Comparison of mini nutritional assessment tool and geriatric nutrition risk index in predicting 12-year mortality among community-dwelling older persons.

BACKGROUND: Malnutrition is a common and dangerous condition in older adults, which has been associated with an increased risk of mortality. OBJECTIVES: This study aims to evaluate and compare the abilities of Mini Nutritional Assessment short form (MNA-SF), MNA full form (MNA-FF), and geriatric nutritional risk index (GNRI) to predict all-cause and expanded cardiovascular disease (CVD)-related mortality in community-dwelling older adults. METHODS: This research is an observational cohort study conducted in a community-setting, with a 12-year follow-up involving 1,001 community-living older adults aged ≥65 years who are enrolled in 2009 and followed up until 2021. Nutritional status assessment was carried out in 2009 using MNA-SF, MNA-FF, and GNRI. Multivariate Cox proportional hazards regression was applied to determine adjusted hazard ratios of mortality with 95% confidence intervals. RESULTS: A total of 368 deaths (36.76%) and 122 expanded CVD-related deaths (12.19%) were observed after a median follow-up of 12 years. Compared with normal nutritional status, poor nutritional status assessed by the MNA-SF, MNA-FF, and GNRI was found to be associated with an increased all-cause mortality in older persons. MNA-SF and MNA-FF, but not GNRI, were associated with expanded CVD-related mortality. The MNA-FF showed better discriminatory accuracy for all-cause and expanded CVD-related mortality (C-statistics = 0.77, 95% CI = 0.63-0.79; 0.79, 0.70-0.83) than MNA-SF (0.76, 0.73-0.79; 0.76, 0.72-0.81) and GNRI (0.75, 0.73-0.79; 0.76, 0.72-0.80). CONCLUSIONS: Our findings indicate that MNA-SF, MNA-FF, and GNRI were all independent predictors of all-cause mortality. In particular, the MNA-FF may be the best nutritional assessment tool for predicting all-cause and CVD-related mortality among older persons residing in community, compared with MNA-SF and GNRI.

Association of echocardiographic parameters with all-cause and cardiovascular mortality in patients with type 2 diabetes.

BACKGROUND: This study aimed to evaluate associations between echocardiography markers and mortality in patients with type 2 diabetes mellitus (T2DM). METHODS: Diabetes Care Management Program database of a medical center was used, including 5612 patients with T2DM aged 30 years and older and who underwent echocardiography assessment between 2001 and 2021. Cox proportional hazard regression models were used to evaluate associations of echocardiography abnormalities with all-cause and expanded cardiovascular disease (CVD) mortality. RESULTS: During a mean follow-up of 5.8 years, 1273 patients died. Hazard ratios (95% confidence intervals) of all-cause mortality for each standard deviation increase were presented for the cardiac systolic function indicator of left ventricular ejection fraction (0.77, 0.73-0.81), cardiac structural parameters of left ventricular mass index (1.25, 1.19-1.31) and left atrial volume index (1.31, 1.25-1.37), and cardiac diastolic function of E/A ratio (1.10, 1.07-1.13), E/e' ratio (1.37, 1.30-1.45), and TR velocity (1.25, 1.18-1.32); meanwhile, the values of expanded CVD mortality included left ventricular ejection fraction (0.67, 0.62-0.72), left ventricular mass index (1.35, 1.25-1.45), left atrial volume index (1.40, 1.31-1.50), E/A ratio (1.12, 1.08-1.16), E/e' ratio (1.57, 1.46-1.69), and TR velocity (1.29, 1.19-1.39), respectively. CONCLUSIONS: Cardiac systolic function indicator of left ventricular ejection fraction, cardiac structural parameters of left ventricular mass index and left atrial volume index, and cardiac diastolic function indicators of E/A ratio, E/e' ratio, and TR velocity are associated with all-cause and expanded CVD mortality in patients with T2DM.

Ohwia caudata aqueous extract attenuates senescence in aging adipose-derived mesenchymal stem cells.

