Physical Activity Levels of University Students Based on the International Physical Activity Questionnaire

Abstract

This study assessed physical activity (PA) levels and energy expenditure among students across various medical disciplines at Wroclaw Medical University. Data were collected in late 2024 using the International Physical Activity Questionnaire (IPAQ) long-form. Statistical analysis, including Mann–Whitney U and Kruskal–Wallis tests were used to reveal significant differences based on gender, age, and field of study. While female students generally achieved higher metabolic equivalent (MET) MET-min/week values at home and in transport, male students demonstrated significantly higher scores in total physical activity, total vigorous physical activity, and vigorous activity in free time. Gender based analysis did not reveal any statistically significant differences. Significant variations across study programs were observed only in occupational PA, same as in age-related analysis. The findings highlight sedentary risks within specific student subgroups, which may contribute to professional burnout and diminished effectiveness as future health promoters. Consequently, the study suggests that medical institutions should incorporate lifestyle medicine and health promotion strategies into their curricula to foster the long-term well-being of future healthcare professionals.

1. Introduction

Studies [1,2,3] have found many benefits of physical activity (PA). Results of those studies present strong evidence of reduced rates of all-cause mortality, cardiorespiratory health, metabolic health, cancers (bladder, breast, colon, endometrial, oesophageal), and depression. Today, lack of physical activity is a global pandemic. Coronary heart disease, type 2 diabetes, breast cancer, and colon cancer are some of the most common diseases whose incidence increases with a lack of physical activity [4]. Unfortunately, research conducted by Strain et al. [5] indicates that 31% of the population did not meet the recommended level of physical activity in 2022. In 2000, only 23.4% of the population failed to meet these recommendations, but this number has increased over the years. Moreover, it was observed that 9% of premature deaths were caused by physical inactivity. Guthold et al. [6], have found that the problem of insufficient physical activity begins among the youngest part of our population. PA does not always mean performing exercise during free time. It can also be performed during household chores, professional or agricultural work, and even transportation, such as walking or biking.

In 2020, the WHO published guidelines on physical activity and sedentary behavior [1]. Adolescents should do at least an average of 60 min per day of moderate to vigorous intensity, mostly aerobic, PA, and at least 3 days of vigorous-intensity aerobic activities, as well as those that strengthen muscle and bone. Moreover, adolescents should limit the amount of time spent sedentary, especially the time spent using the TV screen or computer/laptop monitor. Adults, aged 18–64 years, should do at least 150–300 min of moderate-intensity aerobic PA; or at least 75–150 min of vigorous-intensity aerobic PA throughout the week. Additionally, adults should strengthen muscles by performing activities involving all major muscle groups.

PA is defined as any body movement that results in energy expenditure. It can be divided into many categories, for example, occupational, sports-related, or activity associated with household duties [7]. PA, like any other area of physical endeavor, should be monitored and evaluated. The assessment of PA must be as accurate as possible [8]. When determining a person’s PA level, both objective and subjective measurement methods can be used. The first mentioned group is based on collecting biological data from devices used during exercise, e.g., indirect calorimetry, the doubly labeled water method, direct observation, heart rate monitoring, and accelerometers [9]. Devices include all wearable monitors that directly measure at least one biosignal, such as acceleration, heart rate, or some other indicator of PA. Subjective methods rely on individual perceptions and assessments of the subject based on interviews, maintained diaries, or responses collected in the questionnaires [10].

The International Physical Activity Questionnaire (IPAQ) represents one of the subjective methods for assessing PA. It is a widely used instrument for evaluating PA in scientific research within the 18–65-year age group [11]. It estimates the amount of energy expended during those activities. The questionnaire requires reporting the total duration of activities in minutes over the course of the week. Metabolic Equivalent of Task (MET) points represent the energy cost of physical activities. One MET is approximately equivalent to 3.5 mL of oxygen consumed per kg of body weight per minute while sitting quietly. Higher MET values indicate more intense activities [12]. Every type of PA can be expressed in MET units [13]. To calculate the total value in MET-min/week, one must multiply the coefficient assigned to that activity by the number of days it is performed per week, and by the duration in minutes per day [14].

