Physical Activity Patterns and Associated Factors Among First-Year Female University Students in Saudi Arabia: A Cross-Sectional Study​

Summary

This is a cross-sectional study that included 431 female university students aiming to assess physical activity patterns and their associated factors. Physical inactivity was prevalent, and regular exercise, activity duration, and sedentary behavior were important factors associated with weekly participation in vigorous, moderate, and walking activities.

Abstract

The World Health Organization (WHO) recommends at least 150 min of moderate-intensity or 75 min of vigorous-intensity physical activity (PA) per week for adults. In Saudi Arabia, over 70% of young adults are physically inactive. This study aimed to describe PA patterns among first-year Saudi female university students and determine factors that are associated with weekly participation in vigorous PA using convenience sampling. Participants completed an anonymous online survey after providing their informed consent. The survey comprised: i) demographic information, ii) PA level assessment using the International Physical Activity Questionnaire short form, and iii) exercise environments. Of the 431 students (mean age 19 ± 0.64 years) who participated in the study, 40% reported no regular PA. Walking was the most common activity type (32.56%), followed by home (16.63%) and gym (10.16%) exercises. Among the students, 38.75% reported no participation in vigorous PA, 30.40% in moderate activity, and 21.81% in daily walking. The majority of students (92.5%) reported sitting for >8 h per day. The regression analyses showed that vigorous activity frequency was positively associated with regular exercise pattern (standardized β = 0.389, p < 0.001) and negatively with weekday sitting time (standardized β = −0.149, p = 0.001). Moderate PA was associated only with the exercise pattern (standardized β = 0.265, p < 0.001). Walking frequency was associated with longer walking duration (standardized β = 0.232, p < 0.001) and exercise pattern (standardized β = 0.151, p = 0.001). Physical inactivity was prevalent, with limited engagement in moderate- and vigorous-intensity activity. The study’s findings support institutional actions that prioritize PA promotion particularly for female college students. Academic institutions should implement targeted strategies to reduce sedentary behavior and promote structured PA programs, particularly for female students.

Introduction

WHO recommends at least 150 min of moderate-intensity activity or 75 min of vigorous-intensity activity per week for adults aged 18 and older¹. However, more than one-third of adults aged 18 and older worldwide do not meet these PA recommendations^2,3. This has led to an alarming increase in physical inactivity, especially in high-income countries, where lifestyle changes have led to rising obesity and related health issues^4–6.

In Saudi Arabia, physical inactivity remains a major public health issue, with current national estimates indicating that more than half of Saudi adults have insufficient PA levels, although prevalence estimates vary according to the population studied, the year of data collection, and the criteria used to define physical inactivity³. Previous published studies among Saudi young adults have reported high rates of physical inactivity that fall below the WHO PA recommendations^7–11. Some studies identified barriers to engaging in PA among young Saudi adults, including lack of time, motivation, and access to recreational facilities^8,12. In addition to the transition to a more sedentary lifestyle, a strong emphasis on cultural gender roles and expectations may also restrict women's participation in PA, leading to greater sedentary behavior among women than men in many societies^4,13. Similar to global trends, in Saudi Arabia, women have consistently reported lower engagement in PA than men^9,11. However, a recent shift has been observed in Saudi Arabia toward PA policy. The most apparent change was in the culture shift permitting women’s sports activities¹⁴. For example, national data from 2021 showed that 38.7% of Saudi females aged 15 years and older participated in PA, representing an improvement when compared with 2018 and 2019 data¹⁵. More recent data from Saudi Arabia showed that only 43.1% of Saudi women meet the WHO PA recommendations compared to 66.5% of men meeting these PA recommendations⁹.

The transition from high school to university is a critical period for individuals. This transition is marked by increased academic demands, greater independence, and changes in daily routines, all of which may influence PA level and sedentary behavior in new university students^16–18. A recent systematic review of 44 studies involving 29,580 Saudi college students found consistently low levels of PA, with only 27% meeting WHO-recommended PA cutoffs¹⁹. Moreover, first-year university students are more vulnerable to unhealthy behaviors such as insufficient PA and smoking²⁰. In addition, it has been reported that culture and environmental factors may explain the gap between women's and men's PA levels²¹. Not prioritizing exercise, lack of time, engagement in housework and daily activities, and lack of motivation and interest are the most reported personal factors impacting PA levels among women^13,22.

