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Changes in plantar pressure and spatiotemporal parameters during gait in older adults after two different training programs
Gait & Posture 77 (2020) 250–256
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Full length article
Changes in plantar pressure and spatiotemporal parameters during gait in older adults after two different training programs
T
Roberto Sanchis-Sanchisa, Cristina Blasco-Lafargab, Alberto Encarnación-Martíneza, Pedro Pérez-Sorianoa,* a b
Research Group in Sports Biomechanics (GIBD), Department of Physical Education and Sports, University of Valencia, Valencia, Spain Sport Performance and Physical Fitness Research Group (UIRFIDE), Department of Physical Education and Sports, University of Valencia, Valencia, Spain
ARTICLE INFO
ABSTRACT
Keywords: Elderly Exercise Walking Instrumented insole Foot
Background: Improving gait is in exercise programs for older adults (OAs) but little is known about how different gait-training approaches affect spatiotemporal parameters and plantar pressure distributions in OAs. High plantar pressures are linked to tissue injury risk, ulceration, and pain in OAs, but no studies have yet compared how they affect podobarometric variables. Research question: The effect of changing plantar pressure on absolute and mean maximum pressure, the pressure-time integral, stride time, stance time, and gait speed in OAs following either a multicomponent training program (EG) or interval-walking training (WG). Methods: Comfortable gait speed, strength (seat-to-stand test), and plantar pressure (Pedar-X mobile in-shoe system), were evaluated in 23 OAs (EG: n = 12, 7 female, 71.58 ± 4.56 years; WG: n = 11, 6 female, 69.64 ± 3.56 years), by dividing the plantar area into 9 regions. Results: After 14 weeks, the maximum pressure in medial and central metatarsus areas in the dominant leg were reduced in the EG (p = 0.01 & p = 0.04, respectively), but increased in the non-dominant leg lateral heel in the WG (p = 0.03). The mean maximum pressure also increased in the WG in medial heel in the dominant leg (p = 0.02) and lateral heel in the non-dominant leg (p = 0.03). The overall pressure-time integral reduced in the whole plantar area in both legs in both groups. WG reduced stride time (dominant: p = 0.01; non-dominant: p = 0.01) and stance time (dominant: p < 0.005; non-dominant: p < 0.005). Gait speed did not change in any group. As expected, lower limb strength improved after both exercise programs (EG: p = 0.02; WG: p = 0.01). Significance: Although these training interventions were short, they indicate the importance of exercise types. Our results suggest that OAs might benefit from periodized training, especially when multicomponent programs are introduced prior to the walking goals. Future, larger studies should explore situations in which special populations with specific foot problems might benefit from these interventions.
1. Introduction Foot problems such as pain, neuropathy, and deformities are very common in older adults (OAs) and are related to different risk factors such as age, obesity, or inappropriate footwear [1]. High plantar pressure values during gait are linked to a risk of tissue injury, ulceration, and pain in OAs [2] because their maximum pressures are higher compared to those of younger people [3]. Moreover, these kinds of problems are associated with a reduction in physical activity levels, deconditioning, balance deterioration, and falls [1]. It is well known that training improves physical-function in OAs. Indeed, specific programs based on balance and/or strength exercises [4], as well as
⁎
multicomponent training regimens [5] and/or walking-based programs [6] can effectively improve static/dynamic balance, agility, postural control, lower limb strength, and/or gait speed. There is a proven relationship between high plantar pressure and metatarsalgia [7], ulceration [2], and falls [8] in OAs and so reducing these values is a useful goal in this population. Plantar pressure distribution during gait has been widely studied in elderly populations by analysing different variables including barefoot versus shoe wearing [2], shoe sole hardness [9], or the use of accommodative insoles [7]. Moreover, several different studies have reported a reduction in plantar peak pressure distributions in this population after completing an exercise program [10]. Physical exercise seems to reduce both stride and
Corresponding author at: Department of Physical Education and Sports (University of Valencia), C/Gascó Oliag, nº 3, 46010, Valencia, Spain. E-mail address: [email protected] (P. Pérez-Soriano).
https://doi.org/10.1016/j.gaitpost.2020.01.015
0966-6362/ © 2020 Elsevier B.V. All rights reserved.
Gait & Posture 77 (2020) 250–256
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2.2. Study design
Table 1 Group demographic data.
Age (years) Gender (male/female) Weight (kg) Height (m) 6-m Gait Speed (m/s) 5rep-StS (s)
EG (n = 12)
WG (n = 11)
p
71.58 (4.56) 5/7 79.03 (16.84) 1.57 (0.087) 1.31 (0.19) 13.18 (2.74)
69.64 (3.56) 5/6 80.40 (7.62) 1.63 (0.087) 1.37 (0.22) 12.98 (2.29)
0.27a 0.86b 0.81a 0.12a 0.50a 0.85a
The participants were divided into two experimental groups: the multicomponent program EFAM-UV© [17] group (EG) comprising 12 individuals and the walking group (WG) comprising 11 participants. We used a homogeneous sample distribution method (Table 1) and considered the following criteria: age, sex, weight, height, 6-metre gait speed, and lower-limb strength using the Five-repetition sit-to-stand test [18]. Each group carried out one of the training programs for 14 weeks and both groups were evaluated before participating in the program (pre-training) and after its end (post-training). The EG trained twice a week for approximately 60 min each session, as previously described [17] (Fig. 1). The methodology supporting the EFAM-UV© was built upon a six-domain taxonomy designed to progressively retrain neuromotor function in the participants’ basic domains (Bs), including postural control, gait patterns, rhythm, and motor skills, as well as in the more complex complementary second-level physical literacy domains (Cs) requiring a dual-tasking approach to sustain improvements in manipulative and mental capabilities. We followed the EFAM-UV© interval training guidelines designed to increase bioenergetic, neuromuscular, and cognitive patient loads by retraining or relearning processes, individually tailoring these to each participant. The WG performed a walking-interval training program described elsewhere [6] with three sessions per week, each lasting an average of 41.54 ± 3.17 min. We controlled the training intensity in both groups using a heart rate monitor and a Spanish adaptation of the OMNI-Resistance Exercise Scale (OMNI-RES), a visual version of the perceived exertion scale (scored 1–10) with pictures used represent different training intensities [19].
Values are mean (SD). a p-value from independent t-test. b p-value from Mann-Whitney test; EG = EFAM (multicomponent) training group; WG = Walking training group; 5rep-StS = Five-repetition sit-to-stand test.
stance time in OAs [11]—both factors which are affected by ageing [12] and which are related to several diseases such as cognitive decline and dementia [13] or Parkinson’s disease [14]. Gait speed, which is related to life expectancy [15], can also be improved by exercise [16]. However, so far, no studies have compared the effects of different training programs on podobarometric variables in OAs. The aim of this present study was to analyse the effects of multicomponent versus interval walking on different plantar pressures and spatiotemporal parameters during gait in OAs. The hypotheses we proposed were that in OAs: (1) multicomponent training but not interval walking training will reduce the maximum pressure and mean maximum pressure values and (2) will reduce pressure-time integral values; (3) interval walking training but not multicomponent training will reduce stride and stance time; and (4), both training styles will increase gait speed.