Previous literature utilizing the Metabolic Equivalent of Task (MET) values to assess physical activity has demonstrated that the majority of university students, including those enrolled in medical programs, exhibit alarmingly low levels of PA.

In the study by Jodczyk et al., 28.41% of medical students had low PA (<600 MET). The largest number of people studied (44.44%) were characterized by moderate PA (600 MET to 3000 MET), while 21.27% of medical students represented a high level of PA (>3000 MET) [15]. Similar research results were also obtained by Baj-Korpak J et al. [16], in which low PA was reported in 25.7% of medical studies, moderate PA in 44.1%, and moderate PA in 44.1%. High PA was noticed in 30.2% of respondents. In these studies, women represented 3/4 of all respondents. In addition, a significant difference in the results between women and men was noticed. Differences in this type were also noted in the studies by Kosendiak et al. [17], in which the average MET was 1542.5 in women and 1845.8 in men. In the studies conducted by Sykora J et al. [18], the average MET of 3334.6 in women and 3767.6 MET in men were higher than in other studies. The results of this study are high. This could have been because men were the dominant group in the population (53.69%), and the participants were not medical students.

However, based on the literature review, few studies have identified PA levels among university students. Some of these were conducted during the COVID-19 pandemic, when many participants spent most of their time at home. Therefore, an attempt was made to determine PA levels several years after the pandemic ended, when access to PA was not limited. Furthermore, previous studies have not found differences in physical activity levels based on age or medical field.

2. Materials and Methods

2.1. Study Design

This study aimed to determine the level of individual PA categories among medical students, as reported in the IPAQ. It was assumed that their level differentiates respondents based on gender, age, and field of study.

2.2. Participants

This single-center, cross-sectional study was conducted at the Medical University of Wroclaw. First- and second-year students from various fields of study were asked to complete the electronic version of the IPAQ via Google Forms during the first compulsory physical education classes between 9 and 25 October 2024. education class. All participants who had no contraindications to daily physical activity, were of legal age, did not attend physical education classes in English, and were present at physical education classes during that period were recruited. Participation was voluntary. A total of 691 students participated in the study (58% of first-year respondents and 42% of second-year respondents). The study was conducted in a large sports hall. Students from the following medical fields participated: medicine, dentistry, emergency medical services, obstetrics, dietetics, medical analysis, pharmacy, and physiotherapy. Trained researchers provided detailed information and explanations regarding the study, its aims, and implementation. Participants were informed that they could request clarification regarding the questionnaires at any time. Participants voluntarily agreed to participate in the study after receiving full information about the protection of their anonymity, the use of their data solely for research purposes, and the absence of any risks associated with participation. Participation in the study was unpaid, and no one received compensation for their contribution. Participants were spaced 2 m apart, which prevented communication. None of the participants objected to completing the survey. It was explained (to ensure students’ freedom of choice) that non-participation would not result in any disadvantages, including lower grades. After data collection, the researcher reviewed the respondents’ responses to ensure their accuracy before submitting them for further analysis. Incorrectly completed or incomplete questionnaires were excluded. Surveys from 667 respondents (496 women and 171 men) were included in the further analysis. All research procedures were conducted in accordance with the principles of the 1975 Declaration of Helsinki [19] as amended in 2013.

