Abstract
Objectives
Muscle strength decreases with age, causing a decline in physical and oro‐facial function. However, the impact of physiological and pathophysiological factors on tongue pressure (TP) has not been clarified. The purpose of this systematic review and meta‐analysis was to compare and analyse TP and handgrip strength (HGS) between individuals aged <60 and ≥60 years, gender and need for care (independent older adults (IC) and older adults receiving nursing care (NC)). Furthermore, the effect of HGS in physical function on TP was examined.
Methods
Human clinical studies reporting HGS and TP were searched systematically using PubMed and Ichushi‐Web published from 1969 to Nov 2021. Random‐effects meta‐regressions were performed to compare between subgroups and to examine the association between HGS and TP (α < .05).
Results
Forty‐four studies with a total of 10 343 subjects were included. TP and HGS values were significantly higher in people aged <60 years relative to ≥60 years and in IC relative to NC (all p < .001). Regarding gender, there was no significant difference in TP (p = .370). However, a significant gender‐dependent difference in TP was observed in people aged <60 years (p < .001), but not in aged ≥60 years in IC group (p = .118) and aged ≥60 years in NC group (p = .895). There was a significant positive correlation of HGS and TP (p < .001).
Conclusions
Similar to decrease in HGS, age‐related sarcopaenia seems to have an effect on oro‐facial muscles like the tongue. Research on rehabilitation measures for oro‐facial muscle strength, similar to HGS might be beneficial to improve the personally acquired oro‐facial potential.
Keywords: frailty, geriatric dentistry, hand strength, muscle strength, pressure, tongue
This systematic review and meta ‐ analysis focused on muscle strength, hypothesising that age‐related decline in physical muscle strength represented by handgrip strength could equally be found in tongue pressure and analysed the effects of age, gender and the need for care.
1. INTRODUCTION
As a result of the global trend of an aging population, nursing care needs will grow correspondingly. 1 In this situation, frailty adults are at risk for falls, hospitalisation, disability and death. 2 The most well‐known model of the frailty phenotype was proposed by Fried et al., 2 and their criteria for physical frailty are based on: unintentional weight loss, self‐reported exhaustion, low physical activity, slow walking speed and weakness (handgrip strength (HGS)). Falling into a frailty cycle leads to a vicious circle of sarcopaenia and decreased general function. 2 , 3 Most frail older adults exhibit sarcopaenia, and some older adults with sarcopaenia are frail. 4 Primary sarcopaenia is considered to be age‐related loss of skeletal muscle mass or quantity, muscle strength and physical performance, while secondary sarcopaenia is progressive generalised muscle weakness secondary to disease, malnutrition and inactivity. 5 Sarcopaenia is often assessed with HGS for muscle strength, skeletal muscle mass index (SMI) for muscle mass and gait speed for physical performance. 5 As sarcopaenia progresses, metabolism and consumed energy decrease, and then appetite (food intake) decreases, causing weight loss and malnutrition, further promoting sarcopaenia. Several studies have reported that systemic sarcopaenia and frailty are associated with decreased oro‐facial function in older adults. 6 , 7 , 8
The decline in oral function with aging is predicted to affect the decline in nutritional status and physical function. 6 , 9 A recent study has proposed that in line with the Meikirch model for health, that there is an age‐related decline of the biologically given potential of the oro‐facial system during physiological aging processes. 10 The management of oral hypofunction is expected to delay the need for nursing care and contribute to the extension of healthy life expectancy. Diagnosis of oral hypofunction is necessary prior to management, which allows for a comprehensive assessment of oral function. There are seven criteria for diagnosis of oral hypofunction proposed by the Japanese Society of Gerodontology: oral cleanness, oral dryness, lip and tongue motor function, tongue pressure (TP), occlusal force, masticatory function and swallowing function. 11 Moreover, previous studies have examined the associations between oral health and sarcopaenia, 12 oral function and sarcopaenia, 13 , 14 , 15 , 16 swallowing muscles and sarcopaenic dysphagia, 17 , 18 oral function and physical performance, 19 , 20 , 21 , 22 , 23 oral function and cognitive function 24 and oral function and polypharmacy. 7 Especially, TP and tongue thickness, which are sensitive markers for oral frailty, decrease with age. 25 However, the association between general physiology and pathophysiological factors on TP has not been clarified.
Hence, we focused on muscle strength, hypothesising that age‐related decline in physical muscle strength represented by HGS could equally be found in TP and analysed the effects of age, gender and the need for care. This systematic review and meta‐analysis designed to evaluate the relationship between HGS and TP among aged <60 and ≥60 years. The null hypothesis was that there would be no correlation between HGS and TP in people older and younger than 60 years. Furthermore, the influence of gender, need for care (independent older adults (i.e. without need for care) (IC) vs. older adults receiving nursing care (NC)) and measuring device was analysed as secondary outcomes.
2. MATERIALS AND METHODS
2.1. Protocol and registration
This systematic review was conducted following the Preferred Reporting Items for Systematic Reviews and Meta‐Analyses (PRISMA) guidelines. 26 The PRISMA checklist is provided in the Appendix S1. The focused question was designed based on the PICO format (P: population, I: intervention, C: comparison, O: outcome) as follows: P (general populations), I (physiology), C (pathophysiology) and O (TP). Accordingly, the PICO question was: ‘In patients younger or older than 60 years, is there an association between TP and general physiology and pathophysiology.’ This study protocol for the systematic review and meta‐analysis was registered in PROSPERO (registration number CRD42020187265).
2.2. Eligibility criteria
Studies were eligible if they met the following inclusion criteria: (a) human clinical studies (randomised controlled trials (RCTs), non‐randomised controlled trials (non‐RCTs), cross‐sectional studies, cohort studies, case–control studies), (b) subjects over 18 years of age, (c) studies with more than 10 subjects in study arm or group, (d) studies with TP values assessed with the JMS tongue strength measurement device (JMS) (JM‐TPM; JMS Co., Ltd.) or Iowa Oral Performance Instrument (IOPI; IOPI Medical LLC), (e) studies reporting HGS in kg or kgf, (f) publications in English, German or Japanese.
Studies were excluded if they met the following criteria: (a) in vitro or animal studies, (b) subjects younger than 18 years old or age not reported (c) fewer than 10 subjects in each relevant study arm/group, (d) insufficient documentation of TP and HGS, (e) measurement of TP in units other than kPa, (f) TP during swallowing, (g) publications not written in English, German or Japanese.
2.3. Search strategy
Two reviewers (SAA and IA) searched electronically in the PubMed/MEDLINE and the Japanese database Ichu Shi‐Web for publications in English, German, and Japanese between 1969 and Nov 30th, 2021. In the initial search, the following search terms and combinations were applied: ((patient OR population OR subject OR people OR individuals) AND (condition OR muscle OR body OR capacity OR power OR performance OR physiology OR pathophysiology) AND (‘tongue strength’ OR ‘tongue pressure’ OR ‘tongue force’ OR ‘lingual pressure’)). An additional hand search was carried out on the reference lists of related review articles dealing with similar topics in the following journals: Dysphagia, Journal of Speech, Language, and Hearing Research, Journal of Medical Speech‐language Pathology, Archives of otolaryngology‐head & neck surgery, Seminars in Speech and Language, Perspectives on Swallowing and Swallowing Disorders (Dysphagia), Journal of Motor Behaviour, Journal of the American Geriatrics Society, Archives of Physical Medicine and Rehabilitation. Collecting references and eliminating duplicates were performed using a reference manager software (EndNote X8®).
