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The Malaysian Journal of Medical Sciences : MJMS logoLink to The Malaysian Journal of Medical Sciences : MJMS
. 2020 Aug 19;27(4):108–118. doi: 10.21315/mjms2020.27.4.10

Growth Charts for Tribal, School-Going Children in Jharkhand Using Anthropometry and Lambda-Mu-Sigma Methods to Create Growth Charts

Dewesh Kumar 1, Rana Rishabh Kumar 2,✉, Anit Kujur 1, Chandramani Kumar 3, Shalini Sunderam 1, Vivek Kashyap 1, Haribansh Kumar Singh 2
PMCID: PMC7444840  PMID: 32863750

Abstract

Background

This study intends to find the growth patterns of selected school children. Globally accepted statistical methods were used to evaluate the data and prepare a growth chart.

Methods

This cross-sectional study was conducted with school-going children from 16 selected schools of a tribal district in Jharkhand using multistage cluster random sampling. In each selected school, 60 students, 30 boys and 30 girls, were chosen randomly, totaling 960 children (full data was for 935 children only). Growth charts were created using Lambda-Mu-Sigma (LMS) chart maker version 2.5 for height, weight and body mass index (BMI). In the charts, the LMS values with Z scores for each age and respective height and weight for boys and girls were recorded.

Results

The 468 boys and 467 girls were in the range of 6–14 years of age. Percentile values obtained for the measured heights in centimetres were evaluated and compared with Indian Academy of Pediatrics reference charts for boys and girls for the same age group, and our values were found to be on the lower side. We were able to plot a growth chart of the data set; as the tribal children’s ethnicity is different, this growth chart might be used to assess nutritional status.

Conclusion

We concluded that growth curves for height, weight, and BMI may be used for evaluating children of age 6–14 years in the tribal population. The measures can be a good indicator of their nourishment status and overall growth patterns, which might be indigenous to their ethnicity. A larger sample size of similar tribal populations may give a clearer picture.

Keywords: child health, growth chart, tribal school children

Introduction

Growth charts are integral tools for public health professionals and clinicians alike, providing a way to assess the health status and growth patterns of children and adolescents. Growth charts have evolved over the years in the statistical methods used and the designs of charts (1). Globally, children are evaluated for their well-being on the basis of their nutritional status as evaluated using growth charts and patterns (2). Ever since World Health Organization (WHO) determined growth charts and reference values in 2005 and proposed them as an international growth reference, these have been used in India and adopted by various agencies like the Indian Academy of Pediatrics (IAP) and United Nations Children’s Fund (UNICEF) to evaluate children in India. This was based on the data obtained for children aged 0–5 years on the multicentric growth reference study, a longitudinal, population-based study done on a group of breastfed babies in six countries. The data, thus obtained were merged, and smooth transitions were applied using the Lambda-Mu-Sigma (LMS) method (3). After the charts were available, evidence from various countries presented some altered figures compared to the WHO figures, but speaking in a broad manner, the overall growth patterns across different ethnicities were similar to the growth patterns for the initial three years of life (4–7). However, as ages progressed, the differences in the growth chart became apparent across various groups, remarkably during puberty. Evidence across different populations in terms of height achieved suggest that heights are not similar in children of the same age group, even if they are from the same socioeconomic class and similar geographic locations (8–11). As a population grows over time, the patterns of growth also change, and regular updating of the reference growth charts is mandated to reflect the ongoing growth patterns for the children. These charts can also represent a secular trend due to their updates (12). International and national growth standards do give a brief snapshot about countries where the population is relatively uniform and follows similar dietary patterns; however, in a country like India with varied population heterogeneity along with food diversity, different growth patterns are expected for different population subgroups as they vary significantly from the rest of country due to their own ethnic lifestyles and food habits. The tribal population in Jharkhand has been known to be different than the rest of the country owing to their own indigenous lifestyle, differing food habits due to poor economic conditions, rampant nutritional deprivation and intertribal differences, making it more complex than other tribes in Northeast or Southern India (13–15). Despite recommendations for nutritional assessments of different tribal populations across the country, evidence is sparse, particularly for school children in Jharkhand (16). Studies have repeatedly pointed out the acuteness of malnutrition in the country, which may cause further complications as children continue to grow (17). There is a clear relationship between nourishment and immunity, which implicates further the importance of the health of children who can be exposed to multiple infectious agents during school outings.