Stem cells exhibit pluripotency and self-renewal abilities. Adipose-derived mesenchymal stem cells can potentially be used to reconstruct various tissues. They possess significant versatility and alleviate various aging-related diseases. Unfortunately, aging leads to senescence, apoptosis, and a decline in regenerative capacity in adipose-derived mesenchymal stem cells. These changes necessitate a strategy to mitigate the effects of aging on stem cells. Ohwia caudata (O. caudata) has therapeutic effects against several illnesses. However, studies on whether O. caudata has therapeutic effects against aging are lacking. In this study, we aimed to identify potential therapeutic anti-aging effects in the crude aqueous extract of O. caudata on adipose-derived mesenchymal stem cells. Using 0.1 µM doxorubicin, we induced aging in human adipose-derived mesenchymal stem cells (hADMSCs) and evaluated whether various concentrations of O. caudata aqueous extract exhibit anti-aging effects on them. The O. caudata extract exhibited significant antioxidant effects on hADMSCs without any toxicity. Furthermore, after treatment with the O. caudata aqueous extract, the levels of mitochondrial superoxide, DNA double-strand breaks, and telomere shortening were reduced in the hADMSCs subjected to doxorubicin-induced aging. The extract also suppressed doxorubicin-induced aging by upregulating klotho and downregulating p21 in hADMSCs. These findings indicated that the O. caudata extract exhibited anti-aging properties that modulated hADMSC homeostasis. Therefore, it could be a potential candidate for restoring the self-renewal ability and multipotency of aging hADMSCs.

Association of carotid atherosclerosis markers with all-cause and cardiovascular disease-specific mortality in persons with type 2 diabetes: a causal mediation analysis with glucose variation.

AIMS: Glucose variation (GV) is independently associated with mortality in patients with diabetes. However, no study has examined the effects of carotid atherosclerosis markers on mortality after considering GV. Our purpose is to investigate the independent effects of carotid atherosclerosis markers in persons with type 2 diabetes (T2DM) after considering GV and the mediation effects of carotid atherosclerosis markers on associations between GV with cardiovascular disease (CVD) mortality. MATERIALS AND METHODS: This study is a retrospective cohort study including 3628 persons with T2DM who were admitted to a medical center between January 01, 2001 and October 31, 2021. GV was defined as a coefficient of variation (CV) of repeated measurements within a year before the index date (date of first IMT assessment). Carotid atherosclerosis markers included intima-media thickness (IMT), plaque, and stenosis. The outcomes consisted of all-cause and expanded cardiovascular disease (CVD) mortality. Cox proportional hazards models were applied. RESULTS: Among the participants, 286 (7.9%) had IMT ≥ 2 mm, 2834 (78.1%) had carotid plaque, and 464 (12.8%) had carotid stenosis ≥ 50%. When GV was considered, IMT, carotid plaque, and carotid stenosis were significant factors for all-cause mortality (except IMT considering HbA1c-CV) and expanded CVD mortality. IMT was a significant mediator in the associations of fasting plasma glucose (FPG)-CV with all-cause and expanded CVD mortality (2 and 3.19%, respectively), and carotid stenosis was a significant mediator in the association between FPG-CV and expanded CVD mortality (3.83%). CONCLUSIONS: Our statistical evaluations show suggests that carotid atherosclerosis markers are important predictors of CVD mortality in persons with T2DM if GV is considered. In addition, IMT and carotid stenosis were significant mediators in the association between GV and mortality.

Mitochondrial DNA haplogroup D and brain microstructure regulate cognitive function among community-dwelling older adults.

INTRODUCTION: Maintaining physical and cognitive function among older adults is important. These functional states are affected by mitochondria through various mechanisms, such as cellular energy production and oxidative stress control. Owing to its involvement in the relations among the brain, cognition, and physical function, mitochondrial function may be affected by mitochondrial DNA (mtDNA) haplogroups. This study explored the effect of mtDNA haplogroups and brain microstructure on physical and cognitive functions among community-dwelling older adults. METHODS: This study was a community-based cross-sectional research. A total of 128 subjects aged 65 years and older without dementia completed several assessments, including mtDNA sequencing, physical and cognitive function tests, and magnetic resonance imaging (MRI) scans. Cognitive function and impairment were assessed by the MMSE and AD8 questionnaires. mtDNA haplogroups were classified by HaploGrep 2 software, and white matter microstructural integrity was scanned by 3T MRI. RESULTS: The mean age of the subjects was 77.3 years. After the adjustment for covariates, the mtDNA haplogroup D carriers showed significantly lower mini-mental state examination (MMSE) scores than other carriers (p = 0.047). Further considering the brain microstructure, the mtDNA haplogroup D (p = 0.002) and white matter volumes in the left precuneus corrected for total intracranial volumes (p = 0.014) were found to be independently influencing factors of the MMSE scores. CONCLUSIONS: The mtDNA haplogroup D and white matter microstructure regulated the cognitive function among community-dwelling older adults. The findings provide new insights into the research gap. Scientists must further venture into this field.

