Associations between adverse childhood experiences and progression to incident psychiatric disorders in older adults: A 22-year cohort study

Associations between adverse childhood experiences and progression to incident psychiatric disorders in older adults: A 22-year cohort study | 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 Article Associations between adverse childhood experiences and progression to incident psychiatric disorders in older adults: A 22-year cohort study Hui-Ying Fan, Mu-Rui Zheng, Xiao-Xuan Meng, Qinge Zhang, Zhi-Cheng Du, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7307635/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 19 You are reading this latest preprint version Abstract The long-term impact of adverse childhood experiences (ACEs) on the development of psychiatric disorders in older adults remains unclear. This study examined associations between ACEs and incident psychiatric disorders in older adults (PDOA) over 22 years. Data from the 2000–2022 Health and Retirement Study (HRS) were analyzed. Time-varying Cox regression and multistate Markov models were applied to explore the impact of ACEs on transitions across five health states: healthy, physical conditions (PC), mental symptoms (MS), comorbid PC & MS, and PDOA. Models were adjusted for demographic, behavioral, and disease-related factors. Among 8,628 participants during average 16.8-year follow-up, 1,429 developed psychiatric disorders (incidence: 9.85 per 1,000 person-years). ACEs, particularly trauma/ violence (aHR = 1.279) and family dysfunction (aHR = 1.358), were significantly associated with higher risk. A dose-response relationship was found. Participants with ACEs had higher transition percentages and intensities from healthy to less healthy states, notably from PC & MS to PDOA (percentages: 3.7% vs. 3.2%) and from the healthy state to MS (intensities: 0.130 vs. 0.104). They also spent less time in the healthy state and more time in comorbid states, with a 33% higher 22-year cumulative probability of PDOA (25.3% vs. 19.0%). Risk was further elevated by younger age, female sex, higher educational level, low physical activity, insomnia, lung diseases, and arthritis. ACEs appear to have enduring adverse impacts on mental health in later life by accelerating the progression to comorbidity and the development of psychiatric disorders. Early screening and physical-mental health interventions are essential for prevention. Health sciences/Diseases/Psychiatric disorders Health sciences/Biomarkers/Predictive markers adverse childhood experiences psychiatric disorder older adults disease progression comorbidities Figures Figure 1 Figure 2 Figure 3 1. Introduction With the rapidly aging population worldwide, poor mental health in older adults has become a major public health challenge, contributing substantially to high disability, low quality of life and increased healthcare utilization 1 . Previous research found that approximately 14% of individuals aged 60 and above suffer from psychiatric disorders globally 2 . The 2019 Global Health Estimates indicated that mental health conditions, particularly depression and anxiety, accounted for 10.6% of the total disability-adjusted life years (DALYs) among older adults 1 . Mental health in later life is largely influenced by physical conditions, social environments as well as the cumulative effects of life experiences. Factors, such as exposure to adversity, loss of intrinsic capacity and declining functional ability, can lead to increased psychological distress 1 . Among the early life factors, adverse childhood experiences (ACEs) have emerged as a critical determinant of mental well-being with lasting impact on mental health across the lifespan. ACEs refer to experiences of potentially traumatic events occurring before age 18 years, which can disrupt a person’s sense of safety, stability, and bonding 3 . Common types of ACEs include child abuse, neglect, or household dysfunction involving substance abuse, mental illness, incarceration, domestic violence and parental separation or divorce 3 , 4 . Additionally, research on ACEs has expanded the scope to other significant stressors such as exposure to natural disasters, extreme economic hardship, bullying, school and community violence, life-threatening illnesses or injuries, and even school grade retention 5 , 6 . Exposure to ACEs can increase the risk of a wide range of psychiatric problems, including depression, anxiety, post-traumatic stress disorder and substance use disorders 7 – 12 . For example, a large birth cohort study found that each additional ACE was associated with a 52% increase in the odds of developing any psychiatric disorder in adulthood, even after adjusting for shared genetic and environmental influences 12 . Neuroimaging research has shown that ACEs can lead to alterations of blood flow, activity, and connectivity in specific brain regions which may potentially mediate the impact of ACEs on the development of psychiatric disorders 13 , 14 . Despite the growing body of evidence, most studies have focused on the associations between ACEs and mental health issues among children, adolescents, young and middle-aged adults, with relatively few longitudinal studies tracking the progression of psychiatric disorders into later life 15 . In addition, most studies used cross-sectional designs or short follow-up periods, which limit the ability to capture the dynamic changes in mental health status over time. There is a lack of research on how ACEs can influence the transition between different mental states in older populations, such as from subclinical symptoms to a diagnosed psychiatric disorder. Furthermore, late-life psychiatric disorders often co-occur with chronic physical illnesses, which may affect the progression and management of psychiatric disorders 16 . To address these gaps, we conducted a cohort study using follow-up data from the nationally representative Health and Retirement Study (HRS) across a 22-years period to: (1) examine the associations between different ACEs and the incidence of psychiatric disorders, incorporating time-varying covariates and repeated assessments; and (2) explore how ACEs influence the changes across various health states (e.g., physical and mental health symptoms transitioning to psychiatric disorders). Findings from this study could inform the development of preventive measures to mitigate the adverse impact of ACEs, and intervention strategies to improve the mental health outcomes in older populations. 2. Methods 2.1 Study design and samples This was a cohort study based on the most recent 22-year dataset (2000–2022; waves 5–16) of the Health and Retirement Study (HRS). The HRS is a nationally representative longitudinal study that has biennially surveyed U.S. residents aged 50 and older since 1992 (Wave 1). The study is funded by the National Institute on Aging (grant numbers NIA UO1AG009740 and NIA RO1AG073289) and is conducted by the University of Michigan 17 . The details of the HRS methodology have been described previously (Heeringa and Connor, 1995). Our study used the data obtained from the RAND HRS Longitudinal File (Version P, including 2000–2020 wave of sociodemographic and health-related data), HRS core data (including ACEs-related data and 2022 wave of all related data) and exit data (including all-cause mortality data). The RAND HRS Longitudinal File, developed by the RAND Center for the Study of Aging, provides systematically cleaned and processed data from all waves of the HRS except for the 2022 wave 18 . The study cohort included individuals who participated in the 2000 wave (i.e., baseline) and followed up longitudinally to 2022. Participants who fulfilled the inclusion criteria: 1) were aged 50 years or older at baseline; 2) were interviewed during at least one follow-up assessment; 3) completed ACEs assessments during the 2008–2012 surveys; and 4) had no psychiatric disorders at baseline. For covariates with missing values related to demographic, health, or lifestyle variables, we applied imputation using last observation carried forward (LOCF) and next observation carried forward (NOCF), as previously recommended 19 , 20 . The HRS received ethical approval from the Institutional Review Board of Virginia Commonwealth University (HM20023839). All participants provided informed consent. As a secondary analysis of HRS data, this study was exempt from ethical review. 2.2 Measurements 2.2.1 Adverse childhood experiences Following previous studies 21 , 22 , the presence of ACEs was assessed using nine items extracted from the Leave-Behind Questionnaires (LBQ) 23 , 24 that was completed during the 2008–2012 waves of the HRS. Participants were asked whether they had ever experienced the events before 18 years old or that the year of ACE occurrence before 18 years old was recorded in the HRS database. All items were handled as binary variables (1="Yes" and 0= "No"). The total scores of ACEs ranged from 0 to 9, with higher scores indicating more severe ACEs. As per previous research 6 , 24 , 25 , ACEs were classified into three types: Trauma & violence (4 items including “been in a major fire or disaster”, “fire a weapon in combat”, “ever victim of physical attack”, and “life-threatening illness”), Family dysfunction (3 items including “mother neglect”, “parents drink or use drugs and caused family problems”, and “physical abused by parents”) and Social problem (2 items including a year of school over again, and trouble with the police). The description and coding of the ACE items are listed in Table S1 . 2.2.2 Incidence of psychiatric disorders Following previous research 26 , psychiatric disorders were identified based on the standardized question at each HRS wave: “Have you been diagnosed with emotional, nervous, or psychiatric problem by a doctor?”. The study outcome was the incidence of psychiatric disorders which was first identified during follow-up. 2.2.3 Covariates 2.2.3.1 Sociodemographic data Sociodemographic variables potentially related to psychiatric disorders included age, sex (male vs. female), race (White/ Caucasian, Black/ African American or other), marital status (categorized as married, divorced/separated, widowed, or never married/other), educational level (> 12 years vs. ≤12 years), living with others (yes vs. no), vigorous physical activity (≥ 3 times/ week, yes vs. no), alcohol use (yes vs. no) and cigarette smoking (yes vs. no). 2.2.3.2 Health-related variables Chronic diseases included self-reported physician-diagnosed major physical diseases recorded in the HRS such as diabetes, cancer, heart disease, stroke, hypertension, lung diseases, and arthritis. Depression was evaluated using the 8-item Center for Epidemiologic Studies Depression Scale (CESD-8) 27 . Each item was scored as 1 or 0 (yes or no), with items 4 and 6 being reverse scored. The total scores ranged from 0 to 8, with higher scores indicating more severe depressive symptoms. A cutoff score of 4 was used to identify individuals having depressive symptoms (depression hereafter) 28 . Cognitive function was assessed using the modified version of the Telephone Interview for Cognitive Status (TICS-m) 29 . Following a previous study 30 , the total score of TICS-m was calculated by adding up the respective scores of memory, attention and calculation domains, which ranged from 0 to 27, with higher scores indicating better cognitive performance. A cutoff score of 11 was used to identify individuals having cognitive impairment 31 , 32 . Sleep was measured using the 4-item Jenkins Sleep Scale (JSS-4) 33 . Each item was rated on a 3-point Likert scale ranging from 1 (“most of the time”) to 3 (“rarely or never”). Item 4 was reverse scored. Higher total scores reflected more severe insomnia symptoms, and a cutoff score of 5 was used to identify those with insomnia symptoms (insomnia hereafter) 34 . All covariates were assessed at each HRS biennial wave. 2.3 Statistical Analyses Frequencies and percentages as well as means and standard deviations (SDs) were used to describe categorical and continuous variables, respectively. All covariates were compared between different ACE types using Chi-square, t and Wilcoxon rank sum tests, as appropriate. All statistical analyses were conducted using R (version 4.4.2) 35 . A two-sided P -value < 0.05 was considered statistically significant. To examine the longitudinal association between ACEs and the risk of psychiatric disorders in older age (PDOA), we used Cox proportional hazards regression models with time-varying covariates 36 . Participants were followed up from baseline (2000) until the occurrence of a psychiatric disorder, death, loss to follow-up, or end of study (2022), whichever came first. Time-varying covariates, such as health-related variables and lifestyle factors, were updated at each wave to account for the changes over time. Three Cox models were constructed, adding covariates progressively. Model 1 adjusted for age, sex and race; Model 2 added marital status, education level, living with others, lifestyle variables (i.e., smoking, alcohol use, and vigorous physical activity) based on Model 1; Model 3 further added major physical diseases (i.e., diabetes, cancer, heart conditions, stroke, hypertension, lung diseases, and arthritis), depression (i.e., total CESD-8 score), insomnia (i.e., total JSS-4 score) and cognitive function (i.e., total TICS-m scores) based on Model 2. Following previous studies 12 , 37 , ACEs were analyzed in three forms: (1) ACE type (i.e., no ACEs, Trauma & violence, Family Dysfunction, Social problems) with no ACEs group as the reference; (2) total number of ACEs (i.e., 0, 1, 2, and 3 + ACEs) as a categorical variable with the 0 ACE group as the reference, and (3) continuous ACE scores (ranging, 0–9). Schoenfeld residuals were used to assess the proportional hazards assumption and to ensure no violation was found. Kaplan-Meier survival curves were plotted to examine potential differences in incidence rates across types and number of ACEs. We also conducted subgroup analyses to explore whether the associations between ACEs and the incidence of PDOA were moderated by age (50–64 years vs. ≥65 years), sex, marital status, educational level, living with others, alcohol use, cigarette smoking, engagement in vigorous activity, insomnia (JSS-4 scores < 4 vs. ≥4), depression (CESD < 5 vs. ≥5), and cognitive impairment (TICS-m ≤ 11) between the group with and without ACEs. To assess the robustness of the associations between ACEs and the incidence of psychiatric disorders, five sensitivity analyses were conducted by: (1) excluding cases with psychiatric disorders during the first two years after the baseline; (2) excluding cases with psychiatric disorder in the first follow-up wave; (3) using the total number of physical diseases as a time-varying covariate in Model 3, instead of adjusting for individual physical diseases; (4) using traditional Cox regression model adjusting only for baseline covariates; (5) performing competing risk analyses using Fine–Gray subdistribution hazard models, given that death may preclude the occurrence of psychiatric disorders. Cumulative incidence function (CIF) curves were constructed to compare the risks of psychiatric disorders and death overtime across different types and number of ACEs. Additionally, the multistate Markov model was implemented to capture the dynamic transitions of health status among individuals with ACEs and those without ACEs, focusing particularly on how ACEs affected transitions across physical and mental health states and ultimately led to psychiatric disorders. Such an approach provides an integrated perspective on disease process and enables identification of influential risk factors and long-term predictions 38 . In this study, each participant was followed up with repeated health assessments across multiple follow-up waves, and transitions between defined states were tracked accordingly. Five states were defined to represent key clinical trajectories: (1) absence of physical conditions or mental health symptoms (No PC & No MS); (2) presence of physical conditions only (PC); (3) presence of mental health symptoms only [MS, depression (CESD ≤ 4) and (or) cognitive impairment (TICS-m ≤ 11)]; (4) co-occurrence of both physical conditions and mental health symptoms (PC & MS); and (5) having psychiatric disorders, defined as the absorbing state. The state structure is shown in Fig. 2 A. States 1 to 4 were defined as transient states, while state 5 as the absorbing state. Transition intensity parameters (q ij ) represent the instantaneous transition risk from state i to j . These were estimated through maximum likelihood under the assumption of continuous time Markov processes. For instance, q 3→5 reflects the instantaneous hazard of progressing from only having mental health symptoms to a diagnosed psychiatric disorder. Figure 2 B illustrates representative individual-level transitions in our sample, showing the heterogeneous patterns of disease progression observed during follow-up. The transition intensity matrix Q based on 5-state model was formulated as follows: In this context, the transition probability represents the likelihood of a transition from one state to another within a given time interval. To assess the influence of potential factors on transition dynamics, a series of univariate Markov models was fitted first, each incorporating a single covariate (e.g., ACEs in the total sample, and all other covariates in the ACE-exposed group) independently. Cumulative transition probabilities over a 22-year horizon were then computed. All multistate models were implemented using the R package msm . 