1. Introduction
Adolescence is a pivotal stage in human development, characterized by profound physical, emotional, and social changes that significantly influence the health and well-being of young people. During this period, adolescents face challenges related to identity construction and social integration, which directly impact their self-perceived health, mood, and behaviors related to substance use. The perception that adolescents have of their own health, as well as their emotional well-being, is closely linked to the adoption of risky behaviors, such as the use of alcohol, tobacco, and other drugs [
1]. During adolescence, vulnerability to adopting risky behaviors increases significantly, including the use of toxic substances, disturbances in sleep patterns, and the abuse of digital technologies [
2]. These habits, which often emerge during this stage, can have a significant impact on the overall health and well-being of young people, both in the short and long term. Studies indicate that the use of alcohol, tobacco, and cannabis is alarmingly prevalent among adolescents [
3]. In Spain, for instance, 77% of adolescents aged 14 to 18 have tried alcohol, 30% have used cannabis, and 24% have smoked tobacco. Early initiation of these habits is associated with a higher risk of developing substance use disorders in adulthood, and gender differences also play an important role in consumption patterns [
4].
Mental health problems, such as anxiety and depression, are prevalent during adolescence and are often related to low self-perceived health and negative mood. These factors are also influenced by inadequate sleep patterns, which are common during this stage and are linked to both substance use and excessive use of digital technologies [
5]. According to the Health Behavior in School-Aged Children (HBSC) study [
6], more than 40% of Spanish adolescents aged 14 to 17 do not meet the recommended minimum of 8 hours of sleep per day. This sleep deprivation affects academic performance, increases the risk of emotional disorders, and is associated with greater substance use.
Dietary habits, particularly breakfast consumption, play a crucial role in adolescent health and development [
7]. Skipping breakfast or consuming inadequate meals, whether before leaving home or mid-morning during school hours, is associated with poorer academic performance, decreased concentration, and increased susceptibility to risky behaviors. Breakfast consumption impacts physical growth, cognitive development, and emotional stability, highlighting its importance in this critical life stage. Adolescents who maintain consistent breakfast habits are more likely to exhibit better attention spans, higher energy levels, and improved emotional regulation, whereas irregular habits can contribute to long-term health challenges [
8,
9].
Moreover, the abuse of digital technologies has increased sedentary behavior and contributed to disturbances in sleep patterns [
10]. According to the National Health Survey (2020), 80% of young people aged 15 to 19 in Spain use digital technologies in their leisure time, averaging 6.8 hours per day, primarily on social media and video games. This excessive use of electronic devices negatively impacts sleep, also affecting the physical and mental health of adolescents [
11].
Understanding these interconnected habits and behaviors—dietary patterns, substance use, sleep quality, and digital technology engagement—enables the implementation of comprehensive public health strategies aimed at improving adolescent health [
12]. Community health initiatives, in particular, offer a platform for addressing these challenges in a holistic manner. By incorporating schools, local governments, primary care centers, and community organizations, these strategies can foster environments that promote healthier behaviors and create a supportive ecosystem for adolescents [
13].
Public health interventions should focus on promoting balanced nutrition, reducing risky behaviors, and encouraging physical and emotional well-being. Municipal governments have a critical role in fostering collaborations between educational institutions, families, and healthcare providers to design and implement health promotion programs. These initiatives should consider the specific needs of the community, address socio-economic disparities, and account for gender differences to maximize their impact. For instance, interventions aimed at encouraging regular breakfast consumption could integrate school-based nutrition programs that provide accessible and balanced meals [
14].
This article focuses on analyzing self-perceived health, mood, sleep patterns, substance use, dietary habits, and leisure activities among adolescents, as well as proposing municipal strategies that promote overall well-being. By exploring these dimensions together, the aim is to contribute to the development of effective interventions that enhance the quality of life of adolescents and strengthen the role of community and public health efforts in supporting youth development.