A data-based growth chart can serve as a reference for all future studies and a comparative source for understanding the growth and other associated parameters of school children in the tribal region in Jharkhand.

This study intends to determine the growth patterns of the schoolchildren selected by evaluating obtained data and plotting it in graph using the LMS method. The LMS graph thus created will also be used to compare with the IAP growth chart.

Methods

The present study was conducted in the selected 16 schools under the Gift Milk programme funded by the National Foundation of Nutrition (NFN) India, a joint venture of the National Dairy Development Board (NDDB) and the Rural Electricity Corporation Limited (REC Ltd) (18). The schools were selected randomly from the district of Latehar in Jharkhand as it is a tribal subplan district under Government of India with special emphasis on the tribal population (19). A total of three blocks of the district were chosen for the whole project based on geographic homogeneity, similar demographic populations and logistic availability. Approval for the study was taken by the Institutional Ethical Committee of the Rajendra Institute of Medical Sciences in Ranchi. The project was started in November 2017, and we were to complete the analysis and report-writing by November 2018. We adopted the standard procedures as described in the seminal paper for such projects by Waterlow et al. (20). These guidelines mandate that we have representatives from different age groups and participants from both sexes with a sample size of more than 500 children, use a cross-sectional design, use a defined and reproducible sampling procedure, measure carefully, and, using trained observers, record measurements meticulously using instruments that have been periodically calibrated and tested. In each selected school, 60 students, 30 boys and 30 girls, were chosen randomly, amounting to a total of 960 children between the ages of 6 and 14 years. During data cleaning, owing to some incomplete data on hard copies, we had a final total of 935 children’s records for evaluation. In some schools, we had comparatively fewer children from certain age groups. For example, for age 6, we had only 9 boys and 5 girls, while for age 7 we had 18 children. For older age groups we had even more.

A pilot study was completed initially to check the feasibility of the study and address any problems. All members of the field team were encouraged to participate in the capacity-building. Piloting was done as an external pilot survey in which a nearby, government-run school was selected. Questionnaires and other assessments were used to obtain a full picture of things to come in the field. The piloting was done on 10% of the total sample size of 960 children. The children were selected randomly so that we could a have fair representation of all age groups. We included 10 children from each age group from 6–14 years. Five males and 5 females were randomly selected from each age group. Ten extra children, 5 male and 5 female, were selected, too. The questionnaire was designed after checking its face validity, which was found to be satisfactory by the Principal Investigator. The data entries of 100 children’s data were supervised after 12 trained physicians recorded the measurements of the children during piloting. The test-retest reliability of the questionnaire was found to be satisfactory, with an overall score of r = 0.80. All data were collected by the questionnaire designed and finalised in the Department of Preventive and Social Medicine, Rajendra Institute of Medical Sciences Ranchi. The questionnaire had three sections: i) questions related to demographic details; ii) questions related to anthropometric measurements and iii) questions related to dietary habits. Data collected using the anthropometric measurements are used in this paper. We employed the techniques as per the WHO’s monograph (21) to measure all school children. We measured children aged 6–14 years using a stadiometer (Charder HM200PW Wall Mounted Stadiometer), and measurements were performed by one observer following the recommendations. Measurements for height were taken to the nearest 0.1 cm. Freeman’s 15 m fiberglass-top measuring tape was also kept for any need-based measurements. Weight was recorded to the nearest 0.1 kg with minimal clothing. An Omron bathroom scale was used to measure and record the weights. The equipment used was standardised; it was newly purchased for this project and was easily recalibrated, carried and moved around in each school. All data, thus collected were entered in MS Excel sheets and double-checked by trained team members. We also used statistical techniques to minimise the errors expected due to the large volume of data. Data that were collected in the field after piloting were cross-checked by our funders during their field visits. Data after collection in the field on hard copies were entered on MS Office Excel sheets with in-built data checks for all cells in the sheets so that data were not entered in the wrong format. Birth dates were obtained from the children’s school records, which were dependent on the Universal Identity Number UID (Adhaar Card) being mandatorily taken by the schools to cross-check the ages of their enrolled children (22). The decimal age was calculated from their recoded ages and date of visit.

Inclusion Criterion

After formal consent (permission from district authorities, consent from teachers, consent from adolescents), all randomly selected students were asked about their well-being and willingness to participate. All willing students after random selection were included in the study. Formal consent was also taken from the teachers.

