Association of adverse childhood experiences with total and disability-free life expectancy in later life: a nationwide multi-state life table analysis

Association of adverse childhood experiences with total and disability-free life expectancy in later life: a nationwide multi-state life table analysis | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Association of adverse childhood experiences with total and disability-free life expectancy in later life: a nationwide multi-state life table analysis Xue Xia, Xue Tian, Qin Xu, Yijun Zhang, Xiaoli Zhang, Jing Li, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8389754/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 7 You are reading this latest preprint version Abstract Background Adverse childhood experiences (ACEs) can trigger long-term health deficits, whereas their overall impact on disability-free longevity remains underexplored. This study aimed to examine the association of ACEs with functional disability and mortality, thus quantifying their effects on total life expectancy (TLE) and disability-free LE (DFLE). Methods The China Health and Retirement Longitudinal Study (CHARLS) was a nationwide cohort established in 2011 and followed up until 2020. we included 11,033 individuals aged ≥ 45 years with data on ACEs and Activities of Daily Living (ADL) at baseline and during follow-ups. ACEs were assessed retrospectively via 20 items as 6 subtypes. Cumulative ACE burden was defined as counts of ACE subtypes (0–6) and further classified as low (0–4) and high ACE burden group (≥ 5). Functional disability was defined as difficulty in ≥ 1 ADL item. Multi-state life table (MLST) was adopted to estimate TLE and DFLE related to ACE burden. Modification by sociodemographic characteristics was assessed via stratified analyses. Results Of individuals included, the median age was 57.0 years, 49.7% were men, and 82.9% were identified as disability-free. Higher ACE burden was associated with elevated risks of disability and premature death. TLE was 46.0 years for low ACE burden versus 38.2 years for high ACE burden, of which 31.7 years (69.0%) and 23.4 years (61.3%) were spent disability-free, respectively. Childhood violence exhibited the strongest impact among all subtypes, with odds ratio (OR) and 95% confidence interval (CI) of 1.39 (1.29–1.51) for transition to disability and 1.37 (1.08–1.75) for transition to death from a disability-free state. Significant interactions by sex ( P interaction =0.03) and marital status ( P interaction =0.01) were observed, heightening the vulnerability of women and married/partnered participants. Conclusions For middle-aged and older Chinese, high ACE burden was associated with reduced longevity and enlarged healthspan-lifespan gap, emphasizing the importance of preventing ACEs to promote healthy aging. adverse childhood experience Activities of Daily Living life expectancy multi-state life tables CHARLS Figures Figure 1 BACKGROUND Globally, life expectancy (LE) at birth increased by 22.7 years between 1950 and 2021, with a more substantial gain of 28.7 years in China.( 1 ) However, China currently confronts a critical public health challenge: gains in healthy LE (HLE) have not kept pace with increases in total LE (TLE), resulting in an expanding proportion of adults spending their later years in unhealthy states.( 2 ) Among metrics of HLE, disability-free LE (DFLE), defined as the expected years lived without functional impairment limiting independence, provides a direct measure of geriatric care burdens and social services demands. (3, 4) Given China’s rapidly aging population with complex care needs, strategies aimed at preventing or delaying functional disability progression have been prioritized within national health policies.( 5 ) Although chronic diseases in later life are primary drivers of functional disability, their risk factors often originate in childhood. The life-course perspective underscores the enduring impact of modifiable early-life exposures on well-being throughout the lifespan. Adverse childhood experiences (ACEs), encompassing a range of potentially stressful experiences (such as abuse, neglect, bullying, household dysfunction, and unsafe communities) during childhood, can trigger long-term health deterioration through complex biological mechanisms including neurodevelopmental disruption, epigenetic alteration, and stress response dysregulation.( 6 – 11 ) Beyond their established links to chronic mental and physical diseases, population-based studies have further associated ACEs with the accumulation of non-specific health deficits over time. ( 12 , 13 ) Moreover, both experimental animal studies and population-based findings have suggested that ACEs may accelerate biological aging, as evidenced by shortened telomere length and altered DNA methylation patterns.( 14 – 16 ) Despite biological and clinical plausibility linking ACEs to premature disability and mortality, evidence on their impact on LE or HLE remains scarce. Furthermore, extant evidence predominantly originates from North America and Europe, with a notable paucity of data from Asian populations like China, where the prevalence, subtypes, and sociocultural contexts of ACEs differ substantially.( 9 ) To address this critical gap, we conducted a multi-state life table (MSLT) analysis utilizing data from the China Health and Retirement Longitudinal Study (CHARLS) to quantify the associations of ACEs with TLE, years lived disability-free, and years lived with functional disability (assessed via the Activities of Daily Living [ADL] scale) among middle-aged and older adults in China. METHODS Study design and participants The CHARLS is an ongoing prospective cohort in China. Initiated in 2011, CHARLS enrolled a nationally representative sample of 17,708 residents from 150 counties/districts and 450 villages/resident committees across 28 provinces using multistage stratified probability-proportionate-to-size sampling. Biennial follow-up interviews were conducted from 2013 to 2020, supplemented by a life history survey in 2014. During each wave, trained interviewers administered face-to-face structured questionnaires and physical examinations. Detailed methodological descriptions are available in previous publications.( 17 , 18 ) The present study was restricted to 14,776 individuals who completed both the 2011 baseline survey and the 2014 life history survey. After further excluding participants aged < 45 years at baseline, those lost to follow-up, or those lacking valid data on ADL or ACEs, the final analytical sample comprised 11,033 participants ( Figure S1 ). Adverse childhood experiences ACEs were assessed through self-reported exposures retrospectively collected in the CHARLS life history survey in 2014. Aligned with the ACE International Questionnaire (ACE-IQ) and previous studies,( 10 , 19 ) 20 ACE-related items were selected to define six subtypes of ACE exposure: childhood adverse family situation, family abuse, adverse personal situation, insufficient companions, adverse communities, and violence (see Table S1 for detailed item definitions and questionnaire source). Responses to each item were dichotomized as yes or no, and each subtype was coded as present if at least one of its constituent items was endorsed. Accordingly, the cumulative ACE burden was defined as the count of ACE subtypes experienced (ranging from 0 to 6). Based on the distribution of cumulative ACE burden, we further categorized individuals into a low ACE burden group (0–4 subtypes) and a high ACE burden group (≥ 5 subtypes). The threshold of 5 subtypes was selected as it approximately corresponded to the top 10% of the ACE distribution, representing the most severely exposed subgroup in our sample. Health states Functional disability was assessed using the ADL scale, a validated measure of physical function for older adults.( 5 , 20 ) Respondents were asked if they required assistance with six basic physical tasks, including dressing, bathing, eating, transferring, toileting, and continence control. Consistent with established criteria, having difficulty in ≥ 1 item was identified as functional disability.( 21 ) Accordingly, three mutually exclusive health states (disability-free, disability, and death) were defined and dynamically tracked from baseline until death or the last available follow-up. Baseline and time-varying covariates All covariates were obtained via face-to-face interviews. Socio-demographic variables included age, sex (men/women), education (below high school/high school and above), residence (rural village/urban community), employment status (employed/not employed), marital status (married or partnered/ unmarried including single, divorced, or widowed), and household income per capita (below median/median and above). Household income per capita was selected over total household income as it better reflected economic status, particularly in rural areas.( 10 ) Lifestyle variables comprised current smoking (yes/no), current drinking (yes/no), and body mass index (BMI), which was calculated as self-reported weight in kilograms divided by height in meters squared. Statistical analysis Basic characteristics of participants were summarized as frequency (percentage) or median (interquartile range, IQR) as appropriate, overall and by stratified baseline functional disability status. MSLT analysis was employed to model health state transitions as a continuous-time Markov process within a finite state space comprising three mutually exclusive states. Transitions were permitted between the two living states (i.e., disability-free and disability), while the transition to death was irreversible. Therefore, four possible transitions were assumed, that is, from disability-free to disability, from disability-free to death, from disability to disability-free, and from disability to death ( Figure S2 ). Age-specific state-dependent transition probabilities were estimated using multinomial logistic regression. A simulated cohort of 100,000 individuals aged 45 years at baseline was generated via microsimulation, with survival trajectories projected from age 45 years onwards based on the estimated transition probabilities.