Skip to main content

Type and intensity distribution of structured and incidental lifestyle physical activity of students and office workers: a retrospective content analysis

Abstract

Background

Physical activity (PA) guidelines acknowledge the health benefits of regular moderate-to-vigorous physical activity (MVPA) regardless of bout duration. However, little knowledge exists concerning the type and intensity distribution of structured and incidental lifestyle PA of students and office workers. The present study aimed to i) assess the duration and distribution of intensity of MVPAs during waking hours ≥50% of heart rate reserve (HRR), ii) to identify the type of PA through diary assessment, iii) to assign these activities into structured and lifestyle incidental PA, and iv) to compare this information between students and office workers.

Methods

Twenty-three healthy participants (11 students, 12 office workers) recorded heart rate (HR) with a wrist-worn HR monitor (Polar M600) and filled out a PA diary throughout seven consecutive days (i.e. ≥ 8 waking h/day). Relative HR zones were calculated, and PA diary information was coded using the Compendium of PA. We matched HR data with the reported PA and identified PA bouts during waking time ≥ 50% HRR concerning duration, HRR zone, type of PA, and assigned each activity to incidental and structured PA. Descriptive measures for time spend in different HRR zones and differences between students and office workers were calculated.

Results

In total, we analyzed 276.894 s (76 h 54 min 54 s) of waking time in HRR zones ≥50% and identified 169 different types of PA. The participants spend 31.9 ± 27.1 min/day or 3.9 ± 3.2% of their waking time in zones of ≥50% HRR with no difference between students and office workers (p > 0.01). The proportion of assigned incidental lifestyle PA was 76.9 ± 22.5%.

Conclusions

The present study provides initial insights regarding the type, amount, and distribution of intensity of structured and incidental lifestyle PA ≥ 50% HRR. Findings show a substantial amount of incidental lifestyle PA during waking hours and display the importance of promoting a physically active lifestyle. Future research could employ ambulatory assessments with integrated electronic diaries to detect information on the type and context of MVPA during the day.

Peer Review reports

Background

Physical inactivity is a global challenge [1] and facilitates the development of a variety of unfavorable health consequences such as non-communicable [2] or mental diseases [3]. To tackle the risk of physical inactivity, the World Health Organization (WHO) [4, 5] as well as many nations [6,7,8] provide physical activity (PA) recommendations to guide and inform governing bodies and individuals about the contribution of PA for promoting health and well-being across the life span [4]. The key message of the recently updated WHO guidelines on PA and sedentary behavior states that “every move counts”, emphasizing that i) the minimum weekly threshold of 150–300 min of moderate-to-vigorous-intensity physical activity (MVPA) as well as ii) the interruption of sedentary behavior with all kinds of PA (regardless of their intensity) essentially counteracts negative health outcomes [4].

Compared to the WHO PA guidelines of 2010, the updated guidelines do not recommend the accumulation of PA in at least 10 min bouts [9]. This recent modification reflects the growing evidence that PA of any bout duration is associated with improved health outcomes, including all-cause mortality [10, 11]. Additionally, the updated British PA guidelines explicitly acknowledge the health benefits of shorter exercise durations comprising of very vigorous-intensity PA such as sprinting or stair climbing [12] or performed as a high-intensity interval exercise (HIIT) with vigorous-intensity exercise “snacks” as described previously [13, 14]. The recognition of short (intense) PA benefiting various dimensions of health supports public health messages advocating lifestyle PA that are unlikely to last 10 min or longer, e.g. climbing staircases, carrying heavy shopping items or toddlers, managing housework [10].

.The aforementioned activities are categorized as incidental lifestyle PAs, i.e. activities as part of daily living and not intended for recreational or health purposes without requiring optional time [15]. Incidental PA represents the opposite of structured PA or exercise characterized by scheduled, pre-planned, and intentionally directed activities e.g. visiting a gym, jogging, cycling, or other activities for recreation, improving or maintaining physical fitness, performance, or health [16]. Incidental lifestyle PAs with an intensity exceeding 6 MET or ≥ 14 on Borg’s 6-to-20 scale [17] and shorter than < 5 min are defined as “vigorous intermittent lifestyle physical activities” [18]. However, little knowledge exists of (i) how frequently, (ii) with which type of behavior, (iii) in which PA domain (work, household, transport, or leisure), and (iv) to which extend incidental lifestyle PA, in general (long and shorter bouts), are distributed throughout the waking hours of different populations. To gather first information about the type and intensity distribution of incidental lifestyle PA, the selection of homogenous populations concerning their learning or working environment seems reasonable. For this study students and office-workers were selected, as these population groups are often prone to an inactive lifestyle [19,20,21].

Assessment of incidental lifestyle PAs or PAs of short duration is challenging since PA questionnaires are ineffective in capturing short and intermittent PA bouts and are prone to recall bias [22]. Advancements in wearable accelerometer-based technologies provide opportunities to reveal incidental PA throughout waking hours, however, accelerometry per se monitors a selection of external load markers and does not allow to judge internal loading. Additionally, obtaining valid accelerometer-based activity data is challenging because of correct accelerometer placement, data smoothing process, cut-off points, etc. [18].

