Background
Health literacy is an essential individual characteristic and social resource that enables individuals and communities to access, understand, evaluate, and use health information and services in decision-making. It also includes the ability to communicate, prioritize, and express decisions (World Health Organization, 2014). Health literacy is vital as it reflects the ability to practice self-care and has been shown to improve health outcomes (Sørensen, 2024). Moreover, health literacy is linked to health outcomes across all age groups, with particular importance during adolescence—a period marked by increased risky health behaviors. Promoting health literacy enhances individuals’ capacity to understand, access, and utilize information and resources effectively for health promotion and disease prevention (Cordero Jr, 2023). Obesity is a significant health issue among adolescents.
A study examining health literacy in eight European countries using the HLS-EU-Q found that 12.00% of participants had limited health literacy, while 47.00% had insufficient health literacy (Sørensen et al., 2015). Duong et al. (2017) investigated health literacy levels in seven Asian countries using the same instrument and found that the mean health literacy score ranged from 29.60 to 34.40, indicating problematic health literacy among participants. In Thailand, the Thai Health Literacy Survey (THL-S) was used to assess health behaviors, diet, exercise, and emotions among people aged 15 and over (Ministry of Public Health, 2019). Unfortunately, 32.4% of this population still lacks health literacy due to an inability to access reliable health information (Khampang et al., 2022).
According to the current health situation of adolescents, overweight is increasing rapidly. More than 340 million male and female adolescents worldwide are overweight or obese (World Health Organization, 2022). In Thailand, overweight among adolescents is also rising. A survey by the Health Data Center (HDC) reported the prevalence of overweight (Body Mass Index: BMI ≥25 kg/m²) (World Health Organization, 2022) among the Thai population aged 20 years and over (21.40% of males and 47.00% of females) (Rittirong et al., 2021). Being overweight is related to daily healthy lifestyle behaviors, intrapersonal factors, environmental, family, and social factors, and habits or old ways of life resulting from health literacy. Therefore, health literacy is crucial for effectively managing overweight in adolescents.
The health behaviors of individuals are related to their health literacy. People with low health literacy often lack access to appropriate health information and services, leading to inadequate motivation to maintain good health, which results in inappropriate behaviors and health problems (Sørensen et al., 2012). Health literacy in the context of weight management is complex. People with high health literacy seek insights to maintain a healthy weight. Weight control involves many factors, including diet, exercise, behavior modification, education, motivation, and lifelong changes. Deciding to change and create a new way of life is essential for weight management and achieving desired goals (Carels et al., 2017; Winik & Bonham, 2018).
Late adolescents, aged 18-21 years, have a higher prevalence of overweight and obesity compared to children and early adolescents because this period involves transitioning from high school to university and from final-year students to adults. This developmental stage affects health behaviors that can either protect against or increase the risk of overweight and obesity (Somjaineuk & Suwanno, 2020). Despite the WHO recommendation for adolescents over 15 years to engage in moderate-to-vigorous physical activity for more than 60 minutes daily, many do not follow this guideline (Rhodes et al., 2019). Promoting overweight management and changing health behaviors in these groups will lead to better health in the next stages of life.
From the literature review, most previous studies have focused on general adolescent health literacy and related factors. Existing literature shows that health literacy among adolescents is influenced by age, gender, education, social support, and self-efficacy (Loer et al., 2020). Lee et al. (2016) confirmed that self-care activities were associated with health literacy among people living with diabetes. Additionally, a study in Taiwan suggested that perceived health status and depression were linked to health literacy (Chu-Ko et al., 2021). Previous studies also identified factors related to health literacy, including age, gender, educational level, prior knowledge, participation in activities, access to health services, and health behaviors (Basargekar et al., 2023; Bodur et al., 2017; Ramón-Arbués et al., 2023; Timur & Metin, 2023). Some studies in Thailand on obesity prevention behavior found a positive relationship between health literacy and obesity prevention behavior in undergraduate students at a moderate level. Moreover, health literacy showed a moderately positive correlation with obesity prevention behavior in adolescents (Chobthamasakul, 2019; Saeloo & Wiriyasirikul, 2020). While these studies cover various age groups, few have specifically addressed late adolescents regarding health literacy in overweight management, which presents the gap in this study.
