Literature DB >> 29389975

Does poor oral health status increase the risk of falls?: The JAGES Project Longitudinal Study.

Yuki Mochida1, Tatsuo Yamamoto1, Shinya Fuchida1, Jun Aida2, Katsunori Kondo3,4,5.   

Abstract

We sought to examine if self-reported oral health conditions regarding difficulty eating tough foods, dry mouth, choking, number of teeth and denture use are associated with incident falls. Our study was based on panel data from the Japan Gerontological Evaluation Study conducted in 2010 and 2013 using self-administered questionnaires. Data from 19,995 male and 20,858 female community-dwelling older people aged ≥65 years without a history of falls within the previous year in 2010 were analyzed. Multilevel logistic regression models were used to determine the association between poor oral health in 2010 and multiple incident falls in 2013 after adjusting for possible confounders and considering differences in municipalities. The percentage of males and females who reported falls in 2013 were 2.4% and 2.1%, respectively. After adjusting for age, educational attainment, equivalized income, depression, self-rated health, instrumental activities of daily living, body mass index, present illness related to falls, social participation, walking in min/day, alcohol drinking status, and municipality population density, dry mouth in males (odds ratio [OR] = 1.41; 95% confidence interval [CI]: 1.12-1.77) and choking in females (OR = 1.64; 95% CI: 1.27-2.11) were significantly associated with incident falls. Difficulty eating tough foods in both sexes and choking in males were marginally associated with incident falls (p<0.1). Females having 10-19 teeth without dentures (OR = 1.63; 95% CI: 1.14-2.31), ≤9 teeth with dentures (OR = 1.36; 95% CI: 1.03-1.80), and ≤9 without dentures (OR = 1.46; 95% CI: 1.02-2.08) were significantly associated with incident falls compared with those having ≥20 teeth, respectively. These findings suggest that poor oral function, having fewer teeth, and not using dentures are predictors of incident falls. Further studies are needed to determine whether improving oral health can reduce the risk of falls.

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Mesh:

Year:  2018        PMID: 29389975      PMCID: PMC5794168          DOI: 10.1371/journal.pone.0192251

Source DB:  PubMed          Journal:  PLoS One        ISSN: 1932-6203            Impact factor:   3.240


Introduction

As the world’s population continues to age, falls are becoming an increasingly major public health problem. In England, it has been reported that approximately 28–35% of older people aged ≥65 years experienced a fall in the previous year [1,2]. Injuries from falls can range from light bruises to hip fractures, and can even result in death [3]. At least 10% of fallers in the U.S. experienced serious injuries [4]. In addition, falls and fractures account for 12.2% of all causes leading to the need for long-term care among older people in Japan [5]. It is therefore important to identify risk factors for falls. Although little can be done about biological risk factors such as age, sex, and chronic illness, behavioral risk factors such as lack of exercise and medication use can be modified by interventions and changes in individual behavior [6]. One recent study revealed that having a low number of teeth and not using dentures were associated with a higher frequency of falls [7]. A longitudinal study involving 4,425 community-dwelling older people showed that those having ≤19 teeth without dentures had a significantly higher risk for incident falls than those having ≥20 teeth [7]. However, the association between oral function and falls remains controversial. One cross-sectional study involving 87 older people showed an association between a decrease in occlusal function and postural instability [8]. Another longitudinal study involving 348 older people showed that occlusal disharmony is a risk factor for a decrease in balance function [9]. A cross-sectional study involving 34 frail older people showed that lower occlusal force was associated with a higher risk of falls, as assessed using a 21-item fall risk index [10]. On the other hand, a longitudinal study found no significant associations between self-reported chewing ability and incident falls [7]. Swallowing is another oral function closely linked to chewing ability because it follows mastication and bolus formation. Saliva production also contributes to mastication, bolus formation, and swallowing [11]. Questions regarding three oral functions, difficulty eating tough foods, dry mouth and choking are included on the basic screening checklist for frail older people in the Japanese long-term care insurance system [12]. A cross-sectional study reported that these questions were significantly associated with falls [13]; however, their temporal relationship remains unknown. If a decline in oral function is found to precede falls, it could become an accurate predictor of falls and be useful for collaborating oral health and fall prevention in older people from the perspective of health policy. Therefore, the present study investigated the association between oral function and incident falls using longitudinal data from community-dwelling older people. In addition, it has been suggested that falls show regional differences [14], so the association between number of teeth and/or denture use and incident falls was also investigated to verify the reproducibility of the results of a previous study [7] using a large sample and multilevel logistic regression models.

