Problematic parental digital technology use, parental technoference and childhood BMI z-score in Latino children ages 4-6 years old
Location
Moultrie, GA
Start Date
17-4-2026 12:00 PM
End Date
17-4-2026 1:00 PM
Description
Introduction: Childhood obesity has many influences, including home environment, parental behaviors, screentime, physical activity, nutrition, socioeconomic status, and sleep duration. However, the association between child obesity and parental digital technology use and the degree to which digital technology interferes with parent-child connection (also termed technoference), has not been examined. We hypothesize that disruptive technology use may be associated with child body mass index (BMI) due to inadequate parental bonding during moments of intimacy as well as unregulated excessive screentime exposure. The purpose of this study was to analyze the extent to which measures of parental problematic digital technology use and technoference were associated with body mass index (BMI) z-scores in Latino children ages 4 to 6 years old.
Methods: Baseline data from the COACH 2.0 randomized clinical trial to reduce childhood obesity were used. Participants were n=300 Hispanic parent-child dyads. Two separate prespecified ordinary least-squares linear regression models tested whether there were statistically significant relationships between parent problematic technology use or technoference and child BMI z-score. Both models adjusted for the same set of covariates including child age, and sex, and the following parent variables: age, education, and birth region. Statistical significance of any relationship was determined by a two-sided p-value < 0.05.
Results: Analyses were unable to detect statistically significant relationships between problematic technology use or technoference and child BMI z-score.
Discussion: While we were unable to detect associations between disruptive technology use and BMI z-score in this sample population, future analyses should evaluate whether it might be related to other important parent and child health behaviors or measures of well-being.
We speculate this is potentially due to some factors that concomitantly influence BMI z –score such as health behavior measures, screentime and sleep disturbance. Although we were unable to identify this relationship, exploration of potential associations with various sleep measures, media exposures, WHO-5 well-being index and less direct measures like diet and exercise are potential outcome measures for future studies.
Embargo Period
5-29-2026
Problematic parental digital technology use, parental technoference and childhood BMI z-score in Latino children ages 4-6 years old
Moultrie, GA
Introduction: Childhood obesity has many influences, including home environment, parental behaviors, screentime, physical activity, nutrition, socioeconomic status, and sleep duration. However, the association between child obesity and parental digital technology use and the degree to which digital technology interferes with parent-child connection (also termed technoference), has not been examined. We hypothesize that disruptive technology use may be associated with child body mass index (BMI) due to inadequate parental bonding during moments of intimacy as well as unregulated excessive screentime exposure. The purpose of this study was to analyze the extent to which measures of parental problematic digital technology use and technoference were associated with body mass index (BMI) z-scores in Latino children ages 4 to 6 years old.
Methods: Baseline data from the COACH 2.0 randomized clinical trial to reduce childhood obesity were used. Participants were n=300 Hispanic parent-child dyads. Two separate prespecified ordinary least-squares linear regression models tested whether there were statistically significant relationships between parent problematic technology use or technoference and child BMI z-score. Both models adjusted for the same set of covariates including child age, and sex, and the following parent variables: age, education, and birth region. Statistical significance of any relationship was determined by a two-sided p-value < 0.05.
Results: Analyses were unable to detect statistically significant relationships between problematic technology use or technoference and child BMI z-score.
Discussion: While we were unable to detect associations between disruptive technology use and BMI z-score in this sample population, future analyses should evaluate whether it might be related to other important parent and child health behaviors or measures of well-being.
We speculate this is potentially due to some factors that concomitantly influence BMI z –score such as health behavior measures, screentime and sleep disturbance. Although we were unable to identify this relationship, exploration of potential associations with various sleep measures, media exposures, WHO-5 well-being index and less direct measures like diet and exercise are potential outcome measures for future studies.