
The elderly population in Korea is steadily increasing, expected to transition into a super-aged society by 20251). In 2020, the frailty prevalence among the elderly was 23%, reaching 56% when considering pre-frailty, indicating that over half of the aged 65 and older population is at risk of frailty2). Recognizing the importance of preventing frailty for healthy aging and overall well-being in older adults, it becomes imperative to discuss appropriate interventions and timely strategies.
Frailty is state of increased functional dependence, vulnerability, or a heightened likelihood of hospitalization due to age-related physical functional decline3). A primary preventive approach to efficiently address frailty is either inhibiting its occurrence4) or delaying its onset. Achieving this goal requires the identification of risk factors contributing to frailty. Previous studies have highlighted factors such as low muscle mass5), malnutrition6), and poor oral health7) as significant contributors to frailty, underscoring the necessity for intervention in these areas. Oral frailty, specifically, is defined as age-related functional decline in the orofacial structure8). Individuals with oral frailty9) are at a two-fold higher risk of general frailty com-pared to those without, and oral frailty can influence the development of general frailty10). Because oral function affects life expectancy11) and contributes to improving the quality of life in the elderly12), thus, early identification and intervention are important.
Studies conducted in the UK have expanded the understanding of frailty, revealing its prevalence in adults aged 37 years and above, indicating that frailty is not limited to the elderly13). Similarly, research involving French middle-aged adults (50∼65 years) showed that 70% of this population is at risk for frailty14). Early detection and prevention of frailty in middle age can significantly influence the quality of life in older age, in addition, may reducing medical, hospitalization, and welfare-related public expenditures15). Despite the high prevalence of frailty among the middle-aged people in Korea, limited research has been conducted in this regard. Furthermore, existing studies have primarily focused on rehabilitation and recover of oral function, rather than emphasizing the critical importance of early prevention and intervention16).
This study aimed to identify the onset age for early intervention by investigating age ranges deviating from the ‘normal’ oral frailty status and assessing the association between age and oral frailty.
This cross-sectional study utilized stratified sampling with age and gender A survey was conducted through face-to-face interviews with adults aged 30 to 90 years residing in Gangwon province in May 2023. A total of 719 participants were informed of the study and provided consent to participate. The participants were assured that the collected data would not be used for other purposes. the study received approval from the Institutional Review Board of Yonsei University Mirae Campus (IRB No. 1041849-202211-SB-216-02).
Socio-economic and demographic variables included gender, age, education, income, and occupation. Gender was categorized into men and women, while age was grouped into 5-year intervals, resulting in 12 groups. Education was classified into 4 categories: ≤middle school, high school, 2/3-year College, and ≥4-year university. Income was measured in Korean Won (1,000 KRW) and was categorized into 6 grades: <2,000, 2,000∼2,999, 3,000∼3,999, 4,000∼4,999, 5,000∼5,999, and 6,000 or more. Occupation was grouped into eight categories based on the Korean Standard Classification of Occupations: managers/professions employees; office workers; service workers; sales workers; farmers and fishers; machine operators, daily labors, and simple labors; the others (soldiers, freelancers, non-response); and inoccupation (housewives, students).
The investigator assessed the number of present teeth face-to-face using a questionnaire. Participants with complete dentures were considered to have 0 present teeth. Those with prosthetic teeth (crowns and implants) were excluded, and the total number of teeth, including wisdom teeth, ranged from 0 to 32.
The condition of oral frailty was determined using a screening instrument for oral frailty reported by the Korean Academy of Geriatric Dentistry17). The questionnaire included 11 questions related to frailty symptoms and oral frailty symptoms, such as difficulties with chewing, swallowing, and speaking. The condition level of oral frailty was categorized based on the summed scores of 11 questions, ranging from 0 to 18.5. The three risk categories were ‘Normal (0∼0.5 points),’ ‘Risk (1∼3 points),’ and ‘High-risk (≥3.5 points).’ Those at ‘risk’ and ‘high-risk’ of oral frailty may require clinical examinations and diagnosis. The reliability of the screening instrument for oral frailty demonstrated a Cronbach’s alpha of 0.88.
Frailty was assessed using the Kihon Checklist (KCL) developed by the Ministry of Health, Labour and Welfare18). The Korean version of KCL, translated by Sunwoo et al.19), was revised for this study. It comprises seven dimensions, including frail condition, physical strength, nutritional status, oral function, cognitive function, and depression (24 items in total)20). The total score ranges from 0 (minimum) to 24 (maximum), with higher scores indicating more frailty. Participants were categorized into ‘Robust (0∼3 points),’ ‘Pre-frailty (4∼7 points),’ and ‘Frailty (≥8 points)’ based on frailty criteria. The reliability of the frailty instrument demonstrated a Cronbach’s alpha of 0.77.