2.4. Study selection and data extraction
Duplicate articles were removed, and the titles and abstracts of the remaining articles were screened independently by two reviewers (IA, YW) according to the eligibility criteria. Next, the full‐text articles that met eligibility criteria were evaluated by the same reviewers and the reasons for exclusion were noted. Studies with insufficient data, unstable subjects, etc., were finally excluded for meta‐analysis. Disagreements between two reviewers regarding included studies were discussed and resolved by a third reviewer (SAA).
After the full‐text screening, a first reviewer (IA) collected the following extracted data from all applicable studies and recorded them in a spreadsheet software (Excel, Microsoft Office 2017): authors, year of publication, sample size, age, gender, TP and HGS values (mean, minimum, maximum), TP measuring device (JMS or IOPI), need for care (IC or NC) and study design. The second reviewer (YW) checked the extracted data. Discordance in data extraction between these two authors were discussed and decided in consultation with a third reviewer (SAA). Kappa score was calculated to identify the level of agreement between internal reviewers.
2.5. Risk of bias in individual studies
The methodological quality was evaluated individually by two authors (IA, YW) using the Newcastle‐Ottawa‐Scale (NOS) 27 for the included observational studies and the Cochrane risk of bias tool 28 for the included RCTs and non‐RCTs. The NOS was used to assess the quality of observational studies, including case–control studies, cohort studies and cross‐sectional studies, in three major domains: selection (four items), comparability (one item) and exposure (three items for case–control study) or outcome (three items for cohort study and cross‐sectional study). Each item was given a certain number of stars if the study met the criteria. Studies with 7–10 stars corresponded to high quality, 4–6 stars to intermediate quality, and 1–3 stars to low quality. The Cochrane risk of bias tool is a domain‐based assessment comprising the seven domains: random sequence generation, allocation concealment, blinding of participants and personnel, blinding of outcome assessment, incomplete outcome data, selective reporting and other sources of bias. The assigned judgement for each domain is assessed as ‘low risk of bias’, ‘high risk of bias’ or ‘unclear risk of bias’.
2.6. Data synthesis and statistical analysis
All statistical analysis was conducted using Stata/IC 16.0 for Unix (StataCorp LLC), with two‐sided at a significance level of 0.05. For the analysis, the results were sorted and processed into subgroups according to participant age, gender, TP measuring device type and need for care. Unweighted TP and HGS values from each included study were aggregated for each subgroup and calculated as mean, standard deviation (SD), median, minimum and maximum values, respectively. A test of homogeneity was performed for this meta‐analysis. A random‐effects meta‐regression was applied to TP and HGS, respectively, to estimate weighted mean (EWM) with a 95% confidence interval (95% CI) for the various subgroups as well as estimating weighted mean difference (WMD) between subgroups and inter‐subgroup comparison, including age (<60 vs. ≥60 years), device (JMS vs. IOPI), gender (men vs. women) and need for care (IC vs. NC). Additionally, the effect of HGS on TP was analysed using a random‐ effects meta‐regression with TP as dependent variable and HGS as independent variable. The results were presented as coefficients, 95% CIs, p‐values and the adjusted R 2 (%), which indicates the proportion of between study variance of mean TP explained by mean HGS. Individual mean TPs and HGSs, estimated overall mean TPs and HGSs, their 95% CIs and the weights of each study were provided as forest plots.
3. RESULTS
3.1. Study selection
The systematic electronic search found 1376 articles and the hand search found 47 articles, resulting in a total of 1423 articles identified. After removing 71 duplicate articles, 1352 titles were screened independently by two reviewers (IA and YW) to assess their suitability for the inclusion criteria, and 767 abstracts were assessed for further screening. The remaining 116 articles were assessed in full text, and 72 articles were excluded since they did not meet the eligibility criteria due to the following reasons: insufficient data (58 articles), incorrect unit (six articles), no measuring device mentioned (three articles), ineligible subjects (five articles). Finally, a total of 44 articles were eligible and included in the qualitative and quantitative synthesis in this systematic review and meta‐analysis. The Kappa scores indicated high agreement, between the two reviewers (title: κ = .88, abstract: κ = .88, full‐text: κ = .92). The flow diagram of the literature search and screening process is shown in Figure 1. The included and excluded studies during data extraction are listed in the Appendix S2.
FIGURE 1.
Flow diagram of screening and selection of publications for systematic review and meta‐analysis.
3.2. Study characteristics
A total of 10 343 subjects' data in 44 studies published between 2013 and 2021 were analysed. Extracted data for subjects <60 years of age (young) were reported in seven studies included 829 subjects with a mean age of 31.4 ± 11.9 [range 19.7–53.5] years, and those for subjects ≥60 years (older adults) were in 41 studies included 9514 subjects with a mean age of 76.9 ± 5.2 [range 66.2–88.0] years. In regard to gender, a total of 5767 data were analysed: 2015 men (17 studies) and 3752 women (23 studies). In regard to the TP measuring device, 549 subjects (three studies) were assessed with the IOPI, and 9794 subjects (41 studies) were assessed with the JMS. In regard to need for care, there were 28 studies included 8270 subjects with IC and 14 studies included 1244 subjects with NC. Table 1a summarise the characteristics of the included studies. An overview of the unweighted synthesis values, separated by age, gender, measuring device, need for care, and the combination of those parameters (JMS data only) is presented in Table 1b for TP and in Table 1c for HGS. The mean TP assessed with JMS of individual studies, their 95% CIs and their weights and the estimated overall mean TP for combinations of age and need for care are described as forest plots, HGS are drawn as well (Figure S1).
TABLE 1.
(a) Study characteristics of included studies (n = 44), (b) Tongue pressure ‐descriptive analysis and (c) Handgrip strength ‐descriptive analysis.
