European Journal of Public Health

BackgroundVaccination against SARS-CoV-2 has been deployed in France since January 2021. Evidence was beginning to show that the most vulnerable populations were the most affected by COVID-19. Without specific action for different population subgroups, the inverse equity hypothesis postulates that people in the least deprived neighbourhoods will be the first to benefit. MethodsWe performed a spatial analysis using primary data from the vaccination centre of the Avicenne Hospital in Bobigny (Seine-Saint-Denis, France) from January 8th to September 30th, 2021. We used secondary data to calculate the social deprivation index. We performed flow analysis, k-means aggregation, and mapping. ResultsDuring the period, 32,712 people were vaccinated at the study centre. Vaccination flow to the hospital shows that people living in the least disadvantaged areas were the first to be vaccinated. The number of people immunized according to the level of social deprivation then scales out with slightly more access to the vaccination centre for the most advantaged. The furthest have travelled more than 100 kilometres, and more than 1h45 of transport time to get to this vaccination centre. Access times are, on average, 50 minutes in February to 30 minutes in May 2021. ConclusionThe study confirms the inverse equity hypothesis and shows that vaccination preparedness strategies must take equity issues into account. Public health interventions should be implemented according to proportionate universalism and use community health, health mediation, and outreach activities for more equity.

BackgroundUndiagnosed diabetes represents a major challenge for health systems worldwide. While low socioeconomic status is typically associated with reduced healthcare access, the relationship between socioeconomic position and diabetes detection remains poorly characterized in Latin American settings with fragmented health systems. MethodsWe analyzed data from 4,409 Argentine adults who underwent capillary glucose measurement in the Third Step of the 2018 National Survey of Risk Factors. Among 471 individuals with elevated glucose ([≥]110 mg/dL), we examined the association between household income quintile and undiagnosed status using multivariable logistic regression, adjusting for age, sex, health coverage type, education, body mass index, physical activity, and smoking. ResultsContrary to expectations, undiagnosed dysglycemia increased with socioeconomic status: from 45.8% in the lowest quintile to 67.8% in the fourth quintile, with a slight decrease to 61.1% in the highest quintile. After full adjustment, each higher income quintile was associated with 22% greater odds of remaining undiagnosed (OR=1.22; 95% CI: 1.04-1.44; p=0.014). Notably, enrollment in public assistance programs (Plan Estatal) was associated with substantially lower odds of undiagnosed dysglycemia compared to social security coverage (OR=0.27; 95% CI: 0.09-0.79). Results were robust across multiple weighting specifications. ConclusionsHigher socioeconomic status paradoxically increases the likelihood of undiagnosed dysglycemia in Argentina, challenging conventional assumptions about healthcare access. Targeted public programs appear effective at identifying cases among vulnerable populations, while gaps persist in higher-income groups. These findings suggest that diabetes screening strategies should not overlook populations traditionally considered to have adequate healthcare access.

BackgroundBoth enhancing life expectancy as well as diminishing inequalities in lifespan among social groups represent significant goals for public policy. However, there is a lack of methodological tools to simultaneously monitor progress in both dimensions. Additionally, there is a consensus that absolute and relative inequalities in lifespan must be scrutinized together. MethodsWe introduce a novel graphical representation that combines national mortality rates with social inequalities, considering both absolute and relative measures. We use French and German data stratified by place of residence to illustrate this representation. ResultsFor all-age mortality we detect for France a rather continuous pace of decline in both mortality levels and variation. In Germany, substantial progress was made in the 1990s, which was mostly driven by convergence between eastern and western Germany, followed by a period with less progress. Age-specific analyses reveal for Germany some worrying regional divergence trends at ages 35-74 in recent years. This is particularly pronounced among women. ConclusionOur novel visual approach allows evaluating easily the dynamics of societal progress in terms of longevity, and facilitates meaningful comparisons between populations, even when their current mortality rates differ. The methods we employ can be reproduced easily in any country with longitudinal mortality data stratified by relevant socio-economic information or regions. It is both useful for scientific analyses as well as policy advice. Key messagesO_ST_ABSWhat is already known on this topicC_ST_ABSImproving life expectancy as well as reducing social inequalities in longevity are major public policy objectives. However, there is a lack of proper methodological tools to evaluate progress on these objectives. What this study addsThis study proposes an innovative graphical representation that combines national mortality and social inequalities in both absolute and relative terms in order to assess the dynamics of societal progress in longevity and make relevant comparisons between populations whose mortality rates are not at the same level nowadays. How this study might affect research, practice or policyMethods are freely and easily reproducible for all countries with longitudinal mortality data stratified by socio-economic information or geographic regions.