( 22 ) For each individual in the simulated cohort, time spent in every health state was estimated. Accordingly, the TLE at 45 years was calculated as the average total survival time from age 45 years, with DFLE and DLE defined as the average years lived in the disability-free state and the disabled state, respectively. Primary analyses were conducted both unadjusted and adjusted. Adjusted models were fitted with fixed covariates of sex and education measured at baseline, and time-varying covariates (residence, employment status, marital status, and household income per capita). Sensitivity analyses were performed by additionally adjusting for time-varying lifestyle factors of smoking, drinking, and BMI in the models. Moreover, subgroup analyses were conducted to evaluate potential effect modification by sex, education, residence, marital status, and income level. All analyses were performed using SAS version 9.4 (SAS Institute Inc). A two-sided P < 0.05 was considered statistically significant. Ethical Considerations The study protocol was approved by the Ethics Review Committee of Peking University (IRB00001052-11015) and all participants provided written informed consent before participation. RESULTS Participant characteristics The final analytical sample comprised 11,033 participants, with 49.7% being male and a median age of 57.0 years (IQR:51.0–64.0). Baseline assessment identified 17.1% of participants in the disabled state and 82.9% as disability-free. Participants with functional disability exhibited significantly higher prevalence of all ACE subtypes and greater cumulative ACE burden compared to disability-free individuals. They were also more likely to be less well-educated, unmarried, and have lower household income per capita, with a higher proportion of women and rural residents (Table 1 ). Table 1 Baseline characteristics according to disability states at baseline survey. Characteristics Disability free N = 9,142 Disability N = 1,891 Total N = 11,033 P -value Age, years 57.0 (51.0, 64.0) 63.0 (56.0, 70.0) 58.0 (52.0, 65.0) < 0.001 Men 4544 (49.70) 757 (40.03) 5301 (48.05) < 0.001 Rural Village 5988 (65.50) 1406 (74.35) 7394 (67.02) < 0.001 High school and above 1034 (11.31) 81 (4.28) 1115 (10.11) < 0.001 Married or partnered 8152 (89.17) 1543 (81.60) 9695 (87.87) < 0.001 Household income per capita 3685.4 (1000.0, 9333.3) 1850.0 (500.0, 5513.3) 3228.6 (840.0, 8495.0) < 0.001 Employed 6336 (69.31) 918 (48.55) 7254 (65.75) < 0.001 Current smoking 2824 (30.89) 450 (23.80) 3274 (29.67) < 0.001 Current drinking 3207 (35.08) 476 (25.17) 3683 (33.38) < 0.001 Body mass index, kg/m 2 23.0 (20.8, 25.6) 22.9 (20.4, 26.1) 23.0 (20.7, 25.7) 0.51 Subtypes of ACEs Childhood adverse family situation 6306 (68.98) 1482 (78.37) 7788 (70.59) < 0.001 Childhood family abuse 3797 (41.53) 922 (48.76) 4719 (42.77) < 0.001 Childhood adverse personal situation 7401 (80.96) 1637 (86.57) 9038 (81.92) < 0.001 Childhood lacking companions 5183 (56.69) 1265 (66.90) 6448 (58.44) < 0.001 Childhood adverse communities 1001 (10.95) 316 (16.71) 1317 (11.94) < 0.001 Childhood violence 1270 (13.89) 386 (20.41) 1656 (15.01) < 0.001 Cumulative counts of ACE subtypes 0 319 (3.49) 24 (1.27) 343 (3.11) < 0.001 1 1227 (13.42) 162 (8.57) 1389 (12.59) 2 2439 (26.68) 399 (21.10) 2838 (25.72) 3 2695 (29.48) 595 (31.46) 3290 (29.82) 4 1727 (18.89) 411 (21.73) 2138 (19.38) 5 550 (6.02) 181 (9.57) 731 (6.63) 6 185 (2.02) 119 (6.29) 304 (2.76) Data are expressed as frequency (%) or median (inter-quartile range, IQR). Between-group comparisons were done using χ2 test or Fisher's exact test or Mann-Whitney U test, where appropriate. Abbreviations: ACEs, adverse childhood experiences. Primary findings As illustrated in Fig. 1 and Table S3 , individuals with higher cumulative ACE burden had greater transition probabilities to develop functional disability and were less likely to recover from disability state to disability-free state. Notably, mortality risk increased substantially for those exposed to ≥ 5 subtypes of ACEs, regardless of initial health status. After adjustment, TLE at 45 years decreased from 46.0 years for low ACE burden individuals to 38.2 years for those with high ACE burden, while the corresponding DFLE shortened from 31.7 years to 23.4 years, with the proportion of DFLE in TLE declining from 69.0% to 61.3%. The magnitude of reductions in TLE and DFLE was comparable for individuals initially in disability-free or disabled states ( Table S2 , Table 2 ). Besides, the detrimental impact of ACEs was observed to be persistent throughout the lifespan: At age 45 years, participants with low and high ACE burden spent 31.0% and 38.7% of remaining TLE with functional disability; By age 85 years, the corresponding proportions rose to 59.8% and 68.8%, respectively ( Figure S3 ). Table 2 Total life expectancy (TLE), disability free life expectancy (DFLE), and disability life expectancy (DLE) at age 45 years by low and high burden of adverse childhood experiences (ACEs). ACE burden LE, years TLE DFLE, (%) DLE, (%) Unadjusted Overall Low ACE burden 42.5 30.0 (70.6) 12.5 (29.4) High ACE burden 35.8 22.9 (63.8) 13.0 (36.2) Initial state of disability free Low ACE burden 42.5 30.3 (71.2) 12.2 (28.8) High ACE burden 35.9 23.3 (64.9) 12.6 (35.1) Initial state of disability Low ACE burden 42.2 27.4 (64.9) 14.8 (35.1) High ACE burden 35.7 20.3 (56.9) 15.4 (43.1) Adjusted * Overall Low ACE burden 46.0 31.7 (69.0) 14.3 (31.0) High ACE burden 38.2 23.4 (61.3) 14.8 (38.7) Initial state of disability free Low ACE burden 46.1 32.1 (69.6) 14.0 (30.4) High ACE burden 38.4 24.0 (62.5) 14.4 (37.5) Initial state of disability Low ACE burden 45.5 29.1 (63.9) 16.4 (36.1) High ACE burden 37.4 20.6 (55.1) 16.8 (44.9) *Sex, education level, time-varying residence, time-varying marital status, time-varying employment status, and time-varying household income per capita were adjusted. Abbreviations: ACEs, adverse childhood experiences; DFLE, disability free life expectancy; DLE, disability life expectancy; LE, life expectancy. Analyses of each ACE subtype revealed generally consistent associations, though childhood adverse communities and childhood violence exhibited particularly strong effects ( Table S4 ). Compared to disability-free individuals unexposed to childhood violence, those exposed had 39% higher risk of disability (odds ratio [OR]: 1.39, 95% confidence interval [95%CI]: 1.29–1.51) and 37% higher risk of death (OR:1.37, 95%CI:1.08–1.75). Meanwhile, exposure to each ACE subtype was related to reduced TLE and DFLE at age 45 years, alongside enlarged proportion of life spent in the disabled state (Table 3 ). For instance, childhood adverse family situation shortened DFLE by 4 years (29.4 years vs. 33.4 years) and reduced the DFLE proportion from 74.6% to 66.8%. Table 3 Total life expectancy (TLE), disability free life expectancy (DFLE), and disability life expectancy (DLE) at age 45 years by subtypes of adverse childhood experiences (ACEs). ACE subtypes Adjusted LE * , years TLE DFLE, (%) DLE, (%) Childhood adverse family situation Absent 44.8 33.4 (74.6) 11.4 (25.4) Present 44.0 29.4 (66.8) 14.6 (33.2) Childhood family abuse Absent 45.3 31.8 (70.3) 13.4 (29.7) Present 43.4 28.9 (66.6) 14.5 (33.4) Childhood adverse personal situation Absent 45.4 34.0 (75.0) 11.3 (25.0) Present 44.1 29.8 (67.6) 14.3 (32.4) Childhood lacking companions Absent 45.2 31.8 (70.5) 13.3 (29.5) Present 44.0 29.8 (67.8) 14.2 (32.2) Childhood adverse communities Absent 45.7 31.5 (68.8) 14.3 (31.2) Present 40.5 26.2 (64.7) 14.3 (35.3) Childhood violence Absent 45.9 31.7 (69.1) 14.2 (30.9) Present 39.9 25.4 (63.8) 14.4 (36.2) *Sex, education level, time-varying residence, time-varying marital status, time-varying employment status, and time-varying household income per capita were adjusted. Abbreviations: ACEs, adverse childhood experiences; DFLE, disability free life expectancy; DLE, disability life expectancy; TLE, total life expectancy. Sensitivity and stratified analyses Sensitivity analyses with further adjustments for time-varying lifestyle variables produced results consistent with primary findings ( Table S5–S6 ). Stratified analyses demonstrated generally homogeneous effects, whereas significant interactions were observed with sex and marital status. In comparison with men, high ACE burden was associated with greater probabilities of disability-to-death transition among women ( P interaction =0.03), which resulted in greater TLE reduction (-9.7 years vs -6.0 years). Similarly, the association between ACE burden and disability incidence was stronger among married/partnered individuals than unmarried counterparts ( P interaction =0.01), resulting in a larger decrease in the proportion of DFLE (-9.8% vs. -2.5%) ( Table S7 and Table 4 ). Table 4 Stratified analyses of total life expectancy (TLE), disability free life expectancy (DFLE), and disability life expectancy (DLE) at age 45 years by low and high burden of adverse childhood experiences (ACEs). Stratified analyses Adjusted LE * , years TLE DFLE, (%) DLE, (%) By sex Men Low ACE burden 43.0 32.3 (75.2) 10.7 (24.8) High ACE burden 37.0 24.6 (66.4) 12.4 (33.6) Women Low ACE burden 49.1 31.1 (63.4) 18.0 (36.6) High ACE burden 39.4 22.6 (57.3) 16.8 (42.7) By education Below high school Low ACE burden 45.5 31.1 (68.3) 14.4 (31.7) High ACE burden 38.1 23.0 (60.2) 15.2 (39.8) High school and above Low ACE burden 53.0 36.9 (69.5) 16.3 (30.6) High ACE burden 36.2 25.7 (70.8) 10.6 (29.2) By residence Rural village Low ACE burden 45.1 30.8 (68.3) 14.3 (31.7) High ACE burden 38.3 23.0 (59.9) 15.4 (40.1) Urban community Low ACE burden 47.7 33.2 (69.7) 14.5 (30.4) High ACE burden 37.4 24.1 (64.4) 13.3 (35.6) By marital status Married/partnered Low ACE burden 45.5 31.6 (69.5) 13.9 (30.5) High ACE burden 39.1 23.3 (59.7) 15.8 (40.3) Unmarried Low ACE burden 42.5 27.7 (65.1) 14.8 (34.9) High ACE burden 33.6 21.0 (62.6) 12.5 (37.4) By household income per capita Below median Low ACE burden 45.0 31.1 (69.1) 13.9 (30.9) High ACE burden 38.0 23.4 (61.5) 14.6 (38.5) Median and above Low ACE burden 48.3 32.7 (67.6) 15.6 (32.4) High ACE burden 38.3 23.5 (61.4) 14.8 (38.6) *Sex, education level, time-varying residence, time-varying marital status, time-varying employment status, and time-varying household income per capita were adjusted, expect the stratified variable itself. Abbreviations: ACEs, adverse childhood experiences; DFLE, disability free life expectancy; DLE, disability life expectancy; TLE, total life expectancy. DISCUSSION This nationally representative longitudinal study revealed that high cumulative ACE burden was associated with elevated risks of functional disability and premature death, corresponding to shortened TLE and reduced DFLE proportion. Individuals aged 45 years with high ACE burden had a 7.8-year shorter TLE than their counterparts with low burden and spent only 61.3% of remaining life disability-free (vs. 69.0% in the low ACE burden group). Among ACE subtypes, childhood violence exhibited the strongest associations, with 6.0-year reduction in TLE and 6.3-year reduction in DFLE. Stratified analyses further indicated heightened vulnerability to ACEs among women and married/partnered individuals, while no significant effect modification was observed for education, residence, and income. To our knowledge, this is the first study quantifying the association of ACE, both cumulative and subtype-specific, with DFLE and its proportion in TLE in China, a rapidly aging population underexplored in prior research. Beyond well-documented associations between ACEs and chronic diseases or multimorbidity across the lifespan,( 10 , 23 – 27 ) emerging evidence has indicated that ACEs might accelerate functional decline. For instance, the Survey of Health Aging and Retirement in Europe reported a graded relationship between ACEs and ADL limitations.( 28 ) A longitudinal study further indicated that ACEs predicted accelerating functional decline.( 29 ) Complementing this, the Danish Life Course cohort study proved that multi-domain ACEs correlated with elevated mortality risk in early adulthood.