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This paper analyses competitive balance in the “big five” women's football leagues in Asia longitudinally between 2010 and 2019.

Competitive balance has been measured using recognised measures of concentration, HICB and NHICB, alongside recognised measures of dominance, i.e., identification of top teams. A time-trend analysis has been employed to identify trends of CB in the respective leagues followed by ANOVA and relevant post-hoc tests to identify difference in concentration measures. A multiple linear regression analysis has been conducted to identify the impact of external economic factors on CB.

Some significant differences were detected in the levels of concentration between leagues. There was also some variation in terms of some leagues being dominated by a fewer number of teams. However, these two measures of competitive balance (concentration and dominance) were not necessarily correlated with each other. The paper also tries to find the optimum number of teams to maintain CB in the women's football leagues in Asia, but an exact figure could not be found.

Some significant differences were detected in the levels of concentration between leagues. There was also some variation in terms of some leagues being dominated by a fewer number of teams. However, these two measures of competitive balance (concentration and dominance) were not necessarily correlated with each other. External economic factors were found to have negative impact on CB.

The paper is an original research and aims to add to the growing body of CB research in world through analysis of competitive balance (ACB).

Migration appears to be a determinant in health-care utilisation, particularly among the elderly in India. Ageing and migration are essential socio-demographic phenomena in the 21st century for developing and developed countries to establish better public health-care policies. This study aims to focus on the status and determinants of health-care utilisation among elderly migrants who have migrated after attaining the age of 45 and above.

This study used the data from the first wave of the longitudinal ageing study in India (LASI) in 2017–2018. Two outcome variables were used to examine the health-care utilisation, including in-patient and out-patient care. Binary logistic regression was used to explore the predictors of healthcare utilisation in terms of in-patient and out-patient care among the elderly migrant population.

A total of 82.9% of elderly migrants had visited out-patient care when they were sick, whereas 15.3% have used in-patient care. Enabling factors, such as wealth quintile and health insurance, and need factor, such as chronic disease and self-rated health, were more significant factors influencing the health-care utilisation.

This study contributes to our understanding of older migrants’ health-care utilisation. Focussing on this study’s outcome, policymakers and decision makers may consider improving older migrants’ access to health-care by raising their income level, offering local health insurance and health awareness programs.