European Journal of Public Health

Urban mobility may provide insight into population health by capturing how residents connect to services, resources, and urban systems. This is relevant for communities facing higher disease burden and limited resources, where reduced connectivity may signal barriers to care, healthy environments, and participation. Mobility patterns are furthermore shaped by socioeconomic position, housing, environmental quality, facilities access, lifestyle patterns, and population composition. Mobility-health associations may therefore reflect underlying social and environmental disadvantage rather than mobility itself, risking misdirected public-health policy responses. This ecological cross-sectional study examined associations between aggregated mobile phone-based mobility and health outcomes in The Hague, Netherlands, from January-July 2019. Mobile phone mobility was measured as mean outgoing mobility distance across eight regions. Contextual and health indicators were available at neighbourhood-level and were aggregated or linked to regions where required. Health outcomes were operationalised as indicators of disease burden, including cardiometabolic medication prescriptions, polypharmacy, and a syndemic-based measure of interacting health conditions. Contextual domains were selected using spatial clustering and ordinary least squares models, after which residual mobility-health associations were assessed. Outgoing mobility varied across regions and was strongly patterned by contextual factors. Lifestyle, housing, physical environment, and income accounted for 73.2% of variance in outgoing mobility. After adjustment, residual mobility showed weak, non-significant associations with cardiometabolic medication prescription, polypharmacy, and the syndemic-based measure. Sensitivity analyses supported these findings. Aggregated mobility should not be interpreted as a straightforward independent determinant of health. Instead, it appears to function as an integrative marker of urban context, spatial structure, and population composition.

The analysis uses a global 2010-2023 panel comprising 3,038 economy-years across 217 economies. It explicitly separates between-economy and within-economy estimands and tests the longitudinal interpretation using an identical-sample temporal analysis with cluster-aware coefficient contrasts, a formal isometric log-ratio sensitivity analysis, independent fixed-effects replication, and wild-cluster-bootstrap inference. The central finding is deliberately calibrated: cross-economy agreement cannot validate national sugar availability for longitudinal obesity surveillance. The study identifies temporal and construct instability without claiming that sugar is protective or that the mechanisms producing the instability have been identified. The manuscript aligns well with PLOS ONEs emphasis on technically sound, transparent and reproducible research of broad relevance. All data required to reproduce the findings, complete metadata, executable code, full-precision results, diagnostic outputs and a completed STROBE checklist are provided as S1-S5. Figures are provided separately as compliant 350-dpi TIFF files. The study used only publicly available, aggregated economy-year statistics and involved no individual participants, identifiable information or biological specimens; institutional ethics review and consent were therefore not required. This is original work; it is not under consideration elsewhere, and the sole author has approved the submission and accepts responsibility for its content. Funding and competing-interest declarations will be entered accurately in the submission portal. An Academic Editor with expertise in nutritional epidemiology, global health metrics, longitudinal panel methods, or food-system surveillance would be well placed to assess the work.

Aim: Neighbourhood food outlet availability influences dietary behaviours and nutrition related health outcomes. However, food environment research across Europe remains limited by inconsistent spatial data, heterogenous food outlet classifications, and the lack of publicly available high-resolution retail food data. We developed and evaluated a scalable framework to acquire, classify, validate, and analyse food-related points of interest (POIs) from Google Maps across 39 countries in Europe and Turkey. We also developed a method for characterizing the joint co-occurrence of multiple outlet types as neighbourhood-level food environment exposures. Methods: We harmonized ~3.26 million food-related POIs. Outlets were classified into five main categories (cafes and bakeries, restaurants, fast-food and snack outlets, groceries and food retail, and bars and pubs) and 25 subcategories. We assessed data quality against official registers in five regions (the Netherlands, United Kingdom, Denmark, Madrid (Spain), and Brno (Czech Republic)), testing agreement in positional accuracy, completeness, spatial clustering (Nearest Neighbour Index), and spatial density (kernel density estimation (KDE)). To enable cross-country comparisons, POIs were aggregated to national and city scales, with food outlet density calculated as outlets per 1,000 residents and standardised using z-scores. To characterize neighbourhood-level co-exposures, we applied Principal Component Analysis (PCA) followed by Latent Class Analysis (LCA) to z-standardized outlet densities across 500 m hexagonal grid cells in eight major European cities. Results: Google Maps data showed high positional accuracy, with 91% of outlets located within 30m of registry records. Completeness varied by region, while KDE comparisons showed moderate-to-strong spatial agreement with city-specific variation. PCA identified two components explaining 68.4% of the variance (PC1: 51.3%, PC2: 17.1%), with PC2 differing between cafe/bar and fast-food/supermarket densities. LCA identified four neighbourhood classes: low-access, moderate-mixed, dining-out, and high-density-mixed. Conclusion: Our harmonized high-resolution framework supports cross-national monitoring of retail food environments and spatial epidemiological research across European settings.

