Sagittal Posture Measurement in Adolescent Athletes: Which Parameters Are Reliable over the Course of a Day?

Abstract

Analyzing the posture of athletes is an important preventive diagnostic tool, especially because some posture parameters appear to be associated with risk of muscle injury and complaints. So far, it is unclear how these parameters change during the day under sport-related stress. In this pilot study, the posture parameters of pelvic tilt, body lean, trunk lean, and pelvic displacement were analyzed in 20 soccer players (16.61 ± 0.28 years, 179.38 ± 6.40 cm, 70.35 ± 7.79 kg, playing in the German Youth Academy League) at three points in time on one day, in each case with habitual posture and active posture with eyes open and closed. Intensive sporting activities took place between the measurement points. A repeated two-factor ANOVA was calculated for each posture parameter with the factors of measurement time and posture. Cohen’s d was determined as a measure of the effect size, and the intra-class correlation coefficient was calculated for the three measurement times. Only pelvic tilt and body lean remained stable throughout the day. We therefore recommend using both parameters to assess the posture of athletes, especially because studies show that they can be associated with possible complaints and injuries. However, since the examined posture parameters change significantly depending on whether a habitual or actively tense posture is adopted, particular attention must be paid to reproducible postures and clear instructions to the test subjects.

1. Introduction

Knowledge of the biomechanical properties of athletes’ bodies is becoming increasingly important in both amateur and professional sports. This includes, for example, the analysis of leg axes, the position of the pelvis, and the extent of spinal curvature. The relationships between such somatic characteristics and both posture and muscle properties have been investigated by Barczyk-Pawelek [1]. Conversely, the relationships between muscular performance and posture in athletes have been increasingly well researched. For example, lower isokinetic trunk muscle strength in people with poor posture could be found [2]. Grabara [3] showed that posture also changes in a sport-specific way. He found that the spinal alignment of soccer players showed a more flattened lumbar lordosis compared to their untrained peers. These changes may be adaptation phenomena of the organism due to sport-specific neuromuscular requirements.

These findings provide approaches to specifically improve posture in athletes in a targeted manner. Yoo [4], for example, examined how targeted muscular training could improve pelvic tilt. Similar results were also found by Ludwig et al. [5] and Klee [6]. Preece et al. [7] found that hip muscle stretching may lead to immediate reductions in pelvic tilt, as did López-Minarro et al. [8], who were able to show that hamstring stretching could improve the pelvic position and sagittal spinal curvatures in a standing position.

Since it is known that individual posture-related factors can influence athletic performance, posture analyses appear to be particularly important in an athletic context. For example, stabilization of the lumbar region and the thoracolumbar transition is especially important when back squatting and can be adversely affected by an altered lumbar lordosis and thoracic kyphosis [9]. An increased pelvic tilt can in turn have a negative effect when sprinting, because anteversion of the pelvis creates tension on the tendon of the long biceps head, which reduces the range of hip flexion. This can affect athletic performance, for example when sprinting [10]. Likewise, an increased pelvic tilt can increase the risk of hip complaints in soccer players, especially in the context of an existing hip impingement [11,12].

In this context, the examination of posture has established itself in recent years as a helpful method in the field of sports and leisure [13,14,15,16]. Sagittal posture analysis provides information about the alignment of the body segments with respect to each other (local parameters such as the pelvic tilt), as well as the positioning of the body in relation to the base of support (global parameters such as the body lean) [17,18,19].