3. Results 3.1 Participant characteristics Of the 19,580 participants in the 2000 wave, we included 8,628 participants who followed-up with 79,477 observations from 2000 to 2022 (Figure S1 ). Baseline sociodemographic and health-related characteristics of participants stratified by the four ACE types are summarized in Table 1 . The mean age of participants was 64.75 years (SD = 8.01), and the majority were female (n = 4,998; 57.2%), married (n = 6,310; 73.1%), and had lower than high school education (n = 4,901; 56.8%). Univariate analyses showed significant differences between ACE types in terms of age, sex, race, marital status, educational level, living status, vigorous physical activity, suffering from heart conditions, depression score and cognition score ( P < 0.05). Table 1 Baseline characteristics of the total sample and by different types of ACEs (N = 8,628) Variables Total (N = 8,628) Types of ACEs Univariate analyses No adversity (N = 5,672, 65.7%) Trauma & violence (N = 2,160, 25.0%) Family dysfunction (N = 608, 7.0%) Social problems (N = 188, 2.2%) N % N % N % N % N % χ 2 P Male 3,692 42.8 2,158 38.0 312 53.6 577 41.6 645 65.3 284.920 < 0.001 Race 14.143 0.028 White/ Caucasian 7,331 85.0 4,785 84.4 516 88.7 1,192 86.0 838 84.8 Black/ African American 1,005 11.6 689 12.1 44 7.6 149 10.8 123 12.4 Other 291 3.4 197 3.5 22 3.8 45 3.2 27 2.7 Married 6,310 73.1 4,120 72.6 451 77.5 974 70.3 765 77.4 21.382 < 0.001 High school education or above (≥ 12 years) 3,727 43.2 2,562 45.2 287 49.3 591 42.6 287 29.0 98.640 < 0.001 Living with others 6,680 77.4 4,354 76.8 473 81.3 1,049 75.7 804 81.4 17.573 < 0.001 Alcohol use 2,801 32.5 1,831 32.3 203 34.9 425 30.7 342 34.6 5.770 0.123 Smoking 1,120 13.0 714 12.6 68 11.7 200 14.4 138 14.0 5.070 0.167 Vigorous physical activity 4499 52.1 2929 51.6 347 59.6 697 50.3 526 53.2 16.007 0.001 Physical disease Diabetes 958 11.1 615 10.8 59 10.1 151 10.9 133 13.5 6.568 0.087 Cancer 848 9.8 563 9.9 57 9.8 147 10.6 81 8.2 3.970 0.265 Heart conditions 1298 15.0 818 14.4 104 17.9 208 15.0 168 17.0 8.325 0.040 Stroke 260 3.0 169 3.0 18 3.1 39 2.8 34 3.4 0.843 0.839 Hypertension 3857 44.7 2529 44.6 238 40.9 627 45.2 463 46.9 5.472 0.140 Lung diseases 482 5.6 293 5.2 41 7.0 93 6.7 55 5.6 7.568 0.056 Arthritis 4582 53.1 2979 52.5 327 56.2 739 53.3 537 54.4 3.637 0.304 Mean SD Mean SD Mean SD Mean SD Mean SD t/Z P Age (years) 64.75 8.01 65.22 8.11 65.55 8.34 62.82 7.55 64.28 7.40 106.660 < 0.001 Depression (CESD-8 total) 1.14 1.59 1.07 1.54 1.22 1.64 1.31 1.75 1.25 1.63 27.831 * < 0.001 Sleep (JSS-4 total) 6.71 2.03 6.69 2.02 6.88 2.04 6.69 2.08 6.73 2.00 5.549 * 0.136 Cognition (TICS-m) 16.08 4.21 16.24 4.20 16.25 4.15 16.13 4.19 15.00 4.18 73.380 * < 0.001 Notes: Bolded values indicate P < 0.05; ACE: adverse childhood experience; SD: standard deviation. CESD-8: 8-item Center for Epidemiological Studies Depression Scale; JSS-4: 4-item Jenkins Sleep Scale; TICS-m: modified version of the Telephone Interview for Cognitive Status Scale. * Analyzed using Wilcoxon rank sum test. 3.2 ACEs and the incidence of psychiatric disorders in older adults 3.2.1 Incidence rate of psychiatric disorders in older adults During an average follow-up duration of 16.8 years, 1,429 (16.6%) participants experienced psychiatric disorders. The overall incidence rate was 9.85 (95%CI: 9.34–10.37) per 1,000 person-years. The incidence rate of PDOA increased with the total number of ACEs: 8.85 per 1,000 person-years for participants with no ACE, 11.2, 13.0 and 15.0 per 1,000 person-years for those with one, two, and ≥ 3 ACEs, respectively (Table S3). The incidence rate was also different between different ACE types: 11.4, 14.1, 8.9 per 1,000 person-years for those with trauma & violence, family dysfunction, and social problems, respectively (Table 2 ). Table 2 The associations between types of ACEs and the incidence of PDOA (N = 8,628) Variables Cases N Incidence rate, per 1000 person-years Model 1 Model 2 Model 3 HR 95%CI P HR 95%CI P HR 95%CI P ACE type No adversity 5,672 8.85 Reference Reference Reference Trauma & violence 582 11.4 1.372 1.123–1.678 0.002 1.384 1.132–1.693 0.002 1.279 1.052–1.555 0.014 Family dysfunction 1,386 14.1 1.607 1.412–1.830 < 0.001 1.557 1.366–1.775 < 0.001 1.358 1.190–1.548 < 0.001 Social problems 988 8.92 1.152 0.964–1.377 0.119 1.099 0.918–1.317 0.305 0.974 0.813–1.167 0.772 Age (years) 0.994 0.987–1.001 0.091 0.982 0.974–0.989 < 0.001 0.970 0.962–0.978 < 0.001 Male 0.637 0.568–0.713 < 0.001 0.777 0.689–0.876 < 0.001 0.768 0.680–0.867 < 0.001 Race White/ Caucasian Reference Reference Reference Black/ African American 0.765 0.641–0.914 0.003 0.649 0.541–0.778 < 0.001 0.544 0.452–0.654 < 0.001 Other 1.095 0.834–1.438 0.515 0.966 0.734–1.270 0.802 0.839 0.646–1.090 0.189 Married 0.672 0.500-0.904 0.009 0.787 0.580–1.068 0.125 High school education or above (≥ 12 years) 0.945 0.847–1.054 0.309 1.176 1.049–1.320 0.006 Living with others 1.115 0.825–1.507 0.478 1.154 0.848–1.571 0.362 Alcohol use 0.624 0.549–0.708 < 0.001 0.703 0.619–0.799 < 0.001 Smoking 1.060 0.883–1.274 0.531 0.949 0.788–1.143 0.578 Vigorous physical activity 0.634 0.563–0.714 < 0.001 0.815 0.721–0.921 < 0.001 Physical disease Diabetes 0.947 0.836–1.072 0.387 Cancer 0.882 0.769–1.013 0.075 Heart conditions 1.127 1.004–1.266 0.043 Stroke 1.443 1.226–1.698 < 0.001 Hypertension 1.102 0.977–1.243 0.116 Lung diseases 1.253 1.081–1.452 0.003 Arthritis 1.294 1.136–1.474 < 0.001 Depression score (CESD-8) 1.317 1.285–1.349 < 0.001 Sleep score (JSS-4) 1.067 1.039–1.096 < 0.001 Cognition score (TICS-m) 0.961 0.948–0.974 < 0.001 Notes: Bolded values indicate P < 0.05. ACE: adverse childhood experience; PDOA: psychiatric disorders in older adults; HR: Hazard ratio; CI: Confidence interval; CESD-8: 8-item Center for Epidemiological Studies Depression Scale; JSS-4: 4-item Jenkins Sleep Scale; TICS-m: modified version of the Telephone Interview for Cognitive Status Scale. Model 1 was adjusted for age, sex and race/ethnicity. Model 2 was adjusted for age, sex, race/ethnicity, marital status, living with others, educational level, vigorous activities, smoking, and alcohol use. Model 3 was adjusted for the same covariates as model 2 plus history of major physical diseases (diabetes, cancer, heart conditions, stroke, hypertension, lung diseases, and arthritis), total CESD-8 score, total JSS-4 score and total TICS-m score. 3.2.2 The associations between ACEs and the incidence of psychiatric disorders in older adults Table 2 shows significant associations between trauma & violence, and family dysfunction with the incidence of PDOA. In the fully adjusted model, participants with childhood trauma & violence, and family dysfunction had 27.9% and 35.8% higher risks of PDOA, respectively, as compared to those with no ACE exposure [adjusted Hazard ratio (aHR): 1.279, 95%CI: 1.052–1.555 vs. aHR: 1.358, 95%CI: 1.190–1.548]. However, no association was observed between childhood social problems and the incidence of PDOA. Table S2 shows a dose-response relationship between the total number of ACE and the incidence of PDOA, which persisted across all three models. In the fully adjusted model, participants with two and ≥ 3 ACEs had 27.9% and 50.6% higher risks of PDOA, respectively, compared to those with no ACE [aHR: 1.279, 95%CI: 1.056–1.549 vs. aHR: 1.506, 95%CI: 1.128–2.011]. The Kaplan-Meier survival curve (Figure S1 ) illustrates significant differences in incidence rates across different types and number of ACEs ( P < 0.001). Figure 1 shows that the association between ACEs and the incidence of psychiatric disorders was more pronounced among individuals aged 50–64 years (aHR: 1.71, 95% CI:1.36–2.15) than those aged ≥ 65 years (aHR: 1.23, 95% CI: 1.09 to 1.39; P for interaction: 0.013); among participants with higher educational level (aHR: 1.71, 95% CI: 1.45–2.02) than those with lower educational level (aHR: 1.12, 95% CI: 0.98–1.29, P for interaction: <0.001); and among those with cognitive decline (HR: 1.49, 95% CI: 1.31–1.70) compared to those without cognitive decline (aHR:1.06, 95% CI:0.88–1.27; P for interaction: 0.002). In sensitive analyses, consistent associations between ACEs and the incidence of psychiatric disorders were observed (Tables S3- S6). The competing risk analyses showed that the association between ACEs and the incidence of PDOA remained significant when accounting for death as a competing event (Table S7). The CIF curves revealed a higher cumulative risk of PDOA over time in individuals with greater exposure to ACEs and those with family dysfunction or direct trauma & violence, although death became more prominent as a competing risk after approximately 100 months of follow-up (Figure S3). 3.3 Transitions between health states among participants with and without ACEs 3.3.1 State transition percentage and intensity The observed state transitions during follow-up are summarized in Table S8. Among participants with ACEs, transitions from comorbid physical conditions and mental health symptoms (PC & MS) to psychiatric disorders accounted for the largest proportion (3.7%), followed by transitions from MS alone (3.5%). In contrast, among those without ACEs, the proportion transitioning to psychiatric disorders was lower across all states, with the highest transition from the PC & MS state (3.2%). Participants with ACEs were also more likely to transition between vulnerable health states (e.g., from MS to PC & MS: 8.2%) compared to those without ACEs (7.5%). Participants with ACEs showed consistently higher transition intensities across most state transitions compared to those without ACEs, e.g., the transitions from No PC & No MS to MS (0.130 vs. 0.104) and from PC to PC & MS (0.146 vs. 0.129) (Table S9). 3.3.2 State transition probability and total duration Figures 3 (left panel) and S4 illustrate the 22-year transition probability curves across five health states, stratified by participants with ACEs and those without ACEs. The probability of remaining in the healthy state (1→1, No PC & No MS) declined sharply for both groups, especially in ACE group. At baseline, the probabilities of state 1 were over 0.8 in both groups, while by the year 2022, the probabilities dropped to 0.153 in the ACE group and 0.196 in the no-ACE group, respectively. The probability of transitioning from the healthy state to more adverse states (e.g., 1→2, 1→4, and especially 1→5) increased over time. Certain transitions, such as recovery to healthy states (e.g., 2→1, 3→1), remained low and stable in both groups, indicating more likelihood of accelerated health deterioration and less likelihood of recovery. Notably, the group with ACEs exhibited higher and faster probabilities of progressing from the healthy state or any intermediate states to the absorbing state 5 (psychiatric disorders) over the 22 years; for instance, at 22 years, 1→5: ACE 0.253 vs. no ACE 0.190; 2→5: ACE 0.245 vs. no ACE 0.209; 3→5: ACE 0.269 vs. no ACE 0.215; 4→5: ACE 0.269 vs. no ACE 0.233. We calculated the 22-year cumulative transition probabilities from four transient health states (States 1–4) to the incidence of psychiatric disorders (State 5). The cumulative transition probabilities ranged from 19.0–23.3% and from 25.3–26.9% across states in the group without ACE and the group with ACEs, respectively. Even among participants initially in a healthy state (State 1), those with ACE exposure had a 33% higher risk of transitioning to psychiatric disorders (25.3% vs. 19.0%) by the year 2022. Furthermore, the group with ACEs exhibited consistent higher probabilities of transitioning between intermediate states (e.g., 1→2, 1→4, 3→4, and 2→4), indicating a higher likelihood of progression to early physical conditions, as well as comorbid physical and mental health conditions. Figure 3 (right panel) shows the standardized percentages of total duration across the five states. Over the 22-year follow-up period, most of the duration was in state 2 (PC), accounting for approximately 48% of the total time across both groups. This was followed by state 4 (PC & MS), comprising around 31%, and state 1 (No PC & No MS), at about 15%. Hence, both total duration of PC and PC & MS prolonged, while those of healthy state (No PC & No MS) shortened. When comparing participants with ACEs and those without ACEs, the group with ACEs spent less time in the healthy state (state 1) (14.5% vs 15.6%) and more time in the comorbid state (state 4) (31.2% vs 30.1%) than their non-ACE counterparts. These trends indicated that ACEs might be associated with earlier onset and longer duration of complex comorbidity prior to the onset of psychiatric disorder. 3.3.3 Covariate effects on state transitions Across the whole sample, univariate Markov models demonstrated that individuals with ACEs had a significantly higher risk of developing both physical and mental health conditions. Specifically, participants with ACEs had 19.0%, 25.3% and 85.9% higher risks of transition from No PC & No MS to PC, MS, and to psychiatric disorder, respectively; and 13.8% higher risk of transition from PC to PC & MS (Table S10). Among participants with ACEs, univariate models (Table S11) showed that older age (≥ 65 years) and male sex were consistently associated with a lower risk of transitioning from all states to psychiatric disorders (e.g., No PC & No MS → Psychiatric disorders, HR:0.538, 95% CI: 0.362–0.798 for age; HR:0.536, 95% CI: 0.359–0.802 for male). Vigorous physical activity was protective for developing psychiatric disorders among those with No PC & No MS (HR:0.620, 95% CI: 0.424–0.906). Insomnia (JSS-4 total score ≥ 5) significantly increased the risk of transition from combined physical and mental symptoms to psychiatric disorders (HR: 2.721, 95% CI: 1.244–5.952). Among physical diseases, lung diseases (HR: 2.592, 95% CI: 1.524–4.356) and arthritis (HR: 1.530, 95% CI: 1.028–2.275) were associated with a higher risk of psychiatric disorders from No PC & No MS state. High school education or above also increased the risk of transition from mental symptoms to psychiatric disorders (HR: 1.864, 95% CI: 1.114–3.120). 4. Discussion To the best of our knowledge, this was the first cohort study to investigate the associations between ACEs and the incidence of psychiatric disorders in older adults, based on 22 years of follow-up data. We found that ACEs were strongly associated with an increased risk of psychiatric disorders in later life after adjusting for the time-varying confounders regarding lifestyle, physical and mental health conditions. We also identified effect modifications in the relationship between ACEs and the incidence of psychiatric disorders based on stratification by sociodemographic, lifestyle, and health-related factors. Moreover, we explored how ACEs influenced the transition from healthy and intermediate health states to psychiatric disorders and identified risk factors for such transitions. Our study demonstrated that ACEs could significantly increase the risk of PDOA over a 22-year follow-up. Using time-varying Cox regression, we found that the total ACE score, cumulative number of ACEs and specific ACE types, such as trauma & violence and family dysfunction, were all significantly associated with an elevated risk of psychiatric disorders. The risk increased in a dose–response manner, with individuals exposed to three or more ACEs having the highest risk. The competing risk model further validated that these associations were not confounded by the differential risk of mortality across groups. These results are consistent with previous findings that ACEs contribute to poorer cognitive, physical, and mental health outcomes in later life 39 . In terms of ACE subtypes, childhood family dysfunction and trauma & violence were associated with the highest risks of psychiatric disorder. Due to the severe and chronic nature of ACEs, such adversities could cause profound disruptions in emotional regulation, early attachment, and neurobiological development, resulting in lasting impact on mental health in middle and older adulthood 40 , 41 . In contrast, social problems (e.g., school difficulties, trouble with police) showed weaker or nonsignificant associations, probably because they are more transient or likely mediated by other factors such as social support or resilience 39 . Our multistate Markov model revealed several key findings about the impact of ACEs on mental health trajectories in older adults. First, ACEs accelerated transitions toward PDOA, since older adults with ACEs transitioned more frequently and more rapidly from healthy to less healthy states. For example, transitions from comorbid physical and mental health conditions (PC & MS) to psychiatric disorders were more frequent in the group with ACEs (3.7% vs. 3.2%); transitions from the healthy state (No PC & No MS) to mental health symptoms (MS) were also faster in the group with ACEs (intensity: 0.130 vs. 0.104), underscoring the role ACEs in accelerating progression towards psychiatric disorders. Such results is aligned with previous research showing that ACEs accelerated the progression of both physical and mental health conditions, predisposing individuals to complex multimorbidity and psychiatric illness 39 . Second, ACEs prolonged vulnerability states and reduced time in healthy state. The group with ACEs spent less time in the healthy state (14.5% vs. 15.6%) and more time in the comorbid PC & MS state (31.2% vs. 30.1%) over the study period. This pattern indicated that ACEs might not only influence the onset of psychiatric disorders but also prolong the periods of subclinical vulnerability, which overall likely exacerbate psychiatric risks. Third, individuals with ACEs showed consistently higher cumulative risk of transitioning from healthy or intermediate states to having psychiatric disorders. For instance, by the year 2022, the transition probability from the healthy state to psychiatric disorders was 25.3% in the group with ACEs compared to 19.0% in the group with ACEs, representing a 33% increased risk. Univariate Markov models also demonstrated that individuals with ACEs had 19.0%, 25.3% and 85.9% higher risks of transition from No PC & No MS to PC, MS, and to psychiatric disorder, respectively; and 13.8% higher risks of transition from PC to PC & MS. A previous study using multi-state model also found that higher ACE scores (≥ 4) were associated with an increased probability of forward transitions toward worsening physical health states, such as from robust to pre-frail (HR = 1.37, 95% CI: 1.21–1.54) and from pre-frail to frail (HR = 1.39, 95% CI: 1.18–1.63), as well as a decreased probability of reverting to healthier states (pre-frail to robust, HR = 0.64, 95% CI: 0.55–0.76) 42 . Our findings hence extended previous research by dynamically characterizing how ACEs could influence long-term mental health trajectories in older adults, emphasizing the enduring effects of early life stressors on psychiatric morbidity decades later. Several potential mechanisms may explain the enduring impact of ACEs on late-life mental health trajectories. First, the association between ACEs and poor adult health is likely mediated by psychosocial factors, including having increased exposure to stressful life events, higher perceived stress, negative emotionality, and unhealthy behaviors in adulthood 43 ,. Second, chronic stress related to ACEs may induce multisystem dysregulation, including neuroendocrine and inflammatory processes, which cumulatively impair physical and mental health 44 . Third, neuroimaging studies indicates that alterations related to ACEs in brain regions critical for emotional regulation and cognitive control, such as the prefrontal cortex and hippocampus, may mediate increased vulnerability to psychiatric disorders, particularly in individuals experiencing cognitive decline 13 , 14 . These psychosocial and biological processes can cumulatively generate sustained risk factors, including chronic inflammation, maladaptive coping strategies, and health-risk behaviors, that may delay recovery from mental health challenges or accelerate transitions to psychiatric disorders. Subgroup analyses revealed a strong association between ACEs and the incidence of psychiatric disorders among individuals aged 50–64 years and those with higher educational attainment. This aligns with the results of our multi-state model, showing that individuals aged 50–64 years with ACEs had greater risks of transitioning from all health states to psychiatric disorders, while those with a higher education level and ACEs had greater risks of transitioning from MS or PC & MS to psychiatric disorders. Individuals aged 50–64 years often experience greater work-related stress, family obligations, and caregiving responsibilities, compared to those aged 65 and older. Such stressors, combined with psychosocial vulnerabilities resulting from ACEs, can contribute to increased emotional distress and risk of psychiatric disorders 43 . Individuals with a higher education level may exhibit greater awareness of mental health symptoms and are more likely to seek help, leading to increased rates of psychiatric disorder diagnosis 45 . Furthermore, despite having socioeconomic advantages, individuals with a higher education level may still experience major psychosocial stressors (e.g., career pressure and social expectations) that can exacerbate the impact of early adversities 46 . Our findings that females with ACEs had increased risks of transitions from all health states to psychiatric disorders is also consistent with the higher prevalence of mental illness observed in females 47 . Biological sensitivities, including hormonal fluctuations and neural differences, combined with gender-specific psychosocial stressors such as caregiving burdens and exposure to gender-based violence, can amplify the impact of early adversities on emotional regulation and psychiatric vulnerability in women 48 , 49 . The interaction between ACEs and female-specific factors might contribute to the elevated psychiatric risk across various health trajectories observed in our study. Furthermore, in the group with ACEs, univariate multi-state analysis identified other factors that significantly influenced the risk of transition to psychiatric disorders. Behavioral factors, such as physical inactivity and insomnia, could further increase psychiatric risk, highlighting the role of lifestyle in modulating outcomes of ACEs. Chronic physical conditions, including lung diseases and arthritis, also elevated the risk of progression profoundly from healthy (No PC & No MS) or physical condition (PC) states to psychiatric disorders, potentially through mechanisms related to systemic inflammation 50 and functional impairment 51 . From a clinical perspective, our findings highlight the importance of routine screening for ACEs in older adults to identify those with elevated risk for psychiatric disorders, especially among individuals exposed to trauma, violence and family dysfunction in early life. Behavioral interventions targeting those with risk factors such as younger age, female gender, and high education level as well as modifiable factors such as physical activity and sleep disturbances, may mitigate the development of psychiatric morbidity. Further, effective management of chronic physical conditions like lung diseases and arthritis can be crucial to reduce the transition towards psychiatric disorders. Future research to explore integrated care models addressing both multimorbidity and psychosocial adversities is warranted to improve the mental health outcomes in older populations with ACEs. The strengths of this study