What this is
- This study assesses regular soft drink consumption among Brazilian adolescents based on the 2019 National Survey of School Health.
- It examines how sociodemographic factors, eating habits, and lifestyle choices relate to this consumption.
- The findings reveal significant associations, highlighting the need for targeted interventions to reduce soft drink intake.
Essence
- Regular soft drink consumption among Brazilian adolescents is 17.3%. Key associations include sociodemographic factors, unhealthy eating habits, and sedentary lifestyles.
Key takeaways
- Regular soft drink consumption is higher among boys (18.2%) than girls (16.5%). This difference underscores gender-based dietary patterns.
- Adolescents who frequently consume fast food show a 2.28Γ higher likelihood of regular soft drink consumption compared to those who eat fast food sporadically.
- Spending more than three hours on sedentary activities is associated with a 1.18Γ higher prevalence of regular soft drink consumption.
Caveats
- Data reliance on self-reports may introduce information bias, affecting the accuracy of consumption estimates.
- The study cannot quantify the exact amount of soft drinks consumed, limiting insights into consumption patterns.
Definitions
- Regular consumption: Defined as consuming soft drinks five or more days in the last week.
- Sociodemographic characteristics: Includes factors like region of residence, sex, age, and education level.
AI simplified
INTRODUCTION
Adolescent health is a recurring topic in national1,2 and international3,4 population surveys. In this context, studies on excessive weight gain in this age group, which results in overweight or obesity among adolescents, stand out. These are conditions that can persist into adulthood, with consequences in the short, medium, and long term5,6, such as the development of noncommunicable diseases and injuries (NCDIs) and psychosocial impacts7,8.
In addition to overweight and obesity, other risk factors associated with adult NCDIs include sociodemographic characteristics, eating habits, and lifestyle9. Considering that adolescence is a period in which habits are established and often maintained in adulthood, the consolidation of healthy eating habits and lifestyles at this stage is essential for the prevention of overweight/obesity and, consequently, of NCDIs10,11.
Among unhealthy eating habits, soft drinks consumption has been investigated in both adolescents and adults due to the increasing consumption and association with NCDIs12β14. It is also known that excessive consumption of sweetened beverages contributes to the development of obesity, type 2 diabetes, cardiovascular diseases, and other metabolic conditions15,16.
The identification of characteristics and habits of adolescents in relation to the consumption of soft drinks can contribute to establishing prevention actions more directed to specific groups16,17. Thus, the objective of this study was to outline the profile of Brazilian adolescents in relation to soft drinks consumption and to verify possible associations of regular soft drinks consumption with sociodemographic characteristics, eating habits, and lifestyle.
METHODS
Study design and population
This is a cross-sectional study in which microdata of the 2019 National Survey of School Health (Pesquisa Nacional de SaΓΊde do Escolar β PeNSE) were analyzed. This school-based survey with national representativeness was carried out in 2009, 2012, 2015, and the most recent edition in 2019. The research consists of an electronic questionnaire self-administered by adolescents enrolled and regularly attending the seventh to ninth grades of Elementary School and the tenth to twelfth grades of High School (morning, afternoon, and evening shifts) from public and private schools. In the 2019 edition, data were collected from 4,253 schools in 1,288 municipalities and questionnaires from 160,721 students, totaling 159,245 valid questionnaires (in which the adolescent registered that he/she would like to participate in the research, in addition to informing sex and age, in classes that reached minimum requirements for achievement)18. In the present study, adolescents aged 13 to 17 years were included and those with missing data on the variables of interest were excluded. The flowchart of the exclusions made until obtaining the studied sample is described in Figure 1.
The 2019 edition of PeNSE was approved by the National Commission of Ethics in Research (ComissΓ£o Nacional de Γtica em Pesquisa β Conep) of the National Health Council (Conselho Nacional de SaΓΊde β CNS), under opinion No. 3.249.268, of April 8, 2019.
Sample selection flowchart.
Definition of the analyzed variables
The dependent variable under study was soft drink consumption, assessed through the question: "In the last seven days, in how many of them did you have soft drinks?". Responses were categorized into: sporadic consumption, defined as consumption in less than five days in the last week, and regular consumption, defined as consumption in five or more days in the last week19. The independent variables analyzed included sociodemographic characteristics, eating habits, and lifestyle.
The sociodemographic variables selected were region of residence (Northeast; North; Southeast; South; Midwest), sex (girls; boys), age group (13 to 15 years; 16 to 17 years), skin color or race (brown; white; Black; Asian; Indigenous), level of education (elementary school; high school), and type of school (public; private).
