Accelerated aging leads to increasing burdens of chronic diseases in late life, posing a huge challenge to the society. With two well-developed aging measures (i.e., physiological dysregulation [PD] and frailty index [FI]), this study aimed to evaluate the relative contributions of life course circumstances (e.g., childhood and adulthood socioeconomic status) to variance in aging. We assembled data for 6224 middle-aged and older adults in China from the 2014 life course survey (June to December 2014), the 2015 biomarker collection (July 2015 to January 2016), and the 2015 main survey (July 2015 to January 2016) of the China Health and Retirement Longitudinal Study. Two aging measures (PD and FI) were calculated, with a higher value indicating more accelerated aging. Life course circumstances included childhood (i.e., socioeconomic status, war, health, trauma, relationship, and parents’ health) and adulthood circumstances (i.e., socioeconomic status, adversity, and social support), demographics, and behaviours. The Shapley value decomposition, hierarchical clustering, and general linear regression models were performed. The Shapley value decomposition revealed that all included life course circumstances accounted for about 6·3% and 29·7% of variance in PD and FI, respectively. We identified six subpopulations who shared similar patterns in terms of childhood and adulthood circumstances. The most disadvantaged subpopulation (i.e., subpopulation 6 [more childhood trauma and adulthood adversity]) consistently exhibited accelerated aging indicated by the two aging measures. Relative to the most advantaged subpopulation (i.e., subpopulation 1 [less childhood trauma and adulthood adversity]), PD and FI in the most disadvantaged subpopulation were increased by an average of 0·14 (i.e., coefficient, by one-standard deviation, 95% confidence interval [CI] 0·06–0·21; p < 0·0001) and 0·10 (by one-point, 95% CI 0·09–0·11; p < 0·0001), respectively. Our findings highlight the different contributions of life course circumstances to phenotypic and functional aging. Special attention should be given to promoting health for the disadvantaged subpopulation and narrowing their health gap with advantaged counterparts. National Natural Science Foundation of China, Milstein Medical Asian American Partnership Foundation, Natural Science Foundation of Zhejiang Province, Fundamental Research Funds for the Central Universities, National Institute on Aging, National Centre for Advancing Translational Sciences, and Yale Alzheimer's Disease Research Centre.

Background: Compared with adults with normal glucose metabolism, those with prediabetes tend to be frail. However, it remains poorly understood whether frailty could identify adults who are most at risk of adverse outcomes related to prediabetes. Objective: We aimed to systematically evaluate the associations between frailty, a simple health indicator, and risks of multiple adverse outcomes including incident type 2 diabetes mellitus (T2DM), diabetes-related microvascular disease, cardiovascular disease (CVD), chronic kidney disease (CKD), eye disease, dementia, depression, and all-cause mortality in late life among middle-aged adults with prediabetes. Methods: We evaluated 38,950 adults aged 40 years to 64 years with prediabetes using the baseline survey from the UK Biobank. Frailty was assessed using the frailty phenotype (FP; range 0-5), and participants were grouped into nonfrail (FP=0), prefrail (1≤FP≤2), and frail (FP≥3). Multiple adverse outcomes (ie, T2DM, diabetes-related microvascular disease, CVD, CKD, eye disease, dementia, depression, and all-cause mortality) were ascertained during a median follow-up of 12 years. Cox proportional hazards regression models were used to estimate the associations. Several sensitivity analyses were performed to test the robustness of the results. Results: At baseline, 49.1% (19,122/38,950) and 5.9% (2289/38,950) of adults with prediabetes were identified as prefrail and frail, respectively. Both prefrailty and frailty were associated with higher risks of multiple adverse outcomes in adults with prediabetes (P for trend <.001). For instance, compared with their nonfrail counterparts, frail participants with prediabetes had a significantly higher risk (P<.001) of T2DM (hazard ratio [HR]=1.73, 95% CI 1.55-1.92), diabetes-related microvascular disease (HR=1.89, 95% CI 1.64-2.18), CVD (HR=1.66, 95% CI 1.44-1.91), CKD (HR=1.76, 95% CI 1.45-2.13), eye disease (HR=1.31, 95% CI 1.14-1.51), dementia (HR=2.03, 95% CI 1.33-3.09), depression (HR=3.01, 95% CI 2.47-3.67), and all-cause mortality (HR=1.81, 95% CI 1.51-2.16) in the multivariable-adjusted models. Furthermore, with each 1-point increase in FP score, the risk of these adverse outcomes increased by 10% to 42%. Robust results were generally observed in sensitivity analyses. Conclusions: In UK Biobank participants with prediabetes, both prefrailty and frailty are significantly associated with higher risks of multiple adverse outcomes, including T2DM, diabetes-related diseases, and all-cause mortality. Our findings suggest that frailty assessment should be incorporated into routine care for middle-aged adults with prediabetes, to improve the allocation of health care resources and reduce diabetes-related burden.