Background: Self reported height and weight are prone to misreporting, which can bias BMI estimates. This study identifies misreporting determinants, develops calibration equations and examines how measured, self-reported, and calibrated BMI affect estimates of obesity prevalence and socioeconomic inequalities. Methods: We analysed survey-weighted, sex stratified data from 3,404 adults (18-64 years) in the Portuguese National Food, Nutrition and Physical Activity Survey (IAN-AF 2015-2016), including self reported and measured anthropometry. Misreporting determinants were assessed using multinomial logistic regression. Calibration equations for height and weight were estimated using measured values, self-reports, age, region of residence and education level. Calibrated BMI was derived from predicted values. Obesity prevalence was estimated for each BMI assessment method (30 kg/m^2). Education, income and employment inequalities in obesity were compared across BMI methods using prevalence difference and ratio, slope index and relative indexes of inequality. Results: Height is systematically overreported and weight underreported, with misreporting increasing with age and BMI. Calibration eliminates underestimation of obesity prevalence from self-reported BMI, bringing calibrated estimates close to measured values. Regarding education-related inequalities in obesity, calibration widen disparities among women, whereas among men corrects the overestimation observed from self-reported BMI. Income and employment-inequality patterns are similar across BMI methods. Conclusions: Among Portuguese adults, the systematic and socially patterned misreport of self-reported anthropometry affects obesity prevalence and inequality estimates. Calibration based on simple sociodemographic models improves validity and equity of obesity surveillance and could be routinely integrated into national surveys to strengthen monitoring of obesity and its socioeconomic distribution.

Introduction Education is a core social determinant of health for children and adolescents. Unfortunately, academic achievement, health, and wellbeing of adolescents have decreased in many developed countries in the past decade. The purpose of the Wellbeing and Education linkages in school-aged children (WELL-ED) study is to examine associations of school absences and academic achievement with use of school-based and community-based health and social welfare services. In addition, we will assess user experiences and multi-sector services pathways of school-aged children for a better understanding of how the service system could respond to the needs of children. Methods and analysis WELL-ED is a large population-based study that combines register data on school absences and educational support from municipalities with register data on healthcare and social service use collected from wellbeing services counties in Finland. The study cohort includes all children who attended mandatory education in public schools in Southern Finland in school year 2023-2024. A smaller cohort of adolescents in school year 8 was invited to complete a user experience survey. The primary outcomes of this study are related to equity of service use. Ethics and dissemination The Regional Committee on Medical Research Ethics of the Helsinki and Uusimaa Hospital District (2803/2024) has approved the WELL-ED study protocol. For the survey, adolescents in year 8 and parents of adolescents younger than 15 provided informed consent. Results will be published in peer-reviewed journals, summaries will be sent to participating municipalities and wellbeing services counties and press releases will be written on key findings.

