The Gini Coefficient: A New Approach to Assess Physical Activity Inequality in COPD

Inequality in Physical Activity in Organized Group Settings for Children: A Cross-Sectional Study

BACKGROUND

Adult-led organized settings for children (eg, classrooms) provide opportunities for physical activity (PA). The structure of setting time may influence inequalities (ie, unequalness) in the distribution of PA. This study examined differences in PA inequality by setting and time-segment purpose in time-segmented organized group settings for children.

METHODS

PA and setting meetings were assessed using accelerometer and video observation data from school, before-/after-school, and youth club groups (n = 30) for third- through sixth-grade children (n = 699) in 2 rural US communities. Meetings (n = 130) were time-segmented into smaller units (sessions; n = 835). Each session was assigned a purpose code (eg, PA). Accelerometer data were paired with the meetings and sessions, and the Gini coefficient quantified inequality in activity counts and moderate to vigorous PA minutes for each segment. Beta generalized estimating equations examined differences in PA inequality by setting and session purpose.

RESULTS

Activity count inequality was lowest (P < .05) during youth club meetings (Gini = 0.17, 95% CI, 0.14-0.20), and inequality in moderate to vigorous PA minutes was greatest (P < .01) during school (Gini = 0.34, 95% CI, 0.30-0.38). Organized PA sessions (Gini = 0.20, 95% CI, 0.17-0.23) had lower activity count inequality (P < .0001) than academic (Gini = 0.30, 95% CI, 0.27-0.34), enrichment (Gini = 0.31, 95% CI, 0.27-0.36), and nonactive recreation (Gini = 0.30, 95% CI, 0.25-0.34) sessions. Inequality in moderate to vigorous PA minutes was lower (P < .05) in organized PA (Gini = 0.26, 95% CI, 0.20-0.32) and free play (Gini = 0.28, 95% CI, 0.19-0.39) than other sessions.

CONCLUSIONS

PA inequality differed by setting time structure, with lower inequality during organized PA sessions. The Gini coefficient can illuminate PA inequalities in organized settings and may inform population PA improvement efforts in rural communities.

Inequality in Children's Physical Activity Across Time-Segmented Youth Sport Practice

Purpose: Youth sport (YS) is a community system for promoting children's physical activity (PA). Studies have examined mean PA during YS practices, but few have examined inequalities in the distribution of PA among children during practice time. This study examined PA inequality in time-segmented YS practices and differences in inequality by time segment characteristics. Methods: Children's PA and YS practices were examined using accelerometer and video observation data from a sample of YS teams (n = 36 teams, n = 101 practices) for third- through sixth-grade children (n = 392), approximately eight to 12 years old, in two rural U.S. communities. Practices were time-segmented into smaller units (episodes; n = 991). Episodes were assigned codes for purpose (e.g. warm-up), member arrangement (e.g. whole group), and setting demand (i.e. fosters participation, creates exclusion). Group accelerometer data were paired with episodes, and the Gini coefficient quantified inequality in activity counts and minutes of moderate-to-vigorous PA (MVPA). Beta generalized estimating equations examined the influence of episode structure on PA inequality. Results: Warm-up (Gini = 0.22), fitness (Gini = 0.24), and sport skill (Gini = 0.24) episodes had significantly lower inequality (p < .05) in activity counts than other purpose types. Management (Gini = 0.32) and strategy (Gini = 0.40) episodes had significantly greater inequality (p < .05) in MVPA minutes than other purpose types. Episodes fostering participation (Gini = 0.32) had significantly lower activity count inequality (p < .05) than episodes creating exclusion (Gini = 0.35). Conclusion: PA inequality among children during YS varied by practice structure. Metrics such as the Gini coefficient can illuminate inequalities in PA and may be useful for guiding efforts to improve population PA in children. Trial Registration: This study is registered at www.clinicaltrials.gov (Identifier: NCT03380143).

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 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.