A Multi-Domain Physical Fitness Dataset of Central European Adults: Strength, Flexibility, Stability, and Aerobic Capacity

Abstract

Physical fitness is a multifaceted construct integral to physical performance, health, and quality of everyday life. Publicly available datasets offering comprehensive fitness assessments across individual or multiple fitness domains in adults from the general population are limited. This dataset presents comprehensive data on physical fitness encompassing anthropometric, body composition, strength, flexibility, postural stability, and aerobic capacity measures in a sample of central European adults (N = 128, aged 18–40). Data was collected using standardized protocols to ensure comparability with the existing body of research. This dataset aims to support cross-disciplinary research, benchmarking, or the development of evidence-based interventions. Potential applications include evaluating individual fitness and the effectiveness of fitness interventions, as well as exploring associations between physical fitness and broader health and behavioral outcomes. This dataset addresses gaps in existing resources by providing an extensive list of measures that cover various aspects of physical fitness, thereby contributing to replicable and generalizable research.

Background & Summary

Physical fitness reflects an individual’s ability to perform physical activities and is one of the key indicators of physical performance and health^1–4. Measures of physical fitness are used across various fields of research, including sports science, sports and exercise medicine, kinanthropology, and behavioral sciences; they can inform fitness assessments⁵ and guide exercise programs. They also serve as markers of broader health outcomes (such as cardiovascular and metabolic health)^6,7, or affect appearance and relatedly various aspects of social psychology, such as first impressions formation^8–10. Despite its wide-ranging importance, research in these domains is often constrained by a limited focus on simplified assessments^8,9,11,12 (namely, handgrip strength) or selected specific measures, such as isometric elbow strength^13,14, the chair-stand test¹⁵ or cardiovascular capacity^16,17; however, see^5,18,19 for examples of more complex examinations. While convenient, the resulting data fail to represent a more complete spectrum of individuals’ physical fitness. Physical fitness encompasses diverse attributes such as body composition, muscle strength, flexibility, postural stability, and cardiorespiratory capacity¹. Previously collected data are also limited in their sample scope, frequently describing specific populations, such as military conscripts⁵, performance athletes^20,21, seniors²², youth²³, or patients^2,24, whose characteristics may not generalize to the broader adult demographic²⁵. These limitations of previous evidence hinder the development of holistic models of physical fitness and the exploration of their relationship with other health or psychological outcomes, making generalization of their findings difficult²⁶.

Comprehensive, publicly available datasets encompassing a wider range of standard laboratory fitness assessments are essential for benchmarking both individual and group-level performance, comparing data across studies, and enabling secondary analyses^27,28. However, despite their importance, datasets capturing the breadth of physical fitness dimensions in the general population, particularly among adults, remain scarce.

This dataset addresses these gaps by presenting a wide array of basic physical performance domains captured using standard and frequently employed laboratory methods, providing a holistic assessment of physical fitness in a cohort of young (18–30) and early midlife (30–40) adults. Focusing on a relatively heterogeneous sample (including both sexes and varying fitness levels) from the general population of adults, this dataset offers descriptive values crucial for cross-study comparisons, development of evidence-based interventions, and support for research across disciplines, including sports science, public health, and psychology, being a valuable resource for researchers and practitioners. Including anthropometric data, body composition, strength, flexibility, postural stability, and aerobic capacity measures collected using rigorous, standardized protocols makes it comparable with other studies, enhancing the replicability and generalizability of research findings.

This dataset (although limited in size and age distribution but comparable to previous studies, e.g.¹⁹) has the potential to support a wide range of research and practical applications, including normative benchmarking, evaluating the impact of health and fitness interventions, and exploring associations between physical fitness, behavior, quality of life, and other outcomes.

Methods

The present dataset was created as part (i.e., Phase 1) of a research project focusing on attractiveness cues to physical fitness across perceptual modalities (visual, acoustic, olfactory). In addition to physical fitness assessments, the data collection includes completing questionnaires, audio-video recordings, and collecting body odor samples. This article focuses solely on measures related to physical fitness. The project and its data collection methods were pre-registered on the Open Science Framework (10.17605/OSF.IO/EFD2M).

