Intrinsic Capacity, Polygenic Risk Score, APOE Genotype, and Risk of Dementia: A Prospective Cohort Study Based on the UK Biobank.

BACKGROUND AND OBJECTIVES: The World Health Organization recently released a novel metric for healthy aging: intrinsic capacity (IC). The relationship between IC and the incidence of dementia, and its subtypes, is unknown. We aimed to analyze the relationship between IC and the incidence of dementia and its subtypes. Moreover, we tested whether genetic susceptibility to dementia could be modified by IC. METHODS: This cohort study involved 366,406 participants from the UK Biobank between 2006 and 2010. We analyzed 7 factors that reflected functional status across 4 IC domains to compute a comprehensive IC deficit score. Cox models were used to elucidate the relationship between the IC deficit score and the incidence of dementia. RESULTS: Among the 366,406 participants, 5,207 cases of dementia were documented, encompassing 2,186 and 1,175 cases of Alzheimer disease (AD) and vascular dementia (VD), respectively. Compared with participants with an IC score of 0, individuals with an IC score of 4+ had a markedly elevated risk of dementia (hazard ratio [HR] 2.17, 95% CI 1.92-2.45). In the joint analysis, for participants with a high polygenic risk score (PRS) and an IC score of 4 or more, the HR of all-cause dementia was 8.11 (95% CI 6.28-10.47) compared with individuals with a low PRS and an IC score of 0. Similar results were seen in the AD and VD groups. DISCUSSION: In summary, IC is associated with a higher risk of dementia, particularly in those combined with genetically predisposed to dementia.

Association between residential greenness and incident delirium: A prospective cohort study in the UK Biobank.

BACKGROUND: Contemporary environmental health investigations have identified green space as an emerging factor with promising prospects for bolstering human well-being. The incidence of delirium increases significantly with age and is fatal. To date, there is no research elucidating the enduring implications of green spaces on the occurrence of delirium. Therefore, we explored the relationship between residential greenness and the incidence of delirium in a large community sample from the UK Biobank. METHODS: Enrollment of participants spanned from 2006 to 2010. Assessment of residential greenness involved the land coverage percentage of green space within a buffer range of 300 m and 1000 m. The relationship between residential greenness and delirium was assessed using the Cox proportional hazards model. Further, we investigated the potential mediating effects of physical activity, particulate matter (PM) with diameters ≤2.5 (PM2.5), and nitrogen oxides (NOx). RESULTS: Of 232,678 participants, 3722 participants were diagnosed with delirium during a 13.4-year follow-up period. Compared with participants with green space coverage at a 300 m buffer in the lowest quartile (Q1), those in the highest quartile (Q4) had 15 % (Hazard ratio [HR] = 0.85, 95 % confidence interval [CI]: 0.77, 0.94) lower risk of incident delirium. As for the 1000 m buffer, those in Q4 had a 16 % (HR = 0.84, 95 % CI: 0.76, 0.93) lower risk of incident delirium. The relationship between green space in the 300 m buffer and delirium was mediated partially by physical activity (2.07 %) and PM2.5(49.90 %). Comparable findings were noted for the green space percentage within the 1000 m buffer. CONCLUSIONS: Our results revealed that long-term exposure to residential greenness was related to a lower risk of delirium. Air pollution and physical activity exerted a significant mediating influence in shaping this association.

Visceral adiposity associated with incidence and development trajectory of cardiometabolic diseases: A prospective cohort study.