Materials and methods

Study population

Data from a longitudinal study, collected as part of the Japan Gerontological Evaluation Study (JAGES) project, an ongoing Japanese prospective cohort study [15,16], were used for the present study. The JAGES aims to investigate factors associated with the loss of healthy years, such as functional decline, cognitive impairment, and death among non-institutionalized older people. The JAGES sample was restricted to those who did not already have physical or cognitive disability at baseline, which was defined as not receiving long-term public care insurance benefits and having self-reported dependence in walking, toileting, and bathing. Our analyses used the panel data from two surveys. The baseline survey was conducted between August 2010 and January 2012 among 141,452 people aged ≥65 years. Self-administered questionnaires were mailed to the entire population of 10 municipalities, and randomly to selected residents in 14 municipalities based on the official residential registers obtained from the respective municipal governments. A total of 92,272 people responded to the questionnaires (response rate: 65.2%). A follow-up survey using self-administered questionnaires was conducted between October 2013 and December 2013 on the same respondents in the same municipalities. Collectively, 62,438 individuals completed both the 2010 and 2013 questionnaires. Data from 40,853 respondents (19,995 males and 20,858 females) were used for the analyses after excluding those from 2,007 who already had self-reported dependence in walking, toileting, and bathing at baseline, 16,240 who had experienced single or multiple falls at baseline, 2,675 who provided no information on falls at baseline, and 663 who provided no information on falls at follow-up (Fig 1. Flow chart of the participant selection process). The JAGES protocol was reviewed and approved by the Nihon Fukushi University Ethics Committee (No. 10–05), and the Ethical Committee of Kanagawa Dental University (No. 466) approved the analysis of data in the present study.
Fig 1

Flow chart of the participant selection process.

Outcome variables

The incidence of falls was determined by asking, “How many times have you fallen within the past year?”, with possible answers of “multiple times”, “once”, or “none”. Multiple falls was utilized as an outcome after combining the last two categories because previous studies have shown that single fallers are more similar to nonfallers than to recurrent fallers on a range of medical, physical, and psychological risk factors [17-19].

Oral health variables

Oral function, including difficulty eating tough foods, dry mouth, and choking, and dental status were assessed using self-administered questionnaires. Difficulty eating tough foods, dry mouth, and choking were determined by asking, “Do you have any difficulties eating tough foods now compared with 6 months ago?”, “Do you often have dry mouth?”, and “Have you recently choked on your tea or soup?”, respectively, with possible answers dichotomized into yes and no, as utilized in a basic checklist for nursing care prevention in the Japanese long-term care insurance system [12]. Dental status was categorized as follows: having ≥20 teeth, having 10–19 teeth with dentures, having 10–19 teeth without dentures, having ≤9 teeth with dentures, and having ≤9 teeth without dentures.

