Dataset Information

The association of adolescents' television viewing with Body Mass Index percentile, food addiction, and addictive phone use.

ABSTRACT: Television (TV) viewing remain a popular forms of screen time for adolescents. Greater TV viewing is associated with a number of negative consequences for adolescent health. In a changing media landscape, it is important to understand adolescents' overall and commercial TV exposure, and how TV viewing is linked to health risks (e.g., obesity, food addiction, and phone addiction). The purpose of this study was to: 1) examine differences by age, gender, race/ethnicity, and parental education in overall TV and commercial TV viewing and 2) investigate whether adolescents who watch more overall TV and commercial TV programming were more likely to have a higher BMI percentile, more addictive eating, and more addictive phone use. A sample of 190 adolescents (13-16 years of age) completed Time-Use Diaries (TUDs) in 2015-2017. We found that girls had more overall weekday TV time than males. No other gender differences were detected for weekend TV time or commercial TV time. Higher BMI percentile was not correlated with greater overall or commercial TV viewing. However, we did identify a positive association between overall TV viewing and commercial TV viewing with addictive-eating and addictive phone use. This effect was mainly driven by boys. To our knowledge, this is the first study to investigate patterns of television viewing and addictive-like eating and addictive phone use. We conclude that adolescents, particularly boys, with higher TV viewing may be more likely to present with problems with addictive eating behavior and phone use. Our findings add to the research on the behavioral health correlates of TV viewing among adolescents.

SUBMITTER: Domoff SE

PROVIDER: S-EPMC7855083 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:Levying excise taxes on sugar-sweetened beverage (SSB) distributors, which are subsequently passed on to consumers, is a policy implemented to reduce the high prevalence of cardiometabolic disease and generate public health funding. Taxes are associated with lower SSB purchases and consumption, but it is unknown whether they are associated with weight-related outcomes in youth. To determine the association of SSB excise taxes with youth body mass index (BMI) trajectories. This cohort study was conducted from 2009 to 2020, including 6 years before tax implementation and 4 to 6 years after tax implementation. The California cities of Albany, Berkeley, Oakland, and San Francisco, which implemented SSB excise taxes, were compared against 40 demographically matched control cities in California. Participants included Kaiser Permanente members aged 2 to 19 years at cohort entry (baseline) with continuous residence in selected cities with at least 1 pretax and 1 posttax BMI recorded in their electronic health record. Data analysis was performed from January 2021 to May 2023. Implementation of SSB excise taxes. Centers for Disease Control and Prevention age-specific and sex-specific BMI percentiles and percentage of youth with overweight or obesity before tax implementation through 4 to 6 years after implementation were compared with control cities. Statistical analysis was conducted using the difference-in-differences (DID) method. A sensitivity analysis used the synthetic control method. A total of 44 771 youth (mean [SD] age at baseline, 6.4 [4.2] years; 22 337 female [49.9%]) resided in the cities with SSB taxes; 345 428 youth (mean [SD] age, 6.9 [4.2] years; 171 0168 female [49.5%]) resided in control cities. There was a -1.64-percentage point (95% CI, -3.10 to -0.17 percentage points) overall difference in the mean change of BMI percentile between exposure and control cities after SSB tax implementation. There was no significant overall difference in the percentage of youth with overweight or obesity or youth with obesity compared with control cities. All DID estimates were significant for youth residing in exposure cities in terms of BMI percentile (age 2-5 years in 2017, -2.06 percentage points [95% CI, -4.04 to -0.09 percentage points]; age 6-11 years in 2017, -2.79 percentage points [95% CI, -4.29 to -1.30 percentage points]), percentages of youth with overweight or obesity (age 2-5 years, -5.46 percentage points [95% CI, -8.47 to -2.44 percentage points]; age 6-11 years, -4.23 percentage points [95% CI, -6.90 to -1.57 percentage points]), and percentages of youth with obesity (age 2-5 years; -1.87 percentage points [95% CI, -3.36 to -0.38 percentage points]; age 6-11 years, -1.85 percentage points [95% CI, -3.46 to -0.24 percentage points]). Compared with control cities, changes in mean BMI percentiles were significant for male (-1.98 percentage points; 95% CI, -3.48 to -0.48 percentage points), Asian (-1.63 percentage points; 95% CI, -3.10 to -0.16 percentage points), and White (-2.58 percentage points; 95% CI, -4.11 to -1.10 percentage points) youth. Compared with control cities, White youth in exposure cities had improvements in the percentage with overweight or obesity (-3.73 percentage points; 95% CI, -6.11 to -1.35 percentage points) and the percentage with obesity (-2.78 percentage points; 95% CI, -4.18 to -1.37 percentage points). In this cohort study, SSB excise taxes were associated with lower BMI percentile among youth. Policymakers should consider implementing SSB excise taxes to prevent or reduce youth overweight and obesity and, ultimately, chronic disease, particularly among children younger than 12 years.

Project description:This study's objective was to depict sugar-sweetened food (SSF) consumption in medical college students stratified by sex from Shanghai, China, and to explore the association between the Mobile Phone Addiction Index (MPAI) and SSF intake. The data were obtained from 1121 medical college students from the Fudan University, Shanghai, China, who took an online questionnaire investigation in December 2020. Data included demographics, the MPAI, the Nutrition Literacy Assessment Questionnaire (NLAQ), total and food expenditure per month, the International Physical Activity Questionnaire (IPAQ), and a food frequency questionnaire (carbonated beverages (CB), other sugar-based beverages (OSBB), sugar/chocolate). We evaluated the association between the MPAI and three types of SSF intake according to multivariate logistic regression analysis stratified by sex. The mean CB, OSBB, and sugar/chocolate intakes were, respectively, 65.66 mL/d, 74.20 mL/d, and 4.96 g/d in men and 30.42 mL/d, 71.48 mL/d, and 4.99 g/d in women. The MPAI was positively associated with SSF intake, regardless of sex. In men, the CB and OSBB odds ratios (ORs) were, respectively, 1.023 (95% CI: 1.004-1.042), 1.019 (95% CI: 1.001-1.038); and in women, the CB, OSBB, and sugar/chocolate ORs were, respectively, 1.026 (95% CI: 1.013-1.039), 1.020 (95% CI: 1.007-1.033), and 1.019 (95% CI: 1.006-1.032). Age, NLAQ, total expenditure, food expenditure, and total physical activity also were related to SSF intake. Age and the application capacity of the NLAQ were negatively associated with SSF intake, whereas comprehension capacity of the NLAQ, total and food expenditure, and total physical activity were positively associated with SSF intake. This study confirmed that SSF intake is widespread among medical college students from Shanghai, China, even if they have relatively high nutrition health literacy. From a public health perspective, it is necessary to reduce SSF intake in medical college students by decreasing the MPAI, controlling the total and food expenditure per month in high-consumption areas, and improving the application ability of the NLAQ. Further studies are needed to explore the MPAI and other potential factors that may influence SSF intake of college students by expanding the sample size of college students throughout China, and the causal association between them.

Dataset Information

The association of adolescents' television viewing with Body Mass Index percentile, food addiction, and addictive phone use.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets