Simple method for developing percentile growth curves for height and weight

Growth in height and its association with overweight and obesity in Mexican children: an evaluation based on a nationally representative sample (ENSANUT 2018)

The present study aimed to estimate the height growth curve for Mexican boys and girls based on their body mass index (BMI) status (normal and overweight/obese) and to develop a height Lambda, Mu, and Sigma (LMS) growth reference for Mexican children aged 2 to 18 years.

Methods

Chronological age and height records (7,097 boys and 6,167 girls) were obtained from the Mexican National Survey of Health and Nutrition database. Height growth curves were fitted using the Preece-Baines 1 (PB1) model and the LMS method.

Results

Age at peak height velocity (APHV) was 12.4 and 12.7 years for overweight-obese and normal-weight boys, respectively, and was 9.6 and 10.4 years for overweight-obese and normal-weight girls, respectively. Growth velocity was higher at the age of take-off (TO) in overweight-obese children than in normal-weight children (5.2 cm/year vs. 5 cm/year in boys and 6.1 cm/year vs. 5.6 cm/year in girls); nevertheless, the growth velocity at APHV was higher for normal-weight children than for overweight-obese children (7.4 cm/year vs. 6.6 cm/year in boys and 6.8 cm/year vs. 6.6 cm/year in girls, respectively). Distance curves developed in the present study and by the World Health Organization (WHO) using LMS showed similar values for L and S parameters and a higher M value compared with the WHO reference values.

Conclusion

This study concluded that overweight-obese children had earlier APHV and lower PHV than normal-weight children. Furthermore, Mexican children and adolescents were shorter than the WHO growth reference by age and sex.

Preece-Baines 1 model validation for cross-sectional data in male soccer players according to maturity status

AIM

The aim of the present study was to compare the Preece-Baines 1 (PB1) model fit between longitudinal and cross-sectional data in male soccer players and to adjust the height growth curve by maturity status.

METHODS

A final sample of 57 male Portuguese soccer players from professional soccer academies was included. Longitudinal height records were measured between 8 and 17 times in each subject from 2-8 years to 14-17 years. Additionally, longitudinal height records were used as cross-sectional data along with 1087 cross-sectional height records taken from 602 Portuguese soccer players. Skeletal age was estimated by Tanner-Whitehouse III method from a left hand-wrist radiograph. Age at peak height velocity (PHV) was estimated by PB1 model for longitudinal and cross-sectional data and by maturity status.

RESULTS

No significant differences were found between all the longitudinal estimates of 57 players and the random cross-sectional samples for, S1 parameter and for growth velocity at PHV, at TO, and for age at PHV. The age at PHV in early, on-time, and late maturers were 12.26, 12.9, and 13.58 years, respectively.

CONCLUSION

PB1 adjusted the height growth of Portuguese male soccer players from cross-sectional data, obtaining an estimate PHV very similar to that found from longitudinal data. A maturity time difference of ≈0.6 years was found between the age at PHV of on-time, early, and on-time and late maturity state.

Turner Syndrome Growth Charts: A Western India Experience

BACKGROUND AND OBJECTIVES

Disease specific growth charts are useful to monitor growth and disease progress in specific disorders such as Turner syndrome. As there is a paucity of data on spontaneous growth of Indian girls with Turner syndrome, the objectives were to construct reference curves for height and assess height velocity in Indian girls with Turner syndrome from 5 centers from western India.

MATERIAL AND METHODS

Three hundred forty-eight readings of height and weight on 113 genetically proven girls with Turner Syndrome from 5 centers from western India were collected and retrospectively analyzed. Data were collected over the last 2 decades (GH treatment naive girls were included). The method described by Lyon et al. was used to compute smoothed standard deviations and percentiles for height. For computing growth velocities, longitudinal data were used on 104 untreated girls (longitudinal readings for height for a minimum of 3 years were used). Midparental height z scores (MPHZ) were computed.

RESULTS

In girls with Turner syndrome, the mean adult height was found to be 140.1 cm. Height velocity was low at all ages compared to normal girls with a notable difference beyond the age of 10 years where normally, a growth spurt is expected. The MPH Z-score correlated positively with the height Z-score. The 3^rd, 50^th, and 97^th height percentiles of Turner girls at all ages were lower than normal girls' charts.

CONCLUSION

Turner syndrome charts for height are presented; these charts may be used to monitor growth in girls with Turner syndrome.

Indian Growth References from 0-18-Year-Old children and Adolescents - A Comparison of Two Methods

BACKGROUND AND AIMS

For updating growth references, large datasets are usually required; collection of these data are expensive and cumbersome. Using a combination of regression equations, Preece Baines model and global LMS values, synthetic growth references for the target population can be generated. The objective of this study is to compare growth references created from continuous anthropometric data using LMS method versus those created synthetically from anthropometric means at key ages.

