Predicting the incidence of mild cognitive impairment with a computer-based cognitive assessment tool in community-dwelling older adults: The Otassha study.

This study examined the ability of a computer-based cognitive assessment tool (CompBased-CAT) to predict mild cognitive impairment (MCI) in community-dwelling older adults. A two-year longitudinal study was conducted using data from 2016 to 2018 from the Otassha study cohort of community-dwelling older adults. MCI was defined as a Mini-Mental Status Examination (MMSE) score of <27. The CompBased-CAT was used at baseline, with each subtest score converted into a Z-score. Subsequently, the total Z-scores were calculated. Participants were divided into robust and MCI groups, and all variables were compared using the t-test or χ2 test. Receiver operating characteristic (ROC) curves and logistic regression analyses were conducted, with MCI and total Z-scores as dependent and independent variables, respectively. Among the 455 participants (median age, 72 years; range, 65-89 years; 282 women and 173 men), 32 developed MCI after two years. The participants in the MCI group were significantly older. They had lower maximal gait speed, baseline MMSE scores, subtest Z-scores, and total Z-scores than those in the robust group. The area under the ROC curve was 0.79 (95% confidence interval: 0.70-0.87; P <0.01). The sensitivity was 0.76, and the specificity was 0.75. The logistic regression analysis showed an odds ratio of 1.34 (95% confidence interval: 1.18-1.52; P <0.01). This study showed that CompBased-CAT can detect MCI, which is an early stage of dementia. Thus, CompBased-CAT can be used in future community health checkups and events for older adults.

A Single Motivational Lecture Can Promote Modest Weight Loss: A Randomized Controlled Trial.

BACKGROUND: Obesity is a public health problem worldwide. To widely disseminate weight-loss interventions across the target population, a cost-effective approach is needed. OBJECTIVE: We aimed to test whether a single motivational lecture could promote weight loss. METHODS: Our study was a 3-month randomized controlled trial, and we recruited participants via local newspaper advertisements in 3 cities in Ibaraki Prefecture, Japan, and randomly assigned them to a control group (no intervention) and an intervention group, who attended a single motivational lecture lasting approximately 2 h. No other lectures or textbooks were provided. The eligibility criteria included an age of 40-64 years, a body mass index (BMI) of 25-40 kg/m2, and the presence of at least 1 component of metabolic syndrome. The primary outcome was body weight change at 3 months. RESULTS: We enrolled 145 eligible participants with a mean age of 53.8 ± 7.1 years and a BMI of 28.5 ± 3.1 kg/m2. The 3-month body weight change in the control and intervention groups was -0.65 kg (95% confidence interval [CI] -1.09 to -0.20) and -2.48 kg (95% CI -3.01 to -1.95), respectively. The between-group difference was 1.83 kg (95% CI 1.15-2.51). CONCLUSIONS: The significant difference suggested that a single motivational lecture is an effective option to promote modest weight loss in the short term.

Effects of Vibrotactile Feedback on Sedentary Behaviors in Adults: A Pilot Randomized Controlled Trial.

No effective and easily implemented intervention strategies for reducing sedentary behavior have been established. This pilot trial (UMIN000024372) investigated whether vibrotactile feedback reduces sedentary behavior. Twenty-six adults aged 30-69 years who were sedentary ≥8 h/day were randomly assigned to control (n = 13) or vibration (n = 13) groups. Participants wore a monitor 9 h daily for seven-day periods at baseline (week zero), during the intervention (weeks one, three, five, and seven), and after the intervention (week eight). During the eight-week intervention, vibration-group participants were notified by a vibration through the monitor whenever continuous sedentary time reached ≥30 min; they also received weekly reports of their sedentary patterns. Control-group participants did not receive feedback. The primary outcome was change in total sedentary time. Changes in longer bouts of sedentary time (≥35 min) were also assessed. No significant difference was found in the change in total sedentary time (control: -17.5 min/9 h, vibration: -9.1 min/9 h; p = 0.42). Although no significant differences were observed in sedentary time in longer bouts, vibration-group participants exhibited significantly lower sedentary time (-21.6 min/9 h, p = 0.045). Thus, vibration feedback does not appear to offer any advantages in reducing total sedentary time.

Accuracy of 12 Wearable Devices for Estimating Physical Activity Energy Expenditure Using a Metabolic Chamber and the Doubly Labeled Water Method: Validation Study.

