European Journal of Public Health

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.

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.

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.

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

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.

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.

Background: Rising rates of young people Not in Education, Employment, or Training (NEET) in the UK have recently coincided with declining youth physical and mental health but no study has asked whether this reflects a growing proportion of young people with health problems (prevalence) or those with health problems becoming more likely to be NEET (penalty). Methods: Using 15 years of Understanding Society data (2009-23), we analysed 15,242 respondents aged 16-24 (66,160 observations). We employed three complementary approaches: descriptive trends, Blinder-Oaxaca-Kitagawa (BO) probit decomposition comparing 2009-2013 and 2019-2023 against a 2014-2018 reference period, and fixed-effects (FE) Poisson models with lagged health status. Exposures included self-reported health conditions or disability (SRHD), psychological distress , diagnosed conditions and socio-demographic factors. Findings: NEET rates were lowest in 2014-18 (10.5-11.5%) and higher in 2009-13 (12-15%) and 2019-23 (15-16%). Higher prevalence of SRHD, psychological distress, diagnosed depression and multimorbidity explained changes in NEET prevalence across both the 2009-13 to 2014-2018 and 2014-18 to 2019-23 periods. No change in penalty was observed for any health variable across periods, except for an increase in the penalty for SRHD between the 2009-13 to 2014-18 periods. Interpretation: Rising NEET rates among UK youth are driven largely by more young people having physical and psychological ill health. Whilst labour market and education accommodations remain important, reducing NEET rates will require reversing the decline in youth health, not just accommodating it.

Introduction: Cash transfer programs could reduce diabetes risk by decreasing chronic stress and increasing food security, physical activity, and preventive care, but there is an evidence gap on the relationship between cash transfer access and diabetes and prediabetes incidence. Methods: We used data from the Health and Ageing in Africa: Longitudinal Studies in South Africa (HAALSA) Indepth cohort of Black South Africans ages 40+ (N=5059). We fit log binomial models to estimate the relationship between household cash transfer eligibility (HCT) and cumulative incidence of diabetes and prediabetes between 2014/15 and 2021/22. We performed quantile regression to estimate change in continuous glucose values across the glucose distribution with additional HCT. Results: No association was observed between HCT and diabetes risk. Each additional unit of HCT was associated with reduced prediabetes risk [aCIR (95% CI): 0.94 (0.90, 0.98); p=0.007]. The largest reduction in glucose values associated with additional HCT was at the highest end of the glucose distribution. Discussion: Our observations suggest household cash transfer access reduces risk of prediabetes but not diabetes. However, household cash transfer access was associated with the largest decrease in glucose for the most severely glucose-impaired, implying the potential for HCT to reduce risk of hyperglycemic complications.

Background: High rates of young people who are not in education, employment or training (NEET) are a major societal concern in the UK. Whilst other studies have highlighted that adolescent health can predict NEET status in young adulthood, robust and recent longitudinal evidence remains limited. Methods: This study used data from the Millennium Cohort Study, a longitudinal study of people born in the UK in the early 2000s, to estimate the extent to which mental health conditions, physical health conditions and health behaviours during adolescence predict NEET status in early adulthood (median age: 23). Co-occurrence of exposures was also considered and population attributable fractions were calculated to account for differences in exposure prevalence. Results: Among 8,374 young people, 12.5% were NEET at age 23; approximately two thirds were seeking work and one third were economically inactive. Estimates adjusted for demographic factors indicated that multiple health exposures increased risk of being NEET at age 23, with mental health conditions predicting greater risk than physical health conditions and health behaviours. For instance, a longstanding mental health condition more than doubled the risk of being NEET (adjusted relative risk [aRR] = 2.39, 95% CIs = 1.85, 3.09), while autism (aRR = 3.60, 95% CIs = 2.69, 4.83) and ADHD (aRR = 3.25, 95% CIs = 2.38, 4.44) more than tripled the risk. A greater number of reported adolescent mental health conditions was associated with greater risk of being NEET in young adulthood. Obesity predicted being NEET at age 23 (aRR = 1.54, 95% CIs = 1.18, 2.01) and obesity accompanied by a mental health condition further increased risk (aRR = 2.01, 95% CIs = 1.38, 2.93). Follow-up analyses indicated that associations between adolescent mental health and young adult NEET status were more pronounced for females than males and for the economically inactive than those seeking work. Conclusions: Findings indicate that adolescent health, especially mental health, strongly predicts being NEET in early adulthood. Early, integrated health and education interventions may help reduce later educational and labour market disengagement.