A non-invasive mouse model that recapitulates disuse-induced muscle atrophy in immobilized patients.

Disuse muscle atrophy occurs consequent to prolonged limb immobility or bed rest, which represents an unmet medical need. As existing animal models of limb immobilization often cause skin erosion, edema, and other untoward effects, we here report an alternative method via thermoplastic immobilization of hindlimbs in mice. While significant decreases in the weight and fiber size were noted after 7 days of immobilization, no apparent skin erosion or edema was found. To shed light onto the molecular mechanism underlying this muscle wasting, we performed the next-generation sequencing analysis of gastrocnemius muscles from immobilized versus non-mobilized legs. Among a total of 55,487 genes analyzed, 787 genes were differentially expressed (> fourfold; 454 and 333 genes up- and down-regulated, respectively), which included genes associated with muscle tissue development, muscle system process, protein digestion and absorption, and inflammation-related signaling. From a clinical perspective, this model may help understand the molecular/cellular mechanism that drives muscle disuse and identify therapeutic strategies for this debilitating disease.

Association of time-varying sleep duration and cognitive function with mortality in the elderly: a 12-year community-based cohort study.

BACKGROUND: Sleeping problems and cognitive impairment are common in elders. Baseline sleep duration and cognitive status are predictors of mortality. But few studies have explored whether longitudinal changes in sleep duration and cognitive function are related to mortality in older adults. The present study investigated the time-varying relationships of sleep duration and cognitive function with subsequent mortality among community-dwelling elders by using 12 years of repeated-measure data. METHODS: Taichung Community Health Study for Elders (TCHS-E) is a retrospective, population-based cohort that started in 2009 (wave 1) with a total of 912 elders aged 65 years or above. Follow up was conducted in 2010 (wave 2), 2018 (wave 3), and 2020 (wave 4). Sleep duration and Mini-Mental State Examination (MMSE) forms were executed at baseline and three visits during follow-up. Time-varying Cox proportional hazards regression estimated adjusted hazard ratios (HRs) of mortality with 95% confidence intervals (CIs). RESULTS: During about 12 years (9,396 person-years) follow-up, 329 deaths from all causes were documented, including 102 deaths due to expanded cardiovascular disease (CVD). In the multivariable-adjusted, time-varying Cox proportional hazard model, the adjusted HR values of all-cause mortality were 1.47 (1.02-2.12) for sleep duration > 9 h/day (vs. 7 h/day) and 1.81 (1.26-2.59) for MMSE < 27 (vs. 30). The adjusted HR values of the expanded CVD mortality were 2.91 (1.24-6.83) for MMSE of 29; 2.69 (1.20-6.05) for MMSE of 27-28; and 4.32 (95% CI: 1.92-9.74) for MMSE < 27. The dose-dependent relationship was significant (p < 0.001). The combinations of sleep duration longer than 9 h/day and MMSE < 27 were linked with the highest risks for expanded CVD and all-cause mortality. CONCLUSIONS: Long sleep duration and low cognitive function were jointly and independently linked with higher risk of mortality in elders residing in community.

Using machine learning algorithm to analyse the hypothyroidism complications caused by radiotherapy in patients with head and neck cancer.

