Loading [MathJax]/jax/output/SVG/jax.js
Case report Special Issues

Combined face-to-face and telerehabilitation physiotherapy management in a patient with chronic pain related to piriformis syndrome: A case report

  • Received: 16 April 2024 Revised: 08 May 2024 Accepted: 22 May 2024 Published: 03 June 2024
  • Piriformis syndrome is characterised as being one of the possible causes of sciatic pain, as well as being a syndrome that tends to become chronic. Because of this, different types of treatments for both this syndrome and the associated pain it causes have been investigated over the years. Nowadays, the evidence increasingly favors treating chronic pain with a multimodal physiotherapy treatment based on a biobehavioral approach. This case report describes the physiotherapy intervention performed on a 44-year-old woman with chronic pain related to piriformis syndrome. The multimodal intervention lasted for 9 weeks with a total of 12 sessions and included manual therapy, therapeutic exercise, neural mobilization, and pain neuroscience education. Initially, the pain characteristics alongside somatosensory, motor-functional, and psychosocial factors were assessed. Due to the Covid-19 pandemic, only the pain characteristics and psychosocial factors could be reassessed post intervention. Improvements in both pain characteristics and psychosocial factors were achieved, resulting in a better general condition of the patient. This case report suggests that a multimodal physiotherapy intervention adapted to telerehabilitation was an effective option to improve the pain symptoms and psychosocial factors in the reported patient during the Covid-19 pandemic. Therefore, this may be a treatment option in patients with chronic pain that are in a situation where face-to-face physiotherapy is not feasible.

    Citation: Carlos Forner-Álvarez, Ferran Cuenca-Martínez, Alba Sebastián-Martín, Celia Vidal-Quevedo, Mónica Grande-Alonso. Combined face-to-face and telerehabilitation physiotherapy management in a patient with chronic pain related to piriformis syndrome: A case report[J]. AIMS Medical Science, 2024, 11(2): 113-123. doi: 10.3934/medsci.2024010

    Related Papers:

    [1] Elizabeth Procter-Gray, Barbara Olendzki, Kevin Kane, Linda Churchill, Rashelle B. Hayes, Annabella Aguirre, Hyung-joo Kang, Wenjun Li . Comparison of Dietary Quality Assessment Using Food Frequency Questionnaire and 24-hour-recalls in Older Men and Women. AIMS Public Health, 2017, 4(4): 326-346. doi: 10.3934/publichealth.2017.4.326
    [2] Wenjun Li, Elizabeth Procter-Gray, Gretchen A. Youssef, Scott E. Crouter, Jie Cheng, Kristen Brown, Linda Churchill, Anthony Clarke, Judith K. Ockene, Michelle F. Magee . Racial Differences in Neighborhood Perceptions and their Influences on Physical Activity among Urban Older Women. AIMS Public Health, 2017, 4(2): 149-170. doi: 10.3934/publichealth.2017.2.149
    [3] Jane Law . Exploring the Specifications of Spatial Adjacencies and Weights in Bayesian Spatial Modeling with Intrinsic Conditional Autoregressive Priors in a Small-area Study of Fall Injuries. AIMS Public Health, 2016, 3(1): 65-82. doi: 10.3934/publichealth.2016.1.65
    [4] Robby Carlo A. Tan, Kyler Kenn M. Castilla, Angely P. Garcia, Kristine D. Macatangay, Shelley Ann F. de la Vega, Michael E. Serafico, Marco Mensink, Lisette de Groot . An overview of the healthy aging program for PinoY (HAPPY) senior citizens research: A cross-sectional study among community-dwelling older Filipinos. AIMS Public Health, 2025, 12(2): 536-556. doi: 10.3934/publichealth.2025029
    [5] Gerhard Ruedl, Markus Posch, Elena Pocecco, Katja Tecklenburg, Birgit Schliernzauer, Michael D. Kennedy, Martin Faulhaber, Martin Burtscher . Association of personal and equipment-related factors on ACL injury risk in alpine skiers with cautious or risk-taking behaviour: A case-control study. AIMS Public Health, 2023, 10(2): 348-359. doi: 10.3934/publichealth.2023026
    [6] Sameer Badri Al-Mhanna, Alexios Batrakoulis, Abdulrahman M. Sheikh, Abdulaziz A. Aldayel, Abdulwali Sabo, Mahaneem Mohamed, Hafeez Abiola Afolabi, Abdirizak Yusuf Ahmed, Sahra Isse Mohamed, Mehmet Gülü, Wan Syaheedah Wan Ghazali . Impact of COVID-19 lockdown on physical activity behavior among students in Somalia. AIMS Public Health, 2024, 11(2): 459-476. doi: 10.3934/publichealth.2024023
    [7] Kate E. Thomason, Gisli Gudjonsson, Elaine German, Robin Morris, Susan Young . Sociomoral Reasoning in Adults with ADHD: A Pilot Study. AIMS Public Health, 2014, 1(3): 147-159. doi: 10.3934/publichealth.2014.3.147
    [8] Lucy K. Lewis, Toby Hunt, Marie T. Williams, Coralie English, Tim S. Olds . Sedentary Behavior in People with and without a Chronic Health Condition: How Much, What and When?. AIMS Public Health, 2016, 3(3): 503-519. doi: 10.3934/publichealth.2016.3.503
    [9] Sandra Racionero-Plaza, Itxaso Tellado, Antonio Aguilera, Mar Prados . Gender violence among youth: an effective program of preventive socialization to address a public health problem. AIMS Public Health, 2021, 8(1): 66-80. doi: 10.3934/publichealth.2021005
    [10] Klaus Greier, Clemens Drenowatz, Theresa Bischofer, Gloria Petrasch, Carla Greier, Armando Cocca, Gerhard Ruedl . Physical activity and sitting time prior to and during COVID-19 lockdown in Austrian high-school students. AIMS Public Health, 2021, 8(3): 531-540. doi: 10.3934/publichealth.2021043
  • Piriformis syndrome is characterised as being one of the possible causes of sciatic pain, as well as being a syndrome that tends to become chronic. Because of this, different types of treatments for both this syndrome and the associated pain it causes have been investigated over the years. Nowadays, the evidence increasingly favors treating chronic pain with a multimodal physiotherapy treatment based on a biobehavioral approach. This case report describes the physiotherapy intervention performed on a 44-year-old woman with chronic pain related to piriformis syndrome. The multimodal intervention lasted for 9 weeks with a total of 12 sessions and included manual therapy, therapeutic exercise, neural mobilization, and pain neuroscience education. Initially, the pain characteristics alongside somatosensory, motor-functional, and psychosocial factors were assessed. Due to the Covid-19 pandemic, only the pain characteristics and psychosocial factors could be reassessed post intervention. Improvements in both pain characteristics and psychosocial factors were achieved, resulting in a better general condition of the patient. This case report suggests that a multimodal physiotherapy intervention adapted to telerehabilitation was an effective option to improve the pain symptoms and psychosocial factors in the reported patient during the Covid-19 pandemic. Therefore, this may be a treatment option in patients with chronic pain that are in a situation where face-to-face physiotherapy is not feasible.