2.3. Plantar pressure assessment procedure
2. Methods
To analyse plantar pressure, we used a Pedar-X mobile in-shoe system (Novel gmbh, Munich, Germany); these are 1.99 mm thick, flexible insoles containing 99 capacitance sensors homogeneously distributed over the insole area. A previous study has shown that this system is valid and reliable for measuring plantar pressure [20]. The insoles were calibrated according to the manufacturer’s instructions before each trial and plantar pressures were recorded at a frequency of 100 Hz. To control differences in each individual’s personal footwear, all the participants used standard trainers [21] (Reebok Classic NPC RAD) and were allowed to familiarise themselves with the new footwear by feely walking around the room for 5 min before recording commenced [22]. The Pedar-X insoles can be affected by foot heat and humidity [22] and so these sensors were also calibrated inside the shoes during this familiarisation phase. To collect the data, participants were instructed to walk at a ‘comfortable and safe’ speed along a straight 10-metre corridor, a total of 10 times; the accelerometery data was recorded during the 6 central meters, considering the first and last 2 m acceleration and deceleration
2.1. Participants This study included 23 OAs (10 men and 13 women, aged 70.65 ± 4.14 years; mean height = 160.09 ± 8.96 cm, mean weight = 79.68 ± 12.99 kg). The inclusion criteria were (1) age ≥65 years; (2) individuals with no walking difficulties who did not use any walking aids; (3) 6-metre gait speed ≥0.8 m/s; (4) individuals not receiving any physiotherapeutic rehabilitation or occupational therapy treatments; (5) no participation in any other physical exercise programs; and (6), a Mini-Mental Score Examination Test (MMSE) score ≥24 points, indicating the absence of any cognitive impairments. All our experiments complied with the ethical principles set out in the Declaration of Helsinki and were approved by the University of Valencia Ethics Committee (reference number: H1478084714217) before commencing. The patients we recruited gave their written informed consent before participating in the study.
Fig. 1. The neuromotor training methodology of EFAM-UV© program [17]. 251
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training data points, and our analysis considered 8 steps 4 right leg and 4 left leg in each trial 1640 pre-training and 1624 post-training steps which was sufficient to achieve a high reliability coefficient [23]. Plantar pressure data and stride parameters (stride time and stance time) were analysed with Pedar software according to manufacturer’s instructions. As described elsewhere [21], we divided the plantar area into 9 regions (Fig. 2) the medial heel (MH), lateral heel (LH), medial arch (MA), lateral arch (LA), medial metatarsus (MM; first metatarsus), central metatarsus (CM; second and third metatarsals), lateral metatarsus (LM; fourth and fifth metatarsals), hallux (HX), and the remaining toes (RT). The edges of each region were defined according to the congruent plantar anatomy, as described elsewhere [24]. The following pressure variables were extracted for each foot using Pedar software: maximum pressure (MP; highest pressure recorded for each region at any time during the data collection period), mean maximum pressure (MMP; average of all the peak pressures recorded for each region), and pressure-time integral (PTi; the product of the mean pressure and the time during which it was applied) [2]. Stride time (StrT; time elapsed from the heel contact of one foot to the next heel contact of the same foot), and stance time (StnT; time elapsed between the first to the last contact of a footfall, i.e. from the heel contact to the toe-off) were also extracted, considering each foot as a whole (i.e., not dividing it into 9 regions). 2.4. Lower-limb strength assessment Lower-limb strength was assessed using the Five-Repetition Sit-toStand Test [18]; from a sitting position and with the individual maintaining their arms crossed across their chest, the participants had to completely get up from a chair and sit down again 5 times in a row in the shortest time possible. We preformed the test twice per person and considered the fastest result for our analysis. 2.5. Leg dominance determination Leg dominance was determined through the question “If you were to kick a ball at a target, which leg would you use?” [25]. All the participants were right-handed. 2.6. Statistical analysis All the data were analysed with the SPSS software, version 25 (IBM Corp., Armonk, NY.). After checking the normality of the variables with a Kolmogorov–Smirnov test, we used paired t-tests to compare intraindividual differences for the parametric variables before and after training in each group (EG-pre vs. EG-post; WG-pre vs. WG-post) and employed Wilcoxon tests to analyse the nonparametric variables. The effect size (ES) was assessed using Cohen’s d as the parametric test and Rosenthal’s r for the nonparametric data. Significance was defined as p < 0.05 or as a moderate to high ES (d ≥ 0.5; r ≥ 0.3). 3. Results No differences were found in gait speed after training in the WG (1.32 ± 0.18 m/s vs. 1.44 ± 0.25 m/s, p = 0.23, d = 0.58) or EG (1.30 ± 0.21 m/s vs. 1.23 ± 0.28 m/s, p = 0.26, d = 0.31). However, there were statistically significant reductions in stride time (Fig. 3) in the WG after training, both in the dominant (1.048 ± 0.058 s vs. 0.992 ± 0.058 s, p = 0.01, d = 0.96) and non-dominant leg (1.048 ± 0.059 s vs. 0.992 ± 0.057 s, p = 0.01, d = 0.97). In contrast, no similar differences were found in the EG in the dominant (1.051 ± 0.088 s vs. 1.012 ± 0.095 s, p = 0.10, d = 0.43) or nondominant leg (1.051 ± 0.087 s vs. 1.010 ± 0.094 s, p = 0.10, d = 0.45). Fig. 3 shows pre- versus post-training differences in each group in terms of stance time, both in the dominant and non-dominant leg. After
Fig. 2. Area regions in plantar pressure analysis. MH = medial heel; LH = lateral heel; MA = medial arch; LA = lateral arch; MM = medial metatarsus; CM = central metatarsus; LM = lateral metatarsus; HX = hallux; RT = rest of toes.
zones, respectively [2]. The gait speed of each repetition was registered using a photocells system (Chronojump Boscosystem©) but was not controlled so as to avoid modifying the participants’ natural gait [2]. The average speed of all the series was then calculated for each participant, discarding any outliers exceeding 5 % of each individual’s average speed (to minimise any effect walking speed could have on plantar pressure) [2]. We obtained 205 pre-training and 203 post252
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Fig. 3. Pre vs post-training differences in (a) stride time and (b) stance time, in both legs (Mean and SD). EG: EFAM (multicomponent) training group; WG: Walking training group; * p < 0.05 and d > 0.5.
