Trajectories of frailty with aging:Coordinated analysis of five longitudinal studies

BACKGROUND AND OBJECTIVES: There is an urgent need to better understand frailty and its predisposing factors. Although numerous cross-sectional studies have identified various risk and protective factors of frailty, there is a limited understanding of longitudinal frailty progression. Furthermore, discrepancies in the methodologies of these studies hamper comparability of results. Here, we use a coordinated analytical approach in 5 independent cohorts to evaluate longitudinal trajectories of frailty and the effect of 3 previously identified critical risk factors: sex, age, and education. RESEARCH DESIGN AND METHODS: We derived a frailty index (FI) for 5 cohorts based on the accumulation of deficits approach. Four linear and quadratic growth curve models were fit in each cohort independently. Models were adjusted for sex/gender, age, years of education, and a sex/gender-by-age interaction term. RESULTS: Models describing linear progression of frailty best fit the data. Annual increases in FI ranged from 0.002 in the Invecchiare in Chianti cohort to 0.009 in the Longitudinal Aging Study Amsterdam (LASA). Women had consistently higher levels of frailty than men in all cohorts, ranging from an increase in the mean FI in women from 0.014 in the Health and Retirement Study cohort to 0.046 in the LASA cohort. However, the associations between sex/gender and rate of frailty progression were mixed. There was significant heterogeneity in within-person trajectories of frailty about the mean curves. DISCUSSION AND IMPLICATIONS: Our findings of linear longitudinal increases in frailty highlight important avenues for future research. Specifically, we encourage further research to identify potential effect modifiers or groups that would benefit from targeted or personalized interventions

Contributions of the MyD88-Dependent Receptors IL-18R, IL-1R, and TLR9 to Host Defenses following Pulmonary Challenge with Cryptococcus neoformans

Signaling via the adapter protein, MyD88, is important in the host defense against Cryptococcus neoformans infection. While certain Toll-like receptors (TLRs) can enhance the clearance of Cryptococcus, the contributions of MyD88-dependent, TLR-independent pathways have not been fully investigated. We examined the roles of IL-1R and IL-18R in vivo by challenging C57BL/6 mice with a lethal strain of Cryptococcus. We found that the absence of IL-18R, but not IL-1R, causes a shift in the survival curve following pulmonary delivery of a virulent strain of C. neoformans (H99). Specifically, IL-18R-deficient mice have significantly shorter median survival times compared to wild-type mice following infection. Cytokine analysis of lung homogenates revealed that deficiency of IL-IR, IL-18R, or MyD88 is associated with diminished lung levels of IL-1β. In order to compare these findings with those related to TLR-deficiency, we studied the effects of TLR9-deficiency and found that deficiency of TLR9 also affects the survival curve of mice following challenge with C. neoformans. Yet the lungs from infected TLR9-deficient mice have robust levels of IL-1β. In summary, we found that multiple signaling components can contribute the MyD88-dependent host responses to cryptococcal infection in vivo and each drives distinct pulmonary responses

Supplementary Material for: A Regression Tree Analysis to Identify Factors Predicting Frailty: The International Mobility in Aging Study

Introduction: Frailty is a complex geriatric syndrome with a multifaceted etiology. We aimed to identify the best combinations of risk factors that predict the development of frailty using recursive partitioning models. Methods: We analyzed reports from 1,724 community-dwelling men and women aged 65–74 years participating in the International Mobility in Aging Study (IMIAS). Frailty was measured using frailty phenotype scale that included five physical components: unintentional weight loss, weakness, slow gait, exhaustion, and low physical activity. Frailty was defined as presenting three of the above five conditions, having one or two conditions indicated prefrailty and showing none as robust. Socio-demographic, physical, lifestyle, psycho-social, and life-course factors were included in the analysis as potential predictors. Results: 21% of pre-frail and robust participants showed a worse stage of frailty in 2014 compared to 2012. In addition to functioning variables, fear of falling (FOF), income, and research site (Canada vs. Latin America vs. Albania) were significant predictors of the development of frailty. Additional significant predictors after exclusion of functioning factors included education, self-rated health, and BMI. Conclusions: In addition to obvious risk factors for frailty (such as functioning), socio-economic factors and FOFs are also important predictors. Clinical assessment of frailty should include measurement of these factors to identify high-risk individuals

Development of a Frailty Ladder Using Rasch Analysis: If the Shoe Fits

BACKGROUND: The current measurement approach to frailty is to create an index of frailty status, rather than measure it. The purpose of this study is to test the extent to which a set of items identified within the frailty concept fit a hierarchical linear model (e.g., Rasch model) and form a true measure reflective of the frailty construct. METHODS: A sample was assembled from three sources: community organization for at-risk seniors (n=141); colorectal surgery group assessed post-surgery (n=47); and hip fracture assessed post-rehabilitation (n=46). The 234 individuals (age 57 to 97) contributed 348 measurements. The frailty construct was defined according to the named domains within commonly used frailty indices, and items drawn to reflect the frailty came from self-report measures. Performance tests were tested for the extent to which they fit the Rasch model. RESULTS: Of the 68 items, 29 fit the Rasch model: 19 self-report items on physical function and 10 performance tests, including one for cognition; patient reports of pain, fatigue, mood, and health did not fit; nor did body mass index (BMI) nor any item representing participation. CONCLUSION: Items that are typically identified as reflecting the frailty concept fit the Rasch model. The Frailty Ladder would be an efficient and statistically robust way of combining results of different tests into one outcome measure. It would also be a way of identifying which outcomes to target in a personalized intervention. The rungs of the ladder, the hierarchy, could be used to guide treatment goals

The relationship of meteorological conditions to the epidemic activity of respiratory syncytial virus

Our aim was to obtain knowledge of how meteorological conditions affect community epidemics of respiratory syncytial virus (RSV) infection. To this end we recorded year-round RSV activity in nine cities that differ markedly in geographic location and climate. We correlated local weather conditions with weekly or monthly RSV cases. We reviewed similar reports from other areas varying in climate. Weekly RSV activity was related to temperature in a bimodal fashion, with peaks of activity at temperatures above 24–30°C and at 2–6°C. RSV activity was also greatest at 45–65% relative humidity. RSV activity was inversely related to UVB radiance at three sites where this could be tested. At sites with persistently warm temperatures and high humidity, RSV activity was continuous throughout the year, peaking in summer and early autumn. In temperate climates, RSV activity was maximal during winter, correlating with lower temperatures. In areas where temperatures remained colder throughout the year, RSV activity again became nearly continuous. Community activity of RSV is substantial when both ambient temperatures and absolute humidity are very high, perhaps reflecting greater stability of RSV in aerosols. Transmission of RSV in cooler climates is inversely related to temperature possibly as a result of increased stability of the virus in secretions in the colder environment. UVB radiation may inactivate virus in the environment, or influence susceptibility to RSV by altering host resistance