Fitness facilities provide a structured environment rich with resources that can enhance motivation and facilitate various forms of exercise; in addition, the social aspects of the fitness facilities environment, including interaction with peers and access to group fitness classes, significantly enhance motivation and adherence to exercise routines^23,24. While exercising at home is convenient and accessible, allowing young adults to engage in PA without the time constraints of traveling to the gym, prior studies indicate that gym-based exercise is significantly associated with PA levels^22,25,26. Access to supportive exercise environments, including appropriate facilities and opportunities for PA, has been associated with greater participation in PA among adults^25,26. Women represent the fastest-growing segment in the Saudi fitness club, with a major increase expected between 2026 and 2031.

Regarding cultural PA-related barriers, a recent systematic review suggested that cultural differences and variations in educational systems may lead to PA disparities among university students from different countries²⁷. Since many university students experience increased academic demands and limited time for exercise, understanding the factors associated with PA during this transition is important. PA is known to be associated with physical health and quality of life among university students^28,29. Therefore, first-year university students represent an important population and are worth investigating in terms of their PA behavior.

Understanding factors associated with PA participation among first-year female university students is important for developing targeted health promotion strategies during the transition to university life²⁷. Although previous studies have reported the prevalence of physical inactivity among Saudi university students^7–10,16, limited evidence has examined potential factors associated with different components of PA among first-year female university students. Understanding these factors may help inform the future development of targeted PA promotion strategies for young adults. The primary aim of this study was to describe PA patterns among first-year Saudi female university students. A secondary aim of this study was to examine whether age, exercise regularity, exercise duration (minutes per day), and sedentary behavior (minutes per day) are associated with weekly participation in vigorous-, moderate-, and walking-related PA. It was hypothesized that demographic and lifestyle characteristics, including age, exercise behavior, activity duration, and sedentary time, would be associated with vigorous, moderate, and walking-related PA among first-year female university students.

Protocol

Study design

This study employed a cross-sectional design to assess PA levels among first-year female university students in Saudi Arabia. The cross-sectional design was chosen to enable the assessment of PA behaviors and related factors at a single time point during the first year of university, a period known to be associated with changes in lifestyle and health behaviors. It was conducted in accordance with the ethical principles outlined in the Declaration of Helsinki and was approved by the Ethics Committee of Princess Nourah bint Abdulrahman University, Riyadh, Kingdom of Saudi Arabia (IRB Log Number: 24-0218; Approval date February 01, 2024).

Details of the materials and software used in this study are provided in the Table of Materials.

Study participants

The target population consisted of first-year female university students enrolled in Saudi Arabian universities during the 2024 academic year. The inclusion criteria for this study were as follows: participants must be first-year university students aged 18–21 years, residing in Saudi Arabia, and willing to participate by providing informed consent. Students who had been diagnosed with medical conditions that are known as contraindications for engagement in PA (such as severe cardiovascular disorders, musculoskeletal impairments, or post-surgical conditions), those with disabilities limiting mobility, or those who provided incomplete questionnaire responses were excluded from participation.

Sampling method

Convenience sampling was employed by distributing the survey link through official university mailing lists, academic platforms, and widely used student social media groups across Saudi Arabia. This approach, although non-random, was aimed at maximizing reach and obtaining responses from diverse geographic and demographic segments of first-year students.

Sample size calculation

The total population of first-year university students in Saudi Arabia in 2023 was 362,231³⁰. To ensure sufficient statistical power, the sample size was calculated using an online epidemiological sample size calculator (OpenEpi software), with a 95% confidence level, a 5% margin of error, and an assumed response distribution of 50%. The minimum required sample size was determined to be 384 respondents. The sample size calculation was based on the descriptive objective of estimating the prevalence of PA.