Machine learning algorithms were used to analyze the odds and predictors of complications of thyroid damage after radiation therapy in patients with head and neck cancer. This study used decision tree (DT), random forest (RF), and support vector machine (SVM) algorithms to evaluate predictors for the data of 137 head and neck cancer patients. Candidate factors included gender, age, thyroid volume, minimum dose, average dose, maximum dose, number of treatments, and relative volume of the organ receiving X dose (X: 10, 20, 30, 40, 50, 60 Gy). The algorithm was optimized according to these factors and tenfold cross-validation to analyze the state of thyroid damage and select the predictors of thyroid dysfunction. The importance of the predictors identified by the three machine learning algorithms was ranked: the top five predictors were age, thyroid volume, average dose, V50 and V60. Of these, age and volume were negatively correlated with thyroid damage, indicating that the greater the age and thyroid volume, the lower the risk of thyroid damage; the average dose, V50 and V60 were positively correlated with thyroid damage, indicating that the larger the average dose, V50 and V60, the higher the risk of thyroid damage. The RF algorithm was most accurate in predicting the probability of thyroid damage among the three algorithms optimized using the above factors. The Area under the receiver operating characteristic curve (AUC) was 0.827 and the accuracy (ACC) was 0.824. This study found that five predictors (age, thyroid volume, mean dose, V50 and V60) are important factors affecting the chance that patients with head and neck cancer who received radiation therapy will develop hypothyroidism. Using these factors as the prediction basis of the algorithm and using RF to predict the occurrence of hypothyroidism had the highest ACC, which was 82.4%. This algorithm is quite helpful in predicting the probability of radiotherapy complications. It also provides references for assisting medical decision-making in the future.

Application of artificial intelligence in endoscopic image analysis for the diagnosis of a gastric cancer pathogen-Helicobacter pylori infection.

Helicobacter pylori (H. pylori) infection is the principal cause of chronic gastritis, gastric ulcers, duodenal ulcers, and gastric cancer. In clinical practice, diagnosis of H. pylori infection by a gastroenterologists' impression of endoscopic images is inaccurate and cannot be used for the management of gastrointestinal diseases. The aim of this study was to develop an artificial intelligence classification system for the diagnosis of H. pylori infection by pre-processing endoscopic images and machine learning methods. Endoscopic images of the gastric body and antrum from 302 patients receiving endoscopy with confirmation of H. pylori status by a rapid urease test at An Nan Hospital were obtained for the derivation and validation of an artificial intelligence classification system. The H. pylori status was interpreted as positive or negative by Convolutional Neural Network (CNN) and Concurrent Spatial and Channel Squeeze and Excitation (scSE) network, combined with different classification models for deep learning of gastric images. The comprehensive assessment for H. pylori status by scSE-CatBoost classification models for both body and antrum images from same patients achieved an accuracy of 0.90, sensitivity of 1.00, specificity of 0.81, positive predictive value of 0.82, negative predicted value of 1.00, and area under the curve of 0.88. The data suggest that an artificial intelligence classification model using scSE-CatBoost deep learning for gastric endoscopic images can distinguish H. pylori status with good performance and is useful for the survey or diagnosis of H. pylori infection in clinical practice.

Three-year trajectories of sleep duration and mortality in patients with type 2 diabetes-a hospital-based retrospective cohort study.

OBJECTIVES: Most studies have shown that a single item of self-reported sleep duration is related to mortality risk. However, the long-term effect of sleep duration on mortality remains unclear in patients with diabetes. This study aimed to examine the associations of 3-year trajectory patterns of sleep duration with all-cause and expanded cardiovascular disease mortality in patients with type 2 diabetes. METHODS: Patients with type 2 diabetes and self-reported sleep duration during a 3-year interval were included. Expanded cardiovascular disease was defined as death due to cardiovascular disease, diabetes, and kidney diseases. Cox's proportional hazards models were employed to examine the associations between sleep duration patterns and mortality after controlling for sociodemographic factors, lifestyle behaviors, diabetes-related variables, diabetic complications, and medication use. RESULTS: A total of 7591 patients were included for analysis, and 995 deaths (13.11%) and 424 expanded cardiovascular disease deaths (5.59%) were observed during a mean follow-up of 8.51 years. Five trajectory patterns of sleep duration were identified: cluster 1: "constant 7- to 8-hour group" (50.03%); cluster 2: "constant low group" (19.68%); cluster 3: "high with decreasing trend group" (3.08%); cluster 4: "low with fluctuation group" (1.28%); and cluster 5: "constant high group" (25.93%). Compared with cluster 1, clusters 3 and 4 were associated with increased risks of all-cause mortality (1.41, 1.08-1.84; 1.44, 1.01-2.05), and cluster 5 was associated with high risks of all-cause and expanded cardiovascular disease mortality (1.26, 1.08-1.46; 1.42, 1.12-1.79). CONCLUSIONS: Sleep duration trajectories with constant high or unstable patterns may be associated with higher mortality.

