|Year : 2022 | Volume
| Issue : 4 | Page : 288-294
Anthropometric parameters of idiopathic familial short stature females and its correlation with height and comparison with the control group
Karishma Sharma1, Rishita Chandra2, Brijendra Singh1, Shashi Ranjan Mani Yadav3, Manisha Naithani3, Surekha Kishore4, Vivek Mishra5, Kriti Mohan6, Prashant Kumar Verma7
1 Department of Anatomy, All India Institute of Medical Sciences, Rishikesh, Uttarakhand, India
2 Department of MPH, All India Institute of Medical Sciences, Rishikesh, Uttarakhand; Project Manager-MIS, PHRS Department of Community and Family Medicine, Odisha, India
3 Department of Biochemistry, All India Institute of Medical Sciences, Rishikesh, Uttarakhand, India
4 Department of Community and Family Medicine, AIIMS, Gorakhpur, Uttarakhand, India
5 Department of Anatomy, AIIMS, Gorakhpur, Uttarakhand, India
6 Department of Paediatrics, AIIMS, Gorakhpur, Uttarakhand, India
7 Department of Paediatrics, All India Institute of Medical Sciences, Rishikesh, Uttarakhand, India
|Date of Submission||09-Nov-2021|
|Date of Decision||20-Jan-2022|
|Date of Acceptance||31-Jul-2022|
|Date of Web Publication||01-Dec-2022|
Dr. Prashant Kumar Verma
Department of Paediatrics, All India Institute of Medical Sciences, Rishikesh - 249 203, Uttarakhand
Source of Support: None, Conflict of Interest: None
Introduction: Familial Short stature is considered one of the most common causes of Short Stature along with the constitutional delay in growth and puberty (CDGP) from which it can easily be distinguish. The core parameters of anthropometry represent diagnostic criteria for obesity and other non-communicable diseases. To measure the anthropometric parameters in the patients with idiopathic clinically non-syndromic familial short-stature and to correlate those parameters with their height and compare them with the control group. Material and Methods: A cross-sectional study was conducted among Familial Short Stature females of 5-18 years age group referred from Paediatric and Genetic OPD of AIIMS, Rishkesh. Non-parametric tests were applied for comparing the variables and correlation coefficients were obtained. Results: There was a significant difference between the groups in terms of Standing Height (cm) (W = 376.000, P = <0.001), BMI (Kg/m2) (W = 1128.500, P = 0.002), with the median BMI (Kg/m2) and Waist/Height Ratio (W = 1164.500, P = <0.001), with the median Waist/Height Ratio being highest in the Short-Stature group. There was moderate to strong positive correlation between standing height and other anthropometric parameters. The mean waist to height ratio of 0.6 among short stature and 0.5 among the control group, with short stature having more odds of getting overweight and also shows a greater predilection of short-stature group for developing Cardio-vascular diseases. Discussion and Conclusion: Familial short stature though being a manifestation of some underlying cause, can fall in a non-syndromic group until further studies including karyotyping, next-generation sequencing etc. Extensive research for appropriate categorization and how this can effectively help combat the burden of malnutrition and non-communicable diseases should be done.
Keywords: Anthropometry, familial short stature, idiopathic short stature, standing height
|How to cite this article:|
Sharma K, Chandra R, Singh B, Mani Yadav SR, Naithani M, Kishore S, Mishra V, Mohan K, Verma PK. Anthropometric parameters of idiopathic familial short stature females and its correlation with height and comparison with the control group. J Anat Soc India 2022;71:288-94
|How to cite this URL:|
Sharma K, Chandra R, Singh B, Mani Yadav SR, Naithani M, Kishore S, Mishra V, Mohan K, Verma PK. Anthropometric parameters of idiopathic familial short stature females and its correlation with height and comparison with the control group. J Anat Soc India [serial online] 2022 [cited 2023 Mar 27];71:288-94. Available from: https://www.jasi.org.in/text.asp?2022/71/4/288/362549
| Introduction|| |
Short stature (SS) is defined as “a condition in which the height of an individual is 2 standard deviations (SDs) below the corresponding mean height of a given age, sex, and population group.” It can be a manifestation of some underlying conditions related to genetic or familial predisposition, endocrine disorders, skeletal dysplasia, malnutrition, and some chronic diseases.
Familial SS (FSS) is a condition in which the final adult height achieved is less than the third percentile for the patient's age, gender, and population. It is considered one of the most common causes of SS along with the constitutional delay in growth and puberty (CDGP) from which it can easily be distinguished. A child presenting with SS two or more SDs below the mean for age, gender, and population where no other causes can be found is deemed to have idiopathic SS (ISS). By adopting this definition, some authorities have included cases of FSS and CDGP as part of ISS. Hence, a category of familial ISS is distinguished from the nonfamilial ISS. On the other hand, others have listed it as a separate entity.
