General Versus Vocational Education in High School: Cross-Sectional Associations with Student's Health
ABSTRACT
BACKGROUND
The aim of the present study was to analyze the association between course type and health among high school students.
METHODS
A cross-sectional study with 675 Brazilian high school students. The independent variable was course type (general or vocational) and dependent variables were health characteristics. All information was obtained by a self-report questionnaire and the following health characteristics were analyzed: mental health, physical activity, sedentary behavior, food consumption, daytime sleepiness, tobacco use, alcohol consumption, aggression, and musculoskeletal symptoms. The prevalence ratio (PR) was estimated by Poisson regression.
RESULTS
Vocational students presented a higher prevalence in 7 of the 20 mental health symptoms analyzed (PR = 1.21-1.64), daytime sleepiness (PR = 1.39-1.71), and musculoskeletal symptoms in neck, shoulders, low back, and knees (PR = 1.31-1.41), and a lower likelihood of being physically active (PR = 0.59-0.70). Conversely, vocational students showed lower sedentary behavior on TV and videogames during the week (PR = 0.35-0.46), consumption of snacks, cookies, and crackers (PR = 0.56-0.72), and experiences of aggression (PR = 0.13-0.17), all P < .05.
CONCLUSIONS
High school can affect students' health distinctly, indicating that intervention programs and health monitoring should be specific to course type.
Adolescence is a critical period of human development, representing the transition between childhood and adulthood, and is characterized by pronounced changes in biological, cognitive, emotional, and social characteristics.1 Specifically during adolescence, some health risks have been reported, including physical inactivity, sedentary behavior, poor diet, tobacco use, alcohol consumption, musculoskeletal symptoms, experience of aggression, sleep disturbance, and mental health disorders.2-11 Furthermore, there is an increased risk of various work-based injuries.12, 13 In view of this, healthy cognitive, physical, sexual, and psychosocial development is necessary to successfully enter adulthood.1
Adolescence is also a period when students need to decide their trajectory into high school and a future career. Although education-related legislation, nomenclature, and requirements are different across countries, students can opt for general high school or vocational courses, which are also known as career, technical, work-based learning, or training courses. The main aim of vocational courses, is to prepare students with technical skills to enter the labor market in a specific profession after ending high school, with a small part of the course consisting of basic academic content.14 On the other hand, general or academic high school courses prepare students to continue their studies at University and for challenging tasks in society.14 Another possibility is a hybrid course, which consists of vocational education plus deeper academic content and focuses both on the world of work and academic knowledge for educational progression.14
The decision regarding vocational or general education can impact adolescent health, as courses have different objectives, curriculums, routines, study demands, and perspectives. Recently, there has been increasing interest in the health characteristics of vocational students.2, 15-17 A higher proportion of unfavorable health characteristics regarding body mass index and diet was described among vocational students compared to those enrolled in general high school, while for physical activity and smoking there was a similar prevalence.2 Another study demonstrated a high risk of overweight among vocational students.18 Although both vocational and general high school have been implemented worldwide, information regarding the association between course type and a wide range of health characteristics is still scarce. Since schools have an important role in the health promotion of students,19 the comparison of health profiles between vocational and general students will improve knowledge regarding health and exposure to high school courses (vocational or general) and provide information for the implementation of strategies to monitor and prevent health risks.
Thus, the aim of the present study was to analyze the association between course type and health among Brazilian high school students.
METHODS
Participants
A cross-sectional study from a project entitled “Health risks among adolescents: association with the type of course in high school,” conducted in 2019 in Boituva City, São Paulo, Brazil. Boituva is located 100 km from the State capital São Paulo and has a population of 62,170. The study population was estimated at 2460 adolescents enrolled in high school, with 3 schools in the city public education system. The sample size was calculated using the software Open Epi, OpenEpi Project (Atlanta, U.S.A.), version 3.01 and the following parameters: N = 2460, prevalence of 50%, precision of 5%, design effect of 1.5, and confidence interval of 95%. The prevalence of 50% was used to ensure the largest sample size to enable estimation of different outcomes. Thus, the study required a sample of at least 499 participants.
- General students, a 3-year half shift academic course (5 hours a day during morning, evening, or night shift) focusing on 13 compulsory subjects. At the end of the course, the student is able to enter higher education, through a matriculation examination, or to find a job that does not require higher education or technical training.
-
Vocational students, a 3-year full-time course (9 hours across the morning and afternoon), aimed at preparing students for the labor market through learning technical skills (informatics or industrial automation) and academic content. This course includes 29 subjects: 13 academic, 13 vocational (that vary according to course type), and 3 optional. This course enables the student to enter higher education through a matriculation examination, or find a job that requires specific technical training.
All schools (2 state schools that offer general courses and 1 federal vocational high school) were invited to compose the study and 2 agreed to participate. The schools are located within a 3 km radius in the central region of the city. The participants were randomly selected within each classroom, stratified by course type, sex, and grade of study. When a participant did not agree to participate, another in the same stratum was selected.
