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Development of birthweight and length for gestational age and sex references in Yucatan, Mexico
(2022)
Objective To develop sex- and gestational age specific reference percentiles and curves for birth weight and length for Yucatec neonates using data from birth registers of infants born during 2015-2019. Material and methods Observational, descriptive, epidemiologic study in a 5-year period including every registered birth in the state of Yucatan, Mexico using birth registries. A total of 158 432 live, physically healthy singletons (76 442 females and 81 990 males) between 25 and 42 weeks of gestation were included in the analysis. We used the LMS method to construct smoothed reference centiles (3rd, 10th, 25th, 50th, 75th, 95th, and 97th) and curves for males and females separately. Results Mean maternal age was 26 (SD = 6.22) years. Fifty-two percent of births occurred by vaginal delivery, 37% were firstborn and similar proportions were second (33%) and third or more (30%) born. 5.5% of newborns included in the references corresponds to neonates born before 37 weeks of gestation (5.9% boys and 5.1% girls). In both sexes, the percentage of infants with a birthweight less than 2500 g was 6.7%. The birthweight at the 50th percentile for males and females at 40 weeks of gestation in this cohort was 3256 and 3167 g, respectively, and the corresponding values for birth length were 50.23 and 49.84 cm (mean differences between sexes: 89 g and 0.40 cm, respectively). Conclusion The reference percentile and curves developed in this study are useful for research purposes and can help health practitioners to assess the biological status of infants born in Yucatan.
Background: It has been shown that modern life style with reduced physical activity can lead to lower bone accumulation. Also a decline trend in external skeletal robustness in children and young adolescents, measured by the Frame Index (FI), seems to have a parallel trend with the increase in overweight and obesity. Based on these findings we estimate that likely, the FI should be changed after a decade in the Argentinean population as well as in others population of the world. Thereby, the aim of the present study was to describe, using the FI, the pattern of external skeletal robustness in school children aged 6-14 years from two cohorts of Argentina (Puerto Madryn, Chubut) and to compare them with the European reference (Czech Republic, Germany, Poland and Russia). Methods: Elbow breadth and height of Puerto Madryn school children were collected in two cross-sectional studies conducted between 2001-2006 (cohort 1 = C1) and 2014-2016 (cohort 2 = C2). Percentiles (P) values, for males and females, from C1 and C2 were calculated combining the LMSmethod and its extension. A t-test has been used to compare, by age and sex, the FI values between the Argentinean cohorts and the European reference (ER). Then, in order to know the percentage of the variation of the percentiles values between cohorts, as well as with ER, percent differences between means (PDM%) were employed. Results: FI from Argentinean cohorts differed significantly from ER. Even more, C2 was not only smaller than ER, but also than C1. In males, C1-C2 showed significant differences at 6-8, 11 and 12 years and in females at all ages. Then, respect to ER each Argentinean cohort showed significant differences in males of C1 at 6, 12-14 years and in females at 6 and 11-14 years; and of C2, in both sexes, from 6 to 14 years. The PDM% values for elbow breadth of male were negative in ER-C1 in all percentiles analyzed; in ER-C2 positive (P3 and P50) and negative (P97) and C1-C2 recorded positive values. In females, elbow breadth showed negative values for ER-C1 (P50 and P97), and positive for the remaining values. Finally, height registered, in both sexes, negative values in ER-C1 (except P97 in females), ER-C2 and C1-C2. Conclusions: After ten years of the first study carried on in Puerto Madryn, school children show a negative trend in the external skeletal robustness. Additionally, the children of both Argentinean cohorts have lower values compared to the European reference, and mainly the actual cohort. This situation would be explained, in part, by the progressive increase over time of overweight and obesity as consequence, among others, of the change in the quantity and/or quality of the food that children have access to and with the physical activity they do at school and outside.
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 degrees 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 degrees. 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.
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.
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.
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.
Changes in body height throughout extended historic periods are very complex and dynamic processes. Thispilot study aimed to investigate the pattern of longitudinal height z-scores changes in children before and after entering kindergarten. In summer 2016, we measured height and weight of 32 children from 4 groups of two kindergartens aged 3–6 years. All ages were centered according to the age of entry into the kindergarten. For each child we determined mean z-scores for height before and after entering the kindergarten, and assessed the variances for each kindergarten group. Twenty-two children targeted in height z-scores towards average height of their respective kindergarten group, 10 children did not. Due to the small numbers, the convergence in height variance however, remained insignificant (chi-squared independence test, p = 0.127). Additional studies with larger sample sizes are needed to confirm this pilot study.
Impact of normal weight obesity on fundamental motor skills in pre-school children aged 3 to 6 years
(2017)
Normal weight obesity is defined as having excessive body fat, but normal BMI. Even though previous research revealed that excessive body fat in children inhibited their physical activity and decreased motor performance, there has been only little evidence about motor performance of normal weight obese children. This study aims to establish whether normal weight obese pre-school children aged 3-6 years will have a significantly worse level of fundamental motor skills compared to normal weight non-obese counterparts. The research sample consisted of 152 pre-schoolers selected from a specific district of Prague, the Czech Republic. According to values from four skinfolds: triceps, subscapula, suprailiaca, calf, and BMI three categories of children aged 3-6 years were determined: A) normal weight obese n = 51; B) normal weight non-obese n = 52; C) overweight and obese n = 49. The Movement Assessment Battery for Children (MABC-2) was used for the assessment of fundamental motor skills. Normal weight obese children had significantly higher amount of adipose tissue p < 0.001 than normal weight non-obese children but the same average BMI. Moreover, normal weight obese children did not have significantly less amount of subcutaneous fat on triceps and calf compared to their overweight and obese peers. In majority of MABC-2 tests, normal weight obese pre-schoolers showed the poorest performance. Moreover, normal weight obese children had significantly worse total standard score = 38.82 compared to normal weight non-obese peers = 52.27; p < 0.05. In addition, normal weight obese children had a more than three times higher frequency OR = 3.69 CI95% (1.10; 12.35) of severe motor deficit performance <= 5th centile of the MABC-2 norm. These findings are strongly alarming since indices like BMI are not able to identify normal weight obese individual. We recommend verifying real portion of normal weight obese children as they are probably in higher risk of health and motor problems than overweight and obese population due to their low lean mass.
Background:
Physical growth of children and adolescents depends on the interaction of genetic and environmental factors e.g. diet and living conditions. Aim: We aim to discuss the influence of socioeconomic situation, using income inequality and GDP per capita as indicators, on body height, body weight and the variability of height and weight in infants and juveniles.
Material and methods:
We re-analyzed data from 439 growth studies on height and weight published during the last 35 years. We added year-and country-matched GDP per capita (in current US$) and the Gini coefficient for each study. The data were divided into two age groups: infants (age 2) and juveniles (age 7). We used Pearson correlation and principal component analysis to investigate the data.
Results:
Gini coefficient negatively correlated with body height and body weight in infants and juveniles. GDP per capita showed a positive correlation with height and weight in both age groups. In infants the standard deviation of height increases with increasing Gini coefficient. The opposite is true for juveniles. A correlation of weight variability and socioeconomic indicators is absent in infants. In juveniles the variability of weight increases with declining Gini coefficient and increasing logGDP per capita.
Discussion:
Poverty and income inequality are generally associated with poor growth in height and weight. The analysis of the within-population height and weight variations however, shows that the associations between wealth, income, and anthropometric parameters are very complex and cannot be explained by common wisdom. They point towards an independent regulation of height and weight.
Background: In our modern world, the way of life in nutritional and activity behaviour has changed. As a consequence, parallel trends of an epidemic of overweight and a decline in external skeletal robusticity are observed in children and adolescents. Aim: We aim to develop reference centiles for external skeletal robusticity of European girls and boys aged 0 to 18 years using the Frame Index as an indicator and identify population specific age-related patterns. Methods: We analysed cross-sectional & longitudinal data on body height and elbow breadth of boys and girls from Europe (0-18 years, n = 41.679), India (7-18 years, n = 3.297) and South Africa (3-18 years, n = 4.346). As an indicator of external skeletal robusticity Frame Index after Frisancho (1990) was used. We developed centiles for boys and girls using the LMS-method and its extension. Results: Boys have greater external skeletal robusticity than girls. Whereas in girls Frame Index decreases continuously during growth, an increase of Frame Index from 12 to 16 years in European boys can be observed. Indian and South African boys are almost similar in Frame Index to European boys. In girls, the pattern is slightly different. Whereas South African girls are similar to European girls, Indian girls show a lesser external skeletal robusticity. Conclusion: Accurate references for external skeletal robusticity are needed to evaluate if skeletal development is adequate per age. They should be used to monitor effects of changes in way of life and physical activity levels in children and adolescents to avoid negative health outcomes like osteoporosis and arthrosis.