Malnourishment Undefined

Data is the backbone of most policies and subsequently the areas of intervention by the government. But, it is difficult to identify if the data collected is sufficient enough an evidence for the government to take action in that particular domain. At times, domains overlap- thus the effects of flawed data create a problem for people at large across the spectrum.

The problem is exacerbated when data for ‘The World’ is calculated. World Health Organization, United Nations, Amnesty International and Organization for Economic Co-operation and Development are just a few such organizations trying to map the world statistics on one plane. But, there is a problem.

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Malnutrition rates in India are among the worst in the world. So, much so that even much-poorer sub-Saharan African countries claim to do better on the scale. Whats even more interesting is that the scale is set by the WHO or World Health Organization- so the data is reliable. Malnutrition is measured by various indicators- weight and height being the primary ones. So, most Indians are said to be underweight and are said to have a stunted growth.

To understand why that is- looking towards India is important of course, but it is equally important to understand how the data was caluculated.

Deep-diving into that- the WHO set a standard in early 2000s (10–15 years ago) which formed the baseline that determines how many children are stunted and how many aren’t. So, the World Health Organization measured samples of healthy 8,440 children in Brazil, Ghana, India, Oman and United States. It then categorized them under age, sex and other criterion and took the height of the child at the bottom 2.25 percentile as the yardstick for comparison of children of same/similar age and sex. For underweight children, a similar method was followed.

One could always argue that there isn’t a better standard of measurement to justify this, but clearly this method has a lot of assumptions attached to it- the key assumption being that proper nourishment will produce similar outcomes as that of the 8,440 families sampled.

Much is left for explanation, but clearly the measurement of social indicators needs to improve as it creates a rhetoric that we can’t forget easily. The amount of population suffering remains undefined and needs an acute identity for any welfare intervention to take place.

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