Towards a consensus definition of allostatic load: a multi-cohort, multi-system, multi-biomarker individual participant data (IPD) meta-analysis.

BACKGROUND: Allostatic load (AL) is a multi-system composite index for quantifying physiological dysregulation caused by life course stressors. For over 30 years, an extensive body of research has drawn on the AL framework but has been hampered by the lack of a consistent definition. METHODS: This study analyses data for 67,126 individuals aged 40-111 years participating in 13 different cohort studies and 40 biomarkers across 12 physiological systems: hypothalamic-pituitary-adrenal (HPA) axis, sympathetic-adrenal-medullary (SAM) axis, parasympathetic nervous system functioning, oxidative stress, immunological/inflammatory, cardiovascular, respiratory, lipidemia, anthropometric, glucose metabolism, kidney, and liver. We use individual-participant-data meta-analysis and exploit natural heterogeneity in the number and type of biomarkers that have been used across studies, but a common set of health outcomes (grip strength, walking speed, and self-rated health), to determine the optimal configuration of parameters to define the concept. RESULTS: There was at least one biomarker within 9/12 physiological systems that was reliably and consistently associated in the hypothesised direction with the three health outcomes in the meta-analysis of these cohorts: dehydroepiandrosterone sulfate (DHEAS), low frequency-heart rate variability (LF-HRV), C-reactive protein (CRP), resting heart rate (RHR), peak expiratory flow (PEF), high density lipoprotein cholesterol (HDL-C), waist-to-height ratio (WtHR), HbA1c, and cystatin C. An index based on five biomarkers (CRP, RHR, HDL-C, WtHR and HbA1c) available in every study was found to predict an independent outcome - mortality - as well or better than more elaborate sets of biomarkers. DISCUSSION: This study has identified a brief 5-item measure of AL that arguably represents a universal and efficient set of biomarkers for capturing physiological 'wear and tear' and a further biomarker (PEF) that could usefully be included in future data collection.

Intergenerational Social Mobility and Allostatic Load in Midlife and Older Ages: A Diagonal Reference Modeling Approach.

OBJECTIVES: This study aims to understand the association of life-course intergenerational social mobility with allostatic load (AL) burden in midlife and older ages in Ireland. METHODS: The study involved biological data for 3,987 older adults participating in The Irish Longitudinal Study on Ageing (TILDA). Intergenerational social mobility was characterized using the cross-classification of origin socioeconomic position (SEP; i.e., father's occupation) and destination SEP (i.e., own occupation). AL was operationalized using 12 biomarkers tapping cardiovascular, metabolic, renal, and immune system dysregulation. Diagonal reference modeling (DRM) and ordinary least square regression techniques were applied to explore the effect of social mobility on AL burden. RESULTS: A total of 55.5% experienced intergenerational mobility: 37.5% were upwardly mobile, 18.0% were downwardly mobile. A social gradient in AL was observed among the socially non-mobile. Destination SEP (b = 0.74, 95% CI = 0.57, 0.92) predominated in influence over origin, although both life stages exerted significant influence on later-life AL. Social mobility in either direction was not associated with AL burden. Mobility coefficients were substantially small across a large variety of model specifications. DISCUSSION: Findings provide evidence for an accumulation model of social inequalities in which disparities in health are diluted rather than increased by social mobility (i.e., gradient constraint), with the socially mobile having an AL score that is intermediate between their origin class and destination class. This implies that the effects of origin SEP on health are not immutable, but are instead responsive to changing socioeconomic circumstances across the life course.

Psychosocial adversity and allostatic load burden in midlife and older ages.

OBJECTIVE: To investigate the individual and cumulative impact of childhood and adulthood adversity on allostatic load (AL) burden. METHOD: Retrospective cross-sectional study design involving 4,165 participants from the first wave of The Irish Longitudinal study on Ageing (TILDA). AL was operationalized using 12 biomarkers across four physiological systems (cardiovascular, metabolic, renal, and immune). Measures of psychosocial adversity included poverty, abuse, loss, and illness. Negative binomial regression models estimated the relationship of individual adversities and a cumulative count of adversities with AL burden, controlling for age and sex. Multivariable models adjusted additionally for a range of other sociodemographic and lifestyle factors. RESULTS: Childhood poverty, childhood physical abuse, and having a spouse/partner/child experience a life-threatening illness/accident were associated with 10% (95% CI [1.04, 1,16]), 10% (95% CI [1.01, 1.18]), and 6% (95% CI [1.01, 1.11]) greater AL burden, respectively. Cumulative adversity was associated with 3% (95% CI [1.01, 1.04]) higher AL burden. Adjusting for sociodemographic and lifestyle covariates rendered the association of childhood poverty (IRR= 1.04, 95% CI [.98, 1.09]; p = .190) and childhood physical abuse (IRR= 1.07, 95% CI [.99, 1.15]; p = .081) with AL burden nonsignificant, while the association of having an ill spouse/partner/child on AL persisted (IRR= 1.06, 95% CI [1.01, 1.11]; p = .021). CONCLUSIONS: This study provided limited support for the idea that psychosocial stress leads to higher AL, with just three out of 11 adversities associated with AL. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Does the choice of Allostatic Load scoring algorithm matter for predicting age-related health outcomes?

Allostatic Load (AL) is posited to provide a measure of cumulative physiological dysregulation across multiple biological systems and demonstrates promise as a sub-clinical marker of overall health. Despite the large heterogeneity of measures employed in the literature to represent AL, few studies have investigated the impact of different AL scoring systems in predicting health. This study uses data for 4477 participants aged 50+ years participating in the Irish Longitudinal Study on Ageing (TILDA) to compare the utility of 14 different scoring algorithms that have been used to operationalise AL (i.e. count-based high-risk quartiles, deciles, two-tailed cut-points, z-scores, system-weighted indices, clinical cut-points, sex-specific scores, and incorporating medication usage). Model fit was assessed using R2, Bayesian Information Criterion (BIC), and the area under the Receiver Operating Characteristic curve (AUC). The measure incorporating medications predicted walking speed and SRH marginally better than others. In general, AL was not predictive of grip strength. Overall, the results suggest that the choice of AL scoring algorithm exerts a relatively modest influence in predicting a number of important health outcomes.

Epigenetic Clocks and Allostatic Load Reveal Potential Sex-Specific Drivers of Biological Aging.

Allostatic load (AL) and epigenetic clocks both attempt to characterize the accelerated aging of biological systems, but at present it is unclear whether these measures are complementary or distinct. This study examines the cross-sectional association of AL with epigenetic age acceleration (EAA) in a subsample of 490 community-dwelling older adults participating in The Irish Longitudinal study on Aging (TILDA). A battery of 14 biomarkers representing the activity of four different physiological systems: immunological, cardiovascular, metabolic, renal, was used to construct the AL score. DNA methylation age was computed according to the algorithms described by Horvath, Hannum, and Levine allowing for estimation of whether an individual is experiencing accelerated or decelerated aging. Horvath, Hannum, and Levine EAA correlated 0.05, 0.03, and 0.21 with AL, respectively. Disaggregation by sex revealed that AL was more strongly associated with EAA in men compared with women as assessed using Horvath's clock. Metabolic dysregulation was a strong driver of EAA in men as assessed using Horvath and Levine's clock, while metabolic and cardiovascular dysregulation were associated with EAA in women using Levine's clock. Results indicate that AL and the epigenetic clocks are measuring different age-related variance and implicate sex-specific drivers of biological aging.