Objectives: To examine the conformance to type 2 diabetes NICE guidelines across cardiovascular risk strata; and to quantify geographical variation in treatment pathways following the COVID-19 pandemic, encompassing guideline changes. Design: We carried out a retrospective observational study using linked electronic health records across England. Process mining, a data driven method that can reconstruct clinical treatment pathways, was applied to map 12-month treatment trajectories after treatment initiation. Conformance with NICE NG28 (2022) was quantified using a structural similarity index. Further, behavioural and entropy-based similarity (capturing treatment variability and complexity) measures were used to assess sequencing and heterogeneity of treatment. Setting: Primary and secondary care in England datasets within the National Health Service England Secure Data Environment (NHSE SDE), analysed first at national level and then across 42 Integrated Care Boards (ICBs) which are the devolved health care geographical delivery regions in England. Participants: 822,650 individuals with newly diagnosed T2DM between 1-February-2022 and 1-November-2025, stratified into low cardiovascular risk (LR-C; QRISK3<10), high risk (HR-C; QRISK3>=10 or receiving statins/blood pressure lowering treatment), and established cardiovascular disease (eCVD-C). Participants were followed for 12 months after first dispensed glucose lowering therapy. Main outcome measure: First line therapy, treatment intensification and switching within 12 months; change in glycated haemoglobin (HbA1c); quantified conformance to NICE recommended pathways; and regional variation in broader similarity measures. Results: Metformin monotherapy was the dominant initiation strategy in LR-C and HR-C cohorts (92.4% and 90.2%, respectively), whereas eCVD-C showed lower uptake of metformin (68.9%) and higher uptake of SGLT2 inhibitors (26.3%). Intensification from metformin to combination therapy was infrequent across all cohorts (<1%), although HR-C demonstrated the highest treatment transitions and switching behaviour. Dispensed SGLT2 inhibitor use was nearly threefold higher in eCVD-C (26.7%) than in LR-C (9.0%) or HR-C (10.7%). Overall, conformance to NICE-recommended pathways remained modest nationally, particularly in LR-C and HR-C. Across 42 ICBs, substantial regional heterogeneity in treatment pathways and guideline conformance was observed, with conformance ranging from 0.29 to 1.00 in LR-C pathways, 0.40 to 1.00 in HR-C pathways, and 0.54 to 0.92 in eCVD pathways. Conclusion: National T2DM treatment pathways for post-pandemic showed higher alignment to NICE guidelines in eCVD-C compared to the other risk groups, with ongoing gaps and large regional variations in other risk groups. Process mining offers a scalable approach to monitor implementation of guideline recommended care that could support learning health systems. Using T2DM during and post COVID-19 pandemic as a case study, this work demonstrates how these methods can assess the use of existing and innovative therapies, identify gaps and guide future adoption to ensure recommended treatments reach the right patient groups.