Covariates

Factors associated with falls, including age [7,20,21], educational attainment [7,22], equivalized income [22,23], depression [7,21], self-rated health [7,24], instrumental activities of daily living (IADL) [13], body mass index (BMI) [24], present illness related to falls [20,21], social participation [22], walking in min/day [22], alcohol drinking status [25] and population density [22], were used as covariates. Age was categorized as follows: 65–69, 70–74, 75–79, 80–84 or ≥85 years. Educational attainment was categorized as follows: ≤9, 10–12, or ≥13 years. Equivalized income was calculated by dividing household income by the square root of the number of household members, and was categorized as follows: ≤1,999,999 JPY (1 USD = 100 JPY), 2,000,000–3,999,999 JPY, or ≥4,000,000 JPY. Depression was assessed using the Japanese short version of the Geriatric Depression Scale-15 [26], and was grouped into three categories: 0–4 (no), 5–9 (mild), or 10–15 (moderate to severe). Self-rated health was determined by asking, “How is your health at present?”, with answers categorized as follows: “excellent”, “good”, “fair”, or “poor”. IADL was assessed using the Tokyo Metropolitan Institute of Gerontology Index of Competence (TMIG-IC) questionnaire [27], and categorized as follows: independence (13 points) or dependence (≤12 points). BMI was categorized into three groups: <18.5, 18.5–24.9, or ≥25.0. Self-reported current medical treatment for stroke, osteoporosis, joint disease/neuralgia, injury/fracture, impaired vision and/or impaired hearing was used as a variable for present illness related to falls and categorized into two groups: yes or no. Social participation was determined by asking, “Do you belong to the following organization or group?” in relation to the following types of community organizations: neighborhood/senior association, citizen/firefighting club, religious group, political group/organization, industrial or trade association, volunteer group, citizen/consumer group, hobby group, and sports club/group. Answers were categorized into two groups: participation (yes) or nonparticipation (no). Walking in min/day was categorized as follows: ≥90 min, 60–89 min, 30–59 min, or <30 min. Alcohol drinking status was categorized as follows: current, former, or never drinker. Municipality population density was categorized as follows: metropolitan (density over 4,000 people per km2), urban (density between 1,500 and 4,000 people per km2), semi-urban (density between 1,000 and 1,499 people per km2), and rural (density below 1,000 people per km2).

Statistical analysis

Categorical variables that included missing values were recorded by reassigning missing values to separate “data missing” categories to maximize the number of participants included in the statistical analysis and thereby maximize statistical power. In the follow-up survey, incident falls was defined as a history of multiple falls. First, univariate associations between incident falls and oral health variables and covariates in males and females were examined. Then, two-level (first level: individuals; second level: municipality) logistic regression models with random intercepts and fixed slopes were used for males and females separately to calculate multilevel odds ratios (ORs) and 95% confidence intervals (CIs) for incident falls at follow-up. In the first model, univariate ORs and 95% CIs were calculated for each oral health variable. In the second model, multilevel ORs and 95% CIs were calculated for each oral health variable after adjusting for age. In the third model, multilevel ORs and 95% CIs were calculated for each oral health variable after adjusting for all covariates, i.e., age, educational attainment, equivalized income, depression, self-rated health, IADL, BMI, present illness related to falls, social participation, walking in min/day and alcohol drinking status, as individual-level variables, and population density as a municipality-level variable. In the fourth model, difficulty eating tough foods, dry mouth, and choking were simultaneously added after adjusting for all covariates. In the fifth model, all oral health variables were simultaneously added after adjusting for all covariates and checking the multicollinearity among the oral health variables. All statistical analyses were performed using MLwiN 2.36 (Centre for Multilevel Modelling, University of Bristol, Bristol, UK) and IBM SPSS Statistics (version 23.0; IBM Co., New York, NY, USA).

Results

The number (%) of males and females who reported having multiple falls in the follow-up survey were 475 (2.4%) and 430 (2.1%), respectively. Table 1 shows the rates of males and female fallers at follow-up according to oral health variables and covariates. In both sexes, participants with difficulty eating tough foods, dry mouth, choking, poor dental status, older age, low educational attainment, low equivalized income, depression, poor self-rated health, low IADL, low BMI, present illness related to falls, social nonparticipation, <30 min walking/day, status as a former drinker and living in rural areas were more likely to report the occurrence of incident falls.
Table 1

Univariate associations of oral health variable and covariates with incident falls in males and females.