In this line, recent studies have shown that the position of the pelvis in the sagittal plane can influence the incidence of muscle injuries in sports. Bayrak and Patlar [20], for example, examined the relationship between pelvic tilt and hamstring injuries in a prospective study of 76 professional soccer players in the Premier Division over a period of five years. They were able to show that an increase in pelvic tilt from a cut-off angle of 13° is associated with a higher incidence of hamstring injuries. They emphasized that poor posture can lead to musculoskeletal pathologies, with pelvic position playing a crucial role in many postural problems [20]. An increased risk of hamstring injury due to a fatigue-related increase in pelvic tilt was also observed by Romero et al. [21]. Mendiguchia et al. provided the theoretical basis for this phenomenon. They were able to show that an increase in pelvic tilt led to a significant increase in tissue strain in all regions of the three ischiocrural muscles (semitendinosus, semimembranosus, and long head of biceps femoris). This was greater in the proximal region, which is most susceptible to injury—with more than 1 cm of tissue strain per 5° of pelvic tilt—when compared to the distal region [22].

Therefore, preventive posture analyses are now part of many performance sports examinations [23]. In this context, photogrammetry has been established as a proven method, with the test quality parameters of objectivity, validity, and reliability having been proven for photogrammetric measurements [24,25,26,27,28,29]. At the same time, the equipment required is manageable and can therefore also be used in a training environment.

Posture—in particular, the sagittal position of the pelvis—depends on muscular balance. The abdominal and gluteal muscles, as well as the hamstrings, have the potential to lift the anterior pelvic hand (retroversion). If they are too weak or the antagonistic muscle groups (iliopsoas muscle, quadriceps femoris muscle) are shortened or hypertonic, the pelvis tilts forward; the so-called anteversion [30]. As a result, lumbar lordosis can increase, leading to hollow back symptoms [31,32,33]. Hyperlordosis of the lumbar spine, in turn, is suspected of contributing to lower back pain [34]. Weakness of muscles relevant to posture, which may be due to training or fatigue, can consequently affect posture [35,36].

Therefore, posture analysis can help to identify potential risk factors at an early stage [37]. However, it is still unclear whether and how the pelvic tilt and other posture parameters change during a typical athlete’s day with different sporting activities. While the short-term repeatability of a posture measurement has been demonstrated [38], long-term studies sometimes show poor reproducibility [39]. Assuming that prolonged muscular fatigue occurs after intensive exertion, a change in posture during the course of the day would be expected. This would not only have possible consequences in terms of risk of injury but would also have implications for the point in time at which posture should be determined diagnostically.

Therefore, the aim of the present pilot study was to examine whether and to what extent global and local posture parameters in athletes remain constant over the course of a day after physical exertion and in different postural situations.

2. Materials and Methods

2.1. Subjects

To the best of the authors’ knowledge, no empirical studies are presented in the literature that indicate the effect sizes for the change in the parameters we examined, i.e., their variability over the course of the day. Therefore, no sample size could be calculated a priori for this pilot study, and, based on the suggestions of Julious and Patterson [40], a sample size of >12 was chosen for this pilot study. In this case, the entire available soccer team was included. A total of 21 adolescent soccer players aged 16 to 17 years from a youth academy initially participated in this study. They all played in the German Youth Academy League (the highest league in their age group and successor to the German Youth Bundesliga). The players had four training sessions a week of 90 min each, as well as a match in the league on the weekend.

One player had to be excluded due to injury (the anthropometric data of the 20 players analyzed are listed in Table 1). The examinations were carried out during the course of a day at an external training camp, such that the stress and recovery conditions were controlled and comparable for all the participants. The adolescents and their legal guardians had previously been informed about the procedure and purpose of the study and confirmed their participation with a written statement. This study was conducted in accordance with the guidelines of the Declaration of Helsinki and was approved by the university ethics committee under ref. no. 2023-57.

