special education placement. Special education is a “catch-all” outcome that likely involves a variety of neurocognitive and behavioral dysfunctions, including LDs such as reading difficulties, dyslexia, ADHD, and language/ communication disorders, as well as behavior problems, psychiatric conditions, and per- haps some physical dysfunctions. The broad heterogeneous nature of both special educa- tion and LD as outcome measures prevents inferences about specific learning or cognitive domains. We are not aware of prior epide- miologic studies directly relating cadmium exposure and special education. However, any of the previously mentioned animal or human studies that link cadmium exposure to adverse neurobehavioral/neurocognitive or general health outcomes may be relevant here, because these outcomes could lead to special education placement. There are data supporting the biological plausibility of cadmium exposure as a risk factor for LD and special education place- ment. For example, cadmium can inhibit the calcium flux required for neurotransmitter release (Hirning et al. 1988; Nation et al. 1989) and might thereby disrupt the neural communication required for synaptic network formation during development. Cadmium has also been shown to influence the prolif- eration and differentiation of neuroblasts in culture (Gulisano et al. 2009), and there is evidence that cadmium could indirectly affect the developing brain by disrupting thyroid hormone function (Iijima et al. 2007). ADHD. Our findings for ADHD did not reach statistical significance, but the direc- tion of the association suggests a possible decreased risk of ADHD diagnosis in children with urinary cadmium levels above the 25th percentile. There is only limited information from prior epidemiologic studies on cadmium exposure and ADHD/executive function. Lee et al. (2007) reported a nonsignificant trend of increasing odds of ADHD with increasing blood cadmium levels that was not present after adjustment for persistent organic pol- lutants based on an analysis of 1999–2000 NHANES data. As mentioned above, the dif- ferent exposure metrics may partly explain the difference in our findings, because blood cad- mium is a marker of recent exposure, whereas urine cadmium is a marker of chronic expo- sure (Lauwerys et al. 1994). Cao et al. (2009) reported a nonsignificant trend of increasing problem behavior scores at 7 years of age with increasing blood cadmium levels measured at 2 years of age, but there were no obvious trends with increasing blood cadmium in the attention/executive subdomains, the hyper- activity subdomain, or the ADHD index. The prospective approach is a strength of their study, but their unique population consisted solely of lead-poisoned children (blood lead Environmental Health Perspectives • volume 120 | number 5 | May 2012 Cadmium exposure and neurodevelopmental outcomes levels of 20–44 gμ/dL at enrollment), and the results may not be generalizable to non-lead- poisoned children. Previous animal-based studies have dem- onstrated a variety of seemingly inconsistent effects of cadmium exposure on neurophysiol- ogy and activity levels. These findings include, for example, reduced exploratory activity and decreased time spent moving, but they also include hyperactivity, and evidence of changes in central nervous system dopamine and serotonin metabolism (Ali et al. 1986; Desi et al. 1998; Nation et al. 1989, 1990). These two neurotransmitter systems have been implicated in the etiology of ADHD (Faraone et al. 2005). The varied direction of effects on activity level seen in the animal literature might be related to differences in the timing of cadmium exposure during neurodevelop- ment, the presence of other uncontrolled vari- ables, and/or the specific phenotype measured in each study. We lack detailed information on exposure timing, which makes it diffi- cult to interpret the direction of the ORs for ADHD in the context of the animal litera- ture (Andersen and Navalta 2004). If elevated cadmium exposure decreased activity levels, this may have made ADHD diagnosis less likely. It is also possible that cadmium may cause other neurocognitive dysfunctions that serve as competing risks to ADHD diagno- sis (perhaps children with other diagnostic labels were less likely to receive an ADHD label), and the potential influence of chance should not be overlooked. Because these are cross-sectional data, the temporal relationship Table 2. Urinary cadmium concentration by outcome status.a aValues for the study population, not weighted for oversampling. Table 3. ORs (95% CIs) for neurodevelopmental outcomes by quartile of urinary cadmium concentration. Odds ratio (95% CI) Adjusted for creatinine onlya Outcome LD Yes No Missing/refused/don’t know Special education Yes No Missing/refused/don’t know ADHD Yes No Missing/refused/don’t know Urinary Cadmium (μg/L) LD Quartile 1 (0.0000–0.0576) Quartile 2 (0.0580–0.1097) Quartile 3 (0.1100–0.1800) Quartile 4 (0.1802–14.9400) Special education Quartile 1 (0.0000–0.0576) Quartile 2 (0.0580–0.1097) Quartile 3 (0.1100–0.1800) Quartile 4 (0.1802–14.9400) ADHD Quartile 1 (0.0000–0.0576) Quartile 2 (0.0580–0.1097) Quartile 3 (0.1100–0.1800) Quartile 4 (0.1802–14.9400) n (% total) 276 (12.6) 1,913 (87.0) 10 (0.5) 231 (10.5) 1,965 (89.4) 3 (0.1) 198 (9.0) 1,997 (90.8) 4 (0.2) 1 (reference) 1.06 (0.63, 1.79) 1.56 (0.83, 2.91) 2.44 (1.09, 5.44) 1 (reference) 1.51 (0.85, 2.69) 1.90 (0.77, 4.67) 2.41 (1.12, 5.18) 1 (reference) 0.58 (0.32, 1.04) 0.62 (0.32, 1.23) 0.58 (0.26, 1.31) Median urinary Cd [μg/L (IQR)] 0.130 (0.063–0.213) 0.107 (0.056–0.179) 0.115 (0.070–0.210) 0.130 (0.070–0.215) 0.108 (0.056–0.180) 0.059 (0.000–0.170) 0.100 (0.048–0.167) 0.110 (0.060–0.182) 0.121 (0.033–0.247) Fully adjustedb 1 (reference) 0.98 (0.53, 1.79) 1.72 (0.88, 3.37) 3.21 (1.43, 7.17) 1 (reference) 1.49 (0.80, 2.76) 2.15 (0.78, 5.93) 3.00 (1.12, 8.01) 1 (reference) 0.50 (0.25, 0.98) 0.52 (0.23, 1.19) 0.67 (0.28, 1.61) ADHD 0.84 (0.61, 1.16) 1.11 (0.65, 1.91) 0.73 (0.52, 1.03) 0.91 (0.50, 1.69) 0.79 (0.56, 1.11) 761 aUrinary creatinine included as an independent covariate in the models. bCovariates included in the models: urinary creatinine, age, sex, blood lead, smoker in the home, serum cotinine, prenatal smoke exposure (mother smoked while pregnant), and poverty income ratio. LD model also included education level of household reference person. Special education model also included race/ethnicity, preschool attendance, and education level of household reference per- son. ADHD model also included race/ethnicity, mother’s age at birth, preschool attendance, and insurance coverage. Table 4. Fully adjusted ORs (95% CIs) associated with a one-quartile increase in urinary cadmium concentration. Stratum Study population Below median lead Above median lead Female Male LD 1.51 (1.14, 2.00) 1.67 (1.09, 2.56) 1.39 (0.98, 1.95) 1.24 (0.75, 2.04) 1.75 (1.24, 2.46) Special education 1.44 (1.03, 2.01) 1.74 (0.91, 3.30) 1.29 (0.83, 2.01) 1.31 (0.81, 2.13) 1.73 (1.02, 2.92)