Data collection tool

Data were collected using a structured, self-administered online survey through a web-based survey platform (Google Forms). The survey began with an introductory page outlining the study’s purpose, the voluntary nature of participation, assurances of confidentiality, and contact details for further inquiries. Informed consent was obtained at the start of the survey. To prevent duplication, submissions were limited to one response per user through the survey-platform settings.

PA was assessed using the International Physical Activity Questionnaire–Short Form (IPAQ-SF) among first-year students^31,32. The IPAQ-SF is a standardized self-report instrument developed for assessing PA in individuals aged 15 years and older^31,32. The Arabic version of the IPAQ-SF was administered to participants and has been used in previous studies conducted in Saudi Arabia, including studies involving university students^19,33–35. The IPAQ-SF assesses the number of days and time (minutes) per week participants engaged in vigorous-intensity physical activity, moderate-intensity physical activity, and walking for at least 10 min per occasion³¹. The present study focused on frequency of participation (days per week) and PA volume (minutes per day) for vigorous-intensity physical activity, moderate-intensity physical activity, and walking³¹. IPAQ-SF data were processed in accordance with the official IPAQ scoring protocol. Activity bouts shorter than 10 min were excluded. Extreme duration values were truncated according to IPAQ data-processing guidelines, and implausible activity values were identified and removed during data cleaning. For participants reporting zero days of vigorous-intensity, moderate-intensity, or walking activity, the corresponding duration variables were recorded as 0 min.

Because activity frequency and activity duration describe related dimensions of the same PA behavior, these variables may exhibit conceptual overlap when included simultaneously in regression models. Therefore, the duration coefficients were interpreted as conditional associations rather than evidence of independent causal effects. The same consideration applies to the exercise-pattern variable, which represents a general pattern of PA and may overlap conceptually with the activity-frequency outcomes.

Furthermore, questions were added to evaluate participants’ self-satisfaction regarding their current PA levels (yes/no-based responses) and their regular pattern of PA, including walking, exercising at home, exercising at a gym or not practicing regular PA. Demographic data were collected, including age, gender, university affiliation, year of study, presence of chronic diseases, and health issues that could contraindicate or limit daily activities.

The questionnaire included a multiple-choice item asking participants to indicate their usual exercise pattern, with four mutually exclusive response options: (1) not practicing PA regularly, (2) practicing walking only, (3) exercising primarily at home, and (4) exercising primarily at a gym. This variable was treated as a categorical independent variable in the regression analyses, with "not practicing PA regularly" used as the reference category. A pilot test was conducted with five first-year female students to assess the clarity and comprehensibility of the questionnaire. The pilot participants were not included in the final analytic sample. Feedback confirmed that the questionnaire was clear and understandable, and no substantive modifications were required.

Procedure

An online survey was conducted between May and June 2024. All responses were collected anonymously and stored securely in a password-protected database accessible only to the research team. After data collection was completed, responses were reviewed for completeness, and those with significant missing data or inconsistent answers were excluded from the final analysis. Because only complete questionnaires were included, no imputation of missing data was performed, and no formal missing data analysis was required.

Data analysis

Statistical analyses were performed using statistical software (SPSS statistics). Descriptive analyses were used to report frequencies and percentages for all PA variables, as well as the mean and standard deviation for participants’ ages. The associations between PA types (vigorous-intensity PA, moderate-intensity PA, and walking) and duration (minutes per day), age, exercise pattern, and weekday sitting time were examined using multiple linear regression. Regression diagnostics were assessed for homoscedasticity, linearity, residual normality, and multicollinearity using normal probability plots, histograms, and scatter plots. The statistical significance for all analyses was set a priori at p < 0.05.

Exercise patterns were entered into the regression models as a categorical independent variable using dummy coding. The four mutually exclusive categories were walking only, home-based exercise, gym-based exercise, and not practicing PA regularly. Participants who did not practice PA regularly were used as the reference category; therefore, three dummy variables were included in each regression model (walking vs. no regular exercise, home-based exercise vs. no regular exercise, and gym-based exercise vs. no regular exercise). Dummy coding was automatically generated using the categorical variable function in the statistical software. Multicollinearity among the independent variables was assessed using variance inflation factors (VIFs), and no evidence of problematic multicollinearity was identified.