Exclusion Criterion

Those who were severely ill or not willing to participate were excluded from the study. LMS chart maker version 2.5 was used to create the curves, smooth the height and weight and calculate BMI using the following formula: weight in kg/length or height in m2 (23). Data analysis was done using SPSS version 23.0 for calculating percentiles of the obtained values for height, weight and BMI. These were then compared with IAP growth charts.

Results

While evaluating weight in kg for boys and girls, we found the majority of the boys (377) to be in the age range of 10–13 years; in age group of 6–9 years we had 68 boys, and there were 23 boys in the age group of 14 years. In most of these boys, upon comparing the values of the 3rd, 10th, 25th, 50th, 75th, 90th and 97th percentiles from the IAP, we found these values to be less than that of the IAP chart (Supplementary Table 1). We also saw observed the standard deviation values to be less than that IAP values (Supplementary Table 1). During the evaluation of girl students in different schools, we found most (368) girls to be in the age range of 10–13 years, while in age group of 6–9 years we had only 68 girls. For age group of 14 years, we had 31 girls. Like with the boys, among girl students, when we compared the various percentiles with IAP values, we found our percentile scores to be less than that of the IAP, including the standard deviation scores across girls of age group 6–14 years (Supplementary Table 2). Among boys and girls for age 6 years, as the sample size was smaller, we saw all percentile values obtained during observation to be more than the IAP-recommended percentile values. Percentile values obtained for the measured height in cm were evaluated and compared with the IAP reference chart for the same boys and girls (Supplementary Tables 3 and 4). Here, too, for age 6 in boys and girls, as the sample size was less than 10, observed percentile values were more than the IAP reference chart. However, the number of boys or girls in any age was more than 10, so the percentile values obtained were less than the IAP-recommended values.

By using the software LMS chart maker, we were able to have the LMS values with Z scores for each age and their respective height and weight for boys and girls. The M score values were the same as the values of the Z (0 score) (Tables 1 and 2). By calculating BMI from height and weight and using the standard formula for calculating BMI, we were able to have LMS scores of BMI for boys and girls as well. The age range taken in our study was 6–14 years (Tables 1 and 2). By obtaining the values using the software, we were able to make the reference charts/growth curves for weight, height, and BMI for boys and girls aged 6–14 years (Figures 1–3).

Table 1.

LMS values and Z scores for boys’ and girls’ weight (kg) (values of M and Z score of 0 are same)

LMS values and Z scores for boy’s weight (kg)
Age L M S −3 −2 −1 +1 +2 +3
6 −1.14555 19.72371 0.109339 16.39805 17.32013 18.3756 21.3035 22.97853 24.9362
7 −1.15034 20.87505 0.125019 16.95297 18.02042 19.26084 22.81126 24.9194 27.45955
8 −1.18715 21.32745 0.138624 16.99377 18.1523 19.51784 23.54948 26.037 29.13597
9 −1.31613 23.06292 0.149187 18.16369 19.44694 20.98334 25.69169 28.74495 32.73445
10 −1.41934 25.3406 0.157877 19.77924 21.21155 22.94821 28.4417 32.16594 37.26144
11 −1.3428 27.76437 0.164005 21.44869 23.07194 25.04358 31.29647 35.54165 41.34731
12 −1.03552 29.51492 0.168009 22.45525 24.3012 26.51595 33.29594 37.65652 43.27733
13 −0.48786 31.93998 0.170266 23.71968 25.95865 28.56316 35.94692 40.2284 45.24367
14 −0.20389 33.90303 0.17157 24.28141 27.07328 30.15633 38.01126 42.03885 46.34071
LMS values and Z scores for girl’s weight (kg)
6 −0.51297 19.59918 0.159398 14.82959 16.1387 17.65176 21.89106 24.31952 27.14001
7 −0.48981 19.89915 0.171595 14.7471 16.14848 17.78046 22.41715 25.1122 28.27487
8 −0.46599 21.52224 0.183053 15.63921 17.22659 19.08764 24.44066 27.59181 31.32291
9 −0.43749 24.2 0.192335 17.297 19.14939 21.33123 27.65779 31.41137 35.87892
10 −0.38446 27.09217 0.197152 19.15574 21.28739 23.79691 31.05443 35.34066 40.4187
11 −0.30959 29.66316 0.194643 20.97062 23.32729 26.08131 33.91756 38.45578 43.74809
12 −9.1602 31.87909 0.186929 22.55412 25.15312 28.12309 36.18937 40.61659 45.57276
13 0.209076 33.1694 0.177235 23.47885 26.28299 29.38738 37.32641 41.41051 45.78088
14 0.50894 33.80515 0.165311 24.0985 27.01638 30.13911 37.67756 41.339 45.11665
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Table 2.