( 30 ) Despite these advances, critical knowledge gaps still persist. As far as we know, no prior longitudinal study has simultaneously quantified the impact of ACEs on both functional disability and life-years lost. Therefore, it remains unclear whether ACE prevention could translate to extended healthy longevity, as the self-care ability of daily living itself gradually deteriorates with age starting in midlife. Our findings substantiate and further extend existing evidence. We revealed that high ACE burden shortened TLE primarily through reducing DFLE, thereby increasing the proportion of life spent with functional disability. Notably, beyond replicating the gradient relationship between cumulative ACE burden and disability incidence, our current analyses indicated that individuals with higher ACE burden were less likely to recover from the disabled state to functional independence, thus further shortening DFLE. The association between high ACE burden and mid-adulthood mortality was also confirmed in our analyses, regardless of initial self-care capacity. Moreover, few prior studies have examined the specific impact of ACE subtypes, and the limited evidence shows significant heterogeneity across populations and health outcomes.( 8 , 30 ) The Collaborative Perinatal Project (CPP), for example, reported that the cluster of poverty and crowded housing was associated with higher risk of premature mortality for U.S population,( 31 ) whereas a retrospective study conducted in China revealed that individuals with childhood adverse family and personal situations had the highest risk for mental health disorder in later life. ( 19 ) As an extension to current literature, our study identified that childhood violence, including childhood bully and crime, led to the greatest loss in both TLE and DFLE. Given the relatively high prevalence of childhood exposure to domestic and family violence,( 32 ) the issue of child violence necessitates more specialized research attention. Furthermore, there is a pressing need for culturally sensitive prevention and intervention services provided by governments and welfare organizations. Of note, the current analyses identified significant effect modifications by sex and marital status, with women and married/partnered individuals exhibiting heightened vulnerability to functional disability or mortality. While available evidence on the interaction between sex and ACEs remains inconsistent, neuroendocrine mechanisms could be a possible explanation: sex differences in the hypothalamic-pituitary-adrenal axis dysregulation in response to stress may render women more susceptible to the consequences of psychosocial stress, including ACEs.( 33 – 35 ) The modification effect of marriage status should be interpreted with more caution. Although marriage traditionally confers psychosocial and economic protective benefits, marital distress and conflict are also linked to poor physical health.( 36 , 37 ) For those with high ACE burden, marriage may represent a source of conflict rather than support, thus paradoxically exacerbating their health risks. More longitudinal studies should incorporate marital satisfaction metrics and reasons for non-marriage to further elucidate this counterintuitive finding. This study has several notable strengths. Critically, while the conventional 10-item ACE scales from the CDC- Kaiser Permanente ACE Study has been widely applied, emerging evidence underscores sociocultural variations in ACE subtypes and perceptions across population.( 9 , 30 , 38 ) To address this, we defined ACEs using 20 validated items from the CHARLS life history survey, which were believed to better capture the most intensive and frequently occurring sources of stress in Chinese childhood contexts.( 19 ) Moreover, since certain ACE subtypes may exert disproportionate health effects, we analyzed the impact of ACE exposure by not only total burdens but also subtypes, which provide further insights beyond prior studies relying solely on summed ACE counts.( 31 ) Methodologically, our application of the time-inhomogeneous, finite-space, continuous-time Markov models enabled simultaneous quantification of ACE effects on disability incidence, functional recovery, and premature death, thereby generating integrated estimates of healthspan reduction. Finally, the nationally representative sampling, the large sample size, and the longitudinal design with repeated follow-ups collectively enhanced the validity and generalizability of our findings. Nonetheless, several limitations also warrant consideration. Firstly, retrospective ascertainments of ACEs in the 2014 life history survey might induce recall bias, despite that previous studies have demonstrated the good test-retest reliability of adult-recall ACE measures.( 39 , 40 ) Secondly, even though a wide range of ACE-related items have been included, some crucial ACE subtypes like sexual abuse were not evaluated due to lack of data, which might bias effect estimates. Besides, our analyses did not consider the life-course window, frequency, or severity of ACEs, whereas all of them might modulate health consequences. Further studies incorporating prospective ACE assessments with detailed exposure characterization are needed to further advance knowledge about the long-term negative consequences of ACEs. CONCLUSIONS In conclusion, this longitudinal study revealed that higher ACE burden was associated with elevated risks of functional disability and premature mortality among middle-aged and older Chinese adults, resulting in shortened TLE and compressed disability-free survival. Notably, childhood violence linked to the highest risk among ACE subtypes, and women exhibited heightened susceptibility to ACE-related health consequences. These findings underscored the need for multisectoral ACE prevention initiatives and life-course health strategies to mitigate resultant disability and death, with targeted interventions on childhood violence and enhanced support programs for high-risk women. Abbreviations ACEs adverse childhood experiences ADL Activities of Daily Living BMI body mass index CHARLS China Health and Retirement Longitudinal Study CI confidence interval CPP Collaborative Perinatal Project DFLE disability-free life expectancy HLE healthy life expectancy IQR interquartile range MLST Multi-state life table OR odds ratio TLE total life expectancy Declarations Ethics approval and consent to participate The study protocol was approved by the Ethics Review Committee of Peking University (IRB00001052-11015) and all participants provided written informed consent before participation. Consent for publication Not applicable. Availability of data and materials Data used for the analyses are publicly available from the China Health and Retirement Longitudinal Study (https://charls.charlsdata.com/pages/data/111/zh-cn.html). Competing interests All authors declare no competing interests. Funding None. 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Adverse Childhood Experiences and Trajectories of ADL Disability among Middle-Aged and Older Adults in China: Findings from the CHARLS Cohort Study. J Nutr Health Aging. 2022;26(12):1034–41. Rod NH, Bengtsson J, Budtz-Jørgensen E, Clipet-Jensen C, Taylor-Robinson D, Andersen AN, et al. Trajectories of childhood adversity and mortality in early adulthood: a population-based cohort study. Lancet. 2020;396(10249):489–97. Yu J, Patel RA, Haynie DL, Vidal-Ribas P, Govender T, Sundaram R et al. Adverse childhood experiences and premature mortality through mid-adulthood: A five-decade prospective study. Lancet Reg Health Am. 2022;15. Whitten T, Tzoumakis S, Green MJ, Dean K. Global Prevalence of Childhood Exposure to Physical Violence within Domestic and Family Relationships in the General Population: A Systematic Review and Proportional Meta-Analysis. Trauma Violence Abuse. 2024;25(2):1411–30. Gilbert R, Widom CS, Browne K, Fergusson D, Webb E, Janson S. Burden and consequences of child maltreatment in high-income countries. Lancet. 2009;373(9657):68–81. Rao RT, Androulakis IP. Modeling the Sex Differences and Interindividual Variability in the Activity of the Hypothalamic-Pituitary-Adrenal Axis. Endocrinology. 2017;158(11):4017–37. Soares ALG, Hammerton G, Howe LD, Rich-Edwards J, Halligan S, Fraser A. Sex differences in the association between childhood maltreatment and cardiovascular disease in the UK Biobank. Heart. 2020;106(17):1310–6. South SC, Krueger RF. Marital satisfaction and physical health: evidence for an orchid effect. Psychol Sci. 2013;24(3):373–8. South SC, Mann FD, Krueger RF. Marital Satisfaction as a Moderator of Molecular Genetic Influences on Mental Health. Clin Psychol Sci. 2021;9(4):719–31. Felitti VJ, Anda RF, Nordenberg D, Williamson DF, Spitz AM, Edwards V, et al. Relationship of childhood abuse and household dysfunction to many of the leading causes of death in adults. The Adverse Childhood Experiences (ACE) Study. Am J Prev Med. 1998;14(4):245–58. Brewin CR, Andrews B, Gotlib IH. Psychopathology and early experience: a reappraisal of retrospective reports. Psychol Bull. 1993;113(1):82–98. Hardt J, Rutter M. Validity of adult retrospective reports of adverse childhood experiences: review of the evidence. J Child Psychol Psychiatry. 2004;45(2):260–73. Additional Declarations No competing interests reported. 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13:03:10","extension":"png","order_by":5,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":75356,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-8389754/v1/ad6b5af532d1cca79b438459.png"},{"id":100406966,"identity":"79caf955-1bfc-4f2d-8944-f06f720055a6","added_by":"auto","created_at":"2026-01-16 13:03:34","extension":"xml","order_by":6,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":129049,"visible":true,"origin":"","legend":"","description":"","filename":"0c138a8b51b24456a2e1a04a97463f541structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-8389754/v1/fd06103fe17fdd947658923f.xml"},{"id":100406971,"identity":"dd81c21b-117f-4c0a-b4e6-ee5262fb3c90","added_by":"auto","created_at":"2026-01-16 13:03:34","extension":"html","order_by":7,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":141961,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8389754/v1/6e53f70d43633a5294d55cf4.html"},{"id":100406710,"identity":"2b4ab810-3d40-4733-8c6a-35c5b22ec30c","added_by":"auto","created_at":"2026-01-16 13:03:11","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":303544,"visible":true,"origin":"","legend":"\u003cp\u003eAssociations between cumulative ACE burden and risk of disability and all-cause mortality. Abbreviations: ACEs, adverse childhood experiences; OR (95%CI), odds ratio (95% confidence interval).\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8389754/v1/87c249ece00405e912ae0b6c.png"},{"id":100414440,"identity":"b9ef23ff-cd0f-449e-9cf0-48ac89e0ae29","added_by":"auto","created_at":"2026-01-16 13:19:20","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1500309,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8389754/v1/d2e16114-bd48-4187-8d02-0b15cadd35b4.pdf"},{"id":100405713,"identity":"cfe363cf-4171-4fd9-a52b-4858974480c0","added_by":"auto","created_at":"2026-01-16 12:16:37","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":150207,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementaryfiles.docx","url":"https://assets-eu.researchsquare.com/files/rs-8389754/v1/2db5bfe51a612bc5df163d25.