Accelerometer-Determined Steps/Day and Metabolic Syndrome

ArticleinAmerican journal of preventive medicine 38(6):575-82 · June 2010with16 Reads
Impact Factor: 4.53 · DOI: 10.1016/j.amepre.2010.02.015 · Source: PubMed
Abstract

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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    • "...sidering 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. ..."
      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.
    Full-text · Article · Feb 2015
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    • "...ID: nagarajulum Time: 12:56 I Path: N:/3b2/HIPO/Vol00000/140157/APPFile/JW-HIPO140157 (Sisson et al., 2010). The Community Health Activities Model Program for Seniors variable was log transformed because of its..."
      ID: nagarajulum Time: 12:56 I Path: N:/3b2/HIPO/Vol00000/140157/APPFile/JW-HIPO140157 (Sisson et al., 2010). The Community Health Activities Model Program for Seniors variable was log transformed because of its skewed distribution.Table 1Fig.
    [Show abstract] [Hide abstract] ABSTRACT: Hippocampal atrophy is associated with memory impairment and dementia and serves as a key biomarker in the preclinical stages of Alzheimer's disease. Physical activity, one of the most promising behavioral interventions to prevent or delay cognitive decline, has been shown to be associated with hippocampal volume; specifically increased aerobic activity and fitness may have a positive effect on the size of the hippocampus. The majority of older adults, however, are sedentary and have difficulty initiating and maintaining exercise programs. A modestly more active lifestyle may nonetheless be beneficial. This study explored whether greater objectively measured daily walking activity was associated with larger hippocampal volume. We additionally explored whether greater low-intensity walking activity, which may be related to leisure-time physical, functional, and social activities, was associated with larger hippocampal volume independent of exercise and higher-intensity walking activity. Segmentation of hippocampal volumes was performed using FMRIB's Software Library (FSL) and daily walking activity was assessed using a step activity monitor (SAM) on 92, non-demented, older adult participants. After controlling for age, education, body mass index (BMI), cardiovascular disease risk factors, and the Mini Mental State Exam (MMSE), we found that a greater amount, duration, and frequency of total daily walking activity were each associated with larger hippocampal volume among older women, but not men. These relationships were specific to hippocampal volume, compared to the thalamus, used as a control brain region, and remained significant for low-intensity walking activity, independent of moderate- to vigorous-intensity activity and self-reported exercise. This is the first study, to our knowledge, to explore the relationship between objectively measured daily walking activity and hippocampal volume in an older adult sample. Findings suggest the importance of better understanding whether increasing non-exercise, lifestyle physical activities may produce measurable cognitive benefits and effect hippocampal volume through molecular pathways unique to those related to moderate-intensity exercise. This article is protected by copyright. All rights reserved. © 2014 Wiley Periodicals, Inc.
    Full-text · Article · Dec 2014 · Hippocampus
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    • "... numerous cross-sectional associations between PA and health outcomes (Healy et al., 2011; Sisson et al., 2010; Carson and Janssen, 2011). While the NCI's SAS programs provide several indicators of overall PA an..."
      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). While the NCI's SAS programs provide several indicators of overall PA and moderate-to-vigorous PA (MVPA), researchers are increasingly writing customized scripts in programs such as MATLAB (The MathWorks, Inc., 2014), LabVIEW (National Instruments, 2014), and R for more flexibility in data processing (Tudor-Locke et al., 2011).
    [Show abstract] [Hide abstract] 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.
    Full-text · Article · Dec 2014 · The R Journal
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