Abstract
Purpose
To analyze the temporal trend of leisure screen time among adults in Brazil between 2016 and 2021.
Design
Time-series analysis of six cross-sectional surveys.
Setting
Data from the Surveillance System for Risk and Protective Factors for Chronic Diseases by Telephone Survey (Vigitel) (2016/21).
Subjects
A probabilistic sample of 265 252 adults (≥18 years).
Measures
Time watching television (TV), or using cell phone, computer, or tablet (CCT) during leisure time, and indicators of prolonged exposure for the total population and sociodemographic groups.
Analysis
Prais-Winsten regression models were used to identify trends in the studied period.
Results
Mean time watching TV remained stable (2.3 h to 2.2 h/day) as the frequency of adults watching TV ≥ 3 hours/day (25.7% to 25.1%) for 2016/21. There was an increase in mean time spent on CCT (1.7 h to 2.0 h/day; .08 h/day/year; P < .001) and in the frequency of adults spending ≥ 3 hours/day on CCT (19.9% to 25.5%; 1.33 pp/year; P < .001) for 2016/21. The increase in screen time was relevant in all sociodemographic groups.
Conclusion
Leisure screen time has increased in Brazil, with greater intensity over time.
Purpose
Screen time is currently the biggest expression of sedentary behavior and therefore associated with several adverse health outcomes.1,2 Despite that, a consensus is mostly formed in the scientific community regarding its increase over time. 2 However, most data refer to high-income countries.1,2
Among adults in the United States (US), between 2003 and 2016, prevalence of prolonged TV watching (≥2 h/day) remained stable in high level (65%), while that of computer use (≥1 h/day) increased sharply (from 29% to 50%), resulting in greater screen time. 3 Similar scenario is also observed for other high-income countries. 4 This increase in screen time due to inclusion of new screen types seems to have stronger impacts on younger and more educated individuals.4,5 Due to the restrictions imposed to contain the COVID-19 pandemic, an even more intense increase in screen activities is likely to have occurred since 2020. 6
In Brazil, the prevalence prolonged TV watching (≥3 h/day) was also stable between 2008 and 2017 (25%). 7 However, the time spent on other screens, like cell phone, computer, or tablet (CCT), remains poorly described, 8 preventing an accurate time trend analysis of screen time. Therefore, we aimed to analyze the temporal trend of leisure screen time among adults in Brazil between 2016 and 2021.
Methods
Study Design
Time-series study of six cross-sectional surveys carried out with adults in Brazil.
Sample
Brazilian adults (≥18 years) from the 26 state capitals and the Federal District (FD) interviewed by the Surveillance System for Risk and Protective Factors for Chronic Diseases by Telephone Survey (Vigitel), between 2016 and 2021 (n = 265 252) (Table 1S).
For each year, approximately 10 000 landlines for each city were systematically selected from official landline phone records. 9 One of the adults living in the household was randomly selected to be interviewed. Minimum sample of 1500 interviews per year for each city was established to estimate the prevalence of any indicator at maximum error of three percentage points (pp) (a smaller sample of 1000 interviews per city was employed during COVID-19 pandemic (2020/21), with errors up to four pp). 9 Weighting factors were employed to correct unequal probability of selection (households with more than one landline or adult), and to match the sociodemographic distribution of the sample to that projected to the total adult population. 9 Further details about sampling and data collection are described elsewhere. 9
Measures
TV screen time was recorded based on the question: “How many hours a day, on average, do you often watch TV? (<1 | 1 to 2 | 2 to 3 | 3 to 4 | 4 to 5 | 5 to 6 | > 6 | Does not watch TV)”. For CCT time, two questions were used: “Do you often use the computer, tablet, or cell phone in your free time to engage in social networks, to watch movies or to play games? (yes | no | I do not know)”; and, if yes, “How many hours of your free time (excluding work) do you spend using this computer, tablet, or cell phone per day, on average? (<1 | 1 to 2 | 2 to 3 | 3 to 4 | 4 to 5 | 5 to 6 | > 6)”.
Four indicators were used: daily time (h/day) watching TV or in leisure activities on CCT (midpoint of the response provided) and prolonged exposure (≥3 hours/day) to each of these screen types.
Sex (male | female), age group (18-34 | 35-59 | ≥ 60 years), and schooling (0-8 | 9-11 | ≥ 12 years) were also included.
Analysis
The mean time (h/day) and frequency (%) of prolonged exposure, per year, were estimated for TV and CCT, for total population and according to sociodemographic groups. Prais-Winsten regression models were used to identify time trends for each indicator in the studied period. The regression coefficient indicates the mean annual rate of increase or decrease of the indicator (expressed in h/day/year or pp/year). The 5% level of significance was adopted.
Stata version 16.1 was used to organize and analyze the data. Vigitel databases are available for public access (<http://svs.aids.gov.br/download/Vigitel/>).
