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| ORIGINAL ARTICLE |
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| Ahead of print publication |
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A comparative analysis among three world health organization growth charts
Chaitali A Borgaonkar1, Chinmay N Gokhale2, Mridula J Solanki3, Sunita S Shanbhag3
1 Department of Community Medicine, Dr. DY Patil Medical College, Hospital and Research Centre, Pune, Maharashtra, India
2 Department of Community Medicine, HBTMC and RNCH, Mumbai, Maharashtra, India
3 Department of Community Medicine, GSMC and KEMH, Mumbai, Maharashtra, India
| Date of Submission | 30-Apr-2021 |
| Date of Decision | 02-Jul-2021 |
| Date of Acceptance | 08-Jul-2021 |
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Correspondence Address:
Chinmay N Gokhale,
MHADA/20-B, Orchard Avenue Road, POWAI, Mumbai - 400 076, Maharashtra
India
 Source of Support: None, Conflict of Interest: None DOI: 10.4103/mjdrdypu.mjdrdypu_519_21
Background: India is in a phase of nutrition transition. Child nutrition and growth monitoring services are provided under the state-run Integrated Child Development Scheme program. Classically, only one kind of growth chart is used to quantify nutrition status and categorize the children. Materials and Methods: This cross-sectional study involving 222 children was done to compare the outcome of nutritional status evaluated using three World Health Organization growth charts: weight-for-age, height-for-age, and weight-for-height. The results obtained by the use of these three charts were further compared and analyzed for concordance. Results: The three growth charts showed that 58% of children were underweight, 53% had stunting, and 35% were wasted among the study population. The comparisons using sensitivity/specificity, Kappa statistics, and ANOVA showed bidirectional disagreements between the three charts. Similar results could be deduced from large surveys done previously in Iraq and Congo. Conclusion: Hence, simultaneous use of three growth charts to categorize nutrition status is essential. This will help in preventing missing out cases of malnutrition and perhaps may aid in detecting child malnutrition at a relatively earlier stage.
Keywords: Comparison between growth charts, malnutrition, World Health Organization growth charts
How to cite this URL:
Borgaonkar CA, Gokhale CN, Solanki MJ, Shanbhag SS. A comparative analysis among three world health organization growth charts. Med J DY Patil Vidyapeeth [Epub ahead of print] [cited 2023 Mar 20]. Available from: https://www.mjdrdypv.org/preprintarticle.asp?id=336822 |
| Introduction | |  |
India is in a phase of nutritional transition, and thus, it is vital to update growth references regularly. A joint directive by the two ministries of Government of India was issued in 2008 according to which the World Health Organization (WHO) 2006 standards were to be used for assessing nutritional status of preschool children under both National Rural Health Mission and Integrated Child Development Scheme (ICDS), the two state-run flagship programs related to child health and nutrition.[1]
ICDS is one of the world's largest community-based programs. Under this program, child nutrition and growth monitoring services are provided free of cost to all children, especially in rural areas of India. These services are delivered through centers known as “Anganwadi centers” (AWCs) which are managed by Anganwadi workers. They are trained in using the weight-for-age growth chart to classify child nutrition and provide further management or referral services on the basis of the nutrition category of the child.[1],[2]
Weight-for-age, height-for-age, and weight-for-height are the three commonly used growth charts, indicating “underweight,” “stunting,” and “wasting,” respectively. Although they are related, yet they depict different forms of child's malnutrition, and hence, emphasizing on both weight- and height-based parameters has gained importance in recent times.[3] In alignment with this theoretical concept, India's National Family Health Survey (NFHS) gives malnutrition estimates using all the three growth charts. As per the NFHS-4, the proportion of stunted under-5 children from across India were 31%, wasted were 20%, and underweight were 29.1%.[4] However, the use of a single kind of growth chart for growth monitoring is a routine practice and is even backed by many government-issued guidelines including those for ICDS workers.[1],[5]
This study was planned to compare the outcome of a child's nutrition status given by the three kinds of WHO growth charts and to test the utility of combined use of three growth charts.
| Materials and Methods | | |
This cross-sectional study was conducted in rural area located few kilometers from Mumbai, Maharashtra, India. Data were collected from all the affiliated Anganwadis of rural field practice area of a tertiary care health institute. All children aged 3–5 years registered in these Anganwadis were included in this study, and the total sample size was 222. Ethical approval was taken from Institutional Ethics Committee, and informed written consent was taken from all participants' parents/guardians. Nutrition-related parameters such as weight, height, and age were collected for children. Standard equipment, i.e., weighing machine and stadiometer, were used for recording weight and height of children.
The growth assessment tools used to classify nutrition status included three kinds of WHO growth charts: weight-for-age, height-for-age, and weight-for-height. Nutrition status was classified into severe, moderate, and normal as per the standard definitions: <−3 SD is severe category, between −3 SD and −2 SD is moderate category, and >−2 SD is normal category. WHO Anthro Software[6] was used to calculate Z-scores on three growth charts. As per the standard definitions, the categories were labeled as “severe,” “moderate,” and “normal” on each growth chart, viz., severely underweight, moderately underweight, and normal weight on weight-for-age chart, and so on.