Results

A total of 597 individuals accessed the survey, of whom 501 provided consent and completed the questionnaire. Following application of the eligibility criteria, 431 participants were included in the final analysis (Figure 1). None of the participants reported being diagnosed with medical conditions that are known as contraindications for engaging in PA or disabilities that could limit mobility. The participants’ mean age was 19 years ± 0.64 years (Table 1).

Relationship between vigorous-intensity PA frequency and duration, age, exercise pattern, and weekday sitting time

Table 2 presents a multiple linear regression analysis that was conducted to examine the associations between the number of days of vigorous-intensity PA per week and vigorous-intensity activity duration, age, exercise pattern, and weekday sitting time. Exercise pattern was represented by three dummy variables, with participants who did not practice PA regularly serving as the reference group. The overall regression model was statistically significant, F(6,424) = 16.943, p < 0.001, explaining 19.3% of the variance in vigorous-intensity PA (R² = 0.193; adjusted R² = 0.182). Compared with participants who did not practice PA regularly, those who reported walking only (B = 1.204, 95% CI [0.802, 1.605], p < 0.001), exercising at home (B = 1.535, 95% CI [1.040, 2.031], p < 0.001), or exercising at a gym (B = 2.331, 95% CI [1.727, 2.935], p < 0.001) reported a greater number of vigorous-intensity activity days per week. Weekday sitting time was inversely associated with vigorous-intensity activity frequency (B = −0.178, 95% CI [−0.285, −0.071], p = 0.001). Vigorous-intensity activity duration (B = 0.257, p = 0.123) and age (B = 0.148, p = 0.278) were not statistically significant predictors.

Relationship between moderate-intensity PA frequency and duration, age, exercise pattern, and weekday sitting time

Table 3 presents a multiple linear regression analysis that was conducted to examine the associations between the number of days of moderate-intensity PA per week and moderate-intensity activity duration, age, exercise pattern, and weekday sitting time. Exercise pattern was represented by three dummy variables, with participants who did not practice PA regularly serving as the reference group. The overall regression model was statistically significant, F(6,424) = 7.813, p < 0.001, explaining 10.0% of the variance in moderate-intensity PA frequency (R² = 0.100; adjusted R² = 0.087). Compared with participants who did not practice PA regularly, those who reported walking only (B = 1.080, 95% CI [0.662, 1.499], p < 0.001), exercising at home (B = 1.286, 95% CI [0.770, 1.803], p < 0.001), or exercising at a gym (B = 1.334, 95% CI [0.706, 1.961], p < 0.001) reported a greater number of moderate-intensity PA days per week. Age (B = 0.184, p = 0.197), weekday sitting time (B = −0.030, p = 0.591), and moderate-intensity activity duration (B = 0.405, p = 0.185) were not statistically significant predictors.

Relationship between walking frequency and duration, age, exercise pattern, and sitting time

Table 4 shows a multiple linear regression analysis that was conducted to examine the associations between the number of days participants walked for at least 10 min per week and walking duration, age, exercise pattern, and weekday sitting time. Exercise pattern was represented by three dummy variables, with participants who did not practice PA regularly serving as the reference group. The overall regression model was statistically significant, F(6,424) = 10.825, p < 0.001, explaining 13.3% of the variance in walking frequency (R² = 0.133; adjusted R² = 0.121). Compared with participants who did not practice PA regularly, those who reported walking only (B = 1.531, 95% CI [1.028, 2.035], p < 0.001), exercising at home (B = 0.835, 95% CI [0.214, 1.456], p = 0.009), or exercising at a gym (B = 0.945, 95% CI [0.195, 1.694], p = 0.014) reported a greater number of walking days per week. Walking duration was also positively associated with walking frequency (B = 0.922, 95% CI [0.549, 1.294], p < 0.001). Age (B = −0.162, p = 0.344) and weekday sitting time (B = −0.035, p = 0.603) were not statistically significant predictors.

DATA AVAILABILITY:

The de-identified dataset supporting the findings of this study is publicly available through the Zenodo repository at [DOI:10.5281/zenodo.22117075].