included a large, nationally representative cohort with longitudinal data spanning over two decades, the use of a comprehensive set of time-varying covariates to reduce potential confounding, and the application of multi-state Markov modeling that enabled a nuanced understanding of dynamic progress to the onset of psychiatric disorders. However, some limitations should be noted. First, ACEs were retrospectively self-reported, which might introduce recall bias. However, a prior study has reported on the reasonable validity of adult retrospective reporting of ACEs 52 . Similar to previous research 26 , 53 , psychiatric disorders were based on self-reported diagnosis by physicians, which might lead to underreporting. Second, the measurement of ACEs in the HRS included a limited set of adverse events, particularly regarding social problems, which might not fully capture the breadth of childhood adversities. Third, potential confounding factors that might influence health trajectories, such as genetic predisposition, social support or later-life stressors, were not included in the analyses. Fourth, missing data in certain time-varying covariates (i.e., CESD-8, JSS-4, and TICS-m) were imputed using LOCF and NOCF methods, which might introduce bias regarding the constancy of data across time. Fifth, due to limited number of transitions between health states, we were unable to perform multivariate Markov modeling incorporating all variables that were significantly associated with transitions in the univariate analyses, thus limiting the adjustment for confounding factors. Finally, although the cohort is representative of the US older adult population, findings might not be generalizable to those in other cultural or socioeconomic contexts. In conclusion, this long-term cohort study revealed that ACEs could significantly increase the risk of PDOA as well as accelerate the progression to PDOA, especially among those exposed to past trauma and violence and family dysfunction. The association between ACEs and PDOA were more pronounced among females, participants aged 50–64 years, and those with higher education level or with cognitive decline. Individuals with ACEs showed faster transitions from healthy and intermediate states to having psychiatric disorders, spent less time in healthy state, and had prolonged periods of multimorbidity prior to onset of psychiatric disorder. Demographic, behavioral, and physical health factors (such as age, sex, education level, physical activity, insomnia, lung diseases, and arthritis) might further modify these risks. Our findings highlighted the enduring impact of early life adversity on mental health trajectories in later life, and further underscored the need for integrated, trauma-informed care to mitigate psychiatric morbidity in older populations. Declarations Acknowledgements The authors are grateful to all participants and clinicians involved in this study. Conflict of Interest The authors have no conflicts of interest to declare. Funding Sources The study was supported by Hainan Provincial Natural Science Foundation of China (No. 821QN249), the Education Department of Hainan Province (Hnjg2024ZC-55), Beijing High Level Public Health Technology Talent Construction Project (Discipline Backbone-01-028), the Beijing Municipal Science & Technology Commission (No. Z181100001518005), the Capital's Funds for Health Improvement and Research (CFH 2024-2-1174) and the University of Macau (MYRG-GRG2023-00141-FHS; CPG2025-00021-FHS). Authors Contributions Study design: Hui-Ying Fan, Mu-Rui Zheng, Qinge Zhang, Chee H. Ng, Yu-Tao Xiang. Data collection, analysis and interpretation: Hui-Ying Fan, Mu-Rui Zheng, Xiao-Xuan Meng, Qinge Zhang, Chee H. Ng, Yu-Tao Xiang, Zhi-Cheng Du, Zhaohui Su, Teris Cheung, Gabor S. Ungvari. Drafting of the manuscript: Hui-Ying Fan, Mu-Rui Zheng, Yu-Tao Xiang. Critical revision of the manuscript: Chee H. Ng. Approval of the final version for publication: all co-authors. Data Availability Statement The data that support the findings of this study are available from The University of Michigan Health and Retirement Study Platform at https://hrsdata.isr.umich.edu/data-products/public-survey-data References Mental health of older adults. https://www.who.int/news-room/fact-sheets/detail/mental-health-of-older-adults , 2023, Accessed Date Accessed 2023 Accessed. Global Health Data Exchange (GHDx). https://vizhub.healthdata.org/gbd-results/ , 2023, Accessed Date Accessed 2023 Accessed. About Adverse Childhood Experiences. https://www.cdc.gov/aces/about/index.html , 2024, Accessed Date Accessed 2024 Accessed. 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. AMERICAN JOURNAL OF PREVENTIVE MEDICINE 1998; 14(4): 245–258. Finkelhor D, Shattuck A, Turner H, Hamby S. Improving the Adverse Childhood Experiences Study Scale. JAMA Pediatrics 2013; 167(1): 70–75. Oral R, Ramirez M, Coohey C, Nakada S, Walz A, Kuntz A et al. Adverse childhood experiences and trauma informed care: the future of health care. PEDIATRIC RESEARCH 2016; 79(1): 227–233. Chapman DP, Whitfield CL, Felitti VJ, Dube SR, Edwards VJ, Anda RF. Adverse childhood experiences and the risk of depressive disorders in adulthood. J Affect Disord 2004; 82(2): 217–225. Thurston C, Murray AL, Franchino-Olsen H, Meinck F. Prospective longitudinal associations between adverse childhood experiences and adult mental health outcomes: a protocol for a systematic review and meta-analysis. Syst Rev 2023; 12(1): 181. Sahle BW, Reavley NJ, Li W, Morgan AJ, Yap MBH, Reupert A et al. The association between adverse childhood experiences and common mental disorders and suicidality: an umbrella review of systematic reviews and meta-analyses. Eur Child Adolesc Psychiatry 2022; 31(10): 1489–1499. Gonçalves H, Soares AL, Santos AP, Ribeiro CG, Bierhals IO, Vieira LS et al. Adverse childhood experiences and consumption of alcohol, tobacco and illicit drugs among adolescents of a Brazilian birth cohort. Cad Saude Publica 2016; 32(10): e00085815. Ho GWK, Bressington D, Karatzias T, Chien WT, Inoue S, Yang PJ et al. Patterns of exposure to adverse childhood experiences and their associations with mental health: a survey of 1346 university students in East Asia. Soc Psychiatry Psychiatr Epidemiol 2020; 55(3): 339–349. Daníelsdóttir HB, Aspelund T, Shen Q, Halldorsdottir T, Jakobsdóttir J, Song H et al. Adverse Childhood Experiences and Adult Mental Health Outcomes. JAMA Psychiatry 2024; 81(6): 586–594. Keator DB, Salgado F, Madigan C, Murray S, Norris S, Amen D. Adverse childhood experiences, brain function, and psychiatric diagnoses in a large adult clinical cohort. Front Psychiatry 2024; 15: 1401745. Hosseini-Kamkar N, Varvani Farahani M, Nikolic M, Stewart K, Goldsmith S, Soltaninejad M et al. Adverse Life Experiences and Brain Function: A Meta-Analysis of Functional Magnetic Resonance Imaging Findings. JAMA Netw Open 2023; 6(11): e2340018. Kobayashi LC. Adverse Childhood Experiences and Later-Life Cognitive Aging: Persistent Methodological Challenges Limit the Evidence Base. J Gerontol A Biol Sci Med Sci 2024; 79(8). Manning LK, Bouchard LM, Flanagan JL. Comorbidities of physical and psychiatric syndromes in later life. Oxford Research Encyclopedia of Psychology 2018. Sonnega A, Faul JD, Ofstedal MB, Langa KM, Phillips JW, Weir DR. Cohort Profile: the Health and Retirement Study (HRS). International Journal of Epidemiology 2014; 43(2): 576–585. Bugliari D, Carroll J, Hayden O, Hayes J, Hurd MD, Lee S et al. RAND HRS Longitudinal File 2020 (V2) Documentation. Aging 2024. Lydersen S. Last observation carried forward. Tidsskrift for den Norske Laegeforening 2019; 139(9). Nakai M, Chen D-G, Nishimura K, Miyamoto Y. Comparative study of four methods in missing value imputations under missing completely at random mechanism. Open Journal of Statistics 2014; 2014. Matthews TA, Li J. Adverse Childhood Experiences, Social Isolation, Job Strain, and Cardiovascular Disease Mortality in U.S. Older Employees. Medicina (Kaunas) 2023; 59(7). Bürgin D, Cyril B, Marc S, Paige T, and O’Donovan A. Fact or artefact? Childhood adversity and adulthood trauma in the U.S. population-based Health and Retirement Study. European Journal of Psychotraumatology 2020; 11(1): 1721146. Clarke P, Fisher G, House J, Smith J, Weir D. Guide to content of the HRS psychosocial leave-behind participant lifestyle questionnaires: 2004 & 2006. Ann Arbor, MI : University of Michigan 2008. Smith J, Ryan L, Fisher G, Sonnega A, Weir D. Psychosocial and lifestyle questionnaire 2006–2016: Documentation Report Core Section LB Survey Research Center. Institute for Social Research, University of Michigan 2017. Krause N, Shaw BA, Cairney J. A descriptive epidemiology of lifetime trauma and the physical health status of older adults. Psychology and aging 2004; 19(4): 637. Cigolle CT, Langa KM, Kabeto MU, Tian Z, Blaum CS. Geriatric conditions and disability: the Health and Retirement Study. Ann Intern Med 2007; 147(3): 156–164. Van de Velde S, Levecque K, Bracke P. Measurement equivalence of the CES-D 8 in the general population in Belgium: a gender perspective. Archives of Public Health 2009; 67(1): 15. Mojtabai R, Olfson M. Major depression in community-dwelling middle-aged and older adults: prevalence and 2- and 4-year follow-up symptoms. Psychological Medicine 2004; 34(4): 623–634. Brandt J, Spencer M, Folstein M. The telephone interview for cognitive status. Neuropsychiatry, Neuropsychology, and Behavioral Neurology 1988; 1(2): 111–117. Crimmins EM, Kim JK, Langa KM, Weir DR. Assessment of cognition using surveys and neuropsychological assessment: the Health and Retirement Study and the Aging, Demographics, and Memory Study. Journals of Gerontology Series B: Psychological Sciences and Social Sciences 2011; 66 Suppl 1(Suppl 1): i162-171. Covello AL, Horwitz LI, Singhal S, Blaum CS, Li Y, Dodson JA. Cardiovascular disease and cumulative incidence of cognitive impairment in the Health and Retirement Study. BMC Geriatrics 2021; 21(1): 274. Lee JH, Luchetti M, Aschwanden D, Sesker AA, Strickhouser JE, Terracciano A et al. Cognitive Impairment and the Trajectory of Loneliness in Older Adulthood: Evidence from the Health and Retirement Study. J Aging Health 2022; 34(1): 3–13. Jenkins CD, Stanton BA, Niemcryk SJ, Rose RM. A scale for the estimation of sleep problems in clinical research. Journal of Clinical Epidemiology 1988; 41(4): 313–321. von Känel R, Meister-Langraf RE, Zuccarella-Hackl C, Schiebler SLF, Znoj H, Pazhenkottil AP et al. Sleep disturbance after acute coronary syndrome: A longitudinal study over 12 months. PLoS One 2022; 17(6): e0269545. R Development Core Team. R: A language and environment for statistical computing.. R Foundation for Statistical Computing Vienna, Australia, 2020. Zhang Z, Reinikainen J, Adeleke KA, Pieterse ME, Groothuis-Oudshoorn CGM. Time-varying covariates and coefficients in Cox regression models. Ann Transl Med 2018; 6(7): 121. 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 REGIONAL HEALTH-AMERICAS 2022; 15. Meira-Machado L, de Uña-Alvarez J, Cadarso-Suárez C, Andersen PK. Multi-state models for the analysis of time-to-event data. STATISTICAL METHODS IN MEDICAL RESEARCH 2009; 18(2): 195–222. Haczkewicz KM, Shahid S, Finnegan HA, Monnin C, Cameron CD, Gallant NL. Adverse childhood experiences (ACEs), resilience, and outcomes in older adulthood: A scoping review. Child Abuse & Neglect 2024: 106864. Hughes K, Bellis MA, Hardcastle KA, Sethi D, Butchart A, Mikton C et al. The effect of multiple adverse childhood experiences on health: a systematic review and meta-analysis. Lancet Public Health 2017; 2(8): e356-e366. Anda RF, Felitti VJ, Bremner JD, Walker JD, Whitfield C, Perry BD et al. The enduring effects of abuse and related adverse experiences in childhood. A convergence of evidence from neurobiology and epidemiology. Eur Arch Psychiatry Clin Neurosci 2006; 256(3): 174–186. Li J, Pei H, Yan X, Wei Y, Chen G, Pei L. Adverse Childhood Experiences and Social Participation on Frailty State Transitions among middle-aged and older adults: evidence from a 10-year prospective study in China. J Nutr Health Aging 2024; 28(12): 100400. Bourassa KJ, Moffitt TE, Harrington H, Houts R, Poulton R, Ramrakha S et al. Childhood Adversity and Midlife Health: Shining a Light on the Black Box of Psychosocial Mechanisms. Prevention Science 2023; 24(5): 817–828. Danese A, McEwen BS. Adverse childhood experiences, allostasis, allostatic load, and age-related disease. Physiology & Behavior 2012; 106(1): 29–39. Gonzalez JM, Alegría M, Prihoda TJ, Copeland LA, Zeber JE. How the relationship of attitudes toward mental health treatment and service use differs by age, gender, ethnicity/race and education. Social Psychiatry and Psychiatric Epidemiology 2011; 46(1): 45–57. Thoits PA. Stress and Health: Major Findings and Policy Implications. Journal of Health and Social Behavior 2010; 51(1_suppl): S41-S53. Whitaker RC, Dearth-Wesley T, Herman AN, Block AE, Holderness MH, Waring NA et al. The interaction of adverse childhood experiences and gender as risk factors for depression and anxiety disorders in US adults: a cross-sectional study. BMC Public Health 2021; 21(1): 2078. Bangasser DA, Valentino RJ. Sex differences in stress-related psychiatric disorders: Neurobiological perspectives. Frontiers in Neuroendocrinology 2014; 35(3): 303–319. Kuehner C. Why is depression more common among women than among men? The Lancet Psychiatry 2017; 4(2): 146–158. Miller AH, Raison CL. The role of inflammation in depression: from evolutionary imperative to modern treatment target. Nat Rev Immunol 2016; 16(1): 22–34. Scott KM, Bruffaerts R, Tsang A, Ormel J, Alonso J, Angermeyer MC et al. Depression-anxiety relationships with chronic physical conditions: results from the World Mental Health Surveys. J Affect Disord 2007; 103(1–3): 113–120. Hardt J, Rutter M. Validity of adult retrospective reports of adverse childhood experiences: review of the evidence. J Child Psychol Psychiatry 2004; 45(2): 260–273. Zhou Y, Kivimäki M, Yan LL, Carrillo-Larco RM, Zhang Y, Cheng Y et al. Associations between socioeconomic inequalities and progression to psychological and cognitive multimorbidities after onset of a physical condition: a multicohort study. EClinicalMedicine 2024; 74: 102739. Additional Declarations The authors have declared there is NO conflict of interest to disclose Supplementary Files SupplementaryMaterials.docx Supplementary Materials Cite Share Download PDF Status: Under Review Version 1 posted Unknown event 09 Dec, 2025 Editorial decision: Reject after peer review 14 Nov, 2025 Review # 3 received at journal 08 Nov, 2025 Review # 4 received at journal 05 Nov, 2025 Review # 6 received at journal 04 Nov, 2025 Review # 5 received at journal 30 Oct, 2025 Reviewer # 6 agreed at journal 28 Oct, 2025 Reviewer # 5 agreed at journal 28 Oct, 2025 Reviewer # 4 agreed at journal 22 Oct, 2025 Reviewer # 3 agreed at journal 22 Oct, 2025 Review # 2 received at journal 30 Sep, 2025 Reviewer # 2 agreed at journal 25 Sep, 2025 Review # 1 received at journal 10 Sep, 2025 Reviewer # 1 agreed at journal 28 Aug, 2025 Reviewers invited by journal 22 Aug, 2025 Editor assigned by journal 08 Aug, 2025 Submission checks completed at journal 08 Aug, 2025 First submitted to journal 07 Aug, 2025 Unknown event 06 Aug, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7307635","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":504370627,"identity":"be91d449-67fa-4dcf-8590-23655d3eedd5","order_by":0,"name":"Hui-Ying Fan","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA5ElEQVRIie3PPQrCMBTA8VcCqcMT1+cHniGlUN28iiJ0iuDYQdQpU9HVYxS8gFDM1AN0U/ACTuIgYquTS9pRMP8hkPB+kAdgs/1g7q44roL6LXYo79SrJJgDOLto6LfV+E2wFmGYRZNEjz8P1aQbC2gqcvaa6U6+GCK46TExkl4moK2IBZpPfamLj2EY5iYyIinAU8SDU+xdJC8IYWAkWJKJIvQVilQ+65JDRiQ4epeZqkXCubOOSFC5y2xDyKt2QZom7CGWq61iuitvy37LTbWRADQG9687N4+XuefqGZvNZvvvXosmPlncD/QqAAAAAElFTkSuQmCC","orcid":"https://orcid.org/0000-0002-9335-4021","institution":"University of Macau","correspondingAuthor":true,"prefix":"","firstName":"Hui-Ying","middleName":"","lastName":"Fan","suffix":""},{"id":504370628,"identity":"e1110e45-d678-488d-b25c-66c43165a39d","order_by":1,"name":"Mu-Rui Zheng","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Mu-Rui","middleName":"","lastName":"Zheng","suffix":""},{"id":504370629,"identity":"27b466b8-3804-4a3a-81b7-8bddf7a08fa4","order_by":2,"name":"Xiao-Xuan Meng","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Xiao-Xuan","middleName":"","lastName":"Meng","suffix":""},{"id":504370630,"identity":"a04615ee-ee98-4682-8eee-87a437cbfa7b","order_by":3,"name":"Qinge Zhang","email":"","orcid":"","institution":"Beijing anding hospital","correspondingAuthor":false,"prefix":"","firstName":"Qinge","middleName":"","lastName":"Zhang","suffix":""},{"id":504370631,"identity":"4b15fb30-1ac9-439d-a9c4-bc77ab88ab89","order_by":4,"name":"Zhi-Cheng Du","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Zhi-Cheng","middleName":"","lastName":"Du","suffix":""},{"id":504370632,"identity":"ebceba38-a47e-45d1-992f-fd1c98d1466f","order_by":5,"name":"Zhaohui Su","email":"","orcid":"https://orcid.org/0000-0003-2005-9504","institution":"Southeast University","correspondingAuthor":false,"prefix":"","firstName":"Zhaohui","middleName":"","lastName":"Su","suffix":""},{"id":504370633,"identity":"bd55de85-b75a-400d-8cac-b0a2a395356c","order_by":6,"name":"Teris Cheung","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Teris","middleName":"","lastName":"Cheung","suffix":""},{"id":504370634,"identity":"9e05a1d8-3eac-449d-8e64-b83f51bf00bf","order_by":7,"name":"Gabor Ungvari","email":"","orcid":"","institution":"University Notre Dame Australia","correspondingAuthor":false,"prefix":"","firstName":"Gabor","middleName":"","lastName":"Ungvari","suffix":""},{"id":504370635,"identity":"71255ab6-c4a5-43e3-bc7d-320cab93e64a","order_by":8,"name":"Chee H. Ng","email":"","orcid":"https://orcid.org/0000-0002-3811-2732","institution":"University of Melbourne","correspondingAuthor":false,"prefix":"","firstName":"Chee","middleName":"H.","lastName":"Ng","suffix":""},{"id":504370636,"identity":"a189a783-d547-4e48-9481-ad283f371824","order_by":9,"name":"Yu-Tao Xiang","email":"","orcid":"https://orcid.org/0000-0002-2906-0029","institution":"Unit of Psychiatry, Faculty of Health Sciences","correspondingAuthor":false,"prefix":"","firstName":"Yu-Tao","middleName":"","lastName":"Xiang","suffix":""}],"badges":[],"createdAt":"2025-08-06 08:45:12","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7307635/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7307635/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":90381150,"identity":"4e1b39f8-7508-41a0-859f-6285a28b85c6","added_by":"auto","created_at":"2025-09-02 06:46:39","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":334444,"visible":true,"origin":"","legend":"\u003cp\u003eThe association between ACEs and the incidence of PDOA stratified by demographic and clinical correlates\u003c/p\u003e\n\u003cp\u003eNotes: Graphs show hazard ratios (HRs) and 95% confidence intervals (CIs) for psychiatric disorders in older adults. ACEs was assessed using a binary variable (yes vs. no). ACEs: adverse childhood experiences; PDOA: psychiatric disorders in older adults; HR: Hazard ratio; CI: Confidence interval; CESD-8: 8-item Center for Epidemiological Studies Depression Scale; JSS-4: 4-item Jenkins Sleep Scale.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7307635/v1/25e0d93f3ab26fd03070c623.png"},{"id":90382833,"identity":"97e8a31b-07a6-451e-b147-fd1de3d5fe00","added_by":"auto","created_at":"2025-09-02 06:54:39","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":81932,"visible":true,"origin":"","legend":"\u003cp\u003e(A) Transitions among multi states in the Markov model: State 1 (No PC \u0026amp; No MS): participants without physical conditions (PC, including diabetes, stroke, heart conditions and cancers) and mental symptoms (MS, including depressive symptoms and cognitive impairment); State 2 (PC): participants with physical conditions; State 3 (MS): participants with mental symptoms; State 4 (PC \u0026amp; MS): participants with mental symptoms and physical conditions; State 5 (absorbing state): participants with psychiatric disorder. The arrows illustrate the possible transitions between the transient status and the absorbing state. Each transition parameter \u003cem\u003eq\u003c/em\u003e illustrates the transition intensity and \u003cem\u003eq\u003c/em\u003e\u003csub\u003ei→j\u003c/sub\u003e is defined as the instantaneous transition risk from state i to j. (B) Possible transition paths for four selected subjects with ACEs. Observations were truncated once the absorbing states appeared. The nodes represent the actual observed states, with solid lines indicating potential transition trajectories observed during the follow-up period. Possible transition paths were selected randomly based on the recorded states. ACEs: adverse childhood experiences.