Evidence map›Paper›PMID 40048877›Full record

ArticleThe journal of nutrition, health & aging2025

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

Yu Huang, Shuo Wang, Le Tian, Xueli Zhang, Shunming Liu, Zhuoting Zhu, Wei Wang, Danli Shi, Mingguang He, Xianwen Shang

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in The journal of nutrition, health & aging, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Yu HuangGuangdong 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.
Shuo WangDepartment of Mathematics, National University of Singapore, 119076, Singapore.
Le TianComprehensive Department, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China.
Xueli ZhangGuangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, 510080, China; Medical Research Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, 510080, China.
Shunming LiuGuangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, 510080, China.
Zhuoting ZhuGuangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, 510080, China; Centre for Eye Research Australia, Royal Victorian Eye and Ear Hospital, Melbourne, VIC 3002, Australia.
Wei WangState Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, 510060, China.
Danli ShiSchool 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.
Mingguang HeSchool 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: mingguang.he@polyu.edu.hk.
Xianwen ShangGuangdong 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: xianwen.shang@polyu.edu.hk.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesThis 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.

resultsBoth 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.

conclusionsHigher 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.

Indexed as

Educational StatusHealthy LifestyleAgedAlcohol DrinkingDiet, HealthyExerciseFemaleHumansMaleMiddle AgedProspective StudiesRisk FactorsSleepSmokingUnited KingdomAge-related health conditionsEducational attainmentHealthy lifestyle habitMediation analysisModeration analysisMortality

Identifiers

PMID40048877
PMCPMC12179974

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LicenceCC BY-NC-ND
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.