training, there was a significant decrease in stance time in the WG dominant (0.652 ± 0.042 s vs. 0.607 ± 0.041 s, p = 0.00, d = 1.07) and non-dominant leg (0.654 ± 0.044 s vs. 0.607 ± 0.047 s, p = 0.00, d = 1.03). However, no differences were found in the EG dominant (0.656 ± 0.071 s vs. 0.623 ± 0.076 s, p = 0.05, d = 0.46) or nondominant leg (0.660 ± 0.066 s vs. 0.625 ± 0.075 s, p = 0.07, d = 0.50). Pre- and post-training differences in the MP, MMP, and PTi plantar pressure variables in each group are shown in Table 2 for both legs and for the nine different plantar regions. After training, significant reductions in the MP were found in the dominant leg in the EG, both in the medial and central metatarsus, while an increase was found in lateral heel of the non-dominant leg in the WG. There was an increase both in the medial heel MMP of the dominant leg and lateral heel MMP of the non-dominant leg in the WG, and a reduction in the hallux MMP of the non-dominant leg. Interestingly, the stance time reduced in the WG for areas in which the MP and MMP increased (MH dominant leg: 0.459 ± 0.056 vs. 0.412 ± 0.074 s, p = 0.06, d = 0.73; LH non-dominant leg: 0.513 ± 0.102 vs. 0.444 ± 0.089 s, p = 0.01, d = 0.72). We found a PTi decrease in the lateral arch, medial metatarsus, central metatarsus, and lateral metatarsus of the dominant leg in the EG and in the medial and lateral heel, lateral arch, and central and lateral metatarsus of the EG non-dominant leg. Lastly, we noticed a reduction in PTi in the medial and lateral heel, lateral arch, and lateral metatarsus of the
dominant leg in the WG and reductions in the medial and lateral heel, medial and central metatarsus, and hallux in the non-dominant leg. Finally, lower-limb strength significantly improved in both groups (Fig. 4) after completion of the training programs (EG: 13.18 ± 2.74 s vs. 11.48 ± 2.34 s, p = 0.02, d = 0.67; WG: 12.98 ± 2.29 s vs. 11.20 ± 1.83 s, p = 0.01, d = 0.86). 4. Discussion This study aimed to analyse the effects on the maximum pressure, mean maximum pressure, pressure-time integral, stride time, stance time, and gait speed in OAs during gait after completing either a multicomponent (EFAM-UV©) training program [17] or an intervalwalking program [6]. In summary, after training, the MP values reduced in the medial and central metatarsal areas of the dominant leg in the EG but increased in the lateral heel of the non-dominant leg in the WG; MMP values also increased in medial heel of the dominant leg and lateral heel of the non-dominant leg in the WG. There was a general reduction in PTi values in both training groups, stride and stance time reduced both in the dominant and non-dominant leg in the WG, and there was an increase in lower-limb strength after training in both the EG and WG; no differences were found in gait speed for either group. Here we studied elevated pressures during gait because of their relationship with the risk of tissue injury, ulceration, and pain among elderly individuals [2]. Previous studies have shown that MP values are 253
254
44.26 44.19 34.98 49.30 52.25 53.71 44.44 40.25 37.98
PTi (kPa*s) MH LH MA LA MM CM LM HX RT
(58.86) (72.88) (30.33) (41.80) (54.85) (46.52) (38.01) (95.73) (82.14)
41.44 41.56 31.52 43.82 46.86 49.11 41.51 38.00 37.72
(8.32) (7.95) (9.73) (10.66) (13.55) (11.84) (10.85) (13.96) (11.14)
200.85 (48.60) 204.06 (61.17) 93.06 (28.17) 119.65 (32.02) 173.85 (40.82) 191.15 (44.13) 147.90 (35.34) 207.23 (85.18) 149.93 (74.96)
228.96 237.08 108.96 153.96 223.75 214.38 181.46 257.92 176.88
post
0.06 0.07 0.18 0.02 0.02 0.00 0.05 0.39 0.69
0.16 0.12 0.21 0.88 0.53 0.12 0.94 0.81 0.94
0.33 0.17 0.64 0.88 0.01 0.04 0.42 0.29 0.33
p
0.38 0.37 0.27 0.48 0.48 0.58 0.40 0.18 0.08
0.29 0.32 0.26 0.03 0.13 0.32 0.02 0.05 0.02
0.20 0.28 0.10 0.03 0.50 0.42 0.16 0.22 0.20
r (47.95) (53.24) (42.37) (48.36) (50.10) (60.28) (34.88) (77.54) (52.80)
53.17 52.50 35.58 48.36 49.62 53.60 40.13 40.38 34.29
(9.68) (10.64) (12.78) (14.96) (11.28) (12.88) (8.63) (14.99) (7.56)
216.40 (43.81) 205.84 (48.21) 96.77 (32.71) 118.96 (34.33) 180.14 (34.48) 209.24 (59.34) 142.25 (29.21) 196.73 (72.85) 132.20 (45.03)
244.38 235.83 118.75 158.33 241.25 234.17 172.71 247.29 156.67
pre (64.43) (60.17) (38.81) (57.48) (53.60) (49.60) (33.17) (79.64) (64.73)
47.83 45.94 31.66 42.07 46.56 49.81 37.38 38.51 32.91
(8.13) (8.12) (11.34) (12.98) (11.68) (12.09) (9.00) (12.62) (6.83)
224.49 (53.79) 208.51 (52.18) 90.98 (30.32) 113.28 (39.15) 180.41 (34.23) 201.05 (50.64) 141.02 (32.69) 208.30 (74.73) 136.68 (57.98)
257.08 239.58 113.75 155.63 241.46 225.83 175.21 250.83 160.00
post
Non-dominant leg
0.02 0.01 0.14 0.01 0.16 0.03 0.02 0.53 0.18
0.69 0.88 0.81 0.31 1.00 0.24 0.88 0.14 0.58
0.58 0.97 0.66 0.64 1.00 0.35 0.54 0.76 0.72
p
0.48 0.54 0.30 0.54 0.29 0.43 0.46 0.13 0.27
0.08 0.03 0.05 0.21 0.00 0.24 0.03 0.30 0.11
0.11 0.01 0.09 0.10 0.00 0.19 0.13 0.06 0.07
r
49.99 47.30 33.13 43.24 68.61 64.89 45.15 38.16 43.09
(36.91) (38.79) (34.87) (19.04) (73.74) (57.09) (50.38) (56.34) (91.11)
(42.41) (44.10) (43.55) (27.06) (108.71) (77.73) (65.00) (61.86) (102.12)
(8.65) (7.60) (13.79) (6.65) (23.67) (19.52) (18.93) (14.29) (20.26)
203.83 194.03 100.19 113.46 251.27 234.73 150.80 201.73 165.97
225.00 216.82 123.18 152.50 337.27 272.50 197.27 250.68 203.18
pre (37.66) (37.16) (42.22) (46.26) (82.87) (83.27) (55.27) (70.58) (107.06)
46.25 43.55 30.75 38.47 63.10 61.44 42.60 36.89 42.68
(8.97) (8.09) (10.68) (8.55) (21.67) (18.62) (17.89) (13.54) (19.91)
213.40 (34.82) 202.03 (32.25) 97.13 (29.33) 107.19 (22.87) 248.40 (63.43) 234.84 (60.12) 147.21 (46.35) 213.49 (61.97) 170.93 (87.33)
232.95 224.77 116.82 143.41 315.68 268.86 185.23 252.05 197.05
post
Dominant leg
0.01 0.00 0.25 0.01 0.06 0.05 0.04 0.53 0.59
0.02 0.08 0.53 0.37 0.79 0.86 0.66 0.37 0.86
0.30 0.14 0.07 0.57 0.13 0.69 0.56 1.00 0.51
p
0.55 0.63 0.25 0.55 0.40 0.42 0.44 0.13 0.11
0.49 0.38 0.13 0.19 0.06 0.04 0.09 0.19 0.04
0.22 0.31 0.38 0.12 0.32 0.09 0.12 0.00 0.14
r
52.94 50.43 32.71 38.16 70.25 65.60 44.96 42.01 39.94
(10.31) (8.05) (13.73) (6.37) (23.27) (16.23) (13.55) (16.75) (13.91)
213.52 (38.74) 203.31 (30.24) 99.49 (38.61) 95.27 (15.49) 255.56 (88.44) 233.65 (44.27) 140.62 (28.06) 204.61 (71.66) 150.83 (60.00)
(46.28) (35.92) (56.13) (27.56) (153.41) (47.42) (37.39) (80.29) (60.11)
pre 239.09 228.86 125.23 140.45 357.50 269.09 191.14 257.05 177.27
WG (n = 11)
(48.16) (43.79) (47.72) (34.49) (103.53) (57.59) (64.14) (92.17) (61.98)
48.78 46.53 31.65 36.79 60.59 60.93 44.32 36.69 38.40
(10.50) (8.43) (11.87) (6.81) (15.80) (14.94) (16.60) (16.14) (12.35)
221.53 (42.31) 214.73 (36.84) 99.72 (37.28) 98.84 (16.19) 235.88 (54.90) 236.71 (50.73) 149.56 (41.17) 196.75 (78.00) 152.99 (56.66)
245.91 243.18 129.55 137.95 320.00 265.68 192.73 236.59 178.41
post
Non-dominant leg
0.02 0.03 0.37 0.53 0.00 0.00 0.66 0.01 0.66
0.37 0.03 0.66 0.29 0.18 0.48 0.18 0.05 0.59
0.68 0.03 0.53 0.86 0.10 0.51 0.57 0.06 0.88
p
0.51 0.45 0.19 0.13 0.63 0.63 0.09 0.53 0.09
0.19 0.45 0.09 0.23 0.28 0.15 0.28 0.42 0.11
0.09 0.47 0.13 0.04 0.35 0.14 0.12 0.40 0.03
r
Mean (SD); EG = EFAM (multicomponent) training group; WG = Walking training group; p = p-value from Wilcoxon test; r = effect size, Rosenthal’s r.; pre = before training; post = after training; MP = maximum pressure; MMP = mean maximum pressure; PTi = pressure-time integral; MH = medial heel; LH = lateral heel; MA = medial arch; LA = lateral arch; MM = medial metatarsus; CM = central metatarsus; LM = lateral metatarsus; HX = hallux; RT = rest of toes.
