needed to make an strong causal statements or the evidence that is available is simply not
compelling. For example, evidence of Vitamin A deficiency is scant, and Walker et al (2007)
argue that this can be ignored as a priority since there is little evidence to suggest that vitamin
A supplements would have a large impact on the development outcomes for young children.
By way of contrast, zinc deficiencies are estimated to affect one third of the worlds population,
yet the evidence of the role of zinc in child development is unclear. Importantly,zinc supple-
mentation may produce negative outcomes if provided to children who are not lacking zinc to
begin with, since it affects the balance of other micronutrients. However, that being said, zinc
supplementation has been associated with better motor development and behaviour amongst
children in a Bangladesh study (Stoltzfus et al, 2001) but no such effect was found in India or
Indonesia (Grantham-McGregor et al 2007).
Iodine forms part of thyroid hormones and as such, is crucial for the functioning of the central
nervous system. It also aids in regulating physiological processes, and deficiency can lead to
mental retardation. Despite a worldwide campaign to combat iodine deficiency through salt
iodisation, this deficiency is still considered a risk factor. A 1994 meta-analysis of 18 studies of
children and adolescents concluded that IQ scores were 13.5 points lower amongst children with
iodine deficiency (Walker et al, 2007). Another meta-analysis in 2005 (based on publications
in Chinese journals) showed that IQ scores were 12.5 points lower for children living in iodine-
deficient areas, and who had lived there during their childhood years. Moreover, children who
received iodine supplementation both pre- and post-natally had IQ scores that were 8.7 points
higher on average than children who did not receive such supplementation (Walker et al, 2007).
Finally, a longitudinal study in China suggests that iodine supplementation during the first and
second trimesters of pregnancy may be more effective than supplementation during the third
trimester, or during infancy.
There have been other studies of potential direct effects of health interventions aimed at
improving water, sanitation and infrastructure. While the number of randomized controlled
trials are increasing, there still only remains a limited number that examine longer term or eco-
nomic effects. Access to clean water and proper sanitation reduces the risk of diarrhoeal disease
for young children. Diarrhoea is especially prevalent during the first 2 years of life, making it
an important risk factor, although Walker et al (2007) argue that there is no proper evidence
concerning the link between diarrhoeal disease and child development per se. While two small-
scale studies in Brazil suggest there is an association between the incidence of diarrhoea in the
first two years of life and cognitive outcomes, a larger cohort study in Peru that controls for
other covariates does not find any such association (Berkman et al, 2002; Guerrant et al, 1999;
Niehaus et al, 2002). The lack of evidence in this regard does not mean that no link exists,
simply that there is insufficient documented evidence to be persuasive that an intervention on
this front yields substantial developmental benefits.
8 Conclusions
Randomization is often viewed as the ideal method to deal with the problem of selection bias.
When appropriate to the policy context, the results of randomized evaluations are relatively
easy to communicate because they generally do not require substantial qualifying assumptions.
An added advantage is the transparency associated with choosing a control group ex-ante.
However, these advantages of randomization justify its use to the exclusion of other methods
only when interventions are of such a nature that they affect an entire population. In the case of
a health intervention, if participation is rendered mandatory and the intervention is rolled out
randomly across districts, then randomization at the district level will yield population-wide
average treatment effects that are unconfounded by selection bias.
However since participation in health interventions is most often voluntary, randomization
alone is usually insufficient. Under this more realistic scenario more explicit modeling exercises
are required to identify treatment effects. Propensity score matching has been shown to be quite
effective when coupled with less-than-perfect experimental designs. Heckman and Smith (1996)
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