Predominance of small dense LDL differentiates metabolically unhealthy from metabolically healthy overweight adults in Korea

Sue Kim, Hyangkyu Lee, Duk Chul Lee, Hye Sun Lee, Ji Won Lee

Research output: Contribution to journalArticlepeer-review

11 Citations (Scopus)

Abstract

Objective The purposes of this study were (1) to determine the association between lipoprotein subfraction profiles and metabolically healthy overweight (MHO) phenotype, as defined by visceral adiposity; and (2) to identify the strongest predictor of metabolic health among the lipoprotein measurements. Materials/Methods This cross-sectional study was comprised of 462 overweight patients, who were classified as MHO or non-MHO based on their visceral adipose tissue (VAT) area to subcutaneous adipose tissue area (SAT) ratio (VAT/SAT ratio). Serum lipoprotein subfraction analyses and other metabolic parameters were measured. Results Among the overweight participants, two hundred fifty-five individuals (53.7%) had the MHO phenotype. After adjusting for age, sex, medication, lifestyle factors, and confounding metabolic characteristics, the non-MHO group showed significantly higher lipid levels and a greater prevalence of unfavorable lipid profiles. LDL subclass pattern type B was the most significant predictor of the non-MHO phenotype (odds ratio 2.70; 95% CI 1.55-4.69), while serum LDL cholesterol level was not a significant predictor of the non-MHO phenotype. Conclusions Lipoprotein subfraction particle measurements were significantly associated with the non-MHO phenotype and a higher VAT/SAT ratio, with small dense LDL predominance being the most significant predictor of MHO phenotype. These findings will help identify MHO and non-MHO phenotypes and perhaps lead to a development of cost-effective individualized treatments.

Original languageEnglish
Pages (from-to)415-421
Number of pages7
JournalMetabolism: Clinical and Experimental
Volume63
Issue number3
DOIs
Publication statusPublished - 2014 Mar

Bibliographical note

Funding Information:
This work was supported by the Biomedical Technology Development Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT and Future Planning (NRF-2013M3A9B6046413).

All Science Journal Classification (ASJC) codes

  • Endocrinology, Diabetes and Metabolism
  • Endocrinology

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