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Abstract

Background

Health-promoting behaviors are crucial for maintaining well-being, especially among university students who face various lifestyle challenges.

Aim

This study aimed to evaluate Taibah University students’ Health-Promoting Lifestyle Profiles in Saudi Arabia, focusing on the influence of age, gender, and body mass index (BMI) on health-related behaviors.

Methods

A descriptive, cross-sectional study was conducted in Saudi Arabia. A total of 397 valid questionnaires were analyzed. A systematic random sampling method was employed, selecting every 20th student from predetermined lists to ensure a balanced representation, with 100 students from each college. Data were collected using a demographic questionnaire and the validated Health-Promoting Lifestyle Profile II (HPLP-II).

Results

Most participants had a normal BMI (18.5–24.9 kg/m²), with 71.4% of males and 63.3% of females classified as normal weight. Underweight status was more prevalent among females (23.4%) than males (13.4%) (χ² = 7.973, p = .047), and obesity was rare (2.8% in males, 0.9% in females). Females had significantly higher health responsibility scores (M = 24.99, SD = 6.74) compared to males (M = 23.41, SD = 7.19) (t = 2.252, p = .025). They were more engaged in health-promoting behaviors, with 66.1% of females classified at a high HPLP-II level versus 41.3% of males. Younger females (>20 years) exhibited significantly higher physical activity scores (M = 22.67, SD = 5.22) than older females (>20 years) (M = 19.93, SD = 6.87) (p = .004).

Conclusion

Females demonstrated higher health responsibility and engagement in health-promoting activities than males, with younger females being more physically active. Body mass index significantly influences spiritual growth and overall health behaviors, highlighting the importance of considering demographic and anthropometric factors in health promotion strategies among university students.

Keywords

health physical activity nutrition spiritual stress management university students promoting well-being lifestyle

Introduction

University life in Saudi Arabia, as elsewhere, marks a critical developmental stage during which students face a range of psychological, social, and academic pressures that significantly influence their health behaviors (Deng et al., 2022; Zaky, 2017). These behaviors are vital determinants of both current and future health outcomes, as unhealthy lifestyles adopted during this period can lead to chronic illnesses and mental health issues (Ramadan Atta et al., 2024; Rasmussen et al., 2020; Reyes-Molina et al., 2022; Zhang et al., 2022).

To date, no study has systematically examined the six core components of a health-promoting lifestyle—health responsibility, physical activity, nutrition, spiritual growth, interpersonal relations, and stress management—within this population. This lack of integrated data limits the ability of institutions to develop targeted strategies that foster student well-being and academic success (Almutairi et al., 2018; Atta et al., 2024a; Sales et al., 2024; Sinval et al., 2024). Therefore, this study seeks to fill this gap by being the first to comprehensively evaluate health responsibility, physical activity, nutrition, spiritual growth, interpersonal relations, and stress management among university students in Saudi Arabia, offering evidence to inform culturally relevant and effective health-promotion interventions.

Review of Literature

The academic stage represents a crucial transition from adolescence to adulthood, marked by significant behavioral, psychological, and physiological changes (Ali et al., 2024; Amin et al., 2025; Zaky, 2017). During this period, students experience increased independence, responsibility, and exposure to diverse social and academic pressures (Atta et al., 2024b; Deng et al., 2022). These developmental changes often influence their health-related behaviors, shaping their overall well-being. The combination of academic demands, social expectations, and personal growth may lead students to adopt healthy or unhealthy lifestyles (Lesińska-Sawicka et al., 2021). A healthy lifestyle includes health responsibility, physical activity, nutrition, spiritual growth, interpersonal relations, and stress management. However, the extent to which students engage in these behaviors varies, and many may struggle to maintain a balanced approach to health (Haddad et al., 1998), which increases their risk for chronic diseases and mental health disorders (Aceijas et al., 2017; Rasmussen et al., 2020; Reyes-Molina et al., 2022; Zhang et al., 2022).

The World Health Organization (WHO) defines health promotion as a transformative process that enables people to actively improve their health and assume responsibility for their well-being (WHO, 2021). University students are particularly vulnerable to poor health outcomes due to academic stress (Rushdan et al., 2024; Zhang et al., 2022), sedentary behaviors (Merchán-Sanmartín et al., 2022; Reyes-Molina et al., 2022), unhealthy dietary patterns (Lanuza et al., 2022), social influences (Aceijas et al., 2017), and the stress associated with life transitions (Amin et al., 2024; Gardani et al., 2022).

A lifestyle encompasses a person's way of living and can be classified as either healthy or unhealthy based on individual behavioral choices. Walker et al. (1987) define a health-promoting lifestyle as a multidimensional pattern of self-initiated actions and perceptions aimed at maintaining or improving wellness, self-actualization, and personal fulfillment. A health-promoting lifestyle is a crucial determinant of overall health status and plays a significant role in maintaining and enhancing well-being (Mirghafourvand et al., 2015).