Figure 1: Flow diagram of participant recruitment and inclusion. The online survey was distributed through university mailing lists, academic platforms, and student social media groups. Because the total number of students who received the survey invitation was unknown, a true response rate could not be calculated. Please click here to view a larger version of this figure.

Variable	Category	n	%
Age (years)	Mean ± SD	19 ± 0.64
	Range	18–21
Regular exercise	No	175	40.6
	Yes, walking	140	32.5
	Yes, at home	72	16.7
	Yes, at gym	44	10.2
Vigorous-intensity physical activity (days/week)	None	167	38.7
	1 day	62	14.4
	2 days	49	11.4
	3 days	52	12.1
	4 days	55	12.8
	5 days	24	5.6
	6 days	7	1.6
	7 days	15	3.5
Moderate-intensity physical activity (days/week)	None	131	30.4
	1 day	75	17.4
	2 days	48	11.1
	3 days	65	15.1
	4 days	64	14.8
	5 days	25	5.8
	6 days	7	1.6
	7 days	16	3.7
Walking ≥ 10 min (days/week)	None	54	12.5
	1 day	55	12.8
	2 days	36	8.4
	3 days	61	14.2
	4 days	59	13.7
	5 days	56	13
	6 days	16	3.7
	7 days	94	21.8
Regular exercise pattern	Not practicing activity regularly	175	40.6
	Walking	140	32.6
	Exercise at home	72	16.6
	Exercise at gym	44	10.2
Time spent sitting on a typical weekday	30 min–2 hours	5	1.2
	2.5–4 hours	5	1.2
	4.5–6 hours	9	2.1
	6.5–8 hours	13	3
	>8 hours	399	92.5

Table 1: Sociodemographic and physical activity characteristics of participants (n = 431). Continuous data are presented as mean ± standard deviation (SD), and categorical data are presented as frequency (n) and percentage (%).

Model		Unstandardized Coefficients		Standardized Coefficients	t	p	95.0% CI for B		Collinearity Statistics
		B	SE	Beta			Lower Bound	Upper Bound	Tolerance	VIF
1	(Constant)	-1.795	2.612		-0.687	0.492	-6.929	3.34
	Walking vs. no regular exercise	1.204	0.204	0.284	5.896	0	0.802	1.605	0.819	1.22
	Home vs. no regular exercise	1.535	0.252	0.289	6.091	0	1.04	2.031	0.847	1.181
	Gym vs. no regular exercise	2.331	0.307	0.356	7.585	0	1.727	2.935	0.865	1.155
	Vigorous-intensity physical activity duration	0.257	0.167	0.069	1.543	0.123	-0.07	0.584	0.94	1.064
	Age	0.148	0.136	0.048	1.086	0.278	-0.12	0.416	0.992	1.008
	Sitting time	-0.178	0.054	-0.145	-3.271	0.001	-0.285	-0.071	0.964	1.037

Table 2: Relationship between vigorous-intensity physical activity frequency and vigorous-intensity physical activity duration, age, exercise pattern, and sitting time. The dependent variable was the number of days during the past seven days on which participants engaged in vigorous-intensity physical activity. Abbreviations: PA = physical activity; CI = confidence interval; VIF = variance inflation factor.

Model		Unstandardized Coefficients		Standardized Coefficients	t	p	95.0% CI for B		Collinearity Statistics
		B	SE	Beta			Lower Bound	Upper Bound	Tolerance	VIF
1	(Constant)	-2.131	2.725		-0.782	0.435	-7.487	3.225
	Walking vs. no regular exercise	1.08	0.213	0.258	5.077	0	0.662	1.499	0.82	1.219
	Home vs. no regular exercise	1.286	0.263	0.245	4.894	0	0.77	1.803	0.847	1.18
	Gym vs. no regular exercise	1.334	0.319	0.206	4.178	0	0.706	1.961	0.872	1.146
	Age	0.184	0.142	0.06	1.292	0.197	-0.096	0.463	0.992	1.008
	Sitting time	-0.03	0.057	-0.025	-0.538	0.591	-0.142	0.081	0.967	1.034
	Moderate-intensity physical activity duration	0.405	0.305	0.063	1.328	0.185	-0.194	1.004	0.946	1.057

Table 3: Relationship between moderate-intensity physical activity frequency and moderate-intensity physical activity duration, age, exercise pattern, and sitting time. The dependent variable was the number of days during the past seven days on which participants engaged in moderate-intensity physical activity. Abbreviations: PA = physical activity; CI = confidence interval; VIF = variance inflation factor.