BackgroundDespite a well-funded healthcare system with universal insurance coverage, Switzerland has one of the highest neonatal and infant mortality rates among high-income countries. Identifying avoidable risk factors targeted by evidence-based policies is a public health priority. We describe neonatal and infant mortality in Switzerland from 2011-2018 and explore associations with neonatal and pregnancy-related variables, parental sociodemographic information, regional factors, and socioeconomic position (SEP) using data from a long-term nation-wide cohort study. MethodsWe included 680,077 live births--representing 99.3% of all infants born in Switzerland between January 2011 and December 2018. We deterministically linked the national live birth register with the mortality register and with census and survey data to create a longitudinal dataset of neonatal and pregnancy-related variables; parental sociodemographic information, such as civil status, age, religion, education, nationality; regional factors, such as urbanity, language region; and the Swiss neighbourhood index of SEP (Swiss-SEP index). Information on maternal education was available for a random subset of 242,949 infants. We investigated associations with neonatal and infant mortality by fitting multivariable Poisson regression models with robust standard errors. Several sensitivity analyses assessed the robustness of our findings. ResultsOverall, neonatal mortality rates between 2011 and 2018 were 3.0 per 1000 live births, varying regionally from 3.2 in German-speaking to 2.4 in French-speaking and 2.1 in Italian-speaking Switzerland. For infant mortality, respective rates were 3.7 per 1000 live births overall, varying from 3.9 to 3.3 and 2.9. Adjusting for sex, maternal age, multiple birth and birth rank, neonatal mortality remained significantly associated with language region [rate ratio (RR) 0.72, 95% confidence interval (CI): 0.64-0.80 for French-speaking and RR 0.66, 95% CI: 0.51-0.87 for Italian-speaking region], with marital status (RR 1.55, 95% CI: 1.40-1.71 for unmarried), nationality (RR 1.40, 95% CI: 1.21-1.62 for non-European Economic Area vs. Swiss), and the Swiss-SEP index (RR 1.17, 95% CI: 1.00-1.36 for lowest vs. highest SEP quintile). In the subset, we showed a possible association of neonatal mortality with maternal education (RR 1.24, 95% CI: 0.95-1.61 for compulsory vs tertiary education). ConclusionWe provide detailed evidence about the social patterning of neonatal and infant mortality in Switzerland and reveal important regional differences with about 30% lower risks in French-and Italian-speaking compared with German-speaking regions. Underlying causes for such regional differences, such as cultural, lifestyle, or healthcare-related factors, warrant further exploration to inform and provide an evidence base for public health policies.

We follow population trends in the monthly birth rate in Switzerland almost up to the present and place the latest developments in a historical context. Birth rates in 2022 were the lowest since the 1870s, and the trend is continuing in 2023. The latest decline had already begun 1-2 years before Covid-19. Previous pandemics (1890, 1918, 1920, 1957) had led to a temporary decline in births {bsim}9 months after the epidemic peaks. With Covid-19, this appears more complex. During and shortly after the first two waves and shutdowns in 2020, there were more conceptions and thus excess birth rates in 2021, in all available subgroups except Italian-speaking Switzerland, and somewhat more pronounced among >30-year-old mothers and second parities. Possible reasons for the mini-boom include: The increased time at home during the shutdowns has - planned or not - led to more conceptions which has brought pregnancies forward; the corona virus was still circulat-ing too infrequently in this 1st phase of the pandemic to have a negative impact on pregnancies or fertility; at the end of the waves and shutdowns, the perceived end of the pandemic threat could have led to an optimistic mood and thus also more conceptions. The subsequent decline from January 2022 was stronger than the in-crease before. The first part of the decline in 2022 is most likely due to a negative rebound from the advance-ment of births in 2020/2021 and deliberately postponed pregnancies due to the start of the vaccination pro-gram. The second part of the decline in 2022 is associated with conceptions during the large Omicron wave in the winter of 2021/2022, when many people in Switzerland fell ill. In addition, prices have been rising and real wages falling since 2021, the global political situation has become more unstable, and a general change in values regarding the willingness to have children may also be underway. Following these observations at population level (with limited depth of variables), more in-depth studies must now follow to better under-stand the dynamic ups and downs in the birth rate in Switzerland in recent years.