    Falls are a major health concern for older adults aged 65 years or older. In the United States, about one-third of older adults fall each year, with one-fifth reporting severe fall-related injuries such as fractures or head traumas [1],[2]. The medical cost of treating fall-related injuries is projected to increase from $35 in 2012 to $101 billion in 2030 [3]. Falls also affect older adults' functional capacities, reduce both mobility and quality of life, and even increase mortality rates [1],[4],[5]. In 2021, there were 38,742 deaths as a result of unintentional falls in older adults, and it is estimated that seven older adults may die from falls every hour by 2030 [6],[7]. Furthermore, the profiles for indoor and outdoor falls are quite different. Indoor falls occur more often among frail older adults, whereas outdoor falls are more frequent among active older adults [8],[9]. Only one study found that women reported lower outdoor fall rates but higher injurious indoor fall rates than men [10]. Walking is the most common type of physical activity and a recommended activity for community-dwelling older adults as it is convenient, cost-effective, and adaptable. Walking can serve two main purposes: utilitarian and recreation. Utilitarian walking refers to walking for essential errands or daily life tasks such as going to the grocery store, post office, or bank. Recreational walking refers to walking for exercise or leisure [11]. Adults do less utilitarian walking but more recreational walking as they age [12]. Gender differences in recreational walking are complex; some studies found that more older men did recreational walking than women, but others did not find any differences [13],[14].

    However, the association between recreational walking and indoor and outdoor fall rates has not been well-studied, and the possible gender differences in these relationships remain unknown. Using data from the Healthy Aging and Neighborhood Study (HANS) prospective cohort study, we estimated gender differences in the association between recreational walking and indoor and outdoor falls among community-dwelling older adults living in Massachusetts, USA. The three hypotheses are as follows: a) Hypothesis a: higher frequency of recreational walking is associated with lower rates of indoor and outdoor fall; b) Hypothesis b: The association between recreational walking and indoor fall rate is stronger in women than men; c) Hypothesis c: The association between recreational walking and outdoor fall rate is stronger in men than women.

    HANS is a longitudinal cohort study conducted in central and northeastern Massachusetts, USA, that started in 2018. The details about study recruitment and procedures have been published elsewhere [15]. Briefly, individuals were eligible if they were 65 years of age or older, planned to live in the area for at least three years, and were able to walk with or without assistive devices. Individuals were excluded if they were unable to do interviews or questionnaires due to visual or auditory impairments, not living independently, had severe memory issues measured using the Short Portable Mental Status Questionnaire (SPMSQ), were unable to do all study-related activities independently, or did not report their fall status during the study (<5%). Direct mailing was the primary method of recruiting participants. Recruitment presentations were given in group settings such as senior centers, older adults' day care centers, and veterans' organizations. Individuals expressing interest in the study were contacted by research staff who provided details about the study and conducted eligibility screening. A total of 716 community-dwelling adults were enrolled in the study during the period 2018–2023. The study protocol was approved by the University of Massachusetts Lowell Institutional Review Board (#: 20-142-LI-XPD; 21-017-LI-XPD). All study participants provided written informed consent.

    A fall was defined as unintentionally coming to rest on the ground or a lower surface. Information related to falls and associated conditions was obtained from a monthly falling calendar followed by a standardized questionnaire, both administered by trained professional research staff. Participants used the monthly falling calendar to record daily if they had fallen and mailed back the monthly falling calendar to the study office at the end of each month. Research staff then called participants who had reported falls and asked for details about their fall(s) including circumstances, location, footwear worn, potential influence of lighting or medication, and whether they were injured and went to the hospital. An indoor fall was defined as occurring inside any building other than a parking garage, and an outdoor fall was defined as occurring outside any building or in a parking garage. The number of indoor and outdoor falls was collected from June 12, 2018, to December 31, 2023.

    Recreational walking was defined as walking for exercise for at least 10 min in the participants' neighborhood, not including walking to stores or businesses. Participants were asked about their frequency of recreational walking habits in the past month, with the following distribution: 20.67% did not walk at all, 7.54% walked less than once a month, 10.89% walked 1–3 times a month, 11.59% walked 1–2 times per week, 18.16% walked 3–4 times per week, 12.29% walked 5–6 times per week, and 18.85% walked at least once a day. The information about recreational walking was collected at participants' baseline visits. For analysis, the responses were summarized into two groups, in which 0 corresponded to less than once per week, and 1 corresponded to at least once per week.

