The aim of this study was to examine the correlation between the number of remaining natural teeth (NRT) and the appendicular skeletal muscle mass index (SMI) in older adults.
This study was based on data from the 2008–2010 Korea National Health and Nutritional Examination Surveys. The participants were 2,378 older participants (984 men and 1,394 women) aged over 65 years. Survey dentists conducted oral health examinations, and ASM was measured using dual-energy X-ray absorptiometry.
The participants with NRT≥20 had more ASM and SMI than those with NRT<20 in both sexes. SMI was correlated with NRT in men (r=0.018, p<0.001) and in women (r=−0.007, p<0.001). The positive correlation between the NRT and SMI remained significant in men even after adjusting for age, marital status, income, smoking, drinking, physical activity, protein intake, energy intake, calcium intake, body mass index, fasting blood glucose level, medications, and prostheses (β=0.011, p=0.001). In women, the correlation disappeared after adjustment for smoking, alcohol, physical activity, protein intake, energy intake, calcium intake, marital status, income, fasting basal glucose, medication administration, and prostheses.
This study showed a correlation between NRT and SMI in those ≥65 years of age in Korea. The relationship persisted in men, but not in women, even after adjusting for confounders.
Oral health, and more specifically, the functioning of the mouth is closely related to the overall health of the elderly. Digestion of foods begins with chewing and depends largely on the condition of the teeth. Compared to older individuals with their own set of teeth, older individuals with complete dentures consume fewer calories and eat lower-quality foods, possibly leading to various diseases.
Decreasing skeletal muscle mass is an important physical change associated with aging that can be objectively measured. A decrease in skeletal muscle mass can lead to improper responses to external stressors and vulnerabilities, which can further be associated with falls and trauma, functional disorders, increased hospital admission rates, decreased quality of life, and increased mortality.
A previous study reported that unfavorable oral health, including a reduced number of teeth, is associated with disability,
We analyzed the data from the Fourth and Fifth KNHANES, which were conducted in 2008–2010 by the Korea Centers for Disease Control and Prevention (KCDC). The sampling protocol of the KNHANES involves a representative sample of civilians in Korea who are not institutionalized and is designed as a complex, stratified, multistage, probability-cluster survey. The survey was performed by the Korean Ministry of Health. The survey targeted non-institutionalized Korean individuals who were aged over 1 year at the time of the study. The survey utilized stratified multistage probability sampling units based on geographic area, sex, and age that were determined using the household registries of the 2005 National Census Registry, the latest 5-year national census of Korea. Two hundred primary sampling units were selected nationally using the 2005 census data. The final sample set of the KNHANES included 4,600 households. A detailed description of the sampling can be found in the KNHANES report (KCDC 2008–2010).
A total of 29,235 participants were included in the KNHANES. Among them, 4,772 people aged over 65 years had a periodontal examination. We excluded individuals who did not have dual-energy X-ray absorptiometry (DXA) data (n=1,128); those who had a history of stroke, coronary artery disease, thyroid, lung, liver, or renal disease or any cancers (n=671); those with any missing test data (including fasting blood glucose) (n=162); and nonprostheses respondents (n=56). The exclusion criteria were chosen to ensure selection of healthy participants and to minimize the confounding effects of muscle mass. The present study included 2,378 participants.
An oral health examination was conducted by survey dentists, and the data from participants whose teeth were orally examined as reported in the KNHANES were used. In previous studies, the presence of 20 teeth or more was considered necessary for maintaining adequate masticatory function.
All participants underwent DXA (DISCOVERY-W fan-beam densitometer; Hologic Inc., Holliston, MA, USA) to assess the body composition. A standardized daily quality control of the instrument had been performed using a spine phantom provided by the manufacturer before the study commenced. ASM, which reflects the mass of skeletal rather than smooth muscles, was measured to identify the decrease in muscle mass in relation to aging. ASM was calculated as the sum of muscle mass in the arms and legs, assuming all nonfat and nonbone tissue as skeletal muscle
The measurements of body weight and height were rounded to the nearest tenth of a kilogram and centimeter, respectively. Body mass index (BMI) was calculated as weight/height2 (kg/m2). Samples for blood tests were collected during the health examination survey. These samples were collected from the antecubital veins and refrigerated immediately. The samples were then transported on dry ice to a designated central testing facility. The blood samples were analyzed within 24 hours.