Instruments
The independent variable of the present study was high school course type (general and vocational high school). Dependent variables were health characteristics, as follows: symptoms of mental health disorders, physical activity, sedentary behavior, food consumption, tobacco use, alcohol consumption, experience of aggression, daytime sleepiness, and musculoskeletal symptoms. The covariates were age, sex, socioeconomic status, study shift, and work status. All variables were collected using a self-report questionnaire, composed of the instruments described below.
Symptoms of mental health disorders were evaluated using the Brazilian version of the Self-report questionnaire.20 The questionnaire contains 20 questions related to symptoms in the previous 30 days, with answerer options of “Yes” and “No.” Questions were distributed into 4 dimensions: depressive-anxious mood, decrease in vital energy, somatic symptoms, and depressive thoughts. The instrument demonstrates acceptable psychometric properties and an internal consistency of 0.80.20 Moderate to vigorous physical activity during leisure time was estimated by the Long form of the Brazilian version of the international Physical Activity Questionnaire.21 Sedentary behavior (≥2 hours/day)22 was assessed using questions about the use of television, electronic games, internet, and academic activities in leisure time.23 Daytime sleepiness was evaluated by the Brazilian version of the Pediatric Daytime Sleepiness Scale.24 Musculoskeletal symptoms were assessed using the Brazilian version of the Nordic musculoskeletal questionnaire.25 Socioeconomic status was assessed by the level of education of the household head.26 Alcohol use was assessed using 2 questions extracted from the Brazilian version of the Alcohol Use Disorders Identification Test27: (a) “How often do you drink alcohol?” “Never,” “monthly or less,” “2 to 4 times a month,” “2 to 4 times a week,” “4 or more times a week”; (b) “How often do you drink 6 or more doses at once?” “Never,” “Less than once a month,” “Monthly,” “Weekly,” “Every or almost every day.” Researchers described the dose volume for beer, wine, and distilled drink. Food consumption, tobacco use, and aggression variables were assessed by the questions used in the National Adolescent School-based Health Survey.28 Food consumption was assessed by a self-report questionnaire with the question “In the past 7 days, on how many days did you eat the following foods or drinks?” with answer options “none,” “1 day,” “2 days,” “3 days,” “4 days,” “5 days,” “6 days,” and “7 days” in the week. A list of 11 foods was displayed and the cut-off adopted was the consumption of each food in 5 or more days.29 The instrument presented satisfactory validity compared to a qualitative interview.30 Tobacco use, “In the past 30 days, on how many days did you smoke cigarettes?” only cigarettes were considered.31 Aggression, “In the past 30 days, how many times have you been physically assaulted by an adult in your family?” and “In the past 30 days, how many times have you been involved in a fight where someone had a firearm or any kind of knife.” The cut-off used was ≥1.32 Work status, “Do you work formally or informally in the period of the day when you are not studying?” with answer options “yes” “ or “no.”
Procedure
All procedures were performed in each school where participants were enrolled. The schools were visited by researchers and the project was presented to the principals. After receiving authorization from the principals, the aims, procedures, risks, and benefits of the project were presented to all students in each classroom. Students were invited to participate voluntarily in the study and only those who provided assent and returned signed parental consent forms were included. The data collection was scheduled and any absent students were able to participate on another day in the following week (within a maximum of 7 days after the first data collection).
Data Analysis
The sample size for prevalence was estimated according to procedures described by Dean et al.33 Descriptive statistics were conducted using relative frequency. The bivariate association between high school course and health was assessed by the Pearson chi-squared test. Multivariate analysis adjusted for potential covariates was conducted using Poisson regression with robust variance estimators to estimate prevalence ratios (PRs) and confidence intervals of 95% (CI95%), using STATA software 14.0, STATA Corp., College Station, Texas, USA. In all cases, significance was set at P < .05.
RESULTS
Data collection was conducted in a total of 675 participants; however, the sample varied according to the outcome (n = 593-650), due to incomplete information on any question of the questionnaire. Sample loss varied from 3.70% to 12.15%. The exclusion of participants with missing information did not substantially change the sample characteristics (Appendix 1), indicating no pattern of non-respondent participants across the variables of the study. The distribution of the sample according to sex, age, parental schooling, or skin color was homogeneous (Table 1). However, a higher frequency of females and parents with at least a high school degree was found among vocational students and a higher prevalence of work (35.3% vs. 15.6%) was found in those from general courses (P < .05). General students were from morning (44%), evening (31.1%), or night shift courses (24.9%), while all vocational students attended full-time courses (morning and afternoon).
| School type | |||
|---|---|---|---|
| Variables | All (n = 675) | General (n = 466) | Vocational (n = 209) |
| Sex | |||
| Male | 46.7 | 49.1 | 41.1 |
| Female | 53.3 | 50.9 | 58.9* |
| Age | |||
| 14–15 | 43.1 | 42.1 | 45.5 |
| 16–18 | 56.9 | 57.9 | 54.5 |
| Parental schooling | |||
| Elementary school | 35.6 | 39.7 | 26.3 |
| High school | 35.0 | 30.5 | 45.0* |
| College | 29.4 | 29.8 | 28.7 |
| Work* | |||
| No | 70.9 | 64.7 | 84.4 |
| Yes | 29.1 | 35.3 | 15.6* |
| Skin color | |||
| White | 49.3 | 44.0 | 39.2 |
| Other | 50.7 | 56.0 | 60.8 |
| Study shift | |||
| Morning | 30.4 | 44.0 | — |
| Evening | 21.5 | 31.1 | — |
| Night | 17.1 | 24.9 | — |
| Full time | 31.0 | — | 100 |
- P < 0.05 in chi-squared test.
