[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"detail-sidebar-cat-0-en-105":3,"doc-seo-427552-105":59,"doc-detail-427552-en":130},{"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":123,"head_meta":125,"extra_data":127,"updated_unix":129},105,"en","bathtub-curve-patterns-of-mortality-risk-in-cardiometabolic-diseases-a-cohort-study-using-the-uk-biobank","BATHTUB CURVE PATTERNS OF MORTALITY RISK IN - CARDIOMETABOLIC DISEASES: A COHORT STUDY USING THE UK BIOBANK","","Observational studies suggest nonlinear mortality patterns in cardiometabolic diseases, with acute events showing early risk spikes and chronic conditions accumulating gradually. This cohort study validates bathtub-curve theory in CMD epidemiology using UK Biobank data (n=502,130) covering 17 CMDs among 73,908 patients. A piecewise exponential survival model estimates time-dependent hazards, adjusting for age, sex, BMI, education, and lifestyle factors. Diabetes-like chronic diseases follow a bathtub-shaped risk profile, while acute conditions decline rapidly over time. The framework supports improved risk stratification and lifecycle patient management.",{"@graph":69,"@context":122},[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/bathtub-curve-patterns-of-mortality-risk-in-cardiometabolic-diseases-a-cohort-study-using-the-uk-biobank/427552/",{"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/bathtub-curve-patterns-of-mortality-risk-in-cardiometabolic-diseases-a-cohort-study-using-the-uk-biobank/427552.png","ImageObject",300,407,{"name":92,"@type":93},"Valentina","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-10-14","2026-09-29",true,{"@type":102,"interactionType":103,"userInteractionCount":24},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118],{"name":109,"@type":110,"acceptedAnswer":111},"What does the study test about mortality risk in cardiometabolic diseases?","Question",{"text":112,"@type":113},"It evaluates whether bathtub-curve theory accurately describes nonlinear mortality risk dynamics over time in cardiometabolic disease patients.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"What data and sample size were used in the UK Biobank analysis?",{"text":117,"@type":113},"The study used UK Biobank data (n=502,130), analyzing 17 CMDs among 73,908 patients with linked primary care, inpatient, and death records.",{"name":119,"@type":110,"acceptedAnswer":120},"How do chronic and acute diseases differ in their mortality risk trajectories?",{"text":121,"@type":113},"Chronic diseases such as diabetes show a bathtub-shaped pattern (elevated early, lower mid-term, rising long-term), whereas acute conditions decline rapidly over time.","https://schema.org",{"og:url":83,"og:type":124,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":126,"canonical":83},"index,follow",{"doc_id":128,"site_id":62},427552,1791311295,{"code":4,"msg":5,"data":131},{"doc_id":128,"user_id":132,"nickname":92,"user_avatar":133,"doc_module":4,"category_id":39,"category_name":40,"doc_title":65,"doc_description":67,"doc_content":134,"file_id":135,"file_url":136,"file_type":137,"file_size":138,"view_count":24,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":8,"language":139,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":140,"faqs":141,"seo_title":142,"seo_description":67,"update_tm":143,"read_time":81},13056703020460,"https://ap-avatar.wpscdn.com/avatar/be000253dac470eee5d?_k=1778207105932848923","Innovation in Aging, 2025, Vol. 9, No. S2 853  \nBeijing, China (People’s Republic), 2. Peking University, Beijing, Beijing, China (People’s Republic)  \nObservational studies suggest nonlinear mortality patterns in cardiometabolic diseases (CMDs): acute events show early risk spikes, while chronic conditions exhibit gradual risk accumulation. These trends superficially align with the bathtub curve—an engineering model describing triphasic failure rates. However, systematic validation of this framework in chronic disease epidemiology remains limited. This study aims to explore and validate the nonlinear temporal dynamics of mortality risk in CMD patients based on bathtub curve theory. Using data from the UK Biobank (n = 502,130), we analyzed 17 CMDs with linked primary care, inpatient and death records among 73,908 patients. A piecewise exponential survival model segmented mortality risk into intervals to capture time-dependent hazard rates. Chronic (e.g., diabetes) and acute diseases (e.g., myocardial infarction) were analyzed separately. Models were adjusted for age, sex, BMI, education, and smoking/alcohol status. Chronic diseases, such as diabetes, exhibited a bathtub-shaped mortality risk: elevated initially, declining in mid-term, and rising again long-term. Each phase showed increased risk with older age at diagnosis. Acute conditions (e.g., heart failure) demonstrated rapidly declining risks over time. Heterogeneity in high-risk time windows was observed across diseases, with hypertension and diabetes consistently following the bathtub curve. Using the piecewise exponential model, we validate the bathtub curve framework could provide a novel nonlinear perspective for understanding mortality risk evolution in CMDs. This approach supports stratified patient management, intensive early intervention, stable-phase monitoring, and late-phase complication control, enhancing precision in public health strategies. The findings underscore the theory’s potential in optimizing lifecycle management of CMDs and guiding personalized interventions.  \nAbstract citation ID: igaf122.2889  \nBATHTUB CURVE PATTERNS OF MORTALITY RISK IN  \nCARDIOMETABOLIC DISEASES: A COHORT STUDY  \nUSING THE UK BIOBANK  \nYuming Chen1, Shui-kit Cheuk2, Hui Liu2, Yanran Deng1, and Beibei Xu2, 1. Peking University Health Science Center, Beijing,","cbCaibaxWEAbcpoj","https://ap.wps.com/l/cbCaibaxWEAbcpoj","pdf",763001,"English","# Study objective and rationale\n## Data source and cohort design\n## Statistical modeling approach\n## Results by chronic vs acute diseases\n## Public health implications","[{\"question\":\"What does the study test about mortality risk in cardiometabolic diseases?\",\"answer\":\"It evaluates whether bathtub-curve theory accurately describes nonlinear mortality risk dynamics over time in cardiometabolic disease patients.\"},{\"question\":\"What data and sample size were used in the UK Biobank analysis?\",\"answer\":\"The study used UK Biobank data (n=502,130), analyzing 17 CMDs among 73,908 patients with linked primary care, inpatient, and death records.\"},{\"question\":\"How do chronic and acute diseases differ in their mortality risk trajectories?\",\"answer\":\"Chronic diseases such as diabetes show a bathtub-shaped pattern (elevated early, lower mid-term, rising long-term), whereas acute conditions decline rapidly over time.\"}]","BATHTUB CURVE PATTERNS OF MORTALITY RISK IN - CARDIOMETABOLIC DISEASES: A COHORT STUDY USING THE UK BIOBANK | PDF",1790644199]