Associations between life course socioeconomic conditions and the Pace of Aging

Pace of Aging in older adults matters for healthspan and lifespan

As societies age, policy makers need tools to understand how demographic aging will affect population health and to develop programs to increase healthspan. The current metrics used for policy analysis do not distinguish differences caused by early-life factors, such as prenatal care and nutrition, from those caused by ongoing changes in people's bodies due to aging. Here we introduce an adapted Pace of Aging method designed to quantify differences between individuals and populations in the speed of aging-related health declines. The adapted Pace of Aging method, implemented in data from N=13,626 older adults in the US Health and Retirement Study, integrates longitudinal data on blood biomarkers, physical measurements, and functional tests. It reveals stark differences in rates of aging between population subgroups and demonstrates strong and consistent prospective associations with incident morbidity, disability, and mortality. Pace of Aging can advance the population science of healthy longevity.

Cognitive aging and the life course: A new look at the Scaffolding theory

Our understanding of human neurocognitive aging, its developmental roots, and life course influences has been transformed by brain imaging technologies, increasing availability of longitudinal data sets, and analytic advances. The Scaffolding Theory of Aging and Cognition is a life course model, proposed originally in 2009, featuring adaptivity and compensatory potential as lifelong mechanisms for meeting neurocognitive challenges posed by the environment and by developing or declining brain circuitry. Here, we review the scaffolding theory in relation to new evidence addressing when during the life course potentially enriching and depleting factors exert their effects on brain health and scaffolding, and we consider the implications for separable, and potentially reciprocal, influences on the level of cognitive function and the rate of decline in later life.

Influencing Factors of Healthy Aging Risk Assessed Using Biomarkers: A Life Course Perspective

Assessing individual risks of healthy aging using biomarkers and identifying associated factors have become important areas of research. In this study, we conducted a literature review of relevant publications between 2018 and 2023 in both Chinese and English databases. Previous studies have predominantly used single biomarkers, such as C-reactive protein, or focused on specific life course stages and factors such as socioeconomic status, mental health, educational levels, and unhealthy lifestyles. By summarizing the progress in this field, our study provides valuable insights and future directions for promoting healthy aging from a life course perspective.

Exploration of the factors influencing the quality of life among adolescents during the COVID-19 pandemic: the data from a cross-sectional study in Shandong

BACKGROUND

The COVID-19 pandemic has sparked unprecedented transformations in the lives of adolescents, with reshaping their routines, social dynamics, educational experiences, and overall well-being. Our study delves into the influence of various factors on adolescents' quality of life (QOL) among the COVID-19 pandemic in Shandong Province, China.

METHODS

Employing a cross-sectional research approach combined with multivariable analysis, we scrutinize the association of demographic factors (age, gender, education level, ethnic groups, urban area, and family economic status) and health-related behaviors (sleep duration, and self-reported health status) with QOL in 9953 students.

RESULTS

During the pandemic, the average QOL for adolescents in Shandong Province was 133. Our analysis revealed that sleep duration and age had statistically significant associations with total QOL, with the OR values of 1.43 (95% confidence interval (CI): 1.03 to 1.83) and 0.44 (95% CI: 0.19 to 0.70), respectively. Notably, we observed that adolescents from economically disadvantaged families, or those with poorer self-reported health status, were more likely to report lower QOL scores.

CONCLUSIONS

Overall, our study highlights the potential association of sleep duration, age, family economic status, and self-reported health with the QOL of adolescents in Shandong Province during the pandemic. During similar public health crises, policymakers, educators, and healthcare providers can actively work through resource allocation and effective intervention measures towards alleviating financial burdens, improving health conditions, and ultimately enhancing the total QOL for adolescents.

Association of Childhood Adversity With Frailty and the Mediating Role of Unhealthy Lifestyle: A Lifespan Analysis

OBJECTIVES

Childhood adversity and lifestyle have been associated with frailty in later life, but not much is known about factors that may explain these associations. Therefore, this study aims to investigate the association of childhood adversity with frailty, and the mediating role of unhealthy lifestyle in the association.

METHODS

This lifespan analysis included 152,914 adults aged 40-69 years old from the UK Biobank. We measured childhood adversity with five items: physical neglect, emotional neglect, sexual abuse, physical abuse, and emotional abuse through online mental health survey. Frailty was measured by the frailty index; an unhealthy lifestyle score (range: 0-5) was calculated based on unhealthy body mass index, smoking, alcohol consumption, physical inactivity, and unhealthy diet at the baseline survey. Multiple logistic regression and mediation analysis were performed.

RESULTS

A total of 10,078 participants (6.6%) were defined as having frailty. Participants with any childhood adversity had higher odds of frailty. For example, in the fully adjusted model, with a one-point increase in cumulative score of childhood adversity, the odds of frailty increased by 38% (odds ratio: 1.38; 95% Confidence Interval: 1.36, 1.40). Unhealthy lifestyle partially mediated the associations of childhood adversity with frailty (mediation proportion: 4.4%-7.0%). The mediation proportions were largest for physical (8.2%) and sexual (8.1%) abuse.