\u003c/p\u003e\n\u003cp\u003eTransitions between transient states and absorbing state (psychiatric disorder) (A) and possible transition paths for the selected subjects with ACEs (B)\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7307635/v1/cd09c3222bac4763e0b4b4d9.png"},{"id":90383740,"identity":"4dea929d-de7c-4478-852b-af95cf09ac15","added_by":"auto","created_at":"2025-09-02 07:02:39","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":124700,"visible":true,"origin":"","legend":"\u003cp\u003eTransition probability curves and estimated percentage of total duration for five health states over 22 years\u003c/p\u003e\n\u003cp\u003eNotes: State 1-5: 1. Participants without physical conditions (diabetes, stroke, heart conditions and cancers) and mental symptoms (depressive symptoms and cognitive impairment); 2. Participants with physical conditions; 3. Participants with mental symptoms; 4. Participants with mental symptoms and physical conditions; 5. Participants suffering from psychiatric disorder. ACEs: adverse childhood experiences.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-7307635/v1/25afa429990b7ecd7186e56e.png"},{"id":96362750,"identity":"8ba07993-948a-40c7-978f-233efb2b11c3","added_by":"auto","created_at":"2025-11-20 09:47:35","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2081583,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7307635/v1/cffbd9b9-8cc6-4b03-907e-de3203dc1a65.pdf"},{"id":90381155,"identity":"9474553c-855e-499d-b004-cbf7e7159f2c","added_by":"auto","created_at":"2025-09-02 06:46:39","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":1862145,"visible":true,"origin":"","legend":"Supplementary Materials","description":"","filename":"SupplementaryMaterials.docx","url":"https://assets-eu.researchsquare.com/files/rs-7307635/v1/b98f30e496a9727cc4b7bf4f.docx"}],"financialInterests":"The authors have declared there is \u003cb\u003eNO\u003c/b\u003e conflict of interest to disclose","formattedTitle":"Associations between adverse childhood experiences and progression to incident psychiatric disorders in older adults: A 22-year cohort study","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eWith the rapidly aging population worldwide, poor mental health in older adults has become a major public health challenge, contributing substantially to high disability, low quality of life and increased healthcare utilization \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. Previous research found that approximately 14% of individuals aged 60 and above suffer from psychiatric disorders globally \u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. The 2019 Global Health Estimates indicated that mental health conditions, particularly depression and anxiety, accounted for 10.6% of the total disability-adjusted life years (DALYs) among older adults \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. Mental health in later life is largely influenced by physical conditions, social environments as well as the cumulative effects of life experiences. Factors, such as exposure to adversity, loss of intrinsic capacity and declining functional ability, can lead to increased psychological distress \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. Among the early life factors, adverse childhood experiences (ACEs) have emerged as a critical determinant of mental well-being with lasting impact on mental health across the lifespan.\u003c/p\u003e\u003cp\u003eACEs refer to experiences of potentially traumatic events occurring before age 18 years, which can disrupt a person\u0026rsquo;s sense of safety, stability, and bonding \u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. Common types of ACEs include child abuse, neglect, or household dysfunction involving substance abuse, mental illness, incarceration, domestic violence and parental separation or divorce \u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. Additionally, research on ACEs has expanded the scope to other significant stressors such as exposure to natural disasters, extreme economic hardship, bullying, school and community violence, life-threatening illnesses or injuries, and even school grade retention \u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. Exposure to ACEs can increase the risk of a wide range of psychiatric problems, including depression, anxiety, post-traumatic stress disorder and substance use disorders \u003csup\u003e\u003cspan additionalcitationids=\"CR8 CR9 CR10 CR11\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. For example, a large birth cohort study found that each additional ACE was associated with a 52% increase in the odds of developing any psychiatric disorder in adulthood, even after adjusting for shared genetic and environmental influences \u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. Neuroimaging research has shown that ACEs can lead to alterations of blood flow, activity, and connectivity in specific brain regions which may potentially mediate the impact of ACEs on the development of psychiatric disorders \u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eDespite the growing body of evidence, most studies have focused on the associations between ACEs and mental health issues among children, adolescents, young and middle-aged adults, with relatively few longitudinal studies tracking the progression of psychiatric disorders into later life \u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. In addition, most studies used cross-sectional designs or short follow-up periods, which limit the ability to capture the dynamic changes in mental health status over time. There is a lack of research on how ACEs can influence the transition between different mental states in older populations, such as from subclinical symptoms to a diagnosed psychiatric disorder. Furthermore, late-life psychiatric disorders often co-occur with chronic physical illnesses, which may affect the progression and management of psychiatric disorders \u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eTo address these gaps, we conducted a cohort study using follow-up data from the nationally representative Health and Retirement Study (HRS) across a 22-years period to: (1) examine the associations between different ACEs and the incidence of psychiatric disorders, incorporating time-varying covariates and repeated assessments; and (2) explore how ACEs influence the changes across various health states (e.g., physical and mental health symptoms transitioning to psychiatric disorders). Findings from this study could inform the development of preventive measures to mitigate the adverse impact of ACEs, and intervention strategies to improve the mental health outcomes in older populations.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1 Study design and samples\u003c/h2\u003e\u003cp\u003eThis was a cohort study based on the most recent 22-year dataset (2000\u0026ndash;2022; waves 5\u0026ndash;16) of the Health and Retirement Study (HRS). The HRS is a nationally representative longitudinal study that has biennially surveyed U.S. residents aged 50 and older since 1992 (Wave 1). The study is funded by the National Institute on Aging (grant numbers NIA UO1AG009740 and NIA RO1AG073289) and is conducted by the University of Michigan \u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. The details of the HRS methodology have been described previously (Heeringa and Connor, 1995). Our study used the data obtained from the RAND HRS Longitudinal File (Version P, including 2000\u0026ndash;2020 wave of sociodemographic and health-related data), HRS core data (including ACEs-related data and 2022 wave of all related data) and exit data (including all-cause mortality data). The RAND HRS Longitudinal File, developed by the RAND Center for the Study of Aging, provides systematically cleaned and processed data from all waves of the HRS except for the 2022 wave \u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eThe study cohort included individuals who participated in the 2000 wave (i.e., baseline) and followed up longitudinally to 2022. Participants who fulfilled the inclusion criteria: 1) were aged 50 years or older at baseline; 2) were interviewed during at least one follow-up assessment; 3) completed ACEs assessments during the 2008\u0026ndash;2012 surveys; and 4) had no psychiatric disorders at baseline. For covariates with missing values related to demographic, health, or lifestyle variables, we applied imputation using last observation carried forward (LOCF) and next observation carried forward (NOCF), as previously recommended \u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. The HRS received ethical approval from the Institutional Review Board of Virginia Commonwealth University (HM20023839). All participants provided informed consent. As a secondary analysis of HRS data, this study was exempt from ethical review.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2 Measurements\u003c/h2\u003e\u003cdiv id=\"Sec5\" class=\"Section3\"\u003e\u003ch2\u003e2.2.1 Adverse childhood experiences\u003c/h2\u003e\u003cp\u003eFollowing previous studies \u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e, the presence of ACEs was assessed using nine items extracted from the Leave-Behind Questionnaires (LBQ) \u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e that was completed during the 2008\u0026ndash;2012 waves of the HRS. Participants were asked whether they had ever experienced the events before 18 years old or that the year of ACE occurrence before 18 years old was recorded in the HRS database. All items were handled as binary variables (1=\"Yes\" and 0= \"No\"). The total scores of ACEs ranged from 0 to 9, with higher scores indicating more severe ACEs. As per previous research \u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e, ACEs were classified into three types: Trauma \u0026amp; violence (4 items including \u0026ldquo;been in a major fire or disaster\u0026rdquo;, \u0026ldquo;fire a weapon in combat\u0026rdquo;, \u0026ldquo;ever victim of physical attack\u0026rdquo;, and \u0026ldquo;life-threatening illness\u0026rdquo;), Family dysfunction (3 items including \u0026ldquo;mother neglect\u0026rdquo;, \u0026ldquo;parents drink or use drugs and caused family problems\u0026rdquo;, and \u0026ldquo;physical abused by parents\u0026rdquo;) and Social problem (2 items including a year of school over again, and trouble with the police). The description and coding of the ACE items are listed in Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section3\"\u003e\u003ch2\u003e2.2.2 Incidence of psychiatric disorders\u003c/h2\u003e\u003cp\u003eFollowing previous research \u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e, psychiatric disorders were identified based on the standardized question at each HRS wave: \u0026ldquo;Have you been diagnosed with emotional, nervous, or psychiatric problem by a doctor?\u0026rdquo;. The study outcome was the incidence of psychiatric disorders which was first identified during follow-up.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section3\"\u003e\u003ch2\u003e2.2.3 Covariates\u003c/h2\u003e\u003cdiv id=\"Sec8\" class=\"Section4\"\u003e\u003ch2\u003e2.2.3.1 Sociodemographic data\u003c/h2\u003e\u003cp\u003eSociodemographic variables potentially related to psychiatric disorders included age, sex (male vs. female), race (White/ Caucasian, Black/ African American or other), marital status (categorized as married, divorced/separated, widowed, or never married/other), educational level (\u0026gt;\u0026thinsp;12 years vs. \u0026le;12 years), living with others (yes vs. no), vigorous physical activity (\u0026ge;\u0026thinsp;3 times/ week, yes vs. no), alcohol use (yes vs. no) and cigarette smoking (yes vs. no).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec9\" class=\"Section4\"\u003e\u003ch2\u003e2.2.3.2 Health-related variables\u003c/h2\u003e\u003cp\u003eChronic diseases included self-reported physician-diagnosed major physical diseases recorded in the HRS such as diabetes, cancer, heart disease, stroke, hypertension, lung diseases, and arthritis.\u003c/p\u003e\u003cp\u003eDepression was evaluated using the 8-item Center for Epidemiologic Studies Depression Scale (CESD-8) \u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. Each item was scored as 1 or 0 (yes or no), with items 4 and 6 being reverse scored. The total scores ranged from 0 to 8, with higher scores indicating more severe depressive symptoms. A cutoff score of 4 was used to identify individuals having depressive symptoms (depression hereafter) \u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eCognitive function was assessed using the modified version of the Telephone Interview for Cognitive Status (TICS-m) \u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. Following a previous study \u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e, the total score of TICS-m was calculated by adding up the respective scores of memory, attention and calculation domains, which ranged from 0 to 27, with higher scores indicating better cognitive performance. A cutoff score of 11 was used to identify individuals having cognitive impairment \u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eSleep was measured using the 4-item Jenkins Sleep Scale (JSS-4) \u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e. Each item was rated on a 3-point Likert scale ranging from 1 (\u0026ldquo;most of the time\u0026rdquo;) to 3 (\u0026ldquo;rarely or never\u0026rdquo;). Item 4 was reverse scored. Higher total scores reflected more severe insomnia symptoms, and a cutoff score of 5 was used to identify those with insomnia symptoms (insomnia hereafter) \u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e. All covariates were assessed at each HRS biennial wave.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003e2.3 Statistical Analyses\u003c/h2\u003e\u003cp\u003eFrequencies and percentages as well as means and standard deviations (SDs) were used to describe categorical and continuous variables, respectively. All covariates were compared between different ACE types using Chi-square, \u003cem\u003et\u003c/em\u003e and Wilcoxon rank sum tests, as appropriate. All statistical analyses were conducted using R (version 4.4.2) \u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e. A two-sided \u003cem\u003eP\u003c/em\u003e-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e\u003cp\u003eTo examine the longitudinal association between ACEs and the risk of psychiatric disorders in older age (PDOA), we used Cox proportional hazards regression models with time-varying covariates \u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e. Participants were followed up from baseline (2000) until the occurrence of a psychiatric disorder, death, loss to follow-up, or end of study (2022), whichever came first. Time-varying covariates, such as health-related variables and lifestyle factors, were updated at each wave to account for the changes over time. Three Cox models were constructed, adding covariates progressively. Model 1 adjusted for age, sex and race; Model 2 added marital status, education level, living with others, lifestyle variables (i.e., smoking, alcohol use, and vigorous physical activity) based on Model 1; Model 3 further added major physical diseases (i.e., diabetes, cancer, heart conditions, stroke, hypertension, lung diseases, and arthritis), depression (i.e., total CESD-8 score), insomnia (i.e., total JSS-4 score) and cognitive function (i.e., total TICS-m scores) based on Model 2. Following previous studies \u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e, ACEs were analyzed in three forms: (1) ACE type (i.e., no ACEs, Trauma \u0026amp; violence, Family Dysfunction, Social problems) with no ACEs group as the reference; (2) total number of ACEs (i.e., 0, 1, 2, and 3\u0026thinsp;+\u0026thinsp;ACEs) as a categorical variable with the 0 ACE group as the reference, and (3) continuous ACE scores (ranging, 0\u0026ndash;9). Schoenfeld residuals were used to assess the proportional hazards assumption and to ensure no violation was found. Kaplan-Meier survival curves were plotted to examine potential differences in incidence rates across types and number of ACEs.\u003c/p\u003e\u003cp\u003eWe also conducted subgroup analyses to explore whether the associations between ACEs and the incidence of PDOA were moderated by age (50\u0026ndash;64 years vs. \u0026ge;65 years), sex, marital status, educational level, living with others, alcohol use, cigarette smoking, engagement in vigorous activity, insomnia (JSS-4 scores\u0026thinsp;\u0026lt;\u0026thinsp;4 vs. \u0026ge;4), depression (CESD\u0026thinsp;\u0026lt;\u0026thinsp;5 vs. \u0026ge;5), and cognitive impairment (TICS-m\u0026thinsp;\u0026le;\u0026thinsp;11) between the group with and without ACEs.\u003c/p\u003e\u003cp\u003eTo assess the robustness of the associations between ACEs and the incidence of psychiatric disorders, five sensitivity analyses were conducted by: (1) excluding cases with psychiatric disorders during the first two years after the baseline; (2) excluding cases with psychiatric disorder in the first follow-up wave; (3) using the total number of physical diseases as a time-varying covariate in Model 3, instead of adjusting for individual physical diseases; (4) using traditional Cox regression model adjusting only for baseline covariates; (5) performing competing risk analyses using Fine\u0026ndash;Gray subdistribution hazard models, given that death may preclude the occurrence of psychiatric disorders. Cumulative incidence function (CIF) curves were constructed to compare the risks of psychiatric disorders and death overtime across different types and number of ACEs.\u003c/p\u003e\u003cp\u003eAdditionally, the multistate Markov model was implemented to capture the dynamic transitions of health status among individuals with ACEs and those without ACEs, focusing particularly on how ACEs affected transitions across physical and mental health states and ultimately led to psychiatric disorders. Such an approach provides an integrated perspective on disease process and enables identification of influential risk factors and long-term predictions \u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eIn this study, each participant was followed up with repeated health assessments across multiple follow-up waves, and transitions between defined states were tracked accordingly. Five states were defined to represent key clinical trajectories: (1) absence of physical conditions or mental health symptoms (No PC \u0026amp; No MS); (2) presence of physical conditions only (PC); (3) presence of mental health symptoms only [MS, depression (CESD\u0026thinsp;\u0026le;\u0026thinsp;4) and (or) cognitive impairment (TICS-m\u0026thinsp;\u0026le;\u0026thinsp;11)]; (4) co-occurrence of both physical conditions and mental health symptoms (PC \u0026amp; MS); and (5) having psychiatric disorders, defined as the absorbing state. The state structure is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA. States 1 to 4 were defined as transient states, while state 5 as the absorbing state. Transition intensity parameters (q\u003csub\u003e\u003cem\u003eij\u003c/em\u003e\u003c/sub\u003e) represent the instantaneous transition risk from state \u003cem\u003ei\u003c/em\u003e to \u003cem\u003ej\u003c/em\u003e. These were estimated through maximum likelihood under the assumption of continuous time Markov processes. For instance, q\u003csub\u003e3\u0026rarr;5\u003c/sub\u003e reflects the instantaneous hazard of progressing from only having mental health symptoms to a diagnosed psychiatric disorder. Figure\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB illustrates representative individual-level transitions in our sample, showing the heterogeneous patterns of disease progression observed during follow-up. The transition intensity matrix \u003cem\u003eQ\u003c/em\u003e based on 5-state model was formulated as follows:\u003c/p\u003e\u003cp\u003e\u003cimg src=\"data:image/png;base64,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\" width=\"584\" height=\"82\"\u003e\u003c/p\u003e\u003cp\u003eIn this context, the transition probability represents the likelihood of a transition from one state to another within a given time interval. To assess the influence of potential factors on transition dynamics, a series of univariate Markov models was fitted first, each incorporating a single covariate (e.g., ACEs in the total sample, and all other covariates in the ACE-exposed group) independently. Cumulative transition probabilities over a 22-year horizon were then computed. All multistate models were implemented using the R package \u003cem\u003emsm\u003c/em\u003e.