Socio-demographic factors included age, sex, income, and marital status. Income was adjusted for the number of household members and categorized into 4 groups of <25%, 25%–49%, 50%–75%, and >75% of total equivalized income. Alcohol consumption status was categorized as either yes or no. Participants were questioned about their level of physical activity during a week, with moderate exercise defined as strenuous physical activity performed for at least 20 minutes at a time, at least 3 times a week. Dietary intake including total energy, calcium, and protein intake was estimated using a 24-hour dietary recall questionnaire administered by a trained dietitian.
This study was approved by the Institutional Review Board of Kyung Hee University Hospital, Seoul, Korea (approval number: KMCIRB 1419-11).
All data are presented as mean±standard error (SE) for continuous variables or as proportions (SE) for categorical variables. Participant characteristics were compared according to sex using an independent-samples Student t-test for continuous measures and Rao-Scott chi-square test for categorical measures. A regression analysis was used to assess the association between the NRT and SMI after adjusting for age and BMI, smoking, alcohol, physical activity, protein intake, energy intake, calcium intake, marital status, income, fasting basal glucose, medication administration, and prostheses. Statistical analyses were performed using the survey procedure in SAS ver. 9.2 (SAS Institute Inc., Cary, NC, USA) to account for the complex sampling design and to provide nationally representative prevalence estimates. A p-value of <0.05 was considered to indicate significance.
Of the 2,378 participants, there were 984 men (41.4%) and 1,394 women (58.6%) with a mean age of 71.9 years. The mean NRT was 16.3, and 486 men (49.4%) and 766 women (54.9%) had NRT<20. In both men and women, the proportion of the group with NRT<20 increased with age, and 84.62% of the men and 81.48% of the women over 85 years of age had NRT<20. In women, there were differences in age, marital status, income, smoking, BMI, prostheses, nutrition, and muscle mass between those with NRT≥20 and those with NRT<20. In men, age, smoking, BMI, prostheses, nutritional status, and muscle mass differed between the 2 groups. Marital status and low family income were associated with NRT<20 only in women. The mean ASM was 20.17 and 21.21 kg in men with NRT<20 and NRT≥20, respectively (p<0.001) and 14.02 and 14.48 kg in women with NRT<20 and NRT≥20, respectively (p<0.001). The mean SMI was 7.47 and 7.74 kg/m2 in men with NRT<20 and NRT≥20, respectively (p<0.001) and 6.25 and 6.26 kg/m2 in women with NRT<20 and NRT≥20, respectively (p=0.782) (
This is, to the authors’ knowledge, the first study to identify the correlation between the NRT and SMI, both of which are important for the overall health and quality of life in the elderly. In both men and women, a lower NRT was related to a lower SMI.
A reduction in the number of teeth can lead to nutritional deficiencies, resulting in muscle loss. Hildebrandt et al.
However, in women, a relationship between the NRT and SMI was not found after controlling for smoking, alcohol, physical activity, protein intake, energy intake, calcium intake, marital status, income, fasting basal glucose, medication administration, and prostheses.
It is well known that in older adults, both the number of teeth and ASM are related to social and economic factors; those with a higher income and higher educational level as well as those who live with a spouse and live in a city have been known to possess a higher number of functional teeth.
Older women had much less skeletal muscle mass than men. The choice of food may differ between men and women,
Furthermore, functional dentition (NRT≥20) showed a negative relationship with SMI in females, unlike in males. Inui et al. also reported negative correlation between skeletal muscle mass and NRT in females only. Additionally, females presented lower mean skeletal muscle mass in class A group with good occlusal support which implies that occlusal support, as well as NRT, affects sarcopenia.