- * Formal or informal work.
The results of bivariate and multivariate analysis of the association between course type and the dependent variables analyzed are described in Tables 2 to 5. The prevalence of symptoms of common mental disorders varied from 18% for poor digestion to 70% for feeling nervous, tense, or worried in the total sample. In the multivariate analysis, vocational students presented a higher PR of the following symptoms of common mental disorders: poor appetite (PR = 1.38), bad sleep (PR = 1.64), being easily frightened (PR = 1.28), feeling nervous, tense, or worried (PR = 1.26), difficulty enjoying daily activities (PR = 1.48), suffering at school or work (PR = 1.56), and getting tired easily (PR = 1.21), all P < .05 (Table 2).
| Course type | |||||
|---|---|---|---|---|---|
| General | Vocational | Crude PR (CI95%) | Adjusted PR (CI95%) | ||
| Variable (n = 604) | All | % | % | Reference group: General course | |
| 1. Do you often have headaches? | 38.1 | 36.1 | 42.4 | 1.17 (0.95–1.45) | 1.14 (0.92–1.41) |
| 2. Is your appetite poor? | 28.0 | 25.4 | 34.0* | 1.35 (1.04–1.75) | 1.38 (1.05–1.84) |
| 3. Do you sleep badly? | 42.4 | 36.3 | 55.5* | 1.52 (1.19–1.95) | 1.64 (1.33–2.01) |
| 4. Are you easily frightened? | 41.4 | 37.5 | 49.7* | 1.32 (1.02–1.71) | 1.28 (1.04–1.58) |
| 5. Do you have shaking hands? | 29.8 | 29.5 | 30.4 | 1.02 (0.75–1.40) | 0.99 (0.74–1.33) |
| 6. Do you feel nervous, tense, or worried? | 70.0 | 65.1 | 80.6* | 1.23 (1.01–1.50) | 1.26 (1.13–1.41) |
| 7. Is your digestion poor? | 18.0 | 16.7 | 20.9 | 1.25 (0.84–1.85) | 1.07 (0.73–1.55) |
| 8. Do you have trouble thinking clearly? | 46.5 | 45.0 | 49.7 | 1.10 (0.86–1.41) | 1.18 (0.98–1.43) |
| 9. Do you feel unhappy? | 53.8 | 52.3 | 57.1 | 1.09 (0.86–1.37) | 1.07 (0.91–1.26) |
| 10. Do you cry more than usual? | 37.4 | 35.8 | 40.8 | 1.13 (0.86–1.49) | 1.12 (0.91–1.38) |
| 11. Do you find it difficult to enjoy your daily activities? | 48.7 | 43.1 | 60.7* | 1.40 (1.11–1.78) | 1.48 (1.25–1.77) |
| 12. Do you find it difficult to make decisions? | 65.4 | 65.1 | 66.0 | 1.01 (0.82–1.25) | 0.98 (0.86–1.11) |
| 13. Is your daily work/study suffering? | 28.1 | 24.0 | 37,2* | 1.55 (1.14–2.10) | 1.56 (1.18–2.06) |
| 14. Are you unable to play a useful part in life? | 32.1 | 30.8 | 35.1 | 1.14 (0.84–1.53) | 1.24 (0.95–1.63) |
| 15. Have you lost interest in things? | 55.0 | 52.8 | 59.7 | 1.13 (0.90–1.42) | 1.13 (0.97–1.33) |
| 16. Do you feel you are a worthless person? | 37.3 | 38.3 | 35.1 | 0.91 (0.68–1.22) | 0.88 (0.69–1.12) |
| 17. Has the thought of ending your life been in your mind? | 25.3 | 27.6 | 20.4 | 0.73 (0.51–1.06) | 0.76 (0.54–1.07) |
| 18. Do you feel tired all the time? | 55.1 | 52.5 | 60.7 | 1.15 (0.92–1.44) | 1.09 (0.93–1.27) |
| 19. Are you easily tired? | 53.3 | 49.4 | 61.8* | 1.25 (1.00–1.56) | 1.21 (1.03–1.41) |
| 20. Do you have uncomfortable feelings in your stomach? | 32.8 | 31.0 | 36.6 | 1.18 (0.93–1.49) | 1.16 (0.91–1.49) |
- * p < 0.05 in chi-squared test; bold denotes significance at p < 0.05.
- PR, prevalence ratio; CI 95%, confidence interval of 95%. Multivariate analysis adjusted for age, sex, socioeconomic status, study shift, aggression, work, alcohol consumption, and tobacco use.
