Healthy nutrient-rich dietary patterns and mortality in older Chinese: a 16-year follow-up of Guangzhou Biobank Cohort Study
Year: 2026
Type: article
Study design: Observational Study
Abstract: Using different techniques to derive dietary patterns (DP) could evaluate real-world diet behaviours and provide DP recommendations. Therefore, we identified DP using hybrid methodologies and examined the associations of DP with all-cause and CVD mortality among older Chinese. Using data from the Guangzhou Biobank Cohort Study, dietary intake was assessed using a validated FFQ. DP were derived using hybrid methods including reduced rank regression (RRR) and partial least squares (PLS), focusing on nutrients commonly insufficient in Asian diets. Associations of the DP with mortality and CVD risk factors were examined using Cox regression and generalised linear models, respectively. Of 19 598 participants with an average follow-up of 15·8 years, 4966 deaths occurred. Two DP were derived based on the riboflavin-density, K:Na ratio and vitamin C-density. The DP derived from both RRR and PLS featured high intakes of green vegetables, yellow/orange fruits and whole grains and low intakes of refined grains and plant oils, with additional high intakes of fish identified by RRR and milk by PLS. These DP were associated with lower all-cause and CVD mortality risks. Compared with the lowest quartile, the highest quartiles showed lower risks of all-cause (hazard ratio (HR): 0·89–0·91, all P < 0·01) and CVD mortality (HR: 0·79–0·82, all P < 0·01). Moreover, both DP were associated with favourable cardiometabolic profiles, including lower systolic blood pressure, TAG and high-sensitivity C-reactive protein levels, and higher HDL-cholesterol levels. These findings suggest that nutrient-rich DP using hybrid methods may support the development of dietary recommendations to reduce mortality among older Chinese.
Source: British Journal Of Nutrition
Language: English
Topic: Nutritional Studies and Diet
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
Estimated APC paid: $3,550
Awards: G2818395600, G2968694728, G4598296790
OpenAlex ID: W7140896203
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