Allostatic load and stress biomarkers in a sample of community-dwelling older adults

Allostatic Load, Morbidity, and Mortality Among Older Adults: A Multi-Wave Analysis From the National Health and Aging Trends Study

Although allostatic load (AL) is a key concept to reflect physiologic wear and tear from stress, older adults are underrepresented in AL-related research, especially the oldest old (≥80). Further, attenuative factors are often unaccounted for. This longitudinal analysis using data from National Health and Aging Trends Study investigated relationships of AL in 2017 and multi-wave (1) comorbidity accumulation using multilevel Poisson modeling and (2) mortality risk using survival analysis. By year five (2022), each incremental AL increase that older adults (n = 3614) experienced was associated with a 47% increase in comorbidity (p < .001), and a 33% increased mortality risk (p < .001). This research supports a shift to a more proactive, health promotion/risk mitigation paradigm through informing intervention research targeting AL, which is currently scarce. Identifying potentially modifiable and key driving factors influencing the relationship between AL and health among older adults is an important next step to inform intervention design.

Elucidating individual differences in chronic pain and whole person health with allostatic load biomarkers

Chronic pain is a stressor that affects whole person functioning. Persistent and prolonged activation of the body's stress systems without adequate recovery can result in measurable physiological and neurobiological dysregulation recognized as allostatic load. We and others have shown chronic pain is associated with measures of allostatic load including clinical biomarker composites, telomere length, and brain structures. Less is known regarding how different measures of allostatic load align. The purpose of the study was to evaluate relationships among two measures of allostatic load: a clinical composite and pain-related brain structures, pain, function, and socioenvironmental measures. Participants were non-Hispanic black and non-Hispanic white community-dwelling adults between 45 and 85 years old with knee pain. Data were from a brain MRI, questionnaires specific to pain, physical and psychosocial function, and a blood draw. Individuals with all measures for the clinical composite were included in the analysis (n = 175). Indicating higher allostatic load, higher levels of the clinical composite were associated with thinner insula cortices with trends for thinner inferior temporal lobes and dorsolateral prefrontal cortices (DLPFC). Higher allostatic load as measured by the clinical composite was associated with greater knee osteoarthritis pathology, pain disability, and lower physical function. Lower allostatic load as indicated by thicker insula cortices was associated with higher income and education, and greater physical functioning. Thicker insula and DLPFC were associated with a lower chronic pain stage. Multiple linear regression models with pain and socioenvironmental measures as the predictors were significant for the clinical composite, insular, and inferior temporal lobes. We replicate our previously reported bilateral temporal lobe group difference pattern and show that individuals with high chronic pain stage and greater socioenvironmental risk have a higher allostatic load as measured by the clinical composite compared to those individuals with high chronic pain stage and greater socioenvironmental buffers. Although brain structure differences are shown in individuals with chronic pain, brain MRIs are not yet clinically applicable. Our findings suggest that a clinical composite measure of allostatic load may help identify individuals with chronic pain who have biological vulnerabilities which increase the risk for poor health outcomes.

Associations of Socioeconomic Factors and Unhealthy Lifestyles with Allostatic Load: A Meta-analysis

BACKGROUND

Allostatic load (AL) is a biological tool for objectively assessing chronic stress and has been discussed inconsistently for its correlation with socioeconomic factors and unhealthy lifestyles. Therefore, this meta-analysis was performed to explore the impact of socioeconomic factors and unhealthy lifestyles on AL.

METHOD

Different databases, including Web of Science, PubMed, EBSCOhost, Embase, CNKI, VIP, SinoMed, and Wanfang, were searched from inception to June 6, 2023. A total of 25 studies, reporting the correlations of seven socioeconomic factors and three unhealthy lifestyles with AL, were finally included. The pooled odds ratios (OR) and 95% confidence intervals (CIs) were examined using random-effect and fixed-effect models. Literature quality, heterogeneity, and publication bias were evaluated.

RESULTS

The meta-analysis showed a significantly increased risk of high AL in the older individuals as compared to the younger ones (OR = 1.05, 95% CI 1.04-1.06), in the individual with low education as compared to those with high education (OR = 1.25, 95% CI 1.05-1.48), and in the individuals with low physical activities as compared to those with high physical activities (OR = 1.44, 95% CI 1.26-1.64). This meta-analysis also showed a significantly decreased risk of high AL in the individuals with high income as compared to those with low income (OR = 0.77, 95% CI 0.71-0.83) and in women as compared to men (OR = 0.80, 95% CI 0.80-0.81).

CONCLUSION

This meta-analysis showed older people, men, and people having low physical activity, low income, and low education were more likely to have a high AL.

TRIAL REGISTRATION

This meta-analysis was registered on the PROSPERO database with trial registration number CRD42022326105. Instead of providing information at registration, we added an author (Tingyu Mu), who provided critical revisions to the paper in this meta-analysis.