2.3. Measurement

All faculties got the same measurement protocol. After arriving at the Physical Education and Sports Department at UMED Wroclaw, students received the survey protocols to complete during the first scheduled class. They all received detailed information and explanations about the research, objectives, and implementation. Participants were informed that they could ask for clarification on any ambiguities at any time. Sex, three age groups (18–19 years, 20–21 years, 22 years and more) and 8 faculties of students were considered. As the survey was anonymous, participants were asked to complete the form as honestly and reliably as possible. To maintain strict anonymity, we did not cross-reference participation with official attendance records, which precludes the calculation of a formal response rate. To determine the PA level among students, the long-form IPAQ was used. IPAQ represents one of the subjective methods for assessing PA. It is a commonly used tool to assess PA in research studies among people aged 18–65. PA was evaluated in four spheres using the IPAQ-long form (work, transportation, housework, and leisure time). Every estate activity-score was calculated separately for each domain of PA (at work, transportation, housework, and leisure) in MET (Metabolic Equivalent of Task). One MET is equal to the energy expended during rest (3.5 mL O₂·kg⁻¹·min⁻¹). The questionnaire required providing the number of days per week on which individual domains of physical activity were performed and their total duration on one of these days. To calculate the total value in MET-min/week, the appropriate factor assigned to a specific domain of activity was multiplied by the number of days it was performed per week and the duration in minutes per day [14]. Before analysis, the raw data underwent a screening process. We excluded entries with logical inconsistencies (e.g., overlapping timeframes for different intensities) or a lack of answers. We applied the truncation rule, where all activity sessions exceeding 180 min were truncated to 180 min to prevent outlier inflation. Furthermore, any responses where the combined total of all physical activity categories exceeded 960 min (16 h) per day were considered implausible and excluded from the final analysis. Additionally, only activity sessions lasting at least 10 min were included in the MET-minute calculations [20].

2.4. Statistical Analysis

The data analysis was performed using a software system, Microsoft Excel for Mac (Version.16.97 with Real Statistics Resource Pack for Macintosh, Version 9.4.5). Firstly, MET-min/week was calculated. The weekly duration of a given type of activity in minutes was multiplied by a given multiplier, depending on the type of activity according to the procedure by Biernat et al. (2007) [14]: 8 for vigorous PA, 5.5 for vigorous PA around the house, 4 for moderate PA, 3 for moderate PA around the house, 3.3 for walking and 6 for cycling as a means of transport. Median, mean, and interquartile range values in each category of the physical activity for men and women, intervals of age, and different fields of study were calculated.

Confidence intervals for proportions were calculated using the Wilson score interval method [21]. The Wilson score interval has been shown to perform well across the full range of proportions, including extreme values, and has been recommended as a preferred method for proportion estimation in applied research [22]. The Shapiro–Wilk test was employed to assess the normality of the data distribution. Since there were outliers and the variance between groups was variable, a nonparametric test was chosen. The data was analyzed using the Mann–Whitney U test across six categories to assess the significance of differences between male and female participants. The Mann–Whitney U test compares two independent groups to determine if they differ on a single ordinal variable without assuming any distribution. To determine the significance of differences between age intervals and fields of study, the Kruskal–Wallis test was used. It is a nonparametric test used to evaluate whether there are significant differences among three or more independent groups based on a continuous variable that does not follow a normal distribution [23]. Afterwards, for categories of PA whose differences were found significant, Dunn’s test was performed to determine between which groups specifically, the significant differences can be found. It is a non-parametric method for conducting pairwise comparisons when the results of a Kruskal–Wallis test indicate significant group differences [24]. All the statistically significant differences were investigated for their effect size. For the Kruskal–Wallis test, because it is an omnibus test, it was calculated as eta squared (η²), where η² < 0.06 indicates a small effect, η² ≥ 0.06 a medium effect, and η² ≥ 0.14 a large effect [25]. The effect size for the pairwise comparisons (Dunn’s test and Mann–Whitney U test) was calculated as a rank biserial correlation (r), where r < 0.3 indicates a small effect, r ≥ 0.3 a medium effect, and r ≥ 0.5 a large effect [26]. The Bonferroni correction was used to account for the fact that the statistical tests were used multiple times on the same dataset.

3. Results

Firstly, the number of students who had ≥600 MET-min/week in moderate and vigorous physical activity was checked. This minimum value of MET-min/week has been recommended by the WHO for adults and can be achieved during activity for work, during transport and leisure time [20]. 502 (75.3%, 95% CI: 71.8–78.4%) participants achieved at least 600 MET-min/week.

