Physiological Dysregulation Predicted Poorer Health and Lower Survival in a Survey of the Older Population (original) (raw)
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Physiological dysregulation and changes in health in an older population
Experimental Gerontology, 2006
We investigate whether a multi-system measure of physiological dysregulation based on 16 biological measures is associated with deterioration in physical and mental health over a 3-year period. The data come from a national survey of persons 54 and older in Taiwan that collected standard clinical markers related to cardiovascular and metabolic function and ''non-clinical'' measures pertaining to the immune, neuroendocrine and sympathetic nervous systems. The dysregulation score counts the number of biomarkers for which values are in the lowest or highest decile. Statistical models examine whether dysregulation predicts four health outcomes (survival, physical functioning, cognitive functioning and depressive symptoms), in the presence of extensive controls for baseline health. The estimates reveal significant associations between dysregulation and health for each outcome, although there is variability across outcomes. The associations are often attenuated in the presence of health controls, underscoring the importance of longitudinal analysis. This study extends previous research on the health consequences of physiological dysregulation by considering a broader range of outcomes and biomarkers in a non-Western population-based sample. Our analysis suggests that such dysregulation provides early warning signs of a broad range of comorbidities.
Physiological Dysregulation, Frailty, and Impacts on Adverse Health and Functional Outcomes
Frontiers in Medicine, 2021
Background: Multi-system physiological dysregulation (PD) may represent a biological endo-phenotype of clinical frailty. We investigated the co-occurrence of PD with physical frailty and its contributions to the known impact of frailty on adverse health outcomes.Methods: Data of 2,725 participants from the Singapore Longitudinal Aging Studies (SLAS-2), included baseline measures of physical frailty and PD derived from Mahalanobis distance (Dm) value of 23 blood biomarkers. We analyzed their concurrent association and their impacts on 9-year mortality, MMSE cognition, GDS depression, number of medications, disability, and hospitalization at baseline and follow up (mean 4.5 years).Results: Global PD (Log10Dm, mean = 1.24, SD = 0.24) was significantly but weakly associated with pre-frailty-and-frailty. Controlling for age, sex and education, pre-frailty-and-frailty (HR = 2.12, 95% CI = 1.51–3.00) and PD (HR = 3.88, 95% CI = 2.15–6.98) predicted mortality. Together in the same model, mo...
Frontiers in Public Health, 2016
While longitudinal changes in biomarker levels and their impact on health have been characterized for individual markers, little is known about how overall marker profiles may change during aging and affect mortality risk. We implemented the recently developed measure of physiological dysregulation based on the statistical distance of biomarker profiles in the framework of the stochastic process model of aging, using data on blood pressure, heart rate, cholesterol, glucose, hematocrit, body mass index, and mortality in the Framingham original cohort. This allowed us to evaluate how physiological dysregulation is related to different aging-related characteristics such as decline in stress resistance and adaptive capacity (which typically are not observed in the data and thus can be analyzed only indirectly), and, ultimately, to estimate how such dynamic relationships increase mortality risk with age. We found that physiological dysregulation increases with age; that increased dysregulation is associated with increased mortality, and increasingly so with age; and that, in most but not all cases, there is a decreasing ability to return quickly to baseline physiological state with age. We also revealed substantial sex differences in these processes, with women becoming dysregulated more quickly but with men showing a much greater sensitivity to dysregulation in terms of mortality risk.
The journals of gerontology. Series A, Biological sciences and medical sciences, 2018
Recently suggested novel implementation of the statistical distance measure (DM) for evaluating "physiological dysregulation" (PD) in aging individuals (based on measuring deviations of multiple biomarkers from baseline/normal physiological states) allows reducing high-dimensional biomarker space into a single PD estimate. Here we constructed DM using biomarker profiles from FRAMCOHORT (Framingham Heart Study) and CHS (Cardiovascular Health Study) Research Materials obtained from the NHLBI Biologic Specimen and Data Repository Information Coordinating Center, and estimated effect of PD on total survival, onset of unhealthy life (proxy for "robustness") and survival following the onset of unhealthy life (proxy for "resilience"). We investigated relationships between PD and declines in stress resistance and adaptive capacity not directly observed in data. PD was more strongly associated with the onset of unhealthy life than with survival after disease sug...
