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Background Prospective cohort studies suggest that frailty is associated with an increased risk of incident cardiovascular disease (CVD) morbidity and mortality, but their mechanistic and developmental relations are not fully understood. We investigated whether frailty predicted an increased risk of incident nonfatal and fatal CVD among community-dwelling older adults. Methods A population cohort of 5015 participants aged 55 years and above free of CVD at baseline was followed for up to 10 years. Pre-frailty and frailty were defined as the presence of 1–2 and 3–5 modified Fried criteria (unintentional weight loss, weakness, slow gait speed, exhaustion, and low physical activity), incident CVD events as newly diagnosed registered cases of myocardial infarction (MI), stroke, and CVD-related mortality (ICD 9: 390 to 459 or ICD-10: I00 to I99). Covariate measures included traditional cardio-metabolic and vascular risk factors, medication therapies, Geriatric Depression Scale (GDS), Mini-Mental State Exam (MMSE), and blood biomarkers (haemoglobin, albumin, white blood cell counts and creatinine). Results Pre-frailty and frailty were significantly associated with elevated HR = 1.26 (95%CI: 1.02–1.56) and HR = 1.54 (95%CI:1.00–2.35) of overall CVD, adjusted for cardio-metabolic and vascular risk factors and medication therapies, but not after adjustment for GDS depression and MMSE cognitive impairment. The HR of association between frailty status and both CVD mortality and overall mortality, however, remained significantly elevated after full adjustment for depression, cognitive and blood biomarkers. Conclusion Frailty was associated with increased risk of CVD morbidity and especially mortality, mediated in parts by traditional cardio-metabolic and vascular risk factors, and co-morbid depression and associated cognitive impairment and chronic inflammation. Given that pre-frailty and frailty are reversible by multi-domain lifestyle and health interventions, there is potential benefits in reducing cardiovascular diseases burden and mortality from interventions targeting pre-frailty and early frailty population.

BackgroundSarcopenia and obesity are reportedly associated with risk of cognitive decline, and sarcopenic obesity (SO) heightens the risk, but the evidence is sparse and inconclusive. This study aimed to examine the association between SO and cognitive impairment.MethodsA total of 542 community-dwelling adults aged between 21 and 90 years were recruited. All participants were assessed for body composition (dual X-ray absorptiometry), handgrip strength (HGS), gait speed (GS), and cognitive function (Repeatable Battery for the Assessment of Neuropsychological Status). Sarcopenia was defined by the presence of low appendicular lean mass index (ALMI) and low HGS or low GS according to the 2019 Asian Working Group for Sarcopenia criteria, and obesity was defined based on the upper two quintiles of fat mass index (FMI).ResultsSarcopenia alone or in combination with obesity were not significantly associated with cognitive impairment after controlling for confounding variables. Obesity on its own was significantly associated with greater odds of impaired attention (OR: 2.05, 95%CI 1.12-3.82). Low ALMI was not associated, but low HGS, slow GS, and high FMI were individually associated with cognitive impairment: low HGS and immediate memory (OR: 1.91, 95% CI 1.04-3.49); low GS and immediate memory (OR: 2.17, 95% CI 1.26-3.72); high FMI and attention (OR: 2.06, 95% CI 1.22-3.51). Co-occurring high FMI with either low HGS or slow GS exacerbated the observed odds of global and domain-specific (attention, visuospatial) cognitive impairment.ConclusionsLean mass is not relevant, whereas muscle strength and physical performance or adiposity are relevant in defining sarcopenia or sarcopenic obesity in terms of their cognitive impacts.

