Xiaoqi Su, Shanliang Zhu, Ye Chen, Xin Zhou, Jun Chen, Nishant Patel, Xuming Mo
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引用次数: 0
Abstract
Background: The relationship between serum vitamin C (sVC) and blood lipids in adolescents in the US has not been thoroughly studied. This study investigates the correlation between sVC and blood lipids among adolescents using data from the National Health and Nutrition Examination Survey (NHANES).
Methods: Data from the NHANES 2003-2006 and 2017-2018 cycles, encompassing 4,965 participants aged 12-19 years, were analyzed. sVC served as the independent variable and blood lipids as the dependent variables. Multiple linear regression models assessed the relationship between sVC and blood lipids, with subgroup analyses based on sex, age, and race. Additionally, smooth curve fitting and saturation threshold analysis were employed to explore nonlinear relationships.
Results: Adjusted analyses revealed a positive correlation between sVC and high-density lipoprotein cholesterol (HDL-C) (β = 2.77, 95%CI 2.06-3.47), with no significant association with total cholesterol, low-density lipoprotein cholesterol (LDL-C), or triglycerides. This positive correlation persisted across subgroups divided by age, gender, and race (p < 0.05). The nonlinear relationship between sVC and HDL-C was characterized by an inverted U-shaped curve in adolescents aged 12-15 years, males, females, and non-Hispanic Whites.
Conclusions: This study confirms a positive association between sVC levels and HDL-C in adolescents, suggesting that higher vitamin C intake/status may be associated with a higher HDL-C in adolescents.
期刊介绍:
Nutrition & Metabolism publishes studies with a clear focus on nutrition and metabolism with applications ranging from nutrition needs, exercise physiology, clinical and population studies, as well as the underlying mechanisms in these aspects.
The areas of interest for Nutrition & Metabolism encompass studies in molecular nutrition in the context of obesity, diabetes, lipedemias, metabolic syndrome and exercise physiology. Manuscripts related to molecular, cellular and human metabolism, nutrient sensing and nutrient–gene interactions are also in interest, as are submissions that have employed new and innovative strategies like metabolomics/lipidomics or other omic-based biomarkers to predict nutritional status and metabolic diseases.
Key areas we wish to encourage submissions from include:
-how diet and specific nutrients interact with genes, proteins or metabolites to influence metabolic phenotypes and disease outcomes;
-the role of epigenetic factors and the microbiome in the pathogenesis of metabolic diseases and their influence on metabolic responses to diet and food components;
-how diet and other environmental factors affect epigenetics and microbiota; the extent to which genetic and nongenetic factors modify personal metabolic responses to diet and food compositions and the mechanisms involved;
-how specific biologic networks and nutrient sensing mechanisms attribute to metabolic variability.