Relationship between adverse childhood experiences and motoric cognitive risk in Chinese older adults: A nationwide study

Relationship between adverse childhood experiences and motoric cognitive risk in Chinese older adults: A nationwide 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 Research Article Relationship between adverse childhood experiences and motoric cognitive risk in Chinese older adults: A nationwide study Yan Wu, Yang Yang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9217244/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 5 You are reading this latest preprint version Abstract Background With the rapid advancement of aging, cognitive impairment has become an important factor contributing to the increase in medical costs for older adults. Motor Cognitive Risk (MCR) is a pre-dementia syndrome. Early identification and intervention of MCR’s risk factors may reduce the incidence of dementia. However, previous studies mainly focused on the contemporaneous risk factors of MCR and paid less attention to the long-term impact of adverse childhood experiences (ACEs) on health outcomes in later life. Thus, this study assesses the relationship between adverse childhood experiences (ACEs) and motoric cognitive risk (MCR) among Chinese older adults. Methods We adopted data from the 2014 Life History Survey and the 2015 follow-up wave of the China Health and Retirement Longitudinal Study (CHARLS). The study excluded participants who were under the age of 60 and had dementia and mobility impairments. ACEs were evaluated by three dimensions and 8 items. MCR was assessed by two single-item questions. Logistic regression was used to estimate the relationship between ACEs and MCR. Results The final sample included 4,937 older adults. After adjusting for covariates, childhood neglect was related with increased risk of MCR (OR = 1.382, 95% CI: 1.099–1.738). Each additional ACEs were linked to a 16.5% increased risk of MCR (OR = 1.165, 95% CI: 1.038–1.307). In addition, participants who reported three or more ACEs showed higher risk of MCR than those with no ACEs (OR = 2.050, 95% CI: 1.136–3.699). Conclusion These findings suggest that childhood neglect and exposure to multiple ACEs increased the risk of MCR in old age. The results highlight the long-term effects of early adversity on cognitive and motor health of older adults, which underscore the important of early ACEs screening and interventions across the lifespan. Chinese older adults Adverse childhood experiences Motoric cognitive risk Figures Figure 1 Text box 1.Contributions to the literature This study indicates the importance to distinguish the effects of child neglect from child abuse on cognitive decline of older adults. Highlights the importance of improving the socioeconomic conditions of older adults to buffer the long-term health consequences caused by adverse childhood experiences. Provides a simple and evidence-based tool of cumulative risk threshold (≥3 adverse childhood experiences) for identifying older adults at an increased risk of cognitive decline in clinical and community setting. 1. Introduction As population is aging worldwide, health problems are increasingly prevalent among older adults. Cognitive impairment represents a major contributor to disability and rising medical costs among older adults. There were currently more than 50 million patients with cognitive impairment in worldwide [ 1 ]. In China, the number of people with dementia has reached 15.07 million in 2020 [ 2 ], and by 2030, the social and economic costs of dementia is expected to reach 114.2 billion US dollars [ 3 ]. These trends underscore the critical need for early and intervene in high-risk groups for cognitive impairment. Studies have showed that motoric cognitive risk (MCR) has become as a reliable predictor of progressive dementia [ 4 ], which refers to subjective memory complaint and slow walking speed that occur in the absence of mobility disorders and dementia [ 5 ]. Identifying and intervening the risk factors for MCR are the key to reducing the incidence of MCR. While previous research has primarily focused on contemporaneous risk factors of MCR chronic diseases [ 6 – 8 ]. However, the life course theory and the cumulative inequality theory suggested that early-life hardships increased the risk of developing health problems in later life [ 9 ]. This theoretical foundation has spurred growing advocacy for early-life interventions to promote healthy aging [ 10 ]. Adverse childhood experiences (ACEs) are predictors of poor health outcomes in later life [ 11 ], including disadvantaged socioeconomic status in childhood, childhood abuse, and childhood neglect [ 12 ]. Adverse childhood experiences have been widely proven to contribute to the development of general cognitive function [ 13 ] in old age. However, prior studies overlooked ACEs’ potential influence on MCR, which captured the coordinated decline of both cognitive and motor functions. Fortunately, recent evidences have indicated a potential connection between ACEs and MCR. From a biological perspective, ACEs frequently stimulate the individual’s stress response system, delay the development of hippocampus, amygdala, prefrontal cortex and prefrontal limbic circuits, leading to reduced corresponding executive functions. Additionally, the reduction of brain/cognitive reserves and the damaging effect of apolipoprotein E on cells can all contribute to cognitive dysfunction [ 14 , 15 ]. Long-term stress during childhood can impair the individual’s physiological control system for responding to the environment, leading to accelerate declines in motor functions [ 16 ]. From a socioeconomic perspective, individuals with ACEs are limited their access to healthcare and healthy food, leading to health disadvantages and cognitive dysfunction in old age [ 17 ]. Therefore, based on the above hypotheses, this study aims to explore the association between ACEs and the risk of MCR through the CHARLS data. 2. Method 2.1. Participants We adopted data from the China Health and Retirement Longitudinal Study (CHARLS), which employed a stratified sampling design to survey participants aged 45 and over in China, ensuring broad geographical and demographic representation. The study adopted data from the 2014 Life History Survey and the 2015 follow-up wave. The analytic sample was restricted to participants aged 60 or older. Those with dementia or disability were excluded, as well as data with missing values for ACEs, cognitive risks related to physical activity, and covariates. Finally, 4,937 samples were included. The data screening process is shown in Fig. 1 . Before this study began, all participants indicated informed consent. CHARLS was approved by the Biomedical Ethics Review Committee of Peking University (IRB00001052-11015). 