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Association of adverse childhood experiences with total and disability-free life expectancy in later life: a nationwide multi-state life table analysis","fulltext":[{"header":"BACKGROUND","content":"\u003cp\u003eGlobally, life expectancy (LE) at birth increased by 22.7 years between 1950 and 2021, with a more substantial gain of 28.7 years in China.(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) However, China currently confronts a critical public health challenge: gains in healthy LE (HLE) have not kept pace with increases in total LE (TLE), resulting in an expanding proportion of adults spending their later years in unhealthy states.(\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) Among metrics of HLE, disability-free LE (DFLE), defined as the expected years lived without functional impairment limiting independence, provides a direct measure of geriatric care burdens and social services demands.\u003csup\u003e(3, 4)\u003c/sup\u003e Given China\u0026rsquo;s rapidly aging population with complex care needs, strategies aimed at preventing or delaying functional disability progression have been prioritized within national health policies.(\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eAlthough chronic diseases in later life are primary drivers of functional disability, their risk factors often originate in childhood. The life-course perspective underscores the enduring impact of modifiable early-life exposures on well-being throughout the lifespan. Adverse childhood experiences (ACEs), encompassing a range of potentially stressful experiences (such as abuse, neglect, bullying, household dysfunction, and unsafe communities) during childhood, can trigger long-term health deterioration through complex biological mechanisms including neurodevelopmental disruption, epigenetic alteration, and stress response dysregulation.(\u003cspan additionalcitationids=\"CR7 CR8 CR9 CR10\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e) Beyond their established links to chronic mental and physical diseases, population-based studies have further associated ACEs with the accumulation of non-specific health deficits over time. (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e) Moreover, both experimental animal studies and population-based findings have suggested that ACEs may accelerate biological aging, as evidenced by shortened telomere length and altered DNA methylation patterns.(\u003cspan additionalcitationids=\"CR15\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eDespite biological and clinical plausibility linking ACEs to premature disability and mortality, evidence on their impact on LE or HLE remains scarce. Furthermore, extant evidence predominantly originates from North America and Europe, with a notable paucity of data from Asian populations like China, where the prevalence, subtypes, and sociocultural contexts of ACEs differ substantially.(\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e) To address this critical gap, we conducted a multi-state life table (MSLT) analysis utilizing data from the China Health and Retirement Longitudinal Study (CHARLS) to quantify the associations of ACEs with TLE, years lived disability-free, and years lived with functional disability (assessed via the Activities of Daily Living [ADL] scale) among middle-aged and older adults in China.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design and participants\u003c/h2\u003e \u003cp\u003eThe CHARLS is an ongoing prospective cohort in China. Initiated in 2011, CHARLS enrolled a nationally representative sample of 17,708 residents from 150 counties/districts and 450 villages/resident committees across 28 provinces using multistage stratified probability-proportionate-to-size sampling. Biennial follow-up interviews were conducted from 2013 to 2020, supplemented by a life history survey in 2014. During each wave, trained interviewers administered face-to-face structured questionnaires and physical examinations. Detailed methodological descriptions are available in previous publications.(\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e) The present study was restricted to 14,776 individuals who completed both the 2011 baseline survey and the 2014 life history survey. After further excluding participants aged\u0026thinsp;\u0026lt;\u0026thinsp;45 years at baseline, those lost to follow-up, or those lacking valid data on ADL or ACEs, the final analytical sample comprised 11,033 participants (\u003cb\u003eFigure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e\u003c/b\u003e).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eAdverse childhood experiences\u003c/h3\u003e\n\u003cp\u003eACEs were assessed through self-reported exposures retrospectively collected in the CHARLS life history survey in 2014. Aligned with the ACE International Questionnaire (ACE-IQ) and previous studies,(\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e) 20 ACE-related items were selected to define six subtypes of ACE exposure: childhood adverse family situation, family abuse, adverse personal situation, insufficient companions, adverse communities, and violence (see \u003cb\u003eTable \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e\u003c/b\u003e for detailed item definitions and questionnaire source). Responses to each item were dichotomized as yes or no, and each subtype was coded as present if at least one of its constituent items was endorsed. Accordingly, the cumulative ACE burden was defined as the count of ACE subtypes experienced (ranging from 0 to 6). Based on the distribution of cumulative ACE burden, we further categorized individuals into a low ACE burden group (0\u0026ndash;4 subtypes) and a high ACE burden group (\u0026ge;\u0026thinsp;5 subtypes). The threshold of 5 subtypes was selected as it approximately corresponded to the top 10% of the ACE distribution, representing the most severely exposed subgroup in our sample.\u003c/p\u003e\n\u003ch3\u003eHealth states\u003c/h3\u003e\n\u003cp\u003eFunctional disability was assessed using the ADL scale, a validated measure of physical function for older adults.(\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e) Respondents were asked if they required assistance with six basic physical tasks, including dressing, bathing, eating, transferring, toileting, and continence control. Consistent with established criteria, having difficulty in \u0026ge;\u0026thinsp;1 item was identified as functional disability.(\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e) Accordingly, three mutually exclusive health states (disability-free, disability, and death) were defined and dynamically tracked from baseline until death or the last available follow-up.\u003c/p\u003e\n\u003ch3\u003eBaseline and time-varying covariates\u003c/h3\u003e\n\u003cp\u003eAll covariates were obtained via face-to-face interviews. Socio-demographic variables included age, sex (men/women), education (below high school/high school and above), residence (rural village/urban community), employment status (employed/not employed), marital status (married or partnered/ unmarried including single, divorced, or widowed), and household income per capita (below median/median and above). Household income per capita was selected over total household income as it better reflected economic status, particularly in rural areas.(\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e) Lifestyle variables comprised current smoking (yes/no), current drinking (yes/no), and body mass index (BMI), which was calculated as self-reported weight in kilograms divided by height in meters squared.\u003c/p\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eBasic characteristics of participants were summarized as frequency (percentage) or median (interquartile range, IQR) as appropriate, overall and by stratified baseline functional disability status.\u003c/p\u003e \u003cp\u003eMSLT analysis was employed to model health state transitions as a continuous-time Markov process within a finite state space comprising three mutually exclusive states. Transitions were permitted between the two living states (i.e., disability-free and disability), while the transition to death was irreversible. Therefore, four possible transitions were assumed, that is, from disability-free to disability, from disability-free to death, from disability to disability-free, and from disability to death (\u003cb\u003eFigure S2\u003c/b\u003e). Age-specific state-dependent transition probabilities were estimated using multinomial logistic regression. A simulated cohort of 100,000 individuals aged 45 years at baseline was generated via microsimulation, with survival trajectories projected from age 45 years onwards based on the estimated transition probabilities.(\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e) For each individual in the simulated cohort, time spent in every health state was estimated. Accordingly, the TLE at 45 years was calculated as the average total survival time from age 45 years, with DFLE and DLE defined as the average years lived in the disability-free state and the disabled state, respectively.\u003c/p\u003e \u003cp\u003ePrimary analyses were conducted both unadjusted and adjusted. Adjusted models were fitted with fixed covariates of sex and education measured at baseline, and time-varying covariates (residence, employment status, marital status, and household income per capita). Sensitivity analyses were performed by additionally adjusting for time-varying lifestyle factors of smoking, drinking, and BMI in the models. Moreover, subgroup analyses were conducted to evaluate potential effect modification by sex, education, residence, marital status, and income level.\u003c/p\u003e \u003cp\u003eAll analyses were performed using SAS version 9.4 (SAS Institute Inc). A two-sided \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eEthical Considerations\u003c/h2\u003e \u003cp\u003e The study protocol was approved by the Ethics Review Committee of Peking University (IRB00001052-11015) and all participants provided written informed consent before participation.\u003c/p\u003e \u003c/div\u003e"},{"header":"RESULTS","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eParticipant characteristics\u003c/h2\u003e \u003cp\u003eThe final analytical sample comprised 11,033 participants, with 49.7% being male and a median age of 57.0 years (IQR:51.0\u0026ndash;64.0). Baseline assessment identified 17.1% of participants in the disabled state and 82.9% as disability-free. Participants with functional disability exhibited significantly higher prevalence of all ACE subtypes and greater cumulative ACE burden compared to disability-free individuals. They were also more likely to be less well-educated, unmarried, and have lower household income per capita, with a higher proportion of women and rural residents (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBaseline characteristics according to disability states at baseline survey.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDisability free\u003c/p\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;9,142\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDisability\u003c/p\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;1,891\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;11,033\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge, years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e57.0 (51.0, 64.