2.2. Examination Procedure

This is an observational pilot study in which posture analyses were performed at three different times of the day: in the morning, immediately after getting up and before breakfast, at noon after a strenuous athletic session (averaged reported rating of 6.7 on a 10-point Borg scale), and in the late afternoon after an intense soccer game (rating of 8.1 on a 10-point Borg scale). The posture measurement station was set up in a separate room. The analyses were carried out in underwear. In the morning, the following anatomical reference points were palpated by an experienced examiner and marked on the skin using a skin-friendly pen (Edding^® tattoo marker). This ensured that the actual marker points (colored adhesive dots with a diameter of 10 mm) and marker spheres (polystyrene spheres with a diameter of 15 mm) could be applied to the same points in a reproducible manner throughout the day. The skin markings remained visible even after multiple showers. All assessments were carried out by a single examiner with more than 25 years of experience in posture analysis. The accuracy of determining the pelvic tilt depends on the accuracy of the placement of the marker spheres on the skin. In an own earlier study [41], the retest reliability of the marker positioning was determined by the same examiner on twelve subjects at intervals of one day. Cronbach’s alpha was 0.998 and confirmed very good reliability. The mean deviation of the placement of the marker spheres was 1.4 ± 0.9 mm, which led to an error of <1.5° in the determination of the calculated pelvic tilt angle.

The posture photos were taken in front of a calibration wall using a digital camera (Logitech Webcam C920, Full HD, 1080p) on a tripod at a distance of 2 m. The positioning of the subjects was ensured to be reproducible through the use of a marking mat on the floor with printed foot silhouettes. A self-leveling laser plummet (Nikotek NK-01GT) was projected onto the subject to calibrate the camera.

During the measurements, the subjects were instructed to stand still and relaxed at first, looking straight ahead with their arms hanging loosely. For a second “activated” posture recording, the subjects were asked to straighten their posture (“to become more upright”) but to continue breathing normally. For the third posture recording, the subjects were asked to maintain the active posture but to close their eyes. The recording was then taken after 30 s. This methodology of measuring three postures has proven useful for checking the quality of postural control with and without the visual sense [42]. The photometric measurement of posture has been well studied in terms of test quality criteria and has established itself as a reliable method [23,26,27,28,29,43,44,45,46].

One soccer player had to drop out during the day due to injury; thus, the data from 20 subjects were evaluated. A total of 180 posture recordings were analyzed. The data of two subjects were partially inconsistent (marker points not visible) and were therefore not included in all calculations. Figure 1 shows the study procedure and dropouts according to the STROBE recommendations [47].

2.3. Posture Analysis

The following parameters were analyzed using the posture photographs and the Dartfish ProSuite software, version 6 (Dartfish Inc., Fribourg, Switzerland) (Figure 2). The classification differs in part from Dolphens et al. [18] because we consider all parameters that do not refer to a ground reference point to be local/segmental.

• Global alignment (global posture parameter):

  • (1). Body lean: angle between the line connecting the lateral malleolus and C7 and the vertical.

  • (2). Pelvic displacement: angle between the line connecting the lateral malleolus and the greater trochanter and the vertical.

• Local alignment (local/segmental posture parameters):

  • (3). Pelvic tilt: angle between the line connecting the anterior superior iliac spines and the horizontal.

  • (4). Trunk lean: angle between the line connecting the greater trochanter to C7 and the vertical.

Figure 2

Posture parameters and corresponding anatomical landmarks. ML—lateral malleolus, TM—greater trochanter, C7—7th cervical vertebra, ASIS—anterior superior iliac spine, PSIS—posterior superior iliac spine.

[Figure omitted. See PDF]

2.4. Statistics

For each parameter, a repeated two-way ANOVA (with Greenhouse–Geisser correction if sphericity was violated) was calculated using the two repeated factors of measurement time and posture. Post hoc t-tests were calculated after Bonferroni correction. Cohen’s d was determined as a measure of effect size, where values < 0.5 indicate a small effect, values between 0.5 and 0.8 indicate a medium effect, and values > 0.8 indicate a strong effect [48]. The fluctuation of the parameters over the course of the day were additionally determined for all three postures (habitual, activated, activated with eyes closed) using the intra-class correlation coefficient (ICC). In addition, the standard errors of measurements (SEM) and the minimal detectable changes (MDC) were calculated. All calculations were performed using the R software (version 4.4.3) [49].