Modifiable behaviors such as dietary habits, physical activity, and smoking significantly contribute to the development of chronic diseases. Research from both Western and Arab regions indicates that adolescents and young adults fail to meet dietary and physical activity recommendations. Common unhealthy behaviors include insufficient consumption of fruits and vegetables, meal skipping, high-fat intake, and inadequate physical activity (Musaiger et al., 2017; Santaliestra-Pasías et al., 2014; Yahia et al., 2016). Additionally, findings from a large national survey in Saudi Arabia revealed that among individuals aged 15 years and older, 12.2% were current tobacco users. In contrast, 16.0% had smoked tobacco at some point in their lives. The prevalence of smoking was notably higher among males (21.5%) compared to females (1.1%) (Moradi-Lakeh et al., 2015).

Theoretical Underpinnings and the Gap in Knowledge

Understanding health behaviors among university students requires a holistic perspective that considers the broader determinants of health. The Dahlgren and Whitehead socioecological model provides a comprehensive framework by organizing health determinants across five hierarchical levels: (i) general socioeconomic, cultural, and environmental conditions; (ii) living and working conditions; (iii) social and community networks; (iv) individual lifestyle factors; and (v) age, sex, and constitutional factors (Dahlgren et al., 2006; Dahlgren & Whitehead, 2021 2021). Each level interacts to influence health outcomes, with inequitable access to protective or risk-modifying resources contributing to health disparities (Jahnel et al., 2022).

To better understand and address the factors contributing to unhealthy behaviors among university students, it is essential to adopt a conceptual and theoretical lens grounded in established behavior change models. Frameworks such as the Health Belief Model (HBM) and Social Norms Theory emphasize the role of individual perceptions, peer influence, and perceived susceptibility in shaping health-related decisions. More recently, the COM-B model, standing for Capability, Opportunity, and Motivation, has been widely recognized as a comprehensive approach to analyzing the drivers of behavior (Michie et al., 2011; Michie et al., 2014). According to this model, behavior change interventions must account for an individual's psychological and physical capability, the social and environmental opportunities available to them, and the motivational processes that energize or inhibit action. In the context of student populations, such as pharmacy students across twelve countries, studies have shown that academic resilience and behavioral responses are shaped by multiple interacting personal and contextual factors (Elnaem et al., 2024).

A study conducted in Saudi Arabia by Almutairi et al. (2018) examined the health-promoting lifestyle of university students through a cross-sectional assessment. The findings indicated that the majority of participants were female (70.4%), with 20% classified as overweight and 11.3% as obese. A significant difference was observed between students in health-related and nonhealth-related colleges concerning health responsibility, with those in health colleges demonstrating higher awareness. However, students from both groups exhibited inadequate adherence to physical activity and healthy eating recommendations.

Failure to adopt healthy behaviors during this critical stage can have significant consequences on students’ health. Poor health responsibility, such as neglecting preventive care or unhealthy coping mechanisms, can increase vulnerability to chronic diseases (Sales et al., 2024). Physical inactivity and poor nutrition contribute to obesity, metabolic disorders, and weakened immune function. A lack of spiritual growth and weak interpersonal relationships may lead to emotional distress, reduced resilience, and a decline in mental well-being. Furthermore, inadequate stress management can result in anxiety, depression, and burnout, negatively impacting academic performance and overall quality of life (Hamzaa et al., 2024). Addressing these challenges requires fostering awareness and encouraging students to adopt sustainable, health-promoting behaviors that support their transition into adulthood (Mesman et al., 2021; Sinval et al., 2024).

Although some studies have explored health-promoting behaviors among university students in Saudi Arabia (Almutairi et al., 2018; Sales et al., 2024; Sinval et al., 2024), this remains an underresearched area. Almutairi et al. (2018) highlighted a significant gap in research focusing specifically on health-promoting behaviors among students in Saudi universities. Furthermore, Sales et al. (2024) emphasized that early-life factors such as socioeconomic status (SES), exposure to adverse childhood experiences, and environmental influences are strongly linked to health outcomes in later life. These findings suggest that early adversities contribute to chronic diseases, mental health issues, and overall well-being in adulthood. Additionally, Sinval et al. (2024) demonstrated that depression, anxiety, and stress (DAS) significantly impact academic engagement and dropout intentions, ultimately affecting students’ GPAs. Addressing DAS could foster academic engagement and reduce dropout rates, leading to improved academic performance.

Despite the growing interest in health-promoting behaviors, there is limited research specifically examining the different dimensions of health promotion, such as health responsibility, physical activity, nutrition, spiritual growth, interpersonal relationships, and stress management, among university students in Saudi Arabia. Existing studies primarily focus on broader health concerns or psychological well-being without a comprehensive evaluation of students’ engagement in health-promoting behaviors. Therefore, our study aimed to evaluate the key dimensions of health-promoting behaviors and their predictors among university students in Saudi Arabia.

Research Objectives

To assess whether health-promoting behaviors (nutrition, spiritual growth, stress management, physical activity, interpersonal relations, and health responsibility) differ between male and female students at Taibah University.

To examine the relationship between age and health-promoting behaviors among university students.

To investigate whether there are significant gender-based differences in health responsibility among university students.

To examine the sociodemographic factors (age, body mass index [BMI], gender) that predict variations in specific health-promoting behaviors such as nutrition and stress management.

To determine the key predictors of overall health-promoting lifestyle profile II behaviors (HPLP-II) among male and female students.

Methods

Study Design

This study adopted a cross-sectional analytical design and adhered to the reporting standards outlined in the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines.

