Using NFHS data, we track progress in five areas: standard of living, child nutrition, adult nutrition, maternal and child health, and basic literacy.
The fifth edition of the National Family Health Survey, or NFHS, was released recently.
This piece discusses some of the key findings from this survey and provides some historical context to survey data. Specifically, we look at how things have changed in the various human development metrics measured by the NFHS under the current Modi regime and the previous UPA regime.
But first, some background.
The Indian republic has always strived to be a welfare state, where the government plays an active, deliberate role in providing economic and social support to all its citizens. Since independence, every regional and national political party has adhered to this vision, espousing intents to improve the lives of the millions that remain mired in poverty. When elected to power, these parties have implemented countless schemes to mirror their rhetoric. Be it good intentions, principled politics, or just electoral calculus, public welfare is a central plank of both political discourse and public policy in India.
However, intentions don’t always translate to outcomes, especially in public policy.
Assessing the efficacy of any public welfare initiative is a key challenge. It is easy to monitor the inputs allocated to any effort. But there are no easy feedback mechanisms to gauge the outputs especially in welfare domains such as food security, health, education, etc. The only way to close this loop is to undertake the arduous task of conducting extensive surveys and statistical analysis.
In India, one such effort of collecting systematic data from households across the country is the National Family Health Survey. The NFHS is a large-scale, multi-round survey conducted throughout India. It measures a wide array of indicators related to health, nutrition, social issues, literacy, and access to public utilities – all measures of public wellbeing . The survey, which is commissioned by the ministry of health and family welfare, MOHFW, was first conducted in 1992-93 and has since been administered four more times.
As per the NFHS website, “each successive round of the NFHS has had two specific goals: a) to provide essential data on health and family welfare needed by the Ministry of Health and Family Welfare and other agencies for policy and programme purposes, and b) to provide information on important emerging health and family welfare issues.”
To this end, the survey collects detailed information across a wide spectrum of issues spanning health, education, and living conditions, providing a detailed dataset at a very granular level. To illustrate, the latest survey collected information on 131 key indicators from 6,36,699 households, 7,24,115 women, and 1,01,839 men and provides district level data granularity.
The last two surveys were conducted in 2004-05 and 2015-16. providing a rich dataset to infer trends across and policy efficacy across various socio-economic dimensions – both at the state level and the national level.
Either by coincidence or by design, the last three survey timelines neatly align with regime changes at the national level. Changes in data between NFHS-3 (2004-05) and NFHS-4 (2014-15) can be broadly attributed to the United Progressive Alliance government which was in power from 2004 to 2014. Similarly, changes in data between NFHS-4 (2014-15) and NFHS-5 (2019-21) can be attributed to policies instituted by the Modi-led NDA government.
Of course, all such sweeping inferences are prone to over simplification. But some broad observations and inferences can be drawn which are rooted in data, rather than pure narrative.
Keep in mind that although the timelines align with the UPA and NDA years, health and education, which are the primary realms being discussed, are state subjects. While the central government often influences policy in these areas, both through the budgetary outlays and various central schemes, state governments and policies are more influential in determining the final outcomes in each state. As such, the purpose of the comparisons between the UPA and NDA years is not to pin responsibility on either regime, but to get a broad sense of how things have changed across these periods. Plus, comparing trends over time provides context to the latest data.
As mentioned earlier, NFHS-5 collects information on 131 indicators. To keep this analysis palatable, we track trends across 20 key indicators within the larger pool that can be grouped into five distinct dimensions:
(1) standard of living
(2) child nutrition
(3) adult nutrition
(4) maternal and child health
(5) basic literacy
Note that most indicators chosen for this analysis are attributable to direct government intervention, unlike others on the survey that may also be influenced by individual choices and societal attitudes (such as sex ratio, under-age marriage, family planning, etc).
Quality of life
NFHS collects information on basic amenities available to a household which include access to clean drinking water, sanitation, electricity, and clean cooking fuel, all of which significantly affect one’s quality of life.
