ArticleStatistics in biosciences2019
Organizing and analyzing the activity data in NHANES.
Article in Statistics in biosciences, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 53 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
53 citing papers in PubMed, 99 citations in OpenAlex.
- Trial
- Clustering-Based Accelerometer Measures of Physical Activity Patterns in Children With Overweight or Obesity: Baseline Cross-Sectional Methodological Analysis.JMIR formative research · 2026Article
- Smartphone-Based Passive Sensing of Activity Levels and Behavioral Activation During Psychosocial Interventions for Older Adults With Depression: Longitudinal Observational Study.Journal of medical Internet research · 2026Observational
- Continuous assessment of daily-living gait using self-supervised learning of wrist-worn accelerometer data.NPJ digital medicine · 2026Article
- Association between physical activity, sleep quality and diabetes: a population-based analysis.Diabetology & metabolic syndrome · 2026Article
- Functional quantile principal component analysis.Biostatistics (Oxford, England) · 2025Article
- Regression and alignment for functional data and network topology.Biostatistics (Oxford, England) · 2025Article
- Positive association between standing height and bone mineral density in adolescents aged 12-19: NHANES 2011-2018 : Author.BMC pediatrics · 2025Article
- High-dimensional mediation analysis reveals the mediating role of physical activity patterns in genetic pathways leading to AD-like brain atrophy.BioData mining · 2025Article
- Generation of realistic virtual adult populations using a model-based copula approach.Journal of pharmacokinetics and pharmacodynamics · 2024Article
- Association between platelet to high-density lipoprotein cholesterol ratio (PHR) and hypertension: evidence from NHANES 2005-2018.Lipids in health and disease · 2024Article
- Self-supervised learning of wrist-worn daily living accelerometer data improves the automated detection of gait in older adults.Scientific reports · 2024Article
- Automated Gait Detection in Older Adults during Daily-Living using Self-Supervised Learning of Wrist-Worn Accelerometer Data: Development and Validation of ElderNet.Research square · 2024Article
- Evaluating data quality for blended data using a data quality framework.Statistical journal of the IAOS · 2024Article
- Deep learning of movement behavior profiles and their association with markers of cardiometabolic health.BMC medical informatics and decision making · 2024Article
- Direct Bayesian linear regression for distribution-valued covariates.Electronic journal of statistics · 2024Article
- Analysis of the association between non-alcoholic fatty liver disease and mortality in United States adults.Frontiers in nutrition · 2024Article
- Scalar-Function Causal Discovery for Generating Causal Hypotheses with Observational Wearable Device Data.Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing · 2024Article
- Article
- Gender difference in "second-shift" physical activity: New insights from analyzing accelerometry data in a nationally representative sample.SSM - population health · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors at 4 institutions in 1 country.
Funding
Abstract
The NHANES study contains objectively measured physical activity data collected using hip-worn accelerometers from multiple cohorts. However, using the accelerometry data has proven daunting because: 1) currently, there are no agreed upon standard protocols for data storage and analysis; 2) data exhibit heterogeneous patterns of missingness due to varying degrees of adherence to wear-time protocols; 3) sampling weights need to be carefully adjusted and accounted for in individual analyses; 4) there is a lack of reproducible software that transforms the data from its published format into analytic form; and 5) the high dimensional nature of accelerometry data complicates analyses. Here, we provide a framework for processing, storing, and analyzing the NHANES accelerometry data for the 2003-2004 and 2005-2006 surveys. We also provide an NHANES data package in R, to help disseminate high quality, processed activity data combined with mortality and demographic information. Thus, we provide the tools to transition from "available data online" to "easily accessible and usable data", which substantially reduces the large upfront costs of initiating studies of association between physical activity and human health outcomes using NHANES. We apply these tools in an analysis showing that accelerometry features have the potential to predict 5-year all cause mortality better than known risk factors such as age, cigarette smoking, and various comorbidities.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.