AimTo compare trends and undertake statistical analyses of differences in public health performance (confirmed cases and fatalities) of Nordic countries; Denmark, Finland, Norway and Sweden, and New Zealand, in response to the COVID-19 pandemic. MethodsPer capita trends in total cases and per capita fatalities were analysed and difference-in-difference statistical tests undertaken to assess whether differences in stringency of mandated social distancing (SD) measures, testing rates and border closures explain cross-country differences. ResultsSweden is a statistical outlier, relative to its Nordic neighbours, for both per capita cases and per capita fatalities associated with COVID-19 but not in terms of the reduction in economic growth. Swedens public health differences, compared to its Nordic neigbours, are partially explained by differences in terms of international border closures and the level of stringency of SD measures (including testing) implemented from early March to June 2020. ConclusionsWe find that: one, early imposition of full international travel restrictions combined with high levels of government-mandated stringency of SD reduced the per capita cases and per capita fatalities associated with COVID-19 in 2020 in the selected countries and, two, in Nordic countries, less stringent government-mandated SD is not associated with higher quarterly economic growth.

BackgroundImplementing population-based policies such as mandatory menu calorie labelling in out-of-home food businesses and sugar-sweetened beverage (SSB) taxes are promising approaches to improve population health. We aimed to estimate and compare the likely impacts of menu calorie labelling and SSB taxes on reducing obesity prevalence, cardiovascular disease (CVD) mortality, and socioeconomic-related equitable impacts, in two European countries (Belgium and Germany). MethodsWe used microsimulation models over a 20-year simulation horizon (2022-2041). For both policies, we modelled the impacts through assumed changes in energy intake due to consumer responses and food industry reformulation. Scenarios of partial (in "large" out-of-home businesses; [≥] 250 employees) and full (in all out-of-home businesses) implementation for menu calorie labelling and different tax rates for SSBs (10%, 20%, 30%) were simulated. FindingsCompared to the counterfactual scenario (e.g., without additional policies), assuming policies effects on both consumer and industry behaviour, menu calorie labelling applied to all out-of-home businesses was estimated to reduce obesity prevalence by 3{middle dot}61 (95% uncertainty interval-UI: [2{middle dot}78, 4{middle dot}30]) and 4{middle dot}28 (95% UI: [3{middle dot}64, 5{middle dot}06]) percentage points and prevent 1600 (95% UI: [400, 3800]) and 30000 (95% UI: [10000, 58000]) CVD deaths in Belgium and Germany over 20 years, respectively. The 30% SSB tax was estimated to reduce obesity prevalence by 0{middle dot}27 (95% UI: [0{middle dot}17, 0{middle dot}43]) and 0{middle dot}27 (95% UI: [0{middle dot}17, 0{middle dot}39]) percentage points and postpone 2500 (95% UI: [800, 5200]) and 16000 (95% UI: [7500, 28000]) CVD deaths in Belgium and Germany, respectively. SSB taxation may have socioeconomic-related equitable impacts, while menu calorie labelling may not. InterpretationThe menu calorie labelling and SSB taxation have substantial impacts in reducing obesity prevalence and preventing CVD deaths in Belgium and Germany. Implementing both policies will be important to reduce obesity and related CVD burden. FundingEuropean Research Council, National Institute of Health and Care Research Research in contextO_ST_ABSEvidence before this studyC_ST_ABSWe searched simulation modelling studies on the impacts of food-related policies in MEDLINE from 1st January 2000 to 30th September 2024 using the search terms ("food polic*" OR "health polic*" OR "fiscal polic*" OR "SSB" OR "sugar" OR "menu label*" OR "calorie label*" OR "energy label*") AND (simulation OR microsimulation) based on titles and abstracts, restricted to human subjects. We identified 602 articles. To date, a few simulation modelling studies estimated the population-level impacts of mandatory menu calorie labelling. In England, implementation of mandatory menu calorie labelling in all out-of-home food businesses were estimated to reduce obesity prevalence by 2{middle dot}65 percentage points and prevent 9200 cardiovascular (CVD) deaths over 20 years. Two different studies in the US estimated 27646 CVD deaths and 16700 cancer deaths prevented over lifetime. Given these estimated impacts and England having pioneered the implementation of mandatory menu calorie labelling in Europe, this policy is currently be considered for implementation in many other European countries. However, no studies have examined the potential impacts of implementing this policy in other countries in Europe, nor the extent to which it may offer greater benefits compared to other widely implemented policies, such as sugar-sweetened beverage (SSB) taxes. Many European countries have implemented SSB taxes, including Belgium and the UK. While SSB taxes have been found to be effective in reducing CVD burden based on a scoping review summarising a handful of studies using simulation modelling approaches in different countries, there are gaps in the literature on the impacts of this policy compared to other policies. No studies have estimated and compared the impacts of mandatory menu calorie labelling and SSB taxes on reducing obesity prevalence and CVD mortality in European countries. Added value of this studyThis study is the first to estimate and compare the impacts of mandatory menu calorie labelling and SSB taxes in two European countries, Belgium and Germany. Our estimates indicate consistent evidence across both countries for greater benefits in reducing obesity prevalence and CVD mortality from implementing menu calorie labelling in all out-of-home food businesses compared to its implementation limited to large out-of-home food businesses only. While higher tax rates on SSBs were estimated to have bigger benefits, the impact on reducing obesity prevalence was estimated to be smaller compared to mandatory menu calorie labelling in both countries. However, the impact of SSB taxes on CVD mortality was projected to be greater than the mandatory calorie labelling in Belgium, but smaller in Germany. More importantly, based on the current evidence used to inform our models, these policies are complementary as they are estimated to impact CVD mortality through different pathways: mandatory menu calorie labelling primarily affects body mass index (BMI), while SSB taxes mainly operate through a direct BMI-independent effect. In terms of equitable impacts, menu calorie labelling may prevent more deaths in high than low education groups, whereas SSB taxation may postpone more deaths in low than high education groups. Implemented together, these policies will result in greater benefits in addressing diet-related diseases. Implications of all the available evidenceMandatory menu calorie labelling and SSB taxation were estimated to have substantial impacts on reducing obesity prevalence and preventing CVD mortality. The findings inform the policymakers of both countries and emphasise both the need to implement mandatory menu calorie labelling across out-of-home food businesses and apply higher SSBs tax rates to maximise public health impacts.