Participants’ socio-economic and demographic characteristics, number of present teeth, and frailty status were analyzed using descriptive statistics. Cross-sectional analysis was performed for the socio-economic and demographic characteristics and oral frailty status as per frailty condition. To perform multiple logistic regression analysis, a score of “1” was given to ‘Normal’ among the oral frailty risk level, while a score of “0” was given to ‘Risk’ and ‘High-risk.’ The multiple logistic regression models were used to identify influencing factors in groups with oral frailty by age. Model I is a crude model. Model II adjusted for socio-economic and demographic characteristics (gender, education, income, and occupation), Model III adjusted for socio-economic and demographic characteristics and number of present teeth, and Model IV adjusted for socio-economic and demographic characteristics, number of present teeth, and frailty status. Data were analyzed using R (version: 4.3.1; R Core Team, 2023). The p-value of <0.05 was considered statistically significant.
Table 1 shows participants’ socio-economic and demographic characteristics. The mean age of the study population was 51.6±13.5 years, and 53.5% (385 of 719) were women. Most participants were in their 50s (50∼54, 55∼59 years of age), accounting for 24.9%. Most participants were 4-year university graduates, accounting for 35.6%, followed by high school (31.7%) and 2/3-year College (19.2%). At 21.3%, income of ‘5,000,000 KRW’ was the highest income, and most participants were sales workers (20.4%), followed by office workers (18.1%) and inoccupation (15.3%). The mean number of present teeth was 24.5±7.2 teeth. In frailty, 332 participants (46.2%) were robust, 203 (28.2%) were pre-frailty, and 184 (25.6%) were frailty.
Variable Distributions of the Study Subjects
Variable | Value |
---|---|
Total | 719 (100) |
Gender | |
Men | 334 (46.5) |
Women | 385 (53.5) |
Average age (y) | 51.6±13.5 |
Age (y) | |
30∼34 | 101 (14.0) |
35∼39 | 65 (9.0) |
40∼44 | 73 (10.2) |
45∼49 | 77 (10.7) |
50∼54 | 100 (13.9) |
55∼59 | 79 (11.0) |
60∼64 | 91 (12.7) |
65∼69 | 86 (12.0) |
70∼74 | 13 (1.8) |
75∼79 | 16 (2.2) |
80∼84 | 8 (1.1) |
85∼89 | 10 (1.4) |
Education | |
≤Middle school | 97 (13.5) |
High school | 228 (31.7) |
2/3-year College | 138 (19.2) |
≥4-year University | 256 (35.6) |
Income (1,000 KRW) | |
<2,000 | 117 (16.3) |
2,000∼2,999 | 90 (12.5) |
3,000∼3,999 | 151 (21.0) |
4,000∼4,999 | 108 (15.0) |
5,000∼5,999 | 153 (21.3) |
≥6,000 | 100 (13.9) |
Occupation | |
Managers and Professionals | 81 (11.3) |
Office workers | 130 (18.1) |
Service workers | 87 (12.1) |
Sales workers | 147 (20.4) |
Farmers and Fishers | 68 (9.5) |
Machine operators and Daily labors | 61 (8.5) |
The others | 35 (4.9) |
Inoccupation | 110 (15.3) |
Frailty | |
Robust | 332 (46.2) |
Pre-frailty | 203 (28.2) |
Frailty | 184 (25.6) |
Average number of present teeth | 24.5±7.2 |
Values are presented as n (%) or mean±standard deviation.
Table 2 classified the participants into normal, risk, and high-risk groups by oral frailty conditions, and socio-economic and demographic characteristics. Most participants (54.0%) were in the normal group, followed by 170 (23.6%) and 161 (22.4%) were in risk and high-risk groups, respectively. In the normal group, the mean age was 47.6±11.9 years old, and the mean age of the risk (52.0±12.8 years old) and high-risk (61.0±13.1 years old) groups was 5 and 14 years older than that of the normal group, respectively. In the normal group, participants aged 30∼34 years and who have income of 6,000,000 KRW were highest (p<0.001). The occupation shows the highest concentration in managers, professionals, and relevant employees (p<0.001). The mean number of present teeth was 26.1, 25.4, and 21.8 teeth for normal, risk, and high-risk groups, respectively, showing that as the number of present teeth decreases, the oral frailty score increases (p<0.001).
