METHODS: Fourteen trained male cyclists (age: 32 ± 12 year; height: 178 ± 6 cm; mass: 76 ± 9 kg; [Formula: see text]: 59 ± 9 mL kg-1 min-1; body surface area: 1.93 ± 0.12 m2; peak power output: 393 ± 53 W) volunteered, and underwent 1 exercise bout in moderate heat (MOD: 34.9 ± 0.2 °C, 50.1 ± 1.1% relative humidity) and 1 in mild heat (MILD: 29.2 ± 0.2 °C, 69.4 ± 0.9% relative humidity) matched for vapor pressure (2.8 ± 0.1 kPa), with trials counterbalanced.

METHODS AND STUDY DESIGN: The data used for this analysis were from 1143 children, 6-12 years old, that participated in the South East Asian Nutrition Survey (SEANUTS). Physical activity (PA) was measured using pedometers for 2 consecutive days and was categorized low, moderate and high. Child nutritional status was categorized based on body mass index for age z-scores (BAZ) into normal weight (-2 SD ≤BAZ≤1 SD) or overweight (BAZ >1 SD). Energy intake was calculated from a one day 24 hour recall and compared to the Indonesian recommended dietary allowance (RDA) for energy.

RESULTS: Children with low PA had higher risk (ODDs 3.4, 95% CI: 2.0, 6.0) of being overweight compared to children who had high PA. Children with moderate PA and energy take >100% RDA had higher risk (ODDs 4.2, 95% CI 1.9, 9.3) of being overweight than children with high PA and energy intakes ≤100% RDA.

METHODS: This was a single-center, prospective, and single-blind randomized controlled trial conducted at the University Malaya Medical Centre. Patients older than 65 years presenting to the hospital emergency department or geriatric clinic with 1 injurious fall or 2 falls in the past year and with impaired functional mobility were included in the study. The intervention group received a modified OEP intervention (n = 34) for 3 months, while the control group received conventional care (n = 33). All participants were assessed at baseline and 6 months.

RESULTS: Twenty-four participants in both OEP and control groups completed the 6-month follow-up assessments. Within-group analyses revealed no difference in grip strength in the OEP group (P = 1.00, right hand; P = .55, left hand), with significant deterioration in grip strength in the control group (P = .01, right hand; P = .005, left hand). Change in grip strength over 6 months significantly favored the OEP group (P = .047, right hand; P = .004, left hand). Significant improvements were also observed in mobility and balance in the OEP group.

OBJECTIVE: Thus, we aimed to determine the impacts of protein supplementation and exercise in older adults with sarcopenic obesity.

METHOD: A systematic database search was conducted for randomised controlled trials, quasi experimental study and pre-post study design addressing the effects of protein supplementation in improving sarcopenic obesity among older adults. This scoping review was conducted based on PRISMA-Scr guidelines across PubMed, Embase, Web of Science and Cochrane Library databases. To assess record eligibility, two independent reviewers performed a rigorous systematic screening process.

RESULTS: Of the 1,811 citations identified, 7 papers met the inclusion criteria. Six studies were randomised controlled trials and one study was a pre-post test study design. The majority of studies discussed the use of both protein supplements and exercise training. The included studies prescribed protein intake ranging from 1.0 to 1.8 g/kg/BW/day for the intervention group, while the duration of exercise performed ranged from 2 to 3 times per week, with each session lasting for 1 hour. Whey protein supplementation has been shown to be effective in improving sarcopenic conditions and weight status in SO individuals. The combination of exercise training especially resistance training and the used of protein supplement provided additional benefits in terms of lean muscle mass as well as biomarkers. The study also revealed a lack of consistency in exercise design among interventions for sarcopenic obesity.

METHODS: Data of 328 eligible housewives who participated in the MyBFF@Home study was used. Intervention group of 169 subjects were provided with an intervention package which includes physical activity (brisk walking, dumbbell exercise, physical activity diary, group exercise) and 159 subjects in control group received various health seminars. Physical activity level was assessed using short-International Physical Activity Questionnaire. The physical activity level was then re-categorized into 4 categories (active intervention, inactive intervention, active control and inactive control). Physical activity, blood glucose and lipid profile were measured at baseline, 3rd month and 6th month of the study. General Linear Model was used to determine the effect of physical activity on glucose and lipid profile.

RESULTS: At the 6th month, there were 99 subjects in the intervention and 79 control group who had complete data for physical activity. There was no difference on the effect of physical activity on the glucose level and lipid profile except for the Triglycerides level. Both intervention and control groups showed reduction of physical activity level over time.

METHODS: This was a quasi-experimental study conducted in low-cost flats in Kuala Lumpur, Malaysia. A total of 255 overweight and obesity individuals aged between 18 to 59 years old were assigned to either the lifestyle intervention group (n = 169) or the usual care group (n = 146) over a period of 6 months. Individuals in the intervention group received 6 individual lifestyle counselling comprised of physical activity, diet counselling and self-monitoring components aimed to achieve at least 5% weight loss while individuals in the usual care group obtained six sessions of health care seminars from health care providers. These individuals were then followed-up for another 6 months without any intervention as part of maintenance period.

RESULTS: An intention-to-treat analysis of between-groups at 6-month of intervention (β, 95% CI) revealed greater changes in weight among intervention individuals' (- 1.09 kg vs. -0.99; p  0.05). Individuals in the intervention group showed a significant increase for skeletal muscle mass (0.13 kg) than those individuals in the control group (- 0.37 kg), p = 0.033, throughout the study period.

