Skip to main content
Key Specialties
Cardiology Diabetology Endocrinology Gastroenterology Geriatrics and Gerontology Gynecology and Obstetrics Hematology Infectious Disease Internal Medicine Nephrology Neurology Oncology Pediatrics Respiratory Medicine Rheumatology Surgery
Congress Coverage
2024 ACC Congress 2023 ESMO Congress 2023 EASD Congress 2023 ERS Congress 2023 ESC Congress
Clinical Collections
Advances in Alzheimer’s

Keynote webinar | Spotlight on medication adherence

LIVE: Thursday 27th June 2024, 18:00-19:30 (CEST)
Join our expert panel to discover why you need to understand the drivers of non-adherence in your patients, and how you can optimize medication adherence in your clinics to drastically improve patient outcomes.
ADVANCED SEARCH
Log in
Top
International Journal for Equity in Health
Published in: International Journal for Equity in Health 1/2022

Open Access 01-12-2022 | COVID-19 | Research

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

Authors: Dyah Anantalia Widyastari, Aunyarat Khanawapee, Wanisara Charoenrom, Pairoj Saonuam, Piyawat Katewongsa

Published in: International Journal for Equity in Health | Issue 1/2022

Login to get access

Abstract

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.
Literature
1.
Guthold R, Stevens GA, Riley LM, Bull FC. Worldwide trends in insufficient physical activity from 2001 to 2016: a pooled analysis of 358 population-based surveys with 1· 9 million participants. Lancet Glob Health. 2018;6(10):e1077–86.PubMedCrossRef
2.
Althoff T, Hicks JL, King AC, Delp SL, Leskovec J. Large-scale physical activity data reveal worldwide activity inequality. Nature. 2017;547(7663):336–9.PubMedPubMedCentralCrossRef
3.
Gordon-Larsen P, Nelson MC, Page P, Popkin BM. Inequality in the built environment underlies key health disparities in physical activity and obesity. Pediatrics. 2006;117(2):417–24.PubMedCrossRef
4.
Pabayo R, Fuller D, Lee EY, Horino M, Kawachi I. State-level income inequality and meeting physical activity guidelines; differential associations among US men and women. J Public Health (Oxf). 2018;40(2):229–36.CrossRef
5.
Sfm C, Van Cauwenberg J, Maenhout L, Cardon G, Lambert EV, Van Dyck D. Inequality in physical activity, global trends by income inequality and gender in adults. Int J Behav Nutr Phys Act. 2020;17(1):142.PubMedPubMedCentralCrossRef
6.
Werneck AO, Barboza LL, Araújo RHO, Oyeyemi AL, Damacena GN, Szwarcwald CL, Silva DR. Time Trends and Sociodemographic Inequalities in Physical Activity and Sedentary Behaviors Among Brazilian Adults: National Surveys from 2003 to 2019. J Phys Act Health. 2021;18(11):1332–41.PubMedCrossRef
7.
Christensen A, Bond S, McKenna J. The COVID-19 Conundrum: Keeping safe while becoming inactive. A rapid review of physical activity, sedentary behaviour, and exercise in adults by gender and age. PloS one. 2022;17(1):e0263053.PubMedPubMedCentralCrossRef
8.
Katewongsa P, Widyastari DA, Saonuam P, Haemathulin N, Wongsingha N. The effects of the COVID-19 pandemic on the physical activity of the Thai population: Evidence from Thailand’s Surveillance on Physical Activity 2020. J Sport Health Sci. 2021;10(3):341–8.
9.
Ricardo LIC, Knuth AG, Nunes BP, Hallal PC, Santos LP, Harter J, Pellegrini DdCP, Crochemore-Silva I. Inequalities in Physical Activity During the COVID-19 Pandemic: Report on 4 Consecutive Population-Based Surveys in Southern Brazil. Journal of Physical Activity and Health. 2022;1(aop):1–7.
10.
Clouston SA, Natale G, Link BG. Socioeconomic inequalities in the spread of coronavirus-19 in the United States: A examination of the emergence of social inequalities. Soc Sci Med. 2021;268: 113554.PubMedCrossRef
11.
Nie P, Ding L, Chen Z, Liu S, Zhang Q, Shi Z, Wang L, Xue H, Liu GG, Wang Y. Income-related health inequality among Chinese adults during the COVID-19 pandemic: evidence based on an online survey. International journal for equity in health. 2021;20(1):1–13.CrossRef
12.
Katewongsa P, Potharin D, Rasri N, Palakai R, Widyastari DA. The Effect of Containment Measures during the Covid-19 Pandemic to Sedentary Behavior of Thai Adults: Evidence from Thailand’s Surveillance on Physical Activity 2019–2020. Int J Environ Res Public Health. 2021;18(9):4467.PubMedPubMedCentralCrossRef
13.
WHO: Fair Play: Building a strong physical activity system for more active people. Geneva: WHO; 2021.
14.
Colley RC, Butler G, Garriguet D, Prince SA, Roberts KC. Comparison of self-reported and accelerometer-measured physical activity in Canadian adults. Health Rep. 2018;29(12):3–15.PubMed