Questions about eating habits included: having meals accompanied by an adult, having meals while using a screen (TV, computer, or cell phone), and eating breakfast. Habit ("Do you usuallyβ¦") and frequency (times a week) were considered. These variables were categorized into regular consumption, if consumed five or more days a week, or sporadic consumption, if consumed less than five days a week. Also regarding eating habits, questions were asked about the consumption in the last seven days of: beans, vegetables, sweets (exemplified in the question as: candies, confectionery, chocolates, gums, bonbons, lollipops, and others), fresh fruits or fruit salad. Regular consumption of these foods was defined as five or more days in the last seven days, or sporadic consumption, if it occurred less than five days in the last week18,20. Frequent fast food consumption was considered as three or more days, defined through the question: "In the last seven days, in how many of them did you eat in diners, hot dog stands, pizzerias, fast-food restaurants, etc.?". Less than three days was defined as sporadic consumption for this variable21.
Regarding lifestyle, the variables of physical and sedentary activities, use of cigarette and alcohol were evaluated. Physical activity was measured by total time in the last week, including time spent commuting, physical education classes, and leisure time. This total time was categorized as less than recommended (less than 300 minutes per week) or recommended (greater than or equal to 300 minutes per week)22. The daily time of sedentary activities (watching television, playing video games, using a cell phone or computer, and other sitting activities), without considering Saturday and Sunday and time spent sitting at school, was inquired regarding habit ("How many hours a day do you usuallyβ¦?") and dichotomized as more than three hours or three hours or less per day23. Cigarette use was dichotomized into βyesβ for those who answered that they had smoked one or more cigarettes in the last 30 days and βnoβ otherwise24. For the use of alcohol, no cutoff points were identified for the consumption of adolescents; therefore, the criteria for defining binge drinking (heavy episodic drinking) of the World Health Organization for adults was considered, categorizing the answers into βyesβ if the adolescent reported that he/she had four or more drinks on at least one occasion or βnoβ if he/she had less than four drinks in the last 30 days25. The pieces of information on all analyzed variables were self-reported.
Statistical analyses
Descriptive analyses were performed for all variables included in the study. Weighted prevalence and 95% confidence intervals (95%CI) were calculated for categorical variables. For comparisons between each exposure variable and the regular consumption of soft drinks, the Rao-Scott Ο2 test was used, which considers the sample design of the study. A Poisson regression model was developed to verify possible associations between regular soft drinks consumption and independent variables. In the final model, only the variables that were statistically significant in the bivariate analysis were included. The analyses were carried out in SAS on Demand for Academics, version 3.81, considering the complex research sample design. A value of p<0.05 was considered statistically significant.
RESULTS
The frequency of regular soft drinks consumption among adolescents was 17.3% (95%CI 16.7β18.0%). According to the bivariate analyses, there was an association between the prevalence of regular soft drinks consumption and the adolescent's region of residence, sex, and skin color/race. We observed a higher prevalence in boys (18.2%) when compared to girls (16.5%) (Table 1).
In the unadjusted analysis of the variables of eating habits, a higher prevalence of regular consumption of soft drinks was observed among adolescents who eat meals while using screens (20.4%), those who have breakfast sporadically (20.2%), those who consume sweets (30.0%) regularly, and among adolescents who frequently consume fast food (39.2%) (Table 2).
Regarding lifestyle, adolescents who reported more than three hours of sedentary activities per day had a higher prevalence of regular soft drinks consumption (20.5%). Cigarette and alcohol use were also associated with a higher prevalence of regular soft drinks consumption, with frequencies of 28.2 and 27.7%, respectively (Table 3).
In the multivariate analysis, there was a greater chance of regular consumption of soft drinks in adolescents living in the North (prevalence ratio β PR=1.13; 95%CI 1.04β1.23), Southeast (PR=1.49; 95%CI 1.40β1.60), South (PR=1.31; 95%CI 1.20β1.41), and Midwest (PR=1.50; 95%CI 1.41β1.59) when compared to Northeast residents. In addition, the regular consumption of soft drinks was more frequent among boys (PR= 1.22; 95%CI 1.16β1.29). As for eating habits, adolescents who reported having meals while using a screen had a greater chance of regular soft drinks consumption (PR=1.20; 95%CI 1.13β1.27). Likewise, those who reported eating breakfast sporadically (PR=1.14; 95%CI 1.08β1.21) and consuming sweets regularly (PR=2.16; 95%CI 2.03β2.29) also showed a greater chance of regular soft drinks consumption. Adolescents who reported consuming fast food frequently had 2.28 times the chance of having regular consumption of soft drinks when compared to those who consumed fast food sporadically (PR=2.28; 95%CI 2.16β2.41). Regular soft drinks consumption was 18% higher among adolescents with sedentary activities for more than three hours a day (PR=1.18; 95%CI 1.12β1.25). In addition, the regular consumption of soft drinks was more than 20% higher among those who reported using cigarettes (PR=1.22; 95%CI 1.11β1.33) and binge drinking (PR=1.21; 95%CI 1.12β1.30) (Table 4).