BACKGROUND AND AIMS: There is a lack of literature concerning the effects of visceral adipose on the development of first cardiometabolic disease (FCMD) and its subsequent progression to cardiometabolic multimorbidity (CMM) and mortality. METHODS AND RESULTS: 423,934 participants from the UK Biobank with different baseline disease conditions were included in the analysis. CMM was defined as the simultaneous presence of coronary heart disease, T2D, and stroke. Visceral adiposity was estimated by calculating the visceral adiposity index (VAI). Multistate models were used to assess the effect of visceral adiposity on the development of CMM. During a median follow-up of 13.5 years, 50,589 patients had at least one CMD, 6131 were diagnosed with CMM, whereas 24,634 patients died. We observed distinct roles of VAI with respect to different disease transitions of CMM. HRs (95 % CIs) of high VAI were 2.35 (2.29-2.42) and 1.64 (1.50-1.79) for transitions from healthy to FCMD and from FCMD to CMM, and 0.97 (0.93-1.02) for all-cause mortality risk from healthy, FCMD and CMM, respectively. CONCLUSIONS: Our study provides the first evidence that visceral adipose may contribute to the development of FCMD and CMM in healthy participants. However, visceral adipose may confer resistance to all-cause mortality in participants with existing CMD or CMM. A better understanding of the relationship between visceral adipose and CMM can focalize further investigations on patients with CMD with high levels of visceral fat and help take targeted preventive measures to reduce the medical burden on individual patients and society.

Effect of self-regulating fatigue on health-related quality of life of middle-aged and elderly patients with recurrent stroke: a moderated sequential mediation model.

Although the association between self-regulation of fatigue and health-related quality of life (HRQoL) has been confirmed, the potential mechanism remains unclear. This study aimed to explore the role of health literacy, health behavior, and exercise frequency in the relationship among middle-aged and elderly patients with recurrent stroke. A cross-sectional survey was conducted. A total of 176 patients completed the survey, in which self-regulation of fatigue, HRQoL, health literacy and health behavior were measured by questionnaires. Based on Bootstrap analyses, a moderating sequential mediation model using PROCESS software was constructed with health literacy and health behavior as mediators and exercise frequency as the moderator. Of the participants, the mean age was 65.44 ± 12.43 years. Self-regulation of fatigue was found to affect HRQoL indirectly through two significant mediation pathways: (1) health literacy (ß=-0.11, 95%CI = -0.20, -0.03), which accounted for 28.79% of the total effect, and (2) health literacy and health behavior (ß=-0.02, 95%CI = -0.05, -0.00), which accounted for 4.80% of the total effect. Exercise frequency moderated the relationship between self-regulating fatigue and HRQoL. Specifically, the interaction term between self-regulating fatigue and exercise frequency significantly predicted HRQoL (ß = 0. 25, t = 2.55, p < 0.05). These findings highlight the role of health literacy and health behavior as sequential mediators of the relationship between self-regulating fatigue and HRQoL. Moreover, exercise frequency moderated the relationship between self-regulating fatigue and HRQoL. Encouraging patients with recurrent stroke to increase exercise frequency appropriately might improve HRQoL for patients with poor health literacy and health behavior.

Trajectories of quality of life and cognition in different multimorbidity patterns: Evidence from SHARE.

OBJECTIVES: The study aimed to observe the trajectory of quality of life (QoL) and cognition, and to a analyze the bidirectional association between cognition and QoL for diverse multimorbidity patterns. METHODS: In total, 16,153 older participants age ≥50 years were included from the Survey of Health, Ageing and Retirement in Europe (SHARE). We used latent class analysis (LCA) to identify multimorbidity patterns in the baseline population. We used linear mixed models (LMM) to examine the trajectory of cognition and QoL in different multimorbidity patterns. A cross-lagged model was employed to analyze the bidirectional association between cognition and QoL in diverse multimorbidity patterns. RESULTS: Latent class analysis identified four multimorbidity patterns: high and low comorbidity burden (HC and LC), cardiometabolic (CA), and osteoarthrosis (OS). The HC group had the poorest cognitive function and QoL (p for trend < 0.001). Delayed and immediate episodic memory in the OS group declined at a highest rate (p for trend < 0.001). Additionally, a bidirectional association between cognition and QoL was observed. The effect of cognitive function on QoL was relatively stronger than the reverse in the CA and LC groups. CONCLUSIONS: The rate of decline in cognition and QoL over the time differs in diverse multimorbidity patterns, and patients with four or more chronic diseases should be specially considered. Notably, early monitoring of cognitive function and can help break the vicious cycle between cognitive deterioration and poor QoL in patients with OS or CA diseases.