Background YouTube highlights packages are a major and growing route to football consumption, particularly among children and young people, but brand exposure within them has not been quantified. We measured unhealthy commodity brand exposure in English Premier League (EPL) and FIFA World Cup (WC) highlights. Methods We coded brand appearances lasting two or more seconds in 10 Sky Sports EPL highlights (final 10 games of the 2025/26 season) and 19 official FIFA 2026 WC highlights, recording commodity category, placement, and match moment, alongside pre-roll YouTube adverts. Data were collected between 4 June and 27 July 2026. Five highlights were double-coded (Cohen's kappa 0.85). Results Overall brand density was similar across competitions (13.1 vs 13.9 references per minute), but composition differed markedly. Unhealthy commodity branding occupied 38.0% of EPL screen time versus 18.7% at the WC, a difference driven almost entirely by gambling (32.6% vs 1.5%). Gambling appeared in every EPL package, mainly on pitchside boards and LED screens (50.4%), with front-of-shirt accounting for 27.1%. WC exposure was more evenly spread across HFSS food (13%), alcohol (4%) and trading/crypto/prediction markets (3.7%), and appeared almost exclusively pitchside. Gambling brands accounted for ten of twelve pre-roll EPL adverts (123 of 153 seconds); no gambling adverts preceded WC highlights. Conclusions Gambling dominates unhealthy commodity exposure in EPL highlights, both in-video and in pre-roll advertising. Because most appearances occur away from the front of shirt, the voluntary front-of-shirt sponsorship withdrawal will leave the majority of this exposure intact. The WC comparison shows that tighter central control of the advertising environment produces lower and more diffuse exposure, and that governments and governing bodies with such control could restrict unhealthy categories altogether.

Purpose: The Swedish Evaluation Through Follow-up study of Learning Later in Life (UGU-LIFE) was established to study the factors that shape lifelong learning and advance evidence-based means to facilitate learning in older age. Participants: UGU-LIFE builds on the Evaluation Through Follow-up (Utvardering Genom Uppfoljning, UGU, in Swedish) study, which consists of nationally representative samples of Swedish birth cohorts. The two oldest cohorts, born 1948 (N = 11,945) and 1953 (N = 9,927), were assessed at age 13 years and invited for follow-up assessments as part of UGU-LIFE in 2025 (age 72/77 years; N = 5,738). Findings to date: Data collection in childhood included a survey (on school and family conditions), cognitive tests, and school administrative data. The follow-up assessment in late adulthood included a survey (on personal and contextual factors), cognitive tests, learning tasks, and saliva sampling for DNA extraction. In addition, registry data was collected from Statistics Sweden (census), the National Board of Health and Welfare (medical records), and the Swedish National Archives (military conscription). Analysis of selectivity at follow-up showed higher retention rate among individuals with higher education and better cognitive ability in childhood, which was only partially explained by selectivity in survival. Future plans: Data collected in UGU-LIFE will be used to describe the predictors of lifelong learning, the factors that influence learning gains and engagement in learning in older age, and the mechanistic pathways through which these factors affect learning in older age. Work to add birth records and geocoding to the data is ongoing. A subsample of participants will be invited to take part in an in-depth data collection of learning an ecologically relevant task over several days. The findings will be used to design and test interventions aiming to facilitate learning in older age.

OBJECTIVE To examine parents perceptions regarding the introduction of a social media ban for children and to identify factors associated with these attitudes. METHOD A cross-sectional study was carried out in Greece in April 2026. Potential predictors of parents views on a social media ban included (a) sociodemographic variables (such as gender, age, educational attainment, and financial status), (b) social media usage patterns (number of accounts, daily usage duration, and posting frequency), and (c) level of political engagement (how often participants follow political news and discuss political issues). Outcome variables comprised parents agreement with the ban, level of awareness about its implementation, perceived necessity for additional measures, confidence in the ban effectiveness, perceived effects on children lives, and parents familiarity with digital parental control tools. RESULTS Overall, 68.0% of parents supported implementing a social media ban for children under 15. A large majority (91.8%) expressed the need for more governmental information regarding the ban. Additionally, 89.3% believed that further measures beyond the ban are required to effectively address the issue. Suggested measures included digital literacy courses in schools (86.1%), active parental involvement in digital literacy (74.6%), prohibition of inappropriate content (77.9%), reasonable parental limits on social media use (73.8%), and restriction of addictive platform features (73.0%). Older parents demonstrated greater confidence in the effectiveness of the ban. Furthermore, age, financial status, number of social media accounts, and time spent online were positively associated with perceived impacts of the ban. Younger age was linked to greater parental familiarity with digital control tools, while having more social media accounts was also positively associated with such familiarity. CONCLUSIONS There is a clear need for comprehensive, evidence-based policy approaches that combine regulation, education, and shared responsibility among stakeholders. Policymakers should leverage existing public support for child protection while investing in digital literacy initiatives, empowering parents, and strengthening regulatory oversight of social media platforms to achieve long-term and equitable results.

