Association of LDL-C between parents and younger offspring: A cross-sectional study using the Korea National Health and Nutrition Examination Survey

초록

BACKGROUND: Atherosclerotic cardiovascular disease develops in adulthood, but its metabolic precursors, such as dyslipidemia, often emerge during childhood. OBJECTIVE: This study aimed to evaluate the associations of parental low-density lipoprotein cholesterol (LDL-C) levels with their offspring's LDL-C levels and dyslipidemia risk. METHODS: This study examined the intergenerational association between parental dyslipidemia (LDL-C-defined) and offspring LDL-C levels using nationally representative data from the Korea National Health and Nutrition Examination Survey (2017-2023). RESULTS: A total of 2702 first-born children aged 7 to 18 years with available parental lipid data were included. Offspring hypercholesterolemia was defined as LDL-C >= 130 mg/dL, and parental dyslipidemia as a diagnosis of dyslipidemia (ie, total cholesterol >= 240 mg/dL, LDL-C >= 160 mg/dL, or use of lipid-lowering medication). Linear regression was used to assess associations between parental and offspring LDL-C, and logistic regression to estimate odds ratios (ORs) for offspring hypercholesterolemia (high LDL-C levels) according to parental dyslipidemia (LDL-C-defined). Statistical interaction terms between maternal LDL-C and offspring biological sex or age group (7-12 vs 13-18 years) were tested. Both maternal and paternal LDL-C were significantly associated with offspring LDL-C (beta = 0.214 and 0.113, respectively; both P < .001). Offspring hypercholesterolemia (high LDL-C levels) risk increased with parental dyslipidemia (LDL-C-defined) (OR = 2.12 for father only, 4.03 for mother only, and 3.83 for both parents; all P < .01). CONCLUSION: These findings highlight maternal LDL-C as a predominant determinant of offspring lipid levels and emphasize the importance of family-based early screening and preventive strategies. (c) 2026 National Lipid Association. Published by Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies.

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