Bayesian Approaches in Exploring Gene-environment and Gene-gene Interactions: A Comprehensive Review.

Rapid advancements in high-throughput biological techniques have facilitated the generation of high-dimensional omics datasets, which have provided a solid foundation for precision medicine and prognosis prediction. Nonetheless, the problem of missing heritability persists. To solve this problem, it is essential to explain the genetic structure of disease incidence risk and prognosis by incorporating interactions. The development of the Bayesian theory has provided new approaches for developing models for interaction identification and estimation. Several Bayesian models have been developed to improve the accuracy of model and identify the main effect, gene-environment (G×E) and gene-gene (G×G) interactions. Studies based on single-nucleotide polymorphisms (SNPs) are significant for the exploration of rare and common variants. Models based on the effect heredity principle and group-based models are relatively flexible and do not require strict constraints when dealing with the hierarchical structure between the main effect and interactions (M-I). These models have a good interpretability of biological mechanisms. Machine learning-based Bayesian approaches are highly competitive in improving prediction accuracy. These models provide insights into the mechanisms underlying the occurrence and progression of complex diseases, identify more reliable biomarkers, and develop higher predictive accuracy. In this paper, we provide a comprehensive review of these Bayesian approaches.

Mediation analysis method review of high throughput data.

High-throughput technologies have made high-dimensional settings increasingly common, providing opportunities for the development of high-dimensional mediation methods. We aimed to provide useful guidance for researchers using high-dimensional mediation analysis and ideas for biostatisticians to develop it by summarizing and discussing recent advances in high-dimensional mediation analysis. The method still faces many challenges when extended single and multiple mediation analyses to high-dimensional settings. The development of high-dimensional mediation methods attempts to address these issues, such as screening true mediators, estimating mediation effects by variable selection, reducing the mediation dimension to resolve correlations between variables, and utilizing composite null hypothesis testing to test them. Although these problems regarding high-dimensional mediation have been solved to some extent, some challenges remain. First, the correlation between mediators are rarely considered when the variables are selected for mediation. Second, downscaling without incorporating prior biological knowledge makes the results difficult to interpret. In addition, a method of sensitivity analysis for the strict sequential ignorability assumption in high-dimensional mediation analysis is still lacking. An analyst needs to consider the applicability of each method when utilizing them, while a biostatistician could consider extensions and improvements in the methodology.

Ultra-processed food consumption, mediating biomarkers, and risk of chronic obstructive pulmonary disease: a prospective cohort study in the UK Biobank.

Background: Ultra-processed food (UPF) is a popular supplement in the UK and other developed countries. However, whether and how UPF intake is associated with chronic obstructive pulmonary disease (COPD) remains unclear. Objective: We aimed to examine the association between UPF consumption and COPD incidence and explore the potential mediating effects of COPD-related biomarkers. Methods: This prospective cohort study included 207 002 participants without COPD at recruitment and completed 24-hour dietary recalls. UPF was defined according to the NOVA classification system. Incident COPD was ascertained using electronic hospital and mortality records. Cox regression models were used to estimate UPF consumption and the subsequent risk of COPD. Substitution analysis was performed to assess the risk of COPD by substituting UPF with an equivalent proportion of unprocessed or minimally processed food (UNPF). Mediation analyses were performed to evaluate the contribution of biomarkers related to the lipid profile, glucose metabolism, and systemic inflammation to the observed associations. Results: During a median follow-up of 13.1 (interquartile range: 12.5-13.9) years, 4670 COPD events were recorded. The adjusted hazard ratio (HR) of COPD in the highest quintile versus the lowest quintile of the UPF consumption proportion (weight percentage of the UPF) was 1.22 (95% confidence interval [CI]: 1.11-1.34). There was a 10% elevated risk of COPD incidence per SD increase in UPF intake (HR: 1.10; 95% CI: 1.08-1.13). Replacing 20% of the UNPF weight with the UPF was associated with a 13% decrease in COPD risk (95% CI: 0.84-0.91). In mediation analyses, biomarkers explained 1.0-10.1% of the association between UPF intake and COPD. Results from stratified and sensitivity analyses further support the robustness of these findings. Conclusions: Elevated UPF consumption was associated with a higher risk of COPD, and this association was primarily mediated by glucose, inflammation, and lipids, whereas substituting UNPF for UPF was associated with a decreased risk of COPD.

