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Year : 2019  |  Volume : 5  |  Issue : 1  |  Page : 39-43

Nutritional assessment among children (1–5 years of age) using various anthropometric indices in a rural area of Haryana, India

1 Department of Community Medicine, GMC, Shahdol, Madhya Pradesh, India
2 Department of Community Medicine, SHKM GMC, Nalhar, Haryana, India
3 Department of Community and Family Medicine, AIIMS, Bhubaneswar, Odisha, India

Date of Web Publication4-Jul-2019

Correspondence Address:
Vikas Gupta
105-B, Sukhi Ram Park Matiala Road, P.O. Uttam Nagar, New Delhi - 110 059
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/IJCFM.IJCFM_14_19

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Background: Global Nutrition Targets 2025 specified a set of six global nutrition targets, and one aim is to achieve a 40% reduction in the number of children under 5 years of age who are stunted. National data on underweight provided under National Family Health Survey-4 (NFHS-4) (2015–2016) revealed an underweight prevalence rate around 35.7% as compared to NFHS-3 where it was 42.5%, which reflects only 6.8% reduction in underweight over a decade.
Methods: This cross-sectional study was conducted in the rural area of Rohtak district during October 2014 to September 2015 among children who were 1–5 years of age. The anthropometric measurement and nutritional status categorization among children were done using the WHO guidelines.
Results: A total of 600 children participated in the study. Around 41.3% of the study participants had stunting as their nutritional status, while taking composite index of anthropometric failure (CIAF) for nutritional status into consideration, nearly 54.4% of the participants were undernourished. Stunting and underweight were more prevalent among girls.
Conclusions: Composite anthropometric index provides the actual prevalence or proportion of undernourished children in a community, so the policies should be based on the basis of CIAF so to reduce the prevalence of undernutrition in the community more effectively.

Keywords: Composite index of anthropometric failure, stunting, underweight, wasting

How to cite this article:
Gupta V, Chawla S, Mohapatra D. Nutritional assessment among children (1–5 years of age) using various anthropometric indices in a rural area of Haryana, India. Indian J Community Fam Med 2019;5:39-43

How to cite this URL:
Gupta V, Chawla S, Mohapatra D. Nutritional assessment among children (1–5 years of age) using various anthropometric indices in a rural area of Haryana, India. Indian J Community Fam Med [serial online] 2019 [cited 2021 Oct 25];5:39-43. Available from: https://www.ijcfm.org/text.asp?2019/5/1/39/262115

  Introduction Top

Global Nutrition Targets 2025 specified a set of six global nutrition targets, and one aim is to achieve a 40% reduction in the number of children under 5 years of age who are stunted. Child malnutrition significantly increases the risk of infant and child death, with some estimates suggesting that child malnutrition is responsible for half or more of child deaths in the developing world.[1] The National Family Health Survey-4 (NFHS-4) data analysis showed a strong relationship between under-five child mortality rates and child underweight rates.[2] There is also a large body of evidence from around the world relating undernutrition in childhood to lower levels of school performance, cognitive development, and health and ultimately in adulthood to lower levels of labor productivity. Thus, the economic and human costs of child malnutrition in India are likely to be very high.[3] NFHS-4 data revealed the prevalence of underweight, stunting, and wasting as 35.7%, 38.4%, and 21% when compared to NFHS-3 42.5%, 48%, and 19.8% in India, which reflects slow reduction in the prevalence of malnutrition.[2],[4] It also suggests that Indian children suffer from both aspects of undernutrition which means short-term, acute food deficits (as reflected in low weight-for-age) as well as from long-term, chronic undernutrition (as manifested in high rates of stunting).

The undernutrition is due to multidimensional aspects such as poverty and diseases. Keeping that in mind, the rate of decline in undernutrition is lacking behind, and to achieve the pace in the reduction of undernutrition prevalence, Svedberg suggested new classification of undernutrition known as composite index of anthropometric failure (CIAF).[5] It was revised by Nandy et al. by addition of one more subgroup “Y” (underweight only) to existing one. The anthropometric subgroups of the children are as follows: A – no failure, B – wasting only, C – wasting + underweight, D – wasting + stunting + underweight, E – stunting + underweight, F – stunting only, and finally, Y – underweight only.[6] The sum of the children in groups B–F provides the CIAF. As a single indicator, CIAF provides a single number to the overall estimate of undernourished children in a population, which none of the current indicators do. This classification gave concern that children can have multiple growth failure and need special attention. Global Nutrition Targets 2025 are yet to be achieved at both national and state level (Haryana).[2] As in Haryana there is a paucity of studies based on CIAF, this was conducted to measure the undernutrition prevalence by both conventional methods and CIAF and to observe the reliability of CIAF.