Trained researchers and lab assistants at the Human Movement Laboratory of the Faculty of Physical Education and Sport, Charles University, performed all physical fitness performance, anthropometric, and body composition measurements. The data collection took place from April to November 2024.

Participants

We recruited 128 participants (63 men and 65 women), of whom ~80% were ≤ 30 years old (mean age = 25.4, SD = 5.83, range 18–40 yrs). The participants were primarily invited through advertisements on social media (e.g., Facebook and Instagram; see the ad in the supplementary materials at osf.io/efd2m) from the general public. They expressed their interest in participating by filling out an online form and subsequently were contacted with available terms and further details about the data collection. Participants were reimbursed for their participation with 600 CZK (~24 EUR; equivalent to 2 hours of the average hourly wage in the nation’s capital, Prague) and were provided with their physical fitness status results (see example in²⁹). The available reimbursement budget and the project’s time frame limited the sample size³⁰, following the stopping rules as per our pre-registration.

Procedure

Prior to the data collection, participants received an email with information about the data collection schedule and instructions on what to bring (comfortable sports shoes, drinks, snacks if needed, and a towel). They selected from available weekday time slots (from ~9 AM to 4 PM, in 30-minute intervals). Participants were instructed to arrive hydrated and satiated, but not to consume water, food, sports supplements, or stimulants for at least 2 hours prior. They were also advised to refrain from engaging in demanding exercise or performing physically demanding tasks the day before. To ensure consistency in body odor sample collection (not discussed in this article), participants were also instructed to avoid aromatic or pungent foods and refrain from using scented cosmetic products before participation.

All recruited participants were introduced to the study aims and signed the informed consent form upon arrival at the laboratory. They changed into the provided fitted sportswear, consisting of short-sleeve t-shirts and shorts; women were also provided with sports bras (all Decathlon). First, they started a body odor collection, followed by full-body video and voice recordings³¹. Participants then completed questionnaires (e.g., basic demographic data, fitness activities, partner status, self-perception; see the next chapter). Next, they underwent a standardized sequence of anthropometric, body composition, and physical fitness assessments (flexibility, postural and gait stability, isokinetic and explosive strength, and aerobic capacity). At the end, participants were debriefed about the scope of the overall project and provided their bank information to receive monetary compensation.

The overall time spent participating averaged ~2 hours. Due to the study’s logistics, participants’ attendance was spread throughout the data collection days, with some undergoing the procedure in the morning and some in late afternoons. This may lead to non-optimal results in some tests, increasing variability in the data. Exact times of undergoing (some) tests can be found in individual protocol outputs²⁹.

Basic demographics and self-perceived physical fitness questionnaire

In a purpose-built survey battery, participants filled out (in Czech, online via Google Forms) their basic demographic information (e.g., self-reported sex, age) followed by questions about their engagement in physical activities; they were asked to report about the type of physical activity, years of experience practicing a given activity, and the frequency of the activity (i.e., hours of activity/training per week) intended to evaluate our sample’s variability in their level of physical fitness (see Descriptive statistics of the sample below). Further questions concerned self-perceived physical fitness, partner status, self-esteem, body image, mate value, socio-sexuality, and body odor-related items.

The present dataset provides only data about basic demographics, physical activities, and self-reported physical fitness.

Physical fitness assessment

Anthropometric and body composition measurements

Body morphology measures, including body height, circumferences of the shoulders, xiphoid and mesosternal chest, waist, hips, thighs, calves, and upper arms (in cm), were acquired following standard protocols³⁰ using a digital stadiometer (Seca 264, Seca, Germany) and a tape measure (see Table 1).

Table 1.

Anthropometry and body composition descriptives.

