the influences of economic crises on birth weight, the measurement of self-confidence and its impact on growth, the associations between obesity, peer relationship, and behavior among Turkish adolescents, height trends in Indonesia, physiological neonatal weight loss, methods for assessing biological maturation in sportsmen, and a new method for skeletal age determination. The participants also discussed the association between acute myocardial infarction and somatotype in Estonia, rural-urban growth differences in Mongolian children, socio-environmental conditions and sexual dimorphism, biological mortality bias, and new statistical techniques for describing inhomogeneity in the association of bivariate variables, and for detecting and visualizing extensive interactions among variables.},
  language  = {en}
}
@article{MummHermanussen2022,
  author    = {Mumm, Rebekka and Hermanussen, Michael},
  title     = {The dilemma of misclassifying weight in short and in historic population},
  series = {Human biology and public health},
  volume    = {2021},
  journal   = {Human biology and public health},
  number    = {3, Summer School Supplement},
  publisher = {Universit{\"a}tsverlag Potsdam},
  address   = {Potsdam},
  issn      = {2748-9957},
  doi       = {10.52905/hbph2021.3.28},
  pages     = {7},
  year      = {2022},
  abstract  = {Background: Clinicians often refer anthropometric measures of a child to so-called "growth standards" and "growth references. Over 140 countries have meanwhile adopted WHO growth standards. Objectives: The present study was conducted to thoroughly examine the idea of growth standards as a common yardstick for all populations. Weight depends on height. We became interested in whether also weight-for-height depends on height. First, we studied the age-group effect on weight-for-height. Thereafter, we tested the applicability of weight-for-height references in short and in historic populations. Sample and Methods: We analyzed body height and body weight and weight-for-height of 3795 healthy boys and 3726 healthy girls aged 2 to 5 years measured in East-Germany between 1986 and 1990. We chose contemporary height and weight charts from Germany, the UK, and the WHO growth chart and compared these with three geographically commensurable growth charts from the end of the 19th century. Results: We analyzed body height and body weight and weight-for-height of 3795 healthy boys and 3726 healthy girls aged 2 to 5 years measured in East-Germany between 1986 and 1990. We chose contemporary height and weight charts from Germany, the UK, and the WHO growth chart and compared these with three geographically commensurable growth charts of the end of the 19th century. Conclusion: Weight-for-height depends on age and sex and apart from the nutritional state, reflects body proportion and body built particularly during infancy and early childhood. Populations with a relatively short average height are prone to high values of weight-for-height for arithmetic reasons independent of the nutritional state.},
  language  = {en}
}