\u003c/p\u003e\u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003e3.1 Participant characteristics\u003c/h2\u003e\u003cp\u003eOf the 19,580 participants in the 2000 wave, we included 8,628 participants who followed-up with 79,477 observations from 2000 to 2022 (Figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). Baseline sociodemographic and health-related characteristics of participants stratified by the four ACE types are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The mean age of participants was 64.75 years (SD\u0026thinsp;=\u0026thinsp;8.01), and the majority were female (n\u0026thinsp;=\u0026thinsp;4,998; 57.2%), married (n\u0026thinsp;=\u0026thinsp;6,310; 73.1%), and had lower than high school education (n\u0026thinsp;=\u0026thinsp;4,901; 56.8%). Univariate analyses showed significant differences between ACE types in terms of age, sex, race, marital status, educational level, living status, vigorous physical activity, suffering from heart conditions, depression score and cognition score (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\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 of the total sample and by different types of ACEs (N\u0026thinsp;=\u0026thinsp;8,628)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"14\"\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\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eVariables\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c3\" namest=\"c2\" rowspan=\"2\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003cp\u003e(N\u0026thinsp;=\u0026thinsp;8,628)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"8\" nameend=\"c11\" namest=\"c4\"\u003e\u003cp\u003eTypes of ACEs\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" morerows=\"1\" nameend=\"c14\" namest=\"c12\" rowspan=\"2\"\u003e\u003cp\u003eUnivariate analyses\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003eNo adversity\u003c/p\u003e\u003cp\u003e(N\u0026thinsp;=\u0026thinsp;5,672, 65.7%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u003cp\u003eTrauma \u0026amp; violence (N\u0026thinsp;=\u0026thinsp;2,160, 25.0%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u003cp\u003eFamily dysfunction (N\u0026thinsp;=\u0026thinsp;608, 7.0%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e\u003cp\u003eSocial problems (N\u0026thinsp;=\u0026thinsp;188, 2.2%)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eN\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e%\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eN\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e%\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eN\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003e%\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eN\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u003cp\u003e%\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c10\"\u003e\u003cp\u003eN\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c11\"\u003e\u003cp\u003e%\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c12\"\u003e\u003cp\u003e\u003cem\u003eχ\u003c/em\u003e\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c13\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"1\" nameend=\"c14\" namest=\"c14\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3,692\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e42.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2,158\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e38.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e312\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e53.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e577\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e41.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e645\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e65.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e284.920\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c14\" namest=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRace\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\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e14.143\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e\u003cb\u003e0.028\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c14\" namest=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWhite/ Caucasian\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7,331\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e85.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4,785\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e84.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e516\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e88.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e1,192\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e86.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e838\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e84.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c14\" namest=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBlack/ African American\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1,005\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e11.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e689\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e12.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e44\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e7.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e149\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e10.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e123\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e12.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c14\" namest=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOther\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e291\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e197\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e3.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e3.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e2.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c14\" namest=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMarried\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6,310\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e73.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4,120\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e72.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e451\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e77.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e974\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e70.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e765\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e77.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e21.382\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c14\" namest=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHigh school education or above (\u0026ge;\u0026thinsp;12 years)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3,727\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e43.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2,562\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e45.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e287\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e49.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e591\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e42.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e287\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e29.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e98.640\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c14\" namest=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLiving with others\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6,680\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e77.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4,354\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e76.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e473\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e81.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e1,049\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e75.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e804\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e81.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e17.573\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c14\" namest=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAlcohol use\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2,801\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e32.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1,831\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e32.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e203\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e34.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e425\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e30.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e342\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e34.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e5.770\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e0.123\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c14\" namest=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSmoking\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1,120\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e13.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e714\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e12.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e68\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e11.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e200\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e14.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e138\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e14.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e5.070\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e0.167\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c14\" namest=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVigorous physical activity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4499\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e52.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2929\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e51.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e347\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e59.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e697\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e50.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e526\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e53.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e16.007\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c14\" namest=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePhysical disease\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\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c14\" namest=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDiabetes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e958\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e11.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e615\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e10.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e59\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e10.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e151\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e10.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e133\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e13.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e6.568\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e0.087\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c14\" namest=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCancer\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e848\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e9.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e563\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e9.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e57\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e9.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e147\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e10.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e81\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e8.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e3.970\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e0.265\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c14\" namest=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHeart conditions\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1298\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e15.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e818\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e14.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e104\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e17.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e208\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e15.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e168\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e17.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e8.325\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e\u003cb\u003e0.040\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c14\" namest=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eStroke\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e260\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e169\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e3.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e2.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e3.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e0.843\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e0.839\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c14\" namest=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHypertension\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3857\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e44.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2529\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e44.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e238\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e40.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e627\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e45.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e463\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e46.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e5.472\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e0.140\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c14\" namest=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLung diseases\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e482\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e293\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e5.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e41\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e7.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e93\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e6.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e55\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e5.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e7.568\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e0.056\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c14\" namest=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eArthritis\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4582\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e53.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2979\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e52.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e327\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e56.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e739\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e53.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e537\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e54.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e3.637\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e0.304\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c14\" namest=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003eMean\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003eSD\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003eMean\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003eSD\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003eMean\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003eSD\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u003cb\u003eMean\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e\u003cb\u003eSD\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e\u003cb\u003eMean\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e\u003cb\u003eSD\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e\u003cb\u003et/Z\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e\u003cb\u003eP\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c14\" namest=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge (years)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e64.75\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e8.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e65.22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e8.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e65.55\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e8.34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e62.82\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e7.55\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e64.28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e7.40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e106.660\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c14\" namest=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDepression (CESD-8 total)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.59\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.54\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1.64\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e1.31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e1.75\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e1.25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e1.63\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e27.831\u003csup\u003e\u003cb\u003e*\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c14\" namest=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSleep (JSS-4 total)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6.71\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6.69\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e6.88\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e2.04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e6.69\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e2.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e6.73\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e2.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e5.549\u003csup\u003e\u003cb\u003e*\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e0.136\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c14\" namest=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCognition (TICS-m)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e16.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e16.24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e4.20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e16.25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e4.15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e16.13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e4.19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e15.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e4.18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e73.380\u003csup\u003e\u003cb\u003e*\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c14\" namest=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"14\" nameend=\"c14\" namest=\"c1\"\u003e\u003cp\u003eNotes: Bolded values indicate \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05;\u0026nbsp;ACE: adverse childhood experience; SD: standard deviation.