Inter-segmental motions of the foot: differences between younger and older healthy adult females

This study was approved by the institutional review board, and all participants submitted informed consent prior to participation. The sample size was estimated as follows. We considered 2 degrees of difference in ISA between the older group and young control group would be significant, and estimated the expected standard deviation to be 3.5 degrees (α-error 0.05, β-error 0.2). The sample size was calculated to be 48 participants in each gender group [18]. Our previous study population for young healthy participants was composed of 50 participants in each gender group [18].

Volunteers were recruited from the local area. Participants were divided into an older group (60–69 years old) and younger group (20–35 years old). Inclusion criteria were (i) no history of fracture or surgery on the lower extremities; (ii) no subjective symptom such as pain or discomfort during gait; (iii) no observed radiographic features of progressed osteoarthritis (grade 2, 3, 4 osteoarthritis by Kellgren-Lawrence scale) in simple radiographs of the hip, knee and, ankle and foot (whole leg radiograph [19], foot anteroposterior and lateral radiograph); (iv) no history of cardiac or respiratory disease or uncorrected visual impairment; and (v) normal function of the foot and ankle (100 points of American Orthopaedic Foot & Ankle Society ankle-hindfoot questionnaire score).

For evaluation of inter-segmental foot motion, we used a foot model (Foot3D model) proposed by Henley et al. [15] with confirmed repeatability by Seo et al. [16], in which they added six additional markers (diameter: 3 mm) per foot to the conventional Cleveland Clinic low extremity marker set. The placement of the markers, definition of the coordinate systems based on these markers and the method calculating the joint rotation and arch parameters have been described previously [15, 16, 18]. In brief, placement of the markers was as follows: two markers were placed on the knee (medial [Knee medial] and lateral [Knee lateral] joint line of femoral condyle), three markers on the tibial shank (upper apex [Shank upper], lower front [Shank front] and lower rear [Shank rear] of the shank triangle at the lateral aspect of middle lower leg), two markers on the ankle (apex of the medial malleolus [Ankle medial] and lateral malleolus [Ankle lateral]), two markers on the calcaneus (on the line bisecting posterior aspect of the heel at the height of the toe marker [Heel] and just above the fat pad [Heel distal]), two markers on midfoot (navicular tuberosity [Navicular] and just proximal and superior to the base of the 5th metatarsal bone [Cuboid]) and four markers on the forefoot (dorsal metatarsal head just proximal to the 1st metatarsophalangeal joint [MTH1], dorsal web space just proximal between the 2nd and 3rd metatarsophalangeal joint [Toe], dorsal metatarsal head just proximal to the 5th metatarsophalangeal joint [MTH5], in the middle of the hallux nail bed [Hallux]) (Fig. 1).

Experimental procedures were the same as our previous studies [16, 18]. In brief, data of each subject was collected during a single visit to the laboratory. After explaining the procedures, we measured each participant’s demographic data including height, body weight, leg length, foot length and width. Range of joint motion (hip, knee, ankle, and metatarsal phalangeal joint) was measured.

The participants performed a five-minute warm-up protocol of comfortable walking. After warming up, each participant had 15 reflective markers placed on each side of foot and lower extremities. All procedures in marker placement were performed by one experienced operator. After the marker attachment, the walk practice was performed three times through the walkway. At first, static data were obtained in a calibration trial position with the foot flat on the ground. After the calibration trial, participants were asked to walk at their comfortable speed along an eight metre walkway with the knee and ankle markers removed. Gait data were collected using 12 cameras with an optical motion capture system (Motion Analysis Co., Santa Rosa. CA) at a sample rate of 120 Hz. Eva Real-Time software (EVaRT, Motion Analysis Co.) was used for real-time motion capture and for post-processing and tracking the marker data. Kinematic data of inter-segmental foot motion was collected and tracked using the Foot3D Multi-Segment Software (Motion Analysis Co., Santa Rosa. CA). Three representative strides from five separate trials were selected and the mean value was used for analysis.

For radiographic examinations, standing anteroposterior radiographs of the ankle and knee and weight-bearing anteroposterior and lateral radiographs of the foot and ankle were taken and reviewed. From the radiographs, the alignment of the lower extremity and the existence of pathologic findings such as arthritic change and previous fracture were checked. Non-existence of radiographic evidence of osteoarthritis was checked and confirmed by musculoskeletal radiologists.

The spatiotemporal gait parameters such as cadence, speed, stride length, step width, step time, and proportion of stance phase were calculated. Data of gait speed, stride length and width, foot length and width, arch height, and arch length were normalized with height of the subject to reflect the effect of body size [20].

To assess the inter-segmental position of foot (hindfoot relative to tibia, forefoot to hindfoot, and hallux to forefoot) during the gait cycle, we divided the whole gait cycle into 100 time points with 1% interval and collected inter-segmental angles at each time points. The start of the gait cycle was based on the first point of detection on the force plate. Three AMTI (Advanced Mechanical Technology Inc., Watertown, MA, USA) force plates were used to collect kinetic data. The sampling rate of force plate is 1200 Hz. Parameters calculated were as follows; (i) hindfoot relative to tibia: dorsiflexion (+) / plantarflexion (−), pronation (−) / supination (+), and internal (+) / external rotation (−); (ii) forefoot relative to hindfoot: dorsiflexion (+) / plantarflexion (−), pronation (−) / supination (+), and abduction (−) / adduction (+); (iii) hallux relative to forefoot: dorsiflexion (+) / plantarflexion (−) and valgus (−) / varus (+); and (iv) arch data: height, arch length, and arch index (arch height/arch length). The X-axis is the motion of the sagittal plane, the Y-axis is the motion of the coronal plane, and the Z-axis is the motion of the transverse plane.

