ArticlePopulation health metrics2024
Enabling the examination of long-term mortality trends by educational level for England and Wales in a time-consistent and internationally comparable manner.
Article in Population health metrics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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5 citing papers in PubMed.
- New insights into inequalities in life expectancy and mortality: evidence from an Individual-level Socio-Economic Index (ISEI) in Australia.Population health metrics · 2026Article
- The contribution of education-specific mortality trends to the life expectancy stagnation in England & Wales.European journal of epidemiology · 2025Article
- Improving the validity of estimates of mortality inequalities by education in England & Wales.Population health metrics · 2025Article
- Trends in educational inequalities in obesity-attributable mortality in England and Wales, Finland, and Italy.Obesity (Silver Spring, Md.) · 2025Article
- Long-term trends in educational inequalities in alcohol-attributable mortality, and their impact on trends in educational inequalities in life expectancy.Frontiers in public health · 2024Article
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Abstract
backgroundStudying long-term trends in educational inequalities in health is important for monitoring and policy evaluation. Data issues regarding the allocation of people to educational groups hamper the study and international comparison of educational inequalities in mortality. For the UK, this has been acknowledged, but no satisfactory solution has been proposed.
objectiveTo enable the examination of long-term mortality trends by educational level for England and Wales (E&W) in a time-consistent and internationally comparable manner, we propose and implement an approach to deal with the data issues regarding mortality data by educational level.
methodsWe employed 10-year follow-ups of individuals aged 20+ from the Office for National Statistics Longitudinal Study (ONS-LS), which include education information from each decennial census (1971-2011) linked to individual death records, for a 1% representative sample of the E&W population. We assigned the individual cohort data to single ages and calendar years, and subsequently obtained aggregate all-cause mortality data by education, sex, age (30+), and year (1972-2017). Our data adjustment approach optimised the available education information at the individual level, and adjusts-at the aggregate level-for trend discontinuities related to the identified data issues, and for differences with country-level mortality data for the total population.
resultsThe approach resulted in (1) a time-consistent and internationally comparable categorisation of educational attainment into the low, middle, and high educated; (2) the adjustment of identified data-quality related discontinuities in the trends over time in the share of personyears and deaths by educational level, and in the crude and the age-standardised death rate by and across educational levels; (3) complete mortality data by education for ONS-LS members aged 30+ in 1972-2017 which aligns with country-level mortality data for the total population; and (4) the estimation of inequality measures using established methods. For those aged 30+ , both absolute and relative educational inequalities in mortality first increased and subsequently decreased.
conclusionWe obtained additional insights into long-term trends in educational inequalities in mortality in E&W, and illustrated the potential effects of different data issues. We recommend the use of (part of) the proposed approach in other contexts.
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