    Sociodemographic variables included participant's age, self-reported gender (women, men, other), self-reported race and ethnicity, geographic region (urban, suburban, rural), household income (<$50K, $50K or more, unknown), and educational attainment (high school or lower, college, beyond college). Physical health variables included self-rated health (good-excellent, poor-fair), body mass index (BMI) (<25 kg/m2, 25–29.9 kg/m2, ≥30 kg/m2), the number of medical comorbidities, and bodily pain (none-mild, moderate-severe). Functional status was assessed by the five-timed chair stand test (<15.96 s, ≥15.96 s), hand grip [male: low (<30 kg), medium (30–36 kg), high (>36 kg); female: low (<20 kg), medium (20–23 kg), high (>23 kg)], activities of daily living (ADL) [16] (no difficulty, at least some difficulty), and instrumental activities of daily living (IADL) [17] (no difficulty, at least some difficulty). Mental health variables included the Center for Epidemiologic Studies Depression Scale (CES-D) [18], the Beck Anxiety Inventory (BAI) [19], the Perceived Stress Scale (PSS-4) [20], and the modified Brief Resilience Scale [21]. Lifestyle behaviors were evaluated using the Physical Activity Scale for the Elderly (PASE) [22], measures of social support and social activity (≤17, >17 times per month) [23], and by determining whether participants drank alcoholic beverages (no, yes), smoked (no, yes), or lived alone (no, yes). The level of concern about falling was measured by the Falls Efficacy Scale International (FES-I) [24].

    Participant characteristics were summarized overall and stratified by gender. Continuous variables were described using means and standard deviations (Mean ± SD); their differences by gender were compared using t-tests or Wilcoxon rank-sum tests. Categorical variables were described using frequency and percentages [n (%)], and gender differences were compared using Chi-squared or Fisher exact tests.

    Mixed effects negative binomial models were performed to estimate gender differences in associations between recreational walking and rates of outdoor and indoor falls, separately for men and women. Unadjusted negative binomial models were used to estimate the crude relationships between recreational walking and indoor/outdoor falls (Model 1). Model 2 included all covariables to estimate the adjusted associations between recreational walking and indoor/outdoor falls. An interaction term between female sex and recreational walking was added into Model 2 to estimate gender differences in the associations (Model 3). For a parsimonious model, we included age and race/ethnicity as a priori variables, and other covariables with statistically significant associations with indoor/outdoor fall rates were retained. Using a stepwise elimination approach, statistically insignificant covariables were eliminated sequentially. Collinearity was assessed using variance inflation factor (VIF) and generalized VIF, with a threshold of VIF/GVIF > 10 indicating a collinearity issue. The GVIF was performed using the car package in R version 4.1.1.

    The percentages of missing values for covariates ranged from 0% to 1.7% (1.7% for comorbidity variables and less than 1% for other covariates). Participants with complete data were included in models at each level of adjustment. Model fit was evaluated by the Akaike information criterion (AIC) and the Bayesian information criterion (BIC). Data were analyzed using Stata 18 (Stata Corp., College Station, TX, USA). Two-sided p-values < 0.05 were considered statistically significant.

    Among the 716 participants, 394 (55.0%) were female and 322 (45.0%) were male; no participants selected the “other” category. Additionally, 464 (64.9%) self-reported as non-Hispanic White, 378 (52.9%) lived in urban areas, 244 (34.1%) in suburban areas, and 93 (13.0%) in rural areas, and the mean (SD) age of participants at baseline visits was 74.08 (6.29) years old. Compared to men, a higher proportion of women reported lower household income, lower educational attainment, fair or poor health, poorer physical function, and lived alone. Moreover, women had more anxiety symptoms, more medical comorbidities, and greater concern of falling, as well as lower levels of physical activity and resilience (Table 1). About 61% of participants reported they engaged in recreational walking at least once a week. The prevalence of it was 60.4% among women and 61.5% among men, and there were not any significant gender differences in the frequency of recreational walking (p = 0.77).

    The mean (SD) follow-up for women was 2.20 (0.08) years, 2.01 (0.08) years for men, and there were no gender differences in follow-up time (p = 0.10). A total of 353 participants (49.30%) reported experiencing at least one fall during the study period. Compared to men, women had a significantly lower rate of outdoor falls (32 vs. 40 per 100 person-years, p = 0.01). Gender differences in the rate of indoor falls were not statistically significant (women vs. men: 31 vs. 34 per 100 person-years, p = 0.34) (Table 1).

    Table 2 shows the associations between recreational walking and indoor fall rates. More frequent recreational walking was significantly associated with a lower indoor fall rate (Model 1); the association remained significant after adjusting for covariables (Model 2). Both Models 3 and 4 found that the interaction between female sex and recreational walking was significant, indicating gender differences in the associations between recreational walking and indoor fall rates. In the parsimonious model (Model 4), higher rates of indoor falls were associated with non-Hispanic White race and ethnicity [IRR (95% CI): 2.36 (1.72, 3.25)], a higher level of anxiety [1.05 (1.03, 1.07)], and a greater concern about falling [1.03 (1.01, 1.05)]. Obesity was associated with a lower rate of indoor falls 0.70 (0.50, 1.00); being overweight did not show a significant association.

    In Model 4, for men, recreational walking was not significantly associated with indoor fall rate [IRR (95% CI): 0.90 (0.61, 1.32)]. However, women engaging in recreational walking had a 62% lower indoor fall rate [IRR (95% CI): 0.38 (0.21, 0.71)] than those who did not engage. Model 4 had the lowest BIC, indicating the best model performance.

