The efficacy of exercise to reverse frailty in the aging population has not been extensively investigated. This study aimed to investigate the effectiveness of a multicomponent exercise program (MCEP) on frailty, physical performance (handgrip strength, Berg Balance Scale (BBS), Timed Up and Go test (TUG), and VO₂Max), blood biomarkers (Interleukin-6 (IL-6) and C-reactive protein (CRP)) in frail older adults. A randomized controlled trial using an allocation concealment method, included 64 older adults (77.78 ± 7.24 years), were divided into two parallel groups using block randomization: an MCEP group (n = 32) and a control group (n = 32). The combined center- and home-based MCEP training consisted of chair aerobic, resistance, and balance, which was carried out 3 days per week for 24 weeks. A mixed model repeated measure ANOVA demonstrated significant interaction effects of group x time for BBS, TUG and frailty scores (p < 0.001). Additionally, the post-hoc analysis revealed that the MCEP group showed significantly improved BBS, TUG, and frailty scores (p < 0.01), at both 12- and 24-weeks. When compared with controls at 12-weeks, the MCEP group decreased IL-6 and CRP levels (p < 0.05). The combined center- and home-based MCEP were effective in reversing frailty to pre-frailty and improving physical performance especially balance in the older population.

Effective interventions for indicated fall prevention are necessary for older adults with frailty. We aimed to determine the effectiveness of a Multi-system Physical Exercise (MPE) for fall prevention and Health-Related Quality of Life (HRQOL) in pre-frail older adults. This randomized control trial with allocation concealment included 72 adults aged 65 and above, identified as pre-frailty and with mild and moderate fall risk scores measured by the Physiological Profile Assessment (PPA). Randomly, using block randomization, participants were divided into two groups: an MPE group (n = 36) and a control group (n = 36). The intervention consisted mainly of proprioception, muscle strengthening, reaction time, and balance training and was carried out three days per week for 12 weeks. The primary outcome was fall risk assessed using PPA at 12 weeks post-baseline and at a 24 week follow-up. Significant differences were found in the improvement in fall risk, proprioception, muscle strength, reaction time and postural sway, and fear of fall scores in the MPE group compared with controls at week 12 and 24. In addition, HRQOL had increased significantly in the MPE group in comparison to controls. The MPE program significantly increased muscle strength and improved proprioception, reaction time, and postural sway leading to fall risk reduction in older adults with pre-frailty. Therefore, the MPE program is recommended for used in day-to-day primary care practice in the pre-frail population.

Introduction. Frailty is a condition in older adults with decreased physical and cognitive performance that can affect health outcomes associated with fracture, disability, and falls. The aim of this study was to compare fall risk with different physical frailty statuses and investigate factors associated with fall risk in community-dwelling older adults.Methods. The population studied included 367 older adults (mean age = 73.2 years ± 7.0; 237 females (64.6%) and 130 males (35.4%)) who live in Chiang Mai, Thailand. This study was of cross-sectional design. Fried’s phenotype was used to screen the physical frailty status. The physiological profile assessment (PPA) was used to screen for fall risk. One-way ANOVA analysis was used to compare the fall risk between the different levels of frailty status. Linear regression analysis was used to assess the association between frailty status and fall risk.Results. The prevalence of the frailty group was 8.7% and that of the prefrailty group was 76.8%. The three statuses of frailty identified were found to have different levels of risk of falling. The frailty group had a higher fall risk than the nonfrailty group and the prefrailty group. In addition, the nonfrailty group had a lower fall risk than the prefrailty group.Conclusion. The frailty group had the highest fall risk in this cohort of older adults living in a community-dwelling facility. Therefore, it is important to assess the frailty status among older adults as it can be a predictor for fall risk. This assessment will therefore lead to a reduction in the rate of disability and death in the community.

Cognitive frailty (CF) is defined by the coexistence of physical frailty and mild cognitive impairment. Malnutrition is an underlying factor of age-related conditions including physical frailty. However, the evidence associating malnutrition and cognitive frailty is limited. This cross-sectional study aimed to determine the association between malnutrition and CF in the elderly. A total of 373 participants aged 65–84 years were enrolled after excluding those who were suspected to have dementia and depression. Then, 61 CF and 45 normal participants were randomly selected to measure serum prealbumin level. Cognitive function was assessed using the Montreal Cognitive Assessment-Basic (MoCA-B). Modified Fried’s criteria were used to define physical frailty. Nutritional status was evaluated by the Mini Nutritional Assessment–short form (MNA-SF), serum prealbumin, and anthropometric measurements. The prevalence of CF was 28.72%. Malnourished status by MNA-SF category (aOR = 2.81, 95%CI: 1.18–6.67) and MNA-SF score (aOR = 0.84, 95%CI = 0.74–0.94) were independently associated with CF. However, there was no correlation between CF and malnutrition assessed by serum prealbumin level and anthropometric measurements. Other independent risk factors of CF were advanced age (aOR = 1.06, 95%CI: 1.02–1.11) and educational level below high school (aOR = 6.77, 95%CI: 1.99–23.01). Malnutrition was associated with CF among Thai elderly. High-risk groups who are old and poorly educated should receive early screening and nutritional interventions.

Health literacy is an essential social determinant of health and has been associated with positive health outcomes. While many sources of health information are widely available, people of different ages also have diverse social contexts and preferences for health information sources. This study aimed to identify health information sources and socio-demographics influencing health literacy in different social contexts across age groups: 15–29 years (young), 30–59 years (middle-age), and ≥60 years (elderly). We obtained secondary data from a cross-sectional study in northern Thailand from March to August 2019. Multivariate linear regression with age group subgroup analysis was used to determine factors associated with general health literacy by the Thai version of the health literacy questionnaire. Receiving health information from physicians was significantly associated with higher general health literacy in young (β 6.45, 95%CI 0.44–12.45; p = 0.035) and elderly (β 5.18, 95%CI 1.84–8.52; p = 0.002) groups, while receiving health information from health volunteers was significantly associated with a higher general health literacy in the middle-aged (β 2.89, 95%CI 0.38–5.39; p = 0.024) group. Although younger participants showed more frequent access to health information via the media than the other age groups, there were no media sources significantly linked with their general health literacy. Health information from physicians is a vital source of health information.

This study aimed to determine the prevalence and associated factors of frailty among Thai older persons. A cross-sectional study was conducted with a representative sample of 1806 older persons aged 60 years or older. Frailty was assessed by Fried’s frailty phenotypes, which consists of five criteria, namely, unintended weight loss, exhaustion, slow walking, weak handgrip and decreased physical activity. Older people who met 3 in 5, 1–2 in 5, and none of the criteria were considered frail, pre-frail and non-frail respectively. The prevalence was calculated and multinomial logistic regression was performed. Prevalence rates of frailty, pre-frailty and non-frailty were 13.9% (95% CI 9.9 to 18.8), 50.9% (95% CI 47.5 to 54.1) and 35.1% (95% CI 31.5 to 39.9), respectively. Increasing age, lower education, having no spouse, poorer health perception, increasing number of comorbidities, osteoarthritis and smaller mid-arm circumference increased the risk of frailty (p < 0.001). The prevalence of geriatric frailty syndrome in this study was much higher than that of developed countries but was lower than that of less developed countries. Factors associated with frailty reflect common characteristics of disadvantaged older persons in Thailand.