3. Results

Figure 3 and Table 2 show the changes in the four posture parameters over the course of the day. It can be clearly seen that individual posture parameters such as body lean differ significantly between postures (habitual, active, eyes closed). Likewise, a change in individual parameters, for example trunk lean, can be seen over the course of the day. The pelvic tilt, on the other hand, does not appear to differ greatly between postures and between measurement times. The statistical results are presented in more detail below.

3.1. Pelvic Tilt

The repeated ANOVA showed no effects for the measurement time or the interaction of the factors for the pelvic tilt, whereas significant differences were found between all postures (Table 3). The statistical analysis of these differences is shown for all posture parameters in Table 4, with the results of the paired t-tests after Bonferroni correction.

For the three postures (i.e., habitual, activated, and activated with eyes closed), ICCs of 0.95, 0.97, and 0.95 were calculated for the three measurement points.

3.2. Body Lean

No significant effects were found for the measurement time or the interaction of the factors, whereas a significant difference between the different postures was observed (Table 2). For the three postures—habitual, active, and active with eyes closed—ICCs of 0.81, 0.74, and 0.79 were calculated, indicating good reliability in each case.

Significant differences between postures were found between the habitual and active postures and between the active posture and that with eyes closed (Table 4, Figure 3).

3.3. Trunk Lean

Significant effects were found for posture and measurement time, while the interaction showed no significant effect (Table 3). The post hoc t-tests showed significant differences between the habitual and both active postures (Table 4), with high effect sizes. For the three postures—habitual, activated, and activated with eyes closed—ICCs of 0.91, 0.88, and 0.90 were calculated.

In addition, t-tests were performed to analyze the differences between the measurement times. Significant differences were found between the first measurement (habitual posture) and the two subsequent measurements (Table 4).

3.4. Pelvic Displacement

Significant differences were found between the three measurement points, as well as between the postures (Table 3), with high effect sizes for the habitual posture compared to the activated posture and the activated posture compared to the closed-eyes posture (Table 4). For the three postures, respective ICCs of 0.91, 0.91, and 0.93 were calculated.

Further t-tests were conducted to analyze the differences between the measurement times. Significant differences were found between the first measurement (habitual posture) and the two subsequent measurements (Table 5). Table 6 shows the standard errors of the measurements (SEM) and the minimally detectable changes (MDC) for all parameters in all postures.

4. Discussion

Posture is determined not only by passive stabilizing structures (i.e., the skeleton and ligaments) but also by muscular activity [36]. Given that these can presumably change as a result of muscular fatigue due to previous exertion, this pilot study was designed to examine the stability of posture parameters over the course of the day.

The pelvic tilt proved to be particularly stable over the course of the day, with high ICC values of 0.95 and 0.97, indicating high reliability [50], and a lack of significance of the time factor in the repeated ANOVA, keeping in mind the minimum detectable changes of almost 4° (Table 6). The pelvic tilt is particularly relevant for an analysis of posture, as the pelvis—or, rather, the sacrum—is the anatomical base for the spine, and changes in pelvic position can therefore affect the posture of the trunk. An increase in pelvic tilt can also increase lumbar lordosis [30], increase the load on the intervertebral joints [51], and create a hollow back [32,52]. The fact that the pelvic tilt decreased during the transition from a passive habitual posture to an active posture is consistent with the change in posture parameters in our own earlier studies, as is the fact that posture deteriorated (in this case, the pelvic tilt increased again) when the eyes were closed due to reduced sensory information [42].

Stolinski et al. examined the reproducibility of some sagittal parameters such as pelvic tilt and pelvic displacement in children [44]. They also found good reproducibility both after one hour and after one week. However, only children (aged 7–10 years) in a relaxed state were examined. In the prevention of sports injuries, however, the state after muscular exertion is more important.