Oral Frailty According to Independent Variables
Variable | Total (n) | Oral Frailty | p | ||
---|---|---|---|---|---|
Normal | Risk | High-risk | |||
Total | 719 | 388 (54.0) | 170 (23.6) | 161 (22.4) | |
Gender | |||||
Men | 334 | 167 (50.0) | 82 (24.6) | 85 (25.4) | 0.098 |
Women | 385 | 221 (57.4) | 88 (22.9) | 76 (19.7) | |
Average age (y) | 51.6±13.5 | 47.6±11.9 | 52.0±12.8 | 61.0±13.1 | <0.001 |
Age (y) | |||||
30∼34 | 101 | 74 (73.3) | 21 (20.8) | 6 (5.9) | <0.001 |
35∼39 | 65 | 42 (64.6) | 18 (27.7) | 5 (7.7) | |
40∼44 | 73 | 53 (72.6) | 15 (20.5) | 5 (6.8) | |
45∼49 | 77 | 48 (62.3) | 13 (16.9) | 16 (20.8) | |
50∼54 | 100 | 58 (58.0) | 27 (27.0) | 15 (15.0) | |
55∼59 | 79 | 42 (53.2) | 19 (24.1) | 18 (22.8) | |
60∼64 | 91 | 36 (39.6) | 23 (25.3) | 32 (35.1) | |
65∼69 | 86 | 25 (29.1) | 28 (32.6) | 33 (38.4) | |
70∼74 | 13 | 5 (38.5) | 2 (15.4) | 6 (46.2) | |
75∼79 | 16 | 4 (25.0) | 2 (12.5) | 10 (62.5) | |
80∼84 | 8 | - | 1 (12.5) | 7 (87.5) | |
85∼89 | 10 | 1 (10.0) | 1(10.0) | 8 (80.0) | |
Education | |||||
≤Middle school | 97 | 24 (24.7) | 27 (27.8) | 46 (47.4) | <0.001 |
High school | 228 | 106 (46.5) | 48 (21.1) | 74 (32.5) | |
2/3-year College | 138 | 82 (59.4) | 37 (26.8) | 19 (13.8) | |
≥4-year University | 256 | 176 (68.8) | 58 (22.6) | 22 (8.6) | |
Income (1,000 KRW) | |||||
<2,000 | 117 | 49 (41.9) | 22 (18.8) | 46 (39.3) | <0.001 |
2,000∼2,999 | 90 | 48 (53.3) | 26 (28.9) | 16 (17.8) | |
3,000∼3,999 | 151 | 90 (59.6) | 40 (26.5) | 21 (13.9) | |
4,000∼4,999 | 108 | 48 (44.4) | 24 (22.2) | 36 (33.3) | |
5,000∼5,999 | 153 | 87 (56.9) | 34 (22.2) | 32 (20.9) | |
≥6,000 | 100 | 66 (66.0) | 24 (24.0) | 10 (10.0) | |
Occupation | |||||
Managers and Professionals | 81 | 57 (70.4) | 19 (23.5) | 5 (6.2) | <0.001 |
Office workers | 130 | 82 (63.1) | 26 (20.0) | 22 (16.9) | |
Service workers | 87 | 50 (57.5) | 25 (28.7) | 12 (13.8) | |
Sales workers | 147 | 74 (50.3) | 34 (23.1) | 39 (26.6) | |
Farmers and Fishers | 68 | 30 (44.1) | 20 (29.4) | 18 (26.5) | |
Machine operators and Daily labors | 61 | 24 (39.3) | 17 (27.9) | 20 (32.8) | |
The others | 35 | 19 (54.3) | 7 (20.0) | 9 (25.7) | |
Inoccupation | 110 | 52 (47.3) | 22 (20.0) | 36 (32.7) | |
Number of present teeth | 24.5±7.2 | 26.1±5.7 | 25.4±6.7 | 21.8±9.6 | <0.001 |
Frailty | |||||
Robust | 332 | 242 (72.9) | 76 (22.9) | 14 (4.2) | <0.001 |
Pre-frailty | 203 | 111 (54.7) | 56 (27.6) | 36 (17.7) | |
Frailty | 184 | 35 (19.0) | 38 (20.7) | 111 (60.3) |
Values are presented as n (%) or mean±standard deviation.
