Introduction

Malnutrition remains a major global public health concern, threatening child's survival and their ability to thrive.[1,2] Childhood nutritional deficiencies may trigger cognitive impairments, hinder academic performance and reduce productivity.[3,4] Joint child malnutrition estimates, 2022 reported that 22% of children under five were stunted and 7% were wasted, with more than 90% of the burden concentrated in Asia and Africa.[5] According to the Global Hunger Index (2025), which measures hunger using indicators such as undernourishment, child stunting, child wasting, and under-five mortality, India ranks 102^nd among 123 countries with a score of 25.8, placing it in the ‘serious category’.[6] In India, NFHS-5 data indicates that 32.1% children under five years of age were underweight, 19.3% were wasted, and 35.5% were stunted.[7] The situation among tribal children is even more concerning, with 40.9% stunted, 23.2% wasted, and 39.5% underweight.[7] Major risk factors responsible for high undernutrition prevalence among tribal children include socioeconomic, cultural, environmental and political factors such as economic instability, poverty, parental unemployment, parental education, maternal nutrition, faulty feeding practices, traditional beliefs, poor hygiene and lack of ration cards.[8–16]

Malnutrition among children under five years of age is commonly assessed using anthropometric indicators such as stunting (low height-for-age), underweight (low weight-for-age), and wasting (low weight-for-height).[17] However, these indicators often overlap to varying degrees. For example, some underweight children may also be stunted and/or wasted, while some stunted children can also be underweighted, and others may experience all three forms of anthropometric failure simultaneously i.e. stunting, wasting, and underweight. Consequently, using any one of these conventional indicators alone does not fully capture the overall burden of undernutrition.

In 2000, Swedish economist Professor Peter Svedberg proposed an alternative indicator to estimate the overall burden of undernutrition: the Composite Index of Anthropometric Failure (CIAF).[18,19] Svedberg proposed six subgroups: Group A (no failure), Group B (wasting only), Group C (wasting and underweight only), Group D (wasting, stunting, and underweight), Group E (stunting and underweight), and Group F (stunting only).[18] Later, Nandy et al.[20] expanded this framework by introducing an additional subgroup, Group Y (underweight only). Subsequently, Kuiti and Bose[21] added Group G (stunting with overweight) and Group H (overweight only). More recently, Mahapatra and Bose[22] proposed Category I, representing children who are stunted and wasted but not underweight (Table 1). The CIAF provides an actual burden of undernutrition by classifying children into specific subgroups, allowing for a more comprehensive analysis of the interrelationships among various forms of undernutrition.[22] The present study aims to assess undernutrition using conventional anthropometric indices alongside CIAF among the Korku children under five years of age in the Melghat region of Maharashtra.

Materials and Methods

Study design

The present community-based cross-sectional study was carried out from October 2023 to February 2024 among under-five Korku tribal children residing in Melghat region of Amravati district, Maharashtra, India. Melghat region comprises of Chikhaldara and Dharni tahsils. The area is covered with a dense forest and primarily inhabited by the Korku tribe. According to 2011 census, the total population of Melghat region is 3,03,480 persons (1,54,621 males and 1,48,859 females). Scheduled tribes comprised 2, 35,241 persons (1,19,313 males and 1,15,928 females) which is 77.5 % of the total population of Melghat. Korku are the largest indigenous group in Melghat. They belong to Munda subgroup and primarily speak Korku language which is a part of the Austro-Asiatic language family.[23,24] Their livelihood is primarily based upon agriculture, livestock, and forest products.

Sample Size and Sampling Method

The minimum sample size for the present study was estimated as 366 individuals using the single population proportion formula.[25] A stratified random sampling method was used to select villages having more than 80% tribal population. Further, study participants were purposively selected. Accordingly, the study was conducted among 384 Korku children under 5 years of age (192 boys and 192 girls) from Chikhaldara and Dharni blocks of Melghat, Amravati district, Maharashtra, India.

Inclusion and Exclusion Criteria

Healthy children from the Korku tribal community who i) were aged 0-5 years ii) had authentic vaccination card as a record of their date of birth were included in the study. Children were excluded if they: (i) had any chronic illness affecting their nutritional status, or (ii) were born with congenital anomalies, or (iii) were born extremely premature (less than 28 weeks of gestational age).

