Carol H. Gold

Health-related quality of life among older adults with arthritis

BackgroundHealth-related quality of life (HRQOL) is a key outcome in arthritis, but few population-based studies have examined the relationship of specific arthritic conditions, such as osteoarthritis (OA) and rheumatoid arthritis (RA) with HRQOL.MethodsOlder adults in Pennsylvania completed a mail version of the Centers for Disease Control and Prevention (CDC) HRQOL modules. Medicare data were used to identify subjects with OA, RA, and no arthritis diagnosis. We compared HRQOL responses among these groups, and we also examined relationships of demographic characteristics to HRQOL among subjects with arthritis.ResultsIn analyses controlling for demographic characteristics and comorbidity, subjects with OA and RA had poorer scores than those without arthritis on all HRQOL items, including general health, physical health, mental health, activity limitation, pain, sleep, and feeling healthy and full of energy. HRQOL scores were also lower for those with RA compared to OA. Among individuals with arthritis, all subject characteristics (including age, race, sex, nursing home residence, marital status, income, and comorbid illnesses) were significantly related to at least one HRQOL item. Older age, nursing home residence, and greater comorbidity were the most consistently associated with poorer HRQOL.ConclusionsResults of this study show that both OA and RA have a significant impact on multiple dimensions of HRQOL among older adults. Results also suggest the CDC HRQOL items are suitable for use among older adults and in mail surveys. Due to the rising number of older adults in many countries, the public health burden of arthritis is expected to increase dramatically. Efforts are needed to enhance access to medical care and disseminate self-management interventions for arthritis.

Personalized State-space Modeling of Glucose Dynamics for Type 1 Diabetes Using Continuously Monitored Glucose, Insulin Dose, and Meal Intake: An Extended Kalman Filter Approach

Background: An essential component of any artificial pancreas is on the prediction of blood glucose levels as a function of exogenous and endogenous perturbations such as insulin dose, meal intake, and physical activity and emotional tone under natural living conditions. Methods: In this article, we present a new data-driven state-space dynamic model with time-varying coefficients that are used to explicitly quantify the time-varying patient-specific effects of insulin dose and meal intake on blood glucose fluctuations. Using the 3-variate time series of glucose level, insulin dose, and meal intake of an individual type 1 diabetic subject, we apply an extended Kalman filter (EKF) to estimate time-varying coefficients of the patient-specific state-space model. We evaluate our empirical modeling using (1) the FDA-approved UVa/Padova simulator with 30 virtual patients and (2) clinical data of 5 type 1 diabetic patients under natural living conditions. Conclusion: Compared to a forgetting-factor-based recursive ARX model of the same order, the EKF model predictions have higher fit, and significantly better temporal gain and J index and thus are superior in early detection of upward and downward trends in glucose. The EKF based state-space model developed in this article is particularly suitable for model-based state-feedback control designs since the Kalman filter estimates the state variable of the glucose dynamics based on the measured glucose time series. In addition, since the model parameters are estimated in real time, this model is also suitable for adaptive control.

Gender differences in depression: a study of older unlike-sex twins.

Gender differences in depressive symptoms, in the diagnosis of major/minor depression, and in the use of antidepressant medication were investigated. The sample included 249 pairs of unlike-sex twins, who were between 70 and 80 years of age at the initial, baseline assessment. A follow-up, in which both members of 145 twin pairs participated, was carried out four years later. Participants completed the Centre for the Epidemiologic Studies Depression Scale (CES-D) for depressive symptoms. Current use of antidepressant medicine was assessed. Medical records of major/minor depression from the period 1985–1998, including a summary of those diagnoses in earlier years, were gathered from several sources. Women had a higher frequency of depressive symptoms and depression diagnoses than their twin brothers. Depressive symptoms and diagnosis of depression increased over time, slightly more among men. The gender difference and increase over time in the depressive symptoms were related to differences in socio-economic status and physical functioning in men and women. No gender difference was found in the use of antidepressant medication.

Depressed Mood but Not Fatigue Mediate the Relationship between Physical Activity and Perceived Stress in Middle-Aged Women

OBJECTIVE To determine whether depressed mood and fatigue mediate the relationships between physical activity, body mass index, menopausal hot flashes, and perceived stress. METHOD This study is a secondary analysis of data obtained from a sub-sample of peri- and postmenopausal women (N=212) from the TREMIN Research Program on Womens Health. RESULTS The hypothesized mediational model was tested using path analysis within a structural equation modeling framework in Mplus Version 5.1. In unadjusted analysis, the relationships between physical activity, menopausal hot flashes, and perceived stress were mediated by depressed mood; fatigue mediated the relationships between hot flashes, body mass index, and perceived stress. When adjusting for age, insomnia, menopausal and hormone use status, the mediational effects of depressed mood on stress remained significant only for physical activity, and fatigue mediated the relationship between hot flashes and stress. The adjusted model explained 70% of variance in perceived stress, 82% of variance in depressed mood, and 81% of variance in fatigue. CONCLUSION Depressed mood may partially explain the relationship between physical activity and perceived stress in middle-aged women, however further studies are needed to corroborate causality.

The role of medication use and health on the decision to quit drinking among older adults.

