Location: Location not imported yet.Title: Several steps/day indicators predict changes in anthropometric outcomes: HUB city steps) Author
Submitted to: BioMed Central(BMC) Public Health
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 11/14/2012
Publication Date: 11/15/2012
Publication URL: http://handle.nal.usda.gov/10113/62015
Citation: Thomson, J.L., Landry, A.S., Zoellner, J.M., Tudor-Locke, C., Webster, M., Connell, C., Yadrick, K. 2012. Several steps/day indicators predict changes in anthropometric outcomes: HUB city steps. BioMed Central(BMC) Public Health. 12:983. Interpretive Summary: Walking for exercise remains the most frequently reported leisure-time activity, likely because it is simple, inexpensive, and easily incorporated into most people’s lifestyle. Pedometers are simple, convenient, and economical means by which to count the number of steps taken per day (steps/day), allowing for an estimate of activity level. Participants in many walking studies have benefited from improvements in health measures, such as reduced weight and blood pressure. However, the direct relationship between increased steps/day and improved health outcomes is not well defined. Hence, we tested the usefulness of different methods of summarizing steps/day (as measured by pedometers) for predicting changes in health outcomes. We also tested whether treating steps/day data for improbable or highly unlikely values changed the relationship between steps/day measures and changes in health outcomes. We used data from a six-month, community-based, walking study, HUB City Steps. This study was conducted in 2010 with 269 southern, African American adults. Its primary purpose was to reduce blood pressure through increased walking. Study participants tracked their walking by recording the number of steps/day taken in weekly logs. We measured health outcomes (body fat measures, blood pressure, cholesterol, and blood glucose) at the beginning and end of the study to determine if changes had taken place in the participants during the six months. Various statistical methods were used to determine if significant relationships existed between the steps/day measures and changes in health outcomes. We found significant relationships between many of the steps/day measures and changes in health outcomes. In all cases, increases in steps/day were associated with improved health outcomes. However, when we accounted for characteristics of the participants, such as age, sex, income, and fitness level, only the relationships between steps/day measures and measures of body fat remained significant. Additionally, we did not find that excluding improbable steps/day values changed the relationships between the steps/day measures and changes in the health outcomes. Based on these results, we suggest that an average change in steps/day taken during a study may be the most useful measure for predicting changes in body fat measures.
Technical Abstract: Walking for exercise remains the most frequently reported leisure-time activity, likely because it is simple, inexpensive, and easily incorporated into most people’s lifestyle. Pedometers are simple, convenient, and economical tools that can be used to quantify step-determined physical activity. Few studies have attempted to define the direct relationship between dynamic changes in pedometer-determined steps/day and changes in anthropometric and clinical outcomes. Hence, the objective of this secondary analysis was to evaluate the utility of descriptive indicators of pedometer-determined steps/day for predicting changes in anthropometric and clinical outcomes using data from a community-based walking intervention, HUB City Steps, conducted in a southern, African American population. A secondary aim was to evaluate whether treating steps/day data for implausible values affected the ability of these data to predict intervention-induced changes in clinical and anthropometric outcomes. The data used in this secondary analysis were collected in 2010 from 269 participants in a six-month walking intervention targeting a reduction in blood pressure. Throughout the intervention, participants submitted weekly steps/day diaries based on pedometer self-monitoring. Changes (six-month minus baseline) in anthropometric (body mass index, waist circumference, percent body fat [%BF], fat mass) and clinical (blood pressure, lipids, glucose) outcomes were evaluated. Associations between steps/day indicators and changes in anthropometric and clinical outcomes were assessed using bivariate tests and multivariable linear regression analysis which controlled for demographic and baseline covariates. Significant negative bivariate associations were observed between steps/day indicators and the majority of anthropometric and clinical outcome changes (r = -0.2 to -0.3: P < 0.05). After controlling for covariates in the regression analysis, only the relationships between steps/day indicators and changes in anthropometric (not clinical) outcomes remained significant. For example, a 1,000 steps/day increase in intervention mean steps/day resulted in a 0.1% decrease in %BF. Results for the three pedometer datasets (full, truncated, and excluded) were similar and yielded few meaningful differences in interpretation of the findings. Several descriptive indicators of steps/day may be useful for predicting anthropometric outcome changes. Further, manipulating steps/day data to address implausible values has little overall effect on the ability to predict these anthropometric changes.