Setting

The research was conducted at Taibah University in Saudi Arabia and included four colleges representing a variety of academic disciplines. Two were medical colleges, encompassing students pursuing health-related fields such as medicine, nursing, and allied health sciences. The remaining two were nonmedical colleges, consisting of students from nonhealth-related programs, including business, education, and arts or humanities.

Sampling and Study Participants

The sample size was determined using the GPower 3.1.9.7 software (Faul et al., 2007). The calculation was based on a power of 0.95, an alpha level of 0.001, and a moderate effect size of 0.15, which indicated that at least 354 participants were required. The sample size was adjusted to 400 participants to account for potential attrition. Ultimately, 397 valid questionnaires were collected and included in the final analysis. To ensure a balanced representation from each college, 100 students were selected. A systematic random sampling method was employed, where every 20th student from a predetermined list of students in each college was chosen.

Inclusion and Exclusion Criteria

The inclusion criteria included students enrolled at Taibah University, aged 18 years or older, from medical and nonmedical colleges, and willing to participate voluntarily in the study. Participants needed to comprehend and complete the survey in Arabic.

In addition, the exclusion criteria included students with chronic illnesses or disabilities that could significantly influence their lifestyle behaviors and those absent during data collection or who declined to provide informed consent.

Instruments

Demographic Form

The demographic form included additional details on age, sex, and BMI. Students’ weight and height were measured to calculate their BMI using the standard equation: body weight (kg) divided by the square of height (m²). Based on the BMI classification outlined by the WHO, students were categorized as underweight (<18.5), normal weight (18.5–24.9), overweight (25–29.9), or obese (≥30). This categorization aligns with global standards for assessing nutritional status and identifying weight-related health risks (WHO, 2000).

Health Promotion Lifestyle Profile II Questionnaire

The HPLP-II, originally developed by Walker, Sechrist, and Pender in 1987, is a widely used instrument for assessing health-promoting behaviors. It consists of 52 items across six dimensions: health responsibility (9 items), physical activity (8 items), nutrition (9 items), spiritual growth (9 items), interpersonal relations (9 items), and stress management (8 items). Items are rated on a 4-point Likert scale ranging from 1 (never) to 4 (routinely), with higher scores indicating greater engagement in health-promoting practices.

The Arabic version of the HPLP-II was adapted and validated by Haddad et al. in 1998. This version includes 48 items, with four items excluded due to cultural irrelevance to Arabic-speaking populations. The psychometric evaluation of the Arabic HPLP-II demonstrated strong construct validity and reliability. Exploratory factor analysis supported the six-factor model, with factor loadings above 0.40, indicating solid item convergence within subscales. Confirmatory factor analysis showed a good model fit, with a Comparative Fit Index ≥ 0.90, a Root Mean Square Error of Approximation ≤ 0.08, and a chi-square to degrees of freedom ratio below 3, confirming the validity of the structure. The scale demonstrated excellent internal consistency, with a total Cronbach's alpha of 0.92 and subscale values ranging from 0.70 to 0.87. In the current study, the reliability of the Arabic version remained high, with a Cronbach's alpha of 0.88, confirming its suitability for assessing health-promoting behaviors among university students in Saudi Arabia.

Study Procedures

Tool Preparation and Pilot Study

The research instruments were initially developed in Arabic and did not require translation. These tools were carefully selected for their established validity and reliability in Arabic-speaking populations. To ensure their continued relevance and accuracy in the current context, bilingual experts fluent in Arabic and English reviewed the instruments, focusing on cultural appropriateness and alignment with the intended constructs. A group of potential participants also reviewed the instruments for clarity and comprehensibility, ensuring the items were understandable and relevant to the study's objectives. Reliability was assessed using statistical measures such as Cronbach's alpha to evaluate internal consistency. A pilot study involving 40 students was conducted to test the instruments’ clarity, relevance, and reliability within the specific study context. These participants were not included in the final analysis. The pilot study results indicated that the instruments were effective and did not require modifications, confirming their suitability for the primary research.

Data Collection

Data collection for this study was conducted between December 2024 and January 2025, following the acquisition of the necessary permissions and the obtaining of Excel spreadsheets containing the details of all undergraduate students from the academic affairs department. Participants were selected using a random number generator, and the selection process was repeated until the required number of students from each academic year was achieved. Before data collection, researchers thoroughly explained the study's objectives to the students, emphasizing voluntary participation. Written informed consent was obtained from all participants before they could take part in the study. Participants were assured that their responses would remain private to ensure confidentiality and foster trust. Questionnaires were distributed in quiet locations, such as vacant lecture halls and libraries, from 9 am to 2 pm, from Saturday to Thursday. On average, participants spent between 15 and 20 min completing each questionnaire. A total of 400 questionnaires were distributed across the four colleges, with three excluded due to missing data, resulting in a high response rate of 99.2%.

Ethical Considerations

Ethical approval for the study was obtained from the Research Ethics Committee of the Faculty of Nursing at Taibah University, Saudi Arabia (Serial 202402-076-018083-040429). The study complied with all relevant regulations, local laws, and the ethical principles outlined in the Declaration of Helsinki, ensuring participants’ rights and well-being. Participants were fully informed about the study's purpose and assured that their participation was voluntary and anonymous. They were also reassured that all data collected would be kept confidential and accessible only to the authorized members of the research team. Written informed consent was obtained from all participants before the commencement of data collection.

