Inequality in mortality between Black and White Americans by age, place, and cause and in comparison to Europe, 1990 to 2018.

Although there is a large gap between Black and White American life expectancies, the gap fell 48.9% between 1990 and 2018, mainly due to mortality declines among Black Americans. We examine age-specific mortality trends and racial gaps in life expectancy in high- and low-income US areas and with reference to six European countries. Inequalities in life expectancy are starker in the United States than in Europe. In 1990, White Americans and Europeans in high-income areas had similar overall life expectancy, while life expectancy for White Americans in low-income areas was lower. However, since then, even high-income White Americans have lost ground relative to Europeans. Meanwhile, the gap in life expectancy between Black Americans and Europeans decreased by 8.3%. Black American life expectancy increased more than White American life expectancy in all US areas, but improvements in lower-income areas had the greatest impact on the racial life expectancy gap. The causes that contributed the most to Black Americans' mortality reductions included cancer, homicide, HIV, and causes originating in the fetal or infant period. Life expectancy for both Black and White Americans plateaued or slightly declined after 2012, but this stalling was most evident among Black Americans even prior to the COVID-19 pandemic. If improvements had continued at the 1990 to 2012 rate, the racial gap in life expectancy would have closed by 2036. European life expectancy also stalled after 2014. Still, the comparison with Europe suggests that mortality rates of both Black and White Americans could fall much further across all ages and in both high-income and low-income areas.

Age specific trends in mortality disparities by socio-economic deprivation in small geographical areas of England, 2002-2018: A retrospective registry study.

BACKGROUND: Disparities in mortality rates according to socioeconomic position (SEP) have been rising in England. We describe the association between recent changes in socioeconomic inequality and trends in mortality disparities for different age and sex groups at small-area level in England. METHODS: Vital registration data from the Office for National Statistics on resident population size and number of deaths in each Lower Super Output Area (LSOA) in England from 2002 to 2018 were stratified by sex and 5-year age group. We grouped LSOA into ventiles of the Index of Multiple Deprivation (IMD), our indicator of SEP. We examined time trends in smoothed mortality rates, using 3 year moving averages for the period 2003-2017, by age across the IMD distribution. We measured mortality inequalities using the ratio of mortality rates between different deprivation groups. We calculated mortality rate ratios between the most and the least deprived 10% of areas (Total Inequality) and between the median and least deprived (Lower Inequality) 10% of areas by year, gender and age group, to examine where in the distribution of deprivation trends in mortality inequality arose. FINDINGS: Among <1 year olds, the inequality in mortality rates between the poorest 10% of LSOAs and the richest 10% of LSOAs fell between 2003 and 2017 by 22•7% for men and 22•8% for women. The largest inequalities were observed among 40 to 54 year olds. This inequality increased over the study period - from 3•2 times higher mortality rates for men in the most as opposed to the least deprived 10% of LSOAs in 2003 to 3•3 times in 2017. The rise was from 2•4 to 2•6 for women. Age groups ≥65 years, who experience the highest mortality risk, had low but rising inequality. Men and women aged 65 to 79 living in the most deprived LSOAs had a mortality rate 1•9 times higher than the least deprived in 2003 but this had increased to 2•2 times higher for women and 2•3 times higher for men by 2017. This was due to rising inequality in both halves of the distribution - between the top 10% of LSOA and the middle, and between the middle and the bottom 10% of LSOA. INTERPRETATION: Overall mortality inequality rose in England but there were substantial differences in the trends for specific age and sex groups. Infant and child mortality inequality fell. At older ages, mortality inequality rose across cohorts, although in different ways, as each cohort's exposure to life-course to labour market inequality has differed. Policy goals of reducing mortality inequality will be best met by a focus on the risk factors that are specific to particular age and deprivation groups. FUNDING: Economic and Social Research Council, through the ESRC Centre for the Microeconomic Analysis of Public Policy at the IFS. We gratefully acknowledge the support of the Nuffield Foundation, grant reference WEL/43603. The project has been funded by the Nuffield Foundation, but the views expressed are those of the authors and not necessarily the Foundation. Visit www.nuffieldfoundation.org. Research at UCL Great Ormond Street Institute of Child Health is supported by the NIHR Great Ormond Street Hospital Biomedical Research Centre.

Inequalities in Children's Experiences of Home Learning during the COVID-19 Lockdown in England.

This paper combines novel data on the time use, home-learning practices and economic circumstances of families with children during the COVID-19 lockdown with pre-lockdown data from the UK Time Use Survey to characterise the time use of children and how it changed during lockdown, and to gauge the extent to which changes in time use and learning practices during this period are likely to reinforce the already large gaps in educational attainment between children from poorer and better-off families. We find considerable heterogeneity in children's learning experiences - amount of time spent learning, activities undertaken during this time and availability of resources to support learning. Concerningly, but perhaps unsurprisingly, this heterogeneity is strongly associated with family income and in some instances more so than before lockdown. Furthermore, our analysis suggests that any impacts of inequalities in time spent learning between poorer and richer children are likely to be compounded by inequalities not only in learning resources available at home, but also in those provided by schools.