LMS values and Z scores for girls’ and boys’ height (kg) (values of M and Z score of 0 are same)

LMS values and Z scores for boys’ height (cm)
Age L M S −3 −2 −1 +1 +2 +3
6 −3.98546 118.315 4.53E-02 109.9464 112.2945 114.9521 122.2337 126.3915 131.2957
7 −3.73893 121.0166 4.81E-02 111.9415 114.4843 117.3658 125.277 129.8042 135.1521
8 −3.51546 123.8385 5.06E-02 114.0858 116.8174 119.914 128.4191 133.2859 139.0322
9 −3.3768 127.7022 5.24E-02 117.2813 120.1977 123.5061 132.6037 137.8159 143.9748
10 −3.15496 132.5033 5.41E-02 121.3155 124.4532 128.0067 137.7387 143.2819 149.7946
11 −2.69808 137.0053 0.05533 124.9984 128.3983 132.2193 142.5018 148.2238 154.8061
12 −1.94E+00 140.5078 0.055834 127.7023 131.4027 135.4927 146.1117 151.7612 158.0194
13 −0.83078 143.8489 5.52E-02 130.2141 134.2929 138.6699 149.3933 154.7279 160.3461
14 0.431266 146.7704 5.37E-02 132.3812 136.8742 141.513 152.1372 157.0614 162.0098
LMS values and Z scores for girls’ height (cm)
6 −3.98546 118.315 4.53E-02 109.9464 112.2945 114.9521 122.2337 126.3915 131.2957
7 −3.73893 121.0166 4.81E-02 111.9415 114.4843 117.3658 125.277 129.8042 135.1521
8 −3.51546 123.8385 5.06E-02 114.0858 116.8174 119.914 128.4191 133.2859 139.0322
9 −3.3768 127.7022 5.24E-02 117.2813 120.1977 123.5061 132.6037 137.8159 143.9748
10 −3.15496 132.5033 5.41E-02 121.3155 124.4532 128.0067 137.7387 143.2819 149.7946
11 −2.69808 137.0053 0.05533 124.9984 128.3983 132.2193 142.5018 148.2238 154.8061
12 −1.94E+00 140.5078 0.055834 127.7023 131.4027 135.4927 146.1117 151.7612 158.0194
13 −0.83078 143.8489 5.52E-02 130.2141 134.2929 138.6699 149.3933 154.7279 160.3461
14 −0.431266 146.7704 5.37E-02 132.3812 136.8742 141.513 152.1372 157.0614 162.0098
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Figure 1.

Figure 1

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Reference height curve chart for girls and boys with percentile score

Figure 2.

Figure 2

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Reference weight curve chart for girls and boys with percentile score

Figure 3.

Figure 3

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Reference growth curve chart for BMI of girls and boys with percentile score

Discussion

Recent evidence suggests wide variations in growth patterns among various populations globally, challenging the notion of using a universal growth chart (24, 25).

In our study, we found the tribal school children population falling behind the growth parameters set by the IAP (percentile values set by the IAP for boys’ and girls’ weight, height and BMI) (Supplementary Tables 1–4) (26). This reflects the importance of prolonged poor nutrition; the WHO and UNICEF define stunting and wasting as two separate, important indicators for nutrition. However, as is evident, different populations can have different charts for measurement, so we need greater sample sizes to determine if the results are due to poor nutrition or the genetics of the tribal populations specific to Jharkhand. We also propose the Z scores using the LMS method with value of median (M) as the value of Z score 0, along with Z scores of −1, −2, −3 and +1, +2, +3 (Figures 1–3). Based on the results thus obtained, we propose the growth curves with percentile values of the 3rd, 10th, 25th, 50th, 75th, 90th and 97th percentiles. We have not compared our values to those of international standards like those of the WHO or the Centres for Disease Control and Prevention (CDC) as the recent IAP norms have been re-evaluated to conform to international standards.