Psychosocial stress and neuroendocrine biomarker concentrations among women living with or without HIV

OBJECTIVE

Women living with HIV (WLWH) experience psychosocial stress related to social-structural vulnerabilities. To investigate neuroendocrine pathways linking stress and increased cardiovascular disease risk among WLWH, we evaluated associations between psychosocial stress (i.e., perceived stress, posttraumatic stress, and experiences of race- and gender-based harassment) and a composite neuroendocrine biomarker index among WLWH and women without HIV.

METHODS

In 2019-2020, Women's Interagency HIV Study participants in Washington, DC completed a questionnaire and provided blood and 12-hour overnight urine samples for testing of serum dehydroepiandrosterone sulfate (DHEA-S) and urinary free cortisol, epinephrine, and norepinephrine. Psychosocial stress was measured using the Perceived Stress Scale, PTSD Checklist-Civilian Version, and Racialized Sexual Harassment Scale. Latent profile analysis was used to classify participants into low (38%), moderate (44%), and high (18%) stress groups. Composite biomarker index scores between 0-4 were assigned based on participants' number of neuroendocrine biomarkers in high-risk quartiles (≥75th percentile for cortisol, epinephrine, and norepinephrine and ≤25th percentile for DHEA-S). We evaluated associations between latent profile and composite biomarker index values using multivariable linear regression, adjusting for socio-demographic, behavioral, metabolic, and HIV-related factors.

RESULTS

Among 90 women, 62% were WLWH, 53% were non-Hispanic Black, and median age was 55 years. In full multivariable models, there was no statistically significant association between psychosocial stress and composite biomarker index values among all women independent of HIV status. High (vs. low) psychosocial stress was positively associated with higher mean composite biomarker index values among all monoracial Black women (adjusted β = 1.32; 95% CI: 0.20-2.43), Black WLWH (adjusted β = 1.93; 95% CI: 0.02-3.83) and Black HIV-negative women (adjusted β = 2.54; 95% CI: 0.41-4.67).

CONCLUSIONS

Despite a null association in the overall sample, greater psychosocial stress was positively associated with higher neuroendocrine biomarker concentrations among Black women, highlighting a plausible mechanism by which psychosocial stress could contribute to cardiovascular disease risk.

Extremely Low Birth Weight and Accelerated Biological Aging

BACKGROUND AND OBJECTIVES

Extremely low birth weight (ELBW) (<1000 g) survivors are exposed to elevated levels of physiologic stress during their lives and may be susceptible to accelerated aging. Using the oldest known longitudinally followed cohort of ELBW survivors, we compared biological aging in this group using an epigenetic clock to a sample of matched normal birth weight (NBW) (>2500 g) control participants.

METHODS

Buccal cells were collected from 45 ELBW survivors and 49 NBW control participants at 30 to 35 years of age. Epigenetic age was calculated from the weighted average of DNA methylation at 353 cytosine-phosphate-guanine sequence within DNA sites, by using the Illumina Infinium Human Methylation EPIC 850k BeadChip array.

RESULTS

Before and after statistically adjusting for neurosensory impairment and the presence of chronic health conditions, a significant sex by birth weight group interaction was observed in the 353-site epigenetic-clock assay (P = .03), whereby ELBW men had a significantly older epigenetic age than NBW men (4.6 years; P = .01). Women born at ELBW were not found to be epigenetically older than their NBW peers.

CONCLUSIONS

The results of this study suggest that prenatal exposures may play an important role in aging, and that men born preterm may experience accelerated aging relative to their peers. We further highlight the need to monitor and promote the health of preterm survivors, with a particular focus on healthy aging across the life span.

Aging and Allostasis: Using Bayesian Network Analytics to Explore and Evaluate Allostatic Markers in the Context of Aging

Allostatic load reflects the cumulative strain on organic functions that may gradually evolve into overt disease. Our aim was to evaluate the allostatic parameters in the context of aging, and identify the parameters that may be suitable for an allostatic load index for elderly people (>60 years). From previously published studies, 11 allostatic (bio)markers could be identified that sustain sufficient variability with aging to capture meaningful changes in health status. Based on reported statistics (prevalence of a biomarker and its associated outcome, and/or an odds/risk ratio relating these two), seven of these could be adopted in a Bayesian Belief Network (BBN), providing the probability of “disturbed” allostasis in any given elder. Additional statistical analyses showed that changes in IL-6 and BMI contributed the most to a “disturbed” allostasis, indicating their prognostic potential in relation to deteriorating health in otherwise generally healthy elderly. In this way, and despite the natural decline in variance that irrevocably alters the prognostic relevance of most allostatic (bio)markers with aging, it appeared possible to outline an allostatic load index specifically for the elderly. The allostatic parameters here identified might consequently be considered a useful basis for future quantitative modelling in the context of (healthy) aging.

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.