Newly developed optical sensors now allow the continuous recording of heart rate (HR) [23,24,25] which probably is the most evaluated internal marker in various populations and settings in the field of exercise physiology for the assessment of cardiorespiratory load during movement of any kind including PA [22]. Unfortunately, current consumer-grade wearables do not automatically allow information regarding the type or domain of specific incidental PA behavior, for example, whether a specific HR response occurs due to stair climbing, vacuuming cleaning, carrying groceries, rushing to catch the bus, etc. Matching the HR response with subjective information about the specific type of PA such as through PA diaries would assist to understand the relative internal cardiorespiratory loading of certain (incidental lifestyle) PA. Information about the level of internal load during everyday PA behavior, as well as the frequency, duration, and specific type of PA, and how incidental lifestyle PA and structured PA relate to each other would deepen our knowledge in incidental lifestyle PA research. Deeper insights into incidental lifestyle PA would allow directing future public health messages advocating PA lifestyle behaviors, as incidental lifestyle PA does not encounter the multiple barriers to structured exercises, such as lack of time, costs, equipment, lack of skills, or poor fitness [15].

The present investigation aimed to i) assess the amount and distribution of intensity and duration of PAs during waking hours outreaching ≥50% of heart rate reserve (HRR) as an approximate of moderate-intensity PA > 3 MET, ii) to identify the type of these activities through diary assessment, iii) to assign these activities into structured PA and incidental lifestyle PA, and iv) to compare this information between two selected sample groups of students and office workers.

Methods

Study design

The observational study of students and office workers employed a mixed-method approach to assess the amount and distribution of intensity and duration of PAs during waking hours. All participants continuously were equipped with a wrist-worn HR monitor throughout the day for seven consecutive days (besides for charging) and recorded HR. The wrist-worn HR monitor was employed following the manufacturer’s recommendations (e.g. wearing location, settings, etc.). Furthermore, all participants were instructed to fill out a diary indicating their performed PA every 15 min throughout the day for 7 days. The study was approved by the ethical committee of the Sports Science Institute of the University of Würzburg (04/2021) and followed the Declaration of Helsinki [26].

Participants

We recruited 23 healthy voluntary participants (11 university students (age range 18–23), 12 office workers (mean age 48 ± 7 yrs., 6 men)) as a convenient sample. We did not assess the sex and precise age of the students due to the anonymization of the rather small sample. All were informed about each experimental procedure and provided written consent to participate.

Experimental procedures

Heart rate monitoring

A wrist-worn HR monitor (Polar M600, Polar Electro Oy, Kempele, Finland) with optical sensors and a sampling rate of 1 Hz recorded the HR throughout the day. This device provides accurate HR readings during periods of steady-state cycling, walking, jogging, and running and is most likely independent of sex, body mass index, maximal oxygen consumption, skin type, or wrist size [27].

Physical activity diary

In the present study, we employed a modified version of the Bouchard activity diary aiming to assess the type of PA subjectively instead of evaluating the energy expenditure [28]. Therefore, we only used the instrument’s grid-type table, which divides a day into 96 15-min periods over a 24-h period. We did not employ the original front page in our study (table of activities, energy cost, and corresponding categorical values) [28]). In contrast to Bouchard’s original diary, our participants were asked to record the i) type of activity into the grid table and ii) whenever they did not wear the smartwatch, instead of the code for each category of PA. All participants were asked to fill in the modified diary for seven consecutive days.

Data extraction and processing

All HR data were downloaded from each participant’s Polar Flow Applications (Polar, Polar Electro Oy, Kempele, Finland) as a Microsoft Excel file. The HR was smoothed using the average HR of each 15 s interval. Each participant’s maximum HR was estimated employing the equation “220 - age”, and resting HR was defined as the lowest, constant HR for 10 min recorded during the night while sleeping and averaged for 3 days. The traditional age equation formula (220-age) allows us to sufficiently approximate the HRmax in this rather young sample [29]. However, the formula may tend to underestimate HRmax in older populations with the effect of underestimating the true level of cardiorespiratory stress [29]. For the scope of this study, the underestimation of cardiorespiratory stress vs. overestimating cardiorespiratory stress seems to be a minor challenge.

Based on the individual’s maximal and resting HR, 10 individual relative HR zones were defined based on the individual’s heart rate reserve (HRR) which was subsequently divided into 10 equal 10% HRR zones. The HRR was calculated by subtracting the resting HR from the maximal HR [22].

To transfer each individual recorded HR into the individual relative HR for each value, the individual resting HR was subtracted from the smoothed average HR, then divided by the HRR and multiplied by 100. Time in each HRR-zone per day was calculated for each individual.