Model		Unstandardized Coefficients		Standardized Coefficients	t	p	95.0% CI for B		Collinearity Statistics
		B	SE	Beta			Lower Bound	Upper Bound	Tolerance	VIF
1	(Constant)	5.92	3.277		1.806	0.072	-0.522	12.361
	Walking vs. no regular exercise	1.531	0.256	0.299	5.977	0	1.028	2.035	0.818	1.222
	Home vs. no regular exercise	0.835	0.316	0.13	2.642	0.009	0.214	1.456	0.848	1.179
	Gym vs. no regular exercise	0.945	0.381	0.119	2.477	0.014	0.195	1.694	0.884	1.132
	Age	-0.162	0.171	-0.043	-0.947	0.344	-0.498	0.174	0.991	1.009
	Sitting time	-0.035	0.068	-0.024	-0.521	0.603	-0.17	0.099	0.966	1.035
	Walking duration	0.922	0.189	0.225	4.866	0	0.549	1.294	0.959	1.043

Table 4: Relationship between walking frequency and walking duration, age, exercise pattern, and sitting time. The dependent variable was the number of days during the past seven days on which participants walked for at least 10 min at a time. Abbreviations: CI = confidence interval; VIF = variance inflation factor.

Discussion

This study provides important results regarding PA patterns and their behavioral and environmental associations among first-year female university students in Saudi Arabia. The present study extends previous work by focusing specifically on first-year female university students, a transitional stage during which lifestyle behaviors are established, and by examining exercise patterns and the association of sedentary behavior with the frequency of participation in vigorous PA, moderate PA, and walking. Overall, the findings demonstrate that PA behaviors among first-year female university students are shaped primarily by regular engagement in exercise environments and selected behavioral factors rather than by age. Notably, a substantial proportion of the included sample reported physical inactivity (81.58%). Among those who reported being involved in regular activity, walking was the most reported activity, followed by home-based and gym-based exercises. These findings are consistent with previous published research highlighting low levels of PA among young adults in Saudi Arabia, particularly among women^9–11,16. Furthermore, the results indicated limited engagement in moderate- and vigorous activity, with a considerable proportion of students reporting no participation at all in these PA intensities. This aligns with other research emphasizing a decline in PA levels due to transitioning from adolescence to university life, where academic demands, lack of facilities, and/or cultural and social factors are common^{6,10,12,13,18}.

In comparison with Saudi-based evidence, the findings are consistent with prior studies reporting low PA engagement among female university students, with inactivity remaining disproportionately high in this subgroup^9–11,16. This pattern also conforms with national survey analyses indicating that Saudi women are significantly less likely to meet PA recommendations than men, reflecting persistent gender disparities in activity behavior⁹. Additionally, a recent Saudi university-focused synthesis reported that a substantial proportion of university students failed to meet WHO PA recommendations, with female students demonstrating particularly low adherence¹⁹. Low engagement in moderate- to vigorous-intensity PA is reported globally, particularly during the transition into higher education, which is frequently associated with decreased PA¹⁸. This result is mirrored in the present sample, providing more evidence in this critical stage of transition for new students. The high proportion of physically inactive participants observed in this study reflects broader national and cultural trends. Insufficient time, low motivation, cultural and social restrictions, health issues, inadequate knowledge, and environmental factors may contribute to this pattern^9,13,22. Furthermore, traditional gender roles may discourage female students from engaging in gym-based activities, despite their clear benefits in promoting higher-intensity exercise³⁶. The limited availability of university-based exercise facilities and the absence of mandatory physical education programs may contribute to students’ sedentary lifestyles. As previous research has indicated, cultural attitudes toward female PA and a lack of structured exercise opportunities significantly hinder young women’s engagement in regular PA⁹. A recent systematic review among university students noted that barriers to PA include a lack of time, motivation, and facilities. Conversely, facilitators consist of health benefits, social support, and weight management¹⁹. Exercise patterns showed the strongest association with vigorous-intensity PA, whereas weekday sitting time was inversely associated with vigorous activity. These findings suggest that regular engagement in exercise may be more important than age in explaining vigorous-intensity participation among first-year female students. Unlike vigorous activity, age and sitting time were not significantly associated with walking frequency, indicating that walking frequency is primarily linked to walking duration and general exercise engagement rather than sedentary time. This finding indicates that patterns of inactivity and vigorous-intensity activity are meaningfully interconnected and that sedentary time may function as a behavioral barrier to vigorous participation in this group.