Importance: Oral healthcare is often financed outside universal medical coverage, leaving working-age adults exposed to out-of-pocket costs. People with long-term disability may face added financial, physical, and service barriers to care, but longitudinal evidence on disability and oral healthcare unaffordability is limited. Objective: To estimate the effect of time-varying long-term disability on oral healthcare unaffordability among working-age adults in Australia. Design: Longitudinal cohort study using Household, Income and Labour Dynamics in Australia survey data from waves 18 to 22 (2018-2022), analysed with targeted maximum likelihood estimation for longitudinal modified treatment policies. Setting: Nationally representative household panel survey in Australia. Participants: Adults aged 25 to 65 years at wave 18 who could validly contribute to the longitudinal analysis (identified using HILDA longitudinal weights) and had complete baseline covariate data. Exposure: Time-varying self-reported disability at waves 18 to 21 (2018-2022), defined as any long-term health condition, impairment, or disability restricting everyday activities and lasting, or likely to last, for at least 6 months. Hypothetical interventions comprised 50% and 25% reductions in the odds of disability at each wave, and deterministic sustained disability and no disability regimes. Main Outcome and Measure: Self-reported avoidance of dental treatment because of cost at wave 22 (2022). Results: The analytic sample included 9635 adults; 4901 (50.9%) were female, mean age was 44 (SD=12) years, and 2419 (25.1%) reported disability at baseline. A total of 399 participants (4.1%) reported oral healthcare unaffordable at wave 22 follow-up. Compared with the natural course, sustained disability increased the risk of unaffordability (risk ratio [RR], 1.60; 95% CI, 1.15-2.22). No disability at any time point reduced the risk (RR, 0.59; 95% CI, 0.45-0.77). Reducing the odds of disability by 50% and 25% also reduced the risk of oral healthcare unaffordability by 28% (RR, 0.72; 95% CI, 0.65-0.81) and 17% (RR, 0.83; 95% CI, 0.78-0.89), respectively. Conclusions and Relevance: Under the study assumptions, long-term disability was estimated to increase experienced unaffordability of oral healthcare among working-age Australians. Population level policy responses should address both the upstream conditions that shape disability trajectories and the downstream exclusion of adult dental care from routine financial protection.

The COVID-19 pandemic and pandemic response may have long-term consequences. The cumulative impact may be better appraised when post-pandemic years are also considered. For 38 populations with reliable death registration data, we estimated excess deaths for 2020-2025 with 4 models and granular age stratification. The Fa model compared deaths against the mean of 2017-2019. Three other trend models considered changes in mortality rates after 2003 (or after a country reached $20,000 per capita income) factoring trend-of-trends (TTa), including shrinkage (STTa), and factoring also the 2024-2025 data for trend-of-trends calculation (STTa). Slopes (weighted mean -0.58%/year in 2019) and slopes-of-slopes (weighted mean +0.106%/year-squared) for age-stratified mortality rates were highly heterogeneous across populations. On model average, 6 populations (Luxembourg, Ireland, Sweden, New Zealand, Denmark, Korea) had cumulative death deficits during 2020-2025, while another 6 (Chile, Bulgaria, Japan, Greece, USA, Italy) had >4% excess deaths. Differences across populations were more prominent during 2020-2023, while 33/38 countries had estimated death deficits in 2024-2025. Total 2020-2025 excess deaths were 1.16-2.63 million (2020-2023: 2.19-3.03 million; 2024-2025: -1.03 to -0.40 million deficit). Lack of age stratification and use of unchanged linear trends for the baseline grossly biased excess death estimates upwards. Socioeconomically more vulnerable populations had higher pandemic deaths, but a more pronounced post-pandemic death deficit. Excess death estimates require careful consideration of changing population age structure and long-term mortality trajectories. Post-pandemic death deficits, especially in more vulnerable populations, may reflect deaths of people with modest life expectancy during the pandemic with respective pay off in 2024-2025