MalesFemales
TotalFallersTotalFallers
nn%nn%
Oral health variables
Difficulty eating tough foodsNo147492952.00157862701.71
Yes42611553.6441791353.23
Data missing985252.54893252.80
Dry mouthNo157933222.04164802961.80
Yes30611244.0531951053.29
Data missing1141292.541183292.45
ChokingNo166683602.16175393101.77
Yes2302934.042377903.79
Data missing1025222.15942303.18
Dental status≥20 teeth79651301.6379731051.32
10–19 teeth with dentures3280712.163101561.81
10–19 teeth without dentures1707412.401891482.54
≤9 teeth with dentures43791292.9546011342.91
≤9 teeth without dentures1712643.741659523.13
Data missing952404.201633352.14
Covariates
Age (years)65–6973811001.357523781.04
70–7462241221.9665711342.04
75–7940741263.0942781212.83
80–841822854.671874703.74
≥85494428.50612274.41
Educational attainment (years)≤976942373.0896032182.27
10–1268571372.0077201401.81
≥134867751.542798411.47
Data missing577264.51737314.21
Equivalized income (10,000 yen)Low (≤199)77382152.7882271682.04
Middle (200–399)79371381.7466681171.75
High (≥400)2219452.031923291.51
Data missing2101773.6640401162.87
DepressionNo137912621.90133972121.58
Mild29971103.672945842.85
Moderate to severe799486.01719334.59
Data missing2408552.2837971012.66
Self-rated healthExcellent3081401.302887321.11
Good141372962.09152692861.87
Fair23451144.862228924.13
Poor295196.44224188.04
Data missing13764.3825020.80
IADLIndependence (13)70121341.91106721521.42
Dependence (≤12)112092892.5881572102.57
Data missing1774522.932029683.35
Body mass index<18.5826283.391609352.18
18.5–24.9138353192.31142222481.74
≥2546401022.2040261102.73
Data missing694263.751001373.70
Present illness related to falls*No106122312.1891671551.69
Yes39791503.7763222043.23
Data missing5404941.745369711.32
Social participationNo32801003.053191942.95
Yes144762932.02147032581.75
Data missing2239823.662964782.63
Walking in min/day≥903760731.943433581.69
60–893634742.043199521.63
30–5969991562.2374151492.01
<3053191643.0859761442.41
Data missing28382.83835273.23
Alcohol drinking statusNever drinker64711692.61162053412.10
Former drinker985272.7417995.03
Current drinker115822552.203447541.57
Data missing957242.511027262.53
Population density (person per square kilometers)Metropolitan (≥4,000)53401092.045536861.55
Urban (1,500–3,999)50791042.054913791.61
Semiurban (1,000–1,499)45051172.604673972.08
Rural (≤999)50711452.8657361682.93

*Stroke, osteoporosis, joint disease/neuralgia, injury/fracture, impaired vision and/or impaired hearing.

*Stroke, osteoporosis, joint disease/neuralgia, injury/fracture, impaired vision and/or impaired hearing. Table 2 shows the ORs (95% CIs) for male fallers according to oral health variables in the five multilevel logistic regression models. In Models 1 and 2, all oral health variables were significantly associated with incident falls. In Model 3, the associations between falls and difficulty eating tough foods, dry mouth, and choking remained significant; however, no significant associations were found between dental status and incident falls. In Models 4 and 5, three kinds of difficulties in oral function were associated with incident falls, although the statistical significance was marginal for difficulty eating tough foods in Model 5 and choking in Models 4 and 5 (p<0.10). In Model 5, dry mouth had a significantly high OR (1.41; 95% CI: 1.12–1.77); however, no significant association was observed between dental status and incident falls.
Table 2

Odds ratios and their 95% confidence intervals of oral health variables in the adjusted multilevel logistic regression models in males.