| Soft drinks consumption 2 | p-value 3 | |||
|---|---|---|---|---|
| Sporadic (n=99,421) | Regular (n=19,076) | |||
| % (95%CI) | % (95%CI) | |||
| Region of residence | ||||
| Northeast | 87.7 (86.9β88.6) | 12.3 (11.4β13.1) | <0.001 | |
| North | 87.0 (86.1β87.9) | 13.0 (12.1β13.9) | ||
| Southeast | 78.7 (77.3β80.1) | 21.3 (19.9β22.7) | ||
| South | 82.7 (81.4β84.0) | 17.3 (15.9β18.6) | ||
| Midwest | 78.7 (77.6β79.8) | 21.3 (20.2β22.4) | ||
| Sex | ||||
| Girls | 83.5 (82.7β84.2) | 16.5 (15.8β17.3) | 0.001 | |
| Boys | 81.8 (80.9β82.7) | 18.2 (17.3β19.1) | ||
| Age group (years) | ||||
| 13 to 15 | 82.9 (82.1β83.6) | 17.1 (16.4β17.8) | 0.389 | |
| 16 to 17 | 82.2 (81.0β83.5) | 17.8 (16.5β19.0) | ||
| Skin color or race | ||||
| Brown | 84.0 (83.25β84.8) | 16.0 (15.2β16.8) | <0.001 | |
| White | 81.3 (80.3β82.2) | 18.7 (17.8β19.7) | ||
| Black | 82.0 (80.4β83.5) | 18.0 (16.5β19.6) | ||
| Asian | 81.8 (79.0β84.6) | 18.2 (15.4β20.9) | ||
| Indigenous | 84.0 (81.4β86.6) | 16.0 (13.4β18.6) | ||
| Level of education | ||||
| Elementary school | 82.5 (81.7β83.3) | 17.5 (16.7β18.3) | 0.671 | |
| High school | 82.8 (81.8β83.8) | 17.2 (16.2β18.2) | ||
| Type of school | ||||
| Public | 82.7 (81.9β83.4) | 17.3 (16.6β18.0) | 0.987 | |
| Private | 82.5 (81.7β83.3) | 17.5 (16.7β18.3) | ||
| Soft drinks consumption 5 | p-value 6 | |||
|---|---|---|---|---|
| Sporadic (n=99,421) | Regular (n=19,076) | |||
| % (95%CI) | % (95%CI) | |||
| Habit of having meals accompanied by an adult 7 | ||||
| Regular | 82.9 (82.2β83.5) | 17.1 (16.4β17.8) | 0.144 | |
| Sporadic | 82.1 (81.1β83.1) | 17.8 (16.8β18.9) | ||
| Habit of having meals while using a screen 7 | ||||
| Sporadic | 86.7 (85.9β87.5) | 13.3 (12.5β14.1) | <0.001 | |
| Regular | 79.6 (78.7β80.5) | 20.4 (19.5β21.3) | ||
| Habit of eating breakfast 7 | ||||
| Regular | 84.7 (84.0β85.4) | 15.3 (14.6β16.0) | <0.001 | |
| Sporadic | 79.8 (78.8β80.7) | 20.2 (19.3β21.2) | ||
| Beans consumption 5 | ||||
| Regular | 83.0 (82.1β83.8) | 17.0 (16.2β17.9) | 0.171 | |
| Sporadic | 82.2 (81.3β83.1) | 17.8 (16.9β18.6) | ||
| Vegetables consumption 5 | ||||
| Regular | 82.8 (81.8β83.8) | 17.2 (16.2β18.2) | 0.723 | |
| Sporadic | 82.6 (81.9β83.3) | 17.4 (16.7β18.1) | ||
| Sweets consumption 5 | ||||
| Sporadic | 88.9 (88.3β89.4) | 11.1 (10.5β11.6) | <0.001 | |
| Regular | 70.0 (68.7β71.2) | 30.0 (28.7β31.3) | ||
| Fruits consumption 5 | ||||
| Sporadic | 82.9 (82.2β83.6) | 17.1 (16.4β17.8) | 0.117 | |
| Regular | 82.0 (80.9β83.1) | 18.0 (16.9β19.1) | ||
| Fast food 8 | ||||
| Sporadic | 86.7 (86.1β87.3) | 13.3 (12.7β13.9) | <0.001 | |