Therefore, this study aimed to assess the level of health literacy in overweight management, identify factors related to health literacy in overweight management, and determine predictors of health literacy in overweight management among late adolescents in Thailand. The findings from this study may provide nurses with foundational information for promoting health literacy in overweight management for late adolescents who will transition into qualified adults. Nurses play a crucial role in helping adolescents manage their weight. To achieve this, nurses must understand the factors influencing health literacy in managing overweight among this population.
Methods
Study Design
This study employed a cross-sectional design.
Samples/Participants
The participants in this study were late adolescents studying at universities or colleges in Thailand. A purposive sampling technique was used to select the participants. The inclusion criteria were the ability to read and write in Thai. Participants who were absent from class on the data collection date were excluded.
The sample size was determined using the formula for estimating a finite population proportion (Cochran, 1977). The parameters specified were N = 34,021 (Office of the Permanent Secretary, 2022), p (prevalence of health literacy at fair and excellent levels) = 0.406 (National Reform Steering Assembly, 2016), d = 0.05, and α = 0.05. This calculation yielded a sample size of 366. To account for potential missing data, we increased the sample size by 10% (Krejcie & Morgan, 1970), resulting in a final requirement of 403 participants.
Data collection settings were selected using a multi-stage random sampling method. First, six regions in Thailand were randomly selected. Then, a stratified three-stage random sampling was performed: First, one region, the Northeastern region, was chosen. Second, one province within the Northeastern region was selected, which was Ubon Ratchathani. This province had four universities and one nursing college. In the third stage, a simple random sampling method was used to select one faculty from each university and college. The probability proportional to size method was utilized to recruit participants from each faculty. Figure 1 illustrates the multi-stage random sampling method used to select the study areas and samples, as developed by the authors.
Instruments
Ten instruments were used in this study. For instruments 2 through 10, which were newly developed, five experts assessed their content validity, finding that the content validity index ranged from 0.92 to 1.00. Factor analysis, including principal component analysis (Hutcheson & Sofroniou, 1999), was performed to investigate the construct validity using a separate dataset from a group of participants with characteristics similar to those in the main study, consisting of 150 participants. Details of the instruments are as follows:
Demographic Data Form: Developed by researchers, this form included questions about age, gender, marital status, educational level, and BMI.
Access to Health and Weight Control Resources Questionnaire: Developed by researchers and derived from two studies (Dubasi et al., 2019; Mikhail et al., 2020), this 5-item questionnaire was rated from 1 to 5. The total score ranged from 5 to 25, with categories: 5.00-11.67 (low level), 11.68-18.34 (moderate level), and 18.34-25.00 (high level). Construct validity was supported by a variance explanation of 77.59%, and reliability was confirmed with a Cronbach’s alpha coefficient of 0.90.
Prior Knowledge of Health and Control of Body Weight Questionnaire: This 10-item questionnaire, developed by pooling items from two studies (Dubasi et al., 2019; Mikhail et al., 2020), allowed participants to score 1 for correct answers and 0 for incorrect answers. Scores ranged from 0 to 10, categorized as 0.00-3.33 (low level), 3.34-6.67 (moderate level), and 6.68-10.00 (high level). Reliability, tested using KR-20, was 0.78.
Engagement in Training on Health and Weight Control Questionnaire: Developed by researchers and based on items from two studies (Dubasi et al., 2019; Pinto et al., 2013), this 5-item questionnaire was rated from 1 to 5. Scores ranged from 5 to 25, categorized as 5.00-11.67 (low level), 11.68-18.34 (moderate level), and 18.34-25.00 (high level). Construct validity was confirmed with a variance explanation of 76.67%, and reliability was supported by a Cronbach’s alpha coefficient of 0.86.