Figure 1 shows how we have fared on these metrics over the last three NFHS exercises. An additional indicator of access to health insurance is also included in this list.
The numbers above paint an encouraging picture. All five measures show an improving trend which bodes well for the millions who now have access to these life-improving and/or life-saving amenities. Note that some of the indicators above such as access to clean cooking fuel and improved drinking water and sanitation are associated with flagship schemes of the Modi government: Ujjwala and Swacch Bharat.
An interesting side note on clean cooking fuel access: The official government stance is that over 99 percent of the households in India have access to LPG cylinders under the Ujjwala scheme. Yet, as the data above shows, less than 60 percent of the households in the country may be actively using it. This discrepancy reveals that many families may be availing the LPG connection that the government provides, but may be unable to pay for the cylinder refills.
Nonetheless, the survey results clearly show more people have access to these amenities in 2021 than they did in 2014-15. This reflects well on the Modi government. But a better way to judge the progress made in the NDA years would be to compare it with the pace of improvements under the UPA years. As mentioned earlier, the timelines of NFHS-3, NFHS-4 and NFHS-5 allow for such a neat bifurcation of data.
Figure 2 shows this comparison. An important thing to note here is that the change of measure shown in the figure is normalised to a per-year basis to allow for proper comparisons. To illustrate, if a measure improved by 20 percent between NFHS-3 (2004-05) and NFHS-4 (2014-15), its normalised annual change would be two percent (20/10). This method of normalising metrics to a per-year change is used throughout this piece, when comparing changes between 2004-05 to 2015-16 (UPA years) with those between 2015-16 to 2019-21 (NDA years).
The chart above shows that significant improvements have been made since 2014-15 when it comes to access to clean cooking fuel, access to drinking water, and access to sanitation. Specifically, each year (on an average), over four percent of the population got access to sanitation which it did not have previously during the NDA regime. The corresponding figure during the UPA years was a shade under two percent. This data shows that the Swachh Bharat and Ujjwala initiatives under Modi have translated to gains on the ground. For this, the Modi government deserves credit as there are massive knock-on benefits of improvements in these three critical indicators.
For electrification and access to life insurance, the rate of improvement is almost the same. Electrification seems to have become a bit slower in the NDA period, but that is likely due to the fact that over 99 percent of the country has access to electricity, not leaving that much room for growth. Of course, the survey only asks for electricity supply, not uninterrupted electricity supply. So, there is plenty of room of improvement in electricity supply, just not in the way it is measured in the survey.
Next, let us look at how things have progressed on the nutrition front, starting with children.
Figure 3 shows the trend over the last three surveys for five key indicators of child nutrition.
(a) Under-5 mortality rate: The number of kids (per 1,000) that die before turning five.
(b) Infant mortality rate : The number of kids (per 1,000) that die before turning one.
(c) Stunting: The percentage of children that have low height for age. This is indicative of chronic or recurrent undernutrition.
(d) Wasting: The percentage of children that have low weight for height. This is indicative of acute or recent undernutrition.
(e) Anaemia: The percentage of children that are anemic. Anaemia is a condition in which a person lacks enough healthy red blood cells to carry adequate oxygen to the body. Having anaemia, also referred to as low hemoglobin, can make one feel tired and weak. The most common causes of anaemia include nutritional deficiencies, particularly iron.
The absolute numbers show marginal improvements on all metrics except anaemia. A whopping 67.1 percent of all children are anaemic in the latest survey, compared to 58.6 percent in NFHS-4. Note that blood tests are conducted as part of the survey to determine these numbers.
Even for the other metrics that have improved in absolute terms, the numbers are still abysmal with one in three children being stunted and one in five being wasted.
Figure 4 charts the deltas for all five indicators between the UPA and NDA years.
The figure above shows that the pace of improvements for mortality rates and stunting actually slowed down in the period after 2014-15, albeit not dramatically. Wasting showed a slight improvement, especially since it had become worse during the UPA years (as seen by the small negative number). As discussed earlier, the change in childhood anaemia numbers actually turned negative in the NDA years. Overall, the chart above suggests that despite the dire need, our progress in ameliorating childhood malnutrition has slowed down.