Pelvic tilt is also important in the context of injury prevention in sports. Recent studies have suggested that the alignment of the pelvis in the sagittal plane can influence the risk of muscle injuries in sports. As Bayrak and Patlar were able to demonstrate an increase in hamstring injuries with a pelvic tilt exceeding 13° [20], a possible increase in pelvic tilt in the habitual position during the course of the day is significant. Alizadeh and Mattes were able to show that anterior pelvic tilt in soccer players also changes the kinematics in the hip and knee joints, presumably increasing the risk of injury [10].

Even if the pelvic tilt statistically remains constant over our observed group during the course of the day, one must also consider individual results. Figure 3 and Table 2 show that the standard deviation of the pelvic tilt is significantly higher than that of the other parameters. As a local parameter, it is subject to large individual variability, which is partly anatomically based, while global parameters such as body lean must be regulated by the central nervous system within a narrower range, as otherwise equilibrium stability would be affected.

When analyzing posture parameters with a clinical focus, it is important to distinguish between real changes in posture and measurement errors. One way to distinguish between a real change and a random measurement error is to examine the minimum detectable change (MDC), as recommended by Furlan and Sterr [53]. The MDC value can be seen as the minimum change that must be observed to be considered a real change. In the context of the clinical observation that muscular exhaustion can increase the pelvic tilt, values > 3.9° must therefore be considered relevant. Figure 4 shows an example of an athlete in our study with a significant increase in pelvic tilt during the course of the day, likely due to previous muscular exertion.

In this individual case, the pelvic tilt increased by almost 6°. For a parameter that is quite constant over the course of the day but randomly fluctuates, this is an increase that must be considered clinically relevant, particularly because there seems to be an increased risk of injury to the hamstrings if the pelvis is tilted more than 13° [20]. Therefore, when several tiring efforts follow one another in the context of athletic competitions, worsening of the pelvic tilt must still be considered, which can increase the risk of injury.

Even though the reproducibility of the angle measurement was high, it makes sense to consider individual cases in which the posture parameters are measured multiple times in cases of prolonged exertion. The MDC values shown in Table 6 can be consulted to assess whether the observed changes in posture are clinically relevant.

Body lean also proved to be a time-stable parameter with good ICCs (0.74–0.81), presenting no significant influence of the time factor in the ANOVA. However, it changed significantly with activation of the posture. The angle increased, indicating a backward inclination of the body, which was previously somewhat forward-leaning. The body lean is interesting, as there appears to be a correlation with the occurrence of low back pain. Dolphens et al. distinguished several posture types in this regard. In their so-called “sway-back” type, in which the body and trunk are more inclined backward, their studies showed increased values for the body lean angle and trunk lean angle parameters. This posture type is more likely to be associated with the onset of lower back pain [54,55]. However, as the body lean in our study changed significantly with the activation of posture, care must be taken to ensure a reproducible posture, providing clear instructions to the test subjects when taking measurements.

Even parameters that remained stable over the course of the day, such as body lean, showed strong inter-individual fluctuations. Two outliers had values of −1.4° and +2.6°. The changes observed in these cases over the course of the day were within the MDC of 1.42° for habitual posture. This shows that these are indeed different posture types, as described in the literature; for example, by Dolphens et al. [55,56] for children and by Krawczky et al. [57] for adults. This may be of particular clinical interest, since certain posture types, such as the above-mentioned “sway back” cluster, showed a higher prevalence for the occurrence of lower back pain.

The forward displacement of the pelvis (antepulsion)—which is recorded in the parameter of pelvic displacement—did not differ between the active and passive posture, while it did change in relation to the posture with closed eyes. The backward inclination of the upper body (trunk lean), on the other hand, showed a significant increase with activation. As indicated by the significant factor of measurement time in the ANOVA, neither parameter was constant throughout the day (see Table 1); therefore, these seem to be very sensitive to changes in muscular activity.

As posture depends on the muscular interplay of the determining muscle groups, several factors can influence this balance. On the one hand, fatigue can reduce the maximum or resting forces, resulting in a shift in muscular balance. On the other hand, the precision of central nervous system activation influences the regulation of posture [58].