Association between coffee and incident heart failure: A prospective cohort study from the UK Biobank.

BACKGROUND AND AIMS: The relationship between coffee consumption and heart failure (HF) incidence is inconclusive. This study aimed to explore the association between time-varying coffee consumption and incident HF using a longitudinal study design. METHODS AND RESULTS: Data were obtained from the UK Biobank, comprising 497,503 adults (age, 56.5 ± 8.1 years; 54.6% women) who were free from HF at baseline in 2006-2010. The median follow-up time for the HF incidence was 11.9 years. Marginal structural models (MSM) were employed to adjust for potential time-varying confounders and account for bias caused by loss of follow-up. Furthermore, we used a restricted cubic spline to test and describe the nonlinear relationship between coffee consumption and HF risk. At baseline, 70.5% of participants reported drinking ≥1 cups/d coffee and 2.7% participants developed HF. After adjusting for potential confounders, we identified a nonlinear J-shaped association between coffee consumption and HF risk (P < 0.001). Compared with drinking coffee <1 cups/d, 1-2 cups/d (HR = 0.878; 95% CI: 0.838-0.920), 3-4 cups/d (HR = 0.920; 95% CI: 0.869-0.974) may be associated with a reduced risk of HF, while >6 cups/d (HR = 1.209; 95% CI: 1.056-1.385) may be associated with a higher risk of HF. However, sensitive analyses stratified by gender and smoking status indicated that >6 cups/d does not significantly increase the risk of HF. Additionally, the type of coffee was found to significant impact on the incidence of HF (P < 0.05). CONCLUSION: In this large cohort of UK adults, moderate coffee consumption may reduce risk of HF incidence.

Association of ultra-processed food consumption with incident depression and anxiety: a population-based cohort study.

Background: Global ultra-processed food (UPF) consumption has risen rapidly. The development and prognosis of depression and anxiety remain unclarified. Herein, we aimed to examine the association between UPF consumption and the incidence and progression trajectory of depression and anxiety. Methods: In our study, participants were recruited between 2006 and 2010. UPF consumption was expressed as UPF servings, energy ratio, and weight ratio. The relationships between UPF consumption and depression or anxiety were assessed using the Cox proportional hazards model. Multi-state models were used to explore the association between UPF consumption and the risks of all transitions from a healthy state to depression or anxiety and then to all-cause mortality. Results: Among the 183 474 participants, 5453 were diagnosed with depression and 6763 with anxiety during the follow-up of 13.1 years. The participants in the highest quartile (Q4) of UPF servings, energy ratio, and weight ratio had an increased risk of depression compared to those in the lowest quartile (Q1), with hazard ratios (HRs) and 95% confidence intervals [CIs] of 1.22 (1.13-1.31), 1.13 (1.05-1.22), and 1.26 (1.17-1.36), respectively. Similarly, participants in Q4 of UPF consumption had a higher risk of anxiety, with HRs (95% CIs) of 1.13 (1.06-1.21), 1.13 (1.05-1.21), and 1.11 (1.04-1.19), compared to those in Q1. The study also found a significant association between UPF consumption and all-cause mortality, which disappeared for participants with depression or anxiety. Conclusions: Our findings revealed that UPF consumption is associated with depression or anxiety.

Bidirectional Association Between Multimorbidity and Frailty and the Role of Depression in Older Europeans.