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e63.0 (56.0, 70.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e58.0 (52.0, 65.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4544 (49.70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e757 (40.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5301 (48.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRural Village\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5988 (65.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1406 (74.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7394 (67.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh school and above\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1034 (11.31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e81 (4.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1115 (10.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarried or partnered\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8152 (89.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1543 (81.60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9695 (87.87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHousehold income per capita\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3685.4 (1000.0, 9333.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1850.0 (500.0, 5513.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3228.6 (840.0, 8495.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEmployed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6336 (69.31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e918 (48.55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7254 (65.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCurrent smoking\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2824 (30.89)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e450 (23.80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3274 (29.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCurrent drinking\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3207 (35.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e476 (25.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3683 (33.38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBody mass index, kg/m\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e23.0 (20.8, 25.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e22.9 (20.4, 26.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e23.0 (20.7, 25.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.51\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSubtypes of ACEs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChildhood adverse family situation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6306 (68.98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1482 (78.37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7788 (70.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChildhood family abuse\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3797 (41.53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e922 (48.76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4719 (42.77)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChildhood adverse personal situation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7401 (80.96)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1637 (86.57)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9038 (81.92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChildhood lacking companions\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5183 (56.69)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1265 (66.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6448 (58.44)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChildhood adverse communities\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1001 (10.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e316 (16.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1317 (11.94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChildhood violence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1270 (13.89)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e386 (20.41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1656 (15.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCumulative counts of ACE subtypes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e319 (3.49)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e24 (1.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e343 (3.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1227 (13.42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e162 (8.57)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1389 (12.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2439 (26.68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e399 (21.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2838 (25.72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2695 (29.48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e595 (31.46)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3290 (29.82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1727 (18.89)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e411 (21.73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2138 (19.38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e550 (6.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e181 (9.57)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e731 (6.63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e185 (2.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e119 (6.29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e304 (2.76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eData are expressed as frequency (%) or median (inter-quartile range, IQR). Between-group comparisons were done using χ2 test or Fisher's exact test or Mann-Whitney U test, where appropriate. Abbreviations: ACEs, adverse childhood experiences.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003ePrimary findings\u003c/h2\u003e \u003cp\u003eAs illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and \u003cb\u003eTable S3\u003c/b\u003e, individuals with higher cumulative ACE burden had greater transition probabilities to develop functional disability and were less likely to recover from disability state to disability-free state. Notably, mortality risk increased substantially for those exposed to \u0026ge;\u0026thinsp;5 subtypes of ACEs, regardless of initial health status. After adjustment, TLE at 45 years decreased from 46.0 years for low ACE burden individuals to 38.2 years for those with high ACE burden, while the corresponding DFLE shortened from 31.7 years to 23.4 years, with the proportion of DFLE in TLE declining from 69.0% to 61.3%. The magnitude of reductions in TLE and DFLE was comparable for individuals initially in disability-free or disabled states (\u003cb\u003eTable S2\u003c/b\u003e, Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Besides, the detrimental impact of ACEs was observed to be persistent throughout the lifespan: At age 45 years, participants with low and high ACE burden spent 31.0% and 38.7% of remaining TLE with functional disability; By age 85 years, the corresponding proportions rose to 59.8% and 68.8%, respectively (\u003cb\u003eFigure S3\u003c/b\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eTotal life expectancy (TLE), disability free life expectancy (DFLE), and disability life expectancy (DLE) at age 45 years by low and high burden of adverse childhood experiences (ACEs).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eACE burden\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eLE, years\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTLE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDFLE, (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDLE, (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eUnadjusted\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOverall\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow ACE burden\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e42.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30.0 (70.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.5 (29.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh ACE burden\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e35.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22.9 (63.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13.0 (36.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eInitial state of disability free\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow ACE burden\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e42.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30.3 (71.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.2 (28.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh ACE burden\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e35.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23.3 (64.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.6 (35.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eInitial state of disability\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow ACE burden\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e42.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27.4 (64.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14.8 (35.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh ACE burden\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e35.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20.3 (56.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15.4 (43.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAdjusted\u003c/b\u003e\u003csup\u003e\u003cb\u003e*\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOverall\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow ACE burden\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e46.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31.7 (69.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14.3 (31.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh ACE burden\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e38.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23.4 (61.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14.8 (38.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eInitial state of disability free\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow ACE burden\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e46.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32.1 (69.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14.0 (30.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh ACE burden\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e38.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24.0 (62.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14.4 (37.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eInitial state of disability\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow ACE burden\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e45.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29.1 (63.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16.4 (36.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh ACE burden\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e37.