Refining index to measure physical activity inequality: which group of the population is the most vulnerable?

Background: The existing body of research mostly discusses inequality in physical activity (PA) based on the difference in the level of moderate-to-vigorous physical activity (MVPA). Evidence is lacking on the quantified inequality measures (e.g., how big the inequality is, and the distribution) in...

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Main Author: Widyastari D.A.
Other Authors: Mahidol University
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Published: 2023
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Online Access:https://repository.li.mahidol.ac.th/handle/123456789/85267
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spelling th-mahidol.852672023-06-19T00:38:33Z Refining index to measure physical activity inequality: which group of the population is the most vulnerable? Widyastari D.A. Mahidol University Medicine Background: The existing body of research mostly discusses inequality in physical activity (PA) based on the difference in the level of moderate-to-vigorous physical activity (MVPA). Evidence is lacking on the quantified inequality measures (e.g., how big the inequality is, and the distribution) in order to identify the most vulnerable groups of a population. This study measured PA inequality among Thai adults by using three parameters to construct an inequality index: (1) Proportion of the population with sufficient MVPA; (2) Cumulative minutes of MVPA; and (3) The Gini coefficient. Methods: This study employed three rounds of data from Thailand’s Surveillance on Physical Activity (SPA) 2019–2021. In each round, over 6,000 individuals age 18–64 years were selected as nationally-representative samples, and were included in the analysis. PA inequality was constructed by using three parameters, with a combination of the three as the final measure, to identify the sub-groups of the Thai adults who are most vulnerable: groups with the least MVPA, highest insufficiency, and highest inequality index (Gini). Results: Covid-19 containment measures have widened the gap in PA inequality, as shown by a declining proportion of the population meeting the recommended guidelines, from 74.3% in 2019 to 56.7% in 2020 and 65.5% in 2021. PA inequality existed in all sub-populations. However, by combining three parameters, the most vulnerable groups during the Covid-19 epidemic were identified as follows: (1) Those with no income; (2) The unemployed; (3) Those who have no access to PA facilities; (4) Older adults aged 60 + years; and (5) Those earning < 3,500 baht per month. Further, residents of Bangkok, young adults aged 18–24, individuals who attained primary level education or less, those who had no exposure to a PA awareness campaign and those who have a debilitating chronic disease also had elevated risk of PA insufficiency. Conclusion: A concerning level of PA inequality existed in all sub-populations. The use of combined indicators in measuring PA inequality should aid in determining the most vulnerable groups of the population with a refined procedure. This method can be applied in many settings since the baseline data used to measure inequality (i.e., percent sufficient and cumulative minutes of MVPA) are widely available. 2023-06-18T17:38:33Z 2023-06-18T17:38:33Z 2022-12-01 Article International Journal for Equity in Health Vol.21 No.1 (2022) 10.1186/s12939-022-01725-1 14759276 36045368 2-s2.0-85137069822 https://repository.li.mahidol.ac.th/handle/123456789/85267 SCOPUS
institution Mahidol University
building Mahidol University Library
continent Asia
country Thailand
Thailand
content_provider Mahidol University Library
collection Mahidol University Institutional Repository
topic Medicine
spellingShingle Medicine
Widyastari D.A.
Refining index to measure physical activity inequality: which group of the population is the most vulnerable?
description Background: The existing body of research mostly discusses inequality in physical activity (PA) based on the difference in the level of moderate-to-vigorous physical activity (MVPA). Evidence is lacking on the quantified inequality measures (e.g., how big the inequality is, and the distribution) in order to identify the most vulnerable groups of a population. This study measured PA inequality among Thai adults by using three parameters to construct an inequality index: (1) Proportion of the population with sufficient MVPA; (2) Cumulative minutes of MVPA; and (3) The Gini coefficient. Methods: This study employed three rounds of data from Thailand’s Surveillance on Physical Activity (SPA) 2019–2021. In each round, over 6,000 individuals age 18–64 years were selected as nationally-representative samples, and were included in the analysis. PA inequality was constructed by using three parameters, with a combination of the three as the final measure, to identify the sub-groups of the Thai adults who are most vulnerable: groups with the least MVPA, highest insufficiency, and highest inequality index (Gini). Results: Covid-19 containment measures have widened the gap in PA inequality, as shown by a declining proportion of the population meeting the recommended guidelines, from 74.3% in 2019 to 56.7% in 2020 and 65.5% in 2021. PA inequality existed in all sub-populations. However, by combining three parameters, the most vulnerable groups during the Covid-19 epidemic were identified as follows: (1) Those with no income; (2) The unemployed; (3) Those who have no access to PA facilities; (4) Older adults aged 60 + years; and (5) Those earning < 3,500 baht per month. Further, residents of Bangkok, young adults aged 18–24, individuals who attained primary level education or less, those who had no exposure to a PA awareness campaign and those who have a debilitating chronic disease also had elevated risk of PA insufficiency. Conclusion: A concerning level of PA inequality existed in all sub-populations. The use of combined indicators in measuring PA inequality should aid in determining the most vulnerable groups of the population with a refined procedure. This method can be applied in many settings since the baseline data used to measure inequality (i.e., percent sufficient and cumulative minutes of MVPA) are widely available.
author2 Mahidol University
author_facet Mahidol University
Widyastari D.A.
format Article
author Widyastari D.A.
author_sort Widyastari D.A.
title Refining index to measure physical activity inequality: which group of the population is the most vulnerable?
title_short Refining index to measure physical activity inequality: which group of the population is the most vulnerable?
title_full Refining index to measure physical activity inequality: which group of the population is the most vulnerable?
title_fullStr Refining index to measure physical activity inequality: which group of the population is the most vulnerable?
title_full_unstemmed Refining index to measure physical activity inequality: which group of the population is the most vulnerable?
title_sort refining index to measure physical activity inequality: which group of the population is the most vulnerable?
publishDate 2023
url https://repository.li.mahidol.ac.th/handle/123456789/85267
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