The influence of fatigue of the trunk musculature on balance regulation has been well-studied (see the review in [59]), but not the correlation with posture. As a result of neuromuscular fatigue, body segments may be repositioned. Pelvic tilt is mainly determined by the muscular balance of the hip flexors (iliopsoas muscle, rectus femoris muscle) and the hip extensors (rectus abdominis muscle, gluteus maximus muscle, hamstrings) [30]. If these become fatigued during sporting activity—notably, this is to be expected in soccer-specific training in the 6–8 load range on a 10-point Borg scale—an increase in pelvic tilt can be expected [35]. This was also observed in the habitual postures, but without significance. The mean differences found were within the range of the measurement inaccuracy of about 1–2°; thus, this parameter was proven to be stable, even under physical exertion.

The same applies to body lean, which depends on the joint position in the ankle (significantly influenced by the activity of the calf muscles; see [58]) and the hip joint (dependent on the trunk extensors and flexors). If the activity of the trunk flexors decreases due to fatigue, the upper body moves backward (parameter: trunk lean), which, in turn, can be compensated for by moving the pelvis forward (parameter: pelvic displacement). This corresponds to the “sway-back” posture proposed by Dolphens et al. [17,18].

The fact that these parameters describing the posture between two segments (pelvic displacement: ankle joint–hip joint and trunk lean: hip joint–head) are more variable over time can be explained by the fact that global parameters (body lean) are obviously more important control variables in this context. Their lower variability can be explained by the increased variability of subordinate segments, which, at the same time underlines the redundancy of the posture control system [60]. Smith et al. were able to link the combination of increased trunk lean and pelvic displacement to a higher probability of lower back pain [61].

The measurement of pelvic tilt and body lean in the field of sport science can be carried out very quickly using photometric methods, including the undressing of the subjects, the application of markers, the taking of photos, and the evaluation using a graphics software; the complete analysis takes less than 10 min. This makes this measurement interesting and practical for the daily monitoring of high-risk athletes.

Limitations

The conclusions of this study are limited to the examined target group; namely, adolescent male soccer players. Due to the sport-specific load, the pelvic and leg muscles were probably fatigued, which makes the results not directly transferable to other sports with different load profiles. The soccer players participating in this study usually trained four times a week in a youth academy, so they were quite accustomed to the kind of loads they faced on the day of the study. Even if the physical exertion during training was roughly the same, the individual strain—and, thus, muscular fatigue—may have differed. It is therefore not possible to directly deduce which muscle groups were individually responsible for a deterioration in individual posture parameters. Furthermore, the biomechanical properties differed between players and thus also the impacts of the redundant posture-influencing musculature.

The relatively small sample size is also a limiting factor. While posture measurements are always subject to a certain degree of inaccuracy [62] (also compare Table 6), we tried to avoid any possible measurement errors by marking measuring points on the skin, allowing for reproducible defined positioning of the test persons using a permanently installed measuring station.

5. Conclusions

On the basis of the results obtained, we recommend body lean as a time-stable global posture parameter and pelvic tilt as a time-stable local posture parameter for the assessment of posture in clinical and sports practice, as both parameters seem suitable for preventing possible health problems or injuries and can be measured reproducibly throughout the course of the day. However, since the examined posture parameters change significantly depending on whether a habitual or actively tense posture is adopted, particular attention must be paid to reproducible postures and clear instructions to the test subjects. In particular cases, differences may occur during the course of the day, which is why individual examinations for injury prevention make sense.

Future studies should follow up on our findings with a larger sample size to examine the variability of posture parameters over the course of a day and after physical exertion.

Author Contributions

Conceptualization, O.L. and E.B.; methodology, O.L. and J.D.; formal analysis, O.L., E.B. and J.D.; investigation, O.L. and E.B.; writing—original draft preparation, O.L., J.D. and M.F.; writing—review and editing, O.L. and J.D.; visualization, J.D. and O.L.; supervision, M.F. All authors have read and agreed to the published version of the manuscript.