As per a study, about 5.6% of study participants were found to be of SS according to the Indian standard, i.e., below the fifth percentile of growth. Another study reported that 555 of 79,495 (0.7%) had SS, 75% of cases were FSS and CDGP, underlying organic disease 14%, while only 5% had endocrine causes.
A study from South India reported a prevalence rate of 2.86% in school-going children. The major reasons behind SS were genetics and constitutional delay in growth; only 6.69% of children were reported to have SS caused by malnutrition.
SS can appear as an isolated physical trait in an otherwise normal and healthy child, which we call “ISS.” Human height is a polygenic trait that can be inherited which is regulated by multilocus genes. FSS which is also known as genetic SS is the most common type of SS and needs to be explored more.
The core parameters of anthropometry are important because they represent diagnostic criteria for obesity, which significantly increases the risk for conditions such as cardiovascular disease, hypertension, diabetes mellitus, and many more. By measuring the height for age, weight for age, and weight for height, it can be determined if children are stunted, underweight, or wasted. Another anthropometric measurement useful to assess nutritional status in children is mid-upper arm circumference, which can be used to define the severity of malnutrition.
SS is one of the most common causes of referral to the department of pediatric endocrinology. SS not only affects the physique and appearance of an individual but is reported to have a psychological impact on children and their parents. A survey suggested that impaired height has a significant impact on the emotional and mental well-being of a child.
The accurate assessment of physical growth and development in children has attracted much attention from health-care providers and pediatricians. There is a lack of information in this domain. The topic is highly important, but the area is still unexplored, and more research need to be done. Hence, the current study aims to establish the correlation of height with arm span, waist circumference (WC), and waist-to-height ratio of females with FSS. There has not been any such study conducted as best of our knowledge. Hence, the result and inferences obtained would be helpful to find out mild dysmorphic syndrome for defining it as a variation or anomaly and can be a guiding light for many researchers in the same field.
The objectives of this study were to measure the anthropometric parameters, e.g., height, arm span, WC, and waist-to-height ratio in patients with idiopathic clinically nonsyndromic familial SS and to correlate all the mentioned parameters with their height and to compare them with the control group.
| Material and Methods|| |
A cross-sectional study was conducted at All India Institute of Medical Sciences, Rishikesh, Uttarakhand, from February 2019 to May 2021.
A total of 40 patients with FSS of the age group 5–18 years, referred from the Paediatric and Genetic Outpatient Department (OPD) of AIIMS, Rishikesh, were consecutively recruited in the study. Forty healthy females of the normal height of the same age group were enrolled in the study as controls. After a brief session of providing information related to the study, informed consent was obtained from both the groups.
Inclusion criteria for short stature
- Females height below third centile according to WHO, comes in OPD from Uttarakhand.
- FSS after checking midparental height/one of the parents identified as FSS.
Exclusion criteria for short stature
- Height more than 2 SDs below the median (>3rd percentile) and age below 5 years above 18 years
- External genitalia like male or ambiguous
- Chronic protein energy malnutrition
- Chronic disease (congenital heart disease and malabsorption)
- Chronic steroid therapy (nephrotic syndrome, asthma, and atopic disease)
- Skeletal dysplasia
- Acquired causes of SS such as spine fracture, spinal tuberculosis, and limb fracture
- Clinically diagnosed well-known syndrome with growth failure
- SS well defined clinically isolated medical condition and responded with therapy (growth hormone and hypothyroidism)
- Bone age mismatch to chronological age
- Participants not willing to be part of the study
Data collection and analysis
The midparental height of the participants was taken to estimate their stature. Anthropometric parameters were recorded for each participant using digital weight machine, stadiometer, and flexible measuring tape.
The data were analyzed using SPSS v23 (IBM Corp) software. The Chi-square test was applied to find the association between variables. For the data that were not distributed normally, nonparametric tests were applied for comparing the variables of the SS and control groups. To establish the relation between standing height and other anthropometric parameters, correlation coefficients were obtained.
| Results|| |
A total of 40 females with idiopathic FSS and 40 healthy females as control of the age group 5–18 years were recruited for the study. The average age of the SS group was reported to be 13.20 ± 3.88 and the control group was 12.35 ± 3.67. The association between group and age was estimated for both the SS group and the control group. After applying the Chi-square test, it was estimated that there was no significant association between various age groups in terms of age (χ2 = 0.258, P = 0.879). In the SS group, 22.5% of the participants belonged to 5–9 years of age group with 35.0% from 10 to 14 years of age group, and 42.5% belonged to 15–18 years. In Control group 22.5% of the participants were of age 5-9 years, 40.0% of 10-14 years and, 37.5% belonged to the age group of 15-18 years.