| (a) | |||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Author | Year | Subjects (n) | Men (n) | Women (n) | Mean age ± SD (years) | Median age (Q1, Q3) (years) | Min age (years) | Max age (years) | Tongue pressure device | Mean tongue pressure ± SD (kPa) | Median tongue pressure (Q1, Q3) (kPa) | Mean handgrip strength ± SD (kg) | Median handgrip strength (Q1, Q3) (kg) |
| Sugiya | 2021 | 24 | 20 | 4 | 77.5 ± 5.0 | NA | 65 | NA | JMS | 38.0 ± 5.3 | NA | 36.0 ± 8.4 | NA |
| Ogawa | 2021 | 45 | 22 | 23 | 84.3 ± 7.8 | NA | 65 | NA | JMS | 15.8 ± 8.1 | NA | 9.9 ± 6.5 | NA |
| Miyoshi | 2021 | 22 | 0 | 22 | 67.8 ± 1.4 | NA | 65 | 69 | JMS | 35.3 ± 5.9 | NA | 24.0 ± 2.8 | NA |
| 2021 | 99 | 0 | 99 | 75.3 ± 2.6 | NA | 70 | 79 | JMS | 35.0 ± 7.9 | NA | 21.3 ± 3.7 | NA | |
| 2021 | 84 | 0 | 84 | 82.9 ± 2.5 | NA | 80 | 89 | JMS | 31.9 ± 7.5 | NA | 19.7 ± 3.3 | NA | |
| Kugimiya | 2021 | 610 | 0 | 610 | NA | 78 (70, 86) | 65 | NA | JMS | NA | 31.3 (25.8, 35.7) | NA | 21.0 (17.0, 25.0) |
| 2021 | 268 | 268 | 0 | NA | 71 (68, 78.8) | 65 | NA | JMS | NA | 33.4 (27.8, 39) | NA | 35.0 (30.3, 40.0) | |
| Kim | 2021 | 51 | 25 | 26 | 32.1 ± 7.4 | NA | 20 | 45 | JMS | 38.92 ± 10.93 | NA | 31.14 ± 10.49 | NA |
| 2021 | 54 | 26 | 28 | 53.5 ± 4.2 | NA | 46 | 60 | JMS | 38.28 ± 10.50 | NA | 28.22 ± 8.71 | NA | |
| 2021 | 45 | 21 | 24 | 66.2 ± 2.8 | NA | 61 | 70 | JMS | 31.68 ± 7.82 | NA | 27.56 ± 9.29 | NA | |
| 2021 | 61 | 23 | 38 | 77.4 ± 5.2 | NA | 71 | NA | JMS | 26.52 ± 9.74 | NA | 21.44 ± 8.03 | NA | |
| Kato | 2021 | 107 | 0 | 107 | 74.37 ± 4.46 | NA | 66 | 84 | JMS | 32.89 ± 6.41 | NA | 23.66 ± 3.69 | NA |
| Iyota | 2021 | 42 | 23 | 19 | 73.1 ± 3.1 | NA | 68 | 79 | JMS | 33.8 ± 8.4 | NA | 31.2 ± 7.4 | NA |
| Hirata | 2021 | 90 | 55 | 35 | 77.2 ± 8.3 | NA | 65 | NA | JMS | 27.5 ± 9.9 | NA | 22.4 ± 7.8 | NA |
| Chang | 2021 | 26 | 9 | 17 | 73.53 ± 6.33 | NA | 65 | NA | IOPI | 34.84 ± 11.57 | NA | 22.88 ± 6.80 | NA |
| 2021 | 336 | 140 | 196 | 71.61 ± 5.18 | NA | 65 | NA | IOPI | 38.20 ± 14.01 | NA | 26.52 ± 7.33 | NA | |
| Sakai | 2020 | 30 | 15 | 15 | NA | 88 (79.75, 91.00) | 65 | NA | JMS | NA | 26.75 (21.43, 31.78) | NA | 17.4 (12.70, 23.00) |
| 2020 | 30 | 15 | 15 | NA | 89 (85.00, 90.00) | 65 | NA | JMS | NA | 18.10 (14.20, 23.075) | NA | 12.0 (8.40, 13.50) | |
| Nakamori | 2020 | 163 | 163 | 0 | 76.9 ± 5.8 | NA | 65 | NA | JMS | 37.4 ± 10.2 | NA | 28.8 ± 6.9 | NA |
| 2020 | 91 | 0 | 91 | 79.5 ± 6.7 | NA | 65 | NA | JMS | 32.5 ± 10.5 | NA | 15.9 ± 4.5 | NA | |
| Nagano | 2020 | 19 | 19 | 0 | 79.3 ± 7.2 | NA | 65 | NA | JMS | 27.5 ± 10.1 | NA | 17.9 ± 6.5 | NA |
| 2020 | 76 | 0 | 76 | 84.3 ± 5.0 | NA | 65 | NA | JMS | 24.9 ± 8.5 | NA | 12.7 ± 3.4 | NA | |
| Miyoshi | 2020 | 40 | 0 | 40 | 70.4 ± 2.8 | NA | 65 | 74 | JMS | 32.8 ± 7.4 | NA | 23.4 ± 5.0 | NA |
| 2020 | 123 | 0 | 123 | 80.3 ± 4.1 | NA | 75 | NA | JMS | 31.4 ± 7.7 | NA | 20.2 ± 3.4 | NA | |
| Kunieda | 2020 | 16 | 13 | 3 | 85.0 ± 6.6 | NA | NA | NA | JMS | 21.8 ± 5.1 | NA | 14.5 ± 6.3 | NA |
| Kugimiya | 2020 | 282 | 282 | 0 | NA | 75 (70, 79) | 65 | NA | JMS | NA | 30.2 (25.1, 34.5) | NA | 33 (28.8, 38.0) |
| 2020 | 397 | 0 | 282 | NA | 76 (71, 80) | 65 | NA | JMS | NA | 28.4 (23.4, 33.1) | NA | 20 (17.0, 23.2) | |
| Kobuchi | 2020 | 54 | 16 | 38 | 78.8 ± 7.1 | NA | NA | NA | JMS | 28.5 ± 7.7 | NA | 22.4 ± 7.1 | NA |
| Hirano | 2020 | 36 | 0 | 36 | 76.2 ± 5.0 | NA | 65 | NA | JMS | 25.1 ± 9.2 | NA | 21.9 ± 3.7 | NA |
| Hirata | 2020 | 66 | 37 | 29 | NA | 77.0 (70.0, 84.2) | 65 | NA | JMS | NA | 28.9 (22.4, 33.5) | NA | 23.3 (16.9, 27.0) |
| Higa | 2020 | 42 | 42 | 0 | 72.4 ± 4.7 | NA | 65 | NA | JMS | 36.8 ± 8.9 | NA | 35.3 ± 7.2 | NA |
| 2020 | 70 | 0 | 70 | 69.0 ± 4.5 | NA | 65 | NA | JMS | 34.6 ± 8.4 | NA | 22.7 ± 4.1 | NA | |
| Arakawa | 2019 | 68 | 29 | 39 | 81.5 ± 7.3 | NA | 65 | NA | JMS | 22.1 ± 8.9 | NA | 15.8 ± 6.6 | NA |
| 2019 | 99 | 35 | 64 | 79.4 ± 6.5 | NA | 65 | NA | JMS | 27.1 ± 11.2 | NA | 17.1 ± 6.9 | NA | |
| Wakabayashi | 2019 | 108 | 72 | 36 | 76 ± 7 | NA | 65 | NA | JMS | 21.4 ± 9.4 | NA | 17.0 ± 8.0 | NA |
| Morita | 2019 | 52 | 52 | 0 | 77.0 ± 5.3 | NA | 65 | NA | JMS | 31.8 ± 6.4 | NA | 33.0 ± 5.6 | NA |
| 2019 | 179 | 0 | 179 | 74.1 ± 4.8 | NA | 65 | NA | JMS | 30.7 ± 6.4 | NA | 21.5 ± 3.6 | NA | |
| Kugimiya | 2019 | 445 | 445 | 0 | 77.0 ± 4.9 | NA | 70 | NA | JMS | 30.8 ± 9.0 | NA | 32.2 ± 6.3 | NA |
| 2019 | 673 | 0 | 673 | 77.0 ± 4.5 | NA | 70 | NA | JMS | 29.8 ± 7.7 | NA | 21.5 ± 4.5 | NA | |
| Koyama | 2019 | 24 | 0 | 24 | 19.7 ± 1.5 | NA | 18 | NA | JMS | 36.49 ± 6.29 | NA | 26.88 ± 3.87 | NA |
| Kito | 2019 | 86 | 6 | 80 | 75.6 ± 5.6 | NA | 65 | NA | JMS | 32.4 ± 8.0 | NA | 21.6 ± 4.8 | NA |
| Kaji | 2019 | 82 | 82 | 0 | 72.1 ± 7.2 | NA | 60 | NA | JMS | 31.6 ± 10.2 | NA | 30.9 ± 6.2 | NA |
| 2019 | 62 | 0 | 62 | 70.5 ± 5.8 | NA | 60 | NA | JMS | 27.1 ± 8.5 | NA | 20.1 ± 3.7 | NA | |
| Hara | 2019 | 497 | 208 | 289 | 37.7 ± 10.7 | NA | 20 | 59 | JMS | 37.3 ± 7.7 | NA | 32.5 ± 9.8 | NA |
| 2019 | 288 | 97 | 191 | 70.6 ± 5.4 | NA | 60 | 89 | JMS | 31.4 ± 8.0 | NA | 27.2 ± 8.3 | NA | |
| Sakai | 2018 | 25 | 25 | 0 | 82.4 ± 7.8 | NA | 65 | NA | JMS | 19.2 ± 9.7 | NA | 22.3 ± 6.3 | NA |
