Compiling existing post-natal iodization studies which use cognitive tests, I find that—outliers aside—the benefit appears to be nearly zero, and so likely it does not help normal healthy adults, particularly in Western adults.

These experiments are typically done on pregnant women, and results suggest that the benefits of iodization diminish throughout the trimesters of a pregnancy. So does iodization benefit normal healthy adults, potentially even ones in relatively iodine-sufficient Western countries?

Iodization is one of the great success stories of public health intervention: iodizing salt costs pennies per ton, but as demonstrated in randomized & natural experiments, prevents goiters, cretinism, and can boost population IQs by a fraction of a standard deviation in the most iodine-deficient populations.

Iodine deficiency is interesting from the ethical standpoint as one of the most cost-effective—yet obscure—public health measures ever devised which deserves a name like nootropics: a few pennies of iodine added to salt eliminates many cases of mental retardation & goiters.

This has led to an observable impact on the IQ of the children of English women ( Bath et al 2013 ), and there is no reason to expect the effect to be confined to them.

Numerous population studies from a variety of countries including China, Hong Kong, Iran, India, Kyrgyzstan and England have reported iodine deficiency in girls of child bearing age 76 , in pregnant 154 , 155 , 156 , 157 , and in pregnant and lactation women 158 , 159 . Some of these studies included regions where salt iodization is practiced, yet a [substantial] proportion of pregnant and lactating women were still deficient 155 , 156 , 157 , 158 , 159 , 160 , 161 . A few examples of recent studies follow…

More worrisome is recent trends in the developed world such as the War on Salt. Un-iodized salt or low-iodide salt like sea salt is ever more popular. Existing iodized table salt often has far less iodide than recommended, or even what the manufacturer claims it has . Iodized salt used in cooking—as opposed to a straight table-side condiment—loses large chunks of its iodine content . Small samples of ordinary people turn in severe or mild iodine deficiency rates of 67% to as much as 73.7% . This is plausible given a steady secular trend of iodine reduction in the US (although one that seems to have paused in the 2000s) . I was unsurprised to read Morse 2012 :

Of course, iodine can be a double-edged sword. Feyrer et al 2008 mentioned a wave of disorders after iodization of salt, as long-deficient thyroids were shocked with adequate levels of iodine, and natural iodine levels can be so high as to begin to inversely correlate with IQ in China.

The original waves of iodization caused large-scale changes in: numbers of people going to school , working at all , their occupation , how they voted , or even how many recruits from a region are accepted to selective flight schools .

Providing iodine capsules to pregnant mothers is an intervention that helps brain development in fetuses. It costs around 51 cents per dose—and leads to kids who stay in school about five months longer because they are cognitively better able to learn.

Supplementation of iodine in salt, water, or oil increases body iodine levels and reduces iodine deficiency disorders ( Wu et al 2002 ). Supplementing, during pregnancy or infancy, can raise average IQs in the worst-off regions by <13 IQ points (close to a full standard deviation); such an increase is of considerable economic value, even in developed countries with iodization programs (see Monahan et al 2015 & appendices for a cost-benefit analysis). In an additional bonus for our post-feminist society, females benefit more from iodization than males . Because salt production is generally so centralized as a bulk commodity extracted from a very few areas, iodization is almost trivial to implement. (Although humans being humans, there are obstacles even to successful iodization programs .)

Given all this, one naturally wonders what the effect might be in older humans: elementary school age and above. If iodine before birth can be responsible for increasing IQ by a full standard deviation or more in combination with iron, what about iodine post-birth? Iron supplementation treats anemia and there is evidence it also treats the cognitive problems as well, so what about iodine?