    Recreational walking was not significantly associated with outdoor fall rates in both unadjusted and adjusted models [unadjusted IRR: 1.14 (0.86, 1.51); adjusted IRR: 1.09 (0.81, 1.46)]. No significant interaction between females and recreational walking was found. However, participants who self-reported as non-Hispanic White or had difficulties in ADL were more likely to experience outdoor falls (Table 3).

    Table 1.  Characteristics of participants (overall and by gender).
    Project Total (N = 716) Women (N = 394) Men (N = 322) p-value for gender diff.
    Sociodemographic variables
    Age at baseline visit, y, mean (SD) 74.08 (6.29) 73.91 (6.23) 74.28 (6.37) 0.48
    Race and ethnicity, n (%) <0.001
    Non-Hispanic White 464 (64.9) 235 (59.6) 229 (71.3)
    Others1 251 (35.1) 159 (40.4) 92 (28.7)
    Education, n (%) <0.001
    High school or lower 200 (27.9) 127 (32.2) 73 (22.7)
    College 321 (44.8) 181 (45.9) 140 (43.5)
    Beyond college 195 (27.2) 86 (21.8) 109 (33.9)
    Household income, n (%) <0.001
    <$50K 278 (38.8) 180 (45.7) 98 (30.4)
    $50K or more 340 (47.5) 150 (38.1) 190 (59.0)
    Unknown 98 (13.7) 64 (16.2) 34 (10.6)
    Areas, n (%) 0.12
    Rural 93 (13.0) 43 (10.9) 50 (15.6)
    Suburban 244 (34.1) 132 (33.5) 112 (34.9)
    Urban 378 (52.9) 219 (55.6) 159 (49.5)
    Physical health
    BMI, n (%) 0.01
    <25 kg/m2 212 (29.8) 135 (34.6) 77 (24.0)
    25–29.9 kg/m2 294 (41.4) 144 (36.9) 150 (46.7)
    ≥30 kg/m2 205 (28.8) 111 (28.5) 94 (29.3)
    # of medical comorbidities, mean (SD) 1.83 (1.32) 2.05 (1.39) 1.56 (1.16) <0.001
    Bodily pain past four weeks, n (%) 0.05
    None-mild 535 (74.8) 283 (72.0) 252 (78.3)
    Moderate-severe 180 (25.2) 110 (28.0) 70 (21.7)
    Self-rated health, n (%) <0.001
    Good-excellent 566 (79.1) 292 (74.1) 274 (85.1)
    Poor-fair 150 (20.9) 102 (25.9) 48 (14.9)
    Functional status
    Five-timed chair stand test2, n (%)
    High function 454 (63.4) 251 (63.7) 203 (63.0) 0.86
    Low function 262 (36.6) 143 (36.3) 119 (37.0)
    ADL, n (%)
    No difficulty 580 (81.2) 311 (79.1) 269 (83.8) 0.11
    At least some difficulty 134 (18.8) 82 (20.9) 52 (16.2)
    IADL, n (%)
    No difficulty 417 (58.2) 200 (50.8) 217 (67.4) <0.001
    At least some difficulty 299 (41.8) 194 (49.2) 105 (32.6)
    Hand grip (kg)3, n (%) 0.73
    Low 225 (31.6) 128 (32.7) 97 (30.2)
    Medium 240 (33.7) 132 (33.7) 108 (33.6)
    High 248 (34.8) 132 (33.7) 116 (36.1)
    Lifestyle behaviors
    Recreational walking, n (%) 0.77
    Less once/week 280(39.1) 156 (39.6) 124 (38.5)
    At least once/week 436(60.9) 238 (60.4) 198 (61.5)
    Current drinking alcohol, n (%) <0.001
    No 277 (38.8) 174 (44.3) 103 (32.1)
    Yes 437 (61.2) 219 (55.7) 218 (67.9)
    Current smoker, n (%) 0.14
    No 676 (94.5) 377 (95.7) 299 (93.1)
    Yes 39 (5.5) 17 (4.3) 22 (6.9)
    Live alone, n (%) <0.001
    No 517 (72.3) 260 (66.0) 257 (80.1)
    Yes 198 (27.7) 134 (34.0) 64 (19.9)
    PASE, mean (SD) 1.38 (0.79) 1.30 (0.80) 1.49 (0.77) <0.001
    Social support, mean (SD) 3.00 (0.93) 3.00 (0.89) 3.00 (0.97) 0.59
    Social activity4 0.06
    Fewer 376 (52.6) 194 (49.4) 182 (56.5)
    More 339 (47.4) 199 (50.6) 140 (43.5)
    Mental health
    PSS-4, mean (SD) 3.07 (2.73) 3.08 (2.75) 3.06 (2.71) 0.95
    Resilience, mean (SD) 3.80 (0.75) 3.77 (0.76) 3.85 (0.74) 0.05
    CES-D, mean (SD) 6.71 (6.95) 7.02 (7.26) 6.33 (6.53) 0.40
    BAI, mean (SD) 6.18 (7.02) 6.66 (7.01) 5.58 (7.00) <0.001
    Fall-related variables
    FES-I, mean (SD) 23.99 (8.48) 25.45 (9.05) 22.21 (7.36) <0.001
    Indoor fall rate (per 100 person-years) 32 31 34 0.34
    Outdoor fall rate (per 100 person-years) 36 32 40 0.01

    Note:1 Others in this study included 143 (20%) Asian, 76 (10.6%) Hispanic, and 33 (4.6%) unknown. 2 The cutoff point for the five-timed chair stand test was selected based on the mean value. Low function vs. high function was defined as <15.96 s vs. ≥15.96 s. 3 The cutoff point of hand grip was selected based on its distribution. Low function vs. medium function vs. high function was defined as <30 kg, 30–36 kg, >36 kg among men; <20 kg, 20–23 kg, >23 kg among women. 4 Social activity was measured using the sum of monthly frequency of activities. Fewer activities vs. more activities was defined as ≤17 vs. >17 times per month.