Background: The retail food environment is a widely used exposure in behavioural-nutrition and obesity research, on the premise that nearby food retailers shape diet and obesity risk. Over the past quarter-century, grocery stores have declined across rural and small-town America while limited-assortment discount ("dollar") stores have proliferated. Standard food-environment indices classify retailers as healthy or less-healthy but typically exclude dollar stores, now the fastest-growing food-retail format. As a result, a single classification decision may alter how the food environment is measured and the conclusions drawn from it. We develop a dollar-aware index, quantify how counting dollar stores changes the measured exposure, and derive a longitudinal trajectory typology. Methods: Using establishment-level data from Data Axle for all 878 Mississippi census tracts (1997-2024), we classified food retailers into five mutually exclusive categories using a previously validated approach and calculated the modified Retail Food Environment Index (mRFEI) in both its standard and dollar-aware forms, with the latter counting dollar stores as less-healthy outlets. We fitted Nagin-style group-based trajectory models to the tract-level dollar-aware index, related class membership to the Social Vulnerability Index (SVI) and urbanicity with multinomial regression, and characterised spatial clustering (Getis-Ord Gi*, join-counts) and grocery access. Results: Grocery stores fell from 1,616 to 716 while dollar stores rose from 315 to 1,005, intersecting in 2018. Counting dollar stores lowered the index by a margin that widened over time, and a growing number of tracts had only dollar-store retail, undefined under the standard index. Six trajectory classes emerged: stable adequate (5.6% of tracts), steady decline (13.1%), early collapse (11.1%), late collapse (6.7%), persistently constrained (34.1%) and chronic desert (29.3%); only the stable-adequate class (5.2% of children) stayed adequate throughout. Constrained and steady-decline membership rose steeply with vulnerability (RRR 11.7 and 9.9); chronic desert was urban (RRR 5.2, a food-swamp pattern); collapse classes had no cross-sectional social signature. Conclusions: In the US state with the highest adult obesity prevalence, a single retailer-classification decision substantially changes the measured food environment. The dollar-aware index and trajectory typology offer a transferable, time-varying exposure for behavioural-nutrition and obesity research and establish a foundation for future childhood-obesity studies.

Body mass index (BMI), visual function and resting heart rate (RHR) are standard measurements in adolescent physical examinations, yet their interconnections and age- and gender-specific differences are not fully clarified. This multicentre retrospective cohort study analyzed 130,832 screening records of 8-17-year-old adolescents from 2022 to 2024, using mixed-effects models and stratified analyses to examine BMIs independent correlations with UCVA (UCVA) and RHR, alongside the moderating effects of age and sex. Boys presented higher BMI values and greater overweight/obesity prevalence, whereas girls had poorer UCVA. After adjusting for confounders, every 1 kg/m{superscript 2} increment in BMI correlated with a -0.008 log MAR change (a stronger effect in girls) and a 0.26 beat-per-minute rise in RHR. The inverse BMI-UCVA correlation peaked at ages 8-11, weakened among 12-16-year-olds, and reversed at age 17. RHR decreased steadily with age, being marginally lower in boys, with a notable age-sex interaction. Age and sex jointly shaped the correlations among the three indicators, whose statistically significant links varied across developmental periods. Therefore, integrated screening should assess all indicators comprehensively while accounting for age and gender disparities. We propose unified, sex and age-stratified adolescent screening and intervention strategies to simultaneously mitigate obesity, myopia and cardiovascular risks, rather than isolated single-disease prevention.

