The relationship between body mass index (BMI) and frailty remains unclear. Using two validated frailty assessment tools, this study aimed to investigate the relationship between the prevalence of frailty and BMI in Japanese older adults. This cross-sectional study used baseline data of 7191 individuals aged ≥65 years, living in Kameoka City, Kyoto, Japan. The BMI was calculated based on self-reported height and body weight, and classified into six categories. Frailty was defined using two validated assessment tools, the Fried phenotype (FP) model and Kihon Checklist (KCL). We evaluated the relationship between frailty and BMI using a multivariate restricted cubic spline logistic regression. The prevalence of frailty defined using the FP model was 25.3%, 19.6%, 14.3%, 12.4%, 12.6%, and 19.4% for each BMI category of <18.5, 18.5–19.9, 20.0–22.4, 22.5–24.9, 25.0–27.4, and ≥27.5 kg/m², respectively. The spline model showed a significant U-shaped relationship between BMI and the prevalence of frailty defined using both, KCL and FP models. This study found that the BMI range corresponding to lowest prevalence of frailty defined using both tools was 21.4–25.7 kg/m². Thus, a healthy BMI may reduce the prevalence of frailty, and the risk of frailty needs to be evaluated in individuals who are underweight or overweight.

Background: The term “frailty” might appear simple, but the methods used to assess it differ among studies. Consequently, there is inconsistency in the classification of frailty and predictive capacity depending on the frailty assessment method utilised. We aimed to examine the diagnostic accuracy of several screening tools for frailty defined by the phenotype model in older Japanese adults. Methods: This cross-sectional study included 1,306 older Japanese adults aged ≥ 65 years who underwent physical check-up by cluster random sampling as part of the Kyoto-Kameoka Study in Japan. We evaluated the diagnostic accuracy of several screening instruments for frailty using the revised Japanese version of the Cardiovascular Health Study criteria as the reference standard. These criteria are based on the Fried phenotype model and include five elements: unintentional weight loss, weakness (grip strength), exhaustion, slowness (normal gait speed), and low physical activity. The Kihon Checklist (KCL), frailty screening index (FSI), and self-reported health were evaluated using mailed surveys. We calculated the non-parametric area under the receiver operating characteristic curve (AUC ROC) for several screening tools against the reference standard. Results: The participants’ mean (standard deviation) age was 72.8 (5.5) years. The prevalence of frailty based on the Fried phenotype model was 12.2% in women and 10.3% in men. The AUC ROC was 0.861 (95% confidence interval: 0.832–0.889) for KCL, 0.860 (0.831–0.889) for FSI, and 0.668 (0.629–0.707) for self-reported health. The cut-off for identifying frail individuals was ≥ 7 points in the KCL and ≥ 2 points in the FSI. Conclusions: Our results indicated that the two instruments (KCL and FSI) had sufficient diagnostic accuracy for frailty based on the phenotype model for older Japanese adults. This may be useful for the early detection of frailty in high-risk older adults.

Although oral frailty is independently associated with an increased risk of mortality, evidence for the usefulness of screening tools for oral frailty is less than that for physical frailty screening tools. We aimed to investigate the relationship between oral frailty and mortality in older adults. This prospective cohort study included 11,374 adults aged ≥65 years, who provided valid responses to a baseline mail survey questionnaire from the Kyoto-Kameoka study. Oral frailty status was evaluated using the Oral Frailty Index-8 (range, 0 [best] to 10 [worst]). Participants were classified into four categories according to the Oral Frailty Index-8: robust (score, 0-2), oral pre-frailty (score, 3), oral frailty (score, 4-6), and oral severe frailty (score ≥ 7). Physical and psychological frailty were evaluated using the validated frailty-screening index and defined as a score of ≥3 out of a possible 5 points. Mortality data were collected from 30 July 2011 to 30 November 2016. Hazard ratios (HR) for all-cause mortality were calculated using a multivariable Cox proportional hazards model. During the 5.3-year median follow-up period (57,157 person-years), 1184 deaths were recorded. After adjusting for confounders, including physical and psychological frailty, medical history, and lifestyle, in comparison with a robust oral status, oral pre-frailty (HR, 1.29; 95 % confidence interval [CI], 1.02-1.63), oral frailty (HR, 1.22; 95 % CI, 1.01-1.48), and oral severe frailty (HR, 1.43; 95 % CI, 1.16-1.76) were associated with higher HRs of mortality (p for trend = 0.002). Oral frailty is associated with mortality independent of physical and psychological frailty in older adults. The Oral Frailty Index-8 may be useful for identifying individuals at high risk of mortality.