In similar studies done elsewhere, the growth charts have shown a higher curve when compared to WHO curves for similar percentile values. In our study, we also found that if the number of students was less than 10 or 20, the percentile values were on par with the IAP charts for both sexes (Supplementary Tables 3 and 4), especially for girls. This can be attributed to the benefits of the existing mid-day-meal programme and the overall better attendance of girls as visualised and documented by our team during our visits to the schools. Evidence elsewhere has also suggested benefits in the overall nutrition of the mid-day-meal scheme in India (30).

Conclusion

We believe that the present study is sufficient to be projected as a template for school-going children in Jharkhand owing to our sampling procedure following the multi-stage probability random sampling method, which is considered to be one of the strongest methods for studying a sample in large population. This coupled with the reduction of intra- and inter-observation biases, employing accurate instruments and having trained medical professionals taking measurements makes this study better in the sense of quality. Considering this, we recommend our growth curves of height, weight and BMI to be used when studies are conducted to evaluate children of the age group 6–14 years for the tribal population residing in the state of Jharkhand.

Supplementary File

The comparative values of the percentile scores obtained against the Indian Academy of Pediatrics (IAP) recommended percentile values

Supplementary Table 1.

Boys’ weight in kg with percentile values

Age n 3rd 10th 25th 50th 75th 90th 97th mean ± SD
Observed 6 9 18.4 18.4 19.1 19.8 21.2 20.4±2.66
IAP 6 14.5 15.8 17.4 19.3 21.7 24.6 28.3 ±3.6
Observed 7 8 18.4 18.4 19.52 20.45 22.45 21.7±3.8
IAP 7 16 17.6 19.6 21.9 24.9 28.6 33.4 ±4.2
Observed 8 16 14.6 16.98 18.87 21.75 23.1 26.72 21.43±3.37
IAP 8 17.5 19.5 21.9 24.8 28.5 33.2 39.4 ±5.7
Observed 9 35 18.08 20.06 20.8 23.6 25.9 27.64 33.86 23.78±3.49
IAP 9 19.1 21.5 24.3 27.9 32.3 38 45.5 ±6.3
Observed 10 80 20.17 21.4 23.02 25.65 29.2 34.49 45.26 27.00±5.73
IAP 10 20.7 23.5 26.9 31.1 36.3 43 51.8 ±7.9
Observed 11 146 20.98 22.2 25.1 28.3 32 39.13 44.19 29.44±5.99
IAP 11 22.6 25.9 29.8 34.7 40.9 48.7 58.7 ±8.9
Observed 12 106 22.3 24.6 27.07 30.2 34.55 39.76 43.69 31.26±5.66
IAP 12 24.9 28.7 33.3 39 46 54.8 66.1 ±10.0
Observed 13 45 20.81 24.6 27.95 34.4 39.55 43.92 50.7 33.94±7.40
IAP 13 27.5 31.8 37 43.3 51.1 60.7 72.6 ±11.3
Observed 14 23 22.8 25.26 31.8 34.1 37.2 41.58 34.09±5.38
IAP 14 30.7 35.5 41.3 48.2 56.4 66.3 78.3 ±12.1
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Note: Red coloured entries show values observed to be less than the IAP growth chart values

Supplementary Table 2.

Girls’ weight in kg with percentile values

Age n 3rd 10th 25th 50th 75th 90th 97th mean ± SD
Observed 6 5 15.7 15.7 17.05 20.1 24 20.4±3.80
IAP 6 13.7 15.1 16.7 18.7 21.3 24.6 29.1 ±9.1
Observed 7 10 15.6 15.63 16.72 17.75 21.4 23.5 18.8±3.81
IAP 7 15.1 16.8 18.7 21.2 24.2 28.2 33.4 ±3.4
Observed 8 14 15.8 15.95 18.8 22.95 25.77 27.5 22.22±4.06
IAP 8 16.7 18.7 21.1 24 27.6 32.2 38.1 ±8.1
Observed 9 39 18.34 19.5 21.1 23.7 26.4 31.6 38.68 24.40±4.61
IAP 9 18.5 20.9 23.7 27.2 31.5 36.7 43.4 ±3.4
Observed 10 90 18.67 21.03 23.27 26.7 31.55 37.39 39.78 27.74±6.0
IAP 10 20.7 23.5 26.9 31 36 42 49.4 ±9.4
Observed 11 102 22.31 24.26 25.8 28.75 31.72 37.78 43.41 29.81±5.99
IAP 11 23.3 26.7 30.7 35.4 41 47.7 55.9 ±5.9
Observed 12 122 23.1 24.93 26.95 30.3 35.45 40.63 44.48 31.62±5.90
IAP 12 26.2 30 34.5 39.8 46 53.4 62.1 ±2.1
Observed 13 54 24.22 25.8 28.95 32.6 37.1 39.45 42.24 32.78±4.99
IAP 13 28.9 33.1 37.9 43.6 50.2 57.9 67.1 ±7.1
Observed 14 31 24.1 27.44 28.6 34 36.3 42.28 33.77±5.14
IAP 14 31.3 35.6 40.6 46.4 53.2 61.1 70.4 ±0.4
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Note: Red coloured entries show values observed to be less than the IAP growth chart values

Supplementary Table 3.