Background In sub-Saharan Africa, women are navigating overlapping burdens of undernutrition and rising overweight/obesity, often within fragile health system and rapidly changing food environments. In the DRC, theses tensions may be intensified by rapid urbanization, socioeconomic disparities, insecurity and shifting lifestyles. Despite those changes, national level evidence on who is the most affected by excess weight and why remains scarce. This study assessed the determinant of overweight and obesity among Congolese women of reproductive age, aiming to highlight the social and geographic inequalities. Methods We analysed nationally representative data from the 2023 DHS. The analysis included 10,740 non-pregnant women aged 15-49 years with valid anthropometric measurements. Overweight/obesity was defined as BMI [&ge;] 25 Kg/m2. We examined a broad range of potential associated factors, including province, residence, socioeconomic status, household structure, education level, marital status, occupation, dietary diversity score, healthy diet related indicators, media exposure, internet use and health service utilisation. Weighted analyses accounted for the DHS sampling design. Variables associated at p value < 0.20 were retained for multivariable modelling. Multicollinearity was assed via adjusted GVIFs. Four hierarchical weighted logistic regression were built; the fully adjusted model guided final interpretation. Results Nearly on five women of reproductive age (19.5%) lived overweight or obesity. However, this burden was not evenly distributed. Women from Kongo Central and Tshuapa exhibited significantly lower odds, while those in Bas-Uele, Nord-Kivu, Sud-Kivu and Maniema were substantially more affected, highlighting spatial inequities. Women living in rural areas had lower odds of overweight/obesity compared with their urban counterparts (aOR=0.6; 95% CI: 0.48-0.79; p<0.001). A pronounced socioecomic gradient was observed. Compared with the poorest households, the likelihood of excess weight increases progressively among women in middle income household (aOR=1.65;95% CI:1.13-2.41), rich households (aOR=2.41; 95%CI:1.62-3.60), and was highest among the richest (aOR=4.19; 95%CI: 2.45-7.16). Larger households appeared protective, with lower odds observed in household of 4-5 members (aOR=0.68; 95%CI:0.5-0.92), 6-7 (aOR=0.72;95% CI: 0.54-0.97) and [&ge;]8 members (aOR=0.69; 95%CI:0.50-0.95) compared with smaller household. Age was the strongest predictor, with risk sharply accelerating after 30 years. Being married or in union was associated with higher odds. Notably, frequent internet use independently predicted overweight/obesity. In contrast, dietary diversity and unhealthy food indicators were not significantly significant in the fully adjusted models. Conclusion Overweight and obesity are rising among Congolese women, but unevenly and unjustly. Urban residence, socioeconomic status, age and digital exposure strongly sharply shape who is the most affected, revealing deep social and geographic inequities. Addressing this growing epidemic requires equity-oriented, province specific actions, alongside stronger primary prevention. Key-word: Overweight-obesity-associated factors, DRCongo, DHS

Introduction. By the end of 2023, many low-income countries had not reached 50% COVID-19 vaccine coverage, while most high-income countries had exceeded 80%. It remains unclear whether receiving vaccine deliveries translated into faster population coverage. We examined cross-national inequalities in the timing of the vaccine rollout and whether deliveries through the COVID-19 Vaccines Global Access (COVAX) facility were associated with subsequent national uptake. Methods. We conducted an observational study of 218 countries and territories using country-level data up to December 2023. We used generalized additive mixed models to identify country-level correlates of coverage at an early and a later stage of the pandemic, survival analysis to compare the time to 50% coverage between COVAX Advance Market Commitment (AMC) and non-AMC countries, and an event study to estimate the association between the timing of the first COVAX delivery and subsequent monthly coverage in AMC countries. Results. AMC-supported countries reached 50% coverage substantially more slowly than non-AMC countries. The hazard of reaching the threshold was 0.17 times that of non-AMC countries at month 1 (95% CI 0.07 to 0.41) and 0.53 times at month 18 (95% CI 0.33 to 0.85). One year after rollout began, 65.9% of AMC countries (95% CI 56.7 to 76.6) had not reached 50% coverage, compared with 21.1% of non-AMC countries (95% CI 15.1 to 29.5). The timing of COVAX deliveries was not significantly associated with subsequent national uptake in any post-delivery month. In the early stage of rollout, higher maternal mortality was associated with lower coverage, while a larger urban population was associated with higher coverage. By the end of the observation period, larger household size was associated with lower coverage, while higher health expenditure and a larger urban population were associated with higher coverage. Conclusion. Receiving COVAX deliveries was not, on its own, associated with faster coverage. Coverage differences were more consistently associated with country-level structural and health-system characteristics, while we found no significant association with the timing of the first COVAX delivery. Achieving vaccine equality likely requires strengthening the capacity of health systems to convert deliveries into administered doses, and preparedness efforts should invest in last-mile delivery capacity ahead of future emergencies.