Access to Online Social Learning Resources about Health and Weight Control Questionnaire: This 5-item instrument, developed by researchers and based on two studies (Dubasi et al., 2019; Pinto et al., 2013), was rated from 1 to 5. The total score ranged from 5 to 25, with categories: 5.00-11.67 (low level), 11.68-18.34 (moderate level), and 18.34-25.00 (high level). Construct validity showed a variance explanation of 65.45%, and Cronbach’s alpha coefficient was 0.77.
Access to Books, Journals, and Websites on Health and Weight Control Questionnaire: Developed by researchers using items from two studies (Dubasi et al., 2019; Pinto et al., 2013), this 5-item questionnaire was rated from 1 to 5. Scores ranged from 5 to 25, categorized as 5.00-11.67 (low level), 11.68-18.34 (moderate level), and 18.34-25.00 (high level). Construct validity was supported by a variance explanation of 67.84%, and reliability was confirmed with a Cronbach’s alpha coefficient of 0.93.
Engagement in Student Development Programs Aimed at Promoting Health and Managing Weight Questionnaire: This 5-item instrument, developed by researchers and based on Dubasi et al. (2019), was rated from 1 to 5. The total score ranged from 5 to 25, with categories: 5.00-11.67 (low level), 11.68-18.34 (moderate level), and 18.34-25.00 (high level). Construct validity showed a variance explanation of 60.34%, and reliability was confirmed with a Cronbach’s alpha coefficient of 0.88.
Access to Specialized Weight Management Courses Questionnaire: Developed by researchers using items from Pinto et al. (2013), this 5-item questionnaire was rated from 1 to 5. The total score ranged from 5 to 25, categorized as 5.00-11.67 (low level), 11.68-18.34 (moderate level), and 18.34-25.00 (high level). Construct validity showed a variance explanation of 68.83%, and reliability was confirmed with a Cronbach’s alpha coefficient of 0.90.
Management of Weight Control Behavior Questionnaire: Adapted from the weight control strategies scale developed by Pinto et al. (2013), this 10-item instrument was rated from 1 to 5. Scores ranged from 10 to 50, with categories: 10.00-23.33 (low level), 23.34-36.67 (moderate level), and 36.68-50.00 (high level). Construct validity showed a variance explanation of 28.05%, and reliability was confirmed with a Cronbach’s alpha coefficient of 0.81.
Health Literacy in Overweight Management Questionnaire: This 15-item instrument, developed by researchers and based on two studies (Chobthamasakul, 2019; Chu-Ko et al., 2021), included two dimensions: 1) the ability to access data (10 items) and 2) the ability to appraise data (5 items). The total score ranged from 15 to 75, categorized as 15.00-35.00 (low level), 35.01-55.00 (moderate level), and 55.01-75.00 (high level). Construct validity was supported by variance explanations of 45.72% and 32.18%, and reliability was confirmed with a Cronbach’s alpha coefficient of 0.96.
Data Collection
After receiving approval from the Human Research Committee at Ubon Ratchathani Rajabhat University, Thailand, the questionnaires were distributed to the participants, and their recommendations were strictly followed. Data collection was conducted independently by the researchers from March 2023 to May 2023 without the assistance of research aides. The researchers read the questionnaires to each participant and provided appropriate explanations. Participants completed the questionnaires in approximately 20 minutes.
Data Analysis
The Statistical Package for the Social Sciences (SPSS) software version 29.0 (IBM Company, Chicago, USA) was used for data analysis. The researcher ensured the accuracy and completeness of all returned questionnaires. Participant characteristics were examined and described using percentages, means, and standard deviations (SD). The normality of data distribution was assessed using the Kolmogorov-Smirnov test. Pearson’s product-moment correlation coefficient was used for continuous independent variables if the data were normally distributed. Categorical independent variables were analyzed using Chi-square tests. Stepwise multiple regression was employed to evaluate the predictive power of selected variables in the study. Statistical significance was considered at p <0.05. Simple linear regression analysis was used to test assumptions and associations between independent variables, revealing linear associations among all pairs. Multicollinearity was assessed using the variance inflation factor (VIF), which indicated that the correlation between each pair of independent variables was below 2.04, suggesting minimal concern about multicollinearity. Consequently, multiple regression analysis was conducted.