(9.75) (9.67) (12.09) (13.62) (15.30) (12.53) (10.97) (12.63) (8.30)
189.70 (34.34) 192.12 (43.49) 91.89 (26.43) 120.57 (31.54) 176.74 (42.56) 198.59 (46.91) 150.23 (36.19) 196.09 (51.00) 140.14 (40.44)
MMP (kPa) MH LH MA LA MM CM LM HX RT
(37.65) (49.99) (32.82) (48.11) (74.71) (53.22) (44.21) (111.65) (85.64)
216.04 221.46 112.50 158.96 245.00 225.42 185.83 268.13 183.13
MP (kPa) MH LH MA LA MM CM LM HX RT
pre
Dominant leg
EG (n = 12)
Table 2 Maximum pressure, mean maximum pressure and pressure-time integral of the 9 plantar areas, in both legs, in both groups, pre- and post-training.
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Gait & Posture 77 (2020) 250–256
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are of special note because PTi is influenced by changes in pressure and stance-time variables, meaning that higher pressure will be applied over a shorter time period in these areas. This factor should be considered before suggesting exercise programs for special populations, again, such as diabetics [2], which could be affected by this factor. The scientific literature indicates that gait speed reduces with age [31]. Although we found no significant differences in gait speed in either group, in this study it increased by 0.12 m/s in the WG after training. Brown et al. [32] described an increase in gait speed of 0.10 m/s in OAs associated with an 11 % reduction in the risk of premature mortality. Based on previous findings [33], this small improvement corresponds to an increase in life expectancy of approximately 1 and 2 years. Finally, this study had some limitations. Firstly, although we analysed a high number of steps in each participant in both the pre- and post-training evaluations, the analysis of more participants would have also been useful. Second, our interventions lasted for 14 weeks which, according to the recommendations of the American College of Sports Medicine [4], makes it an intermediate-length training program (with short programs lasting 10–12 weeks and long ones, 21–24 weeks). However, 14 weeks may still be insufficient time for the main effects on the variables of interest from this study to become observable. Thus, it might be advisable to increase the duration of the training programs used in future similar research studies. In conclusion, these two training programs resulted in several different changes in plantar pressure and spatiotemporal parameters during gait in OAs. On the one hand, the EFAM-UV© multicomponent training program reduced MP and PTi values. On the other hand, the interval walking program increased MP and MMP values and decreased PTi as well as stride and stance time. Both training programs increased lower-limb strength, but neither improved gait speed. Thus, perhaps the completion of a multicomponent training program prior to a walkingbased program may be useful in OAs. Future studies should also explore the effect of these two programs on special populations with specific foot problems.
Fig. 4. Pre vs post-training differences in lower-limb strength (Mean and SD). EG: EFAM (multicomponent) training group; WG: Walking training group; * p < 0.05 and d > 0.5.
higher in OAs compared to younger people, especially in the forefoot area [3]. Moreover, foot problems, and pain in particular, reduce physical activity patterns and levels in OAs, and this factor is also related to frailty and affects balance and foot function, doubling their risk of falls in this population [1]. The reductions we found in MP in the EG dominant leg medial and central metatarsal areas after training indicate that the postural control and balance exercises this group performed were sufficient to redistribute their plantar pressures. These reductions could mean that there was greater movement control during the initial contact of the gait in the EG compared to the WG, as shown by the increase in the heel area MP values in the latter. These reductions are comparable to those from other studies using similar participants and balance-based interventions [10], indicating that these types of exercise programs help OAs mitigate or avoid plantar problems. However, the fact that plantar heel pressure increases linearly with gait speed [26] could call the increases in dominant leg medial heel MMP and non-dominant leg lateral heel MMP in the WG into doubt. Although the increase in gait speed we observed in the WG (+0.12 m/ s) was not statistically significant, this small increase could have affected the plantar pressure values of these areas and the effect would have been similar for the increase in MP in the post-training nondominant leg lateral heel. Thus, given that 4%–17% of OAs report heel area pain [3], exercise programs with moments reaching moderate to high speeds (1.50–2.00 m/s) are not recommended for OAs susceptible to pain and ulceration in this foot area such as diabetics [26]. The improvements in lower body strength achieved in both groups after training might be related to a generalised reduction in PTi values, because this increased strength would also contribute to increasing the body’s shock-absorbing capacity. The aging process results in progressive muscle and bone weakness as well as plantar fat tissue atrophy and loss of elasticity, which all reduces the body’s shock-absorbing capacity and can lead to increased impact forces [27]. However, strength training like that included in the EFAM-UV© program can reverse this process by increasing muscle hypertrophy and neuromuscular function [28]. Similarly, walking-based training has also been shown to effectively increase lower-extremity strength [29]. Stride and stance time both increase with ageing [3,12] and this, along with the adoption of a more cautious walking pattern [12], is characteristic of many OAs. In addition, OAs experiencing cognitive decline [13] or with Parkinson’s disease [14] also have higher stance times compared to healthy elderly individuals. Both these variables significantly decreased in the WG after training (stride time: both legs 5.34 %; stance time: dominant leg 6.90 %, non-dominant leg 7.19 %), a correlation which hints that this type of physical exercise may help to avoid or delay such mental diseases and promote healthy aging [30]. Although stance time was significantly lower in the WG compared to the EG, WG stance times for areas in which the MP and MMP increased
Funding This work was supported by the Valencian Government (Spain) and the European Social Fund (“European Social Fund, Investing in your Future”) through a predoctoral contract to Dr. Sanchis-Sanchis; Grant number: ACIF/2016/496. CRediT authorship contribution statement Roberto Sanchis-Sanchis: Conceptualization, Methodology, Validation, Formal analysis, Investigation, Resources, Data curation, Writing - original draft, Writing - review & editing, Visualization, Funding acquisition. Cristina Blasco-Lafarga: Conceptualization, Methodology, Validation, Formal analysis, Investigation, Resources, Writing - review & editing, Visualization, Supervision, Project administration, Funding acquisition. Alberto Encarnación-Martínez: Methodology, Validation, Formal analysis, Investigation, Resources, Data curation, Writing - review & editing, Visualization. Pedro PérezSoriano: Conceptualization, Methodology, Validation, Formal analysis, Investigation, Resources, Writing - review & editing, Visualization, Supervision, Project administration, Funding acquisition. Declaration of Competing Interest The authors report no conflicts of interest. Acknowledgements We wish to thank all the study participants. 255
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Full length article
Changes in plantar pressure and spatiotemporal parameters during gait in older adults after two different training programs