Background: Early-life growth is associated with individual cardiometabolic risk factors, but its relationship with overall cardiovascular health (CVH) in low- and middle-income countries (LMICs) is unclear. We examined associations of maternal, household, and child growth factors with young-adult CVH across four LMIC birth cohorts. Methods: We analyzed harmonized data from the Consortium of Health-Oriented Research in Transitioning Societies (COHORTS), including 4,582 participants ages 18-30 years from Brazil, Guatemala, the Philippines, and South Africa. CHV was assessed using a modified American Heart Association Life's Simple 7 score based on body mass index (BMI), blood pressure (BP), fasting blood glucose (FBG), and smoking. Site-specific multivariable ordinal logistic regression models evaluated associations between early-life factors and CVH. Results: Men had poorer CVH than women across most sites, largely because of less favorable BP and smoking profiles. Higher birthweight was associated with lower odds of better CVH in Brazil (AOR=0.81; 95% CI: 0.71-0.94) and the Philippines (AOR=0.63; 95% CI: 0.45-0.87). Greater conditional relative weight at 2 years was also inversely associated with CVH in both sites. Birthweight, conditional height and conditional relative weight at 2 years were strongly associated with adult BMI, whereas associations with BP and FBG were weaker. Attained schooling was associated with CVH in Brazil (AOR = 1.13 per year; 95% CI: 1.10-1.16), and the Philippines (AOR = 1.17; 95% CI: 1.10-1.24). Conclusions: Early-life growth patterns and educational attainment are associated with cardiovascular health in young adulthood across diverse LMIC settings, supporting life-course strategies to promote cardiovascular health.

Unhealthy retail outlets, including liquor stores, bars, convenience stores, and fast food, are concentrated in lower-income neighbourhoods. This is a well-documented cross-sectional fact; the process that sustains it is not. A neighbourhood can hold more because more open there or because those already there survive longer, and these point to different responses. We assembled an establishment-level panel of every business in Rhode Island from 2016 to 2025 (480,923 geocoded establishment-years across nine annual cross-sections), following the same outlets year to year, and classified and counted unhealthy outlets by census tract. We estimated the tract income gradient three ways (negative binomial regression, a concentration index, and a Bayesian spatial model), tested its stability, and decomposed it into openings and closures. The gradient was strong, stable, and robust: about 30 percent fewer unhealthy outlets per resident per standard deviation of higher income, with racial composition and poverty no longer associated once income was included. It was reproduced through entry, not survival: closures were even-handed across income, while new unhealthy outlets opened about 2.2 times as often per resident in the lowest-income tracts as in the highest. This entry was not unhealthy-specific: new healthy food retail tilted toward lower-income tracts at least as strongly, and the unhealthy share of openings did not rise as income fell. The standing burden was nonetheless dominated by convenience stores and off-premise alcohol. Efforts to reshape the retail environment will have more leverage on new openings than on the existing stock, through instruments defined by outlet type.