Ethical Clearance and Participation Consent

The study received ethical clearance from the Institutional Ethics Committee (IEC) of the Sikkim University, ensuring compliance with all relevant guidelines for research involving human participants. The objectives of the study were explained to the mothers before anthropometric measurements were taken. Data were collected after obtaining verbal consent from mothers of under‑five children using a structured interview schedule.

Anthropometric Measurements

Anthropometric measurements such as height and weight were taken following the standard procedure accurate to the nearest 0.1 cm and 0.5 kg, respectively.[26,27] The height and weight of children younger than 2 years were measured using an infantometer and a hanging weighing scale, respectively. For children aged 2 years and above, height was measured using a stadiometer and weight was recorded using a weighing machine.

Assessment of Nutritional Status

Based on anthropometric measurements, Z scores for height-for-age (HAZ), weight-for-age (WAZ), and weight-for-height (WHZ) were computed using Anthro software version 3.2.2. Children were classified as underweight (WAZ <-2 SD), stunted (HAZ <-2 SD), or wasted (WHZ <-2 SD) according to WHO standards[28], with severe undernutrition defined as WAZ, HAZ, or WHZ <-3 SD and moderate undernutrition as scores between -3 and -2 SD. The CIAF was computed using the modified categories proposed by Mahapatra and Bose²² (Table 1).

Statistical Analysis

Anthropometric variables were analyzed statistically using STATA software version 15. Chi-square (χ²) tests were used for assessing sex-specific differences in the prevalence of undernutrition based on conventional anthropometric indices and CIAF. A p-value <0.05 was considered statistically significant. Independent samples t-tests were used to assess differences in mean anthropometric measurements across ages and sexes, with p-values reported to indicate statistical significance (p < 0.05). Euler plot and alluvial plot were prepared using R-studio software.

Results

A total of 384 children were evaluated for their nutritional status, with an equal distribution of boys (50%, n=192) and girls (50%, n=192). The mean age of studied children was 24.7 ± 14.9 months.

The mean weight was higher in boys than girls (9.73 ± 2.75 kg vs.9.32 ± 2.7 kg) (Table 2). Mean height followed the similar pattern (79.04 ± 12.59 cm vs. 77.37 ± 12.45 cm). Sex-differences in both height and weight were not statistically significant. Mean height and weight increased across age groups, showing a linear pattern. As age increased, children became taller and heavier (0-23 months: height 69.81 ± 9.58 cm, weight 7.72 ± 2.00 kg; 24-59 months: height 87.51 ± 8.04 cm, weight 11.53 ± 1.94 kg). Differences across age groups were statistically significant for both height and weight (height t= -19.49, p< 0.001; weight t = -18.89, p< 0.001) (Table 2).

Independent samples t-tests showed statistically significant sex differences across wasting and underweight categories (p > 0.05) (Table 2). The mean prevalence for wasting and underweight was slightly higher among younger age group (wasting: 0.17 ± 0.38 vs 0.13 ± 0.33; underweight: 0.42 ± 0.49 vs. 0.40 ± 0.49). Whereas, the mean prevalence of stunting (HAZ) was higher in older age groups (0.57 ± 0.49 vs. 0.52 ± 0.50). The differences by age were not statistically significant for any anthropometric indicators.

Table 3 presents age and sex-specific, as well as overall, prevalence of conventional anthropometric indicators and CIAF. The overall prevalence of underweight, stunting, wasting and CIAF was 40.9%, 54.7%, 14.8% and 67.7%, respectively. It was observed that boys were more affected by underweight (46.4% vs. 35.9%), severe underweight (15.6% vs. 9.4%), moderately underweight (30.7% vs. 26.6%), stunting (56.8% vs. 53.1%), severe stunting (28.7% vs. 24.5%), wasting (19.8% vs. 9.9%), and moderate wasting (16.7% vs. 5.7%). The girls were slightly more affected by moderate stunting and severe wasting than boys (moderate stunting: 28.7% vs. 28.1%; severe wasting 4.2% vs. 3.1%)

Age wise distribution of undernutrition categories reveled that younger age group (0-23 months) experienced more prevalence of underweight (42.1% vs. 40.1%), severe underweight (13.9% vs. 11.0%), wasting (16.8% vs. 12.6%), and moderate wasting (13.4% vs. 8/.8%). Whereas, severe form of wasting was higher (3.9% vs. 3.5%) in the older age group (24-59 months). The older age group (24-59 months) also experienced higher prevalence of moderate underweight (29.1% vs. 28.2%), severe stunting (26.9% vs. 26.2%), moderate stunting (30.2% vs. 26.7%), and overall stunting (27.1% vs. 53.0%). Pearson’s chi-square test indicated that there is no significant association between age group and any anthropometric indicators.