When comparing mean MET-min/week values between male and female students, we see that the results are inconsistent. In some categories, women have higher median MET-min/week: physical activity at home, physical activity in transport, in some categories, men have higher median values: total physical activity, total vigorous physical activity, and vigorous activity in free time. In physical activity at work, the median MET-min/week is equal (

Table 1. Results of IPAQ in MET-min/week and the Mann-Whitney U test for male and female students.

Category of Physical Activity	Female (n = 496) Male (n = 171)	Median, (Q1–Q3), Mean	p-Value
Total physical activity	Female	4627.00, (2436.75–7957.50), 6224.03	0.879
	Male	4743.00, (2443.00–7746.00), 6038.73
Physical activity at work	Female	290.00, (0.00–840.00), 615.18	0.376
	Male	290.00, (60.00–630.00), 503.94
Physical activity at home	Female	667.50, (295.00–1353.00), 960.28	0.014
	Male	370.00, (180.00–840.00), 869.05
Total vigorous. physical activity	Female	960.00, (160.00–2820.00), 2043.48	0.231
	Male	1290.00, (160.00–2910.00), 2193.00
Vigorous physical activity in free time	Female	0.00, (0.00–60.00), 69.54	0.015
	Male	15.00, (0.00–140.00), 106.58
Physical activity in transport	Female	2161.50, (1138.50–3762.00), 3139.78	0.491
	Male	1881.00, (1119.00–3645.00), 2878.08

).

To assess the statistical significance of those differences, the Mann–Whitney U test was used and since the test was used for 6 distinct categories on the same dataset, the Bonferroni correction was implemented. At α = 0.00833, no statistically significant differences were found.

The data was also assessed to look for differences between students in 3 age groups: 18–19, 20–21, 22 and older. To assess the significance of differences between those age groups, the Kruskal–Wallis test was used. Again, because this test was used for six categories on the same dataset, the Bonferroni correction was used, with α = 0.00833.

Across all PA categories, only in PA at work were the differences between age intervals significant, at p = 0.008 with a small effect size (η² = 0.012) (

Table 2. Results in MET-min/week for students of different age intervals and results of the Kruskal–Wallis test for students of different age intervals.

Category of Physical Activity	Interval Age/n	Median, (Q1–Q3), Mean	p-Value
Total physical activity	18–19 y./472	4598.50, (2486.75–7593.00), 5861.44	0.149
	20–21 y./140	5441.00, (2640.50–9320.25), 7328.30
	22 y. and more/55	3995.00, (1996.00–7671.00), 5912.01
Physical activity at work	18–19 y./472	275.00, (0.00–730.00), 564.16	0.008 *
	20–21 y./140	455.00, (105.00–915.00), 843.39
	22 y. and more/55	130.00, (0.00–495.00), 605.02
Physical activity at home	18–19 y./472	630.00, (270.00–1260.00), 1028.02	0.287
	20–21 y./140	570.00, (172.50–1432.50), 1012.66
	22 y. and more/55	540.00, (200.00–1080.00), 870.95
Total vigorous physical activity	18–19 y./472	965.00, (165.00–2880.00), 1952.83	0.253
	20–21 y./140	1067.50, (140.00–3490.00), 2558.47
	22 y. and more/55	700.00, (0.00–1920.00), 1959.23
Vigorous activity in free time	18–19 y./472	0.00, (0.00–100.00), 81,35	0.761
	20–21 y./140	0.00, (0.00–60.00), 70.32
	22 y. and more/55	5.00, (0.00–90.00), 81.54
Physical activity in transport	18–19 y./472	2079.00, (1146.75–3481.50), 2886.04	0.783
	20–21 y./140	2275.50, (936.75–4566.00), 3552.92
	22 y. and more/55	2406.00, (1071.00–3801.00), 3444.96

*—Statistically significant at p < 0.00833, n = 667, Q1—first quartile, Q3—third quartile.