Boys’ height in cm with percentile values

Age n 3rd 10th 25th 50th 75th 90th 97th mean ± SD
Observed 6 9 113 113 117.5 120.5 124 121.44±6.41
IAP 6 104.2 107.7 111.2 114.8 118.5 122.2 126 ±
Observed 7 8 115 115 118.25 121.75 126.37 123±7.11
IAP 7 109.3 113 116.8 120.7 124.6 128.6 132.6 ±
Observed 8 16 111 114.5 117.125 122.75 129.5 135 123.4±7.167
IAP 8 114.3 118.2 122.3 126.4 130.5 134.8 139.1 ±39.
Observed 9 35 117.08 121 123.5 126.9 132 139.4 145.32 128.4±6.84
IAP 9 119 123.2 127.5 131.8 136.3 140.7 145.3 ±45.
Observed 10 80 121 125 129 133 139.37 143.97 151.85 133.92±7.57
IAP 10 123.6 128.1 132.6 137.2 141.9 146.6 151.4 ±51.
Observed 11 146 123 127.94 132.37 138.5 142.52 147.8 153.01 138.155±8.03
IAP 11 128.2 133 137.8 142.7 147.6 152.5 157.5 ±57.
Observed 12 106 126.31 131 135.37 141 145.15 150.8 157.79 140.98±7.76
IAP 12 133.2 138.3 143.3 148.4 153.5 158.6 163.7 ±8.1
Observed 13 45 124.31 130.92 136.5 145 152 155 159.17 143.82±9.21
IAP 13 138.3 143.7 149 154.3 159.5 164.7 169.9 ±69.
Observed 14 23 134 137.02 139 145.5 151.7 157.18 145.67±7.26
IAP 14 143.4 149 154.5 159.9 165.1 170.3 175.4 ±75.
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Note: Red coloured entries show values observed to be less than the IAP growth chart values

Supplementary Table 4.

Girls’ height in cm with percentile values

Age n 3rd 10th 25th 50th 75th 90th 97th mean ± SD
Observed 6 5 109 109 113 120.5 130.75 121.80±9.81
IAP 6 102.3 106 109.7 113.5 117.4 121.5 125.6 ±25.
Observed 7 10 106 106.3 109.75 119.5 123.62 127.45 117.30±7.764
IAP 7 107.4 111.4 115.4 119.4 123.5 127.7 131.9 ±31.
Observed 8 14 112 113 115 127 135 136 125.66±8.85
IAP 8 112.6 116.8 121.1 125.4 129.6 133.9 138.1 ±38.
Observed 9 39 120.64 122 124 129.7 136 143 148.76 130.76±7.41
IAP 9 117.8 122.4 126.9 131.4 135.8 140.2 144.5 ±44.
Observed 10 90 118.19 123.55 128 134.5 142.2 147.9 150.63 134.83±8.66
IAP 10 123.3 128.1 132.8 137.4 142 146.4 150.8 ±50.
Observed 11 102 127.48 130.36 133.6 138.5 143.12 148.88 156.45 139.13±7.76
IAP 11 128.8 133.7 138.6 143.3 147.9 152.4 156.8 ±56.
Observed 12 122 128.51 133.01 136.01 141.85 148.11 152.63 157.65 142.08±7.53
IAP 12 134 138.9 143.7 148.4 153 157.5 162 ±62.
Observed 13 54 128.25 135 138.87 143.8 148.12 154.5 158.7 143.84±7.22
IAP 13 138.2 142.9 147.6 152.2 156.8 161.3 165.9 ±65.
Observed 14 31 129 136.81 142.01 146 150.6 152.9 145.42±6.11
IAP 14 141.3 145.8 150.2 154.7 159.2 163.7 168.2 ±68.
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Note: Red coloured entries show values observed to be less than the IAP growth chart values

Acknowledgements

We would like to acknowledge the support of students, teachers, and district administration, and our team of junior residents, for their efforts. We would also like to extend our thanks to our funders, REC Ltd and NFN India, for their support.

