Increased footwear comfort is associated with improved running economy – a systematic review and meta-analysis

Figures & data

Figure 1. PRISMA flow diagram of included and excluded studies.

Table 1. Details of included studies.

h	n (M/F); age (y ± SD)	Athlete level; Performance history	Footwear condition Study aim	Wear-in time; Mass compensation	Random Footwear order; Randomization described	Task	Comfort measure	Running related outcome measure	Correlation comfort-running related response; main effect	Limitations
Burke and Papuga (2012)	6(3/3); 32.3 ± 10.07	Recreational Pace: ≤8min/mile (females) ≤7min/mile (males) for ≥30 min.	Own footwear + 1 = custom orthotics 2 = shoe fitted support Aim: to compare VO2 and vVO2 and comfort between the two conditions	NR; No	Yes; No	Submaximal treadmill running at 5 different speeds (10.7–13.8 km.h^−1) 5 x 5 min steady state runs No individual speeds Different speeds for men and women	9 item FCAT Results: all in favour of condition 1 - Overall (P = 0.027). - Heel cushioning (P = 0.002), - Forefoot cushioning (P = 0.036), - Heel cup fit (P = 0.011), - Heel width (P = 0.024), - Length (P = 0.038). Others comfort measures not significant	Submaximal VO2 (ml.min^−1.kg^−1): 1 = 37.7 ± 3.3 2 = 40.7 ± 1.6 (P = 0.023) VO2max ( ml.min^−1.kg^−1): 1 = 53.3 ± 6.5 2 = 53.3 ± 6.1 (NS) (P = 0.962) vV02(mph): 1 = 10.94 ± 0.64 2 = 9.81 ± 0.98 (P = 0.008)	Submaximal VO2 and - overall comfort (r = 0.64) - heel cushioning (r = 0.64) - heel cup fit (r = 0.60) - medial-lateral stability (r = 0.31) - arch height support (r = 0.33) Submaximal VO2 and - overall fit (r ≥ 0.70) - heel width (r = 0.89) - forefoot width (r = 0.86) - length (r = 0.71) No effect measures calculated	- Small Sample size, - Condition 1 preferred condition - Partly funded by orthotic lab
Lindorfer et al. (2020)	15(15/0); 26 ± 4	Recreational Distance: ≥20km/wk	5 standardized footwear conditions with varying in mechanical properties reduced to 1 = most preferred shoe (MC) 2 = least preferred shoe (LC) Aim 1: to determine potential differences in VO2 and biomechanical variables to explain changes in metabolic demand between the two conditions Aim 2: to determine potential differences in coordination variability associated with LE injuries in previous studies between the two conditions.	NR; Yes	Yes; Yes	Submaximal treadmill running at fixed speed (11.3 ± 1.7 km.h^−1) 4 x 6 min steady state runs Individual set speed	Ranking least-most comfortable to reduce 5 pairs to 2. In addition, a 100mm VAS scale used to rate comfort for each pair Absolute difference between MC and LC in rating on the VAS was 57±25 mm. Relative difference between the two conditions was 4±2 times the SMD.	Submaximal VO2(ml.min^−1.kg^−1): 1 = 44.4 ± 8.9 2 = 44.2 ± 9.0 (P = 0.20)	No correlation was calculated Low effect of footwear comfort on VO2 (dz = 0.36; P = 0.20)	- All male group
Luo et al. (2009)	13 (13/0); 23.8 ± 3.4	Proficient Performance history: NR	5 standardized footwear conditions: A = a standard neutral running shoe B = neutral + carbon fiberplate inserted to increase the longitudinal bending stiffness. C = neutral + thin leather insole and an exaggerated arch support. D = flat cross-trainer E = inexpensive shoe (no protective features) reduced to 1 = Most comfortable shoe (MC) 2 = Least comfortable shoe (LC) Aim: to determine if running footwear comfort can influence running economy	NR; Yes	Yes; Yes	Submaximal treadmill running (Speed NR) 4 x 6 min steady state runs Individual set speed	7 and 6 items 5 point Likert scale: 1 is “just right”, 3 acceptable, 5 unacceptable Static Comfort: - shoe length, - toe box height, - forefoot width, - midfoot height, - arch support, - ankle collar height, - heel hold Dynamic comfort: - forefoot cushioning, - Rearfoot cushioning - forefoot flexibility, - stability, - heel-to-toe transition, - shoe weight Dynamic comfort assessed during 5 min preferred speed running Result: Most comfortable: shoe A (n = 10) Least comfortable: shoe B (n = 3), C (n = 4), D (n = 2), E (n = 1)	Submaximal VO2 (ml.min^−1.kg^−1): LC – MC = 0.28 (P = 0.036) 8/10 participants ≤1.9% in VO2 for MC AVG VO2 = 0.28 ml.min^−1.kg^−1 (−0.7%) for MC compared to LC	No correlation was calculated A significant effect of footwear comfort on VO2 (P = 0.036) with AVG 0.28 ml.min^−1.kg^−1 reduction for MC vs LC	- Analysis done on 10 out of 13 participants - No description of participant running level - Speeds not mentioned - In methods mentioning of paired t test to compare AVG oxygen consumption between least and most comfortable shoe condition, but missing in the results - No P values for comfort measures