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20.6 (55.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16.8 (44.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e*Sex, education level, time-varying residence, time-varying marital status, time-varying employment status, and time-varying household income per capita were adjusted. Abbreviations: ACEs, adverse childhood experiences; DFLE, disability free life expectancy; DLE, disability life expectancy; LE, life expectancy.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAnalyses of each ACE subtype revealed generally consistent associations, though childhood adverse communities and childhood violence exhibited particularly strong effects (\u003cb\u003eTable S4\u003c/b\u003e). Compared to disability-free individuals unexposed to childhood violence, those exposed had 39% higher risk of disability (odds ratio [OR]: 1.39, 95% confidence interval [95%CI]: 1.29\u0026ndash;1.51) and 37% higher risk of death (OR:1.37, 95%CI:1.08\u0026ndash;1.75). Meanwhile, exposure to each ACE subtype was related to reduced TLE and DFLE at age 45 years, alongside enlarged proportion of life spent in the disabled state (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). For instance, childhood adverse family situation shortened DFLE by 4 years (29.4 years vs. 33.4 years) and reduced the DFLE proportion from 74.6% to 66.8%.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eTotal life expectancy (TLE), disability free life expectancy (DFLE), and disability life expectancy (DLE) at age 45 years by subtypes of adverse childhood experiences (ACEs).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eACE subtypes\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eAdjusted LE\u003csup\u003e*\u003c/sup\u003e, years\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTLE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDFLE, (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDLE, (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eChildhood adverse family situation\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAbsent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e44.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33.4 (74.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.4 (25.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePresent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e44.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29.4 (66.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14.6 (33.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eChildhood family abuse\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAbsent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e45.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31.8 (70.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13.4 (29.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePresent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e43.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28.9 (66.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14.5 (33.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eChildhood adverse personal situation\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAbsent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e45.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34.0 (75.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.3 (25.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePresent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e44.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29.8 (67.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14.3 (32.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eChildhood lacking companions\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAbsent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e45.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31.8 (70.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13.3 (29.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePresent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e44.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29.8 (67.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14.2 (32.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eChildhood adverse communities\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAbsent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e45.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31.5 (68.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14.3 (31.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePresent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26.2 (64.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14.3 (35.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eChildhood violence\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAbsent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e45.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31.7 (69.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14.2 (30.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePresent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e39.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25.4 (63.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14.4 (36.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e*Sex, education level, time-varying residence, time-varying marital status, time-varying employment status, and time-varying household income per capita were adjusted. Abbreviations: ACEs, adverse childhood experiences; DFLE, disability free life expectancy; DLE, disability life expectancy; TLE, total life expectancy.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eSensitivity and stratified analyses\u003c/h2\u003e \u003cp\u003eSensitivity analyses with further adjustments for time-varying lifestyle variables produced results consistent with primary findings \u003cb\u003e(\u003c/b\u003e\u003cb\u003eTable S5\u0026ndash;S6\u003c/b\u003e). Stratified analyses demonstrated generally homogeneous effects, whereas significant interactions were observed with sex and marital status. In comparison with men, high ACE burden was associated with greater probabilities of disability-to-death transition among women (\u003cem\u003eP\u003c/em\u003e \u003csub\u003einteraction\u003c/sub\u003e=0.03), which resulted in greater TLE reduction (-9.7 years vs -6.0 years). Similarly, the association between ACE burden and disability incidence was stronger among married/partnered individuals than unmarried counterparts (\u003cem\u003eP\u003c/em\u003e \u003csub\u003einteraction\u003c/sub\u003e=0.01), resulting in a larger decrease in the proportion of DFLE (-9.8% vs. -2.5%) (\u003cb\u003eTable S7\u003c/b\u003e and Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eStratified analyses of total life expectancy (TLE), disability free life expectancy (DFLE), and disability life expectancy (DLE) at age 45 years by low and high burden of adverse childhood experiences (ACEs).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eStratified analyses\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eAdjusted LE\u003csup\u003e*\u003c/sup\u003e, years\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTLE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDFLE, (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDLE, (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBy sex\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMen\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow ACE burden\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e43.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32.3 (75.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.7 (24.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh ACE burden\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e37.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24.6 (66.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.4 (33.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWomen\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow ACE burden\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e49.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31.1 (63.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18.0 (36.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh ACE burden\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e39.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22.6 (57.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16.8 (42.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBy education\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBelow high school\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow ACE burden\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e45.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31.1 (68.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14.4 (31.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh ACE burden\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e38.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23.0 (60.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15.2 (39.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHigh school and above\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow ACE burden\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e53.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e36.9 (69.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16.3 (30.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh ACE burden\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e36.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25.7 (70.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.6 (29.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBy residence\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRural village\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow ACE burden\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e45.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30.8 (68.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14.3 (31.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh ACE burden\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e38.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23.0 (59.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15.4 (40.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eUrban community\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow ACE burden\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e47.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33.2 (69.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14.5 (30.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh ACE burden\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e37.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24.1 (64.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13.3 (35.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBy marital status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMarried/partnered\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow ACE burden\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e45.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31.6 (69.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13.9 (30.