BACKGROUND: Although previous studies have reported an association between multimorbidity and frailty, its direction and mechanism remain unclear. This study aimed to investigate the direction of this association, as well as the role of depression among older Europeans. METHODS: We used a cross-lagged panel design to evaluate the temporal relationship between multimorbidity and frailty and the role of depression. Multimorbidity status was assessed by the self-reporting of 14 chronic diseases. Frailty was assessed based on the frailty phenotype. The European-Depression Scale (EURO-D) was used to assess depression. RESULTS: There was a bidirectional relationship between frailty and multimorbidity. More severe multimorbidity predicted greater frailty (ß = 0.159; p < .001) and vice versa (ß = 0.107; p < .001). All paths from multimorbidity to frailty were stronger than the paths from frailty to multimorbidity (b1-a1: ß = 0.051; p < .001). Likewise, early multimorbidity change was a significant predictive factor for late frailty change (ß = 0.064; p < .001) and vice versa (ß = 0.048; p < .001). Depression in Wave 5 (T5) mediated the association between frailty in Wave 4 (T4) and multimorbidity in Wave 6 (T6; indirect effect: ß = 0.004; bootstrap 95% confidence interval: 0.003, 0.006). CONCLUSIONS: A positive, bidirectional association was observed between multimorbidity and frailty. Depression may be a potential cause of an increased risk of multimorbidity later in life in frail older adults. Early monitoring of frailty and depression may slow the progression of multimorbidity, thereby interrupting the vicious cycle.

Trends in cognitive function before and after stroke in China.

BACKGROUND: While cognitive impairment after stroke is common, cognitive trends before stroke are poorly understood, especially among the Chinese population who have a relatively high stroke burden. We aimed to model the trajectories of cognitive function before and after new-onset stroke among Chinese. METHODS: A total of 13,311 Chinese participants aged ≥ 45 years and without a history of stroke were assessed at baseline between June 2011 and March 2012 and in at least one cognitive test between 2013 (wave 2) and 2018 (wave 4). Cognitive function was assessed using a global cognition score, which included episodic memory, visuospatial abilities, and a 10-item Telephone Interview of Cognitive Status (TICS-10) test to reflect calculation, attention, and orientation abilities. RESULTS: During the 7-year follow-up, 610 (4.6%) participants experienced a first stroke. Both stroke and non-stroke groups showed declined cognitive function during follow-up. After adjustment for covariates, there was no significant difference in pre-stroke cognitive trajectories between stroke patients and stroke-free participants. The stroke group showed an acute decline in episodic memory (- 0.123 SD), visuospatial abilities (- 0.169 SD), and global cognition (- 0.135 SD) after stroke onset. In the years following stroke, the decline rate of the TICS-10 test was higher than the rate before stroke (- 0.045 SD/year). CONCLUSIONS: Chinese stroke patients had not experienced steeper declines in cognition before stroke compared with stroke-free individuals. Incident stroke was associated with acute declines in global cognition, episodic memory, visuospatial abilities, and accelerated declines in calculation, attention, and orientation abilities.

Sleep duration is associated with metabolic syndrome in adolescents and children: a systematic review and meta-analysis.

STUDY OBJECTIVES: Studies on the associations between sleep duration and metabolic syndrome in adolescents and children have reported mixed results. To shed more light on this issue, we conducted this meta-analysis by synthesizing the results of previous studies. METHODS: Studies were retrieved from PubMed, Ovid, Cochrane, and Embase from inception to October 2021. Fixed-effects models and random-effects models were used to analyze the effects of sleep time on metabolic syndrome in adolescents. RESULTS: Data from 7 studies, including 13,305 adolescents and children, were meta-analyzed. Compared with the control group, short sleep durations were not associated with a high prevalence of metabolic syndrome in adolescents and children using a random-effects model (odds ratio = 0.92, 95% confidence interval = 0.48-1.37, I2 = 56.5%, P = .378). Using a fixed-effects model on long sleep duration, this association was statistically significant (odds ratio = 0.57, 95% confidence interval = 0.38-0.76, I2 = 0.0%, P < .001) as a protective factor compared with shorter sleep duration. CONCLUSIONS: Long sleep duration, instead of short sleep duration, was significantly associated with a lower prevalence of metabolic syndrome among adolescents and children. CITATION: Xu Y, Hua J, Wang J, Shen Y. Sleep duration is associated with metabolic syndrome in adolescents and children: a systematic review and meta-analysis. J Clin Sleep Med. 2023;19(10):1835-1843.

