[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"detail-sidebar-cat-0-en-105":3,"doc-seo-427635-105":59,"doc-detail-427635-en":134},{"code":4,"msg":5,"data":6},0,"success",[7,13,18,23,28,33,38,43,48,51,55],{"id":8,"doc_module":4,"doc_module_name":9,"category_name":10,"show_sort_weight":11,"slug":12},1,"Document","Story & Novel",90,"story-novel",{"id":14,"doc_module":4,"doc_module_name":9,"category_name":15,"show_sort_weight":16,"slug":17},2,"Literature",80,"literature",{"id":19,"doc_module":4,"doc_module_name":9,"category_name":20,"show_sort_weight":21,"slug":22},4,"Exam",70,"exam",{"id":24,"doc_module":4,"doc_module_name":9,"category_name":25,"show_sort_weight":26,"slug":27},5,"Comic",60,"comic",{"id":29,"doc_module":4,"doc_module_name":9,"category_name":30,"show_sort_weight":31,"slug":32},6,"Technology",50,"technology",{"id":34,"doc_module":4,"doc_module_name":9,"category_name":35,"show_sort_weight":36,"slug":37},7,"Healthcare",40,"healthcare",{"id":39,"doc_module":4,"doc_module_name":9,"category_name":40,"show_sort_weight":41,"slug":42},8,"Research & Report",30,"research-report",{"id":44,"doc_module":4,"doc_module_name":9,"category_name":45,"show_sort_weight":46,"slug":47},9,"Religion & Spirituality",20,"religion-spirituality",{"id":46,"doc_module":4,"doc_module_name":9,"category_name":49,"show_sort_weight":46,"slug":50},"World Cup","world-cup",{"id":52,"doc_module":4,"doc_module_name":9,"category_name":53,"show_sort_weight":52,"slug":54},10,"Lifestyle","lifestyle",{"id":56,"doc_module":4,"doc_module_name":9,"category_name":57,"show_sort_weight":24,"slug":58},19,"General","general",{"code":4,"msg":60,"data":61},"ok",{"site_id":62,"language":63,"slug":64,"title":65,"keywords":66,"description":67,"schema_data":68,"social_meta":127,"head_meta":129,"extra_data":131,"updated_unix":133},105,"en","intersectional-discrimination-and-mental-health-in-later-life-ageism-as-a-core-dimension","INTERSECTIONAL DISCRIMINATION AND MENTAL HEALTH IN LATER LIFE: AGEISM AS A CORE DIMENSION","","Despite extensive literature on how discrimination shapes health, less is known about how specific discrimination attributions relate to differential mental health outcomes in later life. Using 6,282 respondents from the 2016 Health and Retirement Study, latent class analysis identified attribution typologies, followed by regression models with marginal effects. Five typologies emerged, with ageism frequently present. Discrimination—especially intersectional attributions involving explicit characteristics—showed stronger negative associations with depressive symptoms, cognitive function, and loneliness.",{"@graph":69,"@context":126},[70,84,105],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":40,"@type":76,"position":81},"https://docshare.wps.com/document/research-report/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/intersectional-discrimination-and-mental-health-in-later-life-ageism-as-a-core-dimension/427635/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/intersectional-discrimination-and-mental-health-in-later-life-ageism-as-a-core-dimension/427635.png","ImageObject",300,407,{"name":92,"@type":93},"\tJames","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-10-14","2026-09-29",true,{"@type":102,"interactionType":103,"userInteractionCount":44},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118,122],{"name":109,"@type":110,"acceptedAnswer":111},"What is the main research focus of this study?","Question",{"text":112,"@type":113},"The study examines how specific discrimination attributions, including intersectional attributions, differentially affect mental health in later life, with ageism highlighted as a core dimension.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"How were discrimination attribution patterns identified?",{"text":117,"@type":113},"Latent class analysis was used to identify discrimination attribution typologies from responses of 6,282 participants in the 2016 Psychosocial Leave-Behind Questionnaire of the Health and Retirement Study.",{"name":119,"@type":110,"acceptedAnswer":120},"Which mental health outcomes were linked to discrimination?",{"text":121,"@type":113},"Regression analysis found significant associations between discrimination and depressive symptoms, cognitive function, and loneliness.",{"name":123,"@type":110,"acceptedAnswer":124},"Why are intersectional attributions important according to the results?",{"text":125,"@type":113},"The negative mental health effects were strongest for those who experienced discrimination related to intersectional attributions, particularly when discrimination involved explicit characteristics beyond