| 2018 | 38 | 0 | 38 | 84.2 ± 6.1 | NA | 65 | NA | JMS | 20.1 ± 10.6 | NA | 14.3 ± 5.1 | NA | |
| Hiroshimaya | 2018 | 18 | 18 | 0 | 84.4 ± 5.0 | NA | NA | NA | JMS | 21.2 ± 8.3 | NA | NA | 22.6 (19.3, 24.4) |
| 2018 | 46 | 0 | 46 | 87.2 ± 5.6 | NA | NA | NA | JMS | 18.9 ± 10.4 | NA | NA | 13.4 (10.9, 16.5) | |
| Yoshimi | 2018 | 37 | 37 | 0 | NA | 72.81 (69.00, 77.00) | 65 | NA | JMS | 29.63 ± 9.27 | NA | NA | 35.22 (28.88, 41.25) |
| 2018 | 81 | 0 | 81 | NA | 69.57 (66.00, 73.00) | 65 | NA | JMS | 30.85 ± 7.74 | NA | NA | 23.50 (20.50, 26.38) | |
| Yamanashi | 2018 | 1603 | 650 | 953 | 72.8 ± 7.4 | NA | 65 | 95 | JMS | 30.5 ± 10.1 | NA | 26.0 ± 8.8 | NA |
| Suzuki | 2018 | 245 | 0 | 245 | NA | 81.0 (75.0, 85.0) | 65 | NA | JMS | 28.4 ± 9.5 | NA | NA | 19.1 (15.7, 22.0) |
| Morita | 2018 | 262 | 56 | 206 | 74.2 ± 5.9 | NA | 60 | 89 | JMS | 30.9 ± 6.4 | NA | 25.0 ± 6.4 | NA |
| Higashi | 2018 | 241 | 241 | 0 | NA | 71.0 (64.0, 78.0) | NA | NA | JMS | 30.5 ± 10.6 | NA | NA | 31.4 (25.8, 36.9) |
| 2018 | 397 | 0 | 397 | NA | 70.0 (62.0, 77.0) | NA | NA | JMS | 28.3 ± 9.9 | NA | NA | 20.5 (16.1, 23.9) | |
| Hashiguchi | 2017 | 15 | 7 | 8 | 21.9 ± 4.0 | NA | 18 | 25 | JMS | 40.4 ± 8.6 | NA | 34.5 ± 8.5 | NA |
| Sakai | 2017 | 64 | 64 | 0 | NA | 84.5 (78, 89) | NA | NA | JMS | NA | 25.2 (21.4, 32.3) | NA | 17.4 (14.2, 23.3) |
| 2017 | 110 | 0 | 110 | NA | 84.0 (80, 88.3) | NA | NA | JMS | NA | 26.7 (22.4, 32.6) | NA | 13.6 (10.6, 17.3) | |
| Sakai | 2017 | 201 | 70 | 131 | NA | 84 (79, 89) | 65 | NA | JMS | NA | 26.8 (21.8, 32.6) | NA | 15.1 (11.7, 19.5) |
| Yasuhara | 2016 | 47 | 47 | 0 | 25.66 ± 6.43 | NA | 18 | 46 | JMS | 45.60 ± 9.23 | NA | 40.92 ± 6.49 | NA |
| 2016 | 54 | 0 | 54 | 23.48 ± 4.23 | NA | 18 | 39 | JMS | 38.68 ± 7.37 | NA | 24.42 ± 4.33 | NA | |
| Furuya | 2016 | 169 | 169 | 0 | 75.9 ± 6.1 | NA | NA | NA | JMS | 31.8 ± 7.8 | NA | 35.2 ± 6.7 | NA |
| 2016 | 195 | 0 | 195 | 75.4 ± 5.6 | NA | NA | NA | JMS | 29.3 ± 7.1 | NA | 22.7 ± 4.2 | NA | |
| Saito | 2015 | 27 | 9 | 18 | 20.7 ± 0.6 | NA | 20 | 22 | JMS | 32.3 ± 10.4 | NA | 28.8 ± 7.9 | NA |
| 2015 | 17 | 11 | 6 | 74.1 ± 4.5 | NA | 65 | 84 | JMS | 27.1 ± 5.6 | NA | 27.8 ± 7.6 | NA | |
| Nakahigashi | 2015 | 21 | 0 | 21 | 77.4 ± 6.6 | NA | 70 | 89 | JMS | 29.6 ± 10.3 | NA | 19.9 ± 3.2 | NA |
| 2015 | 41 | 0 | 41 | 81.0 ± 7.2 | NA | 70 | 89 | JMS | 24.3 ± 9.3 | NA | 13.5 ± 4.6 | NA | |
| Mendes | 2015 | 30 | NA | NA | 30.37 ± 6.75 | 31.5 (26.00, 36.25) | 18 | 39 | IOPI | 56.57 ± 14.85 | NA | 38.20 ± 12.05 | NA |
| 2015 | 30 | NA | NA | 49.13 ± 5.07 | 50 (45.00, 53.25) | 40 | 58 | IOPI | 51.97 ± 10.81 | NA | 32.20 ± 11.05 | NA | |
| 2015 | 30 | NA | NA | 69.63 ± 8.06 | 67.00 (63.00, 74.75) | 60 | 86 | IOPI | 43.20 ± 13.58 | NA | 26.93 ± 10.15 | NA | |
| Shimada | 2014 | 13 | 13 | 0 | 73.5 ± 5.7 | NA | NA | NA | JMS | 36.1 ± 8.1 | NA | 36.2 ± 7.2 | NA |
| 2014 | 27 | 0 | 27 | 74.4 ± 5.0 | NA | NA | NA | JMS | 32.2 ± 7.0 | NA | 22.3 ± 4.4 | NA | |
| Buehring | 2013 | 48 | 48 | 0 | 81.3 ± 6.3 | NA | 70 | 95 | IOPI | 50.6 ± 12.7 | NA | 32.4 ± 7.4 | NA |
| 2013 | 49 | 0 | 49 | 80.0 ± 5.5 | NA | 70 | 95 | IOPI | 47.0 ± 10.2 | NA | 18.3 ± 4.8 | NA | |
| (b) | |||||||
|---|---|---|---|---|---|---|---|
| Studies | Subgroups | Subjects | Unweighted mean tongue pressure (kPa) | ||||
| Mean | SD | Median | Min‐max | ||||
| Gender | |||||||
| Men | 17 (42.5%) | 17 (38.6%) | 2015 (34.9%) | 32.4 | 7.7 | 31.6 | 19.2–50.6 |
| Women | 23 (57.5%) | 27 (61.4%) | 3752 (65.1%) | 30.6 | 5.7 | 30.9 | 18.9–47.0 |
| Device | |||||||
| JMS | 41 (93.2%) | 68 (90.7%) | 9794 (94.7%) | 30.0 | 5.7 | 30.6 | 15.8–45.6 |
| IOPI | 3 (6.8%) | 7 (9.3%) | 549 (5.3%) | 46.1 | 7.8 | 47.0 | 34.8–56.6 |
| Need for care | |||||||
| Independent (ic) | 28 (66.7%) | 45 (69.2%) | 8270 (86.9%) | 32.7 | 4.9 | 31.7 | 25.1–50.6 |
| Nursing care (nc) | 14 (33.3%) | 20 (30.8%) | 1244 (13.1%) | 23.7 | 3.9 | 24.6 | 15.8–28.5 |
| Age | |||||||
| Older adults (o) | 41 (85.4%) | 65 (86.7%) | 9514 (92.0%) | 30.0 | 6.2 | 30.5 | 15.8–50.6 |
| Young adults (y) | 7 (14.6%) | 10 (13.3%) | 829 (8.0%) | 41.7 | 7.5 | 38.8 | 32.3–56.6 |
| (c) | |||||||
|---|---|---|---|---|---|---|---|
| Studies | Subgroups | Subjects | Unweighted mean handgrip strength (kg) | ||||
| Mean | SD | Median | Min‐max | ||||
| Gender | |||||||
| Men | 17 (42.5%) | 17 (38.6%) | 2015 (34.9%) | 30.6 | 6.6 | 32.4 | 17.9–40.9 |
| Women | 23 (57.5%) | 27 (61.4%) | 3752 (65.1%) | 20.1 | 3.8 | 21.0 | 12.7–26.9 |
| Device | |||||||
| JMS | 41 (93.2%) | 68 (90.7%) | 9794 (94.7%) | 23.8 | 7.1 | 22.4 | 9.9–40.9 |
| IOPI | 3 (6.8%) | 7 (9.3%) | 549 (5.3%) | 28.2 | 6.6 | 26.9 | 18.3–38.2 |
| Need for care | |||||||
| Independent (ic) | 28 (66.7%) | 45 (69.2%) | 8270 (86.9%) | 25.8 | 5.8 | 23.7 | 15.9–36.2 |
| Nursing care (nc) | 14 (33.3%) | 20 (30.8%) | 1244 (13.1%) | 16.7 | 3.9 | 16.4 | 9.9–22.4 |
| Age | |||||||
| Older adults (o) | 41 (85.4%) | 65 (86.7%) | 9514 (92.0%) | 23.0 | 6.7 | 22.3 | 9.9–36.2 |
| Young adults (y) | 7 (14.6%) | 10 (13.3%) | 829 (8.0%) | 31.8 | 5.1 | 31.7 | 24.4–40.9 |
Abbreviations: ic, independent group; NA, not applicable; nc, nursing care group; o, older adults; y, young adults.