So, are we faring better at feeding our adult population?
Figure 5 shows data for adult nutritional indicators: low body mass index (BMI) and anaemia. The numbers shown for each category are the percent of men/women with low BMI and anaemia.
Outcomes of adult nutrition are mixed. The percentage of the population with low BMI, which can be thought of as a proxy for undernutrition in adults, has decreased over time. But more men and women were found to be anaemic in NFHS-5 compared to NFHS-4. Given that instances of anaemia have also risen in children in this period, efforts to understand underlying causes are warranted.
Figure 6 compares the changes to adult nutrition indicators between the UPA and NDA years.
Anaemia, as we know, actually got worse in the NDA years. The portion of the adult population with low BMI reduced during both timeframes (as shown by the negative values in the chart), but the pace of progress on this front slowed down during the NDA years.
Maternal health and child vaccinations
Next, let’s look at some select health parameters: healthcare available during pregnancy, and child vaccinations. The metrics listed here are only a fraction of the ones collected by the NFHS surveys to assess maternal care and child vaccinations, but representative of the overall trends.
Figure 7 shows data for two indicators of maternal healthcare: number of institutional births and number of women who were able to see a doctor at least four times during their pregnancy. It also includes the number of children (under the age of two) who were vaccinated. For all three parameters, things have improved with each successive survey.
There was a huge spike in access to health institutions for child delivery between NFHS-3 and NFHS-4. For the other two parameters, the pace of improvements were mostly steady, with a slight uptick in the rate of childhood vaccination during the NDA years. These trends can be seen in Figure 8 which compares the normalised yearly change between the UPA and NDA years.
Finally, let’s look at indicators that assess basic education: basic literacy for men and women, and any school attendance for women. It should be noted that this data does not convey school attendance rates or educational outcomes. Hence, it should not be confused with an indicator of education quality. Instead, it represents basic literacy – also an essential facet of human development, but different from education per se.
Figure 9 shows the trend over the last three surveys. While the absolute levels of basic literacy for men are higher (84.4 percent) than those for women (71.4 percent), literacy in men has dropped marginally since the last survey. For women, the number of women who are literate and the number that have ever attended school both show a consistent upward trend.
That said, the growth in both those metrics – literacy and any school attendance – has slowed down during the NDA years. This can be seen in Figure 10 below that shows the comparative numbers. For men, even the absolute literacy numbers have declined a bit, as seen by the negative value in the chart below.
Overall, the data on literacy suggests that the basic education has suffered during the NDA years compared to the UPA years.
So, what inferences can be drawn from the data presented in this article, beyond the domain-specific statistical trends?
It can be argued that this data reveals a strategic shift in the conceptualisation and delivery of public welfare under prime minister Narendra Modi. There is an emphasis and marked improvement in the delivery of tangible goods and amenities such as LPG cylinders, water connections, and vaccinations. These improvements have undeniably impacted a large section of the population in a positive way, and the government deserves credit for this.
At the same time, progress in the less tangible domains of education, healthcare and nutrition – determinants of both sustainable empowerment at the individual level and the quality of human capital at the systemic level – has either reversed or slowed down. Arvind Subramaniam and his colleague make a similar point, labeling this strategic shift as “new welfarism”.
It is impossible to say with certainty whether this hypothesised shift in welfare delivery is part of a grand plan informed by electoral calculus, a reflection of PM Modi’s worldview, an indication of the enormity of the challenge, or merely an artifact of the strengths and weaknesses of the current dispensation. After all, improvements in healthcare, nutrition and literacy at scale need a different type of capacity building than delivery of one-shot services such as LPG cylinders, toilets or even vaccinations.
What is beyond debate though is that the data from NFHS-5 provides rich insights into the ground reality of the general population and the efficacy of various government initiatives. One can only hope that policymakers are paying careful attention.
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