Association of body indices and risk of mortality in patients with type 2 diabetes.

INTRODUCTION: A body shape index (ABSI) is independently associated with mortality in general population, but studies on the predictability of ABSI in the risk of mortality in patients with type 2 diabetes (T2D) are limited. We aimed to examine the independent and joint association of ABSI, body mass index (BMI), waist circumference (WC), waist-to-hip ratio (WHR), waist-to-height ratio (WHtR), and body roundness index (BRI) with mortality in patients with T2D. RESEARCH DESIGN AND METHODS: The study included 11 872 patients (46.5% women) aged 30 years and older and who took part in diabetes care management program of a medical center in Taiwan. Body indices were evaluated by anthropometric measurements at baseline between 2001 and 2016, and their death status was followed up through 2021. Multivariate Cox regression models were used to assess the effect of body indices on mortality. RESULTS: During a mean follow-up of 10.2 years, 560 cardiovascular disease (CVD) deaths and 3043 deaths were recorded. For ABSI, WC, WHR, WHtR and BRI, all-cause mortality rates were statistically significantly greater in Q4 versus Q2. For BMI and WHtR, all-cause mortality rates were also statistically significantly greater in Q1 versus Q2. The combination of BMI and ABSI exhibited a superiority in identifying risks of all-cause mortality and CVD mortality (HRs: 1.45 and 1.37, both p<0.01). CONCLUSIONS: Combined use of ABSI and BMI can contribute to the significant explanation of the variation in death risk in comparison with the independent use of BMI or other indices.

Sentiment analysis of Indonesian datasets based on a hybrid deep-learning strategy.

Various attempts have been conducted to improve the performance of text-based sentiment analysis. These significant attempts have focused on text representation and model classifiers. This paper introduced a hybrid model based on the text representation and the classifier models, to address sentiment classification with various topics. The combination of BERT and a distilled version of BERT (DistilBERT) was selected in the representative vectors of the input sentences, while the combination of long short-term memory and temporal convolutional networks was taken to enhance the proposed model in understanding the semantics and context of each word. The experiment results showed that the proposed model outperformed various counterpart schemes in considered metrics. The reliability of the proposed model was confirmed in a mixed dataset containing nine topics.

Trends in energy and macronutrient intake among Taiwanese older adults in 1999-2000, 2005-2008 and 2013-2016 periods.

BACKGROUND: This study aimed to explore trends, in 3 periods, in the intake of energy and macronutrients among Taiwanese older adults. METHODS: Study subjects were those aged ≥65 years in the Nutrition and Health Survey in Taiwan 1999-2000 as well as the surveys in 2005-2008 and 2013-2016. Twenty-four-hour dietary recall data were obtained. This study used the 3 nutrition survey datasets for 1999-2000, 2005-2008, and 2013-2016, including data on the questionnaire, physical examination, and dietary intakes. Each nutrition survey involved the face-to-face household interview, and individual's dietary intake of carbohydrate, fat, and protein (% of energy) was estimated. Subsequently, intake statuses of the three macronutrients were classified into below, meeting, and above intake categories. RESULTS: In the 2013-2016 survey, approximately 40% of the older adults had a low intake of energy. The prevalence of older adults with a meeting intake of carbohydrate, fat, and protein have increased from the 1999-2000 to 2013-2016 periods. The prevalence of people having a low intake of carbohydrate declined from the 1999-2000 period to the 2013-2016 period. The prevalence of high fat intake in 2013-2016 was approximately 5% higher than that in 1999-2000. In the 2013-2016 period, the prevalence of low intake of carbohydrate, fat, and protein were 25.9, 24.5, and 4.9%, respectively; moreover, the prevalence of high intake of the aforementioned macronutrients were 38.7, 36.2, and 17.6%, respectively. CONCLUSIONS: Our study provides important evidence on the dietary patterns, as well as their changes over time among Taiwanese older adults. Such information would be useful for health policy makers about the burden of unbalanced diet and for nutrition educators on planning nutrition promotion interventions about well-balanced dietary for the older persons.