Some previous studies reported higher prevalence of sarcopenia in Korean men than in women when height adjusted skeletal muscle mass was used to define sarcopenia,
A limitation of this study is its cross-sectional design, and the results do not indicate causal relationships. A second limitation is that gait speed or handgrip strength were unavailable, and therefore could not present the relationship between teeth loss and sarcopenia. Nevertheless, this study is based on a general population representative survey and is the first study to identify a correlation between oral health and ASM. Such correlation indicates that maintenance of oral health must be considered in managing skeletal muscle mass in older people.
In conclusion, this study showed a correlation between the NRT and SMI in participants ≥65 years of age in Korea. The relationship persisted in men, even after adjusting for confounders, but not in women.
The researchers claim no conflicts of interest.
Comparison of SMI between NRT<20 and NRT≥20 groups. NRT, number of remaining natural teeth; ASM, appendicular skeletal muscle mass; Ht, height.
Demographic characteristics
Characteristic | Men (n=984) | p-value | Women (n=1,394) | p-value | ||
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NRT<20 (n=486) | NRT≥20 (n=498) | NRT<20 (n=766) | NRT≥20 (n=628) | |||
Age (yr) | 72.83±0.24 | 70.74±0.19 | <0.001 | 73.32±0.19 | 70.36±0.17 | <0.001 |
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65–69 | 152 (40.00) | 228 (60.00) | <0.001 | 208 (39.1) | 324 (60.9) | <0.001 |
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70–74 | 166 (48.26) | 178 (51.74) | 265 (58.89) | 185 (41.11) | ||
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75–79 | 108 (59.67) | 73 (40.33) | 182 (65.23) | 97 (34.77) | ||
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80–84 | 49 (74.24) | 17 (25.76) | 89 (83.96) | 17 (16.04) | ||
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≥85 | 11 (84.62) | 2 (15.38) | 22 (81.48) | 5 (18.52) | ||
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Marital status | ||||||
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Married | 437 (48.29) | 468 (51.71) | 0.062 | 335 (47.79) | 366 (52.21) | <0.001 |
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Widowed | 42 (62.69) | 25 (37.31) | 422 (62.89) | 249 (37.11) | ||
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Divorced | 7 (58.33) | 5 (41.67) | 9 (40.91) | 13 (59.09) | ||
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Family income | ||||||
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Low | 139 (55.16) | 113 (44.84) | 0.146 | 216 (63.34) | 125 (36.66) | 0.001 |
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Mid-low | 118 (48.89) | 123 (51.04) | 195 (53.42) | 170 (46.58) | ||
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Mid-High | 115 (48.32) | 123 (51.68) | 194 (55.27) | 157 (44.73) | ||
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High | 114 (45.06) | 139 (54.94) | 161 (47.77) | 176 (52.23) | ||
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Smoking status | ||||||
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Current smoker | 173 (65.28) | 92 (34.72) | <0.001 | 52 (74.29) | 18 (25.71) | 0.002 |
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Past smoker | 259 (47.26) | 289 (52.74) | 40 (59.7) | 27 (40.3) | ||
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Never smoked | 54 (31.58) | 117 (68.42) | 674 (53.62) | 583 (46.38) | ||
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Current drinking | ||||||
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No | 427 (49.25) | 440 (50.75) | 0.811 | 751 (54.98) | 615 (45.02) | 0.882 |
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Yes | 59 (50.43) | 58 (49.57) | 15 (53.57) | 13 (46.43) | ||
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Moderate physical activity | ||||||
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No | 413 (49.11) | 428 (50.89) | 0.668 | 656 (54.99) | 537 (45.01) | 0.945 |
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Yes | 73 (51.05) | 70 (48.95) | 110 (54.73) | 91 (45.27) | ||
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BMI (kg/m2) | ||||||