Fig. 1 shows the distribution of oral frailty conditions by age. For participants aged 30 to 34 years, the proportion of participants who were in normal, risk, and high-risk groups was 73.3%, 20.8%, and 5.9%, respectively. The highest distribution was observed in the normal group. Among those aged 60∼64 years, the proportion of participants in the normal group was 39.6%, and the proportion of those in the risk and high-risk groups was 60.4%. Among those aged 65∼69 years, the proportion of participants in the normal, risk, and high-risk groups was 29.1%, 32.6%, and 38.4%, respectively. The distribution of high-risk group was higher than the normal group in those aged 65 years and older. As age increases, the distribution of the normal group decreased, whereas the distribution of the high-risk group of oral frailty increased.
Table 3 shows the results of logistic regression analysis performed to investigate influencing factors on oral frailty by age group. Compared to those aged 30∼34 years, odds ratio (OR) for oral frailty to be in normal condition was significant for those aged 50∼54 years and older (OR 0.50, 95% confidence interval [CI] 0.28∼0.91). As age increased, the OR decreased. Similar results were observed in the Model II (OR 0.52, 95% CI 0.28∼0.97) and Model III (OR 0.53, 95% CI 0.28∼0.99). In the Model IV, OR was significant for those aged 55∼59 years and older (OR 0.46, 95% CI 0.22∼0.94). Moreover, OR for oral frailty to be in normal status was 0.45 (95% CI 0.31∼0.65) and 0.09 (95% CI 0.06∼0.13) times higher for pre-frailty and frailty, respectively, compared to robust. Similar results were observed even if gender, education, occupation, and income were adjusted. According to the results, oral frailty condition changes according to the frailty condition. Consequently, age is likely to be the remarkable influencing factor for oral frailty regardless of socio-economic and demographic status, and frailty status is also associated with the oral frailty status via age.
Multivariable Logistic Regression
Model I | Model II | Model III | Model IV | ||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
OR | 95% CI | p | OR | 95% CI | p | OR | 95% CI | p | OR | 95% CI | p | ||||
Age (y) | |||||||||||||||
30∼34 | Intercept | Intercept | Intercept | Intercept | |||||||||||
35∼39 | 0.67 | 0.34∼1.31 | 0.237 | 0.54 | 0.27∼1.08 | 0.082 | 0.54 | 0.27∼1.08 | 0.082 | 0.60 | 0.28∼1.26 | 0.178 | |||
40∼44 | 0.97 | 0.49∼1.92 | 0.922 | 0.87 | 0.43∼1.77 | 0.701 | 0.90 | 0.44∼1.83 | 0.764 | 0.96 | 0.46∼2.03 | 0.957 | |||
45∼49 | 0.60 | 0.32∼1.14 | 0.121 | 0.60 | 0.31∼1.18 | 0.140 | 0.61 | 0.31∼1.20 | 0.155 | 0.71 | 0.35∼1.46 | 0.374 | |||
50∼54 | 0.50 | 0.28∼0.91 | 0.024 | 0.52 | 0.28∼0.97 | 0.041 | 0.53 | 0.28∼0.99 | 0.046 | 0.54 | 0.28∼1.04 | 0.074 | |||
55∼59 | 0.41 | 0.22∼0.77 | 0.006 | 0.43 | 0.22∼0.85 | 0.015 | 0.44 | 0.22∼0.86 | 0.017 | 0.45 | 0.22∼0.93 | 0.035 | |||
60∼64 | 0.24 | 0.13∼0.43 | <0.001 | 0.26 | 0.13∼0.49 | <0.001 | 0.26 | 0.13∼0.50 | <0.001 | 0.33 | 0.16∼0.66 | 0.002 | |||
65∼69 | 0.15 | 0.08∼0.28 | <0.001 | 0.16 | 0.08∼0.33 | <0.001 | 0.17 | 0.08∼0.35 | <0.001 | 0.24 | 0.11∼0.51 | <0.001 | |||
70∼74 | 0.23 | 0.06∼0.74 | 0.016 | 0.22 | 0.06∼0.81 | 0.025 | 0.26 | 0.06∼1.01 | 0.054 | 0.27 | 0.06∼1.09 | 0.113 | |||
75∼79 | 0.12 | 0.03∼0.38 | 0.001 | 0.13 | 0.03∼0.47 | 0.003 | 0.15 | 0.03∼0.57 | 0.007 | 0.22 | 0.05∼0.88 | 0.068 | |||
80∼84 | 0.00 | - | 0.974 | 0.00 | - | 0.973 | 0.00 | - | 0.973 | 0.00 | - | 0.973 | |||
85∼89 | 0.04 | 0.00∼0.23 | 0.003 | 0.05 | 0.00∼0.37 | 0.011 | 0.07 | 0.00∼0.51 | 0.023 | 0.11 | 0.00∼0.86 | 0.105 | |||
AIC | 926.4 | 921.53 | 922.74 | 839.16 | |||||||||||
Frailty | |||||||||||||||
Robust | Intercept | Intercept | Intercept | Intercept | |||||||||||
Pre-frailty | 0.45 | 0.31∼0.65 | <0.001 | 0.45 | 0.30∼0.66 | <0.001 | 0.46 | 0.31∼0.68 | <0.001 | 0.49 | 0.32∼0.73 | 0.001 | |||
Frailty | 0.09 | 0.06∼0.13 | <0.001 | 0.10 | 0.06∼0.16 | <0.001 | 0.10 | 0.06∼0.17 | <0.001 | 0.12 | 0.07∼0.19 | <0.001 | |||
AIC | 852.68 | 843.72 | 843.2 | 839.16 |
OR:odds ratio, CI: confidence intervals, AIC: Akaike information criterion.