METHODS

De-identified data on 46421 children (26037 boys) from 0-18 years of age from several multicentric studies conducted by the authors' group (2007 to 2017) were included in this study; growth references were constructed using the LMS method. For the production of synthetic references, arithmetic means of heights and weights at key ages were used and global LMS values were used from literature.

RESULTS

There was no difference in the medians for height, weight and BMI between the references created by the two methods. The extreme percentile values for height were similar (P < 0.05). However, the spread of values for weight and BMI was narrower in the synthetic references.

CONCLUSION

Growth references produced from continuous data differ from those produced synthetically using anthropometric means mainly at the extreme centiles for weight and body mass index; synthetic references take into consideration global trends over several decades.

Do Class III patients have a different growth spurt than the general population?

INTRODUCTION

Understanding the timing and length of the growth spurt of Class III prognathic patients is fundamental to the strategy of interceptive orthopedic orthodontics as well as to the timing of orthognathic surgery. Consequently, this study was undertaken to determine whether there are any significant differences in the stature growth pattern of Class III subjects compared with non-Class III subjects and the general population.

METHODS

Twelve-year longitudinal stature growth data were collected for 402 randomly selected adolescents in the general population, 55 Class III mandibular prognathic patients, and 37 non-Class III patients. The growth data were analyzed by using the traditional linear interpolation method and nonlinear growth functions. The 6 stature growth parameters were measured: age at takeoff, stature at takeoff, velocity at takeoff, age at peak height velocity, stature at peak height velocity, and velocity at peak height velocity. Comparisons in the stature growth parameters and 15 cephalometric variables among the general population, Class III subjects, and non-Class III subjects were made with multivariate analysis.

RESULTS

Patients with Class III prognathism did not have different growth parameters compared with Class II subjects or the general population.

CONCLUSIONS

This study does not allow meaningful conclusions with regard to the relationship of mandibular size and stature growth pattern. The application of nonlinear growth curves vs the traditional linear interpolation method was also discussed.

Nonlinear least-squares data fitting in Excel spreadsheets

We describe an intuitive and rapid procedure for analyzing experimental data by nonlinear least-squares fitting (NLSF) in the most widely used spreadsheet program. Experimental data in x/y form and data calculated from a regression equation are inputted and plotted in a Microsoft Excel worksheet, and the sum of squared residuals is computed and minimized using the Solver add-in to obtain the set of parameter values that best describes the experimental data. The confidence of best-fit values is then visualized and assessed in a generally applicable and easily comprehensible way. Every user familiar with the most basic functions of Excel will be able to implement this protocol, without previous experience in data fitting or programming and without additional costs for specialist software. The application of this tool is exemplified using the well-known Michaelis-Menten equation characterizing simple enzyme kinetics. Only slight modifications are required to adapt the protocol to virtually any other kind of dataset or regression equation. The entire protocol takes approximately 1 h.

Early stature prediction method using stature growth parameters

BACKGROUND

The creation of an accurate growth prediction method for human stature at a stage of growth has been an interesting challenge in medical science and human biology.

AIM

The aim of this study was to develop a non-radiographic final stature prediction method that is applicable in the early pubertal growth period.

SUBJECTS AND METHODS

Randomly selected 12-year serial stature growth data for 400 Koreans were fitted with two nonlinear growth curves: Preece and Baines model 1 (PB1) and Jolicoeur-Pontier-Pernin-Sempe (JPPS) functions. Five biological parameters, including take-off (TO) related parameters, were derived by differentiation of the two curves, respectively. Those five variables were composed into a multiple linear regression equation for final stature prediction. In the cross-validation subjects, TO-related variables were estimated by linear interpolation from the partial growth data prior to estimation age, then incorporated into the prediction equation.

RESULTS

The final stature prediction model had excellent validity and accuracy when applied to the cross-validation samples. Prediction accuracy increased according to increasing years after take-off.

CONCLUSIONS

This study suggests that a final stature prediction method using multiple regression analysis that includes biological parameters can predict stature growth with sufficient validity and accuracy. Incorporation of TO-related parameters allowed us to develop earlier growth evaluation and prediction methods compared with other previous methods.

SCEW: a Microsoft Excel add-in for easy creation of survival curves

Survival curves are frequently used for reporting survival or mortality outcomes of experimental pharmacological/toxicological studies and of clinical trials. Microsoft Excel is a simple and widely used tool for creation of numerous types of graphic presentations however it is difficult to create step-wise survival curves in Excel. Considering the familiarity of clinicians and biomedical scientists with Excel, an algorithm survival curves in Excel worksheet (SCEW) has been developed for easy creation of survival curves directly in Excel worksheets. The algorithm has been integrated in the form of Excel add-in for easy installation and usage. The program is based on modification of frequency data for binary break-up using the spreadsheet formula functions whereas a macro subroutine automates the creation of survival curves. The advantages of this program are simple data input, minimal procedural steps and the creation of survival curves in the familiar confines of Excel.

