Iodine Deficiency Disorder (IDD) is widely recognized as major global health challenge. IDD is reported to be the world’s leading cause of preventable mental retardation and impaired psychomotor development in young children. Even a moderate deficiency, especially in pregnant women and infants, lowers child intelligence by 10 to 15 IQ points, with incalculable damage to social and economic development of nations and communities. Severe iodine deficiencies cause cretinism, and increase the likelihood of stillbirth and miscarriage among pregnant women. Iodine deficiency is most commonly and visibly associated with goiter.

Universal consumption of adequately iodized salt has been widely promoted as a cost-effective vital link in the global response to combating the numerous IDDs. Through a global partnership of many interested stakeholders, various countries have promulgated or revised national regulations to mandate that all salt meant for human and animal consumption is adequately iodized. Accordingly, a growing number of surveys collect and report on the use of adequately iodized salt among populations in order to track progress. Other surveys directly measure urinary iodine concentration (UIC), especially among children of school going age.

Despite the established fact that the burden (effect/impact) of iodine deficiency disorders are not uniformly spread across age-sex groups, the contemporary approach to computing the indicator of iodine consumption among populations does not explicitly take into the account age-sex composition of populations. In this paper, I propose an alternative computational approach which requires no more data than is routinely collected in the standard household surveys used in computing the current indicator. The proposed indicator adjusts for age-sex compositional differences among households using nutritional recommendations and derived deficiency impact multipliers. I compare properties of this proposed indicator to that of the existing one, and highlight some of the critical policy differences that result from motivating the computation of the indicator from these two different perspectives. Data from various rounds of the Multiple Indicator Cluster Survey (MICS) conducted in two developing countries in Africa by UNICEF are used in the computations and comparisons.

I argue that explicitly accounting for age-sex compositional differences in population sub-groups leads to a more reliable indicator in terms of measuring the intensity and exposure to the risk of IDD. I further demonstrate that this new indicator provides for a more robust basis for efficient targeting of interventions aimed at addressing the iodine deficiency gap.