The association between sex and being underweight was statistically significant χ² = 4.75, df = 1, p = 0.03), reflecting a higher burden among boys (46.4% vs 35.9%). A statistically significant difference was observed between sex and moderate as well as overall wasting (p<0.01)

Assessment of nutritional status using CIAF showed that stunting and underweight (E) was the most prevalent CIAF category, affecting 25.3% of children, followed by stunting only (F), affecting 19.3% of children. There was no prevalence of stunting and wasting only (I) category. In the single anthropometric failure categories overweight only (H), wasting only (B), stunting and overweight (G), and underweight only (Y) showed the lowest prevalence of 1.6%, 3.1%, 3.4%, and 3.4% respectively. Multiple anthropometric failure categories such as stunting and overweight (G), wasting and underweight (C), wasting, underweight and stunting (D) showed similar prevalence pattern (3.4%, 4.9%, 6.8%, 3.4% respectively). Euler plot shows the distribution and overlaps of anthropometric indicators.

Figure 1: Euler plot showing distribution and overlap of child undernutrition indicators: stunting, underweight, and wasting

The overall prevalence of anthropometric failure was higher among boys than girls (71.4% vs. 64.1%). Boys showed higher prevalence among all anthropometric failure categories except for stunting and overweight (G), overweight only (H) and underweight only (Y).

Pearson’s chi-square test showed a significant association between sex and CIAF category (χ2 = 17.31, df= 8, p = 0.027). Alluvial plot shows the distribution of boys and girls across age groups by CIAF status (no failure vs single anthropometric failure and double anthropometric failure) (Figure 2).

Figure 2: Alluvial plot depicting the distribution of boys and girls across age groups by CIAF status. Flows represent transitions between age categories and CIAF classifications (no failure, single anthropometric failure and multiple anthropometric failures)

Discussion

The use of the CIAF in this community-based cross-sectional study underscores several conceptual and practical advantages over single-indicator approaches. More than half of the children (67.7%) were classified as experiencing anthropometric failures according to CIAF. Notably multiple anthropometric failures (40.4%) were more common than single anthropometric failures (27.4%). This finding indicates that a substantial proportion of undernourished children suffer from more nutritional deficits, highlighting the complexity and severity of undernutrition within the study population. The findings support the study hypothesis that the burden of undernutrition is substantially higher when assessed through CIAF compared with conventional anthropometric indicators alone.

The prevalence of CIAF observed in the present study was lower than that reported in the previous study conducted in the same geographical region (Table 4).[29] Although both studies were undertaken in a tribal setting, pervious study included children from multiple tribal communities, whereas the present study focused exclusively on children belonging to Korku tribal group.[29] Differences in the prevalence could be attributable to variations in the socio-economic, cultural and dietary diversity that may exist among different tribal communities. This observation highlights the importance of recognizing that tribal populations are not homogenous and nutritional outcomes may vary between individual tribes. Furthermore, the time interval of more than 10 years between the two studies may have contributed to the lower prevalence observed in the present study. The lower prevalence could be due to implementation of several initiatives such as Integrated Child Development Services (ICDS), POSHAN Abhiyaan, Rajmata Jijau Mission, National Health Mission (NHM), Mission Vatsalya, Saksham Anganwadi, and Mission Indradhanush aimed at improving maternal and child health, nutritional supplementation, immunization coverage, sanitation, and access to healthcare services. The overall prevalence of CIAF in our study is higher than the prevalence among under-five children in Nagpur, Mumbai and Palghar districts of Maharashtra.[30–32] When compared with studies conducted outside Maharashtra, the CIAF prevalence in our study was lower than that reported from Medinipur, West Bengal (76.9%)[33] but higher than the prevalence observed in other studies.[22,31,32,34–40] (Table 4)