Liu et al 2009, and tangential results like Bongers-Schokking et al 2005 (where there was a discernible IQ difference between TSH treatment of infants with congenital hypothyroidism before & after 13 days post-birth) suggest that the window for iodine intervention may close rapidly during pregnancy and be closed post-birth. While iodine has been extensively studied in infants and other unusual populations, the narrow question of iodine’s effect on IQ in healthy adult First World populations has not been (a common problem in nootropics); we are interested in cases only where someone is mentally tested before and after iodine supplementation, or where 1 cohort receives supplementation after birth when compared against a similar cohort who receive no supplementation. Most studies turn out to be either correlational (eg. stratifying by blood levels of thyroid hormone) or comparing fetal supplementation against a non-supplemented control group. Unfortunately, no study is so large and high-quality that it definitively resolves our question. So we resort to meta-analysis of what is available: we pool many studies together to derive a summary average of the overall results, weighted by how many subjects each study had (since more is better) versus how strong a result they yielded. An example of this is the meta-analysis & review, which is the closest existing study to what I want, “Iodine and Mental Development of Children 5 Years Old and Under”:

Several reviews and meta-analyses have examined the effects of iodine on mental development. None focused on young children, so they were incomplete in summarizing the effects on this important age group. The current systematic review therefore examined the relationship between iodine and mental development of children 5 years old and under. A systematic review of articles using MEDLINE (1980-November 2011) was carried out. We organized studies according to four designs: (1) randomized controlled trial with iodine supplementation of mothers; (2) non-randomized trial with iodine supplementation of mothers and/or infants; (3) prospective cohort study stratified by pregnant women’s iodine status; (4) prospective cohort study stratified by newborn iodine status. Average effect sizes for these four designs were 0.68 (2 RCT studies), 0.46 (8 non-RCT studies), 0.52 (9 cohort stratified by mothers’ iodine status), and 0.54 (4 cohort stratified by infants’ iodine status). This translates into 6.9 to 10.2 IQ points lower in iodine deficient children compared with iodine replete children. Thus, regardless of study design, iodine deficiency had a substantial impact on mental development. Methodological concerns included weak study designs, the omission of important confounders, small sample sizes, the lack of cluster analyses, and the lack of separate analyses of verbal and non-verbal subtests. Quantifying more precisely the contribution of iodine deficiency to delayed mental development in young children requires more well-designed randomized controlled trials, including ones on the role of iodized salt.

But its second design conflates supplementation of mothers with that of infants & children, and so the d=0.46 (figure 2) is not directly meaningful (the authors note that the studies are heterogeneous but do not attempt stratifying by fetal vs infancy). More relevant is “Effect of iodine supplementation in pregnancy on child development and other clinical outcomes: a systematic review of randomized controlled trials”, Zhou et al 2013:

…Fourteen publications that involved 8 trials met the inclusion criteria. Only 2 included trials reported the growth and development of children and clinical outcomes. Iodine supplementation during pregnancy or the periconceptional period in regions of severe iodine deficiency reduced risk of cretinism, but there were no improvements in childhood intelligence, gross development, growth, or pregnancy outcomes, although there was an improvement in some motor functions. None of the remaining 6 RCTs conducted in regions of mild to moderate iodine deficiency reported childhood development or growth or pregnancy outcomes. Effects of iodine supplementation on the thyroid function of mothers and their children were inconsistent.

They correctly observe that the available studies are not very methodologically rigorous and most do not allow of any real analysis, but I think it may be worth doing a more permissive summary and see what it says. Taylor et al 2014’s “Impact of iodine supplementation in mild-to-moderate iodine deficiency: systematic review and meta-analysis” looks at Gordon & Zimmerman, combining the available tests and finding:

For the meta-analysis cognitive tests were categorised into the following domains: (i) perceptual reasoning; (ii) processing speed; (iii) working memory; and (iv) global cognitive index. The global cognitive index was derived from the average of the scores in each of the domains. Unadjusted SMDs of the change in cognitive scores from baseline were computed from the raw scores reported by the authors, while adjusted SMDs were derived from the reported mean-adjusted treatment effects. s.e.m.-adjusted treatment effects were calculated using the recommended formula in the Cochrane handbook (44). The results of the analysis for individual domains are presented in Table 3, while Fig. 3 shows the forest plots for the global cognitive index. Beneficial effects of iodine supplementation were seen for both adjusted and unadjusted global indices with mild heterogeneity observed between the studies. For individual unadjusted domain scores, benefits were seen for processing speed but not for perceptual reasoning or working memory, while for the adjusted domains iodine was beneficial for perceptual reasoning although this was associated with significant heterogeneity.