ABSTRACT Objective: To assess the feasibility of diagnosing, enrolling, and managing adults with type 2 diabetes at the primary healthcare level using the WHO Package of Essential Non communicable Disease Interventions (WHO PEN) approach, following identification through community based screening in rural Ethiopia. Design: Single arm, pre post clinical feasibility study. Setting: Primary healthcare facility in Shebedino district, Sidama National Regional State, rural Ethiopia, between September 2024 and February 2025. Participants: 35 adults with newly diagnosed type 2 diabetes, identified through community-based screening and diagnosed according to the WHO and American Diabetes Association criteria. Interventions: A six-month WHO-PEN based intervention comprising metformin based pharmacologic treatment, lifestyle counselling, and health system strengthening. Outcome measures: Feasibility across four domains (acceptability, implementation fidelity, practicality, and preliminary clinical signal); HbA1c change from baseline to six months, analysed using the Wilcoxon signed-rank test and McNemars test. Results: All 35 patients completed the six-month follow up. At baseline, 6(17 %) had comorbid hypertension, 5 (14%) had elevated total cholesterol, 14 (40%) had low HDL cholesterol, 24 (69%) were underweight. Median HbA1c decreased from 52.0 mmol/mol (IQR: 50, 56.0) at baseline to 43.0 mmol/mol (IQR: 42.0, 46.0) at six months (reduction of 9.0 mmol/mol; p <0.001). By six months, 30 of 35 (85.7%) had HbA1c below the control threshold, versus 20 (57%) at baseline (p=0.002). Conclusion: Community identified adults with type 2 diabetes could be successfully diagnosed, linked to care, and retained using the WHO PEN approach at a rural primary healthcare facility, with substantial improvement in glycaemic control. The absence of a control group precludes causal attribution. Medication was not adjusted for patients with persistent hyperglycaemia despite scheduled reviews, indicating a priority need to strengthen implementation of established practices rather than studying further efficacy. Keywords: Type 2 diabetes; WHO-PEN; HbA1c; primary healthcare; community screening; feasibility study; Ethiopia

Introduction: Computerized cognitive training (CCT) is a promising and innovative solution to improve the quality of life for those experiencing age-related cognitive decline. The comprehension of instructions for CCT plays a crucial role in determining technology engagement. This study delves into the relationship between the presentation modes of CCT serious games instructions, their comprehension, and the resulting acceptability among older adults (aged over 65) without any known cognitive impairments. Methodology: In a within-subjects experimental design, two types of CCT instructions were submitted to 128 older participants (mean age 71.5, 70% female): without visual cues and with visual cues. This approach was complemented by a study of the influence of self-efficacy and technology-related anxiety on the acceptability of the games. Results: Instructions without salient visual cues were more acceptable for a complex functional game. Additionally, individuals with lower confidence in their cognitive abilities were less receptive to cognitive training, except for a highly familiar game. Conclusion: The study highlights that older individuals may prefer simpler instructions for complex functional games, suggesting a preference for reduced cognitive load. It also shows the subtle role of self-efficacy in technology acceptance, except for the most familiar games, with higher cognitive self-confidence linked to greater acceptability. It emphasizes the importance of metacognition and self-efficacy in engagement when CCT involves mobilizing cognitive resources. It points the need for simple and personalized instructions to improve acceptance of CCT, and to contribute to the development of tailor-made interventions for older people.

Objective This study evaluated how well subjective life expectancy (SLE) predicts mortality and actual life expectancy (ALE), along with factors associated with inaccurate expectations. Methods Using panel data on approximately 2,000 individuals with up to 28 years of follow-up from a nationally representative sample of older Japanese adults, we examined relationships among SLE, actual mortality, and ALE by survival analysis. We also evaluated health and socioeconomic disparities using concentration indices and investigated factors influencing SLE and ALE discrepancies and focal-point (i.e. rounded or anchored estimates) and do-not-know responses. SLE was measured as a self-reported point estimate, whereas ALE mainly came from official records and family reports. Results SLE was significantly associated with both actual mortality and ALE, even after accounting for demographic and socioeconomic variables. Nonetheless, significant inaccuracies remain: approximately 59% of individuals surpassed their expected lifespan. SLE was positively associated with ALE; however, the association was inelastic. Women and those with higher education levels were more likely to outlive their SLE, whereas those in poorer health were less likely to do so. Higher education correlated with fewer focal point responses to the SLE question. Discussion SLE effectively predicts ALE; however, gaps are non-negligible and differ across gender and socioeconomic groups. Offering more precise data, such as sex- and age-specific remaining life expectancy, can enhance SLE formation and lead to more informed economic choices.