For the PA diary assessment, activities were coded and grouped using the five-digit code of the Compendium of Physical activities [30, 31]. If a participant reported a PA that was not listed in the compendium, a new code was created for this specific activity according to the coding scheme of the compendium (see suppl. 1).

All HR and subjective data were synchronized via timestamps obtained from the wrist-worn HR monitor and PA diary.

For data processing, we included all days with a waking time of ≥8 h/day. We defined waking time by i) wearing the wrist-worn heart rate monitor and ii) excluding time frames of ‘sleeping’ and ‘snoozing’ documented in the PA diary. For the scope of the data analysis, only moderate-to-vigorous PA were relevant. Thereby the HRR zones are normally classified as follows [22, 32]: 40- < 60% as moderate, 60- < 85% as vigorous (hard), 85 - < 100 as vigorous (very hard), and the HRR zone of 100% as maximal. In order not to overestimate moderate-to-vigorous PA, we only included PA with ≥50% of the HRR and parceled the data into 10% HRR zones to be more accurate through smaller zones (i.e. Zone 50–60% HRR, Zone 60–70% HRR, etc.). After identifying all PA bouts during waking time with an intensity ≥50% HRR, we determined the start and stop time, calculated the seconds in each zone through the objective data, and matched the HR-data with the reported specific type of PA from the diary. Then we listed the duration as well as the HRR zone. In case a participant entered two or more PA in the same 15-min period in the PA diary, then the values were assigned to the more vigorous PA. Values ≥50% HRR, which could not be assigned to any PA because of missing subjective PA diary information, were documented as “no answer”.

After classification of the PA type based on the information of the PA diary, we assigned the PA type to incidental or structured PA. Structured PA was defined as i) exercise or performing sports, ii) all activities in the categories conditioning exercise, running and sports, iii) for the activities mountain biking, dance workout/dance, aerobic, dancing, nordic walking, swimming. All other activities were assigned to incidental PA. For every specific type of PA ≥ 50%HRR, we listed the number of participants reporting the PA, the total duration during waking time, the frequency of the type of PA, and the mean duration of PA when occurring.

We calculated the mean minutes per day in zones ≥50% HRR. The percentage of waking time in zones ≥50% HRR was calculated by dividing the accumulated time in each zone and in the Zone ≥50% HRR through the total waking time. To identify the percentage of incidental PA compared to structured PA in zones ≥50% HRR, we divided the time of incidental PA through the total time in each zone only for the participants who featured PA bouts in this zone.

Statistical analysis

Mean, standard deviation, median, and confidence intervals for time spend in different HRR zones was calculated. Most of the dependent variables (daily time in zone 50–100% HRR; percentage of waking time per day in Zone 50–100% HRR [%]; percentage of incidental PA compared to structured PA in Zone > 50% HRR [%]) were not normally distributed (Kolmogorov-Smirnov-Test). To explore differences between students and office workers in the zones of 50–100% of HRR we used the non-parametric Mann-Whitney-U-test. To prevent inflation of type 1 error, we applied an alpha level of p < 0.01. All statistical analysis were performed in the SPSS 23.0 (IBM Corp., Armonk, NY, USA) software package for Microsoft, and figures of descriptive numbers were prepared in Excel 2016.

Results

In total, we recorded 179 days of 23 participants which resulted in 141 valid days (≥ 8 h of waking time) and 6.13 ± 1.01 valid days per participant. In total, we matched 6.951.254 s waking time (i.e. 49,114 ± 4334 s of waking wearing time per participant per valid day (13 h 38 min 34 s ± 1 h 12 min 23 s)) of objective HR with PA diary data and allocated the HR to the different HRR zones. In summary, 276.894 s (76 h 54 min 54 s) of waking time were in HRR zones ≥50% and were employed for further analyses including total time spend in different HRR zones, type of PA (169 different types), frequency of PA ≥ 50% HRR (total of 6.074 events), bout duration and allocation to structured or incidental PA (see Table 1).

Table 1 Descriptive measures of sample and analyzed wearing time (Mean ± SD)

Examples of individual HR patterns with matched PA information of participants are illustrated in Fig. 1a-c.

Fig. 1
figure 1

Examples of 24-h heart rate patterns of a) an office worker with a day off, b an office worker in home office and c) an university student with matched physical activity information from the physical activity diary. Heart rate zones reflect the relative zones of the individual heart rate reserve

The participants spend 31.9 ± 27.1 min/day or 3.9 ± 3.2% of their waking time in zones of ≥50% HRR with no difference between students and office workers (p > 0.01). Office workers spent more time in HRR zones ≥90% compared to students (1.73 ± 2.54 min/day vs. 0.03 ± 0.61 min/day; p < .01; 0.20 ± 0.29% vs. 0.003 ± 0.007%, p < .01) (see Table 2).