  Methods Top

Study design and the participants

This cross-sectional study was conducted in rural field practice area attached to the Department of Community Medicine, PGIMS, Rohtak, Haryana, India, during October 2014 to September 2015. The sample size was calculated (n = 550) considering the prevalence of underweight among under-five children as 41% (approximate) in rural areas of Haryana (NFHS-3) with confidence level of 95% and 10% relative allowable error by applying the following formula: n = (Z1 − a/2)2 × p (1 − p)/d2, where Z = Standard normal variate for level of significance (at 5% type I error [P < 0.05], Z = 1.96 for two-sided test), a = Level of significance (0.05), P = Prevalence (proportion = 41%), d = Relative Allowable error (10%), and n = Sample size.[4] Although the calculated sample size came out to be 550, a sample of 600 study participants was included for the study. The participant involved were children, 1–5 years of age along with their parents/guardians. A total of 112 anganwadi centers (Integrated Child Development Scheme Centers [ICDS centers]) were there under the rural field practice area, of which 30 anganwadi centers were selected by adopting systematic random sampling procedure. From each selected anganwadi center, 20 children were selected by simple random sampling. Thus, a sample of 600 children was included in the study. This study was approved by the ethical committee, and prior consent was taken by parents/guardian of the children before the interview and examination of the child. The children who were unavailable at three consecutive visits or whose birth records at present not available were excluded from the study.

Study tools

A pretested, predesigned questionnaire was used by an investigator to interview the study participants and house-to-house visit was also done. The age of children was recorded using birth/delivery records or anganwadi center (ICDS centers) records and was estimated to the most recently attained month. The anthropometric measurements of children were done using the WHO guidelines.[7] To measure weight and height, parents/guardians were suggested to bring their children to respective anganwadi center (ICDS centers) to increase the accuracy level of respective measuring parameters. The weight of child was measured using a Salter's weighting apparatus developed by the UNICEF in collaboration with the WHO. The height of children who were more than 2 years and were able to stand without support was measured using a stadiometer; and for those below 2 years or were unable to stand or child length < 85 cm, recumbent length was measured using an infant meter.

The participants were classified as stunted, wasted, and underweight as their undernutritional status depending upon the Z-score value which was calculated using WHO Anthro Software (version 3.2.2, 2011, Department of Nutrition, World Health Organization, Avenue Appia 20, 1211 Geneva 27, Switzerland).[8] If Z-score <−2 = moderately undernourished, and if Z-score <−3 = severely undernourished. The undernutritional status of children was also classified on the basis of CIAF using Nandy et al. model of 6 groups (stunted only, underweight only, wasted only, wasting and underweight, stunted and underweight, and finally, stunted, wasted, and underweight) of children was used.[6] Three new indices proposed by Bose and Mandal were also used to asses with the problem of stunting, underweight, and wasting relative to the total prevalence of under nutrition.[9] These three indices are stunting index (SI) = stunting/CIAF; underweight index (UI) = underweight/CIAF; wasting index (WI) = wasting/CIAF.

Statistical methods

The responses to schedule by each participant were entered into excel sheet and data were tabulated and statistical analysis was done using SPSS 20.0 (Statistical Package for the Social Sciences, IBM SPSS Inc., Chicago, Illinois, USA). Categorical data were presented as percentages (%) and Pearson's Chi square test was used to evaluate differences between groups for categorized variables.

  Results Top

A total of 600 children participated in the study. In the study, boys and girls frequency (%) accounted as 337 (56.2%) and 263 (43.8%). The age-wise of distribution among boys and girls of children can be well observed in [Table 1], as maximum participants (23.8%) belonged to 12–23 months of age whether the participant was girl (30.8%) or boy (35.6%). The wasting (severe and moderate) was observed among 18.4% of participants; while 41.3% participants were stunted (severe and moderate), 38.3% were underweight (severe and moderate) [Table 2].
Table 1: Distribution of children by age and sex

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Table 2: Prevalence of undernutrition among children using the WHO child growth standards

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The proportion of wasting and underweight were highly statistically significant (P < 0.05) when compared in terms of age-wise distribution of the study participants [Table 3]. The proportion of wasting was higher among boys, whereas proportion of stunting and underweight was higher among girls. CIAF rate (54.4%) as recently suggested one of indicators of undernutrition was higher than wasting, underweight, and stunting rates [Table 4].
Table 3: Association between nutritional status and age of children

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Table 4: Distribution of children into subgroup of anthropometric failure using composite index of anthropometric failure

