京都大学 / 0048 / 新制・課程博士 / 博士(医学) / 甲第22732号 / 医博第4650号 / 新制||医||1046(附属図書館) / 京都大学大学院医学研究科医学専攻 / (主査)教授 髙橋 良輔, 教授 中山 健夫, 教授 川上 浩司 / 学位規則第4条第1項該当 / Doctor of Medical Science / Kyoto University / DFAM

<p>Frailty, generally characterized as a clinical state of increased vulnerability resulting from age-related decline in reserve and function across multiple physiologic systems, has been gaining attention in recent years due to its high correlates with a number of poor health outcomes including falls, hospitalization, and mortality. Although policy makers, health practitioners, and researchers have acknowledged that frailty is a major public health issue, few have investigated the life course predictors of this devastating and costly syndrome. The purpose of this dissertation is (1) to identify the early and later-life predictors of initial frailty and frailty growth over time among older US adults, (2) to examine if childhood exposures influence frailty directly and/or indirectly through adult risks and resources, and (3) to examine the role that social relationships play in frailty trajectories among older adults. Drawing from cumulative inequality theory, this dissertation uses longitudinal data from the Health and Retirement Study (HRS) to examine the effects of childhood exposures, adult risks/resources, and social relationships on frailty trajectories among adults 65 and older. The empirical investigation is presented in two main chapters.</p> <p>The first study investigates the life course predictors of frailty prevalence and further examines how childhood exposures may be directly and indirectly associated with frailty through adult risks and resources. The second study builds on the findings of the first by examining the predictors of frailty growth over time and investigating how social relationships in later life may shape that growth. Findings reveal each childhood exposure domain influences frailty either directly or indirectly through adult factors and experiences. Specifically, analyses reveal that childhood chronic disease, impairments, and risky adolescent behaviors directly influence frailty in later life. Additionally, results reveal that poor childhood SES was one of the most consistent predictors of adult frailty—but much of the effect was due to its influence on adult risks and resources. Few adult risk factors influence frailty trajectories over time. Among adult resources, socioeconomic status (particularly education) slows frailty growth over time. Finally, findings reveal that both social support and more social roles mediate the relationship between childhood exposures and frailty, and that the effect of more social roles continues over time. </p> <p>This dissertation highlights a number of life course predictors of frailty and identifies areas for potential interventions—particularly those aimed at providing equal access to higher education and quality social relationships over the life course. Most importantly, this dissertation demonstrates that frailty prevention should not be a task delegated exclusively to older adults. Effective prevention of this often devastating and costly syndrome should begin early in life.</p>

Indiana University-Purdue University Indianapolis (IUPUI) / Survival analysis often encounters the situations of correlated multiple events including the same type of event observed from siblings or multiple events experienced by the same individual. In this dissertation, we focus on the joint modeling of bivariate time to event data with the estimation of the association parameters and also in the situation of a semi-competing risk. This dissertation contains three related topics on bivariate time to event mod els. The first topic is on estimating the cross ratio which is an association parameter between bivariate survival functions. One advantage of using cross-ratio as a depen dence measure is that it has an attractive hazard ratio interpretation by comparing two groups of interest. We compare the parametric, a two-stage semiparametric and a nonparametric approaches in simulation studies to evaluate the estimation perfor mance among the three estimation approaches. The second part is on semiparametric models of univariate time to event with a semi-competing risk. The third part is on semiparametric models of bivariate time to event with semi-competing risks. A frailty-based model framework was used to accommodate potential correlations among the multiple event times. We propose two estimation approaches. The first approach is a two stage semiparametric method where cumulative baseline hazards were estimated by nonparametric methods first and used in the likelihood function. The second approach is a penalized partial likelihood approach. Simulation studies were conducted to compare the estimation accuracy between the proposed approaches. Data from an elderly cohort were used to examine factors associated with times to multiple diseases and considering death as a semi-competing risk.