Results
The mean time watching TV remained stable from 2.3 to 2.2 h/day between 2016 and 2021, for total population (Figure 1A). Thus, the frequency of adults watching TV for ≥ 3 hours/day also remained stable, from 25.7% to 25.1% (Figure 1B). This scenario is attributed to the trend observed in all sociodemographic groups (Table 2S). Trends of mean screens time (A) and frequency of prolonged exposure to screens (B) in leisure time among the adult population from Brazilian capitals and Federal District. Vigitel, Brazil, 2016-2021.
Meanwhile, the mean time spent in leisure activities on CCT increased from 1.7 to 2.0 h/day (.08 h/day/year; P < .001) between 2016 and 2021 (Figure 1A), and the frequency of adults engaging in leisure activities on CCT for ≥ 3 hours/day also increased, from 19.9% to 25.5% (1.33 pp/year; P < .001), for total population (Figure 1B). Similar trends were observed in both sexes, all age groups and schooling levels. This increase in mean time was more relevant in adults over 35 years and under 11 years of schooling, while in frequency of prolonged exposure was greater intensity among women, younger adults (18-34 years) and those with intermediate schooling level (9-11 years) (Table 2S).
Discussion
Summary
The systematic analysis of over 265 000 interviews in 6 years (2016/21) showed that time watching TV remained stable, while leisure time spent on CCT increased, for total population and all sociodemographic groups. This suggests an increase in leisure screen time among Brazilian adults.
Limitations
The use of self-reported data collected through landline telephone surveys in state capitals is an important limitation that could interfere with screen time estimates. However, weighting factors were used to mitigate sampling bias. Also, self-reported information (and telephone surveys) has been widely used in epidemiological studies,2-4 due to their low cost and feasibility to be used at large scale. An emergency operation was used to keep Vigitel data collection during 2020 and 2021, based especially in remote data collection (with interviewers working from home and being supervised from a central) and reduced sample size. 9 While this may impact data precision, the results seem to agree with data from this pandemic period, with increased screen time in TV and CCT.
Significance
Our results are relevant by bringing data for two different dimensions (TV and CCT) for a large middle-income country. Time spent with CCT leisure activities emerged as a relevant modal for screen exposure (especially due to cell phone access and use), corresponding to almost half of the screen exposure in 2021 (2.2 h/day for TV vs 2.0 h/day for CCT). This evidence reinforces the belief regarding increasing screen time worldwide and suggest that it is also widespread in middle-income countries, such as Brazil.
In-depth comparisons between the current results and other studies3-5 are limited by the lack of standardized indicators (screen types and cut-off points).
5
Most studies approach exposure to leisure screen time based on a cut-off point often associated with one, or more, adverse health outcomes.
10
Currently, there is not enough evidence to recommend a safe amount of screen time, however, national
11
and international
2
documents recommend limiting sedentary behavior to, as well as interrupting long periods of sedentary activities as much as possible, in addition to compensate excess of sedentary behavior with increased exercising. Although screen time is related to adverse health outcomes, data from high-income countries suggest that it evolves unfavorably over time. Multiple dimensions of screen time exposure were studied for a large sample of a middle-income country. TV screen time remained stable between 2016 and 2021, while leisure time on CCT increased, suggesting an increase in screen time in Brazil. There is an emerging need to reduce prolonged exposure time to screens. In-depth monitoring of screen time is still necessary for the proper design of recommendations. Behavioral interventions aimed at reducing sedentary behavior and setting goals should be provided.SO WHAT?
What is already known on this topic?
What does this article add?
What are the implications for health promotion practice or research?
Supplemental Material
Supplemental Material - Changes in Screen Time in Brazil: A Time-Series Analysis 2016-2021
Supplemental Material for Changes in Screen Time in Brazil: A Time-Series Analysis 2016-2021 by Pollyanna Costa Cardoso, Thaís Cristina Marquezine Caldeira, Taciana Maia Sousa and Rafael Moreira Claro in American Journal of Health Promotion
Footnotes
Author Contributions
Pollyanna Costa Cardoso has contributed to data analysis and interpretation, writing and manuscript review; Thaís Cristina Marquezine Caldeira has contributed to study design, data analysis and manuscript review; Taciana Maia de Sousa has contributed to data analysis and manuscript review; Rafael Moreira Claro has contributed to study design, data analysis and interpretation, manuscript final review.
Declaration of Conflicting Interests
The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Funding
The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) [grant number 001 (Scholarship for TCMC)] and Conselho Nacional de Desenvolvimento Científico e Tecnológico [grant number 311170/2019-6 (Scholarship for RMC)], and Ministry of Health of Brazil.
Ethical Approval
Free and informed consent was verbally obtained during the telephone interviews. Vigitel was approved by the National Ethics Committee on Human Research of the Brazilian Ministry of Health (CAAE: 65610017.1.0000.0008).
ORCID iDs
Supplemental Material
Supplemental material for this article is available online.
References
Supplementary Material
Please find the following supplemental material available below.
For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.
For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.
