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Institute
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
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: 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.