The current study underscores an urgent call for university-led interventions to promote PA among students. Integrating PA promotion initiatives into university curricula such as wellness courses, campus-wide step challenges, or incentives for gym membership may help encourage university students to adopt more active lifestyles during study. Furthermore, leveraging digital and mobile health interventions may provide an alternative solution to increase engagement in structured PA programs. Previous studies have shown that mobile fitness applications and virtual exercise programs can enhance motivation and adherence to PA practice, especially among young adults with time constraints^37,38.

To translate these findings into actionable strategies, universities may adopt a phased implementation approach. In the short term (0–3 months), institutions could launch low-cost initiatives such as campus-wide step challenges, brief, scheduled ‘active breaks’ integrated into first-year orientation and large lecture sessions. In the medium term (3–12 months), universities could expand access to female-friendly fitness facilities by offering designated women-only gym hours, subsidized memberships, and structured group exercise classes led by qualified instructors. In the long term (≥12 months), integrating a mandatory wellness/PA module within first-year curricula and establishing routine monitoring of PA and sedentary behavior using validated tools (e.g., IPAQ) can support sustained behavior change and enable evaluation of intervention effectiveness.

This study provides important insights into PA patterns and their associated factors among first-year female university students in Saudi Arabia. The relatively medium-to-large sample size improves the precision of the estimates, and the study extends previous work by examining factors associated with vigorous-, moderate-, and walking-related PA. However, this study has several limitations. First, PA was assessed using IPAQ-SF, a self-reported tool that may overestimate activity levels compared with objective tools such as accelerometers³¹. Second, the cross-sectional design precludes causal inference, and the observed associations should not be interpreted as cause-and-effect relationships. Further, participants were recruited using convenience sampling, which may introduce selection bias and limit the representativeness and generalizability of the findings. Adherence to the WHO PA recommendations was not formally classified; therefore, the findings reflect individual components of PA rather than overall adherence to PA guidelines. A further limitation is the conceptual overlap among activity frequency, activity duration, and general exercise pattern. These measures describe related aspects of PA behavior and were derived from related questionnaire items. Consequently, the observed associations should not be interpreted as independent causal effects. Finally, although the outcome variables represented bounded count data, ordinary least squares regression was used to provide interpretable estimates of association. Future studies may consider count-based regression models to confirm the robustness of these findings. Future studies should include more representative sampling strategies, objective measures of PA, and rigorous study designs such as longitudinal studies to confirm these findings.

Materials

List of materials used in this article

Name	Company	Catalog Number	Comments
Google Forms	Google LLC	Web-based platform; version not applicable	Web-based platform used to administer the study survey and collect anonymous participant responses.
IBM SPSS Statistics	IBM Corporation, Armonk, NY, USA	Version 30	Statistical software used for descriptive statistics and multiple linear regression analyses.
International Physical Activity Questionnaire–Short Form	International Physical Activity Questionnaire Research Committee	Short Form; questionnaire version	Self-reported questionnaire used to assess the frequency and duration of vigorous-intensity physical activity, moderate-intensity physical activity, walking, and sitting time. The Arabic-language version was administered.
OpenEpi	OpenEpi	Version 3	Online epidemiological calculator used to estimate the minimum required sample size.