Background: Research consistently shows that colorectal cancer (CRC) screening uptake is socially patterned; however, sociodemographic determinants are usually analysed separately, overlooking how multiple social conditions jointly shape inequalities. This also applies to policy research, where heterogeneity in screening programme effects remains underexplored. Methods: Using data from the European Health Interview Survey (2014 and 2019; n=201,214; 24 countries), we applied Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy (MAIHDA) to analyse CRC screening uptake across 72 subgroups defined by sex, education, living arrangement and employment. To assess heterogeneity in screening programme effects, we combined MAIHDA with difference-in-differences (MAIHDA-DiD). Results: MAIHDA revealed inequalities in uptake: lower- and middle-educated men, whether employed or unemployed, had the lowest uptake, whereas men and women not living alone, retired or living with disability, had the highest uptake. Lower-educated homemaker women were the only female group with below-average uptake. MAIHDA-DiD showed that programmes increased overall uptake but did not produce larger gains among groups with lower pre-intervention uptake, and therefore did not reduce inequalities. Instead, programmes generated above-average increases among groups with higher pre-intervention uptake, particularly lower- and middle-educated men and women not living alone and retired. Living arrangement explained more variation in programme effects than other factors, with individuals living alone benefiting less from the programmes. Conclusion: CRC programmes did not reduce (and may have widened) inequalities, underscoring the need for equity-focused strategies in population-based screening. By extending MAIHDA with difference-in-differences, this study introduces a novel approach for evaluating heterogeneous policy effects in public health.

Introduction: Ethnic minority populations are disproportionately affected by type 2 diabetes (T2D). We investigated ethnic differences in the risks of diabetes-related complications and mortality in the Netherlands, and identified clinical, sociodemographic and environmental determinants associated with these differences. Methods: We included 175,112 adults with T2D from the dynamic prospective primary care cohort DIAMANT. DIAMANT data were linked to national registries from Statistics Netherlands and GECCO, a database integrating geographic, environmental and contextual exposures. Ethnic differences in complications risks were estimated using Cox proportional hazards models. Potential mediating factors were explored using machine-learning-based variable selection and association decomposition approaches. Results: At baseline, mean age was 65.4 (SD 12.3) years, 46.6% were women and median T2D duration was 11.3 [IQR 7.2; 15.8] years. Substantial heterogeneity in complication risk was observed across ethnic groups compared with Dutch-origin individuals. Retinopathy risk was consistently higher across nearly all non-Dutch groups (HRs 1.37-2.37). For macrovascular complications, elevated risks were mainly observed among Surinamese and Turkish individuals, including heart failure (HR 1.30 and 1.46, respectively). In contrast, individuals of Indonesian and Moroccan origin showed similar or lower risk for most complications. Environmental exposures (e.g. air pollution, temperature) and sociodemographic factors (e.g. main benefit, household composition) accounted for a substantial attenuation of several observed associations. Discussion: Substantial ethnic differences exist in risks of T2D complications and mortality, which showed to be heterogeneous across outcomes and populations. Our findings suggest that a considerable proportion of these disparities is attributable to differences in environmental and sociodemographic context, highlighting the importance of interventions that take into account differences in environmental and socio-demographic context.