2.2. Measure 2.2.1. ACEs Based on prior researches [ 18 , 19 ], this study defined ACEs from three dimensions: disadvantaged socioeconomic status in childhood, childhood abuse, and childhood neglect. Table 1 showed the questions and response for the assessment of ACEs. The total score of ACEs was the sum of three domain scores. The total score ranges from 0 to 3, with higher scores suggesting greater exposure. Table 1 The questions and response for the assessment of ACEs. Dimensions Questionnaire items Disadvantaged socioeconomic status in childhood (Responses were categorized as 0 = the total score is 0–3; 1 = the total score is 4) What was the highest level of education your mother received? (Responses were categorized as 0 = Illiterates; 1 = Non-illiterates) What was the highest level of education your father received? (Responses were categorized as 0 = Illiterates; 1 = Non-illiterates) Before you were 17 years old, how was your family’s economic situation compared to that of ordinary families in your community/village? (Responses were categorized as 0 = Much better than them and a little better than them; 1 = a little worse than them, much worse than them) Before you were 17 years old, was there a period when your family couldn’t have enough to eat? (Responses were categorized as 0 = No; 1 = Yes) Childhood abuse (Responses were categorized as 0 = the total score is 0; 1 = the total score is 1–2) When you were a child, did you get hit by your female caregiver? (Responses were categorized as 0 = often or sometimes; 1 = rarely or never) When you were a child, did your male caregiver hit you? (Responses were categorized as 0 = often or sometimes; 1 = rarely or never) Childhood neglect (Responses were categorized as 0 = the total score is 0; 1 = the total score is 1–2) Did your female caregivers often express their love for you when you were a child? (Responses were categorized as 0 = often, sometimes or rarely; 1 = never) Did your female caregiver spend a lot of energy taking care of you when you were a child? (Responses were categorized as 0 = a lot, some or a little; 1 = Not at all) 2.2.2. MCR According to established criteria [ 20 , 21 ], MCR was defined as subjective memory complaint and slow walking speed that occur in the absence of mobility disorders and dementia. Subjective memory complaint was assessed by the single question, “How do you feel about your current memory?” If participants responded “Fair” or “Poor”, it indicated the presence of subjective memory complaints for participants. The participants walked at a normal speed on a 2.5m surface twice and the walking time was measured twice and averaged. Walking speed was the distance divided by the time. Slow walking speed a speed lower than the mean specific to gender and age (for < 75 years old and ≥ 75 years old) as determined by the sample, and less than one standard deviation. The thresholds are as follows: 0.639 m/s (for < 75 years males) and 0.491 m/s (for ≥ 75 years males), as well as 0.568 m/s (for < 75 years females) and 0.400 m/s (for ≥ 75 years females). 2.2.3. Covariates Covariates included sociodemographic and health-related factors. Sociodemographic variables were gender (male/female), age, and marital status (married/cohabiting vs. single/separated/widowed). Health-related covariates included body mass index (BMI) and chronic diseases history(yes/no). 2.3. Data analysis Data were extracted from the CHARLS dataset using R and analyzed using SPSS 25.0. Categorical variables were described using frequencies and percentages [N (%)], and Continuous variables were described using mean and standard deviation (M ± SD). Logistic regression was used to analyze the odds ratios (ORs) and 95% confidence intervals (95% CIs) of the association between ACEs and MCR. 3. Results 3.1. Descriptive information of sample characteristics As shown in Table 2 , 14.4%, 26.8%, and 22.2% of the total population reported having experienced childhood neglect, childhood abuse, and disadvantaged socioeconomic status in childhood. 50.4%, 37.2%, 10.9%, and 1.5% of the total population reported had been exposed to at 0, 1, 2, and 3 ACEs. 87.7%, 13.4%, and 11.8% of the total population had subjective memory complaints, slow gait speed, and MCR. The majority of the participants were male (50.6%) and had spouses (82.1%). The three most prevalent chronic diseases of the participants were arthritis or rheumatism (66.8%), hypertension (68.3%), and digestive system diseases (78.8%). The BMI of the participants was 23.70 ± 9.846 and their age was 68.12 ± 6.227. Table 2 Descriptive information of sample characteristics Variables Options Frequencies (N) Proportions (%) Childhood neglect No 4227 85.6% Yes 710 14.4% Childhood abuse No 3612 73.2% Yes 1325 26.8% Disadvantaged socioeconomic status in childhood No 3839 77.8% Yes 1098 22.2% ACEs 0 2488 50.4% 1 1839 37.2% 2 536 10.9% 3 74 1.5% Subjective memory complaints No 608 12.3% Yes 4329 87.7% Slow gait speed No 4273 86.6% Yes 664 13.4% MCR No 4353 88.2% Yes 584 11.8% Gender Male 2498 50.6% Female 2439 49.4% Marital status Have spouses 4053 82.1% No spouses 884 17.9% Hypertension No 3371 68.3% Yes 1566 31.7% Dyslipidemia No 4314 87.4% Yes 623 12.6% Diabetes No 4537 91.9% Yes 400 8.1% Malignant tumor No 4890 99.0% Yes 47 1.0% Chronic pulmonary disease No 4373 88.6% Yes 564 11.4% Liver disease No 4781 96.8% Yes 156 3.2% Heart disease No 4151 84.1% Yes 786 15.9% Stroke No 4837 98.0% Yes 100 2.0% Kidney disease No 4629 93.8% Yes 308 6.2% Digestive system disease No 3889 78.8% Yes 1048 21.2% Emotional and mental disorder No 4893 99.1% Yes 44 0.9% Arthritis or rheumatism No 3299 66.8% Yes 1638 33.2% Asthma No 4694 95.1% Yes 243 4.9% 3.2. Association between the types of ACEs and MCR Before controlling for covariates (gender, age, marital status, BMI, chronic disease history), the three dimensions of ACEs (disadvantaged socioeconomic status in childhood, childhood abuse, and childhood neglect) were used as independent variables, and MCR was used as the dependent variable for regression analysis. Older adults who experienced childhood abuse had about 1.4 times the risk of being diagnosed with MCR compared to those who did not (model 1: OR = 1.414, 95% CI: 1.128–1.772), even after adjusting for covariates (model2: OR = 1.382, 95% CI: 1.099–1.738). Disadvantaged socioeconomic status in childhood and childhood abuse were not associated with MCR. Table 3 showed the above results. Table 3 Relationship between the types of ACEs and MCR ACEs Model 1 Model 2 OR (95%CI) P OR (95%CI) P Disadvantaged socioeconomic status in childhood 1.129(0.922–1.383) 0.239 1.151(0.885–1.338) 0.424 Childhood abuse 1.126(0.930–1.363) 0.223 1.143(0.940–1.391) 0.181 Childhood neglect 1.414(1.128–1.772) 0.003 1.382(1.099–1.738) 0.006 Note : Model2 has been adjusted for the covariates (gender, age, marital status, BMI, chronic disease history). 3.3. The association between the exposure intensity of ACEs and MCR Before adjusting for covariates (gender, age, marital status, BMI, chronic disease history), with the total score of ACEs as a continuous variable, for every additional ACEs, the probability of older adults being diagnosed with MCR increased by 17.8% (model1: OR = 1.178, 95% CI: 1.052–1.320), even after adjusting for covariates (model2: OR = 1.165, 95% CI: 1.038–1.307). Compared with those who had not experienced ACEs, the risk of older adults being diagnosed with MCR who had experienced three ACEs increased (model1: OR = 2.097, 95% CI: 1.173–3.748), and this was still the case even after adjusting for the covariates (model2: OR = 2.050, 95% CI: 1.136–3.699). Detailed results were shown in Table 4 . Table 4 Association between the exposure intensity of ACEs and MCR ACEs Model 1 Model 2 OR (95%CI) P OR (95%CI) P ACEs 1.178(1.052–1.320) 0.005 1.165(1.038–1.307) 0.010 0 1.000 1.000 1 1.162(0.963–1.402) 0.118 1.151(0.951–1.393) 0.150 2 1.301(0.986–1.716) 0.063 1.264(0.952–1.677) 0.105 3 2.097(1.173–3.748) 0.012 2.050(1.136–3.699) 0.017 Note : Model2 was adjusted for the covariates (gender, age, marital status, BMI, chronic disease history). 