T
Roberto Sanchis-Sanchisa, Cristina Blasco-Lafargab, Alberto Encarnación-Martíneza, Pedro Pérez-Sorianoa,* a b
Research Group in Sports Biomechanics (GIBD), Department of Physical Education and Sports, University of Valencia, Valencia, Spain Sport Performance and Physical Fitness Research Group (UIRFIDE), Department of Physical Education and Sports, University of Valencia, Valencia, Spain
ARTICLE INFO
ABSTRACT
Keywords: Elderly Exercise Walking Instrumented insole Foot
Background: Improving gait is in exercise programs for older adults (OAs) but little is known about how different gait-training approaches affect spatiotemporal parameters and plantar pressure distributions in OAs. High plantar pressures are linked to tissue injury risk, ulceration, and pain in OAs, but no studies have yet compared how they affect podobarometric variables. Research question: The effect of changing plantar pressure on absolute and mean maximum pressure, the pressure-time integral, stride time, stance time, and gait speed in OAs following either a multicomponent training program (EG) or interval-walking training (WG). Methods: Comfortable gait speed, strength (seat-to-stand test), and plantar pressure (Pedar-X mobile in-shoe system), were evaluated in 23 OAs (EG: n = 12, 7 female, 71.58 ± 4.56 years; WG: n = 11, 6 female, 69.64 ± 3.56 years), by dividing the plantar area into 9 regions. Results: After 14 weeks, the maximum pressure in medial and central metatarsus areas in the dominant leg were reduced in the EG (p = 0.01 & p = 0.04, respectively), but increased in the non-dominant leg lateral heel in the WG (p = 0.03). The mean maximum pressure also increased in the WG in medial heel in the dominant leg (p = 0.02) and lateral heel in the non-dominant leg (p = 0.03). The overall pressure-time integral reduced in the whole plantar area in both legs in both groups. WG reduced stride time (dominant: p = 0.01; non-dominant: p = 0.01) and stance time (dominant: p < 0.005; non-dominant: p < 0.005). Gait speed did not change in any group. As expected, lower limb strength improved after both exercise programs (EG: p = 0.02; WG: p = 0.01). Significance: Although these training interventions were short, they indicate the importance of exercise types. Our results suggest that OAs might benefit from periodized training, especially when multicomponent programs are introduced prior to the walking goals. Future, larger studies should explore situations in which special populations with specific foot problems might benefit from these interventions.
1. Introduction Foot problems such as pain, neuropathy, and deformities are very common in older adults (OAs) and are related to different risk factors such as age, obesity, or inappropriate footwear [1]. High plantar pressure values during gait are linked to a risk of tissue injury, ulceration, and pain in OAs [2] because their maximum pressures are higher compared to those of younger people [3]. Moreover, these kinds of problems are associated with a reduction in physical activity levels, deconditioning, balance deterioration, and falls [1]. It is well known that training improves physical-function in OAs. Indeed, specific programs based on balance and/or strength exercises [4], as well as
⁎
multicomponent training regimens [5] and/or walking-based programs [6] can effectively improve static/dynamic balance, agility, postural control, lower limb strength, and/or gait speed. There is a proven relationship between high plantar pressure and metatarsalgia [7], ulceration [2], and falls [8] in OAs and so reducing these values is a useful goal in this population. Plantar pressure distribution during gait has been widely studied in elderly populations by analysing different variables including barefoot versus shoe wearing [2], shoe sole hardness [9], or the use of accommodative insoles [7]. Moreover, several different studies have reported a reduction in plantar peak pressure distributions in this population after completing an exercise program [10]. Physical exercise seems to reduce both stride and
Corresponding author at: Department of Physical Education and Sports (University of Valencia), C/Gascó Oliag, nº 3, 46010, Valencia, Spain. E-mail address: [email protected] (P. Pérez-Soriano).
https://doi.org/10.1016/j.gaitpost.2020.01.015
0966-6362/ © 2020 Elsevier B.V. All rights reserved.
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2.2. Study design
Table 1 Group demographic data.
Age (years) Gender (male/female) Weight (kg) Height (m) 6-m Gait Speed (m/s) 5rep-StS (s)
EG (n = 12)
WG (n = 11)
p
71.58 (4.56) 5/7 79.03 (16.84) 1.57 (0.087) 1.31 (0.19) 13.18 (2.74)
69.64 (3.56) 5/6 80.40 (7.62) 1.63 (0.087) 1.37 (0.22) 12.98 (2.29)
0.27a 0.86b 0.81a 0.12a 0.50a 0.85a
The participants were divided into two experimental groups: the multicomponent program EFAM-UV© [17] group (EG) comprising 12 individuals and the walking group (WG) comprising 11 participants. We used a homogeneous sample distribution method (Table 1) and considered the following criteria: age, sex, weight, height, 6-metre gait speed, and lower-limb strength using the Five-repetition sit-to-stand test [18]. Each group carried out one of the training programs for 14 weeks and both groups were evaluated before participating in the program (pre-training) and after its end (post-training). The EG trained twice a week for approximately 60 min each session, as previously described [17] (Fig. 1). The methodology supporting the EFAM-UV© was built upon a six-domain taxonomy designed to progressively retrain neuromotor function in the participants’ basic domains (Bs), including postural control, gait patterns, rhythm, and motor skills, as well as in the more complex complementary second-level physical literacy domains (Cs) requiring a dual-tasking approach to sustain improvements in manipulative and mental capabilities. We followed the EFAM-UV© interval training guidelines designed to increase bioenergetic, neuromuscular, and cognitive patient loads by retraining or relearning processes, individually tailoring these to each participant. The WG performed a walking-interval training program described elsewhere [6] with three sessions per week, each lasting an average of 41.54 ± 3.17 min. We controlled the training intensity in both groups using a heart rate monitor and a Spanish adaptation of the OMNI-Resistance Exercise Scale (OMNI-RES), a visual version of the perceived exertion scale (scored 1–10) with pictures used represent different training intensities [19].
Values are mean (SD). a p-value from independent t-test. b p-value from Mann-Whitney test; EG = EFAM (multicomponent) training group; WG = Walking training group; 5rep-StS = Five-repetition sit-to-stand test.
stance time in OAs [11]—both factors which are affected by ageing [12] and which are related to several diseases such as cognitive decline and dementia [13] or Parkinson’s disease [14]. Gait speed, which is related to life expectancy [15], can also be improved by exercise [16]. However, so far, no studies have compared the effects of different training programs on podobarometric variables in OAs. The aim of this present study was to analyse the effects of multicomponent versus interval walking on different plantar pressures and spatiotemporal parameters during gait in OAs. The hypotheses we proposed were that in OAs: (1) multicomponent training but not interval walking training will reduce the maximum pressure and mean maximum pressure values and (2) will reduce pressure-time integral values; (3) interval walking training but not multicomponent training will reduce stride and stance time; and (4), both training styles will increase gait speed.
