A longitudinal study of health risk behaviors and mental health problems in high school aged adolescents

A longitudinal study of health risk behaviors and mental health problems in high school aged adolescents

Conceptual framework

In the 1980s, youth experienced high morbidity and mortality rates due to harmful behaviors such as substance use, reckless driving, suicidal tendencies, and eating disorders These behaviors, collectively known as "risk-taking behavior," attracted significant attention from health researchers By grouping these behaviors under a single term, researchers can better explore their common patterns and contributing factors, enabling more effective prevention and intervention strategies that address the entire spectrum of risky behaviors rather than tackling each one individually.

In her analysis of risk, Shattell defines it as a potential danger to oneself, encompassing both physical and emotional harm, as well as a crucial aspect of decision-making amid uncertainty The concept of risk has two key attributes: it signifies the possibility of loss or harm and involves an individual's decision-making process that weighs the potential consequences of their actions.

Risk behavior is defined as actions that carry the potential for subjective loss, which can impede an individual's long-term productive development and integration This concept assumes that risk-taking is a voluntary process, where individuals consciously evaluate the potential consequences of their actions before proceeding According to Irwin (1990), risk-taking behavior is characterized as a voluntary action with uncertain outcomes, potentially leading to identifiable negative health consequences.

Numerous risk-taking behaviors have been identified in existing literature, with Hurrelmann and Raithel categorizing them into four main types: health-related, delinquent, financial, and ecological risk behaviors Health-related risk behavior is characterized by its potential for physical and mental harm, including injury, illness, and even death This concept is further supported by other researchers who refer to it using various terms such as health-compromising behavior, risky health behavior, and unhealthy behavior, all of which denote voluntary actions that can adversely affect an individual's health.

Health risk behavior refers to activities performed by individuals at a frequency or intensity that heightens the likelihood of disease or injury Understanding the extent of potential loss associated with these behaviors is crucial for effective health risk management.

Understanding health risk behavior involves recognizing both its potential negative consequences and the possible benefits, such as peer acceptance or stress relief among adolescents Research indicates that individuals weigh perceived losses against perceived gains when deciding to engage in risky activities Adolescents often choose behaviors that promote positive emotions while avoiding those that lead to negative feelings Therefore, prevention and intervention programs should aim to enhance adolescents' ability to differentiate between beneficial and harmful risks, enabling them to make informed choices.

To put it another way, we should not simply view that all health risk behaviors are unhealthy and should be eliminated Indeed, risk behavior is one

Adolescence is a crucial phase in an individual's transition from childhood to adulthood, characterized by role experimentation, social approval, and the establishment of autonomy from parents, all of which contribute to healthy identity formation While some health risk behaviors may not be essential, they can fulfill similar developmental needs as normative behaviors For example, while alcohol use and sexual activity may be typical as adolescents approach adulthood, engaging in these behaviors too early can be risky Similarly, minor delinquent acts and experimentation with substances are common among teenagers, but excessive delinquency or substance abuse are deemed non-normative due to their severity Therefore, it is essential to define risk-taking and health risk behaviors within the context of an individual's developmental stage.

Health risk behaviors refer to actions that can negatively impact physical health and psychosocial development These behaviors are voluntary and stem from a decision-making process where individuals weigh potential benefits against risks Since health risk behaviors are common during adolescence, the focus should be on guiding young people to manage these behaviors within safe limits rather than attempting to eliminate them entirely.

For many years, researchers in the health-related fields have been exploring the theories and evidences to provide a better understanding of the

The etiology of health risk behaviors in adolescents is complex and multifaceted, with no single answer to why they engage in harmful activities Key perspectives to consider include the developmental aspect, where the maturation of the brain's neural networks plays a significant role, and the social perspective, which highlights the impact of peer influence on individual decision-making This section will outline several influential theories that contribute to our understanding of health risk behaviors among adolescents.

The Health Belief Model, developed in the early 1950s, serves as a theoretical framework to understand why individuals often neglect preventive health actions, such as screening for high-incidence diseases This model emphasizes intra-personal factors, including attitudes and beliefs about risk and benefits, which significantly influence health-related decision-making Key constructs of the model include perceived susceptibility, perceived severity, perceived benefits, perceived barriers, cues to action, and self-efficacy, with perceived risk being a central element Perceived risk encompasses both an individual's assessment of the seriousness of health consequences and their personal vulnerability to those risks Ultimately, individuals are unlikely to alter their health risk behaviors unless they perceive the associated risks as significant.

While the Health Belief Model remains one of the most popular theoretical frameworks in health-related fields, there’s enough evidence

Adolescents often overestimate the absolute risks associated with health-related behaviors, showing a higher perceived personal risk compared to those who do not engage in such behaviors Research indicates that adolescents perceive greater risks in their actions than adults do, suggesting that perceived absolute risk may not be the primary influence on behavior; rather, it is the comparative risk judgment that plays a significant role Additionally, Weinstein et al (1982) highlighted the phenomenon of unrealistic optimism, where individuals tend to overrate their chances of positive outcomes while underestimating the likelihood of negative ones This optimism is relative, as adolescents may acknowledge an elevated risk but still believe their personal risk is lower than that of their peers participating in similar behaviors.

[90] This comparative risk perception is likely to predict health behaviors than are absolute perception [89]

Socio-psychological factors significantly influence how individuals perceive the seriousness of risky behaviors and their consequences Concerns about serious illnesses are often diminished when people believe that many others share the same vulnerability, while rare illnesses tend to provoke greater anxiety Additionally, adolescents are more likely to engage in risky behaviors if they perceive these behaviors as common among their peers, which lowers their perceived risk Furthermore, the concept of a "risk image," or a prototype of individuals deemed vulnerable to certain health issues, shapes personal risk perceptions For example, the association of obesity risk with specific demographics, such as overweight white women, can impact how individuals view their own susceptibility to health risks.

14 media, but not themselves also sharing the risk This social comparison process builds up a sense of (relative) invulnerability and relief [93], which can translate into more health risk behaviors

Theory of Reasoned Action and Theory of Planned Behavior

The Theory of Reasoned Action, formulated by Fishbein and Ajzen, posits that an individual's health behavior is primarily influenced by their intention to engage in that behavior This behavioral intention, which reflects a person's conscious plan to act, is the key determinant of actual behavior, with stronger intentions correlating to higher likelihood of action Intention is shaped by personal attitudes and subjective norms regarding the behavior Attitudes are influenced by an individual’s beliefs about the outcomes of their actions, combined with their evaluation of these outcomes; thus, if the outcomes are viewed positively, the individual is more likely to develop a favorable attitude Subjective norms arise from normative beliefs and the motivation to adhere to social expectations, encapsulating the belief that significant others approve or disapprove of a behavior Within the social norm framework, two types of norms exist: descriptive norms, which reflect observed behaviors in one’s environment, and injunctive norms, which concern social approval Research indicates that both types of norms are predictors of health-risk behaviors, with injunctive norms having a more pronounced impact.