Mechanism of the association between sleep quality and mortality in middle-aged and older adults: A prospective study analysis of the UK Biobank.

BACKGROUND: Although sleep quality is known to be associated with mortality, how poor sleep quality contributes to an increased risk of mortality is still unknown. We aimed to examine whether lifestyle, psychosocial and biological factors mediate the association. METHODS: 205,654 participants from UK Biobank were used for the analysis. The outcome was all-cause, cardiovascular disease (CVD) and cancer mortality by February 2022. Exposure was assessed by a sleep score consisting of five sleep behaviors at baseline. Lifestyle, psychosocial, and biological factors are regarded as potential mediators. Mediation analysis based on Cox proportional hazards models was performed. RESULTS: Poor sleep quality was associated with a higher risk of all-cause (Hazard Ratio [HR] = 1.098; 95% CI: 1.058-1.140), CVD (HR = 1.139; 95% CI: 1.045-1.243) and cancer mortality (HR = 1.095; 95% CI: 1.040-1.152). Lifestyle mediators (smoking, physical activity, sedentary, BMI and diet) could explain between 2.6% and 34.0% of the increased risk of all-cause mortality in individuals with poor sleep quality. Self-reported health, frailty, depression, and loneliness were significant psychosocial mediators of this association pathway. About one-fifth of the association can be explained by the biological role of CRP. Similar mediating patterns were observed for CVD and cancer mortality. LIMITATIONS: Both exposure and mediators were measured at baseline, so the possibility of reverse causality cannot be ruled out. CONCLUSIONS: Poor sleep quality is associated with an increased risk of death through a combination of lifestyle, psychosocial and biological pathways. Adopting healthy lifestyles and staying psychosocial well-being are cost-effective interventions to lower the risk of death.

Bidirectional Associations Between Sleep Quality and Grip Strength and the Mediating Role of Depression: Evidence From Two Nationally Representative Cohorts.

BACKGROUND: Although studies have demonstrated associations between sleep quality (SQ) and grip strength (GS) in older adults, the direction and underlying mechanisms of this relationship are yet to be better delineated. We aimed to longitudinally investigate the bidirectional association between SQ and GS and the mediating role of depression in this association. METHODS: Based on 2 nationally representative samples with people aged ≥50 years from the China Health and Retirement Longitudinal Study (CHARLS; 4 200 participants) and English Longitudinal Study of Ageing (ELSA; 5 922 participants), cross-lagged panel models were employed to examine the potential bidirectional relationships between objectively measured GS and self-reported SQ. RESULTS: We observed a GS-SQ bidirectional association dominated by GS. After adjusting for potential confounders, a higher GS at T1 predicted better SQ at T2 (ELSA: ß = 0.075; CHARLS: ß = 0.104, p < .001) and vice versa (ELSA: ß = 0.034; CHARLS: ß = 0.030, p < .01). Moreover, depression partially mediated the impact of GS on subsequent SQ (ELSA, indirect effect: 0.0057, 95% confidence interval [CI]: 0.0035-0.0084; CHARLS, indirect effect: 0.0086, 95% CI: 0.0051, 0.0131), but not vice versa. CONCLUSIONS: The results regarding data from both cohorts consistently supported a bidirectional association between GS and SQ and the mediating role of depression in the dominant pathway of this bidirectional relationship. Older adults with a low GS should be made aware of a potentially vicious cycle related to depression that can affect their sleep. Regular screening for depression may help to break this cycle.