Plasma riboflavin fluorescence as a diagnostic marker of mesenteric ischemia-reperfusion injury in rats.

Due to the delayed and vague symptoms, it is difficult to early diagnose mesenteric ischemia injuries in the dynamics of acute illness, leading to a 60-80 % mortality rate. Here, we found plasma fluorescence spectra can rapidly assess the severity of mesenteric ischemia injury in animal models. Ischemia-reperfusion damage of the intestine leads to multiple times increase in NADH, flavins, and porphyrin auto-fluorescence of blood. The fluorescence intensity ratio between blue-fluorophores and flavins can reflect the occurrence of shock. Using liquid chromatography and mass spectroscopy, we confirm that riboflavin is primarily responsible for the increased flavin fluorescence. Since humans absorb riboflavin from the intestine, its increase in plasma may indicate intestinal mucosa injury. Our work suggests a self-calibrated and reagent-free approach to identifying the emergence of fatal mesenteric ischemia in emergency departments or intensive care units.

Association of high-sensitivity C-reactive protein and diabetic nephropathy in patients with type 2 diabetes: a Mendelian randomization study.

INTRODUCTION: Observational studies support the relationship between C-reactive protein (CRP) level and diabetic nephropathy (DN) in patients with diabetes. The research question regarding whether the relationship between serum high-sensitivity C-reactive protein (hsCRP) level and DN is causal lacks experimental evidence. Therefore, this study aimed to evaluate the causality between hsCRP and DN based on Mendelian randomization (MR) analysis. RESEARCH DESIGN AND METHODS: A total of 2332 participants with type 2 diabetes from the Taiwan Biobank database was analyzed. Genetic risk scores (GRSs), which comprise four validated CRP loci as two instrumental variables, were calculated as unweighted and weighted scores to evaluate the causal relationship of hsCRP with DN risk. The two-stage regression model was used to estimate OR and 95% CI. RESULTS: The analyses of the observational study showed that the hsCRP level was significantly associated with DN after multivariate adjustment (adjusted OR 1.15; 95% CI 1.01 to 1.32). Unweighted/weighted GRSs for log-transformed hsCRP satisfied MR assumptions 1 and 3, respectively; that is, a significant association with hsCRP was observed but that with DN was absent (adjusted OR 1.00, 95% CI 0.92 to 1.09; 1.00, 0.72 to 1.39, respectively). The MR analyses demonstrated that a 1-unit increase in the log-transformed genetically predicted hsCRP by unweighted and weighted GRSs was associated with DN, demonstrating ORs of 1.80 (95% CI 1.51 to 2.14) and 1.67 (95% CI 1.40 to 1.98), respectively. CONCLUSIONS: The current study provided experimental evidence that hsCRP level was causally related to DN. These findings suggest that the elevated hsCRP may be a causal risk factor for DN in patients with type 2 diabetes.

Risk prediction of nephropathy by integrating clinical and genetic information among adult patients with type 2 diabetes.

AIMS: Diabetic nephropathy (DN) is a major healthcare challenge. We developed and internally and externally validated a risk prediction model of DN by integrating clinical factors and SNPs from genes of multiple CKD-related pathways in the Han Chinese population. MATERIALS AND METHODS: A total of 1526 patients with type 2 diabetes were randomly allocated into derivation (n = 1019) or validation (n = 507) sets. External validation was performed with 3899 participants from the Taiwan Biobank. We selected 66 SNPs identified from literature review for building our weighted genetic risk score (wGRS). The steps for prediction model development integrating clinical and genetic information were based on the Framingham Heart Study. RESULTS: The AUROC (95% CI) for this DN prediction model with combined clinical factors and wGRS was 0.81 (0.78, 0.84) in the derivation set. Furthermore, by directly using the information of these 66 SNPs, our final prediction model had AUROC values of 0.85 (0.82, 0.87), 0.89 (0.86, 0.91), and 0.77 (0.74, 0.80) in the derivation, internal validation, and external validation sets, respectively. Under the combined model, the results with a cutoff point of 30% showed 70.91% sensitivity, 67.84% specificity, 51.54% positive predictive value, and 82.86% negative predictive value. CONCLUSIONS: We developed and internally and externally validated a model with clinical factors and SNPs from genes of multiple CKD-related pathways to predict DN in Taiwan. This model can be used in clinical risk management practice as a screening tool to identify persons who are genetically predisposed to DN for early intervention and prevention.

