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Title: Steps/day ability to predict anthropometric changes is not affected by its plausibility

Author
item Thomson, Jessica
item Sample, Alicia - University Of Southern Mississippi
item Zoellner, Jamie - Virginia Polytechnic Institution & State University
item Tudor-locke, Catrine - Pennington Biomedical Research Center
item Webster, Michael - University Of Southern Mississippi
item Connell, Carol - University Of Southern Mississippi
item Yadrick, Kathleen - University Of Southern Mississippi

Submitted to: Experimental Biology
Publication Type: Abstract Only
Publication Acceptance Date: 3/9/2012
Publication Date: N/A
Citation: N/A

Interpretive Summary:

Technical Abstract: We evaluated whether treating steps/day data for implausible values (<500 or >30,000) affected the ability of these data to predict intervention-induced anthropometric (waist circumference, body mass index, percent body fat, and fat mass) changes. Data were from 269 African American participants who submitted weekly steps/day diaries during a six-month intervention (HUB City Steps 2009-2010). Three datasets were used: full (all values analyzed regardless of plausibility), truncated (to plausible values), and excluded (if implausible). Multivariable linear regression was used to estimate the effects of steps/day on anthropometric changes. Meaningful differences in model coefficient magnitudes were not apparent among the datasets, although larger coefficients were obtained using the excluded compared to the full and truncated datasets (range of differences: 0-0.17 between full and excluded; 0-0.15 between truncated and excluded). For example, a mean increase of 1,000 steps/day resulted in 0.34, 0.37 and 0.44 cm decreases in waist circumference using the full, truncated and excluded datasets. These results suggest that manipulating steps/day data to address implausible values has little overall affect on the ability to predict intervention-induced anthropometric changes. Funding for this research was provided by the National Institute on Minority Health and Health Disparities.