\u0026nbsp;\u0026nbsp;CESD-8: 8-item Center for Epidemiological Studies Depression Scale; JSS-4: 4-item Jenkins Sleep Scale;\u0026nbsp;TICS-m: modified version of the Telephone Interview for Cognitive Status Scale. \u003csup\u003e\u003cb\u003e*\u003c/b\u003e\u003c/sup\u003eAnalyzed using Wilcoxon rank sum test.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003e3.2 ACEs and the incidence of psychiatric disorders in older adults\u003c/h2\u003e\u003cdiv id=\"Sec14\" class=\"Section3\"\u003e\u003ch2\u003e3.2.1 Incidence rate of psychiatric disorders in older adults\u003c/h2\u003e\u003cp\u003eDuring an average follow-up duration of 16.8 years, 1,429 (16.6%) participants experienced psychiatric disorders. The overall incidence rate was 9.85 (95%CI: 9.34\u0026ndash;10.37) per 1,000 person-years. The incidence rate of PDOA increased with the total number of ACEs: 8.85 per 1,000 person-years for participants with no ACE, 11.2, 13.0 and 15.0 per 1,000 person-years for those with one, two, and \u0026ge;\u0026thinsp;3 ACEs, respectively (Table S3). The incidence rate was also different between different ACE types: 11.4, 14.1, 8.9 per 1,000 person-years for those with trauma \u0026amp; violence, family dysfunction, and social problems, respectively (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\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\u003eThe associations between types of ACEs and the incidence of PDOA (N\u0026thinsp;=\u0026thinsp;8,628)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"12\"\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\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eVariables\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eCases\u003c/p\u003e\u003cp\u003eN\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eIncidence rate, per 1000\u003c/p\u003e\u003cp\u003eperson-years\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e\u003cp\u003eModel 1\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c9\" namest=\"c7\"\u003e\u003cp\u003eModel 2\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c12\" namest=\"c10\"\u003e\u003cp\u003eModel 3\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eHR\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e95%CI\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eHR\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003e95%CI\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c10\"\u003e\u003cp\u003eHR\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c11\"\u003e\u003cp\u003e95%CI\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c12\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eACE type\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"11\" nameend=\"c12\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo adversity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5,672\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e8.85\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e\u003cp\u003eReference\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c9\" namest=\"c7\"\u003e\u003cp\u003eReference\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c12\" namest=\"c10\"\u003e\u003cp\u003eReference\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTrauma \u0026amp; violence\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e582\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e11.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.372\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.123\u0026ndash;1.678\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e0.002\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1.384\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e1.132\u0026ndash;1.693\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e\u003cb\u003e0.002\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e1.279\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e1.052\u0026ndash;1.555\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e\u003cb\u003e0.014\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFamily dysfunction\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1,386\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e14.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.607\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.412\u0026ndash;1.830\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1.557\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e1.366\u0026ndash;1.775\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e1.358\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e1.190\u0026ndash;1.548\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSocial problems\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e988\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e8.92\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.152\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.964\u0026ndash;1.377\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.119\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1.099\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.918\u0026ndash;1.317\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.305\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0.974\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e0.813\u0026ndash;1.167\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e0.772\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge (years)\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\u003cp\u003e0.994\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.987\u0026ndash;1.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.091\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.982\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.974\u0026ndash;0.989\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0.970\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e0.962\u0026ndash;0.978\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMale\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\u003cp\u003e0.637\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.568\u0026ndash;0.713\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.777\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.689\u0026ndash;0.876\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0.768\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e0.680\u0026ndash;0.867\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRace\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"11\" nameend=\"c12\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWhite/ Caucasian\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\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e\u003cp\u003eReference\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c9\" namest=\"c7\"\u003e\u003cp\u003eReference\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c12\" namest=\"c10\"\u003e\u003cp\u003eReference\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBlack/ African American\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\u003cp\u003e0.765\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.641\u0026ndash;0.914\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e0.003\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.649\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.541\u0026ndash;0.778\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0.544\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e0.452\u0026ndash;0.654\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOther\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\u003cp\u003e1.095\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.834\u0026ndash;1.438\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.515\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.966\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.734\u0026ndash;1.270\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.802\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0.839\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e0.646\u0026ndash;1.090\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e0.189\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMarried\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\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.672\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.500-0.904\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e\u003cb\u003e0.009\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0.787\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e0.580\u0026ndash;1.068\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e0.125\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHigh school education or above (\u0026ge;\u0026thinsp;12 years)\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\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.945\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.847\u0026ndash;1.054\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.309\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e1.176\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e1.049\u0026ndash;1.320\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e\u003cb\u003e0.006\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLiving with others\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\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1.115\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.825\u0026ndash;1.507\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.478\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e1.154\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e0.848\u0026ndash;1.571\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e0.362\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAlcohol use\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\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.624\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.549\u0026ndash;0.708\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0.703\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e0.619\u0026ndash;0.799\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSmoking\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\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1.060\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.883\u0026ndash;1.274\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.531\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0.949\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e0.788\u0026ndash;1.143\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e0.578\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVigorous physical activity\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\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.634\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.563\u0026ndash;0.714\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0.815\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e0.721\u0026ndash;0.921\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePhysical disease\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\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDiabetes\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\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0.947\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e0.836\u0026ndash;1.072\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e0.387\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCancer\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\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0.882\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e0.769\u0026ndash;1.013\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e0.075\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHeart conditions\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\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e1.127\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e1.004\u0026ndash;1.266\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e\u003cb\u003e0.043\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eStroke\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\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e1.443\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e1.226\u0026ndash;1.698\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHypertension\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\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e1.102\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e0.977\u0026ndash;1.243\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e0.116\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLung diseases\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\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e1.253\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e1.081\u0026ndash;1.452\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e\u003cb\u003e0.003\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eArthritis\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\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e1.294\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e1.136\u0026ndash;1.474\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDepression score (CESD-8)\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\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e1.317\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e1.285\u0026ndash;1.349\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSleep score (JSS-4)\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\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e1.067\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e1.039\u0026ndash;1.096\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCognition score (TICS-m)\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\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0.961\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e0.948\u0026ndash;0.974\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"12\" nameend=\"c12\" namest=\"c1\"\u003e\u003cp\u003eNotes: Bolded values indicate \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u0026nbsp;ACE: adverse childhood experience; PDOA: psychiatric disorders in older adults; HR: Hazard ratio; CI: Confidence interval;\u0026nbsp;CESD-8: 8-item Center for Epidemiological Studies Depression Scale; JSS-4: 4-item Jenkins Sleep Scale;\u0026nbsp;TICS-m: modified version of the Telephone Interview for Cognitive Status Scale.\u003c/p\u003e\u003cp\u003eModel 1 was adjusted for age, sex and race/ethnicity.\u003c/p\u003e\u003cp\u003eModel 2 was adjusted for age, sex, race/ethnicity, marital status, living with others, educational level, vigorous activities, smoking, and alcohol use.\u003c/p\u003e\u003cp\u003eModel 3 was adjusted for the same covariates as model 2 plus history of major physical diseases (diabetes, cancer, heart conditions, stroke, hypertension, lung diseases, and arthritis), total CESD-8 score, total JSS-4 score and total TICS-m score.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section3\"\u003e\u003ch2\u003e3.2.2 The associations between ACEs and the incidence of psychiatric disorders in older adults\u003c/h2\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows significant associations between trauma \u0026amp; violence, and family dysfunction with the incidence of PDOA. In the fully adjusted model, participants with childhood trauma \u0026amp; violence, and family dysfunction had 27.9% and 35.8% higher risks of PDOA, respectively, as compared to those with no ACE exposure [adjusted Hazard ratio (aHR): 1.279, 95%CI: 1.052\u0026ndash;1.555 vs. aHR: 1.358, 95%CI: 1.190\u0026ndash;1.548]. However, no association was observed between childhood social problems and the incidence of PDOA. Table S2 shows a dose-response relationship between the total number of ACE and the incidence of PDOA, which persisted across all three models. In the fully adjusted model, participants with two and \u0026ge;\u0026thinsp;3 ACEs had 27.9% and 50.6% higher risks of PDOA, respectively, compared to those with no ACE [aHR: 1.279, 95%CI: 1.056\u0026ndash;1.549 vs. aHR: 1.506, 95%CI: 1.128\u0026ndash;2.011]. The Kaplan-Meier survival curve (Figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e) illustrates significant differences in incidence rates across different types and number of ACEs (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e\u003cp\u003eFigure \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows that the association between ACEs and the incidence of psychiatric disorders was more pronounced among individuals aged 50\u0026ndash;64 years (aHR: 1.71, 95% CI:1.36\u0026ndash;2.15) than those aged\u0026thinsp;\u0026ge;\u0026thinsp;65 years (aHR: 1.23, 95% CI: 1.09 to 1.39; \u003cem\u003eP\u003c/em\u003e for interaction: 0.013); among participants with higher educational level (aHR: 1.71, 95% CI: 1.45\u0026ndash;2.02) than those with lower educational level (aHR: 1.12, 95% CI: 0.98\u0026ndash;1.29, \u003cem\u003eP\u003c/em\u003e for interaction: \u0026lt;0.001); and among those with cognitive decline (HR: 1.49, 95% CI: 1.31\u0026ndash;1.70) compared to those without cognitive decline (aHR:1.06, 95% CI:0.88\u0026ndash;1.27; \u003cem\u003eP\u003c/em\u003e for interaction: 0.002).\u003c/p\u003e\u003cp\u003eIn sensitive analyses, consistent associations between ACEs and the incidence of psychiatric disorders were observed (Tables S3- S6). The competing risk analyses showed that the association between ACEs and the incidence of PDOA remained significant when accounting for death as a competing event (Table S7). The CIF curves revealed a higher cumulative risk of PDOA over time in individuals with greater exposure to ACEs and those with family dysfunction or direct trauma \u0026amp; violence, although death became more prominent as a competing risk after approximately 100 months of follow-up (Figure S3).\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\u003ch2\u003e3.3 Transitions between health states among participants with and without ACEs\u003c/h2\u003e\u003cdiv id=\"Sec17\" class=\"Section3\"\u003e\u003ch2\u003e3.3.1 State transition percentage and intensity\u003c/h2\u003e\u003cp\u003eThe observed state transitions during follow-up are summarized in Table S8. Among participants with ACEs, transitions from comorbid physical conditions and mental health symptoms (PC \u0026amp; MS) to psychiatric disorders accounted for the largest proportion (3.7%), followed by transitions from MS alone (3.5%). In contrast, among those without ACEs, the proportion transitioning to psychiatric disorders was lower across all states, with the highest transition from the PC \u0026amp; MS state (3.2%). Participants with ACEs were also more likely to transition between vulnerable health states (e.g., from MS to PC \u0026amp; MS: 8.2%) compared to those without ACEs (7.5%). Participants with ACEs showed consistently higher transition intensities across most state transitions compared to those without ACEs, e.g., the transitions from No PC \u0026amp; No MS to MS (0.130 vs. 0.104) and from PC to PC \u0026amp; MS (0.146 vs. 0.129) (Table S9).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec18\" class=\"Section3\"\u003e\u003ch2\u003e3.3.2 State transition probability and total duration\u003c/h2\u003e\u003cp\u003eFigures \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e (left panel) and S4 illustrate the 22-year transition probability curves across five health states, stratified by participants with ACEs and those without ACEs. The probability of remaining in the healthy state (1\u0026rarr;1, No PC \u0026amp; No MS) declined sharply for both groups, especially in ACE group. At baseline, the probabilities of state 1 were over 0.8 in both groups, while by the year 2022, the probabilities dropped to 0.153 in the ACE group and 0.196 in the no-ACE group, respectively. The probability of transitioning from the healthy state to more adverse states (e.g., 1\u0026rarr;2, 1\u0026rarr;4, and especially 1\u0026rarr;5) increased over time. Certain transitions, such as recovery to healthy states (e.g., 2\u0026rarr;1, 3\u0026rarr;1), remained low and stable in both groups, indicating more likelihood of accelerated health deterioration and less likelihood of recovery.