In survival analysis or time-to-event analysis, one of the primary goals of analysis is to predict the occurrence of an event of interest for subjects within the study. Even though survival analysis methods were originally developed and used in medical re- search, those methods are also commonly used nowadays in other areas as well, such as in predicting the default of a loan and in estimating of the failure of a system. To include covariates in the analysis, the most widely used models are the propor- tional hazard model developed by Cox (1972) and the accelerated failure time model developed by Buckley and James (1979). The proportional hazard (PH) model as- sumes subjects from different groups have their hazard functions proportionally, while the accelerated failure time (AFT) model assumes the effect of covariates is to accel- erate or decelerate the occurrence of event of interest. In some survival analyses, not all subjects in the study will experience the event. Such a group of individuals is referred to `cured' group. To analyze a data set with a cured fraction, Boag (1948) and Berkson and Gage (1952) discussed a mixture cure model. Since then, the cure model and associated inferential methods have been widely stud- ied in the literature. It has also been recognized that subjects in the study are often correlated within clusters or groups; for example, patients in a hospital would have similar conditions and environment. For this reason, Vaupel et al. (1979) proposed a frailty model to model the correlation among subjects within clusters and conse- quently the presence of heterogeneity in the data set. Hougaard (1989), McGilchrist and Aisbett (1991), and Klein (1992) all subsequently developed parametric frailty models. Balakrishnan and Peng (2006) proposed a Generalized Gamma frailty model, which includes many common frailty models, and discussed model fitting and model selection based on it. To combine the key components and distinct features of the mixture cure model and the frailty model, a mixture cure frailty model is discussed here for modelling correlated survival data when not all the subjects under study would experience the occurrence of the event of interest. Longini and Halloran (1996) and Price and Manatunga (2001) developed several parametric survival models and employed the Likelihood Ratio Test (LRT) to perform a model discrimination among cure, frailty and mixture cure frailty models. In this thesis, we first describe the components of a mixture cure frailty model, wherein the flexibility of the frailty distributions and lifetime survival functions are discussed. Both proportional hazard and accelerated failure time models are considered for the distribution of lifetimes of susceptible (or non-cured) individuals. Correlated ran- dom effect is modelled by using a Generalized Gamma frailty term, and an EM-like algorithm is developed for the estimation of model parameters. Some Monte Carlo simulation studies and real-life data sets are used to illustrate the models as well as the associated inferential methods. / Thesis / Doctor of Philosophy (PhD)

PhD Thesis / Older adults are a rapidly growing segment of the population with unique healthcare needs. As people age, they are more likely to become susceptible to diseases and develop complex health conditions that require tailored strategies to address. These vulnerabilities could also impact different stages of the research process to generate evidence that promote healthy aging and better quality of life for this population. Attrition and missing data are some of the common methodological challenges in research with older adults. These issues could affect the quality of evidence generated if not properly addressed. There is also limited evidence to guide the development of interventions in specific populations of older adults with frailty, who have reduced function and are at higher risk for poor health outcomes. Across six chapters, this thesis addresses these methodological and interventional gaps in research with older adults. Using different research methodologies including a systematic literature survey, secondary data analysis of a cohort study, and two randomized feasibility trials, this thesis provides some important considerations for practice. In particular, we (i) evaluated the magnitude, pattern, and factors associated with attrition in the Global Longitudinal Study of Osteoporosis in Women (GLOW) Hamilton cohort of older adults; (ii) performed a systematic survey of the reporting and handling of missing data in longitudinal observational studies of older adults; (iii) conducted a randomized controlled feasibility trial of the Geras virtual frailty rehabilitation program to build resilience in vulnerable older adults during the COVID-19 pandemic; and (iv) evaluated the feasibility of the FitJoints randomized controlled trial of a multimodal intervention in frail older patients with osteoarthritis awaiting hip and knee replacement. / Thesis / Doctor of Philosophy (PhD) / The number of people who are old is increasing by the day and so is the need to understand how to ensure they are aging well. Old age makes people more prone to diseases. The risks of becoming ill could make the efforts to generate knowledge that can help them thrive challenging. They could drop out of a study making it difficult to collect enough information for data analysis. For some older adults who are frail and have higher risk for diseases, there is little known about how to design programs that will enable them stay active and healthier during the COVID-19 pandemic or before they have hip or knee replacement surgery. This thesis contributes to the knowledge on how to improve the quality of research involving older adults and bridge the gap in the knowledge about how to support those who are frail among them.

