Research Article: Is Economic Growth Associated with Reduction in Child Undernutrition in India?

Date Published: March 8, 2011

Publisher: Public Library of Science

Author(s): Malavika A. Subramanyam, Ichiro Kawachi, Lisa F. Berkman, S. V. Subramanian, Peter Byass

Abstract: An analysis of cross-sectional data from repeated household surveys in India,
combined with data on economic growth, fails to find strong evidence that recent
economic growth in India is associated with a reduction in child
undernutrition.

Partial Text: Macro-economic growth is considered a major, and often the only, policy instrument to
improving health and nutrition in developing countries [1]–[3]. The
premise is that economic growth will improve incomes, especially among the poor, and
increase their access to and consumption of health-promoting goods and services,
leading to improved nutritional status. This argument has also been made in the
context of reducing undernutrition in developing countries (Figure 1) [4]. One can postulate
three non-exclusive pathways through which economic growth could improve nutritional
status among children. These include (i) an increase in income for all, (ii)
reduction in poverty, and (iii) investment in public programs, such as the
Integrated Child Development Services Scheme, which directly or indirectly could
lead to improvement in children’s nutritional status [3],[5]. The distinction between
pathways related to “reduction in poverty” and
“increases in income for all” is important as it emphasizes the
importance of income increases among the poor. One might, for instance, expect the
effect of income on nutrition to be considerably stronger among those with low
incomes, as opposed to income increases at the higher end of the distribution, where
further increases might not result in proportionally higher nutritional dividends.
While the first two pathways rely on behavioral change at the individual or
household level as a result of improved economic standard of living, the third
underscores the role of public investment facilitated either by greater economic
growth and potential increases in revenue or independent of it [6],[7]. The success of such a
“growth-mediated” strategy to reducing undernutrition is,
however, neither automatic nor necessary [8]–[10].
For instance, factors such as education of women and household size have been shown
to have a greater influence on the nutrition of a household than macro-economic
growth translated to improvements in income leading to improvements in nutritional
outcomes [11],[12]. Further, there is a body of research arguing
that it is healthier populations, for example with healthy nutritional indicators,
that are a pre-requisite for increased economic growth and improved standard of
living [13],[14].

The distribution of covariates did not differ in any substantial manner between
children with and without missing data on the outcomes. The greatest difference
between records with and without missing data on underweight (Table S2) was
in the distribution of maternal education (p<0.001) in 1998–99, where 65.59% of those missing data had zero years of education versus 52.28% among those without missing data. The distribution of maternal education between those with and without missing data showed the greatest difference for stunting and wasting as well (p<0.001 for both outcomes). While the difference was 67.36% versus 54.61% for stunting (Table S3), it was 66.45% versus 54.81% for wasting (Table S4). There was variation in the proportion of missing data across states, ranging from 4.7% to 41.89% in 1992–93, 3.23% to 37.13% in 1998–99, and 5.7% to 42.28% in 2004–05. However, there was no correlation (substantively and statistically) between the proportion of missing data in a state and its per capita income (Table S5). The proportion of missing data was negatively correlated with state per capita income in 1992–93 and 1998–99; for example, the correlations for stunting were r = −0.37, p = 0.12 in 1992–93, and r = −0.27, p = 0.26 in 1998–99. However, the correlation was positive in 2004–05 (for stunting, r = 0.39, p = 0.10). We found no consistent association between the risk of child undernutrition and state economic growth in India. A unique strength of our study was linking state economic growth to individual risk of undernutrition at the child level, and doing so with three repeated cross-sections of multilevel data. While we are not aware of any study examining this question in India or elsewhere, our findings are similar to those observed, albeit using cross-sectional multilevel data, on nutritional status of adult women in India, wherein no association was observed between state economic growth and risk of being underweight [35]. In one global ecologic study that used data from 63 countries over 26 years to examine a similar research question [3], it was shown that economic growth at the national level was inversely associated with risk of child undernutrition. The study also concluded that economic growth was responsible for about half the reduction in child undernutrition in that time period and that approximately half of this effect of economic growth was through increased food availability and the rest due to improvements in women's education, quality of health environment, and women's status. However, this is not directly comparable to our study primarily because it was an ecological study that did not account for individual-level factors. Among the eight ecological models we fit, we found support for the inverse association between economic growth (or per capita income in some cases) in only three models. It is important to be cautious while interpreting results from ecological studies in which both the outcome and exposure are measured at aggregate level as there is an assumption that the risk of undernutrition is the same for every child within a state/country. Such analyses are unable to measure the inherently multilevel association between economic growth, whether at the country or state level, and individual risk of undernutrition. Our multilevel findings, which are contrary to those reported in the between-country study, underscore the importance of avoiding generalizations from the country-level scale to the state-level, as well as the shortcomings of ecological analyses in examining a multilevel relationship. Source: http://doi.org/10.1371/journal.pmed.1000424

 

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