\u003c/p\u003e\u003cp\u003eNotably, the group with ACEs exhibited higher and faster probabilities of progressing from the healthy state or any intermediate states to the absorbing state 5 (psychiatric disorders) over the 22 years; for instance, at 22 years, 1\u0026rarr;5: ACE 0.253 vs. no ACE 0.190; 2\u0026rarr;5: ACE 0.245 vs. no ACE 0.209; 3\u0026rarr;5: ACE 0.269 vs. no ACE 0.215; 4\u0026rarr;5: ACE 0.269 vs. no ACE 0.233. We calculated the 22-year cumulative transition probabilities from four transient health states (States 1\u0026ndash;4) to the incidence of psychiatric disorders (State 5). The cumulative transition probabilities ranged from 19.0\u0026ndash;23.3% and from 25.3\u0026ndash;26.9% across states in the group without ACE and the group with ACEs, respectively. Even among participants initially in a healthy state (State 1), those with ACE exposure had a 33% higher risk of transitioning to psychiatric disorders (25.3% vs. 19.0%) by the year 2022. Furthermore, the group with ACEs exhibited consistent higher probabilities of transitioning between intermediate states (e.g., 1\u0026rarr;2, 1\u0026rarr;4, 3\u0026rarr;4, and 2\u0026rarr;4), indicating a higher likelihood of progression to early physical conditions, as well as comorbid physical and mental health conditions.\u003c/p\u003e\u003cp\u003eFigure \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e (right panel) shows the standardized percentages of total duration across the five states. Over the 22-year follow-up period, most of the duration was in state 2 (PC), accounting for approximately 48% of the total time across both groups. This was followed by state 4 (PC \u0026amp; MS), comprising around 31%, and state 1 (No PC \u0026amp; No MS), at about 15%. Hence, both total duration of PC and PC \u0026amp; MS prolonged, while those of healthy state (No PC \u0026amp; No MS) shortened. When comparing participants with ACEs and those without ACEs, the group with ACEs spent less time in the healthy state (state 1) (14.5% vs 15.6%) and more time in the comorbid state (state 4) (31.2% vs 30.1%) than their non-ACE counterparts. These trends indicated that ACEs might be associated with earlier onset and longer duration of complex comorbidity prior to the onset of psychiatric disorder.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec19\" class=\"Section3\"\u003e\u003ch2\u003e3.3.3 Covariate effects on state transitions\u003c/h2\u003e\u003cp\u003eAcross the whole sample, univariate Markov models demonstrated that individuals with ACEs had a significantly higher risk of developing both physical and mental health conditions. Specifically, participants with ACEs had 19.0%, 25.3% and 85.9% higher risks of transition from No PC \u0026amp; No MS to PC, MS, and to psychiatric disorder, respectively; and 13.8% higher risk of transition from PC to PC \u0026amp; MS (Table S10).\u003c/p\u003e\u003cp\u003eAmong participants with ACEs, univariate models (Table S11) showed that older age (\u0026ge;\u0026thinsp;65 years) and male sex were consistently associated with a lower risk of transitioning from all states to psychiatric disorders (e.g., No PC \u0026amp; No MS \u0026rarr; Psychiatric disorders, HR:0.538, 95% CI: 0.362\u0026ndash;0.798 for age; HR:0.536, 95% CI: 0.359\u0026ndash;0.802 for male). Vigorous physical activity was protective for developing psychiatric disorders among those with No PC \u0026amp; No MS (HR:0.620, 95% CI: 0.424\u0026ndash;0.906). Insomnia (JSS-4 total score\u0026thinsp;\u0026ge;\u0026thinsp;5) significantly increased the risk of transition from combined physical and mental symptoms to psychiatric disorders (HR: 2.721, 95% CI: 1.244\u0026ndash;5.952). Among physical diseases, lung diseases (HR: 2.592, 95% CI: 1.524\u0026ndash;4.356) and arthritis (HR: 1.530, 95% CI: 1.028\u0026ndash;2.275) were associated with a higher risk of psychiatric disorders from No PC \u0026amp; No MS state. High school education or above also increased the risk of transition from mental symptoms to psychiatric disorders (HR: 1.864, 95% CI: 1.114\u0026ndash;3.120).\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eTo the best of our knowledge, this was the first cohort study to investigate the associations between ACEs and the incidence of psychiatric disorders in older adults, based on 22 years of follow-up data. We found that ACEs were strongly associated with an increased risk of psychiatric disorders in later life after adjusting for the time-varying confounders regarding lifestyle, physical and mental health conditions. We also identified effect modifications in the relationship between ACEs and the incidence of psychiatric disorders based on stratification by sociodemographic, lifestyle, and health-related factors. Moreover, we explored how ACEs influenced the transition from healthy and intermediate health states to psychiatric disorders and identified risk factors for such transitions.\u003c/p\u003e\u003cp\u003eOur study demonstrated that ACEs could significantly increase the risk of PDOA over a 22-year follow-up. Using time-varying Cox regression, we found that the total ACE score, cumulative number of ACEs and specific ACE types, such as trauma \u0026amp; violence and family dysfunction, were all significantly associated with an elevated risk of psychiatric disorders. The risk increased in a dose\u0026ndash;response manner, with individuals exposed to three or more ACEs having the highest risk. The competing risk model further validated that these associations were not confounded by the differential risk of mortality across groups. These results are consistent with previous findings that ACEs contribute to poorer cognitive, physical, and mental health outcomes in later life \u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e. In terms of ACE subtypes, childhood family dysfunction and trauma \u0026amp; violence were associated with the highest risks of psychiatric disorder. Due to the severe and chronic nature of ACEs, such adversities could cause profound disruptions in emotional regulation, early attachment, and neurobiological development, resulting in lasting impact on mental health in middle and older adulthood \u003csup\u003e\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e. In contrast, social problems (e.g., school difficulties, trouble with police) showed weaker or nonsignificant associations, probably because they are more transient or likely mediated by other factors such as social support or resilience \u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eOur multistate Markov model revealed several key findings about the impact of ACEs on mental health trajectories in older adults. First, ACEs accelerated transitions toward PDOA, since older adults with ACEs transitioned more frequently and more rapidly from healthy to less healthy states. For example, transitions from comorbid physical and mental health conditions (PC \u0026amp; MS) to psychiatric disorders were more frequent in the group with ACEs (3.7% vs. 3.2%); transitions from the healthy state (No PC \u0026amp; No MS) to mental health symptoms (MS) were also faster in the group with ACEs (intensity: 0.130 vs. 0.104), underscoring the role ACEs in accelerating progression towards psychiatric disorders. Such results is aligned with previous research showing that ACEs accelerated the progression of both physical and mental health conditions, predisposing individuals to complex multimorbidity and psychiatric illness \u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eSecond, ACEs prolonged vulnerability states and reduced time in healthy state. The group with ACEs spent less time in the healthy state (14.5% vs. 15.6%) and more time in the comorbid PC \u0026amp; MS state (31.2% vs. 30.1%) over the study period. This pattern indicated that ACEs might not only influence the onset of psychiatric disorders but also prolong the periods of subclinical vulnerability, which overall likely exacerbate psychiatric risks.\u003c/p\u003e\u003cp\u003eThird, individuals with ACEs showed consistently higher cumulative risk of transitioning from healthy or intermediate states to having psychiatric disorders. For instance, by the year 2022, the transition probability from the healthy state to psychiatric disorders was 25.3% in the group with ACEs compared to 19.0% in the group with ACEs, representing a 33% increased risk. Univariate Markov models also demonstrated that individuals with ACEs had 19.0%, 25.3% and 85.9% higher risks of transition from No PC \u0026amp; No MS to PC, MS, and to psychiatric disorder, respectively; and 13.8% higher risks of transition from PC to PC \u0026amp; MS. A previous study using multi-state model also found that higher ACE scores (\u0026ge;\u0026thinsp;4) were associated with an increased probability of forward transitions toward worsening physical health states, such as from robust to pre-frail (HR\u0026thinsp;=\u0026thinsp;1.37, 95% CI: 1.21\u0026ndash;1.54) and from pre-frail to frail (HR\u0026thinsp;=\u0026thinsp;1.39, 95% CI: 1.18\u0026ndash;1.63), as well as a decreased probability of reverting to healthier states (pre-frail to robust, HR\u0026thinsp;=\u0026thinsp;0.64, 95% CI: 0.55\u0026ndash;0.76) \u003csup\u003e\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e. Our findings hence extended previous research by dynamically characterizing how ACEs could influence long-term mental health trajectories in older adults, emphasizing the enduring effects of early life stressors on psychiatric morbidity decades later.\u003c/p\u003e\u003cp\u003eSeveral potential mechanisms may explain the enduring impact of ACEs on late-life mental health trajectories. First, the association between ACEs and poor adult health is likely mediated by psychosocial factors, including having increased exposure to stressful life events, higher perceived stress, negative emotionality, and unhealthy behaviors in adulthood \u003csup\u003e\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e,. Second, chronic stress related to ACEs may induce multisystem dysregulation, including neuroendocrine and inflammatory processes, which cumulatively impair physical and mental health \u003csup\u003e\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e. Third, neuroimaging studies indicates that alterations related to ACEs in brain regions critical for emotional regulation and cognitive control, such as the prefrontal cortex and hippocampus, may mediate increased vulnerability to psychiatric disorders, particularly in individuals experiencing cognitive decline \u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. These psychosocial and biological processes can cumulatively generate sustained risk factors, including chronic inflammation, maladaptive coping strategies, and health-risk behaviors, that may delay recovery from mental health challenges or accelerate transitions to psychiatric disorders.\u003c/p\u003e\u003cp\u003eSubgroup analyses revealed a strong association between ACEs and the incidence of psychiatric disorders among individuals aged 50\u0026ndash;64 years and those with higher educational attainment. This aligns with the results of our multi-state model, showing that individuals aged 50\u0026ndash;64 years with ACEs had greater risks of transitioning from all health states to psychiatric disorders, while those with a higher education level and ACEs had greater risks of transitioning from MS or PC \u0026amp; MS to psychiatric disorders. Individuals aged 50\u0026ndash;64 years often experience greater work-related stress, family obligations, and caregiving responsibilities, compared to those aged 65 and older. Such stressors, combined with psychosocial vulnerabilities resulting from ACEs, can contribute to increased emotional distress and risk of psychiatric disorders \u003csup\u003e\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e. Individuals with a higher education level may exhibit greater awareness of mental health symptoms and are more likely to seek help, leading to increased rates of psychiatric disorder diagnosis \u003csup\u003e\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e. Furthermore, despite having socioeconomic advantages, individuals with a higher education level may still experience major psychosocial stressors (e.g., career pressure and social expectations) that can exacerbate the impact of early adversities \u003csup\u003e\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e. Our findings that females with ACEs had increased risks of transitions from all health states to psychiatric disorders is also consistent with the higher prevalence of mental illness observed in females \u003csup\u003e\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u003c/sup\u003e. Biological sensitivities, including hormonal fluctuations and neural differences, combined with gender-specific psychosocial stressors such as caregiving burdens and exposure to gender-based violence, can amplify the impact of early adversities on emotional regulation and psychiatric vulnerability in women \u003csup\u003e\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u003c/sup\u003e. The interaction between ACEs and female-specific factors might contribute to the elevated psychiatric risk across various health trajectories observed in our study.\u003c/p\u003e\u003cp\u003eFurthermore, in the group with ACEs, univariate multi-state analysis identified other factors that significantly influenced the risk of transition to psychiatric disorders. Behavioral factors, such as physical inactivity and insomnia, could further increase psychiatric risk, highlighting the role of lifestyle in modulating outcomes of ACEs. Chronic physical conditions, including lung diseases and arthritis, also elevated the risk of progression profoundly from healthy (No PC \u0026amp; No MS) or physical condition (PC) states to psychiatric disorders, potentially through mechanisms related to systemic inflammation \u003csup\u003e\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u003c/sup\u003e and functional impairment \u003csup\u003e\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eFrom a clinical perspective, our findings highlight the importance of routine screening for ACEs in older adults to identify those with elevated risk for psychiatric disorders, especially among individuals exposed to trauma, violence and family dysfunction in early life. Behavioral interventions targeting those with risk factors such as younger age, female gender, and high education level as well as modifiable factors such as physical activity and sleep disturbances, may mitigate the development of psychiatric morbidity. Further, effective management of chronic physical conditions like lung diseases and arthritis can be crucial to reduce the transition towards psychiatric disorders. Future research to explore integrated care models addressing both multimorbidity and psychosocial adversities is warranted to improve the mental health outcomes in older populations with ACEs.\u003c/p\u003e\u003cp\u003eThe strengths of this study included a large, nationally representative cohort with longitudinal data spanning over two decades, the use of a comprehensive set of time-varying covariates to reduce potential confounding, and the application of multi-state Markov modeling that enabled a nuanced understanding of dynamic progress to the onset of psychiatric disorders. However, some limitations should be noted. First, ACEs were retrospectively self-reported, which might introduce recall bias. However, a prior study has reported on the reasonable validity of adult retrospective reporting of ACEs \u003csup\u003e\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e\u003c/sup\u003e. Similar to previous research \u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e\u003c/sup\u003e, psychiatric disorders were based on self-reported diagnosis by physicians, which might lead to underreporting. Second, the measurement of ACEs in the HRS included a limited set of adverse events, particularly regarding social problems, which might not fully capture the breadth of childhood adversities. Third, potential confounding factors that might influence health trajectories, such as genetic predisposition, social support or later-life stressors, were not included in the analyses. Fourth, missing data in certain time-varying covariates (i.e., CESD-8, JSS-4, and TICS-m) were imputed using LOCF and NOCF methods, which might introduce bias regarding the constancy of data across time. Fifth, due to limited number of transitions between health states, we were unable to perform multivariate Markov modeling incorporating all variables that were significantly associated with transitions in the univariate analyses, thus limiting the adjustment for confounding factors. Finally, although the cohort is representative of the US older adult population, findings might not be generalizable to those in other cultural or socioeconomic contexts.\u003c/p\u003e\u003cp\u003eIn conclusion, this long-term cohort study revealed that ACEs could significantly increase the risk of PDOA as well as accelerate the progression to PDOA, especially among those exposed to past trauma and violence and family dysfunction. The association between ACEs and PDOA were more pronounced among females, participants aged 50\u0026ndash;64 years, and those with higher education level or with cognitive decline. Individuals with ACEs showed faster transitions from healthy and intermediate states to having psychiatric disorders, spent less time in healthy state, and had prolonged periods of multimorbidity prior to onset of psychiatric disorder. Demographic, behavioral, and physical health factors (such as age, sex, education level, physical activity, insomnia, lung diseases, and arthritis) might further modify these risks. Our findings highlighted the enduring impact of early life adversity on mental health trajectories in later life, and further underscored the need for integrated, trauma-informed care to mitigate psychiatric morbidity in older populations.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors are grateful to all participants and clinicians involved in this study.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have no conflicts of interest to declare.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding Sources\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was supported by Hainan Provincial Natural Science Foundation of China (No. 821QN249), the Education Department of Hainan Province (Hnjg2024ZC-55), Beijing High Level Public Health Technology Talent Construction Project (Discipline Backbone-01-028), the Beijing Municipal Science \u0026amp; Technology Commission (No. Z181100001518005), the Capital\u0026apos;s Funds for Health Improvement and Research (CFH 2024-2-1174) and the University of Macau (MYRG-GRG2023-00141-FHS; CPG2025-00021-FHS).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eStudy design: Hui-Ying Fan, Mu-Rui Zheng, Qinge Zhang, Chee H. Ng, Yu-Tao Xiang.\u003c/p\u003e\n\u003cp\u003eData collection, analysis and interpretation: Hui-Ying Fan, Mu-Rui Zheng, Xiao-Xuan Meng, Qinge Zhang, Chee H. Ng, Yu-Tao Xiang, Zhi-Cheng Du, Zhaohui Su, Teris Cheung, Gabor S. Ungvari.\u003c/p\u003e\n\u003cp\u003eDrafting of the manuscript: Hui-Ying Fan, Mu-Rui Zheng, Yu-Tao Xiang.\u003c/p\u003e\n\u003cp\u003eCritical revision of the manuscript: Chee H. Ng.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eApproval of the final version for publication: all co-authors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data that support the findings of this study are available from The University of Michigan Health and Retirement Study Platform at https://hrsdata.isr.umich.edu/data-products/public-survey-data\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eMental health of older adults. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.who.int/news-room/fact-sheets/detail/mental-health-of-older-adults\u003c/span\u003e\u003cspan address=\"https://www.who.int/news-room/fact-sheets/detail/mental-health-of-older-adults\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e, 2023, Accessed Date Accessed 2023 Accessed.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGlobal Health Data Exchange (GHDx). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://vizhub.healthdata.org/gbd-results/\u003c/span\u003e\u003cspan address=\"https://vizhub.healthdata.org/gbd-results/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e, 2023, Accessed Date Accessed 2023 Accessed.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAbout Adverse Childhood Experiences. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.cdc.gov/aces/about/index.html\u003c/span\u003e\u003cspan address=\"https://www.cdc.gov/aces/about/index.html\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e, 2024, Accessed Date Accessed 2024 Accessed.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFelitti VJ, Anda RF, Nordenberg D, Williamson DF, Spitz AM, Edwards V \u003cem\u003eet al.