Institutional Review Board Statement

This study was conducted in accordance with the Declaration of Helsinki and approved by the Institutional Review Board (reference number 2023-57) on 25 January 2023.

Informed Consent Statement

Informed consent was obtained from all subjects involved in this study. Written informed consent was obtained from the subject in Figure 4 to publish this paper.

Data Availability Statement

The raw data supporting the conclusions of this article will be made available by the authors on request.

Acknowledgments

We would like to thank the players of the U17 soccer team of SV 07 Elversberg for their patient support in this study.

Conflicts of Interest

The authors declare no conflicts of interest.

Footnotes

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Figures and Tables

Figure 1. Flow diagram of the study process and dropouts.

Figure 3. Box plots of the development of the four posture parameters at the three measurement times (green—habitual posture; orange—activated, eyes open; blue—activated, eyes closed); dots mark outliers.

Figure 4. (a–c) Change in pelvic tilt during the day in a subject’s habitual posture as a result of muscular exertion (note that in the third measurement, the cut-off value of 13° according to Bayrak and Patlar [20] is clearly exceeded).

Table 1

Anthropometric parameters of the 20 analyzed subjects.

Age	16.61 ± 0.28 years
Height	179.38 ± 6.40 cm
Weight	70.35 ± 7.79 kg
BMI	21.81 ± 1.63 kg/m2

BMI = Body Mass Index.

Table 2

Mean values, standard deviations (SD), and 95% confidence intervals (CI) for the posture parameters at the three measuring times (T1–T3), Hab—habitual, Act—active, Aec—active eyes closed. All values in degrees.

Parameter	Posture	T1	T2	T3
		Mean ± SD[95% CI]	Mean ± SD[95% CI]	Mean ± SD[95% CI]
Pelvic tilt	Hab	11.91 ±3.96[9.95; 13.88]	12.42 ± 3.57[10.65; 14.20]	12.60 ± 4.18[10.52; 14.67]
	Act	11.56 ± 3.52[9.80; 13.31]	12.09 ± 3.55[10.32; 13.85]	11.74 ± 3.92[10.32; 13.85]
	Aec	12.75 ± 3.54[10.99; 14.51]	13.22 ± 3.90[11.28; 15.16]	13.09 ± 4.12[11.04; 15.14]
Body lean	Hab	0.88 ± 0.95[0.41; 1.36]	0.62 ± 0.74[0.25; 0.99]	0.68 ± 0.68[0.34; 1.02]
	Act	1.46 ± 0.81[1.06; 1.86]	1.51 ± 0.84[1.09; 1.93]	1.32 ± 0.70[0.97; 1.67]
	Aec	0.63 ± 0.87[0.20; 1.06]	0.71 ±0.96[0.23; 1.19]	0.37 ± 0.87[−0.07; 0.80]
Pelvic displacement	Hab	4.14 ± 1.57[3.36; 4.93]	4.72 ±1.64[3.91; 5.54]	4.52 ± 1.62[3.72; 5.33]
	Act	3.74 ±2.87[2.81; 4.67]	4.07 ± 1.63[3.26; 4.88]	4.22 ±1.69[3.38; 5.06]
	Aec	4.23 ±1.55[3.46; 5.00]	4.78 ±1.40[4.07; 5.47]	4.91 ±1.64[4.10; 5.73]
Trunk lean	Hab	6.79 ±1.86[5.86; 7.71]	7.66 ± 1.69[6.82; 8.50]	7.56 ± 2.04[6.55; 8.57]
	Act	7.52 ±1.98[6.53; 8.50]	8.71 ± 1.93[7.75; 9.67]	8.16 ± 2.02[7.16; 9.17]
	Aec	6.50 ±2.07[5.47; 7.53]	7.83 ±1.97[6.85; 8.82]	7.14 ± 1.77[6.26; 8.03]

Table 3

Results of repeated ANOVA for the posture parameters.

