Health literacy among the undergraduate students of Chhayanath Rara Municipality, Mugu

Abstract

Background

Health literacy is a critical component of achieving Sustainable Development Goal 3 (SDG3) and advancing Universal Health Coverage (UHC). Despite its importance, low health literacy is prevalent and linked to poor health outcomes, even among highly educated individuals particularly undergraduate students.

Objective

This study aimed to assess the level of health literacy among undergraduate students and identify factors influencing their health literacy.

Methodology

A quantitative, cross-sectional study was conducted among 196 undergraduate students of Rara Multiple Campus, Chhayanath Rara Municipality, Mugu district. Stratified random sampling with proportional allocation was used to divide students by academic year, followed by random selection within strata using a random number table. Health literacy was assessed using the 16-item short form of the European Health Literacy Survey Questionnaire (HLS-EU-Q16) which showed good reliability (Cronbach’s alpha = 0.85).

Results

Among the participants, 65.8% exhibited limited health literacy, while 34.2% had adequate health literacy. Significant associations were observed between health literacy and academic year, as well as the educational status of fathers. First-year students and those with illiterate fathers were at significantly higher odds of limited health literacy.

Conclusion

The findings reveal a high prevalence of limited health literacy among undergraduate students in Chhayanath Rara Municipality. Academic year and paternal education significantly influence health literacy levels. These results emphasize the need for targeted interventions to enhance health literacy, particularly in non-health-focused academic settings.

Introduction

Health literacy refers to the cognitive and social competencies that influence an individual’s motivation and capability to access, understand, and utilize information for the purpose of maintaining and enhancing their overall health [1]. The concept goes beyond simply reading health information and accessing healthcare services; it involves empowering individuals to effectively access and apply health information, with the goal of not only improving their own health but also contributing to the well-being of others [1]. An individual with an adequate level of health literacy is empowered to make informed decisions regarding their own health. However, improving the health literacy of families and communities is a shared responsibility that requires support from health systems, organizations, and community structures [2].

Over the past three decades, health literacy has gained significant global attention as a critical aspect of public health [3]. The World Health Organization (WHO) highlights health literacy as essential for achieving Sustainable Development Goal 3 (SDG3) and advancing Universal Health Coverage (UHC). Beyond infrastructure, UHC requires empowering individuals to navigate and utilize health resources effectively. During the 9th Global Conference on Health Promotion in 2016, the WHO introduced the Shanghai Declaration, which underscores the critical role of health literacy as a fundamental building block for achieving health and sustainable development in the forthcoming decades [4].

Despite its importance, data on health literacy in developing nations like Nepal remains limited [5]. Nepal’s distinctive cultural heritage and traditional beliefs significantly influence health-related perceptions and practices. There are many misconceptions and deeply rooted cultural beliefs about health, illness, and healthcare persist within society [5]. Widespread internet access has raised significant concerns regarding the health literacy of young adults and the reliability of the information they access. Restricted search capabilities or lower literacy skills can pose challenges for young adults in locating and comprehending high-quality information [6]. These difficulties can significantly impact their ability to engage in self-care and manage chronic illnesses [5].

Young adults are at a crucial stage for developing independent decision-making skills, making accurate and reliable health knowledge essential for fostering lifelong healthy habits and empowering them to take responsibility for their well-being [6]. However, many undergraduate students face literacy challenges, with a significant number unable to read at the expected grade level [7, 8]. Research on health literacy among undergraduate students in rural areas like Chhayanath Rara Municipality, Mugu District, Nepal, is limited, despite unique challenges such as healthcare access, geographical isolation, and cultural norms [5, 9, 10]. This study aims to address these gaps, providing insights to develop tailored health education initiatives that empower undergraduate students of rural populations and promote equitable public health outcomes across Nepal, thus contributing SDG4.

Methodology

A cross-sectional study design was used to assess health literacy among the undergraduate students of Chhayanath Rara Municipality in the Mugu district. Ethical approval was obtained from the Institutional Review Committee of Chitwan Medical College (CMC-IRC/080/081 − 076), and the study was conducted in accordance with the ethical principles outlined in the Declaration of Helsinki. The study was conducted from January to May 2024, and the study population comprised students currently enrolled in Bachelor’s 1st, 2nd, 3rd, and 4th years at Rara Multiple Campus.