The present study observed a higher prevalence of CIAF among boys compared to girls. This finding is consistent with studies conducted among under-five children of Maharashtra, West Bengal, Chhattisgarh, and Odisha, India. [22,32,35,38,40] However, contrasting findings have been reported among under-five children of Kachari tribe of Assam, India and under-five children of Jangalmahal districts of India, who found a higher prevalence of anthropometric failure among girls.[34,39] The inconsistencies in findings across studies may be attributable to differences in study populations, geographical settings, socio-economic conditions, cultural practices and sample characteristics of the children studied. Variations in access to food, healthcare utilization, caregiving practices, and local gender norms may also influence nutritional outcomes differently across communities. Furthermore, the study identified a significant association between sex and anthropometric failure categories along with overall anthropometric failure. Similar results were reported in previous studies.[22,34,36] The comparison of CIAF categories across different studies revealed considerable variation in the pattern of anthropometric failure. Despite these differences, several common trends emerged. In most studies, and in the present investigation, category E (Stunting only) constituted highest proportion of anthropometric failure.[29–33,39] which indicates co-existence of multiple forms of nutritional deprivation. A substantial proportion of children were also classified under category F (Stunting only). This finding suggest that chronic undernutrition remains predominant nutritional challenge across different populations.[22,34,36–38,40] In contrast, categories representing acute forms of undernutrition, such as Category B (wasting only) and Category C (wasting with underweight), generally accounted for a smaller proportion of children in most studies including our study.[22,29–31,33,34,36,37,39,40] This pattern may indicate that chronic nutritional deprivation contributes more substantially to anthropometric failure than short-term nutritional deficits. However, some studies reported relatively higher prevalence of wasting related categories, suggesting possible regional differences in food availability, disease burden, lifestyle differences or environmental conditions.[32,35,38] Notably, 6.8% of children in the present study were classified under Category D, which indicates the coexistence of stunting, wasting, and underweight. This category identifies children experiencing multiple anthropometric failures and therefore at a higher risk of adverse health outcomes. The relatively high prevalence of Category D emphasizes the importance of using CIAF, as conventional indicators assessed separately may fail to adequately capture the extent of overlapping nutritional deficits within the population.

The comparison of conventional anthropometric indicators across studies revealed substantial variation in the prevalence of stunting, wasting, and underweight (Table 5). In the present study stunting (54.7%) was the most prevalent form of undernutrition, followed by underweight (40.9%) wasting (14.8%). A similar pattern where stunting consistently emerged as the predominant anthropometric deficit was reported in previous studies.[22,29,30,32–34,36,38,40]

Although conventional anthropometric indicators are useful for identifying specific forms of undernutrition, they evaluate each nutritional deficit separately and may overlook children experiencing multiple anthropometric failures. In the present study, the prevalence of CIAF exceeded that of any individual conventional indicator, suggesting that a considerable proportion of children suffered from overlapping forms of undernutrition. This observation highlights the limitations of relying solely on conventional indicators and supports the use of CIAF as a more comprehensive measure of the overall burden of anthropometric failure.

Limitations

The present study focused specifically on tribal children belonging to the Korku community in Melghat region of Maharashtra. Therefore, findings may not represent overall situation of tribal populations of the Maharashtra state. However, a major strength of the study is that, according to the 2011 Census, the Korku community in Maharashtra is predominantly concentrated in the Melghat region. Hence, the study findings may reasonably reflect the situation of Korku tribal children in Maharashtra. The cross-sectional nature of the present study is another limitation, as nutritional status of children was assessed at only one point in time. Therefore, temporal changes in nutritional status could not be evaluated. Thus, future longitudinal studies are needed to evaluate the effectiveness of interventions aimed at reducing childhood malnutrition.

Conclusion

In conclusion the present study shows high prevalence of undernutrition among the under-five children of Korku tribal community of Maharashtra. The burden of undernutrition is substantially higher when assessed through CIAF compared with conventional anthropometric indicators alone. Thus, the present study highlights the limitations of relying solely on conventional indicators and supports the use of CIAF as a more comprehensive measure of the overall burden of anthropometric failure. The CIAF provides a holistic overview of nutritional status by assessing varying degrees of undernutrition as well as overnutrition among children. It can help researchers, healthcare providers, and policy makers to better understand the overall burden of malnutrition and facilitate the development of targeted interventions and strategies to improve child health.

Acknowledgement

The authors express sincere gratitude to the mothers of the participating children for their kind cooperation during the study.

Declarations

The authors declare that they have no conflict of interest.

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