Study suggests a U-shaped link between cholesterol levels and mortality among Chinese adults

A new commentary published in Engineering highlights key findings from a large multinational cohort study that re-evaluates cholesterol management for cardiovascular and chronic disease prevention, suggesting a U-shaped association between cholesterol levels and mortality among Chinese adults that challenges the conventional "lower is better" approach. Clinical guidelines have long prioritized lowering low‑density lipoprotein cholesterol (LDL-C) as a cornerstone of atherosclerotic cardiovascular disease (CVD) primary prevention, yet emerging evidence has linked very low LDL-C to higher cancer risk and suggested a U-shaped pattern between LDL-C and all-cause mortality, with inconsistencies often confounded by lipid-lowering medications and comorbidities.

The commentary, authored by Jianxin Li and Xiangfeng Lu from Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, summarizes a large prospective longitudinal study by Jiang et al. that analyzed 163 115 Chinese adults and 317 305 UK adults with a median follow‑up of nearly ten years, focusing on untreated baseline cholesterol and longitudinal changes relative to all‑cause and cause‑specific mortality. By enrolling participants free of severe chronic diseases and lipid‑lowering treatments to reduce reverse causation and confounding, the study uncovered U‑shaped associations for total cholesterol (TC), LDL-C, and non‑high-density lipoprotein cholesterol (HDL-C) with mortality in the Chinese population. Higher cholesterol was tied to greater coronary heart disease mortality, while lower cholesterol correlated with increased all‑cause and cancer mortality, especially for gastrointestinal and urological cancers. Very low levels, specifically LDL‑C below 70 mg·dL¹ and TC below 120 mg·dL¹, were linked to higher hemorrhagic stroke risk independent of nutrition or obesity.

The study defined optimal cholesterol thresholds for Chinese adults at 200 mg·dL¹ for TC, 130 mg·dL¹ for LDL-C, and 155 mg·dL¹ for non-HDL-C, values aligned with guideline borderline‑high cutoffs. Marked ethnic differences emerged: UK adults showed higher optimal thresholds at 250 mg·dL¹ for TC, 175 mg·dL¹ for LDL-C, and 200 mg·dL¹ for non-HDL-C, corresponding to guideline high cholesterol levels. Unlike the U-shaped curve in Chinese participants, the UK population displayed L-shaped dose–response curves, with elevated cholesterol not associated with higher mortality risk, likely due to higher baseline lipid levels, better management, overall healthier status, and genetic heterogeneity.

Longitudinal cholesterol changes also carried prognostic value. Chinese adults with persistently low TC, LDL-C, or non-HDL-C, or those with declining levels from low or medium baselines, faced higher all-cause mortality than those with stable medium levels, a pattern not seen in the UK group, possibly due to sample limitations. These declines may signal underlying health decline such as aging, malnutrition, or frailty, supporting close monitoring for individuals with unexplained low or falling cholesterol not on lipid-lowering therapy.

The commentary notes the study's strengths, including diverse ethnic cohorts of nearly 500 000 people, long follow-up, untreated participants, repeated measurements, and comprehensive cholesterol–mortality analyses. Limitations include unclear sex-specific mortality effects and limited data on genetic risk stratum heterogeneity. The findings support tailored, population-specific cholesterol strategies that balance cardiovascular benefits and cancer or mortality risks, moving beyond one-size-fit-all low targets to precision management based on optimal population thresholds.

Source:
Journal reference:

Li, J., & Lu, X. (2025). Optimizing Cholesterol Management Strategies Based on Cholesterol–Mortality Associations. Engineering. DOI: 10.1016/j.eng.2025.10.004. https://www.sciencedirect.com/science/article/pii/S2095809925005983?via%3Dihub

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