Table 3 shows the results of physical activity and sedentary behavior. In the whole sample, the prevalence of achieving the physical activity guidelines was 22%, while more than 2 hours/day of sedentary behavior ranged from 9.9% and 11.8% for sitting on a car or bus to 62.6% and 80.1% for internet use on week and weekend days respectively. A lower prevalence of physical activity was found in vocational students. However, the multivariate analysis indicated that the association was significant only for physical activity volumes of 300 (PR = 0.70) and 420 minutes/week (PR = 0.59). Vocational students also presented a significantly lower likelihood of reporting sedentary behavior >2 hours/day of watching TV (PR = 0.46) and playing videogames (PR = 0.35) on week days, and watching TV (PR = 0.73), sitting talking with friends (PR = 0.74), and sitting on a bus or car (PR = 0.44) on weekends. No association was found for active commuting (PR = 0.84).
| Course type | |||||
|---|---|---|---|---|---|
| All | General | Vocational | Crude PR (CI95%) | Adjusted PR (CI95%) | |
| Variable | % | % | % | Reference group: General course | |
| Physical activity (n = 631) | |||||
| MVPA 100 minutes/week | 42.5 | 45.2 | 36.5* | 0.80 (0.65–0.99) | 0.86 (0.69–1.06) |
| MVPA 200 minutes/week | 31.7 | 33.6 | 27.5 | 0.81 (0.62–1.06) | 0.85 (0.66–1.11) |
| MVPA 300 minutes/week | 26.3 | 29.5 | 19.5* | 0.66 (0.48–0.91) | 0.70 (0.51–0.97) |
| MVPA 420 minutes/week | 22.0 | 25.8 | 14.0* | 0.54 (0.37–0.79) | 0.59 (0.41–0.88) |
| Active commuting (30 minutes/day) | 19.6 | 21.4 | 15.7 | 0.72 (0.49–1.06) | 0.84 (0.55–1.27) |
| Sedentary behavior on week day (>2 hours/day) (n = 593) | |||||
| Watching TV | 16.7 | 20.4* | 8.9 | 0.43 (0.26–0.71) | 0.46 (0.27–0.80) |
| Playing electronic games | 17.0 | 21.6* | 7.3 | 0.33 (0.19–0.58) | 0.35 (0.21–0.61) |
| Internet use | 62.6 | 64.7 | 58.1 | 0.89 (0.78–1.03) | 0.88 (0.76–1.02) |
| Sitting doing work or homework | 29.8 | 29.9 | 29.8 | 1.00 (0.76–1.30) | 1.03 (0.78–1.37) |
| Sitting talking with friends | 58.0 | 59.7 | 54.5 | 0.91 (0.78–1.06) | 0.89 (0.75–1.04) |
| Sitting on bus or car | 9.9 | 9.7 | 10.5 | 1.07 (0.64–1.80) | 1.23 (0.68–2.23) |
| Sedentary behavior on weekend day (>2 hours/day) (n = 593) | |||||
| Watching TV | 28.8 | 31.6* | 23.0 | 0.72 (0.54–0.98) | 0.73 (0.53–0.99) |
| Playing electronic games | 31.4 | 32.6 | 28.8 | 0.88 (0.67–1.15) | 1.01 (0.77–1.32) |
| Internet use | 80.1 | 77.6 | 85.3* | 1.09 (1.01–1.19) | 1.07 (0.98–1.17) |
| Sitting doing work or homework | 26.1 | 24.1 | 30.4 | 1.25 (0.95–1.66) | 1.30 (0.96–1.77) |
| Sitting talking with friends | 38.8 | 43.3 | 29.3* | 0.67 (0.52–0.86) | 0.74 (0.57–0.96) |
| Sitting on bus or car | 11.8 | 14.4 | 6.3* | 0.43 (0.23–0.79) | 0.44 (0.23–0.87) |
- * P < .05 in chi-squared test.
- Bold denotes significance at P < .05. PR, prevalence ratio; CI 95%, confidence interval of 95%; MVPA, moderate to vigorous physical activity. Multivariate model for physical activity was adjusted for age, sex, socioeconomic status, study shift, work, and sedentary behavior. Multivariate model for sedentary behavior was adjusted for age, sex, socioeconomic status, work, and physical activity.
The results of food consumption, tobacco use, alcohol consumption, and experience of aggression are described in Table 4. In the whole sample, the prevalence of food consumption varied from 13.7 for cooked vegetables and greens to 68.5 for beans, 34% of adolescents experimented with tobacco, 31.8% reported binge drinking in the previous month, and 9.4% suffered some kind of aggression in the previous month. Vocational students presented a significantly lower PR for fried potatoes and snacks (PR = 0.56), and salted or sweet cookie consumption (PR = 0.59-0.72), and lower experiences of aggression from the family (PR = 0.13), aggression using a knife (PR = 0.17), or any type of aggression (PR = 0.14).