Model 1Model 2Model 3Model 4Model 5
OR95% CIpOR95% CIpOR95% CIpOR95% CIpOR95% CIp
LowHighLowHighLowHighLowHighLowHigh
Difficulty eating tough foods (reference: No)Yes1.861.522.26<0.0011.701.392.07<0.0011.331.081.640.0071.271.031.560.0281.230.991.520.060
Data missing1.300.851.970.2221.180.781.790.4411.020.531.980.9452.120.865.210.1031.980.804.890.139
Dry mouth (reference: No)Yes2.031.642.51<0.0011.901.532.35<0.0011.491.191.86<0.0011.411.121.770.0031.411.121.770.003
Data missing1.270.861.870.2331.150.781.690.4910.890.511.550.6841.050.522.100.8981.040.522.090.909
Choking (reference: No)Yes1.911.512.41<0.0011.671.322.11<0.0011.371.071.740.0121.240.971.590.0921.240.971.590.089
Data missing1.010.651.560.9820.920.591.430.7180.620.321.200.1570.370.131.040.0580.380.131.060.065
Dental status (reference: ≥20 teeth)10–19 teeth with dentures1.330.991.790.0561.260.941.690.2191.180.881.590.2651.120.831.510.465
10–19 teethwithout dentures1.471.032.100.0351.370.961.960.0871.160.811.670.4101.130.791.630.504
≤9 teethwith dentures1.811.412.32<0.0011.391.081.800.0111.180.911.530.2031.120.861.460.401
≤9 teethwithout dentures2.301.693.12<0.0011.751.282.38<0.0011.360.991.870.0591.290.931.780.125
Data missing2.711.883.91<0.0012.031.402.93<0.0011.521.032.240.0331.460.992.160.057

Model 1: Univariate analysis

Model 2: Age-adjusted analysis

Model 3: Educational attainment, equivalized income, depression, self-rated health, IADL, body mass index, present illness related falls, social participation, walking in min/day, alcohol drinking status and population density were added to model 2. Oral health variables were not simultaneously included.

Model 4: Adjusted variables in model 3 and oral health variables were simultaneously included.

Model 5: All variables are included into the same model.

Model 1: Univariate analysis Model 2: Age-adjusted analysis Model 3: Educational attainment, equivalized income, depression, self-rated health, IADL, body mass index, present illness related falls, social participation, walking in min/day, alcohol drinking status and population density were added to model 2. Oral health variables were not simultaneously included. Model 4: Adjusted variables in model 3 and oral health variables were simultaneously included. Model 5: All variables are included into the same model. Table 3 shows the ORs (95% CIs) for female fallers according to oral health variables in the five multilevel logistic regression models. In Models 1–3, all oral health variables were significantly associated with incident falls. In Model 4, difficulty eating tough foods and choking were significantly associated with incident falls; however, no significant association was observed for dry mouth. In Model 5, choking had a significantly high OR (1.64; 95% CI: 1.27–2.11); however, no significant association was found between dry mouth and incident falls. The statistical significance for difficulty eating tough foods was marginal (p<0.10). Furthermore, compared with females having ≥20 teeth, those having 10–19 teeth without dentures, ≤9 teeth with dentures, and ≤9 without dentures had significantly increased risk for incident falls, at 1.63-fold (95% CI: 1.14–2.31), 1.36-fold (95% CI: 1.03–1.80), and 1.46-fold (95% CI: 1.02–2.08), respectively.
Table 3

Odds ratios and their 95% confidence intervals of oral health variables in the adjusted multilevel logistic regression models in females.

Model 1Model 2Model 3Model 4Model 5
OR95% CIpOR95% CIpOR95% CIpOR95% CIpOR95% CIp
LowHighLowHighLowHighLowHighLowHigh
Difficulty eating tough foods (reference: No)Yes1.921.552.37<0.0011.731.392.14<0.0011.411.131.750.0021.321.061.650.0151.250.991.570.058
Data missing1.661.092.520.0181.551.022.360.0421.230.702.180.4671.130.522.430.7621.140.522.460.748
Dry mouth (reference: No)Yes1.901.522.39<0.0011.751.392.20<0.0011.381.081.750.0091.210.951.540.1301.210.951.540.132
Data missing1.370.932.020.1151.260.851.870.2460.930.571.510.7560.600.301.170.1350.610.311.200.149
Choking (reference: No)Yes2.231.752.83<0.0012.061.612.62<0.0011.731.352.21<0.0011.631.262.09<0.0011.641.272.11<0.001
Data missing1.831.252.690.0021.721.172.530.0061.550.922.590.0972.071.044.120.0372.071.044.130.038
Dental status (reference: ≥20 teeth)10–19 teethwith dentures1.360.981.890.0691.290.921.790.1351.250.901.740.1811.190.851.660.310
10–19 teethwithout dentures1.921.362.71<0.0011.831.292.600.0011.681.182.380.0041.631.142.310.007
≤9 teethwith dentures2.181.682.83<0.0011.691.292.22<0.0011.461.111.910.0061.361.031.800.030
≤9 teethwithout dentures2.301.643.24<0.0011.761.252.500.0011.551.092.210.0141.461.022.080.038
Data missing1.601.082.360.0191.220.821.810.3250.970.651.450.8750.910.611.380.670