Objective. This systematic review and meta-analysis synthesised the global prevalence of overweight and obesity in people with Down syndrome (DS) across the lifespan, characterised determinants of excess adiposity, and examined associations with adverse cardiometabolic outcomes. Methods. Six databases were searched without date or language restriction. Two independent reviewers screened studies, extracted data, and assessed quality using the Joanna Briggs Institute Critical Appraisal Checklist for Prevalence Studies. Prevalence was pooled using a random-effects logit model. A pre-specified subgroup analysis by age band was conducted. Publication bias was assessed with Egger's test and certainty of evidence with Grading of Recommendations Assessment, Development and Evaluation (GRADE). Results. Twenty-six studies (7,840 individuals; 14 countries) were included. The pooled prevalence was 18% (95% CI 15-22%) in children and adolescents, 36% (95% CI 26-47%) in adults, and 30% (95% CI 20-43%) in mixed-age cohorts; the test for subgroup differences was significant. The overall pooled prevalence was 22% (95% CI 18-26%; prediction interval 7-53%; I^2 = 95.3%). No publication bias was detected (Egger's t = 0.39, p = 0.6964). DS-specific growth charts yielded estimates 14-37 percentage points lower than general-population references applied to the same cohorts. Obesity more than doubled obstructive sleep apnea risk (RR 2.4; 95% CI 1.34-4.34) and non-alcoholic fatty liver disease was present in 82% of obese versus 45% of non-obese children with DS. GRADE certainty was Moderate for prevalence estimates. Conclusions. Overweight and obesity in DS are highly prevalent, age-progressive, and substantially exceed general-population rates at every life stage. Roughly one in five people with DS is affected overall, rising to more than one in three adults. The reference chart applied is the single largest source of heterogeneity in reported estimates. Cardiometabolic surveillance, adapted lifestyle interventions, and primary prevalence research from low- and middle-income countries are the highest-priority gaps.

Background: Mass gathering events (MGEs) are associated with several public health challenges and may cause a strain on healthcare services. Literature findings on the impact of MGEs on emergency departments (EDs) are heterogeneous. Objectives: To examine shifts in ED attendance characteristics during a major sporting tournament, namely the UEFA European Football Championship 2024 held in Germany. Methods: We conducted a retrospective observational study using ED data from the Emergency Department Data Registry. We compared baseline ED attendance characteristics between the tournament and the reference period, defined as two weeks before and two weeks after the tournament, and between Germany game days and non-Germany game days. Hourly attendance patterns were analysed for all Germany games using a reference range. Results: We included data from 41 EDs, totalling 253,493 attendances during the study period. A 1.57% increase in attendance was observed during the tournament compared to the reference period, with baseline characteristics remaining similar. The median daily attendance within all EDs was slightly lower on Germany game days (4066) compared to non-Germany game days (4128). Modest changes were observed in the hourly attendance on Germany game days, most notable during the last Germany game where a decrease in attendance below the reference range extended over three hours. Conclusions: The observed shifts in ED attendance were minimal, suggesting that no major changes of public health relevance occurred in ED attendance during the tournament. We highlight the utility of using ED data for monitoring and for enhancing the understanding of the public health risks and challenges associated with MGEs.

Aim: Inequalities in diabetic foot ulcer (DFU) outcomes are driven by several factors including sociodemographic factors. This study examined the intersectional risks of ethnicity, sex, and deprivation on DFU progression, which prior research often evaluated in isolation. Methods: A retrospective cohort study (2009 - 2024) of 2,125 patients at Lancashire Teaching Hospitals Trust utilized flexible parametric survival modelling. Models assessed DFU onset, overall mortality, and post-clinic prognostic survival, adjusting for demographics and comorbidities. Results: The most deprived patients presented significantly younger (median 64 vs. 73 years). Male sex accelerated DFU onset (HR: 1.24) and increased overall mortality risk (HR: 1.14). Black patients presented older with higher comorbidity burdens but paradoxically exhibited lower overall mortality risk (HR: 0.49). Deprivation heavily impacted life expectancy as the most deprived group showed higher mortality rates (HR: 0.73) and reduced 5-year prognostic survival (48.7% vs. 59.1%). Presence of comorbidities linearly increased overall mortality risk. Furthermore, severe deprivation caused greater overall life-years lost in men (4.0) than women (2.5). Conclusions: Patient outcomes with DFU are heavily influenced by cumulative demographic and socioeconomic factors. Effective management requires accessible, holistic care that actively accommodates these complex biosocial-economic realities.