15.
Guthold R, Stevens GA, Riley LM, Bull FC. Global trends in insufficient physical activity among adolescents: a pooled analysis of 298 population-based surveys with 1· 6 million participants. The Lancet Child & Adolescent Health. 2020;4(1):23–35.CrossRef
16.
Ferrari G, Dulgheroff PT, Claro RM, Rezende LFM, Azeredo CM. Socioeconomic inequalities in physical activity in Brazil: a pooled cross-sectional analysis from 2013 to 2019. Int J Equity Health. 2021;20(1):188.PubMedPubMedCentralCrossRef
17.
Smith RA, Schneider PP, Cosulich R, Quirk H, Bullas AM, Haake SJ, Goyder E. Socioeconomic inequalities in distance to and participation in a community-based running and walking activity: A longitudinal ecological study of parkrun 2010 to 2019. Health Place. 2021;71: 102626.PubMedPubMedCentralCrossRef
18.
Vega-Salas MJ, Caro P, Johnson L, Armstrong MEG, Papadaki A. Socioeconomic Inequalities in Physical Activity and Sedentary Behaviour among the Chilean Population: A Systematic Review of Observational Studies. Int J Environ Res Public Health. 2021;18(18):9722.PubMedPubMedCentralCrossRef
19.
Katewongsa P, Yousomboon C, Haemathulin N, Rasri N, Widyastari DA. Prevalence of sufficient MVPA among Thai adults: pooled panel data analysis from Thailand’s surveillance on physical activity 2012–2019. BMC Public Health. 2021;21(1):1–12.CrossRef
20.
Liangruenrom N, Craike M, Biddle SJ, Suttikasem K, Pedisic Z. Correlates of physical activity and sedentary behaviour in the Thai population: a systematic review. BMC Public Health. 2019;19(1):1–26.CrossRef
21.
Katewongsa P, Widyastari DA, Choolers P, Iamyaem W. ’Does the community use the built environment?’Assessing the utilization of healthy space model in bridging physical activity inequalities for the Thai population. Human Geographies. 2020;14(1):107–23.
22.
23.
Champernowne DG, Cowell FA. Economic inequality and income distribution. Cambridge: Cambridge University Press; 1998.
24.
Campano F, Salvatore D. Income Distribution: Includes CD. New York: Oxford University Press; 2006.
25.
Gold R, Kawachi I, Kennedy BP, Lynch JW, Connell FA. Ecological analysis of teen birth rates: association with community income and income inequality. Matern Child Health J. 2001;5(3):161–7.PubMedCrossRef
26.
Dagum C. Decomposition and interpretation of Gini and the generalized entropy inequality measures. Statistica (Bologna). 1997;57(3):295–308.
27.
Atkinson AB, Micklewright J, Micklewright M. Economic transformation in Eastern Europe and the distribution of income. Cambridge: Cambridge University Press; 1992.
28.
Pabayo R, Fuller D, Lee EY, Horino M, Kawachi I. State-level income inequality and meeting physical activity guidelines; differential associations among US men and women. J Public Health. 2018;40(2):229–36.CrossRef
29.
Manyanga T, Barnes JD, Abdeta C, Adeniyi AF, Bhawra J, Draper CE, Katapally TR, Khan A, Lambert E, Makaza D. Indicators of physical activity among children and youth in 9 countries with low to medium human development indices: a global matrix 3.0 paper. Journal of Physical Activity and Health. 2018;15(s2):S274–83.
30.
Sugiyama T, Cole R, Koohsari MJ, Kynn M, Sallis JF, Owen N. Associations of local-area walkability with disparities in residents’ walking and car use. Prev Med. 2019;120:126–30.
31.
Chen Y, Ge Y, Yang G, Wu Z, Du Y, Mao F, Liu S, Xu R, Qu Z, Xu B, et al. Inequalities of urban green space area and ecosystem services along urban center-edge gradients. Landsc Urban Plan. 2022;217: 104266.CrossRef
32.
Chaput JP, Barnes JD, Tremblay MS, Fogelholm M, Hu G, Lambert E, Maher C, Maia J, Olds T, Onywera V. Inequality in physical activity, sedentary behaviour, sleep duration and risk of obesity in children: a 12-country study. Obes Sci Pract. 2018;4(3):229–37.PubMedCrossRef
33.
Hunter RF, Boeri M, Tully MA, Donnelly P, Kee F. Addressing inequalities in physical activity participation: implications for public health policy and practice. Prev Med. 2015;72:64–9.PubMedCrossRef
34.
Hirata RP, Oliveira JM, Schneider LP, Bertoche MP, Rodrigues LAL, Rodrigues A, Mantoani LC, Hernandes NA, Pitta F, Furlanetto KC. The Gini Coefficient: A New Approach to Assess Physical Activity Inequality in COPD. COPD. 2020;17(6):623–6.PubMedCrossRef
35.
Kothari CR. Research methodology: Methods and techniques. New Delhi: New Age International; 2004.
36.
Armstrong T, Bull F. Development of the world health organization global physical activity questionnaire (GPAQ). J Public Health. 2006;14(2):66–70.CrossRef
37.