Data Analysis

The statistical analysis for this study was performed using SPSS version 25 (IBM Corp, Armonk, NY). Descriptive statistics, including frequencies, percentages, means, and standard deviations, were used to summarize the participants’ sociodemographic characteristics and their scores on the HPLP dimensions. To compare categorical variables between male and female participants, the Chi-square test (χ²) was employed, with significance set at p ≤ .05. This was used to assess differences in the distribution of age and BMI categories between the two groups. For continuous variables, independent samples t-tests were conducted to compare male and female participants’ mean scores of the HPLP-II dimensions (nutrition, spiritual growth, stress management, physical activity, interpersonal relations, health responsibility, and total HPLP-II). A p-value of ≤.05 was considered statistically significant for these comparisons. Additionally, a one-way analysis of variance (ANOVA) was performed to evaluate the relationships between the HPLP-II dimensions and demographic variables (age and BMI) for male and female participants separately. All statistical tests were two-tailed, and the significance level for all analyses was set at p ≤ .05.

Results

Table 1 shows that a more significant proportion of female participants (78.9%) were aged 20 years or younger than male participants (50.8%). More males (49.2%) were older than 20 than females (21.1%). This difference in age distribution was statistically significant (χ² = 34.614, p < .001). Regarding BMI, most participants in both groups fell within the normal BMI range (18.5–24.9 kg/m²), with 71.4% of males and 63.3% of females classified as having a normal weight. However, a significantly higher proportion of females were underweight (23.4%) compared to males (13.4%), while the prevalence of overweight individuals (BMI 25–29.9 kg/m²) was similar between males (13.4%) and females (12.4%). Obesity (BMI ≥ 30 kg/m²) was rare in both groups, with only 2.8% of males and 0.9% of females classified as obese.

Table 1.

Sociodemographic Characteristics among Male and Female Participants (N = 397).

Sociodemographic data	Male (n = 179)		Female (n = 218)		Total (n = 397)
Sociodemographic data	N	%	N	%	N	%	χ²	p
Age
≤20 years	91	50.8	172	78.9	263	66.2	34.614	.000*
>20 years	88	49.2	46	21.1	134	33.8	34.614	.000*
BMI
Underweight (BMI 18.5 kg/m²)	24	13.4	51	23.4	75	18.9	7.973	.047*
Normal (BMI 18.5–24.9 kg/m²)	126	71.4	138	63.3	264	66.5
Overweight (BMI 25–29.9 kg/m²)	24	13.4	27	12.4	51	12.8
Obese (BMI 30 kg/m²)	5	2.8	2	0.9	7	1.8

BMI = body mass index.

χ²: Chi square test.

* Statistically significant at p ≤ .05.

Table 2 reveals that the mean scores for nutrition, spiritual growth, stress management, physical activity, interpersonal relations, and total HPLP-II were relatively similar between genders. Still, significant differences were observed in health responsibility. Males had a mean score of 23.41 (SD = 7.19), while females scored higher with a mean of 24.99 (SD = 6.74), leading to a statistically significant difference (t = 2.252, p = .025). For other variables, no significant differences were observed between males and females. For nutrition, males had a mean score of 15.91 (SD = 4.61), while females scored slightly higher at 16.33 (SD = 4.31). In spiritual growth, males scored M = 34.73 (SD = 5.02) compared to females at M = 34.60 (SD = 5.02). Stress management scores were similar, with males scoring M = 16.47 (SD = 4.22) and females M = 16.79 (SD = 4.04). Physical activity scores were slightly higher among males (M = 23.01, SD = 5.59) than among females (M = 22.10, SD = 5.70).

Table 2.

Mean and Standard Deviation of Variables among Male and Female Participants (n = 397).

	Male (n = 179)		Female (n = 218)		Total (n = 397)
Variables	M	SD	M	SD	M	SD	t	p
Nutrition	15.91 ± 4.61		16.33 ± 4.31		16.14 ± 4.45		0.945	.345
Spiritual growth	34.73 ± 5.02		34.60 ± 5.02		34.66 ± 5.02		0.247	.805
Stress management	16.47 ± 4.22		16.79 ± 4.04		16.65 ± 4.12		0.755	.450
Physical activity	23.01 ± 5.59		22.10 ± 5.70		22.51 ± 5.67		1.594	.112
Interpersonal relations	26.06 ± 4.18		26.56 ± 3.76		26.34 ± 3.96		1.249	.212
Health responsibility	23.41 ± 7.19		24.99 ± 6.74		24.27 ± 6.99		2.252	.025*
Total HPLP-II	139.59 ± 24.45		141.37 ± 24.35		140.56 ± 24.38		0.724	.470

HPLP-II: Health-Promoting Lifestyle Profile II.

t: Independent samples test.

* Statistically significant at p ≤ .05.

Figure 1 illustrates the distribution of HPLP-II levels by gender, showing that 54.2% (97) of males and 49.1% (107) of females were within the moderate level. In contrast, 66.1% (144) of females were classified at the high HPLP-II level compared to 41.3% (74) of males. This indicates that females were more likely to engage in health-promoting behaviors at a higher level than males. In contrast, a slightly more significant proportion of males were concentrated in the moderate category.

