Literature DB >> 18166236

Beyond BMI: the value of more accurate measures of fatness and obesity in social science research.

Richard V Burkhauser1, John Cawley.   

Abstract

Virtually all social science research related to obesity studies a person's body mass index (BMI). Yet there is wide agreement in the medical literature that BMI is seriously flawed because it does not distinguish fat from fat-free mass such as muscle and bone. This paper studies data that include multiple measures of fatness and finds that many important patterns, such as who is classified as obese, group rates of obesity, and correlations of obesity with social science outcomes, are all sensitive to the measure of fatness and obesity used. We show that, relative to percent body fat, BMI misclassifies substantial fractions of individuals as obese or non-obese; in general, BMI is less accurate classifying men than women. Furthermore, when percent body fat instead of BMI is used to define obesity, the gap in obesity between white and African American men increases substantially but the gap in obesity between African American and white women is cut in half. Finally, total body fat is negatively correlated with employment for some groups and fat-free mass is not significantly correlated with employment for any group, a difference that was obscured in previous research that studied BMI. In the long run, social science datasets should include more accurate measures of fatness. In the short run, estimating more accurate measures of fatness using height and weight is not possible except by making unattractive assumptions, but there is also no reason to adhere uncritically to BMI as a measure of fatness. Social science research on obesity would be enriched by greater consideration of alternate specifications of weight and height and more accurate measures of fatness.

Entities:  

Mesh:

Year:  2007        PMID: 18166236     DOI: 10.1016/j.jhealeco.2007.05.005

Source DB:  PubMed          Journal:  J Health Econ        ISSN: 0167-6296            Impact factor:   3.883


  137 in total

1.  Religion and BMI in Australia.

Authors:  Michael A Kortt; Brian Dollery
Journal:  J Relig Health       Date:  2014-02

2.  Patient Barriers to Mammography Identified During a Reminder Program.

Authors:  Adrianne C Feldstein; Nancy Perrin; A Gabriela Rosales; Jennifer Schneider; Mary M Rix; Russell E Glasgow
Journal:  J Womens Health (Larchmt)       Date:  2011-01-28       Impact factor: 2.681

3.  Explaining the female black-white obesity gap: a decomposition analysis of proximal causes.

Authors:  David W Johnston; Wang-Sheng Lee
Journal:  Demography       Date:  2011-11

4.  Food prices and overweight patterns in Italy.

Authors:  L Pieroni; D Lanari; L Salmasi
Journal:  Eur J Health Econ       Date:  2011-09-21

5.  The unethical use of BMI in contemporary general practice.

Authors:  Stephen Humphreys
Journal:  Br J Gen Pract       Date:  2010-09       Impact factor: 5.386

6.  Race, socioeconomic status, and the use of bariatric surgery in Michigan.

Authors:  Nancy J O Birkmeyer; Niya Gu
Journal:  Obes Surg       Date:  2012-02       Impact factor: 4.129

7.  Maternal Prepregnancy Weight and Children's Behavioral and Emotional Outcomes.

Authors:  Julianna Deardorff; Louisa H Smith; Lucia Petito; Hyunju Kim; Barbara F Abrams
Journal:  Am J Prev Med       Date:  2017-07-13       Impact factor: 5.043

8.  Math skills and market and non-market outcomes: Evidence from an Amazonian society of forager-farmers.

Authors:  Eduardo A Undurraga; Jere R Behrman; Elena L Grigorenko; Alan Schultz; Julie Yiu; Ricardo A Godoy
Journal:  Econ Educ Rev       Date:  2013-12

9.  Association of obesity with IgE levels and allergy symptoms in children and adolescents: results from the National Health and Nutrition Examination Survey 2005-2006.

Authors:  Cynthia M Visness; Stephanie J London; Julie L Daniels; Jay S Kaufman; Karin B Yeatts; Anna-Maria Siega-Riz; Andrew H Liu; Agustin Calatroni; Darryl C Zeldin
Journal:  J Allergy Clin Immunol       Date:  2009-02-23       Impact factor: 10.793

Review 10.  STRATOS guidance document on measurement error and misclassification of variables in observational epidemiology: Part 1-Basic theory and simple methods of adjustment.

Authors:  Ruth H Keogh; Pamela A Shaw; Paul Gustafson; Raymond J Carroll; Veronika Deffner; Kevin W Dodd; Helmut Küchenhoff; Janet A Tooze; Michael P Wallace; Victor Kipnis; Laurence S Freedman
Journal:  Stat Med       Date:  2020-04-03       Impact factor: 2.373

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.