     | Show Table
    DownLoad: CSV
    Table 2.  Associations between recreational walking and indoor fall rates among older adults.
    Project Indoor fall rate
    Model 1 IRR (95%CI) (N = 716) Model 2 IRR (95%CI) (N = 686) Model 3 IRR (95%CI) (N = 686) Model 4 IRR (95%CI) (N = 709)
    Female 0.89 (0.67, 1.17) 1.17 (0.81, 1.69) 1.21 (0.84, 1.76)
    Recreational walking 0.60 (0.45,0.79) 0.69 (0.52, 0.90) 0.93 (0.63, 1.37) 0.90 (0.61, 1.32)
    Female × Recreational walking 0.56 (0.33, 0.95) 0.52 (0.31, 0.87)
    Sociodemographic
    Age 1.01 (0.99, 1.04) 1.01 (0.99, 1.04) 1.01 (0.99, 1.03)
    non-Hispanic White (ref: others) 2.85 (1.90, 4.26) 2.97 (1.98, 4.45) 2.36 (1.72, 3.25)
    College (ref: high school or less) 1.33 (0.96, 1.86) 1.30 (0.93, 1.82)
    Beyond college (ref: high school or lower) 1.49 (1.00, 2.22) 1.42 (0.95, 2.12)
    Household income ≥ 50K) 1.05 (0.73, 1.50) 1.03 (0.72, 1.47)
    Household income unknown (ref: <$50K) 0.68 (0.44, 1.05) 0.68 (0.44, 1.05)
    Suburban (ref: rural area) 0.98 (0.61, 1.58) 0.97 (0.60, 1.56)
    Urban (ref: rural area) 1.41 (0.88, 2.25) 1.40 (0.87, 2.23)
    Physical health
    25–29.9 kg/m2 (ref: <25 kg/m2) 0.87 (0.63, 1.20) 0.86 (0.62, 1.19) 0.88 (0.64, 1.21)
    ≥30 kg/m2 (ref: <25 kg/m2) 0.69 (0.48, 1.00) 0.67 (0.46, 0.96) 0.70 (0.50, 1.00)
    # of medical comorbidities 1.04 (0.92, 1.17) 1.03 (0.91, 1.16)
    Moderate-severe body pain (ref: none-mild body pain) 0.94 (0.67, 1.33) 0.96 (0.68, 1.35)
    Poor-fair health (ref: good-excellent health) 1.12 (0.71, 1.77) 1.13 (0.72, 1.78)
    Functional status
    Low function in five-timed chair stand test (ref: high function) 0.95 (0.71, 1.27) 0.95 (0.71, 1.26)
    At least some difficulty in ADL (ref: no difficulty) 1.00 (0.69, 1.44) 1.00 (0.69, 1.45)
    At least some difficulty in IADL (ref: no difficulty) 0.92 (0.65, 1.30) 0.92 (0.66, 1.30)
    Medium group in hand grip (ref: low) 1.15 (0.82, 1.62) 1.20 (0.85, 1.69)
    High group in hand grip (ref: low) 1.12 (0.78, 1.61) 1.16 (0.81, 1.67)
    Lifestyle behaviors
    Current drinking alcohol (ref: not drinking) 0.95 (0.70, 1.31) 0.91 (0.67, 1.25)
    Current smoker (ref: not smoking) 1.18 (0.71, 1.94) 1.15 (0.70, 1.89)
    Living alone (ref: not living alone) 0.97 (0.71, 1.32) 1.00 (0.73, 1.36)
    PASE 0.85 (0.70, 1.04) 0.86 (0.70, 1.05)
    Social support 1.01 (0.86, 1.18) 1.01 (0.86, 1.18)
    More social activities (ref: fewer social activities) 0.88 (0.67, 1.16) 0.92 (0.70, 1.21)
    Mental Health
    PSS-4 1.00 (0.94, 1.06) 0.99 (0.94, 1.06)
    Resilience 1.23 (1.01, 1.48) 1.20 (0.99, 1.45)
    CES-D 1.02 (1.00, 1.05) 1.02 (1.00, 1.05)
    BAI 1.05 (1.02, 1.07) 1.05 (1.02, 1.07) 1.05 (1.03, 1.07)
    Fall-related variables
    FES-I 1.03 (1.00, 1.05) 1.02 (1.00, 1.05) 1.03 (1.01, 1.05)
    Model fit
    AIC 2244.52 2241.79 2252.55
    BIC 2435.81 2438.70 2320.36

    Note: Model 1: unadjusted association between recreational walking and indoor falls; Model 2: model 1 + covariables; Model 3: model 2 + interaction between female and recreational walking; Model 4: parsimonious model.

