Long-term effects of large-volume liposuction on metabolic risk factors for coronary heart disease

B. Selma Mohammed, Samuel Cohen, Dominic Reeds, V. Leroy Young, Samuel Klein

Research output: Contribution to journalArticlepeer-review

75 Scopus citations

Abstract

Abdominal obesity is associated with metabolic risk factors for coronary heart disease (CHD). Although we previously found that using liposuction surgery to remove abdominal subcutaneous adipose tissue (SAT) did not result in metabolic benefits, it is possible that postoperative inflammation masked the beneficial effects. Therefore, this study provides a long-term evaluation of a cohort of subjects from our original study. Body composition and metabolic risk factors for CHD, including oral glucose tolerance, insulin resistance, plasma lipid profile, and blood pressure were evaluated in seven obese (39 ± 2 kg/m 2) women before and at 10, 27, and 84-208 weeks after large-volume liposuction. Liposuction surgery removed 9.4 ± 1.8 kg of body fat (16 ± 2% of total fat mass; 6.1 ± 1.4 kg decrease in body weight), primarily from abdominal SAT; body composition and weight remained the same from 10 through 84-208 weeks. Metabolic endpoints (oral glucose tolerance, homeostasis model assessment of insulin resistance, blood pressure and plasma triglyceride (TG), high-density lipoprotein (HDL)-cholesterol, and low-density lipoprotein (LDL)-cholesterol concentrations) obtained at 10 through 208 weeks were not different from baseline and did not change over time. These data demonstrate that removal of a large amount of abdominal SAT by using liposuction does not improve CHD metabolic risk factors associated with abdominal obesity, despite a long-term reduction in body fat.

Original languageEnglish
Pages (from-to)2648-2651
Number of pages4
JournalObesity
Volume16
Issue number12
DOIs
StatePublished - Dec 2008

Fingerprint

Dive into the research topics of 'Long-term effects of large-volume liposuction on metabolic risk factors for coronary heart disease'. Together they form a unique fingerprint.

Cite this