CONCLUSIONS

Childhood adversity was positively associated with frailty, and unhealthy lifestyle partially mediated the association. This newly identified pathway highlights the potential of lifestyle intervention strategies among those who experienced childhood adversity (in particular, physical, and sexual abuse) to promote healthy aging.

Resilience, Accelerated Aging and Persistently Poor Health: Diverse Trajectories of Health in Malawi

Individuals age at vastly different rates resulting in significant within-population heterogeneity in health and aging outcomes. This diversity in health and aging trajectories has rarely been investigated among low-income aging populations that have experienced substantial hardships throughout their lifecourses. Utilizing 2006-2018 data from the Malawi Longitudinal Study of Families and Health (MLSFH) and estimating group-based trajectory models (GBTM), our analyses identified three distinct lifecourse health trajectories: (1) comparatively good initial mental and physical health that persisted throughout the lifecourse ("resilient aging"); (2) relatively good initial mental and physical health that started to deteriorate during mid-adulthood ("accelerated aging"); and (3) poor initial mental and physical health that further declined over the lifecourse ("aging with persistently poor health"). For both physical and mental health, men were more likely to enjoy resilient aging than women. Predictors other than gender of trajectory membership sometimes confirmed, and sometimes contradicted, hypotheses derived from high-income country studies. Our analyses highlight the long arm of early life conditions and gender in determining aging trajectories and show that a non-trivial sub-population is characterized by aging with persistently poor health. The study uncovers widening gaps in health outcomes between those who age with resilience and those who experience accelerated aging.

Two-sample Mendelian randomization analysis evaluates causal associations between inflammatory bowel disease and osteoporosis

Introduction

Over the past few years, multiple observational studies have speculated a potential association between inflammatory bowel disease (IBD), which includes ulcerative colitis (UC) and Crohn's disease (CD), and osteoporosis. However, no consensus has been reached regarding their interdependence and pathogenesis. Herein, we sought to further explore the causal associations between them.

Methods

We validated the association between IBD and reduced bone mineral density in humans based on genome-wide association studies (GWAS) data. To investigate the causal relationship between IBD and osteoporosis, we performed a two-sample Mendelian randomization study using training and validation sets. Genetic variation data for IBD, CD, UC, and osteoporosis were derived from published genome-wide association studies in individuals of European ancestry. After a series of robust quality control steps, we included eligible instrumental variables (SNPs) significantly associated with exposure (IBD/CD/UC). We adopted five algorithms, including MR Egger, Weighted median, Inverse variance weighted, Simple mode, and Weighted mode, to infer the causal association between IBD and osteoporosis. In addition, we evaluated the robustness of Mendelian randomization analysis by heterogeneity test, pleiotropy test, leave-one-out sensitivity test, and multivariate Mendelian randomization.

Results

Genetically predicted CD was positively associated with osteoporosis risk, with ORs of 1.060 (95% CIs 1.016, 1.106; p = 0.007) and 1.044 (95% CIs 1.002, 1.088; p = 0.039) for CD in the training and validation sets, respectively. However, Mendelian randomization analysis did not reveal a significant causal relationship between UC and osteoporosis (p > 0.05). Furthermore, we found that overall IBD was associated with osteoporosis prediction, with ORs of 1.050 (95% CIs 0.999, 1.103; p = 0.055) and 1.063 (95% CIs 1.019, 1.109; p = 0.005) in the training and validation sets, respectively.

Conclusion

We demonstrated the causal association between CD and osteoporosis, complementing the framework for genetic variants that predispose to autoimmune disease.

Association of childhood adversity with frailty and the mediating role of unhealthy lifestyle: Findings from the UK biobank

Background

Childhood adversity and lifestyle have been associated with frailty in later life, but not much is known about factors that may explain these associations. An unhealthy lifestyle may play an important role in the pathway from childhood adversity to frailty. Therefore, this study aims to investigate the association of childhood adversity with frailty, and the mediating role of unhealthy lifestyle in the association.

Methods

This lifespan analysis included 152914 adults aged 40-69 years old from the UK Biobank. We measured childhood adversity with five items: physical neglect, emotional neglect, sexual abuse, physical abuse, and emotional abuse through online mental health survey. Frailty was measured by the frailty index; an unhealthy lifestyle score (range: 0-5) was calculated based on unhealthy body mass index, smoking, drinking, physical inactivity, and unhealthy diet at the baseline survey. Multiple logistic regression and mediation analysis were performed.