To promote inclusive participation, various strategies were considered to minimize barriers for students with disabilities. The questionnaire was designed with simple and clear language in Nepali, pilot-tested, and revised to be accessible to students with varying levels of comprehension. Participants were also given the option to seek clarification on any question in a respectful and non-intrusive manner.

However, students who were deaf, had significant degrees of hearing loss, or were acutely ill at the time of data collection were excluded. This was due to the study’s reliance on verbal interaction for informed consent and the standardized nature of the self-reported health literacy tool, which had not been validated in sign language or alternate communication modes. We acknowledge this as a limitation in inclusivity. In future studies, adaptation of tools in sign language and use of assistive technologies will be considered to ensure broader accessibility and participation of individuals with diverse auditory conditions.

Prior to participation, students provided informed written consent and were clearly informed about the study’s objectives, procedures, and their rights, including the right to withdraw from the study at any time without repercussions. Permission to conduct the study was also granted by Rara Multiple Campus. The researcher was directly involved in every step of the research process, ensuring thoroughness and adherence to research standards [Clinical trial number: Not applicable]. The total sample size for the study was 196 calculated using Cochran’s formula for finite population.

Sampling technique

The Stratified Random Sampling technique with proportional allocation was used in this study. At first, we created four strata i.e. Strata 1 (Bachelor 1st year), Strata 2 (Bachelor 2nd year), Strata 3 (Bachelor 3rd year) and Strata 4 (Bachelor 4th year) where we assumed there was homogeneity regarding education level within four different strata and heterogeneity regarding currently studying year between strata [16]. Then, the total sample size was divided for these four strata proportionately. After deciding the sample size for each strata proportionately, we created a sampling frame for each strata before 1 week of data collection and entered the data in MS Excel. Finally, the participants from each strata were chosen by simple random sampling (random number table). The flowchart illustrating the sampling technique is shown in Fig. 1.

Fig. 1.

Flowchart of sampling technique

A semi-structured interviewer administered questionnaire was developed to collect data from all the students. The questionnaire included two sections:

Section A: Socio-demographic characteristics.

Section B: Self Rated Variables.

Section C: European Health Literacy Survey Questionnaire.

The European Health Literacy Survey Questionnaire consists of 16 items and items related to health care are (7 out of 16 questions), disease prevention (5 out of 16) and health promotion (4 out of 16).

The 16 items were rated on a scale ranging from “very difficult” to “very easy,” with an additional option for “don’t know.” Each response was assigned a numerical value: 1 for “very difficult,” 2 for “difficult,” 3 for “easy,” 4 for “very easy,” and 0 for “don’t know.” The average score across all items was computed, and subsequently transformed into an index using the prescribed formula by the European health literacy consortium [5].

The index scores were categorized into four levels of health literacy according to the thresholds set by the HLS-EU consortium: Excellent (scores between 42 and 50), Sufficient (scores between 33 and 42), Problematic (scores between 25 and 33), and Inadequate (scores between 0 and 25) [11]. A self-administered questionnaire was employed for data collection, allowing participants to provide their responses independently. The questionnaire took approximately 15 min, was administered in Nepali language, and some questions were simplified after pilot testing. This method was chosen to minimize interviewer bias and ensure the confidentiality of participants’ responses. The content validity of the tool was ensured through consultations with supervisors, subject matter experts, and public health faculty, alongside peer review and a thorough review of relevant literature. To ensure translation accuracy, the questionnaire was back-translated by a peer with no prior knowledge of the original version, allowing for comparisons with the original to maintain quality and consistency. The HLS-EU-16 questionnaire showed good internal consistency with a Cronbach’s alpha of 0.85 [12].

After the collection of data, data were checked thoroughly, editing and coding were done and entered in EpiData 3.1 and exported to IBM SPSS 20 version software for further analysis. The collected data was analyzed using basic descriptive statistics, including percentages and frequencies, median, and IQR depending upon the normality test checked by using Shapiro-wilk test. Bivariate analysis, either using the Chi-square test or Fisher’s exact test, was conducted to investigate the non-directional relationship between the dependent variable (health literacy) and each independent variable. The categories “adequate” and “limited” health literacy were coded as 0 and 1, respectively, for the dependent variable. Similarly, the explanatory variables were coded as 1 for presence of a categorical effect and 0 for the absence of a categorical effect. To check significance of different factors, the chi-square test was used separately for each explanatory variable. Variables which were significantly associated with limited health literacy at 5% level of significance in chi-square test were further proceeded to check the assumption of multicollinearity between independent variables. Considering all significant factors from the chi-square test and those which satisfy the assumption of multicollinearity, a multiple binary logistic regression was run to see the impact of those significant factors in limited health literacy.

