Exploring age and gender disparities in cardiometabolic phenotypes and lipidomic signatures among Chinese adults: a nationwide cohort study

Abstract

Understanding sex disparities in modifiable risk factors across the lifespan is essential for crafting individualized intervention strategies. We aim to investigate age-related sex disparity in cardiometabolic phenotypes in a large nationwide Chinese cohort. A total of 254,670 adults aged 40 years or older were selected from a population-based cohort in China. Substantial sex disparities in the prevalence of metabolic diseases were observed across different age strata, particularly for dyslipidemia and its components. Generalized additive models were employed to characterize phenotype features, elucidating how gender differences evolve with advancing age. Half of the 16 phenotypes consistently exhibited no sex differences, while four (high-density lipoprotein [HDL] cholesterol, apolipoprotein A1, diastolic blood pressure, and fasting insulin) displayed significant sex differences across all age groups. Triglycerides, apolipoprotein B, non-HDL cholesterol, and total cholesterol demonstrated significant age-dependent sex disparities. Notably, premenopausal females exhibited significant age-related differences in lipid levels around the age of 40–50 years, contrasting with the relatively stable associations observed in males and postmenopausal females. Menopause played an important but not sole role in age-related sex differences in blood lipids. Sleep duration also had an age- and sex-dependent impact on lipids. Lipidomic analysis and K-means clustering further revealed that 58.6% of the 263 measured lipids varied with sex and age, with sphingomyelins, cholesteryl esters, and triacylglycerols being the most profoundly influenced lipid species by the combined effects of age, sex, and their interaction. These findings underscore the importance of age consideration when addressing gender disparities in metabolic diseases and advocate for personalized, age-specific prevention and management.

Keywords

sex difference / aging / metabolic diseases / modifiable risk factors / lipidomics

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