| Frequent | 60.8 (59.3β62.3) | 39.2 (37.7β40.7) | ||
| Soft drinks consumption 10 | p-value 11 | |||
|---|---|---|---|---|
| Sporadic (n=99,421) | Regular (n=19,076) | |||
| % (95%CI) | % (95%CI) | |||
| Total time of physical activity in the last week | ||||
| Below recommended | 82.8 (82.1β83.5) | 17.2 (16.5β17.9) | 0.273 | |
| Recommended | 82.2 (81.2β83.2) | 17.8 (16.8β18.8) | ||
| Daily time of sedentary activities (hours) | ||||
| β€3 | 86.4 (85.7β87.1) | 13.6 (12.9β14.3) | <0.001 | |
| >3 | 79.5 (78.7β80.4) | 20.5 (19.6β21.3) | ||
| Cigarette use in the last 30 days | ||||
| No | 83.4 (82.8β84.0) | 16.6 (16.0β17.2) | <0.001 | |
| Yes | 71.8 (69.4β74.2) | 28.2 (25.8β30.6) | ||
| Binge drinking | ||||
| No | 83.8 (83.1β84.4) | 16.2 (15.6β16.9) | <0.001 | |
| Yes | 72.3 (70.5β74.1) | 27.7 (25.9β29.5) | ||
| PR(95%CI) 13 | p-value 14 | ||
|---|---|---|---|
| Region of residence | |||
| Northeast | Ref. | ||
| North | 1.13 (1.04β1.23) | 0.004 | |
| Southeast | 1.49 (1.40β1.60) | <0.001 | |
| South | 1.31 (1.20β1.41) | <0.001 | |
| Midwest | 1.50 (1.41β1.59) | <0.001 | |
| Sex | |||
| Girls | Ref. | <0.001 | |
| Boys | 1.22 (1.16β1.29) | ||
| Skin color or race | |||
| Brown | Ref. | ||
| White | 1.05 (0.99β1.12) | 0.088 | |
| Black | 1.03 (0.95β1.12) | 0.449 | |
| Asian | 1.12 (0.97β1.29) | 0.129 | |
| Indigenous | 1.01 (0.85β1.19) | 0.934 | |
| Habit of having meals while using a screen 15 | |||
| Sporadic | Ref. | <0.001 | |
| Regular | 1.20 (1.13β1.27) | ||
| Habit of eating breakfast 15 | |||
| Regular | Ref. | <0.001 | |
| Sporadic | 1.14 (1.08β1.21) | ||
| Sweets consumption 16 | |||
| Sporadic | Ref. | <0.001 | |
| Regular | 2.16 (2.03β2.29) | ||
| Fast food 17 | |||
| Sporadic | Ref. | <0.001 | |
| Frequent | 2.28 (2.16β2.41) | ||
| Daily time of sedentary activities (hours) | |||
| β€3 | Ref. | <0.001 | |
| >3 | 1.18 (1.12β1.25) | ||
| Cigarette use in the last 30 days | |||
| No | Ref. | <0.001 | |
| Yes | 1.22 (1.11β1.33) | ||
| Binge drinking | |||
| No | Ref. | <0.001 | |
| Yes | 1.21 (1.12β1.30) | ||
DISCUSSION
Our results point to the profile of regular soft drinks consumption among Brazilian adolescents, with regional variations, by skin color/race, and higher in boys. Regarding eating habits, the regular consumption of soft drinks was associated with eating meals while using screens, not having breakfast on five or more days of the week, and the frequent consumption of sweets and fast food. Lifestyles with prolonged time in sedentary activities, cigarette use, and binge drinking were also associated with regular soft drinks consumption.
