Brain connectivity is linked to better health outcomes in youth living in violent neighborhoods
Growing up in a neighborhood prone to violence puts the health of the community at risk, yet not all youth suffer these consequences. Researchers funded by NHLBI, NIDA, NIDCD, and NIMH found youth with greater brain connectivity patterns related to resilience escaped the negative health effects.
Researchers recruited 218 adolescents (ages 12–14 years) from the Chicago area and assessed them for cardiometabolic risk through a series of tests for blood pressure, adiposity, glucose, and insulin resistance. Resting state functional connectivity of the central executive network (CEN), anterior salience network (aSN), and the default mode network (DMN) was measured using fMRI. Geocoding was used to describe neighborhood exposure to murders over a 5-year span.
In teens with lower CEN connectivity, greater cardiometabolic risk was associated with high-murder-rate neighborhoods. Teens with high resting functional connectivity of the CEN, however, did not show this correlation. No significant effects were found in the aSN and DMN. CEN is activated during self-control, reassessing threatening stimuli, and suppressing unpleasant thoughts. Therefore, teens with higher CEN connectivity may be more resilient to violent exposure and its subsequent negative health effects.
Efforts to strengthen connectivity of this region through training tasks in at-risk teens may improve self-control and reduce negative reactions to stressful living environments.
Citation:
Miller GE, Chen E, Armstrong CC, Carroll AL, Ozturk S, Rydland KJ, Brody GH, Parrish TB, Nusslock R. 2018. Functional connectivity in central executive network protects youth against cardiometabolic risks linked with neighborhood violence. Proc Natl Acad Sci. 115(47):12063-8.
More young people are using marijuana before cigarettes and alcohol
A recent report funded by NICHD and NIDA indicates young people are increasingly using marijuana before cigarettes and alcohol.
Using data from the U.S. National Survey on Drug Use and Health, initiation of substance use among youth aged 12–21 years (n = 275,559) between 2004–2014 was analyzed. First, initiation of marijuana use was examined by sex, age, race, and ethnicity. Next, drug-related outcomes were measured by examining if using marijuana prior to other substances led to substance use disorders, such as cannabis use disorder (CUD), alcohol use disorder (AUD), and nicotine dependence (ND).
Overall, there were slight increases in age of first substance use across marijuana, tobacco, alcohol, and other drugs. Researchers found the proportion who first reported using marijuana before other substances increased from 4.8 percent in 2004 to 8 percent in 2014. Conversely, those who first started smoking cigarettes decreased during this time as well from 21 percent to 9 percent. Demographics suggest older, black, American Indian/Alaskan Native, multiracial, and Hispanic men were more likely to use marijuana first, opposed to white or Asian men. Results indicate using marijuana first may lead to higher odds of heavy marijuana use and CUD.
Identifying trends of marijuana use suggests novel targets for prevention and intervention measures, particularly targeted to specific populations.
Citation:
Fairman BJ, Furr-Holden CD, Johnson RM. 2018. When Marijuana Is Used before Cigarettes or Alcohol: Demographic Predictors and Associations with Heavy Use, Cannabis Use Disorder, and Other Drug-related Outcomes. Prev Sci. doi: 10.1007/s11121-018-0908-3. Epub ahead of print.
Computer-detected postural changes in children with autism
Although not a core symptom, differences in motor function are early indicators of autism spectrum disorder (ASD). Researchers funded by NICHD recently used computer vision analysis to detect differences in postural changes, an aspect of motor function, during periods of directed attention to short movies in toddlers with and without ASD.
Participants were 104 children (aged 16–31 months), including 22 with a previous ASD diagnosis. To evaluate subtle midline head movements that are related to postural stability, researchers showed the children a series of movies that included social and nonsocial stimuli. Computer vision analysis (CVA) was used to track head movements and objectively quantify spontaneous head movements in children with and without ASD.
For four out of five of the movies, there were significant differences in head movement between ASD and non-ASD individuals. The rate ratio was higher for movies with more animated and complex stimuli; the rate of head movement in participants with ASD ranged from 1.53 times to 2.45 times that of non-ASD children. These results suggest postural control, an aspect of early motor development, may be an important feature of ASD. Using CVA provides an objective, quantifiable measure to identify subtle differences in postural control during directed attention in children with and without ASD.
Citation:
Dawson G, Campbell K, Hashemi J, Lippmann SJ, Smith V, Carpenter K, Egger H, Espinosa S, Vermeer S, Baker J, Sapiro G. 2018. Atypical postural control can be detected via computer vision analysis in toddlers with autism spectrum disorder. Sci Rep. 8(1):17008.