In [Figure 1], the association between standing height and the age group is depicted for the SS and control groups. As the variable standing height (cm) was not distributed normally, nonparametric tests (Kruskal–Wallis test) were used to make group comparisons. There was a significant difference between the groups in terms of standing height (cm) among the SS group (χ2 = 27.033, P ≤ 0.001) and the control group (χ2 = 25.645, P ≤ 0.001), with the median standing height (cm) being highest in 15–18 years of age group.
The comparison was established between the SS group and the control group for other anthropometric measures, e.g., standing height, weight, body mass index (BMI), arm span, WC, and waist/height ratio, as described in [Table 1]. For the variables that were not distributed normally, nonparametric test (Wilcoxon–Mann–Whitney U-test), and for normally distributed variables, parametric test (t-test) was used to make group comparisons. There was a significant difference between the two groups in terms of standing height (cm) (W = 376.000, P ≤ 0.001), with the median standing height (cm) being highest in the control group; BMI (kg/m2) (W = 1128.500, P = 0.002), with the median BMI (kg/m2) being highest in the SS group; and waist/height ratio (W = 1164.500, P ≤ 0.001), with the median waist/height ratio being highest in the SS group.
|Table 1: Comparison between standing height and other anthropometric measures among the short stature and control groups|
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The BMI interpretation, as shown by the graph in [Figure 2], suggested a significant difference as well (χ2 = 4.021, P = 0.045). Participants in the control group had a larger proportion of acceptable BMI as compared to the SS group that reflected a larger proportion of overweight BMI. The females of the SS group reported an odds of 3.41 to be overweight as compared to 0.29 odds of the control group to be overweight.
|Figure 2: BMI interpretation among the short stature and control groups. BMI: Body index mass|
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The correlation coefficients for both the groups, i.e., the SS group and the control group for the anthropometric measures of age, weight, BMI, arm span, WC, and waist-to-hip ratio with the standing height, were estimated and are depicted in [Figure 3]. Among the SS group and the control group, there was a strong positive correlation between age (years) and standing height (cm). This correlation was statistically significant for the SS group (rho = 0.85, P ≤ 0.001) and for the control group (rho = 0.82, P ≤ 0.001). For every 1 unit increase in age (years), the standing height (cm) increases by 3.71 units in the SS group, and in the control group, for every 1 unit increase in age (years), the standing height (cm) increases by 3.65 units. There was a strong positive correlation between weight (kg) and standing height (cm), and this correlation was statistically significant (rho = 0.75, P ≤ 0.001) among the SS group, and for every 1 unit increase in weight (kg), the standing height (cm) increases by 1.13 units. Among the control group, there was a very strong positive correlation between weight (kg) and standing height (cm), and this correlation was statistically significant (rho = 0.9, P ≤ 0.001), and for every 1 unit increase in weight (kg), the standing height (cm) increases by 1.43 units.
|Figure 3: Correlation of anthropometric parameters with standing height among the SS and control groups. SS: Short stature, BMI: Body index mass|
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Short stature control
Among the SS group as well as the control group, there was a moderate positive correlation between BMI (kg/m2) and standing height (cm). This correlation was statistically significant (rho = 0.52, P ≤ 0.001), and for every 1 unit increase in BMI (kg/m2), the standing height (cm) increases by 2.30 units in the SS group, and among the control group (rho = 0.44, P = 0.004), for every 1 unit increase in BMI (kg/m2), the standing height (cm) increases by 3.66 units.
There was a strong positive correlation between arm span (cm) and standing height (cm), among both the groups. Among the short-stature group ,rho = 0.89, P = <0.001 and among the control group rho = 0.9, P = <0.001.
There was a strong positive correlation recorded between WC (cm) and standing height (cm) in both the groups. Among the SS group (rho = 0.71, P ≤ 0.001), for every 1 unit increase in WC (cm), the standing height (cm) increases by 0.87 units, and in the control group (rho = 0.81, P ≤ 0.001), for every 1 unit increase in WC (cm), the standing height (cm) increases by 0.81 units. There was a significant difference between the two groups in terms of waist/height ratio (W = 1164.500, P ≤ 0.001), with the median waist/height ratio being highest in the SS group.
| Discussion|| |
Several studies have been conducted to estimate the growth pattern among children. The anthropometric parameters have been stated as one of the significant measures to assess the nutritional status of the children, with arm span being quoted by many studies. The standing height was correlated with sitting height, leg length, and arm wingspan, while other studies used knee height to estimate height. However, in all these studies, the variable that proved to be consistently reliable was the arm wing span. Similarly, in the present study, the correlation between arm wing span and height with r = 0.89 for SS and 0.9 for control, respectively, agreed with the study among biracial populations, where a correlation of 0.852 was recorded for Black population. However, the estimation equations obtained from this study differ from the one obtained for the present study, thereby justifying that the association between anthropometric measures differs in ethnic and racial groups. Even though several studies of this nature are available on Western populations, very limited data are available on Indian subjects.