Souza et al. (2018)	15 (NR/NR); 28.1 ± 5.8	Recreational Frequency: ≥3x/wk, Distance: 15–20 km/wk Pace: 5–6 min/km	1 = Cushioned shoes 2 = Barefoot Aim: to evaluate the effect of various ground conditions and barefoot vs regular running shoes in race performance, in rating of perceived exertion and in pain perception.	No, No	Yes; No	1 = 15-minute Balke synthetic track test 2 = 3000 m beach run 3 = Submaximal treadmill running (8 km.h^−1) 2 x 6 min steady state runs No individual speeds	A = OMNI scale (RPE) B = EMADOR (Pain) Balke test OMNIscale 1 = 6.40 ± 1.42 2 = 4.90 ± 1.52 (P = 0.036) EMADOR 1 = 0.50 ± 1.58 2 = 3.30 ± 3.33 (P = 0.027) Beach run OMNIscale 1 = 8.10 ± 1.05 2 = 7.60 ± 1.07 (P = 0.237) EMADOR 1 = 3.20 ± 3.19 2 = 1.30 ± 2.40 (P = 0.150) Treadmill run No OMNI or EMADOR Results	Balke test Speed (m/s): 1 = 2.58 ± 0.19 2 = 2.46 ± 0.36 (P = 0.345) Beach run Speed (m/s): 1 = 1.85 ± 0.17 2 = 1.96 ± 0.13 (P = 0.128) Treadmill Stride frequency (Hz): 1 = 165.00 ± 10.96 2 = 165.20 ± 9.62 (P = 0.966) Stride amplitude: 1 = 57.23 ± 6.72 2= 54.17 ± 6.17 (P = 0.303) Angle (deg): 1 = 172.50 ± 6.73 2 = 168.10 ± 5.17 (P = 0.119)	No correlation was calculated Effect of footwear during Balke test on RPE (d = 0.10; P = 0.036) Pain (d = 1.07; P = 0.027) Speed (d = 0.41; P = 0.345) Effect of footwear during Beach run on RPE (d = 0.04; P = 0.237) Pain (d = 0.08; P = 0.150) Speed (d = 0.72; P = 0.128) Effect of footwear during Treadmill on Stride frequency (d = 0.01; P = 0.966) Stride amplitude (d = 0.47; P = 0.303) Angle (d = 0.07; P = 0.119)	- No mentioning of sex participant group - No VO2 data gathered during submaximal treadmill run
Sinclair, McGrath, et al. (2016)	12(12/0); 22.4 ± 2.2	Active Frequency: ≥3/wk Distance: ≥35km/wk	1 = Saucony PGGII (conventional) 2 = Adidas Energy Boost (energy return claim) Aim: to comparatively explore the effects of energy return footwear on the oxygen cost of steady-state running in relation to conventional running shoes	Yes; Yes	Yes; No	Submaximal treadmill running (12 km.h^−1) 2 x 6 min steady state runs No individual speeds	Borgscale (6-20 point) 150mm VAS Comfort extreme left side = “not comfortable at all” and extreme right = “most comfortable condition imaginable” RPE: 1 = 11.0 ± 1.9 VS 2 = 10.5 ± 1.3 VS (P > 0.008) VAS: 1 = 10.1 ± 2.9 VS 2 = 12.0 ± 1.9 VS (P = 0.006)	VO2 (ml.min^−1.kg^−1): 1 = 43.6 ± 3.7 2 = 41.8 ± 3.2 ^1 (P = 0.008) RER: 1 = 0.99 ± 0.06 2 = 0.98 ± 0.08 (P = 0.007) HR no significant differences	No correlation calculated, The majority had a lower VO2 for the energy return shoe, the overall preference was 50/50% for either shoe Footwear main effect on comfort favouring condition 2 (n^2 = 0.49; P = 0.006) Footwear main effect on VO2 favouring condition 2 (n^2 = 0.48; P = 0.008)	- Bonferroni <0.008 but 0.006 and 0.007 regarded as statistically significant.
Sinclair, Shore, et al. (2016)	10 (10/0); 23.4 ± 2.1	Recreational Performance history: NR	1 = minimalist shoe 2 = maximalist shoe 3 = energy return shoe Aim: to explore the effects of minimalist, maximalist and energy return footwear of equal mass on economy and substrate utilization during steady state running.	Yes; Yes	Yes; No	Submaximal treadmill running (13 km.h^−1) 3 x 6 min steady state runs No individual speeds	Borgscale (6–20 point) 150 mm VAS Comfort extreme left side = “not comfortable at all” and extreme right = “most comfortable condition imaginable” RPE: 1 = 11.6 ± 2.0 2 = 10.4 ± 1.2 3 = 10.3 ± 0.8 (P > 0.05) VAS: 1 = 7.0 ± 2.9 2 = 9.7 ± 1.8 3 = 10.0 ± 2.4 (P ≤ 0.05)	VO2 (ml.min^−1.kg^−1): 1 = 37.8 ± 5.2 VS 2 = 37.8 ± 4.9 VS 3 = 35.9 ± 3.4 (P ≤ 0.05)	No correlation calculated, however, on average lowest VO2 measure in energy return shoe Overall preference was 1 = 20% 2 = 30% 3 = 50% Footwear Comfort main effect favouring condition 3 (pn^2 = 0.30) (P ≤ 0.05)	- No information on level of recreational runners