Model I Unadjusted model. Model II adjusted for Gender, Education, Income and Occupation. Model III adjusted for Gender, Education, Income, Occupation and Number of present teeth. Model IV adjusted for Gender, Education, Income, Occupation, Number of present teeth and Frailty group.
This study was to explore the onset age for early intervention in oral frailty, conducted cross-sectional a face-to-face survey, including 719 participants (51.6±13.5 years). Findings showed that oral frailty is associated with age and frailty. Notably, a significant deviation from the ‘normal’ status of oral frailty occurred among individuals aged ‘50∼54 years.’
Early intervention in frailty is crucial for identifying and mitigating risk factors, potentially reducing the prevalence of dysfunction, and yielding economic benefits, including a decrease in hospitalization and medical expenses21,22). Early intervention can enhance overall health and quality of life during old age, contributing to a larger population of healthy older adults and ensuring a more active aging population23).
Frailty is recognized as an age-related symptom, and previous research has illustrated that aging does not progress uniformly throughout life but speeds up at specific ages, such as 34, 60, and 78 years old24). We observed the aging process to start approximately 34 years old, with an increased risk of frailty from that point onwards.
In Korea, the definition and concept of older adults varies on the purposes (i.e. starting point of welfare benefits and retirement, etc.) The Welfare of senior citizen Act25) and the Long-Term Care Insurance Act26) both define older adults as those aged ≥65 years, or those aged <65 years with senile diseases like dementia/cerebrovascular diseases. Although the conventional definition considers individuals aged 65 years or older as so-called “elderly and/or older adults”. This study revealed that 71% of those aged 65 years and older were already at risk or high-risk for oral frailty, emphasizing the need for early intervention in middle-aged adults before they reach older adulthood.
Early intervention in oral frailty can be achieved through national screening programs for the transitional ages, from middle-aged to old-aged. Health risk factors and chronic diseases can be detected and managed early by this program for those aged 65 and older receiving insurance benefits. People will be screened for eyesight, hearing, osteoporosis (for women), depression (70 years old), and teeth27). To monitor oral frailty, oral health questionnaires should include items related to it. Early intervention in oral frailty can delay the onset of oral dysfunction, improving quality of life in relation to oral health.
This study has some limitations. First, this study population was limited to Gangwon province of Korea. It could not be generalized to the entire population. Second, there is a possibility that this study could be biased by unmeasured factors such as multimorbidity, polypharmacy, etc. Third, this study could not be confirmed causality between age and oral frailty due to its cross-sectional design.
None.
No potential conflict of interest relevant to this article was reported.
This study was approved by the institutional review board of Yonsei University (IRB No.1041849-202211-SB-216-02).
Conceptualization: Hye-Lim Hong and Nam-Hee Kim. Data acquisition: Hye-Lim Hong and Nam-Hee Kim. Formal analysis: Hye-Lim Hong. Funding: Nam-Hee Kim. Supervision: Nam-Hee Kim. Writing–original draft: Hye-Lim Hong and Nam-Hee Kim. Writing–review & editing: Hye-Lim Hong and Nam-Hee Kim.
This research was supported by “Regional Innovation Strategy (RIS)” through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (MOE) (2022RIS-005).
Data files are available upon request.
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