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Using Nandy et al.'s CIAF classification for participants [Table 4], it was observed that the frequency of subgroup “E” among growth failure (B–Y) subgroups was the highest (22.1%), which accounted for 20.1% and 24.7% in respective proportion of boys and girls participants. The SI (0.783) and UI (0.587) were higher among girls and WI was higher among boys (0.359) [Table 5].
Table 5: Comparison of composite index of anthropometric failure indices among children

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  Discussion Top

The time trend of undernourished children in India is showing declining pattern, but the pace of reduction is not matching the criteria set by United Nation Development Project under millennium developmental goals for India. This is matter of concern as undernutrition causes a significant contribution in under-5 year children mortality.[10] The present study conducted in rural area showed the prevalence of stunting, underweight, and wasting among the study participants as 41.3%, 38.3%, and 18.4%, respectively, which when compared to latest available data of NHFS-4 (Haryana), the prevalence for stunting (39.6%) and wasting (19.0%) was similar, but it differed underweight (45.7%) rate.[11] As the prevalence of undernutrition is declining and NFHS-3 (Haryana) provides a decade back scenario, the prevalence rate of stunting, underweight, and wasting calculated in it was of higher range when compared with our study.[12] The prevalence of stunting and underweight was coming out to be on lower side in our study in comparison to other studies.[9],[13]

The present study showed the highest prevalence for stunting (41.3%), followed by underweight (38.3%) and least for wasting (18.4%). Similar trends for prevalence were noticed in NFHS-4 (Haryana, stunting 45.7%, underweight 39.6%, and wasting 19.0%) and other studies but differed from Bose and Mandal's observation.[11],[13],[14],[15],[16] In our study, the prevalence of stunting (44.2%) and underweight (40.3%) was higher among girls than boys (stunting 39.2%; underweight, 36.8%), which again followed similar pattern of NFHS-4 (Haryana) data and Berger et al.'s study but not in agreement with other studies.[11],[16],[17],[18]

When taking CIAF into consideration for calculating prevalence of undernourished children, it was coming out to be 54.4%, which tends to be higher than the overall prevalence rates of stunting, wasting, and underweight calculated using conventional methods and this tendency was in agreement with the observations of other studies.[13],[17],[19],[20] CIAF prevalence calculated in other studies was elevated than the prevalence calculated in the present study; on the other hand, CIAF prevalence estimation concerned with Dasgupta et al.'s study was lower than the present study.[13],[16],[18],[19] Underweight as the only criterion for identifying undernourished children may underestimate the true prevalence of underutrition, by as much as 16.1% in the present study. As far as SI, UI, and WI are concerned, studies of Nandy et al. and Anwar et al. found lower value for SI, WI, and UI than the present study.[6],[19] From above discussion, CIAF classification seems to being welcomed by various authors, but Bhattacharyya has criticized it and raised issues regarding its usefulness.[21] As the main objective of study was to calculate undernutrition burden using current conventional indicators and CIAF classification, the information regarding calorie and protein intake, morbidity history, and socioeconomic status of the participants was not gathered in the present study which can be considered as its limitation.

  Conclusions Top

In speeding up to decline the rate of undernutrition in community, additional steps have to be taken. CIAF must be included under routine growth monitoring at the community level as it requires inclusion of measurement of height at anganwadi centers (ICDS centers) in addition to weight measurement. Underestimating this proportion might prevent undernourished children from receiving the benefit of the extra supplementation they deserve. It must be emphasized, however, that conventional indices reflect distinct biological processes and cannot be disregarded, but this issue has been addressed with the construct of the new indicator CIAF and its merits further consideration as a policy and monitoring tool for planning purposes. The disaggregation of undernourished children into different subgroups as done in CIAF allows the researchers to further examine the relationship between particular combinations of undernutrition and poverty or morbidity/mortality data. This is a very serious problem, by any scale. Under such conditions, our intervention efforts need to be broader than providing supplementary nutrition alone.

Financial support and sponsorship


Conflicts of interest

There are no conflicts of interest.