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh ACE burden\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e39.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23.3 (59.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15.8 (40.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eUnmarried\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow ACE burden\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e42.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27.7 (65.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14.8 (34.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh ACE burden\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e33.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21.0 (62.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.5 (37.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBy household income per capita\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBelow median\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow ACE burden\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e45.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31.1 (69.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13.9 (30.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh ACE burden\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e38.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23.4 (61.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14.6 (38.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMedian and above\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow ACE burden\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e48.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32.7 (67.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15.6 (32.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh ACE burden\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e38.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23.5 (61.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14.8 (38.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e*Sex, education level, time-varying residence, time-varying marital status, time-varying employment status, and time-varying household income per capita were adjusted, expect the stratified variable itself. Abbreviations: ACEs, adverse childhood experiences; DFLE, disability free life expectancy; DLE, disability life expectancy; TLE, total life expectancy.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eThis nationally representative longitudinal study revealed that high cumulative ACE burden was associated with elevated risks of functional disability and premature death, corresponding to shortened TLE and reduced DFLE proportion. Individuals aged 45 years with high ACE burden had a 7.8-year shorter TLE than their counterparts with low burden and spent only 61.3% of remaining life disability-free (vs. 69.0% in the low ACE burden group). Among ACE subtypes, childhood violence exhibited the strongest associations, with 6.0-year reduction in TLE and 6.3-year reduction in DFLE. Stratified analyses further indicated heightened vulnerability to ACEs among women and married/partnered individuals, while no significant effect modification was observed for education, residence, and income. To our knowledge, this is the first study quantifying the association of ACE, both cumulative and subtype-specific, with DFLE and its proportion in TLE in China, a rapidly aging population underexplored in prior research.\u003c/p\u003e \u003cp\u003eBeyond well-documented associations between ACEs and chronic diseases or multimorbidity across the lifespan,(\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan additionalcitationids=\"CR24 CR25 CR26\" citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e) emerging evidence has indicated that ACEs might accelerate functional decline. For instance, the Survey of Health Aging and Retirement in Europe reported a graded relationship between ACEs and ADL limitations.(\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e) A longitudinal study further indicated that ACEs predicted accelerating functional decline.(\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e) Complementing this, the Danish Life Course cohort study proved that multi-domain ACEs correlated with elevated mortality risk in early adulthood.(\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e) Despite these advances, critical knowledge gaps still persist. As far as we know, no prior longitudinal study has simultaneously quantified the impact of ACEs on both functional disability and life-years lost. Therefore, it remains unclear whether ACE prevention could translate to extended healthy longevity, as the self-care ability of daily living itself gradually deteriorates with age starting in midlife.\u003c/p\u003e \u003cp\u003eOur findings substantiate and further extend existing evidence. We revealed that high ACE burden shortened TLE primarily through reducing DFLE, thereby increasing the proportion of life spent with functional disability. Notably, beyond replicating the gradient relationship between cumulative ACE burden and disability incidence, our current analyses indicated that individuals with higher ACE burden were less likely to recover from the disabled state to functional independence, thus further shortening DFLE. The association between high ACE burden and mid-adulthood mortality was also confirmed in our analyses, regardless of initial self-care capacity. Moreover, few prior studies have examined the specific impact of ACE subtypes, and the limited evidence shows significant heterogeneity across populations and health outcomes.(\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e) The Collaborative Perinatal Project (CPP), for example, reported that the cluster of poverty and crowded housing was associated with higher risk of premature mortality for U.S population,(\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e) whereas a retrospective study conducted in China revealed that individuals with childhood adverse family and personal situations had the highest risk for mental health disorder in later life. (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e) As an extension to current literature, our study identified that childhood violence, including childhood bully and crime, led to the greatest loss in both TLE and DFLE. Given the relatively high prevalence of childhood exposure to domestic and family violence,(\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e) the issue of child violence necessitates more specialized research attention. Furthermore, there is a pressing need for culturally sensitive prevention and intervention services provided by governments and welfare organizations.\u003c/p\u003e \u003cp\u003eOf note, the current analyses identified significant effect modifications by sex and marital status, with women and married/partnered individuals exhibiting heightened vulnerability to functional disability or mortality. While available evidence on the interaction between sex and ACEs remains inconsistent, neuroendocrine mechanisms could be a possible explanation: sex differences in the hypothalamic-pituitary-adrenal axis dysregulation in response to stress may render women more susceptible to the consequences of psychosocial stress, including ACEs.(\u003cspan additionalcitationids=\"CR34\" citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e) The modification effect of marriage status should be interpreted with more caution. Although marriage traditionally confers psychosocial and economic protective benefits, marital distress and conflict are also linked to poor physical health.(\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e) For those with high ACE burden, marriage may represent a source of conflict rather than support, thus paradoxically exacerbating their health risks. More longitudinal studies should incorporate marital satisfaction metrics and reasons for non-marriage to further elucidate this counterintuitive finding.\u003c/p\u003e \u003cp\u003eThis study has several notable strengths. Critically, while the conventional 10-item ACE scales from the CDC- Kaiser Permanente ACE Study has been widely applied, emerging evidence underscores sociocultural variations in ACE subtypes and perceptions across population.(\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e) To address this, we defined ACEs using 20 validated items from the CHARLS life history survey, which were believed to better capture the most intensive and frequently occurring sources of stress in Chinese childhood contexts.(\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e) Moreover, since certain ACE subtypes may exert disproportionate health effects, we analyzed the impact of ACE exposure by not only total burdens but also subtypes, which provide further insights beyond prior studies relying solely on summed ACE counts.(\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e) Methodologically, our application of the time-inhomogeneous, finite-space, continuous-time Markov models enabled simultaneous quantification of ACE effects on disability incidence, functional recovery, and premature death, thereby generating integrated estimates of healthspan reduction. Finally, the nationally representative sampling, the large sample size, and the longitudinal design with repeated follow-ups collectively enhanced the validity and generalizability of our findings.\u003c/p\u003e \u003cp\u003eNonetheless, several limitations also warrant consideration. Firstly, retrospective ascertainments of ACEs in the 2014 life history survey might induce recall bias, despite that previous studies have demonstrated the good test-retest reliability of adult-recall ACE measures.(\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e) Secondly, even though a wide range of ACE-related items have been included, some crucial ACE subtypes like sexual abuse were not evaluated due to lack of data, which might bias effect estimates. Besides, our analyses did not consider the life-course window, frequency, or severity of ACEs, whereas all of them might modulate health consequences. Further studies incorporating prospective ACE assessments with detailed exposure characterization are needed to further advance knowledge about the long-term negative consequences of ACEs.\u003c/p\u003e"},{"header":"CONCLUSIONS","content":"\u003cp\u003eIn conclusion, this longitudinal study revealed that higher ACE burden was associated with elevated risks of functional disability and premature mortality among middle-aged and older Chinese adults, resulting in shortened TLE and compressed disability-free survival. Notably, childhood violence linked to the highest risk among ACE subtypes, and women exhibited heightened susceptibility to ACE-related health consequences. These findings underscored the need for multisectoral ACE prevention initiatives and life-course health strategies to mitigate resultant disability and death, with targeted interventions on childhood violence and enhanced support programs for high-risk women.