ArticleBMC geriatrics2026
Social factors, wearable activity tracker use frequency, and physical activity patterns among U.S. older adults: findings from a national cross-sectional survey.
Article in BMC geriatrics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
backgroundFew studies have investigated wearable activity tracker (WAT) use frequency and physical activity (PA) patterns among older adults. The present study aims to describe PA patterns (moderate-to-vigorous physical activity (MVPA) and sedentary behavior) and to examine the association of social factors and WAT use frequency with PA patterns among U.S. older adults.
methodsWe used cross-sectional self-reported data from 3,370 older adults from the Health Information National Trends Survey. Linear regression models and multinomial logistic regression models were used to identify associations among social factors, WAT use, and PA patterns. Mediation analysis was conducted to explore whether WAT use statistically explained the association between socioeconomic status and activity.
resultsMost participants (63.7%) had < 150 min/week of MVPA, and 60.1% reported > 6 h/day of sedentary time. Female (b=-55.79, 95% CI: -101.5, -10.52) and older (≥ 75 years) adults (b=-51.47, 95% CI: -98.90, -4.04) had lower MVPA. Higher income was associated with higher MVPA (b = 60.90, 95% CI: 3.98, 117.81) and greater odds of “High MVPA & Low Sedentary” group (AOR = 2.16, 95% CI: 1.26, 3.68). College education was associated with higher odds of “High MVPA & Low Sedentary” group (AOR = 1.65, 95% CI: 1.08, 2.53). Frequent WAT use was associated with longer MVPA (b = 58.54, 95% CI: 4.73, 112.34) and “High MVPA & Low Sedentary” group (AOR = 1.92, 95% CI: 1.10, 3.34). Income had a significant indirect effect on MVPA through WAT use (IE = 4.08, 95% CI: 0.04, 8.13), but not education or sedentary behavior.
conclusionSocial disparities existed in PA patterns, but WAT use frequency partially explained the associations between income and MVPA time. This may inform a need to promote PA patterns especially in socially and economically disadvantaged older adults.
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.