Cancer risk in normal weight individuals with metabolic obesity: A narrative review

Bethina Liu, Hugh E. Giffney, Rhonda S. Arthur, Thomas E. Rohan, Andrew J. Dannenberg

Research output: Contribution to journalReview articlepeer-review

1 Scopus citations

Abstract

Obesity represents one of the most significant public health challenges worldwide. Current clinical practice relies on body mass index (BMI) to define the obesity status of an individual, even though the index has long been recognized for its limitations as a measure of body fat. In normal BMI individuals, increased central adiposity has been associated with worse health outcomes, including increased risks of cardiovascular disease and metabolic disorders. The condition leading to these outcomes has been described as metabolic obesity in the normal weight (MONW). More recent evidence suggests that MONW is associated with increased risk of several obesity-related malignancies, including postmenopausal breast, endometrial, colorectal, and liver cancers. In MONW patients, the false reassurance of a normal range BMI can lead to lost opportunities for implementing preventive interventions that may benefit a substantial number of people. A growing body of literature has documented the increased risk profile of MONW individuals and demonstrated practical uses for body composition and biochemical analyses to identify this at-risk population. In this review, we survey the current literature on MONW and cancer, summarize pathophysiology and oncogenic mechanisms, highlight potential strategies for diagnosis and treatment, and suggest directions for future research.

Original languageEnglish (US)
Pages (from-to)509-520
Number of pages12
JournalCancer Prevention Research
Volume14
Issue number5
DOIs
StatePublished - May 2021

ASJC Scopus subject areas

  • Oncology
  • Cancer Research

Fingerprint

Dive into the research topics of 'Cancer risk in normal weight individuals with metabolic obesity: A narrative review'. Together they form a unique fingerprint.

Cite this