Model 1: Univariate analysis

Model 2: Age-adjusted analysis

Model 3: Educational attainment, equivalized income, depression, self-rated health, IADL, body mass index, present illness related falls, social participation, walking in min/day, alcohol drinking status and population density were added to model 2. Oral health variables were not simultaneously included.

Model 4: Adjusted variables in model 3 and oral health variables were simultaneously included.

Model 5: All variables are included into the same model.

Model 1: Univariate analysis Model 2: Age-adjusted analysis Model 3: Educational attainment, equivalized income, depression, self-rated health, IADL, body mass index, present illness related falls, social participation, walking in min/day, alcohol drinking status and population density were added to model 2. Oral health variables were not simultaneously included. Model 4: Adjusted variables in model 3 and oral health variables were simultaneously included. Model 5: All variables are included into the same model.

Discussion

The results of the present study suggest that older people reporting poor oral function, including difficulty eating tough foods, dry mouth, and choking, are more likely to experience falls. These results agree with those from a previous cross-sectional study showing associations between the three questions and falls [13], and further clarify the temporal relationship between poor oral function and incident falls. In the Japanese long-term care insurance system, three questions are used to screen subjects with poor oral function and encourage participation in care prevention services [12]. The results from the present study suggest that the integration of these questions into those regarding fall risk could improve the accuracy of the assessments. Further studies are needed to determine whether improvement of oral function may reduce the risk of falls. Several possible explanations for the association between poor oral function and incident falls can be envisaged. First, there may be other underlying factors between poor oral health and incident falls, although some adjustments for possible confounders have already been made. For example, some medications are associated with dry mouth [28], and patients treated with such medications are more likely to experience falls [6]. The variable, self-reported present illnesses related to dry mouth, which includes cancer, heart disease, hypertension, diabetes, obesity, hyperlipidemia, respiratory illness, gastrointestinal illness, mental illness, urinary disease and sleep disorder [28], was added to Models 3–5 in consideration of the effects of medication on the association between dry mouth and falls; however, no significant changes were observed in the ORs for dry mouth (data not shown). Further studies using patients’ medication data are necessary to examine the possibility of residual confounders. Neuromuscular disorders may also represent an underlying factor because they can cause symptoms such as swallowing disorders [29] and an increased risk of falls [6]. To address this issue, two variables of physical activity, ascertained by asking the participants “Do you go upstairs without holding on to the handrail or the wall?” and “Do you get up out of a chair without holding anything?”, with possible answers dichotomized into yes and no [22], were added to Models 3–5. No significant changes were observed in the ORs for difficulty eating tough foods or choking (data not shown); however, further studies using data regarding neuromuscular conditions are needed to address the possibility of residual confounders. Second, a decline in oral function may be part of a self-perpetuating cycle of frailty [30], which could in turn increase the risk of falls. Several studies have reported associations between chewing ability and physical fitness, such as lower extremity dynamic strength and equilibrium [31], which is a primary cause of falls [32]. One review showed that swallowing or chewing problems and poor oral intake were associated with an increased likelihood of weight loss [33]. We were unable to consider all potential confounders regarding general frailty because the present study was observational. Although further studies are necessary to examine the causal associations between incident falls and dry mouth and choking, the findings suggest that these indicators could be used as predictors. Another possibility is that poor oral function could increase the degree of risk factors for falls, such as depression. One recent longitudinal study reported that older people who experienced more difficulty chewing tough foods developed