4. Discussion This study confirmed the relationship between ACEs and MCR in a national sample of Chinese older adults. The results support the study hypothesis, indicating that childhood neglect and a higher cumulative burden of ACEs are associated with increased MCR risk. These findings emphasized the potential value of screening for adversity at an early stage and the importance of improving socioeconomic conditions throughout life to mitigate its long-term health consequences. The results showed that childhood neglect was linked to MCR. Previous studies have indicated that individuals who experienced childhood neglect had a reduced ability to effectively utilize cognitive resources [ 22 ]. According to the cumulative disadvantage theory [ 23 ], the disadvantages that individuals encounter in early life can continue to accumulate as they progress through life. Based on this, it can be speculated that cognitive impairments during childhood accumulate over time and affect cognitive functions in old age. Therefore, policies and social services should strengthen support for families at risk of childhood neglect, establish early identification and intervention mechanisms, such as conducting regular screenings through schools, communities, and medical institutions, and providing educational publicity, psychological assistance, and child development resources for families with neglect behaviors, These measures may be reduce the potential harm of childhood neglect at its source. In contrast, disadvantaged socioeconomic status in childhood and childhood abuse were not related to the occurrence of MCR in this study. Three possible reasons may account for these results. First, the research indicates that the negative impact of childhood socioeconomic disadvantage on health may be buffered by a good living standard and medical care in old age. The adverse circumstances of childhood do not have to be irreversible [ 24 ]. Individuals can obtain resources and opportunities through a higher social economic status in adulthood to reduce the negative effects of the early adverse situations [ 25 ]. This suggests that improving the social economic conditions in adulthood may effectively alleviate ACEs’ negative effects. Therefore, public policies should strive to create more fair opportunities for social mobility, strengthen lifelong education, vocational training, and the construction of social security systems, helping individuals to compensate for the early disadvantages. Second, the retrospective self-reporting assessment of ACEs may have recall bias and social expectation deviation. Moreover, influenced by the traditional concept of “beating produces filial piety”, older adults do not consider parental beating as physical abuse [ 26 ]. These reasons may weaken the influence of ACEs on MCR. Therefore, future research should adopt objective, multi-source and cultural adapted measurement tools for ACEs. Third, the results may be an illusion caused by the selective mortality [ 27 ]. Those frail individuals with sever ACEs may have died before entering old age, while those who survived were physically strong older adults, which may weaken the negative impact of ACEs on MCR. This also reinforces the necessity of conducting health promotion and intervention throughout the entire life stage. This study also revealed the dose-response relationship between the intensity of ACE exposure and the risk of MCR. Individuals with three or more ACEs had a significantly higher risk than those without such experiences, which supports the use of a cumulative risk model for ACEs screening. In practical applications, individuals with high ACEs scores (e.g., ≥ 3) can be prioritized for early assessment and intervention in community and clinical settings. Limitations Although this study has significant findings, some limitations still need to be considered. Firstly, the retrospective assessment of ACEs is prone to be influenced by recall bias and social expectation bias, which may reduce the accuracy of exposure measurement and introduce selection bias. Future research would be more beneficial if it could incorporate objective records or historical data. Second, the cross-sectional design precludes causal inference. Prospective life-course studies tracking individuals from childhood are needed to clarify these associations. Finally, while key covariates were adjusted for, residual confounding by unmeasured factors remains possible. 5. Conclusion This study indicates that childhood neglect and exposure to three or more types of ACEs increase the risk of developing MCR in old age. These findings demonstrate that early screening for ACEs and creating a favorable socioeconomic environment throughout one’s life could be effective strategies for promoting cognitive and motor health in older adults. Abbreviations MCR Motoric cognitive risk ACEs Adverse childhood experiences ORs Odds ratios 95% CIs 95% confidence intervals Declarations Acknowledgements None. Funding This work was supported by the General Project of Nanjing Medical University Science and Technology Development Fund in 2024 [grant number NMUB20240216]. Author information Authors and Affiliations Cardiothoracic Surgery Department, Nanjing Medical University Affiliated Brain Hospital, Nanjing, Jiangsu 210029, China Yan Wu Cardiothoracic Surgery Department, Nanjing Medical University Affiliated Brain Hospital, Nanjing, Jiangsu 210029, China Yang Yang Contributions Yan Wu: conceptualization, data curation, methodology, formal analysis, visualization, writing, reviewing and editing. Yang Yang: conceptualization, data curation, methodology, supervision, writing, reviewing, and editing. Corresponding author Correspondence to Yang Yang Ethical considerations The study was conducted in accordance with the principles of the Helsinki Declaration and approved by the Biomedical Ethics Review Committee of Peking University (IRB00001052-11015). Consent for publication Not applicable. Compete interests The authors declare that they have no compete of interest. References Collaborators GDF. Estimation of the global prevalence of dementia in 2019 and forecasted prevalence in 2050: an analysis for the global burden of disease study. Lancet Public Health. 2019;7(2):e105–25. Jia L, Du Y, Chu L, Zhang Z, Li F, Lyu D, Li Y, Li Y, Zhu M, Jiao H, Song Y, Shi Y, Zhang H, Gong M, Wei C, Tang Y, Fang B, Guo D, Wang F, Zhou A, Chu C, Zuo X, Yu Y, Yuan Q, Wang W, Li F, Shi S, Yang H, Zhou C, Liao Z, Lv Y, Li Y, Kan M, Zhao H, Wang S, Yang S, Li H, Liu Z, Wang Q, Qin W, Jia J, COAST Group. 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Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 11 May, 2026 Reviewers invited by journal 04 May, 2026 Editor assigned by journal 13 Apr, 2026 Submission checks completed at journal 10 Apr, 2026 First submitted to journal 08 Apr, 2026 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-9217244","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":637340807,"identity":"368c1765-ab8e-433d-9427-260cb7c8a049","order_by":0,"name":"Yan Wu","email":"","orcid":"","institution":"Nanjing Medical University Affiliated Brain Hospital","correspondingAuthor":false,"prefix":"","firstName":"Yan","middleName":"","lastName":"Wu","suffix":""},{"id":637340808,"identity":"37efe21d-a93c-4679-a408-43278d59c835","order_by":1,"name":"Yang Yang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAzklEQVRIiWNgGAWjYFCCM2xAwoaBsQHEYSNeSxpJWnhAyg5DOcRoMWc8e+wxb9v5POZpZwwYPpQdZuCf3YBfi2XDuXRj3rbbxYyzcwwYZ5w7zCBx5wB+LQYHzphJA7UkNgK1MPO2HWYwkEggSss5iJa/JGg5ANHCSJyWc2mSc84lA7WkFRzsOZfOI3GDkJYbZ49JvCmzS9w4O3njgx9l1nL8MwhoYZA4wMDEC4wOwwYGhgNAPg8B9UDA38DA+OMPA4M8YaWjYBSMglEwUgEAZ+5IMyV16+cAAAAASUVORK5CYII=","orcid":"","institution":"Nanjing Medical University Affiliated Brain Hospital","correspondingAuthor":true,"prefix":"","firstName":"Yang","middleName":"","lastName":"Yang","suffix":""}],"badges":[],"createdAt":"2026-03-25 02:38:42","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9217244/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9217244/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":109101602,"identity":"0f4855b7-c911-4b10-a52c-3255d21dc964","added_by":"auto","created_at":"2026-05-12 14:29:08","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":95998,"visible":true,"origin":"","legend":"\u003cp\u003eFlowchart for screening included participants\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-9217244/v1/e03e27aa24061bbfc84060a1.png"},{"id":109101982,"identity":"e644d442-fc87-4a8e-adbd-cb65f58793b9","added_by":"auto","created_at":"2026-05-12 14:30:45","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":398739,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9217244/v1/3a0d4682-33d7-42eb-a258-39004e8d0eb3.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Relationship between adverse childhood experiences and motoric cognitive risk in Chinese older adults: A nationwide study","fulltext":[{"header":"Text box 1.Contributions to the literature","content":"\u003cli\u003eThis study indicates the importance to distinguish the effects of child neglect from child abuse on cognitive decline of older adults.