Ethical approval
Ethical approval was granted by the Isfahan University of Medical Sciences (IR.MUI.RESEARCH.REC.1398.451) and informed consent was obtained from all persons before their participation.
Recruitment
Participants were recruited from 15 health centers (one representative of each urban area) of Isfahan, Iran between April and November, 2020. Older people were deemed ineligible for the study if they were unable to ambulate for at least 10 m without an assistive device, scored < 7 for the Short Portable Mental Status Questionnaire, had diabetic foot syndrome, neurological diseases, or previously had lower extremity surgery. From the 984 potential participants, 584 met the inclusion criteria according to the information provided in their medical records. Following more detailed telephone screening, 240 were deemed eligible. These individuals were then randomly selected and contacted by telephone and invited into the study. If they declined or were ineligible, the next person from the randomisation list was contacted until the sample size was met.
Sample size
Sample size (n) was calculated using the sample size formula:
$$\mathrm n=\frac{z_{\mathit1\mathit-\alpha\mathit/\mathit2}^{\mathit2}p\left(\mathit1\mathit-p\right)}{d^{\mathit2}}$$
…where z is the confidence level (1.96 standard deviations; 95%), α is the alpha level (0.05), \(p\) is the estimated probability of having a foot problem (0.45) and \(d\) is the precision (0.06). This calculation identified that 264 participants would need to be recruited. However, due to the impact of the coronavirus pandemic, recruitment had to cease at 225 participants (94% of the eligible sample), and of these, 38 cases were excluded due to errors in the plantar pressure data. Therefore, the final study sample comprised 187 community dwelling older people (106 females) aged 62–90 years (mean 70.5 ± 5.2, body mass index 27.7 ± 4.1).
Foot and ankle structural and functional characteristics
Structural and functional characteristics of the foot and ankle were tested across the domains of foot posture, muscle strength, range of motion, tactile sensitivity, deformity, foot pain, and plantar pressure.
Foot posture was assessed using foot posture index (FPI), arch index (AI), and normalised navicular height truncated (NNHt). The FPI involved the rating of 6 criteria, the sum of which provided a single index of the pronated/supinated foot posture. The AI was calculated by the ratio of midfoot area to the foot (excluding toes) using the EMED pressure plate (novelGmbH, Munich, Germany, 2 sensor/cm2, 50Hz). NNHt represents the navicular height divided by truncated foot length (i.e. foot length excluding the toes) in bipedal standing.
Isometric muscle strength of the ankle (dorsiflexion, plantar flexion, inversion, and eversion) was measured with a hand-held dynamometer (Digital Force Gauge 5kg; accuracy 0.001 kg) mounted on an apparatus to ensure isometric contraction via the make-test. Hallux and lesser toe muscle strength were quantified using a previously developed protocol. Participants were instructed to push down as hard as possible on an EMED pressure platform. The test protocols have been described in detail elsewhere [5].
Two measures of foot and ankle passive range of motion, passive ankle dorsiflexion and hallux first metatarsophalangeal (MTP) joint extension, were performed via a single standard video camera (50 Hz, 25 fps) which was placed perpendicular to the plane of motion and three skin markers (based on the same goniometry protocol) employed to capture the range of motion. Frame by frame advance was used to identify the instance of the maximum range of motion. Kinovea software (https://www.kinovea.org/) was used to measure these angles. Tactile sensitivity at the ankle was assessed using a single Semmes–Weinstein-type pressure monofilament. The monofilament was applied three times to the lateral malleolus of the ankle while the participant kept their eyes closed.
Hallux valgus was documented using the Manchester scale, a reliable and valid clinical tool based on four photographs of the foot [9]. The presence of foot pain was determined with the Manchester Foot Pain and Disability Index (MFPDI) [10].
Foot function was assessed using barefoot plantar pressure analysis using the EMED-le pressure plate. Three trials were recorded for each participant’s dominant limb with a two-step gait initiation protocol at a comfortable walking speed. Following data collection, the novel scientific software v23 was used to calculate the pressure-time integral in the total foot, centre of pressure (COP) velocity of the total foot, and the centre of pressure excursion index (CPEI), a measure of the mediolateral shift in COP throughout the gait cycle.
Fear of falling and mobility assessment
The Falls Efficacy Scale International (FESI) was used to assess the level of concern of falling during 16 activities of daily living, including social activities that may contribute to the quality of life [11]. The level of concern for each item was scored using a four-point scale (1 = not at all concerned, 4 = very concerned) within a total score range of 16–64. Mobility was assessed using the Timed Up and Go (TUGT) test by measuring the time taken for the participant to stand up from a chair, walk 3m, turn around, walk back, and sit down. Three trials were recorded for each participant and averaged. The TUGT has good validity and reliability as a measure of mobility [12].
Statistical analysis
Statistical analyses were carried out using IBM Statistical Package for the Social Sciences (SPSS) (IBM Corporation, Armonk, NY) with a 5% level of significance. Descriptive statistics were used to provide an overview of the demographic variables. The Kolmogorov–Smirnov test was used to check the normality of the data. Pearson’s r linear correlation was used where the relationship between normally distributed parameters was assessed. Otherwise, Spearman’s rho correlation test was used. Independent samples t-tests were performed to evaluate differences in FESI and TUGT according to dichotomous variables. All variables significantly associated with the dependent variable were entered in two stepwise multiple linear regression models to determine their relative importance in explaining variance in FESI and TUGT. Variables were selected based on the results of the correlation results (r > 0.3) or t-test (p < 0.2) for dichotomous variables. Preliminary analyses were conducted to ensure no violation of the assumption of normality, linearity, multicollinearity, and homoscedasticity. The overall fit of linear regression models was quantified by R2.