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

8 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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