Integrated multicomponent interventions to support healthy aging of the whole person

Machine learning methods to discover hidden patterns in well-being and resilience for healthy aging

BACKGROUND

A whole person approach to healthy aging can provide insight into social factors that may be critical. Digital technologies, such as mobile health (mHealth) applications, hold promise to provide novel insights for healthy aging and the ability to collect data between clinical care visits. Machine learning/artificial intelligence methods have the potential to uncover insights into healthy aging. Nurses and nurse informaticians have a unique lens to shape the future use of this technology.

METHODS

The purpose of this research was to apply machine learning methods to MyStrengths+MyHealth de-identified data (N = 988) for adults 45 years of age and older. An exploratory data analysis process guided this work.

RESULTS

Overall (n = 988), the average Strength was 66.1% (SD = 5.1), average Challenges 66.5% (SD = 7.5), and average Needs 60.06% (SD = 3.1). There was a significant difference between Strengths and Needs (p < 0.001), between Challenges and Needs (p < 0.001), and no significant differences between average Strengths and Challenges. Four concept groups were identified from the data (Thinking, Moving, Emotions, and Sleeping). The Thinking group had the most statistically significant challenges (11) associated with having at least one Thinking Challenge and the highest average Strengths (66.5%) and Needs (83.6%) compared to the other groups.

CONCLUSION

This retrospective analysis applied machine learning methods to de-identified whole person health resilience data from the MSMH application. Adults 45 and older had many Strengths despite numerous Challenges and Needs. The Thinking group had the highest Strengths, Challenges, and Needs, which aligns with the literature and highlights the co-occurring health challenges experienced by this group. Machine learning methods applied to consumer health data identify unique insights applicable to specific conditions (e.g., cognitive) and healthy aging. The next steps involve testing personalized interventions with nurses leading artificial intelligence integration into clinical care.

β-Cyclocitral from Lavandula angustifolia Mill. Exerts Anti-Aging Effects on Yeasts and Mammalian Cells via Telomere Protection, Antioxidative Stress, and Autophagy Activation

We used a replicative lifespan (RLS) experiment of K6001 yeast to screen for anti-aging compounds within lavender extract (Lavandula angustifolia Mill.), leading to the discovery of β-cyclocitral (CYC) as a potential anti-aging compound. Concurrently, the chronological lifespan (CLS) of YOM36 yeast and mammalian cells confirmed the anti-aging effect of CYC. This molecule extended the yeast lifespan and inhibited etoposide (ETO)-induced cell senescence. To understand the mechanism of CYC, we analyzed its effects on telomeres, oxidative stress, and autophagy. CYC administration resulted in notable increases in the telomerase content, telomere length, and the expression of the telomeric shelterin protein components telomeric-repeat binding factor 2 (TRF2) and repressor activator protein 1 (RAP1). More interestingly, CYC reversed H2O2-induced telomere damage and exhibited strong antioxidant capacity. Moreover, CYC improved the survival rate of BY4741 yeast under oxidative stress induced by 6.2 mM H2O2, increasing the antioxidant enzyme activity while reducing the reactive oxygen species (ROS), reactive nitrogen species (RNS), and malondialdehyde (MDA) levels. Additionally, CYC enhanced autophagic flux and free green fluorescent protein (GFP) expression in the YOM38-GFP-ATG8 yeast strain. However, CYC did not extend the RLS of K6001 yeast mutants, such as Δsod1, Δsod2, Δcat, Δgpx, Δatg2, and Δatg32, which lack antioxidant enzymes or autophagy-related genes. These findings reveal that CYC acts as an anti-aging agent by modifying telomeres, oxidative stress, and autophagy. It is a promising compound with potential anti-aging effects and warrants further study.

Biological and Physical Performance Markers for Early Detection of Cognitive Impairment in Older Adults

Dementia is a major cause of poor quality of life, disability, and mortality in old age. According to the geroscience paradigm, the mechanisms that drive the aging process are also involved in the pathogenesis of chronic degenerative diseases, including dementia. The dissection of such mechanisms is therefore instrumental in providing biological targets for interventions and new sources for biomarkers. Within the geroscience paradigm, several biomarkers have been discovered that can be measured in blood and that allow early identification of individuals at risk of cognitive impairment. Examples of such markers include inflammatory biomolecules, markers of neuroaxonal damage, extracellular vesicles, and DNA methylation. Furthermore, gait speed, measured at a usual and fast pace and as part of a dual task, has been shown to detect individuals at risk of future dementia. Here, we provide an overview of available biomarkers that may be used to gauge the risk of cognitive impairment in apparently healthy older adults. Further research should establish which combination of biomarkers possesses the highest predictive accuracy toward incident dementia. The implementation of currently available markers may allow the identification of a large share of at-risk individuals in whom preventive interventions should be implemented to maintain or increase cognitive reserves, thereby reducing the risk of progression to dementia.

Healthy aging: Linking causal mechanisms with holistic outcomes

Identifying and understanding the impact of differing exposures over the lifecourse necessitates contextualizing different levels of influence ranging from genetics, epigenetics, geography, and psychosocial networks.

Making a Case for Whole Person Health

Background: Our conventional approach to health care tends to separate patients' health by body system, treating each independently and "efficiently"-e.g., minimal time with a provider, reliance on medications, and little investment to support behavioral and lifestyle improvements. Meanwhile, the United States has the most expensive health care in the world, with some of the worse outcomes. Purpose In this paper, we make the case for transforming health care from a disease-centric approach to a "whole person" model. Research Design: We provide detailed health and health care utilization assumptions for a hypothetical patient, Mrs. M, over her life from age 40 to 80 years under 2 care scenarios: the continuation of conventional care (Version A) and a whole person care approach (Version B). Analysis We developed a set of health care utilization assumptions for each scenario, applied 2023 U.S. dollar (USD) resource prices, and estimated cumulative total health care costs. The price and the health care utilization assumptions for the conventional care scenario were validated using Medical Expenditures Panel Survey (MEPS) data. Results: At age 80, with conventional care, we find Mrs. M increasingly frail and living in a skilled nursing facility, with total cumulative health care costs of $353,155. With whole person care, we find her active and generally healthy at age 80, with total cumulative health care costs of $52,425. Conclusions: Although based on an "imagined" case, the 2 versions of Mrs. M's history illustrate how an investment beginning in early middle age to support a healthy diet, physical activity, and stress management can plausibly lead to improved health and well-being, as well as reduced health care spending.

Integrated multicomponent interventions to support healthy aging of the whole person

Healthy aging is an integrated "whole person" process that involves an individual's biology, behavior, and social/physical environment. With the recent development of antiaging drugs, careful consideration of the respective roles of pharmacologic and nonpharmacologic approaches to both health and aging is in order. Recent advances in understanding the cellular and molecular mechanisms of aging are providing new measures that can be used as clinical outcomes in studying the impact of antiaging interventions in humans. This paper outlines the strategic interest of the National Center for Complementary and Integrative Health (NCCIH) in supporting the development, testing, and implementation of effective, scalable, and integrated multicomponent interventions to support healthy aging of the whole person.