Association of biological age with health outcomes and its modifiable factors

Liu, Wei‐Shi; You, Jia; Ge, Yi‐Jun; Wu, Bang‐Sheng; Zhang, Yi; Chen, Shi‐Dong; Zhang, Ya‐Ru; Huang, Shu‐Yi; Ma, Ling‐Zhi; Feng, Jian‐Feng; Cheng, Wei; Yu, Jin‐Tai

doi:10.1111/acel.13995

Cited by 3 publications

(1 citation statement)

References 101 publications

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“…Any psychiatric disorder (F00-F99) was coded using the International Classification of Disease, 10th version (ICD-10) [ 34 ]. Considering the higher prevalence rate in the general population, this study also examined certain specific psychiatric disorders, including dementia (F00-F03), substance abuse (F10-F19), psychotic disorder (F20-F29), depression (F32-F33), and anxiety (F40-F41) [ 1 , 34 , 35 ]. More details about the outcomes are provided in Additional file 1 : Table S1.…”

Section: Methodsmentioning

confidence: 99%

Exposure to residential green and blue space and the natural environment is associated with a lower incidence of psychiatric disorders in middle-aged and older adults: findings from the UK Biobank

Liu,

Huxley,

Schikowski

et al. 2024

BMC Med

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Background There is increasing evidence for the role of environmental factors and exposure to the natural environment on a wide range of health outcomes. Whether exposure to green space, blue space, and the natural environment (GBN) is associated with risk of psychiatric disorders in middle-aged and older adults has not been prospectively examined. Methods Longitudinal data from the UK biobank was used. At the study baseline (2006–2010), 363,047 participants (women: 53.4%; mean age 56.7 ± 8.1 years) who had not been previously diagnosed with any psychiatric disorder were included. Follow-up was achieved by collecting records from hospitals and death registers. Measurements of green and blue space modeled from land use data and natural environment from Land Cover Map were assigned to the residential address for each participant. Cox proportional hazard models with adjustment for potential confounders were used to explore the longitudinal associations between GBN and any psychiatric disorder and then by specific psychiatric disorders (dementia, substance abuse, psychotic disorder, depression, and anxiety) in middle-aged and older adults. Results During an average follow-up of 11.5 ± 2.8 years, 49,865 individuals were diagnosed with psychiatric disorders. Compared with the first tertile (lowest) of exposure, blue space at 300 m buffer [hazard ratio (HR): 0.973, 95% confidence interval (CI): 0.952–0.994] and natural environment at 300 m buffer (HR: 0.970, 95% CI: 0.948–0.992) and at 1000 m buffer (HR: 0.975, 95% CI: 0.952–0.999) in the third tertile (highest) were significantly associated with lower risk of incident psychiatric disorders, respectively. The risk of incident dementia was statistically decreased when exposed to the third tertile (highest) of green space and natural environment at 1000 m buffer. The third tertile (highest) of green space at 300 m and 1000 m buffer and natural environment at 300 m and 1000 m buffer was associated with a reduction of 30.0%, 31.8%, 21.7%, and 30.3% in the risk of developing a psychotic disorder, respectively. Subgroup analysis suggested that the elderly, men, and those living with some comorbid conditions may derive greater benefits associated with exposure to GBN. Conclusions This study suggests that GBN has significant benefits for lowering the risk of psychiatric disorders in middle-aged and older adults. Future studies are warranted to validate these findings and to understand the potential mechanistic pathways underpinning these novel findings.

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Section: Methodsmentioning

confidence: 99%

Exposure to residential green and blue space and the natural environment is associated with a lower incidence of psychiatric disorders in middle-aged and older adults: findings from the UK Biobank

Liu,

Huxley,

Schikowski

et al. 2024

BMC Med

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The role of quality of life data as an endpoint for collecting real-world evidence within geroscience clinical trials

Harinath,

Zalzala,

Nyquist

et al. 2024

Ageing Research Reviews

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Heterogeneous metabolomic aging across the same age and prediction of health outcome

Jia,

Fan,

et al. 2024

Preprint

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Existing metabolomic clocks exhibit deficiencies in capturing the heterogeneous aging rates among individuals with the same chronological age. Yet, the modifiable and non-modifiable factors in metabolomic aging have not been systematically studied. Here, we leveraged metabolomic profiles of 239,291 UK Biobank participants for 10-year all-cause mortality prediction to generate and validate a new aging measure--MetaboAgeMort. The MetaboAgeMort showed significant associations with all-cause mortality, cause-specific mortality, and diverse incident diseases. Adding MetaboAgeMort to conventional risk factors model improved the predictive ability of 10-year mortality. We identified 99 modifiable factors for MetaboAgeMort, where 16 factors representing pulmonary function, body composition, socioeconomic status, dietary quality, smoking status, alcohol intake, and disease status showed quantitatively stronger associations. The genetic analyses revealed 99 genomic risk loci and 271 genes associated with MetaboAgeMort. Our study illuminates heterogeneous metabolomic aging across the same age, which provides avenues for developing anti-aging therapies and personalized interventions.

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Association of biological age with health outcomes and its modifiable factors

Cited by 3 publications

References 101 publications

Exposure to residential green and blue space and the natural environment is associated with a lower incidence of psychiatric disorders in middle-aged and older adults: findings from the UK Biobank

Exposure to residential green and blue space and the natural environment is associated with a lower incidence of psychiatric disorders in middle-aged and older adults: findings from the UK Biobank

The role of quality of life data as an endpoint for collecting real-world evidence within geroscience clinical trials

Heterogeneous metabolomic aging across the same age and prediction of health outcome

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