\u003c/li\u003e\n\u003cli\u003eHighlights the importance of improving the socioeconomic conditions of older adults to buffer the long-term health consequences caused by adverse childhood experiences.\u003c/li\u003e\n\u003cli\u003eProvides a simple and evidence-based tool of cumulative risk threshold (\u0026ge;3 adverse childhood experiences) for identifying older adults at an increased risk of cognitive decline in clinical and community setting.\u003c/li\u003e"},{"header":"1. Introduction","content":"\u003cp\u003eAs population is aging worldwide, health problems are increasingly prevalent among older adults. Cognitive impairment represents a major contributor to disability and rising medical costs among older adults. There were currently more than 50\u0026nbsp;million patients with cognitive impairment in worldwide [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. In China, the number of people with dementia has reached 15.07\u0026nbsp;million in 2020 [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e], and by 2030, the social and economic costs of dementia is expected to reach 114.2\u0026nbsp;billion US dollars [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. These trends underscore the critical need for early and intervene in high-risk groups for cognitive impairment.\u003c/p\u003e \u003cp\u003eStudies have showed that motoric cognitive risk (MCR) has become as a reliable predictor of progressive dementia [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e], which refers to subjective memory complaint and slow walking speed that occur in the absence of mobility disorders and dementia [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Identifying and intervening the risk factors for MCR are the key to reducing the incidence of MCR. While previous research has primarily focused on contemporaneous risk factors of MCR chronic diseases [\u003cspan additionalcitationids=\"CR7\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. However, the life course theory and the cumulative inequality theory suggested that early-life hardships increased the risk of developing health problems in later life [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. This theoretical foundation has spurred growing advocacy for early-life interventions to promote healthy aging [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAdverse childhood experiences (ACEs) are predictors of poor health outcomes in later life [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], including disadvantaged socioeconomic status in childhood, childhood abuse, and childhood neglect [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Adverse childhood experiences have been widely proven to contribute to the development of general cognitive function [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e] in old age. However, prior studies overlooked ACEs\u0026rsquo; potential influence on MCR, which captured the coordinated decline of both cognitive and motor functions. Fortunately, recent evidences have indicated a potential connection between ACEs and MCR.\u003c/p\u003e \u003cp\u003eFrom a biological perspective, ACEs frequently stimulate the individual\u0026rsquo;s stress response system, delay the development of hippocampus, amygdala, prefrontal cortex and prefrontal limbic circuits, leading to reduced corresponding executive functions. Additionally, the reduction of brain/cognitive reserves and the damaging effect of apolipoprotein E on cells can all contribute to cognitive dysfunction [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Long-term stress during childhood can impair the individual\u0026rsquo;s physiological control system for responding to the environment, leading to accelerate declines in motor functions [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. From a socioeconomic perspective, individuals with ACEs are limited their access to healthcare and healthy food, leading to health disadvantages and cognitive dysfunction in old age [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Therefore, based on the above hypotheses, this study aims to explore the association between ACEs and the risk of MCR through the CHARLS data.\u003c/p\u003e"},{"header":"2. Method","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Participants\u003c/h2\u003e \u003cp\u003eWe adopted data from the China Health and Retirement Longitudinal Study (CHARLS), which employed a stratified sampling design to survey participants aged 45 and over in China, ensuring broad geographical and demographic representation. The study adopted data from the 2014 Life History Survey and the 2015 follow-up wave. The analytic sample was restricted to participants aged 60 or older. Those with dementia or disability were excluded, as well as data with missing values for ACEs, cognitive risks related to physical activity, and covariates. Finally, 4,937 samples were included. The data screening process is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Before this study began, all participants indicated informed consent. CHARLS was approved by the Biomedical Ethics Review Committee of Peking University (IRB00001052-11015).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Measure\u003c/h2\u003e \u003cdiv id=\"Sec5\" class=\"Section3\"\u003e \u003ch2\u003e2.2.1. ACEs\u003c/h2\u003e \u003cp\u003eBased on prior researches [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e], this study defined ACEs from three dimensions: disadvantaged socioeconomic status in childhood, childhood abuse, and childhood neglect. Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e showed the questions and response for the assessment of ACEs. The total score of ACEs was the sum of three domain scores. The total score ranges from 0 to 3, with higher scores suggesting greater exposure.\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\u003eThe questions and response for the assessment of ACEs.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDimensions\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eQuestionnaire items\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eDisadvantaged socioeconomic status in childhood\u003c/p\u003e \u003cp\u003e(Responses were categorized as 0\u0026thinsp;=\u0026thinsp;the total score is 0\u0026ndash;3; 1\u0026thinsp;=\u0026thinsp;the total score is 4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWhat was the highest level of education your mother received? (Responses were categorized as 0\u0026thinsp;=\u0026thinsp;Illiterates; 1\u0026thinsp;=\u0026thinsp;Non-illiterates)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWhat was the highest level of education your father received? (Responses were categorized as 0\u0026thinsp;=\u0026thinsp;Illiterates; 1\u0026thinsp;=\u0026thinsp;Non-illiterates)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBefore you were 17 years old, how was your family\u0026rsquo;s economic situation compared to that of ordinary families in your community/village? (Responses were categorized as 0\u0026thinsp;=\u0026thinsp;Much better than them and a little better than them; 1\u0026thinsp;=\u0026thinsp;a little worse than them, much worse than them)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBefore you were 17 years old, was there a period when your family couldn\u0026rsquo;t have enough to eat? (Responses were categorized as 0\u0026thinsp;=\u0026thinsp;No; 1\u0026thinsp;=\u0026thinsp;Yes)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eChildhood abuse\u003c/p\u003e \u003cp\u003e(Responses were categorized as 0\u0026thinsp;=\u0026thinsp;the total score is 0; 1\u0026thinsp;=\u0026thinsp;the total score is 1\u0026ndash;2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWhen you were a child, did you get hit by your female caregiver? (Responses were categorized as 0\u0026thinsp;=\u0026thinsp;often