		Sex	N	Mean	SD	IQR	Shapiro-Wilk (P-value)	Min - Max
Anthropometry	Body height (cm)	Women	65 (0%)	167.072	5.53	6.5	0.972 (0.142)	155.3–181.2
		Men	63 (0%)	181.813	6.371	8.85	0.981 (0.449)	167.5–201
	Shoulder circumference (cm)	Women	65 (0%)	100.237	8.649	7	0.74 (<0.001)	88.3–145.2
		Men	63 (0%)	114.076	5.949	8.5	0.988 (0.784)	101–129.5
	Chest circumference (mesosternal) (cm)	Women	65 (0%)	88.591	7.163	6.5	0.884 (<0.001)	78–116
		Men	63 (0%)	97.711	5.861	7.25	0.97 (0.126)	88–113.5
	Waist circumference (cm)	Women	65 (0%)	74.886	8.329	10	0.937 (0.003)	59–99
		Men	63 (0%)	84.294	10.184	9.75	0.715 (<0.001)	70.5–144
	Hips circumference (cm)	Women	65 (0%)	94.622	7.236	12	0.959 (0.03)	81.5–110
		Men	63 (0%)	98.959	5.207	8.25	0.984 (0.595)	87–111
Body composition	Body weight (kg)	Women	60 (7.7%)*	63.243	10.444	12.775	0.907 (<0.001)	48–97.7
		Men	59 (6.3%)**	78.444	8.293	8.2	0.933 (0.003)	62–109
	Fat (%)	Women	60 (7.7%)*	24.587	5.232	6.525	0.989 (0.848)	13.2–37.9
		Men	59 (6.3%)**	16.214	5.33	7	0.99 (0.894)	4.6–29.7

Note: *out of 65, **out of 63; numbers in brackets represent the percentage of missing data.

Body composition was estimated by a tetrapolar bioimpedance analyzer (Tanita MC-980, Tanita Corporation, Japan). Data about body weight (kg), total body water, as well as intra- and extra-cellular water volumes (l), body fat mass (kg, converted to %), muscle mass (kg, converted to %), and bone mass (kg) were recorded (see Table 1 for selected measures and dataset in²⁹ for full results). All participants were asked to empty their bladders before bioimpedance measurements.

Flexibility

We used two indirect measures of static flexibility, one for the upper body and one for the lower body, to represent participants’ flexibility status.

We used the Back Scratch Test (BST), a functional assessment of shoulder flexibility commonly used in adults^3,4 to assess upper body flexibility. We followed the procedure described in Heyward & Gibson¹. Participants stood and placed one hand (participants chose the hand they wanted to start with) over their thoracic spine (homolateral shoulder, with the palm facing their back, elbow pointing up, and fingers extended) and down the back. The second hand was to reach around from the lower back and up the middle of the back (with the palm facing out, elbow pointing down, and fingers extended). The goal was to try reaching with both hands’ fingers as far as possible to touch or superimpose. This procedure was repeated for the opposite side. The overlap reached (minus score) or gap (plus score) between the middle fingers of each hand (i.e., a lower score is a better performance) was measured in centimeters using a ruler. A zero was recorded if the fingers only touched each other.

The Standard Sit-and-Reach Test (SSRT) assessed lower-body flexibility. It is a valid and reliable measure for testing hip and hamstring flexibility in regular and active adult populations^18,32,33. During the SRT, participants sat on the floor with their legs parallel, knees fully extended, and feet placed flat against the edge of the measuring box (~15 cm apart). Then, they were asked to stretch their arms evenly, with palms facing down, and slowly reach forward as far as possible along the measuring scale on top of the measuring box, which had a centimeter scale (Sit and Reach Bench, Eveque, UK). They were to hold the maximally stretched position for 5 seconds while exhaling³² and keeping their knees fully extended. Using the built-in scale, the scores reached were recorded in centimeters (to the nearest 0.5 cm); the 15 cm mark represents the point at which participants’ fingertips are in line with their toes. Negative values were recorded when participants did not reach zero on the built-in scale using an additional ruler (Table 2).

Table 2.

Flexibility, stability, gait and aerobic capacity.