Objective: To evaluate the road safety impact arising from Scotlands 2014 reduction in the legal blood alcohol concentration (BAC) limit for drivers, and to assess whether the effect of the reform varied across different spatial contexts. Design: A quasi-experimental statistical longitudinal study using a Synthetic Difference-in-Differences (SDID) approach. Setting: Small-area panel data for Great Britain, with areas (Middle-layer Super Output Areas, MSOAs, in England and Wales and Intermediate Zones, IZs, in Scotland) classed into control and treatment groups according to whether they were exposed to Scotlands BAC reform. The control and treatment groups comprise 7088 spatial units in England and Wales and 852 spatial units in Scotland, respectively, observed over the period 2008-2019. Participants: The study primarily analyses police-reported road traffic collision data from the UK Department for Transports STATS19 system. Data were analysed at the MSOA/IZ level. This is a secondary dataset, and we therefore did not involve patients or the public in formulating the research question, determining outcome measures, or designing and conducting the study. Main Outcome Measures: The main outcome measures were log-transformed rates of total road traffic crashes, and (weekend) night-time crashes (22:00-04:00) per 100,000 population. The latter is used as a proxy measure for drunk driving. Results: Our results indicate that the reduction in the legal BAC limit led to statistically significant declines in road traffic crash rates. Aggregate estimates suggest reductions of 12.0% (95% confidence interval (CI): [-13.7%, -10.3%]) in total crashes, 15.6% (95% CI: [-20.7%, -10.2%]) in night-time crashes, and 12.4% (95% CI: [-16.7%, -7.9%]) in weekend night-time crashes. We also find substantial heterogeneity in treatment effects across spatial contexts. Effects were strongest in rural and less densely populated areas, where reductions exceeded 16% (95% CI: [-18.7%, -13.9%]) for total crashes and reached up to 29.6% (95% CI: [-35.8%, -22.8%]) for night-time and 21.4% (95% CI: [-28.3%, -13.9%]) for weekend night-time crashes. Moderate but statistically significant effects were also observed in dense urban areas, whereas effects in suburban and transitional areas were smaller and not statistically significant. Conclusions: Our analysis suggests that lowering the legal BAC limit in Scotland led to meaningful reductions in road traffic crashes, particularly during higher-risk periods and in rural areas. The findings further suggest that the effectiveness of BAC regulation may vary across local contexts, highlighting the importance of accounting for spatial heterogeneity when evaluating road safety policies.

Incidence of type 2 diabetes is increasing at ages when education, work, family, and financial transitions are taking place, yet we lack robust evidence of whether earlier treatment changes life-course outcomes and over which time span this takes place. This paper uses the medical cutoff for diabetes diagnosis (HbA1c of 6.5 percent) as a natural experiment to study the effects of diabetes treatment using electronic health records (EHR) and panel data. This paper has three main findings. First, using EHR data, we find that there is a sharp increase in the probability of both diagnosis of diabetes and prescription when the HbA1c equals 6.5 percent. Second, we find that treating diabetes reduces HbA1c levels, weight, BMI, and blood pressure and increases the amount of care received, proxied by the number of HbA1c tests. Both the diagnosis and a prescription are independently able to produce positive changes in metabolic health, although a prescription is more effective in this regard. Third, we conclude that treating diabetes does not have a significant effect on life-course outcomes for a cohort of young Americans aged 24-32, although it does result in a reduction in HbA1c levels that are seen even eight years after the intervention. Taken together, these findings suggest that receiving a diagnosis and prescription are both effective treatments for diabetes, but they do not translate to significant alterations in the lives of young adults in the medium-term.

