Association between cardiovascular health metrics and retinal ageing
Related Experiment Video
Updated: Aug 6, 2025

Using Retinal Imaging to Study Dementia
Published on: November 6, 2017
Ruiye Chen1,2,3, Jinyi Xu4, Xianwen Shang1,2,3
1Department of Ophthalmology, Guangdong Academy of Medical Sciences, Guangdong Provincial People's Hospital, Guangzhou, China.
Insights
Maintaining good cardiovascular health (CVH) slows retinal aging. Ideal CVH metrics, including healthy smoking status, body mass index (BMI), blood pressure (BP), and blood glucose, are crucial for reducing retinal age gap and biological aging.
Area of Science:
- Ophthalmology and Cardiovascular Science
Background:
- Cardiovascular health (CVH) is a significant determinant of overall health and aging.
- Retinal age gap, a measure of biological aging derived from fundus images, may reflect systemic aging processes.
Purpose of the Study:
- To investigate the association between cardiovascular health (CVH) metrics and retinal aging, specifically the retinal age gap.
- To determine if maintaining ideal CVH can slow biological aging as indicated by retinal age.
Main Methods:
- Utilized data from 26,354 UK Biobank participants with CVH metrics and retinal imaging.
- Assessed CVH using 7 metrics: smoking, physical activity, diet, BMI, cholesterol, BP, and blood glucose, summarized into overall scores (poor, intermediate, ideal).
- Calculated retinal age gap and used logistic regression to analyze associations between CVH and retinal aging.
Main Results:
- A higher overall CVH score was significantly associated with a lower retinal age gap (OR=0.89).
- Ideal CVH was linked to a substantially lower retinal age gap compared to poor CVH (OR=0.58).
- Specific CVH metrics like smoking, BMI, BP, and blood glucose showed significant associations with increased retinal age gap.
Conclusions:
- There is a significant inverse dose-response relationship between CVH metrics and retinal age gap.
- Maintaining optimal cardiovascular health, particularly controlling smoking, BMI, BP, and blood glucose, is vital for decelerating biological aging.
Abstract:
The study aims to investigate associations between cardiovascular health (CVH) metrics and retinal ageing indexed by retinal age gap. A total of 26,354 participants from the UK Biobank study with available CVH metrics and qualified retinal imaging were included in the present analysis. CVH included 7 metrics (smoking, physical activity, diet, body mass index [BMI], total cholesterol, blood pressure [BP], blood glucose). These were summarized to classify the overall CVH as poor (0-7), intermediate (8-10) or ideal (11-14). Retinal age gap was defined as the difference between biological age predicted by fundus images and chronological age. Accelerated and non-accelerated retinal ageing was defined if retinal age gap was in the upper or lower 50% quantiles of the study population, respectively. Linear and logistic regression models estimated the association of overall CVH and each metric of CVH with retinal age gap respectively. Our results showed that in the fully adjusted model, each one-unit score increase in overall CVH was negatively associated with retinal age gap (odds ratio [OR] = 0.89, 95% confidence interval [CI]: 0.87-0.92, P < 0.001). Compared with poor overall CVH, people with intermediate and ideal overall CVH had significantly lower retinal age gap (OR = 0.76, 95%CI: 0.67-0.85, P < 0.001; OR = 0.58, 95%CI: 0.50-0.67, P < 0.001). Similar associations were found between overall CVH and accelerated retinal ageing. CVH metrics including smoking, BMI, BP, and blood glucose were also significantly associated with higher retinal age gap. Taken together, we found a significant and inverse dose-response association between CVH metrics and retinal age gap, indicating that maintaining healthy metrics especially smoking, BMI, BP, and blood glucose may be crucial to slow down biological ageing.
More Related Videos
10:11Fundus Photography as a Convenient Tool to Study Microvascular Responses to Cardiovascular Disease Risk Factors in Epidemiological Studies
Published on: October 22, 2014
07:18Evaluation of Capillary and Other Vessel Contribution to Macular Perfusion Density Measured with Optical Coherence Tomography Angiography
Published on: February 18, 2022