Participants
This study is a part of an aging and OA project with the goal of establishing epidemiologic indexed towards development of effective preventive strategy for knee OA and extension of healthy life span. In this cross-sectional study, participants were identified through the medical record system and recruited from a community orthopedic clinic located in a rural mountainous community in Hiroshima and Kyoto, Japan. We recruited participants who were visiting the clinic for the conservative treatment of knee OA in January 2014 within a 3-day window. All recruited participants had a history of pain in one or both knees. The required sample size was not calculated and there was no limit to the maximum number of recruited participants. The eligibility criteria of the current cross-sectional study was as follows: (1) age ≥ 60 years and (2) ability to walk independently on a flat surface without any ambulatory assistive device. Two experienced physical therapists visually checked the participant’s walking ability on a flat surface. Since radiography was available only for painful knee, this study could not consider bilateral knee OA cases separately from unilateral cases. This study included participants with age ≥ 60 years because knee pain is common in community-dwelling older adults in Japan [17] and is recommended criteria for sarcopenia diagnosis according to Asian Working Group for Sarcopenia (AWGS) [18]. The exclusion criteria were (1) a history of knee surgery, (2) rheumatoid arthritis, (3) periarticular fracture, or (4) present neurological problems such as hemiplegia and Parkinson’s disease, all of which were assessed by medical record. There was no limit for time interval between these disease condition and study recruitment. This study was approved by the ethics committees in Kyoto University Graduate School and Faculty of Medicine and conducted in accordance with the principles of the Declaration of Helsinki. Written informed consent was obtained from all participants before their enrollment. This study was carried out in accordance with STROBE statement (see Supplemental Appendix S1).
Measurements
Skeletal muscle mass index (SMI), handgrip strength (i.e., a metric of muscle strength), gait velocity (i.e., a metric of physical performance), and radiographic knee OA were evaluated. Fall experience was evaluated as outcome measurement. All outcome measures were evaluated by experienced physical therapists with > 6 years of clinical experience in musculoskeletal disorders and a postgraduate master’s degree qualification at the time of participant inclusion. Demographic characteristics and knee OA-related self-reported measures of knee pain and disability were also assessed as participant characteristics and/or covariates.
Assessment of sarcopenia
A bioelectrical impedance data acquisition system (Inbody 430; Biospace Co., Ltd., Seoul, Korea) was used to determine bioelectrical impedance in accordance with manufacture instruction [19]. This system uses electrical current at different frequencies (5, 50, and 250 kHz) to directly measure the amount of extracellular and intracellular water in the body and has been used in the previous epidemiological studies [20, 21]. The data acquisition system calculated the resistance value and muscle mass of the respective body parts (right arm, left arm, right leg, left leg, and trunk). The participants stood on 2 metallic electrodes and held metallic grip electrodes. The appendicular skeletal muscle mass was determined using the segmental body composition and muscle mass excluding the trunk part. SMI was calculated by dividing the skeletal muscle mass by height in square meters (kg/m2) [22]. The handgrip strength in both hands was measured using a hand dynamometer (Smedley Style Hand Grip Dynamometer; Tsutsumi Seisakusho Co., Ltd., Tokyo, Japan) [23] that shows excellent test-retest reliability [24]. The participants kept their arms by the sides of their body and squeezed the dynamometer using maximum isometric effort. Other body movements were prohibited [23]. To assess gait velocity, the participants were instructed to walk for 10 m at a self-selected speed. A trained examiner measured the time taken to walk 10 m with a stopwatch (TD-392; TANITA Corp., Tokyo, Japan), in accordance with a previously suggested method [25]. Gait velocity (m/s) was manually calculated as 10 m divided by the time needed to walk 10 m.
We defined sarcopenia as the presence of both low muscle function (low physical performance or low muscle strength) and low muscle mass in accordance with the recommended diagnostic algorithm of the AWGS [18]. If a participant had both low muscle function (slow walking speed [0.8 m/s] or low grip strength [< 26 and < 18 kg for men and women, respectively]) and low SMI (< 7.0 and < 5.7 kg/m2 for men and women, respectively), sarcopenia was diagnosed [18]. The prevalences of presarcopenia (i.e., low SMI without low muscle function) and severe sarcopenia (i.e., low SMI with slow walking speed and low grip strength) were provided for descriptive purposes.