2.3. Plantar pressure assessment procedure
2. Methods
To analyse plantar pressure, we used a Pedar-X mobile in-shoe system (Novel gmbh, Munich, Germany); these are 1.99 mm thick, flexible insoles containing 99 capacitance sensors homogeneously distributed over the insole area. A previous study has shown that this system is valid and reliable for measuring plantar pressure [20]. The insoles were calibrated according to the manufacturer’s instructions before each trial and plantar pressures were recorded at a frequency of 100 Hz. To control differences in each individual’s personal footwear, all the participants used standard trainers [21] (Reebok Classic NPC RAD) and were allowed to familiarise themselves with the new footwear by feely walking around the room for 5 min before recording commenced [22]. The Pedar-X insoles can be affected by foot heat and humidity [22] and so these sensors were also calibrated inside the shoes during this familiarisation phase. To collect the data, participants were instructed to walk at a ‘comfortable and safe’ speed along a straight 10-metre corridor, a total of 10 times; the accelerometery data was recorded during the 6 central meters, considering the first and last 2 m acceleration and deceleration
2.1. Participants This study included 23 OAs (10 men and 13 women, aged 70.65 ± 4.14 years; mean height = 160.09 ± 8.96 cm, mean weight = 79.68 ± 12.99 kg). The inclusion criteria were (1) age ≥65 years; (2) individuals with no walking difficulties who did not use any walking aids; (3) 6-metre gait speed ≥0.8 m/s; (4) individuals not receiving any physiotherapeutic rehabilitation or occupational therapy treatments; (5) no participation in any other physical exercise programs; and (6), a Mini-Mental Score Examination Test (MMSE) score ≥24 points, indicating the absence of any cognitive impairments. All our experiments complied with the ethical principles set out in the Declaration of Helsinki and were approved by the University of Valencia Ethics Committee (reference number: H1478084714217) before commencing. The patients we recruited gave their written informed consent before participating in the study.
Fig. 1. The neuromotor training methodology of EFAM-UV© program [17]. 251
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training data points, and our analysis considered 8 steps 4 right leg and 4 left leg in each trial 1640 pre-training and 1624 post-training steps which was sufficient to achieve a high reliability coefficient [23]. Plantar pressure data and stride parameters (stride time and stance time) were analysed with Pedar software according to manufacturer’s instructions. As described elsewhere [21], we divided the plantar area into 9 regions (Fig. 2) the medial heel (MH), lateral heel (LH), medial arch (MA), lateral arch (LA), medial metatarsus (MM; first metatarsus), central metatarsus (CM; second and third metatarsals), lateral metatarsus (LM; fourth and fifth metatarsals), hallux (HX), and the remaining toes (RT). The edges of each region were defined according to the congruent plantar anatomy, as described elsewhere [24]. The following pressure variables were extracted for each foot using Pedar software: maximum pressure (MP; highest pressure recorded for each region at any time during the data collection period), mean maximum pressure (MMP; average of all the peak pressures recorded for each region), and pressure-time integral (PTi; the product of the mean pressure and the time during which it was applied) [2]. Stride time (StrT; time elapsed from the heel contact of one foot to the next heel contact of the same foot), and stance time (StnT; time elapsed between the first to the last contact of a footfall, i.e. from the heel contact to the toe-off) were also extracted, considering each foot as a whole (i.e., not dividing it into 9 regions). 2.4. Lower-limb strength assessment Lower-limb strength was assessed using the Five-Repetition Sit-toStand Test [18]; from a sitting position and with the individual maintaining their arms crossed across their chest, the participants had to completely get up from a chair and sit down again 5 times in a row in the shortest time possible. We preformed the test twice per person and considered the fastest result for our analysis. 2.5. Leg dominance determination Leg dominance was determined through the question “If you were to kick a ball at a target, which leg would you use?” [25]. All the participants were right-handed. 2.6. Statistical analysis All the data were analysed with the SPSS software, version 25 (IBM Corp., Armonk, NY.). After checking the normality of the variables with a Kolmogorov–Smirnov test, we used paired t-tests to compare intraindividual differences for the parametric variables before and after training in each group (EG-pre vs. EG-post; WG-pre vs. WG-post) and employed Wilcoxon tests to analyse the nonparametric variables. The effect size (ES) was assessed using Cohen’s d as the parametric test and Rosenthal’s r for the nonparametric data. Significance was defined as p < 0.05 or as a moderate to high ES (d ≥ 0.5; r ≥ 0.3). 3. Results No differences were found in gait speed after training in the WG (1.32 ± 0.18 m/s vs. 1.44 ± 0.25 m/s, p = 0.23, d = 0.58) or EG (1.30 ± 0.21 m/s vs. 1.23 ± 0.28 m/s, p = 0.26, d = 0.31). However, there were statistically significant reductions in stride time (Fig. 3) in the WG after training, both in the dominant (1.048 ± 0.058 s vs. 0.992 ± 0.058 s, p = 0.01, d = 0.96) and non-dominant leg (1.048 ± 0.059 s vs. 0.992 ± 0.057 s, p = 0.01, d = 0.97). In contrast, no similar differences were found in the EG in the dominant (1.051 ± 0.088 s vs. 1.012 ± 0.095 s, p = 0.10, d = 0.43) or nondominant leg (1.051 ± 0.087 s vs. 1.010 ± 0.094 s, p = 0.10, d = 0.45). Fig. 3 shows pre- versus post-training differences in each group in terms of stance time, both in the dominant and non-dominant leg. After
Fig. 2. Area regions in plantar pressure analysis. MH = medial heel; LH = lateral heel; MA = medial arch; LA = lateral arch; MM = medial metatarsus; CM = central metatarsus; LM = lateral metatarsus; HX = hallux; RT = rest of toes.
zones, respectively [2]. The gait speed of each repetition was registered using a photocells system (Chronojump Boscosystem©) but was not controlled so as to avoid modifying the participants’ natural gait [2]. The average speed of all the series was then calculated for each participant, discarding any outliers exceeding 5 % of each individual’s average speed (to minimise any effect walking speed could have on plantar pressure) [2]. We obtained 205 pre-training and 203 post252
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Fig. 3. Pre vs post-training differences in (a) stride time and (b) stance time, in both legs (Mean and SD). EG: EFAM (multicomponent) training group; WG: Walking training group; * p < 0.05 and d > 0.5.