or sometimes; 1\u0026thinsp;=\u0026thinsp;rarely or never)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWhen you were a child, did your male caregiver hit you? (Responses were categorized as 0\u0026thinsp;=\u0026thinsp;often or sometimes; 1\u0026thinsp;=\u0026thinsp;rarely or never)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eChildhood neglect\u003c/p\u003e \u003cp\u003e(Responses were categorized as 0\u0026thinsp;=\u0026thinsp;the total score is 0; 1\u0026thinsp;=\u0026thinsp;the total score is 1\u0026ndash;2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDid your female caregivers often express their love for you when you were a child? (Responses were categorized as 0\u0026thinsp;=\u0026thinsp;often, sometimes or rarely; 1\u0026thinsp;=\u0026thinsp;never)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDid your female caregiver spend a lot of energy taking care of you when you were a child? (Responses were categorized as 0\u0026thinsp;=\u0026thinsp;a lot, some or a little; 1\u0026thinsp;=\u0026thinsp;Not at all)\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=\"Sec6\" class=\"Section3\"\u003e \u003ch2\u003e2.2.2. MCR\u003c/h2\u003e \u003cp\u003eAccording to established criteria [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e], MCR was defined as subjective memory complaint and slow walking speed that occur in the absence of mobility disorders and dementia. Subjective memory complaint was assessed by the single question, \u0026ldquo;How do you feel about your current memory?\u0026rdquo; If participants responded \u0026ldquo;Fair\u0026rdquo; or \u0026ldquo;Poor\u0026rdquo;, it indicated the presence of subjective memory complaints for participants. The participants walked at a normal speed on a 2.5m surface twice and the walking time was measured twice and averaged. Walking speed was the distance divided by the time. Slow walking speed a speed lower than the mean specific to gender and age (for \u0026lt;\u0026thinsp;75 years old and \u0026ge;\u0026thinsp;75 years old) as determined by the sample, and less than one standard deviation. The thresholds are as follows: 0.639 m/s (for \u0026lt;\u0026thinsp;75 years males) and 0.491 m/s (for \u0026ge;\u0026thinsp;75 years males), as well as 0.568 m/s (for \u0026lt;\u0026thinsp;75 years females) and 0.400 m/s (for \u0026ge;\u0026thinsp;75 years females).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section3\"\u003e \u003ch2\u003e2.2.3. Covariates\u003c/h2\u003e \u003cp\u003eCovariates included sociodemographic and health-related factors. Sociodemographic variables were gender (male/female), age, and marital status (married/cohabiting vs. single/separated/widowed). Health-related covariates included body mass index (BMI) and chronic diseases history(yes/no).\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Data analysis\u003c/h2\u003e \u003cp\u003eData were extracted from the CHARLS dataset using R and analyzed using SPSS 25.0. Categorical variables were described using frequencies and percentages [N (%)], and Continuous variables were described using mean and standard deviation (M\u0026thinsp;\u0026plusmn;\u0026thinsp;SD). Logistic regression was used to analyze the odds ratios (ORs) and 95% confidence intervals (95% CIs) of the association between ACEs and MCR.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.1. Descriptive information of sample characteristics\u003c/h2\u003e \u003cp\u003eAs shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, 14.4%, 26.8%, and 22.2% of the total population reported having experienced childhood neglect, childhood abuse, and disadvantaged socioeconomic status in childhood. 50.4%, 37.2%, 10.9%, and 1.5% of the total population reported had been exposed to at 0, 1, 2, and 3 ACEs. 87.7%, 13.4%, and 11.8% of the total population had subjective memory complaints, slow gait speed, and MCR. The majority of the participants were male (50.6%) and had spouses (82.1%). The three most prevalent chronic diseases of the participants were arthritis or rheumatism (66.8%), hypertension (68.3%), and digestive system diseases (78.8%). The BMI of the participants was 23.70\u0026thinsp;\u0026plusmn;\u0026thinsp;9.846 and their age was 68.12\u0026thinsp;\u0026plusmn;\u0026thinsp;6.227.\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\u003eDescriptive information of sample characteristics\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOptions\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFrequencies (N)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eProportions (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eChildhood neglect\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4227\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e85.6%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e710\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e14.4%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eChildhood abuse\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3612\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e73.2%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1325\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e26.8%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eDisadvantaged socioeconomic status in childhood\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3839\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e77.8%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1098\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e22.2%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eACEs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2488\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e50.4%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1839\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e37.2%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e536\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10.9%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.5%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSubjective memory complaints\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e608\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e12.3%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4329\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e87.7%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSlow gait speed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4273\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e86.6%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e664\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e13.4%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eMCR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4353\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e88.2%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e584\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e11.8%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2498\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e50.6%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2439\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e49.4%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eMarital status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHave spouses\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4053\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e82.1%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo spouses\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e884\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e17.9%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eHypertension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3371\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e68.3%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1566\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e31.7%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eDyslipidemia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4314\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e87.4%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e623\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e12.6%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eDiabetes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4537\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e91.9%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e400\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8.1%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eMalignant