Normative Peak Physical Activity Values for Monitor-Independent Movement Summary Units: National Health and Nutrition Examination Survey 2011–2014

规范性 全国健康与营养检查调查 体力活动 运动(音乐) 久坐行为 心理学 环境卫生 医学 物理医学与康复 政治学 法学 人口 美学 哲学
作者
Scott W. Ducharme,James D. Pleuss,Dusty Turner,Peixuan Zheng,Israel I. Adandom,Elroy J. Aguiar
出处
期刊:Journal of Physical Activity and Health [Human Kinetics]
卷期号:: 1-10 被引量:1
标识
DOI:10.1123/jpah.2025-0182
摘要

Background : The most recent physical activity (PA) monitor data from the US National Health and Nutrition Examination Survey (NHANES) were processed using a novel monitor-independent movement summary (MIMS) algorithm. To date, few studies have utilized these data, likely due to a general unfamiliarity with MIMS-related metrics. The purpose of this study was to establish normative values for peak MIMS metrics as measures of free-living PA intensity and natural ambulatory effort. Methods : Data from the National Health and Nutrition Examination Survey 2011–2012 and 2013–2014 survey cycles were used, including 8729 individuals aged 20–80+ years. MIMS data were obtained from wrist-worn accelerometers worn for at least 1 valid day (<5% nonwear time per day). Peak-1 MIMS (ie, the highest 1-min MIMS value within a day) and Peak-30 MIMS (ie, the average of the 30 highest 1-min MIMS values) were obtained, averaged across all valid days, and reported as sample-weighted means (95% confidence intervals), and across 5th to 95th percentiles. Results : Mean (95% confidence interval) values for Peak-1 MIMS and Peak-30 MIMS were 59.9 (59.2–61.6) and 42.9 (42.4–43.3) MIMS/minute, respectively. Both peak metrics declined across the adult lifespan. Men displayed greater Peak-1 MIMS , while Peak-30 MIMS was similar between sexes. Both MIMS metrics trended lower with increasing body mass index. Conclusion : We provide normative values for peak MIMS metrics which reflect PA intensity/effort. We also developed an R-Shiny App whereby users can input age, sex, body mass index category, and MIMS metrics to determine individual-specific MIMS percentile values. Given the universal nature of the MIMS algorithm, these population representative data may be useful as a reference data set for device-based PA surveillance within the United States and for comparison globally.
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