Results

A total of 10078 participants (6.6%) were defined as having frailty. Participants with any childhood adversity had higher odds of frailty. For example, in the fully adjusted model, with a one-point increase in cumulative score of childhood adversity, the odds of frailty increased by 41% (Odds Ratio: 1.41; 95% Confidence Interval: 1.39, 1.44). Unhealthy lifestyle partially mediated the associations of childhood adversity with frailty (mediation proportion: 4.4%-7.0%). The mediation proportions were largest for physical (8.2%) and sexual (8.1%) abuse.

Conclusions

Among this large sample, childhood adversity was positively associated with frailty, and unhealthy lifestyle partially mediated the association. This newly identified pathway highlights the potential of lifestyle intervention strategies among those who experienced childhood adversity (in particular, physical and sexual abuse) to promote healthy aging.

Positive social factors prospectively predict younger epigenetic age: Findings from the Health and Retirement Study

OBJECTIVES

Positive social factors may slow biological aging, but this has yet to be rigorously tested. This study investigated whether baseline levels or changes over time in social support and contact frequency prospectively predicted epigenetic age.

METHOD

Health and Retirement Study participants (N = 1912, 46.3 % male, aged 42-87 at baseline) reported longitudinal social support and contact frequency data up to 3 times between 2006 and 2016 and provided blood in 2016. Baseline levels (intercepts) and changes over time (slopes) in social support from and contact frequency with spouses, children, friends, and other family were outputted from multilevel models and used to predict epigenetic age, estimated from Horvath, Hannum, GrimAge, PhenoAge, and Dunedin Pace of Aging.

RESULTS

In models adjusted for demographic and health characteristics, higher baseline levels of support from and contact frequency with friends were prospectively associated with a slower Pace of Aging (support: p = .002; contact: p = 0.009) and a lower GrimAge (contact: p = .001). In addition, higher contact frequency with children at baseline was prospectively associated with a lower GrimAge (p < .001), and higher contact frequency with family at baseline and an increase in family contact over time was associated with a lower Hannum age (baseline: p = .005; slope: p = .015).

CONCLUSIONS

Perceived support from and contact with close others, particularly friends, may have implications for healthy biological aging. Notably, the effect sizes for friends were comparable to the effect of body mass index on epigenetic age. Positive social factors were generally associated with second- and third-generation clocks, which may be more sensitive to psychosocial factors than first-generation clocks.

Life-course socioeconomic factors are associated with markers of epigenetic aging in a population-based study

Adverse socioeconomic circumstances negatively affect the functioning of biological systems, but the underlying mechanisms remain only partially understood. Here, we explore the associations between life-course socioeconomic factors and four markers of epigenetic aging in a population-based setting. We included 684 participants (52 % women, mean age 52.6 ± 15.5 years) from a population and family-based Swiss study. We used nine life-course socioeconomic indicators as the main exposure variables, and four blood-derived, second generation markers of epigenetic aging as the outcome variables (Levine's DNAmPhenoAge, DunedinPoAm38, GrimAge epigenetic age acceleration (EAA), and the mortality risk score (MS)). First, we investigated the associations between socioeconomic indicators and markers of epigenetic aging via mixed-effect linear regression models, adjusting for age, sex, participant's recruitment center, familial structure (random-effect covariate), seasonality of blood sampling, and technical covariates. Second, we implemented counterfactual mediation analysis to investigate life-course and intermediate mechanisms underlying the socioeconomic gradient in epigenetic aging. Effect-size estimates were assessed using regression coefficients and counterfactual mediation parameters, along with their respective 95 % confidence intervals. Individuals reporting a low father's occupation, adverse financial conditions in childhood, a low income, having financial difficulties, or experiencing unfavorable socioeconomic trajectories were epigenetically older and had a higher mortality risk score than their more advantaged counterparts. Specifically, this corresponded to an average increase of 1.1-1.5 years for Levine's epigenetic age (β and 95 %CI range, β (minimum and maximum): 1.1-1.5 95 %CI[0.0-0.2; 2.3-3.0]), 1.1-1.5 additional years for GrimAge (β: 1.1-1.5 95 %CI[0.2-0.6; 1.9-3.0]), a 1-3 % higher DunedinPoAm38 age acceleration (β: 0.01-0.03 95 %CI[0.00; 0.03-0.04]), and a 10-50 % higher MS score (β: 0.1-0.4 95 %CI[0.0-0.2; 0.3-0.4]) for the aforementioned socioeconomic indicators. By exploring the life-course mechanisms underlying the socioeconomic gradient in epigenetic aging, we found that both childhood and adulthood socioeconomic factors contributed to epigenetic aging, and that detrimental lifestyle factors mediated the relation between socioeconomic circumstances in adulthood and EAA (31-89 % mediated proportion). This study provides emerging evidence for an association between disadvantaged life-course socioeconomic circumstances and detrimental epigenetic aging patterns, supporting the "sensitive-period" life-course model. Counterfactual mediation analyses further indicated that the effect of socioeconomic factors in adulthood operates through detrimental lifestyle factors, whereas associations involving early-life socioeconomic factors were less clear.