		Sex	N	Mean	SD	IQR	Shapiro-Wilk (P-value)	Min - Max
Flexibility	Sit and reach test (cm)*	Women	65 (0%)	22.112	12.913	14.5	0.941 (0.004)	−8–44
		Men	63 (0%)	16.527	11.387	16.25	0.978 (0.324)	−9–41
	BST left (cm)°	Women	65 (0%)	−3.485	6.476	6	0.938 (0.003)	−20.5–13
		Men	63 (0%)	−0.389	8.865	10	0.921 (<0.001)	−16–21
	BST right (cm)°	Women	65 (0%)	−2.554	11.997	8	0.757 (<0.001)	−23.5–41.5
		Men	63 (0%)	−1.04	9.171	10.5	0.892 (<0.001)	−20–22
Postural stability	TTW narrow stance open eyes°	Women	65 (0%)	74.015	32.27	37	0.896 (<0.001)	27–208
		Men	63 (0%)	87.921	36.62	47	0.965 (0.074)	25–192
	TTW narrow stance closed eyes°	Women	65 (0%)	110.338	64.05	73	0.892 (<0.001)	32–329
		Men	63 (0%)	141.127	82.46	98	0.857 (<0.001)	19–536
Gait symmetry	3 km gait symmetry (Loading Peak Force SI) (%) °	Women	48 (26.2%)*	0.021	1.263	2	0.869 (<0.001)	−5–2
		Men	53 (15.9%)**	0.283	1.199	1	0.912 (<0.001)	−3–3
	5 km gait symmetry (Loading Peak Force SI) (%)°	Women	48 (26.2%)*	−0.042	1.288	2	0.927 (0.005)	−3–4
		Men	52 (17.5%)**	0.038	1.96	2	0.958 (0.062)	−4–6
Aerobic capacity	VO2/kg (ml/min/ kg)	Women	63 (3.1%)*	43.537	12.148	10.45	0.916 (<0.001)	8–71.6
		Men	60 (4.8%)**	54.395	9.722	10.825	0.97 (0.151)	33.4–80.2

Note: °A lower score indicates better performance; * out of 65, ** out of 63; numbers in brackets represent the percentage of missing data.

Postural stability

Static postural stability was assessed following a standardized static posturography procedure using a narrow stance (feet side by side, with eyes open and closed) and a single-leg stance from the Romberg’s standing tests battery^34,35. The measurements were carried out using a pressure mat Footscan (58 × 42 × 1.2 cm; RSscan, Belgium).

For the narrow stance examination, participants stood on the mat barefoot, with both feet parallel and placed as close together as possible without their knees or thighs touching, and their arms hanging freely along their bodies. They were asked to focus their gaze on a visual spot (set at eye level) on a wall (located 1.7 m in front of them) to maintain an upright head posture. They were instructed to stand as still as possible for 30 seconds while measurements were taken. The same procedure was used for the closed-eye condition, with a 60-second rest between the open- and closed-eye tests.

For the single-leg stance examination, participants stood on the mat with both feet parallel and shoulder-width apart, their arms freely along their body, and their gaze fixed on the visual spot in front of them. Then, they were asked to lift one leg (participants chose the leg they wanted to start with, not the tested leg) above the surface and bend the knee to a flexion (thigh kept vertical). They were instructed to stand as still as possible for 30 seconds while measurements were taken. The procedure was repeated for the other leg with a 60-second rest between tests.

For all four tests, we measured the range of maximal displacement reached in the medio-lateral (ΔX) and anterior-posterior (ΔY) directions (all in mm) and the total trajectory of the center of pressure displacement (i.e., Total Traveled Way (TTW)). Additionally, the body weight distribution difference between limbs (in %) was measured in the narrow stance with open eyes as a measure of bipedal stance symmetry. Finally, the between-limb symmetry (in %) of the single-leg stance was calculated as the difference in the total trajectory of the center of pressure displacement of the right and left leg. All data available in the dataset; TTW values for open and closed eyes conditions are reported in Table 2.

Gait symmetry

Gait symmetry was analyzed using a single-belt 150 × 50 cm running area 3D ergometer, Gaitway 3D (HP COSMOS, Germany), which measured ground reaction force components during walking (h/p/cosmos Sports & Medical GmbH, Nussdorf, Germany; with an Arsalis 8-channel 10 kHz force amplifier, Université Catholique de Louvain, Belgium).

Two gait speeds were used to assess the presence of an asymmetry in regular and fast gait. Before the gait test, participants familiarized themselves with walking on the treadmill by walking at a 3 km/h pace for ~1 minute. The test started at 3 km/h and rose to 5 km/h. Data from a minimum of 10 complete gait cycles (after 60 seconds of steady-state pacing) for each speed were analyzed. Participants were informed about the upcoming pace change but were not instructed about the technique or walking style.