Results

Table 1 presents the background information of the respondents.

Table 1.

Socio-demographic information (n = 196)

Variables	Frequency	Percentage (%)
Age group
20–24	150	76.5
25–29	46	23.5
Median(Q3-Q2) = 23(24 − 22)
Min/Max = 20/28
Sex
Male	95	48.5
Female	101	51.5
Place of origin
Rural	154	78.6
Urban	42	21.4
Employment status mother
Unemployed	40	20.4
Employed	156	79.6
Employment status of father
Unemployed	31	15.8
Employed	165	84.2
Educational status of Father
Illiterate	56	17.3
Literate	140	82.7
If literate, ( n  = 140)
Informal education	13	2.86
Primary education (1–8)	56	40
Secondary education (9–12)	71	50.7
Educational status of mother
Illiterate	65	20.1
Literate	131	79.9
If literate, (n = 131)
Informal education	6	4.6
Primary education (1–8)	84	64.1
Secondary education (9–12)	41	31.3
Academic year
Bachelor 1st year	52	16.0
Bachelor 2nd year	42	13.0
Bachelor 3rd year	48	14.8
Bachelor 4th year	54	16.7

Socio- demographic characteristics

A total of 196 students were included in the analysis. The age of the respondents ranged from 20 to 29 years, with the median age of 23 years and an interquartile range (IQR) of 2. The majority of respondents (76.5%) were aged between 20 and 24 years. Females constituted the majority, accounting for 51.5% of the participants. When categorizing place of origin as rural and urban, the majority of respondents (78.6%) were from rural areas. A significant proportion of participants reported that their mothers (79.6%) and fathers (84.2%) were employed. In terms of academic progression, the highest enrollment was observed among fourth-year bachelor-level students, representing 27.6% of the total student population.

Table 2 shows that websites were the most common source of health information (15.2%), followed closely by friends (14.8%), parents (14.4%), and health workers (14.3%). Schools, media (radio/TV), and social media also contributed similarly, each around 13–14%. This highlights the diverse sources individuals use, emphasizing the need for multi-channel health communication strategies.

Table 2.

Source of information (n = 196)

Source of information##	Frequency	Percentage (%)
Parents	145	14.4
Friends	149	14.8
Doctors or health workers	144	14.3
Internet or websites	153	15.2
Schools or educational programs	140	13.9
Radio or TV	133	13.2
Social media platforms	145	14.4

## Multiple response questions

Table 3 summarizes participants’ health and financial status. Most reported moderate health (53.6%) or good health (32.1%), with fewer indicating excellent (7.7%) or poor health (6.6%). Financially, the majority identified as middle class (81.2%), followed by poor (16.3%) and rich (2.5%). These findings shed light on participants’ perceived well-being.

Table 3.

Self-rated variables information (n = 196)

Self-rated variables	Frequency	Percentage (%)
Health Status
Excellent	15	7.7
Good	63	32.1
Moderate	105	53.6
Poor	13	6.6
Financial status
Poor	32	16.3
Middle class	159	81.2
Rich	5	2.5

Table 4 illustrates the distribution of health literacy levels among the students, presented into four categories: inadequate, problematic, sufficient, and excellent. Among the respondents, 14.8% of the total had inadequate health literacy levels. A slightly higher proportion i.e. 16.8% of the sample fell into the problematic category while 26% were categorized as having sufficient health literacy. Notably, the largest segment of respondents i.e. nearly half (42.3%) of the total, demonstrated excellent health literacy levels.

Table 4.

