H1.4.2 Child Stunting

Model Description:

This Bayesian network models the level of Stunted Children due to malnourishment. This models considers the type of delivery, the care/attention provided to the child and the mother, what form of nourishment is provided and considering all this tries to analyze the number of Stunted Children due to malnourishment. 

The malnourishment data is reported based on children that are registered in Anganawadis. 

Nodes/Attributes

The above model is based on the following nodes. The color scheme used represents the type of node/attribute. (Purple – Independent node; Orange – Dependent node; Red – Target node)

Node/Attribute Description Data Source
No. of new-born children_1353 Total number of children born recently KAG 2020-21
Total Anganawadi Centres_1512 Number of Anganwadi Centers KAG 2020-21
No. of Anganawadi Workers_1523 Number of Anganwadi Workers KAG 2020-21
No. of Anganawadi Helpers_1524  Number of Anganwadi Helpers KAG 2020-21
No. of Beneficiaries availed Janani Suraksha Yojana (JSY)_1338  No. of pregnant women availing the scheme KAG 2020-21
No. of institutional deliveries_1350 No. of pregnant women delivering in a hospital KAG 2020-21
No. of deliveries at home_1351  No. of pregnant women delivering at home KAG 2020-21
Total No. of Children in Anganwadi_1525 No. of children enrolled in Anganwadi s KAG 2020-21
Total number of new-born children breastfed within one hour_1356 Total number of new-born children breastfed within one hour KAG 2020-21
Total number of live babies weighed at birth_1357 Total number of live babies weighed at birth KAG 2020-21
Number of breastfeeding children receiving adequate diet_1365 Number of breastfeeding children who received adequate diet for nutrition KAG 2020-21
Low birth weight babies reported (less than 2500g)_1358  New born babies with weight less than 2500 gm KAG 2020-21
Severely Malnourished_1528 Number of babies who are severely malnourished KAG 2020-21
Stunted_Children_1529 (Target Variable) Number of babies who fall in the stunted category KAG 2020-21
Node Description Table

Intervention Modelling

It sets the network variables to specific levels, to track the changes in the target variable in the network. For instance: If we fix the value of the variable ‘Number of Beneficiaries availed Janani Suraksha Yojana_1338’ to ‘high’, then we would study the impact of this intervention on the target variable i.e., “Stunted_Children_1529″ of the network across varieties of Taluks in Karnataka.

Intervention Code Intervening Node Description Ease of Intervention
[1-most difficult, 5-easy]
Total Models Impacted Models Impacted Domains Impacted Data Stories impacted upon intervention
I1 Number of Beneficiaries availed Janani Suraksha Yojana
_1338
Increasing the number of beneficiaries that avail the JSY scheme in order to assess the nutritional health of a new-born child. Beneficiaries can be increased by spending more resources on deploying more ASHA workers and spreading awareness amongst the general public. 3 4 1.Maternal Deaths
2. Child Malnutrition
3. Child Stunting
4. Child Wasting
Health
I2 Total Anganawadi Centres_1512 Increasing the number of Anganawadi centres with the aim of registering more new-born children and their mothers under the Anganawadi system and seeing what impact it has on the nutritional health of the child. 4 2 1. Child Stunting
2. Child Wasting
Health
I3 No. of Anganawadi Workers_1523 Increasing the number of Anganawadi Workers with the aim of providing better care to more new-born children and their mothers that have registered in an Anganawadi and seeing how much of a positive impact it has on the nutritional health of the child. 4 2 1. Child Stunting
2. Child Wasting
Health
I4 Total Anthyodaya Ration Card Holders_32 Increasing the ratio of number of Anthyodaya ration card holders to People BPL we can determine whether the benefits provided by the Anthyodaya scheme are  actually beneficial in improving children’s nutritional health. Can also be used to adjust the benefits provided by the scheme so that nutritional needs are better met. 3 2 1. Child Stunting
2. Child Wasting
Health
I5 No. of institutional deliveries_1350 By promoting institutional deliveries through schemes and ads not limited to but including JSY we can aim at educating women on child nourishment and care to be taken to ensure nourishment through counselling by doctors and professionals at the hospitals. 4 4 1.Maternal Deaths
2. Child Malnutrition
3. Child Stunting
4. Child Wasting
Health
Intervention Modelling Table

DISCLAIMER: AI predictive models are meant to support and augment expert decision-making, and not a replacement for the same. It is important for AI model predictions to be vetted by domain experts before committing to action