Radiographic OA severity in knee joint
The radiographic severity of the tibiofemoral joint in index knee was assessed by a trained examiner (HI) using the original version of the Kellgren and Lawrence (K&L) grading system [26]. The index knee was defined as the more painful knee in the past or present. If a participant considered the pain in both knees to be equal, the index knee was randomly selected using a computer-generated permuted block randomization scheme [27]. We previously reported excellent intra-examiner (κ: 0.876; 95% confidence interval [CI]: 0.829, 0.924) and inter-examiner (κ: 0.845; 95% CI: 0.793, 0.897) reliability scores [28]. The presence of radiographic OA was defined as K&L grade ≥ 2.
Assessment of falls
A fall was defined as unintentionally coming to rest on the ground or at some other lower level, not because of a major intrinsic event (e.g., stroke) or an overwhelming external force (e.g., impact from a moving vehicle). Falls in the previous 12 months were evaluated using a self-reported question: “How many times did you have a fall within the past year?” An individual was considered a faller and recurrent faller if he or she has had at least 1 fall and 2 falls in the preceding 12 months, respectively. This 12-month falls recall questionnaire has been used in the previous epidemiological studies [5, 7, 8] and is acceptable alternative to prospective daily falls questionnaire in community-dwelling older adults [29].
Participant characteristics and covariates
Data on age, sex, and height were self-reported by the participants. Body mass was measured on a digital scale, with the participants dressed but not wearing shoes. Body mass index (BMI) was calculated by dividing the body mass (kg) by height in square meters (m2). The knee pain severity and self-reported disability were evaluated using the Japanese Knee Osteoarthritis Measure (JKOM) subcategories “pain and stiffness” (0–32 points) and “activities of daily living” (0–40 points) as a person-specific assessment [30]. The concurrent and construct validities of the JKOM were established by comparing with the Western Ontario and McMaster Universities Arthritis Index and the Medical Outcomes Study 36-item Short-form Health Survey [30].
Classification based on sarcopenia and knee OA
All subjects were allocated to one of the following four subgroups based on sarcopenia and radiographic OA in index knee: (1) control (non-knee OA and non-sarcopenia), (2) isolated sarcopenia, (3) isolated knee OA, and (4) sarcopenia + knee OA. Figure 1 shows diagnostic algorithms for the classification of four subgroups determined by sarcopenia and knee OA.
Statistical analyses
We statistically analyzed the differences among the four groups using analysis of variance with a subsequent post hoc Tukey-Kramer test for parametric continuous variables, Kruskal-Wallis test with subsequent post hoc Steel-Dwass test for nonparametric continuous variables, and Fisher’s exact test for categorical variables. The normality of continuous variables was assessed using the Shapiro-Wilk test.
Binary logistic regression analyses were performed to assess the relationship between the four subgroups, an independent variable, and a fall (≥1 fall; 0: no, 1: yes) or recurrent falls (≥2 falls; 0: no, 1: yes) in the preceding 12 months, a dependent variable. In this analysis, the four subgroups were included as a dichotomous variable, such as control (reference), isolated sarcopenia (0: no; 1: yes), isolated sarcopenia (0: no; 1: yes), and sarcopenia + knee OA (0: no; 1: yes). As recurrent falls may have different risk factors and have been associated with increased physician contact and functional decline [5,6,7,8], this parameter (≥2 falls) was also included as a dependent variable in a separate binary logistic regression model. Ordinal logistic regression analysis was also performed, and falls were included as an ordinal dependent variable (1: no fall, 2: 1 fall, 3: ≥2 falls). In these analyses, age (continuous), female sex, and BMI (continuous) were included as covariates. These covariates were chosen a priori based on clinical judgment and their potential association with sarcopenia and knee OA [31, 32], not according to the causal pathway. The knee pain intensity (continuous) was further included as a covariate in a separate post-hoc logistic regression analysis.
To test the interaction between sarcopenia and radiographic knee OA, another logistic regression analysis was performed with sarcopenia (0: no; 1: yes), knee OA (0: no; 1: yes), and their interaction term (i.e., sarcopenia × knee OA) as independent variables. In this analysis, the dependent variable and covariates were included as mentioned above. Data analyses were performed using JMP 14.0 (SAS Institute, Cary, NC, USA).