Level of health literacy (n = 196)

Health literacy level	Frequency (%)	Percentage (%)
Inadequate	92	46.9
Problematic	36	18.4
Sufficient	46	23.5
Excellent	22	11.2
Dichotomized level of health literacy
Adequate health literacy	67	34.2
Limited health literacy	129	65.8

Dichotomized categorization of health literacy levels among the participants, categorized into two groups: limited health literacy and adequate health literacy. Among the respondents, 31.6% of the total, were identified as having adequate health literacy while more than half 68.4% of the students demonstrated limited health literacy.

Table 5 presents the bivariate analysis of health literacy and socio-demographic factors. No significant associations were found between limited health literacy and characteristics such as age, sex, place of origin, or parents’ employment and mothers’ education. However, academic year was significantly associated with health literacy (p < 0.001). First-year students were more likely to have limited health literacy compared to fourth-year students (COR = 23.182, 95% CI: 6.395–84.031), with similar trends observed for second- and third-year students. Additionally, father’s education showed a significant association; students with literate fathers had a 46.6% lower likelihood of limited health literacy compared to those with illiterate fathers.

Table 5.

Association of socio-demographic variables with level of health literacy (n = 196)

Socio-demographic characteristics	Health literacy		p-value (χ2)	COR (95% CI)
	Adequate (%)	Limited (%)
Age
20–24	46(30.7)	101(69.3)	0.061	0.754(0.294–1.939)
25–29	21(45.7)	25(54.3)		Ref
Sex
Male	38(40)	57(60)	0.096	0.816(0.419–1.589)
Female	29(28.7)	72(71.3)		Ref
Place of origin
Rural	54(35.1)	100(64.9)	0.618	0.968(0.434–2.157)
Urban	13(31.0)	29(69.0)		Ref
Employment status of mother
Employed	13(32.5)	27(67.5)	0.801	1.095(0.515–2.329)
Unemployed	54(34.6)	102(65.4)		Ref
Employment status of father
Employed	12 (38.7)	19 (61.3)	0.563	0.713(0.317–1.604)
Unemployed	55 (33.3)	110 (66.7)		Ref
Mother’s educational status
literate	54(34.6)	27(67.5)	0.801	1.119(0.513–2.443)
Illiterate	13(32.5)	102(65.4)		Ref
Father’s educational status
literate	26(46.4)	30(53.6)	0.022*	0.466(0.245–0.888)
Illiterate	41(29.3)	99(70.7)		Ref
Academic year
Bachelor 1st year	3	51	< 0.001*	23.182(6.395–84.031)
Bachelor 2nd year	16	26	0.061	2.216(0.965–5.087)
Bachelor 3rd year	18	30	0.05*	2.273(1.019–5.071)
Bachelor 4th year	30	22		Ref

*= Significant association (by applying Pearson chi-square test at 5% level of significance), Ref = Reference category, COR = Crude Odds Ratio (from bivariate analysis), CI = Confidence Interval

Table 6 examines the relationship between self-rated factors and health literacy levels. No significant association was found between self-rated health status and health literacy (p = 0.532). However, self-rated financial status showed a significant association (p = 0.004). Participants with poor financial status had significantly higher odds of limited health literacy compared to those with good financial status (COR = 4.245, 95% CI: 1.399–12.881).

Table 6.

Association of self-rated variables with level of health literacy (n = 196)

Self-rated variables	Health literacy		p-value (χ2)	COR (95% CI)
	Adequate (%)	Limited (%)
Self–Rated Health Status
Unsatisfactory	39(32.5)	81(67.5)	0.532	1.276(0.676–2.410)
Satisfactory	28(36.8)	48(63.2)		Ref
Self–Rated Financial Status
Poor	4(12.5)	28(87.5)	0.004#	4.245(1.399–12.881)
Good	63(38.4)	101(61.6)		Ref

# denotes significant association by applying Fisher Exact test at 5% level of significance), Ref = Reference category, COR = Crude Odds Ratio, CI = Confidence Interval

Multicollinearity between independent variables

Those independent variables which were statistically significant (p < 0.05) and associated with limited health literacy among students were further used to test the multicollinearity among those independent variables. Since, all the values of VIF’s are less than 10 and the tolerance value is greater than 0.1, it indicates that there is no multicollinearity among the independent variables in the proposed model (Table 7).

Table 7.