| Course type | |||||
|---|---|---|---|---|---|
| All | General | Vocational | Crude PR (CI95%) | Adjusted PR (CI95%) | |
| Variables | % | % | % | Reference group: General course | |
| Food consumption ≥5 day a week) (n = 622) | % | % | % | ||
| Raw salad | 29.4 | 28.0 | 32.5 | 1.16 (0.90–1.49) | 1.15 (0.87–1.51) |
| Cooked vegetables and greens | 13.7 | 13.3 | 14.5 | 1.09 (0.71–1.65) | 1.07 (0.68–1.68) |
| Dried or fruit salad | 16.7 | 16.8 | 16.5 | 0.98 (0.67–1.43) | 0.87 (0.58–1.30) |
| Beans | 68.5 | 68.2 | 69.0 | 1.01 (0.90–1.13) | 1.00 (0.88–1.13) |
| Milk or yogurt | 46.3 | 48.1 | 42.5 | 0.88 (0.73–1.06) | 0.82 (0.67–1.00) |
| Fried potatoes and snacks | 14.3 | 17.3* | 8.0 | 0.46 (0.27–0.77) | 0.56 (0.32–0.98) |
| Burgers and sausages | 19.3 | 22.5* | 12.5 | 0.55 (0.36–0.83) | 0.70 (0.45–1.09) |
| Salted cookies and crackers | 28.1 | 32.5* | 18.5 | 0.56 (0.40–0.78) | 0.59 (0.42–0.83) |
| Sweet cookies and crackers | 35.2 | 38.6* | 28.0 | 0.72 (0.56–0.93) | 0.72 (0.55–0.95) |
| Soft drinks | 27.2 | 30.1* | 21.0 | 0.69 (0.51–0.95) | 0.81 (0.58–1.12) |
| Tobacco (n = 632) and alcohol use (n = 650) | |||||
| Tobacco experimentation | 34.0 | 38.1* | 25.0 | 0.58 (0.42–0.79) | 0.77 (0.57–1.05) |
| Current smoker (previous month)† | 28.5 | 32.7* | 19.1 | 0.65 (0.50–0.85) | 0.86 (0.66–1.12) |
| Alcohol consumption (≥2 times in a month) | 24.7 | 28.2* | 16.6 | 0.58 (0.41–0.83) | 0.82 (0.58–1.16) |
| Binge drinking‡ | 31.8 | 35.3* | 23.8 | 0.67 (0.51–0.89) | 0.87 (0.66–1.15) |
| Aggression experience (n = 650) | |||||
| Aggression from family | 6.6 | 8.8* | 2.0 | 0.22 (0.08–0.62) | 0.13 (0.03–0.57) |
| Aggression using knife | 1.5 | 2.0* | 0.5 | 0.11 (0.02–0.85) | 0.17 (0.02–1.43) |
| Aggression using gun | 3.1 | 4.3* | 0.5 | 0.24 (0.03–1.91) | 0.28 (0.10–1.56) |
| Any type of aggression | 9.4 | 12.4* | 2.9 | 0.23 (0.10–0.54) | 0.14 (0.04–0.46) |
- * P < .05 in chi-squared test.
- Bold denotes significance at P < 0.05. PR, prevalence ratio; CI95%, confidence interval of 95%. Multivariate models for food consumption adjusted for age, sex, socioeconomic status, study shift, and work. Models for alcohol consumption were adjusted for age, sex, socioeconomic status, study shift, aggression, common mental disorders, and tobacco use; the same variables were used for tobacco use, except for the inclusion of alcohol consumption instead of tobacco use; Models for aggression were adjusted for age, sex, socioeconomic status, study shift, alcohol, tobacco, and common mental disorders.
- † Any amount of tobacco in previous month.
- ‡ More than 6 doses at once in previous month.
The prevalence of sleep disturbance varied according to the cut-off adopted (12.8-54.8%), while musculoskeletal symptoms ranged from 11.1% for elbows to 49.7% for low back regions. Higher PRs for sleep disturbance were found in vocational students, independent of the cut-off adopted (PR = 1.39-1.71). The same was described for musculoskeletal symptoms in the neck (PR = 1.31), shoulders (PR = 1.36), low back (PR = 1.41), and knees (PR = 1.31), Table 5.
| Course type | |||||
|---|---|---|---|---|---|
| All | General | Vocational | Crude PR (CI95%) | Adjusted PR (CI95%) | |
| Variables | % | % | % | Reference group: General course | |
| Daytime sleepiness (n = 650) | |||||
| Percentile 50 | 54.8 | 48.1 | 69.4* | 1.44 (1.26–1.64) | 1.39 (1.21–1.59) |
| Percentile 60 | 41.4 | 35.3 | 54.9* | 1.55 (1.30–1.85) | 1.48 (1.23–1.79) |
| Percentile 70 | 34.2 | 27.3 | 49.5* | 1.81 (1.47–2.22) | 1.71 (1.37–2.14) |
| Percentile 80 | 23.6 | 19.1 | 33.5* | 1.75 (1.33–2.30) | 1.59 (1.19–2.11) |
| Percentile 90 | 12.8 | 10.2 | 18.4* | 1.81 (1.21–2.69) | 1.58 (1.04–2.42) |
| Musculoskeletal symptoms† (n = 622) | |||||
| Neck | 45.2 | 42.1 | 52.1* | 1.23 (1.03–1.47) | 1.31 (1.07–1.60) |
| Shoulders | 34.6 | 31.2 | 42.2* | 1.35 (1.08–1.68) | 1.36 (1.07–1.72) |
| Upper back | 43.6 | 42.3 | 46.4 | 1.09 (0.90–1.32) | 1.12 (0.91–1.37) |
| Elbows | 11.1 | 11.6 | 9.9 | 0.85 (0.51–1.40) | 0.87 (0.51–1.51) |
| Wrists/hands | 42.3 | 43.0 | 40.6 | 0.94 (0.77–1.15) | 0.93 (0.75–1.16) |
| Low back | 49.7 | 43.7 | 63.0* | 1.44 (1.23–1.67) | 1.41 (1.19–1.67) |
| Hip/thighs | 33.4 | 34.4 | 31.3 | 0.90 (0.71–1.16) | 0.92 (0.70–1.20) |
| Knees | 36.0 | 34.2 | 40.1 | 1.17 (0.94–1.45) | 1.31 (1.02–1.67) |
| Ankles | 41.2 | 42.3 | 38.5 | 0.91 (0.73–1.12) | 0.88 (0.69–1.11) |
- * P < .05 in chi-squared test.