Ethical Considerations
This research was approved by the Ubon Ratchathani University Ethics Committee for Human Research (Reference Number: HE662002). The consent and rights of the participants were prioritized. The researcher explained the research objectives to the participants and asked them to sign a consent form to participate. All obtained information was treated confidentially. The participants’ real names and surnames were not disclosed, and information was presented as an overview of the entire sample group. Participants could withdraw from the study at any time before the conclusion of data analysis without providing an explanation or affecting their learning.
Results
Characteristics of the Participants
The study results were based on a sample of 403 participants. Most participants were female (91.10%), with an average age of 20.70 ± 1.11 years. The majority were aged 20-21 years (54.30%) and were in their second year of study (38.50%). Their BMI categories were predominantly average (71.72%), overweight/obese (25.06%), and Class 2 obesity (3.22%).
Health Literacy in Overweight Management among Late Adolescents in Thailand
The findings of this study indicated that the mean health literacy score in overweight management among late adolescents in Thailand was at a moderate level (M = 47.7, SD = 8.17). Details regarding each dimension of health literacy in overweight management are presented in Table 1.
| Health literacy in overweight management | X | SD | Interpretation |
|---|---|---|---|
| Having the ability to access the data | 28.47 | 5.26 | Low level |
| Having the ability to appraise the data | 16.17 | 3.11 | Low level |
| Total scores | 47.77 | 8.17 | Moderate level |
Factors Related to Health Literacy in Overweight Management among Late Adolescents in Thailand
This study identified four factors significantly related to health literacy in overweight management among late adolescents in Thailand. First, access to health and weight control resources was moderately correlated with health literacy in overweight management (r = 0.368, p <0.001). Second, access to online social learning resources about health and weight control also showed a moderate correlation (r = 0.321, p <0.001). Third, access to books, journals, and websites on health and weight control was moderately correlated with health literacy in overweight management (r = 0.340, p <0.001). Finally, the management of weight control behaviors was also correlated, though to a lesser extent (r = 0.145, p <0.001) (see Table 2).
| Variables | r | p-value |
|---|---|---|
| Gender | -0.018a | 0.600 |
| Educational level | 0.028a | 0.100 |
| Age | 0.007 | 0.884 |
| BMI | 0.045 | 0.372 |
| Access to health and weight control resources | 0.368 | <0.001* |
| Prior knowledge of health and the control of body weight | -0.003 | 0.948 |
| Engagement in training on health and weight control | -0.070 | 0.162 |
| Access to online social learning resources pertaining to health and weight control | 0.321 | <0.001* |
| Access to books, journals, and websites on health and weight control | 0.340 | <0.001* |
| Engagement in student development programs aimed at promoting health and managing weight | 0.076 | 0.127 |
| Access specialized weight management courses | 0.085 | 0.089 |
| Management of weight control behavior | 0.145 | <0.001* |
Predicting factors of health literacy in overweight management among late adolescents in Thailand
Table 3 presents the results of the multiple regression analysis. It was found that the predictors of health literacy in overweight management among late adolescents in Thailand were access to health and weight control resources (X7), access to books, journals, and websites on health and weight control (X11), management of weight control behavior (X14), and access to online social learning resources about health and weight control (X10). Together, these four factors accounted for 20% of the variance in health literacy in overweight management among late adolescents in Thailand.