We describe a network-based method to obtain a subset of representative variables from clinical data of subjects of the second Singapore Longitudinal Aging Study (SLAS-2), while preserving to a good extent the predictive performance of the full set with regards to a multi-faceted index of successful aging, SAGE. To examine differences in predictive performance of high-degree nodes ("hubs") and high-centrality ones ("cores"), we implement four subsetting strategies (two degree-based, two centrality-based) and obtain four surrogate sets of variables, which we use as input features for machine learning models to predict the SAGE index of subjects. All four models have variables belonging to the physical, cardiovascular, cognitive and immunological domains among their fifteen most important predictors. A fifth domain (leisure-time activities, LTA) is also present in some form. From a comparison of the surrogate sets' size and predictive performance, a centrality-based approach (selection of the most central variable-nodes within each cluster) yielded the smallest-sized surrogate set, while having high prediction accuracy (measured by its model's area-under-curve, AUC) in comparison to its analogous degree-based strategy (selection of the highest-degree nodes per cluster). Inclusion of the next most-central variables yielded negligible changes in predictive performance while more than doubling the surrogate set size. The centrality-based approach thus yields a surrogate set which offers a good balance between number of variables and prediction performance, and can act as a representative subset of the SLAS-2 clinical dataset.

UnlabelledCognitive decline in aging is a pressing issue associated with significant healthcare costs and deterioration in quality of life. Previously, we reported the successful use of a novel brain-computer interface (BCI) training system in improving symptoms of attention deficit hyperactivity disorder. Here, we examine the feasibility of the BCI system with a new game that incorporates memory training in improving memory and attention in a pilot sample of healthy elderly. This study investigates the safety, usability and acceptability of our BCI system to elderly, and obtains an efficacy estimate to warrant a phase III trial. Thirty-one healthy elderly were randomized into intervention (n = 15) and waitlist control arms (n = 16). Intervention consisted of an 8-week training comprising 24 half-hour sessions. A usability and acceptability questionnaire was administered at the end of training. Safety was investigated by querying users about adverse events after every session. Efficacy of the system was measured by the change of total score from the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) before and after training. Feedback on the usability and acceptability questionnaire was positive. No adverse events were reported for all participants across all sessions. Though the median difference in the RBANS change scores between arms was not statistically significant, an effect size of 0.6SD was obtained, which reflects potential clinical utility according to Simon's randomized phase II trial design. Pooled data from both arms also showed that the median change in total scores pre and post-training was statistically significant (Mdn = 4.0; pTrial registrationClinicalTrials.gov NCT01661894.

ObjectivesThis study establishes age- and sex-specific reference values for fat mass index (FMI), lean mass index (LMI), appendicular LMI (aLMI), and body fat distribution indices including Android/Gynoid % fat ratio and Trunk/Limb % fat ratio in multi-ethnic Singaporean adults.MethodsA population-based cross-sectional study using dual-energy X-ray absorptiometry (Hologic Discovery Wi) was carried out to measure whole body and regional fat and lean mass in community-dwelling adults. A total of 537 adults (57.5% women), aged from 21 to 90 years, were recruited from the large north-eastern residential town of Yishun. Age- and sex-specific percentile reference values were generated for FMI, LMI, aLMI, Android/Gynoid % fat ratio and Trunk/Limb % fat ratio using the Lambda-Mu-Sigma method. The relationship between the parameters and age were assessed through the Pearson's correlation coefficient.ResultsAll parameters demonstrated significant correlation with age (p < 0.05) for both men and women, except for LMI in women, with the strength of r ranging from 0.12 (weak correlation) to 0.54 (strong correlation). LMI (r = -0.45) and appendicular LMI (r = -0.54) were negatively associated with age in men while none (r = -0.06) to weak correlation (r = -0.14) were shown in women for the same parameters respectively. The Android/Gynoid % fat ratio and Trunk/Limb % fat ratio were positively related to age for both men (r = 0.37 & 0.43, p < 0.001) and women (r = 0.52 & 0.48, p < 0.001).ConclusionWe have established DXA-based body composition reference data for the Singapore adult population. These reference data will be particularly useful in geriatric, obesity and oncology clinics, enabling the prescription of appropriate therapy to individuals at risk of morbidity from unfavorable body composition phenotypes. It also adds on to the limited reference database on Southeast Asian body composition.