- Bold denotes significance at P < .05; PR, prevalence ratio; CI95%, confidence interval of 95%. Multivariate models for daytime sleepiness were adjusted for age, sex, socioeconomic status, study shift, and sedentary behavior (TV, internet, and game). Models for musculoskeletal symptoms were adjusted for age, sex, socioeconomic status, study shift, and sedentary behavior (TV, internet, game, and sitting time).
- † Musculoskeletal symptom in previous month.
DISCUSSION
The aim of the present study was to assess the association between course type and health characteristics among Brazilian high school students. The main finding was that vocational students presented a higher prevalence of mental health disorder symptoms, musculoskeletal symptoms in the neck, shoulder, and low back, daytime sleepiness, and lower leisure physical activity, however a better profile was found for ultra-processed food consumption, sedentary behavior, and aggression experience.
Vocational students presented a higher prevalence ratios in 7 of the 20 mental disorder symptoms analyzed. Mental health during adolescence has a complex multifactorial etiology.4 In addition to the already known determinants of mental health, the positive association between vocational education and mental health symptoms could be attributed to higher school responsibilities such as higher class workload, a larger number of disciplines, homework, exams, and projects for course conclusion. In Brazil, high school vocational students study for the vocational course plus academic formation of general education, which results in a double academic workload, and this characteristic can increase the risk for mental disorders.11 Curiously, previous research with a sample of Finnish students demonstrated that general academic students presented a greater risk of exhaustion than those on vocational courses which became more pronounced at 18 years of age, as a consequence of high academic demand due to the examination at the end of high school,34 which is not a target for vocational students. Country differences regarding education characteristics can explain the differences between the present results and previous studies.11, 34 The vocational students analyzed were from a Federal school that has an admission exam due to the limited number of vacancies, and provides formation both for technical work and to continue studying in College (double graduation). In Brazil, there are vocational courses with a short length for students that are only interested in technical formation, but the present sample was composed of students enrolled in courses that have a full-time requirement for 3 years during high school. In Brazil, College Education can lead to higher wages and professional value in the future, so most students choose to enter university after completing vocational high school. This process demands high engagement from students because they have 2 objectives at the end of high school: to be approved for admission exams in a University and complete their vocational education by presenting a final innovative project, in addition to passing all disciplines. The present results highlight possible mental health risks that can emerge from a full-time vocational curriculum during high school.
The prevalence of moderate to vigorous leisure time physical activity and active commuting was lower in vocational students for all volumes analyzed, but the significant association in the multivariate analysis occurred only for 300 minutes/week and the current guidelines (420 minutes/week). A wide range of variables can impact the practice of physical activity35; however, for these students the lack of free time is an important variable. This can be reinforced by the fact that the significant association occurred only in the higher volumes analyzed. Physical activity was analyzed considering leisure time and for the vocational students analyzed, the only period that they are out of school is the evening (after 6 pm). In this period, in addition to tiredness there are overlapping activities such as going home, having dinner, taking a shower, doing their homework, having some free time for activities or work, and sleeping. In view of this, common barriers to physical activity related by adolescents such as laziness, lack of time, low motivation, and preference for other activities36 probably have a higher impact in these students. Another aspect that should be considered is that students on the general course presented a higher physical activity prevalence (25.8%) compared to adolescents worldwide (21.2%)3 and vocational students were less active (14.0%) than the general population. Since vocational students stay at school for approximately 9 hours a day, participation and expansion of the volume of physical education classes could be an important strategy to compensate the low amount of physical activity in leisure time due to its positive effect on motor experiences, daily physical activity, and health promotion.37
Conversely to physical activity, vocational students presented significantly lower prevalence ratios for sedentary behavior considering TV viewing and playing videogames during the week. Probably, the same aspects that make it difficult to practice physical activity could protect these adolescents from excessive sedentary behavior in these contexts. A compensatory effect was also observed, with an increase in weekend sedentary behavior (almost 4-fold for videogame and 3-fold for TV viewing in comparison with the weekdays). Although it was not associated with type of high school course, both groups of students presented a high prevalence of sedentary behavior in the other contexts. The association between sedentary behavior and health is still controversial, because for mental health, higher TV viewing is associated with behavior and emotional problems but not with depression or suicide risk.38 However, recent current recommendations suggest that children and adolescents should limit their sedentary time, particularly the amount of recreational screen time, due to its detrimental effect on fitness and cardiometabolic health, adiposity, behavioral conduct/pro-social behavior, and sleep duration.22