\u003c/em\u003e Relationship of childhood abuse and household dysfunction to many of the leading causes of death in adults - The adverse childhood experiences (ACE) study. \u003cem\u003eAMERICAN JOURNAL OF PREVENTIVE MEDICINE\u003c/em\u003e 1998; 14(4): 245\u0026ndash;258.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFinkelhor D, Shattuck A, Turner H, Hamby S. Improving the Adverse Childhood Experiences Study Scale. \u003cem\u003eJAMA Pediatrics\u003c/em\u003e 2013; 167(1): 70\u0026ndash;75.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eOral R, Ramirez M, Coohey C, Nakada S, Walz A, Kuntz A \u003cem\u003eet al.\u003c/em\u003e Adverse childhood experiences and trauma informed care: the future of health care. \u003cem\u003ePEDIATRIC RESEARCH\u003c/em\u003e 2016; 79(1): 227\u0026ndash;233.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eChapman DP, Whitfield CL, Felitti VJ, Dube SR, Edwards VJ, Anda RF. Adverse childhood experiences and the risk of depressive disorders in adulthood. \u003cem\u003eJ Affect Disord\u003c/em\u003e 2004; 82(2): 217\u0026ndash;225.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eThurston C, Murray AL, Franchino-Olsen H, Meinck F. Prospective longitudinal associations between adverse childhood experiences and adult mental health outcomes: a protocol for a systematic review and meta-analysis. \u003cem\u003eSyst Rev\u003c/em\u003e 2023; 12(1): 181.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSahle BW, Reavley NJ, Li W, Morgan AJ, Yap MBH, Reupert A \u003cem\u003eet al.\u003c/em\u003e The association between adverse childhood experiences and common mental disorders and suicidality: an umbrella review of systematic reviews and meta-analyses. \u003cem\u003eEur Child Adolesc Psychiatry\u003c/em\u003e 2022; 31(10): 1489\u0026ndash;1499.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGon\u0026ccedil;alves H, Soares AL, Santos AP, Ribeiro CG, Bierhals IO, Vieira LS \u003cem\u003eet al.\u003c/em\u003e Adverse childhood experiences and consumption of alcohol, tobacco and illicit drugs among adolescents of a Brazilian birth cohort. \u003cem\u003eCad Saude Publica\u003c/em\u003e 2016; 32(10): e00085815.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHo GWK, Bressington D, Karatzias T, Chien WT, Inoue S, Yang PJ \u003cem\u003eet al.\u003c/em\u003e Patterns of exposure to adverse childhood experiences and their associations with mental health: a survey of 1346 university students in East Asia. \u003cem\u003eSoc Psychiatry Psychiatr Epidemiol\u003c/em\u003e 2020; 55(3): 339\u0026ndash;349.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDan\u0026iacute;elsd\u0026oacute;ttir HB, Aspelund T, Shen Q, Halldorsdottir T, Jakobsd\u0026oacute;ttir J, Song H \u003cem\u003eet al.\u003c/em\u003e Adverse Childhood Experiences and Adult Mental Health Outcomes. \u003cem\u003eJAMA Psychiatry\u003c/em\u003e 2024; 81(6): 586\u0026ndash;594.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKeator DB, Salgado F, Madigan C, Murray S, Norris S, Amen D. Adverse childhood experiences, brain function, and psychiatric diagnoses in a large adult clinical cohort. \u003cem\u003eFront Psychiatry\u003c/em\u003e 2024; 15: 1401745.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHosseini-Kamkar N, Varvani Farahani M, Nikolic M, Stewart K, Goldsmith S, Soltaninejad M \u003cem\u003eet al.\u003c/em\u003e Adverse Life Experiences and Brain Function: A Meta-Analysis of Functional Magnetic Resonance Imaging Findings. \u003cem\u003eJAMA Netw Open\u003c/em\u003e 2023; 6(11): e2340018.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKobayashi LC. Adverse Childhood Experiences and Later-Life Cognitive Aging: Persistent Methodological Challenges Limit the Evidence Base. \u003cem\u003eJ Gerontol A Biol Sci Med Sci\u003c/em\u003e 2024; 79(8).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eManning LK, Bouchard LM, Flanagan JL. Comorbidities of physical and psychiatric syndromes in later life. \u003cem\u003eOxford Research Encyclopedia of Psychology\u003c/em\u003e2018.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSonnega A, Faul JD, Ofstedal MB, Langa KM, Phillips JW, Weir DR. Cohort Profile: the Health and Retirement Study (HRS). \u003cem\u003eInternational Journal of Epidemiology\u003c/em\u003e 2014; 43(2): 576\u0026ndash;585.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBugliari D, Carroll J, Hayden O, Hayes J, Hurd MD, Lee S \u003cem\u003eet al.\u003c/em\u003e RAND HRS Longitudinal File 2020 (V2) Documentation. \u003cem\u003eAging\u003c/em\u003e 2024.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLydersen S. Last observation carried forward. \u003cem\u003eTidsskrift for den Norske Laegeforening\u003c/em\u003e 2019; 139(9).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNakai M, Chen D-G, Nishimura K, Miyamoto Y. Comparative study of four methods in missing value imputations under missing completely at random mechanism. \u003cem\u003eOpen Journal of Statistics\u003c/em\u003e 2014; 2014.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMatthews TA, Li J. Adverse Childhood Experiences, Social Isolation, Job Strain, and Cardiovascular Disease Mortality in U.S. Older Employees. \u003cem\u003eMedicina (Kaunas)\u003c/em\u003e 2023; 59(7).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eB\u0026uuml;rgin D, Cyril B, Marc S, Paige T, and O\u0026rsquo;Donovan A. Fact or artefact? Childhood adversity and adulthood trauma in the U.S. population-based Health and Retirement Study. \u003cem\u003eEuropean Journal of Psychotraumatology\u003c/em\u003e 2020; 11(1): 1721146.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eClarke P, Fisher G, House J, Smith J, Weir D. Guide to content of the HRS psychosocial leave-behind participant lifestyle questionnaires: 2004 \u0026amp; 2006. \u003cem\u003eAnn Arbor, MI\u003c/em\u003e: \u003cem\u003eUniversity of Michigan\u003c/em\u003e 2008.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSmith J, Ryan L, Fisher G, Sonnega A, Weir D. Psychosocial and lifestyle questionnaire 2006\u0026ndash;2016: Documentation Report Core Section LB Survey Research Center. \u003cem\u003eInstitute for Social Research, University of Michigan\u003c/em\u003e 2017.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKrause N, Shaw BA, Cairney J. A descriptive epidemiology of lifetime trauma and the physical health status of older adults. \u003cem\u003ePsychology and aging\u003c/em\u003e 2004; 19(4): 637.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCigolle CT, Langa KM, Kabeto MU, Tian Z, Blaum CS. Geriatric conditions and disability: the Health and Retirement Study. \u003cem\u003eAnn Intern Med\u003c/em\u003e 2007; 147(3): 156\u0026ndash;164.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eVan de Velde S, Levecque K, Bracke P. Measurement equivalence of the CES-D 8 in the general population in Belgium: a gender perspective. \u003cem\u003eArchives of Public Health\u003c/em\u003e 2009; 67(1): 15.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMojtabai R, Olfson M. Major depression in community-dwelling middle-aged and older adults: prevalence and 2- and 4-year follow-up symptoms. \u003cem\u003ePsychological Medicine\u003c/em\u003e 2004; 34(4): 623\u0026ndash;634.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBrandt J, Spencer M, Folstein M. The telephone interview for cognitive status. \u003cem\u003eNeuropsychiatry, Neuropsychology, and Behavioral Neurology\u003c/em\u003e 1988; 1(2): 111\u0026ndash;117.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCrimmins EM, Kim JK, Langa KM, Weir DR. Assessment of cognition using surveys and neuropsychological assessment: the Health and Retirement Study and the Aging, Demographics, and Memory Study. \u003cem\u003eJournals of Gerontology Series B: Psychological Sciences and Social Sciences\u003c/em\u003e 2011; 66 Suppl 1(Suppl 1): i162-171.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCovello AL, Horwitz LI, Singhal S, Blaum CS, Li Y, Dodson JA. Cardiovascular disease and cumulative incidence of cognitive impairment in the Health and Retirement Study. \u003cem\u003eBMC Geriatrics\u003c/em\u003e 2021; 21(1): 274.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLee JH, Luchetti M, Aschwanden D, Sesker AA, Strickhouser JE, Terracciano A \u003cem\u003eet al.\u003c/em\u003e Cognitive Impairment and the Trajectory of Loneliness in Older Adulthood: Evidence from the Health and Retirement Study. \u003cem\u003eJ Aging Health\u003c/em\u003e 2022; 34(1): 3\u0026ndash;13.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eJenkins CD, Stanton BA, Niemcryk SJ, Rose RM. A scale for the estimation of sleep problems in clinical research. \u003cem\u003eJournal of Clinical Epidemiology\u003c/em\u003e 1988; 41(4): 313\u0026ndash;321.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003evon K\u0026auml;nel R, Meister-Langraf RE, Zuccarella-Hackl C, Schiebler SLF, Znoj H, Pazhenkottil AP \u003cem\u003eet al.\u003c/em\u003e Sleep disturbance after acute coronary syndrome: A longitudinal study over 12 months. \u003cem\u003ePLoS One\u003c/em\u003e 2022; 17(6): e0269545.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eR Development Core Team. R: A language and environment for statistical computing.. R Foundation for Statistical Computing Vienna, Australia, 2020.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhang Z, Reinikainen J, Adeleke KA, Pieterse ME, Groothuis-Oudshoorn CGM. Time-varying covariates and coefficients in Cox regression models. \u003cem\u003eAnn Transl Med\u003c/em\u003e 2018; 6(7): 121.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eYu J, Patel RA, Haynie DL, Vidal-Ribas P, Govender T, Sundaram R \u003cem\u003eet al.\u003c/em\u003e Adverse childhood experiences and premature mortality through mid-adulthood: A five-decade prospective study. \u003cem\u003eLANCET REGIONAL HEALTH-AMERICAS\u003c/em\u003e 2022; 15.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMeira-Machado L, de U\u0026ntilde;a-Alvarez J, Cadarso-Su\u0026aacute;rez C, Andersen PK. Multi-state models for the analysis of time-to-event data. \u003cem\u003eSTATISTICAL METHODS IN MEDICAL RESEARCH\u003c/em\u003e 2009; 18(2): 195\u0026ndash;222.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHaczkewicz KM, Shahid S, Finnegan HA, Monnin C, Cameron CD, Gallant NL. Adverse childhood experiences (ACEs), resilience, and outcomes in older adulthood: A scoping review. \u003cem\u003eChild Abuse \u0026amp; Neglect\u003c/em\u003e 2024: 106864.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHughes K, Bellis MA, Hardcastle KA, Sethi D, Butchart A, Mikton C \u003cem\u003eet al.\u003c/em\u003e The effect of multiple adverse childhood experiences on health: a systematic review and meta-analysis. \u003cem\u003eLancet Public Health\u003c/em\u003e 2017; 2(8): e356-e366.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAnda RF, Felitti VJ, Bremner JD, Walker JD, Whitfield C, Perry BD \u003cem\u003eet al.\u003c/em\u003e The enduring effects of abuse and related adverse experiences in childhood. A convergence of evidence from neurobiology and epidemiology. \u003cem\u003eEur Arch Psychiatry Clin Neurosci\u003c/em\u003e 2006; 256(3): 174\u0026ndash;186.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLi J, Pei H, Yan X, Wei Y, Chen G, Pei L. Adverse Childhood Experiences and Social Participation on Frailty State Transitions among middle-aged and older adults: evidence from a 10-year prospective study in China. \u003cem\u003eJ Nutr Health Aging\u003c/em\u003e 2024; 28(12): 100400.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBourassa KJ, Moffitt TE, Harrington H, Houts R, Poulton R, Ramrakha S \u003cem\u003eet al.\u003c/em\u003e Childhood Adversity and Midlife Health: Shining a Light on the Black Box of Psychosocial Mechanisms. \u003cem\u003ePrevention Science\u003c/em\u003e 2023; 24(5): 817\u0026ndash;828.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDanese A, McEwen BS. Adverse childhood experiences, allostasis, allostatic load, and age-related disease. \u003cem\u003ePhysiology \u0026amp; Behavior\u003c/em\u003e 2012; 106(1): 29\u0026ndash;39.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGonzalez JM, Alegr\u0026iacute;a M, Prihoda TJ, Copeland LA, Zeber JE. How the relationship of attitudes toward mental health treatment and service use differs by age, gender, ethnicity/race and education. \u003cem\u003eSocial Psychiatry and Psychiatric Epidemiology\u003c/em\u003e 2011; 46(1): 45\u0026ndash;57.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eThoits PA. Stress and Health: Major Findings and Policy Implications. \u003cem\u003eJournal of Health and Social Behavior\u003c/em\u003e 2010; 51(1_suppl): S41-S53.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWhitaker RC, Dearth-Wesley T, Herman AN, Block AE, Holderness MH, Waring NA \u003cem\u003eet al.\u003c/em\u003e The interaction of adverse childhood experiences and gender as risk factors for depression and anxiety disorders in US adults: a cross-sectional study. \u003cem\u003eBMC Public Health\u003c/em\u003e 2021; 21(1): 2078.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBangasser DA, Valentino RJ. Sex differences in stress-related psychiatric disorders: Neurobiological perspectives. \u003cem\u003eFrontiers in Neuroendocrinology\u003c/em\u003e 2014; 35(3): 303\u0026ndash;319.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKuehner C. Why is depression more common among women than among men? \u003cem\u003eThe Lancet Psychiatry\u003c/em\u003e 2017; 4(2): 146\u0026ndash;158.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMiller AH, Raison CL. The role of inflammation in depression: from evolutionary imperative to modern treatment target. \u003cem\u003eNat Rev Immunol\u003c/em\u003e 2016; 16(1): 22\u0026ndash;34.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eScott KM, Bruffaerts R, Tsang A, Ormel J, Alonso J, Angermeyer MC \u003cem\u003eet al.\u003c/em\u003e Depression-anxiety relationships with chronic physical conditions: results from the World Mental Health Surveys. \u003cem\u003eJ Affect Disord\u003c/em\u003e 2007; 103(1\u0026ndash;3): 113\u0026ndash;120.\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. \u003cem\u003eJ Child Psychol Psychiatry\u003c/em\u003e 2004; 45(2): 260\u0026ndash;273.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhou Y, Kivim\u0026auml;ki M, Yan LL, Carrillo-Larco RM, Zhang Y, Cheng Y \u003cem\u003eet al.\u003c/em\u003e Associations between socioeconomic inequalities and progression to psychological and cognitive multimorbidities after onset of a physical condition: a multicohort study. \u003cem\u003eEClinicalMedicine\u003c/em\u003e 2024; 74: 102739.\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":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"translational-psychiatry","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"tp","sideBox":"Learn more about [Translational Psychiatry](http://www.nature.com/tp/)","snPcode":"41398","submissionUrl":"https://mts-tp.nature.com/cgi-bin/main.plex","title":"Translational Psychiatry","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"adverse childhood experiences, psychiatric disorder, older adults, disease progression, comorbidities ","lastPublishedDoi":"10.21203/rs.3.rs-7307635/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7307635/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe long-term impact of adverse childhood experiences (ACEs) on the development of psychiatric disorders in older adults remains unclear. This study examined associations between ACEs and incident psychiatric disorders in older adults (PDOA) over 22 years. Data from the 2000\u0026ndash;2022 Health and Retirement Study (HRS) were analyzed. Time-varying Cox regression and multistate Markov models were applied to explore the impact of ACEs on transitions across five health states: healthy, physical conditions (PC), mental symptoms (MS), comorbid PC \u0026amp; MS, and PDOA. Models were adjusted for demographic, behavioral, and disease-related factors. Among 8,628 participants during average 16.8-year follow-up, 1,429 developed psychiatric disorders (incidence: 9.85 per 1,000 person-years). ACEs, particularly trauma/ violence (aHR\u0026thinsp;=\u0026thinsp;1.279) and family dysfunction (aHR\u0026thinsp;=\u0026thinsp;1.358), were significantly associated with higher risk. A dose-response relationship was found. Participants with ACEs had higher transition percentages and intensities from healthy to less healthy states, notably from PC \u0026amp; MS to PDOA (percentages: 3.7% vs. 3.2%) and from the healthy state to MS (intensities: 0.130 vs. 0.104). They also spent less time in the healthy state and more time in comorbid states, with a 33% higher 22-year cumulative probability of PDOA (25.3% vs. 19.0%). Risk was further elevated by younger age, female sex, higher educational level, low physical activity, insomnia, lung diseases, and arthritis. ACEs appear to have enduring adverse impacts on mental health in later life by accelerating the progression to comorbidity and the development of psychiatric disorders. Early screening and physical-mental health interventions are essential for prevention.\u003c/p\u003e","manuscriptTitle":"Associations between adverse childhood experiences and progression to incident psychiatric disorders in older adults: A 22-year cohort study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-02 06:46:34","doi":"10.21203/rs.3.rs-7307635/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"transferred","content":"Translational Psychiatry","date":"2025-12-09T16:48:11+00:00","index":"","fulltext":""},{"type":"decision","content":"Reject after peer review","date":"2025-11-14T10:16:29+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"This content is not available.","date":"2025-11-08T14:51:54+00:00","index":3,"fulltext":"This content is not available."},{"type":"editorInvitedReview","content":"This content is not available.","date":"2025-11-05T18:33:24+00:00","index":4,"fulltext":"This content is not available."},{"type":"editorInvitedReview","content":"This content is not available.","date":"2025-11-04T11:13:44+00:00","index":6,"fulltext":"This content is not available."},{"type":"editorInvitedReview","content":"This content is not available.","date":"2025-10-30T10:33:56+00:00","index":5,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2025-10-28T10:49:08+00:00","index":6,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2025-10-28T07:47:12+00:00","index":5,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2025-10-22T22:32:17+00:00","index":4,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2025-10-22T17:28:53+00:00","index":3,"fulltext":"This content is not available."},{"type":"editorInvitedReview","content":"This content is not available.","date":"2025-09-30T20:18:12+00:00","index":2,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2025-09-25T08:49:46+00:00","index":2,"fulltext":"This content is not available."},{"type":"editorInvitedReview","content":"This content is not available.","date":"2025-09-10T08:18:28+00:00","index":1,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2025-08-28T10:02:06+00:00","index":1,"fulltext":"This content is not available."},{"type":"reviewersInvited","content":"","date":"2025-08-22T19:47:36+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-08-08T09:55:19+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-08-08T09:44:24+00:00","index":"","fulltext":""},{"type":"submitted","content":"Molecular Psychiatry","date":"2025-08-07T13:34:22+00:00","index":"","fulltext":""},{"type":"checksFailed","content":"","date":"2025-08-06T10:44:56+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"translational-psychiatry","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"tp","sideBox":"Learn more about [Translational Psychiatry](http://www.nature.com/tp/)","snPcode":"41398","submissionUrl":"https://mts-tp.nature.com/cgi-bin/main.plex","title":"Translational Psychiatry","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"fdd8d912-5299-4772-a556-b7e5cabf24c3","owner":[],"postedDate":"September 2nd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":53589416,"name":"Health sciences/Diseases/Psychiatric disorders"},{"id":53589417,"name":"Health sciences/Biomarkers/Predictive markers"}],"tags":[],"updatedAt":"2025-12-15T23:25:36+00:00","versionOfRecord":[],"versionCreatedAt":"2025-09-02 06:46:34","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7307635","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7307635","identity":"rs-7307635","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}