Background: Within the VEBIS-EHR project, monthly vaccine effectiveness (VE) of COVID-19 vaccines is routinely estimated across EU/EEA countries. While VE quantifies direct protection, it does not capture the overall population benefit of vaccination campaigns in terms of severe outcomes prevented. Aim: To estimate the impact of the 2023 and 2024 autumn COVID-19 vaccination campaigns in adults aged [≥]65 years. Methods: We conducted a retrospective cohort study using electronic health records data from Belgium, Denmark, Italy, Navarre (Spain), Portugal, Norway and Sweden. Weekly numbers of averted COVID-19-related hospitalisations and deaths during the 12 months following each campaign were estimated using observed COVID-19-related events, vaccine coverage (VC) and interpolated weekly VE. Results: Across participating countries/regions, among adults aged [≥]65 years, the 2023 autumn vaccination campaign averted approximately 6,200 hospitalisations (prevented fraction [PF] 10%) compared with 2,200 (PF 12%) in 2024. Among those aged [≥]80 years, the number of averted COVID-19-related deaths was 811 (PF 13%) for the 2023 campaign and 156 (PF 12%) for the 2024 campaign. Impact varied across countries, reflecting differences in VC, vaccination timing and outcome occurrence. Conclusion: The 2023 and 2024 autumn vaccination campaigns resulted in substantially different numbers of averted COVID-19-related hospitalisations and deaths among older adults, with fewer events averted in 2024. These findings highlight that the impact of vaccination programmes depends not only on VC and VE but also on alignment between vaccination timing and periods of increased viral circulation.

Abstract Objective To describe variation in hospital costs among children with different combinations of health conditions, special educational needs or disability (SEND) and children social care (CSC) indicators. Study Setting and Design This cross-sectional study used regression analysis to test whether two-way and three-way interactions of cross-public sector service use (health, education and social care) are associated with higher hospital costs in England. Data Sources and Analytic Sample Hospital care costs between April 2022 and March 2023 for the 8.9 million children aged 5-18 years were obtained from linked administrative hospital, education or social care data in the ECHILD database. Children were classified into eight categories based on combinations of indicators of chronic health conditions, SEND or CSC. Principal Findings Over one-third (35.4%) of children had some hospital costs during the year. Average costs were 317GBP for all children and 895GBP for children with non-zero hospital costs. By age 18, few children had no indicator in any sector (35.1% of boys, 43.7% of girls) and indicators in all three sectors were not rare (7.1% of boys, 6.2% of girls). At age 5, children with indicators recorded in all three sectors had the highest hospital costs (2,952GBP for boys and 3,674GBP for girls). At age 18, males and females with indicators in all three sectors accounted for 21% and 23% of hospital costs, respectively. SEND and social care indicators without chronic health conditions were associated with only slightly higher hospital costs. Hospital costs were much higher for children with SEND if they also had a chronic health condition. Hospital costs were only higher for children with social care if they also had both a chronic health condition and SEND. Conclusions. Taking account of additional support from non-health sectors is important for understanding health sector costs. The compounding associations between use of other public sectors on health sector costs indicates scope for targeting of integrated care.

Objectives: To describe age-group differences in inability to afford dental treatment and cost related dental delay, among the US community-dwelling population. Study design: Descriptive analysis of nationally representative survey data. Methods: Using nationally representative Medical Expenditure Panel Survey data (2018-2021), we examined trends in inability to afford dental treatment and cost-related dental treatment delays across four age groups (2-17, 18-39, 40-64, [&ge;]65 years). Weighted analyses accounted for the complex survey design; statistical significance was set at p<0.001. Results: Cost-related delays declined modestly from 2018 to 2021 but remained most prevalent among adults aged 40-64 (4.8% for ages 40-64, 3.4% for ages 18- 64, 2.2% for ages>65 in 2021; p<0.001). Conclusion: Middle-aged adults seem to experience delays due to cost, underscoring the need for dental coverage to expand dental coverage for this group and to reduce their out-of-pocket costs.