» Articles » PMID: 36056190

Wearable Accelerometer-derived Physical Activity and Incident Disease

Overview
Journal NPJ Digit Med
Date 2022 Sep 2
PMID 36056190
Authors
Affiliations
Soon will be listed here.
Abstract

Physical activity is regarded as favorable to health but effects across the spectrum of human disease are poorly quantified. In contrast to self-reported measures, wearable accelerometers can provide more precise and reproducible activity quantification. Using wrist-worn accelerometry data from the UK Biobank prospective cohort study, we test associations between moderate-to-vigorous physical activity (MVPA) - both total MVPA minutes and whether MVPA is above a guideline-based threshold of ≥150 min/week-and incidence of 697 diseases using Cox proportional hazards models adjusted for age, sex, body mass index, smoking, Townsend Deprivation Index, educational attainment, diet quality, alcohol use, blood pressure, anti-hypertensive use. We correct for multiplicity at a false discovery rate of 1%. We perform analogous testing using self-reported MVPA. Among 96,244 adults wearing accelerometers for one week (age 62 ± 8 years), MVPA is associated with 373 (54%) tested diseases over a median 6.3 years of follow-up. Greater MVPA is overwhelmingly associated with lower disease risk (98% of associations) with hazard ratios (HRs) ranging 0.70-0.98 per 150 min increase in weekly MVPA, and associations spanning all 16 disease categories tested. Overall, associations with lower disease risk are enriched for cardiac (16%), digestive (14%), endocrine/metabolic (10%), and respiratory conditions (8%) (chi-square p < 0.01). Similar patterns are observed using the guideline-based threshold of ≥150 MVPA min/week. Some of the strongest associations with guideline-adherent activity include lower risks of incident heart failure (HR 0.65, 95% CI 0.55-0.77), type 2 diabetes (HR 0.64, 95% CI 0.58-0.71), cholelithiasis (HR 0.61, 95% CI 0.54-0.70), and chronic bronchitis (HR 0.42, 95% CI 0.33-0.54). When assessed within 456,374 individuals providing self-reported MVPA, effect sizes for guideline-adherent activity are substantially smaller (e.g., heart failure HR 0.84, 95% CI 0.80-0.88). Greater wearable device-based physical activity is robustly associated with lower disease incidence. Future studies are warranted to identify potential mechanisms linking physical activity and disease, and assess whether optimization of measured activity can reduce disease risk.

Citing Articles

Within-person changes in objectively measured activity levels as a predictor of brain atrophy in multiple sclerosis.

Fitzgerald K, Sanjayan M, Dewey B, Niyogi P, Rjeily N, Fadlallah Y medRxiv. 2025; .

PMID: 39974055 PMC: 11838989. DOI: 10.1101/2025.01.27.25321205.


"Weekend Warrior" Physical Activity and Adipose Tissue Deposition.

Kany S, Al-Alusi M, Ramo J, Pirruccello J, Ajufo E, Churchill T JACC Adv. 2025; 4(3):101603.

PMID: 39954344 PMC: 11872521. DOI: 10.1016/j.jacadv.2025.101603.


Discriminating Myalgic Encephalomyelitis/Chronic Fatigue Syndrome and comorbid conditions using metabolomics in UK Biobank.

Huang K, de Sa A, Thomas N, Phair R, Gooley P, Ascher D Commun Med (Lond). 2024; 4(1):248.

PMID: 39592839 PMC: 11599898. DOI: 10.1038/s43856-024-00669-7.


Associations of "Weekend Warrior" Physical Activity With Incident Disease and Cardiometabolic Health.

Kany S, Al-Alusi M, Ramo J, Pirruccello J, Churchill T, Lubitz S Circulation. 2024; 150(16):1236-1247.

PMID: 39324186 PMC: 11803568. DOI: 10.1161/CIRCULATIONAHA.124.068669.


Data Analytics in Physical Activity Studies With Accelerometers: Scoping Review.

Liang Y, Wang C, Hsiao C J Med Internet Res. 2024; 26:e59497.

PMID: 39259962 PMC: 11425027. DOI: 10.2196/59497.


References
1.
Kraigher-Krainer E, Lyass A, Massaro J, Lee D, Ho J, Levy D . Association of physical activity and heart failure with preserved vs. reduced ejection fraction in the elderly: the Framingham Heart Study. Eur J Heart Fail. 2013; 15(7):742-6. PMC: 3857918. DOI: 10.1093/eurjhf/hft025. View

2.
Garriguet D, Tremblay S, Colley R . Comparison of Physical Activity Adult Questionnaire results with accelerometer data. Health Rep. 2015; 26(7):11-7. View

3.
Craig C, Marshall A, Sjostrom M, Bauman A, Booth M, Ainsworth B . International physical activity questionnaire: 12-country reliability and validity. Med Sci Sports Exerc. 2003; 35(8):1381-95. DOI: 10.1249/01.MSS.0000078924.61453.FB. View

4.
Peduzzi P, Concato J, Feinstein A, Holford T . Importance of events per independent variable in proportional hazards regression analysis. II. Accuracy and precision of regression estimates. J Clin Epidemiol. 1995; 48(12):1503-10. DOI: 10.1016/0895-4356(95)00048-8. View

5.
Okbay A, Wu Y, Wang N, Jayashankar H, Bennett M, Nehzati S . Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals. Nat Genet. 2022; 54(4):437-449. PMC: 9005349. DOI: 10.1038/s41588-022-01016-z. View