tumor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4890\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e99.0%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.0%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eChronic pulmonary disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4373\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e88.6%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e564\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e11.4%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eLiver disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4781\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e96.8%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e156\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.2%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eHeart disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4151\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e84.1%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e786\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15.9%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eStroke\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4837\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e98.0%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.0%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eKidney disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4629\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e93.8%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e308\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6.2%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eDigestive system disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3889\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e78.8%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1048\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e21.2%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eEmotional and mental disorder\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4893\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e99.1%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.9%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eArthritis or rheumatism\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3299\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e66.8%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1638\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e33.2%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAsthma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4694\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e95.1%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e243\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.9%\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=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.2. Association between the types of ACEs and MCR\u003c/h2\u003e \u003cp\u003eBefore controlling for covariates (gender, age, marital status, BMI, chronic disease history), the three dimensions of ACEs (disadvantaged socioeconomic status in childhood, childhood abuse, and childhood neglect) were used as independent variables, and MCR was used as the dependent variable for regression analysis. Older adults who experienced childhood abuse had about 1.4 times the risk of being diagnosed with MCR compared to those who did not (model 1: OR\u0026thinsp;=\u0026thinsp;1.414, 95% CI: 1.128\u0026ndash;1.772), even after adjusting for covariates (model2: OR\u0026thinsp;=\u0026thinsp;1.382, 95% CI: 1.099\u0026ndash;1.738). Disadvantaged socioeconomic status in childhood and childhood abuse were not associated with MCR. Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e showed the above results.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eRelationship between the types of ACEs and MCR\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eACEs\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eModel 1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eModel 2\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOR (95%CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eOR (95%CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDisadvantaged socioeconomic status in childhood\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.129(0.922\u0026ndash;1.383)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.239\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.151(0.885\u0026ndash;1.338)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.424\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChildhood abuse\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.126(0.930\u0026ndash;1.363)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.223\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.143(0.940\u0026ndash;1.391)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.181\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChildhood neglect\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.414(1.128\u0026ndash;1.772)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.382(1.099\u0026ndash;1.738)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003cem\u003eNote\u003c/em\u003e: Model2 has been adjusted for the covariates (gender, age, marital status, BMI, chronic disease history).\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.3. The association between the exposure intensity of ACEs and MCR\u003c/h2\u003e \u003cp\u003eBefore adjusting for covariates (gender, age, marital status, BMI, chronic disease history), with the total score of ACEs as a continuous variable, for every additional ACEs, the probability of older adults being diagnosed with MCR increased by 17.8% (model1: OR\u0026thinsp;=\u0026thinsp;1.178, 95% CI: 1.052\u0026ndash;1.320), even after adjusting for covariates (model2: OR\u0026thinsp;=\u0026thinsp;1.165, 95% CI: 1.038\u0026ndash;1.307). Compared with those who had not experienced ACEs, the risk of older adults being diagnosed with MCR who had experienced three ACEs increased (model1: OR\u0026thinsp;=\u0026thinsp;2.097, 95% CI: 1.173\u0026ndash;3.748), and this was still the case even after adjusting for the covariates (model2: OR\u0026thinsp;=\u0026thinsp;2.050, 95% CI: 1.136\u0026ndash;3.699). Detailed results were shown in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAssociation between the exposure intensity of ACEs and MCR\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eACEs\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eModel 1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eModel 2\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOR (95%CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eOR (95%CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eACEs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.178(1.052\u0026ndash;1.320)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.165(1.038\u0026ndash;1.307)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.010\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.162(0.963\u0026ndash;1.402)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.118\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.151(0.951\u0026ndash;1.393)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.150\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.301(0.986\u0026ndash;1.716)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.063\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.264(0.952\u0026ndash;1.677)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.105\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.097(1.173\u0026ndash;3.748)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.050(1.136\u0026ndash;3.699)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.017\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003cem\u003eNote\u003c/em\u003e: Model2 was adjusted for the covariates (gender, age, marital status, BMI, chronic disease history).