Introduction: The frailty phenotype is a commonly used tool to study frailty. Two characteristics evaluated as part of the frailty phenotype are “low” grip strength and “low” physical activity, defined by the lowest quintile thresholds for age and sex. In studies of frailty in different geographic regions of the world, it is not established whether these thresholds should be applied universally or whether region-specific thresholds of grip strength and physical activity should be applied. This study aims to determine which way of defining frailty is more appropriate. Methods: Using data from the Prospective Urban Rural Epidemiology study, two variations of the frailty phenotype were defined: universal frailty in which thresholds for low grip strength and physical activity were taken to be the lowest quintile of the entire study population and region-specific frailty, in which these thresholds were calculated separately for each region. Frailty prevalence was calculated for each definition and Cox proportional hazards modelling was used to determine which definitions predicted mortality. Likelihood ratio tests statistics, area under the receiver operating characteristics curve, and the net reclassification improvement index were also calculated. Results: Overall frailty prevalence was 5.6% using universal definitions of frailty and 5.8% for region-specific definitions of frailty. Across regions, universal frailty prevalence ranged from 2.4% (North America/Europe) to 20.1% (Africa), while region-specific frailty ranged from 4.1% (Russia and Central Asia) to 8.8% (Middle East). The hazards ratios for all-cause mortality were 2.66 (95% CI: 2.47-2.86) and 2.09 (95% CI: 1.94-2.26) for universal frailty and region-specific frailty respectively (adjusted for age, sex, education, smoking status and alcohol consumption); statistical tests indicated that universal frailty better fit survival data and predicted mortality slightly better. Conclusions: Frailty prevalence varies greatly across regions depending on how the thresholds for low physical activity and grip strength are calculated. Using region-specific thresholds does not help improve the predictive value of frailty when measuring frailty in heterogenous populations using the frailty phenotype. / Thesis / Master of Science (MSc)

No description available.

BACKGROUND. Frailty is a syndrome characterized by a decreased resistance to stressors, leading to increased vulnerability to adverse outcomes, including mortality. Multi-morbidity refers to the presence of two or more chronic diseases, and is associated with increased risk of adverse health outcomes. Most of the literature in frailty is based on older people (65+ years) living in high income countries. OBJECTIVE. To compare the predictive ability of three frailty indices for all-cause and one-year mortality among high- (HIC), middle- (MIC), and low- income country (LIC) participants; and to assess the mortality risk associated with multi-morbidity. METHODS. Using data from the Prospective Urban and Rural Epidemiological (PURE) study, we developed three indices using different definitions of frailty (one phenotypic frailty index; two cumulative deficit indices). All indices were tested for predictive ability for mortality both individually and with multi-morbidity. RESULTS. Prevalence of phenotypic frailty was greatest in LIC (8%), intermediate in MIC (7%), and lowest in HIC (4%). Multi-morbidity was most prevalent in HIC (20%), intermediate in MIC (15%), and lowest in LIC (13%). Increased frailty was associated with greater mortality risk using all frailty indices (e.g. HR (95% CI) of 2.63 (2.35-2.95) for the phenotypically frail relative to the robust). At each frailty level, mortality risk was higher within one year of baseline measurement than afterwards, and increased if it was accompanied by concurrent multi-morbidity (e.g. HR of phenotypic frailty increases from 2.27 (1.96-2.62) to 5.08 (4.34-5.95) if accompanied by multi-morbidity). CONCLUSION. All frailty indices predicted mortality. This study is unique in evaluating the prognostic ability of frailty indices in middle-aged adults across HIC, MIC, and LICs. / Thesis / Master of Science (MSc)