     | Show Table
    DownLoad: CSV
    Table 3.  Associations between recreational walking and outdoor fall rate among older adults.
    Project Outdoor fall rate
    Model 1 IRR (95% CI) (N = 716) Model 2 IRR (95% CI) (N = 686) Model 3 IRR (95% CI) (N = 686)
    Female 0.72 (0.54, 0.97) 0.64 (0.41, 1.00)
    Recreational walking 1.14 (0.86, 1.51) 1.09 (0.81, 1.46) 0.99 (0.66, 1.47)
    Female × Recreational walking 1.23 (0.70, 2.15)
    Sociodemographic
    Age 0.98 (0.96, 1.01) 0.98 (0.96, 1.01)
    Non-Hispanic White (ref: others) 2.90 (1.89, 4.45) 2.86 (1.86, 4.39)
    College (ref: high school or less) 0.92 (0.64, 1.31) 0.93 (0.65, 1.33)
    Beyond college (ref: high school or less) 1.17 (0.78, 1.75) 1.19 (0.79, 1.79)
    Household income ≥50K) 0.97 (0.66, 1.43) 0.98 (0.66, 1.44)
    Household income unknown (ref: <$50K) 1.00 (0.66, 1.51) 1.00 (0.66, 1.51)
    Suburban (ref: rural area) 0.86 (0.57, 1.32) 0.86 (0.57, 1.32)
    Urban (ref: rural area) 0.97 (0.63, 1.50) 0.97 (0.63, 1.50)
    Physical health
    25–29.9 kg/m2 (ref: <25 kg/m2) 0.64 (0.46, 0.91) 0.65 (0.46, 0.91)
    ≥30 kg/m2 (ref: <25 kg/m2) 0.46 (0.31, 0.69) 0.47 (0.32, 0.70)
    # of medical comorbidities 1.01 (0.89, 1.15) 1.01 (0.89, 1.16)
    Moderate-severe body pain (ref: none-mild body pain) 1.42 (0.96, 2.09) 1.42 (0.96, 2.09)
    Poor-fair health (ref: good-excellent health) 0.98 (0.56, 1.72) 0.97 (0.55, 1.71)
    Functional status
    Low function in five-timed chair stand test (ref: high function) 0.88 (0.64, 1.20) 0.88 (0.64, 1.20)
    At least some difficulty in ADL (ref: no difficulty) 1.54 (1.01, 2.36) 1.54 (1.00, 2.36)
    At least some difficulty in IADL (ref: no difficulty) 0.75 (0.51, 1.10) 0.75 (0.51, 1.10)
    Medium group in hand grip (ref: low) 1.24 (0.84, 1.81) 1.22 (0.83, 1.80)
    High group in hand grip (ref: low) 1.23 (0.83, 1.82) 1.22 (0.82, 1.80)
    Lifestyle behaviors
    Current drinking alcohol (ref: not drinking) 1.16 (0.83, 1.63) 1.17 (0.83, 1.64)
    Current smoker (ref: not smoking) 1.33 (0.80, 2.24) 1.34 (0.80, 2.25)
    Living alone (ref: not living alone) 0.78 (0.55, 1.11) 0.78 (0.55, 1.11)
    PASE 1.13 (0.92, 1.38) 1.12 (0.92, 1.37)
    Social support 1.07 (0.90, 1.29) 1.07 (0.90, 1.29)
    More social activities (ref: fewer social activities) 0.92 (0.70, 1.22) 0.91 (0.69, 1.21)
    Mental Health
    PSS-4 1.01 (0.94, 1.09) 1.01 (0.94, 1.09)
    Resilience 0.93 (0.76, 1.14) 0.93 (0.76, 1.14)
    CES-D 0.98 (0.96, 1.01) 0.98 (0.96, 1.01)
    BAI 1.03 (0.99, 1.06) 1.03 (0.99, 1.06)
    Fall-related variables
    FES-I 1.01 (0.99, 1.04) 1.01 (0.99, 1.04)
    Model fit
    AIC 2335.21 2336.70
    BIC 2526.49 2533.62

    Note: Model 1: unadjusted association between recreational walking and outdoor fall rate; Model 2: model 1 + covariables; Model 3: model 2 + interaction between female and recreational walking.

     | Show Table
    DownLoad: CSV

    This prospective cohort study provides novel information about gender differences in the relationships between recreational walking and rates of indoor and outdoor falls among community-dwelling older women and men. Key findings from the study included the following: a) a higher frequency of recreational walking was associated with a lower rate of indoor falls, but showed no effect on outdoor falls; b) women had a significant association between recreational walking and indoor fall rate that was not observed in men; c) non-Hispanic White race and ethnicity, fear of falling, and anxiety symptoms were associated with higher rates of indoor falls.

    Previous studies have found that mental health issues, poor physical function, and a higher burden of chronic diseases such as cardiovascular disease are risk factors for indoor falls [8],[25]. The effects of walking on these risk factors have been reported. Recreational walking has been shown to be associated with reduced mental health issues such as anxiety, depression, and stress [26][28]. Additionally, a study found that higher intensity of recreational walking was associated with better mental health [29]. The mechanism of the effects of recreational walking on mental health could involve a reduction in amygdala activity. The amygdala, responsible for processing emotional stimuli, becomes overactive under adverse conditions, such as re-exposure to traumatic reminders [30],[31]. Overactivity increases the risk of mental health issues such as anxiety, depression, and stress [31][33]. Research indicates that recreational walking can reduce amygdala activity, thereby improving mental health [34]. In terms of physical function and chronic diseases, systematic reviews have found that walking can reduce the risk factors of cardiovascular disease, such as lowering blood pressure and increasing aerobic capacity [35]. Furthermore, walking can improve physical function including increasing lower-body strength as well as static and dynamic balance [36],[37]. The positive effects on mental health, physical function, and cardiovascular diseases could provide potential explanations for the observed association between recreational walking and indoor fall rates.

    Consistent with previous studies, the current study did not find a significant association between recreational walking and outdoor fall rates [38]. This lack of association may be attributed to a complex interplay between the physical benefits of recreational walking and the impacts of environmental hazards on outdoor falls. While recreational walking is associated with better functional abilities and physical health, which could reduce rates of outdoor falls, these protective effects may not sufficiently counteract the impacts of environmental hazards on outdoor falls. Research has found that about 73% of outdoor falls were precipitated by environmental factors such as uneven or wet surfaces, tripping, or slipping on objects [8]. Therefore, even though older adults engaging in recreational walking have protective factors against outdoor falls, their exposure to environmental risks may counteract these benefits, contributing to the observed lack of significant association.