Purpose: Whether the association between objectively assessed physical activity and mortality differs between adults with versus those without frailty is unclear. We investigated this association in community-dwelling older adults. Methods: This prospective study used the data of 4165 older adults 65 yr or older from the Kyoto–Kameoka study in Japan who wore a triaxial accelerometer (EW-NK52). The number of steps was classified by quartiles using the average daily value of data obtained from the accelerometer across four or more days. Frailty was evaluated using the validated Kihon Checklist. We evaluated the association between mortality and daily steps using a multivariable Cox proportional hazards analysis and restricted spline model. Results: The average daily steps for the first, second, third, and fourth quartiles were 1786, 3030, 4452, and 7502, respectively. In total, 113 deaths were recorded during a median follow-up of 3.38 yr (14,061 person-years). After adjusting for confounders, the top quartile was associated with a lower hazard ratio (HR) for mortality than the bottom quartile (HR = 0.39, 95% confidence interval = 0.18–0.85). In a stratified model by frailty status, the daily step count dose–response curve at which the HR for mortality plateaued among nonfrail individuals was approximately 5000–7000 steps per day. By contrast, the daily step count showed an inverse relationship with mortality at approximately 5000 steps or more per day in frail individuals. Conclusions: The relationship between daily steps and mortality is different between those with and those without frailty, and people with frailty may require more daily steps than those with nonfrailty to achieve the inverse relationship with mortality. These findings may be useful for informing future physical activity guidelines.

Accurate assessments of a target population’s energy intake (EI) are essential to prevent poor nutritional status. However, self-reported dietary records (DRs) or food frequency questionnaires (FFQs) are not always accurate, thereby requiring validation and calibration studies. This study aimed to validate the EI estimated by a FFQ using the doubly labeled water (DLW) method. Participants were 109 Japanese older adults (50 women and 59 men) aged 65–88 years. The EI was obtained by a DR and 47-item FFQ over 1 year. The total energy expenditure (TEE) was measured by DLW for ~2 weeks. EI was significantly lower than TEE (p < 0.01); ratios of EI assessed by DR and FFQ against TEE were 0.91 ± 0.17 and 0.82 ± 0.22, respectively. TEE was significantly and moderately correlated with the EI estimated by the DR (r = 0.45, p < 0.01) and FFQ (r = 0.37, p < 0.01). Furthermore, the EI correlation coefficients estimated by DR and the FFQ in this study were not significantly different (p = 0.46). The EI/TEE ratio was significantly and negatively correlated with the body mass index (BMI). In conclusion, EI estimated with a DR or FFQ modestly correlated with TEE, and calibrating EI with a developed equation in this study can attenuate the underestimation of EI.

The relationship between mixing ability of masticatory functions and frailty has not been well evaluated. This study investigated the prevalence of physical and comprehensive frailty and its association with mixing ability in 1106 older adults aged ≥65 years who underwent physical examination as part of the Japanese Kyoto–Kameoka Study. Mixing ability was assessed using color-changing chewing gum (1–5 points, 5 representing the best mixing ability). Participants were divided into four groups (5 points, 4 points, 3 points, and 1 or 2 points). The modified Japanese versions of the Cardiovascular Health Study (mJ-CHS) criteria and the validated Kihon Checklist (KCL) were used to assess physical and comprehensive frailty, respectively. Multivariate logistic regression was used to evaluate the association between frailty and mixing ability. The prevalence of physical and comprehensive frailty was 11.8% and 27.9%, respectively. After adjusting for confounders, the odds ratios of physical and comprehensive frailty comparing the highest to the lowest chewing gum score groups were 3.64 (95% confidence interval (CI): 1.62 to 8.18; p for trend = 0.001) and 2.09 (95% CI: 1.09 to 4.03; p for trend = 0.009), respectively. Mixing-ability tests involving chewing gum may be an indicator associated with both physical and comprehensive frailty.