BackgroundExisting studies on contextual health effects struggle to account for selection bias, limiting causal interpretation. We use refugee dispersal in Germany as natural experiment to study the effect of small-area deprivation on mental and physical health, while considering the potential mediating role of housing and social context. MethodsRefugees subject to dispersal (n=1400) are selected from a nation-wide longitudinal refugee study (IAB-SOEP-BAMF Panel; 2016-2018). Multi-level linear regression models, adjusted for age, sex, education, region of origin, federal state, asylum status and length of residence in Germany, are fitted to the change in mental and physical health subscales of the SF-12 depending on quintiles (Q1 - Q5) of district-level socioeconomic deprivation (German Index of Socio-Economic Deprivation, GISD). This is followed by mediation analyses (for housing and social context) and sensitivity analyses. FindingsResidency in districts with moderate-high deprivation (Q4) has a negative impact on physical health (coef{middle dot}: -2{middle dot}2, 95%CI: -4{middle dot}1;-0{middle dot}2) compared to lowest deprivation (Q1). Moderate-high deprivation (Q4) also has a positive impact on mental health, but the effect is statistically insignificant following covariate adjustment (coef{middle dot}: 2{middle dot}5, 95%CI: -0{middle dot}7;5{middle dot}6). Comparisons with other deprivation quintiles are statistically insignificant. InterpretationThe results point to gaps in health and social service provision for refugees living in the most deprived regions. Further efforts should be made to support integration of refugees into health and social systems in resource-poor regions, including improved interpreting services, specifically trained social workers and diversity-sensitive information offerings. Further research using longer timeframes and larger sample sizes are required to confirm results. FundingGerman Science Foundation (FOR: 2928/ GZ: BO5233/1-1).

BackgroundThe mechanisms that influence the uptake of risky behaviours among immigrants are influenced by the interrelation between characteristics operating in different phases of their migratory experience. Characterizing their behavioural risk profile is needed to prioritize actions for prevention and health services organization. We therefore analysed health behaviours and their determinants among immigrants in Italy, jointly accounting for sociodemographic factors, migration pathways and integration indicators. MethodsData come from a national survey conducted in 2011-2012 on a sample of about 12000 households with at least one foreigner residing in Italy. The independent impact of a variety of sociodemographic, migratory and integration characteristics on obesity, smoking and daily alcohol consumption was assessed using multivariable Poisson models. ResultsThe survey involved more than 15,000 first generation immigrants. Unhealthy lifestyles are more common among men than among women and vary widely by ethnic group. There is a significant impact of employment status and family composition, while the educational level loses importance. Longer duration of residence and younger age at arrival are associated with an increased behavioural risk. Among women we also observed an independent impact of the integration indicators, less important for men. ConclusionsThe profile of the main unhealthy lifestyles among migrants is shaped by cultural, socioeconomic and migratory characteristics, which differ by gender. Understanding these factors can help to design tailored preventive messages, necessary to interrupt the deterioration of migrants health capital. Low levels of integration have an additional negative impact on health, so inclusion and integration policies should complement health promotion strategies.