Figure 1.

Health-Promoting Lifestyle Profile II levels among participants by gender.

Table 3 reveals that male participants aged 20 years or younger reported a mean nutrition score of 16.18 (SD = 4.79), while those older than 20 had a lower mean of 15.64 (SD = 4.42). However, this difference was insignificant (t = 0.782, p = .435). In terms of spiritual growth, younger males scored slightly lower (M = 34.71, SD = 5.11) compared to older males (M = 34.74, SD = 4.96), with no significant difference (t = 0.032, p = .974). Stress management and physical activity scores were also similar across age groups, with no significant differences observed (p > .05). When examining BMI categories, underweight participants had the highest mean score for spiritual growth (M = 36.00, SD = 4.23), while overweight participants reported the lowest total HPLP-II score (M = 134.71, SD = 24.49). However, these differences across BMI categories were not statistically significant for any HPLP variables (p > .05).

Table 3.

Relationship Between Variables and the Demographic Data among Male Participants (n = 179).

Demographic data	Nutrition
Demographic data	Mean ± SD.	Spiritual growth	Stress management	Physical activity	Interpersonal relations	Health responsibility	Total HPLP-II
Age
≤20 years	16.18 ± 4.79	34.71 ± 5.11	16.52 ± 4.15	23.58 ± 5.49	26.13 ± 4.13	22.99 ± 7.29	140.11 ± 24.27
>20 years	15.64 ± 4.42	34.74 ± 4.96	16.43 ± 4.32	22.41 ± 5.67	25.99 ± 4.24	23.84 ± 7.11	139.05 ± 24.77
t	0.782	0.032	0.134	1.407	0.229	0.792	0.290
p	.435	.974	.894	.161	.819	.430	.772
BMI
Underweight (BMI 18.5 kg/m²)	16.38 ± 5.55	36.00 ± 4.23	16.38 ± 4.39	21.96 ± 7.12	26.25 ± 4.29	23.71 ± 7.68	140.67 ± 29.15
Normal (BMI 18.5–24.9 kg/m²)	16.09 ± 4.54	34.77 ± 4.78	16.67 ± 4.32	23.34 ± 5.34	26.13 ± 3.95	23.58 ± 7.21	140.58 ± 23.74
Overweight (BMI 25–29.9 kg/m²)	14.67 ± 4.33	33.88 ± 6.57	15.92 ± 4.04	22.25 ± 5.17	25.92 ± 5.19	22.08 ± 7.42	134.71 ± 24.49
Obese (BMI 30 kg/m²)	15.20 ± 2.28	31.60 ± 5.59	14.80 ± 0.45	23.20 ± 6.50	24.00 ± 4.69	24.00 ± 2.92	132.80 ± 20.52
F	0.762	1.402	0.489	0.576	0.441	0.317	0.527
p	.517	.244	.691	.632	.724	.813	.664

BMI = body mass index; HPLP-II = Health-Promoting Lifestyle Profile II.

t: Independent samples test ; F: One-way ANOVA.

* Statistically significant at p ≤ .05.

Table 4 shows that female participants aged 20 years or younger had higher mean scores in nutrition (M = 16.57, SD = 4.15) and health responsibility (M = 25.24, SD = 6.51) compared to those older than 20 years, who scored lower in these areas (nutrition: M = 15.46, SD = 4.83; health responsibility: M = 24.04, SD = 7.55). The differences in physical activity were particularly notable, with younger females scoring significantly higher (M = 22.67, SD = 5.22) than older participants (M = 19.93, SD = 6.87), indicating a statistically significant difference (p = .004). Additionally, the analysis of BMI categories showed that normal-weight females had the highest mean score in spiritual growth (M = 35.36, SD = 4.61) and total HPLP-II (M = 144.32, SD = 22.87).

Table 4.

Relationship Between Variables and the Demographic Data among Female Participants (n = 218).

Demographic data	Nutrition
Demographic data	Mean ± SD.	Spiritual growth	Stress management	Physical activity	Interpersonal relations	Health responsibility	Total HPLP-II
Age
≤20 years	16.57 ± 4.15	34.69 ± 4.82	16.76 ± 3.90	22.67 ± 5.22	26.84 ± 3.53	25.24 ± 6.51	142.77 ± 22.67
>20 years	15.46 ± 4.83	34.26 ± 5.74	16.91 ± 4.56	19.93 ± 6.87	25.50 ± 4.41	24.04 ± 7.55	136.11 ± 29.52
t	1.561	0.516	0.234	2.944	2.169	1.068	1.656
p	.120	.606	.815	.004*	.031*	.287	.099
BMI
Underweight (BMI 18.5 kg/m²)	16.20 ± 4.22	34.39 ± 4.10	16.47 ± 4.52	21.76 ± 5.95	26.76 ± 3.30	24.71 ± 6.35	140.29 ± 23.65
Normal (BMI 18.5–24.9 kg/m²)	16.64 ± 4.29	35.36 ± 4.61	17.27 ± 3.75	22.50 ± 5.42	26.89 ± 3.58	25.65 ± 6.76	144.32 ± 22.87
Overweight (BMI 25–29.9 kg/m²)	15.26 ± 4.60	31.70 ± 7.03	14.96 ± 4.11	21.00 ± 6.71	24.74 ± 4.66	22.52 ± 7.06	130.19 ± 29.72
Obese (BMI 30 kg/m²)	13.00 ± 1.41	26.50 ± 0.71	16.50 ± 4.95	17.50 ± 0.71	23.00 ± 8.49	19.50 ± 0.71	116.00 ± 12.73
F	1.219	6.239	2.655	1.054	3.205	2.159	3.443
p	.304	.000*	.049*	.370	.024*	.094	.018*

BMI = body mass index; HPLP-II = Health-Promoting Lifestyle Profile II.

t: Independent samples test; F: One-way ANOVA.

