Demographic, Psychological, Behavioral, and Cognitive Correlates of BMI in Youth: Findings from the Adolescent Brain Cognitive Development Study

2019 ◽  
Author(s):  
Joshua Gray ◽  
Natasha Schvey ◽  
Marian Tanofsky-Kraff

Background: Previous research has implicated demographic, psychological, behavioral, and cognitive variables in the onset and maintenance of pediatric overweight/obesity. No adequately-powered study has simultaneously modeled these variables to assess their relative associations with body mass index (BMI; kg/m2) in a nationally representative sample of youth. Methods: Multiple machine learning regression approaches were employed to estimate the relative importance of 43 demographic, psychological, behavioral, and cognitive variables previously associated with BMI in youth to elucidate the associations of both fixed (e.g., demographics) and potentially modifiable (e.g., psychological/behavioral) variables with BMI in a diverse representative sample of youth. The primary analyses consisted of 9-10 year olds divided into a training (n = 2724) and test (n = 1123) sets. Secondary analyses were conducted by sex, ethnicity, and race.Results: The full sample model captured 12% of the variance in both the training and test sets, suggesting good generalizability. Stimulant medications and demographic factors were most strongly associated with BMI. Lower attention problems and matrix reasoning (i.e., nonverbal abstract problem solving and inductive reasoning) and higher social problems and screen time were robust positive correlates in the primary analyses and in analyses separated by sex. Conclusions: Beyond demographics and stimulant use, this study highlights abstract reasoning as an important cognitive variable and reaffirms social problems and screen time as significant correlates of BMI and as modifiable therapeutic targets. Prospective data are needed to understand the predictive power of these variables for BMI gain.

2019 ◽  
Vol 50 (9) ◽  
pp. 1539-1547 ◽  
Author(s):  
Joshua C. Gray ◽  
Natasha A. Schvey ◽  
Marian Tanofsky-Kraff

AbstractBackgroundPrevious research has implicated demographic, psychological, behavioral, and cognitive variables in the onset and maintenance of pediatric overweight/obesity. No adequately-powered study has simultaneously modeled these variables to assess their relative associations with body mass index (BMI; kg/m2) in a nationally representative sample of youth.MethodsMultiple machine learning regression approaches were employed to estimate the relative importance of 43 demographic, psychological, behavioral, and cognitive variables previously associated with BMI in youth to elucidate the associations of both fixed (e.g. demographics) and potentially modifiable (e.g. psychological/behavioral) variables with BMI in a diverse representative sample of youth. The primary analyses consisted of 9–10 year olds divided into a training (n = 2724) and test (n = 1123) sets. Secondary analyses were conducted by sex, ethnicity, and race.ResultsThe full sample model captured 12% of the variance in both the training and test sets, suggesting good generalizability. Stimulant medications and demographic factors were most strongly associated with BMI. Lower attention problems and matrix reasoning (i.e. nonverbal abstract problem solving and inductive reasoning) and higher social problems and screen time were robust positive correlates in the primary analyses and in analyses separated by sex.ConclusionsBeyond demographics and stimulant use, this study highlights abstract reasoning as an important cognitive variable and reaffirms social problems and screen time as significant correlates of BMI and as modifiable therapeutic targets. Prospective data are needed to understand the predictive power of these variables for BMI gain.


2021 ◽  
Author(s):  
Sharon Horwood ◽  
Jeromy Anglim ◽  
Sumudu R. Mallawaarachchi

This study utilized data from a nationally representative sample of Australian adults (n =1164; 50.7% female; age M = 44.9 years, SD = 16.3) to examine the relationships between age, technology concerns, self-rated and objective amount of smartphone use, and problematic smartphone use. Participants completed measures of problematic smartphone use and technology concern, while amount of smartphone use was self-rated and objectively measured using smartphone screen time reporting tools (Screen Time for iOS and Digital Wellbeing for Android). Amount of self-rated and objective smartphone use declined linearly with age. In contrast, problematic smartphone use was relatively high and stable in young adults before rapidly declining around age 40. People were reasonably good at estimating their amount of smartphone use (r = .73), although they did tend to underestimate usage. Technology concern was high across all ages, but unrelated to amount of usage and problematic smartphone usage. Age related differences are interpreted in terms of a combination of developmental and generational changes. Results also suggest that amount of use is an important but not complete cause of problematic smartphone use.


2007 ◽  
Author(s):  
Kimberly Babson ◽  
Casey Trainor ◽  
Matthew Feldner ◽  
Natalie Sachs- Ericsson ◽  
Norman Schmidt ◽  
...  

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