| Model | Unstandardized Coefficients | Standardized Coefficients | 95% Confidence Interval for B | Collinearity Statistics | |||||
|---|---|---|---|---|---|---|---|---|---|
| B | Std. Error | Beta (β) | t | Sig. | Lower Bound | Upper Bound | Tolerance | VIF | |
| (Constant) | -0.404 | 0.470 | -0.859 | 0.391 | -1.327 | 0.520 | |||
| Access to health and weight control resources (X7) | 0.318 | 0.092 | 0.192 | 3.472 | <0.001 | 0.138 | 0.499 | 0.657 | 1.522 |
| Access to books, journals, and websites on health and weight control (X11) | 0.304 | 0.081 | 0.196 | 3.762 | <0.001 | 0.145 | 0.463 | 0.740 | 1.351 |
| Management of weight control behavior (X14) | 0.249 | 0.094 | 0.121 | 2.646 | 0.008 | 0.064 | 0.434 | 0.969 | 1.032 |
| Access to online social learning resources pertaining to health and weight control (X10) | 0.110 | 0.042 | 0.141 | 2.622 | 0.009 | 0.028 | 0.192 | 0.699 | 1.432 |
| Model | df | F | Sig. | ||||||
| Regression | 4 | 24.874 | <0.001 | ||||||
| Multiple R = 0.447; R2 = 0.200; adjusted R2 = 0.192; S.E.est = 0.490; p <0.001 | |||||||||
Discussion
The findings showed that 91.10% of participants were female, and the prevalence of overweight was 25.06%. This aligns with the HDC survey, which reported a prevalence of overweight (BMI ≥25 kg/m²) among Thai people aged 20 years as 21.40% for males and 47.00% for females (Rittirong et al., 2021). It is evident that overweight remains a significant public health issue in Thailand, affecting people of all ages, including late adolescents. Contributing factors include improper eating habits, insufficient physical activity, and a sedentary lifestyle. This is consistent with the 6th physical examination report on Thai health (2019-2020), which found that 30.92% of Thai people aged 15-29 years had insufficient physical activity, while 24.93% had adequate leisure-time physical activity (34.71% of males and 14.60% of females) (Vancampfort et al., 2021).
The overall health literacy in overweight management among late adolescents was at a moderate level. Each aspect of health literacy—access, understanding, appraisal, and application—was also moderate, as based on Sørensen et al. (2012). This is consistent with Chobthamasakul (2019), which found that undergraduate students had an average level of health literacy in preventing obesity. The study found a moderate level of obesity prevention behavior, with health literacy positively related to these behaviors. This finding aligns with international research indicating that low health literacy is associated with higher rates of overweight and obesity (Chu et al., 2022). Individuals with low health literacy were more likely to have poor weight control strategies and seek inadequate weight-related health information (Toçi et al., 2021). Furthermore, low health literacy negatively impacted adherence to weight control methods and self-management of health behaviors (Liechty et al., 2015). Enhancing health literacy is crucial for better weight management outcomes and healthier lifestyles. Late adolescents need to practice healthy behaviors to manage excess weight effectively. With moderate knowledge of overweight management, their effectiveness in weight management and obesity prevention may be limited.
The study explored factors related to health literacy in overweight management among late adolescents in Ubon Ratchathani Province, including individual characteristics such as age, gender, education level, and BMI. The results indicated that these individual factors were not significantly related to health literacy in overweight management. This finding contrasts with other studies that found relationships between health literacy and factors such as age, gender, education level, knowledge, access to information, participation in activities, and overweight management behaviors (Bodur et al., 2017; Ramón-Arbués et al., 2023; Timur & Metin, 2023). It also differs from Simmons et al. (2017), which found a significant relationship between health literacy and BMI. Overweight/obesity was twice as high among individuals with insufficient knowledge compared to those with high levels of knowledge (Toçi et al., 2021). These differences may be due to variations in sample groups, such as age, education level, income, health literacy, and health behaviors. Additionally, late adolescents transitioning into early adulthood may have more opportunities to seek health information, which could improve their health literacy (Rong et al., 2017). As undergraduate students, they also have access to health education and promotion activities on campus, which can help manage their health issues to some extent.
The study identified four factors related to health literacy in overweight management among late adolescents in Ubon Ratchathani Province: 1) access to health and weight control resources, 2) access to online social learning resources about health and weight control, 3) access to books, journals, and websites on health and weight control, and 4) management of weight control behaviors. The overall predictive power of these factors on health literacy in overweight management among late adolescents was 20%.