Footnotes

Conflict of Interest

None.

Funds

None.

Authors’ Contributions

Conception and design: DK, RKR

Analysis and interpretation of the data: DK

Drafting of the article: RKR

Critical revision of the article for important intellectual content: DK, AK, CK, SS, VK, HS

Final approval of the article: RKR

Provision of study materials or patients: AK, CK

Statistical expertise: DK, RKR

Obtaining of funding: DK, RKR

Administrative, technical, or logistic support: AK, CK, SS, VK, HS

Collection and assembly of data: AK, CK, RKR

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplementary Table 1.

Boys’ weight in kg with percentile values

Age n 3rd 10th 25th 50th 75th 90th 97th mean ± SD
Observed 6 9 18.4 18.4 19.1 19.8 21.2 20.4±2.66
IAP 6 14.5 15.8 17.4 19.3 21.7 24.6 28.3 ±3.6
Observed 7 8 18.4 18.4 19.52 20.45 22.45 21.7±3.8
IAP 7 16 17.6 19.6 21.9 24.9 28.6 33.4 ±4.2
Observed 8 16 14.6 16.98 18.87 21.75 23.1 26.72 21.43±3.37
IAP 8 17.5 19.5 21.9 24.8 28.5 33.2 39.4 ±5.7
Observed 9 35 18.08 20.06 20.8 23.6 25.9 27.64 33.86 23.78±3.49
IAP 9 19.1 21.5 24.3 27.9 32.3 38 45.5 ±6.3
Observed 10 80 20.17 21.4 23.02 25.65 29.2 34.49 45.26 27.00±5.73
IAP 10 20.7 23.5 26.9 31.1 36.3 43 51.8 ±7.9
Observed 11 146 20.98 22.2 25.1 28.3 32 39.13 44.19 29.44±5.99
IAP 11 22.6 25.9 29.8 34.7 40.9 48.7 58.7 ±8.9
Observed 12 106 22.3 24.6 27.07 30.2 34.55 39.76 43.69 31.26±5.66
IAP 12 24.9 28.7 33.3 39 46 54.8 66.1 ±10.0
Observed 13 45 20.81 24.6 27.95 34.4 39.55 43.92 50.7 33.94±7.40
IAP 13 27.5 31.8 37 43.3 51.1 60.7 72.6 ±11.3
Observed 14 23 22.8 25.26 31.8 34.1 37.2 41.58 34.09±5.38
IAP 14 30.7 35.5 41.3 48.2 56.4 66.3 78.3 ±12.1
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Note: Red coloured entries show values observed to be less than the IAP growth chart values

Supplementary Table 2.

Girls’ weight in kg with percentile values

Age n 3rd 10th 25th 50th 75th 90th 97th mean ± SD
Observed 6 5 15.7 15.7 17.05 20.1 24 20.4±3.80
IAP 6 13.7 15.1 16.7 18.7 21.3 24.6 29.1 ±9.1
Observed 7 10 15.6 15.63 16.72 17.75 21.4 23.5 18.8±3.81
IAP 7 15.1 16.8 18.7 21.2 24.2 28.2 33.4 ±3.4
Observed 8 14 15.8 15.95 18.8 22.95 25.77 27.5 22.22±4.06
IAP 8 16.7 18.7 21.1 24 27.6 32.2 38.1 ±8.1
Observed 9 39 18.34 19.5 21.1 23.7 26.4 31.6 38.68 24.40±4.61
IAP 9 18.5 20.9 23.7 27.2 31.5 36.7 43.4 ±3.4
Observed 10 90 18.67 21.03 23.27 26.7 31.55 37.39 39.78 27.74±6.0
IAP 10 20.7 23.5 26.9 31 36 42 49.4 ±9.4
Observed 11 102 22.31 24.26 25.8 28.75 31.72 37.78 43.41 29.81±5.99
IAP 11 23.3 26.7 30.7 35.4 41 47.7 55.9 ±5.9
Observed 12 122 23.1 24.93 26.95 30.3 35.45 40.63 44.48 31.62±5.90
IAP 12 26.2 30 34.5 39.8 46 53.4 62.1 ±2.1
Observed 13 54 24.22 25.8 28.95 32.6 37.1 39.45 42.24 32.78±4.99
IAP 13 28.9 33.1 37.9 43.6 50.2 57.9 67.1 ±7.1
Observed 14 31 24.1 27.44 28.6 34 36.3 42.28 33.77±5.14
IAP 14 31.3 35.6 40.6 46.4 53.2 61.1 70.4 ±0.4
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Note: Red coloured entries show values observed to be less than the IAP growth chart values

Supplementary Table 3.