). In this category, Dunn’s test showed a significant difference between the age groups 18–19 and 20–21, with p = 0.00685 and a small effect size (r = 0.109). Here, the 20–21 age group had a higher median MET-min/week by 180.00. A significant difference with p = 0.00844 was also found between age groups 20–21 and 22 years and more with a small effect size (r = 0.189). The 20–21 age group had a higher median MET-min/week by 325.00.

Lastly, students of different fields of study were compared in those same categories of physical activity. The fields of study included: medical analysis, dietetics, pharmacy, physiotherapy, medicine, dentistry, nursing, obstetrics, and emergency medical services. To assess the significance of the difference between those groups, the Kruskal–Wallis test was performed. Once again, a non-parametric test was chosen as the variance between groups was high, and the Bonferroni correction was used because this test was applied on the same dataset for six distinct categories, with α = 0.00833.

The Kruskal–Wallis test revealed a statistically significant difference between results for physical activity at work. A post hoc analysis employing Dunn’s test with Bonferroni correction (α = 0.00139) showed statistical differences between dietetics and nursing at p < 0.001 with a medium effect size (r = 0.385) where nursing had a higher median MET-min/week by 1269.00. Another statistically significant difference was found between medicine and nursing, nursing having a higher median MET-min/week by 1260.00 at p < 0.001 with a small effect size (0.256). The last statistically significant difference was found between nursing and obstetrics, nursing having higher median MET-min/week by 1295.00 at p = 0.001 with a medium effect size (r = 0.434) (see Supplementary Material, Table S1).

4. Discussion

The main aim of this study was to determine the level of PA among medical students and to assess differences in MET m/w values across fields of study and gender.

In the current study, gender differences in PA levels were not observed. Based on the results of the Mann–Whitney U test, there were no significant differences between male and female MET values in all six PA categories: total PA, PA at work, PA at home, total vigorous physical activity, vigorous activity in free time, and PA in transport.

This finding contrasts with previous literature on Polish medical student populations, where gender differences are frequently reported. According to the findings of the 2020 and 2021 study conducted at Wroclaw Medical University on its student population [17], the mean MET m/w was, however, lower in the female population than in the male population, and that difference was statistically significant. In October 2020, a mean MET m/w of 1542.5 was observed in the female population (75.7% of the study population) and 1845.8 mean MET m/w in males. Moreover, the study was conducted during the COVID-19 pandemic and ‘lockdown’ period as well, which must have affected the mean MET m/w values. In the current study, both females and males showed higher mean MET m/w values (6224.03 MET m/w and 6038.73 MET m/w, respectively).

Notably, a study by Jodczyk et al. [15], conducted in 2021 in Poland, reported the mean MET m/w value of 1376.03 MET m/w for females and 1922.35 MET m/w for males—both lower than the values reported in the current study and in the study by Kosendiak et al. [17].

In 2020 and 2021, significant differences in moderate METs were observed between the clinical and non-clinical student groups [17]. The non-clinical group included students from the following fields: medical laboratory sciences, public health, dietetics, and pharmacy. The clinical group included students from the following fields: physiotherapy, medicine, dentistry, nursing, emergency medical services, and midwifery. Students from non-clinical fields achieved significantly higher scores than students from clinical fields in 2020, but in 2021, this difference was not significant. The current study, however, confirms significant differences in PA at work between medical and nursing students as well as dietetics and nursing students and between obstetrics and nursing students in PA at work. It is worth mentioning that nursing consistently demonstrated higher PA at work compared to the other aforementioned student groups.

According to a study carried out in 2022 by Baj-Korpak J et al. [16], differences in mean MET m/w values were observed based on gender in the population of Polish medical students. The mean MET m/w value among Polish female students was 4281.2, and among Polish male students it was 6047.9, with that difference being statistically significant. However, the values obtained in that study are lower for females than the mean MET m/w values calculated in this article (female mean: 6224.03 MET m/w). For males (6038.73 MET m/w), the values obtained in the current study are slightly lower than those reported by Baj-Korpak J et al. [16]. This difference may be explained by a growing interest in fitness and healthy lifestyle habits among women. Although it is important to relate the obtained means in this study to the median MET w/m for females and males, that was 4627.00 and 4743.00, respectively.