Obesity marker trajectories and cognitive impairment in older adults: a 10-year follow-up in Taichung community health study for elders.

BACKGROUND: Obesity and cognitive impairment prevalence increases as age increases. Recent growing evidence finds links between obesity and cognitive impairment in older adults. However, the association between the two is controversial. This study aims to identify obesity marker trajectory patterns, and to assess whether these patterns are associated with cognitive impairment and cognitive decline during a 10-year follow-up period among community-dwelling older adults. METHODS: A total of 626 older adults aged 65 and older were involved in the study, with at least two repeated measurements at baseline, one-year or 10-year follow-up. Cognitive function was measured through the Mini Mental State Examination. Obesity markers included body mass index, waist circumference, waist-to-hip (WHR), fat mass (FM), and abdominal fat (AF) measured by dual-energy X-ray absorptiometry. Multivariate logistic regression analyses were performed to estimate the adjusted odds ratios (ORs) and 95% confidence intervals (CIs) of cognitive impairment and cognitive decline for obesity marker trajectory patterns. RESULTS: After a 10-year follow-up, 168 older adults with incident cognitive impairment and 156 with rapid cognitive decline were defined as the top 25th percentile of cognitive decline. Four distinct trajectory groups of obesity markers were identified. In multivariate logistic regression analyses, a low likelihood of cognitive impairment was observed in the consistently high-level group from FM trajectory (ORs = 0.41, 95% CI = 0.20-0.85); the high-level U-shaped group from WHR trajectory (0.43, 0.22-0.84); and the median-level flat inverse U-shaped, consistently high-level, and low-level flat U-shaped groups from AF trajectory (0.44, 0.26-0.77; 0.33, 0.18-0.61; 0.39, 0.18-0.82). In addition, a low likelihood of rapid decline was found in the low-level, slightly increasing trend group from WHR trajectory (0.43, 0.22-0.85). CONCLUSION: FM and AF trajectories with consistent high levels and WHR trajectory with high level with U-shaped group are associated with low risks of incident cognitive impairment in older adults. Similarly, WHR trajectory with a low but slowly increasing trend is associated with a decreased risk of cognitive decline.

Joint effect of blood pressure and glycemic variation on the risk of cardiovascular morbidity and mortality in persons with type 2 diabetes.

OBJECTIVE: Few studies have explored the association of visit-to-visit variation in blood pressure (BP) and glycemic factors with cardiovascular disease (CVD) morbidity and mortality. This study aimed to examine the independent and joint effect of visit-to-visit BP and glycemic variation on CVD morbidity and mortality in persons with T2DM. METHODS: The present study consisted of two retrospective cohort studies. The Taiwan Diabetes Study was based on a database of the National Diabetes Care Management Program (DCMP) and linked with cardiovascular morbidity incidence. The Taichung Diabetes Study was based on the DCMP database of a medical center, which can be linked with the National Death Registry dataset. The outcomes were analyzed by using Cox's proportional hazard models. RESULTS: A total of 13,280 and 10,894 persons with T2DM in Taiwan and Taichung Diabetes Study, respectively, were included. SBP-CV, FPG-CV, and HbA1c-CV were significant predictors of stroke, CVD event or death, all-cause mortality, and expanded CVD mortality, whereas DBP-CV was a significant predictor of all-cause mortality and expanded and non-expanded CVD mortality. The joint effect of SBP, FPG, and HbA1c predicted the incidence of stroke and CVD event or death with increased risks of 16 %-35 %. In addition, the joint effect of SBP, DBP, FPG, and HbA1c was associated with all-cause and expanded CVD mortality with increased risks of 29 %-81 %. CONCLUSIONS: The joint effect of BP and glucose variation improved the prediction of cardiovascular morbidity and mortality. Moreover, simultaneous measurement of visit-to-visit BP and glycemic variation may stratify persons with cardiovascular risks and may be regarded as important therapeutic goals in the care of T2DM.

Predicting frailty in older adults using vocal biomarkers: a cross-sectional study.