depressive symptoms [16], which is a risk factor for incident falls [7,21]. However, depression was adjusted as a covariate in the present study, so other pathways may be involved. In another previous study, analyses were not conducted separately by sex because of the relatively small sample size [7]. Balance performance in females was worse than that in males among older people [34, 35], suggesting that the effects of dental status on incident falls may be significant in females, but not in males. The ORs for females having 10–19 teeth without dentures, but not for those having 10–19 teeth with dentures, were significantly high. These results agree with those of a previous study [7], even though in that study, 10–19 teeth and ≤9 teeth were combined in the same category. The ORs for three oral function variables in Model 4 were lower than were those in Model 3, indicating an association between these variables. In addition, the ORs for difficulty eating tough foods and dental status in Model 5 were lower than were those in Model 3, indicating an association. From the results of present study, we could not conclude whether oral function and dental status were the cause of falls, or whether they were mediators between systemic conditions and falls. However, our results do show that poor oral function and dental status significantly increased the risk of falls, even after adjusting for variables in relation to systemic conditions. Therefore, we consider that in addition to the effect of systemic conditions, oral function and dental status, especially occlusion, exert a direct effect on incident falls. One possible explanation for the mechanism between falls and occlusion is the effect of jaw position on body posture [36]. Proprioceptive receptors of the masticatory muscular system and dentoalveolar ligaments provide sensory afferent input [37]; hence, poor dental occlusion may decrease that proprioception, thereby interfering with the stability of head posture and increasing the risk of falls. In fact, one longitudinal study showed that partial or complete loss of dental occlusion was associated with a decline in lower extremity dynamic strength and balance function [9], and a clinical study showed that denture use improves balance and control in older people [38]. The primary strength of this study was its large sample size, population-based sampling, and control for numerous confounding factors. In addition, a wide range of municipalities was surveyed to consider regional differences in incident falls [14]. This study did have several limitations. First, oral health status was based on self- rather than clinical assessments. However, the validity and reliability of self-assessed oral health status has been established and widely used in epidemiological studies [39]. Furthermore, the validity of our questionnaire for dental status has been confirmed [40]. Second, self-reported falls may not be completely factual. However, the associations between falls and demographic factors and other covariates were in the generally expected direction, suggesting that there may be sufficient value in these outcomes.

Conclusions

This longitudinal study using data from community-dwelling older people showed that poor oral function, including difficulty eating tough foods, dry mouth, and choking, was associated with incident falls. Moreover, having fewer teeth and not using dentures were independent predictors of falls in older females. Further studies are needed to determine whether improvement of oral health can reduce the risk of falls.
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6.  Risk factors for recurrent nonsyncopal falls. A prospective study.

Authors:  M C Nevitt; S R Cummings; S Kidd; D Black
Journal:  JAMA       Date:  1989-05-12       Impact factor: 56.272

7.  Effect of complete dentures on body balance during standing and walking in elderly people.

Authors:  Mai Okubo; Yukiko Fujinami; Shunsuke Minakuchi
Journal:  J Prosthodont Res       Date:  2009-10-09       Impact factor: 4.642

Review 8.  Factors associated with weight loss, low BMI, and malnutrition among nursing home patients: a systematic review of the literature.

Authors:  Bruce K Tamura; Christina L Bell; Kamal H Masaki; Elaine J Amella
Journal:  J Am Med Dir Assoc       Date:  2013-04-30       Impact factor: 4.669

9.  Sex differences in the postural sway characteristics of young and elderly subjects during quiet natural standing.

Authors:  Ji-Won Kim; Gwang-Moon Eom; Chul-Seung Kim; Da-Hye Kim; Jae-Ho Lee; Byung Kyu Park; Junghwa Hong
Journal:  Geriatr Gerontol Int       Date:  2010-01-19       Impact factor: 2.730