Table 2 Descriptive measures (mean ± standard deviation, median; 95% confidence interval) and the difference between students and office workers concerning time per day of activities ≥50% heart rate reserve, the percentage of time compared to total waking wearing time in heart rate reserve zones ≥50%, and the percentage of assigned incidental lifestyle physical activity compared to assigned structured PA in heart rate reserve zones ≥50%

Comparing the proportions of assigned incidental and assigned structured PA ≥ 50% HRR, 76.9 ± 22.5% was spent in incidental PA with no differences between students and office workers. In zone 90–100% of HRR, the proportion of assigned incidental PA compared to assigned structured PA was 30.3 ± 45.7%.

Tables 3 and 4 summarize the reported type of PA (incidental and structured) accomplished by all students and office workers (all types of physical activities are reported in the supplementary material). Within the incidental PA of students’ leisure time, activities such as self-care and miscellaneous activities (total of 403.6 min) and transportation activities (total of 306.5 min) were most often reported. Office workers reported most often incidental PA in the categories transportation (total of 960.5 min), household activities (total of 652.6 min), and leisure time activities (total of 573.6 min) in HRR zones ≥50%.

Table 3 Description of reported incidental lifestyle PA and structured PA of n = 11 students in the HRR zone ≥50% with total reported duration during waking time, frequency, and mean duration of PA when it occurred (total duration of waking time in HRR zones ≥50% = 83.929 s (23.31 h); total frequency in waking time in HRR zones ≥50% = 1913)
Table 4 Description of reported incidental lifestyle PA and structured PA of n = 12 office workers in the HRR zone ≥50% with total reported duration during waking time, frequency, and mean duration of PA when it occurred (total duration of waking time in HRR zones ≥50% = 192.965 s (53.60 h); total frequency in waking time in HRR zones ≥50% = 4161)

Discussion

The main findings of our study are that our sample achieved about 30 min per day in zones ≥50% HRR and that more than 75% of the PA in ≥50% HRR zones were accomplished through incidental lifestyle PA, with little difference between students and office workers. We furthermore identified that most of the incidental lifestyle PA ≥ 50% HRR in students included leisure and transportation activities and in office workers transportation, household, and leisure time activities.

Since the mean duration of PA ≥ 50% HRR was > 30 min per day in most participants, our sample sufficiently achieved the updated WHO recommendation for PA and sedentary behavior [9]. Considering the predominant short duration of the bouts in zones ≥50% HRR it becomes obvious that most of the activities in ≥50% HRR zones lasted less than 10 min. Recent evidence, however, supports the fact that PA of any bout duration is associated with improved health outcomes [10, 11]. Most of the accomplished PA ≥ 50% HRR in the present study (21.87 ± 17.15 min/day) comprised of moderate-intensity PA (i.e. 50 - < 60% HRR) [22, 33]. However, almost one-third of the PA (10.0 ± 12.1 min/day) included vigorous, very vigorous, or maximal intensities (≥ 60% HRR) [22, 33]. Following epidemiological evidence, a proportion of ≥30% vigorous PA of total PA suggests additional health benefits compared to an equivalent amount of moderate-intensity PA [34,35,36]. As stated previously [23], future studies should further investigate and compare the roles of low to vigorous-intensity activities (independent of quantifying total activity energy expenditure) for health promotion, disease prevention, and management, so that public health messaging can be directed more specifically to the type and proportion of different intensity PA should ideally have.

Interestingly, the proportion of assigned incidental compared to assigned structured PA was considerably high with more than 75% of overall PA in zones ≥50% HRR in the two studied sample populations. The high contribution of incidental PA in our results resembles in part the findings of a representative study in the population of US adults [37], in which lifestyle activities were more frequently reported than sports and/or recreational activities. Our findings reveal to some extent the moderate- and the vigorous-intensities of incidental lifestyle PA and consequently exhibit the importance of promoting a physically active lifestyle to achieve the minimum recommended PA for a healthy life. Especially in physically inactive populations reporting a perceived lack of time or a low priority for exercising [38], lifestyle embedded PA could play an essential role to engage in sufficient MVPA.

In respect to the high contribution of incidental PA in more vigorous intensity zones, the participants in this study displayed a considerable amount of vigorous lifestyle PA [15, 18] (i.e. Home activities (‘cleaning’, ‘cooking’, ‘putting away groceries’, ‘hanging laundry’, etc.), ‘sightseeing’, ‘celebrating’, ‘playing piano’, ‘biking’, ‘walking’, ‘climbing stairs’ etc.). Following the results of previous experimental studies, also short intense exercise bouts of incidental PA could, at least to some extent, positively impact cardiorespiratory fitness [13, 14]. To date, the knowledge about vigorous intermitted (short) lifestyle PAs is limited [18] and the relatively high contribution of these activities in our study sample supports the importance and need for the recently established research framework to better understand the health potential of vigorous intermitted lifestyle PA [18]. For example, it seems meaningful i) to better understand the contribution of vigorous intermittent lifestyle physical activities in PA patterns, ii) to recognize and understand the short and long-term dose-response of vigorous intermittent lifestyle PA concerning health, and iii) to gain knowledge about how to convince and empower people to be more physically active in their daily lives [15].