The results obtained by the use of these three tools were further compared and analyzed for concordance. As weight-for-age chart is recommended and routinely used in this area, it was taken as a standard and results of other two charts were compared against the results of weight-for-age chart.
| Results | | |
Of the 222 children included in this study, 98 (44.14%) were boys and rest 124 (55.85%) were girls. The comparison of the three different growth assessment tools [Table 1] showed that weight-for-age chart yielded the most cases of malnutrition – 58.1% underweight (51 severely underweight and 78 moderately underweight) followed by height-for-age – 53.6% stunting (42 severely stunted and 77 moderately stunted) and the least by weight-for-height – 35.1% wasting (30 severely wasted and 48 moderately wasted).
On comparing weight-for-height chart with weight-for-age [Figure 1], it was found that only 45% of severely underweight children were labeled as severely wasted, another 33% were labeled as moderately wasted, and a shocking 22% were missed by weight-for-height chart. Similarly, 65% of those classified as moderately underweight (on weight-for-age chart) were missed and labeled as normal by weight-for-height chart. Conversely, of those who were labeled as normal on weight-for-age chart, 12% of them were found to be malnourished as per the weight-for-height chart. The value for Cohen's Kappa between results of weight-for-height and weight-for-age chart was 0.37, which denotes minimal agreement. The sensitivity of weight-for-height chart was only 51% which indicates that it missed out on many underweight children [Table 2]. | Figure 1: Comparison of weight-for-height and weight-for-age growth charts
Click here to view |
The discordance between height-for-age and weight-for-age chart [Figure 2] was also apparent with 16% of severely underweight children and 42% of moderately underweight children, being labeled as normal by height-for-age chart. Further, 33% of children having normal weight for their age were classified as stunted by height-for-age chart, indicating that the disagreement is bidirectional. Kappa value of 0.34 and sensitivity of just 68% further elucidate the dissimilarities in results [Table 3].
Even when weight-for-height was compared with height-for-age, the Cohen's Kappa value was −0.03 (P = not significant) which denotes almost negligible agreement between these two charts.
Furthermore, using all the Z-scores (continuous data) as given by the three growth charts for all children, the results of one-way ANOVA test showed that three groups were significantly different (F = 75.64, P < 0.001). This again reaffirms the fact that the results by three charts are significantly different, and hence, the use of single chart carries a threat of missing out malnutrition cases.
| Discussion | | |
The majority of Indian populations (and under-5 children) reside in rural areas where the routine growth monitoring is primarily done in AWCs using single growth chart, which invariably is weight-for-age. Even in the study area, it is a common practice to use only weight-for-age chart for monitoring the growth of children.
Many previously published studies[7],[8] have compared the use of corresponding growth charts given by two different agencies. However, we were not able to find significant amount of literature where a simultaneous use of the results given by three kinds of growth charts from same agency (WHO in case of our study) was compared. However, we did find a few articles where all three growth charts were used. For instance, in a mass-level survey done in Iraq, 12% were underweight, 13.8% were stunted, and 9.2% were wasted using standard cutoff definitions.[9] Clearly, there is a difference in yield of the three growth charts, especially considering the fact that the sample size was large (>6000), and hence, even a miniscule difference in proportions would correspond to a significant actual number of malnourished children.
Another large-scale survey comprising 5000 children from the Democratic Republic of Congo showed that, on applying the WHO growth standards, the incidence of wasting was 8.5% and this was different from incidence of underweight (6.6%). This survey again shows difference in yield from two growth charts. In the current study, the proportion of underweight (deduced from weigh-for-age chart) was much more than that of wasting (deduced from weight-for-height chart), which is in contrast to the Congo survey where wasting was more than proportion of underweight children.[10]
The module by WHO for training on interpreting the growth indicators clearly vouches for simultaneous use of all kinds of chart, which would help in understanding the nature of growth problem.[11] Therefore, it can be summarized that the findings of this study are in line with the prestated WHO guidelines. An important finding to note was that none of the three charts were found superior as all charts missed out on malnutrition cases that were picked by other two charts. All kinds of analysis – sensitivity/specificity, Kappa statistics, and ANOVA – re-affirmed these facts.
| Conclusion | | |
There was widely prevalent malnutrition in study area as found using all the three different growth assessment tools. However, there were disparities in the nutrition status indicated by the three different growth charts with the disagreement being bi-directional in between all the three kinds of growth charts. In summary, it could be said that the practice of using a solitary growth chart carries a threat of missing out cases and thereby delaying the diagnosis of the dreadful disease named malnutrition. Hence, simultaneous use of all three kinds of WHO growth charts is recommended for routine growth monitoring at all levels right from peripheral health workers to the very specialist levels. This practice is likely to reduce the chance of missing malnutrition cases and perhaps may even aid in detecting child malnutrition at a relatively earlier stage.
Acknowledgment
We would like to thank all the Anganwadi staff members for their contribution to this study. We also wish to express gratitude toward Late Dr. Ratnendra R. Shinde for his contribution to this study.
Financial support and sponsorship
Nil.
Conflicts of interest
There are no conflicts of interest.
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[Figure 1], [Figure 2]
[Table 1], [Table 2], [Table 3]
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