3.3. Quality assessment
In the quality assessment, 39 cross‐sectional studies, two before and after studies, one prospective cohort study, one RCT and one non‐RCT were evaluated. Forty‐two analytical studies were assessed with NOS (Table 2a); six studies (14.3%) were considered low quality, 27 studies (64.3%) intermediate and nine studies (21.4%) high quality. One RCT was rated as having a low risk of bias or unclear risk of bias and one non‐RCT was rated as having a high risk (Table 2b).
TABLE 2.
Results of quality assessment for (a) analytical study according to NOS, and for (b) included randomised clinical trials (RCTs) according to Cochrane Collaboration's tool for assessing risk of bias.
| (a) | |||||||
|---|---|---|---|---|---|---|---|
| Author | Year | Study design | Selection | Comparability | Outcome | Ottawa total stars | Quality |
| Sugiya | 2021 | Cross‐sectional | 3 | 0 | 1 | 4 | Intermediate |
| Ogawa | 2021 | Cross‐sectional | 3 | 2 | 2 | 7 | High |
| Miyoshi | 2021 | Cross‐sectional | 1 | 2 | 1 | 4 | Intermediate |
| Kugimiya | 2021 | Cross‐sectional | 5 | 2 | 2 | 9 | High |
| Kim | 2021 | Cross‐sectional | 2 | 2 | 2 | 6 | Intermediate |
| Kato | 2021 | Cross‐sectional | 3 | 1 | 2 | 6 | Intermediate |
| Hirata | 2021 | Cross‐sectional | 1 | 2 | 2 | 5 | Intermediate |
| Chang | 2021 | Cross‐sectional | 4 | 2 | 2 | 8 | High |
| Sakai | 2020 | Cross‐sectional | 4 | 0 | 2 | 6 | Intermediate |
| Nakamori | 2020 | Cross‐sectional | 1 | 2 | 2 | 5 | Intermediate |
| Nagano | 2020 | Before and after | 1 | 2 | 2 | 5 | Intermediate |
| Miyoshi | 2020 | Cross‐sectional | 2 | 2 | 2 | 6 | Intermediate |
| Kunieda | 2020 | Cross‐sectional | 3 | 0 | 1 | 4 | Intermediate |
| Kugimiya | 2020 | Cross‐sectional | 5 | 2 | 1 | 8 | High |
| Kobuchi | 2020 | Cross‐sectional | 3 | 2 | 2 | 7 | High |
| Hirano | 2020 | Cross‐sectional | 1 | 0 | 1 | 2 | Low |
| Hirata | 2020 | Cross‐sectional | 1 | 1 | 2 | 4 | Intermediate |
| Higa | 2020 | Before and after | 1 | 1 | 2 | 4 | Intermediate |
| Arakawa | 2019 | Cross‐sectional | 2 | 1 | 2 | 5 | Intermediate |
| Wakabayashi | 2019 | Prospective cohort | 3 | 2 | 0 | 5 | Intermediate |
| Morita | 2019 | Cross‐sectional | 3 | 1 | 1 | 5 | Intermediate |
| Kugimiya | 2019 | Cross‐sectional | 4 | 2 | 1 | 7 | High |
| Koyama | 2019 | Cross‐sectional | 1 | 0 | 1 | 2 | Low |
| Kaji | 2019 | Cross‐sectional | 3 | 2 | 2 | 7 | High |
| Hara | 2019 | Cross‐sectional | 3 | 2 | 2 | 7 | High |
| Sakai | 2018 | Cross‐sectional | 3 | 2 | 1 | 6 | Intermediate |
| Hiroshimaya | 2018 | Cross‐sectional | 3 | 1 | 2 | 6 | Intermediate |
| Yoshimi | 2018 | Cross‐sectional | 3 | 1 | 2 | 6 | Intermediate |
| Yamanashi | 2018 | Cross‐sectional | 2 | 1 | 2 | 5 | Intermediate |
| Suzuki | 2018 | Cross‐sectional | 2 | 1 | 1 | 4 | Intermediate |
| Morita | 2018 | Cross‐sectional | 1 | 2 | 1 | 4 | Intermediate |
| Higashi | 2018 | Cross‐sectional | 3 | 1 | 3 | 7 | High |
| Hashiguchi | 2017 | Cross‐sectional | 1 | 1 | 1 | 3 | Low |
| Sakai (Tongue) | 2017 | Cross‐sectional | 2 | 1 | 2 | 5 | Intermediate |
| Sakai (Relationship) | 2017 | Cross‐sectional | 3 | 1 | 2 | 6 | Intermediate |
| Yasuhara | 2016 | Cross‐sectional | 1 | 1 | 1 | 3 | Low |
| Furuya | 2016 | Cross‐sectional | 2 | 2 | 1 | 5 | Intermediate |
| Saito | 2015 | Cross‐sectional | 0 | 1 | 1 | 2 | Low |
| Nakahigashi | 2015 | Cross‐sectional | 0 | 1 | 1 | 2 | Low |
| Mendes | 2015 | Cross‐sectional | 2 | 1 | 1 | 4 | Intermediate |
| Shimada | 2014 | Cross‐sectional | 2 | 2 | 1 | 5 | Intermediate |
| Buehring | 2013 | Cross‐sectional | 3 | 2 | 1 | 6 | Intermediate |
| (b) | |||||||||
|---|---|---|---|---|---|---|---|---|---|
| Author | Year | Study design | Random sequence generation | Allocation concealment | Blinding of participants and personnel | Blinding of outcome assessment | Incomplete outcome data | Selective reporting | Other bias |
| Iyota | 2021 | Non‐RCT | High risk | High risk | Low risk | Low risk | Low risk | Low risk | High risk |
| Kito | 2019 | RCT | Unclear | Low risk | Low risk | Low risk | Low risk | Low risk | Low risk |
3.4. Synthesis of results
3.4.1. Tongue pressure
Regarding analysis of age group, the WMD between young and older groups was 11.5 kPa (SE: 2.13 kPa), indicating that TP was significantly higher in subjects <60 years (p < .001). Regarding analysis of measuring device, the TP value assessed with the IOPI was significantly higher than those with the JMS, with a WMD of 15.9 kPa (SE: 2.36 kPa) (p < .001). Analysing the TP values measured with the JMS only among IC for both genders, significantly higher TP values were found in the younger group than in the older adults' group for both men (p < .001) and women (p = .001).