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003eACEs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 350px;\"\u003e\n \u003cp\u003eadverse childhood experiences\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003eADL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 350px;\"\u003e\n \u003cp\u003eActivities of Daily Living\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003eBMI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 350px;\"\u003e\n \u003cp\u003ebody mass index\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003eCHARLS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 350px;\"\u003e\n \u003cp\u003eChina Health and Retirement Longitudinal Study\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003eCI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 350px;\"\u003e\n \u003cp\u003econfidence interval\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003eCPP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 350px;\"\u003e\n \u003cp\u003eCollaborative Perinatal Project\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003eDFLE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 350px;\"\u003e\n \u003cp\u003edisability-free life expectancy\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003eHLE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 350px;\"\u003e\n \u003cp\u003ehealthy life expectancy\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003eIQR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 350px;\"\u003e\n \u003cp\u003einterquartile range\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003eMLST\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 350px;\"\u003e\n \u003cp\u003eMulti-state life table\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003eOR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 350px;\"\u003e\n \u003cp\u003eodds ratio\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003eTLE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 350px;\"\u003e\n \u003cp\u003etotal life expectancy\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003eEthics approval and consent to participate\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study protocol was approved by the Ethics Review Committee of Peking University (IRB00001052-11015) and all participants provided written informed consent before participation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eConsent for publication\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eNot applicable.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAvailability of data and materials\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData used for the analyses are publicly available from the China Health and Retirement Longitudinal Study (https://charls.charlsdata.com/pages/data/111/zh-cn.html).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eCompeting interests\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eFunding\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNone.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAuthors\u0026apos; contributions\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eXX: conceptualization, data curation, writing-original draft, writing-review \u0026amp; editing.\u003c/p\u003e\n\u003cp\u003eXT: data curation, conceptualization.\u003c/p\u003e\n\u003cp\u003eQX: data curation, supervision.\u003c/p\u003e\n\u003cp\u003eYZ: data curation.\u003c/p\u003e\n\u003cp\u003eXZ: data curation\u003c/p\u003e\n\u003cp\u003eJL: data curation.\u003c/p\u003e\n\u003cp\u003eAW: writing-review \u0026amp; editing, supervision, conceptualization.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAcknowledgements\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors acknowledged all staff and participants of the China Health and Retirement Longitudinal Study (CHARLS) for their important participation and contribution.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eGBD2021DemographicsCollaborators. 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Lancet. 2020;396(10249):489\u0026ndash;97.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYu J, Patel RA, Haynie DL, Vidal-Ribas P, Govender T, Sundaram R et al. Adverse childhood experiences and premature mortality through mid-adulthood: A five-decade prospective study. Lancet Reg Health Am. 2022;15.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWhitten T, Tzoumakis S, Green MJ, Dean K. Global Prevalence of Childhood Exposure to Physical Violence within Domestic and Family Relationships in the General Population: A Systematic Review and Proportional Meta-Analysis. Trauma Violence Abuse. 2024;25(2):1411\u0026ndash;30.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGilbert R, Widom CS, Browne K, Fergusson D, Webb E, Janson S. Burden and consequences of child maltreatment in high-income countries. Lancet. 2009;373(9657):68\u0026ndash;81.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRao RT, Androulakis IP. Modeling the Sex Differences and Interindividual Variability in the Activity of the Hypothalamic-Pituitary-Adrenal Axis. Endocrinology. 2017;158(11):4017\u0026ndash;37.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSoares ALG, Hammerton G, Howe LD, Rich-Edwards J, Halligan S, Fraser A. Sex differences in the association between childhood maltreatment and cardiovascular disease in the UK Biobank. Heart. 2020;106(17):1310\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSouth SC, Krueger RF. Marital satisfaction and physical health: evidence for an orchid effect. Psychol Sci. 2013;24(3):373\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSouth SC, Mann FD, Krueger RF. Marital Satisfaction as a Moderator of Molecular Genetic Influences on Mental Health. Clin Psychol Sci. 2021;9(4):719\u0026ndash;31.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFelitti VJ, Anda RF, Nordenberg D, Williamson DF, Spitz AM, Edwards V, et al. Relationship of childhood abuse and household dysfunction to many of the leading causes of death in adults. The Adverse Childhood Experiences (ACE) Study. Am J Prev Med. 1998;14(4):245\u0026ndash;58.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBrewin CR, Andrews B, Gotlib IH. Psychopathology and early experience: a reappraisal of retrospective reports. Psychol Bull. 1993;113(1):82\u0026ndash;98.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHardt J, Rutter M. Validity of adult retrospective reports of adverse childhood experiences: review of the evidence. J Child Psychol Psychiatry. 2004;45(2):260\u0026ndash;73.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"population-health-metrics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pohm","sideBox":"Learn more about [Population Health Metrics](http://pophealthmetrics.biomedcentral.com/)","snPcode":"12963","submissionUrl":"https://submission.nature.com/new-submission/12963/3","title":"Population Health Metrics","twitterHandle":"@PHMjournal","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"adverse childhood experience, Activities of Daily Living, life expectancy, multi-state life tables, CHARLS","lastPublishedDoi":"10.21203/rs.3.rs-8389754/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8389754/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eAdverse childhood experiences (ACEs) can trigger long-term health deficits, whereas their overall impact on disability-free longevity remains underexplored. This study aimed to examine the association of ACEs with functional disability and mortality, thus quantifying their effects on total life expectancy (TLE) and disability-free LE (DFLE).\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003e The China Health and Retirement Longitudinal Study (CHARLS) was a nationwide cohort established in 2011 and followed up until 2020. we included 11,033 individuals aged\u0026thinsp;\u0026ge;\u0026thinsp;45 years with data on ACEs and Activities of Daily Living (ADL) at baseline and during follow-ups. ACEs were assessed retrospectively via 20 items as 6 subtypes. Cumulative ACE burden was defined as counts of ACE subtypes (0\u0026ndash;6) and further classified as low (0\u0026ndash;4) and high ACE burden group (\u0026ge;\u0026thinsp;5). Functional disability was defined as difficulty in \u0026ge;\u0026thinsp;1 ADL item. Multi-state life table (MLST) was adopted to estimate TLE and DFLE related to ACE burden. Modification by sociodemographic characteristics was assessed via stratified analyses.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eOf individuals included, the median age was 57.0 years, 49.7% were men, and 82.9% were identified as disability-free. Higher ACE burden was associated with elevated risks of disability and premature death. TLE was 46.0 years for low ACE burden versus 38.2 years for high ACE burden, of which 31.7 years (69.0%) and 23.4 years (61.3%) were spent disability-free, respectively. Childhood violence exhibited the strongest impact among all subtypes, with odds ratio (OR) and 95% confidence interval (CI) of 1.39 (1.29\u0026ndash;1.51) for transition to disability and 1.37 (1.08\u0026ndash;1.75) for transition to death from a disability-free state. Significant interactions by sex (\u003cem\u003eP\u003c/em\u003e \u003csub\u003einteraction\u003c/sub\u003e=0.03) and marital status (\u003cem\u003eP\u003c/em\u003e \u003csub\u003einteraction\u003c/sub\u003e=0.01) were observed, heightening the vulnerability of women and married/partnered participants.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eFor middle-aged and older Chinese, high ACE burden was associated with reduced longevity and enlarged healthspan-lifespan gap, emphasizing the importance of preventing ACEs to promote healthy aging.\u003c/p\u003e","manuscriptTitle":"Association of adverse childhood experiences with total and disability-free life expectancy in later life: a nationwide multi-state life table analysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-16 10:42:58","doi":"10.21203/rs.3.rs-8389754/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-05-03T11:10:18+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"317010705935971167774589083442499757938","date":"2026-04-16T14:26:32+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"55278882795516392048199389203776078611","date":"2026-02-05T12:53:19+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-01-12T18:52:20+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-12-23T22:00:29+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-12-23T21:59:56+00:00","index":"","fulltext":""},{"type":"submitted","content":"Population Health Metrics","date":"2025-12-18T00:42:25+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"population-health-metrics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pohm","sideBox":"Learn more about [Population Health Metrics](http://pophealthmetrics.biomedcentral.com/)","snPcode":"12963","submissionUrl":"https://submission.nature.com/new-submission/12963/3","title":"Population Health Metrics","twitterHandle":"@PHMjournal","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"d274bf6a-240a-437e-ac35-b6a90b60b224","owner":[],"postedDate":"January 16th, 2026","published":true,"recentEditorialEvents":[{"type":"editorInvitedReview","content":"","date":"2026-05-03T11:10:18+00:00","index":37,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-01-16T10:42:58+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-16 10:42:58","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8389754","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8389754","identity":"rs-8389754","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}