Data collection
We used a cross-sectional descriptive correlative approach as the study design. We scheduled study gatherings at nine different community halls in the city from February 17 to March 31, 2014. Each participant chose a convenient time and visited the study site using their own mode of transportation, including walking. There were two measurements, extensive physical assessments of five items including MOF, which took approximately 30 min (Additional file
1), and a questionnaire concerning the demographic characteristics and health status of the participants, which also took approximately 30 min (Additional file
2).
As extensive physical assessment, we measured five items: MOF, handgrip strength, maximal knee extensor strength, one-leg standing time with eyes open and body sway. Moon & Lee [
9] described the definition of occlusion as contact between the maxillary and mandibular teeth during chewing or at rest. Therefore, in this study, we defined occlusal force as the force produced by occlusion. MOF (kN) was measured according to a standard procedure using an occlusal force-measuring device (GM10 Morita Occlusal Force Meter; J. Morita Corporation, Tokyo, Japan). Dentures were worn when present. MOF measurement was performed with the participants in an unsupported, natural seated position. We explained the measurement method before it was performed. We did not obtain MOF measurements from participants who reported pain at the beginning of the measurement. We also asked the participants to stop biting as soon as they felt pain or discomfort. MOF was measured unilaterally on the right and left sides at the molar. The maximum value of either the right or the left measurement was used as the MOF value.
Handgrip strength values (kg) of the dominant and non-dominant hands were alternately measured, using Takei Digital Hand Grip Dynamometer T.K.K. 5401 (Takei Scientific Instruments Co., Ltd., Niigata, Japan), during two trials with each patient in an unsupported, natural standing position. The maximum value of either the right or the left measurement was used as the handgrip strength value.
Maximal knee extensor strength (kg) was measured using μTas MF-1 (Anima Co. Ltd., Tokyo, Japan). The participants sat on a chair and held both hands behind their back to support their upper body. The thighs, knees, and ankles were held at a right angle. A sensor pad was attached to the lower front of the shin with an elastic band, and the band was looped around the leg of the chair. We asked the participants to kick their leg with the sensor pad as hard as possible and to keep that strength for five seconds. The trials were conducted twice for the right and left legs. We also asked the participants to breathe out when kicking to reduce the burden on the heart and to stop the trial when they felt pain or discomfort. The maximum value of either the right or the left measurement was used as the knee extensor strength value.
One-leg standing time with eyes open was measured with the hands on the waist while standing on one foot while the other foot was off the floor. The time (seconds) was recorded until the participants lost their balance, began to hop around, moved their hands off the waist, or lowered the raised foot to the floor. They performed one trial for the right foot first; after a 10-s break, they did the same with the left foot. The highest value of either the right or the left measurement was used as the time for one-leg standing, with a maximum score of 120 s.
The total length of body sway was measured using a 5-km/h moving image (cm), Gravi Coda GS3000 (Anima Co., Ltd., Tokyo, Japan), and Eye Trek FMD-150 W (Olympus, Tokyo, Japan). First, the body sway of participants was measured for 30 s in a natural standing position with the eyes open. After 30 s of rest, participants put the Eye Trek gear on their head. As they watched an image moving 5 km/h through the gear, their body sway was measured for 30 s by following a certain point of the body surface. We calculated the total length of the movement of the point as the body sway value. When we performed the body sway measurement, all participants were supported by research assistants standing beside and behind them on the equipment to prevent them from falling. We did not perform the measurement for participants who claimed a tendency for motion sickness, medical history of cerebrovascular disease or epilepsy, or anxiety regarding their health status. Fortunately, we found no such cases.
For the safety of participants and precise data collection, we trained 13 research assistants, including three licensed registered nurses, for one week to skillfully perform the extensive physical assessments. Each assistant was in charge of his/her specific assessment item only. Reproducibility of measurements was examined using peer measurements. We confirmed that the skill levels of the assistants were satisfactory.
We developed our original questionnaire, including previous research regarding health status and falls among the community-dwelling elderly. The questionnaire items were as follows: age; sex; history of disease; denture use; regular/ routine exercise habits such as walking, jogging, or playing sports; ADL using the Tokyo Metropolitan Institute of Gerontology Index of Competence (TMIG-IC) [
19,
20]; and falls during the past year. TMIG-IC, which was created in the United States in the 1970s, was modified in the 1980s to assess the competence of Japanese elderly individuals in terms of instrumental self-maintenance, intellectual activity, and social role. The index consists of 13 yes (1 point) and no (0 points) questions. Higher scores (maximum of 13 points) indicated that participants were able to perform ADL better and more independently ([
21‐
23]. TMIG-IC also questions five items regarding quality of life: sense of subjective health, relationship with family, relationship with friends, financial satisfaction, and subjective happiness. Participants were asked to rate their values for the items using a 100-mm visual analogue scale, with the worst value on the left end and the best value on the right.
Before implementing the structured questionnaire, research assistants were trained regarding how to help the elderly answer it. During registration at the survey gatherings, we asked participants their names and postal addresses, so that data could be returned to them after the survey. We distributed a set of data collection sheets including the structured questionnaire with an identification number for each participant. To help the participants answer the questionnaire, the research assistants sat face-to-face with them and read aloud the questions, sentences, and answers slowly. After the participants finished all the measurements and questions, the completed data collection sheets were collected by the research assistants to analyze the data. The full set of the questionnaire sheet included additional question items, which were not relevant to the present study. Therefore, we did not provide the data of those question items in this paper.
Data analysis
We obtained descriptive statistics regarding age, sex, history of disease, current disease status, denture use, presence or absence of regular/routine exercise habits or playing sports, ADL using TMIG-IC, and falls during the past year. Mean scores and standard deviations were calculated for age and the total points of the TMIG-IC. Associations were examined using Mann-Whitney tests for falls and MOF, handgrip strength, maximal knee extensor strength, one-leg standing time with eyes open, and total length of body sway using a 5-km/h moving image. We performed logistic regression to determine odds ratios (ORs) of falls. The covariates included the following five items which have significant correlation and are related with muscle: MOF, handgrip strength, maximal knee extensor strength, one-leg standing time with eyes open, and total length of body sway with a 5-km/h moving image. We performed statistical calculations using SPSS version 22.0 for Windows (IBM Japan, Tokyo, Japan) with a significance level of P < 0.05.