February 28, 2021
Behavioral disinhibition is a trait associated with both ADHD and several genes that affect dopamine signaling. Anew study by three American medical researchers set out to examine how threaded risk genes – DRD4 (dopamine 4 receptor density), DAT1 (dopamine 1transporter), and DBH (dopamine beta-hydroxylase) – affect estimated life expectancy in young adulthood.
The method used was a longitudinal study of 131 hyperactive children and 71 matched controls through early adulthood. The original evaluations were done in 1979-1980, when both groups were children in the 4 to 12 age range. They were reevaluated in1987-1988 as adolescents aged 12 to 20. The next follow-up was in 1992-1996 in early adulthood, aged 19 to 25. The final follow-up was in 1998-2004, as adults aged 24 to 32. All agreed to physical examinations that formed the basis for calculating estimated life expectancy using actuarial tables that factor in the effects of smoking, body mass index, alcohol, and other risk factors on expected longevity. Participants also provided blood samples that enabled gene typing.
For the DAT1gene, participants who had the homozygous nine-repeat allele (9/9) had an a five-year reduction in estimated life expectancy relative to those with the ten-repeat allele (10/10). Those with the intermediate (9/10) configuration had a three-year reduction in estimated life expectancy.
For the DBHTaq1 gene, those with a heterozygous (A1/A2) combination had almost a three-year reduction in estimated life expectancy relative to those with homozygous (A1/A1 or A2/A2) configurations.
For DRD4, on the other hand, no significant differences were found for estimated life expectancy.
In a related study, several background traits were found to be significantly predictive of variance in estimated life expectancy. The largest of these was behavioral disinhibition, followed by verbal IQ, self-rated hostility, and a nonverbal fluency test. But no significant differences were found between any of the gene polymorphisms on any of these four measures, indicating that the present gene associations were independent of the background traits.
The researchers next sought to determine which variables used in the estimated life expectancy calculations were associated with the two significant genes. For DBH, one variable stood out. Those with the A1/A2 heterozygous pairings had almost twice the alcohol consumption of those with homozygous pairings (p = 0.023).
For DAT1, two variables stood out. Overall, the 9/9 pairings smoked two and a half times as much as the 10/10 pairings, with the 9/10 pairings midway between the extremes(p = 0.036). They were also 73 percent more likely to be smokers relative to the 10/10 pairings, and 61 percent more likely relative to the 9/10 pairings. They also had significantly less education than the 10/10 pairings, with the 9/10pairings again being intermediate (p = 0.027).
An obvious limitation of the study was its small sample size. The authors cautioned, “our findings should be considered quite preliminary and in need of much greater research before being given much weight in the literature or in public policy.
“With these limitations in mind,” they concluded, “the present study demonstrated that two ADHD risk genes (DBH and DAT1) independently contributed to a reduction in ELE [estimated life expectancy] beyond the second order variables of behavioral disinhibition, IQ, hostility, and nonverbal fluency that contributed in the related study to variation in ELE. The gene polymorphisms seemed to be influencing ELE through their affiliation with first-order or more proximal factors related to ELE such as education, smoking, alcohol use, and possibly exercise.”
Russell A. Barkley, Karen Müller Smith, and MariellenFischer, “ADHD risk genes involved in dopamine signaling and metabolism are associated with reduced estimated life expectancy at young adult follow-up hyperactive and control children,” American Journal of Medical Genetics (2019), DOI: 10.1002/ajmg.b.32711.
Background:
Noting that “Previous research has demonstrated that attention significantly influences various domains such as language, literacy, and mathematics, making it a crucial determinant of academic achievement,” an international study team performed a comprehensive search of the peer-reviewed medical literature for studies evaluating effects of physical activity on attention.
The Study:
The team’s meta-analysis of ten studies with a combined total of 474 participants found moderate reductions in attention problems following physical activity. They found no significant evidence of publication bias, but there was considerable variation in outcomes between studies (heterogeneity).
To tease out the reasons for this variability, the team looked at specific attributes of the physical activity regimens used in the studies.
The seven studies with 168 participants that involved mentally engaging physical activity reported large reductions in attention problems, whereas the three studies with 306 persons that used aerobic exercise found no reduction whatsoever. Heterogeneity in the former was reduced, in the latter all but disappearing.
Comparing studies with other interventions as control groups (6 studies, 393 participants) with those with no intervention as control (4 studies, 81 participants), the former reported only small improvements in attention problems, while the latter reported large improvements.
Duration of physical activity made little difference. The four studies with physical activity of an hour or more reported better outcomes than the six with less than an hour, but the difference was not significant.
Greater frequency did make a difference, but in a counterintuitive way. The seven studies with one or two physical activity interventions per week (162 participants) reported large reductions in attention problems, whereas the three studies with three or more interventions per week (312 participants) showed no improvement.