The Theory of Planned Behavior expands upon the Theory of Reasoned Action by adding perceived behavioral control as a crucial predictor of behavior, alongside attitudes and subjective norms.

Perceived behavioral control significantly affects an individual's intention to perform a behavior, serving as a key determinant of that behavior This concept reflects a person's belief in their ease or difficulty in executing a specific action Generally, individuals are more inclined to engage in behaviors they feel they can control However, perceived behavioral control can fluctuate based on the context and specific actions, leading to diverse perceptions depending on the situation This perception is shaped by an individual's assessment of available resources, which encompass both internal factors like skills and information, as well as external factors such as opportunities, reliance on others, and potential barriers.

Literature review

1.2.1 An overview of health risk behaviors

Health risk behaviors typically emerge in adolescence and can persist into adulthood, leading to detrimental effects on both short-term and long-term health Poor dietary choices and a lack of physical activity are linked to a higher likelihood of overweight and obesity later in life Furthermore, individuals who begin smoking and drinking at a young age are more prone to developing substance abuse issues in the future.

Global studies reveal a concerning prevalence of health risk behaviors among adolescents, often focusing on clusters of these behaviors rather than isolated instances, as simultaneous engagement is linked to higher morbidity and premature mortality Research indicates that various individual and environmental factors, including gender, age, family structure, parental education, and employment, significantly influence these health risk behaviors Additionally, psychosocial elements such as personality traits, self-esteem, and the influence of family and peers are also associated with the clustering of health risk behaviors in adolescents.

1.2.1.1 Unhealthy dietary behaviors and physical inactivity

In 2010, dietary risk factors and physical inactivity contributed to nearly 10% of global disability-adjusted life years A significant number of adolescents exhibited behaviors linked to obesity, such as skipping breakfast, consuming low amounts of fruits and vegetables, drinking high quantities of soft drinks, snacking excessively, engaging in little physical activity, and spending excessive time on screens.

Poor dietary habits, including high consumption of soft drinks, fats, sugars, and sodium, along with low fruit and vegetable intake, are strongly linked to overweight and obesity These unhealthy behaviors, combined with increased sedentary time, often continue into adulthood, significantly raising the risk of developing chronic diseases such as cardiovascular disease and type 2 diabetes.

Research indicates a concerning decline in healthy dietary practices among adolescents, with many failing to adhere to recommended dietary guidelines This shift has led to an increase in poor eating habits, including skipping breakfast and a higher consumption of fast food.

Many adolescents in Vietnam are reported to have unhealthy eating habits, characterized by a diet high in fats, saturated fats, and sodium, while lacking sufficient fruits and vegetables Studies indicate a correlation between dining out and increased intake of energy from fats and sugars, as well as the influence of healthy eating values on the consumption of convenience foods among teenagers.

Physical inactivity has emerged as a significant health concern, contributing to the obesity epidemic and increasing rates of non-communicable diseases, making it the fourth leading risk factor for global mortality Research indicates that most adolescents do not meet the recommended levels of physical activity and instead engage in prolonged sedentary behavior A review of studies across 24 countries highlights a concerning prevalence of insufficient physical activity among children Recent data from 30,284 adolescents aged 13-15 in ASEAN countries between 2007 and 2013 revealed an alarming 80.4% prevalence of physical inactivity and 33% of sedentary behaviors Additionally, a study of 2,660 junior high school students in Vietnam found that 24.3% were classified as inactive, possibly due to lower classification standards than those set by the WHO or the US Centers for Disease Control and Prevention.

Age, gender, parental education and household income were indicated as significant related factors to physical inactivity and unhealthy dietary behaviors

[207] Socioeconomic status may play a huge part in why an adolescent may not be getting their nutritional and dietary needs met Evidence suggests that an

43 increased income allows for the purchase of foods with higher nutritional value

Adolescents from lower socioeconomic backgrounds often face limited access to nutritious foods, relying instead on local restaurants and stores that offer cheap, unhealthy options high in calories, fat, and sodium Additionally, minority and lower SES adolescents are significantly less likely to engage in organized activities compared to their Caucasian and higher socioeconomic peers.

It is shown people in lower social classes with high crime rates and lack of resources in the living neighborhood are less likely to exercise regularly [211-

Regarding gender difference, boys and girls appear to exhibit different patterns Males report more unhealthy eating habits than female adolescents

Male adolescents generally engage in higher levels of moderate to vigorous physical activity compared to their female counterparts However, substance use and antisocial behaviors are reported to be more common among males, while females tend to experience higher rates of physical inactivity and unhealthy eating habits.

Adolescents with less educated parents are more likely to engage in physical inactivity and unhealthy eating habits Research from the Add Health survey indicates a strong positive correlation between higher maternal education levels and increased participation in physical activities among adolescents Similarly, lower parental education is linked to poor dietary choices, such as higher consumption of sweets, energy drinks, and fast food, while higher parental education correlates with increased fruit and vegetable intake However, a study on Vietnamese adolescents presents findings that contradict these global trends.

Research indicates that children from the wealthiest families are the least active, as affluent households often offer modern recreational amenities like computers and televisions, which reduce opportunities for physical activity Additionally, in wealthier urban areas, limited play spaces and perceived safety concerns further contribute to this trend, highlighting differences between Vietnam and Western countries.

Tobacco use remains the leading preventable cause of death globally, with 6.4 million deaths attributed to smoking in recent years, marking a 4.7% increase since 2005 The majority of smokers begin during adolescence, and nearly half of long-term users are expected to die from smoking-related diseases Approximately one-third of these deaths are linked to cardiovascular disease and stroke, another third to cancer, and about 20% to respiratory diseases Smoking is pervasively harmful, impacting nearly every organ in the body, as highlighted in the Surgeon General's report.

A global analysis of smoking prevalence across 195 countries revealed a significant decline in smoking rates and age-standardized smoking figures; however, high smoking rates persist, particularly among individuals aged 15 to 19 While male smoking rates remain significantly higher than those of females, the most notable reductions from 1990 to 2015 were observed among men, with some regions experiencing little change or even increases in female smoking rates Additionally, smoking is closely linked to lower socioeconomic status (SES), with particularly elevated rates among socioeconomically disadvantaged groups, including the unemployed and homeless.

Single parents may face challenges such as low social support and motivation to quit smoking, along with stronger tobacco addiction and psychological factors like low self-efficacy, particularly in lower socioeconomic groups Socio-demographic factors, including age, sex, and race/ethnicity, have shown inconsistent associations with smoking onset Psychological traits like impulsivity, sensation seeking, and rebelliousness are positively linked to smoking, while academic performance and self-esteem are inversely related Social influences, such as family and peer smoking, along with parental supervision, also contribute to smoking initiation Additionally, global alcohol consumption among adolescents and young adults is on the rise, contributing to approximately 5% of the global disease burden, making it a leading risk factor While men typically consume more alcohol than women, this gender gap narrows among younger individuals.