2. Methodology
2.1. Study Design
This study employed a cross-sectional descriptive design with a quantitative approach, conducted in a municipality in the province of Barcelona during the 2023-2024 academic year. The study focuses on analyzing self-perceived health, mood, sleep patterns, substance use, dietary habits, and leisure activities among adolescents, as well as proposing municipal strategies that promote overall well-being, and leisure activities among Spanish adolescents aged 14 to 17, with particular attention to 4th-year ESO students. Additionally, it aims to propose municipal strategies that promote overall well-being, contributing to the development of effective interventions that improve adolescents' quality of life and strengthen the role of the community and family in supporting youth health.
2.2. Study Population
The study population consisted of 120 4th-year ESO students from the selected school. Participants completed an online questionnaire individually and anonymously during class hours, following the acquisition of informed consent from their legal guardians. Participation was entirely voluntary, and data were collected confidentially, ensuring that all information was used exclusively in aggregated form to preserve participants' privacy.
Of the 4th-year ESO students invited to participate, 86.3% completed the survey, representing a final sample of 120 students. This response rate reflects a high level of commitment and collaboration from the students, which adds robustness to the study results.
2.3. Ethical Procedures
This study was conducted in accordance with the ethical guidelines set forth in the Declaration of Helsinki . Informed consent was obtained from the legal guardians to ensure the voluntary, anonymous, and confidential participation of the students. The study was approved by the Ethics Committee of the educational institution and the Public Health Service of the municipal government, with approval number SP:23/002 (September 19, 2023). Each participant provided written informed consent.
2.4. Data Collection Instruments
An online questionnaire consisting of 76 validated questions, categorized into various health-related domains, was used for this study. The questionnaire covered topics such as substance use, sleep patterns, and leisure activities. The aim of the study is to analyze the relationship between substance use, sleep patterns, and leisure activities among Spanish adolescents aged 14 to 17, with particular attention to 4th-year ESO students, identify risk factors, compare behaviors and risks, monitor these behaviors, and assess the impact of these habits on their health.
2.5. Data Collection Procedure
The survey was distributed electronically to students during class hours. Data collection took place between November 2023 and February 2024.
2.6. Statistical Analysis
Descriptive statistics, including frequencies, percentages, means, and standard deviations (SD), were calculated. Pearson’s chi-square test was employed to compare groups and assess associations between demographic characteristics, knowledge, attitudes, and practices related to substance use, sleep patterns, and leisure activities. A p-value of < 0.05 was considered statistically significant. All analyses were performed using R statistical software (R Project for Statistical Computing).
3. Results
Sample Description
The sample comprised 120 students from 4th year of Secondary Education (4th ESO) at a public high school in a town in the province of Barcelona, aged between 14 and 18 years. The average age was 15.2 years, with a gender distribution of 57.3% female and 42.7% male. Most students were native (71.8%), with 3.2% being first-generation immigrants, 16.9% second-generation immigrants, and 8.1% who did not specify their background.
Regarding family structure, 71% had a biparental family, 24.2% had a single-parent family, and 3.2% had a restructured family. Socioeconomic status was classified as high for 63.7%, medium for 29.8%, and low for 6.5%.
The educational levels of the parents showed that most had secondary education (39.1%) or university degrees (28.2%). A small percentage had no formal education (5.6%), primary education (8.5%), and 18.6% did not specify or were unsure.
The distribution of self-perceived health by gender showed no significant differences in the categories "very good" (p = 0.620), "good" (p = 0.879), or "poor/very poor" (p = 0.723). However, women were more likely to report "fair" health (15.9%) compared to men (7.8%), with a p-value approaching statistical significance (p = 0.095).
The mood state distribution shows significant differences between boys and girls, as indicated in
Table 1, with a global chi-square value of 6.46 and a global p-value of 0.0395. However, when analyzing individual categories, none reached statistical significance, as all p-values exceeded 0.05. Additionally, a high positive correlation (r = 0.77) was observed between the frequencies of boys and girls across mood categories. Nevertheless, this correlation was not statistically significant (p = 0.436).
