Key result
Suboptimal diet is linked to ~53% of cardiovascular disease mortality in Zhejiang Province.
Why the study?
Does suboptimal dietary intake increase the population-attributable fraction of cardiovascular disease mortality in Chinese adults?
Cross-Sectional (n=56,018)
Yes
Does suboptimal dietary intake increase the population-attributable fraction of cardiovascular disease mortality in Chinese adults?
Answers are grounded in this paper and cite their sources.
Suboptimal dietary patterns account for approximately half of the cardiovascular disease mortality burden in Zhejiang Province, and adopting healthier regional diets like the Jiangnan pattern could avert tens of thousands of CVD deaths annually in higher-burden regions.
Background/Objectives: Suboptimal diet is a major modifiable contributor to cardiovascular disease (CVD) mortality in China, and provincial disparities in dietary quality may contribute to geographic variation in CVD burden. This study aimed to quantify temporal trends in CVD mortality attributable to suboptimal dietary factors in Zhejiang Province and evaluate the potential reduction in CVD deaths in Henan Province under a counterfactual Jiangnan dietary pattern. Methods: This repeated cross-sectional study used data from multiple rounds of population-based nutrition surveillance conducted in Zhejiang Province between 2008 and 2024, with additional comparative data from Henan Province in 2015. A total of 56,018 adults were included. Dietary intake was assessed using 3-day 24-h dietary recalls combined with household condiment weighing. Ten dietary factors were evaluated, including fruits, vegetables, aquatic products, nuts, whole grains, red meat, processed meat, sugar-sweetened beverages, condiment salt, and omega-3 fatty acids. The prevalence of suboptimal dietary exposures was standardized according to the urban–rural population distribution. Population-attributable fractions (PAFs) of cardiovascular disease (CVD) mortality associated with individual and combined dietary factors were estimated using a comparative risk-assessment framework based on published relative-risk estimates. A counterfactual scenario was further used to estimate the number of CVD deaths in Henan Province that might be averted if the diet-attributable PAF were reduced to the level observed in coastal Zhejiang. Results: The dietary profile in Zhejiang was characterized by relatively lower prevalences of inadequate intake of aquatic products, whole grains, and vegetables, together with a decline in excessive salt intake. The estimated proportion of CVD mortality attributable to suboptimal dietary factors based on comparative risk assessment was 49.8% (95% UI, 40.8–57.4) in 2008, increased numerically to 55.3% (48.1–61.6) in 2022, and was 52.5% (45.6–58.6) in 2024. Among the examined subgroups, women living in coastal Zhejiang had the lowest estimated diet-attributable PAF. Zhejiang had a healthier dietary profile and a lower PAF for diet-attributable CVD mortality than Henan. Under the specified counterfactual scenario, by matching Henan’s dietary pattern to that of coastal Zhejiang, it was estimated that approximately 23,575 annual CVD deaths could be averted. Conclusions: Suboptimal dietary exposures remained responsible for a substantial and persistent proportion of CVD mortality. Although Zhejiang had a lower estimated diet-attributable CVD mortality burden than Henan, important gaps remained, particularly for low intakes of nuts, fruit, and whole grains. Refining the Jiangnan dietary pattern and adapting its favorable components to high-burden regions may inform region-specific CVD prevention.
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He et al. (2026) conducted a cross-sectional in Cardiovascular disease mortality risk (n=56,018). Suboptimal dietary patterns vs. Optimal dietary patterns (counterfactual) was evaluated on Population-attributable fraction (PAF) of cardiovascular disease mortality in 2024 (PAF 52.5%, 95% CI 45.6-58.6). Suboptimal dietary factors accounted for an estimated 52.5% (95% UI 45.6-58.6) of cardiovascular disease mortality in Zhejiang Province in 2024.
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