Accelerometer-Determined Steps/Day and Metabolic Syndrome

Pennington Biomedical Research Center, Baton Rouge, Louisiana 70808, USA.
American journal of preventive medicine (Impact Factor: 4.53). 06/2010; 38(6):575-82. DOI: 10.1016/j.amepre.2010.02.015
Source: PubMed


There is a lack of knowledge about the relationship between objectively measured physical activity and the odds of having metabolic syndrome (MetS) and cardiovascular (CVD) risk factors.
This study aims to investigate associations between accelerometer-determined steps/day and the odds of having MetS and its individual CVD risk factors in the U.S. population.
Adults in 2005-2006 NHANES with accelerometer-determined steps/day and measurements necessary to determine MetS by AHA/NHLBI were included (n=1446, 48.2% men, 33.5% with MetS, mean age=47.5 years, mean BMI=28.7 kg/m(2)). Logistic regression was used to estimate the odds of having MetS or abnormal CVD risk factors from incrementally higher levels of steps/day.
MetS prevalence decreased as steps/day increased (p<0.0001), with 55.7% of participants in the lowest categoric level of steps/day and 13.3% in the highest level having MetS. The odds of having MetS were 10% lower for each additional 1000 steps/day (OR=0.90, 95% CI=0.86, 0.93). The likelihood of having MetS was OR=0.28 (95% CI=0.18, 0.44) for active to highly active and 0.60 (0.43, 0.82) for low to somewhat-active compared to sedentary adults (p<0.0001). Adults who took more steps/day tended to have lower waist circumference, higher high-density lipoprotein (HDL) cholesterol level, and lower levels of triglycerides.
Adults who maintain an active lifestyle by accumulating more steps are likely to have a lower prevalence of MetS and its individual CVD risk factors. Although other concomitant lifestyle behaviors may influence this lower prevalence, the evidence presented here on steps/day and metabolic syndrome, and elsewhere on physical activity and other health and disease states, suggest that it is a fundamental component of daily living.

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    • "Most current knowledge on PA patterns, however, relies predominantly upon self-reporting with its known limitations affecting accuracy, such as recall bias and social desirability bias [11]. Motion sensors, such as accelerometers and pedometers, overcome many of the limitations related to self-reporting because they provide accurate and reliable estimates of the daily PA level by measuring incidental activities and considering all domains of PA (occupation, transportation , household and yard/garden, leisure time) [12]. furthermore, pedometers have the advantage of being inexpensive, unobtrusive and easy to use. "
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    • "Using these programs, researchers around the world could access the time-series accelerometer data from NHANES and run SAS programs to derive meaningful PA variables to use in statistical analyses. Over the past seven years, the NCI's SAS programs have facilitated great progress in understanding the distribution of PA behaviors in America (Troiano et al., 2008; Tudor-Locke et al., 2010), and have helped to identify numerous cross-sectional associations between PA and health outcomes (Healy et al., 2011; Sisson et al., 2010; Carson and Janssen, 2011). "
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    ABSTRACT: Accelerometers are a valuable tool for measuring physical activity (PA) in epidemiological studies. However, considerable processing is needed to convert time-series accelerometer data into meaningful variables for statistical analysis. This article describes two recently developed R packages for processing accelerometer data. The package accelerometry contains functions for performing various data processing procedures, such as identifying periods of non-wear time and bouts of activity. The functions are flexible, computationally efficient, and compatible with uniaxial or triaxial data. The package nhanesaccel is specifically for processing data from the National Health and NutritionExamination Survey (NHANES), years 2003–2006. Its primary function generates measures of PA volume, intensity, frequency, and patterns according to user-specified data processing methods. This function can process the NHANES 2003–2006 dataset in under one minute, which is a drastic improvement over existing software. This article highlights important features of packages accelerometry and nhanesaccel and demonstrates typical usage for PA researchers.
    The R Journal 12/2014; 6(2):52-62. · 1.04 Impact Factor
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    • "Also using pedometer promotes self-efficacy by focusing on walking activities (Freak-Poli, Cumpston, Peeters, & Clemes, 2013). Although, pedometers are widely used in the measurement of physical activity in many countries , they are not yet common in Turkey (Church, Earnest, Skinner, & Blair, 2007; Sisson et al., 2010). "
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    ABSTRACT: Abstract Physical activity and healthy eating are of the utmost importance in treatment of obesity. However obese generally tend to have a sedentary lifestyle. Walking is a form of physical activity that is both simple and can be performed by everyone, but it requires an objective measurement. Number of steps taken during tracking can be recorded with the pedometer, a device used to measure the level of physical activity. We aimed to investigate whether or not using pedometers as a motivational technique to increase the level of physical activity in obese women has an impact on weight loss. Eighty-four obese women who are similar age referring to Ataturk University Faculty of Medicine Healthy Living Clinic, Turkey were randomly divided into two groups. Intervention group were given pedometers, and control group were prescribed similar diet and physical activity with a three-month follow-up plan without pedometers. Mean weight in pedometer group initially was 88.9 ± 8.4 kg, which decreased to 80.2 ± 8.7 kg after the programme. Mean weight in control group was 86.1 ± 9.2 kg at the beginning, and it decreased to 84.7 ± 8.8 kg after three months. It was observed in pedometer group that the mean number of steps 8817 ± 2725 steps/day at the beginning increased to mean 9716 ± 2811 steps/day at the end of the study. Weight, body mass index, body fat percentage and waist circumference measurements decreased more greatly in the pedometer when compared to the control group (p < 0.001). Pedometers may be recommended to obese patients to monitor and increase the level of physical activity and to promote weight loss.
    European Journal of Sport Science 07/2014; 15(4):1-6. DOI:10.1080/17461391.2014.940558 · 1.55 Impact Factor
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