    The observed gender difference in the relationship between recreational walking and indoor fall rate is another important finding, which could be explained by gender differences in walking companionship. Compared to men, women were more likely to do physical activity with their friends or participate in group walking [39],[40], which serves as both physical and social activities. Group walking not only increases physical activity but also provides psychological benefits that improve mental well-being [41][43]. These benefits include distracting from negative feelings and increased release of neurotransmitters including endorphins, dopamine, and serotonin, which are known to contribute to mental health [44][47].

    Furthermore, improved physical activity and mental health have been found to enhance cognitive function and functional ability and reduce fear of falling, all of which were associated with lower rates of indoor falls [25],[48][51]. Therefore, women's greater likelihood to engage in group walking may offer combined physical and mental benefits that men are less likely to experience, explaining the observed reduction in indoor fall rates among women.

    Non-Hispanic White ethnicity was associated with higher rates of indoor and outdoor falls, but the results were different from the Maintenance of Balance, Independent Living, Intellect, and Zest in the Elderly of Boston study (MOBILIZE Boston Study), which suggested no difference in indoor fall rates among non-Hispanic White older adults but an increased rate of outdoor falls [25]. This difference may stem from methodological differences, as the MOBILIZE Boston Study primarily focused on urban areas, whereas our HANS study included urban, suburban, and rural areas. Our HANS study found that the proportion of non-Hispanic White participants living in highly car-dependent suburban and rural areas was higher than that of the other groups, which potentially might have led to spending more time indoors, being less physically active, and having higher risks of indoor falls. Additionally, our models adjusted for covariables, including sociodemographic factors, amount of physical activity, functional status, and mental health. Moreover, our study showed that higher levels of fear of falling were associated with higher indoor fall rates, consistent with findings from prior studies [9]. Importantly, a meta-analysis found a positive association between anxiety and falls, but our specific findings suggested that anxiety symptoms may be related more to indoor rather than outdoor falls [52].

    This study has several strengths. First, it contributes to the understanding of gender differences in recreational walking and falls among community-dwelling older adults. Further, we found that gender differences should be considered in fall prevention; this study may be the first to provide estimates of differences between women and men in terms of recreational walking and its effect on indoor and outdoor falls. There are also some limitations in this study. First, recall bias or age-related memory issues could affect the reliability and accuracy of the collected data. To minimize this issue, monthly falling calendars and phone interviews shortly after a fall was reported were used to improve accuracy. Second, the measurement of recreational walking is based on frequency but lacks duration and intensity, which could also affect fall risks. Recreational walking was only collected at the baseline visit, and participants' recreational walking habits may change over the study period; this could affect the associations between recreational walking and falls. Finally, in addition to the risk factors considered in the current study, specific medical conditions, medication use, and environmental factors such as living space, public safety, or flat terrain could affect the associations. Further studies are needed to account for these factors.

    In conclusion, the primary finding of this study was that for older women, but not men, a higher frequency of recreational walking was associated with lower rates of subsequent indoor falls. These results provide specific information about gender differences in the relationship between recreational walking and indoor and outdoor fall rates and elucidate the social and health factors associated with indoor and outdoor falls. These findings provide new insights and hypotheses about how recreational walking may affect falls differently in men and women.

    The authors declare they have not used Artificial Intelligence (AI) tools in the creation of this article.



    Author contributions



    Ferran Cuenca-Martínez, Mónica Grande-Alonso: conceptualization, supervision; all authors: methodology, validation, data curation, writing—original draft preparation, writing—review and editing, visualization; Mónica Grande-Alonso: investigation, project administration. All authors have read and agreed to the published version of the manuscript.

    Conflict of interest



    The authors declare no conflict of interest.