Pubertal correlates in black and white girls

OBJECTIVES

Since pubertal maturation is an important covariate in studies that evaluate physical and social changes that occur during the teen years, we examined pubertal parameters in a group of US girls.

STUDY DESIGN

Black and white girls recruited at age 9 were followed annually for 10 years. Preece-Baines model 1 was used to estimate tempo and growth parameters. The temporal trend between age of menarche and onset of puberty was calculated.

RESULTS

The study included 615 (77.2% prepubertal) white and 541 (49.4% prepubertal) black participants. Mean onset of puberty was 10.2 and 9.6 years in white and black girls, respectively, menarche was 12.6 and 12.0, achievement of Tanner growth stage 5 was 14.3 and 13.6, and achievement of adult height was 17.1 and 16.5 years. The Pearson's correlation coefficient between menarche and onset of puberty was .37.

CONCLUSIONS

Menarche is often used as a marker for onset of puberty and for timing of puberty. Data gathered over the past 20 years suggest only moderate correlation between menarche and onset of puberty (.37-.38), which has decreased significantly during the last 50 years. This suggests the existence of both similar and unique factors that impact the age at onset of puberty and age at menarche.

Adolescent growth in main somatometric traits of Japanese boys: Ogi Longitudinal Growth Study

Considerable information is available on peak growth velocity characteristics of various body dimensions but the age at minimal velocity (AMV) and the duration of the spurt are not that well documented. Authors applied the mathematical growth model of Preece and Baines (PBGM1) to six longitudinally followed somatometric traits [height, sitting height, iliospinal height (B-ic), upper limb length (a-da), biacromial diameter (a-a), and biiliocristal diameter (ic-ic)] of Japanese boys of Ogi Growth Study. Biological variables derived from the estimated parameters were studied with emphasis on duration and velocity characteristics of the adolescent spurt. Ages for measurements at peak velocities tend to be younger than previously reported non-Japanese ones. Spurt duration in limb measurements was significantly the shortest. Earlier AMV and later age at peak velocity (APV), thus the longest spurt duration, are the characteristic for transverse measurements (a-a, ic-ic). B-ic and a-da had the largest, while a-a and ic-ic had the smallest relative velocity at AMV. Another result for the transverse measurements is that the magnitudes of differences between relative minimal and peak velocities (RMV, RPV) are the largest. It is suggested that a high level of RMV results from early maturation of bones, thus leading to the shortest spurt duration in limb dimensions, while a low level of RMV results from late maturation of the bones, consequently leading to the longest spurt duration in transverse measurements. This tendency of reverse relation was present in the rest of the measurements as well. Transformation of velocity variables (minimal velocity -- MV, peak velocity -- PV) to relative ones, proved to be useful in observing the relation of spurts in measurements.

Effects of heterosis on growth in height and its segments: a cross-sectional study of the Khasi girls in Northeast India

BACKGROUND

It is generally believed that improvement in environmental quality is the main factor responsible for the better growth and nutritional status of children in developing countries. However, it is still not clear whether this better growth performance is also associated with heterosis and/or gene flow that may take place as a result of the geographical movement of individuals, or migration.

AIM

The present paper attempts to examine the effects of heterosis on physical growth of girls in height and its segments.

SUBJECTS AND METHODS

A cross-sectional sample of the Khasi girls of Shillong in Northeast India was considered in the present analysis. The height and sitting height of 1368 girls aged 3-18 years were measured with a Harpenden anthropometer, following standard techniques. The sample was divided into two groups, namely hybrid (HB) and non-hybrid (NHB) girls,in order to test the effects of heterosis using analysis of covariance with the household income as a covariate. The Preece-Baines model I (M. A. Preece and M. F. Baines, Annals of Human Biology, 5, 1-24, 1978) was used to fit the adjusted means of height and its segments with a view to assess the variation in adult height, age at peak velocity and size at peak velocity.

RESULTS

Both HB and NHB girls were similar in age at maximum increment for height(12 years) and sitting height (13 years), although it was much earlier in the former(10.5 years) than in the latter (11.9 years) with respect to subischial length. The results indicated that HB girls were larger than NHB girls across ages. Such a higher anthropometric status in HB girls was mainly due to their higher growth velocities before the adolescent period. The effect of heterosis after household income was highly significant at many ages from 6 to 18 years, although it was not clearly perceptible in the case of subischial length.

CONCLUSION

Subject to further studies, the role of heterosis and/or gene flow in influencing growth and development of children cannot be completely ruled out, especially after 5 years of age when the variation in growth patterns is likely to be associated not only with environmental quality but also with genetic mechanisms.