Multicollinearity between independent variables

Variables	Tolerance	VIF
Father’s educational status	0.758	1.319
Self-rated financial status	0.983	1.018
Academic year	0.747	1.339

VIF denotes Variance Inflation Factor

Three variables—self-rated financial status, academic year, and father’s educational status—were significantly associated with limited health literacy (P < 0.05) during bivariate analysis and were included in the multivariate logistic regression. Multicollinearity testing revealed no serious collinearity issues (highest VIF = 1.28).

Table 8 presents the factors associated with the level of health literacy, including the odds ratios and confidence intervals. Participants with illiterate fathers had significantly reduced odds of adequate health literacy (AOR = 0.469, 95% CI: 0.238–0.926, P = 0.029) compared to those with literate fathers. First-year students were significantly more likely to have limited health literacy compared to fourth-year students (AOR = 27.024, 95% CI: 6.224–117.34, P < 0.001). While self-rated financial status was significant in the bivariate analysis, it lost significance after adjustment.

Table 8.

Factors associated with level of health literacy (n = 196)

Variables	β	COR (95% of CI)	AOR (95% of CI)	P-value
Father’s educational status
Illiterate	-0.883	0.466(0.245–0.888)	0.469(0.238–0.926)	0.019*
Literate			Ref
Academic year
Bachelor 1st year	3.297	23.182(6.395–84.031	27.024(6.224–117.34)	0.001*
Bachelor 2nd year	0.790	2.216(0.965–5.087)	2.203(0.915–5.303)
Bachelor 3rd year	0.747	2.273(1.019–5.071)	2.111(0.931–4.787)
Bachelor 4th year		Ref	Ref
Constant	-0.022

*=Significant at p < 0.05, Ref = Reference Category, COR = Crude Odds Ratio, AOR = Adjusted Odds Ratio (from multivariate analysis), CI = Confidence Interval, Cox & Snell R² = 0.201, Nagelkerke R² = 0.278, Hosmer and Lemeshow = 0.902

These findings confirm that academic year and father’s educational status are key determinants of health literacy among students.

Log odds of limited health literacy among students = -0.022– 0.883 illiterate father.

+ 3.297 first year student is the fitted logistic regression equation.

Discussions

This study revealed that 65.8% of undergraduate students in Chhayanath Rara Municipality, Mugu, Nepal, had limited health literacy. This finding is in line with a university-based study conducted at Tribhuvan University, which reported that 60.8% of students had limited health literacy [5]. Similarly, a recent study in rural Nepal [9] found that over 70% of adults had problematic or inadequate health literacy, demonstrating a widespread issue in underserved areas. A finding of this study also coincides with similar findings from a university-based study conducted in Ghana [12].

The high prevalence of limited health literacy in Nepalese students contrasts with results from higher-income countries. In a study across eight European countries, the prevalence of limited health literacy ranged from 29 to 62%, with an average of 47% [11]. In the United States and Canada, studies have reported substantially lower rates, with only 7–15% of university students exhibiting limited health literacy [13]. These disparities may be attributed to variations in study settings; developed countries with higher levels of economic development tend to enjoy greater allocations of health resources and improved access to health information, unlike developing nations such as Nepal [5].

In our study, a significant association was found between academic year and health literacy. Fourth-year students were far more likely to possess adequate health literacy than first-year students (AOR = 27.02, 95% CI: 6.22–117.34). This trend aligns with findings from both Nepal and other countries. For example, a study observed that health sciences students in advanced academic years had better health literacy scores [1]. Similarly, Australia [14] and China [15] noted an increase in health literacy with academic progression. These results support the idea that educational exposure and maturity contribute to improved health literacy skills, aligning with SDG4, which advocates for inclusive and equitable education at all levels [16].

Another key predictor identified in this study was the educational status of the father. Students with literate fathers had significantly better health literacy compared to those with illiterate fathers (AOR = 0.469, 95% CI: 0.238–0.926). This observation is consistent with findings from Palestine [3] and China [17], where parental education was positively correlated with student health literacy. Within Nepal, two studies similarly reported the influence of parental education, especially fathers, as a determinant of literacy outcomes [5, 18].

Though financial status was not significant in multivariate analysis, bivariate results showed that students with poor self-rated financial status were more likely to have limited health literacy. This aligns with a study from Rasuwa, Nepal [9] which found that economic hardship was associated with lower health literacy. Similarly, another study found that in Southeast Asia, socioeconomic disparities strongly influenced health literacy levels [19].