Risk-prediction models for intravenous immunoglobulin resistance in Kawasaki disease: Risk-of-Bias Assessment using PROBAST.

BACKGROUND: The prediction model of intravenous immunoglobulin (IVIG) resistance in Kawasaki disease can calculate the probability of IVIG resistance and provide a basis for clinical decision-making. We aim to assess the quality of these models developed in the children with Kawasaki disease. METHODS: Studies of prediction models for IVIG-resistant Kawasaki disease were identified through searches in the PubMed, Web of Science, and Embase databases. Two investigators independently performed literature screening, data extraction, quality evaluation, and discrepancies were settled by a statistician. The checklist for critical appraisal and data extraction for systematic reviews of prediction modeling studies (CHARMS) was used for data extraction, and the prediction models were evaluated using the Prediction Model Risk of Bias Assessment Tool (PROBAST). RESULTS: Seventeen studies meeting the selection criteria were included in the qualitative analysis. The top three predictors were neutrophil measurements (peripheral neutrophil count and neutrophil %), serum albumin level, and C-reactive protein (CRP) level. The reported area under the curve (AUC) values for the developed models ranged from 0.672 (95% confidence interval [CI]: 0.631-0.712) to 0.891 (95% CI: 0.837-0.945); The studies showed a high risk of bias (ROB) for modeling techniques, yielding a high overall ROB. CONCLUSION: IVIG resistance models for Kawasaki disease showed high ROB. An emphasis on improving their quality can provide high-quality evidence for clinical practice. IMPACT STATEMENT: This study systematically evaluated the risk of bias (ROB) of existing prediction models for intravenous immunoglobulin (IVIG) resistance in Kawasaki disease to provide guidance for future model development meeting clinical expectations. This is the first study to systematically evaluate the ROB of IVIG resistance in Kawasaki disease by using PROBAST. ROB may reduce model performance in different populations. Future prediction models should account for this problem, and PROBAST can help improve the methodological quality and applicability of prediction model development.

The Longitudinal Association Between Frailty, Cognition, and Quality of Life in Older Europeans.

OBJECTIVES: Evidence on the association between frailty and quality of life (QoL) is mostly limited to cross-sectional studies. Thus, the temporal order and potential mechanisms of this association are largely unknown. Our study examines both the directionality of this association and the role of cognition in this association in longitudinal data. METHODS: Cross-lagged panel models were employed to examine the temporal relationship between frailty and QoL, as well as cognition's role among 19,649 older adults in Europe. Frailty, QoL, and cognition were assessed using the health deficit index, CASP-12, and 3 standard cognitive tests, respectively. RESULTS: We observed a bidirectional association between frailty and QoL and their dynamics. High initial levels of frailty predicted poorer QoL later and vice versa (ß = -0.151 and -0.052, p < .001). The early change in frailty predicted the late change in QoL, and vice versa (ß = -0.093 and -0.061, p < .001). Frailty or its early change drives this interrelationship. Cognition at Wave 5 partially mediated frailty's effect at Wave 4 on QoL at Wave 6 (indirect effect: ß = -0.005, 95% confidence interval = -0.006, -0.004). DISCUSSION: Our findings supported that early prevention of frailty and its risk factors may have more influential protective effects on later physical and mental health, as well as the need for ongoing screening for mental health in aging population. Also, the maintenance of good cognitive performance may help interrupt this possible vicious cycle linking frailty and QoL decline.

Moderated-mediation analysis of multimorbidity and health-related quality of life among the Chinese elderly: The role of functional status and cognitive function.