The findings of this study show significant differences in the age groups only in physical activity at work. Dunn’s test showed a significant difference between the age groups 18–19 and 20–21. A significant difference was also found between age groups 20–21 and 22 and older. This means that the statistically different PA levels were only associated with PA at work, but not between every age group. There was no available comparative data on age groups and their corresponding mean MET m/w values in the studies referenced above.

Finally, 75.3% of the subjects engaged in physical activity of ≥600 MET m/w, which corresponds to the recommended physical activity by the WHO. In different age groups, the statistically significant difference was, as mentioned above, observed in the physical activity at work exclusively. Therefore, these findings may provide valuable guidance for the authorities of medical faculties as they indicate the age groups of students that should be targeted by physical activity and physical activity at work programs.

4.1. Study Limitations

Several methodological constraints should be kept in mind when interpreting these results. First, our recruitment strategy relied on approaching students just before mandatory physical education classes. This approach inherently introduces a selection bias, as the sample excludes those who were absent or who habitually avoid these sessions. Because the survey was strictly anonymous and we lacked access to official school attendance records, we could not determine a precise response rate or compare the profiles of attendees versus non-attendees. Consequently, the findings lean toward the perspectives of students who are more consistently present in the academic environment.

The use of the IPAQ Long Form (IPAQ-LF) also presents specific challenges. While we selected this version to capture a comprehensive view of various activity contexts, it remains a self-report tool. Research consistently shows that the IPAQ-LF is prone to overestimation of physical activity compared to objective data. Furthermore, medical students may be susceptible to social desirability bias, potentially reporting higher activity levels to align with professional or health-related expectations [27]. Without validation against objective measures, such as accelerometers or pedometers, these reported levels should be viewed as subjective estimates rather than absolute values.

Finally, the study’s cross-sectional design offers only a snapshot of student behavior, failing to account for how physical activity might fluctuate during exam periods or with changing seasons. Our analysis was also limited by the variables collected; we did not account for socioeconomic status, living arrangements, or prior athletic history, all of which likely influence current habits. Future research would benefit from longitudinal tracking and the inclusion of wearable devices to better map the physical activity trajectories of medical students throughout their training.

4.2. Future Directions

Future research in this area should incorporate objective monitoring tools, such as accelerometers or pedometers, in conjunction with the IPAQ. Combining self-reported data with device-based measurements would allow for the validation of subjective responses and significantly enhance the methodological rigor and quality of future investigations, especially because IPAQ long-form data are prone to overestimation and reporting bias. Consequently, the present work should be viewed as a foundational starting point rather than an endpoint, providing a basis for more technologically integrated studies in the field of physical activity.

5. Conclusions

The study was conducted to determine the level of PA among medical students. A substantial majority of the surveyed participants (75.3%) successfully met the WHO recommendation of achieving at least 600 MET-min/week of physical activity. This finding stands above the global benchmarks presented in the WHO Global Status Report, which indicates that nearly one-third of the global adult population does not meet the minimum requirements for physical activity [28,29].

No statistically significant differences in physical activity levels were found between male and female students across any of the six analyzed categories. Median values fluctuated. Men scored higher in total and vigorous leisure activity. Women scored higher in domestic and transport-related activity. The overall gender gap in physical activity has effectively closed within this cohort.

Statistically significant differences between subgroups were strictly confined to the category of physical activity at work.

• By Field of Study: Nursing students exhibited a significantly higher median occupational MET-min/week compared to students of dietetics, medicine, and obstetrics.
• By Age Group: Academic age significantly impacts workplace activity, with the 20–21 age group demonstrating a significantly higher median occupational MET-min/week than both the younger (18–19) and older (22 and above) student cohorts.

Since variations in physical activity are driven by specific fields of study and age groups within the occupational and clinical training domain, we believe that university authorities should utilize these target-specific insights to design tailored PA programs and health interventions.