BackgroundPrevious studies highlighted the relationships between socioeconomic inequalities and the populations risk to become disease or die during COVID-19 epidemic. In France, socioeconomic inequalities vary across metropolitan areas, but little is known if that could explain the spatial disparities observed in terms of incidence and testing rates. We assessed the impact of socioeconomic inequalities on testing and incidence rates of COVID-19 for each metropolitan area and wave. MethodsFor each of the 22 metropolitan areas, we relied on socioeconomic variables from census data to define socioeconomic profiles using classification on the principal components. We analysed associations between socioeconomic profiles, testing and incidence rates by epidemic wave from July-2020 to March-2023, using spatialised generalised additive mixed models. We performed meta-regressions to study the distribution of testing and incidence rate ratios (socially deprived vs privileged) across metropolitan areas, according to vaccination rates. ResultsSocially deprived metropolitan areas had lower testing rates than privileged, but during wave 4 (July-October-2021, extended health pass), testing rates increased in more deprived areas. Incidence rates were higher in deprived areas (waves 2-4, July-2020 to October-2021) but reversed between waves 6 to 9 (March-2022 to March-2023). Meta-regression analysis indicated that high vaccination coverage narrowed testing and incidence gaps between deprived and privileged. ConclusionsThe impact of social inequalities on the populations testing and incidence COVID-19 epidemic was driven by socioeconomic inequalities across metropolitan areas and varied across epidemic waves. Vaccination rates and the presence of health measures (lockdowns, health pass) seem to help reduce these disparities.

We analyzed the impact of the COVID-19 policy restrictions on mobility patterns and excess mortality at the regional level in The Netherlands between 2020 and 2022. Our analysis combines data on public policies, mobility patterns from the Google Mobility Reports, officially registered COVID-19 cases and deaths, and region-specific measures of excess mortality over a relatively long time period extending beyond the first wave of the pandemic. We modeled the dynamic relationships of these variables as a system in which policy responds to information about the pandemic; mobility reacts both to information about the pandemic and to policy; the number of COVID-19 cases is influenced by changes in mobility and policy; and excess mortality is affected directly by the policy restrictions and indirectly via the impact of policy on mobility. The results confirm that the stringency of policy restrictions increased with the number and growth rates of COVID-19 cases and deaths. Mobility, as reflected in presence in public places (transport hubs, retail, work), decreased while presence at residential locations increased in response to stricter policies and higher COVID-19 case and death counts in preceding weeks. The number of new COVID-19 cases declined when stricter policy restrictions were enacted and reduced presence in public places (following a two-week lag). Excess mortality decreased with stricter policy restrictions (with a five-week lag) and, to a lesser extent, with reduced presence in public places and increased presence in places of residence. Importantly, the effects of policy restrictions and mobility diminished with consecutive COVID-19 waves. Overall, the evidence shows that policy restrictions were effective in limiting the spread of the pandemic and in saving lives. While policies influenced mobility patterns, their impact was not fully mediated by mobility changes.

BackgroundThe burden of COVID-19 has been heterogeneous, indicating that the effects of this disease are synergistic with both other non-communicable diseases and socioeconomic status (SES), high-lighting its syndemic character. While the appearance of vaccines has moderated the pandemic effects, their coverage has also been heterogeneous, both when comparing different countries, and when comparing different populations within countries. Of note, once again SES appears to be a correlated factor. MethodsTo examine the relationship between SES and vaccination coverage, we analyzed publicly available data detailing the percentage of school-aged vaccinated children in different municipalities belonging to the Metropolitan Area (MA) of Santiago, Chile, one of the most largely vaccinated countries in the world. Vaccination data was compiled per school type, either public, state-subsidized and private, at three different dates along the COVID-19 pandemic so to cover the dispersion of Delta, and Omicron, including Omicron subvariants BA.4 and BA.5. We computed the median vaccination ratio for each municipality and school type and calculated their Spearmans rank correlation coefficient with each one of nine SES indices. FindingsIn the MA of Santiago, Chile, the percentage of school-age children who have received vaccinations against COVID-19 correlates with SES. Vulnerable municipalities with low SES exhibit low levels of vaccination coverage. Of note, this strong correlation is observed in both public and state-subsidized schools, but to a meaningless extent in private schools. Although inequity in vaccination coverage decreases over time, it remains higher among students enrolled either in public and state-subsidized schools compared to those of private schools. InterpretationAvailable data is insufficient to explore plausible causes behind lower vaccination coverage in vulnerable municipalities in the MA of Santiago, Chile. However, considering the available literature, it is likely that a combination of factors including the lack of proper information about the importance of vaccination, the lack of incentives for childrens vaccination, low trust in the government, and/or limited access to vaccines for lower-income people, may all have contributed to this low vaccination coverage. Importantly, unless corrected, the inequity in vaccination coverage will exacerbate the syndemic nature of COVID-19. FundingThis material is based upon work supported by the U.S. Air Force Office of Scientific Research under award number FA9550-20-1-0196. Financial support is also acknowledged to Centro Ciencia & Vida, FB210008, Financiamiento Basal para Centros Cientificos y Tecnologicos de Excelencia de ANID.

