title: Can adjusting BMI for age and sex provide for a better predictor of colonic neoplasia?
abstract: OBJECTIVE
  The aim of this study was to evaluate the influence of BMI on colonic neoplasia in average-risk patients aged between 40 and 59 years, analyzed by sex.
  
  
  METHODS
  A total of 4443 patients aged between 40 and 59 years undergoing a first-time screening or average-risk colonoscopy were included in this study. Data on demographics, smoking, and BMI were collected and correlated to the presence of adenomas and advanced adenomas.
  
  
  RESULTS
  We evaluated 1197 colonoscopies in patients aged between 40 and 49 years, and 3246 in those aged between 50 and 59 years. Among men between 40 and 49 years, increasing BMI [odds ratio (OR)=1.05, 95% confidence interval (CI): 1.00-1.09] and BMI of at least 27 (OR=1.95, 95% CI: 1.15-3.29) were predictors of adenomas. Younger men with a BMI of at least 27 were more likely to have proximal adenomas (OR=2.23, 95% CI: 1.14-4.37) but not advanced adenomas. There was no relation between BMI and adenomas in younger women. Among women aged between 50 and 59 years, increasing BMI (OR=1.03, 95% CI: 1.01-1.05) and a BMI of at least 24 (OR=1.43, 95% CI: 1.06-2.94) was found to be correlated with adenomas, and increasing BMI was also found to be associated with proximal adenomas (OR=1.67, 95% CI: 1.13-2.45). Among men aged between 50 and 59 years, there was no relation between BMI and adenomas, but there was a positive correlation for advanced adenomas (OR=1.05, 95% CI: 1.002-1.09). Among women aged between 50 and 59 years, BMI was not predictive of advanced adenomas.
  
  
  CONCLUSIONS
  The association between BMI and adenoma differs by age and sex. If BMI is utilized to refine screening practices for colorectal cancer, its influence on sex and age should be taken into account.
authors.affiliation: Department of Gastroenterology, Cleveland Clinic Florida, Weston, Florida, USA.
authors.forename: Jorge
authors.initials: J
authors.lastname: Zapatier
authors.forename: Danny
authors.initials: D
authors.lastname: Avalos
authors.forename: Kanwarpreet
authors.initials: K
authors.lastname: Tandon
authors.forename: Anas
authors.initials: A
authors.lastname: Souqiyyeh
authors.forename: Marlow
authors.initials: M
authors.lastname: Hernandez
authors.forename: Sonia
authors.initials: S
authors.lastname: Rai
authors.forename: Brenda
authors.initials: B
authors.lastname: Jimenez
authors.forename: Fernando J
authors.initials: FJ
authors.lastname: Castro
mesh_terms: D000236:Adenoma / Q000453:epidemiology* / Q000473:pathology; D000328:Adult; D017677:Age Distribution; D000367:Age Factors; D015992:Body Mass Index; D016009:Chi-Square Distribution; D003110:Colonic Neoplasms / Q000453:epidemiology* / Q000473:pathology; D003113:Colonoscopy; D055088:Early Detection of Cancer / Q000379:methods; D005260:Female; D005431:Florida / Q000453:epidemiology; D006801:Humans; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D009765:Obesity / Q000175:diagnosis / Q000453:epidemiology*; D016017:Odds Ratio; D018579:Patient Selection; D011237:Predictive Value of Tests; D015995:Prevalence; D012189:Retrospective Studies; D018570:Risk Assessment; D012307:Risk Factors; D017678:Sex Distribution; D012737:Sex Factors; D012907:Smoking / Q000009:adverse effects / Q000453:epidemiology