Musculoskeletal symptoms in the neck, shoulder, low back, and knees are another health risk associated with vocational education. Students of vocational education who participated in this study were enrolled in technological courses such as industrial automation and computer networks, which expose them to many hours in laboratories using computers or machines. This results in prolonged periods in a static position, not always with the correct posture, which can affect the neck, shoulder, low back, knees, and consequently the emergence of musculoskeletal symptoms.5 In addition to laboratory activities, all other activities (except physical education) are performed in classrooms that also expose students to sitting in a static position while watching classes. Due to the higher number of disciplines, more materials are also required, transported in heavy schoolbags, which can affect musculoskeletal health.5 Although the routine of students in schools may explain the higher prevalence of musculoskeletal symptoms in vocational students, it is relevant to state that general education students also present a high prevalence of musculoskeletal symptoms (11.6-43.7%), which, in addition to their individual characteristics and school routine, can be attributed to other risk factors including sedentary behavior.5 In the present sample, the high prevalence of musculoskeletal symptoms in the wrists/hands (42.3%) and upper back (43.6%) could also be attributed to high internet use with electronic devices39 and sitting time doing homework or with friends, which were highly prevalent behaviors, as presented in Table 3.
The indicator of sleep quality used in the present study was excessive daytime sleepiness, that is, an increased sensation of sleepiness and decreased alertness.24 The results showed that independently of the cut-off adopted, vocational students presented a higher PR of daytime sleepiness compared to general students. Some aspects that were extensively described in this discussion could explain these associations. First, One symptom of mental disorders that presented a positive association in vocational students was bad sleep behavior, indicating that these students have poor night sleep, which, consequently, influences daytime sleepiness the next day. Second, vocational students have full-time classes during the week, so they need to wake up early and do not have the possibility of extra sleep or the opportunity and infrastructure to rest between classes. For this reason, delaying the school start time has been proposed as a policy change to address insufficient sleep among adolescents.40 It is important to state that there is a wide range of factors that affect sleepiness, such as biological, health-related, environmental, and lifestyle variables.6 In this sense, the higher volume of homework, tests, and poor mental health can also affect sleep behavior of vocational students compared to general students.6
One covariate that could contribute to the present findings is work status. Employment during adolescence is widely discussed and can imply both beneficial and harmful influences on youth development, depending on several aspects. Teachers, counselors, coaches, and parents should be aware of youth and parents beliefs, workplace conditions, safety, choices of the young person, particular experiences while working, such as the quantity and quality of work, as well as adolescents' social backgrounds, academic promise, link between work and school, motivations to work, and future expectations.41 The prevalence of work was higher in the general students (35.3% vs. 15.6%) which could be due to the vocational students remaining at school for 9 hours a day, making formal work a little unfeasible. This characteristic indicates that vocational students may be more engaged in informal work because they are not available during business hours, exposing them to inappropriate conditions, often through obligation, which is a risk generally downplayed by parents.42 As a result, they have reduced leisure time, hours of rest, sleep, and extra-school study. This hypothesis can be supported by some findings of the present study such as a higher likelihood of difficulty enjoying daily activities, suffering during daily working or study, daytime sleepiness, and low physical activity in leisure time among vocational students.
Three other health behaviors analyzed were tobacco use, alcohol consumption, and experience of aggression. For all of these, a lower prevalence was found for vocational students. However, in the multivariate analysis, only experience of aggression remained significantly associated with course type. Conversely to the results of the present study, recent information described a higher prevalence of smoking in apprentices compared to high school students,43 which can be explained by curricular characteristics. Differently to our study, where vocational students are enrolled only in schools, apprentices have different assignments and are at the same time students and employees, often in manual employment, and have regular contact with an older and professional environment and receive a salary.43 It is not possible to know if the same occurs with cigarillos, filtered cigars, pipe tobacco, hookah, snus pouches, smokeless tobacco (loose snus, moist snuff, dip, spit, or chewing tobacco), and dissolvable tobacco,44 as other types of tobacco exposure among adolescents were not assessed in the present study. With regard to aggression, mechanisms such as personal factors, peers, family environment, and school context are associated with this behavior.7, 45 Previous studies indicated that parental support has an important role in the pro-social behavior of children and during adolescence both family and peers have a relevant influence.45 Furthermore, school belonging also has an important role in mitigating possible transference of violence from family to school.7 Considering this information, it can be speculated that in the sample analyzed vocational students could have a better family environment of affect, support, and communication, as well as peer attachment. Since vocational students stay at school 2 shifts a day, they may be more protected from parents and peer aggression and have a better sense of belonging.