Having good health knowledge, easy access to health services, health awareness, and participation in activities enables individuals to pursue knowledge, enhance skills, develop self-reliance, and foster a healthy mindset (Simmons et al., 2017). This indicates that these late adolescents utilized online health knowledge exchange channels to manage their excess weight. In today’s online and social media-driven society, late adolescents have access to quick and up-to-date information on health through platforms such as Facebook, LINE, and TikTok. This easy and convenient access to information about weight management—covering aspects such as food control, exercise, emotion management, and role models—helped them make informed decisions about weight management. As a result, they engaged in weight control behaviors, leading to healthy weight loss.
These findings align with a study by Rounsefell et al. (2020), which found that social media engagement and exposure to image-related content were significantly associated with body dissatisfaction, dieting, overeating, and healthy food choices. The qualitative analysis highlighted comparisons related to image modification, the perceived impact of social media, and seeking external information.
The literature review supports a significant and linear relationship between health literacy and adolescent health behaviors (Fleary et al., 2018). With the increasing digitalization of society, health information and services are now more accessible through various digital platforms and technologies. Digital health literacy—including the ability to obtain, comprehend, evaluate, and utilize digital health information—is crucial for effective health management (Sørensen, 2024).
However, individual factors and prior health literacy levels were not significantly related to health literacy in overweight management in this study. Nevertheless, the results emphasize the importance of online health knowledge exchange, access to health resources, and effective management of weight control behaviors in influencing health literacy among late adolescents. This highlights the need for further research, such as using meta-analysis methods to identify the most effective weight management programs for overweight adolescents (Narmkul et al., 2024) to enhance understanding of effective weight loss and health strategies.
Strengths and Limitations
The study offers several strengths and limitations. Among its strengths, the research stands out for its comprehensive analysis, employing multiple methods and instruments to assess health literacy in overweight management, which enhances the validity of the findings. The data collection from a sample of 403 participants, using various questionnaires and regression analyses, contributes to understanding the factors involved. Additionally, the focus on online social learning resources reflects contemporary trends in digital health literacy, aligning with technological advancements. However, there are notable limitations. The cross-sectional design restricts causal inferences, as it identifies correlations without determining causality. Although the sample size was sufficient, it was confined to late adolescents in Ubon Ratchathani Province, Thailand, which may limit the generalizability of the findings to other regions or age groups. The reliance on self-reported data could introduce biases, affecting the accuracy of the results. The absence of longitudinal data limits the ability to assess long-term effects on health literacy and weight management behaviors. Additionally, the study may have overlooked other influencing factors, such as socio-economic status or psychological factors, which could affect health literacy. Lastly, the cultural and contextual specificity of the study means that the findings may not be fully generalizable to different settings or populations.
Implications for Nursing Practice
The results of this study offer valuable insights for nursing practice in several key areas. First, nurses should routinely assess adolescents’ health literacy levels in overweight management using standardized instruments to ensure accurate evaluations. Second, based on the study’s findings, nurses should develop and implement comprehensive nursing interventions according to the specific factors identified. These interventions should emphasize enhancing adolescents’ access to health and weight control resources, such as social media platforms, books, journals, and websites, to improve their knowledge and skills in managing weight. Additionally, effective interventions should incorporate strategies for managing weight control behaviors, thereby supporting adolescents in adopting healthier habits and achieving better weight management outcomes.
Conclusion
This study highlights critical factors influencing health literacy in overweight management among late adolescents in Ubon Ratchathani Province, Thailand. The findings reveal that access to health and weight control resources, online social learning resources, books and journals on health, and management of weight control behaviors are significantly associated with health literacy. The predictive model shows that these factors collectively account for 20% of the variance in health literacy, indicating their importance in effectively managing overweight. This suggests that interventions should focus on enhancing access to diverse health resources and improving weight management behaviors rather than solely targeting individual demographics. The results also emphasize the growing role of digital and social media in disseminating health information. Future research should explore targeted, evidence-based interventions and programs to further enhance health literacy and address overweight issues among adolescents. By integrating these insights into practice, nurses and other healthcare professionals can better support adolescents in developing effective weight management strategies and promoting healthier lifestyles.
Declaration of Conflicting Interest
The authors declare no potential conflict of interest in this study.