In terms of TP, there was no difference between men and women (WMD: −1.8 kPa; SE: 1.97 kPa; p = .370). However, when the gender differences in TP values measured with the JMS were analysed in combination with age and need for care, a significantly higher TP was found in men than in women in the younger IC (p < .001), whereas there was no significant gender difference in older adults' IC (p = .118) and in older adults' NC (p = .895).
Regarding analysis of need for care, TP was significantly higher in the IC compared to in the NC, with a WMD of −8.8 kPa (SE: 1.2 kPa) (p < .001). When analysing the difference in TP values of older adults measured with JMS between IC and NC, TP was significantly higher in the IC than in the NC for both men and women (both p < .001). Table 3a provides a detailed overview on the EWM TP for each group and the WMD between groups.
TABLE 3.
(a) Tongue pressure and gender, device, need for care, age (estimation by random‐effects meta‐regression a ), (b) Handgrip strength and gender, device, need of care, age (estimation by random‐effects meta‐regression a ).
| (a) | |||||||
|---|---|---|---|---|---|---|---|
| No. of studies | No. of subgroups (rows) | No. of subjects | EWM/WMD | SE | 95% CI | p‐value | |
| Gender | |||||||
| Men | 17 | 17 | 2015 | 32.4 | 1.83 | 28.8–36.0 | |
| Women | 23 | 27 | 3752 | 30.6 | 1.06 | 28.5–32.7 | .370 |
| Women versus men | WMD | −1.8 | 1.97 | −5.6 to 2.1 | |||
| Device | |||||||
| JMS | 41 | 68 | 9794 | 30.0 | 0.68 | 28.7–31.4 | |
| IOPI | 3 | 7 | 549 | 46.0 | 2.90 | 40.3–51.7 | <.001 |
| IOPI versus JMS | WMD | 15.9 | 2.36 | 11.2–20.5 | |||
| Need for care | |||||||
| ic | 28 | 45 | 8270 | 32.6 | 0.69 | 31.3–34.0 | |
| nc | 14 | 20 | 1244 | 23.8 | 0.87 | 22.1–25.5 | <.001 |
| ic versus nc | WMD | −8.8 | 1.20 | −11.2 to −6.5 | |||
| Age | |||||||
| o | 41 | 65 | 9514 | 29.9 | 0.75 | 28.5–31.4 | |
| y | 7 | 10 | 829 | 41.5 | 2.28 | 37.0–46.0 | <.001 |
| y versus o | WMD | 11.5 | 2.13 | 7.3–15.7 | |||
| JMS only: Men/women | |||||||
| Men y ic | 1 | 1 | 47 | 45.6 | 1.35 | 43.0–48.2 | |
| Women y ic | 2 | 2 | 78 | 37.7 | 1.09 | 35.6–39.9 | <.001 |
| Women y ic versus men y ic | WMD | −7.9 | 2.02 | −11.8 to −3.9 | |||
| Men o ic | 11 | 11 | 1794 | 32.5 | 0.81 | 31.0–34.1 | |
| Women o ic | 16 | 19 | 3314 | 31.0 | 0.59 | 29.8–32.1 | .118 |
| Women o ic versus men o ic | WMD | −1.5 | 0.99 | −3.5 to 0.4 | |||
| Men o nc | 4 | 4 | 126 | 23.6 | 1.95 | 19.8–27.4 | |
| Women o nc | 5 | 5 | 311 | 23.3 | 1.56 | 20.2–26.4 | .895 |
| Women o nc versus men o nc | WMD | −0.3 | 2.48 | −5.2 to 4.5 | |||
| Young adults/older adults | |||||||
| Men y ic | 1 | 1 | 47 | 45.6 | 1.35 | 43.0–48.2 | |
| Men o ic | 11 | 11 | 1794 | 32.5 | 0.81 | 31.0–34.1 | <.001 |
| Men o ic versus men y ic | WMD | −13.1 | 2.95 | −18.8 to −7.3 | |||
| Women y ic | 2 | 2 | 78 | 37.7 | 1.09 | 35.6–39.9 | |
| Women o ic | 16 | 19 | 3314 | 31.0 | 0.59 | 29.8–32.1 | .001 |
| Women o ic versus women y ic | WMD | −6.6 | 1.93 | −10.4 to −2.9 | |||
| Independent/nursing care | |||||||
| Men o ic | 11 | 11 | 1794 | 32.5 | 0.81 | 31.0–34.1 | |
| Men o nc | 4 | 4 | 126 | 23.6 | 1.95 | 19.8–27.4 | <.001 |
| Men o nc versus men o ic | WMD | −8.9 | 1.83 | −12.5 to −5.3 | |||
| Women o ic | 16 | 19 | 3314 | 31.0 | 0.59 | 29.8–32.1 | |
| Women o nc | 5 | 5 | 311 | 23.3 | 1.56 | 20.2–26.4 | <.001 |
| Women o nc versus women o ic | WMD | −7.6 | 1.42 | −10.4 to −4.8 | |||
| (b) | |||||||
|---|---|---|---|---|---|---|---|
| No. of studies | No. of subgroups (rows) | No. of patients | EWM /WMD | SE | 95% CI | p‐value | |
| Gender | |||||||
| Men | 17 | 17 | 2015 | 30.6 | 1.59 | 27.5–33.7 | |
| Women | 23 | 27 | 3752 | 20.1 | 0.73 | 18.7–21.5 | <.001 |
| Women versus men | WMD | −10.5 | 1.54 | −13.5 to −7.5 | |||
| Device | |||||||
| JMS | 41 | 68 | 9794 | 23.7 | 0.86 | 22.0–25.4 | |
| IOPI | 3 | 7 | 549 | 28.0 | 2.50 | 23.2–32.9 | .125 |
| IOPI versus JMS | WMD | 4.3 | 2.83 | −1.2 to 9.9 | |||
| Need for care | |||||||
| ic | 28 | 45 | 8270 | 25.7 | 0.85 | 24.1–27.4 | |
| nc | 14 | 20 | 1244 | 16.7 | 0.88 | 14.9–18.4 | <.001 |
| nc versus ic | WMD | −9.0 | 1.41 | −11.8 to −6.3 | |||
| Age | |||||||
| o | 41 | 65 | 9514 | 23.0 | 0.83 | 21.4–24.6 | |
| y | 7 | 10 | 829 | 31.7 | 1.64 | 28.4–34.9 | <.001 |
| y versus o | WMD | 8.7 | 2.24 | 4.3–13.1 | |||
| JMS only: Men/women | |||||||
| Men y ic | 1 | 1 | 47 | 40.9 | 0.95 | 39.1–42.8 | |
| Women y ic | 2 | 2 | 78 | 25.6 | 1.23 | 23.2–28.0 | <.001 |
| Women y ic versus men y ic | WMD | −15.3 | 2.22 | −19.7 to −11.0 | |||
| Men o ic | 11 | 11 | 1794 | 33.1 | 0.69 | 31.8–34.5 | |
| Women o ic | 16 | 19 | 3314 | 21.3 | 0.44 | 20.5–22.2 | <.001 |
| Women o ic versus men o ic | WMD | −11.8 | 0.78 | −13.3 to −10.2 | |||
| Men o nc | 4 | 4 | 126 | 20.2 | 1.18 | 17.9–22.5 | |
| Women o nc | 5 | 5 | 311 | 13.4 | 0.31 | 12.8–14.1 | <.001 |
| Women o nc versus men o nc | WMD | −6.7 | 0.90 | −8.4 to −4.9 | |||
| Young adults/older adults | |||||||
| Men y ic | 1 | 1 | 47 | 40.9 | 0.95 | 39.1–42.8 | |
| Men o ic | 11 | 11 | 1794 | 33.1 | 0.69 | 31.8–34.5 | .001 |
| Men o ic versus men y ic | WMD | −7.8 | 2.43 | −12.6 to −3.1 | |||
| Women y ic | 2 | 2 | 78 | 25.6 | 1.23 | 23.2–28.0 | |
| Women o ic | 16 | 19 | 3314 | 21.3 | 0.44 | 20.5–22.2 | .003 |
