Investigating work place intervention and change in metabolic equivalence of task using multilevel data

Pratik Manandhar, The University of Texas School of Public Health

Abstract

Obesity rates in the United States have increased markedly over the past three decades and with it, the need for effective intervention strategies to reduce it. Shape Up Houston is a workplace intervention strategy aimed at reducing obesity among Houstonians through social marketing strategies. The data structure of Shape Up Houston is hierarchical in nature, with 900 employees nested within 6 hospital clusters. Metabolic Equivalence of Tasks (METs) was modeled using Hierarchical Linear Model, No-Intercept Fixed Effects Model and Bootstrapping techniques. Shape Up Houston intervention was analyzed for its effectiveness as well as for presence of any fixed effects at the cluster level. For all intervention hospitals, positive and significant associations were found with METs, however, the largest significant association for METs was found to be with the non-intervention hospital. On further investigation, it was found that the non-intervention hospital had an alternate wellness initiative already in place besides Shape Up Houston.^

Subject Area

Biostatistics|Epidemiology

Recommended Citation

Manandhar, Pratik, "Investigating work place intervention and change in metabolic equivalence of task using multilevel data" (2015). Texas Medical Center Dissertations (via ProQuest). AAI1602748.
http://digitalcommons.library.tmc.edu/dissertations/AAI1602748

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