For the assessment of gait symmetry, the focus was on inverse dynamic ground reaction force parameters, specifically force impulse (in Newton-seconds). The between-limb symmetry index (SI, in %) commonly used for assessing ground reaction forces of walking symmetry^36,37 was utilized. All data from the h/p/cosmos sports & medical GmbH system were output (see protocols and dataset). The between-limb loading peak force symmetry index (SI, in %) is reported below in Table 2.

Muscle strength

Handgrip strength (in N)^11,12,38,39 was assessed using a calibrated hand dynamometer (Takei, TKK 5401, Takei Scientific Instruments, Tokyo, Japan). While seated in a straight back chair (with feet flat on the floor, shoulders adducted and neutrally rotated, both arms freely along the body, forearms in neutral position and wrists held between 0 and 30° extension and between 0 and 15° ulnar deviation), participants were asked to grip the dynamometer with maximal effort three times for each limb, with 10 seconds rest between attempts^40,41. Peak forces for all three trials of each hand were recorded; see in Table 3.

Table 3.

Muscle strength descriptives.

		Sex	N	Mean	SD	IQR	Shapiro-Wilk (P-value)	Min - Max
Isometric strength	Mean left handgrip strength (N)	Women	65 (0%)	26.981	4.725	6.3	0.991 (0.924)	15.97–40.07
		Men	63 (0%)	43.075	6.622	9.065	0.986 (0.693)	28.67–56.83
	Mean right handgrip strength (N)	Women	65 (0%)	27.258	4.598	6.34	0.986 (0.702)	15.8–41.87
		Men	63 (0%)	43.445	6.233	8.48	0.988 (0.785)	30.1–57.53
Isokinetic strength	Right knee extensors mean peak torque (Nm)	Women	65 (0%)	116.881	35.356	24.75	0.88 (<0.001)	0–235.25
		Men	62 (1.6%)**	190.585	34.79	41.375	0.981 (0.444)	79–284.25
	Left knee extensors mean peak torque (Nm)	Women	65 (0%)	101.577	35.037	25.5	0.884 (<0.001)	5–228.25
		Men	63 (0%)	165.725	35.354	36.75	0.931 (0.002)	33–258.75
	Right knee flexors mean peak torque (Nm)	Women	65 (0%)	54.473	18.518	14.75	0.917 (<0.001)	4–107.25
		Men	63 (0%)	90.727	21.665	23.625	0.943 (0.006)	10.75–137.5
	Left knee flexors mean peak torque (Nm)	Women	65 (0%)	55.336	19.692	16.75	0.905 (<0.001)	4.25–120.75
		Men	63 (0%)	91.896	21.631	21.125	0.956 (0.024)	14.5–153.25
	Right elbow extensors mean peak torque (Nm)	Women	63 (3.1%)*	29.09	7.035	8.665	0.885 (<0.001)	16.33–59
		Men	62 (1.6%)**	41.758	8.227	8.08	0.977 (0.306)	22.67–62.33
	Left elbow extensors mean peak torque (Nm)	Women	63 (3.1%)*	22.101	7.632	9	0.885 (<0.001)	6–49.67
		Men	62 (1.6%)**	39.376	9.26	11.41	0.986 (0.718)	15.67–60
	Right elbow flexors mean peak torque (Nm)	Women	63 (3.1%)*	30.661	9.519	10.335	0.892 (<0.001)	8.33–70
		Men	62 (1.6%)**	56.823	10.46	11.833	0.975 (0.225)	32–78.33
	Left elbow flexors mean peak torque (Nm)	Women	63 (3.1%)*	29.645	9.096	9.83	0.872 (<0.001)	14.67–64
		Men	62 (1.6%)**	56.691	12.164	12.998	0.98 (0.397)	19.33–84.33
Explosive strength	Mean CMJFA (cm)	Women	47 (27.7%)*	26.148	5.033	6.18	0.984 (0.751)	14.87–39.53
		Men	44 (30.2%)**	37.735	8.645	12.52	0.978 (0.537)	21.93–58.23
	Mean CMJ (cm)	Women	47 (27.7%)*	23.923	5.104	6.885	0.959 (0.097)	13–36.2
		Men	44 (30.2%)**	33.944	7.272	10.392	0.979 (0.611)	20.43–52.3
	Mean CMPJ (cm)	Women	47 (27.7%)*	12.623	11.495	14.285	0.841 (<0.001)	0–46.03
		Men	44 (30.2%)**	10.428	6.633	6.817	0.76 (<0.001)	2.37–41.53

Note: CMJFA – Counter Movement Jump Free Arms; CMJ - Counter Movement Jump; CMPJ - Counter Movement Push Jump; * out of 65, ** out of 63; numbers in brackets represent the percentage of missing data.