The average sleep duration was similar between boys (7.45 hours) and girls (7.60 hours). In
Table 2, statistical analyses revealed no significant differences across most sleep categories, with individual p-values exceeding 0.05. However, the 8.5-hour category showed a significant difference (p = 0.0090), supported by a higher chi-square value. The global chi-square analysis (p = 0.110) confirmed the absence of significant overall differences in sleep patterns between genders. These findings suggest that sleep patterns are largely comparable between genders, despite minor variations and one significant category that may warrant further investigation.
In
Table 3: Gender Differences in the Prevalence of Addictive Substance Use (Including Tobacco) and Alcohol Among Youth highlights significant differences in substance use between boys and girls. Marijuana use is higher among girls (23.2%) compared to boys (13.7%), with a statistically significant difference (p=0.029). Regarding alcohol, 82.6% of girls reported having consumed it at least once, compared to 56.9% of boys (p=0.003), with consumption during class days reported only by girls (37% girls, 0% boys, p<0.001). For smoking, 42.15% of girls have smoked at least once compared to 19.83% of boys (p<0.001). While the use of tranquilizers and other substances is higher among girls, these differences are not statistically significant. These findings underscore gender-specific patterns that require targeted interventions to prevent substance use.
In
Table 4: Gender Differences in Physical Activity Among Adolescents, it is observed that while the proportion of boys and girls engaging in physical activity is similar (15.7% vs. 17.4%, p=0.042), a higher percentage of girls (17.4%) do not participate in sports or physical activities compared to boys (11.8%). This statistically significant difference highlights the need for targeted strategies to promote physical activity among girls, addressing potential social, cultural, or accessibility barriers that may be limiting their participation.
In
Table 5: Gender Differences in Night Out Frequency and Return Times Among Adolescents, it is observed that the proportions of boys and girls engaging in night outings are generally similar across most categories, with no statistically significant differences (p=1.000). However, notable trends can be identified: a higher proportion of both boys and girls (29.0%) report never going out at night, while a smaller percentage (7.3%) go out more than twice a week. Regarding return times, the majority of participants return home before midnight or between midnight and 2 AM (29.8%), with negligible differences between genders. These findings suggest that night outing behaviors are relatively uniform across genders, highlighting the need for interventions that address general adolescent safety and well-being during night outings rather than focusing on gender-specific behaviors.
Table 6 shows that boys are more likely to eat breakfast every day before leaving home (54.9% vs. 47.8%), while girls are more inclined to skip breakfast entirely (33.3% vs. 21.6%). Similarly, boys exhibit a higher tendency to skip mid-morning breakfast compared to girls. However, the differences in breakfast habits between boys and girls, both before leaving home (p=0.2968) and mid-morning (p=0.1398), are not statistically significant. These findings underscore the importance of promoting consistent and healthy breakfast routines across both genders to support better nutritional habits and overall well-being.
4. Discussion
The results of this study provide important data on adolescent health, behavior and lifestyle patterns, revealing significant differences between genders and areas requiring intervention. It examines the prevalence of substance use, physical activity, sleep patterns and leisure activities among adolescents, offering critical insights into gender-specific differences and broader behavioral trends. The results contribute to a comprehensive understanding of these behaviors and their implications for health promotion strategies.
The most striking finding is the higher prevalence of substance use among adolescent girls. Girls show significantly higher rates of marijuana (23.2% vs. 13.7%, p=0.029), alcohol (82.6% vs. 56.9%, p=0.003) and tobacco (42.15% vs. 19.83%, p<0.001) use compared to boys. This contrasts with previous studies that have traditionally reported higher rates of use in adolescent boys[
15].This shift in consumption patterns may reflect changing social norms and peer pressures specifically affecting adolescent girls. Further research is needed to understand the factors underlying this trend and to develop preventive interventions specifically targeting girls.
The most common substance uses in childhood and adolescence have to do with alcohol and cannabis. Despite alcohol use declined along with that of tobacco, alcohol remains by far the most psychoactive substance used by adolescents. More than one-third of adolescents' report having used alcohol in the past 30 days, while 9% report having used it at least once per week in the past year. Most adolescents have their first experiences with tobacco and alcohol between the ages of 13 and 15. In this study, Girls exhibit significantly higher rates of alcohol, even drinking alcohol during class days, and tobacco use compared to boys. This finding aligns with previous research, indicating a shift in consumption patterns influenced by evolving social norms and peer pressures [
16].