IntroductionThe spread of the COVID-19 pandemic, and its severity, is spatially heterogenous. At the individual level, the socioeconomic status (SES) profile is known to be associated with COVID-19 incidence and severity. The aim of this geo epidemiological study was to investigate the link between SES profile and potential confounders, and COVID-19 incidence and hospitalization rates, at a fine geographical scale. MethodsWe analyzed COVID-19 incidence and severity during two epidemic waves between September 2020 and June 2021, in Provence Alpes Cotes dAzur, a 5 million inhabitants French region. The region is divided into sub-municipal areas that we have classified according to their SES profile. We then conducted a spatial analysis of COVID-19 indicators depending on SES profile, age structure, and health services provision. This analysis considered spatial autocorrelation between areas. ResultsCOVID-19 incidence rates in more deprived areas were similar to those in wealthiest ones. Hospitalization rates of COVID-19 cases in conventional care units were greater in more deprived vs wealthiest areas: Standardized Incidence Ratio (SIR) were respectively 1.34 [95% confidence interval 1.18 - 1.52] and 1.25 [1.13 - 1.38] depending on the epidemic wave. This gap was even greater regarding hospitalization rates of cases in critical care units: SIR = 1.64 [1.30 - 2.07] then 1.33 [1.14 - 1.55] depending on the epidemic wave. Hospitalization rates of COVID-19 cases in conventional care units were also greater in areas with high proportion of elderly people vs young people: SIR respectively 1.24 [1.11 - 1.38] and 1.22 [1.13 - 1.32] depending on the wave. ConclusionConsidering age structure and health services provision, a deprived SES profile is associated to a greater COVID-19 severity in terms of hospitals admissions, in conventional care units and in critical care units. This result implies targeting risk prevention efforts on these areas in pandemic situations, and highlights the need to develop access to healthcare to deprived populations in anticipation of periods of crisis. Key messagesWhat is already known on this topic - Socioeconomic status is associated to COVID-19 incidence and severity, at an individual scale or at a large spatial scale. What this study adds - We showed the positive relationship between deprivation and COVID-19 incidence and hospitalization rates at a fine sub-municipal geographical scale. We considered confusion factors like demographic structure and health services provision. How this study might affect research, practice or policy - These findings may help predict at a fine scale where the impact will be most severe in pandemic situations and make it possible to target risk prevention efforts on these areas.

BackgroundThe COVID-19 pandemic brought major reductions in healthcare visits in Europe. The long-run consequences for healthcare systems depend on the paths to post-pandemic levels, especially among the groups in highest need of sustained care. MethodsWe used individual longitudinal data from 27 European countries from the Survey of Health, Ageing and Retirement in Europe, divided in three phases: pre-pandemic (2004-2019), pandemic (2021), and post-pandemic (2022). We analysed the number of healthcare visits by gender over time and their correlation with age and chronic conditions using a Bayesian spatio-temporal model. ResultsBefore COVID-19, the nominal rate of healthcare visits varied among countries from two to six visits per year and increased over time. The COVID-19 pandemic severely affected the number of healthcare visits, with an estimated reduction from 65% to 95% across countries. During COVID-19, older individuals and those with chronic conditions had a more than proportional reduction in the number of healthcare visits. After COVID-19, the pattern of healthcare visits mostly returned to pre-pandemic levels, with an over-shooting for people with cancer and a lag for people with cardiovascular diseases. ConclusionThe quick recovery in the number of healthcare visits for most European countries indicate that access to care stabilised again. Yet, the different trends for vulnerable groups show that these groups require timely action to prevent long-term consequences of missed care.

BackgroundSocioeconomic status in the risk of developing type 1 diabetes seems inconsistent. We investigated whether risk of childhood-onset type 1 diabetes differed by parental education or occupation in a nationwide cohort. MethodsThis cohort study included all children born in Norway from 1974 to 2013. In individually linked data from nationwide population registries following children born in Norway up to 15 years of age, we identified 4647 with newly diagnosed type 1 diabetes during 15,381,923 person-years of follow-up. ResultsChildren of mothers with a masters degree had lower risk of type 1 diabetes than children of mothers with completed upper secondary education only: adjusted incidence rate ratio, aIRR=0.81 95% confidence interval: 0.69 - 0.95). There was no difference between upper secondary and lower secondary maternal education (aIRR=0.98, 95% confidence interval 0.89-1.08). Paternal education was not significantly associated with type 1 diabetes. While maternal elementary occupation was associated with a lower risk of type 1 diabetes, specific maternal- or paternal occupations were not. ConclusionsOur results suggested inverse U-shaped associations between maternal socioeconomic status and risk of type 1 diabetes. Non-linear associations be part of the reason why previous literature has been inconsistent.