Data First, the data from the surviving studies: study group year n.e mean.e sd.e n.c mean.c sd.c age dose multi country Bautista Bautista 1982 100 69.43 10.96 100 70.31 10.96 8.75 475 0 Bolivia Boyages Boyages 1990 28 34.4 15.4 24 29.5 8.5 29.5 720 0 China Schoenthaler.1 Schoenthaler 1991 100 10.1 8.9 33.3 8.9 7.3 14 12.68 1 USA Schoenthaler.2 Schoenthaler 1991 105 12.6 7.9 33.3 8.9 7.3 14 25.35 1 USA Schoenthaler.3 Schoenthaler 1991 105 10.4 7.6 33.3 8.9 7.3 14 25.35 1 USA Southon Southon 1994 22 63.94 2.6 29 64.1 1.87 13.5 16.8 1 UK Shrestha.1 Shrestha 1994 72 17.1 1.8 36 10.7 2.4 7.1 490 0 Malawi Shrestha.2 Shrestha 1994 80 18.2 1.5 36 10.7 2.4 7.1 490 0 Malawi Isa Isa 2000 60 85.25 14.6 100 83.6 16.2 11.39 480 0 Malaysia Huda Huda 2001 145 14.88 3.28 142 14.60 3.19 9.8 400 0 Bangladesh Zimmerman Zimmerman 2006 159 25 6.3 151 20.5 5.6 11 400 0 Albania McNeill McNeill 2007 398 11.5 2.3 374 11.7 2.1 72 54.75 1 UK Gordon Gordon 2009 84 10.2 3 82 9.6 2.4 11.5 29.4 0 NZ Dewi Dewi 2012 33 110.27 9.04 34 103.06 9.99 3.1 8.4 0 Indonesia Salarkia Salarkia 2004 19 96 10 246 89 13 1.5 1272 0 Iran Untoro Untoro 1999 121 89 7 43 88 6 9 464 0 Indonesia Redman Redman 2011 86 20.85 3.43 86 20.59 3.27 21.28 45 0 NZ Solon Solon 2003 412 1.82 0.22 419 1.66 0.22 9.9 10.752 1 Philippines Comments: “age” variable is based on a simple average age in years of subjects (unweighted) or the reported mean; “dose” is total administered iodine in milligrams (note that studies typically report in micrograms/μg per day or week); multi is whether the study used solely iodine (0) or other chemicals such as iron (1) Bautista notes: Stanford-Binet IQ, some data re-derived Boyages: the two groups were not randomly chosen and may have pre-existing differences in IQ Schoenthaler: RAPM IQ Cao: an earlier version of this meta-analysis used its “developmental quotient” excluding the pregnant women’s offspring; since this does not seem to be IQ, I removed it Southon: Non-verbal IQ scores pooled McNeill: Digit span used in place of IQ scores (WM correlates highly with IQ) Gordon: score from matrix subtest (1 of 4 subtest scores; 2 showed positive trend but not significance) Manger: earlier version used Manger’s backwards digit span (backwards is a WM test which loads on g); however, the meta-analysis Melby-Lervåg & Hulme 2013 & my own n-back meta-analysis found that WM exercises which transferred to digit spans did not also transfer to IQ tests, raising questions about using digit span as a proxy for IQ in a causal rather than correlational analysis Stuijvenberg: see Manger Isa: IQ scores reported in unhelpful format; means & deviations reverse-engineered from percentile distribution ; as usual, pregnancy-related scores are omitted Shrestha: ‘Fluid intelligence’ scores reported, omitting ‘Crystallized intelligence’ & ‘Perceptual skill’; the control group is split across the iodine intervention (“Shrestha.1”) and the iodine+iron intervention (“Shrestha.2”) Salarkia: the paper’s original control group using contemporary age/sex-matched Tehran children, doesn’t account for their superior IQ scores and likely superior SES ; I have instead used the reported 1989 IQ scores of the previous generation of children the administered iodine includes the 480mg from iodized oil but also the 6 years of iodized salt consumption (40mg/kg, national daily per capita average salt consumption 9g) or 132mg a year) for a total of 1272mg Untoro: there were 3 dose groups (200/400/800mg) but Untoro reported summary statistics for the iodine group as a whole: The urinary iodine concentration and thyroid volume of all treatment groups were [statistically-]significantly improved after the supplementation, but there were no differences among the supplemented groups in cognitive performance. Therefore we combined the three iodized oil supplemented groups into one group. The listed dose is a weighted average. Redman: dose is calculated as: 150 μg, 100 pills a bottle, 3 bottles (1 initial bottle, 2 replacements in mail) = 150⋅100⋅3 = 45000μg; scores are from the Matrix Reasoning subtest The result of the meta-analysis: Random - Effects Model ( k = 17 ; tau ^ 2 estimator : REML) tau ^ 2 (estimated amount of total heterogeneity) : 1.2100 ( SE = 0.4432 ) tau (square root of estimated tau ^ 2 value) : 1.1000 I ^ 2 (total heterogeneity / total variability) : 97.87 % H ^ 2 (total variability / sampling variability) : 47.02 Test for Heterogeneity : Q ( df = 16 ) = 285.8785 , p - val < .0001 Model Results : estimate se zval pval ci.lb ci.ub 0.6204 0.2716 2.2844 0.0223 0.0881 1.1527 Test for Heterogeneity : Q ( df = 16 ) = 285.8785 , p - val < .0001 Model Results : estimate se zval pval ci.lb ci.ub 0.2565 0.0380 6.7536 < . 0001 0.1820 0.3309 So the effect size is, as expected, small: d=0.2. A far cry from the d>1 which we might estimate from the prenatal studies. The large difference in d—0.2 vs 0.6—between the fixed-effects and random-effects models is concerning. Given the extremely high heterogeneity of the i2, which indicates that there are large differences between some of the studies, a random-effects is more appropriate in principle; but further analysis shows this is being driven by a far outlier of Shrestha, and so I believe the fixed-effects estimate of 0.2 winds up being more accurate. A pretty forest plot summary: A forest plot of iodine studies