*Statistically significant at p ≤ .05.

Table 5 displays the one-way ANOVA results, indicating that the overall model is statistically significant (F = 2.879, p < .001), Among the predictors, Age (p = .019), BMI (p < .001), and the three-way interaction between Age, Gender, and BMI (p < .001) are statistically significant, with BMI and the three-way interaction having the most prominent effect sizes (η² = 0.051 for both). Gender alone approaches significance (p = .058), while the two-way interactions (Age and Gender, Age and BMI, Gender, and BMI) are not statistically significant (p > .05). The small effect sizes (η² < 0.020 for most predictors) suggest that while some predictors contribute to the model, their impacts are relatively modest. Overall, the model highlights the importance of BMI and the combined effects of Age, Gender, and BMI in explaining the variance in the outcome variable.

Table 5.

Effects of Age, Gender, and BMI on HPLP-II Scores.

Source	Type III sum of squares	df	Mean square	F	Sig.	Partial eta squared
Corrected model	22468.423^a	14	1604.887	2.879	0.000	0.095
Intercept	1323002.576	1	1323002.576	2373.498	0.000	0.861
Age	3099.019	1	3099.019	5.560	0.019	0.014
Gender	2013.307	1	2013.307	3.612	0.058	0.009
BMI	11508.581	3	3836.194	6.882	0.000	0.051
Age * Gender	1068.739	1	1068.739	1.917	0.167	0.005
Age * BMI	2934.023	3	978.008	1.755	0.155	0.014
Gender* BMI	4256.261	3	1418.754	2.545	0.056	0.020
Age * Gender * BMI	11487.243	2	5743.621	10.304	0.000	0.051
Error	212929.189	382	557.406
Total	8079444.000	397
Corrected total	235397.612	396

BMI = body mass index; HPLP-II = Health-Promoting Lifestyle Profile II.

R-squared = .095 (Adjusted R-squared = 0.062).

Discussion

Empowering health is a critical focus in contemporary education, particularly among university students at a pivotal stage in developing lifelong habits. This study evaluates the lifestyle profiles aiming to understand their health-promoting behaviors across various dimensions, such as nutrition, physical activity, and stress management. By assessing these lifestyle factors, the research seeks to identify trends and disparities among different demographics, ultimately providing insights to inform targeted health promotion initiatives.

The current results reveal significant differences in the sociodemographic characteristics of male and female participants, particularly in age distribution and BMI. A striking observation is the higher proportion of female participants aged 20 years or younger than their male counterparts. This disparity may reflect broader societal trends where younger females are more engaged in health-related activities or studies, possibly due to increased health awareness or social pressures regarding body image. Conversely, the more significant proportion of males over 20 suggests that life responsibilities and priorities may influence their participation in such studies, as older males may have different health-seeking behaviors than younger individuals (Boua et al., 2018).

Understanding these findings necessitates considering the effects of health inequalities and variations in SES. Students from lower SES backgrounds often encounter obstacles, such as restricted access to healthcare, nutritious foods, and recreational facilities, which can adversely affect their health-promoting behaviors (Gautam et al., 2023). This perspective aligns with the Social Determinants of Health Theory, which asserts that health outcomes are influenced by the environments in which individuals are born, live, and work (Hinnant et al., 2022). Acknowledging these disparities is vital for creating effective interventions that tackle the specific challenges faced by different socioeconomic groups.

Regarding BMI, most participants from both genders fall within the normal weight range, indicating a generally healthy population. However, the data also highlight a significant difference in the prevalence of underweight individuals, with a notably higher percentage of females classified as underweight compared to males. This finding aligns with existing literature that suggests societal pressures and cultural norms often lead to higher rates of underweight classifications among women, as they may feel compelled to conform to specific body ideals (Stoś et al., 2022). The similar prevalence of overweight individuals across genders indicates that lifestyle factors influencing weight may be consistent, suggesting that both males and females face comparable challenges regarding weight management.

The low rates of obesity in both groups are encouraging, yet the differences in underweight classifications warrant further investigation. Understanding the factors contributing to these disparities is crucial, as they may relate to dietary habits, physical activity levels, and psychological influences on body image and health behaviors(Pou et al., 2022). These findings underscore the importance of considering gender differences in sociodemographic data when evaluating health-related behaviors and outcomes.

Understanding these findings can be enhanced by applying Social Cognitive Theory (SCT), which emphasizes the role of observational learning and social influences in behavior change (Krcmar, 2019). Younger females’ higher engagement in health-promoting behaviors may be attributed to positive role models and social networks that prioritize health. In contrast, older males may lack such influences, highlighting the need for targeted interventions that foster supportive environments.

