Luke Munford

Background: Socio-spatial health inequalities are increasing in England, as in many other high-income countries. While most research focuses on inequalities between the extreme ends of the deprivation continuum, a less recognised but critical pattern is that the largest gap within the socio-spatial gradient occurs at its lower end - between the two most deprived fifths. Our aim was to understand the drivers of this gap. Methods: Using aggregate-level data from official national statistics for a period 2015–2022 and Blinder–Oaxaca decomposition, we provide the first empirical examination of the contributors to the life expectancy gap between the most and second most deprived fifths of local authorities in England and compare these findings with the more conventional comparison between the most and least deprived areas. We assess the relative contributions of material, behavioural, psychosocial, and political economy factors. Results: We find that household income accounts for around a third of the life expectancy gap between the two most deprived fifths of local authorities for both men and women (30% and 35%, respectively). It contributes more to inequality at the bottom end of the socio-spatial distribution than between the most and least deprived local authorities. Welfare benefit losses are the next greatest contributor. Conclusion: Household income and welfare benefit losses were the strongest contributors to life expectancy inequalities between the two most deprived fifths of local authorities, highlighting the importance of income and wider political economy determinants of health inequalities.

Universal Credit, one of the most significant welfare reforms in the UK in recent decades, was de- signed to simplify the benefit system and strengthen work incentives by consolidating six means- tested programmes into a single payment. We evaluate its short-term economic impacts using two complementary strategies. First, exploiting the phased geographical introduction of Univer- sal Credit across Local Authority Districts in England between 2013 and 2018, we implement a difference-in-differences design using district-level administrative data on economic activity and employment rates, weighting districts by their baseline working-age population. Second, we use individual-level panel data from the UK Household Longitudinal Study to estimate the differen- tial effect of unemployment under Universal Credit relative to the legacy system on employment, hours worked and income. At the district level, the estimated effects are small and not statis- tically significant, at −0.13 percentage points for economic activity and 0.21 for employment. At the individual level, previously unemployed individuals in areas that had introduced Uni- versal Credit experience a statistically significant reduction in monthly income of approximately 7.7%. The penalty reflects lower earnings that the benefit system does not offset, and it is not accompanied by improvements in employment or hours worked. Set alongside existing evidence on the adverse mental-health consequences of the reform, Universal Credit delivered no measur- able short-term economic gains while coinciding with declines in income security and population mental health.

Background: Policy models increasingly guide policy decision‐making. Incorporating public and stakeholder perspectives into modelling processes can produce evidence that is more relevant, appropriate and acceptable to the public. However, public and stakeholder involvement (PSI) in modelling studies is an emerging practice in the field of health inequalities, with little guidance available to support researchers. Objective: We present a methodological reflection on a PSI process supporting development of a policy model estimating the health impacts of major income supplementation policies. We include a multi‐layered systems map, co‐developed with public and stakeholder contributors, which guided modelling strategy development. Methods: We engaged 32 people with lived experience of income insecurity and over 60 stakeholders with expertise in socio‐economic determinants of health. Perspectives were gathered through three participatory systems mapping workshops and five policy prioritisation workshops. Workshop contributions were analysed using descriptive thematic analysis. Insights were fed back to the research team, who made changes or additions to the modelling strategy. Results: We experienced successes and challenges incorporating public and stakeholder perspectives into model development, specifically: engaging people with lived experience of income insecurity; ensuring PSI settings support effective engagement; and appropriately remunerating and safeguarding public contributors. We learned the importance of breaking down methodological silos within research teams to translate rich qualitative insights into actionable modelling outputs. Conclusion: In data‐driven modelling studies, PSI requires carefully considered design, strong collaboration between team members, and appropriate resourcing to create enjoyable, productive engagement spaces where contributors can safely share experiences and expertise. Patient or Public Involvement and Engagement (PPIE) Contribution: PSI was central to this work. Our project partners at The Poverty Alliance, a third sector organisation, facilitated involvement of people with lived experience of income insecurity using their internal trauma‐informed approaches throughout all stages.