We detected a marginally greater contribution of time in the ≥90% HRR zone in office workers than in students (1.73 ± 2.54 min vs. 0.03 ± 0.61 min). Recognized PA of the diary was predominately identified during leisure time with activities such as ‘jogging’, ‘walking the dog’, ‘mountain biking’, ‘circuit training’, ‘treadmill’, ‘Qi Gong (shaking exercise)’ etc. but also unstructured activities such as ‘getting changed’ in office workers. One reason for little time spent in ≥90% HHR may also arise from the inert kinetics of HR. Typically, after the onset of vigorous activity, the neuro-humoral and metabolic mechanisms stimulating HR increase require several seconds to meet the oxygen need of the working muscle, and usually HR plateaus after approximately 60s with high intensity [39]. Thus, any type of vigorous activity < 60 s will not be sufficiently described by continuous HR recording.

In both samples, transportation activities such as walking, cycling, and transportation or combinations of these contribute considerably to the PA behaviors exceeding 50% HRR, which is in line with previous findings [40] and underpins the importance of promoting active transportation for health and PA promotion [41,42,43]. Household activities ≥50% HRR were more present in office workers than in students, potentially because office workers live in households with more than one person and take more actions for cleaning, washing, grocery shopping, etc. Students may often live in single-room flats, or in their family homes, where they might engage in fewer household activities. Therefore, cognitive restructuring [44, 45] of often unpopular household activities, i.e. highlighting the health potential of carrying heavy shopping bags or vacuum cleaning could be a strategy to support PA promotion and achieving recommended PA. Unexpectedly, leisure time self-care activities such as showering, eating, dressing (see supplementary material 1) often exceeded 50% HRR. This could be due to frequent changes in body positions during showering and dressing, possible time constraints or possible inaccuracy i) arising from faulty PA diary recording, or ii) HR monitoring due to fluid interference with the optical sensors of the wrist-worn HR monitor.

Limitations

Assessing HR and linking the data to PA has some limitations as the HR not only responds to the oxygen needs in connection with PA. Numerous other factors including changes in body position (e.g. moving from supine to erect posture in healthy adults may induce an immediate increase in heart rate) [46], smoking [47], consumption of alcohol [48], and neurohormonal factors such as psychological stress [49] and emotional circumstances may cause sympathetic reactivity (e.g. due to scary or enjoyable situations) triggering plasma catecholamines increase, which is a main driver for HR elevation [50].

Hence, changes in HR throughout the day are the result of a quite complex interplay and may affect present HR data. However, controlling these factors while freely living is challenging. The HR monitor employed in the present study is accurate during periods of steady-state endurance exercise [27] but has not been validated for all-day activities. Furthermore, the validation of the used HRmax formula in our sample and further integration of anthropometric variables could add accuracy to future studies. Additionally, the sex of the student population was not recorded, which may have an impact on the interpretation of the results.

In some cases, reported PAs in the diary, e.g. sitting and working which were assigned to sedentary behaviors (i.e. a metabolic equivalent of < 1.5 MET [51]) revealed short durations with heart rates ≥50% HRR zones. These findings point out that within sedentary or low-intense behaviors (e.g, sitting, working, or driving a car) short durations of intense cardio-respiratory loading may occur. One explanation could be that these moderate-to-vigorous-intensity behaviors are not always captured by the relatively long diary reporting time frame (i.e. 15 min) for PA assessment [28]. Another reason could be that participants reported a (longer) bout of intense PA (e.g. jogging) within one or two 15 min-frames and this activity could have lasted several minutes (e.g. 3 min) within the proceeding 15-min frame but without mentioning in the PA diary. Another reason could be that the HR elevation may have been caused by non-movement situations, i.e. psychological stress.

The identified challenges suggest a methodological modification for future studies. One modification could be to ask participants to document non-movement events that may have triggered a rise in HR (i.e. emotional event, alcohol intake, smoking, etc.). A more sophisticated possibility could be to employ ambulatory assessment including movement monitoring (i.e. external load) via e.g. accelerometry and HR (internal load) with ecological momentary assessment, such as electronic diaries [52] to capture real-time self-reported information. The strengths of ambulatory assessments are the acquisition of data near real-time, thereby i) minimizing retrospective biases in real-world settings and ii) enabling ecological valid findings [52].

Conclusion

The present study provides initial insights regarding the type, amount, and distribution of intensity of structured and incidental lifestyle PA ≥ 50% HRR during the day in students and office workers. The present findings revealed that more than 75% of the PA ≥ 50% HRR was assigned to incidental lifestyle PA and that a substantial amount was spent engaging in vigorous intensity. The present data underline the importance of promoting a physically active lifestyle next to structured PA and points to the need for future research to better understand the health potential of incidental lifestyle PA. Therefore ambulatory assessments with integrated electronic diaries could help to detect information on the type and context of MVPA during the day.

Availability of data and materials

The datasets of the current study are available from the corresponding author on reasonable request.