The prevalence of tobacco consumption in Vietnamese adolescents from

In 2013, the smoking prevalence among youths aged 13 to 17 was 5.4%, which decreased to 2.8% by 2019 Key factors linked to smoking include gender, parental monitoring, emotional issues like loneliness and suicidal tendencies, as well as behavioral problems such as truancy and the use of other addictive substances Additionally, a study by Thoa and Hoang revealed that 16.5% of youths aged 10 and above in Northern Vietnam engage in alcohol use.

Overview of research design

This study aims to investigate the relationship between emotional mental health and health risk behaviors in high school adolescents, assessing whether changes in one predict changes in the other Additionally, it seeks to explore how delay discounting and parental monitoring may moderate this relationship.

A longitudinal design was utilized in this study, allowing researchers to follow participants over extended periods This approach employs repeated measures to gather data on one or more variables across multiple occasions Unlike cross-sectional designs, longitudinal studies facilitate the exploration of individual changes over time and provide insights into the reasons behind these changes This method is particularly effective for examining the evolution of health risk behaviors and emotional mental health, enabling the testing of whether these variables serve as predictors for observed changes.

This study utilized self-report questionnaires to collect data over a six-month period, with assessments conducted in October 2018 and April 2019, ensuring that data collection occurred at least two weeks prior to semester final examinations to mitigate stress-related influences The primary variables examined included health risk behaviors, emotional mental health, delay discounting, and parental monitoring Health risk behaviors were assessed through five specific risky behaviors: unhealthy eating, physical inactivity, alcohol consumption, smoking, and problematic Internet use Emotional mental health was evaluated based on levels of stress, depression, and anxiety.

Indicators of Health risk behaviors and Emotional mental health:

Emotional mental health predicts change in Health risk behaviors; Delay discounting & Parental monitoring as moderators

Health risk behaviors predicts change in Emotional mental health; Delay discounting & Parental monitoring as moderators

Smoking Drinking Problematic Internet use

Research procedure

We conducted a literature review of health risk behaviors, its relation to emotional mental health, the psychosocial factors contributing to that relation (focusing on parental monitoring and delay discounting)

After synthesizing the collected information and identifying existing gaps, we formulated our research questions A longitudinal design was selected for this study, with further details provided in section 2.1 of the research design.

For this study, we opted for self-administered questionnaires, with a comprehensive description of the tool provided in section 2.4 The selection and adaptation of the instruments involved evaluating their psychometric properties and prior usage with adolescents in the Vietnamese context We investigated existing Vietnamese translations of the instruments and assessed their accuracy and clarity In cases where no translations were available, one researcher translated the instruments, followed by a review from two additional researchers Additionally, we conducted four focus group interviews with parents and adolescents from both urban and suburban areas in Hanoi to gather insights.

(1) gather information about the types of physical activities, eating habits, patterns of parental monitoring in Vietnam; and to (2) seek for their opinions on the scales

The instrument was adjusted to enhance clarity, with minor revisions made to the original translation of the scale items A 7-day monitoring form was created to assist participants in tracking their eating and physical activity habits over the past week, including examples of both physical activities and eating habits For the pilot phase, seven high school students from urban and suburban areas of Hanoi completed the monitoring form and questionnaire, providing valuable feedback on language clarity, questionnaire length, format, and personal suggestions to the research team.

Based on participant feedback, the instrument was revised to enhance clarity and usability The monitoring form now includes brief instructions and examples, and we allocated 15-20 minutes for participants to familiarize themselves with it before taking it home Additionally, the main questionnaire format was adjusted for easier navigation, with minor wording changes to improve comprehension.

• Step 4: Recruitment and training of local research assistants

In each province, a local coordinator and a minimum of two research assistants were recruited to oversee the data collection process Their responsibilities included obtaining consent and assent forms from students and parents, guiding students in completing the monitoring form, administering the main questionnaire, providing compensation to students and schools, and managing local data effectively.

We conducted training for research coordinators and assistants in each province: the training content included overview of the research, description

70 of data collection procedure and the research instrument, research ethics, practice of questionnaire administration, research assistants’ responsibilities and planning for each province

• Step 5: Contacting schools and recruitment of participants

In Hanoi, four urban schools and two suburban schools were selected for participation, while each other province included two urban schools and one suburban school The study involved randomly selected students from these schools.

In Hanoi, we gathered the public high school list from the Ministry of Education and Training's website, while in other provinces, we reached out to the provincial Departments of Education and Training for assistance in connecting with local school boards Each school accommodates 24 students, with 4 students per class across 6 classes for the 10th and 11th grades.

Researchers initiate contact with school boards to outline the study's objectives, design, data collection timelines, and participant benefits and requirements If a high school declines participation, a replacement school from the same regional background is selected.

After the school agrees to participate, research coordinators will randomly select three classes from each grade and then choose four students from each class These selected students will be informed about the study and asked to provide their assent, followed by sending a letter with an introduction to the research and a consent form to their parents Parents will be made aware that participation is voluntary and that student names will be replaced with identification codes to maintain confidentiality The consent form will also include contact information, ensuring that researchers are available to address any concerns from students or parents during the data collection process.

After obtaining students' assent and parental consent, participants were asked to fill out a 7-day monitoring form tracking their physical activity and eating habits Upon completion of the monitoring period, researchers conducted the main survey, which included both a paper questionnaire and an online delay discounting questionnaire, with each student identified by a unique code This survey was administered during scheduled times coordinated with the school board.

Six months after the initial data collection, parents and students were reminded about the study and invited to participate again If they agreed, local research assistants followed the same administrative procedures as before.

Study sites and participants

Public high schools in different divisions of the 5 provinces from North to South were chosen to represent different types of urban area and suburban areas of Vietnam:

Lao Cai province, situated in Vietnam's mountainous Northwest region, boasts its capital city, Lao Cai, which is classified as a Class-2 City Home to a population exceeding 700,000 residents, the province features a GDP per capita of 61.84 million, highlighting its economic significance in the area.

16 th in 2018 2 schools in urban wards (Binh Minh and Duyen Hai) and 1 school in suburban commune of Lao Cai (Cam Duong) were included in the study

- Hanoi: special urban area, located in Northern Vietnam, the capital city of Vietnam and the second largest city with over eight million residents in 2019

4 schools in urban districts (Ba Dinh, Thanh Xuan, Hoang Mai, Hai Ba Trung) and 2 schools in suburban districts (Thach That and Nam Tu Liem) were included in the study

Ninh Binh province, situated in Northern Vietnam, has its capital in Nha Trang, classified as a Class-2 City The province boasts a population exceeding 970,000 and achieved a GDP per capita of 48.5 million, ranking 39th in 2018 The study focused on two schools located in urban wards, Ninh Phong and Van Gia, as well as one school in the suburban commune of Hoa Lu.