Conclusion:
The authors concluded, “Our study suggests that cognitively engaging exercise is more effective in improving attention problems in school-aged children with ADHD.” Moreover, “the benefits of improved attention in school-age children with ADHD are not necessarily positively correlated with higher frequency and longer duration of physical activity.” Also keep in mind that exercise, while important for all children, should not replace medical and psychological treatments for the disorder.
The National Health Interview Survey (NHIS) is conducted annually by the National Center for Health Statistics at the Centers for Disease Control and Prevention. The NHIS is done primarily through face-to-face computer-assisted interviews in the homes of respondents. But telephone interviews are substituted on request, or where travel distances make in-home visits impractical.
For each interviewed family, only one sample child is randomly selected by a computer program.
The total number of households with a child or adolescent aged 3-17 for the years 2018 through 2021 was 26,422.
Based on responses from family members, 9.5% of the children and adolescents randomly surveyed throughout the United States had ADHD.
This proportion varied significantly based on age, rising from 1.5% for ages 3-5 to 9.6% for ages 6-11 and to 13.4% for ages 12-17.
There was an almost two-to-one gap between the 12.4% prevalence among males and the 6.6% prevalence among females.
There was significant variation by race/ethnicity. While rates among non-Hispanic whites (11.1%) and non-Hispanic blacks (10.5%) did not differ significantly, these two groups differed significantly from Hispanics (7.2%) and Others (6.6%).
There were no significant variations in ADHD prevalence based on highest education level of family members.
But family income had a significant relationship with ADHD prevalence, especially at lower incomes. For family incomes under the poverty line, the prevalence was 12.7%. That dropped to 10.3% for family incomes above the poverty level but less than twice that level. For all others it dropped further to about 8.5%. Although that might seem like poverty causes ADHD, we cannot draw that conclusion. Other data indicate that adults with ADHD have lower incomes. That would lead to more ADHD in kids from lower income families.
There was also significant geographic variation in reported prevalence rates. It was highest in the South, at 11.3%, then the Midwest at 10%, the Northeast at 9.1%, with a jump down to 6.9% in the West.
Overall ADHD prevalence did not vary significantly by year over the four years covered by this study.
This study highlights a consistently high prevalence of developmental disabilities among U.S. children and adolescents, with notable increases in other developmental delays and co-occurring learning and intellectual disabilities from 2018 to 2021. While the overall prevalence remained stable, these findings emphasize the need for continued research into potential risk factors and targeted interventions to address developmental challenges in youth.
It is also important to note that this study assessed the prevalence of ADHD being diagnosed by healthcare professionals. Due to variations in healthcare accessibility across the country, the true prevalence of ADHD may differ still.
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Background:
An international research team used the nationally representative 2020–2021 U.S. Survey of Children’s Health to explore associations between ADHD, weeknight sleep insufficiency, and bedtime irregularity.
"Sleep sufficiency" refers to the recommended amount of sleep for an individual. Sleep recommendations vary by age and other factors, such as health and lifestyle. For example, 7-9 hours is typically considered sufficient sleep for most adults, but an active teen may require closer to 10 hours of sleep per day.
Previous studies have shown that issues with both falling and staying asleep are common in individuals with ADHD.
The Study:
The team matched 7,671 children and adolescents with ADHD aged 3-17 to 51,572 controls.
Noting that “The few available population-based studies examining sleep in children with ADHD have focused on circumscribed age ranges, limiting generalizability across childhood, and have seldom included controls,” and “bedtime irregularity has received limited empirical attention in children with ADHD,” this study focused on these aspects of sleep impairment.
The study group excluded children and adolescents with ADHD with Down syndrome, current or lifetime cerebral palsy, and current or lifetime intellectual disability. In the control group, it excluded individuals with Down syndrome, cerebral palsy, intellectual disability, speech and language disorder, autism spectrum disorder, ADHD, anxiety, depression, behavioral or conduct problems, Tourette syndrome, and use of mental health services in the preceding 12 months. These groups were excluded to limit potential confounding factors.
After adjustment for covariates, parents of children and adolescents with ADHD reported weekday sleep insufficiency 65% more frequently than parents of controls.
However, when comparing matched controls with children and adolescents with ADHD who were being treated with ADHD medication, there was no significant difference.
Similarly, there was a small but significant effect size increase in bedtime irregularity among children and adolescents with ADHD relative to their matched controls.
Yet there was also a small but significant effect size decrease in bedtime irregularity among those taking medication for ADHD relative to those who were unmedicated.
The team noted, “Interestingly, here, ADHD medication use was linked to less bedtime irregularity across full and age-stratified samples, and not related to sleep insufficiency. However, research indicates the association between stimulant use and sleep problems is attenuated with longer duration of use, and also suggests the potential for stimulants to produce positive effects on sleep through reduced bedtime resistance. Further, ADHD medication type, not specified, may have influenced outcomes.”
The Take-Away:
The study concluded that ADHD in children was linked to insufficient sleep and irregular bedtimes in a nationally representative sample, reinforcing and expanding previous research. The findings emphasize the influence of various factors on sleep insufficiency and bedtime irregularity, including race, screen time, poverty, ADHD severity, and depression.
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