Isokinetic strength tests for flexors and extensors of knees and elbows (lower and upper limbs) were assessed by an isokinetic dynamometer (Cybex NORM®, Humac, CA, USA) set with a predefined angular velocity. The peak torque (Nm)^42,43 generated during each repetition was calculated and recorded using the Humac Norm software. Specifically, the peak flexion and extension torques of the knee and elbow joints were measured to evaluate lower and upper limb strength. Further symmetry of the produced torque across the upper and lower limbs was examined.

Before the Isokinetic testing, participants performed a standardized warm-up routine consisting of 2 sets of 6 squats, 2 sets of 6 lunges, 2 sets of 6 glute bridges, 2 sets of 6 triceps and biceps extensions, and 2 sets of 6 flexions using a resistance band, and 2 sets of 6 supported push-ups with arms placed on the ladder at chest height. There was a 2-minute break between the lower and upper limb trials; each participant started their trials with the same arm or leg that the previous participant had ended with.

Isokinetic strength of the lower limbs: According to the Cybex manual, participants were seated on an ergonomic dynamometer seat, and the trunk and thigh of the tested leg were secured with belts attached to the dynamometer seat. The contralateral leg was braced against a stabilizing handle, and participants were to hold onto the brace handles to prevent movement. The dynamometer’s measuring arm rotational axis was adjusted to align with the rotational axis of the knee joint, and the motion range was set to 90° of knee flexion. Before testing, participants completed five progressive familiarization trials of knee flexion and extension at submaximal intensity.

The testing protocol consisted of three trials of knee flexion and three trials of knee extension to measure maximal voluntary concentric contractions of the hamstrings (knee flexion) and quadriceps (knee extension) at an angular velocity of 60°/sec, with a 10-second rest period between trials^1,44. The range of motion was set from 10° to 90° knee flexion⁴⁵.

Isokinetic strength of the upper limbs: According to the Cybex manual, participants were positioned supine on an ergonomic dynamometer seat in a flat position, with their knees flexed and feet resting on the seat’s footrest. The rotational axis of the dynamometer’s measuring arm was adjusted to align with the rotational axis of the elbow joint. Participants were instructed to position their arm at 45° abduction, with their elbow resting on the seat while gripping the handle in a supinated wrist position. Participants were asked to rest their other hand on their chest.

The testing protocol included three warm-up and familiarization trials followed by three trials of both arms’ elbow flexion and extension movements to measure maximal voluntary concentric contractions of the triceps (elbow extension) and biceps (elbow flexion) at angular velocities of 60°/sec and 180°/sec (data from 60°/sec reported below, 180°/sec are available in dataset²⁹). A rest period of 10 seconds was allowed between each trial and 10 seconds between different angular velocities. The range of motion was set from 10° to 120° of elbow flexion^13,14. All Humac Norm data on generated torque were output into short and long protocol formats (see protocols and dataset); peak torque is reported in Table 3).

Explosive strength

Explosive strength tests for the lower and upper body were performed on two force plates (Kistler Instrumente, Winterthur, Switzerland) with a sampling frequency of 1000 Hz, measuring maximal vertical ground reaction force calculated as body mass-relative generated force (N/kg)⁴⁶. Data about maximal (peak) force, propulsion phase force impulse, and traveled height were recorded; height is reported in Table 3.

Before testing, participants received detailed instructions on how to execute each test properly. Subsequently, they underwent one familiarization submaximal trial, and corrections were provided on proper execution. Then, each type of explosive strength test was repeated three times, with 30 seconds of rest between each attempt and ~1 minute of rest between tests.

