Our comprehensive study found several factors associated with ADHD including some that have not been examined together in conjunction with other variables, especially at the national level. The significant association found between ADHD and DEP, ANX, sex, race, FAMILY, POVERTY, and EDUC is consistent with previous studies on ADHD
]. However, after accounting for the ADHD related factors, obesity was not found to be significant, contrary to some previous studies
]. The variables SMOKE, INS, SPORTS, and TV were found to be associated with ADHD at the national level for the first time in our study. A child with DEP, ANX, TV ≥1 hour, or with someone SMOKE in household had an increased odds of being diagnosed with ADHD. On the other hand, if a child was underweight, non-Hispanic White, living in a two-parent FAMILY, or in SPORTS, he/she had decreased odds of being diagnosed with ADHD.
This study is not without limitations. The NSCH is a random digital dialing telephone survey based on the responses of parent/guardians. So the responses could be affected by recall bias or the given information could be fallacious (such as misreporting of height/weight). In particular, the diagnosis of ADHD was solely dependent on the response given by a parent to a single question [“Has a doctor or health professional ever told you that S.C. has attention deficit disorder or attention deficit hyperactive disorder, that is, ADD or ADHD?”]; this may have resulted in diagnostic misclassification. In other words, as this is not a clinical study, it is unclear how many children who met the ADHD criteria were undiagnosed and/or untreated. Further, the survey question on SMOKE [Does anyone living in the household use cigarettes, cigar, and pipe tobacco?] does not specify whether the child or someone else in the household including parent/guardian was a smoker; results may alter if the smoker in the household was the child him/herself. Also, some bias is expected due to the cross-sectional nature of the study. For example, the survey fails to capture whether the ADHD, DEP, and ANX diagnosis were concurrent or at different time points in the lifetime of the child. Due to these and the observational nature of the study design, the association found in our study cannot be interpreted as causation for ADHD. For example, the association observed between ADHD and the factors SPORTS and CLUBS could be due to the fact that ADHD diagnosed children are just not welcomed on a sport/club teams because of their behavioral problems rather than lack of sporting/physical activity being a risk factor for ADHD. That is, some of the associated factors could be consequences of having ADHD.
The results show that the ADHD diagnosed children were most likely from a household having insurance. It is not known how many of the children from the uninsured households may have met the ADHD criteria but were undiagnosed. We performed a sensitivity analysis by analyzing only the insured 5–17
years old. The results were similar as before (Table
) except for minor changes in significance of few variables: TV and race lost their significance marginally while CLUBS gained significance marginally.
With the inclusion of the medication effect, the significance of the association of ADHD with TV and SPORTS was lost. This suggests that these associations could be due to a behavior related factor that could be monitored. However, the results from the model utilizing medication effect may not be totally reliable due to limitations in the medication variable as collected in the NCSH. First, the survey question does not collect information about past medication use for ADHD because of which a child who was diagnosed with ADHD in the past and hence took medication in the past would be categorized into the ADHD-NCM group. While this group is supposed to include only those children who satisfy the conditions of having ADHD and not taking medication for ADHD concurrently. This limitation is similar in essence to the one elucidated earlier due to the cross-sectional nature of the survey. Secondly, the unweighted sample sizes for ADHD-NCM (1,690) and ADHD-CM (3,735) groups do not add up to the total number of ADHD-diagnosed children (7,137 from Table
) due to missing values for the medication use question. Although our bivariate analysis showed obesity to be significantly associated with ADHD, this was not the case in the multivariate analysis irrespective of whether medication use was considered, contrary to some previous studies
]. Following Waring and Lapane
], who had analyzed the NCSH 2003 data, we fitted a model using the same data and with the following subset of variables: sex, race, DEP, ANX, POVERTY, age, and BMI, and the dependent variable as the trichotomized ADHD with medication classification, and indeed found obesity to be significantly associated in this model. However, with the addition of even one or two of the remaining variables, the significance of this association was lost. Thus, our study shows that obesity per se may not have a direct association with ADHD and hence sheds a new light on this research topic.