| Women o ic versus women y ic | WMD | −4.3 | 1.46 | −7.1 to −1.4 | |||
| Independent/nursing care | |||||||
| Men o ic | 11 | 11 | 1794 | 33.1 | 0.69 | 31.8–34.5 | |
| Men o nc | 4 | 4 | 126 | 20.2 | 1.18 | 17.9–22.5 | <.001 |
| Men o nc versus men o ic | WMD | −12.9 | 1.38 | −15.6 to −10.2 | |||
| Women o ic | 16 | 19 | 3314 | 21.3 | 0.44 | 20.5–22.2 | |
| Women o nc | 5 | 5 | 311 | 13.4 | 0.31 | 12.8–14.1 | <.001 |
| Women o nc versus women o ic | WMD | −7.7 | 0.90 | −9.5 to −6.0 | |||
Abbreviations: EWM, estimated weighted mean; ic, independent group; nc, nursing care group; o, older adults; WMD, estimated weighted mean difference between groups; y, young adults.
Except for JMS only, women e nc versus men e nc (t‐test for independent group).
3.4.2. Handgrip strength
Regarding age group, the WMD between young and older adults' groups was 8.7 kg (SE: 2.24 kg), indicating that HGS was significantly higher in subjects <60 years (p < .001). Furthermore, a significantly higher HGS values among IC were found in younger group than in older adults' group both for men (p = .001) and women (p = .003).
Regarding gender, the HGS was significantly higher in men than in women (WMD: −10.5 kg; SE: 1.54 kg; p < .001). Analysing the gender differences in combination with age and need for care, a significantly higher HGS was shown in men than in women in the younger IC, in older adults IC and in older adults NC (all p < .001).
Regarding need for care, the HGS was significantly higher in the IC compared to the NC, with a WMD of −9.0 kg (SE: 1.41 kg) (p < .001). When analysing the difference in HGS values between IC and NC in older adults, HGS was significantly higher in the IC than in the NC for both men and women (both p < .001). Table 3b provides a detailed overview on the EWM HGS for each group and the WMD between groups.
3.4.3. Effect of handgrip strength on tongue pressure
The null hypothesis of homogeneity of studies was rejected by statistical test (p < .05 for each analysis) for all forest plots. Therefore, random‐effects models were used for the analysis in this study because this approach allows variation (heterogeneity) of study outcomes, that is heterogeneity of studies is incorporated in the analysis. The random‐effects meta‐regression analysis to evaluate the effect of HGS on TP was performed separately for all studies and for different groups, including age, gender, device and need for care. There is a significant positive correlation between TP and HGS in older adults' group (p < .001), in men (p = .006), in women (p = .002), in the group with TP values measured with JMS (p < .001), in IC (p = .001) and in NC (p = .024), whereas no significant correlation in young group (p = .053) and in the group with TP values measured with IOPI (p = .100; Table 4a; Figure 2) Subsequently, the multivariate analysis based on data from all studies (n = 75), adjusting for age, device and need for care, showed a significant positive effect of HGS and TP (p < .001; Table 4b).
TABLE 4.
(a) Effect of handgrip strength on tongue pressure – analysis of all studies and subgroups (multivariate random‐effects meta‐regression) and (b) Effect of handgrip strength on tongue pressure (multivariate random‐effects meta‐regression adjusted for device, need for care and age) (n = 75).
| (a) | ||||
|---|---|---|---|---|
| No. of subgroups | Coeff. [95% CI] | p‐value | Adj. R 2 (%) | |
| Total | 75 | 0.69 [0.51–0.86] | <.001 | 46.9 |
| Gender | ||||
| Men | 17 | 0.74 [0.25–1.23] | .006 | 38.9 |
| Women | 27 | 0.83 [0.34–1.33] | .002 | 32.2 |
| Device | ||||
| JMS | 68 | 0.58 [0.45–0.71] | <.001 | 56.2 |
| IOPI | 7 | 0.79 [−0.22 to 1.79] | .100 | 34.7 |
| Need for care | ||||
| Independent | 55 | 0.46 [0.20–0.71] | .001 | 19.5 |
| Nursing care | 20 | 0.50 [0.07–0.92] | .024 | 26.1 |
| Age | ||||
| Older adults | 65 | 0.53 [0.35–0.72] | <.001 | 36.1 |
| Young adults | 10 | 0.90 [−0.01 to 1.80] | .053 | 34.5 |
| (b) | |
|---|---|
| Coeff. [95% CI] | p‐value |
| 0.28 [0.14–0.42] | <.001 |
Note: (a): Estimation by random‐effects meta‐regression. (b): Estimation by random‐effects meta‐regression adjusted for device, need for care and age.
FIGURE 2.
Linear relationship between mean tongue pressure and mean handgrip strength estimated by random‐effects meta‐regression (straight line) and the scatter plot of mean tongue pressure and mean handgrip strength (circles) for (A) men, (B) women, (C) independent subjects, (D) subjects with nursing care, (E) older adults, (F) young people, (G) subjects who were measured for tongue pressure with JMS, (H) subjects who were measured for tongue pressure with IOPI.
4. DISCUSSION
In this systematic review and meta‐analysis, TP and HGS values were summarised by age groups, gender, need for care and measuring device, and the effect of HGS on TP was analysed. TP and HGS were significantly higher in people <60 years than in those ≥60 years, in men than in women and in people living independently than in people receiving nursing care. In addition, there was a significant difference in TP between measured with IOPI and JMS. A significant correlation between HGS and TP was observed. Therefore, the null hypothesis was rejected.