training, there was a significant decrease in stance time in the WG dominant (0.652 ± 0.042 s vs. 0.607 ± 0.041 s, p = 0.00, d = 1.07) and non-dominant leg (0.654 ± 0.044 s vs. 0.607 ± 0.047 s, p = 0.00, d = 1.03). However, no differences were found in the EG dominant (0.656 ± 0.071 s vs. 0.623 ± 0.076 s, p = 0.05, d = 0.46) or nondominant leg (0.660 ± 0.066 s vs. 0.625 ± 0.075 s, p = 0.07, d = 0.50). Pre- and post-training differences in the MP, MMP, and PTi plantar pressure variables in each group are shown in Table 2 for both legs and for the nine different plantar regions. After training, significant reductions in the MP were found in the dominant leg in the EG, both in the medial and central metatarsus, while an increase was found in lateral heel of the non-dominant leg in the WG. There was an increase both in the medial heel MMP of the dominant leg and lateral heel MMP of the non-dominant leg in the WG, and a reduction in the hallux MMP of the non-dominant leg. Interestingly, the stance time reduced in the WG for areas in which the MP and MMP increased (MH dominant leg: 0.459 ± 0.056 vs. 0.412 ± 0.074 s, p = 0.06, d = 0.73; LH non-dominant leg: 0.513 ± 0.102 vs. 0.444 ± 0.089 s, p = 0.01, d = 0.72). We found a PTi decrease in the lateral arch, medial metatarsus, central metatarsus, and lateral metatarsus of the dominant leg in the EG and in the medial and lateral heel, lateral arch, and central and lateral metatarsus of the EG non-dominant leg. Lastly, we noticed a reduction in PTi in the medial and lateral heel, lateral arch, and lateral metatarsus of the
dominant leg in the WG and reductions in the medial and lateral heel, medial and central metatarsus, and hallux in the non-dominant leg. Finally, lower-limb strength significantly improved in both groups (Fig. 4) after completion of the training programs (EG: 13.18 ± 2.74 s vs. 11.48 ± 2.34 s, p = 0.02, d = 0.67; WG: 12.98 ± 2.29 s vs. 11.20 ± 1.83 s, p = 0.01, d = 0.86). 4. Discussion This study aimed to analyse the effects on the maximum pressure, mean maximum pressure, pressure-time integral, stride time, stance time, and gait speed in OAs during gait after completing either a multicomponent (EFAM-UV©) training program [17] or an intervalwalking program [6]. In summary, after training, the MP values reduced in the medial and central metatarsal areas of the dominant leg in the EG but increased in the lateral heel of the non-dominant leg in the WG; MMP values also increased in medial heel of the dominant leg and lateral heel of the non-dominant leg in the WG. There was a general reduction in PTi values in both training groups, stride and stance time reduced both in the dominant and non-dominant leg in the WG, and there was an increase in lower-limb strength after training in both the EG and WG; no differences were found in gait speed for either group. Here we studied elevated pressures during gait because of their relationship with the risk of tissue injury, ulceration, and pain among elderly individuals [2]. Previous studies have shown that MP values are 253
254
44.26 44.19 34.98 49.30 52.25 53.71 44.44 40.25 37.98
PTi (kPa*s) MH LH MA LA MM CM LM HX RT
(58.86) (72.88) (30.33) (41.80) (54.85) (46.52) (38.01) (95.73) (82.14)
41.44 41.56 31.52 43.82 46.86 49.11 41.51 38.00 37.72
(8.32) (7.95) (9.73) (10.66) (13.55) (11.84) (10.85) (13.96) (11.14)
200.85 (48.60) 204.06 (61.17) 93.06 (28.17) 119.65 (32.02) 173.85 (40.82) 191.15 (44.13) 147.90 (35.34) 207.23 (85.18) 149.93 (74.96)
228.96 237.08 108.96 153.96 223.75 214.38 181.46 257.92 176.88
post
0.06 0.07 0.18 0.02 0.02 0.00 0.05 0.39 0.69
0.16 0.12 0.21 0.88 0.53 0.12 0.94 0.81 0.94
0.33 0.17 0.64 0.88 0.01 0.04 0.42 0.29 0.33
p
0.38 0.37 0.27 0.48 0.48 0.58 0.40 0.18 0.08
0.29 0.32 0.26 0.03 0.13 0.32 0.02 0.05 0.02
0.20 0.28 0.10 0.03 0.50 0.42 0.16 0.22 0.20
r (47.95) (53.24) (42.37) (48.36) (50.10) (60.28) (34.88) (77.54) (52.80)
53.17 52.50 35.58 48.36 49.62 53.60 40.13 40.38 34.29
(9.68) (10.64) (12.78) (14.96) (11.28) (12.88) (8.63) (14.99) (7.56)
216.40 (43.81) 205.84 (48.21) 96.77 (32.71) 118.96 (34.33) 180.14 (34.48) 209.24 (59.34) 142.25 (29.21) 196.73 (72.85) 132.20 (45.03)
244.38 235.83 118.75 158.33 241.25 234.17 172.71 247.29 156.67
pre (64.43) (60.17) (38.81) (57.48) (53.60) (49.60) (33.17) (79.64) (64.73)
47.83 45.94 31.66 42.07 46.56 49.81 37.38 38.51 32.91
(8.13) (8.12) (11.34) (12.98) (11.68) (12.09) (9.00) (12.62) (6.83)
224.49 (53.79) 208.51 (52.18) 90.98 (30.32) 113.28 (39.15) 180.41 (34.23) 201.05 (50.64) 141.02 (32.69) 208.30 (74.73) 136.68 (57.98)
257.08 239.58 113.75 155.63 241.46 225.83 175.21 250.83 160.00
post
Non-dominant leg
0.02 0.01 0.14 0.01 0.16 0.03 0.02 0.53 0.18
0.69 0.88 0.81 0.31 1.00 0.24 0.88 0.14 0.58
0.58 0.97 0.66 0.64 1.00 0.35 0.54 0.76 0.72
p
0.48 0.54 0.30 0.54 0.29 0.43 0.46 0.13 0.27
0.08 0.03 0.05 0.21 0.00 0.24 0.03 0.30 0.11
0.11 0.01 0.09 0.10 0.00 0.19 0.13 0.06 0.07
r
49.99 47.30 33.13 43.24 68.61 64.89 45.15 38.16 43.09
(36.91) (38.79) (34.87) (19.04) (73.74) (57.09) (50.38) (56.34) (91.11)
(42.41) (44.10) (43.55) (27.06) (108.71) (77.73) (65.00) (61.86) (102.12)
(8.65) (7.60) (13.79) (6.65) (23.67) (19.52) (18.93) (14.29) (20.26)
203.83 194.03 100.19 113.46 251.27 234.73 150.80 201.73 165.97
225.00 216.82 123.18 152.50 337.27 272.50 197.27 250.68 203.18
pre (37.66) (37.16) (42.22) (46.26) (82.87) (83.27) (55.27) (70.58) (107.06)
46.25 43.55 30.75 38.47 63.10 61.44 42.60 36.89 42.68
(8.97) (8.09) (10.68) (8.55) (21.67) (18.62) (17.89) (13.54) (19.91)
213.40 (34.82) 202.03 (32.25) 97.13 (29.33) 107.19 (22.87) 248.40 (63.43) 234.84 (60.12) 147.21 (46.35) 213.49 (61.97) 170.93 (87.33)
232.95 224.77 116.82 143.41 315.68 268.86 185.23 252.05 197.05
post
Dominant leg
0.01 0.00 0.25 0.01 0.06 0.05 0.04 0.53 0.59
0.02 0.08 0.53 0.37 0.79 0.86 0.66 0.37 0.86
0.30 0.14 0.07 0.57 0.13 0.69 0.56 1.00 0.51
p
0.55 0.63 0.25 0.55 0.40 0.42 0.44 0.13 0.11
0.49 0.38 0.13 0.19 0.06 0.04 0.09 0.19 0.04
0.22 0.31 0.38 0.12 0.32 0.09 0.12 0.00 0.14
r
52.94 50.43 32.71 38.16 70.25 65.60 44.96 42.01 39.94
(10.31) (8.05) (13.73) (6.37) (23.27) (16.23) (13.55) (16.75) (13.91)
213.52 (38.74) 203.31 (30.24) 99.49 (38.61) 95.27 (15.49) 255.56 (88.44) 233.65 (44.27) 140.62 (28.06) 204.61 (71.66) 150.83 (60.00)
(46.28) (35.92) (56.13) (27.56) (153.41) (47.42) (37.39) (80.29) (60.11)
pre 239.09 228.86 125.23 140.45 357.50 269.09 191.14 257.05 177.27
WG (n = 11)
(48.16) (43.79) (47.72) (34.49) (103.53) (57.59) (64.14) (92.17) (61.98)
48.78 46.53 31.65 36.79 60.59 60.93 44.32 36.69 38.40
(10.50) (8.43) (11.87) (6.81) (15.80) (14.94) (16.60) (16.14) (12.35)
221.53 (42.31) 214.73 (36.84) 99.72 (37.28) 98.84 (16.19) 235.88 (54.90) 236.71 (50.73) 149.56 (41.17) 196.75 (78.00) 152.99 (56.66)
245.91 243.18 129.55 137.95 320.00 265.68 192.73 236.59 178.41
post
Non-dominant leg
0.02 0.03 0.37 0.53 0.00 0.00 0.66 0.01 0.66
0.37 0.03 0.66 0.29 0.18 0.48 0.18 0.05 0.59
0.68 0.03 0.53 0.86 0.10 0.51 0.57 0.06 0.88
p
0.51 0.45 0.19 0.13 0.63 0.63 0.09 0.53 0.09
0.19 0.45 0.09 0.23 0.28 0.15 0.28 0.42 0.11
0.09 0.47 0.13 0.04 0.35 0.14 0.12 0.40 0.03
r
Mean (SD); EG = EFAM (multicomponent) training group; WG = Walking training group; p = p-value from Wilcoxon test; r = effect size, Rosenthal’s r.; pre = before training; post = after training; MP = maximum pressure; MMP = mean maximum pressure; PTi = pressure-time integral; MH = medial heel; LH = lateral heel; MA = medial arch; LA = lateral arch; MM = medial metatarsus; CM = central metatarsus; LM = lateral metatarsus; HX = hallux; RT = rest of toes.