Khanh Hoa province, situated on Vietnam's South-Central Coast, boasts Nha Trang as its capital and a Type I urban area With a population exceeding 1.2 million and a GDP per capita of 62.13 million, it ranked 15th in 2018 The study focused on two schools located in urban wards, Vinh Phuoc and Vinh Hoa, as well as one school in the suburban commune of Vinh Thanh, Nha Trang.

Dong Nai province, situated in the Southeast region of Vietnam, boasts Bien Hoa as its capital, recognized as a Class-1 City With a population exceeding 3 million and a GDP per capita of 124 million, it ranked 6th in 2020 The study focused on two schools located in urban wards, Quyet Thang and Tam Hiep, along with one school in the suburban commune of Nha Trang, Hiep Hoa.

In Hanoi, a total of 4 urban schools and 2 suburban schools were invited to participate in the study, while each other province contributed 2 urban schools and 1 suburban school The study involved randomly selected students from the 10th and 11th grades, and the following section provides a detailed description of the sample characteristics.

In the initial phase of data collection, 432 students and parents consented to participate in the study, but one participant withdrew, resulting in a total of 431 participants By the second round of data collection, 424 participants remained, while 7 participants either relocated, changed schools, or opted out of the study A detailed demographic description of the sample is provided in the accompanying table.

Table 2.1 Sociodemographic Characteristics of Participants at Baseline

University or post-graduate degree

Note N = 431 Participants were on average 15.64 years old (SD = 593), with the age range from 15 to 17 years old.

Instruments

The initial section of the questionnaire focuses on collecting socio-demographic variables, such as the residential area (suburban or urban), age, gender (male or female), family structure (living with both parents, having divorced parents, or having a deceased parent), and the highest educational level attained by parents or main caregivers (ranging from primary school or under to university or postgraduate degree).

The International Physical Activity Questionnaire (IPAQ), specifically its long version for youth and adults aged 15-69, was utilized to measure participants' physical activity levels This instrument has demonstrated reliable measurement properties across diverse cultures The IPAQ encompasses four key domains of physical activity: work-related, transportation, housework/gardening, and leisure-time activities It records the frequency and duration of both moderate and vigorous activities, including walking time across these domains Additionally, the questionnaire provides practical examples of culturally relevant activities that fall within moderate and vigorous intensity levels.

The IPAQ has previously been utilized in research involving Vietnamese adolescents, but it has shown poor validity due to participants' difficulty in accurately recalling their physical activity durations from the past week To address this issue, the current study provided participants with a 7-day monitoring form to track their physical activities prior to the survey This form was structured similarly to the IPAQ and included detailed explanations and examples of moderate and vigorous activities Focus group interviews with parents and adolescents from both suburban and urban areas were conducted to identify common physical activities and sedentary habits among adolescents, ensuring their inclusion in the monitoring form and the IPAQ The study demonstrated good internal reliability of the scale, with a Cronbach’s α of 74.

The scoring protocol utilized in this study is based on the International Physical Activity Questionnaire (IPAQ) guidelines for data processing and analysis, applicable to both short and long forms Initial data reporting will follow these established protocols.

Physical activity intensity is quantified using a continuous measure known as metabolic equivalents (METs), which represent the ratio of energy consumption during specific activities to a standard metabolic rate This standard is conventionally set at 3.5 ml of oxygen per kilogram of body weight per minute, allowing for a clear understanding of the energy expenditure associated with various physical activities.

One MET, defined as the resting metabolic rate during quiet sitting, is equivalent to 0.2 kg −1 min −1 or 1 kcal kg −1 h −1 (4.184 kJ kg −1 h −1) To calculate MET-minutes per week, multiply the MET value of each activity by the duration and frequency of that activity Different physical activities, such as walking, moderate-intensity, and vigorous-intensity exercises, each have their own specific MET values The overall total physical activity score in MET-minutes per week is derived by summing the MET-minutes scores from all activities performed.

Participants in the study were classified into three levels of physical activity: high, moderate, and low Those categorized as "high" engaged in vigorous-intensity activities for at least three days a week, accumulating a minimum of 1500 MET-minutes weekly, or participated in activities totaling at least 3000 MET-minutes over seven days To qualify as "moderate," participants needed to meet one of several criteria, including at least 20 minutes of vigorous activity for three days or 30 minutes of moderate activity for five days, totaling 600 MET-minutes weekly Individuals who did not meet the criteria for either high or moderate activity were classified as having low physical activity levels According to WHO guidelines, a "high" level of activity is defined as approximately one hour per day, while "moderate" activity is considered sufficient for health benefits.

76 an hour of at least moderate-intensity physical activity on most days) considered as minimum and “low” as insufficient level

The main analysis of the relationship between emotional mental health issues and health risk behaviors utilizes the continuous variable of total physical activity measured in MET-minutes per week In contrast, a categorical variable is used to describe patterns of health risk behaviors among adolescents A higher score in the continuous variable indicates a lower level of physical inactivity.

The Adolescent Food Habits Checklist (AFHC), consisting of 23 items, was utilized to evaluate participants' dietary practices, demonstrating high internal reliability with a Cronbach’s α of 82 in previous studies This checklist has been extensively applied in research on adolescent eating behaviors In the current study, the AFHC exhibited good internal reliability with a Cronbach’s α of 77, confirming its effectiveness in assessing dietary habits among adolescents.

The study evaluates the consumption of fats, sugars, fruits, vegetables, carbohydrates, and fast food through a 23-item questionnaire After translating the questionnaire into Vietnamese, we refined the items based on focus group interviews with parents and adolescents, incorporating relevant food examples and modifying or eliminating unsuitable items Participants also tracked their daily food intake over a 7-day period prior to completing the questionnaire.

Participants responded with 'true,' 'false,' or 'not applicable to me' to assess their adherence to various dietary practices, encompassing both healthy and unhealthy behaviors Each healthy response earned participants one point, and total scores were computed by tallying the healthy responses, with adjustments for 'not applicable' and missing answers.

77 responses (AFHC score = number of ‘healthy’ response × (23/number of items completed)) Maximum score to be attained is 23 A low score demonstrates unhealthy eating habits on the part of the individual

The study assessed cigarette and alcohol consumption frequency through a series of four questions for each substance Participants were asked whether they had ever used alcohol or tobacco, the last time they consumed either, the number of days they consumed these substances in the past 30 days, and the daily amount consumed during that period The daily and monthly intake frequencies were standardized to create a final variable for smoking and drinking, which was utilized in the regression analysis.

The Young’s Internet Addiction Test is a 20-item questionnaire designed to assess the impact of Internet usage on individuals' daily lives, social interactions, productivity, sleep patterns, and emotional well-being Participants rate each item on a five-point Likert scale, ranging from 0 (“rarely”) to 4 (“always”), with total scores varying from 0 to 80 Higher scores indicate greater issues related to Internet use According to Young, a score of 0–19 suggests an average user with good control over their Internet habits, while a score of 20–49 indicates frequent problems, and a score of 50–80 signifies significant Internet-related issues Participants with more than one missing item were excluded from the analysis.