\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThis study confirmed the relationship between ACEs and MCR in a national sample of Chinese older adults. The results support the study hypothesis, indicating that childhood neglect and a higher cumulative burden of ACEs are associated with increased MCR risk. These findings emphasized the potential value of screening for adversity at an early stage and the importance of improving socioeconomic conditions throughout life to mitigate its long-term health consequences.\u003c/p\u003e \u003cp\u003eThe results showed that childhood neglect was linked to MCR. Previous studies have indicated that individuals who experienced childhood neglect had a reduced ability to effectively utilize cognitive resources [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. According to the cumulative disadvantage theory [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e], the disadvantages that individuals encounter in early life can continue to accumulate as they progress through life. Based on this, it can be speculated that cognitive impairments during childhood accumulate over time and affect cognitive functions in old age. Therefore, policies and social services should strengthen support for families at risk of childhood neglect, establish early identification and intervention mechanisms, such as conducting regular screenings through schools, communities, and medical institutions, and providing educational publicity, psychological assistance, and child development resources for families with neglect behaviors, These measures may be reduce the potential harm of childhood neglect at its source.\u003c/p\u003e \u003cp\u003eIn contrast, disadvantaged socioeconomic status in childhood and childhood abuse were not related to the occurrence of MCR in this study. Three possible reasons may account for these results. First, the research indicates that the negative impact of childhood socioeconomic disadvantage on health may be buffered by a good living standard and medical care in old age. The adverse circumstances of childhood do not have to be irreversible [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Individuals can obtain resources and opportunities through a higher social economic status in adulthood to reduce the negative effects of the early adverse situations [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. This suggests that improving the social economic conditions in adulthood may effectively alleviate ACEs\u0026rsquo; negative effects. Therefore, public policies should strive to create more fair opportunities for social mobility, strengthen lifelong education, vocational training, and the construction of social security systems, helping individuals to compensate for the early disadvantages. Second, the retrospective self-reporting assessment of ACEs may have recall bias and social expectation deviation. Moreover, influenced by the traditional concept of \u0026ldquo;beating produces filial piety\u0026rdquo;, older adults do not consider parental beating as physical abuse [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. These reasons may weaken the influence of ACEs on MCR. Therefore, future research should adopt objective, multi-source and cultural adapted measurement tools for ACEs. Third, the results may be an illusion caused by the selective mortality [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Those frail individuals with sever ACEs may have died before entering old age, while those who survived were physically strong older adults, which may weaken the negative impact of ACEs on MCR. This also reinforces the necessity of conducting health promotion and intervention throughout the entire life stage.\u003c/p\u003e \u003cp\u003eThis study also revealed the dose-response relationship between the intensity of ACE exposure and the risk of MCR. Individuals with three or more ACEs had a significantly higher risk than those without such experiences, which supports the use of a cumulative risk model for ACEs screening. In practical applications, individuals with high ACEs scores (e.g., \u0026ge;\u0026thinsp;3) can be prioritized for early assessment and intervention in community and clinical settings.\u003c/p\u003e \u003cp\u003e \u003cb\u003eLimitations\u003c/b\u003e \u003c/p\u003e \u003cp\u003eAlthough this study has significant findings, some limitations still need to be considered. Firstly, the retrospective assessment of ACEs is prone to be influenced by recall bias and social expectation bias, which may reduce the accuracy of exposure measurement and introduce selection bias. Future research would be more beneficial if it could incorporate objective records or historical data. Second, the cross-sectional design precludes causal inference. Prospective life-course studies tracking individuals from childhood are needed to clarify these associations. Finally, while key covariates were adjusted for, residual confounding by unmeasured factors remains possible.\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eThis study indicates that childhood neglect and exposure to three or more types of ACEs increase the risk of developing MCR in old age. These findings demonstrate that early screening for ACEs and creating a favorable socioeconomic environment throughout one\u0026rsquo;s life could be effective strategies for promoting cognitive and motor health in older adults.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMCR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eMotoric cognitive risk\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eACEs\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAdverse childhood experiences\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eORs\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eOdds ratios\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e95% CIs\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003e95% confidence intervals\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNone.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the General Project of Nanjing Medical University Science and Technology Development Fund in 2024 [grant number NMUB20240216].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors and Affiliations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCardiothoracic Surgery Department, Nanjing Medical University Affiliated Brain Hospital, Nanjing, Jiangsu\u0026nbsp;210029, China\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eYan Wu\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCardiothoracic Surgery Department, Nanjing Medical University Affiliated Brain Hospital, Nanjing, Jiangsu 210029, China\u003c/p\u003e\n\u003cp\u003eYang Yang\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eContributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eYan Wu: conceptualization, data curation, methodology, formal analysis, visualization, writing, reviewing and editing.\u003c/p\u003e\n\u003cp\u003eYang Yang: conceptualization, data curation, methodology, supervision, writing, reviewing, and editing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCorresponding author\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCorrespondence to Yang Yang\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical considerations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was conducted in accordance with the principles of the Helsinki Declaration and approved by the Biomedical Ethics Review Committee of Peking University (IRB00001052-11015).