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Characterizing Longitudinal Patterns of Physical Activity in Mid-Adulthood Using Latent Class Analysis: Results From a Prospective Cohort Study

The authors aimed to describe how longitudinal patterns of physical activity during mid-adulthood (ages 31–53 years) can be characterized using latent class analysis in a population-based birth cohort study, the Medical Research Council’s 1946 National Survey of Health and Development. Three differe...

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Autores principales: Silverwood, Richard J., Nitsch, Dorothea, Pierce, Mary, Kuh, Diana, Mishra, Gita D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3276296/
https://www.ncbi.nlm.nih.gov/pubmed/22074812
http://dx.doi.org/10.1093/aje/kwr266
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author Silverwood, Richard J.
Nitsch, Dorothea
Pierce, Mary
Kuh, Diana
Mishra, Gita D.
author_facet Silverwood, Richard J.
Nitsch, Dorothea
Pierce, Mary
Kuh, Diana
Mishra, Gita D.
author_sort Silverwood, Richard J.
collection PubMed
description The authors aimed to describe how longitudinal patterns of physical activity during mid-adulthood (ages 31–53 years) can be characterized using latent class analysis in a population-based birth cohort study, the Medical Research Council’s 1946 National Survey of Health and Development. Three different types of physical activity—walking, cycling, and leisure-time physical activity—were analyzed separately using self-reported data collected from questionnaires between 1977 and 1999; 3,847 study members were included in the analysis for one or more types of activity. Patterns of activity differed by sex, so stratified analyses were conducted. Two walking latent classes were identified representing low (52.8% of males in the cohort, 33.5% of females) and high (47.2%, 66.5%) levels of activity. Similar low (91.4%, 82.1%) and high (8.6%, 17.9%) classes were found for cycling, while 3 classes were identified for leisure-time physical activity: “low activity” (46.2%, 48.2%), “sports and leisure activity” (31.0%, 35.3%), and “gardening and do-it-yourself activities” (22.8%, 16.5%). The classes were reasonably or very well separated, with the exception of walking in females. Latent class analysis was found to be a useful tool for characterizing longitudinal patterns of physical activity, even when the measurement instrument differs slightly across ages, which added value in comparison with observed activity at a single age.
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spelling pubmed-32762962012-02-09 Characterizing Longitudinal Patterns of Physical Activity in Mid-Adulthood Using Latent Class Analysis: Results From a Prospective Cohort Study Silverwood, Richard J. Nitsch, Dorothea Pierce, Mary Kuh, Diana Mishra, Gita D. Am J Epidemiol Practice of Epidemiology The authors aimed to describe how longitudinal patterns of physical activity during mid-adulthood (ages 31–53 years) can be characterized using latent class analysis in a population-based birth cohort study, the Medical Research Council’s 1946 National Survey of Health and Development. Three different types of physical activity—walking, cycling, and leisure-time physical activity—were analyzed separately using self-reported data collected from questionnaires between 1977 and 1999; 3,847 study members were included in the analysis for one or more types of activity. Patterns of activity differed by sex, so stratified analyses were conducted. Two walking latent classes were identified representing low (52.8% of males in the cohort, 33.5% of females) and high (47.2%, 66.5%) levels of activity. Similar low (91.4%, 82.1%) and high (8.6%, 17.9%) classes were found for cycling, while 3 classes were identified for leisure-time physical activity: “low activity” (46.2%, 48.2%), “sports and leisure activity” (31.0%, 35.3%), and “gardening and do-it-yourself activities” (22.8%, 16.5%). The classes were reasonably or very well separated, with the exception of walking in females. Latent class analysis was found to be a useful tool for characterizing longitudinal patterns of physical activity, even when the measurement instrument differs slightly across ages, which added value in comparison with observed activity at a single age. Oxford University Press 2011-12-15 2011-11-10 /pmc/articles/PMC3276296/ /pubmed/22074812 http://dx.doi.org/10.1093/aje/kwr266 Text en American Journal of Epidemiology © The Author 2011. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. http://creativecommons.org/licenses/by-nc/3.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Practice of Epidemiology
Silverwood, Richard J.
Nitsch, Dorothea
Pierce, Mary
Kuh, Diana
Mishra, Gita D.
Characterizing Longitudinal Patterns of Physical Activity in Mid-Adulthood Using Latent Class Analysis: Results From a Prospective Cohort Study
title Characterizing Longitudinal Patterns of Physical Activity in Mid-Adulthood Using Latent Class Analysis: Results From a Prospective Cohort Study
title_full Characterizing Longitudinal Patterns of Physical Activity in Mid-Adulthood Using Latent Class Analysis: Results From a Prospective Cohort Study
title_fullStr Characterizing Longitudinal Patterns of Physical Activity in Mid-Adulthood Using Latent Class Analysis: Results From a Prospective Cohort Study
title_full_unstemmed Characterizing Longitudinal Patterns of Physical Activity in Mid-Adulthood Using Latent Class Analysis: Results From a Prospective Cohort Study
title_short Characterizing Longitudinal Patterns of Physical Activity in Mid-Adulthood Using Latent Class Analysis: Results From a Prospective Cohort Study
title_sort characterizing longitudinal patterns of physical activity in mid-adulthood using latent class analysis: results from a prospective cohort study
topic Practice of Epidemiology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3276296/
https://www.ncbi.nlm.nih.gov/pubmed/22074812
http://dx.doi.org/10.1093/aje/kwr266
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