Our study also highlights the importance of place of residence. While not statistically significant in our analysis, other studies emphasize that rural residents generally face more barriers to accessing health information, health services, and education, leading to lower health literacy [10, 20].

Mass media and internet use were frequently cited as sources of health information by our participants. However, the quality and credibility of these sources remain a concern. Studies have shown that while digital sources are popular, they often contribute to misinformation when students lack the skills to evaluate content critically [6, 21].

In summary, academic year, father’s education, and financial background emerge as the most influential predictors of health literacy in our study. These findings align with the growing body of research in both Nepal and other countries, indicating that education, socioeconomic status, and access to information are key drivers of health literacy. Recognizing these predictors is essential for developing targeted interventions and integrating health literacy education across university curricula, especially in rural and under-resourced areas. Our study provides crucial evidence that can support policymaking, educational reform, and public health initiatives aimed at improving youth health literacy in Nepal.

Limitations

This study has several limitations that should be considered when interpreting its findings. The research was conducted within a single rural municipality and included students from only one academic institution, which may limit the generalizability of the results to the broader undergraduate population in Nepal.

The use of self-reported data introduces potential response bias, as participants may have provided socially desirable answers or responded without fully considering each item. This could affect the accuracy of the measured levels of health literacy.

Although the HLS-EU-Q16 is a validated tool, it was originally developed in a European context. Despite rigorous translation, back-translation, and pilot testing, some items may not fully reflect the cultural and contextual realities of rural Nepali youth. This underscores the need for further development or contextual adaptation of health literacy tools for the Nepali population.

Despite efforts to promote inclusivity, individuals who were deaf or had significant hearing loss were not included in the study. The tool’s reliance on verbal instructions and lack of validation in sign language or alternative communication methods limited their participation. This exclusion affects the representativeness of the findings and highlights the importance of incorporating accessible research tools in future studies.

The cross-sectional design of the study also limits the ability to infer causality between health literacy and associated factors. Future research could benefit from mixed-methods or longitudinal approaches and broader, more diverse samples across both urban and rural settings.

Conclusions

This study revealed a high prevalence of limited health literacy among undergraduate students in Chhayanath Rara Municipality, with significant associations observed between health literacy levels and both academic year and father’s educational status. These findings suggest that health literacy challenges persist even among populations engaged in higher education, highlighting gaps in the current education system’s ability to equip students with practical health-related knowledge and skills. Limited health literacy can hinder individuals’ capacity to make informed health decisions, potentially impacting their well-being and that of their families and communities.

The findings underscore the need for public health policies that prioritize health literacy as a fundamental component of health promotion, especially in remote regions. There is a pressing need to integrate structured health literacy components into academic curricula, particularly within non-health institutions, to ensure that students are adequately equipped to understand and navigate healthcare systems.

Participants also conveyed a clear need for organizations in Nepal such as schools, healthcare institutions, and local governments to strengthen their organizational health literacy, making health information and services more accessible and understandable. Simultaneously, the development of personal health literacy is hindered by limited access to digital infrastructure, culturally relevant educational materials, and community-based health education support.

In conclusion, improving health literacy in Nepal requires a coordinated and localized approach that strengthens both individuals’ capacity to understand and use health information, and institutions’ ability to support them effectively.

Recommendations

It is of essence to enact targeted policies aimed at fostering health literacy-friendly environments within healthcare institutions. Additionally, it is recommended to conduct further studies utilizing longer versions of health literacy survey questionnaires along with qualitative aspects to delve deeper into the determinants of health literacy. Furthermore, efforts should be made to integrate health literacy education into academic curricula across various disciplines, ensuring that individuals receive adequate training regardless of their field of study.

Author contributions

P.G. conceptualized the study, designed the methodology, conducted data collection, data analysis and interpretation. N.M. contributed in drafting the manuscript. D.K. assisted in preparing tables and figures and also in reviewing relevant literature. And U.B. reviewed and revised the manuscript critically for intellectual content. All authors reviewed and approved the final manuscript.

Funding

No funding sources.

Data availability

Data is provided within the related files.

Declarations

Competing interests

The authors declare no competing interests.