The effectiveness of using various anthropometric parameters to predict an individual's height has been reported. The arm span was reported to be the most reliable parameter for predicting height.,
However, exact height cannot be measured directly in the cases with deformities in lower limb,in individuals who have undergone amputation of lower limbs or shortening due to fractures and bone decomposition. In these circumstances, an estimation of the height has to be done with the help of other anthropometric body parameters. The current study advocates that the diagnosis of FSS can also be done by estimating their anthropometric parameters to predict height.
BMI is an index for assessing under- or overnutrition in children, adolescents as well as adults. It is an indicator to evaluate general adiposity. Obesity in children is associated with chronic diseases in adulthood, such as heart disease, hyperlipidemia, hyperinsulinemia, hypertension, and atherosclerosis. However, the WC, which is a measure of central/abdominal obesity, has been found to have more risk related to cardiovascular diseases as compared to BMI.
To the best of our knowledge, this is one of the pioneer studies in the field of addressing familial SS female children and their comparison with healthy female children of the same age. The correlation between BMI and standing height in the present study was found to have a moderate positive relationship with r = 0.52 and 0.44, respectively, for the SS group and the control group. The moderate association of BMI with height as found in the present study is in alignment to the results found in several studies.,, The current study reported a larger proportion of overweight individuals among the SS group that justifies the positive correlation between BMI and height. The comparison made between the SS group and the control group for BMI and waist-to-height ratio reflected a significant difference in both the groups as per this current study similar to a study that reported a significant correlation between height and BMI.
Association of WC with risk factors such as diastolic blood pressure and insulin resistance has been reported. Waist-to-height ratio has been reported to be an alternative tool for assessing obesity in children.,
The current study reported a strong positive relation between standing height and waist-to-height ratio in both the groups. Due to the role of the visceral fat depot in health risks associated with obesity, WC is also the preferred measurement in the context of population studies.,
The Waist-to-height ratio (WHtR) is a newly developed index, proposed to be superior to the BMI, because of its relationship to cardiovascular risks, as a consequence of abdominal obesity. A study reported a 0.5 WHtR cutoff in both men and women and proposed a health initiative that WC does not exceed one-half of the height. Our study reflected a mean waist-to-height ratio of 0.6 among the SS group and 0.5 among the control group and shows a greater predilection of the SS group for developing cardiovascular diseases.
The current study reported that the females of the SS group reported an odds of 3.41 to be overweight as compared to 0.29 odds of the control group to be overweight. Due to the unavailability of significant literature, as there have been minimal or no studies where an issue like FSS has been addressed extensively, many of the findings in the current study are one of a kind. The correlation coefficients between standing height and other anthropometric parameters showed a positive correlation in both the SS and control groups with a minor difference between their correlation coefficient, r. This might indicate that although the SS group is showing a strong prediction for obesity/overweight as reflected by BMI and waist-to-height ratio comparisons, the SS group may have other anthropometric measures as normal as the control group of the same age. To derive the more significant associations and patterns of relationship among the anthropometric parameters of SS individuals, more investigation and research are required. As FSS has a predilection toward getting cardiovascular diseases, so detailed knowledge of nutrition had to be given and parents should be educated about the risk of diseases associated with obesity and the importance to seek proper health care.
The current study advocates that genetic analysis plays a vital role in providing information on an individual's genotyping. There are many methods such as Barr body estimation, karyotyping, and polymerase chain reaction (PCR) to assess and evaluate the genomic cause of SS, developmental delay, genetic disorders, and intellectual disability. Therefore, extensive research for appropriate categorization of genetically syndromic and nonsyndromic FSS, importance of nutrition, and how this can effectively help combat the burden of malnutrition and noncommunicable diseases should be done.
| Conclusion|| |
The study is one of its kind in the domain of health that has not been extensively researched. FSS is a condition that is considered to have a genetic predisposition and might also curve into an idiopathic, nonsyndromic group. The study reported that SS female children have more odds of getting overweight/obese than the control group of healthy females of the same age. The anthropometric measures showed a positive correlation with standing height in both the groups with a significant difference in BMI and waist-to-height ratio. FSS, though being a manifestation of some underlying cause, can fall into a nonsyndromic group until further studies including karyotyping and next-generation sequencing.
Limitation of the study
The current study used a smaller sample size and is one of the novel research in the field, and the findings need to be validated by more research.
For assessing the cause of FSS and to curve it in the domain of genetic predisposition, more techniques need to be used, e.g., Sanger's sequencing and reverse transcription-quantitative PCR next-generation sequencing.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
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[Figure 1], [Figure 2], [Figure 3]