The Implicit Association Test (IAT) has been widely utilized in Asia, demonstrating strong internal consistency with a Cronbach’s alpha ranging from 90 to 93 and a test-retest reliability of r = 0.85 In this study, the internal reliability of the scale is confirmed to be adequate, with a Cronbach’s alpha of 90.

To explore emotional mental health issues in adolescents, particularly internalizing problems, we utilize the DASS-21, a 21-item self-report measure assessing negative affect over the past week Designed to evaluate distinct aspects of anxiety and depression, the DASS-21 also includes a stress component that highlights common features of these conditions The factor structure of the DASS-21 is robust, demonstrating strong convergent and discriminant validity along with high internal consistency It has also shown suitable psychometric properties within the Vietnamese population, with Cronbach’s α values of 79 for depression (DASS-D), 71 for anxiety (DASS-A), and 74 for stress (DASS-S) in this study.

Statistical analyses

Data was stored, cleaned and analyzed by SPSS for Windows and SAS for Windows Statistical significance was set at p < 0.05

Descriptive statistics, such as frequencies, means, and standard deviations, were employed to analyze the sample and investigate the prevalence of health risk behaviors and emotional mental health indicators, specifically DASS variables To assess the impact of demographic factors—like parental education, residential area, family structure, and gender—chi-square tests and one-way ANOVA were utilized Additionally, correlation tests were conducted to examine the relationships between DASS variables and five identified risk behaviors.

The study employed a general linear model to investigate the predictive relationship between health risk behaviors and emotional mental health, as well as the impact of delay discounting and parental monitoring on these associations The independent and dependent variables for each analysis will be detailed in the Results section The equations for the four research questions guided the formulation of the univariate general linear model in SPSS.

Question 1: Does Emotional Mental Health predict changes in Health Risk Behaviors?

Question 2: Does Health Risk Behaviors predict changes in Emotional Mental Health?

Question 3: Does Delay Discounting moderate the effect between Health Risk Behaviors and Emotional Mental Health?

HRB_T2 = β0 + β1*HRB_T1 + β2*DASS_T1 + β3*DD_T1 + β4*DASS_T1*DD_T1 + ε

DASS_T2 = β0 + β1*DASS_T1 + β2*HRB_T1 + β3*DD_T1 + β4*HRB_T1*DD_T1 + ε

Question 4: Does Parental Monitoring moderate the effect between Health Risk Behaviors and Emotional Mental Health?

HRB_T2 = β0 + β1*HRB_T1 + β2*DASS_T1 + β3*PM_T1 + β4*DASS_T1*PM_T1 + ε

DASS_T2 = β0 + β1*DASS_T1 + β2*HRB_T1 + β3*PM_T1 + β4*HRB_T1*PM_T1 + ε

HRB (Health Risk Behaviors): including 5 variables: IPAQ score (International Physical Activity Questionnaire score), AFHC score (Adolescent Food Habit Checklist score), SMOKING, DRINKING, IAT score (Internet Addiction Test score)

DASS (Depression Anxiety Stress Scale 21 score): including 3 variables: DASS-S (Stress subscale score), DASS-D (Depression subscale score), DASS-

Ethical considerations

Participants in the study faced minimal risks, though some questions may have caused discomfort Research assistants clearly communicated the process, assuring participants they could pause the study and seek assistance if needed.

The research team compiled a list of mental health care services in Hanoi, Nha Trang, and Ho Chi Minh City, and referred individuals to mental health professionals as needed Although information on mental health care in Lao Cai and Ninh Binh was unavailable, a counseling team was established, and a mental health hotline was provided for participants seeking professional support.

The school board and teachers were aware of the students' involvement in the study, but they did not participate in the questionnaire administration or have access to the students' responses All student information was kept private and not shared with anyone outside the study To maintain confidentiality, a data management system was implemented, replacing students' names with identification codes.

Research assistants entered data into a password-protected management form, securely saved on a shared point accessible only to the research team Paper questionnaires and consent forms were stored at the research center, with data files also kept on the secure shared point While the names of provinces and schools may be included in publications, personal information identifying participants will remain confidential.

After finishing the questionnaire, each participant received a compensation (50.000VND) that acknowledged their time and effort

Participants were randomly selected from the student roster, and researchers communicated directly with both the students and their parents to explain the study and obtain consent, ensuring there was no pressure from the school.

Parents were informed of their right to allow or decline their children's participation in the study without penalty, and students were also made aware that their involvement was voluntary, with the option to withdraw at any time The consent form included contact information, ensuring that researchers were available to address any concerns from students or parents regarding the administration process throughout the study.

Descriptive analyses

3.1.1.Health Risk Behaviors among Vietnamese adolescents

The mean for total physical activity score reported by 422 participants is

In a study measuring physical activity levels, participants averaged 2039.99 MET-minutes per week (SD = 1415.5) According to the Ipaq Research Committee classification, 37.4% of participants achieved a high level of physical activity, 39.8% met moderate criteria, and 22.7% fell into the low activity category Notably, 37.4% of participants aligned with the World Health Organization's global recommendations for health-related physical activity.

85 accumulated sufficient moderate- to vigorous-intensity physical activity (at least 60 minutes daily) and so 62.5% could be categorized as physical inactive

Table 3.1 presents the chi-square test results highlighting significant differences in physical activity levels based on gender and parental education (p < 05), while no significant differences were found related to residential area or family structure Notably, 31.5% of males achieved the recommended physical activity levels, more than double the 13.3% of females Additionally, children of parents with low educational attainment (primary school or below) are more likely to be insufficiently active.

Table 3.2 Chi-square results for demographic characteristics and physical activity

The mean of Adolescent Food Habit Checklist score for all respondents (NB3) is M = 12.14, SD = 4.5 The frequency of respondents’ healthy/unhealthy answer are displayed in the table below:

Table 3.3 Frequency of respondents’ healthy/unhealthy answers

1 If I am having lunch away from home, I often choose a low- fat option

2 I usually avoid eating fried foods 56.8 43.2

3 I usually eat sweets for dessert if there is one available 49.6 50.4

4 I make sure I eat at least one serving of fruit a day 40.9 59.1

5 I try to keep my overall fat intake down 66.4 33.6

6 If I am buying crisps, I often choose a low-fat brand 38.9 52.1 9.0

7 I avoid eating lots of sausages and burgers 49.9 46.3 3.8

8 I often buy pastries or cakes 33.7 66.3

9 I try to keep my overall sugar intake down 63.8 36.2

10 I make sure I eat at least one serving of vegetables or salad a day

11 If I am having a dessert at home, I try to have something low in fat

13 I try to ensure I eat plenty of fruit and vegetables 71.5 28.5

14 I often eat sweet snack between meals 36.2 63.8

15 I usually eat at least one serving of vegetables (excluding potatoes) or salad with my evening meal

16 When I am buying a soft drink, I usually choose a diet drink 14.5 76.5 9.0

17 When I put butter or margarine on bread, I usually spread it thinly

18 If I have a packed lunch, I usually include some snacks like chocolate, biscuits, etc

19 When I have a snack between meals, I often choose fruit 50.4 32.2 17.4

20 If I am having a dessert in a restaurant, I usually choose the healthiest one

21 I often have cream on desserts 11.0 71.4 17.6

22 I eat at least three servings of fruit most days 26.6 73.4

23 I generally try to have a healthy diet 80.8 19.2

Note: Healthy responses are emboldened

The analysis reveals a significant disparity between healthy and unhealthy dietary responses, particularly in attitudes towards healthy eating, such as the commitment to maintaining a nutritious diet and consuming ample fruits and vegetables While there is a predominance of healthy responses related to fruit and vegetable intake, this trend shifts when participants are asked about meeting specific recommended servings, with fewer individuals reporting adherence to the guideline of consuming at least three servings of fruit most days Additionally, Item 16 regarding diet drinks shows a marked prevalence of unhealthy responses, highlighting a concerning aspect of participants' dietary choices.

A one-way analysis of variance (ANOVA) was performed to assess the impact of demographic factors on dietary behaviors The results indicated that none of the factors, including gender, showed statistically significant effects, with F(1,421) = 2.14 and p > 0.05.

= 14], residence [F(1,421) = 56, p = 81], parental education [F(3,351) = 2.17, p = 09], and family structure [F(2,419) = 37, p = 69]

3.1.1.3 Tobacco smoking and Alcohol drinking

Out of 422 respondents, 9.9% (42 students) have experimented with smoking, while only 1.1% (5 students) reported smoking in the past 30 days Specifically, 2 students smoked for 1 or 2 days, 1 student smoked for 3 to 5 days, and another 2 students smoked for 10 to 19 days within that timeframe.

88 day (count the day they smoke), 4 students reported 1 cigarette per day, and 1 student reported 2 to 5 per day

Applying chi-square test to determine whether there is an association between demographic factors and respondents’ smoking behavior, only gender is found to have a significant relationship, χ 2 (1, N = 422) = 12.16, p < 01

Male students (10.8%) are more likely to have smoked than female (2.4%) There is no significant association between respondents’ smoking and residential area [χ 2 (1, N = 422) = 1.90, p = 21], family structure [χ 2 (2, N 422) = 53, p = 77], and parental education [χ 2 (3, N = 352) = 3.32, p = 77]

A survey of 422 respondents revealed that 200 individuals (47.4%) had experimented with alcohol Among these, 69 students (16.3%) consumed alcohol within the last 30 days, with the majority (55) drinking on only 1 or 2 occasions, while 10 students reported drinking 3 to 5 times during that period.

In a recent survey, 2 respondents indicated a waiting period of 6 to 9 days, while another 2 reported a duration of 10 to 19 days When asked about their average daily alcohol consumption, 40 students stated they consume 1 drink per day, 18 students reported consuming between 2 to 5 drinks daily, and 10 students noted an intake of 6 to 10 drinks per day.

Chi-square tests were used to determine whether there is an association between demographic factors and respondents’ attempt to drink; only gender had a significant relationship, χ 2 (1, N = 422) = 12.10, p < 01 Male students

(54.5%) are more likely to drink than female (37.8%) There is no significant association between respondents’ drinking and residential area [χ 2 (1, N = 422)

= 1.05, p = 59], family structure [χ 2 (2, N = 422) = 8.16, p = 08], and parental education [χ 2 (3, N = 352) = 8.58, p = 19]

The mean of Internet Addiction Test score for all valid respondents (NB0) is M = 29.18, SD = 14.27 Using Young’s suggested classification,

111 respondents (26.4%) scoring under 20 are considered average user; 273

89 respondents (65%) scoring from 20 to under 50 are likely to have frequent problems due to Internet usage; and 36 respondents (8.6%) scoring more than

A one-way analysis of variance (ANOVA) was performed to assess the impact of demographic factors on problematic Internet use The results indicated that none of the factors examined showed statistically significant effects: gender (F(1,418) = 96, p = 33), residence (F(1,418) = 28, p = 59), parental education (F(3,350) = 95, p = 41), and family structure (F(2,416) = 1.04, p = 35).

3.1.2 Emotional mental health among Vietnamese adolescents

Table 3.3 displays the total scores and severity classifications for Depression, Anxiety, and Stress using the DASS-21 scale, which evaluates the perceived intensity of related symptoms Following the cut-off score established by Lovibond and Lovibond, this study provides prevalence estimates of mental health issues in adolescents rather than formal diagnoses The findings reveal that approximately 10% of students experience severe depressive symptoms, including dysphoria and anhedonia, while another 10% report severe anxiety symptoms, characterized by heightened anxious feelings and autonomic arousal Additionally, 20% of students exhibit severe stress symptoms, such as difficulty relaxing and impatience.

Table 3.4 Description of Depression Anxiety Stress Scale-21 score

Note: cut-off score of 21 is derived from a set of severity ratings proposed by Lovibond and Lovibond [387]

A one-way analysis of variance test indicates that parental education, residential area, and family structure do not significantly affect DASS scores for depression, anxiety, and stress While gender shows no significant correlation with depression and stress levels, it does have a significant association with anxiety, where females (M=10.76, SD=7.88) exhibit notably higher anxiety scores compared to males (M=9.81, SD=7.7) [F(1,420) = 6.62, p = 01].

Main findings

3.2.1 Research Question 1: Does Emotional Mental Health predict changes in Health Risk Behaviors?

General linear models were employed to investigate the impact of emotional mental health issues on changes in health risk behaviors The analysis focused on health risk behaviors at Time 2, using emotional mental health problems and health risk behaviors at Time 1 as independent variables It is noteworthy that in this high school sample, regular alcohol use was reported at approximately 15%, while regular smoking was extremely low at around 1%, which considerably diminished the analytical power for these variables Results can be found in Table 3.4.

A study revealed a significant correlation between depression scores and smoking frequency, with a positive beta estimate of β = 10 (F[1,410] = 4.25, p < 05) This indicates that higher levels of depression at Time 1 are associated with an increase in smoking frequency at Time 2 Specifically, for each standard deviation increase in depression, there is a corresponding 10 standard deviation rise in smoking frequency No significant effects were observed for other health risk behaviors.

Table 3.5 Effects of Emotional Mental Health (DASS) on Health Risk Behaviors

IPAQ_T2 AFHC_T2 Smoking_T2 Drinking_T2 IAT_T2 β SE t β SE t β SE t β SE t β SE t

DASS: Depression Anxiety Stress Scale 21 score

DASS-D: Depression subscale score; DASS-A: Anxiety subscale score; DASS-S: Stress subscale score

IPAQ: International Physical Activity Questionnaire score

AFHC: Adolescent Food Habit Checklist score

IAT: Internet Addiction Test score

3.2.2 Research Question 2: Does Health Risk Behaviors predict changes in

In the second analysis, emotional mental health problems at Time 2 served as the dependent variable, while health risk behaviors and emotional mental health issues at Time 1 were the independent variables The findings are detailed in Table 3.5.