Background: While childhood and adulthood traumatic experiences have been linked to subsequent cardiovascular disease (CVD), the relationship between life course traumas and CVD and the underpinning pathways are poorly understood. This study aimed to: (1) examine the associations of childhood, adulthood, and lifetime traumas with CVD; (2) examine the associations between diverse life course traumatic profiles and CVD; and (3) examine the extent to which Phenotypic Age (PhenoAge), a well-developed phenotypic aging measure, mediates these associations. Methods: We included 104,939 participants from the UK Biobank who completed the 2016 online mental health questionnaire. CVD outcomes including ischemic heart disease, myocardial infarction, and stroke were ascertained. Childhood, adulthood, and lifetime traumas were categorized into three subgroups (mild, moderate, and severe), respectively. Four life course traumatic profiles were defined as non-severe traumas across life course, non-severe childhood and severe adulthood traumas, severe childhood and non-severe adulthood traumas, and severe traumas across life course based on both childhood and adulthood traumas. PhenoAge was measured using an equation previously developed. Multivariable logistic models and formal mediation analyses were performed. Results: Of 104,939 participants, 7,398 (7.0%) were diagnosed with CVD. Subgroups of childhood, adulthood, and lifetime traumas were associated with CVD, respectively. Furthermore, life course traumatic profiles were significantly associated with CVD. For instance, compared with subgroups experiencing non-severe traumas across life course , those who experienced non-severe childhood and severe adulthood traumas, severe childhood and non-severe adulthood traumas, and severe traumas across life course had higher odd of CVD, with odds ratios of 1.07 (95% confidence interval [CI]: 1.00, 1.15), 1.17 (95% CI: 1.09, 1.25), and 1.33 (95% CI: 1.24, 1.43), respectively. Formal mediation analyses suggested that PhenoAge partially mediated the above associations. For instance, PhenoAge mediated 5.8% of increased CVD events in subgroups who experienced severe childhood traumas, relative to those experiencing mild childhood traumas. Conclusions: Childhood, adulthood, and lifetime traumas, as well as diverse life course traumatic profiles, were associated with CVD. Furthermore, phenotypic aging partially mediated these associations. These findings suggest a potential pathway from life course traumas to CVD through phenotypic aging, and underscore the importance of policy programs targeting traumatic events over the life course in ameliorating inequalities in cardiovascular health.

INTRODUCTION: Socioeconomic inequality is a non‐negligible risk factor for dementia. However, complex associations of individual socioeconomic status (ISES) and neighborhood socioeconomic status (NSES) with dementia risk have not been determined. METHODS: In 327,641 adults aged 40–69 years from the UK Biobank, we estimated the separate, interactive, and joint associations of ISES and NSES with the risk of dementia and explored the role of inflammatory markers and metabolites. RESULTS: Low ISES and low NSES were associated with higher risks of all‐cause dementia and its subtypes. A stronger association between ISES and dementia was observed in those with low NSES. The subpopulation with disadvantages in both ISES and NSES showed the highest risk of dementia. Inflammatory markers (e.g., lymphocyte percentage) and metabolites (e.g., valine) mediated the associations of socioeconomic status (SES) profiles with all‐cause dementia. DISCUSSION: These findings underscore the importance of eliminating socioeconomic inequality at both individual and neighborhood levels for preventing dementia. Highlights: Disadvantages in both individual socioeconomic status (ISES) and neighborhood socioeconomic status (NSES) are associated with higher risks of dementia. There are significant interactions between ISES and NSES on dementia risk. The low SES subpopulation with disadvantages in both ISES and NSES has the highest risk of dementia. Inflammatory markers and metabolites partially mediate the associations of socioeconomic status (SES) profiles with all‐cause dementia. Narrowing socioeconomic inequality at both the individual and neighborhood levels may help prevent dementia.

Background: The aim of the current study was to explore the trajectories, variabilities, and cumulative exposures of body mass index (BMI) and waist circumference (WC) with cardiac arrhythmia (CA) risks. Methods: In total, 35,739 adults from the Kailuan study were included. BMI and WC were measured repeatedly during the 2006–2010 waves. CA was identified via electrocardiogram diagnosis. BMI and WC trajectories were fitted using a group-based trajectory model. The associations were estimated using Cox proportional hazards models. Results: We identified four stable trajectories for BMI and WC, respectively. Neither the BMI trajectories nor the baseline BMI values were associated with the risk of CA. Compared to the low-stable WC group, participants in the high-stable WC group had a higher risk of CA (hazard ratio (HR) = 1.40, 95% confidence interval (CI): 1.06, 1.86). Interestingly, the cumulative exposures of BMI and WC instead of their variabilities were associated with the risk of CA. In the stratified analyses, the positive associations of the high-stable WC group with the risk of CA were found in females only (HR = 1.98, 95% CI: 1.02, 3.83). Conclusions: A high-stable WC trajectory is associated with a higher risk of CA among Chinese female adults, underscoring the potential of WC rather than BMI to identify adults who are at risk.