Using the 2011 and 2015 waves of the China Health and Retirement Longitudinal Study (CHARLS) linked with the 2014 CHARLS Life History Survey, we provide a comprehensive analysis on inequality of opportunity (IOp) in both body mass index (BMI) and waist circumference (WC) among middle-aged and...

We present a comprehensive analysis of ex ante inequality of opportunity (IOp) in health among Chinese adults aged 60+ and decompose the contributions of different sets of circumstances. Data are drawn from the 2011 and 2015 waves of the China Health and Retirement Longitudinal Study (CHARLS)...

Using nine waves of data from Understanding Society (UKHLS), we study the expansion of higher education in the UK, since the landmark Robbins Report in 1963, and its consequences for levels of and inequalities in household income, physical and mental health. We estimate fixed effects models...

We measure unfair health inequality in the UK using a novel data-driven empirical approach. We explain health variability as the result of circumstances beyond individual control and health-related behaviours. We do this using model-based recursive partitioning, a supervised machine learning...

Using monthly data from the Understanding Society (UKHLS) COVID-19 Survey we analyse the evolution of unmet need and assess how the UK health care system performed against the norm of horizontal equity in health care access during the first wave of COVID-19 wave. Unmet need was most evident for...

We use data from the UK Household Longitudinal Study (UKHLS) to compare measures of socioeconomic inequality in psychological distress, measured by the General Health Questionnaire (GHQ), before (Waves 9 and the Interim 2019 Wave) and during the first wave of the COVID-19 pandemic (April to July...

This paper extends the earlier work of Davillas and Jones (2021) on socioeconomic inequality in mental health, measured by the General Health Questionnaire (GHQ), to include the second national lockdown up to March 2021.