The prevalence of regular soft drinks consumption observed in our study was much lower than the value of 42.8% (95%CI 32.4β50.7%) estimated in a global meta-analysis, which considered daily consumption17. However, when comparing our data on adolescents with data from other national surveys, we noticed a slightly higher prevalence. According to data from the 2017β2018 Consumer Expenditure Survey (Pesquisa Nacional de OrΓ§amentos Familiares β POF), there is a prevalence of 15.4%26 in the total population, and authors of a study with data from the Surveillance System of Risk and Protective Factors for Noncommunicable Chronic Diseases by Telephone Survey (Sistema de VigilΓ’ncia de Fatores de Risco e Proteção para DoenΓ§as CrΓ΄nicas por InquΓ©rito TelefΓ΄nico β VIGITEL) identified a significant reduction in the frequency of regular consumption of soft drinks or synthetic juices by the population of state capitals and the Federal District, from 26.4% in 2008 to 15.0% in 201927.
The regional variations found in our study point to a higher prevalence of regular consumption of soft drinks in adolescents living in the Southeast and Midwest regions, followed by the South and lower prevalence values in the North and Northeast. These prevalence values differ from the POF 2017β2018 results, in which the South region stands out with the highest regular consumption of soft drinks26. The higher prevalence of regular soft drinks consumption found for boys was also observed in other studies12,16.
In our study, a relevant finding was the positive association between regular consumption of soft drinks and eating habits markers of unhealthy diet, quite common in adolescents, such as having meals while using screens, skipping breakfast, and the consumption of sweets and fast food.
Excessive screen time is often studied in adolescents28,29, and eating meals while using screens can lead to loss of perception of food, interfering with physiological signs of hunger and satiety29,30. According to data from the Study of Cardiovascular Risks in Adolescents (Estudo de Riscos Cardiovasculares em Adolescentes β ERICA), approximately 60.0% of adolescents ate meals almost always or always in front of the television, a habit that was associated with the regular consumption of soft drinks in our study30. Authors of a research conducted in Chile showed that more than 85% of adolescents used screens during meals, consuming 42.3% of daily calories while watching TV. However, there were no significant differences in the nutrient profile between having meals with and without using screens, but higher weekly screen time was associated with a less healthy diet, which included higher consumption of sweetened beverages among Chilean adolescents29.
In a study on adolescents from the state of EspΓrito Santo, Brazil, sedentary behavior was associated with inadequate eating habits and poorer diet quality31. It is known that inadequate eating habits associated with sedentary lifestyle in childhood can trigger the onset of cardiometabolic diseases in the future31,32.
Alcohol use in adolescence tends to occur together with other health risk behaviors such as smoking33. When analyzing the data obtained in this study, we found an association between alcohol and tobacco use and regular soft drink consumption by adolescents. Authors of a longitudinal study with adolescents conducted in Finland observed that alcohol use in adolescence increases the risk of smoking in adulthood34. In Brazil, researchers of the ERICA study found that 21% of the interviewed adolescents had consumed alcohol in the 30 days prior to the interview33. Alcohol consumption by this population is worrisome due to the greater tendency to impulsivity in this age group, the impairment of brain development in childhood and adolescence caused by alcohol, and risk behaviors in the adolescent age group that may last into adulthood, influencing the development of other habits35.
Among the limitations of the present study, it should be noted that the obtained data were based on the adolescentsβ reports, which may lead to information bias. Nonetheless, we emphasize that population surveys carried out in several countries also adopt this methodology to collect data in large samples3,4,30. Furthermore, we could not estimate the number of soft drinks consumed by the participants of the 2019 PeNSE due to the lack of information; however, the option for the variable of regular consumption of soft drinks proved to be adequate, as we analyzed adolescentsβ habits.
Reducing the consumption of ultra-processed foods, including soft drinks, is one of the recommendations of the Dietary Guidelines for the Brazilian Population, given that they are associated with excessive calorie consumption and increased risk of obesity36. With our data, we emphasize the need for specific interventions, recognizing the profile of adolescents to promote healthier eating and lifestyle habits. These interventions should consider an integrated approach, acting not only in reducing the consumption of soft drinks, but also in factors associated with this regular consumption β such as the consumption of sweets and fast food. The National School Feeding Program (Programa Nacional de Alimentação Escolar β PNAE) serves public, philanthropic schools, and community entities in this sense, promoting healthy eating habits and developing initiatives on food and nutrition education37.
The incentive to have meals without using screens, to have breakfast daily, to reduce the time of sedentary activities, and to avoid the use of cigarette and alcohol requires, in addition to public policies, an awareness of these aspects by the family. These measures are paramount to protect the health of adolescents and reduce the burden of diseases related to the regular consumption of soft drinks.
ACKNOWLEDGEMENTS
The authors would like to thank the National Council for Scientific and Technological Development (CNPq).