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<18.5 | 5 (38.46) | 8 (61.54) | 0.013 | 23 (38.33) | 37 (61.67) | <0.001 |
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18.5–25 | 94 (43.93) | 120 (56.07) | 237 (52.32) | 216 (47.68) | ||
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25–30 | 352 (49.86) | 354 (50.14) | 465 (55.96) | 366 (44.04) | ||
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≥30 | 35 (68.63) | 16 (31.37) | 41 (82.00) | 9 (18.00) | ||
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Fasting blood glucose (mg/dL) | ||||||
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<100 | 264 (49.44) | 270 (50.56) | 0.246 | 457 (56.00) | 359 (44.00) | 0.628 |
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100–126 | 117 (45.88) | 138 (54.12) | 165 (53.05) | 146 (46.95) | ||
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≥126 | 105 (53.85) | 90 (46.15) | 144 (53.93) | 123 (46.07) | ||
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Medication administration | ||||||
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No | 482 (49.28) | 496 (50.72) | 0.396 | 752 (55.09) | 613 (44.91) | 0.465 |
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Yes | 4 (66.67) | 2 (33.33) | 14 (48.28) | 15 (51.72) | ||
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Prosthesis | ||||||
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No | 36 (16.91) | 187 (83.09) | <0.001 | 37 (15.10) | 208 (84.90) | <0.001 |
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Yes | 450 (59.13) | 311 (40.87) | 729 (63.45) | 420 (36.55) | ||
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Protein intake (g/day) | 60.67±1.27 | 66.29±1.52 | 0.005 | 42.45±0.77 | 48.01±1.01 | <0.001 |
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Energy intake (kcal) | 1,856.48±29.58 | 1,964.29±31.97 | 0.014 | 1,403.25±18.45 | 1,460.05±21.25 | 0.043 |
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Calcium intake (mg/day) | 450.35±17.27 | 499.92±14.43 | 0.028 | 339.34±9.70 | 397.64±23.48 | 0.022 |
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ASM (kg) | 20.17±0.13 | 21.21±0.12 | <0.001 | 14.02±0.07 | 14.48±0.08 | <0.001 |
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ASM/Ht2 (kg/m2) | 7.47±0.04 | 7.74±0.04 | <0.001 | 6.25±0.02 | 6.26±0.03 | 0.782 |
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ASM/BMI (m2) | 0.89±0.00 | 0.91±0.00 | 0.036 | 0.60±0.00 | 0.59±0.00 | 0.566 |
Values are presented as mean±standard deviation or number (%).
NRT, number of remaining natural teeth; BMI, body mass index; ASM, appendicular skeletal muscle mass; Ht, height.
The p-values were based on a chi-square test for categorical variables and t-test for continuous variables.
Multivariate regression for skeletal muscle mass index (SMI) per 1 NRT increase and according to dichotomized NRT (<20 or ≥20)
Men | Women | |||||
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β | SE | p value | β | SE | p value | |
Continuous: per 1 NRT increase | ||||||
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Unadjusted model | 0.018 | 0.003 | <0.001 | −0.007 | 0.002 | <0.001 |
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Adjusted model | ||||||
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Model 1 | 0.006 | 0.003 | 0.016 | −0.007 | 0.002 | <0.001 |
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Model 2 | 0.011 | 0.003 | 0.001 | 0.004 | 0.002 | 0.121 |
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Dichotomous: NRT<20 (reference) vs. NRT ≥20 | ||||||
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Unadjusted model | 1.295 | 0.060 | <0.001 | −0.008 | 0.046 | 0.856 |
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Adjusted model | ||||||
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Model 1 | 0.127 | 0.045 | 0.005 | −0.153 | 0.034 | <0.001 |
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Model 2 | 0.215 | 0.059 | <0.001 | −0.097 | 0.046 | 0.035 |
NRT, number of remaining natural teeth; SE, standard error.
Model 1 was adjusted for age and body mass index (BMI). Model 2 was adjusted for age, BMI, smoking, alcohol, physical activity, protein intake, energy intake, calcium intake, marital status, income, fasting basal glucose, medication administration, and prostheses.