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The relative frailty variance among survivors provides a readily interpretable measure of how the heterogeneity of a population, as represented by a frailty model, evolves over time. We discuss the properties of the relative frailty variance, show that it characterizes frailty distributions and that, suitably rescaled, it may be used to compare patterns of dependence across models and data sets. In shared frailty models, the relative frailty variance is closely related to the cross-ratio function, which is estimable from bivariate survival data. We investigate the possible shapes of the relative frailty variance function for the purpose of model selection, and we review available frailty distribution families in this context. We introduce several new families with contrasting properties, including simple but flexible time varying frailty models. The benefits of the approach that we propose are illustrated with two applications to bivariate current status data obtained from serological surveys.

This study aims to examine the association between Relative Fat Mass (RFM) and the frailty index (FI) among U.S. adults aged 60 years and older, and to assess the discriminative performance of RFM for high FI status. Utilizing NHANES data from 2007 to 2018, RFM was calculated using the formula RFM = 64 - (20 × height/wc) + (12 × sex), where female sex is assigned a value of 1 and male sex a value of 0. The degree of frailty was assessed using the FI based on the Rockwood cumulative deficit model, and an FI ≥ 0.25 was defined as frailty. To investigate the relationship between RFM and the occurrence of high FI, weighted multivariate logistic regression analysis, subgroup analyses, and interaction tests were conducted. Generalized additive modeling (GAM) was applied to account for any non-linear patterns, and receiver operating characteristic (ROC) analysis was utilized to evaluate RFM’s discriminative capacity for high FI. The prevalence of high FI increased by 12% for each unit increase in RFM in a fully adjusted model, indicating a significant and positive relationship between RFM and high FI prevalence (OR: 1.12, 95% CI: 1.10, 1.15; P  < 0.0001). RFM and the prevalence of high FI exhibited a substantial association across the majority of categories. Additionally, no statistically significant interactions were identified in most subgroups. The threshold effect and non-linear relationship were significant in the GAM model. RFM demonstrated superior discriminative performance for the prevalence of high FI compared to BMI and WC across all populations. This study suggests that elevated RFM is significantly associated with the development of high FI in older adults; however, further validation is warranted in a large prospective study.

Background: There exists some inconsistent evidence on the relationship between altered cardiac morphology, its function, and frailty. Therefore, this study aimed to assess the associations among frailty, lean body mass, central arterial stiffness, and cardiac structure and geometry in older people with a normal ejection fraction. Methods: A total of 205 patients >65 years were enrolled into this ancillary analysis of the FRAPICA study and were assessed for frailty with the Fried phenotype scale. Left ventricular dimensions and geometry were assessed with two-dimensional echocardiography. Fat-free mass was measured using three-site skinfold method. Parametric and non-parametric statistics and analysis of covariance were used for statistical calculations. Results: Frail patients were older and women comprised the majority of the frail group. Frail men and women had comparable weight, height, fat-free mass, blood pressure, central blood pressure, and carotid–femoral pulse wave velocity to their non-frail counterparts. There was a linear correlation between the sum of frailty criteria and left ventricular end-diastolic diameter (Spearman R = −0.17; p < 0.05) and relative wall thickness (Spearman R = 0.23; p < 0.05). In the analysis of covariance, frailty and gender were independently associated with left ventricular mass (gender: β of −0.37 and 95% CI of −0.50–−0.24 at p < 0.001), the left ventricular mass index (gender: β of −0.23 and 95% CI of −0.37–−0.09 at p < 0.001), and relative wall thickness (frailty: β of −0.15 and 95% CI of −0.29–−0.01 at p < 0.05; gender: β of 0.23 and 95% CI of 0.09–0.36 at p < 0.01). Frailty was associated with a shift in heart remodeling toward concentric remodeling/hypertrophy. Conclusions: Frailty is independently associated with thickening of the left ventricular walls and a diminished left ventricular end-diastolic diameter, which are features of concentric remodeling or hypertrophy. This association appears to be more pronounced in women. Such adverse cardiac remodeling may represent another phenotypic feature linked to frailty according to the phenotype frailty criteria.

BackgroundAge structure and longevity constitute fundamental determinants of mosquito populations’ capacity to transmit pathogens. However, investigations on mosquito-borne diseases primarily focus on aspects such as abundance or dispersal rather than survival and demography. Here, we examine the post-capture longevity of wild-caught populations of the Asian tiger mosquito Aedes albopictus to investigate the influence of environmental factors and individual frailty on longevity.MethodsWe captured females of Ae. albopictus from June to November 2021 in a vegetated and an urban area by two methods of capture (BG traps and Human Landing catch). They were kept in semi-controlled conditions in the field, and survival was monitored daily across the 859 individuals captured. We studied the differences in longevity per capture method and location and the influence on longevity of seasonal, climatic and individual factors.ResultsPhotoperiod, GDD, minimum and maximum temperature and relative humidity showed an effect on the risk of death of females in the field. Females captured in urban area with Human Landing catch methods had greater longevity than females captured in non-urban areas with BG traps. Individual variance, reflecting individual frailties, had an important effect on the risk of death: the greater the frailty, the shorter the post-capture longevity. Overall, longevity is affected not only by climate and seasonal drivers like temperature and photoperiod but also by the individual frailty of mosquitoes.ConclusionThis work unravels environmental drivers of key demographic parameters such as longevity, as modulated by individual frailty, in disease vectors with strong seasonal dynamics. Further demographic understanding of disease vectors in the wild is needed to adopt new surveillance and control strategies and improve our understanding of disease risk and spread.

: In clinical and observational studies, the event of interest can often recur on the same subject. In a more complicated situation, there exists a terminal event (e.g., death) which stops the recurrent event process. In many such instances, the terminal event is strongly correlated with the recurrent event process. We consider the recurrent/terminal event setting and model the dependence through a shared gamma frailty that is included in both the recurrent event rate and terminal event hazard functions. Conditional on the frailty, a model is specified only for the marginal recurrent event process, hence avoiding the strong Poisson‐type assumptions traditionally used. Analysis is based on estimating functions that allow for estimation of covariate effects on the recurrent event rate and terminal event hazard. The method also permits estimation of the degree of association between the two processes. Closed‐form asymptotic variance estimators are proposed. The proposed method is evaluated through simulations to assess the applicability of the asymptotic results in finite samples and the sensitivity of the method to its underlying assumptions. The methods can be extended in straightforward ways to accommodate multiple types of recurrent and terminal events. Finally, the methods are illustrated in an analysis of hospitalization data for patients in an international multi‐center study of outcomes among dialysis patients.

Recurrent event time data are common in biomedical follow-up studies, in which a study subject may experience repeated occurrences of an event of interest. In this paper, we evaluate two popular nonparametric tests for recurrent event time data in terms of their relative efficiency. One is the log-rank test for classical survival data and the other a more recently developed nonparametric test based on comparing mean recurrent rates. We show analytically that, somewhat surprisingly, the log-rank test that only makes use of time to the first occurrence could be more efficient than the test for mean occurrence rates that makes use of all available recurrence times, provided that subject-to-subject variation of recurrence times is large. Explicit formula are derived for asymptotic relative efficiencies under the frailty model. The findings are demonstrated via extensive simulations.