Bland JM, Altman DG. Statistical methods for assessing agreement between two methods of clinical measurement. Int J Nurs Stud. 2010;47(8):931–6.CrossRef
38.
Bull FC, Al-Ansari SS, Biddle S, Borodulin K, Buman MP, Cardon G, Carty C, Chaput J-P, Chastin S, Chou R. World Health Organization 2020 guidelines on physical activity and sedentary behaviour. Br J Sports Med. 2020;54(24):1451–62.PubMedCrossRef
39.
Dorfman R: A formula for the Gini coefficient. Rev Econ Stat. 1979;61(1):146–9.
40.
Jian J, Jianxiang W, Xiaoyi M, Yuding W, Renyong L. Equality of medical health resource allocation in China based on the Gini coefficient method. Iran J Public Health. 2015;44(4):445.
41.
42.
Martin A, Markhvida M, Hallegatte S, Walsh B. Socio-economic impacts of COVID-19 on household consumption and poverty. Economics of disasters and climate change. 2020;4(3):453–79.PubMedPubMedCentralCrossRef
43.
Celik B, Ozden K, Dane S. The effects of COVID-19 pandemic outbreak on the household economy. Journal of Research in Medical and Dental Science. 2020;8(4):51–6.
44.
Notthoff N, Reisch P, Gerstorf D. Individual characteristics and physical activity in older adults: a systematic review. Gerontology. 2017;63(5):443–59.PubMedCrossRef
45.
Lindsay Smith G, Banting L, Eime R, O’Sullivan G, Van Uffelen JG. The association between social support and physical activity in older adults: a systematic review. Int J Behav Nutr Phys Act. 2017;14(1):1–21.CrossRef
46.
47.
Levin AT, Hanage WP, Owusu-Boaitey N, Cochran KB, Walsh SP, Meyerowitz-Katz G. Assessing the age specificity of infection fatality rates for COVID-19: systematic review, meta-analysis, and public policy implications. Eur J Epidemiol. 2020;35(12):1123–38.PubMedPubMedCentralCrossRef
48.
Armstrong S, Wong CA, Perrin E, Page S, Sibley L, Skinner A. Association of physical activity with income, race/ethnicity, and sex among adolescents and young adults in the United States: findings from the National Health and Nutrition Examination Survey, 2007–2016. JAMA Pediatr. 2018;172(8):732–40.PubMedPubMedCentralCrossRef
49.
Lai KY, Webster C, Kumari S, Sarkar C. The nature of cities and the Covid-19 pandemic. Current Opinion in Environmental Sustainability. 2020;46:27–31.PubMedPubMedCentralCrossRef
50.
Saebu M: Physical disability and physical activity: A review of the literature on correlates and associations. Eur J Adapt Phys Act. 2010;3(2):37–55.
51.
Manaf H. Barriers to participation in physical activity and exercise among middle-aged and elderly individuals. Singapore Med J. 2013;54(10):581–6.PubMedCrossRef
52.
Desveaux L, Goldstein R, Mathur S, Brooks D. Barriers to physical activity following rehabilitation: Perspectives of older adults with chronic disease. J Aging Phys Act. 2016;24(2):223–33.PubMedCrossRef
53.
Hunt ER, Papathomas A. Being physically active through chronic illness: life experiences of people with arthritis. Qualitative Research in Sport, Exercise and Health. 2020;12(2):242–55.CrossRef
54.
Nelson K, Lohsoonthorn V, Williams MA. Preterm delivery risk in relation to maternal occupational and leisure time physical activity among Thai women. Asian biomedicine: research, reviews and news. 2009;3(3):267.
Metadata
Title
Refining index to measure physical activity inequality: which group of the population is the most vulnerable?
Authors
Dyah Anantalia Widyastari
Aunyarat Khanawapee
Wanisara Charoenrom
Pairoj Saonuam
Piyawat Katewongsa
Publication date
01-12-2022
Publisher
BioMed Central
Keyword
COVID-19
Published in
International Journal for Equity in Health / Issue 1/2022
Electronic ISSN: 1475-9276
DOI
https://doi.org/10.1186/s12939-022-01725-1

Other articles of this Issue 1/2022

International Journal for Equity in Health 1/2022 Go to the issue

Review

Challenges to the right to health in sub-Saharan Africa: reflections on inequities in access to dialysis for patients with end-stage kidney failure

Research

Experiences of living with type 2 diabetes in Pakistan: the role of culture and family in physical activity

Research

Qualitative modelling of social determinants of health using group model building: the case of debt, poverty, and health

Research

Assessing equity in health, wealth, and civic engagement: a nationally representative survey, United States, 2020

Review

How does informal employment affect health and health equity? Emerging gaps in research from a scoping review and modified e-Delphi survey

Research

COVID-19 impact on mental health, healthcare access and social wellbeing – a black community needs assessment