{"id":22957,"date":"2026-09-21T16:34:23","date_gmt":"2026-09-21T08:34:23","guid":{"rendered":"https:\/\/health.nugene.com.cn\/?p=22957"},"modified":"2026-09-23T13:27:08","modified_gmt":"2026-09-23T05:27:08","slug":"bad-eating-habits-stack-xiangya-prospective-cohort","status":"publish","type":"post","link":"https:\/\/health.nugene.com.cn\/index.php\/bad-eating-habits-stack-xiangya-prospective-cohort\/","title":{"rendered":"Bad Eating Habits Stack: Xiangya Prospective Cohort"},"content":{"rendered":"\n<p class=\"wp-block-paragraph\">Nutrition epidemiology often asks <em>what<\/em> people eat. A large Chinese cohort asks a complementary question: does the <strong>accumulation of how people eat<\/strong> predict mortality?<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Researchers at The Third Xiangya Hospital reported in <em>American Journal of Preventive Cardiology<\/em> (2025) on <strong>57,737<\/strong> adults from domestic health examinations. They built a weighted composite of <strong>23 dietary habits<\/strong> and tested dose\u2013response links with all-cause, cardiovascular, cancer, and other-cause mortality (median follow-up <strong>2.14 years<\/strong>; <strong>1,692<\/strong> deaths).<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Habit domains (highest weights first)<\/strong> \u2192 <strong>Special behaviors:<\/strong> meal skipping, late-night eating, binge eating, business dining, fast food, snacks, coffee, sugar-sweetened beverages \u2192 <strong>Taste preferences:<\/strong> high salt, spicy preference, pickled foods, fried foods, very hot foods \u2192 <strong>Diet structure gaps:<\/strong> low whole grains, eggs, soy, fruits\/vegetables, fish\/seafood \u2192 <strong>High-fat animal foods:<\/strong> high livestock\/poultry meat, fatty meat, organ meats<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>What the data show<\/strong> After multivariable adjustment, risk rose stepwise with worse habit scores. Highest vs lowest quartile: all-cause mortality <strong>AHR 1.72<\/strong>; CVD <strong>1.82<\/strong>; cancer <strong>1.59<\/strong>; other causes <strong>2.00<\/strong>. <strong>Special dietary behaviors<\/strong> contributed the largest share of risk weight.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Subgroups worth attention<\/strong> \u2192 <strong>Age:<\/strong> little association under 40; strongest effects in <strong>midlife (~40\u201360)<\/strong>; attenuation in older adults\u2014suggesting a high-yield prevention window. \u2192 <strong>BMI:<\/strong> relative harm from poor habits was <strong>stronger in non-obese \/ non\u2013centrally obese<\/strong> adults\u2014normal weight is not a free pass. Absolute metabolic risk remains high in obesity; relative \u201cextra\u201d signal from habits can be partly masked.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Caveats<\/strong> Observational design\u2014association, not proven causation. Habits assessed once at baseline; behaviors change. Urban check-up population and relatively short follow-up limit nationwide generalization.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Takeaway<\/strong> Public health and workplace wellness shouldn\u2019t stop at nutrient lists. Habit clusters stack; removing even one high-weight behavior may matter. Midlife adults and normal-BMI adults still need behavioral dietary hygiene\u2014not only food-group swaps.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Educational summary of published science only\u2014not individualized dietary advice.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">#DietaryHabits #PreventiveCardiology #PublicHealth #CardiometabolicHealth #NutritionScience #Epidemiology #LifestyleMedicine #WorkplaceWellness #NugenePharma<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Nutrition epidemiology often asks what people eat. A large Chinese cohort asks a complementary question: does the accumulation of how people eat predict mortality? Researchers at The Third Xiangya Hospital reported in American Journal of Preventive Cardiology (2025) on 57,737 adults from domestic health examinations. They built a weighted composite of 23 dietary habits and [&hellip;]<\/p>\n","protected":false},"author":16,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_uag_custom_page_level_css":"","site-sidebar-layout":"default","site-content-layout":"","ast-site-content-layout":"default","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","theme-transparent-header-meta":"","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"set","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"ast-content-background-meta":{"desktop":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"footnotes":""},"categories":[1],"tags":[],"class_list":["post-22957","post","type-post","status-publish","format-standard","hentry","category-uncategorized"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v28.2 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Bad Eating Habits Stack: Xiangya Prospective Cohort - NuGene Pharma for Health<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/health.nugene.com.cn\/index.php\/bad-eating-habits-stack-xiangya-prospective-cohort\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Bad Eating Habits Stack: Xiangya Prospective Cohort - NuGene Pharma for Health\" \/>\n<meta property=\"og:description\" content=\"Nutrition epidemiology often asks what people eat. 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