The study found that among the independent variables, only Internet Addiction Test (IAT) significantly impacted emotional mental health issues, specifically depression, anxiety, and stress The analysis revealed that higher levels of problematic internet use at Time 1 predicted increases in depression (β = 21, p < 05), anxiety (β = 21, p < 05), and stress (β = 18, p < 05) scores by Time 2 Specifically, for each standard deviation increase in problematic internet use, participants' predicted depression and anxiety scores rose by 21 standard deviations, while stress scores increased by 18 standard deviations Other variables did not show significant effects.

Table 3.6 Effects of Health Risk Behaviors on Emotional Mental Health (DASS)

DASS-D_T2 DASS-A_T2 DASS-S_T2 β SE t β SE t β SE t

DASS: Depression Anxiety Stress Scale 21 score

DASS-D: Depression subscale score; DASS-A: Anxiety subscale score; DASS-S: Stress subscale score

IPAQ: International Physical Activity Questionnaire score

AFHC: Adolescent Food Habit Checklist score

IAT: Internet Addiction Test score

3.2.3 Research Question 3: Does Delay Discounting moderate the effect between Health Risk Behaviors and Emotional Mental Health?

The analysis examined the moderating effects of delay discounting on the relationship between health risk behaviors and emotional mental health issues The model included health risk behaviors, emotional mental health, delay discounting, and their interactions Results, detailed in Tables 3.6 and 3.7, indicated that the only significant moderation effect was the interaction between delay discounting and anxiety, which impacted changes in the AFHC score [F(3, 405) = 4.23, β = 07, p < 05].

Table 3.7 Delay discounting moderating the effect of Anxiety on Unhealthy eating β SE t p

When Delay Discounting is one standard deviation above the mean, a one standard deviation increase in DASS Anxiety is associated with a decrease of 0.01 standard deviations in AFHC scores from T1 to T2 (β = -0.01).

A one standard deviation (SD) decrease in DASS Anxiety corresponds to a 15 SD reduction in AFHC scores from Time 1 (T1) to Time 2 (T2) This indicates that when youth exhibit lower delay discounting—favoring larger future rewards over smaller immediate ones—there is a notable decrease in anxiety at T1, which subsequently leads to improved healthy eating behaviors.

Table 3.8 Delay Discounting moderating the effects of Emotional Mental Health (DASS) on Health Risk Behaviors

IPAQ_T2 AFHC_T2 Smoking_T2 Drinking_T2 IAT_T2 β SE t β SE t β SE t β SE t β SE t

Model: HRB_T2 = β0 + β1*HRB_T1 + β2*DASS_T1 + β3*DD_T1 + β4*DASS_T1*DD_T1 + ε

DASS: Depression Anxiety Stress Scale 21 score

DASS-D: Depression subscale score; DASS-A: Anxiety subscale score; DASS-S: Stress subscale score

IPAQ: International Physical Activity Questionnaire score

AFHC: Adolescent Food Habit Checklist score

IAT: Internet Addiction Test score

Table 3.9 Delay Discounting moderating the effects of Health Risk Behaviors on Emotional Mental Health (DASS)

DASS-D_T2 DASS-A_T2 DASS-S_T2 β SE t β SE t β SE t

Model: DASS_T2 = β0 + β1*DASS_T1 + β2*HRB_T1 + β3*DD_T1 + β4*HRB_T1*DD_T1 + ε

DASS: Depression Anxiety Stress Scale 21 score

DASS-D: Depression subscale score; DASS-A: Anxiety subscale score; DASS-S: Stress subscale score

IPAQ: International Physical Activity Questionnaire score

AFHC: Adolescent Food Habit Checklist score

IAT: Internet Addiction Test score

3.2.4 Research Question 4: Does Parental Monitoring moderate the effect between Health Risk Behaviors and Emotional Mental Health?

The fourth set of analyses replaced Delay Discounting with Parental Monitoring as the moderator, as detailed in Tables 3.8 and 3.9 The findings revealed a significant interaction between Parental Monitoring and Smoking in relation to Depression [F(3,].

Table 3.10 Parental Monitoring moderating the effect of Smoking on Depression β SE t p

Research indicates that standardized data reveals a significant relationship between parental monitoring and depression levels in adolescents Specifically, when parental monitoring is one standard deviation above the mean, a one standard deviation increase in smoking correlates with a decrease of 0.26 standard deviations in DASS Depression scores from Time 1 (T1) to Time 2 (T2) Conversely, when parental monitoring is one standard deviation below the mean, a similar increase in smoking is associated with an increase of 0.26 standard deviations in DASS Depression scores from T1 to T2 This suggests that high levels of parental monitoring can mitigate the depressive effects of smoking, while low levels may exacerbate them.

2 It is noted that the smoking rate is extremely low, reducing the power of the analyses

Table 3.11 Parental Monitoring moderating the effects of Emotional Mental Health (DASS) on Health Risk Behaviors

IPAQ _T2 AFHC _T2 Smoking _T2 Drinking _T2 IAT _T2 β SE t β SE t β SE t β SE t Β SE t

Model: HRB_T2 = β0 + β1*HRB_T1 + β2*DASS_T1 + β3*PM_T1 + β4*DASS_T1*PM_T1 + ε

DASS: Depression Anxiety Stress Scale 21 score

DASS-D: Depression subscale score; DASS-A: Anxiety subscale score; DASS-S: Stress subscale score

IPAQ: International Physical Activity Questionnaire score

AFHC: Adolescent Food Habit Checklist score

IAT: Internet Addiction Test score

Table 3.12 Parental Monitoring moderating the effect of Health Risk Behaviors on Emotional Mental Health (DASS)

DASS-D_T2 DASS-A_T2 DASS-S_T2 β SE t β SE t β SE t

Model: DASS_T2 = β0 + β1*DASS_T1 + β2*HRB_T1 + β3*PM_T1 + β4*HRB_T1*PM_T1 + ε

DASS: Depression Anxiety Stress Scale 21 score

DASS-D: Depression subscale score; DASS-A: Anxiety subscale score; DASS-S: Stress subscale score

IPAQ: International Physical Activity Questionnaire score

AFHC: Adolescent Food Habit Checklist score

IAT: Internet Addiction Test score

Discussion

3.3.1 Description of health risk behaviors among Vietnamese high school aged adolescents

Preliminary findings indicate that 60% of Vietnamese high school adolescents fail to meet the global recommended physical activity levels, with about one-fifth not achieving the minimum of 30 minutes of daily activity This rate is slightly higher than that of adolescents in other developing countries, where an analysis of 72,845 school children aged 13 to 15 showed that only 23.8% of boys and 15.4% of girls met the recommendation of at least 60 minutes of physical activity on five or more days per week Additionally, a Global School Health Survey from 2007 to 2013 revealed an 80.4% prevalence of physical inactivity among 30,284 adolescents across seven ASEAN countries In contrast, developed countries report lower inactivity rates, with 52.1% of U.S teenagers aged 14-17 not adhering to national guidelines and varying compliance rates among males (35.8%) and females (46.4%) in ten European cities as per the HELENA study.