School-based activity should highlight the importance of the developmental perspective when designing and delivering school-based prevention programs, as heavy cannabis use impairs memory, learning, recall, attention, problem solving, reasoning skills and intelligence. Experimental studies suggest that the epigenetic effects of cannabinoids may impair myelination of the pubertal brain [
17]. In this study, higher substance use in girls underlines the need for targeted prevention campaigns, integrating gender-sensitive approaches to address specific vulnerabilities
The disparity in physical activity levels, where 17.4% of girls report inactivity compared to 11.8% of boys, reflects persistent barriers to participation among girls. These barriers may include cultural norms, reduced access to sports programs, or social perceptions of athletic participation. Encouraging inclusive physical activity initiatives is critical to bridging this gap and fostering long-term health benefits for all adolescents. The World Health Organization emphasizes that physical activity of any intensity, including light physical activity, is fundamental in transitioning from sedentary behavior to an active lifestyle, resulting in health benefit [
18]. Light physical activity could thus serve as a gateway to more intense activities. However, recommendations for moderate to vigorous physical activity should be made to achieve more significant metabolic impacts on adolescent health. Addressing the decline in physical activity and participation among adolescent girls has become a public health priority. The "Girls in Sport" initiative, a multi-component school intervention implemented in urban, regional, and rural areas of New South Wales, Australia, exemplifies efforts to tackle this issue [
19]. With a sample of 1,769 participants, the intervention aimed to promote physical activity among adolescent girls. However, the results were not as favorable as anticipated, primarily due to implementation challenges in most participating schools. Only 4 out of 12 schools achieved the set objectives, highlighting the crucial role of effective intervention presentation and school commitment in ensuring program success. This underscores the complexity of implementing physical activity interventions and the need for comprehensive strategies that address not only individual barriers but also institutional and systemic challenges in promoting adolescent girls' participation in physical activities.
Adolescence is a period of life characterized by biopsychosocial, cognitive, and behavioral changes that affect individuals throughout their lives. Among these changes, a notable alteration in the sleep-wake cycle can be observed, with a predisposition toward a later cycle, leading to a delay in the circadian rhythm, along with a reduction in sleep quality and total sleep duration. Although overall sleep duration is similar between genders (7.45 hours for boys and 7.60 hours for girls), a significant variation is observed in the 8.5-hour sleep category (p=0.0090). This suggests the existence of a subgroup of adolescents experiencing specific challenges. The literature has shown that most adolescents fail to meet public health recommendations, which include at least 60 minutes of moderate to vigorous physical activity, between eight and 10 hours of sleep, and a maximum of two hours of screen time per day. While total sleep duration shows minimal differences between genders, the significant variation in the 8.5-hour sleep category further supports the existence of a possible subgroup of adolescents facing unique challenges, possibly related to digital technology use or academic [
20,
21].
School systems provide opportunities for influencing dietary intake as well as for educating future generations on diet and nutrition.
The importance of nutrition, the short- and long-term consequences of inadequate nutrition, and the current global status of nutrition must be one of the major focusses of attention in the school age years [
22]. In this study, although not statistically significant, a gender difference is observed: boys tend to have breakfast more regularly before leaving home (54.9% vs. 47.8% of girls), while girls are more likely to skip breakfast entirely (33.3% vs. 21.6% of boys). Milosavljević study’ point that breakfast skipping is an often-dietary habit in adolescents because of overweight. Overweight is more frequent in boys and underweight is worrying for the matter of eating disorders girls [
23].
The habit of eating few meals a day or not knowing what to eat for breakfast is a public health issue driven by various factors: students from families with low educational levels, attending subsidized schools, repeating grades, lacking reading habits, or spending significant time with friends, among others, may contribute to these challenges [
24].