This work demonstrates an application of Vibration-Based Occupant Inference (VBOI) in frailty analysis. The rise of both Internet-of-Things (IoT) and VBOI provide new techniques to perform gait analysis via footstep-induced vibration which can be analyzed for early detection of human frailty. Thus, this work provides an application of VBOI to passively track gait parameters (e.g., gait speed) using floor-mounted accelerometers as opposed to using a manual chronometer as it is commonly performed by healthcare professionals. The first part of this thesis describes the techniques used for footstep detection by measuring the power of the footstep-generated vibration waves. The extraction of temporal gait parameters from consecutive footsteps can then be used to estimate temporal features such as cadence and stride time variation. VBOI provides many algorithms to accurately detect when a human-induced vibration event happened, however, spatial information is also needed for many gait parameters used in frailty diagnosis. Detecting where an event happened is a complicated problem because footsteps waves travel and decay in different ways according to the medium (floor system), the number of people walking, and even the walking speed. Therefore, the second part of this work will utilize an energy-based approach of footstep localization in which it is assumed that footstep waves decay exponentially as they travel across the medium. The results from this approach are then used to calculate spatial and tempo-spatial parameters. The main goal of this study is to understand the applicability of VBOI algorithms in gait analysis for frailty detection in a healthcare setting. / Master of Science / Human frailty is responsible for one of the highest healthcare costs and the death of many people every year. Although anyone suffering from frailty has a higher chance of death, it is particularly dangerous for the elderly population and for those suffering from other comorbidities. Diagnosing frailty is hard because it usually happens slowly over time. However, it has been shown that changes in some walking parameters (such as gait speed) can be an early indication of frailty. Many technologies have been created in order to track gait parameters, many of which either require expensive equipment (e.g., force plates) or the use of wearable devices, which can introduce privacy concerns. It has been proposed in the literature that Vibration-Based Occupant Inference (VBOI) techniques could be used in healthcare applications. Such algorithms measure footstep-induced vibration waves in order to detect and track footsteps. This system can provide several advantages in frailty analysis because of its affordability, ease of use, and little impact on patients' privacy. Therefore, the aim of this study is to understand the applicability of VBOI algorithms in gait analysis for frailty detection to be used in a healthcare setting. This thesis will proceed as follows: 1- The demonstration of an energy-based footstep detection and localization algorithm in VBOI. 2 - The application of such algorithms for gait parameters extraction with simulated frail walkers. 3 - Finally, an analysis of the proposed VBOI techniques for deployment in a real hospital setting.

Yes / Background: In older people living with frailty, polypharmacy can lead to preventable harm like adverse drug reactions and hospitalisation. Deprescribing is a strategy to reduce problematic polypharmacy. All stakeholders should be actively involved in developing a person-centred deprescribing process that involves shared decision-making. Objective: To co-design an intervention, supported by a logic model, to increase the engagement of older people living with frailty in the process of deprescribing. Design: Experience-based co-design is an approach to service improvement, which uses service users and providers to identify problems and design solutions. This was used to create a person-centred intervention with the potential to improve the quality and outcomes of the deprescribing process. A ‘trigger film’ showing older people talking about their healthcare experiences was created and facilitated discussions about current problems in the deprescribing process. Problems were then prioritised and appropriate solutions were developed. Review located the solutions in the context of current processes and procedures. An ideal care pathway and a complex intervention to deliver better care were developed. Setting and participants: Older people living with frailty, their informal carers and professionals living and/or working in West Yorkshire, England, UK. Deprescribing was considered in the context of primary care. Results: The current deprescribing process differed from an ideal pathway. A complex intervention containing seven elements was required to move towards the ideal pathway. Three of these elements were prototyped and four still need development. The complex intervention responded to priorities about (a) clarity for older people about what was happening at all stages in the deprescribing process and (b) the quality of one-to-one consultations. Conclusions: Priorities for improving the current deprescribing process were successfully identified. Solutions were developed and structured as a complex intervention. Further work is underway to (a) complete the prototyping of the intervention and (b) conduct feasibility testing. / National Institute for Health and Care Research (NIHR) Yorkshire and Humber Patient Safety Translational Research Centre (NIHR Yorkshire and Humber PSTRC)