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BackgroundChildhood 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.MethodsThis 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.ResultsA 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.ConclusionsAmong 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.

Additional file 1.

Additional file 1.

Additional file 1. Fig. S1. Consort diagram of breast tissue and peripheral blood samples. Fig. S2. Correlations between age and six epigenetic clocks in controls (top row) and cases (bottom row) in breast tissue. Fig. S3. Epigenetic clock accelerations in cases (normal breast tissue > 3 cm away from breast tumor in breast cancer patients) and controls (normal breast tissue from healthy individuals) adjusted for confounders (race, smoking, BMI). Fig. S4. Correlations between age and epigenetic clocks in controls (top row) and cases (bottom row) in peripheral blood. Fig. S5. Using the CpGs in the Levine clock that are associated with polycomb-related genes, we estimated Mahalanobis distance using DNA methylation levels from breast tumor samples as a reference. We then tested whether samples became more tumor like (lower distance) with age in cases (A) and controls (B). When comparing cases to controls, we found that cases had a DNA methylation profile with a lower Mahalanobis distance suggesting they were more breast tumor like (C).

Additional file 4: Table S3. Associations of the three aging metrics incorporating cognitive and physical function with all-cause mortality when additionally adjusting for comorbidities. Figure S2. Kaplan-Meier survival curves of the groups defined by the three aging metrics in NHANES.

Additional file 5: Sensitivity Analyses Results. Table S4. Associations of the three aging metrics incorporating cognitive and physical function with all-cause mortality among older adults aged 60 years and over in NHANES (N = 2751). Figure S3. Association of the three aging metrics with all-cause mortality among older adults aged 60 years and over in NHANES (N = 2751).

Additional file 1: Supplemental Table S1. Characteristics of the study population stratified by quartiles of NLR levels at baseline. Supplemental Table S2. Characteristics of the study population stratified by quartiles of PLR levels at baseline. Supplemental Table S3. Characteristics of the study population stratified by quartiles of SII levels at baseline. Supplemental Table S4. Association of immunity markers with risk of frailty at baseline. Supplemental Table S5. Association of immunity markers with risk of frailty among all individuals at baseline. Supplemental Table S6. Association of immunity markers with risk of frailty among individuals without comorbidity at baseline

Additional file 1: Figure S1. Roadmap for the comprehensive analyses of the three aging metrics incorporating cognitive and physical function.

Additional file 2. Detailed description of the Methods.

Additional file 3: Table S1A. Summary characteristics of the cognition status among different age groups, CHARLS 2011/2012 and NHANES 1999–2002. Table S1B. Characteristics of the included and excluded population. Table S1C. Distribution of the participants with CI-PF and MCR across the FI groups, CHARLS 2011/2012 and NHANES 1999–2002.

2010年广州市千户问卷调查数据表明:城市住房分层结构是一个从低到高依次由 无产权房阶层、有产权房阶层(福利性产权房阶层、商品性产权房阶层、继承性产权 房阶层)和多产权房阶层构成的“三阶五级式”结构;个人的政治资本、人力资本、 职业状况及收入水平对人们获得住房资源有显著影响;城市住房分层既反映社会贫富 分化又可加剧社会贫富差距。因此,住房保障目标、对象及方式的选择应以住房分层 状况为前提。 关键词:住房分层 贫富分化 住房保障 Data from a questionnaire survey of over 1,000 households conducted in Guangzhou in 2010 indicate that urban housing stratification has “three ranks and five levels”: in ascending order, the structure is composed of those who do not own any residential property, those owning one property (comprising those whose home ownership derives from social welfare, commercial purchase, or inheritance) and those owning more than one property. Political capital, human capital, occupation and income have a significant effect on people’s access to home ownership. Urban housing stratification reflects and may exacerbate social polarization between the rich and the poor. Therefore, the objective, targets and mode of housing security should be premised on housing stratification.