Skip to content
naulon
Not checkedNot checked for notices yet.

Unbalanced Baseline in School-Based Interventions to Prevent Obesity: Adjustment Can Lead to Bias - a Systematic Review

Rosely Sichieri, Diana Barbosa Cunha

Obesity Facts · 2014

doi:10.1159/000363438 (opens in a new tab)

We email you when a new notice or a question about this paper appears.

Abstract

Background/Aims: Cluster designs favor unbalanced baseline measures. The aim of the present study was to determine the frequency of unbalanced baseline BMI on school-based randomized controlled trials (RCT) aimed at obesity reduction and to evaluate the analysis strategies. We hypothesized that the adjustment of unbalanced baseline measures may explain the great discrepancy among studies. Methods: The source of data was the Medline database content from January 1995 until May 2012. Our search strategy combined key words related to school-based interventions with such related to weight and was not limited by language. The participants' ages were restricted to 6-18 years. Results: We identified 146 school-based studies on obesity prevention (or overweight or excessive weight change). Of the 146 studies, 36 were retained for the analysis after excluding reviews, feasibility studies, other outcomes, and repeated publications. 13 (35%) of the reviewed studies had statistically significant (p Conclusion: Adjustment for the baseline BMI is frequently done in cluster randomized studies, and there is no standardization for this procedure. Thus, procedures that disentangle the effects of group, time and changes in time, such as mixed effects models, should be used as standard methods in school-based studies on the prevention of weight gain.

Abstract licence: CC BY-NC

Reads

Read by people on this page

None yet.

Checked or read by AI through naulon

None yet.

A person counts once a day per paper. We keep no cookie and no address: a reader is a hash that changes every day. Any month under five reads shows no number.

Are you an author?

Is this your paper?

Claim it to add your note and be paid when agents cite it. Free.