Objectives: To investigate the relationship between multimorbidity and health-related quality of life (HRQoL), and explore the effects of functional status and cognitive function on Chinses elderly behind this relationship. Methods: The Multivariate logistic regression and Tobit regression models were used to determine the influence of multimorbidity on HRQoL. Bootstrap analysis was used to probe the mediating effects of functional status and the moderating role of cognition on multimorbidity and HRQoL. Results: Results of the 2,887 participants age ≥ 60 years included in the analysis, 51.69% had chronic diseases. Stroke (ß = -0.190; 95% confidence interval [CI], -0.232, -0.149; p < 0.001) and the combination of hypertension and stroke (ß = -0.210; 95% CI, -0.259, -0.160; p < 0.001) had the greatest influence on HRQoL. Functional status partially mediated the relationship between the number of non-communicable diseases (No. of NCDs) and HRQoL, while cognitive function had a moderating effect not only in the A-path (No. of NCDs to functional status, ß = 0.143; t = 7.18; p < 0.001) and but also in the C-path (No. of NCDs to HRQoL, ß = 0.007; t = 6.08; p < 0.001). Conclusion: Functional status partially mediated the relationship between multimorbidity and HRQoL in older adults. And cognitive function, if declined, may strengthen this relationship. These findings suggested that improving cognitive function and functional status in those who developed multimorbidity could be a viable prevention or treatment strategy to improve HRQoL in elderly patients.

Joint effect of elevated-c-reactive protein level and hypertension on new-onset stroke: A nationwide prospective cohort study of CHARLS.

Background and aims: This study aimed to examine whether the combination of elevated-C-reactive protein (CRP) levels and hypertension increased the risk of stroke among middle-aged and elderly Chinese. Methods: This analysis included 9,821 Chinese participants aged ≥45 years in the China Health and Retirement Longitudinal Study (CHARLS). Data based on three waves of CHARLS were used (2011, 2013, and 2015). Multivariable Cox proportional hazards regression models were used to estimate hazard ratios (HRs) with a 95% confidence interval (95%CI) of new-onset stroke risk according to elevated-CRP level and hypertension. Moreover, the area under the curve (AUC), net reclassification index (NRI), and integrated discrimination improvement (IDI) were used to evaluate the incremental predictive value. Results: A total of 184 stroke events occurred during follow-up. The median follow-up time was 4 years. Compared with those with normal CRP levels (CRP ≤ 3 mg /L) and blood pressure, the adjusted HRs and 95%CI were 1.86 (0.90-3.85) for individuals with elevated-CRP levels alone, 2.70 (1.71-4.28) for those with hypertension alone, and 4.80 (2.83-8.12) for those with comorbid elevated-CRP levels and hypertension. People with the coexistence of elevated-CRP levels and hypertension had the highest risk of new-onset stroke among all subgroup analyses. Finally, adding the combination of elevated-CRP levels and hypertension to conventional factors significantly improved the risk prediction for new-onset stroke. Conclusion: Our findings indicate that the combined effect of elevated-CRP levels and hypertension increase the risk of new-onset stroke among the middle-aged and geriatric Chinese population.

Prediction Model Risk-of-Bias Assessment Tool for coronary artery lesions in Kawasaki disease.

Objective: To review and critically appraise articles on prediction models for coronary artery lesions (CALs) in Kawasaki disease included in PubMed, Embase, and Web of Science databases from January 1, 1980, to December 23, 2021. Materials and methods: Study screening, data extraction, and quality assessment were performed by two independent reviewers, with a statistics expert resolving discrepancies. Articles that developed or validated a prediction model for CALs in Kawasaki disease were included. The Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modeling Studies checklist was used to extract data from different articles, and Prediction Model Risk-of-Bias Assessment Tool (PROBAST) was used to assess the bias risk in different prediction models. We screened 19 studies from a pool of 881 articles. Results: The studies included 73-5,151 patients. In most studies, univariable logistic regression was used to develop prediction models. In two studies, external data were used to validate the developing model. The most commonly included predictors were C-reactive protein (CRP) level, male sex, and fever duration. All studies had a high bias risk, mostly because of small sample size, improper handling of missing data, and inappropriate descriptions of model performance and the evaluation model. Conclusion: The prediction models were suitable for the subjects included in the studies, but were poorly effective in other populations. The phenomenon may partly be due to the bias risk in prediction models. Future models should address these problems and PROBAST should be used to guide study design.