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompete interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no compete of interest.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eCollaborators GDF. 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Biol Psychiatry. 2007;62(5):391\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMatsuyama Y, Fujiwara T, Aida J, Watt RG, Kondo N, Yamamoto T, Kondo K, Osaka K. Experience of childhood abuse and later number of remaining teeth in older Japanese: a life-course study from Japan Gerontological Evaluation Study project. Community Dent Oral Epidemiol. 2016;44(6):531\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang T, Kan L, Jin C, Shi W. Adverse childhood experiences and their impacts on subsequent depression and cognitive impairment in Chinese adults: A nationwide multi-center study. J Affect Disord. 2023;323:884\u0026ndash;92.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZheng X, Fang Z, Shangguan S, Fang X. Associations between childhood maltreatment and educational, health and economic outcomes among middle-aged Chinese: the moderating role of relative poverty. Child Abuse Negl. 2022;130(Pt 4):105162.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang Q. Association of childhood intrafamilial aggression and childhood peer bullying with adult depressive symptoms in China. JAMA Netw Open. 2020;3(8):e2012557.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang L, Ma J, Ma L, Pei H, He S, Li H. Association between activities of daily living and motoric cognitive risk syndrome in Chinese older adults: the mediating effect of depression. J Alzheimers Dis. 2025;108(3):1257\u0026ndash;67.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eXu Z, Jia S, Huang N, Ma Y, Qin D, Dong B. Association between balance impairment and incidence of motoric cognitive risk syndrome in the China Health and Retirement Longitudinal Study. J Nutr Health Aging. 2025;29(3):100476.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMennen FE, Kim K, Sang J, Trickett PK. Child neglect: definition and identification of youth's experiences in official reports of maltreatment. Child Abuse Negl. 2010;34(9):647\u0026ndash;58.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDannefer D. Cumulative advantage/disadvantage and the life course: cross-fertilizing age and social science theory. J Gerontol B Psychol Sci Soc Sci. 2003;58(6):S327\u0026ndash;37.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTan TX, Wang Y, Ruggerio AD. Childhood adversity and children\u0026rsquo;s academic functioning: Roles of parenting stress and neighborhood support. J Child Fam Stud. 2017;26(10):2742\u0026ndash;52.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBukodi E. Cumulative inequalities over the life-course: Life-long learning and social mobility in Britain. J Soc Policy. 2017;46(2):367\u0026ndash;404.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLyu Y, Chow JC-C, Hwang J-J. Exploring public attitudes of child abuse in mainland China: a sentiment analysis of China\u0026rsquo;s social media weibo. Child Youth Serv Rev. 2020;116:105250.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRan Q, Yang F, Su Q, Li P, Hu Y. Associations between modifiable risk factors and cognitive function in middle-aged and older Chinese adults: joint modelling of longitudinal and survival data. Front Public Health. 2024;12:1485556.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"archives-of-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"aoph","sideBox":"Learn more about [Archives of Public Health](http://archpublichealth.biomedcentral.com/)","snPcode":"13690","submissionUrl":"https://submission.nature.com/new-submission/13690/3","title":"Archives of Public Health","twitterHandle":"@Archpubhealth","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Chinese older adults, Adverse childhood experiences, Motoric cognitive risk","lastPublishedDoi":"10.21203/rs.3.rs-9217244/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9217244/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eWith the rapid advancement of aging, cognitive impairment has become an important factor contributing to the increase in medical costs for older adults. Motor Cognitive Risk (MCR) is a pre-dementia syndrome. Early identification and intervention of MCR\u0026rsquo;s risk factors may reduce the incidence of dementia. However, previous studies mainly focused on the contemporaneous risk factors of MCR and paid less attention to the long-term impact of adverse childhood experiences (ACEs) on health outcomes in later life. Thus, this study assesses the relationship between adverse childhood experiences (ACEs) and motoric cognitive risk (MCR) among Chinese older adults.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eWe adopted data from the 2014 Life History Survey and the 2015 follow-up wave of the China Health and Retirement Longitudinal Study (CHARLS). The study excluded participants who were under the age of 60 and had dementia and mobility impairments. ACEs were evaluated by three dimensions and 8 items. MCR was assessed by two single-item questions. Logistic regression was used to estimate the relationship between ACEs and MCR.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe final sample included 4,937 older adults. After adjusting for covariates, childhood neglect was related with increased risk of MCR (OR\u0026thinsp;=\u0026thinsp;1.382, 95% CI: 1.099\u0026ndash;1.738). Each additional ACEs were linked to a 16.5% increased risk of MCR (OR\u0026thinsp;=\u0026thinsp;1.165, 95% CI: 1.038\u0026ndash;1.307). In addition, participants who reported three or more ACEs showed higher risk of MCR than those with no ACEs (OR\u0026thinsp;=\u0026thinsp;2.050, 95% CI: 1.136\u0026ndash;3.699).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThese findings suggest that childhood neglect and exposure to multiple ACEs increased the risk of MCR in old age. The results highlight the long-term effects of early adversity on cognitive and motor health of older adults, which underscore the important of early ACEs screening and interventions across the lifespan.\u003c/p\u003e","manuscriptTitle":"Relationship between adverse childhood experiences and motoric cognitive risk in Chinese older adults: A nationwide study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-05-12 14:25:44","doi":"10.21203/rs.3.rs-9217244/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"92493815882309139920135313719664945737","date":"2026-05-11T18:27:56+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-05-04T06:30:42+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-04-13T07:05:04+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-04-10T14:59:28+00:00","index":"","fulltext":""},{"type":"submitted","content":"Archives of Public Health","date":"2026-04-09T02:27:33+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"archives-of-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"aoph","sideBox":"Learn more about [Archives of Public Health](http://archpublichealth.biomedcentral.com/)","snPcode":"13690","submissionUrl":"https://submission.nature.com/new-submission/13690/3","title":"Archives of Public Health","twitterHandle":"@Archpubhealth","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"74dae79e-bd88-4d9c-af30-1ba99f6706fd","owner":[],"postedDate":"May 12th, 2026","published":true,"recentEditorialEvents":[{"type":"reviewerAgreed","content":"92493815882309139920135313719664945737","date":"2026-05-11T18:27:56+00:00","index":57,"fulltext":""},{"type":"reviewersInvited","content":"32","date":"2026-05-04T06:30:42+00:00","index":"","fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-12T14:25:44+00:00","versionOfRecord":[],"versionCreatedAt":"2026-05-12 14:25:44","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9217244","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9217244","identity":"rs-9217244","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}