Adolescents are the group of people most prone to addiction. School activity should highlight the importance of developmental perspective when designing and offering school-based prevention programs. Intense cannabis use impairs memory, learning, recall, attention, problem solving, reasoning ability, and intelligence. Experimental studies suggest that the epigenetic effects of cannabinoids can impair myelination of the pubertal brain [
25]. In this study, higher substance use in girls underscores the necessity of targeted prevention campaigns, integrating gender-sensitive approaches to address specific vulnerabilities.
5. Conclusions
This study highlights the importance of designing public health strategies with gender-sensitive approaches to address the social and environmental determinants that influence adolescent health behaviors. Key priorities include substance use prevention through programs that consider gender differences and associated social and psychological factors, as well as the promotion of physical activity by addressing cultural barriers, facilitating access, and fostering inclusive participation from early ages with the support of educational institutions.Additionally, the study emphasizes the need for sleep hygiene education through programs that underline the importance of adequate rest and responsible use of digital technologies, alongside the promotion of healthy eating habits, such as adopting balanced breakfasts and providing nutritious options in schools. These comprehensive interventions, implemented from early childhood, aim to address the intersection of substance use, physical inactivity, sleep disturbances, and dietary habits, creating environments that promote physical, emotional, and social well-being throughout developmental stages.
Author Contributions
Conceptualization, methodology, and formal analysis, Zafra-Agea, José Antonio; formal investigation, all authors; data curation, Zafra-Agea, José Antonio; writing: preparation of the original draft and final writing, all authors. All authors have read and approved the published version of the manuscript.
Funding
This research did not receive external funding.
Institutional Review Board Statement
The study was approved by the Ethics Committee of the educational institution and the Public Health Service of the Municipal Government, with approval number SP:23/002 (September 19, 2023). Each participant signed a written informed consent.
Informed consent statement
Informed consent was obtained from all subjects involved in the study. Written informed consent was signed by the parents or legal guardians of the students, in addition to the municipal public health service of the municipality.
Data availability statement
The data presented in this study are available upon request from the corresponding author.
Conflicts of interest
The authors declare that they have no conflicts of interest.
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Table 1.
Mood State Distribution by Gender with Chi-Square Values and Correlation.
Table 1.
Mood State Distribution by Gender with Chi-Square Values and Correlation.
| Mood State |
Boys (N=51) |
Girls (N=69) |
Total |
P-value |
χ² |
| Positive |
33 (64.7%) |
30 (43.0%) |
63 (52.5%) |
0.1000 |
6.46 |
| Negative |
18 (35.3%) |
38 (55.1%) |
56 (46.7%) |
0.1294 |
6.46 |
| NS/NC |
0 (0.0%) |
2 (2.9%) |
2 (1.7%) |
0.2274 |
6.46 |
| Global |
|
|
|
0.0395 |
6.46 |
| Correlation (r) |
|
|
|
0.436 |
0.77 |
Table 2.
Table of Sleep Hours Distribution.
Table 2.
Table of Sleep Hours Distribution.
| Hours of Sleep |
Boys (N=51) |
Girls (N=69) |
Total |
P-value |
| <6 h |
4 (7,8%) |
8 (11,8%) |
12 (10.0%) |
0.5050 |
| 6h |
5 (9,8%) |
8 (11,8%) |
13 (10.8%) |
0.7488 |
| 6,5h |
6 (11,8%) |
7 (10,3%) |
13 (10.8%) |
0.8102 |
| 7h |
6 (11,8%) |
9 (13,2%) |
15 (12.5%) |
0.8231 |
| 7,5h |
5 (9,8%) |
5 (7,4%) |
10 (8.3%) |
0.6481 |
| 8h |
13 (25,5%) |
12 (17,6%) |
25 (20.8%) |
0.3556 |
| 8,5h |
9 (17,6%) |
2 (2,9%) |
11 (9.2%) |
0.0090 |
| 9h |
1 (2%) |
6 (8,7%) |
7 (5.8%) |
0.1266 |
| 9,5h |
0 (0%) |
2 (2,9%) |
2 (1.7%) |
0.2207 |
| 10h |
2 (3,9%) |
6 (8,7%) |
8 (6.7%) |
0.3074 |
| >10h |
0 (0%) |
3 (4,3%) |
3 (2.5%) |
0.1336 |
Table 3.