The Countermovement Jump (CMJ) and Countermovement Jump with free arms (CMFA) assessed the explosive strength of the lower body. The CMJ and CMFA are standard tests used to assess the explosive strength (power) of the lower limbs. These tests have a high level of reliability and validity and are closely and positively correlated with other tests of lower limb explosive strength^47,48.

Participants performed both jumps on floor-mounted force plate platforms while wearing provided sports shoes. In the CMJ, participants started from a standing position, squatted down to a self-determined depth, and jumped as high as possible with both hands placed on their hips. In the CMFA test, participants performed the same jump from the same position but assisted by a swing of their arms.

Subsequently, participants performed the Countermovement Push Jump (CPJ) to assess their upper body’s explosive strength. The CPJ is a valid and reliable test⁴⁹ for evaluating upper-body maximal explosive strength (power).

As the standard push-up position (with only hands and toes on the ground) may be too demanding for women, we used two variations of the CPJ test according to participants’ sex⁵. Male participants assumed the standard push-up starting position, with their arms fully extended, palms shoulder-width apart, and feet positioned on the same horizontal plane as their hands. Female participants assumed a modified position, with both knees and feet on the ground, with the alignment of the trunk and thighs approximating a straight line (resulting in an angle close to 180°). After establishing a stable baseline force, the administrator initiated the trial with a verbal cue. Subsequently, participants executed a push-up with rapid eccentric countermovement, i.e., lowering their chest until it approached proximity with the force plates with a 90° angle at the elbows, immediately transitioning into the explosive concentric phase of the push-up movement to generate maximal force in efforts to “push” as high as possible^50,51.

Maximal functional aerobic capacity

We measured the peak VO₂Max (volume of maximum oxygen uptake) through a graded running protocol to estimate the cardiovascular system’s functional capacity (cardiorespiratory endurance)¹⁶.

Participants were informed about the course of the upcoming test, and their medical history (e.g., cardiovascular diseases as an exclusion criterion) was checked. Next, participants wore a breathing face mask covering the mouth and nose (Hans Rudolph, Kansas City, USA) and a chest sensor to measure heart rate (Polar heart rate sensor H10, Polar, Finland).

We used the CORTEX Metalyzer 3B gas analyzer (Cortex Gmbh, Germany) and a treadmill (Quasar, H/P/Cosmos, Germany). Maximal aerobic capacity during running on a treadmill was assessed using a graded protocol. The test started at 4 minutes at a submaximal speed of 8 km/h with a 0% belt incline. Next, a graded step protocol (+1.5% belt incline per minute) commenced until voluntary exhaustion. All participants met the following primary peak oxygen uptake (VO₂ peak) criteria: a plateau in oxygen uptake with a respiratory exchange ratio greater than 1.1 and a heart rate (fH) higher than 90% of age-predicted maximum⁵². All data from were recorded via the MetaSoft Studio system (protocols and dataset); VO₂Max is reported in Table 2.

Ethics declarations

The Ethical Committee of the Faculty of Physical Education and Sports, Charles University, approved this work (#141/2023).

Data Records

The dataset²⁹ includes both raw and processed measurements for each participant, along with metadata that details age, sex, and physical fitness. The dataset (and a consolidated data dictionary file) is publicly accessible and can be found at the OSF repository (10.17605/OSF.IO/EFD2M).

During data collection, measures of body dimensions, flexibility, and hand grip strength were manually transcribed into an MS365 Excel spreadsheet table. Data from postural stability and explosive strength measures were output into tables from the device. Results of the body composition, gait symmetry, and isokinetic performance were output into PDF protocols and subsequently machine-processed into tables via MS365 Power Automate.

Due to technical issues and errors by research assistants, some measures for participants across the dataset are missing; see the notes on sample size in Tables 1–3.

Data Overview

We calculated test-retest reliability (ICC) for all measures where repeated trials were recorded (handgrip strength, isokinetic performance, explosive strength). The ICC_(3,1) showed high consistency in performance (>0.8) across all cases. The mean values of the three attempts for these measures are reported below.

Of the 128 participants, 25 (19.5%) and 16 (12.5%) reported practicing running. Twelve (9.3%) participants did not report the type of physical activity they practiced. On average, participants (N = 115) reported spending 4.8 (SD = 3.1) hours per week exercising, with a mode of 2 hours. They also reported having a mean experience of exercising of 7.85 years (SD = 5.8), with a mode of 3 years. The time spent and experience with exercising were both positively skewed (>0.98).