Moderators Age & dose We suspected, based on the equivocal results in post-birth studies and the large decline in effect over the duration of a pregnancy in the Chinese studies, that if there was any benefit, it would be in the young; on the same reasoning, we might expect large doses to do more good than smaller ones. The necessary data is encoded into the table already, so we run a meta-analytic regression on them as independent predictors: tau ^ 2 (estimated amount of residual heterogeneity) : 1.2521 ( SE = 0.4902 ) tau (square root of estimated tau ^ 2 value) : 1.1190 I ^ 2 (residual heterogeneity / unaccounted variability) : 97.49 % H ^ 2 (unaccounted variability / sampling variability) : 39.92 R ^ 2 (amount of heterogeneity accounted for ) : 0.00 % Test for Residual Heterogeneity : QE ( df = 14 ) = 243.6469 , p - val < .0001 Test of Moderators ( coefficient (s) 2 , 3 ) : QM ( df = 2 ) = 1.6083 , p - val = 0.4475 Model Results : estimate se zval pval ci.lb ci.ub intrcpt 0.6793 0.5205 1.3053 0.1918 -0.3407 1.6994 iodine $ age -0.0157 0.0183 -0.8568 0.3915 -0.0515 0.0202 iodine $ dose 0.0006 0.0009 0.6665 0.5051 -0.0011 0.0023 The coefficients and variability are disappointing: the age and dose moderators explain little of what is going on. Some graphs to help us visualize. Graphing by age, we see what might be a slight negative relationship, as the regression suggests (driven by Shrestha 1994): plot(iodine$age, effects$yi) Graphing by dose, we see—despite the calculated significance—no relationship at all to my eyes (outliers are Shrestha 1994, again): plot(iodine$dose, effects$yi) The estimate is the important part: neither of the moderators seem to have a strong relationship with the cognitive benefits (nor are they at least statistically-significant). It would seem that any effectiveness of iodine is unrelated to age and dose. Whether the effectiveness is being driven by a few studies is what we’ll look at next. Multiple supplements One methodological concern is that by including studies like Southon which supplemented many things besides iodine, our results are merely picking up the efficacy of other supplements (iron is a particular concern). Curiously, despite our expectation that the multi-vitamin studies would have higher effect sizes because any of the ingredients could be helpful singly or synergistically, it is strikingly the opposite: QM ( df = 2 ) = 6.7027 , p - val = 0.0350 Model Results : estimate se zval pval ci.lb ci.ub factor (iodine $ multi) 0 0.8250 0.3203 2.5756 0.0100 0.1972 1.4529 factor (iodine $ multi) 1 0.1300 0.4953 0.2625 0.7930 -0.8408 1.1008