The relationship between body mass index (BMI) with mortality risk, in particular the BMI category associated with the lowest all-cause and CVD-and-stroke mortality and the BMI threshold for defining overweight or obesity in older persons is controversial. This study investigated the age-dependent associations of BMI categories with all-cause and cardiovascular disease (CVD) and stroke mortality.Prospective cohort study (Singapore Longitudinal Ageing Studies) of older adults aged 55 and above, followed up from 2003 to 2011. Participants were 2605 Chinese with baseline BMI and other variables. Outcome Measurement: Mortality hazard ratios (HR) for all-cause and CVD and stroke mortality.Overall, BMI showed a U-shaped relationship with all-cause and CVD and stroke mortality, being lowest at Normal Weight-II category (BMI 23.0-24.9 kg/m2). Most evidently among the middle-aged (55-64 years), all-cause mortality risks relative to Normal Weight-II were elevated for underweight (30.0; HR = 4.05,p = 0.0423). Among the old (≥65 years), however, Overweight and Obese categories were not significantly associated with increased all-cause mortality (HR from 0.98 to 1.29), but Overweight-Obese was associated with increased CVD and stroke mortality (HR = 10.0, p = 0.0086).BMI showed a U-shaped relationship with mortality. Among older persons aged 65 and above, the overweight-or-obese category of BMI was not associated with excess all-cause mortality.

BACKGROUND:Changes in criteria and differences in populations studied and methodology have produced a wide range of prevalence estimates for mild cognitive impairment (MCI). METHODS:Uniform criteria were applied to harmonized data from 11 studies from USA, Europe, Asia and Australia, and MCI prevalence estimates determined using three separate definitions of cognitive impairment. RESULTS:The published range of MCI prevalence estimates was 5.0%-36.7%. This was reduced with all cognitive impairment definitions: performance in the bottom 6.681% (3.2%-10.8%); Clinical Dementia Rating of 0.5 (1.8%-14.9%); Mini-Mental State Examination score of 24-27 (2.1%-20.7%). Prevalences using the first definition were 5.9% overall, and increased with age (P < .001) but were unaffected by sex or the main races/ethnicities investigated (Whites and Chinese). Not completing high school increased the likelihood of MCI (P ≤ .01). CONCLUSION:Applying uniform criteria to harmonized data greatly reduced the variation in MCI prevalence internationally.

BACKGROUND: Research on the effects of dietary nutrients on respiratory health in human populations have not investigated curcumin, a potent anti-oxidant and anti-inflammatory compound present principally in turmeric used in large amounts in Asian curry meals. OBJECTIVES: To examine the association of curry intake with pulmonary function among smokers and non-smokers. DESIGN: The frequency of curry intake, respiratory risk factors and spirometry were measured in a population-based study of 2,478 Chinese older adults aged 55 and above in the Singapore Longitudinal Ageing Studies. RESULTS: Curry intake (at least once monthly) was significantly associated with better FEV(1) (b = 0.045±0.018, p = 0.011) and FEV(1)/FVC (b = 1.14±0.52, p = 0.029) in multivariate analyses that controlled simultaneously for gender, age, height, height-squared, smoking, occupational exposure and asthma/COPD history and other dietary or supplementary intakes. Increasing levels of curry intake ('never or rarely', 'occasional', 'often', 'very often') were associated with higher mean adjusted FEV(1) (p for linear trend = 0.001) and FEV(1)/FVC% (p for linear trend = 0.048). Significant effect modifications were observed for FEV(1) (curry* smoking interaction, p = 0.028) and FEV(1)/FVC% (curry*smoking interaction, p = 0.05). There were significantly larger differences in FEV(1) and FEV(1)/FVC% between curry intake and non-curry intake especially among current and past smokers. The mean adjusted FEV(1) associated with curry intake was 9.2% higher among current smokers, 10.3% higher among past smokers, and 1.5% higher among non-smokers. CONCLUSION: The possible role of curcumins in protecting the pulmonary function of smokers should be investigated in further clinical studies.