To evaluate age-related differences in the inter-segmental motion of the foot, the inter-segmental angles (position) at the middle of eight phases of gait (initial contact [0–2%], load response [6–8%], mid-stance [21–23%], terminal stance [40–42%], pre-swing [55–57%], initial swing [67–69%], mid-swing [80–82%], and terminal-swing [93–95%]) were measured and the change of inter-segmental angle (motion) between phases were calculated [3, 21]. Range of inter-segmental angles during the whole cycle of the gait was evaluated by the minimum value, maximum value, and gap between minimum and maximum values of the inter-segmental angle.

To evaluate effect of gait speed on the inter-segmental motion of the foot, subgroup analysis was performed according to gait speed. Both the young and older group were divided into faster and slower groups. The cut-off value was 1.25 m/s in the young group and 1.10 m/s in the older group, and individuals of same speed (1.10 ~ 1.25 m/s) of the young and older groups were compared.

The coefficients of multiple correlations (CMC) were evaluated in order to assess the similarity of kinematic curve patterns between groups [22, 23]. We interpreted that 0.65 ≤ CMC (R) < 0.75 suggests moderate similarity, 0.75 ≤ CMC (R) < 0.85 suggests good similarity, 0.85 ≤ CMC (R) < 0.95 suggests very good similarity, and CMC (R) ≥ 0.95 suggests excellent similarity [18, 24].

Student t-tests were performed to assess gender differences in ranges of each inter-segmental motion, with p-values less than 0.05 regarded as significant. For analysis of ISA at specific gait phases and the change of ISA between phases, we chose to make all comparisons of joint kinematics at a level of p < 0.007 to adjust for multiple tests after a Bonferroni correction (a family wise 5% overall error rate). All statistics were performed using SPSS version 21 for Windows (SPSS Inc., Chicago, IL).

After ruling out 13 participants according to exclusion criteria (grade of Kellgren-Lawerence was more than grade 2 or AOFAS score was not 100), a hundred symptom-free females who were tested at the Laboratory of Human Motion Analysis in Seoul National University Hospital were included in this study. They were divided into young (n = 50, 20–35 years old) [18] and older (n = 50, 60–69 years old) group and analyzed.

Participant characteristics are presented in Table 1. The older group had shorter height, higher body mass index, shorter foot length, and wider foot width than the young group, which is consistent with anthropometric data of Korean population in nation-wide governmental survey (http://​sizekorea.​kats.​go.​kr/​).

Basic temporal gait parameters are presented in Table 2. The speed, stride length, and step width were significantly lower in older females. After being normalized with height, stride length was still significantly lower in older females, but speed and step width were not significantly different. The cadence (steps/min) was similar between young and older females. The proportion of the stance phase in a gait cycle was longer in older females.

The inter-segmental foot motions of healthy older females during the whole gait cycle are presented in ranges (average +/− 1 standard deviation) in Fig. 2. The overall pattern and inflection points of kinematic curves of inter-segmental foot motions during whole gait cycle were quite similar between young and older females. In the CMC analysis by 1% interval of gait cycle, curve patterns from older and young females showed good to excellent similarity in most parameters except for forefoot coronal motion and foot progression angle (Table 3).

The differences between older and young females were most prominent in the range of inter-segmental angles during the whole cycle (Table 4). Range of motion (ROM) was significantly decreased in older females, even though there was no radiographic evidence of arthritis in their joints, compared to young females. ROM in sagittal (p < 0.001) and transverse (p = 0.001) plane motion of the hallux, sagittal plane (p = 0.023) of the forefoot was lower in older females. ROM in coronal (p = 0.014) plane of the forefoot, and sagittal (p < 0.001) plane of the hindfoot was lower in older females.

The inter-segmental angles (position) of the foot segment relative to proximal segment at each phase of whole gait cycle and the change of inter-segmental angles (motion) between adjacent gait phases are presented in Fig. 3. In hallux kinematics relative to the forefoot, the hallux valgus angle was larger in older adults throughout the whole gait cycle. The dorsiflexion motion of the hallux in the pre-swing phase was significantly lower in older females (older 27.9°, young 32.0°) (Fig. 3).

In forefoot kinematics relative to the hindfoot, the forefoot was more dorsiflexed in pre-swing and initial swing phase in older females. The motion in pre-swing phase was significantly lower in older females (older 5.8°, young 7.7°). In coronal plane, the forefoot was significantly supinated in older females. No significant differences were seen in transverse plane motion (Fig. 3).

In hindfoot kinematics relative to the tibia, plantar flexion motion in pre-swing phase was significantly lower in older females (older 10.0°, young 13.9°). In coronal plane, significantly pronated positions were noted in older females. No significant differences were seen in transverse plane motion (Fig. 3).

When subgroup analysis was performed according to gait speed, inter-segmental motion of the foot was not different between faster and slower group in both young and older groups. The Additional file 1: Fig. S1 shows the groups of young adults with fast (over 1.25 m/s) and slow walking speeds (less than 1.25 m/s). It also shows the group of older adults with fast (over 1.10 m/s) and slow (less than 1.10 m/s) walking speeds (Additional file 2: Fig. S2). When we compared young and older females with similar gait speed (1.10–1.25 m/s), differences between the young and older groups remained the similar (Additional file 3: Fig. S3).