A break in the obesity epidemic? Explained by biases or misinterpretation of the data?

Int J Obes (Lond). 2015 Feb;39(2):189-98. doi: 10.1038/ijo.2014.98. Epub 2014 Jun 9.

Abstract

Recent epidemiologic papers are presenting prevalence data suggesting breaks and decreases in obesity rates. However, before concluding that the obesity epidemic is not increasing anymore, the validity of the presented data should be discussed more thoroughly. We had a closer look into the literature presented in recent reviews to address the major potential biases and distortions, and to develop insights about how to interpret the presented suggestions for a potential break in the obesity epidemic. Decreasing participation rates, the use of reported rather than measured data and small sample sizes, or lack of representativeness, did not seem to explain presented breaks in the obesity epidemic. Further, available evidence does not suggest that stabilization of obesity rates is seen in higher socioeconomic groups only, or that urbanization could explain a potential break in the obesity epidemic. However, follow-ups of short duration may, in part, explain the apparent break or decrease in the obesity epidemic. On the other hand, a single focus on body mass index (BMI) ⩾25 or ⩾30 kg m(-)(2) is likely to mask a real increase in the obesity epidemic. And, in both children and adults, trends in waist circumferences were generally suggesting an increase, and were stronger than those reported for trends in BMI. Studies concluding that there is a recent break in the obesity epidemic need to be interpreted with caution. Reported studies presenting a break were mostly of short duration. Further, focusing on trends in waist circumference rather than BMI leads to a less optimistic conclusion: the public health problem of obesity is still increasing.

Publication types

  • Research Support, Non-U.S. Gov't
  • Review

MeSH terms

  • Bias
  • Body Mass Index
  • Data Interpretation, Statistical
  • Epidemics / statistics & numerical data*
  • Humans
  • Nutrition Surveys / statistics & numerical data*
  • Obesity / epidemiology*
  • Policy Making
  • Prevalence
  • Public Health
  • Socioeconomic Factors
  • Waist Circumference