Objectives: To determine the extent to which changes in medication use and health influence the decision to quit drinking among older adults. Method: The sample consisted of 8,883 elderly enrolled in Pennsylvanias Pharmaceutical Assistance Contract for the Elderly (PA-PACE) program who completed surveys in 2000 and 2002. Survey data were linked with prescription claims to examine medication and health factors associated with drinking cessation between baseline and follow-up. Results: Overall, 3.9% of those using alcohol at baseline quit drinking during the study period. Logistic regression results showed that individuals who initiated antipsychotic (OR = 2.92) and antineoplastic therapies (OR = 2.67) were the most likely to quit drinking. Discussion: These findings support the hypothesis that elderly quit drinking in response to ill health. Results have implications for alcohol interventions in older adults and underscore the importance of separating former drinkers from lifetime abstainers in the study of alcohol-health relationships.

Daily physical activity and menopausal hot flashes: Applying a novel within-person approach to demonstrate individual differences

BACKGROUND Physical activity (PA) may be a useful tool in the management of menopausal hot flashes (HFs) but findings are generally inconsistent. There are few well-designed and sufficiently powered RCTs. Applying a longitudinal within-person approach offers an alternative way to examine the PA-HFs relationship which enables complete accommodation of inter-individual differences. OBJECTIVES Aprospective daily diary study which applied experience sampling methods and time series modeling techniques investigated, at the within-person level, the relationship between objectively measured daily PA of varying intensities and self-reported menopausal HFs. METHODS Twenty-four symptomatic middle-aged women (M age=50.4; SD=4.9) completed fitness, body composition and hormonal status screening, and reported on daily HFs using an electronic PDA device across one menstrual cycle or for 30 days (if postmenopausal). Daily PA and PA intensity was measured using accelerometry and subjects completed a battery of psychological measures. RESULTS Within person analysis identified significant relations between PA and HFs in 50% of subjects, although the specific PA indicators that predicted HFs varied, both in terms of direction and magnitude. Perceived control over HFs was the variable that most consistently differentiated between women for whom more PA was associated with fewer HFs as compared to those for whom more PA was associated with more HFs, but other individual difference characteristics such as affect, depressive symptoms, and anxiety were identified. CONCLUSIONS There is great individual variation in the way daily PA impacts self-reported HFs. Affective outcomes and perceived control may help potentially explain this variability.

Behavioral correlates of depressive symptoms in older unlike-sex twin pairs

Background and aimsThis study examines gender-specific behavioral correlates of depressive symptoms using a secondary data analysis of a cross-sectional, population-based sample of older unlike-sex twins.MethodsUnlike-sex twins aged 69–88 were identified through a national Swedish registry and sent a survey about health, including depressive symptoms (CES-D) and the frequency of engaging in physical, social and mental activities. A total of 605 complete twin pairs responded.ResultsDepressive symptom scores were associated with frequency of engagement in physical and mental activities, but only in men. No statistically significant associations with depressive symptom scores for any of the three types of activities were found in women.ConclusionsThe results suggest that engaging in physical and mental activities may protect older men from developing depressive symptoms, but longitudinal data are needed to offer more conclusive findings on the role that physical, mental, and social activities play in the maintenance of psychological health in older men and women.

Development of an Adaptive Dual Controller for Glucose Management in Patients With Insulin-Deficient Diabetes

In this paper, we propose and design an adaptive dual controller for automatic glucose control of diabetic patients. The results could be used in the development of an artificial pancreas, which, while as yet unavailable, must consist of three major components: an insulin delivery device or “pump”, a continuous glucose sensor, and a control algorithm linking insulin delivery to measured glucose concentration. For improved performance the system would also include “feed-forward” information about food intake, physical activity and other blood glucose perturbing inputs. A linear time-varying autoregressive model with exogenous inputs is constructed to characterize the kinetics of both glucose-insulin and glucose-carbohydrate interaction. Combined with a Kalman-filter based estimation scheme for online estimation of the time-varying model coefficients, we design an adaptive dual control that both excites the glucose dynamic system sufficiently to accelerate the parameter estimation and cautiously tracks the desired glucose level. Performance evaluation of the adaptive dual controller is accomplished via simulations on virtual patients constructed using clinical data from five different patients with type-1 insulin-deficient diabetes using continuous subcutaneous insulin infusion for diabetes management during observation. Simulation results show both smaller glucose excursions and a reduction in the number of hypoglycemic events for all but one of the five subjects.Copyright

Receding Horizon Control of type I diabetes based on a data-driven linear time-varying state-space model

In this paper, we consider the problem of blood glucose control for type 1 diabetic patients. In particular, we focus on developing control algorithms for an Artificial Pancreas which is a portable or implantable automated insulin delivery system composed of a continuous glucose monitor, an insulin pump, and a control law that links the measured blood glucose concentration and insulin delivery. We have designed Receding Horizon Control (RHC) (which is also known as the Model Predictive Control) for two specific patients, respectively, based on a data-driven linear time-varying state-space model developed in for each patient using clinical data. The control parameters are tuned specifically for each patient. For patient 1, the RHC algorithm performs well with no information (e.g., amount and time) of meal intake, which results in the so-called feedback alone control. For patient 2, information of meal intake is necessary for the RHC algorithm to reach acceptable closed-loop performance, which results in the so-called feedback plus feedforward control. For both patients, we evaluate the performance of the RHC designs via simulation and compare the simulation results with clinical data. We also test the robustness of the RHC design with respect to estimation errors in the amount of carbohydrate content (CHO) of the meal.