Abbreviations

PA:

Physical activity

MVPA:

Moderate-to-vigorous physical activity

HR:

Heart rate

HRR:

Heart rate reserve

References

  1. Guthold R, Stevens GA, Riley LM, Bull FC. Worldwide trends in insufficient physical activity from 2001 to 2016: a pooled analysis of 358 population-based surveys with 1.9 million participants. Lancet Glob Health. 2018;6(10):e1077–e86.

    PubMed  Google Scholar 

  2. Lee IM, Shiroma EJ, Lobelo F, Puska P, Blair SN, Katzmarzyk PT. Effect of physical inactivity on major non-communicable diseases worldwide: an analysis of burden of disease and life expectancy. Lancet. 2012;380(9838):219–29.

    PubMed  PubMed Central  Google Scholar 

  3. Schuch FB, Vancampfort D, Richards J, Rosenbaum S, Ward PB, Stubbs B. Exercise as a treatment for depression: a meta-analysis adjusting for publication bias. J Psychiatr Res. 2016;77:42–51.

    PubMed  Google Scholar 

  4. Bull FC, Al-Ansari SS, Biddle S, Borodulin K, Buman MP, Cardon G, et al. World Health Organization 2020 Guidelines on physical activity and sedentary behaviour 2020.

    Google Scholar 

  5. World Health Organization W. Global recommendations on physical activity for health. 2010.

    Google Scholar 

  6. Rütten A, Pfeifer K, editors. Nationale Empfehlungen für Bewegung und Bewegungsförderung. Nürnberg: FAU Erlangen-Nürnberg; 2016.

    Google Scholar 

  7. Piercy KL, Troiano RP, Ballard RM, Carlson SA, Fulton JE, Galuska DA, et al. The physical activity guidelines for Americans. JAMA. 2018;320(19):2020–8.

    PubMed  Google Scholar 

  8. Tremblay MS, Warburton DE, Janssen I, Paterson DH, Latimer AE, Rhodes RE, et al. New Canadian physical activity guidelines. Appl Physiol Nutr Metab. 2011;36(1):36–46 7–58.

    PubMed  Google Scholar 

  9. Bull FC, Al-Ansari SS, Biddle S, Borodulin K, Buman MP, Cardon G, et al. World Health Organization 2020 guidelines on physical activity and sedentary behaviour. Br J Sports Med. 2020;54(24):1451–62.

    PubMed  Google Scholar 

  10. Jakicic JM, Kraus WE, Powell KE, Campbell WW, Janz KF, Troiano RP, et al. Association between bout duration of physical activity and health: systematic review. Med Sci Sports Exerc. 2019;51(6):1213–9.

    PubMed  PubMed Central  Google Scholar 

  11. Murphy MH, Lahart I, Carlin A, Murtagh E. The effects of continuous compared to accumulated exercise on health: a Meta-analytic review. Sports Med. 2019;49(10):1585–607.

    PubMed  PubMed Central  Google Scholar 

  12. Gibson-Moore H. UK chief medical officers’ physical activity guidelines 2019: What’s new and how can we get people more active? Nutr Bull. 2019;44(4):320–8.

    Google Scholar 

  13. Jenkins EM, Nairn LN, Skelly LE, Little JP, Gibala MJ. Do stair climbing exercise "snacks" improve cardiorespiratory fitness? Appl Physiol Nutr Metab. 2019;44:681–4.

    PubMed  Google Scholar 

  14. Little JP, Langley J, Lee M, Myette-Cote E, Jackson G, Durrer C, et al. Sprint exercise snacks: a novel approach to increase aerobic fitness. Eur J Appl Physiol. 2019;119:1203–12.

    PubMed  Google Scholar 

  15. Stamatakis E, Johnson NA, Powell L, Hamer M, Rangul V, Holtermann A. Short and sporadic bouts in the 2018 US physical activity guidelines: is high-intensity incidental physical activity the new HIIT? Br J Sports Med. 2019;53(18):1137–9. https://doi.org/10.1136/bjsports-2018-100397.

    Article  PubMed  Google Scholar 

  16. Caspersen CJ, Powell KE, Christenson GM. Physical activity, exercise, and physical fitness: definitions and distinctions for health-related research. Public Health Rep. 1985;100(2):126–31.

    CAS  PubMed  PubMed Central  Google Scholar 

  17. Borg GA. Psychophysical bases of perceived exertion. Med Sci Sports Exerc. 1982;14:377–81.

    CAS  PubMed  Google Scholar 

  18. Stamatakis E, Huang BH, Maher C, Thøgersen-Ntoumani C, Stathi A, Dempsey PC, et al. Untapping the health enhancing potential of vigorous intermittent lifestyle physical activity (VILPA): rationale, scoping review, and a 4-pillar research framework. Sports Med. 2021;51(1):1–10.

    PubMed  Google Scholar 

  19. Castro O, Bennie J, Vergeer I, Bosselut G, Biddle SJH. How sedentary are University students? A systematic review and Meta-analysis. Prev Sci. 2020;21(3):332–43.