Parameter	Effect	F	DF1	DF2	p
Pelvic tilt	time	1.05	2	34	0.363
	posture	15.89	2	34	<0.001 **
	interaction	0.59	4	68	0.669
Body lean	time	0.85	2	34	0.437
	posture	32.70	2	34	<0.001 **
	interaction	2.11	2.87	48.83	0.113
Pelvic displacement	time	3.28	2	34	0.05 *
	posture	17.05	1.19	20.29	<0.001 **
	interaction	1.54	4	68	0.20
Trunk lean	time	8.00	2	34	0.001 *
	posture	13.03	1.51	25.71	<0.001 **
	interaction	1.48	4	68	0.217

DF: degrees of freedom, * significant with p < 0.05, ** significant with p < 0.001.

Table 4

Post hoc tests: results of paired t-tests (degrees of freedom, DF = 53) for all posture parameters between postures after Bonferroni correction.

Parameter	Comparison	t	p	Cohen’s d	95% Confidence Interval
Pelvic tilt	Hab–Act	2.55	0.041 *	0.35	[0.11; 0.92]
	Hab–Aec	−3.89	<0.001 **	0.53	[−1.07; −0.34]
	Act–Aec	−8.16	<0.001 **	1.11	[−1.52; −0.92]
Body lean	Hab–Act	−9.56	<0.001 **	1.30	[−0.85; −0.56]
	Hab–Aec	1.62	0.111	0.22	[−0.04; 0.36]
	Act–Aec	10.4	<0.001 **	1.41	[0.70; 1.03]
Trunk lean	Hab–Act	−4.69	<0.001 **	0.64	[−1.13; −0.46]
	Hab–Aec	1.38	0.522	0.19	[−0.08; 0.43]
	Act–Aec	6.95	<0.001 **	0.95	[0.69; 1.25]
Pelvic displacement	Hab–Act	5.93	<0.001 **	0.81	[0.30; 0.61]
	Hab–Aec	−1.86	0.206	0.25	[−0.36; 0.014]
	Act–Aec	−6.27	<0.001 **	0.85	[−0.83; −0.43]

* significant with p < 0.05, ** significant with p < 0.001, Hab—habitual, Act—active, Aec—active with eyes closed.

Table 5

Results of paired t-tests (degrees of freedom DF = 53) for trunk lean and pelvic displacement between measurement times (T1—morning, T2—noon, T3—afternoon) after Bonferroni correction.

	Comparison	t	p	Cohen’s d	95% Confidence Interval
Trunk lean	T1 vs. T2	−5.85	<0.001 **	0.66	[−1.52; −0.74]
	T1 vs. T3	−3.89	<0.001 **	0.48	[−1.04; −0.33]
	T2 vs. T3	2.39	0.061	0.17	[0.07; 0.82]
Pelvic displacement	T1 vs. T2	−3.31	0.005 *	0.45	[−0.77; −0.19]
	T1 vs. T3	−3.71	0.001 *	0.51	[−0.79; −0.24]
	T2 vs. T3	−0.23	1.00	0.03	[−0.32; 0.26]

* significant with p < 0.05, ** significant with p < 0.001.

Table 6

Standard errors of the measurements (SEM) and minimally detectable changes (MDC) for all parameters in all postures; Hab—habitual, Act—active, Aec—active eyes closed. All values in degrees.

Parameter	Posture	SEM	MDC
Pelvic tilt	Hab	1.41	3.91
	Act	1.01	2.81
	Aec	1.42	3.93
Body lean	Hab	0.51	1.42
	Act	0.56	1.55
	Aec	0.60	1.66
Trunk lean	Hab	0.76	2.12
	Act	0.81	2.25
	Aec	0.67	1.86
Pelvic displacement	Hab	0.87	2.42
	Act	1.06	2.94
	Aec	0.98	2.70

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