Notes: NR = Not reported; FCAT = Footwear Comfort Assessment Tool; AVG = average; VAS = Visual Analogue Scale; OMNI = omnibus scale for perceived exertion; EMADOR = Multidimensional Pain Evaluation Scale; LC = least comfortable; MC = most comfortable; RPE = rating of perceived exertion; VO₂= steady-state oxygen consumption; RER= respiratory exchange ratio; HR = heart rate; P = significance level; n² = effect size eta²; pn² = effect size using partial eta²; d = effect size using Cohens d.

Table 2. Study quality assessment using the effective public health practice project (EPHPP).

Reference	Component rating						Global rating
	Selection bias	Study design	Confounders	Blinding	Data collection	Withdrawals/ drop-outs	Overall study quality
Burke and Papuga (2012)	Weak	Moderate	Strong	Weak	Weak	Strong	Weak
Lindorfer et al. (2020)	Moderate	Strong	Strong	Weak	Weak	Weak	Weak
Luo et al. (2009)	Moderate	Moderate	Strong	Weak	Weak	Moderate	Weak
Souza et al. (2018)	Moderate	Moderate	strong	Weak	Weak	Weak	Weak
Sinclair, McGrath, et al. (2016)	Moderate	Moderate	Strong	Weak	Moderate	Strong	Moderate
Sinclair, Shore, et al. (2016)	Moderate	Moderate	Strong	Weak	Moderate	Weak	Weak

Figure 2. Forest plot representing the association of footwear comfort on running economy (most comfortable footwear vs least comfortable footwear) in order of weight.

Burke, J. R., & Papuga, M. O. (2012). Effects of foot orthotics on running economy: Methodological considerations. Journal of Manipulative & Physiological Therapeutics, 35(4), 327–336. doi:10.1016/j.jmpt.2012.04.001

 PubMed Web of Science ®Google Scholar

Lindorfer, J., Kroll, J., & Schwameder, H. (2020). Does enhanced footwear comfort affect oxygen consumption and running biomechanics? European Journal of Sport Science, 20(4), 468–476. doi:10.1080/17461391.2019.1640288

 PubMed Web of Science ®Google Scholar

Luo, S. P., Worobets, J., Nigg, B., & Stefanyshyn, D. (2009). Improved footwear comfort reduces oxygen consumption during running. Footwear Science, 1(1), 25–29. doi:10.1080/19424280902993001

 Google Scholar

Souza, R. F., Rezende, P. E., Matos, D. G., Zanona, A. F., Silva, R. A., Schemly, P. A., … Aidar, F. J. (2018). Analysis of race performance on different floors using cushioned sneakers and barefoot. Motricidade, 14(S1), 142–148.

 Google Scholar

Sinclair, J., McGrath, R., Brook, O., Taylor, P. J., & Dillon, S. (2016). Influence of footwear designed to boost energy return on running economy in comparison to a conventional running shoe. Journal of Sports Sciences, 34(11), 1094–1098. doi:10.1080/02640414.2015.1088961

 PubMed Web of Science ®Google Scholar

Sinclair, J., Shore, H., & Dillon, S. (2016). The effect of minimalist, maximalist and energy return footwear of equal mass on running economy and substrate utilisation. Comparative Exercise Physiology, 12(1), 49–54. doi:10.3920/cep150029

 Web of Science ®Google Scholar