Background: England’s North–South mortality divide has resisted decades of policies. Whether the COVID-19 pandemic impacted this divide, and how trends differ by age and sex, is unclear.Methods: We conducted a segmented longitudinal population study of the North–South mortality divide in England (1981–2024). Using registered deaths and mid-year population estimates by five-year age group and sex, we calculated standardised mortality rates and estimated adjusted North–South rate ratios using within-year Poisson models. We used segmented Poisson regression to compare mortality trends between 2010–19 and 2020–24. Findings: The North–South mortality divide persisted during 1981–2024, widening among females and males aged 25–49 years. Northern excess mortality among those aged 25–49 years increased by 1·7% per year for females (IRR 1·017, 95% CI 1·013–1·022) and 1·2% per year for males (IRR 1·012, 95% CI 1·008–1·015). There was no statistically significant change in mortality trend among those aged 25–49 years during 2020–24, although excess mortality for males under 75 years rose from 2020, and the widening trend accelerated among females. By 2024, northern excess mortality reached 25·2% (under 75 years) and 39% (aged 25–49 years).Interpretation: Over the past four decades, England’s regional mortality inequalities have widened among working‑age adults – more so among females. This divide was amplified by the COVID‑19 pandemic. Reducing the North–South health divide will require sustained large-scale action across central government and regional authorities.

Introduction: There are gaps in national data on early childhood development to inform progress in closing the inequality gap and to capture the impact of the COVID-19 pandemic on children’s development in different developmental domains. This longitudinal area-level ecological study examined time trends in socioeconomic inequalities in early childhood development at 2–2.5 years in England’s local authorities between 2019 and 2025. Methods: We included 2 105 384 children from 119 upper-tier local authorities. Rates per 100 children not on track in development at 2–2.5 years, assessed on the Ages and Stages Questionnaire 3, were analysed. Area-level income deprivation was assessed using the Income Deprivation Affecting Children Index 2019, converted to the Slope Index of Inequality (SII) and Relative Index of Inequality (RII). Linear mixed-effect models assessed the fixed effects of year, year ² and income deprivation on early childhood development in any developmental domain and in communication, gross motor, fine motor, personal social or problem solving. Results: The average rate of children not on track in any developmental domain increased from 15.2 (95% CI 13.7 to 16.7) in 2019, peaking in 2023 (19.1 (17.5 to 20.7)), but with little sign of recovery by 2025 (year: 1.09 (1.05 to 1.13); year ² : 0.99 (0.99 to 1.00)). Rates for communication, personal social skills and problem solving increased more steeply than gross motor and fine motor. The most versus least income-deprived areas had worse developmental outcomes throughout the period (SII: 5.8 (4.7 to 7.0); RII: 44% (35% to 55%)), with no evidence of year x income deprivation interactions. The largest absolute inequality gap was in communication (SII: 4.7 (4.0 to 5.7); RII: 56% (46% to 72%)). Discussion: In England, early childhood development worsened during the pandemic and children born after the pandemic continue to be affected. Area-level inequalities were striking but did not worsen during this period. Pandemic-recovery efforts need to consider the potentially enormous economic and societal cost of disruption to early childhood development.

We provide new evidence on the mental health and healthcare utilisation impacts of the roll-out of Universal Credit, one of the most significant welfare reforms in Europe in recent decades. Designed to simplify the benefit system and strengthen work incentives by merging six means-tested programmes into a single payment, Universal Credit also introduced features that may adversely affect mental health. Exploiting the plausibly exogenous, staggered geographical introduction of Universal Credit across England between 2013 and 2018, we implement a difference-in-differences design using comprehensive small-area administrative data on clinically recorded mental health and related healthcare utilisation. We find adverse effects of Universal Credit exposure on population mental health: a 0.10 standard-deviation increase in clinically diagnosed depression prevalence and a 0.06 standard-deviation rise in antidepressant prescribing, alongside a smaller 0.03 standard-deviation increase in mental health-related hospital admissions and attendances. In natural units, these correspond to approximately 113,742 additional cases of diagnosed depression, 29,993 extra hospital admissions and attendances, and 1.29 million additional antidepressant prescriptions annually by 2018. Results are robust across specifications, sensitivity analyses, spatial aggregation, and alternative estimators. Because outcomes are measured at the small-area level, our estimates capture population-wide effects that combine direct impacts on Universal Credit recipients with spillovers to non-recipients. Indicative valuations imply sizeable associated quality-of-life losses and direct healthcare costs of approximately £2.84 billion per year. These findings show that welfare reforms can generate substantial mental health externalities, and that the health and healthcare-system consequences of social policy belong squarely within its design and evaluation.