    PubMed  Google Scholar 

  20. Prince SA, Elliott CG, Scott K, Visintini S, Reed JL. Device-measured physical activity, sedentary behaviour and cardiometabolic health and fitness across occupational groups: a systematic review and meta-analysis. Int J Behav Nutr Phys Act. 2019;16(1):30.

    PubMed  PubMed Central  Google Scholar 

  21. Wallmann-Sperlich B, Chau JY, Froboese I. Self-reported actual and desired proportion of sitting, standing, walking and physically demanding tasks of office employees in the workplace setting: do they fit together? BMC Res Notes. 2017;10(1):504.

    PubMed  PubMed Central  Google Scholar 

  22. Strath SJ, Kaminsky LA, Ainsworth BE, Ekelund U, Freedson PS, Gary RA, et al. Guide to the assessment of physical activity: clinical and research applications: a scientific statement from the American Heart Association. Circulation. 2013;128(20):2259–79.

    PubMed  Google Scholar 

  23. Ding D, Ramirez Varela A, Bauman AE, Ekelund U, Lee IM, Heath G, et al. Towards better evidence-informed global action: lessons learnt from the lancet series and recent developments in physical activity and public health. Br J Sports Med. 2020;54(8):462–8.

    PubMed  Google Scholar 

  24. Sallis JF, Saelens BE. Assessment of physical activity by self-report: status, limitations, and future directions. Res Q Exerc Sport. 2000;71(2 Suppl):S1–14.

    CAS  PubMed  Google Scholar 

  25. Düking P, Giessing L, Frenkel MO, Koehler K, Holmberg HC, Sperlich B. Wrist-worn Wearables for monitoring heart rate and energy expenditure while sitting or performing light-to-vigorous physical activity: validation study. JMIR mHealth uHealth. 2020;8(5):e16716.

    PubMed  PubMed Central  Google Scholar 

  26. World Medical Association Declaration of Helsinki. Ethical principles for medical research involving human subjects. JAMA. 2013;310(20):2191–4.

    Google Scholar 

  27. Horton JF, Stergiou P, Fung TS, Katz L. Comparison of polar M600 optical heart rate and ECG heart rate during exercise. Med Sci Sports Exerc. 2017;49(12):2600–7.

    PubMed  Google Scholar 

  28. Bouchard C, Tremblay A, Leblanc C, Lortie G, Savard R, Theriault G. A method to assess energy expenditure in children and adults. Am J Clin Nutr. 1983;37(3):461–7.

    CAS  PubMed  Google Scholar 

  29. Tanaka H, Monahan KD, Seals DR. Age-predicted maximal heart rate revisited. J Am Coll Cardiol. 2001;37(1):153–6.

    CAS  PubMed  Google Scholar 

  30. Ainsworth BE, Haskell WL, Leon AS, Jacobs DR Jr, Montoye HJ, Sallis JF, et al. Compendium of physical activities: classification of energy costs of human physical activities. Med Sci Sports Exerc. 1993;25(1):71–80.

    CAS  PubMed  Google Scholar 

  31. Ainsworth BE, Haskell WL, Herrmann SD, Meckes N, Bassett DR Jr, Tudor-Locke C, et al. Compendium of physical activities: a second update of codes and MET values. Med Sci Sports Exerc. 2011;43(8):1575–81.

    PubMed  Google Scholar 

  32. Pescatello L, Arena R, Riebe D, Thompson P. ACSM’s guidelines for testing and prescription. Baltimore: Lippincott Williams and Wikins; 2014.

    Google Scholar 

  33. Physical Activity Guidelines Advisory Committee. Physical Activity Guidelines Advisory Committee Report, 2008. Washington, DC: Services USDoHaH; 2008.

    Google Scholar 

  34. Gebel K, Ding D, Chey T, Stamatakis E, Brown WJ, Bauman AE. Effect of moderate to vigorous physical activity on all-cause mortality in middle-aged and older Australians. JAMA. Intern Med. 2015;175:970–7.

    Google Scholar 

  35. Gebel K, Ding D, Bauman AE. Volume and intensity of physical activity in a large population-based cohort of middle-aged and older Australians: prospective relationships with weight gain, and physical function. Prev Med. 2014;60:131–3.

    PubMed  Google Scholar 

  36. Rey Lopez JP, Gebel K, Chia D, Stamatakis E. Associations of vigorous physical activity with all-cause, cardiovascular and cancer mortality among 64 913 adults. BMJ Open Sport Exerc Med. 2019;5(1):e000596.

    PubMed  PubMed Central  Google Scholar 

  37. Welk GJ, Kim Y. Context of physical activity in a representative sample of adults. Med Sci Sports Exerc. 2015;47(10):2102–10.

    PubMed  PubMed Central  Google Scholar 

  38. Hoare E, Stavreski B, Jennings GL, Kingwell BA. Exploring motivation and barriers to physical activity among active and inactive Australian adults. Sports. 2017;5(3):47.