    [1] Dionne CE, Dunn KM, Croft PR, et al. (2008) A consensus approach toward the standardization of back pain definitions for use in prevalence studies. Spine 33: 95-103. https://doi.org/10.1097/BRS.0b013e31815e7f94
    [2] Konstantinou K, Dunn KM (2008) Sciatica: review of epidemiological studies and prevalence estimates. Spine 33: 2464-2472. https://doi.org/10.1097/BRS.0b013e318183a4a2
    [3] Robinson DR (1947) Pyriformis syndrome in relation to sciatic pain. Am J Surg 73: 355-358. https://doi.org/10.1016/0002-9610(47)90345-0
    [4] Broadhurst NA, Simmons DN, Bond MJ (2004) Piriformis syndrome: correlation of muscle morphology with symptoms and signs. Arch Phys Med Rehab 85: 2036-2039. https://doi.org/10.1016/j.apmr.2004.02.017
    [5] Pecina HI, Boric I, Smoljanovic T, et al. (2008) Surgical evaluation of magnetic resonance imaging findings in piriformis muscle syndrome. Skeletal Radiol 37: 1019-1023. https://doi.org/10.1007/s00256-008-0538-0
    [6] Che WS (1994) Bipartite piriformis muscle: an unusual cause of sciatic nerve entrapment. Pain 58: 269-272. https://doi.org/10.1016/0304-3959(94)90208-9
    [7] Sayson SC, Ducey JP, Maybrey JB, et al. (1994) Sciatic entrapment neuropathy associated with an anomalous piriformis muscle. Pain 59: 149-152. https://doi.org/10.1016/0304-3959(94)90060-4
    [8] Pace JB, Nagle D (1976) Piriform syndrome. WJM 124: 435.
    [9] Beatty RA (1994) The piriformis muscle syndrome: a simple diagnostic maneuver. Neurosurgery 34: 512-514. https://doi.org/10.1227/00006123-199403000-00018
    [10] Fishman LM, Dombi GW, Michaelsen C, et al. (2002) Piriformis syndrome: diagnosis, treatment, and outcome—a 10-year study. Arch Phys Med Rehab 83: 295-301. https://doi.org/10.1053/apmr.2002.30622
    [11] Hilal FM, Bashawyah A, Allam AE, et al. (2022) Efficacy of botulinum toxin, local anesthetics, and corticosteroids in patients with piriformis syndrome: a systematic review and meta-analysis. Pain Physician 25: 325.
    [12] Siraj SA, Dadgal R (2022) Physiotherapy for piriformis syndrome using sciatic nerve mobilization and piriformis release. Cureus 14.
    [13] Wyant GM (1979) Chronic pain syndromes and their treatment iii. the piriformis syndrome. Canad Anaesth Soc J 26: 305-308. https://doi.org/10.1007/BF03006291
    [14] Cohen SP, Vase L, Hooten WM (2021) Chronic pain: an update on burden, best practices, and new advances. Lancet 397: 2082-2097. https://doi.org/10.1016/S0140-6736(21)00393-7
    [15] Booth J, Moseley GL, Schiltenwolf M, et al. (2017) Exercise for chronic musculoskeletal pain: a biopsychosocial approach. Musculoskeletal Care 15: 413-421. https://doi.org/10.1002/msc.1191
    [16] Bonatesta L, Ruiz-Cárdenas JD, Fernández-Azorín L, et al. (2022) Pain science education plus exercise therapy in chronic nonspecific spinal pain: a systematic review and meta-analyses of randomized clinical trials. J Pain 23: 535-546. https://doi.org/10.1016/j.jpain.2021.09.006
    [17] Bijur PE, Silver W, Gallagher EJ (2001) Reliability of the visual analog scale for measurement of acute pain. Acad Emerg Med 8: 1153-1157. https://doi.org/10.1111/j.1553-2712.2001.tb01132.x
    [18] Nolan MF (1985) Quantitative measure of cutaneous sensation: two-point discrimination values for the face and trunk. Phys Ther 65: 181-185. https://doi.org/10.1093/ptj/65.2.181
    [19] Kinser AM, Sands WA, Stone MH (2009) Reliability and validity of a pressure algometer. J Strength Cond Res 23: 312-314. https://doi.org/10.1519/JSC.0b013e31818f051c
    [20] Chattanooga GroupStabilizaer TM pressure bio-feedback operating instructions (2002).
    [21] Quintana JM, Padierna A, Esteban C, et al. (2003) Evaluation of the psychometric characteristics of the Spanish version of the Hospital Anxiety and Depression Scale. Acta Psychiat Scand 107: 216-221. https://doi.org/10.1034/j.1600-0447.2003.00062.x
    [22] Stratford PW, Binkley J, Solomon P, et al. (1996) Defining the minimum level of detectable change for the Roland-Morris questionnaire. Phys Ther 76: 359-365. https://doi.org/10.1093/ptj/76.4.359
    [23] Martín-Aragón M, Pastor MA, Rodríguez-Marín J, et al. (1999) Percepción de autoeficacia en dolor crónico. Adaptación y validación de la chronic pain selfefficacy scale, (Spanish) [Perception of self-efficacy in chronic pain. Adaptation and validation of the chronic pain selfefficacy scale]. J Health Psychol 11: 51-75. https://doi.org/10.21134/pssa.v11i1.799
    [24] Gómez-Pérez L, López-Martínez AE, Ruiz-Párraga GT (2011) Psychometric properties of the spanish version of the Tampa Scale for Kinesiophobia (TSK). J Pain 12: 425-435. https://doi.org/10.1016/j.jpain.2010.08.004
    [25] García Campayo J, Rodero B, Alda M, et al. (2008) Validation of the Spanish version of the Pain Catastrophizing Scale in fibromyalgia. Med Clin 131: 487-493. https://doi.org/10.1157/13127277
    [26] George SZ, Valencia C, Beneciuk JM (2010) A psychometric investigation of fear-avoidance model measures in patients with chronic low back pain. J Orthop Sport Phys 40: 197-205. https://doi.org/10.2519/jospt.2010.3298
    [27] Marcos-Martín F, González-Ferrero L, Martín-Alcocer N, et al. (2018) Multimodal physiotherapy treatment based on a biobehavioral approach for patients with chronic cervico-craniofacial pain: a prospective case series. Physiother Theor Pr 34: 671-681. https://doi.org/10.1080/09593985.2017.1423522
    [28] López-de-Uralde-Villanueva I, Beltran-Alacreu H, Fernández-Carnero J, et al. (2020) Pain management using a multimodal physiotherapy program including a biobehavioral approach for chronic nonspecific neck pain: a randomized controlled trial. Physiother Theor Pr 36: 45-62. https://doi.org/10.1080/09593985.2018.1480678
    [29] Filip R, Gheorghita Puscaselu R, Anchidin-Norocel L, et al. (2022) Global challenges to public health care systems during the COVID-19 pandemic: a review of pandemic measures and problems. J Pers Med 12: 1295. https://doi.org/10.3390/jpm12081295
    [30] Boletín Oficial del Estado, Royal Decree 463/2020 of 14 March declaring the state of alarm for the management of the health crisis caused by COVID-19. Available from: https://www.boe.es/eli/es/rd/2020/03/14/463
    [31] García-Salgado A, Grande-Alonso M (2021) Biobehavioural physiotherapy through telerehabilitation during the SARS-CoV-2 pandemic in a patient with post-polio syndrome and low back pain: a case report. Phys Ther 24: 295-303. https://doi.org/10.1298/ptr.e10100
  • Reader Comments
  • © 2024 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)
通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

  1. 本站搜索
  2. 百度学术搜索
  3. 万方数据库搜索
  4. CNKI搜索

Metrics

Article views(1681) PDF downloads(116) Cited by(1)

Figures and Tables

Figures(1)  /  Tables(3)

/

DownLoad:  Full-Size Img  PowerPoint
Return
Return

Catalog