(9.75) (9.67) (12.09) (13.62) (15.30) (12.53) (10.97) (12.63) (8.30)
189.70 (34.34) 192.12 (43.49) 91.89 (26.43) 120.57 (31.54) 176.74 (42.56) 198.59 (46.91) 150.23 (36.19) 196.09 (51.00) 140.14 (40.44)
MMP (kPa) MH LH MA LA MM CM LM HX RT
(37.65) (49.99) (32.82) (48.11) (74.71) (53.22) (44.21) (111.65) (85.64)
216.04 221.46 112.50 158.96 245.00 225.42 185.83 268.13 183.13
MP (kPa) MH LH MA LA MM CM LM HX RT
pre
Dominant leg
EG (n = 12)
Table 2 Maximum pressure, mean maximum pressure and pressure-time integral of the 9 plantar areas, in both legs, in both groups, pre- and post-training.
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are of special note because PTi is influenced by changes in pressure and stance-time variables, meaning that higher pressure will be applied over a shorter time period in these areas. This factor should be considered before suggesting exercise programs for special populations, again, such as diabetics [2], which could be affected by this factor. The scientific literature indicates that gait speed reduces with age [31]. Although we found no significant differences in gait speed in either group, in this study it increased by 0.12 m/s in the WG after training. Brown et al. [32] described an increase in gait speed of 0.10 m/s in OAs associated with an 11 % reduction in the risk of premature mortality. Based on previous findings [33], this small improvement corresponds to an increase in life expectancy of approximately 1 and 2 years. Finally, this study had some limitations. Firstly, although we analysed a high number of steps in each participant in both the pre- and post-training evaluations, the analysis of more participants would have also been useful. Second, our interventions lasted for 14 weeks which, according to the recommendations of the American College of Sports Medicine [4], makes it an intermediate-length training program (with short programs lasting 10–12 weeks and long ones, 21–24 weeks). However, 14 weeks may still be insufficient time for the main effects on the variables of interest from this study to become observable. Thus, it might be advisable to increase the duration of the training programs used in future similar research studies. In conclusion, these two training programs resulted in several different changes in plantar pressure and spatiotemporal parameters during gait in OAs. On the one hand, the EFAM-UV© multicomponent training program reduced MP and PTi values. On the other hand, the interval walking program increased MP and MMP values and decreased PTi as well as stride and stance time. Both training programs increased lower-limb strength, but neither improved gait speed. Thus, perhaps the completion of a multicomponent training program prior to a walkingbased program may be useful in OAs. Future studies should also explore the effect of these two programs on special populations with specific foot problems.
Fig. 4. Pre vs post-training differences in lower-limb strength (Mean and SD). EG: EFAM (multicomponent) training group; WG: Walking training group; * p < 0.05 and d > 0.5.
higher in OAs compared to younger people, especially in the forefoot area [3]. Moreover, foot problems, and pain in particular, reduce physical activity patterns and levels in OAs, and this factor is also related to frailty and affects balance and foot function, doubling their risk of falls in this population [1]. The reductions we found in MP in the EG dominant leg medial and central metatarsal areas after training indicate that the postural control and balance exercises this group performed were sufficient to redistribute their plantar pressures. These reductions could mean that there was greater movement control during the initial contact of the gait in the EG compared to the WG, as shown by the increase in the heel area MP values in the latter. These reductions are comparable to those from other studies using similar participants and balance-based interventions [10], indicating that these types of exercise programs help OAs mitigate or avoid plantar problems. However, the fact that plantar heel pressure increases linearly with gait speed [26] could call the increases in dominant leg medial heel MMP and non-dominant leg lateral heel MMP in the WG into doubt. Although the increase in gait speed we observed in the WG (+0.12 m/ s) was not statistically significant, this small increase could have affected the plantar pressure values of these areas and the effect would have been similar for the increase in MP in the post-training nondominant leg lateral heel. Thus, given that 4%–17% of OAs report heel area pain [3], exercise programs with moments reaching moderate to high speeds (1.50–2.00 m/s) are not recommended for OAs susceptible to pain and ulceration in this foot area such as diabetics [26]. The improvements in lower body strength achieved in both groups after training might be related to a generalised reduction in PTi values, because this increased strength would also contribute to increasing the body’s shock-absorbing capacity. The aging process results in progressive muscle and bone weakness as well as plantar fat tissue atrophy and loss of elasticity, which all reduces the body’s shock-absorbing capacity and can lead to increased impact forces [27]. However, strength training like that included in the EFAM-UV© program can reverse this process by increasing muscle hypertrophy and neuromuscular function [28]. Similarly, walking-based training has also been shown to effectively increase lower-extremity strength [29]. Stride and stance time both increase with ageing [3,12] and this, along with the adoption of a more cautious walking pattern [12], is characteristic of many OAs. In addition, OAs experiencing cognitive decline [13] or with Parkinson’s disease [14] also have higher stance times compared to healthy elderly individuals. Both these variables significantly decreased in the WG after training (stride time: both legs 5.34 %; stance time: dominant leg 6.90 %, non-dominant leg 7.19 %), a correlation which hints that this type of physical exercise may help to avoid or delay such mental diseases and promote healthy aging [30]. Although stance time was significantly lower in the WG compared to the EG, WG stance times for areas in which the MP and MMP increased
Funding This work was supported by the Valencian Government (Spain) and the European Social Fund (“European Social Fund, Investing in your Future”) through a predoctoral contract to Dr. Sanchis-Sanchis; Grant number: ACIF/2016/496. CRediT authorship contribution statement Roberto Sanchis-Sanchis: Conceptualization, Methodology, Validation, Formal analysis, Investigation, Resources, Data curation, Writing - original draft, Writing - review & editing, Visualization, Funding acquisition. Cristina Blasco-Lafarga: Conceptualization, Methodology, Validation, Formal analysis, Investigation, Resources, Writing - review & editing, Visualization, Supervision, Project administration, Funding acquisition. Alberto Encarnación-Martínez: Methodology, Validation, Formal analysis, Investigation, Resources, Data curation, Writing - review & editing, Visualization. Pedro PérezSoriano: Conceptualization, Methodology, Validation, Formal analysis, Investigation, Resources, Writing - review & editing, Visualization, Supervision, Project administration, Funding acquisition. Declaration of Competing Interest The authors report no conflicts of interest. Acknowledgements We wish to thank all the study participants. 255
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