Bias checks We do not have enough to reliably check for biases like publication bias, but we can still try. The funnel plot looks pretty bizarre, with almost all studies tightly bunched around the null effect but 2 outliers—the 2 Shrestha 1994 groups we just saw—showing shockingly high effect sizes of d=3.1/4.1. Why did Shrestha 1994 observe such large IQ effects? I don’t know, although the Malawi region was chosen for its iodine deficiency. A test & graph: test for funnel plot asymmetry : z = 3.3206 , p = 0.0009 A funnel plot of effect size versus sample size, checking for bias in publishing only good-looking results on iodine So Shrestha 1994 is driving most of the effect! (Not a surprise at this point.) If we omit those points, the funnel plot is cleaner A funnel plot with Shrestha removed, showing better fit from the weaker estimate. A trim-and-fill check agrees with us and not the test, by deciding not to add in any new studies between Shrestha and the rest; we also notice that the τ2 & i2 are extremely high, which is just telling us what we know—Shrestha 1994 is different from the other studies: Estimated number of missing studies on the left side : 0 ( SE = NA ) Random - Effects Model ( k = 17 ; tau ^ 2 estimator : REML) tau ^ 2 (estimated amount of total heterogeneity) : 1.2100 ( SE = 0.4432 ) tau (square root of estimated tau ^ 2 value) : 1.1000 I ^ 2 (total heterogeneity / total variability) : 97.87 % H ^ 2 (total variability / sampling variability) : 47.02 If we were to redo the analysis but omitting Shrestha 1994, we see a much smaller effect-size: Random - Effects Model ( k = 15 ; tau ^ 2 estimator : REML) tau ^ 2 (estimated amount of total heterogeneity) : 0.0526 ( SE = 0.0313 ) tau (square root of estimated tau ^ 2 value) : 0.2293 I ^ 2 (total heterogeneity / total variability) : 68.75 % H ^ 2 (total variability / sampling variability) : 3.20 Test for Heterogeneity : Q ( df = 14 ) = 53.0253 , p - val < .0001 Model Results : estimate se zval pval ci.lb ci.ub 0.2224 0.0751 2.9602 0.0031 0.0752 0.3697 So, it seems a lot of the effect size is being driven by a few studies turning in large or extremely large effect sizes: Shrestha, Zimmerman, and Dewi (in chronological order). One common factor to these studies seems to be that they worked in the most iodine-deprived areas possible: Shrestha chose his region as being the worst he could find, and Dewi cites reports of goiter in half the population while targeting the supplementation to the most deficient children. At most, we can justify an effect estimate which is much smaller than would be estimated based on the prenatal studies, and the reality of this residual effect can be doubted: looking at the forest plot, the more rigorous and Western studies seem to have the tiniest and closest to zero estimates.