Mechanisms of Ageing and Development, 2013
Previous studies have identified many biomarkers that are associated with aging and related outcomes, but the relevance of these markers for underlying processes and their relationship to hypothesized systemic dysregulation is not clear. We address this gap by presenting a novel method for measuring dysregulation via the joint distribution of multiple biomarkers and assessing associations of dysregulation with age and mortality. Using longitudinal data from the Women's Health and Aging Study, we selected a 14-marker subset from 63 blood measures: those that diverged from the baseline population mean with age. For the 14 markers and all combinatorial sub-subsets we calculated a multivariate distance called the Mahalanobis distance (MHBD) for all observations, indicating how ''strange'' each individual's biomarker profile was relative to the baseline population mean. In most models, MHBD correlated positively with age, MHBD increased within individuals over time, and higher MHBD predicted higher risk of subsequent mortality. Predictive power increased as more variables were incorporated into the calculation of MHBD. Biomarkers from multiple systems were implicated. These results support hypotheses of simultaneous dysregulation in multiple systems and confirm the need for longitudinal, multivariate approaches to understanding biomarkers in aging. ß
Associations between chronic disease, age and physical and mental health status
Chronic Diseases in Canada, 2009
This paper examines the associations between chronic disease, age, and physical and mental health-related quality of life (HRQOL), using data collected in 10 studies representing five chronic conditions. HRQOL was measured using the SF-36 or the shorter subset, SF-12. Physical Component Summary (PCS) and Mental Component Summary (MCS) scores were graphed by condition in age increments of 10 years, and compared to age-and sex-adjusted normative data. Linear regression models for the PCS and MCS were controlled for available confounders. The sample size of 2418 participants included 129 with renal failure, 366 with osteoarthritis (OA), 487 with heart failure, 1160 with chronic wound (leg ulcer) and 276 with multiple sclerosis (MS). For the PCS, there were large differences between the normative data and the mean scores of those with chronic diseases, but small differences for the MCS. Female gender and comorbid conditions were associated with poorer HRQOL; increased age was associated with poorer PCS and better MCS. This study provided additional evidence that, while physical function could be severely and negatively affected by both chronic disease and advanced age, mental health remained relatively high and stable.
Cumulative Deficits and Physiological Indices as Predictors of Mortality and Long Life
2008
We evaluated the predictive potential for long-term (24-year) survival and longevity (85þ years) of an index of cumulative deficits (DI) and six physiological indices (pulse pressure, diastolic blood pressure, pulse rate, serum cholesterol, blood glucose, and hematocrit) measured in mid-to late life (44-88 years) for participants of the 9th and 14th Framingham Heart Study examinations. For all ages combined, the DI, pulse pressure, and blood glucose are the strongest determinants of both long-term survival and longevity, contributing cumulatively to their explanation. Diastolic blood pressure and hematocrit are less significant determinants of both of these outcomes. The pulse rate is more relevant to survival, whereas serum cholesterol is more relevant to longevity. Only the DI is a significant predictor of longevity and mortality for each 5-year age group ranging from 45 to 85 years. The DI appears to be a more important determinant of long-term risks of death and longevity than are the physiological indices.
BMC Medical Research Methodology, 2010
Background: Although aging is accompanied by diminished functioning, many elderly individuals preserve a sense of well-being. While the concept of "successful aging" has been popular for many decades, little is known about its psycho-physiologic and endocrine underpinnings. KORA-Age is a population-based, longitudinal study designed to determine the prevalence of successfully aged men and women between 65 and 94 years old in the MONICA/KORA Augsburg cohort of randomly selected inhabitants. Specifically, we aim to identify predictors of successful aging and to elucidate bio-psychosocial mechanisms that maintain mental health and successful adaptation despite adverse experiences of life and aging.
International Journal of Environmental Research and Public Health
Depression and related syndromes are well identified in older adults. Depression has been reported to increase the incidence of a multitude of somatic disorders. In older adults, the severity of depression is associated with higher mortality rates. The aim of the study is to examine whether the effect of depression screening on mortality is different between individuals with different physical health status. In order to meet this aim, we will first reprove the relationship between depression and mortality rate, and then we will set a subgroup analysis by using self-reported health (SRH) status. Our data source, Taiwan Longitudinal Study on Aging (TLSA), is a population-based prospective cohort study that was initiated by the Health Promotion Administration, Ministry of Health and Welfare, Taiwan. The depression risk was evaluated by 10-items Center for Epidemiologic Studies Depression (CES-D-10), we set 3 CES-D-10 cutting points (5, 10, and 12) and cut our subjects into four groups....