BackgroundSport participation is an important component of a healthy lifestyle and is known to be more common among privileged individuals. However, few studies have examined socio-demographic patterns of participation by type of activity. This study aims at quantifying socio-economic inequalities in sport participation by sport type, and to analyse their trend over 15 years. MethodsWe used 2005-2019 data from the Bus Sante study, a yearly population-based cross-sectional survey of Geneva adults. Sport participation was defined as reporting at least one sporting activity over the previous week; educational level, household income and occupational position were used as indicators of socio-economic position. Socio-economic inequalities in sport participation, and their trend over time, were examined using the relative and slope indexes of inequality (RII/SII). ResultsOut of 7769 participants (50.1% women, mean age 46 years old), 60% participated in a sporting activity. Results showed that the higher the socioeconomic circumstances, the higher the sport participation (RII=1.78; 95% Confidence Interval (CI): 1.64-1.92; SII=0.33; 95%CI: 0.29-0.37 for education). Relative inequalities varied per sport e.g., 0.68 (95%CI: 0.44-1.07) in football participation and 4.25 (95%CI: 2.68-6.75) in tennis/badminton participation for education. Yearly absolute inequalities in sport participation tended to increase between 2005 and 2019 for household income ({beta}=0.01; P-value=0.024). ConclusionWe observed strong socio-economic inequalities in sport participation in Geneva, with different magnitude depending on the type of sport. These inequalities seemed to increase over the 2005-2019 period. Our results call for tailored measures to promote the participation of socially disadvantaged populations in sporting activities. KEY MESSAGESO_LISport participation is associated with higher socioeconomic conditions. Research on the patterning of inequalities per sport type and on their trend over time remains scarce. C_LIO_LIThere are high growing socioeconomic inequalities in sport participation in Geneva. Inequalities in sport participation are heterogeneous and lower in sports practised in group. C_LIO_LITailored sport promotion measures are needed for disadvantaged populations. C_LI

BackgroundA booster with bivalent COVID-19 vaccine was offered in the Netherlands in autumn, 2022. We aimed to investigate vaccine uptake during the autumn 2022 booster round among the population subgroups at risk for severe COVID-19 that were specifically targeted by this campaign: the medical risk group aged 18-59 years and individuals [≥]60 years. We calculated booster uptake in both populations and analyzed determinants of booster uptake among those who had received at least one prior COVID-19 vaccination. MethodsHaving had an autumn 2022 booster dose was defined as having received a COVID-19 vaccination between 19 September 2022 and 7 March 2023. The study population included individuals who received at least one previous COVID-19 vaccination. National registries of sociodemographic determinants and COVID-19 vaccination were linked by a unique person identifier. Voting proportions for political parties were included at neighborhood level. Determinants of COVID-19 vaccine autumn booster uptake were ranked by importance by random forest analyses. ResultsBooster uptake was 68% among those aged [≥]60 and 30% among those aged 18-59 years with a medical risk factor for severe disease. For both target groups the most important determinant for booster uptake was age (15% in 18-29 years to 72% in 80+ years). Voting proportions for progressive liberal political parties ranked second in the random forest analysis in both groups, with an increasing proportion of votes associated with higher uptake. In the 60+ group, household type ranked third, with highest vaccine uptake among married couples without children (72%) and the lowest uptake among unmarried couples with children (47%). In the medical risk group, migration status ranked third. Migrants with two parents born abroad had the lowest uptake (18%), whereas migrants with both parents born in the Netherlands had the highest uptake (35%). ConclusionAmong individuals who had received at least one prior COVID-19 vaccination, the autumn 2022 COVID-19 booster uptake was 68% in people [≥]60 years and 30% in in the medical risk group aged 18-59 years. The most important determinant of booster uptake was age, followed by political preference and household type (60+ group) or migration status (medical risk group). Uptake varied considerably among subgroups in both target groups. Further research should be aimed at understanding the drivers and barriers of vaccine uptake among the subgroups with notably low uptake.