Gender Differences in the Prevalence of Addictive Substance Use (Including Tobacco) and Alcohol Among Youth.
Table 3.
Gender Differences in the Prevalence of Addictive Substance Use (Including Tobacco) and Alcohol Among Youth.
| Substance |
Boys |
Girls |
P-value |
| Hashish or marijuana |
13.7% (10) |
23.2% (19) |
0.029 |
| Tranquilizers |
5.9% (4) |
11.6% (6) |
0.089 |
| Cocaine |
0% (0) |
1.4% (1) |
0.222 |
| Speed/amphetamines |
0% (0) |
0% (0) |
N/A |
| Ecstasy |
0% (0) |
1.4% (1) |
0.222 |
| Inhalants |
0% (0) |
2.9% (2) |
0.135 |
| Alcohol (Ever Drunk |
56.9% (34) |
82.6% (50) |
0.003 |
| Alcohol (During class days) |
0% (0) |
37% (22) |
<0.001 |
| Alcohol (During weekends) |
21% (13) |
27% (16.2) |
0.001 |
| Smoking (Ever smoked) |
19.83% (24) |
42.15% (51) |
<0.001 |
| Smoking (Currently smoking if smoked) |
41.67% (10) |
37.25% (19) |
0.539 |
Table 4.
Gender Differences in Physical Activity Among Adolescents.
Table 4.
Gender Differences in Physical Activity Among Adolescents.
| Physical Activity |
Boys |
Girls |
P-value |
χ² |
| Sports and physical activity |
66.7% (66) |
49.3% (49) |
0.042 |
8.21 |
| Sports |
5.9% (5) |
15.9% (15) |
| Physical activity |
15.7% (15) |
17.4% (17) |
| No sports or physical |
11.8% (11) |
17.4% (17) |
Table 5.
Gender Differences in Night Out Frequency and Return Times Among Adolescents.
Table 5.
Gender Differences in Night Out Frequency and Return Times Among Adolescents.
| Night Out Frequency |
Boys |
Girls |
P-value |
| >2 nights/week |
7.3% (7) |
7.3% (7) |
1.000 |
| 2 nights/week |
20.2% (20) |
20.2% (20) |
1.000 |
| 1 night/week |
17.7% (17) |
17.7% (17) |
1.000 |
| 1-3 nights/month |
10.5% (10) |
10.5% (10) |
1.000 |
| <1 night/month |
15.3% (15) |
15.3% (15) |
1.000 |
| Never |
29.0% (29) |
29.0% (29) |
1.000 |
Table 6.
Comparison of Breakfast Habits Before Leaving Home and Mid-Morning Between Boys and Girls.
Table 6.
Comparison of Breakfast Habits Before Leaving Home and Mid-Morning Between Boys and Girls.
| Breakfast Habits Before Leaving Home |
|
| Night Out Frequency |
Boys |
Girls |
P-value |
χ² |
| Every day |
28 (54.9%) |
33 (47.8%) |
0.4898 |
3.4221 |
| 4-6 times |
4 (7.8%) |
6 (8.7%) |
| 1-3 times |
7 (13.7%) |
7 (10.1%) |
| Never |
11 (21.6%) |
23 (33.3%) |
| NS/NC |
1 (2.0%) |
0 (0.0%) |
| How many times a week do you have a mid-morning breakfast |
| Every day |
29 (56.9%) |
35 (50.7%) |
0.1398 |
6.9274 |
| 4-6 times |
10 (19.6%) |
18 (26.1%) |
| 1-3 times |
5 (9.8%) |
12 (17.4%) |
| Never |
9 (17.6%) |
4 (5.8%) |
| NS/NC |
1 (2.0%) |
0 (0.0%) |
|
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