Tongue pressure increases with age during the growth stage of childhood 29 and decreases with aging. A previous study reported that TP and HGS values in healthy older adults were significantly higher than in older adults receiving nursing care. 30 Regarding the tongue pressure, it was suggested that it may conclude that healthy older people could maintain a value of 30 kPa. 31 In the present study, older adults' groups were classified into those with and without nursing care, and the EWM TP indicated that the independent older adults were 32.5 kPa for men and 31.0 kPa for women, while those requiring nursing care were 23.6 kPa for men and 23.3 kPa for women, supporting the tongue pressure reference value for oral hypofunction. 11 With regard to gender, previous studies found that TP was significantly higher in men than in women among healthy older adults, 32 , 33 whereas no significant gender difference in older adults receiving nursing care 34 , 35 and in healthy older adults 36 as demonstrated in our previous systematic review. 37 The current results similarly indicated a significant gender difference in the healthy young group, while no significant gender difference was found in the older adults' group, either in IC or NC. The proportion of older adults requiring nursing care increases with age, 38 and older adults requiring nursing care have lower potential, ADL and oral function than independent older adults. The first thing to consider is that individual difference might be more influential than gender difference in older adults. The second thing to consider is that there would be less change in tongue pressure with age in women. Among women, aging‐induced decreases in swallowing‐related muscle strength tended to be more gradual than the corresponding decreases in whole‐body strength. 39 In fact, the current study found that WMD between healthy older and younger people was smaller in women with a WMD of −6.6 kPa (SE: 1.93 kPa) than in men with a WMD of −13.1 kPa (SE: 2.95 kPa).
The HGS, one of the criteria for sarcopaenia and frailty, is defined by the Asian Working Group for Sarcopaenia (AWGS) as the threshold for low muscle strength in Asians: <28 kg for men and <18 kg for women. The EWM HGS values in this present meta‐analysis were 33.1 kg for men and 21.3 kg for women in independent older adults, and 20.8 kg for men and 13.8 kg for women in older adults requiring care, which are very reasonable considering the AWGS reference values. HGS is used to assess physical function in the rehabilitation field. 40 One systematic review illustrated that HGS was associated with mobility and ADL in older people. 41 In this present review, adjusting for age, gender, need for care and tongue pressure measuring device, HGS and TP are significantly correlated.
Previous evidence on a correlation between HGS and TP is indecisive. 22 , 30 , 31 , 33 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 In the present meta‐analysis, TP was used as dependent variable and HGS was used as an independent variable, that is the estimated coefficient shows the influence (effect) of handgrip strength on tongue pressure. Significant correlations between HGS and TP could be shown in independent group (p = .001), in requiring nursing care group (p = .024) and in older adults' group (p < .001), but not in young group (p = .053) as the p‐value was just above the level of significance. This result might be due to the small number of young groups studies (n = 7). Furthermore, the estimated coefficients of men and women are very similar (0.74 [0.25–1.23], 0.83 [0.34–1.33]). Since there was no hint that the effect of HGS on TP does depend on gender, it was estimated without adjusting for gender factors in Table 4b. The results of this present study suggested that HGS can be used to roughly analyse TP. Measuring HGS is an easier approach for non‐dental health‐care professionals, as they do not have to look in the patients' mouths. And if HGS is low, it may predict a decline in oro‐facial function and help to collaborate with dentistry.
An accumulated poor oral status including low TP was reported to significantly predict future physical weakening (new onsets of physical frailty, sarcopaenia and disability), 7 and low TP would significantly hinder food bolus formation and propagation, thus leading to malnourishment following decreased oral intake. 45 , 54 A decrease in the food intake diversity is considered to be a risk to decrease the limb skeletal muscle mass. 55 TP is one of the muscle strength indicators of the swallowing muscles, 56 or predictors of the risk of low nutrition. 57 The swallowing muscles are inevitably affected by malnutrition and disuse. 58 It has also been noted that although the swallowing muscles are strained, it receives constant input stimulation from the respiratory centre and are different from other skeletal muscles, and there is no certainty as to whether the swallowing muscle and other skeletal muscles undergo functional decline in parallel. 58 , 59 TP and HGS have been correlated, but the direct mechanism is not yet clear. In the future, with increasing evidence that poor oral function can lead to a deterioration of general health, it may be effective and important to expand the opportunities for TP measurements as well as HGS measurements. Furthermore, a lot studies have suggested that low nutrition, sarcopaenia and dysphagia are closely related. 60 Further research is needed to prevent the vicious circle of ‘sarcopaenia ‐ dysphagia ‐ low nutrition’ 59 from starting.
This systematic review has some limitations. The number of young people was less than that of older adults. In addition, there were only three study investigated TP and HGS in healthy young people, divided by gender. Data on TP values were taken from studies that measured tongue pressure using either JMS or IOPI. As a result, most of the studies used JMS, and most of the studies were performed in Japan. In the future, it will be necessary to analyse research data not only from Japan but also from around the world. It is expected to contribute to the further development of healthy longevity by examining the differences between countries and new perspectives on the characteristics of older people.
It was proposed that oro‐facial fitness is a state in which the physiological, psychosocial and environmental requirements of life of an individual are met. 10 The loss of oro‐facial function may or may not be restored through dental intervention or training. 10 Reduced neuro‐plastic capacity in older adults might preclude a positive outcome of these strategies that might need to be accompanied by functional training and nutritional counselling. 10 However, a few longitudinal studies reported physical and/or intervention and nutritional management for older adults could be effective to improve oral and physical function. 61 , 62 , 63 , 64 Additionally, another previous study suggested that decrease in overall muscle strength, which may result from bedrest during hospitalisation, is more important as a factor than the actual performance of activities of daily living in the reduction of TP. 53 On the other hand, age‐related decline in TP might be associated with high TP, reflecting decreased reserve. 31 Although many studies have shown that age‐related changes result in a decrease in tongue pressure, a previous study was reported that age‐related decline in tongue function might be different from decline in physical function, 31 suggesting that further longitudinal studies are needed. Additionally analysing the relationship between oral function and muscle mass, nutritional status, cognitive function, level of care and psychosocial function will be essential in examining the factors that influence it.
5. CONCLUSIONS
Based on the results of this systematic review and meta‐analysis, it is concluded that when tongue pressure is measured using the JMS:
Tongue pressure and handgrip strength are higher in subjects younger than 60 years relative to subjects 60 years and older in both men and women.
Gender differences were found in tongue pressure and handgrip strength in the younger independent subjects. However, in older adults' group, there is significantly gender difference in handgrip strength, but not tongue pressure regardless of the presence or absence of receiving care.
In older adults' group, subjects who live independently have significantly higher tongue pressure and handgrip strength compared to those who receive care.
Handgrip strength and tongue pressure are significantly correlated.
It is suggested further study might be necessary to research on rehabilitation measures for muscle strength, similar to handgrip strength might be beneficial to improve the personally acquired oro‐facial potential according to age‐related sarcopaenia.
AUTHOR CONTRIBUTION
Itsuka Arakawa‐Kaneko initiated the study together with Samir Abou‐Ayash and Martin Schimmel, and conceptualised and designed the study, collected and analysed data, drafted and revised the manuscript. Yuko Watarai contributed to data collection, and analysis during the systematic search. Martin Schimmel contributed to the conception and design of the study and critically revised the manuscript. Samir Abou‐Ayash contributed to the conception and design of the study, analysing data and critically revised the manuscript.
CONFLICT OF INTEREST
The authors have no conflicts of interest to declare.
PEER REVIEW
The peer review history for this article is available at https://publons.com/publon/10.1111/joor.13362.
Supporting information
Figure S1
Appendix S1
Appendix S2
ACKNOWLEDGEMENTS
The authors express their gratitude to biostatistician Mrs. Hiltrud Niggemann for conducting the statistical analysis. The authors declare they received no financial funding for this investigation. Open access funding provided by Universitat Bern.
Arakawa‐Kaneko I, Watarai Y, Schimmel M, Abou‐Ayash S. Relationship between tongue pressure and handgrip strength: A systematic review and meta‐analysis. J Oral Rehabil. 2022;49:1087‐1105. doi: 10.1111/joor.13362
DATA AVAILABILITY STATEMENT
The original data can be made available upon reasonable request.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Figure S1
Appendix S1
Appendix S2
Data Availability Statement
The original data can be made available upon reasonable request.