age.","https://schema.org",{"og:url":83,"og:type":128,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":130,"canonical":83},"index,follow",{"doc_id":132,"site_id":62},427635,1790701456,{"code":4,"msg":5,"data":135},{"doc_id":132,"user_id":136,"nickname":92,"user_avatar":137,"doc_module":4,"category_id":39,"category_name":40,"doc_title":65,"doc_description":67,"doc_content":138,"file_id":139,"file_url":140,"file_type":141,"file_size":142,"view_count":44,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":8,"language":143,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":144,"faqs":145,"seo_title":146,"seo_description":67,"update_tm":147,"read_time":81},2336474466412,"https://ap-avatar.wpscdn.com/davatar_155a257f0dc6eb9ab79c44ca47cae57d","Innovation in Aging, 2025, Vol. 9, No. S2 645  \ndiscrimination experiences to a list of ten potential reasons (e.g., ethnicity, ancestry, gender, race, age, religion, financial) . Latent class analysis (LCA) was performed to identify discrimination attribution typologies. Regression models with marginal effects were conducted to explore differential mental health effects of different attribution typologies. Five distinct typologies were identified: few discrimination experiences (33%), discrimination with no specified attributes (5%), discrimination due to age (48%), discrimination due to age, race, ethnicity (8%), and discrimination due to age and explicit characteristics (5%) such as physical disability and appearance. Regression analysis revealed significant associations between discrimination and depressive symptoms, cognitive function, and loneliness. Discrimination involving more than just age, especially explicit characteristics, had stronger negative effects on mental health. Ageism emerged as a core dimension and prevalent theme across multiple discrimination experiences, and often co-occurs with other characteristics, highlighting the intersectionality of discrimination. The negative mental health effects were most pronounced for those who experienced discrimination related to intersectional attributions. Implications for practice and research were discussed.  \nAbstract citation ID: igaf122.2205  \nINTERSECTIONAL DISCRIMINATION AND MENTAL  \nHEALTH IN LATER LIFE: AGEISM AS A CORE  \nDIMENSION  \nYi Wang1, Yifan Lou2Huei-wern Shen3, and Ernest Gonzales4, 1. University of Iowa School of Social Work, Iowa City, Iowa, United States, 2. Virginia Commonwealth University, Richmond, Virginia, United States, 3. University of North Texas, Denton, Texas, United States, 4. New York University, New York, New York, United States  \nDespite extensive literature that examines the relationship between discrimination and health, less is known about specific discrimination attributions and how they may differentially affect health outcomes. To address this gap, the current study investigated the latent typology of the discrimination attributions, and the effects of intersectional attributions on mental health in later life. Data came from 6,282 respondents in the 2016 Psychosocial Leave-Behind Questionnaire of the Health and Retirement Study. Participants ascribed their everyday","cbCairy7By2UIjYe","https://ap.wps.com/l/cbCairy7By2UIjYe","pdf",590546,"English","# Background and research gap\n# Data and methods\n## Latent class analysis\n## Regression models with marginal effects\n# Findings: attribution typologies\n# Mental health associations and implications","[{\"question\":\"What is the main research focus of this study?\",\"answer\":\"The study examines how specific discrimination attributions, including intersectional attributions, differentially affect mental health in later life, with ageism highlighted as a core dimension.\"},{\"question\":\"How were discrimination attribution patterns identified?\",\"answer\":\"Latent class analysis was used to identify discrimination attribution typologies from responses of 6,282 participants in the 2016 Psychosocial Leave-Behind Questionnaire of the Health and Retirement Study.\"},{\"question\":\"Which mental health outcomes were linked to discrimination?\",\"answer\":\"Regression analysis found significant associations between discrimination and depressive symptoms, cognitive function, and loneliness.\"},{\"question\":\"Why are intersectional attributions important according to the results?\",\"answer\":\"The negative mental health effects were strongest for those who experienced discrimination related to intersectional attributions, particularly when discrimination involved explicit characteristics beyond age.\"}]","INTERSECTIONAL DISCRIMINATION AND MENTAL HEALTH IN LATER LIFE: AGEISM AS A CORE DIMENSION | PDF",1790644422]