    PubMed Central  Google Scholar 

  39. Poole DC, Jones AM. Measurement of the maximum oxygen uptake V̇o(2max): V̇o(2peak) is no longer acceptable. J Appl Physiol (1985). 2017;122(4):997–1002.

    CAS  Google Scholar 

  40. Buehler R, Pucher J, Merom D, Bauman A. Active travel in Germany and the U.S. contributions of daily walking and cycling to physical activity. Am J Prev Med. 2011;41(3):241–50.

    PubMed  Google Scholar 

  41. Mueller N, Rojas-Rueda D, Cole-Hunter T, de Nazelle A, Dons E, Gerike R, et al. Health impact assessment of active transportation: a systematic review. Prev Med. 2015;76:103–14.

    PubMed  Google Scholar 

  42. Sallis JF, Frank LD, Saelens BE, Kraft MK. Active transportation and physical activity: opportunities for collaboration on transportation and public health research. Transp Res A Policy Pract. 2004;38(4):249–68.

    Google Scholar 

  43. Saunders LE, Green JM, Petticrew MP, Steinbach R, Roberts H. What are the health benefits of active travel? A systematic review of trials and cohort studies. PLoS One. 2013;8(8):e69912.

    CAS  PubMed  PubMed Central  Google Scholar 

  44. Foreyt JP. Need for lifestyle intervention: how to begin. Am J Cardiol. 2005;96(4a):11e–4e.

    PubMed  Google Scholar 

  45. Costain L, Croker H. Helping individuals to help themselves. Proc Nutr Soc. 2005;64(1):89–96.

    PubMed  Google Scholar 

  46. Smith JJ, Porth CM, Erickson M. Hemodynamic response to the upright posture. J Clin Pharmacol. 1994;34(5):375–86.

    CAS  PubMed  Google Scholar 

  47. Cryer PE, Haymond MW, Santiago JV, Shah SD. Norepinephrine and epinephrine release and adrenergic mediation of smoking-associated hemodynamic and metabolic events. N Engl J Med. 1976;295(11):573–7.

    CAS  PubMed  Google Scholar 

  48. Spaak J, Merlocco AC, Soleas GJ, Tomlinson G, Morris BL, Picton P, et al. Dose-related effects of red wine and alcohol on hemodynamics, sympathetic nerve activity, and arterial diameter. Am J Physiol Heart Circ Physiol. 2008;294(2):H605–12.

    CAS  PubMed  Google Scholar 

  49. Valentini M, Parati G. Variables influencing heart rate. Prog Cardiovasc Dis. 2009;52(1):11–9.

    PubMed  Google Scholar 

  50. Carter JR, Ray CA. Sympathetic neural responses to mental stress: responders, nonresponders and sex differences. Am J Physiol Heart Circ Physiol. 2009;296(3):H847–53.

    CAS  PubMed  PubMed Central  Google Scholar 

  51. Tremblay MS, Aubert S, Barnes JD, Saunders TJ, Carson V, Latimer-Cheung AE, et al. Sedentary behavior research network (SBRN) – terminology consensus project process and outcome. Int J Behav Nutr Phys Act. 2017;14(1):75.

    PubMed  PubMed Central  Google Scholar 

  52. Reichert M, Giurgiu M, Koch E, Wieland LM, Lautenbach S, Neubauer AB, et al. Ambulatory assessment for physical activity research: state of the science, best practices and future directions. Psychol Sport Exerc. 2020;50:101742.

    PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgments

We want to thank the participants for taking part in our study.

Funding

Open Access funding enabled and organized by Projekt DEAL. This study was funded mainly by own institutional resources. BWS received a supportive grant (Promotion of young female academics in the Faculty of Human Sciences of the University of Würzburg) to finance an assistant (MM) for data acquisition and management. This publication was supported by the Open Access Publication Fund of the University of Wuerzburg.

Author information

Authors and Affiliations

Authors

Contributions

BWS and PD designed the present study, PD and MM carried out the data acquisition, MM coded the physical activities according to the diaries, BWS & PD & MM performed statistical analyses, interpreted the data, BWS wrote and drafted the initial manuscript, PD & BS edited the manuscript and provided critical revision. IF participated in the conception and design of the study and provided critical revision of the manuscript. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Birgit Wallmann-Sperlich.

Ethics declarations

Ethics approval and consent to participate

We confirm that all study procedures were in accordance with the Declaration of Helsinki and have been approved by the Institute of Sport Science, University of Würzburg. All participates gave informed consent to participate in the study.

Competing interests

The authors declare that they have no competing interests.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Wallmann-Sperlich, B., Düking, P., Müller, M. et al. Type and intensity distribution of structured and incidental lifestyle physical activity of students and office workers: a retrospective content analysis. BMC Public Health 22, 634 (2022). https://doi.org/10.1186/s12889-022-12999-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12889-022-12999-z

Keywords