  References Top

World Health Organization. Global Nutrition Targets 2025: Policy Brief Series (WHO/NMH/NHD/14.2). Geneva: World Health Organization; 2014. Available from: http://www.who.int/iWHO_NMH_NHD-14.2_eng.pdf. [Last accessed on 2017 Oct 23].  Back to cited text no. 1
International Institute for Population Sciences. National Family Health Survey (NFHS-4), 2015–16: India. Vol. 1. Mumbai, India: IIPS; 2017. Available from: http://www.rchiips.org/nfhs/report.shtml. [Last accessed on 2018 Jul 05].  Back to cited text no. 2
World Bank. World Development Report: Equity and Development. Washington, DC: World Bank; 2006. Available from: https://openknowledge.worldbank.org/handle/10986/5988. [Last accessed on 2017 Jul 05].  Back to cited text no. 3
International Institute for Population Sciences. National Family Health Survey (NFHS-3), 2005–06: India. Vol. 1. Mumbai, India: IIPS; 2007. Available from: http://www.rchiips.org/nfhs/report.shtml. [Last accessed on 2018 Jul 05].  Back to cited text no. 4
Svedberg P. Poverty and Under Nutrition: Theory, Measurement and Policy. New Delhi, India: Oxford India Paperbacks; 2000.  Back to cited text no. 5
Nandy S, Irving M, Gordon D, Subramanian SV, Smith GD. Poverty, child undernutrition and morbidity: New evidence from India. Bull World Health Organ 2005;83:210-6.  Back to cited text no. 6
World Health Organization. Expert Committee on Nutrition and Physical Status: Uses and Interpretation of Anthropometry. Geneva: World Health Organization; 1995.  Back to cited text no. 7
World Health Organization. Multicentre Growth Reference Study Group: WHO Child Growth Standards: Length/Height-for-Age, Weight-for-Age, Weight-for-Length, Weight-for-Height and Body Mass Index-for-Age: Methods and Development. Geneva: World Health Organization; 2006.  Back to cited text no. 8
Bose K Jr., Mandal GC. Proposed new anthropometric indices of childhood undernutrition. Malays J Nutr 2010;16:131-6.  Back to cited text no. 9
United Nations Children's Fund. State of the World's Children Report. New York: UNICEF; 2014.  Back to cited text no. 10
International Institute for Population Sciences. National Family Health Survey (NFHS-4), 2015–16: Haryana. Vol. 1. Mumbai, India: IIPS; 2017. Available from: http://www.rchiips.org/nfhs/report.shtml. [Last accessed on 2018 Jul 05].  Back to cited text no. 11
International Institute for Population Sciences. National Family Health Survey (NFHS-3), 2005–06: Haryana. Vol. 1. Mumbai, India: IIPS; 2007. Available from: http://www.rchiips.org/nfhs/report.shtml. [Last accessed on 2018 Jul 05].  Back to cited text no. 12
Seetharaman N, Chacko TV, Shankar SR, Mathew AC. Measuring malnutrition, the role of Z-scores and the composite index of anthropometric failure (CIAF). Indian J Commun Med 2007;32:35-9.  Back to cited text no. 13
Joseph B, Rebello A, Kullu P, Raj VD. Prevalence of malnutrition in rural Karnataka, South India: A comparison of anthropometric indicators. J Health Popul Nutr 2002;20:239-44.  Back to cited text no. 14
Bose K, Biswas S, Bisai S, Ganguli S, Khatun A, Mukhopadhyay A, et al. Stunting, underweight and wasting among integrated child development services (ICDS) scheme children aged 3-5 years of Chapra, Nadia district, West Bengal, India. Matern Child Nutr 2007;3:216-21.  Back to cited text no. 15
Bisai S, Ghosh T, Bose K. Prevalence of underweight, stunting and wasting among urban poor children aged 1- 5 years of West Bengal, India. Int J Curr Res 2010;6:39-44.  Back to cited text no. 16
Berger M, Hollenbeck C, Fields-Gardner C. Prevalence of malnutrition in HIV/AIDS Orphans in the Nyanza province of Kenya: A comparison of conventional indices with a composite index of anthropometric failure (CIAF). J Am Diet Assoc 2006;106:20.  Back to cited text no. 17
Dasgupta A, Parthasarathi R, Prabhakar VR, Biswas R, Geethanjali A. Assessment of undernutrition with composite index of anthropometric failure (CIAF) among under-five children in a rural area of West Bengal. Indian J Commun Health 2014;26:132-8.  Back to cited text no. 18
Anwar F, Gupta MK, Prabha C, Srivastava RK. Malnutrition among rural Indian children: An assessment using web of indices. Int J Public Health Epidemiol 2013;2:78-84.  Back to cited text no. 19
Dang SN, Yan H. Optimistic factors affecting nutritional status among children during early childhood in rural areas of Western China. Zhonghua Yu Fang Yi Xue Za Zhi 2007;41:S108-14.  Back to cited text no. 20
Bhattacharyya AK. Composite index of anthropometric failure (CIAF) classification: Is it more useful? Bull World Health Organ 2006;84:335.  Back to cited text no. 21


  [Table 1], [Table 2], [Table 3], [Table 4], [Table 5]

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