The aim of this study was to quantify the relationships between four physiological parameters of masseter activity during chewing and properties related to the sizes and textures of the six representative test foods. The physiological parameters analyzed were the number of chewing cycles, chewing time, masseter amplitude, and cycle duration, which were obtained from masseter surface electromyography recorded in ten (seven male and three female) healthy, young participants. The six test foods differed in size dimensions (length, width, and height) and in textural properties (hardness, fracturability, and adhesiveness). The quantitative relationships were examined using linear regression. Nine statistically significant regression coefficients were found between the four physiological parameters and the textural properties, but not the height, of the test foods. From the regression coefficients, contributions of the food properties to the physiological parameters were estimated. Individual relationships between the physiological parameters and textural properties of the test foods are discussed in relation to their physiological implications.
Both the size dimensions of foods and the textural properties (such as hardness and adhesiveness) affect the jaw and muscle activity during the chewing of foods. For example, it has been shown that compared to the chewing of a smaller piece of food, the chewing of larger foods is associated with longer jaw-opening and -closing phases and chewing times [
Two challenges have limited our understanding of the effect of food size dimensions, and textural properties on jaw muscle activity during chewing: one being a methodological challenge and the other related to the chewing materials. With regard to the methodological challenge, while many previous studies have examined food parameters (such as size dimensions, and textural properties) and physiological parameters, these parameters have been generally assessed separately. This has hampered our understanding of the causal and quantitative relationships between food and physiological parameters. There have been a limited number of studies that have used a correlation method to analyze the relationships between food and physiological properties [5,6]. In regard to the chewing material challenge, while some model foods have been useful since they allow a more precise focus on specific properties such as hardness [1,2,4], such model foods are not representative of the foods that are consumed every day, which usually possess complex physical and chemical properties. Both challenges can be addressed by employing a linear regression model (LRM), a statistical model that tests how well two or more variables are related by a straight line [
The aim of the present study was to quantify the relationships between the physiological parameters of masseter activity during chewing and the size and textural properties of representative test foods using LRM.
This study was approved by the ethical committee of Niigata University of Health and Welfare. A preliminary report of this study has been presented as an abstract form [
Ten young adults (seven men and three women) with an average age of 20 years participated in this study after providing informed consent. None of the participants had special medical and dental problems related to chewing or swallowing.
Six test foods were used in the present study: processed cheese (Rokko Butter Co., Ltd., Japan), gummy candy (Meiji Co., Ltd., Japan), marshmallow (EIWA Confectionery Co., Ltd., Japan), dried prunes (Uchiyama-Tozaburo firm, Japan), rice crackers (Sanko-Seika Co., Ltd., Japan), and sponge cake (Shimizu-Seika Co., Ltd., Japan). The size dimensions and weight of these foods were described in our preceding paper (
As shown in the preceding paper (
A pair of adhesive electrodes (Ambu Inc., Blue Sensor, Maryland, USA) was attached to the skin just above the masseter muscle (Mass) on the participant’s habitual working side to record a surface electromyogram (EMG). The Mass EMG signals were amplified, filtered (using a bandwidth of 10 Hz - 10 kHz), fully rectified, and integrated (time constant = 0.06 s) using the PowerLab system (ADInstruments Pty Ltd., PowerLab/8 sp, Bella Vista, Australia). An accelerometer (Takei Scientific Instruments Co., Ltd., Tokyo, Japan) was attached to the skin of the chin to monitor jaw movement associated with chewing; the amplitude of the movement was not measured. In addition to the EMG and accelerometer recordings, two video cameras (Logicool®, Qcam Communicate STX, Tokyo, Japan) were used to monitor the movement of the body, neck, and head of each participant from the frontal and lateral sides, respectively. The collected data were stored and analyzed on the PowerLab system.
Each participant was seated on a chair in an electrically shielded room, the temperature of which was around 25˚C. The participant was partitioned from the experimenters by a folding screen and was asked to wear earplugs and a headphone during the experiment to reduce surrounding noise. The participant was provided with instructions regarding chewing tasks from a computer display that was placed on a desk in front of them. One of the six test foods was delivered randomly in front of the participant and they were asked to chew it at their natural rhythm. The participant was not restricted with regard to the chewing side despite the fact that the EMG electrodes were attached on the habitual working side. The participant was also asked to swallow when they felt the food had been fully chewed. After swallowing, the participant was allowed to drink room temperature green tea (Ohi-ocha, Ito-en, Tokyo, Japan). One experimental session consisted of 7 - 12 trials for each participant (1 minute intervals between trials). A total of 108 trials were conducted with the ten participants.
