Types of anthropometric failures among children
An overall CIAF prevalence of 55.1% among children was found as opposed to 38.4% (stunting), 35.7% (underweight) and 21% (wasting) in the NFHS-4 report. Among the CIAF categories, 22.4% of children suffer from only one form of anthropometric failure (groups B, F and G), whereas 26.6% of children have simultaneous two failures (groups C and E) and 6.7% have all three forms of anthropometric failures. Simultaneous two failures of stunting and underweight (18.5%; group E) is the highest reported type of anthropometric failure. Overall, children of ST Poor appear disadvantaged both in rural and urban areas; ST Poor Male Rural children have the highest proportion of simultaneous three forms of anthropometric failures (12.6%), whereas the ST Poor Male urban children have the highest proportion of children undernourished (71.5%). Both cross-tabulation of CIAF with wealth quintiles and the intersectional analysis shows that economic position is an important factor affecting the nutritional status of children measured by CIAF. There is a large difference in CIAF between children from the poor and non-poor economic position with non-poor advantage irrespective of gender, caste, and place of residences.
Table 1: Descriptive table on the distribution of CIAF by intersecting sub-groups of Caste, Economic position, Gender and Place of Residence
Rural v/s urban inequality
The cross-tabulation of urban-rural difference in CIAF shows 58% of children from the rural residence are undernourished by CIAF as against 48.3% of children in urban residences (X2=1649.002, p=.0001). Similarly, while 6.78% of children have simultaneous three failures in rural areas, it is 4.93% in urban areas (X2=235.19, p=.0001). However, the urban advantage is not uniformly distributed among all the social groups. While the urban nutritional advantage is observed more consistently among the ST children in both CIAF and simultaneous three failures, the urban nutritional advantage is reversed among the SC and other caste children from the poor household in most of the cases. The general pattern observed is that while undernutrition among the ST community is clustered more among the rural areas irrespective of gender and economic position, among the SC and Other caste, the urban nutritional advantage is reversed more among the poor households (See Fig: 1).
Figure 1: Rural v/s Urban Intersectional Subgroup Comparison
Concentration curve (CC) (figure 2) shows consistently higher socio-economic inequality in the severe form of undernutrition (simultaneous three failures) than aggregate CIAF index across all caste groups, indicating relatively more unfair clustering of simultaneous three failures across caste groups than with CIAF. While the highest proportion of children from ST suffered simultaneous three failures, the same community reported the lowest rate of inequality in nutritional status by wealth quintiles. The lack of economic improvements among the ST community limits our ability to assess the role of socio-economic position in improving the child nutritional status among ST. In OBC and general category (other) where the spread of households across all socio-economic positions is seen, the rich-poor inequalities are higher (compare with ST). Interestingly, the CC of SC demonstrated a shifting trend; while the poorest wealth quintile, of both SC and ST groups, coincide, higher up on the socioeconomic gradient, the SC group makes a departure from this trend and shows increasing inequality and coincides with OBC and general categories. This means that the nature of inequality in child nutritional status among the SC poorest wealth quintiles is similar to that of the ST community whereas, among the upper wealth quintiles the inequality increases further indicating differential effects of socio-economic improvements within the SC category.
Figure 2: Concentration Curve for CIAF by Caste Category
Based on >1 SD of the mean district prevalence of co-occurring two failures or simultaneous all-three-failures, (>23% for stunting and underweight, > 11.7% wasting and underweight, >9.5% all-three-failures; see supplementary file 1), critical (11), very serious (72) and seriously affected (28) districts were identified. In all the critical districts, nearly half (>45%) of children reported at least two simultaneous anthropometric failures. Among these, the dangs district from Gujarat reported the highest proportion (60.1%) of children with at least two failures. From the states of Bihar and Jharkhand two districts each and from Chhattisgarh, Karnataka, Madhya Pradesh, Rajasthan, Uttar Pradesh, and West Bengal one district each was reported as critical (see supplementary file 2). Among the very serious districts, Pashchimi Singhbhum district in Jharkhand with 64.7% of children with at least two anthropometric failures nearly met the criteria for being a critical district (underweight and wasting prevalence 11.5%; all-three-failures 21.2%; and stunting and underweight 32%). The highest number of very serious districts are reported from Madhya Pradesh (19), followed by Jharkhand (13) (see supplementary file 3 for details). Gujarat has the highest number of serious districts (8) followed by Odisha (4). Overall spatial distribution of critical, very serious and serious district-level prevalence shows geographical clustering of these districts in four undernutrition hotspots spanning over 12 high burden states. In south India, a cluster of eight districts in north Karnataka forms the undernutrition hotspot. The second undernutrition hotspot is eleven districts along the state boundaries of Chhattisgarh (4), Odisha (6) and Maharashtra (1). The third hotspot is spread across the regions spanning the borders between West Bengal, Bihar and Jharkhand consisting of 28 districts, of which 11 are from Bihar, 3 from West Bengal and 14 from Jharkhand. The fourth hotspot is 53 districts spanning across Madhya Pradesh (23), Rajasthan (7), Gujarat (17), Maharashtra (4) and Uttar Pradesh (2) (See figure 3).
Figure 3: Undernutrition hotspots in India
Critical districts = High prevalence in all three failures, stunting and underweight, and underweight and wasting.
Very serious districts = High prevalence in all three failures, stunting and underweight or underweight and wasting.
Serious districts = High prevalence in all three failures or high prevalence in stunting and underweight, and underweight and wasting.
The Moran plot shows a linear fit through the point cloud. The slope of this line corresponds to Local Moran’s I values were 0.615 for stunting, wasting and underweight, 0.69 for stunning and Underweight, and 0.63 for wasting and underweight. All the coefficients were statistically significant (see figure 4). This indicates that the three-dimensional and two-dimensional anthropometric failures among children in India is not uniformly distributed across Indian districts, rather there is significant clustering of the high prevalence of two-dimensional and three-dimensional failures in India, further strengthening the case for identifying hotspots.
Figure 4: Univariate LISA maps of India showing clustering of undernutrition hotspot and cold spot by two dimensional and three-dimensional anthropometric failures