The collected physical fitness values for body composition, flexibility, postural stability, muscle strength, and aerobic capacity were in comparable ranges to previous normative data^18,53–57. For example, handgrip strength measures and aerobic capacity were comparable to those reported in⁵⁵ or⁵⁷. Tables 1–3 provide descriptive statistics of selected measures (Tables S1, S2 in supplementary tables xlsx files provide extended details and percentile distributions).

A noteworthy constraint of the present dataset is the representativeness of the reference data. The sample was recruited from cohorts of young (18–30) and early midlife (30–40) urban adults, thus providing no information on the selected fitness measures for the youth or the senior part of the population. Although previously collected datasets do include data on seniors²² or youth²³, they often limit their scope solely to those cohorts and differ in measures and scope. Thus, future efforts should focus on creating detailed age-stratified reference datasets.

Technical Validation

Standardization

Protocols followed established and valid protocols or guidelines e.g.¹, ensuring methodological rigor.

Reliability

Test-retest reliability was assessed via ICC analysis for all participants across all repeated strength measures (hand-grip strength, isokinetic, and explosive strength).

Usage Notes

This dataset supports research in establishing benchmarks for fitness assessments, evaluating interventions targeting specific fitness domains, and investigating associations between selected aspects of physical fitness.

This dataset is intended for non-commercial, scientific research purposes only. Users of this dataset are not allowed to attempt to identify the individuals included in the dataset. The authors of the dataset are not responsible for any damage arising from its use. The volunteer participants who shared their anonymized data were informed about the publication of the dataset and provided their consent by signing an informed consent form.

Conclusion

This dataset offers a comprehensive overview of physical fitness measures in young Central European adults, effectively addressing the need for publicly available, norm-referenced comparative data. Its extensive coverage—including anthropometric, strength, flexibility, postural stability, and aerobic capacity metrics—and the rigor of its standardized protocols make it an invaluable resource for researchers and practitioners alike. By facilitating cross-disciplinary studies, this dataset enables in-depth benchmarking of fitness levels, the evaluation of intervention efficacy, and the exploration of associations between physical fitness and broader health and behavioral outcomes. Moreover, its application spans multiple fields, from sports science and clinical practice to public health and behavioral research, thereby setting a new standard for future data collection initiatives.

Author contributions

Conceptualization: Vít Třebický, Jitka Třebická Fialová, Jitka Holubová, František Zahálka, Jan Havlíček. Funding Acquisition: Vít Třebický, Jitka Třebická Fialová, Jan Havlíček. Investigation: Vít Třebický, Jitka Třebická Fialová, Jitka Holubová, David Stella, Natálie Folbergerová, Agáta Kolingerová, Vojtěch Nesvadba, František Zahálka. Methodology: Vít Třebický, Jitka Třebická Fialová, Vojtěch Nesvadba, Jitka Holubová, František Zahálka, David Stella. Project Administration: Vít Třebický, Jitka Třebická Fialová. Resources: Vít Třebický. Supervision: Vít Třebický, František Zahálka, Jan Havlíček. Validation: Vít Třebický, Jitka Holubová, František Zahálka. Visualization: Vít Třebický. Writing – Original Draft Preparation: Vít Třebický. Writing – Review & Editing: Vít Třebický, Jitka Třebická Fialová, Jitka Holubová, David Stella, Natálie Folbergerová, Vojtěch Nesvadba, Agáta Kolingerová, František Zahálka, Jan Havlíček.

Data availability

The dataset²⁹ is available at the OSF repository at 10.17605/OSF.IO/EFD2M and includes individual output protocols (body composition, 3D gait analysis, and isokinetic analysis in both short and extended versions), as well as sample participant results, informed consent forms, debriefing documents, and flyer examples.

Competing interests

The authors declare no potential conflicts of interest concerning this article’s authorship and publication. The results of the present study do not constitute an endorsement of any product, company, or manufacturer that might benefit from the results of the present study.

Supplementary information

The online version contains supplementary material available at 10.1038/s41597-026-07094-6.