Achieving the recommended 60 minutes of daily physical activity for children can be challenging, especially since they spend 8-9 hours in school, predominantly engaged in sedentary activities Research indicates that substantial physical activity, ideally 60 minutes or more each day, is essential for health benefits from school-based interventions With Vietnamese adolescents currently falling short of this activity level, it is crucial to explore additional strategies to integrate more physical activity into their daily routines.

With respect to dietary patterns, approximately three quarters of respondents reported healthy attitudes regarding diet (i.e., awareness of the

A significant number of adolescents recognize the importance of a healthy diet, with over half providing positive responses regarding healthy eating habits However, there is a notable gap between their intentions and actual eating behaviors, as fewer students report consuming adequate fruits and vegetables or limiting sweets Specifically, less than 20% choose diet drinks, and under 30% consume three servings of fruit daily This discrepancy may stem from a lack of nutritional knowledge or social desirability bias Additionally, certain eating behaviors, such as the low endorsement of take-out food, may reflect broader Vietnamese dietary customs.

Tobacco smoking rates among Vietnamese youth are significantly lower compared to those in other Western and Asian countries, with only 10% of youth having tried smoking and approximately 1% reporting smoking in the past 30 days This is a decline from previous studies that indicated 8.9% to 18.2% of adolescents experimented with smoking, and 2.8% to 4.6% were current smokers The discrepancies in reported smoking rates may be attributed to variations in the age range of respondents, with studies focusing on older adolescents (ages 16 to 19) showing higher rates than those examining younger groups (ages 13 to 15 and 15 to 17) Additionally, differences in the types of smoking products assessed, such as the inclusion of non-tobacco items like e-cigarettes, along with the questionnaire administration process and sample characteristics, also contribute to the varied findings.

The prevalence of alcohol consumption by high school adolescents was concerning, with nearly half of the respondents reported having tried drinking

Approximately 102 individuals have consumed alcohol, with around 15% having drunk in the past 30 days Most participants only drank for one or two days, indicating they are not regular drinkers; however, the high rate of alcohol experimentation is noteworthy This aligns with existing studies on Vietnamese drinking culture, which promotes early alcohol consumption as a social and traditional practice, potentially increasing the risk of harmful drinking behaviors in the future.

The study revealed that nearly 10% of adolescents exhibited maladaptive Internet use patterns, with approximately two-thirds experiencing frequent issues related to their Internet usage This significant prevalence of problematic Internet use aligns with findings from other Asian countries, highlighting a serious concern for adolescent health and development It is important to note, however, that the cut-off score utilized was based on Young's recommendations and has not been specifically adapted for the Vietnamese context.

Gender significantly influences health risk behaviors, with males more likely to experiment with alcohol and tobacco, while females tend to be more physically inactive This disparity in physical activity may stem from biological differences during adolescence and societal norms shaping youth identities Furthermore, the gender gap in smoking and drinking is more pronounced in Asian societies, where cultural norms discourage these behaviors for females but not for males.

3.3.2 Relations between health risk behaviors and emotional mental health a Relations between four major health risk behaviors and emotional mental health

The "Big-4" health risk behaviors—physical inactivity, unhealthy eating, smoking, and drinking—are major contributors to non-communicable diseases and potential health loss These behaviors are grouped together due to their common characteristics and their similar associations with emotional and mental health issues, distinguishing them from problematic Internet use.

The study found no significant link between the four major health risk behaviors and emotional mental health problems However, a modest correlation was observed between an unhealthy diet and depression at two different timepoints These findings contrast with numerous previous studies, suggesting potential explanations for the discrepancies between this research and the existing literature.

From a developmental perspective, health risk behaviors are often a normative part of adolescence, particularly in Vietnam Experimentation with alcohol and tobacco plays a crucial role in identity formation for Vietnamese adolescents, influencing their acceptance or rejection of these substances Additionally, certain unhealthy dietary habits, such as eating out, serve adaptive functions by facilitating social interactions among peers during this critical developmental stage.

3 Depression was found to predict smoking, but given the extremely low amount of regular smoker, we don’t take this into consideration

Experimentation with such health risk behaviors therefore often is a natural occurrence in adolescence [79]

Excessive and prolonged engagement in unhealthy behaviors can negatively impact individuals' emotional and mental health Many models highlight the long-term effects of factors such as nicotine use, nutritional deficiencies, and a weakened immune system on the brain's neurochemical functioning However, in our study, the relatively short longitudinal timeframe limited our ability to determine if these unhealthy behaviors were becoming established habits or were simply part of normal development Additionally, the low rates of regular smoking and drinking among participants suggest that these behaviors were unlikely to cause observable harm to emotional mental health within the study's timeframe.

This pioneering study explores the predictive relationships between health risk behaviors and emotional mental health in an adolescent community sample from a developing Asian country The observed differences in findings compared to previous research, primarily conducted in Western nations, may stem from the general population's engagement in healthy behaviors and the cultural values surrounding them For instance, in many Asian societies, academic success is prioritized over physical activity, influencing how youth allocate their free time, often constrained by social and familial pressures.

Many students dedicate a significant amount of their free time to homework and supplementary classes to enhance their academic performance, especially during high school This academic pressure often leads them to prioritize studies over part-time jobs, household responsibilities, or sports Consequently, the relationship between physical activity and traits like cooperativeness, self-confidence, and self-directedness may differ in Vietnam compared to Western countries As a result, the lack of physical activity among Vietnamese youth may stem from various factors and might not impact their emotional and mental health during this critical period.

Healthy dietary behavior is linked to emotional mental health, with studies showing that unhealthy diets—characterized by high consumption of fast food, soft drinks, and sweets—are associated with increased mental health issues In Vietnam, however, the context differs; despite the presence of Western foods, their consumption remains low, as fast food is often viewed as a treat for special occasions rather than an everyday option While there is a rising trend in sugar and soft drink intake among Vietnamese teenagers, overall consumption is still below that of industrialized nations As teenagers gain more independence, particularly older teens, the prevalence of eating out and consuming "junk" food increases during this developmental stage.

In Vietnam, out-of-home food plays a crucial role in providing essential nutrition for a healthy diet, unlike in Western countries where "junk food" often leads to excessive calorie consumption.

[403] The prevalence of obesity and overweight is increasing in Vietnam, but it is not yet an issue of major concern in Vietnam [404] Thus, the effects of