Boys’ height in cm with percentile values

Age n 3rd 10th 25th 50th 75th 90th 97th mean ± SD
Observed 6 9 113 113 117.5 120.5 124 121.44±6.41
IAP 6 104.2 107.7 111.2 114.8 118.5 122.2 126 ±
Observed 7 8 115 115 118.25 121.75 126.37 123±7.11
IAP 7 109.3 113 116.8 120.7 124.6 128.6 132.6 ±
Observed 8 16 111 114.5 117.125 122.75 129.5 135 123.4±7.167
IAP 8 114.3 118.2 122.3 126.4 130.5 134.8 139.1 ±39.
Observed 9 35 117.08 121 123.5 126.9 132 139.4 145.32 128.4±6.84
IAP 9 119 123.2 127.5 131.8 136.3 140.7 145.3 ±45.
Observed 10 80 121 125 129 133 139.37 143.97 151.85 133.92±7.57
IAP 10 123.6 128.1 132.6 137.2 141.9 146.6 151.4 ±51.
Observed 11 146 123 127.94 132.37 138.5 142.52 147.8 153.01 138.155±8.03
IAP 11 128.2 133 137.8 142.7 147.6 152.5 157.5 ±57.
Observed 12 106 126.31 131 135.37 141 145.15 150.8 157.79 140.98±7.76
IAP 12 133.2 138.3 143.3 148.4 153.5 158.6 163.7 ±8.1
Observed 13 45 124.31 130.92 136.5 145 152 155 159.17 143.82±9.21
IAP 13 138.3 143.7 149 154.3 159.5 164.7 169.9 ±69.
Observed 14 23 134 137.02 139 145.5 151.7 157.18 145.67±7.26
IAP 14 143.4 149 154.5 159.9 165.1 170.3 175.4 ±75.
Open in a new tab

Note: Red coloured entries show values observed to be less than the IAP growth chart values

Supplementary Table 4.

Girls’ height in cm with percentile values

Age n 3rd 10th 25th 50th 75th 90th 97th mean ± SD
Observed 6 5 109 109 113 120.5 130.75 121.80±9.81
IAP 6 102.3 106 109.7 113.5 117.4 121.5 125.6 ±25.
Observed 7 10 106 106.3 109.75 119.5 123.62 127.45 117.30±7.764
IAP 7 107.4 111.4 115.4 119.4 123.5 127.7 131.9 ±31.
Observed 8 14 112 113 115 127 135 136 125.66±8.85
IAP 8 112.6 116.8 121.1 125.4 129.6 133.9 138.1 ±38.
Observed 9 39 120.64 122 124 129.7 136 143 148.76 130.76±7.41
IAP 9 117.8 122.4 126.9 131.4 135.8 140.2 144.5 ±44.
Observed 10 90 118.19 123.55 128 134.5 142.2 147.9 150.63 134.83±8.66
IAP 10 123.3 128.1 132.8 137.4 142 146.4 150.8 ±50.
Observed 11 102 127.48 130.36 133.6 138.5 143.12 148.88 156.45 139.13±7.76
IAP 11 128.8 133.7 138.6 143.3 147.9 152.4 156.8 ±56.
Observed 12 122 128.51 133.01 136.01 141.85 148.11 152.63 157.65 142.08±7.53
IAP 12 134 138.9 143.7 148.4 153 157.5 162 ±62.
Observed 13 54 128.25 135 138.87 143.8 148.12 154.5 158.7 143.84±7.22
IAP 13 138.2 142.9 147.6 152.2 156.8 161.3 165.9 ±65.
Observed 14 31 129 136.81 142.01 146 150.6 152.9 145.42±6.11
IAP 14 141.3 145.8 150.2 154.7 159.2 163.7 168.2 ±68.
Open in a new tab

Note: Red coloured entries show values observed to be less than the IAP growth chart values

Articles from The Malaysian Journal of Medical Sciences : MJMS are provided here courtesy of School of Medical Sciences, Universiti Sains Malaysia

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