ObjectivesThe main objectives were 1) to calculate and describe travel time by car from the home of Norwegian residents to the office of their named general practitioner (GP); 2) to estimate changes in travel time for residents who started to visit the GP and, if so, to 3) to explore if the residents changed GP or moved to reduce their travel time. MethodsWe used nation-wide individual-level annual registry data 2009-2017 on the exact location of the home of every resident and the GP-office to calculate travel time in minutes by car from home to their assigned GP. First, using data for 2017 only, we calculated travel time at the median and 90th percentile, and by sex, age, immigrant background, county of residence and use of GP in 2017. Second, with annual data 2009-2017, and restricting the sample to residents who had not used their GP over the last two years (t-2 and t-1), we used a difference-indifferences model to estimate changes in travel time in the next two years (t+1 and t+1) for patients with a visit in year t compared with those with no visit in t. Separate models were run for those who changed GP and those who moved from t-2 to t., and for the 20% who lived farthest away in t-1. ResultsWe could calculate the travel time for 3,976,910 residents in 2017, with a median travel time from home to the GP of 4.9 minutes and a travel time at the 90th percentile of 18.3 minutes. In the most sparsely populated northern county of Norway, travel time was about 5 minutes at the median and below 45 minutes at the 90th percentile. Elderly residents and residents who used their GP in 2017 had a somewhat shorter travel time than other groups of the population. Using annual data for 2009-2017 in the difference-in-differences analysis (16,388,151 resident-year observations), travel time dropped by 2.5 minutes (95% confidence interval 2.4 to 2.6) in t+1 and t+2 for patients with a visit in t compared with similar patients with no visit in t. The drop was similar for patients who did and did not change GP, but larger for patients who moved (10.0 minutes; 95%CI 9.7 to 10.4) compared with those who did not move (0.6 minutes; 95%CI 0.5 to 0.7), and particularly large for the 20% living farthest away in t-1 (24.2 minutes; 95%CI 23.3 to 25.2). ConclusionsTravel time from home to ones GP is short for the vast majority of the population in the sparsely populated country of Norway. However, residents move closer to the GP when they start using the services, especially patients who used to live far away. This relocation may reflect strong preferences for proximity to the services, and we conclude that more knowledge is needed to enable transparent balancing of costs and benefits of centralizing GP-services, at least in rural areas. JEL classificationI10, E32, J6

BackgroundOn 1st May 2018, Scotland implemented Minimum Unit Pricing (MUP) of {pound}0.50 per unit of alcohol to lower alcohol consumption and related harms, and reduce health inequalities. We assessed the impact of MUP on road traffic accidents (RTAs) after 20 months of implementation. MethodsA controlled interrupted time series design was used to evaluate the impact of MUP on RTAs (total, fatal, night-time) in Scotland and any effect modification across socio-economic deprivation groups. RTAs in England and Wales (E&W) were used as a control group. Covariates of severe weather events, bank holidays, seasonal and underlying trends were included. ResultsIn Scotland, MUP implementation was associated with a 7.2% (95% CI: 0.9%,13.7% P=0.03) increase in the total number of RTAs. For the corresponding period in E&W, there was a 0.9% increase (95% CI: -2.3%,3.2% P=0.75). It is implausible that MUP caused this increase in RTAs, with the most likely explanation of these results being that unmeasured time-varying confounding affected Scotland and E&W differently. There was no evidence of differential impacts of MUP by level of socio-economic deprivation. ConclusionThe introduction of MUP in Scotland was not associated with a lower level of RTAs.

BackgroundMenarche is a critical developmental milestone, with earlier onset associated with adverse long-term health consequences. Despite a reported global decline in age at menarche over the last century, this trend and its determinants remain insufficiently studied in Spain. ObjectiveTo assess secular trends in age at menarche and its determinants in the Valencian Community, Spain. MethodsThis population-based study included 417,260 participants born between 1931 and 2008. First, secular trends in age at menarche were assessed using time-series models across 5-year birth cohorts for the overall population. Then, participants were categorized as either women (born 1931-1985) or girls (born 1990-2008), and Bayesian linear regression models were fitted for each group, adjusting for birth cohort and continent of birth in all models, and additionally for educational level in women and body mass index (BMI) in girls. ResultsMean age at menarche decreased by 1.9 years, from 13.1 to 11.1, between the 1931-1935 and 2006-2008 birth cohorts, with a steeper decline after 1975. Compared to Europeans, women born in South/Central America ({beta}[95% CI]: 0.33[0.30, 0.36] years) and Africa (0.52[0.45, 0.58] years) experienced later menarche, while girls from South/Central America experienced earlier onset (-0.18[-0.28, -0.09] years). In girls, lower BMI was associated with later menarche (0.96[0.74, 1.18] years) and higher BMI with earlier onset (-0.53[-0.57, -0.48] years). ConclusionThere was a marked decline in age at menarche in the Valencian Community, with no evidence of leveling off. Key determinants included continent of birth (with cohort-specific effects) and BMI.