Addressing these disparities requires implementing individual-level interventions such as personalized health education programs. These programs could focus on promoting healthy body image and nutrition among females, utilizing principles from the HBM. This model suggests that individuals are more likely to engage in health-promoting behaviors if they perceive a threat to their health and believe that taking action would mitigate that threat (Jones et al., 2015).

Furthermore, the current findings provide valuable insights into the health-promoting lifestyle behaviors of male and female participants, particularly in the context of various dimensions measured by the HPLP-II. While the mean scores for nutrition, spiritual growth, stress management, physical activity, and interpersonal relations were relatively similar between genders, a significant difference was noted in health responsibility, with females scoring higher than males. This indicates that female participants may emphasize health-related responsibilities, which could be influenced by societal expectations and norms surrounding health and wellness (Fashafsheh et al., 2021).

The lack of significant differences in other dimensions, such as nutrition and spiritual growth, indicates that both genders may engage similarly in these health-promoting behaviors. For instance, the comparable scores in nutrition indicate that dietary habits may not differ markedly between males and females in this population, which could reflect a shared understanding of healthy eating practices or access to similar nutritional resources(Moghimi et al., 2024). Additionally, the similar scores in spiritual growth highlight that both genders may value personal development and self-awareness equally, which is essential for overall well-being.

Interestingly, while males scored slightly higher in physical activity, this difference was insignificant. This finding aligns with previous research indicating that males often engage in more vigorous physical activities than females (Xu et al., 2022). Nevertheless, the overall engagement in physical activity among both genders remains crucial for health promotion. The close scores in interpersonal relations further denote that both males and females prioritize social connections, which are vital for mental health and emotional support. Overall, the total HPLP-II scores were comparable between genders, indicating that both male and female participants exhibit similar health-promoting lifestyle behaviors. However, the significant difference in health responsibility underscores the need for targeted health education and interventions considering gender-specific motivations and behaviors.

The current study results indicate no significant differences in nutrition, spiritual growth, stress management, physical activity, interpersonal relations, or health responsibility between younger and older males (20 years or younger). This lack of significant difference indicates that age may not be a critical factor influencing these health-promoting behaviors in this demographic, which aligns with previous research indicating that lifestyle choices can remain relatively stable across different age groups (Karki et al., 2021). Regarding nutrition, the mean scores for younger and older males were closely aligned, indicating that both groups may have similar dietary habits. This could reflect a broader trend where nutritional knowledge and practices are consistent among young and older adults, possibly due to increased access to health information through various media (Katz et al., 2024). Similarly, the spiritual growth scores were nearly identical, denoting that both age groups value personal development and self-awareness equally, essential components of overall well-being (Balogun & Guntupalli, 2016).

The analysis of BMI categories reveals that underweight participants reported the highest mean score for spiritual growth, while overweight participants had the lowest total HPLP score. Although these differences were not statistically significant, they highlight a potential trend where body weight may influence health-related behaviors and perceptions. Previous studies have shown that individuals with lower BMI often engage more in health-promoting activities, possibly due to more excellent health and wellness awareness (Blake et al., 2021). However, the absence of significant differences across BMI categories in other health-promoting behaviors indicates that factors beyond weight, such as psychological and social influences, may play a more substantial role in shaping lifestyle choices.

Moreover, the current findings highlight significant differences in health-promoting lifestyle behaviors between female participants aged 20 years or younger and those older than 20. Younger females exhibited higher mean scores in nutrition and health responsibility than their older counterparts. This trend suggests that younger women may be more engaged in health-promoting behaviors due to greater awareness or access to health education during formative years. Research indicates that early adulthood is a critical period for establishing health behaviors that can persist into later life, emphasizing the importance of promoting healthy habits among younger populations (Wei et al., 2012).

The analysis also reveals a significant difference in physical activity levels, with younger females scoring notably higher than older participants. This finding aligns with existing literature that denotes younger individuals often have more opportunities and motivation to engage in physical activities, which can be attributed to factors such as social influences and lifestyle choices that favor active engagement (Rosenkranz et al., 2023). The decline in physical activity among older females may reflect increased responsibilities or lifestyle changes accompanying adulthood, which can detract from regular exercise routines.

Furthermore, examining BMI categories provides additional insights into the relationship between weight status and health-promoting behaviors. Normal-weight females demonstrated the highest mean scores in spiritual growth and overall HPLP, while obese participants scored the lowest across all domains. This pattern underscores the potential impact of weight status on health-related behaviors and perceptions. Previous studies have shown that individuals with higher BMI often report lower levels of physical activity and health responsibility, which can contribute to a cycle of unhealthy behaviors and adverse health outcomes (Moghimi et al., 2024). The significant differences in spiritual growth and physical activity among BMI categories indicate that interventions promoting healthy lifestyles should consider weight status as a critical factor influencing health behaviors.

The comparison of HPLP levels between male and female participants reveals noteworthy gender differences in engagement with health-promoting behaviors. The data indicated that more females fall into moderate and high health-promoting lifestyles than their male counterparts. This trend denotes that females are more likely to engage in health-promoting activities, which various social, cultural, and psychological factors could influence. Research has consistently shown that women prioritize health and wellness more than men, potentially due to societal expectations and norms that encourage females to take a proactive approach to their health (Idris et al., 2023)This heightened awareness may lead to more frequent participation in health-related practices such as regular exercise, balanced nutrition, and health screenings. Furthermore, emphasizing well-being in female social circles can foster a supportive environment encouraging health-promoting behaviors, which may not be as prevalent among males.