BACKGROUND: Frailty is a common issue in the aging population. Given that frailty syndrome is little discussed in the literature on the aging voice, the current study aims to examine the relationship between frailty and vocal biomarkers in older people. METHODS: Participants aged ≥ 60 years visiting geriatric outpatient clinics were recruited. They underwent frailty assessment (Cardiovascular Health Study [CHS] index; Study of Osteoporotic Fractures [SOF] index; and Fatigue, Resistance, Ambulation, Illness, and Loss of weight [FRAIL] index) and were asked to pronounce a sustained vowel /a/ for approximately 1 s. Four voice parameters were assessed: average number of zero crossings (A1), variations in local peaks and valleys (A2), variations in first and second formant frequencies (A3), and spectral energy ratio (A4). RESULTS: Among 277 older adults, increased A1 was associated with a lower likelihood of frailty as defined by SOF (odds ratio [OR] 0.84, 95% confidence interval [CI] 0.74-0.96). Participants with larger A2 values were more likely to be frail, as defined by FRAIL and CHS (FRAIL: OR 1.41, 95% CI 1.12-1.79; CHS: OR 1.38, 95% CI 1.10-1.75). Sex differences were observed across the three frailty indices. In male participants, an increase in A3 by 10 points increased the odds of frailty by almost 7% (SOF: OR 1.07, 95% CI 1.02-1.12), 6% (FRAIL: OR 1.06, 95% CI 1.02-1.11), or 6% (CHS: OR 1.06, 95% CI 1.01-1.11). In female participants, an increase in A4 by 0.1 conferred a significant 2.8-fold (SOF: OR 2.81, 95% CI 1.71-4.62), 2.3-fold (FRAIL: OR 2.31, 95% CI 1.45-3.68), or 2.8-fold (CHS: OR 2.82, 95% CI 1.76-4.51, CHS) increased odds of frailty. CONCLUSIONS: Vocal biomarkers, especially spectral-domain voice parameters, might have potential for estimating frailty, as a non-invasive, instantaneous, objective, and cost-effective estimation tool, and demonstrating sex differences for individualised treatment of frailty.

Independent and joint associations of skeletal muscle mass and physical performance with all-cause mortality among older adults: a 12-year prospective cohort study.

BACKGROUND: Decreased skeletal muscle mass and low physical performance are independently associated with increased mortality in elderly individuals. However, little is known about the effects of skeletal muscle mass combined with physical performance on the prediction of mortality risk among community-dwelling older adults. This study aimed to determine the combined effects of skeletal muscle mass and physical performance on total mortality. METHODS: A community-based prospective cohort study was conducted among 641 participants aged 65 and older in 2009. The height-adjusted skeletal muscle index (hSMI) and the weight-adjusted SMI (wSMI) were determined by dual-energy X-ray absorptiometry examination. Physical performance tests measured at baseline included gait speed (GS), timed up-and-go (TUG) test, timed chair stand (TCS), weight-adjusted leg press (WaLP), and handgrip strength (HS). Cox proportional hazards regression models were applied to determine the adjusted hazard ratios (HRs) of mortality with 95% confidence intervals (95% CIs) for baseline skeletal muscle mass, physical performance, and traditional risk factors. RESULTS: During the follow-up of 12 years, 198 (30.89%) participants died. Low hSMI, low GS, high TUG, high TCS, low WaLP, and low HS were associated with high risks of mortality after the adjustment for confounders. The results of receiver operating characteristic (ROC) curve analyses revealed the values of ROC for models with additional consideration for TUG or all indicators significantly improved the discriminatory ability of mortality compared with the model with traditional factors (all P < 0.05). Elders with low hSMI and low GS (HRs = 4.33, 95% CI: 2.76-6.78), high TUG (4.11, 2.60-6.48), high TCS (2.97, 1.92-4.59), low WaLP (3.19, 2.13-4.79), and low HS (4.08, 2.70-6.17) were associated with high risks of mortality compared with those with high hSMI and their corresponding counterparts. CONCLUSION: The hSMI and physical performance are significantly associated with increased risks of all-cause mortality. The combined use of hSMI and physical performance can provide improved risk stratification, which may be appropriately used as a screening tool targeting high-risk elders for the effective prevention of sarcopenia-related mortality.