Since the Mass EMG was evoked not only by cyclic chewing but also by any voluntary and involuntary contractions, the start of chewing was confirmed on the basis of both the accelerometer data, which displayed the jaw movement trajectory, and visual observations using the video-camera monitors. The start and end of each chewing cycle were determined to be when the Mass EMG had clearly exceeded and returned to the resting activity level, respectively.
Four parameters were analyzed in this study: the number of chewing cycles, chewing time, peak amplitude of the integrated Mass EMG, and cycle duration of the raw Mass EMG. The chewing cycle number was determined by counting the bursts in the Mass EMG that occurred between the start and the end (i.e., just before swallowing) of each chewing sequence. The chewing time was determined to be the cycle duration from the start to the end of each chewing sequence. The peak amplitude was defined as the highest value of the integrated Mass EMG. The cycle duration of the raw Mass EMG was defined as the interval from the start to the end of each burst in the Mass EMG. The peak amplitude and the cycle duration were measured for the first chewing cycle only.
Since the number of chewing cycles was a discrete parameter, two non-parametric methods, namely, the Kruskal-Wallis and Steel-Dwass tests, were used for statistical analyses. The Kruskal-Wallis test was used to detect any significant differences between the six foods and between the participants, while the Steel-Dwass test was used to detect any specific differences between food or participant pairs. Two parametric methods were used to analyze the remaining data, namely, the two-way analysis of variance (ANOVA) and LRM analysis. In the ANOVA, two factors (“Food” and “Participant”) were used to detect significant differences between the parameters for the six foods and the ten participants. The ANOVA was followed by the Tukey’s HSD test to detect specific differences between food pairs but not between participant pairs. In the LRM analysis, the following linear model was assumed:
where y is an observation of one of the parameters (such as cycle duration or peak amplitude), ai (i = 1, 2, 3, 4) are four regressive effects of three textural properties (“Hardness”, “Fracturability”, and “Adhesiveness”) and the “Height” of the foods, ci are four regression coefficients for the four regressive effects, b is a fixed-main effect of “Participant”, and e is a random residual effect. Since the “Cohesiveness” is a ratio of the positive force areas under the first and second compressions [
The estimated contributions of the four food parameters (hardness, fracturability, adhesiveness, and height) to the number of chews from the start of chewing to just before swallowing are shown in
The estimated contributions of the food parameters to the chewing time from the start to the end of chewing are shown in
regression coefficient estimates for fracturability (−0.063) and for adhesiveness (−1.22; Ps < 0.01) with regard to the chewing time. According to the estimated regression coefficients and the measured ranges of these two food parameters, changes in the chewing time were estimated as −5.9 s across the range of fracturability values and −6.9 s across the range of adhesiveness values.
The estimated contributions of the food parameters to the peak amplitudes of the integrated Mass EMG during the first chewing cycle are shown in
The estimated contributions of the food parameters to the cycle durations of the Mass EMG for the first chewing cycle are shown in
cients and the measured ranges of these two food parameters, changes in the cycle duration were estimated as 75.8 ms across the hardness values and −70.8 ms across the adhesiveness values.
Six test foods were used in this study, and their size dimensions and textural properties were previously analyzed (Tables 1 and 2 in [
Previous physiological studies have shown that the type [3,11], hardness [
The peak amplitude of an integrated masseter EMG is a very popular parameter for evaluating the behavior of the chewing apparatus in humans and experimental animals [4,18-21], probably because of its high sensitivity to the hardness of foods. In the present study, the LRM analysis allowed the quantification of the significant contributions of two textural parameters, fracturability and adhesiveness, to the peak amplitude (
In conclusion, quantitative relationships are presented between four physiological parameters of masseter activity during chewing by ten healthy young adults and properties related to the sizes and textures of the six test foods used. Nine statistically significant regression coefficients were found between the four physiological parameters and the textural properties, but not the height, of the test foods. From the significant regression coefficients, contributions of the food properties to the physiological parameters were estimated.
This study was supported in part by Grants-in-Aid for Scientific Research from the Ministry of Education, Science and Culture of Japan (No. 22500740 to YM, No. 23700889 to TY, and No. 2050072 to IA).