BACKGROUND: Self-monitoring using certain types of pedometers and accelerometers has been reported to be effective for promoting and maintaining physical activity (PA). However, the validity of estimating the level of PA or PA energy expenditure (PAEE) for general consumers using wearable devices has not been sufficiently established. OBJECTIVE: We examined the validity of 12 wearable devices for determining PAEE during 1 standardized day in a metabolic chamber and 15 free-living days using the doubly labeled water (DLW) method. METHODS: A total of 19 healthy adults aged 21 to 50 years (9 men and 10 women) participated in this study. They followed a standardized PA protocol in a metabolic chamber for an entire day while simultaneously wearing 12 wearable devices: 5 devices on the waist, 5 on the wrist, and 2 placed in the pocket. In addition, they spent their daily lives wearing 12 wearable devices under free-living conditions while being subjected to the DLW method for 15 days. The PAEE criterion was calculated by subtracting the basal metabolic rate measured by the metabolic chamber and 0.1×total energy expenditure (TEE) from TEE. The TEE was obtained by the metabolic chamber and DLW methods. The PAEE values of wearable devices were also extracted or calculated from each mobile phone app or website. The Dunnett test and Pearson and Spearman correlation coefficients were used to examine the variables estimated by wearable devices. RESULTS: On the standardized day, the PAEE estimated using the metabolic chamber (PAEEcha) was 528.8±149.4 kcal/day. The PAEEs of all devices except the TANITA AM-160 (513.8±135.0 kcal/day; P>.05), SUZUKEN Lifecorder EX (519.3±89.3 kcal/day; P>.05), and Panasonic Actimarker (545.9±141.7 kcal/day; P>.05) were significantly different from the PAEEcha. None of the devices was correlated with PAEEcha according to both Pearson (r=-.13 to .37) and Spearman (ρ=-.25 to .46) correlation tests. During the 15 free-living days, the PAEE estimated by DLW (PAEEdlw) was 728.0±162.7 kcal/day. PAEE values of all devices except the Omron Active style Pro (716.2±159.0 kcal/day; P>.05) and Omron CaloriScan (707.5±172.7 kcal/day; P>.05) were significantly underestimated. Only 2 devices, the Omron Active style Pro (r=.46; P=.045) and Panasonic Actimarker (r=.48; P=.04), had significant positive correlations with PAEEdlw according to Pearson tests. In addition, 3 devices, the TANITA AM-160 (ρ=.50; P=.03), Omron CaloriScan (ρ=.48; P=.04), and Omron Active style Pro (ρ=.48; P=.04), could be ranked in PAEEdlw. CONCLUSIONS: Most wearable devices do not provide comparable PAEE estimates when using gold standard methods during 1 standardized day or 15 free-living days. Continuous development and evaluations of these wearable devices are needed for better estimations of PAEE.

Simultaneous Validation of Seven Physical Activity Questionnaires Used in Japanese Cohorts for Estimating Energy Expenditure: A Doubly Labeled Water Study.

BACKGROUND: Physical activity questionnaires (PAQs) used in large-scale Japanese cohorts have rarely been simultaneously validated against the gold standard doubly labeled water (DLW) method. This study examined the validity of seven PAQs used in Japan for estimating energy expenditure against the DLW method. METHODS: Twenty healthy Japanese adults (9 men; mean age, 32.4 [standard deviation {SD}, 9.4] years, mainly researchers and students) participated in this study. Fifteen-day daily total energy expenditure (TEE) and basal metabolic rate (BMR) were measured using the DLW method and a metabolic chamber, respectively. Activity energy expenditure (AEE) was calculated as TEE - BMR - 0.1 × TEE. Seven PAQs were self-administered to estimate TEE and AEE. RESULTS: The mean measured values of TEE and AEE were 2,294 (SD, 318) kcal/day and 721 (SD, 161) kcal/day, respectively. All of the PAQs indicated moderate-to-strong correlations with the DLW method in TEE (rho = 0.57-0.84). Two PAQs (Japan Public Health Center Study [JPHC]-PAQ Short and JPHC-PAQ Long) showed significant equivalence in TEE and moderate intra-class correlation coefficients (ICC). None of the PAQs showed significantly equivalent AEE estimates, with differences ranging from -547 to 77 kcal/day. Correlations and ICCs in AEE were mostly weak or fair (rho = 0.02-0.54, and ICC = 0.00-0.44). Only JPHC-PAQ Short provided significant and fair agreement with the DLW method. CONCLUSIONS: TEE estimated by the PAQs showed moderate or strong correlations with the results of DLW. Two PAQs showed equivalent TEE and moderate agreement. None of the PAQs showed equivalent AEE estimation to the gold standard, with weak-to-fair correlations and agreements. Further studies with larger sample sizes are needed to confirm these findings.

The influence of physical activity-induced energy expenditure on the variance in body weight change among individuals during a diet intervention.

OBJECTIVE: We investigated the relationship between the variability in body weight change among individuals and diet restriction or physical activity during a 14-week intervention. DESIGN: A prospective clinical trial with a 14-week weight reduction intervention design. In total, 90 middle aged, Japanese, obese women enrolled as subjects. MEASUREMENTS: The outcome variable was the change in body weight during the intervention period. Other primary variables were total energy intake, carbohydrate intake, fat intake, protein intake, total energy expenditure (TEE), and activity energy expenditure (AEE). Diet intake was assessed by 3 days, weighed dietary records and dietary recall interviews. Physical activity was assessed by a uniaxial accelerometry sensor and a diary of exercise. RESULTS: Significant reductions were observed in body weight (-8.5 kg) as a result of intervention. When the subjects were assigned to three categories depending on AEE during intervention, the loss of body weight was significantly greater for subjects within the upper (-9.6 kg) AEE category than for those in the middle (-8.5 kg) or lower AEE (-7.5 kg) categories. In addition, a significant correlation (r = 0.57, p < 0.0001) was observed between a subject's AEE before and during the intervention. On the other hand, no significant correlation was observed between body weight reduction and energy intake, indicating that strict diet restriction does not always result in a large weight loss. CONCLUSION: Activity energy expenditure, not only through voluntary exercise but also through spontaneous, daily, physical activities can have a positive effect on reducing body weight.