The significant difference observed in the high level of engagement further underscores the importance of gender-specific health promotion strategies. Women readily embrace health-promoting behaviors, which may enhance their overall well-being and reduce the risk of chronic diseases. In contrast, the lower engagement levels among males indicate that barriers or a lack of motivation may affect their participation in such activities. Previous studies have indicated that men may prioritize other aspects of life, such as work or social obligations, over health, which can contribute to lower levels of health-related engagement (Ab Aziz et al., 2022; Mursa et al., 2022).

The results of the ANOVA indicate significant effects of age, gender, and BMI on the HPLP-II scores, highlighting the complex interplay between these demographic factors and health-promoting behaviors. The overall model was statistically significant, suggesting that these variables collectively explain a notable portion of the variance in HPLP-II scores. This finding aligns with existing literature that emphasizes the importance of demographic factors in influencing health behaviors among various populations, including university students (Alzahrani et al., 2019; Gilan et al., 2021).

Strengths and Limitations

Despite its contributions, this study has several limitations that should be acknowledged. The cross-sectional design restricts the ability to infer causal relationships between the demographic variables and health-promoting behaviors, limiting the temporal understanding of behavior change. To address this, future studies should consider longitudinal or interventional designs that can better assess causality and the effectiveness of health promotion strategies over time. Another limitation is the reliance on self-reported data, which may be subject to recall bias or social desirability bias. Incorporating objective measures, such as biometric data or validated behavioral tracking tools, would enhance data accuracy in future research. Additionally, the study was conducted at a single university in Saudi Arabia, which may limit the generalizability of the findings to other academic institutions or regions. Expanding the sample across multiple universities with diverse demographic profiles would improve the external validity of the results. Moreover, this study did not comprehensively assess psychosocial factors such as mental health status, social support, or socioeconomic background, which may also influence health-promoting behaviors.

Conclusion and Recommendations

This study identified significant gender- and age-related differences as female students demonstrated greater engagement in health-promoting behaviors. Additionally, females were more likely to be classified at a high level of overall health-promoting lifestyle. Age differences were notable among female participants, with those aged 20 years or younger exhibiting significantly higher physical activity and health responsibility scores compared to older females. The analysis also revealed that the interaction between age, gender, and BMI significantly predicted health-promoting lifestyle scores, though effect sizes were modest. These findings highlight the importance of targeting health promotion efforts according to demographic characteristics, especially in fostering active lifestyles and health responsibility among males and older students.

Nursing Implications

Healthcare educators had a pivotal role in promoting healthy lifestyles among students. The significant gender and age differences in health responsibility and physical activity underscore the need for education programs that focus on increasing physical activity among older female students and enhancing health responsibility among males. Furthermore, the integration of behavioral change models such as the HBM and SCT into nursing-led interventions can enhance their effectiveness by addressing students’ perceptions, motivations, and social influences. By adopting a proactive and student-centered approach, healthcare workers can empower students to engage in sustainable health-promoting behaviors that support both academic success and long-term well-being.

Supplemental Material

sj-docx-1-son-10.1177_23779608251371981 - Supplemental material for “Empowering Health: Evaluating Health-Promoting Behavior of Taibah University Students in Saudi Arabia”

Supplemental material, sj-docx-1-son-10.1177_23779608251371981 for “Empowering Health: Evaluating Health-Promoting Behavior of Taibah University Students in Saudi Arabia” by El-Saied Abd El-Hamid EL-Sayed Salem, Mahmoud Abdelwahab Khedr, Shaimaa Mohamed Amin, Mohamed Hussein Ramadan Atta, Mohamed Masoud Ibrahim Sharaf, Samir Abdelnaby Shaaban Essa, Amira Abdelhamid Shawky Morsy, Maysa M. Hatata, Braa Ibrahim Ahmed Lotfy Sobbih and Mona Metwally El-Sayed in SAGE Open Nursing

Footnotes

Acknowledgment

The authors would like to express their sincere gratitude to Taibah University, Kingdom of Saudi Arabia, and Alexandria University, Egypt for their valuable support and contribution to this research. Their resources, guidance, and encouragement have been instrumental in the successful completion of this study.

ORCID iDs

El-Saied Abd El-Hamid EL-Sayed Salem

Shaimaa Mohamed Amin

Mohamed Hussein Ramadan Atta

Mohamed Masoud Ibrahim Sharaf

Samir Abdelnaby Shaaban Essa

Amira Abdelhamid Shawky Morsy

Braa Ibrahim Ahmed Lotfy Sobbih

Mona Metwally El-Sayed

Ethical Statement

Ethical approval for the study was obtained from the Research Ethics Committee of the Faculty of Nursing at Taibah University, Saudi Arabia (Serial 202402-076-018083-040429).

Patient Consent Statement

Informed consent was obtained from all participants before their inclusion in the study.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Permission to Reproduce Material from Other Sources

Not applicable; this study did not involve reproducing material from other sources.

Supplemental Material

Supplemental material for this article is available online.

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