10.  Community social capital and tooth loss in Japanese older people: a longitudinal cohort study.

Authors:  Shihoko Koyama; Jun Aida; Masashige Saito; Naoki Kondo; Yukihiro Sato; Yusuke Matsuyama; Yukako Tani; Yuri Sasaki; Katsunori Kondo; Toshiyuki Ojima; Tatsuo Yamamoto; Toru Tsuboya; Ken Osaka
Journal:  BMJ Open       Date:  2016-04-05       Impact factor: 2.692

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  8 in total

Review 1.  Oral frailty indicators to target major adverse health-related outcomes in older age: a systematic review.

Authors:  Vittorio Dibello; Frank Lobbezoo; Madia Lozupone; Rodolfo Sardone; Andrea Ballini; Giuseppe Berardino; Anita Mollica; Hélio José Coelho-Júnior; Giovanni De Pergola; Roberta Stallone; Antonio Dibello; Antonio Daniele; Massimo Petruzzi; Filippo Santarcangelo; Vincenzo Solfrizzi; Daniele Manfredini; Francesco Panza
Journal:  Geroscience       Date:  2022-10-15       Impact factor: 7.581

2.  Differences in Falls between Older Adult Participants in Group Exercise and Those Who Exercise Alone: A Cross-Sectional Study Using Japan Gerontological Evaluation Study (JAGES) Data.

Authors:  Takahiro Hayashi; Katsunori Kondo; Satoru Kanamori; Taishi Tsuji; Masashige Saito; Akira Ochi; Susumu Ota
Journal:  Int J Environ Res Public Health       Date:  2018-07-05       Impact factor: 3.390

3.  Frailty is associated with susceptibility and severity of pneumonia in older adults (A JAGES multilevel cross-sectional study).

Authors:  Kousuke Iwai-Saito; Yugo Shobugawa; Jun Aida; Katsunori Kondo
Journal:  Sci Rep       Date:  2021-04-12       Impact factor: 4.379

Review 4.  Systematic Review of the Literature on Dental Caries and Periodontal Disease in Socio-Economically Disadvantaged Individuals.

Authors:  Stefano Cianetti; Chiara Valenti; Massimiliano Orso; Giuseppe Lomurno; Michele Nardone; Anna Palma Lomurno; Stefano Pagano; Guido Lombardo
Journal:  Int J Environ Res Public Health       Date:  2021-11-24       Impact factor: 3.390

5.  Influence of Controlled Stomatognathic Motor Activity on Sway, Control and Stability of the Center of Mass During Dynamic Steady-State Balance-An Uncontrolled Manifold Analysis.

Authors:  Cagla Fadillioglu; Lisa Kanus; Felix Möhler; Steffen Ringhof; Daniel Hellmann; Thorsten Stein
Journal:  Front Hum Neurosci       Date:  2022-03-25       Impact factor: 3.169

6.  Longitudinal Association Between Oral Status and Cognitive Decline Using Fixed-effects Analysis.

Authors:  Sakura Kiuchi; Taro Kusama; Kemmyo Sugiyama; Takafumi Yamamoto; Upul Cooray; Tatsuo Yamamoto; Katsunori Kondo; Ken Osaka; Jun Aida
Journal:  J Epidemiol       Date:  2021-07-10       Impact factor: 3.809

7.  Family social support and stability of preferences regarding place of death among older people: a 3-year longitudinal study from the Japan Gerontological Evaluation Study.

Authors:  Kenjiro Kawaguchi; Kazushige Ide; Katsunori Kondo
Journal:  Age Ageing       Date:  2022-09-02       Impact factor: 12.782

8.  Association between subjective oral dysfunction and locomotive syndrome in community-dwelling older adults.

Authors:  Misa Nakamura; Masakazu Imaoka; Hidetoshi Nakao; Mitsumasa Hida; Fumie Tazaki; Ryota Imai; Hirotoshi Utsunomiya; Hiroshi Hashizume
Journal:  Sci Rep       Date:  2021-06-15       Impact factor: 4.379

  8 in total

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