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Healthy lifestyle habits, educational attainment, and the risk of 45 age-related health and mortality outcomes in the UK: A prospective cohort study. | LitMetric

Healthy lifestyle habits, educational attainment, and the risk of 45 age-related health and mortality outcomes in the UK: A prospective cohort study.

J Nutr Health Aging

Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, 510080, China; Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, 510080, China; School of Optometry, The Hong Kong Polytechnic University, Kowloon, Hong Kong, China; Research Centre for SHARP Vision (RCSV), The Hong Kong Polytechnic University, Kowloon, Hong Kong, China; Centre for Eye and Vision Research (CEVR), 17W Hong Kong Science Park, Hong Kong. Electronic address:

Published: March 2025

Objectives: This study aimed to evaluate to what extent lifestyle habits, contribute to associations between EA and various conditions, and test the variability in risk reduction for specific health conditions linked to a healthy lifestyle across different EA levels.

Design, Setting, Participants, And Measurements: Data were analyzed from 341,632 UK Biobank participants without baseline cardiovascular disease or cancer (2006-2010). A healthy lifestyle score (0-5) was created by assigning one point for each of five habits: a healthy diet, sufficient physical activity, non-current smoking, moderate alcohol consumption, and low-risk sleep duration. Baseline data on self-reported and genotype-predicted EA were collected, with 45 health outcomes assessed until January 2021. Logistic regression models were used to assess the relationship between EA and lifestyle habits, and associations between the healthy lifestyle score and health/mortality outcomes were examined using Cox proportional hazards model. Moderation analysis tested whether EA modified the associations between a healthy lifestyle and health outcomes, while mediation analysis estimated the proportion of the association between EA and health outcomes explained by lifestyle habits.

Results: Both self-reported and genotype-predicted EA were associated with a healthy diet, non-current smoking, low-risk sleep duration, and moderate alcohol consumption, but not low-risk physical activity. A healthy lifestyle is inversely linked to risks for 38 of 45 outcomes, including CVD, type 2 diabetes, lung and colon cancer, depression, and chronic kidney disease, as well as overall, CVD, and cancer mortality. Higher EA reduced risk for 25 conditions, such as CVD, certain cancers, chronic liver disease, and fractures; stronger inverse lifestyle-risk associations were observed among less educated individuals. Lifestyle habits explained 47.2% (95% CI: 35.3-59.4%) of the association between genotype-predicted EA and all-cause mortality, mediating a large proportion of associations with CVDs, cancers, dementia, respiratory diseases, and chronic kidney disease.

Conclusions: Higher EA might encourage the adoption of more healthy lifestyle habits, thus promoting healthy aging. Placing greater emphasis on lifestyle modification is essential for individuals with lower EA to effectively address health inequalities associated with EA.

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Source
http://dx.doi.org/10.1016/j.jnha.2025.100525DOI Listing

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