Food consumption of 11 food types was analyzed and a lower prevalence of consumption of fried potatoes and snacks, and salted and sweet cookies was found in vocational students. All food consumption variables that presented significant associations are classified as ultra-processed food, which do not have a minimum safe recommended intake due to health risks associated with their consumption.10 A previous study demonstrated that students who have a high number of meals at school presented lower consumption of ultra-processed food and higher consumption of fresh and minimally processed food.8 This could explain in part the associations found, since vocational students remain at school full-time and have 3 meals, while general students have only 1. Another aspect is that general education students could consume more ultra-processed foods due to the absence of supervision for a longer period during leisure time. A low prevalence of raw or cooked vegetables was found in the whole sample and is in line with the literature.9 Efforts to promote vegetable and fruit consumption by schools are not sufficient to change this situation, probably because these types of food are not included in the preferences of adolescents and for this reason are not a priority in their diet.46
Limitations
Both general and vocational education are highly influenced by the cultural context and curricular standards across countries, which means that other courses may not be associated with students' health to the same extent as in the present study. The findings of the present study are generalizable mainly for Brazil and countries with a similar educational system. The sample of vocational students was composed of adolescents enrolled in 3-year full-time courses and health characteristics of students enrolled in shorter length vocational courses could also be different. The instrument used to measure food consumption prevented assessment of how the pattern may differ between groups on weekend versus weekdays and the instrument adopted to assess tobacco use refers only to cigarettes and not to other varieties of substance use.44 A second day of data collection was included for students who were absent from school on the first day scheduled to ensure the chance of all students participating in the study, and the lack of information on how many students completed data collection on each day is a limitation. However, it is probable the results were not affected by the “healthy student effect,” similar to what occurs with the healthy worker effect phenomenon,47 due to the following methodological procedures: the sample of students was drawn from the same population, most outcomes assess the previous 30 days or a general week, and no variables were based on a 24-hour recall, which encompasses characteristics of sick days. Multivariate models prevented possible distortions of associations due to an external variable (i.e. work or co morbidity). Finally, the cross-sectional design adopted prevented tests of causality or the direction of relationships between variables; however, we conducted analysis considering a conceptual model of causality in which the course/school can affect student health. The strengths of the study include the probabilistic sample, instruments with adequate psychometric properties, and multivariate analysis adjusted for potential confounders and the main health risks regarding adolescent students.
CONCLUSIONS
This cross-sectional study, conducted in 2019, focusing on how course type can be associated with several health indicators among a Brazilian sample of high school students, revealed that vocational students presented a higher likelihood of mental health symptoms, physical inactivity, excessive daytime sleepiness, and musculoskeletal symptoms. Conversely, higher prevalence of sedentary behavior in TV viewing and playing videogames, greater ultra-processed food consumption, and experiences of aggression were found for general students. Intervention programs and health monitoring should be specific, since course type can affect the health of high school students in different ways. Future studies should investigate mechanisms underlying the associations described, as well as exploring different sociocultural contexts.
Implications for School Health
The present study demonstrated that the associations between type of high school course and health are dependent on the outcome among this sample of Brazilian high school students. For this reason, health interventions focusing on the individual, family, and school should be specific according to high school course type and consider that most of the implications that emerged from the present study can be applied in Brazilian schools and countries with similar educational characteristics
Schools that offer full-time vocational education, with similar curriculum and educational characteristics to those analyzed in this study, should be aware that students can present a lower prevalence of physical activity, and a higher prevalence of mental health disorder symptoms, daytime sleepiness, and musculoskeletal symptoms. The implementation of health programs aimed to prevent these health risks at school include: (a) Physical activity promotion through physical education classes and an active school environment; (b) Periodic screening and mental health support, in addition to continuous reviews of school curricula regarding workload, and bringing the courses closer to the students' expectations; (c) Ergonomic education and adequate furniture use to prevent musculoskeletal symptoms; (d) Support for organization of daily tasks and provision of sleep education in order to ensure adequate sleep hygiene.
Concerning students from general education, although it is also relevant to promote a healthy school environment through formal curriculum and extra-curricular activities, autonomy should be promoted for health behavior decisions since students are out of school most of the day and commonly not entirely supervised by their parents. In view of this, health education programs can provide information for students and parents regarding risks and how to prevent high sedentary behavior in leisure time and ultra-processed food consumption. Furthermore, the encouragement and promotion of extracurricular activities at school can also mitigate health risk behavior, mainly in students with high social vulnerability.
Independent of course type, schools can consider some strategies to implement prevention programs against aggression and promote a sense of belonging in students, including: (a) assistance for students by multidisciplinary school staff; (b) promotion of a positive relationship between staff and students; (c) positive peer relationships, with periodic group meetings, implementation of rigid policies regarding prevention of bullying and to promote inclusion, friendship, and peer support; (d) parental support and involvement; (e) school environment, with adequate recreational and social spaces, positive classroom climate, sense of safety, and fairness of school policies.
Human Subjects Approval Statement
The present study was approved by the local Ethics Research Committee of the Federal Institute of Education, Science and Technology of São Paulo, São Paulo, Brazil, protocol 3.193.081. All participants and their parents signed an informed assent and consent form respectively.
Conflict of Interest
The authors declare no conflict of interest.