METHODS: Thirty-six players were divided into 3 groups; FIFA 11+, HarmoKnee and control (n = 12 per group). These exercises were performed 3 times per week for 2 months (24 sessions). The CSR, DCR and FSR were measured before and after the intervention.

RESULTS: After training, the CSR and DCR of knee muscles in both groups were found to be lower than the published normal values (0.61, 0.72, and 0.78 during 60°.s(-1), 180°.s(-1) and 300°.s(-1), respectively). The CSR (60°.s(-1)) increased by 8% and FSR in the quadriceps of the non-dominant leg by 8% in the 11+. Meanwhile, the DCR in the dominant and non-dominant legs were reduced by 40% and 30% respectively in the 11+. The CSR (60°.s(-1)) in the non-dominant leg showed significant differences between the 11+, HarmoKnee and control groups (p = 0.02). As for the DCR analysis between groups, there were significant differences in the non-dominant leg between both programs with the control group (p = 0.04). For FSR no significant changes were found between groups.

OBJECTIVE: This study aimed to investigate the validity of HR measures of a high-cost consumer-based tracker (Polar A370) and a low-cost tracker (Tempo HR) in the laboratory and free-living settings.

METHODS: Participants underwent a laboratory-based cycling protocol while wearing the two trackers and the chest-strapped Polar H10, which acted as criterion. Participants also wore the devices throughout the waking hours of the following day during which they were required to conduct at least one 10-min bout of moderate-to-vigorous physical activity (MVPA) to ensure variability in the HR signal. We extracted 10-second values from all devices and time-matched HR data from the trackers with those from the Polar H10. We calculated intraclass correlation coefficients (ICCs), mean absolute errors, and mean absolute percentage errors (MAPEs) between the criterion and the trackers. We constructed decile plots that compared HR data from Tempo HR and Polar A370 with criterion measures across intensity deciles. We investigated how many HR data points within the MVPA zone (≥64% of maximum HR) were detected by the trackers.

RESULTS: Of the 57 people screened, 55 joined the study (mean age 30.5 [SD 9.8] years). Tempo HR showed moderate agreement and large errors (laboratory: ICC 0.51 and MAPE 13.00%; free-living: ICC 0.71 and MAPE 10.20%). Polar A370 showed moderate-to-strong agreement and small errors (laboratory: ICC 0.73 and MAPE 6.40%; free-living: ICC 0.83 and MAPE 7.10%). Decile plots indicated increasing differences between Tempo HR and the criterion as HRs increased. Such trend was less pronounced when considering the Polar A370 HR data. Tempo HR identified 62.13% (1872/3013) and 54.27% (5717/10,535) of all MVPA time points in the laboratory phase and free-living phase, respectively. Polar A370 detected 81.09% (2273/2803) and 83.55% (9323/11,158) of all MVPA time points in the laboratory phase and free-living phase, respectively.

METHODS: A population-based cross-sectional study was conducted in Singapore. Participants wore an accelerometer for 7 days to measure physical activity (PA). Demographic, anthropometric and psychological data were also collected. Psychological variables included PA guideline knowledge, motivational profile for PA self-regulation (5 subscales), perceived barriers to PA (4 subscales) and perceived social support for PA. Regression models with adjustment for socio-demographic variables were fitted.

METHODS: A cross-sectional study was conducted in the Kandy district using multistage sampling. A total of 999 older people were recruited, with a female preponderance. Data were collected using interviewer-administered questionnaires on demographic characteristics, depression, and physical activity. Anthropometric measurements including weight, height, mid-upper arm circumference, calf circumference, and HGS were recorded. Complex sample general linear model was used to examine the association between HGS and its associated factors.

RESULTS: The mean highest HGS of the study group was 12.56 kg (95% confidence interval: 11.94-13.19). Male older people had a higher HGS (17.02, 95% confidence interval: 15.55-18.49 kg) than females (10.59, 95% confidence interval: 10.12-11.06 kg). For both men and women, older age was associated with lower HGS, while mid-upper arm circumference was associated with better HGS. Diabetes mellitus, vegetarian diet, and alcohol consumption were associated with HGS for women only.

METHODS: Out of the 7247 students in the ten selected schools studied, a total of 6248 students (2928 males, 3320 females) took part. A validated self-administered questionnaire was used. Data was analysed using SPSS version 22. Multivariable logistic regression was used to determine the adjusted odd ratio.

RESULTS: The prevalence of overweight and obesity was 16.0% and 11.5% respectively. Obesity/overweight was significantly (p<0.05) associated with gender, age, ethnicity, education level of father, education level of mother, physical activity, disordered eating, smoking status, body size perception and body part satisfaction. The multivariable analysis results showed that the odds of being overweight/obesity were higher in males compared to females (OR 1.56, 95%CI: 1.37, 1.77). The results also showed that the odds of being overweight/obesity were highest among those in age group 12 and 13 years and among Malay ethnicity. The odds of overweight/obesity were higher in those who was dissatisfied with their body parts, (OR 1.96, 95%CI: 1.71, 2.25), dissatisfied with their body size (OR: 4.25, 95%CI: 3.60, 5.02), low physical activity (OR 1.23, 95%CI: 1.06, 1.44), current smokers (OR 1.38, 95%CI: 1.07, 1.78) and at risk of having eating disorder (OR: 1.39, 95%CI 1.22, 1.59).